diff --git a/BA10w Max 2,3 Cut_onehot.py b/BA10w Max 2,3 Cut_onehot.py deleted file mode 100644 index 7df2b4e..0000000 --- a/BA10w Max 2,3 Cut_onehot.py +++ /dev/null @@ -1,189 +0,0 @@ -from qiskit import * -from qiskit.tools.monitor import job_monitor - -import numpy as np -import matplotlib.pyplot as pl -from mpl_toolkits.axes_grid1 import make_axes_locatable - -import networkx as nx -from networkx.drawing.nx_agraph import graphviz_layout -from qiskit.visualization import * -from scipy import optimize as opt -from qaoa import * -import os - -import sys -sys.path.append('../') - -from qiskit_utilities.utilities import * -#from classical_maxkcut_solver import * - - -from matplotlib import rc -font = {'size' : 36} -rc('font', **font); -rc('text', usetex=True) -pl.rcParams["figure.figsize"] = 12,8 -pl.rcParams["axes.titlesize"] = 24 -pl.rcParams["axes.labelsize"] = 36 -pl.rcParams["lines.linewidth"] = 3 -pl.rcParams["lines.markersize"] = 10 -pl.rcParams["xtick.labelsize"] = 36 -pl.rcParams["ytick.labelsize"] = 36 -#pl.style.use('bmh') - -numV=10 -G = nx.read_gml("../data/sample_graphs/w_ba_n"+str(numV)+"_k4_0.gml") - -#pos = nx.spring_layout(G) -#nx.draw_networkx(G,apos=pos) - -IBMQ.load_account() -provider = IBMQ.get_provider(hub='ibm-q') - -beta_n = 12 -gamma_n = 24 -beta_max = np.pi/2 -gamma_max = np.pi -optmethod='Nelder-Mead' -shots=1024*2*2*2 -rerun=True - -maxdepth=3 - -depths=range(1,maxdepth+1) - -outstr="" -outstrbest="" - -max_val = np.array([8.657714089848158, 10.87975400338161, 11.059417685176726, 11.059417685176726, 11.059417685176726, 11.059417685176726, 11.059417685176726]) - -backend = provider.get_backend('ibmq_qasm_simulator') - -alpha=None -if alpha == None: - circuit_version=2 -else: - circuit_version=1 - -for k_cuts in [2,3]: - - #max_val, label = find_max_cut_brute_force(G, k_cuts) - #classical_maxkcut_solver(G, k_cuts) - - outstr+=str(k_cuts) - outstrbest+=str(k_cuts) - print(" k=", k_cuts) - name="BA10w"+str(gamma_n)+"x"+str(beta_n)+"_v"+str(circuit_version)+"_k"+str(k_cuts)+"_onehot_alpha_"+str(alpha) - Elandscape, gammabetas, E, best = runQAOA(G, k_cuts, backend, gamma_n, beta_n, gamma_max, beta_max, optmethod=optmethod, circuit_version=circuit_version, shots=shots, name=name, rerun=rerun, maxdepth=maxdepth, onehot=True, onehot_alpha=alpha) - - shiftg=gamma_max/(2*gamma_n) - shiftb=beta_max/(2*beta_n) - - pl.figure(figsize=(20,10)); - pl.clf() - pl.imshow(Elandscape,interpolation='spline36',origin='lower' - ,extent=[-shiftg,gamma_max+shiftg,-shiftb,beta_max+shiftb], aspect=1) - pl.xticks([0,gamma_max/2, gamma_max], ['0', r'$\pi$', r'$2\pi$']) - pl.yticks([0,beta_max], ['0', r'$\pi/2$']) - pl.xlabel('$\gamma$',loc='left') - pl.ylabel(r'$\beta$') - pl.colorbar(shrink=0.75, pad=0.05, orientation="horizontal") - - - #pl.plot(gammabetas['x0_d1'][0], gammabetas['x0_d1'][1],'xw') - pl.plot(gammabetas['xL_d1'][0], gammabetas['xL_d1'][1],'or') - - pl.tight_layout() - pl.savefig("pics/E_"+name+".png") - pl.close() - print("saved", "pics/E_",name,".png") - - #num_shots, av_max_cost, best_cost, distribution = getStatistics(G, k_cuts, backend, gammabetas, circuit_version=circuit_version, shots=shots, name=name+"_best") - - for depth in depths: - outstr+=" & "+"{:.2f}".format(E[str(depth)]/max_val[k_cuts-2]) - outstr+="\\\\ \n" - print(outstr) - - for depth in depths: - outstrbest+=" & "+"{:.2f}".format(best[str(depth)]/max_val[k_cuts-2]) - outstrbest+="\\\\ \n" - print(outstrbest) - - #pl.figure(figsize=(20,10)) - #pl.clf() - #for depth in depths: - # pl.semilogx(num_shots[63:], np.array(av_max_cost[str(depth)][63:])/max_val[k_cuts-2],'x-', base=2, label='d='+str(depth), linewidth=2,markersize=14) - #pl.ylabel('r') - #pl.xlabel('num shots') - #pl.legend() - #pl.grid(True, which="both") - #pl.tight_layout() - #pl.savefig("pics/"+name+"_avE.png") - #pl.close() - - #pl.figure(figsize=(20,10)) - #pl.clf() - #for depth in depths: - # pl.plot(num_shots[:36], np.array(av_max_cost[str(depth)][:36])/max_val[k_cuts-2],'x-', label='d='+str(depth), linewidth=2,markersize=14) - #pl.legend() - #pl.ylabel('r') - #pl.xlabel('num shots') - #pl.legend() - #pl.grid(True, which="both") - #pl.tight_layout() - #pl.savefig("pics/"+name+"_bestE"+str(depth)+".png") - #pl.close() - - #pl.figure(figsize=(20,10)) - #pl.clf() - #for d in depths: - # if d==1: - # col='r' - # elif d==2: - # col='g' - # else: - # col='b' - # sty='' - # if not d==1: - # sty=':' - # pl.plot(np.arange(1,d+1),gammabetas['x0_d'+str(d)][::2],'x'+col+sty,label='depth='+str(d)) - # sty='' - # if not d==1: - # sty='-' - # pl.plot(np.arange(1,d+1),gammabetas['xL_d'+str(d)][::2],'o'+col+sty,label='depth='+str(d)) - #pl.xlabel('depth') - #pl.ylabel(r'$\gamma$') - #pl.legend() - #pl.tight_layout() - #pl.savefig("pics/"+name+"_gamma.png") - #pl.close() - - #pl.figure(figsize=(20,10)) - #pl.clf() - #for d in depths: - # if d==1: - # col='r' - # elif d==2: - # col='g' - # else: - # col='b' - # sty='' - # if not d==1: - # sty=':' - # pl.plot(np.arange(1,d+1),gammabetas['x0_d'+str(d)][1::2],'x'+col+sty,label='depth='+str(d)) - # sty='' - # if not d==1: - # sty='-' - # pl.plot(np.arange(1,d+1),gammabetas['xL_d'+str(d)][1::2],'o'+col+sty,label='depth='+str(d)) - #pl.legend() - #pl.xlabel('depth') - #pl.ylabel(r'$\beta$') - #pl.legend() - #pl.tight_layout() - #pl.savefig("pics/"+name+"_beta.png") - #pl.close() - - - diff --git a/BA10w Max 2,3,4,5,6,7,8 Cut.py b/BA10w Max 2,3,4,5,6,7,8 Cut.py deleted file mode 100644 index 31144ea..0000000 --- a/BA10w Max 2,3,4,5,6,7,8 Cut.py +++ /dev/null @@ -1,193 +0,0 @@ -from qiskit import * -from qiskit.tools.monitor import job_monitor - -import numpy as np -import matplotlib.pyplot as pl -from mpl_toolkits.axes_grid1 import make_axes_locatable - -import networkx as nx -from networkx.drawing.nx_agraph import graphviz_layout -from qiskit.visualization import * -from scipy import optimize as opt -from qaoa import * -from maxkcut import * -import os - -import sys -sys.path.append('../') - -from qiskit_utilities.utilities import * -from classical_maxkcut_solver import * - - -from matplotlib import rc -font = {'size' : 36} -rc('font', **font); -rc('text', usetex=True) -pl.rcParams["figure.figsize"] = 12,8 -pl.rcParams["axes.titlesize"] = 24 -pl.rcParams["axes.labelsize"] = 36 -pl.rcParams["lines.linewidth"] = 3 -pl.rcParams["lines.markersize"] = 10 -pl.rcParams["xtick.labelsize"] = 36 -pl.rcParams["ytick.labelsize"] = 36 -#pl.style.use('bmh') - -numV=10 -G = nx.read_gml("../data/sample_graphs/w_ba_n"+str(numV)+"_k4_0.gml") - -#pos = nx.spring_layout(G) -#nx.draw_networkx(G,apos=pos) - -IBMQ.load_account() -provider = IBMQ.get_provider(hub='ibm-q') - -beta_n = 12 -gamma_n = 24 -beta_max = np.pi/2 -gamma_max = np.pi -optmethod='Nelder-Mead' -circuit_version=2 -shots=1024*2*2*2 -rerun=False - -maxdepth=3 - -depths=range(1,maxdepth+1) - -outstr="" -outstrbest="" - -max_val = np.array([8.657714089848158, 10.87975400338161, 11.059417685176726, 11.059417685176726, 11.059417685176726, 11.059417685176726, 11.059417685176726]) - -for k_cuts in [2,3,4,5,6,7,8]: - if k_cuts<=4: - backend = Aer.get_backend('qasm_simulator') - else: - backend = provider.get_backend('ibmq_qasm_simulator') - - #max_val, label = find_max_cut_brute_force(G, k_cuts) - #classical_maxkcut_solver(G, k_cuts) - - outstr+=str(k_cuts) - outstrbest+=str(k_cuts) - print(" k=", k_cuts) - - options={} - options['G']=G - options['k_cuts']=k_cuts - options['version']=circuit_version - - options['name']="BA10w"+str(gamma_n)+"x"+str(beta_n)+"_v"+str(circuit_version)+"_k"+str(k_cuts) - Elandscape, gammabetas, E, best = runQAOA(createCircuit_MaxCut, measurementStatistics_MaxCut, backend, gamma_n, beta_n, gamma_max, beta_max, optmethod=optmethod, shots=shots, rerun=rerun, maxdepth=maxdepth, options=options) - - shiftg=gamma_max/(2*gamma_n) - shiftb=beta_max/(2*beta_n) - - pl.figure(figsize=(20,10)); - pl.clf() - pl.imshow(Elandscape,interpolation='spline36',origin='lower' - ,extent=[-shiftg,gamma_max+shiftg,-shiftb,beta_max+shiftb], aspect=1) - pl.xticks([0,gamma_max/2, gamma_max], ['0', r'$\pi$', r'$2\pi$']) - pl.yticks([0,beta_max], ['0', r'$\pi/2$']) - pl.xlabel('$\gamma$',loc='left') - pl.ylabel(r'$\beta$') - pl.colorbar(shrink=0.75, pad=0.05, orientation="horizontal") - - - #pl.plot(gammabetas['x0_d1'][0], gammabetas['x0_d1'][1],'xw') - pl.plot(gammabetas['xL_d1'][0], gammabetas['xL_d1'][1],'or') - - pl.tight_layout() - pl.savefig("pics/E_"+options['name']+".png") - pl.close() - print("saved", "pics/E_",options['name'],".png") - - #num_shots, av_max_cost, best_cost, distribution = getStatistics(G, k_cuts, backend, gammabetas, circuit_version=circuit_version, shots=shots, name=name+"_best") - - for depth in depths: - outstr+=" & "+"{:.2f}".format(E[str(depth)]/max_val[k_cuts-2]) - outstr+="\\\\ \n" - print(outstr) - - for depth in depths: - outstrbest+=" & "+"{:.2f}".format(best[str(depth)]/max_val[k_cuts-2]) - outstrbest+="\\\\ \n" - print(outstrbest) - - #pl.figure(figsize=(20,10)) - #pl.clf() - #for depth in depths: - # pl.semilogx(num_shots[63:], np.array(av_max_cost[str(depth)][63:])/max_val[k_cuts-2],'x-', base=2, label='d='+str(depth), linewidth=2,markersize=14) - #pl.ylabel('r') - #pl.xlabel('num shots') - #pl.legend() - #pl.grid(True, which="both") - #pl.tight_layout() - #pl.savefig("pics/"+name+"_avE.png") - #pl.close() - - #pl.figure(figsize=(20,10)) - #pl.clf() - #for depth in depths: - # pl.plot(num_shots[:36], np.array(av_max_cost[str(depth)][:36])/max_val[k_cuts-2],'x-', label='d='+str(depth), linewidth=2,markersize=14) - #pl.legend() - #pl.ylabel('r') - #pl.xlabel('num shots') - #pl.legend() - #pl.grid(True, which="both") - #pl.tight_layout() - #pl.savefig("pics/"+name+"_bestE"+str(depth)+".png") - #pl.close() - - pl.figure(figsize=(20,10)) - pl.clf() - for d in depths: - if d==1: - col='r' - elif d==2: - col='g' - else: - col='b' - sty='' - if not d==1: - sty=':' - pl.plot(np.arange(1,d+1),gammabetas['x0_d'+str(d)][::2],'x'+col+sty,label='depth='+str(d)) - sty='' - if not d==1: - sty='-' - pl.plot(np.arange(1,d+1),gammabetas['xL_d'+str(d)][::2],'o'+col+sty,label='depth='+str(d)) - pl.xlabel('depth') - pl.ylabel(r'$\gamma$') - pl.legend() - pl.tight_layout() - pl.savefig("pics/"+options['name']+"_gamma.png") - pl.close() - - pl.figure(figsize=(20,10)) - pl.clf() - for d in depths: - if d==1: - col='r' - elif d==2: - col='g' - else: - col='b' - sty='' - if not d==1: - sty=':' - pl.plot(np.arange(1,d+1),gammabetas['x0_d'+str(d)][1::2],'x'+col+sty,label='depth='+str(d)) - sty='' - if not d==1: - sty='-' - pl.plot(np.arange(1,d+1),gammabetas['xL_d'+str(d)][1::2],'o'+col+sty,label='depth='+str(d)) - pl.legend() - pl.xlabel('depth') - pl.ylabel(r'$\beta$') - pl.legend() - pl.tight_layout() - pl.savefig("pics/"+options['name']+"_beta.png") - pl.close() - - - diff --git a/Barbell Max 2,3,4,5,6,7,8 Cut.py b/Barbell Max 2,3,4,5,6,7,8 Cut.py deleted file mode 100644 index 106ba04..0000000 --- a/Barbell Max 2,3,4,5,6,7,8 Cut.py +++ /dev/null @@ -1,191 +0,0 @@ -from qiskit import * -from qiskit.tools.monitor import job_monitor - -import numpy as np -import matplotlib.pyplot as pl -from mpl_toolkits.axes_grid1 import make_axes_locatable - -import networkx as nx -from networkx.drawing.nx_agraph import graphviz_layout -from qiskit.visualization import * -from scipy import optimize as opt -from qaoa import * -from maxkcut import * -import os - -import sys -sys.path.append('../') - -from qiskit_utilities.utilities import * -from classical_maxkcut_solver import * - - -from matplotlib import rc -font = {'size' : 36} -rc('font', **font); -rc('text', usetex=True) -pl.rcParams["figure.figsize"] = 12,8 -pl.rcParams["axes.titlesize"] = 24 -pl.rcParams["axes.labelsize"] = 36 -pl.rcParams["lines.linewidth"] = 3 -pl.rcParams["lines.markersize"] = 10 -pl.rcParams["xtick.labelsize"] = 36 -pl.rcParams["ytick.labelsize"] = 36 -#pl.style.use('bmh') - -V = np.arange(0,2,1) -E =[(0,1,1.0)] - -G = nx.Graph() -G.add_nodes_from(V) -G.add_weighted_edges_from(E) - -#pos = nx.spring_layout(G) -#nx.draw_networkx(G,apos=pos) - -Aer.backends() -backend = Aer.get_backend('qasm_simulator') - -beta_n = 12 -gamma_n = 24 -beta_max = np.pi/2 -gamma_max = np.pi -optmethod='Nelder-Mead' -circuit_version=2 -shots=1024*2*2*2 -rerun=True - -maxdepth=3 - -depths=range(1,maxdepth+1) - -outstr="" - -for k_cuts in [2,3,4,5,6,7,8]: - outstr+=str(k_cuts) - print(" k=", k_cuts) - options={} - options['G']=G - options['k_cuts']=k_cuts - options['version']=1 - - options['name']="Barbell"+str(gamma_n)+"x"+str(beta_n)+"_v"+str(circuit_version)+"_k"+str(k_cuts) - Elandscape, gammabetas, E, best = runQAOA(createCircuit_MaxCut, measurementStatistics_MaxCut, backend, gamma_n, beta_n, gamma_max, beta_max, optmethod=optmethod, shots=shots, rerun=rerun, maxdepth=maxdepth, options=options) - - #max_val, label = classical_maxkcut_solver(G, k_cuts) - max_val=1 - - shiftg=gamma_max/(2*gamma_n) - shiftb=beta_max/(2*beta_n) - - pl.figure(figsize=(20,10)); - pl.clf() - pl.imshow(Elandscape,interpolation='spline36',origin='lower' - ,extent=[-shiftg,gamma_max+shiftg,-shiftb,beta_max+shiftb], aspect=1) - pl.xticks([0,gamma_max/2, gamma_max], ['0', r'$\pi$', r'$2\pi$']) - pl.yticks([0,beta_max], ['0', r'$\pi/2$']) - pl.xlabel('$\gamma$',loc='left') - pl.ylabel(r'$\beta$') - pl.colorbar(shrink=0.75, pad=0.05, orientation="horizontal") - - - #pl.plot(gammabetas['x0_d1'][0], gammabetas['x0_d1'][1],'xw') - pl.plot(gammabetas['xL_d1'][0], gammabetas['xL_d1'][1],'or') - - pl.tight_layout() - pl.savefig("pics/E_"+options['name']+".png") - pl.close() - - for depth in depths: - outstr+=" & "+"{:.3f}".format(E[str(depth)]/max_val) - outstr+="\\\\ \n" - print(outstr) - - #num_shots, av_max_cost, best_cost, distribution = getStatistics(G, k_cuts, backend, gammabetas, circuit_version=circuit_version, shots=shots, maxdepth=maxdepth) - - #for depth in depths: - # outstr+=" & "+"{:.3f}".format(av_max_cost[str(depth)][0][0]) - #outstr+="\\\\ \n" - #print(outstr) - - #for depth in depths: - # plot_histogram(distribution[str(depth)], figsize=(20,10)) - # pl.savefig("pics/"+name+"_hist_d"+str(depth)+".png") - # pl.close() - - #pl.figure(figsize=(10,5)) - #pl.clf() - #for depth in depths: - # pl.semilogx(num_shots[63:], np.array(av_max_cost[str(depth)][63:])/max_val,'x-', base=2, label='d='+str(depth), linewidth=2,markersize=14) - #pl.ylabel('r') - #pl.xlabel('num shots') - #pl.legend() - #pl.grid(True, which="both") - #pl.tight_layout() - #pl.savefig("pics/"+name+"_avE.png") - #pl.close() - - #pl.figure(figsize=(10,5)) - #pl.clf() - #for depth in depths: - # pl.plot(num_shots[:36], np.array(av_max_cost[str(depth)][:36])/max_val,'x-', label='d='+str(depth), linewidth=2,markersize=14) - #pl.legend() - #pl.ylabel('r') - #pl.xlabel('num shots') - #pl.legend() - #pl.grid(True, which="both") - #pl.tight_layout() - #pl.savefig("pics/"+name+"_bestE"+str(depth)+".png") - #pl.close() - - #pl.figure(figsize=(10,5)) - #pl.clf() - #for d in depths: - # if d==1: - # col='r' - # elif d==2: - # col='g' - # else: - # col='b' - # sty='' - # if not d==1: - # sty=':' - # pl.plot(np.arange(1,d+1),gammabetas['x0_d'+str(d)][::2],'x'+col+sty,label='depth='+str(d)) - # sty='' - # if not d==1: - # sty='-' - # pl.plot(np.arange(1,d+1),gammabetas['xL_d'+str(d)][::2],'o'+col+sty,label='depth='+str(d)) - #pl.xlabel('depth') - #pl.ylabel(r'$\gamma$') - #pl.legend() - #pl.tight_layout() - #pl.savefig("pics/"+name+"_gamma.png") - #pl.close() - - #pl.figure(figsize=(10,5)) - #pl.clf() - #for d in depths: - # if d==1: - # col='r' - # elif d==2: - # col='g' - # else: - # col='b' - # sty='' - # if not d==1: - # sty=':' - # pl.plot(np.arange(1,d+1),gammabetas['x0_d'+str(d)][1::2],'x'+col+sty,label='depth='+str(d)) - # sty='' - # if not d==1: - # sty='-' - # pl.plot(np.arange(1,d+1),gammabetas['xL_d'+str(d)][1::2],'o'+col+sty,label='depth='+str(d)) - #pl.legend() - #pl.xlabel('depth') - #pl.ylabel(r'$\beta$') - #pl.legend() - #pl.tight_layout() - #pl.savefig("pics/"+name+"_beta.png") - #pl.close() - - - diff --git a/Barbell Max 2,3,4,5,6,7,8 Cut_onehot.py b/Barbell Max 2,3,4,5,6,7,8 Cut_onehot.py deleted file mode 100644 index 58b4632..0000000 --- a/Barbell Max 2,3,4,5,6,7,8 Cut_onehot.py +++ /dev/null @@ -1,113 +0,0 @@ -from qiskit import * -from qiskit.tools.monitor import job_monitor - -import matplotlib as mpl -mpl.use('Agg') - -import numpy as np -import matplotlib.pyplot as pl -from mpl_toolkits.axes_grid1 import make_axes_locatable - -import networkx as nx -from networkx.drawing.nx_agraph import graphviz_layout -from qiskit.visualization import * -from scipy import optimize as opt -from qaoa import * -from maxkcut import * -import os - -import sys -sys.path.append('../') - -from qiskit_utilities.utilities import * - - -from matplotlib import rc -font = {'size' : 36} -rc('font', **font); -rc('text', usetex=True) -pl.rcParams["figure.figsize"] = 12,8 -pl.rcParams["axes.titlesize"] = 24 -pl.rcParams["axes.labelsize"] = 36 -pl.rcParams["lines.linewidth"] = 3 -pl.rcParams["lines.markersize"] = 10 -pl.rcParams["xtick.labelsize"] = 36 -pl.rcParams["ytick.labelsize"] = 36 -#pl.style.use('bmh') - -V = np.arange(0,2,1) -E =[(0,1,1.0)] - -G = nx.Graph() -G.add_nodes_from(V) -G.add_weighted_edges_from(E) - -#pos = nx.spring_layout(G) -#nx.draw_networkx(G,apos=pos) - -Aer.backends() -backend = Aer.get_backend('qasm_simulator') - -beta_n = 12 -gamma_n = 24 -beta_max = np.pi/2 -gamma_max = np.pi -optmethod='Nelder-Mead' -shots=1024*2*2*2 -rerun=True - -maxdepth=3 - -depths=range(1,maxdepth+1) - -outstr="" - -for k_cuts in [2,3]: - for alpha in [0, 2*max(G.number_of_nodes()/k_cuts, k_cuts*G.number_of_edges()), None]: - if alpha == None: - circuit_version=2 - else: - circuit_version=1 - - outstr+="k="+str(k_cuts) - outstr+="alpha="+str(alpha) - outstr+="version="+str(circuit_version) - print(" k=", k_cuts, " alpha=", alpha) - - options={} - options['G']=G - options['k_cuts']=k_cuts - options['alpha']=alpha - options['version']=circuit_version - - options['name']="Barbell"+str(gamma_n)+"x"+str(beta_n)+"_v"+str(circuit_version)+"_k"+str(k_cuts)+"_onehot_alpha_"+str(alpha) - - Elandscape, gammabetas, E, best = runQAOA(createCircuit_MaxCut_onehot, measurementStatistics_MaxCut_onehot, backend, gamma_n, beta_n, gamma_max, beta_max, optmethod=optmethod, shots=shots, rerun=rerun, maxdepth=maxdepth, options=options) - - max_val=1 - - shiftg=gamma_max/(2*gamma_n) - shiftb=beta_max/(2*beta_n) - - pl.figure(figsize=(20,10)); - pl.clf() - pl.imshow(Elandscape,interpolation='spline36',origin='lower' - ,extent=[-shiftg,gamma_max+shiftg,-shiftb,beta_max+shiftb], aspect=1) - pl.xticks([0,gamma_max/2, gamma_max], ['0', r'$\pi$', r'$2\pi$']) - pl.yticks([0,beta_max], ['0', r'$\pi/2$']) - pl.xlabel('$\gamma$',loc='left') - pl.ylabel(r'$\beta$') - pl.colorbar(shrink=0.75, pad=0.05, orientation="horizontal") - - - #pl.plot(gammabetas['x0_d1'][0], gammabetas['x0_d1'][1],'xw') - pl.plot(gammabetas['xL_d1'][0], gammabetas['xL_d1'][1],'or') - - pl.tight_layout() - pl.savefig("pics/E_"+options['name']+".png") - pl.close() - - for depth in depths: - outstr+=" & "+"{:.3f}".format(E[str(depth)]/max_val) - outstr+="\\\\ \n" - print(outstr) diff --git a/Barbell MaxCut.ipynb b/Barbell MaxCut.ipynb deleted file mode 100644 index 91931f7..0000000 --- a/Barbell MaxCut.ipynb +++ /dev/null @@ -1,305 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from qiskit import *\n", - "import numpy as np\n", - "import pylab as pl\n", - "import networkx as nx\n", - "from qiskit.visualization import *\n", - "from qaoa import *\n", - "\n", - "from matplotlib import rc\n", - "font = {'size' : 16}\n", - "rc('font', **font);\n", - "rc('text', usetex=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "V = np.arange(0,2,1)\n", - "E =[(0,1,1.0)] \n", - "\n", - "G = nx.Graph()\n", - "G.add_nodes_from(V)\n", - "G.add_weighted_edges_from(E)\n", - "\n", - "pos = nx.spring_layout(G)\n", - "nx.draw_networkx(G,pos=pos)\n", - "k_cuts=2" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "depth=1\n", - "createCircuit_MaxCut(np.array((np.pi,np.pi)),G,depth,k_cuts,1,True,\"depth1\").draw(output='mpl')" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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C6gwMiYsPUyItUnJdv7vP6vF77FA9jKnCGeWK/+x8xEbrAQjTQlLHpqH9nFPiKP2n5FwTBUupda218QNQbq4p9NjAEBGpRH9HQitrS3DspB0vV1uQlJCC/GzhNvKx0Xo0tTikDJGIFIrjB2kJGxgiIpXLzy5y73T0fK/nf4mI+sLxg9SI18BQ0OR+eBRRKLCupcNckxaxrqXDXIcvnoERyZi48PvuLVu24J577pHny4lCRK66Hp4o+VfK+r0AxxDSJjnqWs6/x+E2hsydOzeo9RyfNQEADOOSPF5L8d1axAZGJEvT5I5AeuvWrePOB2mOXHU9JUfyr5QdxxDSIjnqOhzHD0CeXJeWlga13hPFwoPXX7As93hNweEUMiIiIiIiUg02MEREREREpBpsYChoL730ktwhEImOdS0d5pq0iHUtHeY6fLGBoaDNmDFD7hCIRMe6lg5zTVrEupYOcx2+2MBQ0DIzM+UOgUh0rGvpMNekRaxr6TDX4YsNDBERERERqQYbGApaenq63CEQiY51LR3mmrSIdS0d5jp8sYGhoO3evVvuEIhEx7qWDnNNWsS6lg5zHb7YwBARERERkWqwgSEiIiIiItVgA0NBs1qtcodAJDrWtXSYa9Ii1rV0mOvwxQaGiIiIiIhUgw0MBc1sNssdApHoWNfSYa5Ji1jX0mGuw1eU3AFoxZ8/BE62yfPdY+KApWnyfDf55+PtwJlmeb57eCIwJUee7yb/yVUjrA914BhC3rA+yJdVq1ahvr5e8u+dO3cuSktLRd8uGxiRnGwDGmUaPEj5zjQDzhNyR0FKxhohb1gf5A3rg3ypr69HXV2d3GGIhlPIKGgrV66UOwQi0bGupcNckxaxrqXDXIcvNjAUtEceeUTuEIhEx7qWDnNNWsS6lg5zHb7YwFDQMjIy5A7BbxcvAydar/z+1Vn5YtG6C5eAz1qu/N5+Tr5YgqGmulY7NeW64/yV18e/BM5dlC8WrTvTY8z4rEUYU9RETXWtdsx1+OI1MBS006dPyx2CV+cuAh9+AvzLITQvXa4rn617AxgxFJg+Brg5FUiOly9OLeg4L+R5twNo+gpw9cj1T7YC+hhg9ljgplRg1Aj54vSH0utaS5Se65Z24IMGoP4z4XW30m2ADkDiCGDeBGDBJGBEtFxRasO/vwLebwD2fw44exxg2vC/gE4HJOmB+ROB+QYgZohsYfpF6XWtJcx1+GIDQ5rjcgF7jgt3hjt7of/lvj4H7GoUfuaMBczzgeFDJQtTE7pcwPtHgb/Wez9K6jwLvPux8LMgBVgyDxg6SLIwiQJy4RLw1l6g7gjg6mcZF4Avvgbe2gdsOwDcNgvImQ5Ecl5DQM5eAP6yRzgA0h+XCzjVBvylDXh7H3DX9cDCyUCETro4iUhZ2MBQ0KZPny53CL1cugz8YSdg/zSw9fZ+DhxrBpZlAhOvDU1svjS1OFBZW4y6fVuw7I5itHc68fXZFoyISUB+dpE8QXlx7iLw6j+AI02BrberEfi4CSjMAa4bGZrYBkKJda222vCXEnPd0g6U1QLNX/u/zuUuoHovcPAkUJAFDJPhDIEaa+RUG1C+w/OMiy/nLwHW3cChk8B/LwKGKHAvRol1rcb68IcSc03S0OyxIpvNhsLCQrnD0LStW7fKHYKHy13A794LvHnp1nEe2LRdmN8uh6QEAxYvKERSvAGLFyxHfnYRChYX4+MTu1FZWyJPUP24cAkorw28eenWdhb4dQ3wxVfixiUGpdU1oK7aCITSct3WAfymJrDmpafjXwIv2ryf+Q0VtdVIkxP4jS2w5qWnQ6eAih3C9Y1Ko7S6BtRXH/5SYq7D2bBhwxAVJc1RBc01MHa7HSUlJSgrK0Nra6vvFShoTz75pNwheKg9DOz3cR/80vuEn/5cuCScVeiUYQekP0nxBnx8YrfcYXj4Wz3g8DH12FeuO84Dr74nnDVTEqXVtTdKrI1AKCnXXS5g8/tCc90fXzUNAKecwFYF/S9RYo1cvCyMs94aPX9yfewLYaqf0iiprn1RYn0EQk25VpO4uDgsW7YM5eXl2LlzJ/bt24fdu3fj97//PVatWoXx48f3WmfYsGF4++238cc//lGSJkZzDYzRaERRURHS09PlDkXzqqqq5A7B7YuvhLnRYnCeBd78SJxtDVTDCTs6Op14zFwhdyhujmbhWhYxNDmBmoPibEssSqprb5RYG4FSUq7fP+q7KffXnuPAAQU8VFCpNfL3/cL1Q2LYcVi+s+b9UVJde6PU+giEWnKtFqNGjUJFRQVOnjyJiooKFBQUYMGCBZg1axbS0tJw3333YePGjXA4HHjzzTcxY8YMAFeal0WLFuGGG27AqFGjQh6r5hoYNXj1sRR8dsDm8d7+7eX48wu5MkWkfrWHhSlkYvlnI/BVp3jbC0R7pxP2ozbYj9pQvasMGbPzEButBwDYj9rwzOY8vLvPinf3WfHd9SmSx2cTueGoOyLMayffvNVGwwk7Hi6d554OUlFtQUW1Be2dTvkCVonLXeLXdc0BcbfnL6WPH+cuincABBBupvCOwg6CKBnHEOqP2WzGwYMHsWzZMkRHR2Pbtm1YtWoVMjMzMXv2bNx4441Yvnw5/vCHP+DixYu46667YLfbsW7dOnfz8vnnnyM7OxsnT54MebwKvPzNN7vdDpvNBoPBAL1eD7vdjqIi9V6ERgPTeUE44immLhew6xhw6yxxt+uP2Gg9jKkmAEDq2DTcv34i3nimDQDQfk44WhYbrUdFtQX52RZJY2tpBw6fEneb5y4C9uPAjZPE3a4WeauNyclGrL2/CqVbC5GfXYQpY9ORMdssZ7iqcfCk+AcsPm0BPm8Fxkp8i3Yljx+AcGt7sQ9YHDghnDnXx4i7XS3iGEJ9efjhh/Hiiy8CALZt24ZHH30UDQ0NvZbbtWsXKioq8MMf/hDPPvssVqxYgaeeegoA3M1LY2OjJDGr7gyM3W5HQUEBioqKYDab4XA4UFlZKXdYYamurk7uEAAI0wdCcSHn0X+Lv81AxUbr0d7pRMMJOwDAONnkfu+jBhsWL1guaTzHvuj/trIDoYRcd1NKXftydW0AwoW6k8YYUWothHGyScbo/KOUXDeEqP5CtV1/KW38AEKTExeEsUkplFLXvnAMIQD41re+5W5eHn/8cdx22219Ni89ffnll3j88cdx4MCVU81vvPGGZM0LoMIGpqCgAMXFxe7fGxsbYTIp/y+ZFh08qIzz9p+H6F4NVz/8Ui5J8QY0tQoPSThzVvjDbrAWYLUM85ZDletQbTcYSqlrf/SsjaYW4b/35qyBvcHmnhaiZErJdajq77OW0Gw3EEoaPwBt57qbUuraHxxDwltCQgLKysoAABaLBb/4xS/8Wq/7mpeZM2fi9OnT6OrqwsMPPwyj0RjKcD2oagqZw+GA3W73aFhsNptHQ+PPNuLj46HX6/1aXqfz70lZd/+4FsnTsvyOY/v/FGJIzJUYzp91YkSiwe/1e6qr24Ef3JId1Lr9Wb16tc9lNm7c6HO5jRs3ihVSv7IfeAmzTQ95vOfr7jX9fb7q9Suvz18CooeNxIXOgV9t+vMVtZiTkuV1maYWB3bsrcR1CQZU7yp3Hx1ddXcZ/vZPYYDJmG12Hy2bnGx0z0329g9NXd0OpN8rTn3cueoNpKQt8XhPjFw3fXkWOt2wgQXnByXXtbca8bc2AMDeYMOyxcWoqLagYLHvsVHM+uhJybm+2vdKP8Xwa8Z5vOetrv2paQB4q+Y9PJixaIDRCXyNIaEaPwBxa+SRVy8gMurKU2zFGD8A4OXXtuDu9PwBRuebUutarPoAOIaEiuUFIc86nc7jtZx+8pOfYNSoUdixYwd+9rOf+bVOzwv2u6eNrVy5EqtXr0ZpaSkyMjI8lq+rqwvoz+ly+XfkWFUNjN1u79XdXd3QeNPd7FgsFtnP2uR8rwzjZl6JYf/2cjT8i3fTCEZIBwAJB5ekBEOf/1gYU03uOcsA8PJbFqy6Wxj87A02aU/zhygfcg/iSudvbTS1OJAUb8DkZCOqd5UJvycEd2AkrISq/jh+9BKqv+s6neomlEiKYwhdLSYmBg8++CAAoVn0p3Hoq3lpbGzE2rVr8f3vfx+LFi3CrFmzsH///lCHr64GxmDw/EtUUlISUCNiMplQU1MT0Hf62wn+ugZobA5o06LJzMyC9Tlx5zodOXLE5zIbN27E8uXe51Bv2LBBrJD69dZe4O9X3fHn6qNz3bqP5vX3eU9RkcDZM05EivDv4od/Apwi3FbVflS4e11TiwP2Bhsqa4vx2hrvc04zM7Pg2iROffxpF7Drqq8TI9fX6KP9/rs2EEqu64HWiP2oDS+/ZUFJ4TsAAOPkXDy7OQ9r76/yugMiZn30pORcX+3nbwtTRnvqq24DqWkAuCXnJmx5WpzcijGGBDN+AOLWyJN/Br7uccMEMcYPAPjv+8yo/mX4jiFi1QfHkNB5orgcgLBf2fO1VLKysjyuGbr99tsxcuRI7Ny5E/X19T7X7695AYCOjg5s3rwZK1euxLe//W2PBiYzMxM7duwQ+4+jrgbGaDQiPz8f5eXliI+Px+7du5Gb63nrYYfDAavV6n6QpcViQW5uruxnXLTo6aefljsEAEByiO7yM0YPUZoXMV19tEzqi3CT4wGE4Bo9qe/U5I1S6jpQxlQTXkrd4/49P7sI+dnKvjujUnKdHNe7gRGDkuoakH/8AIRcHwrBLeqVlGul1HWgOIaEl7S0NADw68C+t+alW01NDVauXOnebqipqoEB4HG75PXr12PNmjUenxsMBhQVFfG2yhK455575A4BADDxGiBCJ/4F94ZEcbenBSkhyomScq2Uug4HSsl1SmLvM4tiUFJdK0VKInBI5FuxA8rKtVLqOhww18Hrfgjl3r17vS7nT/MCwH0Wp3u7oaaw48uB6euaGDV4YEOjx/UvADArZzmWPhHY9Da5TZs2Te4QAADDo4FZyeJvl88l6S1JLzSMYoqKANInirvNgVBKXYcDpeR6zjggepDv5QKROAKYpKCdaqWYbxD/zHZKIjBqhLjbHAil1HU4YK6DV1lZieeeew779u3zutxPf/pTn80LADQ3N+P5559HaWlpCKLtTXVnYADhYvyysjLo9XqUl5f7nP9I2pc1Ddj7uXjbm5ks7IBQb9nTgU/eFW9781OA2KHibY8oUIOjgJtTgRoR78iaPU3Sa/hVY3g0kDYR+KeIZ7xyuA9LFLDXX/fvArO1a9di9OjRWLNmjdfnvHR2duLHP/6xWOH5pMoGxmQyBXVNi9Vqhc1mg9PpRHx8vCrP3lDfJl4LLEoF/nF04NsaOggwpw98O1o1KxmYM1achlEfA9w1d+DbIRqoW2YJNd088LumY9Io4IaUgW9Hq755PXDoJHDm3MC3df14YEYIzsATkeDMmTOKnKqnygYmWGazGWazWe4wNCMrK0vuEDzceT1w/EvvD0rzdUcbHYB7Fwg71tQ3nQ7Imw+ccgKnz/S/nK9cR0UA9y8EogeLGt6AKa2u/dHU4kBlbTGaWh1YdkcxJier4+CMknI9KBL47k3CHSXPX+p7GX/uiDUyGvivBcJ1edS3YUOA+28CymqBy119L+NPrhNHKPNgk5Lq2h9qHT8A9eWaxBNWDQyJa9OmTXKH4GFIFLAiByivBT4N4qnMkTrgvoXCfHilaDhhR/WuMnzd2YqOTicyZufJcuegq8UOBVaagE3vAF8EccR6cBTw/QwgZZT4sQ2U0uraHw0n7VhlLkN7pxMbrAV48n51PFNKablOjgce+oYwhpy9EPj6cTHC+vGx4scWDKWOHwCQep0wBrzyD+Di5cDXv24k8FCO0AwpjdLq2he1jh+A+nJN4lH1Rfwkr4ceekjuEHoZNgR4NBe4ZWZgR0CT44Af3Q4YJ4QstKAkJRhgTM3FY+YK5GdZFLPzAQhnqR67TZi6F4iURKDoDmBKUmjiGigl1rUv3U/QBoAR0fGwH7WhotqCUmshntmch3f3WWWMrn9KzPWEa4CixcD00YGtlz4R+L93KOvaOSWPHwAwfYwwFky81v91dAAypghjz0iFnilXYl17o9bxA1Bfrkk8PANDQQvFg4nEEBUJ3DFHuFD0vaPAbgfQebHvZQ3XChfvzhmnvGe+AEBstB5NLQ5gMtDU6pA7nF6GDALuThfm+7/fAOw5DlzoY/qNDkLDcnOqsNOi5Ok1Sq1rf7xcbcGyHk/bNqaaYD9q83j2h5IoNdf6GKAgCzj6b2EMOXiy79u0R0UAc8cBN08RGh+lUfr4AQDXjgAeNQk5fq8BONoE9HVH/MFRQNoEYQwZHSd1lIFRal37orbxA1Bvrmng2MCQZiWOAJamAUuMQPMZ4GSr0MhERgAJscJ0kRiFXX/Rn9hoPdo7nXKH0a/keCD/BmE++r+/Ak61CdcRREUIOyhj4oSbI9DAXH0kNHao3r1zUfGfnY/YaD0AYVpI6tg0tJ9zShylNuh0QtM9JUloyk+2CdMlL10WdqaTRgq3FY+KlDtS35Q+fkREALPGCj/nLgpjdfMZ4fqYoYOA0Xpg1EhlHmRSE44fpCVsYEjzIiKE+dLXjZQ7kuB0PwlZ6U9EBoQdjDFxwg+Jr+dUj54qa0tw7KQdL1dbkJSQ4q4V9xF4GpDBUcI0p0CmOimFmsYPQGhYUkYp8/o4teP4QVrCBoaCdvjwYblDIBKdGus6P7uo1w6qGnZc1ZhrIl/UVtdqHT8A9eWaxMMTshS0LVu2yB0CkehY19JhrkmLWNfSYa7DF8/AiETOKTNyffe6desU+XAjJRqeGJ7frUZy1bVc/5/krA+OIf7jGKIectR1uNYHxxD/zZ07N+B1HJ81AQAM45I8Xof6e/3BBkYkS9PkjoCUbEqO3BGQ0rFGyBvWB3nD+iBfSktLA17nieJyAMALluUer5WAU8iIiIiIiEg12MBQ0F566SW5QyASHetaOsw1aRHrWjrMdfhiA0NBmzFjhtwhEImOdS0d5pq0iHUtHeY6fLGBoaBlZmbKHQKR6FjX0mGuSYtY19JhrsMXGxgiIiIiIlINNjBERERERKQavI0y9Wnq1Kk+l1m3bp1fyxEpBetaOsw1aRHrWjrMNXnDMzAUtKeeekruEIhEx7qWDnNNWsS6lg5zHb7YwBARERERkWqwgSEiIiIiItVgA0NERERERKrBBoaIiIiIiFSDDQwREREREakGGxgiIiIiIlINNjBERERERKQabGAGoLCwELm5ucjLy5M7FCIiIiLSoJKSEuTl5aGwsFDuUAJisVjgdDpDsm02MEGyWq3Iy8tDTU0NDAYDysvL5Q6JiIiIiDTEbrejsbERVVVVmDdvHqxWq9wh+aWwsDCk+8ZsYIJkNBphMpkAALm5udizZ4/MERERERGRlthsNuTm5gIA0tLSUFNTI3NE/ikrK0NaWlrIth8Vsi1rnMFgcL+22+2YN2+ejNEQERERkVL8a+8R7LQf7PX+L1/Z2ut1UmI88u7Igk6n67V8S0sLjEYjAGHf0+FwhChi4GznOfxu6zZcuHjJZ8wAkHdHJkaPuiZk8XjDMzAD5HQ6UVNTg+XLl8sdChEREREpwPUzJqGrqwtNzS1oam5xv3/16+aWNmTMn9Nn8yK1mOihMM6c7DPmpuYWjE26VrbmBWADMyBOpxMFBQWoqqqSOxQiIiIiUohBUVHIvzMbkRHed7VvXZSO666N7/fzhIQE94XwDocDer1exCh7mz9nGqYYxnpdJkE/AotzbgxpHL6wgRkAi8WCioqKkBcTEREREanL6FHXIHdR/9eBTBybhJvTZ3ndhslkcl/30vN6mFDR6XQw356JmOgh/X5+z+IsDBk8KKRx+MIGJkglJSWw2Wz4xje+gXnz5sFisXh87nK5ZIqMiIiIiJQgY/5sjB8zqtf7QwYPQt7iLET4OENjNBqRkpKC3NxcNDY2SnLJwvDYGCy9NaPPz7IWzMH45Ot8bqOwsBAffvghCgoKYLPZxA4ROlcY7WlbrVZUVlZKMuXrT3/djriRsbg1Y37Iv4uIiIiIlKnF+TV++cpWXLhw0f2e+Y5MpM2aImNUvm2proX9QIP799GjEvDw/UsQFRkpY1SCsDgDY7FYEBcXF9IH6vTU1NyC+kPHoNOFRXqJiIiIqB8J+hG4q8c1IzNSJ2DezFQZI/LPN003QT8iFgAQFRmJ/DtzFNG8AGHSwBQXF6OtrQ1ms1mS73vnfTuGDB6Em9NmSvJ9RERERKRcabOnYNqkcYgdFo3/c+siRdx1zJehQwYjb3EWdABuzUzHqGvi5A7JTVNTyCwWC6xWKxwOB0wmE8rKyjye12KxWGC32wN6CNATxaF7iigREREREQlesPh3jY9mHmSZl5fnfiZLfHw8bDabJNPFiIiIiIhIOpo4A+NwOJCSkoK2tjavtzQO5gxMIJqaW/DLV7YiZ6ERt3i5bR4REREREQVHE2dg7HY7DAZDSJ7HEswUsu0f2LH9A7vosRARERERaZW/U8jC4iJ+IiIiIiLSBk2cgTEajXA4HHA6naKfhfG3E/z9GzVoOH4ClhX3IiZ6qKgxEBERERGRQBNnYAwGA8xms/tCfqfTifLycpSXS3MHsabmFhw4+gluSpvF5oWIiIiIKIQ00cAAQFVVFQwGAyZOnIiJEyeipqYGJpMJAFBSUoK4uDiUlJTAZrMhLi4OeXl5on13q/MM4kcO53NfiIiIiIhCTBN3IVOCrq4uRERoph8kIiIiIlIkNjBERERERKQaPGVARERERESqwQaGiIiIiIhUgw0MERERERGpBhsYIiIiIiJSDTYwRERERESkGmxgiIiIiIhINdjAEBERERGRarCBISIiIiIi1WADQ0REREREqsEGhoiIiIiIVIMNDBERERERqQYbGCIiIiIiUg02MEREREREpBpsYIiIiIiISDXYwBARERERkWqwgSEiIiIiItVgA0NERERERKrBBoaIiIiIiFSDDQwREREREakGGxgiIiIiIlINNjBERERERKQabGCIiIiIiEg12MAQEREREZFqsIEhIiIiIiLVYANDRERERESqwQaGiIiIiIhUgw0MERERERGpxv8HZhWgpq4RekwAAAAASUVORK5CYII=\n", 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" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "depth=2\n", - "createCircuit_MaxCut(np.array((np.pi,np.pi,np.pi,np.pi)),G,depth,k_cuts,1,True,\"depth2\").draw(output='mpl')" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'00': 0, '11': 0, '01': 1.0, '10': 1.0}" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "costs=listSortedCosts_MaxCut(G,2)\n", - "costs" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "Aer.backends()\n", - "backend_sim = Aer.get_backend('qasm_simulator')" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0, 0.5, '$\\\\beta$')" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "n=12\n", - "m=24\n", - "beta_max=np.pi\n", - "gamma_max=2*np.pi\n", - "\n", - "circuits=[]\n", - "for beta in np.linspace(0,beta_max,n):\n", - " for gamma in np.linspace(0,gamma_max,m):\n", - " circuits.append(createCircuit_MaxCut(np.array((gamma,beta)),G,1,2,1))\n", - "job_sim = execute(circuits, backend_sim, shots=1024*2*2*2)\n", - "Elandscape_v1,_,_ = measurementStatistics_MaxCut(job_sim.result().results, options={'G' : G, 'k_cuts' : k_cuts})\n", - "f = pl.figure(figsize=(10, 6), dpi= 80, facecolor='w', edgecolor='k');\n", - "pl.imshow(-np.array(Elandscape_v1).reshape(n,m),interpolation='bicubic',origin='lower',extent=[0,gamma_max,0,beta_max])\n", - "pl.colorbar(orientation=\"horizontal\", pad=0.2)\n", - "pl.xlabel(r'$\\gamma$')\n", - "pl.ylabel(r'$\\beta$')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "from scipy import optimize as opt" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "def getval(x, backend, depth=1, version=1, noisemodel=None):\n", - " j = execute(createCircuit_MaxCut(x,G,depth,k_cuts,version), backend, noise_model=noisemodel, shots=1024*2*2*2)\n", - " val,_,_=measurementStatistics_MaxCut(j.result().results, options={'G' : G, 'k_cuts' : k_cuts})\n", - " global it, values, gamma, beta\n", - " #print(x)\n", - " it+=1\n", - " gamma[str(it)] = x[0]\n", - " beta[str(it)] = x[1]\n", - " values[str(it)] = val\n", - " return -val[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: -1.000000\n", - " Iterations: 27\n", - " Function evaluations: 54\n", - "[1.5587047 0.39277718]\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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w8BAvvfRSU7pT6ap+7rnn8MILL+DWrVt4/PHH8dprr+GNN95g6zgeHh7ixo0bODo6SmMYL1++jNu3b+OFF17AwcEB3njjDQaWO1ENGs03OgP6ZJ4LYHERKFqQaACiBoe1OBYvTm1QbKz9yb4IqkJgDS7n0s5pcH7j9bnm4FCzk0BqwaAFmZ4AYA5rifdhDKRPYQ7IQBlsnSPHozBIjGZB0jsCeyRMnpEESI/S+wjk7dDyLPU6LoXGKuxZXsUNQVGGV72ilu2cfWM4t/G6jUxv2FRtW7QtTC6o0tkZXnnuEzsZP93eTg0vIK4GiaQ6SHt17GOsJjIfz7lM5gM0gGTIeDquj9kyqQBJq+4cPFIp8LhvXsd91qZf1HvhhRfw9NNPJ766fv06PvvZz+LOnTvmJOWoUwHHg4OD2eV3nnrqKdy5c6cIf/rpp7c69sbdFsp2AYzFdgMwijAKggwWi0rvq6AoQdACxCKcFH8QcXKbQiAPrwOkBoO1n6UGj3NguWtZoCnDZakYDFqQqEDmHFx6FueZXQ0qJVBmIOT5ql7FYOBjC+XD/eTd5D2MLRptRTSAVLqwPQg8xoIIeGxVFRpr0KbB8ayNkt8GoLgEEJu8kzNA2ASYIk7d19JUbFvVUr03Aozy1rPz0sCN2Lp4f8s88gO6PK4BlenWZ8/WRlvjb7yE2btowaIIDwehXkgNIMmjJ5XXgsekhi7r/ZHb667qTb+oFz+cQh1zBwcH+PKXv8zy07QXs6r3RtaN3AKNsmIQ2GNwSMOkl48BooBFAnZzoKhBogWIEg7j34GWA7ZncRD5yXC5LdNbNlZYimtojbbxRtYmwowK5kpwLEDSgEUJgCxMswt/qfdSQqEFlfmvFq7DZGo84sEoSCoQmTxz0QupuiFSyXNepIGpwiNEmyMarWQgDmFBYx3eCDDWwNCARRUCK/DX6rG07bxuNxO22FMp4tR4w87Sou7tBpldz+ygWrq6jdYFLLuRKcwlr50Bf/kN3sizAomu0U4DSVZ/Yj4aRJIwD6cCJK2mMa0Fj2fSk+iB9Z6C4zZf1Ds8PCzSXrx4ETdv3pw9bgfHKPnk027uFmi0vIkWMBJ7x7Zz2vyMmVoX6i3k2zooapA4B4jFvshDs7XigRL0toXHFk9jC1xq0sCQxc9AogWNNF8VHpUwCYGah9KCyhpQ1mAyb5O/Ycd5lz2NseVyIT42MAGQHARAThmQFiadiQ2P0bTlp5wBoCo0MrjTgdG258VwVrwCh03xxTENQJwBy6rtTBg7rhJXpKvY1bQLJxTtYrUPZKXTbSKIuiJcD4vGEu6ibe429kWaEMH2GVAugUTWlpR2iR9jvaOQFwxkx4BHeLGk9TJCYTRsgUf6BujJAUiZ9gEyPebbhNPSNl/U03p05yYpRz1Q4Nh8EzpluxUaFUCUEDkLjNK7KIBQwqIKj7BBkUJhDRBrYJj+kge05p2UgFeDycGNkNoUHLfpwq6Ne9TiOATmN9M5UFQhEGVcCYZ1qKR2EQxHDwwkzvvw/VXiPcjQOMEe9UQWEOldags8kLuq/dRoe9KShGZGtKKJEHkLJeEx2kDYtYhCD91XIJB6Ge24nEfNu1iDwbm8dK+k5/FaXsx+2X46RhGWt1vC1XiqRq/iplVXGfmgZK7H1qGRgGgFGhNcUshT9hlQGjbOecWb6PLxFChl5dEgMaYjkCiBMXsXwQCy3Cdjpsk1m4XHrp1ql1/U0yYpW3qgwHGxtoVGsS+7pDVgTCbEuyg9iSo8hnRDiuegSCGQQiIFQQl+Eg7NeAUiKQSaXkgJlQVIWtBYAiYArHbhriBaG4Aix7swyFsAizEfCYsWWFp2NaCcg0kGkkACSeqR9N4XEJkYwPvkhfTxvozd2H5qYIAc7lkLIlsTAY+Y6lyabS1/XqeESXl+BBMapZdRglwNGKsguixuytOrYLjEe1nG+dJW2zfD8k4NHDf1Ou6yq7reTS1viJiGFsaII/mW0Bjg0lnxGfpUoJRtisMsTJogScsgAXImTgVIKPuIdRvxtTCXm8Jjso0XjtjEAle8jvuiXXRVv/322/jUpz6V9uVHSjbR0i/q1XTlyhW8+uqrsxNjgA6Ok5YAxxJoJKDoHLeLYxgtD2PNu6h5Fi1YZN5F2KBI4U8DRAmHEd4kPLIwlGE0LVDCXgs8WuCo5bep6tC4Jvs6NNL0CRAL27UJizWoLGAQPG5F44Rn0ZG0jsDh6H3ySCaIxARuvPs673sfPAoTaXKADP4IF1qRCKLJ+0jhkbmKCDyG3UIu+CK1OG+Fi7xmoFGHS1aENihUoLNM48s0EMesAKcKiXOASNMBCQylvR0mLrIESK2KNlbNTSEydycb6TVgHEQUsSm7p30I16ARicQolFHoK+McB76QRc2LSOEwdRdTOJ0DRRGfjut5mgIgFQhMZfG5VrNr6JX9hWCYAPOUtenqG1SPPPIIvvGNb5jx169fN7+cJ/XKK6/g4OBg8Rf1LD3zzDNsqcM5dXCUkmCYKp4vbYDF0KhNetGAMcZrwEgBMIZZnsVoK8MlKM5B4pyXMYdPLQYFuKUAqY1NXNKNDQAr2HBpqfYh+3Ico/A6KtCYbQggBjtpI+NHP/JwYm/B5MpxmIwQmb2MJUjGuGwHjD6PL4wQGQEygmIGyNiUhA5qFwASSC0LiYUJj9SdQeWA1GUNYj4nix0kHFrQaACcum0B3yxI+mpaum9DozfC+XWY8tHhUAVPiDBanSyA1K557XfYsSxgVNv8+Axe8/2cxjEPIkAgk4If2/diH3AEJmOc5kGcwp1io4CkhMO0ncubIFIDxQijXoQjgyEDRq8AI90m8KmFwyN3WZPjJiikXscHWJcvX168JvUuvqh37do1XLlypRkagQ6OyyQfQBImKTTSh4iARg0Yo20BiQow1ryLc7AoPYo0fAobZyDSF3C4HB65tzKKwl5tbKRmL7XJGEfrrVICZW0yTLStdUlzaGyDSg0oLZgsgNFlkHTEIzn62NWVvZGaJzKGj0DyImavI/dAep8REdL72AKPcTu6WrZpT2I7agBhlAWNTtg6ywb1tDzcV9Opx2FhvkwHbdvr4aD7uaVPYFiBx+JapHh+QYuqZ6yofxKsQJ3XSWIxWVadideShwfIpGBGwNIPSJ5BDpS+8EBSmOThMyAZqwSBvXhMCyJZWci/GkBG2xjcBI+RBNNFJTb0OnqxL6XEnzZTeriqU+E0te0X9a5fv46LFy8yaLx27drssocdHKkKMJz+mN7GuC+hMUY1QmMLMAIcGueAUcIiIAAyhFOIk6BIQVCDRBsgSzCMkGeNcbSgcaV5GhWa0Oy2kTamRc6sozYR4ugDRnoLJVTWgXKCRC1uFDAIjMSTqIOkIx7JGkTGRbjz8jrcC0kn1UzSmpM9gkdDE1C57aGxGSR9ka+ZF2RYCYulnQGKM5BYTIopIDNfhBQ2KmE0jxSn/HAzv+U2Yx21sY2u2ACw9szesXgCb0CCzOz1i5GeGOVrOnn6Qv4DCOw5su0FBGa65ZDoBTA6Bn8FRDJwjP8CQAYSrAFkAkWSzVJ4TF3W8qcIx/ZkvwqQe6ZddFUfl1q+qKd9ie/mzZt49dVXceXKlTQD+/DwsGlSTQdH7XVGu0cKYCxBkcbtEhq3AUYJiwASMOoeR1+AYh0gs4dSwmENHCnoURCUAFiLi8evadVAHbXPSckuaQaLpKFaK7Op16IbugRHGygpMI5+wDkX4t0EkxIkY1nG4CVM2xhE3ASMA3ga5x0GAZBT97dPXsgCIIOd5X0cRyyDR+uncgDrrt6ALUpIa4PGJtCrhi0AxgII7bQRFlVQhQKKSjjPk4AnkOBQA0Ore5qFq2Mc7R9OewwvVZrla1VnAZZuyAel0EnNgoO/7I5WgNIH2EtgN1Jg9CpIRpdfBsZY/8ABECBtjiNh/F8CPJmeAiQaQFELWwqPNJ5eegKNzsd83W5uggdQLV/Uk1/ii1+XOTo6wrVr15hty9f4OjjOqOptTOGeVdBdQCMFwV0AowaLQAbDCIV1gMzwp0GiBYca/KlhAgIp9NXiqOZAck7FFwJcCZbUhsbF8ASMTgBkA1BOcLjGGhMQTsCY05fA6EOe4esGLndtWxApu7MjRKoAiYkBhvTXYYz3SDwHpzcjwxDWcJwI04THYnJMuqYkTvwmZpxitgloJjXBoWXr62nUv77IS8IiMJOuAoq5rAQ6Rw6gKZ22D2QotGZaiziaD9WuF/1O+cZDFh5Iz5/hayQiLLumQ/gQYdTRYAaUPsIfhUnqmVRAEiHf1CWdgJK2JQZExotNIVICZDxdCyDpGEgCnTSMThyqweMSzyFLd4Y07mlXddRc17L8Et/BwYG6jmOrOji2SFYMAYq7gsZh2MzLuBrGRcCowaEESIB7JoHJazgHijFvCYgaHK5SOcowGR6PT2WNY9xkYgwQAM6tWdjoHc4bNqMfUtwaE/CNfsD5EB+hkgLlCIfzbj3Bo5tg8DzWKW4C1QHnWPdzCZKj8wwiJ/jjEDmi9ERKgASA2CVdBUiXPY3R+7ge5+ERoUGe2lYOjwlKHMC6rOXParQ2VSdFrXVa4m1U8p0HyeXAOB1PTxeBsSgbPZYGi8y2ARQlJApAZNdDXfdRXDAxttH+rY4BJVy6y/Jh5HN8yDdWWtoGiDfrdGOOIJ7EYDFE0Mww6Z2bzteR9EOEugyUqU2QEBkPzkDQ53tcA0QP0v5UAJKap79pMInpaYQ30ovr6Ao7skC4iLc8j0xW+CnKWmXjQVUHR0sFLG6T14LuadShcUUAcBMvo+ZhLPe5Z1HCouZR1EAxjYGsACIPM8Y5knB9zONMd7XRYsmHAQXE9IbpqP2A84hQSAFygssYFkFxiOAozjXCJfVEDuE1foTDEL2EcFi7kJf32WPpfPAURs+mz7DoHQbnizC46ZrWAHJEcIQ45P14PWK+yN7H1TB1XWMcTHhMM7FjMxXgEX4aC8a6rFPyUAj6s8U8Wh7gFZg04SUetgAzcOiTee0AGncBjMxDSNKmNAIWuWezBMVsWwFEc6yjuMgFUKKqTTyRqncxqlhyJ97gGQYLj+MQX3rIWokSJqP9QDInoBhWw4eEyARUEfrSmxUyREoQ9GU4HQIcQbAARA/dc0jSaHHxEhavgU6PMwHQijtDmqrPGT+JHauD467kKt5GYXNc0HiOeB43BUbpXZSeRelV1DyKEgrLfXvyDB/7KDyOotXXPItLuqrPK88CuoQO0tYQ7NcJNs8jw2WKx5rAYwmT075L+xQk43WkHsnR1SFyHa5HhEgKiwN88kJKgMzXaq12YUfv473wC9TgccAEgprnMa7zSJuptPyNI6HUNSHdJCRNChNAaYIilWYjwC5l2QB90va4obEKjAVY+gSL/HwELGoeRauLWo55ZOMcyTapfuVaj8YPtQOPI6vKEiJHGe4JaHoOlgn6YpqwIcY0pvva5a8lwTnujdQgkkGmY15I71yeuS0AMkOitz2QjqdJ/0bkPGLYMAOPoSozmAwbDCDJZapCpFTMOKalB+3ae3VwjHLiL8DHNyY7r1TUWr7E20iDJTSG+Fr3tAWNqat6B9A4B4yql9GARQsUNQ/iwMJKO5p3slNoYNvZ1WuR5xqOl42MdYm2WnyEyQyEI9bBRzj6ASu3Zh5JCpFrP0xQFzyRI6YZ0UPwFMIN029E9iPGUoAkrQNWAXppF3Z+ix6R1xNJIVN3uXO4Nw5VeCQ9eAkevXfkng9NXgwjXscUjcq+VCssRnOv7BsgaaY3QDDbbAaNGQDp3xlgBA8r0mnASEFwxDwsWqCoQKKzILLR07jrsY7qbTPw8jjHHvTlZhqDaIOkd2665hHWfBjT69w0NjLCkcPkDYzX2oX0CD5CDw6QcFNXdoBQKKAY01Kwy38N7yM9P1/aT+eX42GlUfKgz44JIg0IDHw9+4sTsNwHFWPfH3B1cDwGqd5GgHkbqa1c1DuGa2Maq2syNkDjudCF3OJltDyMFjBqnkUJixIUqRcxA6Y+5pGmj7K6qZcAJJ0RTY89YsBK2K3I+MUBY4DAEI8BK0yANrgxpB9Dugkip5nKHCLhRr7tpnxBAHId4iRATtcg2ESUSxA44V08Lg0rH8w6PEKAIpDhMXpfB0e64zENAXAuN1nRo5jGMgqvY2qknGANCog1WFwIkoV82cZpnkgZZ9ks8TSW+S3zMlKwi9BY9TAawEg9iyYs1kCx1esobVvCWxW7nWU+ztEOhOBtjAAYjkvTBvtkR2yit8+PfsK2IYMfHAIIzgAkENJPx/chXb7VA/gF72MEyBIGF8IjOW1pz7x/1B6wgZE+PxTQo15IDTCtdPuo2sobD6I6OM6p8X6h3dQyOV3kGyCwSGxlF3W0o9BIbeWYxim8xdNoexlj3hIaC3isAKPmXbRgkY9p5N3a8Vgpvui2bptl3aKVmBATHxKxfBEsIwxOcRkkoz0FSQ0i4ZHihrjwt0MTQMKN6ZgTQQyAH1N+AAA/InofIwSuUvc6hcV5eIzeyDj2kqQK12SCQ9plvSaNUvQ6AkgQGdvz5HVE3mfd1VbXdCtIUkkb6Y7S8qjAYpkfATszXv4t7TeGxhkvo+ySXgyMEhY1aLRAsaWr2lgcfDORvOgi3/nGm/4QUGSACAhINCASYAAJTNXOB2iMAOnh08xtNxDMC2nhAkAS72O6vUM+0vu4CTxSL2JRhVw+nuV1NPdjmFF1u+5fdXDchTSXvBIuYTGFyWQEBqOot5GGyZnSKVyFxvpDelNonPMwWsCoeRYtWFwptqzsG86k1iWX5CF500OnB+pQ2qaHLIU6lHFpXQ+ST2gp1nD5GoUu5lVqRSZcm5bVGcVxMjzKRcuB6XeYa6/j70gnzNAB4vFlJnolgQiIcl8AI9lnLc0mUHgMMj2Pmt0MYBbVTYFGKx+WZwUatWPPQmOCVS+AU8DhqABjDRZroKjdcEs8jAL+ZqU9DozeRsZBY9gbvGrjR8fi4lzsCQCDTbiBUxw8MGZ4nHpxCQRq8CjgrAkejUujehFp3iI8eQqtd7navgaXDUp50HGOBEpPVw59cgxXB8cW1e4ZLc6Vzzer25qHeQzSDuWyM7SLOoURb6PUkjGNsns66rigsQaMNa+iBoq7+HrM2g9K3goYAsVDcu0HrOAT8I0+dFVjmM6fQOI6xMFR+AvjH0lL0QqPqaTxOMLzSL2MY8rT9jpqwMnGNopjriv7zKMIsJaGdU+bIHk8royZ96jNgNHIp3asOW9jTdHbqEJjOr4vQLMKjZaX0eqyNifKVECyFlZTi30x5iGExfIMJN7xbefDxJZ4o0evI/FCTvAIkW4CQAyOeO98fvD7Eh5T0XzF8wg6kWfu2kAAJcr2SQHFHM6PVQCh4WnU1FRl9wYM59XHOHI9UOC40/bH+fabXgHEwkSFSAmHRpjmgSOguKk0gJzylkA3FtubQGOLh3Guy1pLMyc6foXml7qoQbuofe7KdmMCzRFD2q/BYwSqbKvDY7pOAR5T2RSoo7C4qzdjep9pa5hpcDjXXe1rMNmouJ4kQv4n2jdWAUMr3Kx+BBBbZHZR1zQqdgIqTwQaW7qsW+IsSbCieVBwi/s1gGyARwA8LqSn8Dgdc/qf9AZmb2MJkfw8gn3EScPrWAc44xiZTJtVrW4LIbC5U2EP4NID6ov0g6yO0Ztox/fQXBfyaUuDMwlmuzyHk4TGaD+Xhs+cVmBaeEm1dSq1vGplYmnUfHyzlzUt6m68aNSkvegAy6uB6Thxhs2Ce4o1aNb2MciaETzrYWyRB1vYWxXxNtbzEgYtYwtbJsdo+W8Cjd5vBo1zabedcKNo41ngdOiAmTfaXgpkmh3YACjvo20u365e6va7eXwg9UB5HE9CmufwOPI9SU2TQPgTbw3H4CbOtD2u4wHTLOfdjmUkx9ySMKxPUu1LF0f+yozrb89Bi5eNU9wkPk6iOI7jnvbPpHX5Hlee2x7Leitp7ebdB1Fv5Y7VzHD7cLn2cD3H/uUYrg6OOxZfv67c3yZfrTJZwDaGmbRyxnCrRjjEcXTSQ0UXrwbiDOKx2I6gt/ZO7TKP8BlBkYJhDMsznD3LM9oApedRQqDmIZwDRbpED4VCmm6tQGEM0/JP8Mbys7Z5eg1A0zI9xyyrS/nUHu0E4JbD34LubRUUleNZdijDa2k0xaGsdOTb1HsXOiwHl5d2sZxubrJnYDaQLlsKbXGaPCtriI/DZjVYZnmIvIGy+9iCR1Zw44RaYFCz4ctYlOHp04Bhf5iJF3kWt1Wx7+p9fINL37mevUUd0hJALbaLwpfaLJXsft6D7uiq/P44APZFHRw3URxYsqO3olEBKw0UTUgMkDcokLjOnxxAevI7TC1SnI2bJm3EbcXDSGb8RhBbp+NOY/jgpwky67T0zMjgkUw7BICQroTHqaQj8zxSgKTgFe2o5kBSkwZg0ouoQWP6eowvoS99oxpDAY0MTMmTf2ThQ3FMDRZH79K3rOP2top5WWMm93KWIYWxVrgUACdtF4Gi1oNbAUhaNQuw21I+riE4inxdgNAQxspNANGPZDka+pfAY8guHNBzSIxgZgGkBnYajLaq1eOoASPZbobGgcflhcNdAZbFClBxMe85JTCc7P1A9mfknW0b48pwV9pV9ouybqmTHrLctbkeOHA0b87aW48V1/qmJFoVH1ZiZR8voAP+gzRQTGv/eW6b4qIILLZ6HdOi0gEe82jsyetI4VEuHWPBYyoLgGndQZ+8kiPNA0h5UoCkDS71QAIlRCZt2P7WQBHQvZBzwDjZZGhcizgKeiPxVlJojF+ToV3MESApNLJz8fkrMfSTg9o+hcTR6zOqY57egMkpnOyj9FTyeRSn10IUkCdBUNmX1U0FQkceCYYHkq3lp5ULOY80gWKB17HIfwAw0q+U+AyPaQWnvHTMFJDhMV4OprgczRxAxuNTWSNNZLpNpKUvlqnQwXERMIp4FRqdiAveRi+P6UJ7tMTbKBXTxLy09JU4NXzpvlqu/epu3kZ7+aJ8inrgwHGx5uBQiw/PbQ6GAFB2YwNgYaOfFlOWAAnkXqS0xl4BirmfqZgVS0Cy6nUEVHhcI8/qnWwI7LkRa78Ky8gAaw+xtmAu43R+I9ZYZS9rio9d0Cvi1cxex1EslZPKJLQO33tpmSRjeSMLrx7tRm6AxcmuDoxxXwJjsS08jRY0cs/j5tBIwzyxo/KwQbKwDXY5QLoyqC22E3kzZFVzBg5VTyOUNDFfck+rMEggUoPJEhIJCLJw0i1My+xEGgUe0zeIg+cxz8WdCpPjkReypvUhAKIJkCukHyytfyi7sWW39MoZPzLJfcmi4LUxgZU10bwFtxsCY7IloBhBMKan8RY05nLA9jYSCNS6x71Mq0GfBpJannP70B0x9xNnefRZ1VIdHIsWA21vUyIPLzyIat4wABJld/XoXQGKNC56HSk2DRI2VViU+9P2iFVe1gVg8MigMYJk7EZm0KgDZMw7Lj8TYVBCZBqziDGctw6SABhMpvMX7oxNRncWXkcBkBQ052CRpm/xMNL8pZexgEeje3pTaJzKbEMjhUQNDEdfAuK0D2Fb3+eRjRVRQmGr3dx+CFO9iEq4hMEY5Yr49F0RGx7lsWLVCzCQupppGgGP0W7yLgZ4dAA8W8xlsl3FNQo94tIyCfoCIHq46YGjjXGkEBnPPlbH6JXUuqm1G2DV+LtrUrtmRZgGimR73vsY86kAY7SP784J4ig8Qvc0LoFG6W2EPB7Kv8jHYZDJrhnKdlD7WQworarl51Xazq790ZkFx6OjIxwcHBzrMZx38EtuXh8exrQCh3A3ZZjDoy2ByNjojpjWxBuRl1GRXsepgBweRxefMtR7GAuRYXH0DoN3GONaj3BhAgz3Po5YTUu+IHsfR79Ky8CMfoVBAcjJ2qWu5MGNTRA5ldIGyaghHCtKQqWlNF5yZqDz3MQU2QU9XSut67ruXaR5ax5GdXvGyziVZbmnkZYTQBUa57yNHoDWTV10T7e4LrYVJThEeCNeSdLmqwCoeSFlnDNgsPAOCk9iDR7jN459OHDM0GO+2xpIy/Sk41DgTAAZyhhgkgFkyKMKkcA0hhLI4yGBDIOxikqgBAqo3LlkFW/xPlY9jzFfAZdOsbGAMdhHYExpCPwVtkugkfzNeStxBmTK9EUe6droVfV+8jJy9S/HSJ0aOF67dg1HR0d48803cXh4iJdeegkXL16sprl58yY+//nPp/2DgwM899xz+NKXvrTo2Mc9CNd70ijQShi8jSowOp+8jECGx6kBD1/tmIHHe+MQ1ulzGHz+Okz6BCGBRQmU0ySVKd3oXALG0bu0n47vPMYAm2tMoDJE+EiLeTuMoWEbIiSRiS9Adv9T4Iszsu/6DHp3seLeRL9i3tm7JF1Ndwls1iQBVAPEKbwOiSmN5k2U4Ci6oYvtLYAxHmeT7uk5aJzzNmrd1N7nL2NEWx4Avr9QmrNChiUInAlLjTA44MUN7l0UMDiEZ83I0zbDo9ZtDT7mMcKgp4DpOUBm8MyZTd4/l0eo+Hx9khNQgmBax5H8nukZRq+2K8YyFh7KoUi0O815HWc8jpN9tFVAkdjWYLHchg2MIe85L6OWNv0dSnsTGiUkGrb52pA4dl0V2/tQfVY116mA4wsvvICnn346eQyvX7+Oz372s7hz586sF/HVV1/FhQsXcHBwMAuaW4m2CCw8ERcIfQHxQS/T+OC19LFzyJPnMWuKCnik+63wCBKmeR9Lb+MElFM3twKQzk/eQj+yfTpxJ0Jk3AaAwQ8MIqc4HSThc7c0HUsiAY7CIQVLYILLKe/N13nUJtqUXdUUCNsgUd0nsCf3JSzGbe65rAPjlOdM1/SOoVHzNnKA5NfWa4DY4spo4Y1Mc7NhrKprXkcSpUFjFR6ByYmfPIXL4TEFzHkfHQqAnMYUInsgnct5kWtCR6nEuFmQBNhDiHev8x/Jp8JROZHHltLa9oqnERC3loREoA6K5JgFLIa0FEBp2jlgpHlyoLO9jJtAI+9mr9hC2NBrY0iryimunnTv1D2OXKcCji+//DIuX76cIDFuf/nLX8bzzz9fTXvhwgVcunTpBEpJJB6ydduEh7lBkO2eBEYDHtcjsBoQO4pVeFx7BwxjgjfvfYBCb3ofawAJgHVhw09fKIleR/jQdRwaIFae4ImcyuZx16/C2Mipe/sukPfdGDyFsXWKYWRiS4gaiOeRw+MqHXfXkg8KDQ6ncFeEq2EVUIz7EkQ1WIx5Wt7Emocx52kDIz3uptBIYREpDGDeRnp9U5z4EZZ4HmOVUrKQ1XaCwlBHNc9kSFjAo4BKmv8sPCJAgdf+EdBT4iZGzN7HaYMDZOwynjyHxAMpCwkAIzn3GOYRvIAEGAVIIh2OQODg8nUB9SxGKCzJvaiux+DMUdt5MpFGhUMAqtdRg0SSrtwH9yyGPBhwOZ6uGRgBJW5LaJQwWEsvZR7Hl/Fd941OBRwPDw9x8+ZN5jG8ePEibt68eRrFQerHUlqB6jjH/BQPAe1ex4o/o4BHFyq5cx7e+ekviNdvHPJkm9Co1AASgNqFPYVniLyX7KYJMatgT6ExgmTcjhCXv0vNP4s3hIYlf586X9sUFqAyhROi0D69tzqGLq/aOEcNDAG5XI8NiDmtK7q4LVCMeUQvYrS1vIspPv3LeWwDjACaoZF5GQU0Rm9jOe4x/tNbGmeEVyX4SfNCqjVRwmPwHE4XZTN4ZPYxohEgM+T5InzqFq9AJKZr7jyQvtGsgSTyb+LisjtxP459BDlGLE/aFr/P4CF1XD3UTCrkKFAo4wjEFt3TSljKZw4Uw98mWEy2JB96vF0D44x9EQax3SrLfs+hcqrue17IE9apgOOdO3eKsMPDQzz11FOzaW/cuIHXX38dFy5cwGuvvYZnnnlmoy7rrcY5xie+ld5HPKSNx+bwCPAJMxFEJUB6l2GxBpAASi9kgD4JjKvQKk3ASOAypoHHPaxSXhEk72GowmT0FlKAlGFRGlyy+MbvNbdKG89SLs/jijg1jNxkNUjk4RwUY1iKV8I1WEzxkGHlMjsaMMpwDRiByDo6NBZd1BIaPQ2rVEjqHbNMnAKGmlysaXKBmgZ4jPHEe+g8AUoWpoMgtaf5ZpDU03kE8JPx4OmqEJmuTwmSKX+ggEmAAGVcCJzkRYz4tR6V3/S4yVGbcCOqdDHTugKHU1jMpwREth/TUSAkeWmwmNITWCzDpF0FGEkZjhUaTVvPymxdZxm/cXt8Aupd1Vx7Mav65s2bODo6wnPPPVe1i+MaL1++DAB46qmn8MQTT6gg+uKLL+LFF19M++P77y8vmGxJgLIypAdnNsjN0ebwGD9VOD3MMxg6Nz27Yvf1mthJgASQvIoRIFNYhMgAfwn8SJoIjEMBjEOCOemRBEDi+JqStJuZHitKiwcELHoOklQaVC6V/gUZZ9poYEjD6+AovZEivAKKMZx3QZewSOO8SMfCPPcwAlCBkYWjDoyTLcC8jVQSGn0Om/M8VuUEEPrMEkpN2xwe0RDm2gCSA6C8Dl6JmzJP8EfBj1y3BJEg4DfS48W8Hdt1EZAI5CWPJBzrgtbgMmmVj59FfoxdyrhV1C+taFAIiO5sai+BscxLhcSwr3oq2bYCiyDbIg8VGNU0JG0jAC6GxpoUm2N+beg6Ae0FOF65cgWvvvrq7MSYixcvMu9iBMkXXnihmFn97LPP4tlnn03751qX7lFaA7W7OroHDJBshsfYKKV/EwhOXc8uZakBZPpqg+jCXoe8o+062ERgXAf4imEAMLghb6Ps0o42OZ7C4UqBRg6PdBa0BEtqD9gAqe1rabaVtqyPfOOcA8ZpW/NEcjikaTSAlHHSc5jsDIi0uqLZPimHL2wyECYbcEiE2LfGNNLJMKf55RhTJlzChscYYMFgMK55INOBxL8Igt7n8YhTmM/AGLJz6fdGGnUDn5fkAbUPt15c4zGWwZExjfE49KL4WE4gLNuTi54OTi8nBU2pJYt8L5GxIHhxu9UmyRjbqidy4HZmV3axz0HR2jZhUYRJeNSAkYfX080ej4rZG97GpdX9GMatb6PuceQ6dXB85pln8NJLLzV1U2uKXdZbyzv9ZpWtCOi+E4GexVXhkWQdLdKWdwQgwbwlEiABsDGQa0xwpUEkjQP4OMcIlzl8SNtACZP574rZ8HgdKqlNtpukAaZmp+WzS2kPCtmFrQGhtGMgKcCQ2mqAqP8dVJsaKKZwAX9aXM27GPdngREwoZEtvUMAs+ptTFBG4jaRCYakW7YBHhM9UhiLwS6He2LDwwlAkvNL8SIMyECIAIIx/+xN5CAJhBfetM1hctp0KQ4gEIQSKgEClvFagNtzojJ+JgKexyotexFW7a4ejHBlUo0GnSogqvFanNOBjW7XYJDk0eQtnAuXNlaaCI1Q0pPzY9tnhMc6OHKdKjheu3YNV65caYbGxx57DK+88srGkCmVHuhNtsTrKJ6R+QlJQXLal/CY3AgOzPsYwdUnUCwBEkDajw1yhEIfWr3J+xgaBOItjNtzIBn/RmjjcSsBjXa3tLTnthIa49hGAYoFOJZN0a7HN0Zp4xwLr6N46i2BR+6ZLOFQs5V/ZddzjJMeRSDflTJeehZjvtr4xSmO21W7pVk4BSZuX4VGSw023hH486LK0jjkmgoowBgPReFNAcjkadTCAXJuJNMUJgBQphFx8TFC4S8C5yxMIudJgTKKeilZWFrQm13mDJnQ45Pd8VRVVeqye8rtUh/r2BLuynDNVgHGdPwZmGRpGmGxsCHpvWJjpoFIo6SL0EjtC0iM6aBr37msgyPXqYHj9evXcfHiRQaB165dw9NPP22mefLJJ/Hkk0+ysNdff312CZ9mBXhjD3/6F0oYTQOQyLzvQ0vjQgVL3keP6cETw72bvCrkzS17HF3Y9sX+6ANchiNmGHQE/CQECrAkaXke5XhECZWqzYKu6Vp3tDaeseZl3AYkrUVeVe8jeTLWurG1rmsrvZaOwqFmKz2JQBskxrReSVssoyNsNVhMNqD7yMCYMhdeRhKuQmMCMP3Bbd4K8q3QgY11jPBHqzUc/dpKCKfAKPcVgEyHFoBX8yayc/YR+Er4k2lKb2IJfSwtcr5lfL5W7JoKeMzh/BlXxCvpNW3bYdDUnqvAKG2cHS9sZ4GShblZOxMSlTC+TfLW7Gp5zOVfsy32fT4PDS7jeZN85TVh2rNu6q5SpwKON2/exKuvvoorV67gxo0bAKZZ1UdHR8nm8PAQV69exSuvvJLCrly5wvKJ8FmDzTmZXkcFHrOHUMZp8BgzifHI3kfZ4LipRaNr86aGcgYiMxyWIBlLMq2vmEFvDibZfjgTDfSkLd2mwFez0/Z1WNyumzotVr7gzXFpd7WWxoJIOsZvDiIl3GmAGO0K4PQ8D+lNlHFesS/DUMIikKEwZK4CY7CzPW8lNJr7lmK9AoFDwktOHIL+YtN+8KA5AxhdBkPaCcGqPY1TIFKeTwmIHCQBkKV1uC3NN4EpBKim/QyVMp8cRnYscBT56DZEJ80CRjVXq38NDNV4p8YtA0oRpkBk2k/bTrfXQK0CnGZaCPum9H42bxMQoRx7D+VRPucfdJ04OB4dHeGLX/wijo6OcO3aNRZHIfHw8BA3btxg36R++umn8cILLwAAbt26haOjI7zxxhu7LWCEQEOpy1qDxykDal3s+/CUjwAZPY3R6ziZ5QeED2WaeDE2aNTrmKFxSuqLsDibmsIkUAIgBUq6r9lSaKNVSvM4avnIbaAERqf8DnVv43atUw0qtTg5waMGkTK9N+IYMIowLU0NEJmdEqdBoh4eC0S8jshhyYamY2mIrYQjDZbS/rTpqB07eClWfelbIameCR4jBILfwz6kTaClAWTIk4KyhEgJiskTSctRAUkU8Y6lnY7pS3uZP02TCijedRkgit8BNA6lVIBsrIvbAmVDe67OqjbSzkOjHV9NawAaC6OASNMrdks8k1aYCou1NEU52qEx/cy1MoQ8907kZbtr0omD48HBgbp8jtRTTz2l2i39LnWLlngdAdieRyA3hrSlSTY+QSatcLERYxUfAZzorLrk2cxdaXnh7wh2joVToJThdEIMiwv7FvxJwJTxLdBIj6PFWWEaTM6laVHtwWDNAK55F4GyTWyFRx5e2qsAadj4SvoaILJwyHB+gsyzGOxkXqqHMYUroKJBowZRlkh9TTCpwSPNjgBhqo9xZrLLx5QAWA2j5QAHOekR1OCPnju1zd5MJ/Z5GaY4r4Tx/IpwJW6Zh3FZQ9tabRe33xX7Fu+jFrYdXDo1vOpxpLY1uxabmeNZAJmP4Zengx5eaB+hsUvVqc+q3ktRt4WAxrgd0c0XT16SR2wpUqOlhAmIBHKDpoJk8IDEhk/CZCqmAZQ0TkJluQ0jnGyTU7eAUe7LFTOkrQV/NWjcxezqubdKDSCbPJG+Hl/aE4g07FrAkMZr9iYgsriyIBooclsZPxMGFHFOsxfSullVo1DHGDyS8moAqXkZkxdSQCTNq/DmeRFG8k91VZ7HDCy2ehNzHC8rKy89XiqPvGFRiHlXZ2wtsfK0J5vslwDkUng00sytB2mFacBWjVsIelq4Ba+t6TXv4qydBYyKfVFG6/m95Hc+RnWPI1cHx6DC66jBI91OjUsDQMaEBBaZDe2ihlI5Q1Tspo5xHiwZK38CRQPyOFg6lg+LF8eQcTU7PV7so9Qmnsa5+BbNrS3Y6nkE9IZQS19CZC2uBEIarkEhi4cVXxacHVuFTSWvAnxmwmX+6Za00hnphRgkphc1HR7puRTflEe2LQFRkFOD588+H/63AMoQ2AyL9Pi0TFZ5Cjut5VfyklpMfwvtUyF2a78EHhfbqwCqx5uA2QKSDbbL4xpg0cpHhovtswSNQAdHqQcLHJVGg2oWHoHcGMm00gNJj0VhkbYKkvyKypTDcyNWAiGnOp8PQ+zTEj5FuDwRHTRjHpatmpeSpsXGCqvlcVyqDdWyQNIOb7Mt7GoAadhZHqXieCZsGse3wEOzqYHeHCxq+ZC81NtDq5sUHkGgCOX9ncDK8aqG+FygVVICYiA5BneivBL02KNCgUgNILV7yAJDExiVfVY+w0Y7ZlWbguE2anw2zHJAJb6adgFU1ru05/PRHAwbxQMlJBrparAILARGclweVgZ17ZceLHAEmuARIDe4ly1FNNS3p+V08rE8A0R2JF4mWQA4s/JJtwmvzCVETodwKiSyastay5id5wYq+JVh2gPBfBaab5ynB4+zY/srrUfNc2lm2wKQSgatIFjkV0un7i+wr4Ei2VYnYTSAqfTEaaLvfLy3IFdw6fhPOxLyoh0trno+ZFcByrLsLUBupdXLMgeZUqoHcSadCpmWTgIeFz4LmpxHuwLQhceoweQS76Sel9fjWgHWOo6RdjEwamXZA3l0j6PUgweOgAFyXKr3kUW2HUqC5JSVBZMiQPWqCPKtPWiEe6R8GxSJ1QeZfqJySRNevra8c16bP0R2DZBNk0FnbGY/p1dLv8BbOQto1rFa0i1J23h8c7ZuAyxO6RvKpySvAmS087xOaWk0mATyPcjile3isUF+VPn7aoA5B5Cz+ShplngZq3m2atO0O6jni9v+TY65C+CsPtPnIawKn035zdijEr+wrOYx90x7+YnUU9SDCY5Rjd7HZC69kCwjZdcp0U40oNSOHcuqYJrLTzc1DWpP/hrIkqDq83+uZak9iJq8ASfhxkBbS9NalGa7DaHTDN/wgVeFWz24uK/nYHTOq4l58CkTlPEN1a2gunLIil2uAhgZoHK74tgGDLNHhqDBFk90LKN6qWbuibnqVY0+oaoJYGvYODYW2PD5tLgLvMVjaaWthJul36oMZxMYo/o6jlwPNjgCBdTVpN37hbdCy3tu+qDKZhWvYkP6oiiyy3mLvObTbVnJZh+8m8BzRZs850/yDXQHXlDryysbH6/VfoHX0vzZl5aHQV/z4aWDnoSXL4ZmHpXrbINcPayp5mrnaeWtBG4zw/ks6Ew4jJpemu2opt+t9TrMvb9WIXeZ46Dr7KmDI1XrE1P0Ws/nO19TthsrM18It7S2HmflXuIh3ZeHzC5a0+NokXdSruO9yLO353GSyganVr0cM70UNSjbylMnuqutYzTJgsyzrH15Tsxpg3fi5qyP4xps07tzVn6TBvUxjlwdHDfRBt14c9rutrxPbuqzdBpnvqXdQkt+p+O+TjvyoLSope1QeyW2P7TRP73wGNsW5KzUz+Mo56bX7ow9J/ZpFNA+qY9x5OrgOKcFFam50m38ENrNzbvxw+GkH4L7UFdP88F/AuffNsN0g4twDGVXyyrHFTaUYatutrm821KfPZ1mXTxLz4Fde9dP+Jnf+qXIyXijonTdB+rgqKk2d2RHkxO27r5rqLRNj5wdPehO6k1ValMv0D5p47ZhabrK0ND6gPjlY0qXz2Cdn7DFxuEtHPc7O7tz4QSC5eOKG3QSgLQPELbvFVLTrieZVduYmUG6DVEyvjDdRXs1+/BoPOYZUO+q5urgSGVN/GqZxbh06RBtFuSCMlmzKFtta+F2PvWB/2dax1H+JfNRduD522Zh4tQGtHjuHIrrVcwnqR1TiyPrKnI7MaOEQOSiRZJjIuv4ztiGAYBLZq9a2vUkgiX2LRX2BIcB7M0DxJ71xP5Y0bN5NbQlvjr7asnxy6D5lQ+UGVyyOMoyBU1tT63HYI/l4XpXtVAHR6AdoCqwaK6tVmmrajDZtGaddJrMwKxqM1OORenmwnekfWlj5rRkoWHVtAh01Xz1hdgbyrUxUImoOS+ktiMnmkno0xbgb4FHUb6UXjsfdszGayE158G0oFjNyzpG5fi1/GK0me+8t9fOcw+9qtuo5uBrBkHuipv7EpT+/JU02ZJG2KvFVQCYtTsiHa2Tqc6WeXjlYLI+q+VsdK6eqnz3OEp1cGyBRrbdDovsVtPiG2CztDOOvyQPJX4xtArtbCmVWl5nSMZzO2uT8Xc06VxXrHYMAqkcqpy2aXrr2BdXDLD00itJr4doLKyfm3lBKUBqDZKWtyy7BEUX81dgsQWyLKhuBvHyzGufADXzTGnbQXQpRJrmzWNCd1epWxb9XzRWjyXUM/fFDa0563RgdIrx3Lfgsx0xqsFja1tAX9hYRY7H89w2VbtQgc3rWoKu/GYGO5aWTy2ua6/0YIPjhtCoxktYFOEsXTVuBkwtwDPfIA0bGDZL0s/BaeWYpv0udVz5L3j5bOlOpbauZrPQ41c7tpM2M544+j31Mu0MVJIGh7W/iq36LWaat3cMHi2vY1E2V56Xt4CSHbxiU/Vi5hNxWhqRrvwOvNidAUq16EWe86CqfzdeydywrYVbOslvz0ft4hv0jLEqcfQG9QQuWRFouPH8TWnNvGk4FNvyWKWdfKgEM/HCVoAk3fak4HEZKfLeJ/MuVAXU09HGLyL3qR5scFSkw5oCc43AaNqLvNugsiFOSIvfFEg38pAaNmY5t9VxV/DGRk55mVcDZrt7a/bSwyfSyPw0G5046n9LOHSKbW6UKJyy7isF+tjn+6LtDCSaaoVGC8q0c6qEq4AYr5UJjMJeFKcGf3PQNx/fnpcZVoRMGhor9OKu7h2oNl5N65Is3pdVEIz7dRsNNjXIZGnCXw6RWoai8mjHjW9uRZsi3txouPYCGDaq6wMbAMl+cgsSa2B5CupfjuF6cMFR82xsAI0aMFZhcQYUm8O1ctdsZVyjvRXfDpFKgY8bIo/jYbNzYHQ8WIM6kSdgw6KjD3cZT8pUhDnF1hsPeJB2xILJFC4aigCSyeMorpP8yVK5BDzyTHWpgMzK6ovyT9saaNqwWECfhER5TYhtvkxlpaL2Ftzx8Hmbwo6ES8irpZvsUcgCwBaAPCl4XAyMImxUoE9ujwrwabY2YHojLm5wsExF8g6OeisDPHqjvZH5qcBI6m0KK54TOd6EyJTPQnici+s6NT244Cg016U7QR+Pd1DChB31LKrg2RImy7gQMmftGmynOK+EzZRViTPDtLRzOumHygxAto819Lq9An4U1Lw2HtGARQaKJIzBXgFEPG+aXxUmayAZClKDSBUg4zkQeGTnRGFSSnr4atBoAWMjLJqg6PKUgWzD4dCJfR42B5IcQgEOahZcDkZ+VtoCLFFKA8Q5aNwnb6MER7nvjTgNGnkYt4t/Rwl+io0ESAssvYcJlMnhl9qlCSbTI0gDSQ0YaxAZg+B5F3bx16e0i+HxlNVnVXM9mODY+ryqjGmU0MgAqgaMs4CZD+Vq8Uo+24OkX5ZOi5PxMk6JV21m7GtSvZwbyLcOvlLMakBI452Im/cickjRwDCVWwPFsC89hwwUKRBGGwqiMT5m53kaOBLmtbDQcER45qdQjINk8Egv1Bx4FNe8ARoNiHQiToVFAnIaKEoQtACxCA/F0MBOA0IN+kxABIrwmgdSxhX7RmWdg8TWru2lqs2G1WBAdknS9HPAqMGghMlyP+dnQaUGlBkiY5gn+cT2aaojnkKed4RI86bz1D5ux0J4UjHTFeAPsVA/WRe2Bo80h4YqvC/qs6q5HkxwFFKhR3Px16Cx2CfpC5gkedG0Yl/1clqgqIS1AOLOvJhmmHxa8F3zwTHHBCfywNEPYj5DDDjU4hmUauBohDllv/TyeT0vCpSbgCJJx8GqhMjCm+j59ZiiQx0BnyigwWO+GEobVhMtJw1LhSU2Eiylh1EAYw0WKQRqQFiDRAl78W8LGA4kH2mjgeeg5EXhbxE0NkLkZDuaccel0Q96eCMsauBI0xYAKfYlEI4aLBKg1LyUGkxSD2TezlAIHzyB8dg1iPThvo77sbKpAOlzPgVTehseXX4YMHhU4LJrP/XggeMmNyYFIbpPoZGBnTPCSRqIOJkfSts58CzT5oeCaqvl1WKPMm/NhoXVwlN8GTgLiCf1oKmASgmIzo5P234WEqd9Z3slBfxZUKkCJYVJlzcLr6QFilpcLA8yQGoex1SeuA9XeB9l++RiG9cKjELJ26hBJIVGCoMkXAPGfAl9FRapR5HBY0g/MJsMiQUMGnAowVDa1YBQg0rNnoJeDRjVLusqQB5vBbY8RdpkhxZgpPAZ85BgWEAgsdOgcg4o57yTPuXnFZCM+8Hz6H3yRqoQGYHV+dSWeQqMESDTAyfsU+9jCmqDx7OgPqua68EDx5oS+Ew3tIQeJ2xboFH3RlJ7sS32JeDVQNLyJGpexFo8L1cjfEKGeb4v7Io4JZ4dX+o0KrLxnCu6tMWJaeDIXtLpRJLCxrN9Yp6OS72H6mQXsZ2gLOQftxmkNoJi9Aw6sp+BkJyyaFvoFZr2Y8Icmexm2peN2iAJimRb9TISYEyXwABGDRYtj6IFihoktgBihLSqR1GAYYTCmi23l+CYoXLVCI7HDYxUrfC4tgCRhs/AYkyn2WlASeMtmKTpRgKIo0f2JIa4OJQlAqPswk7d3G7acREu431MARIKQKa3TC8q5wJ4FNp3r6NH/s26Jj1Y4KiCycI0EuBoPhY0SoBE3i9sUIYX9qwcvkwDcTwrb8htb9tDpAFKODSAksGfvG60x+o4wdGyX/I8MMHRtvEDBcRo70SYN6ARdaiMjQQBSgqTPDwfz/IkOjcDkQoopn+e5Evaiens8qEYTBZxLoMsu4jkPDy3B32ji+VjIIjS27gFNLYAo/Q2arBIu51pnAWKFAQl+KlxM3Bo21F4nNKshI1lFyXh0fI4nlR3tdZFPQ+N67BdQmO0TZDIPItrFRYpUFowKT2TBUg6n0DSe4cV2R5pd7R3GDHd93xcpGcAmeqTBMj0dkkAMtdO8IecqOkKPKZ9ub3RG9/pqIMj14MFjgskPWWhfedi8NcGjUuAUQU8AxZLoFTyhNz2VUhUAbEGh3FbgUETHsm2CvGbdF8DfO2MJdLWGqHFUaJr6ym6dd4ubCIERriUYKlAZYZBApQGTFLPpAqSESLjsci/whNJ40lZnMjHT0UuwwnjRRvQNBDwSMNO+pndCI2twKh5FiUMtoKiBYk1QLTg0AJDK57b2F3XK3Ag3GTGtZaPpjX0cYtUmsdRhtF8tK5pHRrXAhp1qKRAyaFxULuxEwwqIDl6h5XzqYs6Ap8GkdGzGD2R1AsZu7Gd83k8ZEyHWD3DMeAZPMLFmd2UDhV4DCZptnVMsuGjuWt/1MExKoGQK8OEXQl3W0JjM0gaoNcIi3PeSQqKNkzmPIAAiRIOC6ik1y/vsPDRCE/plDB6zF1pXebHlsBhB08WwY4EEQDNoBgfnvHChD/rvD1BWshv4MkSwAHJi5bAKsBmhD26nbpXAwRyL6OASAGH1CtHATI1FV6kI/Exi2jL4FG2OTTBcSqci+lt3AIalwBjhEUgwx31OMpu5xooal5EDQJbAdGC0Ahy1pjGOWBcKR7G2vjHbaSNYVwLz2MLPFKbGK95EUtgHFncGN4OM0hONhpISo/kAIfRibDw1wGInsgIiy4A4hgAMZ4V9UJSgKS1NCIiiPdRwiO8y95K9gwU8CghsXxLTAqMu7fqs6q5OjjOyTe2ZbuExhowivwsr6MTaYsyMLsZUJyDRAmIsgt7FPvkAVHtxtag0HJCHMfo5bRIt8hbODnYYt7xZll7JZx4DwNY1qAytrO5+9kzmIwQOIFYCZIaHJoQSf9Bh0EVIEX7wEBRC6PwGM/T5+vgPHSvI8jOUlEYVuPaoNENCiQqwAjkMAsYKQhSMNRgkXoMKcyVcXVI1ABxDg5r0EhBkAKgFa7FU23bdW3Nmk7ASO4BCpZrZcILDY/QUIJjGa55KEc/FCAZy6uBZIJIAYsUIsfCyxhfHLO3UQPIMXoZFYDMYyAB6n1MFTd2XY/IpDcHVPF5YnkdtTwkcO6B+uQYrlMDx2vXruHo6AhvvvkmDg8P8dJLL+HixYuz6a5fv47bt28DAN58800888wzTek0WW84psdLhTxX2jdCYwIxAxintN6Ml2Ea8NnlUGBRHnMU+ZHrkPMjUGgAoj4DO+ywbm1+Icvrqvwwx1qhM8QxjfJBR08sx7lhCtcW7Q7tCPcgDsRrGCInMPMJftxIgTGApCMZEcgrIJICFAElGT8Hg857+MFN94XD1NUeDGK3+yJ41GyN9mhpm+K1ykzPXYTXPI0Amr2MNWAEsaXAWHgcQ/gcLFIgtEBR8yLWIDFtR3sFDNUwOd5R/FoWHEq7jeSAtfGGIKGS2tE4BpHOsbAMgyVQjqHSjN4xkBwwAG7UgdF5HkagcAzPugksBxI+AeGACTgH53NYA0DGsDhmMl04paaq3sdYidnrXbyWYlurxHsIhV3LdSrg+MILL+Dpp5/GwcEBgAkGP/vZz+LOnTspTNONGzfw6quv4qWXXgIAHB0d4Ytf/CLeeOON3RdyUeuEAr6iNoXGZmCEDDPSpbJ4I70Bi8Ux6qBYzsIWgKjOtiY7GlxGKeMWLfjflVSAkeMg2ZqMPoeNShgADOGxTGDPIcBk3HbRjsBf2GaLT3sDImcA0cdiVQCSgaQMH33Ix033TMxzDPbDAnjUrrEnXkcZ75UwTQUYarAoFveGDo3FUjobQuNSYNS6qKVnUcKi5VHUQJGGSSA09+ksagGkNEyGT3G2V3HbmdajdzivhK8xIA82niDtfIpzKW70A86H7QiWMYzCY9p3YR/TfoRHDSRH73DOBUCUwEggMo17dHkizei9CZB0ce8RuTNk9AEqQ9j012GMv1ewWQSPIUqOeUzwOPPzRZhNOisQ6dEnxwidCji+/PLLuHz5coLEuP3lL38Zzz//vJnu6tWrLP7g4AAXL17E9evXcfny5e0LJm8O66ZOECW8jRpAGtC3E2hsAMYMdV5PE8s48nx42TksWqA4C4kWVAIlhEKksfbp8Y5BTvZ+OccB1pE1COntk7qi+USXCJTZk6jApAqSPgyUy8e1IBKDZ3bUC6kCJHgzwQCP/IUSRpoWHucb0lNHBbXbFBSp5uxdaRO9jXy/HNMY45ZC42oQnkMIiFSAUfMurmbDiMcQ4yJQtCBRAqIOjPqEGQmLZlf1hhV5RNkVHbX2A84jQ2MJkTnR2kVP4QSWEioRwjSYHMJb0AiHIdz8o3dYuwHnkLug186rEDn6IXRD172QVQ+kI/sLvI/5atjwGLumrTGP+frTyurzMwkk6zMn18FR6FTA8fDwEDdv3mRdzBcvXsTNmzfNNEdHR0WamC6C6Maq3NCpLkggFOkLgEQZJmHuRKBxKTCysvnSs1iDRQ0UJSRqk2BSfhQk+SUuv0Bj/GjbDkZx4gExyvAIiWSftlup7zmGkeVlhulBWyx1Q4rtHLLbgMJNHI2e8orxjowPjLQ2Pax9hFE44l2ECpAtcXSo2Bw8ShisQSGDSCPM+dKmGSalHamYdGwjjWe70sNI2sk5aFzNeBk1YASk5zHDoeZdlBNlKBzWYFHdVsCwhMYSEGkYH+NYX+OxZeb0vAQYEk2Al3/N8yCgKexT17tbJ+9l6naO1yDA5OiHdD0m6PPBzuVtFyAyhK/dgMH7aRsDhnCcAQpAwiH5EP10ne9hCF3THvfGFeBC+Dhd5YHUiSXeRzfjeYyzr+WEmXS5HNDqdUxih5GVe/90Zpn3mHQq4Hjnzp0i7PDwEE899ZSZJo5rvHDhAgt//PHHcePGjd0WcInEHWXBYrEv4LEFGjPk1e0LL6GWZsbDaAIjBUHiWZyDxQIS6fYo7C27KKOt2c0Ma9KFLMJpm+SoDXno5U0ClAIm4fwEkeR56SKs+bDURfRkDhOkJigMQOfHADcaQCL8BsIDWXoTqQdBh0EaDk9OwbCPDZeTtoSzVYikxvRiKrAxq1obJABRxjkRz0YhCIDMYbanMdos9TJaXdJzwCi9i3SsouVZpLBoexjHKiRagMghs6y4OxnbSHQe62Kc43knxjGSY7JyK0CZgTCe54DRD1i59QSRmKCyBpETBA4YsOYAGcd0BJRVAZLsn8OYxlmeG+LyPgPODWPhfbwXzqwFHuM4SQmP0csWwdABzPPmXAilPyH1Olo/LYVGok2re9du5n5cu3YNFy5caHLC7cWs6ps3b+Lo6AjPPfecaXN0dLRR3LHJ6KaOUgFS7jP7OjTK7Y28jBEYwcM2AkYGpo2waIHijMexydu4w2lvzHPIjqEBIsKrfkibF/MD1ggQGiDS+wkI6W9vQmTYXyN5ISfPoQKQgwNIuA/pE/yN4N5HbAaPDPoU+7jBwivAqDkaZBjb9zlts1zDNpC7/BEvI/1N5T6f6BLDrDGNm0KjBEZAQqTtYZTAaHkXLc+iHA8Z9yUorkR8TB9FwVBfjmf340woAAJTd/WKdE/bsOiDvcPgRowYsMIY0k8wOcGfDpFp240TqPrgVZwDSMQJNamignob9f0omiaFEHitwyOCN1GOeUxeRvo0iHU4eh3JM4ztR6W3zfRGCza7+gxpn7uqdzH34/DwEFevXsVP//RPN9nvBTheuXIFr776anViTKTpVr344ot48cUX0/74/vtN6VreeApHhQRI6PslLKIAThnOAFArx1JopIBnQCMtZwZUX3oY1S5r6X1shEULFKueR+PH2hQiGSySPOJkGNKf7Mh27CnTIdHXIRIuLN2D4GF08d0+dC+HMUYj8UAiDkkPXd4x/ZBDM9ztAB7jckBegGLcTiCYu6xTQ+ZLuwSRFhBuAojbqOKFnAXI4G2M0ibCUPtNoVHOkJZeRjmmUfMwLgXGVliUXkqahqbT4lh48fBsk/QwxnLFMYjJGxgQahXTBdCL6QeMAf4mSFxhXYVI+BErN4ZtkpcCkLECRpBESJ8GUaft7eFx6v72eR8lPMbu+8HRbvi8gLlLnkMCTU54HePLKYnf2XII+6Y9Lvsu5n7cuHGj6M2taX7Z/WPWM888g5deeqnaTQ3kLmoJkLdu3VKB89lnn8U3vvGN9G94+OHdFLgChjLcAkoJkMy+Eq55AC3VYHZjaAwgyLyMKd7DrWlc+DcCGCcbR8ONeDeOJI5sr8cJFOO/9ajkNfI0S/9Z6eWxZZp0XXy+ViOmxcSJjRtHHk/j4m8xevb78Ovt07WS9wH//cjvSOzk8ATrhaOQcg9a8ez+m6sr0v44RQ9ggOJcNzWVnAEsITGmoUBoaW48Y9RSaFy5kW0P4d8q5ZG3z7t7LL8VRpJ++rdy05jNFcZgm/NYkePRNAPJZ+VGPOTW2T78O481zk9zjzf6F9PLfB9ya3bs8+6eWi5apnxO4V845+JcxLWqXVv79/BKPiE94vjYMd0bcp97tPm4UydsrHuzCEd+IaL1Qnrki0QsA/NW79qx5uZ+tOj69ev48R//8arjTupUPY7Xrl3DlStXZqERQLowslv66Oho43Ucdy2r8ZvzSJZdsciNce1Yc40/yVubBLMYGpHTsHJXvIxzHsZ6dzXZPuHu6qqowyR2ExMlRxpdkmfwiGMYU/zosvcRQOzGnrqfg030PiJ0QXs/eR+H7CekYwtZOTzIsjdk7KZH9eEuPYssrbApunw9t5VOiJpTgmmmjC1S13DcQFrjGjW4Mp7CnBauTYaxVHofy/GMgO5pBAAKjZOdb/YytnoY9XGOene11jVteSAXS72UwjdCj0XtU6UcuF20oZ7BaE/jWPiANSZPZfI2hrxHuOl8U/jmnkf5NRPqZQT497eB/LJTpCNeR1o509dhtP25it1a0c+AJ3Jq8vaThred+xF5agk0Aqfocbx+/TouXrzIoPHatWum/cHBAS5dulR4HA8PD/ETP/ETx1ZOpsYb3ATFOQ+MTKscv8XbWOS58LnsJBjSstW6i3cFjdGzJ/Oknj65T8rlRr/4H5OSp3pcrawkPnkg4zmL85Td/wzO2XVFBnwpT38vMK9jSktt6bWPafzMfSfzmQtvuM+jqi9Vm2hTWDS8i3Koq4TESjZJ9BvTc9LGNdbtS4gEyu5pgE9+iceS+cS0OZ9l0Bi9atEmASrGAiypLS1j6z8pLc/iuCSd1p2+EucnZ5KziT/KxKGYRlv4XEL9tpJeRylXuY80b2MMl3nwALtu3M/atBNLa0p2qW3nfly7dm2jFWlOBRxv3ryJV199FcDUt37jxo30JZmow8NDXLlyhaV77rnn0gBQYLowt2/f3s0ajvug1gZ2RhkGCGTSfW9AoCYNOu1nia0lnkaZRotX7FUIbFQVIlvKJOHRkhY/zsQb2vl3umePtyx837VtwzfXfd0qOYuax+nd1ppawYTBkzE5RfMMtngatWO0jHG0YLCmWhp5jBZ4lGHaWpVafrxM4rgKRMpjtXRZt6j2yUbr3lSBU+43Hv9+Bkkf1rzc5t/bb7+NT33qU+kfnYOxqZbO/aC6fv06nn766Y3SnnhXdZzxc3R0VHgYX3nllbR9eHiIGzdu4OjoiC0Ufvv2bbzwwgs4ODjAG2+8wdIcu47brb6j/FuWNZgmY5TdrMcm2e+xp/LyqzAnrVN6+rb0xFg22/TisLTW9pI8TlBeVLTRu+ZGnipOWNiF6DqCltZwG01EoWsX8mMO1dnRc/HblOk4RD87uK2s72cfx7HmFNdi3EU+dIKM+bOdgW7ok9QjjzyCb3zjG2b89evXmWOspldeeQUHBwds7gftbrbmfkRt2kUddeLgeHBwoK7jKPXUU0+pdpsS8klqZj3VLKViWdCXFuBvrYgOeQxcnNRH59s25OPdNJaueOaLcvPzzYDo6ezjqDh8h844pn+BMOhGhFUH3IRyBOjbxOtoAmPZV6lvx/SO/03j/YYyTRGXwmUZjDLHJXnSX92O5hM/S8jStLQl27Q3xwF2O8gz3nbTjp4ns2nJUwkbG6BonCosUgVJdSzv14BwGrc2FB60aRbwSOw4/K3DbGG5HWFvrcBwhDyZNz1enKkcz5vCY4SlIm0xO7o8X+tb1LIMVKOoYDSP/PWXEuDoZwelrEXEp88L2sfTRD9LyLenMZFyrKKdjw2ho9/d109OZLzfvkHnCZzz5cuXF/eebjr348aNG3jttddweHiYwg4PD/Hyyy/j8PAQX/rSl6rH3YvlePZJs966yg3dtIBpAzzKpUz4Mfin5T121FU4uLSodAJMVk6ykIv3GUynBcC4B9O5aTJIBESAw2ENHqMthUeaPl0IpUWPwLqt17AGi3KfHqsVGll6EifyZRNS0vqMrj7AZMh2CQodoC9qXhGBSjOtAp0RSC1ZHsal4cepvIZduS/jRg+sRLk0D6L3Ls+T2kGFjcvBAADcwLpIx/iGQLqux7AfYSwuGzOk5WSm7tF1mISxCkvQRHiMxxhTmgyPUxnCuYUlawAUABlhSwJk1BxIqtfBgKUaLMp00TaGUdv8qcEhfwqQ2Kcvy3gnANIxkBv9MH3PGm5nXsb8LWtXTHhhdgvj5N1ZBcV9grtj1L52ltXmfjzzzDNmOg1Sv/zlL+MnfuInmuD11Jfj2QsdhzdFNn5WYwi7sc0N90wZk40r0iTPkvA0FWmK/Ig3i8BNghdql77LTONCuiHmJf6RODU+5hv/WTan8W+mXOmcwjlW41l4uIYRGuPvrkCj6m2sQaNyD/B7Rdw7M/dieQ8r96i0c8JeCT9NscZBnCBtPD14g+uVhjt6eLSGefrecPAokYY/g8AEKfo+n00rvVT0+8kSVMYw23fKQ25zj9c6gc70bx3Dg0ctpk//hP1I8lgL27vTKL7i311/jqdp+Gct0sPKRspXLWewjecXr0uExtJeegn5dQUyQMbfIv1u8fdp8Dam+0TsF/eVAEnvHTumvH81IKxB5pTYji/gak9h635Ty9wPbc7INnqwPI4OdhfrAsl0Vtf0nF3qHaP2EL1mMj2yR5B5HdNf9vl5bq90WbM0wesImQ6hyxoARrb0NBCPtpq8hz54Cdl1DUvHxB44piGWw+WJMzGOdkevnHgyuXIBcKX7epEsz5rmVRTbzCtneBiZB7KIAwHwCI0kLkBjyuM4oZH9dTrYCTsZJ8GwFRS5nTfC2/KyD0LSVSqp5uQGuPeRljN6FeMn3NjyJy454XnZw6LQlvQu7LgdvYCxHNELSZaUIYtP5+Pm5WH4djxRujxMLuvog0cRK6xc6KpOlTZ6EVe5i5lcu+kTerSLXJ+Ysk7Lcx9jVzWJt7yLk51j6dcinnoZIzCq2xLgdwCNEhKtbmoGkeaLDNIEDirv697G2ovWfSWPvYbglrkf2pyRqBs3buCVV17B0dERrl69itdee40tKK7pwQLHOS0ZPOwCPhnjF1P7k/kq24VdDpEcBi2YLGCwCN8CHgMEpLUEQ7qUkUcY85jXFHQpvgKQEegIQE5xYhzjiuQT25RoB6AAw9hHKIHS0ug5BNakQeQcKFIbDRbVeJTAGOKZB3cApJeRpj9OaGz1NvLyl1Cp7rPra8Ttok2qvSWK8Y2s2vpQCxhA8rwmoHJIyEaAMSDeJAKPA0tPMk/PEZJShhF4HLGa8iLd1mkbGRoTqAWQWbkRcGMGPbY9rV2/IvlHSFyHcZQ1iJzOb8oPAOke52MbKexok2dsnObSxicCJUBK6JSgOKWZh0W+Pw+MMR8KjDGPXUHjJt5GzevoYUGkWwaK9xlI7us6jlFzcz+sOSMx7qmnnmqemAN0cJxV5J60LdseCoxOA8LMo07m4UQjhQxJ0T4dV/27PTxOoOinh4In6YaAlWFdQAaQIQ3gpjbKE0iMC0AH4It5TPsRmrJHBwAwuhBMXDxsjBm53iOvwE66hTRRr2VKOP8gKMb2aYAotptAEeCwCATYIzZWt3SwNYExxR8jNKrbjocDvKxzAEnKDpGeasmLv/MO5iLgwXtIvYUuQFPeB4vPCSevYwRDYFpAOd5e6ZvAIY0Gj/fGIS2/cg7xnYZ8fhAeQ/JalpNlpjGGcQb15CFce2DlR4zOJZgc/SotDD76FeLajqNfYQgAOQGvC+MQp+3pnMJ4xgpETnZxck3+seg3oEcBhZrXUH5feqksT2Q5UaWERKAERWqrwWI8prptAGPMSwJjDN81NFreRs/CMyhKb2ReSkaECRsegGWVdI89eV22HjxwpKA3ZwfFVgtXgFHGxyTUCymBL24U4YrtJvA4bVCaBfc+usBY0cb70EUMHSA9gFU4pzEAgM/nmB44ibxDQFrL0QBJgAEim5ktJx2wA1lyvI+wpY3akcdxso12DbAY8tO6pJPdwL2RG3sZASVuGTRakGjCobys0gb2fpl2YatD62cMEu8dPrw88XuS1CgKkgIe43ruERTn4DHu38MQQI9ZGbBYAuUEgWFxbwUg1z7D7Bp5yR627QeMaV1GHSKnuOhVzBcteRLZBB3aLc1/OA0S76JcA7FVa6NCy9nI9S5rDok8jE+asWBxOobeJR3zowBX8zLm9LuDxuhtTNdDQCP1NhawGNsFKln99twrt5U64DI9eOC4I00eQc8ri4BK5mVE3jCB0NkgWNiyvyINBTsCgYEVU5qpIQ+B42QnATL13sc8R3JyXhSMZIcxX4fYvs+BJEC7/g2Po4TAZD5Tsxc4NNRZxDK94nFkz00NEjVbAxZTWgpn0sMYbeeAEcjbC7yMqZw1aCTp+HFQ5FUDzhIyxe+5aZtEKxA9gBzXGF6xEhiG8BSTbllRKwMcrpwvuqyXwGM6RwGPEexKWHQYvMMYFopOHsgAkCOCdzF0W48ur+/Ixl+ChIdzGvwwgZwbCTjGSrzC4EbcRR7LGGFyCgvbwdMZRaHwrtfHN94l4xvn1oWcU9lNLcY9KoA4hddmVgtwFJ7FqWyldzFu1zyMMd8lXkaabys0al3UGjRqAAnkeiG7rdXHL4XNM+6J3Peu6pPWAw+OqQ1Jb/dluzKbPm4DrFs6cqXWNa0C4RDSE9jLABjjwMI0QIw9bsxZouUJEh6Iz8Ox71p7iPTx28wx/UjgOaYPy/UAtLs6XoApYfJexqV3UvoIgS7nTx7izqOEuDgucpdS4LF4dpDxkgUgkjw0SNTSaJ7FtG15F0P6qocxHHsOGGn+i4Cx0T6VVdmm6ZgkZFphNanwSDJjEBnNp27uVEclMAp4XIeuZwzjInicGl0fADB2U2cApBNtIkCOobzxqyRDBI8AkfDD9LUZ7zG6eNzpxFaYPJHwolzO465fka/BlPtAHCcZ4TGMXwxjGSNQIoWjCJ/iRtz1eZ9q6VJFtVnAJSzaYx5H5n10ZRgBQ7lPQTEeN3kNDVic8uBwqIVRD+U2XsZa93QNGqm3kcETbaeoaFuhyFXi9lpnsczHqAcTHAkklnGet0qBbdg4R9Dt0p7ZhQ0VFGfDGryPCQzBK20ESC9tSDxEeMp4HiKjWTq3OZAc4jUnMAnkLmnWN0Ku50DD+c+WvYxG4zG3EPjMRBnV86iA4WSrh1chke3nMhWwF+0EYEZYZGEM1tq6pNPxDQDU4xdCo4Q95Rg5znPYZHFKWKuMN8LUPR29jvHNC0hjHeu1cCrz6B0wDhNwhmvknA/7PjXiQwiLsAiXvY8JEgVA8vAAjj57HAHMQuQUnqFx5UfSTU7gMaBtFSYjLAqgnNJNUBnLBAGJ2tdn0gzqDRvo9jGOzoznazu62TALFMswHRZjnjEsptfWZ2wFxpTHMUDj9PxXvJAzsNh1/+nBBMdW1QCTyDu1KUlpY/xW8CgAkXofZwESMi6cXNr3Gf40iERoQOPznoGkS0A3eQMnDwpy0jzhM+6H/BNQxnwAAZUAIwX5pRg4jQOyVmWapKbJMTPphOdT8zrqYTG9y/uFdzKnYYA3B4uhjAW4gdq5Spw8NsQxyPkshUYFHqtwKe2UqMVKmdDKHcYCi1steh2xEB7phBnN+7gOjbYEyAE+jDd0hQcSAPNCIuQ1eRIHDPCFJzKG34u2BCThJ+ibwpDgcYU6TMbjAry7eSD1jIUrv5rWTR3LvYlqX0wpl+ZxZjwbt0nDCQzSfTucg2IK86VnMaaLAJj2I2Aq4V6xb+mW3hk0hnjWVmiqxpV2S4csn6zm24sHSR0cDanOCcpToNt8ZUMJjNEpWQNFOA6DHBBdAMQKQIKHx38JrghEep8hcQI+ApEAfBgPOW1nOJu60jNIAmAwmSHVpeMAgIuAJIESLnkFWVg8n+CoKDyL5HehP5E+zrG9wle/kFKz1aAQEF3Z0VYBRPK36H6WcY6nLaCzBRbB7SSs1tKraWcAVDuODZC+TLtEasVdkJZ4Haf6uQweYzVyBAw172O0lQAJZCD0fprA4ghETus+Eq+jBMloAxo2weHKxQkuOS7mQT8rSPOmdho8WuMYZRxAgJEEz31XexNpy9BoX2uxxzm6YluLT+BnQKKMk6CYtr3uWaTxXknjvYBHLANGAFtDI59MKbaj5P5Z1Fkv/4714IJjIjbS1pAwaZuG7TUoASNIkyLgUYKi8yiaomQsAHIK9xwSoYAnwGwoRE6Nm2e2CSjhyDYHvuwtDHFDPLbXYTJmnC5kCE5w6PKEGgF+GmBq8VG7HueoQovo3uYApIAiwG8cBRABAxLDvgpcYgkeHc5sWKRpTOhDzqN2nGaQlGXYBAyt60rlqUlEwGCf3rxSQNrOr38z8Bjrcvo3QWHcn7ILXdcGQEbPo+zCnq4Z6cYGVIgEImBOdcoCyclraAMjUAfKKd6GSmofpQEmVW0c49KZ1daM6ihtDKQMs6FR66Yu4+cgMcZJT+VI7VCOZ/QirdUdTe1plzRQAiMNo8A4hS+ARiBDI8DbG0PF+MYOY2dWDy441kTHOUqYJPWEw6H8nkoJgQmQyHYNFOGNcNC3Pp8zMIERAhhjXH5gTKftyTYNz3YaTKbyxHSrXA4XJ67QxlyAZYJY4VFMSTzYGoxOxlPNLs2jaKbbWoUbGUb2TW+kBYcsLO9TSExxEvrIdgGbLbCn2rtc7oqd5U00w2m5NYDUvI1xu8jD5+1tJECyCo/IdTZa5Mo5NbQZIOO2DZAAmBdy7cX6jwESqSdyAkGfltNxJI56JAHbc5j/1oERYXFvakPtuC0HTJlG2krt4vvdtYkyWnd22W1tQKMAQ2prweMcJOYwGxSL8AosAmBjGPO+DYw5jAAj0ASNrOLJMA0oqc4iMJ7FMh+jOjhKkXbEO+LVcii8jp60rxY8RkhM0BYiUqMoQZGEaZ5ECn5TO+KSbQIwAZDZo8fz8CQeAO+WZuCn5AMn9mm8J/v8AZLAkoTF8HxhwSTbG6/YEGsrYrmMrIo2SNg1dWMXoOjEvozX4hy30yAv2lfi5LhFmp/cbgVJtexannPQ2KJWu8R5pJKzyjoFSHhMFcaBeR/jA8I7BFj0AR45QAJInsX4EjYEWHRumrAxhPRrEhdBMhYxwqEERvY3nAiPX5l2mueQg2E7OALz8CjTa1oy1rE2vjHblDdIDRplvswLKcCQbltd2BpEUkiMYRwAiS05jtfySOBXptE9inI/GnNgjDYMGll4bnuKbSqf7/tCWvg+QtrWb6j3lx5scLQgEYDldfRAdlARqExxFB5DOg/RPlGY1ADS5QqbisEAj+RbAGau2Hk8Yo6nQAmaX0wPeSxXxE37XuxzqEzHo9eJhfGnA3uwSHC0HiTH/YBpfdYV4EjjnBGu2CvANe27Mn4TwEvbBigqtovizfJnWx00OTQyOXJLbfLs9sh+Q5qewmOskBo8hkqWvI/xARDKrQFkXIUhAiRQ7kuI9KHiTx7IDJsaSJJLW8DeHFCWNivVXqaxuqatbS2Pml1N9NgtoCjVAo7STqbRurBpHhocAlABUcYXYSTPGiiy/GdgMYeDb9O4eDI+exnTMTwNJw2ehEYqGWZto/KM3xNt0pF1P+vBBscGJaCswaIX+9FTIZNRYJT7FCBDAtpdbIOiHS8r+BQ/A5MkLx0K474DrfwSEtnsaNWOP5hrHscinmrXNbrSbW2+dFbBcT5ursta7ss43Rsp8q/Gk7g5+Jsrk1YeCyABFRqZHbgiaDaJ1tu4T8pfwKMw8qFCJe+jn65jGjXpM0BO3nqXyhYhMjF6gsbojcxwGPOiMEhto0cy2kcbdZ+crgaD0r7YFh7LHL/S7Zs8jMfbRa1p227rOjjmbQmGNL6AxwogSjsKiTSOdU2TMlBQ1MJkPGh82E/xCjDmOFIpNWikbU6Qk2m6zrw6OBIxSIwU5p3dZS3qCIdE/om+KjD6nH+qVwIiEYujgSJyHhTwGBymNE7s0/x5IZyRjxflkseIJ2DBYA0Si5nRlQeNixfzGFRpd9RDFjOyG2FSB0nFtgEgF3kSjTy1/VlQlDbWMZmNn4VLlrdxPFMUGj2Qu5hFegaPMcKT9BEgAwR6eY6e0CHJPnohQ2V3Ia8MhGBwCORsxgSOOgg68ZfO19LAsIRAPV+5baU195XK6pxdgY8LGqlqAOmVuCUASdNLKATqYCjz0AAx2nrocd5IY4FitElX3YLFWHgJjClc2YcIC3/VniRhv+/eRgAdeIU6OMp2Q4ZrXdaOwJSoF/QxM+37sC0AkgIjya/w8oFkatlUQFH7a9nNQWV+4Ij0JE8azhiwAEQrbuZhchoV2Gh71DZJhcpKvAaRlbDyE4aWXaNNLS8rrDUPNcyr8SpE0ny1Mliib3qkUjrfCI/Rk6gC5FR5XYTfZIsSIkM5XGisHQFJAMILGZIJmJzCpr9jSkfiwl8LFDn4wQhvh0XtJ5gDSivvJaJ51mCwJg0Ua3nKMG/EaQBJw+mCEBoYyvyXAKK2D2kHGc4PyGAx2Mm8CkCkeRhw6GS+4hiq9hHQvLPL+4Cqg6MQ8y5q4QQeU7tCgRIAaRtym6R5IA1gBAyQpMfO2TI7tq0AnARDCXAUFnl5nBKmHBPgXkMDGCWEmvGKTVWttkufAxX7jQBS2FgTamahj9ortq12avmsMjTkVYbrwKiFFS9MrsynWt5kAP5i6BR4jMdJmSkAGSuKy2F0EQCnnodPkfEZEUEydktHmKT2tAs7FY9BpbYNrNVwG/pqsKjtax9Z0iDQgsalwLjLTw9qsiBSy0faypXBaLwGkX7Glj0uDThUw7S8oMXFDVGGAjRFWtm2SGAUx6FwWUCj8XPWep+69lcdHAHeuGjhpMs6BlPFwfAsLBhS2JzAT5CRcNdrMCY9izx9GcbaRPnQAK+s1vG0eAZ1JjQGODbj9HTVsJT+ZJ8s5oLgVDOwxfOr25ieyQq4aV7KRWDI4LV+fNNGi6egqNia4UreBTRWfpb8guXyDSfqdxxN6OXNRgEy1XsSrkChdi7TV/0cK2+GRJ7GJSokwBf/Oln5IlSKYiuQqcVp+y1pzLAiZNIc9G3qddyFal5HwADHhny8BmpFeItN3DDSsYOWcAktXxavpamAYi1cHnMOGo027yzoLJX1JNTBURHzOlJ4DJGa95Guce1IOuolLCASKEEyFoAesohHivciTG5LUISH+iCcg8VaOYqySjtZViXeDGPpl3kVtlWTE6NmY8RtC5DMxoI6kWYxFFbsyvy8Ed5QhgowsjQN0FhIg0dWHysASQ+uQSQrqwDJFJcfJAkmxbmkx4b6O7gC6jTAZNFaC1fAY2M6w7Zu39bCtryTHYda3j0tuNTCiyHZBhxOAQ0wWNjRcKMs1ePo4brjoRKvXZOlwGjlI21awk9a+1KOPVEHxyjhlVDhEUguDcv7COTKmr8igQIiY1apgfRlBiX0GW96clvsF/koaeluFRaFdtr1PFM5T+Ktb/FQljn7VnhUbOe6jgubFiBshUFAveBz0LvkuCz3Ggi3lINm5ZV4Co1FkQVAknqZyiQbRTZW0nFbWpDwJsnBWACkzIPEeWJOD5BmYxdR5YWpQpoFgLUkcxVxg4p63CC5uLOicoOpADmTvoTISn4VENTzmkvfaLsE8JjTwABGFuaIfaV8LeFdp64OjlQKPAIc8CSFZS9CCZoMpqIZbRhnKlDppeMGMr36vFbG2eh2yuZc/rJ8SpqW4913mmkEW4BQ22/1CNYAsAVY58I3Lr8VZ8Kmb7ARByB1NnVZpwCj3OlwjtdzAOpkmlgIYVuWW3m7lBBIAZHFV95MY7kqkpP2SgPtpKRN9RDhOAsr8il5GmfVcBrVbu7Kszenn7ex82pM25p+7g250jaZa+42QOiZhcbFHoX7Wx0cpZTGQAXIaKNBJMr2gTozzENrDe2CikWdIaphrQwNwJeBUvFqVB5WrcdryvMYtNNnQmtei6HM1+2WQmelDM3xMe8l6Zd6OVu9sNqhqOeRJqxBpGQ+2rUg64NVVtkdUa30jWFFXP1CTJ7KpQeezdY4zrI0TdrL7oWYbmHcrrtnt3lgLThm8bWXOeireCybgXEu7rS0j2U6RXVwtKQ2FCRaQuRkUdoafdpaehUU5TEaHAUNJnoCK9hwKxZd2g15NscbmmtPTuXFcNNjbuKZbAxbBHMt2qataoTh2rGar4WoV+we1SAypTHekirw59TBgkqZUPEQ1vpot76XT6Ey7Az49tzDcxzwtqmdkPl5v02O0wqaC50Ji8tx2trnsp2CziQ4Hh0d4eDg4PgPZEEb7IasqCxa7fEbPncWJtrmXm95/jeNG9pxT9bSc9qL+r7Jb70JVAJtP9xG994GaTY4XvMtXrMzXr6ql4ZOKJC9CtVytF1v13IR9pyV2rSHJ7FNkTa978/kg8rQTKWs16uW/BeVpmsPdGrgeHh4iCtXruCNN95osr958yY+//nPp/2DgwM899xz+NKXvnRcRSzV8ADKXo3t8jFybzPbwbPb6u1u1aaOh7P8DDlWb+cugGoTLflBdvnj7fI8lr68LLJ36uapat8q0eIukPtcS36fXVyz47rum9xn+3ZvtuqslvuYdOLgePPmTbz88stpe4leffVVXLhwAQcHB7h48eLyg5/kg2sX8LY0j9YW7wTgYq/q2YPUYLWe67aeAOPm3Lin8jhvmB3kvRfruDX9ZvM3wNbnsg/XQtN9VM/blgKb+SGWODq66uoXiunEwfHSpUu4dOkSDg8P8cILLyxKe+HCBVy6dOmYSrZci+6lbbsQza5JPbg663IxkC6wfUCGOJ1ZLexWsgfI6wNc7XGxMbw+KWO2mmwZv1W32oIKfywA3T4ktJ5Xy6Nom3p8GmB5HGNwj0utoxZm59TMeLvNtqFisgMYranz1/2hWXD82Z/9WVy5cgXOObz00kv4Q3/oDwEAvvvd7+L27dv4zGc+c9xl3AtVb/gFg/zNcHVCgNaSLzhOim/MpzW/49AuXDr78FDaVaO5qyfsUhCRS4gYgCjTNs/ArM6oArRF3tmtURsKooJvm93Wg/u3bW8X5Ns0Q7X5Wmwxfm2uDPug4xhfWxxj85NvXtqKhFlzvGZXVpDB6jHKQHPM7waQaSXZd6Dcix6HPdIsOP7Nv/k38cYbb+DWrVt44YUXcOHCBXzpS1/C4eEhbt++Deccnn76aXz5y18+9sLeuHEDr7/+Oi5cuIDXXnsNzzzzzGZd1o1qnoDQAnOyEs/lsQRUnbEtbVuP0VBLdrpg76a1csMytK49N/d5MjvhUnvtOHYmbZOSZt0V8/tym7ZYRaPkzbTa+ohThHJ8ZQYaWw6rmpZLfjGJH4afQN1W5CsPtAAw20F2Jt0W5V9Ujlp4La+aTqlXYq4617x89WPXE1UXq9eSF22FjPfJbMkHAApg9CiPJX8bZ7y4kYzNJbWUvCypqx/sizz298XolDQLjk8++SQeffRRPProo/jP/rP/DF/4whfwyiuvJE/j0dER/uJf/Iv4o3/0j+Lv/J2/c2wFjeMaL1++DAB46qmn8MQTT+DOnTs7P5Y+Y3oB6LFKa4BbKxhqaVryJDbOCJdl0D9XVimnzLtFC1uZ5uf4Kb0StsBlU8lm8vH2z2YeYMkXKXL+PodrMOIJsXkRZ3SdefpZzQSBpDUzLxBvTQqANNKaEGUtRGwBr1EUDsV2kbX9XQFgU/lbPJO1shlpth5OsEm6jb2BM4fcouelFXBUs1k4JJsFBOYXMQmeKZ+mNqI8du157tP/RPkKO9mwKCB5ViGyC8CGYxxp9/TBwQH+4l/8i/jKV76Cn/mZn8FP/uRP7qpsTBcvXmTexQiSL7zwgjqz+sUXX8SLL76Y9sf33286ziw0Nr3h+bptLV8N8mbg0ckw9iDQwowyKMVs+fZtEd1Q2Xf1TdulwNhiv9TTWLOveQftb+JaCSx7Hp6f7fGBLeIZJCp5e57OMxuaRqY14uS97cG+yKIuVeO5PV/NW9Ec9IS0TpaPbKugqIFYC6i1fi1jGxhcAM0teatlbTlOg/1GNnPayDsoimHFGeH18YHtecnj6t8qL/NgXka1zRAZOpEGSD8e80QqeaV3RM2OVHXpuaSH8vTg2jCVued79/TtpWbB8eLFi/h7f+/vpbGN3mjVvvjFL+Knf/qnd1u6GcUua03PPvssnn322bR/bpN1Hxe9tTXAYgsIFg+FeUCUcFjY0eySrZIvjVfitPi5cC2P1nRN8dXYScOGT59xS2+iDYZluFatdDsLAhviEwhmm/T89sI+uBe8D1gX3Q0tMBlhMQEfP77azR3LUUaKvCbPozmsWIU7AxpldZThhj2PUwBxCbxtAoU1mJ3JbyOP5lx5pOaq265hYK6aViBQjaqAXhMsbgOKtExOxGugKOw0CPRFnq4ESgGTrIualoOCpPKuyXoBSB5VgGx9AThFdYDlmgXHz33uc/jZn/1Z/MzP/Ax+/Md/HK+//rpp+/jjj++0cFSPPfYYXnnlFTz11FObZzJzk2pvZdM2ym0LGOdgsREUNUicA0QLDtPLp7k/D5EawGmX0oK0pcA5bAibm0Jii2ogqUHeuCEMasdh7X0BhwQEvRU+PdGTM1ECIDBBWQwPQQwoNZgsgNPlHQlXXkAkvfdTEp/HRDJojH/n4ZHJu0XAaNqKc5m3o2UQcTIeetqmvBZBbj2s9D56M47lQTUH9CegbbyIlq1v+UrQHHAWeYY4pX1hAKfsq1BplUf5WxzbOWFDQDLUP0fqoQWRNYDMHROi8p4FeOx95kxNXdWf+9zn8LnPfQ5/62/9Ldy5cyctiyNnVN+6des4yghgGmv55JNPsrDXX38dzz///E7yb3rY1KCxBow1WNwQFDVI1ABRwqEFjbT4FL5q8CjhTgM6DeRa7WS5Wuxb45eoBoxzkGfZzcFiGa/H0W2ahxfxEhT1cM/3wwPeU8jzDi4CKAVJAiIcIoHsdaRAGMLkWEeH5IF0cLlRoX+ptDAJrCwsJ5sDRhUWG4FNBTMavkEe29t5Hm6Upxau7bd4J1W7Hcv0ChqBqr0JgwSkKvZ1zyLZIVVqCSyq3kcJbzHMC0Yj8U6k1UAypQ11lUFkPCd+ujZA3g/w2JW0aIzjn/yTfzJtf+UrX8Grr74KYJog45xLE1eWSPt84OHhIa5evYpXXnklhV25coXZXL9+HRcvXsTTTz+9+Jiz0p5wGjTKSkzTWsBI4Y/GC6CbwJHYQsZzUOTbFXAM+QzMLp/vIMsBGyQlnMl6L+O3gUgLBIeZfq9tJs3Uxi6OylNOwt9SWNTArwi3QDFsR8DU4DLaexJGQTF7JR0HSR/uP+9yuWjLFjyJPjQGjkFn3M52/E6JBXZFsHe+hEdAtEB1SQBiHEBBywBGBmEamLWA4i4BcQEcmvnWyiDOoQaQLcDojKFNM9V2mSq3QpOnEOJ2qsCgm4s38plub6+GxzBHy0ue/6pXkYAejZdQmKqpAZIMGIkNPA1zrPw+/k8CpABLanfm4fGYX3rOmjZeAPyLX/wivvjFL6b9r3zlK3jjjTdw8+ZNHBwc4Mknn8THPvaxIt3h4SFeeuml9NWYK1eu4NKlS3juuecSQB4eHuLGjRsMKp9++um0YPitW7dwdHTU/LnCjaW93WEGGlklF8BIvX6GZ1HCYisoquCIDFw0nMIhjQe1J6dFoa0FIgtgFLWuBRZ3BY+DG824mkY/2HHi6aZ5HWlYDSBpXlYaDRY1yExgKEFRgco5mNRA0nskb6PTIJJAS/RIOkf2U4tCAJK2MNIFJOExHQuqOOTQ1lmk0aCR7VeA0QJOlGEtgDlno3tCPQtrhtMKJGrga3VVL4JJxaZqu1DV9wdXHnypx5BDniRII50ChuqYRgp5IHDpShvvHLMvYLIGkgZ4ejRCZDyuBpAka3alN4XHfdUZKOJJynlrtssWeuutt3Djxg384T/8h1V4PA2dOzjAp//8n1PfaHilp09I8rcVGp29rwIjq6zCs6jAIvUSFvAIGxQpGLLtcLyBhKXjK+EAB7VmeDTST3Gjabs0TMt/G2meRWDeu1juZxBtgUUJfTSdhEcJgRQGpZ0GkxIkbYjk+7RL2keQZOEhXYCxKX3YptBF9xXgS0v3UHALYRTmOIS50pNI8zDTOhYu7dg+yn3be6nHq+mLcnrbtjGvshy+TAdpU4aV4V4PF2mojosTTIichUNXiTPSzYRrkKnbKfEyTN12qp3MQ0IklP1quTRITfG+erxkK/Iuz1e+faDQ1//8X8C9o6My4gR07uAAP/wf/Z+2zueD//RFfOMb39hBiU5fx/LJwUcffZR1a59JKXBor8lYgUbpZSQQlzyMBjDKLudWWNRAkXoSBxEHERbBS8ZJuxQGGj8WtnK7ll63Lb2GKw0kj+m1UIPHdQUMp30JfOsyXPUkloCpeRkLACS2GlCO4c3ei7SOeBVHAmkRMr3zDBK95x7ICRjDvRjh0QGxWzvEIo6TCiMkwSsQ3ffE9RFDPIov0zC3hchKCXMiroBGC0QlfCl5SNgzgW1XoDgDkU7mpZVFHpvtKzBogiMNFxdf+S2aOwBkWgsKZTKto6AAR+VeSnF6Ou/IrgBNJ+ypV46H0X3HsqKeQQl4hTeRtCsTrLnkJXQkveptjHl4pDQa5Lm4TezoTzLFh9rscsJ0fJIR3VV1BryOe168E9eJf6v6TMp4mEz7dWi0vIxzwKh1RVNYBDL4UVikEBk9ihIULUiUUJj+Iu6PanyxDS2etxgrxV7NqwEa54BxSXf1ki7qGjyW4FimifaarYRFCZY1uzmY1ECyhMgAgt5hBJJthkYDIEEaitiKxDGQvLlBEzxSSXNLpusJHABboHEOGA2wtCCvFRRrwGmBaRU4C3tfxOn7nu0DAv4scNR+H+M326RRtn5iCXFlxFQQq9uZVX8GjtTepzLo0BjDHA9jkJjziKYUJnk4KUsERBKe4E1ApPQuFqDoeTgtu4+nSYBRAuAsPKaMxHb4a7377aU6ODJ1cKyJPTh8GS6feBY0EgiU0NjiYZTeRdpdTYFxDhYpCBYASeIsQCxBkgMlkKGOeyF1EKzDo+65TGlRwuA2M62XzpxeQ4fEab/0GurAOJp2EiozBI48nNhLUFyF7SG89o/g4REip0athEjvwQEywKZzvgKQCGMhAQSPpYPwPlJ4pNcutlQAcqsW9xSvY0UM/EC2BQSq9gY0WlA3Fy7zn/bnYbEAvsLez8TH9F4HRAMOU9WT8SSsAOkUzy9uUeW0Napq9kLCGV1KWceruG1cvCNFnAPcOm/n9MFeACaHQZeTpbD8PGdld64EQ0zP8QIkHQEx8o/BKPvnOUBCSSfy8Jj+V4SHSAqMlAHjPoNHiDSO2p1hnenC714dHKniU8t6KmnhosJq0Gh1TWtexl0Ao+VZLAAyhFNQ1LyREhAlHGpgqEGhBYMUAmtd2q2wuNpwQozUWvE+Ukik8Cjj4rYGmDWwlFBZA0rudRyJJ1EHSecdVg4TBLocNhAInRqMDIs1gJwkmxWOiE3wmOnw5JRgi49pbILGGTC0QbAEvRZY5GG+ASp9GU/Tx20LEDXIBFB4KQEGghwgwaTOrt7g91YfzTRwnTNlMMc2fAmgATg5SMb0Yiwf8rXzxCbdxgNLXgIgvABGBSQdOa4LEQQAKUyq3kQCkAi7FkCmMHKK0VyDx+QtZPa5NrPfQyNOq33tOjPq4DgneZOnB4hfVgEINCbYWQiNS4CxBRZroEgBsB0gSwCMsGd1a1vQSOFPeiMlGNa6qpdCJINF8vuW3dT6ZJe10l2twyOPs7qiNaDU4hIwInZF+5TviAGjKyFygGPhESKbATLYaN7HcdwQHuX2Fl5HUzuExmZgtGDPOEYrLEZQLPIQaYEAOxQSVbgUcDiKfVLV9HUhRV2U1c+Yi6m8/1VVvQ0ozAEQ73fBgxhtw9+1z+EaYBJPZoZI4WnToDICIIHJskuagKSLdQ8qCDqSr/zXBJAgUEiKXQ0z4NGUzyasQ4GmlwDJXkb3T3tctFNRB8cG+dpdQyqn6W0k0JgfWJPdMPhjB0YOhWMRToGQwqAVHsMAGxBlOAszoLApXI6VNKBx02V4AH2c41o8KakNg0UyFmpdQOCQHpY2ODoWds6FY7kJGCksTnEOo/McIlFCZO7yHpK3cUxAmOFsRG5nR+8wOJ/Cpr8OY7wHYrmdbG6AYdgQHuce0Jo3Y85cgcHCbpfQ2AiMNghyKCvyTuXyddAcyzCWJ0gegAqJVThkYx1FWhGe96HKXO/RUAIoPTO+Pzo7nuThhimc5pu8hvFcE7wBgAcGAnokgQ/AmDyEowKSGgiSNNLLWDgtNgTIwtOo2MdHVQ0ey20B0lQSFMmp7OJd8FjlcQYKebJ64MHRvB9kuFPCijTz0Fh2T+8OGs+5UQVG2RVNgVGDRd3bODZDogREDQLVMDr+kcTPwaIFiVrX9pzWGJAHOk0a/YDzzMYlm9EPOB+2KVzGcAqPyS48lUc4nMc673uHtRtwLnQ7xzC4NdYYGEiO4RqvvZuFSAqKg1szL6TmgWzxPq7Dpa3B49SGNsAj/TkT6cVrWWlZ5lqdGosIb6OWbmfQuCNgZLBY2FRgUcBm2qagmGw83wYyIGpwOOd1FGMaC7CkWgKPZJwiy0K7HZi3UHob48m6fJ6OhAHAEO7VNGORAN/o6zBJQTLlSwrqAAwEBGMYaUcoIMZ3PFp/GOCRv1DCSG2s2sMr6WvwWKuiMt6AyOb4rlPXAw+OVZlQ6ZXKbZhWoVH+rUPjahhVYKx5GS0PYwRGCxYpbGqgOAeJ5r4Chy3AWBsHWQPEJV3Vaz/gPNZluLPHMtK46IWMYKlBpQWUaz+BnAaSADCEGSdTWPYgDighcojHChApAXJwPnkhLYC8h6HqfcQwtfPr0YZH55TmisJjMm/wOtLWisjs4bLCfGmvQV0LIMau3xowqvlvA4y0/BIYKSxCSQsAoxdlM0CxmHXNATHb5oupAqXcjvlXZHkfuYdRt3GysyDCXdqlEBk2hnxz8e5qn4AyeRBjnjWYjOUnIJm9hU6HyAiQMYx5E0uAbIuLwEr2Y7ln4BGe70t4LNq7BJRkrCMUu7Mq/XZ7YNXBUWrbGz1UZLq4N42TsAjMQ+NqGJu6ps8Fu22BkXoQLVhcCooSEjVAVLu1RSvDu7Pb1nds1XniaaSzoM9j6uJNcrkb+jzWuWs5lOc8sucywmSCOXEdcrxPXdrxGo7OTcCICTDXGKbfzGfbCJGjn+IoLMYH/MqtOUCyG3MESBd6CJm8ngEoMeauc9l1TZwyDB69d+H+5vAoBz1VvY7SfWTAY4tMuPTCRtoZoKdDoTdtNZAsvIU1YISRRgIjO4ZPnkUNNic7zzyKraBY2pELR6plubaj8kM0ehqLR7PWVT3KcF8CZxpvGMJHn9PQGyUAZTH20SHDZIJPEkcgEQ7ThB0X8otLDtAJMTEsACSFu1R74v8USFTtxd9U/BF1eIxl92VaVnUlWDa2m1tU4VPVFs3KfakOjjOqjm+MCm9+6pAbR7yNMSjBI09jeRrnoDGC5SbQWANGDSBXbmRwuBQUJSRqE2UsOJRQKKFym3GNUuedHOu4ZpNcWLkQPY00PgJfBOoIl+E6EJBcw2FwYwGRK7rtJq/j6KfttQsTYvwY9oMXMkAgg8U0hjEgX+Ex0OFxCHaj86rnEd5hcPScwnI+iA1qblqSE8ZNQOidhEjhhQQpIwmLXeZMojWarbKxmzrtK+l9mY8FglPcPDRu7WW0gBHyWHVgND2LrDyNoDiS84ewkdtK9Vw6tpFLQmEOF+95HCYJHaX0wdvHbNPtGzbEzOvkyUM4zdh9LiDSO5eur3eYJtpoABndfNQDSUAxgyAd7oEAy1M5/dAAj56+yhF4JIZVmDQuOaS9ZtMImHunDo5MHRyjNnml0LyKAB/bSGypl3GyIwBJ0soxjUBj97QBjeeGtQmMU95j8ihqwEi9ieo2gcNWUKxBIgVE7oWsj3Xc1TI8UWuRvwaL1K4GkxQk1wEjRz9g5dYmRK79MI1JhMvbbtrOwJgBEm7IYxgTCEpYHDE44N64aoZH1kWN3FWfw/OEGSRPI1AAo/A6OkcasOx+QWolowrIxLIHeQUqC4BU0jJINOAw5bUEGq14oB0alwKj9C7OweIcKJ6gx1GTU8ER7H7xTtwwqUvYkfNwpW2ESQKSqct6cGkfLt+26XScmybbxHCHCfcEQE4rBSADpMtA54R3kIMgh8dcvWfgMWzk8PhlJx6OaIscYHok5U/geXe1baeEdZ0JdXBsEXmzzN0FFVuZVLRWERapzSDC5ESYmG4pNE7gV/cyUqijANkCjJpnsRUWNW9iTqOPeyyX4tG6qzcHSDpDOnUnB2RaEZsVGbs4YAwQmEFxhcnjN7gRIwasMIaxiwMGrIPnkEMk3Mi3oxcy7ANI2yuHBJBxYFfMd9qnIMjhcR28huWDu4THZJtzUbusQWHS52kLJkQSmxAtYFHsS7XCY81mDihlvLZPAU4WcSE0TmUKsDLKPBZCoyhXgkbZHS2Akcc1wqIGirUxjuFYquYgsgBFYR8nwuSbLZcppl1LQAz20Vazi93bAfKm5XtCVfPIYxsdkLBpjQSQEzT6DJAA/Bie7UNGQ1JbNoLHCWL1busSGusgGB8R7BnhRbr4E9zHABicuV1EHRx3qao7IwKj3Pdsn35nGshQSbt0tfUZQexk9zSV1jVN01JotLqkLQ/jUmC0YNECRQ6aCjA2kURdK2WGdIK+WI4AgwAQF2hbuTWDSAAJ6NJaHi7nlSCTxOXF3ka+jQla1xEgWVyGxzEBYYRJGx7nuq3jOEjnfO6yFnA4uDyDO3ZZe5/TAciexBDmmeewnCRTDqTawtMo5Ru2xf4cQEZ7ywu5RLE6sr9bQqPslk5eRAaUDcC4BBaZ91FcCAsMW72O1E7zNq69CPccJuN6hjVApHYxl5ED5BQnABITFALEiwgPjC4v9ZOwksy8Hn32Pm4Aj/R88/ugOAaJ4yeWbS1gVAFSSFbV+04dHJkePHA8prcj+Qxbvl9Cppw9bIIiOCDOTYShot3TNWi0vIx8ezfA2AKLxZI8G86s1r4OM+XHJ8REMEwKh9cgMnsHg60CkGs/eSFZXHqYlx7GyaM5pv21H6bfSIFHACTvdniks8XpfbamwBivDQVEAYcDSRPHOnqyX0ySIaKTUuO1OsmHNqtyFaCM+9YXUZZ6GxkAavabQqPWNc2A0oZGBoRz3ke6PSph1r4V1iIKfzXR6q9XdwGIyN3ZWnwR5+Bj9/6ADGGezDEe3TQT22c8lGAXz6kFHumjiHYepL+al5CcCEtDIFJ6F7fa77pv9eCB42lIgUIqDRDl/lyaGGaH613UEhqpKEBO+SyDxl0A4xJY3KSL2kozgVmOm7qbp+Ov4VK6aDdiyHkpALnGgFXw0A0YGTzG2dLwcXtqJSKorgI50MkzER7ZuRAQrX1721Lqkha3kITDaCuBkgEkOGdJbyPbL4xP0H1hMUsDNEqp3sgGJaAL+W4NjcW5lJ5GALuDRs3DWOuqNkDRzXzHmmUhu6RTJuLNQ+5rEJm6mXO3NgNIEa/FOTjiPSTwiAhpGR5T0WiXcvQ6Nt72HBYVgPZ1yLSAT/U2HkdVPGuQueG7zf0q4/2ra5GKLuoFSeV+AyCWNiX0AXwB71ZJWExhFOrMbQ6Gsiw0bhtoHDAWnkir67r1n3YdZJlSuYi9Nl5T00rA80DAml6vuZni6nkavz/Lh0D+rK1yjJb7aNiiIZD3NI/cPF81u4WNQFG9tf25PCkIMvjbvFyzxwrd01KxezrbV6AxahfQSI8TyzL69G+JzHTyGNq+Vd65bvQ4/tTIr/j9POzrv2MQqd2DO7uvlLzUc74P5fz2/+4ndXDchU5wcEcrCO5yaZptNAdULfYSGllcBRiXaBf2Eni1Bc5PU9uscalp7q4vh1/sIHPXYLNnOtONRms38kLw26VU6Nym+xu0K3/DQlnaj0dBoe2WRep60NTB8ThUvIXZLVxhOgOho9Jaat9WnpZz2axlbT1GW17L0mn27FN+Il4bo7iGK74tPacWe3pszT7GxzLRr8XU8uLlWH6drXGa/HiOr+u4A8l7t3T+OLG/k8PqWnBKu37Pm8vvVCcNWLQu3cPmd58bC9/iblby8tu4qUN6NQ8+C7E9w/SJwNgdvaAsRfeRYjSQvHetLbLdtEz39YSYLlN9jOMxqTZuO39VY9K0NIu+nyY7kHivfGctzagVGuFCCx+mexjujzzDd2BevCl9DluHffrlkyEsKwM/5b8my8/ksYDTOcW4nM5hBc9sR0zjBtfiuNGDF6ErevgiOEnv41J4TOlmQI/mmz8dyKExpUsQGePLtPE71DJN3JbHi+s68uO4Ip+lip8dlKDrvfzazPwYyq0ZcYsMlOphy5p8Q8Jlfmr+c5N4HMikiGzuYB9nsdgxwkxe6eGKNtY4wGEa35dmHce/IS/vlDhg2h4c2FdYZHw8Ft1HHR5dWJew7fwXAOSghFvQqMXTOCvfEK9WFRfycTuAL+sYQbP5twDvpnndL+oOWaYOjjuSCoqkJZDx5T6HSQmHU+NNJzDkxEVYaJW0520EQcSJFJ5PagH4si8rN5I0SLAnZ/5SeJzKQNcujCeR46b9EC4mlazYTGVSeDHmsfDa7bByF55N8USUwEjDpKeRQmPplcywN20PLD3bFtAYtyM0prITiBxTmuxt1PY1EIwgSeWVsNE75l3U8iq9j/X9nYkCnbW9NK2RflocOu60F3FKF0EMBCwDBMbqSObbTjYBEYdpVq8KnQOAkczhjZM/nAvVPy8dM0X4BI/xNBk8QsTR+Hg8gAPkJorl1ACvprnlKyrACGwOjd7lvCMQMqAL6TIsluXyNE34l+wHsZ/iy0vgRVotju3L+Mo+0/0KiVL34RjFbdXBMar2us8aD9JiaKA4TWdjSRM3hfj8jA4P4ASX0xc4BkxlSQst00WYQ+s0ra0XPXAEBkFBMgJiLDLdL+GRbcOGx8l2BJs9nLbjydKlZlDGxeOx+OhBXOUxhPQak59nDW18425GXmieSurh02CRptsUGGMe6jaBxvSdagKNMa85aEznQOAzexrJ96ypLbGJ8iiBEdCAUIHCYh/t8cfxACdVuupdjFDH9gPMGRApvYuW15GBoGbfCo/sGOH5MngOjyl9gEdgmg1M73sCiUVtEADJFtmOWmVIBaB4PkW81FLo1Oxr3fE1WKTxFjCGv+lWHVzOhwFgzptBY2wDHLaDRpJGQmHKX4krbJW0s/HKcZpFfwo/A6hde6cOjttIAUUAqvfQAQABRIAAI0JXMwmL+xD7CesCUCYFGIyfnNNhUe6X8DhilReRRlxDcJXXDJTwiCmfyRvKAXLtp1nCMU+6/MzKjRj91N28xiosVTOkWcUxPwqR6asspJt8OqPYnc21ZHkea5xgbUwlG3tpdEnPAWNMK72MEhjpdvI4Mkh0JL+6pzGX2YbG+I9Cn/clQOZwFLYaVM6tzFKwxKagSGDQBMNKeAmIyj5EeogXRYgwH9OGZV1UuNwdPE7vn7TbOiCri9/qpnCJaS3CGBfBLnz1BCMyIMa4FdIPVtiA5AFMIAmIH5jcH5tMrrG6sGe8jszbJ2GQbNe8jzVgnNKGbTqmUcLfwG13AY2mt5HCYxHudDu6L+PBw7bRmYDG7nFk6uAoRZ/8AJx38HN+ag+EpzQLiw912l0NZKiM++FAISx7HcdwfAqJER5H51AMYXLTN4gHN+LcYMGi3B8w+pAf8ucH4QasPRk7SQByFbcjwITletZ+hfjN4gEudSdPcfMQCWQYiyAJACM5y3icqBW8OqFkRdY9bJUFjxogTuHU88hBkebXAovxOLFLespL75ameZb7FDTnu6fnoLG0c8zbOBJo9CQeQPI2SmD00Ya2GB5lCzLXomwMldnFEeGN0VuyE8dxeVfzOhagKLMlfOGHAI8izabwGFZWz5mELuiUzkWQRBirONnF9R196HaNZUKCSPl8CicWu6vpUjUrcBtily+98aNt0hdY8UqWXcFGupZu6rBNYTHZOyV+DhhDHhow0ny3hUYWjnyMajhy2BwwznoZ5+Kl2NvbnmlPi3Va6uBYk4DIWXMfQFF4IWMj6QDAeQ6MsamIXdIhNMIjHdtI4fHeOODcMKrwCD/g3pgXBB/gMXiH0fm0cDfbdx7R+zgiwGGY6BL30yfmkGddL4HI6Zy4hzABDnmqZ49jPiv++T8xKcRY3+KuXy1aBqcGmRog5uNzjyK1XwKLMQ/pXUzbhUdxGTDGY24KjRQK2b7wYE4cIj2VyPBYtD7QxzdqD+q59zfZ7hAQZICo7Gu2ERALb2LyHNJa3ACPA8TCzQu7rRMchkxGF+DPsxdVDx+6ijEBoHcy8wBwbupYiA5CT6CPjnnUPJESEgkg8ok3/Ecze6dH5R6oqfZOODNJRvU4UhtmG+10WEw2Spc0ta8CI8CBTwBjPsaG0Fj9q9vnMpF9ej20nyvZe/5OuBQggcVtb9fJ6oEHx43GV8TX9SkHSFAEELqnfX6Yu9AIeJImJEpf0VDg0fncRa3B4+A8zkl8iq0UDU1Fzt7G0TsBlC5AIvdAjt6lfSB7ISVEIuxTiJziIjhykLyL0A3t81qHMb8J/HIrE4HybgiK3dB3QwumrhdJPJObSF0ayPA4SkicwvRxiyxuBhZjntoYxpiPBYdTPraXkaavQeN6HExopN5GIG97ER5FvY0qRETIOS7Rqiv2C5iM8ci8FsN0QGzzPPK/OU2KSP/CgegXY2ia9KDIABnhPD3XYp7RAxnhk5xLPC8JkQiHxuAymAbgjF0EySM5ROOpfIRAy/GNKR+iHQxPVpeUkfka3djsNqWQmOwUWwmLwY5vI8NiSNMEjDS9BYyFjQGNg5aXhGByvzhxPRSAzNdkARieYRDcV0foaemBB0dT8o2HcqJln7wE09M6dSfFxsfnGNp8jCMwpO4RDo/ruASG88AwMnh03uOtX/gm3vvWET76qUfx2O/+JIbBEU+jw+DzJwal9xFA4YHMYVPae5g8d0NoOVYYMYbGZ3Aed/2KfW7wrl+lr8/EbYQu7rvhnOh3r+8iLJQdII99USZc88mOdk+PuEugcO5LKDGNVMuaidoMYQ0Op3ABhQokAjBBMR6v5lmM+WmwGPOOsJjy2BAY6ZjGOWhcJ2Dk0NjkbQxx6vhGLV2M0yTAMDrJWJgjNZV4FJM9CWOPAcf3N4ZHAxBl13UGyRIg0zVJBQYHSIi0LptizOc+VbM4dnE6aO6ujicdIZFAIYHJKY6c6Uheij1KePN5bKWqbSbNKPHF7SPGRrIxiiIfDRK1NOaEl5DWgkUAepd0sivTWwBYhqOAuwIaA1jWbaGXa1udJZDs4Mh0auB4eHiIK1eu4I033mhOc/36ddy+fRsA8Oabb+KZZ57BxYsXj6uISeY4xxREWyZXvJ7ELmwfWqSl8Bi7rdfjMHkuncd7v/4W/tmffQXv/9pbcOcG+HtrfOiTj+L3Pf+/wEd/6AeCF9EGyAh+sgsbgAqR8JNXkUJjBMl7GFieEiYB+mm+GaAUAAkAK9KQSIiU8VKD8ExqmhsLKWdZS3ttoW8NEtV9AYpaGJ0BPedZTGngWH6yO7sFGKNdhMb1OOXvvcN65N3XLdBY8zYmsKzBYjK2o0xRcBLhMUs5aUbCowaTc/CY4Q+5K9hrcIgCEJPX0IhPBfDk5CIIjvGYPl3zlM/geB4WSA65kAVMAiVQxjACZvJ3ZoAplSbIzBDFzLqOqudRBmnd0SK8ColsP5cpgl7ezsc3YTHFk7+hLAUEgtopwCjyMqFxKMMt6JTXUbPP295Oi7PLX/vucdyGja5du5a2j46O8KUvfWk2zYmD482bN/Hyyy+n7VbduHEDr776Kl566SUA0wl+8YtfXASeG0k+51grot9NdKwj90DMw+M0Rn3yME5tweRBnIAxPmhG/LM/+wre+/YdYO3h703zid/91hH+8dX/Gv+T/+Lfx2pw8N6bAAnwMZDww+SNDBAJH7517R3uIQNgHhM5QWD0SLbAJAATKAFgIK0M/040v85ytnR1LCNJKj8T2LpAeAGKYp8ujl0DxOmYJSTGcOoNjHnUvIpauAaLNI4BoQKMNK2ndulvBsOtoDHEz0JiVIKvBltHQKiIy9m5SIdqHEp4HDL4xblliMX3IGXM56Z5ERlA+hwuAXGq/57lHeMT6JJ4Cn90sp0jXdAZGKffwRGQpPCcVsyK++E6uYFc1Hjt2LI74vcR5Gj+LgDYu532MjjnbRTFqqYlVbjokpbhLCymF5NhaByDPJe8ejFOg8WUfsa7yPLcBBgrgDgbtoEYPC9OvEXaB0jbsNGVK1fwzDPP4KmnngIAPPbYYzg4OMDTTz9dTXfi4Hjp0iVcunQJh4eHeOGFF5rTXb16Fc8//3zaPzg4wMWLF3H9+nVcvny5vQC1GzHCoHXDFhCZmgOQpgGA3mXdAo/FgRTv4zu/+E28/2tvTevdUK093vv2W7jzc9/Gwb/2WxIURoAEIiwOwduYYXAQ8QASSEYbAFi5IYFcGedTuigKqQDvMqbHjNLiU1xa/gfFcaSWLMUjZS/N46p2+jjHEhB5OJ/UEsOijeVRjOWRoCjzrMEiCyN2rcAI7AYaVW8j3d5UhGtkd3VUBMN43sW2hMcYH71xEb5IPAfEeC4+H58BJg9L/1IYSR/PhdkRACTw530GtGlSjgDJeG6IcOpS/gDgogeNAFzyLI5KWCzvKobT5yI5J74pbFmoElaq+qk8Jaqw16AQ4F7TGiCSv4VHMcTNgWLeNiCQ5K3FS2A1gVFLtwQajfi8XfE2OmP7rMhuak5dm7LR9evXcXR0lKARAL7yla/g0qVLs8c8E2Mcj46OcPPmzcL1evHiRbz88svLwHGJGL+R7moTLJfB4/Rwd6nCufRv8jha3sd3v3kndU8XcsB3/oev4ZHf+SmsBoc1AEe8jiVEekzrP3oChGMBdUMARul9BCaYjLKgcrKzwZKmAeoAaY1p1MYx7kLaWEg69pFu69AovZAlIFrxMk6CYLKrgGJMr8Fi2if51Sa/tHgZpzywOTQel5wGh7mW5jCxbcFj2I7V3vIkMoAEMkQSQKRpI/xRmwSCBPYSMCICpWPpI/Sl48ftcItSmASgAyUcKUOIXzkGyxBwOYWHq6Sszyirb3W84wKZt47StV3Yml3X5XbRVW1AYsqrAorWdgGbdFumK9IqZVkKjLVj16CRiJYV2Gv2mteeFn4bNrp69SquXr3KwlqgETgj4Bj77i9cuMDCH3/8cdy4ceP4CxCen84H9KMVhMKiE/sKPKanunOh63lqlaIFogehApDnfuhxHRoB+LtrfOv6P8Ltf/gv8GP/yRV86BOPphnQQxgfybyLoaw8fMjbBCZjmvyXz3zWoTF0UVfsaP7Sltprtjx897Vbmxwzhde6q11hU4NDLd4CxDkb+l1pFSC97lmkdrGtX+JhzHEogHGKQx0aqSREJhhTbJdqS3hM9ChBMRZXhPPy5+vEvX3cNkGnhwKHIRyOeSxNkAS1ETBJoNB5TMOLaX7g11uCZQonO+UEJ73+HMeYMRMctfACcpwZT8GwsKfQFvbztgGJhd0MKCrbLd7JJvCDHj57XAGN7LrJ6239Li2ilbGr0DZsdHh4iAsXLqQxjkvGRp4JcDw6OtoorlXOk8rhXX5yx0ZC3riZC3OaGXiEn0Axjb+i3sd4mHhsVwfIh3/Hp+vt53rEe9++g3/2f7yO3/3ST6aZ1hEYoqeReiPhUcCihMkoCypZXABLGkbTFOGLwFE/+yXrNi6RNXlGQuVSeCzB0AbE+JcCYi0v6VEEMijKeAsWYxq+3I61jwSMMV3hZUwZKtBI9yk0aqKgVZF3pIqGulSkSyBZgUcChNL7mD2KJFEBiiCgmMtAPZEUIqUd9zwqIAkkjyQDSSjliMAJ8HJkgwIqU1gcg8jCyQxp5TexqmRt4vTGqt0yWhVeAo+uFuZUGxsYFeicSTNv61Q7E/poeg0YIezNNL4Il2UDyK2hXaMUdxw3xW60i6K9/fbb+NSnPpX2n332WTz77LNb5bkpG8X5Ja+99hrr5v7sZz+LN954AwcHB9XjnglwjFR9qgqNgtllzWARIE1LammY9zG2Ps5P+RoA6QNwUoB85599c77hXHu8/+0jfPfnv4VHftenGQSybZRjDZ3Yl6BY2qxUe5nG6pYu0syAo2bD43YHkLUZ1zVw1LqyeZgNh/RvCyCq4eTY0kaCYg7jsBjDeRe03SWdjuuzF1J6GWka7mkzoDFBmEIFNbhkb4M5q7SuNZA8iTV4jGDI0og4DSw1L2I6d+jxCdYskFTScW8i3XZ5GzkNW6qniCdQqdmwE4hxGh3Q+DKsZr+xatBoxc3dUjPd19UwCnRhXwVLI860l6CoxNeAcxYktWMLOxMaYV+XrXTaPEnr3BZ65JFH8I1vfGP7jIi2ZaMvfOELbP/SpUu4evVqmmhj6UyAY3TD3r59m5HwrVu3TDJ+8cUX8eKLL6b98f33lx84thTib+qyjqrBI3vqhwbVxWdSCZAZMqdthykuVkbnHD741h248+fg1x9Ui+/ODXjnm0f40I/+SPBYRrCLeXkTFuMpaUDnDMizgNGyr6WXeWQbGwqPo6uaapNu6xpA0sWxNwXDmm3eB9uX4xVlHO96zrAnYTHZxIL47GFMeWrAGE+gtk/DrH0YYKJUw5Se7NfgMQFjhKYIiT7bM6Cix/TgQKbAnwQ6Cn0MpoON7JJm5y5hkuRbHpOcvMwjnkq6AWgYOdGW38CoisftVKq9S0wFaEznKvESClnYsv05oGTHaYE8JUyFQBnXYMv3fRFXlJ3fagXodnFdv359FtiiXnnlFRwcHGzERgBSd7Tslr5w4QJef/312eOfCXCMJyddr0dHR2Z/vHQDn5txvard1UAdHmnLweAxJgSJ9DkPCZDx2KRSgr6pAqDfjF19wh7jSDXeXePcJx7HvXGYwDGESwDUgJLa0TCWXhzPgkAnWou5yS4SGGV6K52lTYHSAsVavAaD0lYFxw3AkIfxfS1vDRKnvzlcD4sJK7AYDiC7pFNeEhBjfgx+dGgsxjZWfk5addOwEFJHp6WyUMIjzdrR7zyDVV8GlCGcPipA7GmgBooS2hbDJOLxSy8itVG9nfR4rPDkWVMDROU3UGdHN1S9TWFyFhLTAWp5KJEN0GiFq7bNUOna0y20qcHinD238fUyyDBxHKrm328fdMwvPABw+fLlxRN9N2EjAAkqDw8PmyfEUJ0JcDw4OMClS5cKt+zh4SGeeeaZ4znoJvAIcIBkT21H0obWy7tcGb3L3WgKRHpMLOkBPPTbPoPzP/gY7v76bWCsdMs6h/O/7YexXg8EEpFmVVMgs6BSbtMJijUgnIPFGnTWwrS8W9PtQhZMehFedGNXgJCmb4FCua3lrQGk93pcGR4TCDsWFm0ELAYbmUcVGKmdsDW7Qhe0OrHqJc+iAo9kN4fFuh0yKLqio4kGZPR5ETeLc+Z/VU+i+KvZMDgW8Cmhkqb1SpgMn/Uusn2n20gdV/VsvCXMW6cFbjaBSGa3AA6N423lxbTSzUEpBUYtjXZO4njFNtVxu6K31L4Wbxs2euqpp3B4eMjCbt++jSeffHL2uKcOjkdHR4VL9fDwEFevXsUrr7ySwp577jm89NJLac2ho6Mj3L59e6dL8RTDoubgEYg+CfjiCUvyiK1GShtashTmkmlM65RKmU0dPnH1T+HXn//LuPsbt6fvEmryHt//xW/iIz/2IwIE418NEqGELYO+wl6FQszaaHnP2bek3UY1L2QNHjno6WlUeDTy14CQhs/H04wVQGThvDAaKHI7GW+EUVsljnka5d85pbpKKjWpvwnA5OFjlQ+2ESAzDHI4oteGeR4bYZLmNQeU2nFr3sRp1ylhyrFS/vRmkXHK5Vd+j6Zqt8uq2f4OsVFXdg0ezQk1GlTOhNWBsz1/q7wtgFna+gYbpUwow0zQPgvaU3AE2thIY6rnn38eP/VTP5W+FHN0dIQbN27gq1/96uwxTxwcDw8P8dJLL6VZPVeuXMGlS5fw3HPPMffpjRs3GFRevnwZt2/fxgsvvICDgwO88cYb7CLsSs3wCL5tAmSyI62FAEbmXcQU7lN4Pv7kcZz2Vxcu4JPP/4c4euXv4rv/r7+vw+Mw4P1v3caHfvsTIb10VzjWcGoAKcO1fWlft1PCyqRV6GuBxiV2m0hCYi18FyDYaiPjYKVHaaN5mljeS0CxJbzId/pTdJUa6bXxeUwEHuNADfnrpNnWSnFi9WNeRgmRsQpHqFLKVMSxcyWXwxdJbagM2zRfzWvY4klkNgQ0ZTy/Z6CrocrpC35vp+pC4GohlsdXvY8yfg6YLIhqjFcfPw2g2QKKm+YBzAOjWvZ9deedEbWwkcZUly5dwvPPP49nnnkGn/3sZ/Hmm282zagGAOf9MdTiPdS5gwN8+s//uaa3U71Syqfp/HaafV2pRCzfokJW0oe4d17/OXzn//rXlQJPWj3+KD75534K537wsSkZy4uAIg0uzrUNFNW0Ffsa2NXjzKhF+WwrCx6nONu2BnoWHE4BlTyKAtRg0i6b1h2sgqiWX8V7qFaqOWCcyUcFRwlMStmr6azjaukM+CqOYxxrsY32TrokTa1az+VdsWuKm8t3C23lvdoAINVj1rxpLV63Fm9cQ9rlXs15UJzLCzCAsVbmFN92M3z9P/4LuLeDpfc20fkfOMCPPvMfbZ3Pnb/xn+58VvVp6dS7qk9cHrMPCzosMadzInL+UC56JFJ+PqdLeRuNduwvqzwgvPc4uv53q2VY3/kefu35v4Lf/OX/cPrWLsuLNMKsAjvzGlWhrQZ7tWRzD49mD2OT2bFKfQ0rIK4d+vT85DErUFYtRz3ehA4TNCt50XgGOBXYrOQ5d0ukjgLqzYvjtAzvYzocrXokvfQM0nJ4Fu7jf3p5hee3CnD0kaHY8eNa5SlVdDu3guNMvotsTlKbPBsqaeY8fqZNi20NPBfYcjsFEKn9UiitlK/pOrS+PezBMx3A/t3Pp6wHDxwXqAqQ1Eg+0J2+n2dGg8Nkyksch9iVBXN4/5e/hnv/amYdp3HEvX91G+/986/jQ7/9M+VxQn7ys18WhGXwVAvWFFSYtDxEFj5ATgsiTf+9El4A3xzIWfnXWqgljf9seTY87hwozh1LHGfOU0aTkVEZBYHRe54dIdhSDgSpuqwBnblGejcvN5J5lBNQXC5G9TpVYFXYeiWsWuaK/X2vLQFSC5vr9m5KAxQ/8my+LYAo7WbK1dStn2zPGDB2qXowwbHB60gl7/UqSKYDKLvSY+FEQ0ptUvYKWIY07x/+S3tiDM1ytcK9X7sFfPYJJVI5aCxitZJXLuDCSu+Xptmyr+s4obI68KPZM9iYtma/1GZJf19DmYv7ehZC6+Vp7jYVL1uso6B4oRNeGHpMCZ3Rbu46OvZH8SYb6RSoy8XLJLfESzh5Hcvfdc6TWD3FLcFxF93UpzKxYu6Y1ov2AoBq6aKeC98YZFuPuwQSgWU/+D7D4oP4wlTRgwmOQAlzCzRbF6KHQOYt01kZsfbLqeHee7z99/7hTEGC7b01zn3848DaOFnzGuxRTZZd6YvT580TfQYsBclt8juG9OoXW1ry2hKIq3WsBd5qL3sw7iDhatPfCe3rUUCbpgWQXzwuGvIrPYncQJ0ZXclvsfahgT2tx9ZSz2RDulab2cu+4fFnH1GbvgnsUdPSojNW3GPXgwuOUcf4oDPrlPAc1mSZvP/m17D+7vfmCzEMOPfxx/GhH3kC7t5mXcn7oaXQu0x+F64QRVXwAho8gTsrynZaWo6Z8z72JVtmOgKWNOT8ncUu1LEAmRgPKbUUsHv38wlqUS/K5ofZ2AO7zTPvzLQbO1KvI0wdHDfVNjfSDrz3937jO3CrFfza+ILMavp+9PnHH8cn/sxPYVgP9Qwt3Q8VpuGc3YzR0ofzomfyaVzj43zw7+s9s+E5n0rXaD56NWrJpe6rnuynTvf+Oh71e+3+VgfHFlUqwXy39TbHtZ8oD134uA2Nw4BH/+AfxEd+7Mfw8BOfgXMOkKYbPq2O3VO0a235UKbzmXap43iwNv2kezg4/ViXU2m12bQcm/yQJ3FtW72Nm+o+hJ29em5p2gFhbvzcaU1XG+ah6CwApsPZKOdJqoNjTTODz2t2xzJ2i+hDP/wEzl+4gLu3bvHPDjqH849/HBf+yL+lA6NWpjmDhgH9ar5noLLNPeCOffhnyzVqfQhbA/StzLYYd9XchjXcBK3DV815aK0TAqw8ikK0lWe763dGJw3sU1mOS8cNVw3Sh7hs8DZgjYFtSqs/K6qTq6z7w0ijLVKyd/LY/5eKE1YHR00twFjs5xowa2sdY0l54PDJP/00vv2XruHu7dtwzsHfuwf38MP45J9+GoN3LN1GwNoKzsBmoNxajk20I0/jsmOezNNl0exLx4M3nXUJ8J+HRdfKYxTWvr52xWCTT9hJiTLIGaPyWLXF/LV9I6yAvwUAa+okPcLHVbZdHOu41Ow5ayjw4nG/7cdVv0C2NF/1+T1Tsem+MdurWIEgmtfKIOuroTMBkl0dHAvJtqAGgRYsGtusTszAZQt8PvSxC/jh/+Aq3vvVr+KDW9/BW/+/v48Pfu1beP/Nr+L99S/j/OMfx4d++InJ8yjKax5nk7I1pJlNvydq7ppWDTZoHRckUcs2Az3Fg9haCHgmr7isqBqvNQ6AvnSNAoGSbIuFixVb5xvbdpmXdkxjuwqGVW/jQjBd6u3c0ZCEpmWpjmGN1enYJ/SS1foGWH2xtvOYXZ5p8aoExsDVJcBXSZOAtJJWXUqrqOtlOYu1gOUL3UKIBPZo/Ocet1mnoQ6OVDVAmgNGxVYFRcsLaMHmzMNg8A4f/fRn8dFPfxbnzn8I3/6bfwW//rf+Otz58/DrNc4fPI5P/W+exvmDC5U87f0m7+lC2+Y2Y9eVdeFDqG3M4PJibPowdMWGkp/YdoVNDnTCvvalCRNWrfRQwMQBVrtlZe8pKcaEjfCY4jRgVM7BXIxf9SS2QGhjfqJClNdtGVhWocxMYyeZq7BN1WQP3harnwg1I5wam74F3pjR9l938mq81W6wcms20mtI6zH7BuoUp328AsWl4W5JL6puAZ9W2B5qD27fvVIHR0Nz0FgAYwMsViGzdgwjDS2r9x7f+cp/F+I9/AcfAADu3v4OvvlfXsNn/sxVDAVxQJV13CXlmTvOsU4qalWrM2LObmE+VXMVUurloY2+1RVdAKQGMizMFZs1sEzJVSCLhjmM2RpOlqnBiiaUFmFfRHlMp1RMJ229Gs7zrdhUj5HPzPpOPBs/NuOtbIFKtfhahTMq4fLvyptRs2m3TdPsUZyx1zyHS2xL4JNplc5nFRI5tKUq4o3KQpdr0p7JapiSF42T97EPdYQA4KxXMlVcAyDlxdD5vGtP1cExqgmQbGh00t6CxSK8DqJqnJLPu//yq7h3dAuF/Ii7R7fw/q9+FR/59MX585yJX+wlbW2vlj40ltgva1tm7bdZzHdxWgUKa57C1Ihr8a50NNDjOGFblImF5QaGp1OA0oJJAySLhjkAZBpbReCxqcvaOKcqMFpxM+EqHKbrUMKiBZOc4a3KVUKbBK75eAU8G8HRgru5n2M4QffNaMGfYV98R17r7vVyv56mZs9hz+k2AJzwODJPZAGExEDax4qnASNLR8LpvZ6iw/1e+7VrAEkhM0oL2xftY5lOUR0ca5qDRulooGGanQaLi0GzLKbzwN1b3wGGFaAt0TOscPfWd+A+eZGlUfNXjt1sX6Txuo1MT9VYQZe2PYu7h2vPwxlvl57G6SaNsJiCnRJeABHPSwKhmo8GT8LOKXYFHIaNyHcR8qTXMTUeCvglDyexUeFxTkYXdTMw1mBRgqIFicX18TRY2BJwVGCTAh0P121qdrIMQAl0LZA5GPd8zWN4UuBoQSOgA+G4EAhHAXeWrQWKpY03bTj4ibiwnxiNPas9vA94F/bhXZmfBoyk/qYwAZEFQIo6m8NyRWfVl8Bo0h4CZO+q5urgCOiAxOJnoJGEm8BYy2MuTJaNlnH0ePebX8UHt/4V/Pqefn7jGg9/7OMYIlPOQGkNIp14wCzySir723ofWyv0InCcgUY1ehYmc0Etj58W74q4cB9ZsKiAIrU3QdEZab3CaU4DRp6/BEkKYdV2goIiKvCIHCZVG/PJtluAcQ4Wa6AoIFECooRDHRbFMVkYsSOnMijp5bYEPh5XB0YN/LRbugaIxw2PNWiUcbIkRXwNGMk2BU8LHDXY1GzTY1aBSxlHIdB7B+fIOXkHF9MQsEztVgGbAhjjA0+GAfy5ZHkgWf1dAI80/32Atn0owx6pg6Ml8UbWDI3FPknfBJi5CCrQkbAP3rqNr1+/hrtv3Zq8jXQ9x5TJgIc+9jg++okn4NYiL1H+KTyDoQmUDVBrwWPRXigV0qmDiOppFqkBIr01cMsInoNBaucqNixegR7pLZOgpoGlCpUaUDbCZGwDaNk0kKTd0dHD6OF0TySU9sOAx3yhKjeC9DbS66dBowREsW/C4hwoKlBYAqMFkjw/DQjjXwqCGgRaYGgBp3W8FtsUplTUTcY7xrxrMKjJGqM4ikon87XAUMZZHscxAV1pq4GmF3HJFnp8CY7xr+c2oY4wmBQgmSb5MPu4HTJK9U+QnPIW7eGn8Y+0vm4DjzGua6/UwXGJRFvUAo0SEKsACb5fg0vvPb7+yjV8cPQdwI96FzWAhw8+jif++DMYRpfyMr2GBqCaNtV9crE0mCThUdt6H3ei9JDiB14ChnN2BZTSN3cVFvO+hDgn7By8AYv5Ie9EPOuG1kDRis+3FGsAIjC6aOO1MJfKKxg05cnKT6CReR1BEsiw4rpXoJGAn9xPUOgI+LgSFqlHcQ4U1bBQJAl7Eg7zvg2FGmxqIGjFU+irQeOmADnZKi+6W2r0gx6uVNYaMJpeReg2NViUIKjZl/v82N47FSipFzJvx67oAJLhWey8Y/UKJC5BZKyjCSoJBLKugJjIkfymv8cCj6esY3aQnzl1cKQwKODH9BaK9ClevL3p4SQNlDhY+fHtd775Vdz97q0JGqWGAQ8f/Ca8f/vXcPGP/Rk89JFHgbXX84plmAPXIm0DfKIWxmtiiyeyar+BZh0YzWDoGmxovDfCyW6CQcfgMOWvQCX1ksU02RPohW07SELEpVMWx05wSBqJWNbsceSn7jF5QAABi57vM4O5340qlU25YSQ0svPxDBinc47wiBIYK7BIPYoWKGqQaAGiBYeWHbOBDZstEElhbw4al0DkXDpNcx7IpbAo9ymExrw0WNQgU9qrNuRvPGMNKCMQUpj0gbhoWg0ks3cygqGAyACQHuGeIADqQkVMADnlFP6KfQGK9x087mOZTlEdHGekAVDaptBI7QU0toBgzTOppb97+ztwbgWvfFNwGM7hIz/4abx/+9fwzje/ioc/+/tsL+LsdgbEWdgFyIOpvGZ6mKiRWvve6pioVe5G2DAcFgZEioenk/F2Htyz6JSwaOfFPoVCDpUFUEqYpHm0gKSE0tgOUFCMxZeAGTe9sAUyUKZ9xfso4JGN2xJSPZCqIS2jAo0krvAyEmBMZgQYNVgs9kM6CYrUk6jBnwaIEg4tMCzihd0UNrI4zb5Mo8MkAKwkQJoex+NpjTWglBC5LoCRQKLiYawBYw0wC6+jApYaLErvYgZIua2DJPc65n0KkvB+BiCnArhUMwkIFi5+vxU8Mu0rPHYldXBcqNjwFTd2gj0bGi1vn2YzB5IPf+zj8KPePe3HNR79Lb8Dd37pNRz9ys/Cf/ABPvQDH5/GOcKVx07bOiTq2wQQlXOa9j3fp+3LEnhsfIjMtUMtcEFBrIyYyU+C46DHJeBL4d7wNsbykDdzFucLgItd0o7YF95EBRBdKEMCUgUaVVAMD/mUr8ttAvNCItux9iccY2qrchOlXc98AWN6mvmMqA3zLoqbpgEaW4CReRqhwyKDQwMUB5amhL9WQBzcWAXDbFcCIQXBFnhsAcfj6KaO0rqra+A42a/DdgmN1D7mXYNLDSxrNnMwOXqHFYFCR+IcAcTRI+w7jADgPIPIOAYyeRTdDEBO6IdYM3Xvo+NviXPwaIh5HVM5bPsT1z6VZQ/UwTGogA5KBRooxjQM7BZAoxYPO530GH70E5/BQx+7gPffEt3VbsBDP/A4Pvz4pwE34K2v/Ty+941/AT+u8dAjF/Db//DTePiRC/OgyMpqQCIFRAmHBjyqHkjkY6hxUXK9jIVq4QttfREVOF3uYi1sIkis+f5k5xLwpbCBA6uc4BK9jhQCnYDJHO45nAUI5HCJAiIZCBKwShBZA0XHwZABZLw2Ph/Go9y24JHZx4Zu7odk3sR8/Yp0xblvBo0aMFL4i2HSsyhhUXoU6b7mSdTiqfdwDg4lGGpQOA+Petf1ChwM1W7rY/A4qt5GEbaG4V1UPIcaYCboEzYSKjMIjilceilHOAaREyQGYBQgOQg77zxWyPAZIXIMIAggQaR33gRIiogI+canG4VHANz7OB0hbxvg510uT83rqMKjzPeUdAy36plWB0cpC2yQG8fqjbwpNDaETel9CHf47L/1NN78f17DB9+7nbyPD//A4/itf+Sn8Ct/91oCyvHe9BWZ9793C7/86k/jd/87/4f8FRkDFG2QFJCohJceSM/3CQByeOSXUp1dfZwV2CGNBWWHVCezcGhMFgI8s7cvwCB8AZlujZSBBEs/UIDMXdMSJlWQdPl41BuZwFaDyAScYBBJATI94EU66VhIl4nEZ29htqHwuK1avMoFIBvQ6AYsBsaYvQRG2Q3dCosSFCkEyi7mMr4OiJO9DYYyfwqD1nhIy2Y6RullbBnz2CptTONaeB8pKNoA6cx4CnxT/jRch0oKlHMwqYHkECpljHMCIqf66pO3MXshM0TWARJsDKT0PsaZ1XTsowmP8e0RIjrlh+XawXNhK821+Q+gHmxwbLkZDBvT22jZke1NoDEDY457+KMX8GOXr+LtXzvEm3/nZ+DvfYBP/r4/gntvH+GD791WzmXE+2/fwvd//Wv42A8+kfMDMiwWZfXpOtRAscgHSIBIITSlVa4vC9d6sirL9Cx5I5yFCwGKDh4QvV8UJl36H4C153FpMwOjI3ApwTKdSIS4MR/LOZ+6v8tuaQpBLj3zNU+iAzhEkn/UW0mhTwVI6BBIoTIdL8bPwKNsmmR8tRFpidPeBhVoTHCNdmhcCowyfCks1kCxBRLnAFF6LDUopDBIIVBCogREDSKZvRFvzZqmYrDotG7q0rNIwzW4lF3MZXgGSgqT59wEiQVIugCGjkKiJ9sDRsch0gWIpGkiRGoAGaFzjL9zLK+zax4U72Pb2xhI/RNpHJC6rPmh8gPD8jp27aUebHBsVcONrHoYfRnfAo0J0AxgTGXywACHj33is3j0N/92HH395/Ebv/j38eGDHyrgJ5VjWOH9734H7vEn6rAYw0YSRo5rgaIKiRowjjk9u0Yow3OYekq6Z7KiBE6mPAoIWYNd09JzSOKGXJ50HJezTCMLEsSFYw4E+EKekxcvQ2ECSQcgHifAYvYmcogsABFIkKTGW9AXzntqF8oubLWbOp9qGzzOtFEMIhuUgFpmYoRrM6e3hUYNGAs4hOJxDOFLYNECxRokWoAo4VADQwsW2ZhH5RezwFCzZQq/2bpyo0i4lLY0nkGkcyxshMP5MPZRQiUFxwnG1ipMSmCkILmWdi57FUfvQ75gEBlh0XuHwfkUXgNI2YXtvSNTKufhMddnPuax8DpqgCkr7NIKvCda2sbc7+rgqEmpALE91uFP2Eu7mMccNI7SRoFGI/2HDz6Jo6//PN75ztfx7u1vwY/6V2T8uMaHPvo43CjzzmDIYJGA4GTr87kIUORjJsP2CHjv8dZbX8O7793GRx6+gEc/9iPs5TRfHwqWZUU130Q3qNQOMOEaMF6yy89tkG1adiU82g4BvpChMnkPR1/ApBtcCZLRU6VAZNElrQFivABWvAGDLCw3LQVcNoXRHaoElMTrqNhAC5cqwFCDRS8gMUPjdFnaoXEYRhMYAQ6NGjDKbuo4oaUMr8Mi9ShSUNQ8iXOQaO4rYGjBYjHrWu1OWD7m0VqOZ+1k97QASVJvYxyFyxRGAdKtp32XgXJNPIdTHgOBPYd1OJ/J8zcATgFG7zAGuwiXI0pP5NTNzQFy9C5c52GCSAKQ98YQhuBpBJj3cRXCvPMYxwEWPEYXoDbmsbnLOoa4M+x13LfynLI6OO5KFOSELIAsPI0bQiNGj1tvvp6LYkAj3ICHP/o4PnbhMwUc0kktCRjp+UTPogaLsc31vvAkvvfuHfzjX/grePe9OxjcCqNf48MPP4bP/c7/LT58/lF+TcDTFttRO5uQqeQdu4JpWGxoIsxa4xWH/NBk36aObx3OTSDtWDYJJql3Mg9sJLAz8LgEkZHEkp0GgzksmrLndmgQynAbBjeBRwluzpf2JkzOgeISUYgO+3RtwwiN9MbcFBotYIx5DiK8BozSi6iH6bCoeRkpGM5BYg0QeVjbhJm57upZifshgt554k9bY0CcpRYB7zzI+EW3xugHnE/2Loe5dQLKtK/AZIS8IdTVCRoHnMOYxjUWEAlgdD7DYvIg8jA4JCi0ABIYw3I8CGUDzg0j8z5iHAp4jF3X031f1lwf47wyYWZJZaRc2XVfqIMjlYS7pjTK2EYKdTQ/EqaBYBM0jmX427/+Vdx997tmEd3qHOA9Hv7o4/hdf+AnMXhnd0ezvH0uawRGCokxDRBeXz0DTT96/OOf/yt4973b8Bix9tMD/N33buNnf/Gv4t/43f/7NKkDNB9a9mKpnsoPs8TzaHkbRy2Oj1sEPAdMCpYaVA4Z9NihxalTkOSewdAorANBDeStnHoh3eRtdCPCTO0Ag7FdEABZehhrcUizvxfDI7l0ERRTeNzhl1sHRc3WUs2OweD8Pl9yp4RGvsxOGzRKYARQQOMmwCjh0IJFzaM4B4rlfrn+I4VDPv6xvtajlr4mOnElagI5/sOfBzCSykrhksNjgL8IdQmuHN93cVLLEOJ96o6O13R0boJIhDGPbhD7PgDkdDwKiwN8GMdYAmTWmCtjDpk6HQg8xis0eofVMJrwyF+Xpr38mUIy3pEWYQosvY6exzd1XyvaN6/jPpVlH3RmwfHo6AgHBwc7ycu8KWo3izfSiTAGkBWgjHkthUbn/TRmcVip6zoOq3N4/NOfwyd+5Av4gcc/g2kdR5+9jAuAseiKHoWtiH/ru7+Kd9+/Ay8aA48R775/B0ff/Toee+SHORzWvI1Gm7LZ+JPwgFQBMuTHx9hzoGSAScCSjG/MUJwKGmxskPQOwDqExac69Y7FNWkmKpke7ApAJrdi8D6W3kTqQWj0PpL2qgkeiaeh9Gfkc6JeR9ZAeofCq7uJnLVNfyufy5P2IxBmWKTZyDGNm0Jji5dxE2CkYGd5FiksLgXFuK8BIgXDcmmesiLPjm0USmMPxRvCeaeNcfQkPsPlilTwCJEJ/kKZo3eyBpIUIqc4l4By5SZP5AiHdehSpvsRaylATm+GCPfj5MmmXdhV7+OYgbIFHr2PKzXk2ul9fCb5tI9gM+t1jG+pxs+pdlfTtDvtVtihOjgynRo4Xr9+HbdvTzN/33zzTTzzzDO4ePFiNc3Nmzfx+c9/Pu0fHBzgueeew5e+9KXjK2gDHMYwBpLSRoHF7L3j+yw/AZbUPgLfhx6pLAbuPT7xI1/Axx5/Itj7erf0TJe0CYwUfEOX7jvvfMd8uRzcgHffu4ULH/lULGiOJO2KviRPpRa3QmT0DGr2keTIJZ3AkNgO5FjOEah2pX0af6iA5ODCi/kEhC56/HxYbNe5abJNsKFQlz2QOZQ8/qcQ6X3EFvBITsmERwZ+iq30Pop2IkGk1X74HNfUzpjQaG1TmASHRQGQciIM1abQKCe+aNAoJ7tESNQ8jBISqaeRAmINFpeAIu+mtifIWN3U0jNpKXoRVyJ87QesHO2qdizP0Q9YpertQxpHzjeOecx/B6wTSA4YQh7rkPcEkWu4DJF+wODWYTzjNLYxAaR3gNMBMnsRMyxOgOeQMJDc//FKUO/j6LzpeVyHruc45hF0n3gU472cwNDVvY6LZl1rj+cGD+Rpq3scuU4FHG/cuIFXX30VL730EoDJe/jFL34Rb7zxxmzaV199FRcuXMDBwcEsaO5K6eVLwmGUCJMAaQFl6X30qn3hfRRxj3z8M3j4oxfw3tvf4eDkBnzoo4/jBy58RvcyyvOS0EjBMpaPdkkXHsgMkx988Da+9Z1/gtHrQDv6ER85fzDlYYFiSzf1xouCi3R04gu7hgIwCVSyTw4OJG0EycKW2AETlq3jV2N8AMDsUUzdQGFGtxsI6iWQBPwYJtEcEzyCnKbmObS8i9KzyC67CJNQyRrIorGc0SKY5GCoh+veRiptMkxx2AZPI9AGjTUvo+ySLuBxBhjnPIsWLFqgWO+y3myco/Rixi7o1JUswDLGr8i4xQFjAsnUbe3zuYwYsMIYYDTY+BErNwagDN5NN/JtApBwI1bx+G7CuCGu9+jIMZ3wPqqwWIfHEWGcJHi3dfSwxvs2QuPgkLyOQAmM0evoZ972Ypd2FSA3gMN9667uyjoVcLx69Sqef/75tB8h8Pr167h8+XI17YULF3Dp0qXjLuLmqtzopkfSAEINMhnQxTjn8KP/5k/hn/9/fhrvfe9fpfCHHv4B/M7f/5PTI3ELaFTHMSpexnh+v37rF/DPfvW/xd177+jXAQ4feegABx/+NDDS8hjQqMHhrpdHiAt/K+MbC6ikMFkDSWobY0ZXxMcPEE4AGHOY7KaenwCQY4bHKU8CgjuGR8i2gsRZQEi7rOfAUPUsLgXEJZprgWjZDJgsAHKht3FOc93TcvILoEPjnJeRQ2IdGDeBRQsUJSRa3dM1r2MaryhEgZCWjwIlhcm0DA85Pwsi6QsMBcgYZwEkO1aqgPHcBgKM4NvC+zgHj2l8JrkPIzyOyF7F6XpkW8vrKIFRguG0j7KtS5c/FM5DBc1ke5ag8CyV9QQ0v5rqjnV0dISbN28W3sKLFy/i5ZdfPunibK1ae1QFRSO9uq8dg0Ek8PBHLuD3/s95l/0jF34YD3/kMb1wBjRi9Di68zX82rdex9Gdr8EvgMa7d7+Pn/uV6/inb/5NwHt85hO/HwAwuPNwboXVMP39yMMXcOkz/+tpDkjoPgeFx+i9jP9o+Gn8G8U/w86Ff+l6jWW5k00aLkDjQLy2+Rqz685Am8I9CPSTiUzUZlTSGPdv+fJQvwet9MU9p9kZMuuPajwTryUx2rMc701bCYsAqt7GGF/rop4b0yjzsjyNwHbQuMJYQOPK+elfiBtIfumfG8Mx878YtpK28MzOTCP+WWkGlPnH866Wi5YnnVM8fx9+B5lGG0daXts8FnU0fo/yN9xE8R6hSzXJey5KesvLFca8ut2yX+i4XgJPQc5v/+9+0ol7HOO4xgsXLrDwxx9/HDdu3JhNf+PGDbz++uu4cOECXnvttaaxkScm6+Yg4dUbaKah1byNLJ7tDLj97V/At3/lH+CRR38zPnbwGQBkNnVq9LOn8L137+Cf3vxLeO/dO2myzYc/9Bh+77/2p/Dhhw8UqPUJVv7VnV/CL37t/44P7r6NHzz4HfixT//b+IWv/dcAgC/81n8f4/gB3vngDj5y/jEcfOTT+Y1F8zZSD2Ot63oufInk7G4aLruuY/kGEkfskoMiLL/DvI+kK9uPrvRMesCPHhiCTTFu0GfPY2UdykWn7lF6HbWsveFtTHkY4fWeruIYx9rgKBVwtgEUsrqpLVv6NZhNJbuoJShmO949ncKoF3AGGmMaIEMjUHoZax5GdnzyINu2q1qzT15FOpYRAzvuGi6lXfupM3jEwMJW4GMVV5i6pFdumrTC0nikyS7woes6eBVjHtHDyCbPuNytnK+P5nls9zrK9SzjfUFnmDtR8ei+c7w7mu7Lx1+hs+Y57NqJThwcj46ONooDcpd27M5+6qmn8MQTT+DOnTuF7YsvvogXX3wx7Y/vv88NTMg7wdekLSBSxsU2JAKfg4P3a3zt5/9bAMCHPnIBv+tf/0l8+MMHehbrEf/05l/Cu+/eBvwIvw5L57x7G//k5/4K/vXP/wdTByf1hAG4d+89/Itf/e/wre/8Y5xbPYzf9Zl/F5987Pfg9vcOcet7h/jkY78Hj370k4D3eGz84amMEhY3gUbv4b3H0XvfxDt3j/CR8wc4+NBvyRNQiNzo4eWrdXEBBBzKcLauYuojyq/sNJzCYQUepzxQjI8s8g5xDs6+PSPUNXZZz8JZzM+wM3ugvAK0EgaPGw7jYbaANdlFvTx96f05DtU8VQVAim5uvp3LKrunp7S7hUYLGFtmV8uZ1DQvCZG5e9qndCs3MnikYa3wGK/JWt32rIwDgdOy3IO5kHmr4m8nR/RIWIzrQdL9NR3f2FAOlRMb0zZpl3ntUh2OmU7N47iJLl68yLyLESRfeOGFYmb1s88+i2effTbtn9vR0j3HpV190ugjj/5mfP/Ov4QPk1LibOt3v38Lv/A//uf4/B98No2po/ru0a/ivXfvIH8Pb5LHiHffu423vvureOxjn2Fxt45+Bb/45n+D9z/4Lh7/2GfxO5/4Y/jQ+Y/Br0f8i2+8isGt8Fs/+T/b7ERmrse7d9/CG9+8jnfuvoXBDWGyzaP4/G+5jA+ff3T6Mg7VesTRe9/E9+8e4SMPP2ZCZnPZLMDbVDTPhVJhbVeqQd4JAeCx6D7rO9oUUjftHi2Or+RT8zTqZWk7Bwlm24iC4MZ5ECCjy/MAdlnp+o9de677sKt5W504OMYu6tu3b7N1GG/durXRuoyxy/qsy9MlXTQ1dgmM67vGAUa89/1b+O6dr+HRx54oot9999bkrVwra0G6Fd5973YCx3vr9/HLX/t/41u//jpWw8P4sc/8MfyWH7wEeI873/s6vvWdf4y33/t1/MgP/k/x4YceJRmBr8VIvW9zXcT0VLwP0HgHHj4tLP79u7fxP/zLv4bf+0P/Dh778KcSGM5BZnFcqXKAG7048/Yt8ZukCUqfGGxQk7exVWe53ZuZsskdyG6x19F7NzmTT6DFiZM1tGNNM4JJF64fmKdxHWYOtxxjFSaQDMLDtwoTTyQcruESDGrx5THcRh5HWhaqFiDcFhoB3lU8953sfdK2ns5j0T6WqavQiYNj9BjKbumjo6PZsYqPPfYYXnnlFTz11FPHVbztZMEdCWftVQ0GlTizrSOz3O598H27eMMK733/FgNHD+Cto6/hnXe+Y0Ln6O/hQw8/hjvf/Rq+c+uX8Gu/8bP44O7beOxjT+B3/tY/gQ+ffxTvvXeEm7/0V/Hu+0fJ2/kb3/0l/PBv+sIEZxEEB4SZxcizkunfCGIja7kZOB29+w28c+8teOXifbD+Pl775sv40LlH8Ht+6N/Gow9/0oDMO/gf/+Vfw+/55B9jkMkvWAUYAQ6N9NMi8dqmRcHL9EWczH9whRfRO6UMMj5+29rFv9O/JXA5lQU5vXUsNVy7jjP7rXF7otE7tsB1/AqIVjnTZ+O8Hr/p8eHyzF4LGEEmYwAlmFEIjJ+8W4excxQG1+F8KWSmbl/4Ah4prFrwSCGPdTVvcAPMASPNk9pSuxhOPzE47Ye/4YYfMRDbcgFx7RxGPyhlnNZ43AW85U8PcskFumvHWvQJwSLxGai022pHPYL3i04cHA8ODnDp0qWiy/rw8BDPPPNMNe2TTz6JJ598koW9/vrrbGmfk1bNcWFCYgUkWfsi91NY6Z18//u38c//+5/G3fe+Z5Z1XN/FvfXdabSbc3j33Tv4+X/0n+O9d+JvYXn4RvzcP/vruHfvvWRz/vxH8aO/9d/Fhx8+gPceN3/p/4Z33+NfiXnv/Tt441f+On7/j/3vpkcpgUeMxMsqx/1ZABni3rl7hGk1NH2NSMDjvXvfwz/6xn9lXgvA4/319/HaN17GR88f4POf/vHS+xjLnA7tcfT+N6dJPg89hoMPfwpuGEo7CxjDXzU+xYFDI4XAqCGDYP5bOdWaEiBm0DTzqsBkNbyyXxOz3eD8nHflOEelwlKPIu19Z+HFbRh/HwGQodtSgznWcDsE9+8owoBUQdR97vFL+SaQ5MA4woXjTN2o67gfJsiMYQLG5E1sg8f4mIj5SXhMFxJh7CD78QaypY/920Q1WJTHaAHGKWweGkfvyPbA8lnDsfwSLMqyhXGOMa9pewj2+bOD2r6EwZiPDJdgSPfrceBxwEzA/SeH3lUtdSrrOD733HN46aWXkufw6OgIt2/fZms4Hh4e4urVq3jllVdS2JUrV1g+169fx8WLF/H000+fTMFbVPEiVkESYr+ARQ0gJ9PRe/zz//6n8d7bt2aL99Vf+H/g21/7h/hdX/jT+IV/9Jfw7ju3inGNAOCGc/DjGufPfxR3776Ne/feZfF3776D13/uGj75g5/D99/5Nbzz3nfK84XHux/cwZ13voELH/00jwxfU/Gjm4Ds3W/g3fdv4yMPXcCjH/rNeOvdCGgHE6CRySQfeeix5DncXiO+f/c2/r9f+8v47Mf/AD760AV85KHH8OHzj2JwQwLYdz94C298/W9M3d1hZNRHzh/g85/5X+HDDz3KPW1LgDH8Tc/qGjQ6p0JjPm7d2xi7qVtg08u0hu0ikFT2T9NZwWDQGK8pu6wBsG7r0QMDShiNXshUs9zyz+qtg7dSg0fEmbikizqvL5jXDZxgzobH6cSGfO4hPwqING7a53DI8gFPM3rRRc28i6vF18RSDRQBHRZpOulhnOwcS7v2AwPGaD8q8EmhcZ0gkJeBg6Jjx25VBsUSSCNYUoj04C8wcih4K1Bq+/e1OjgynQo4Xr58Gbdv38YLL7yAg4MDvPHGGwwQgQkcb9y4wb5J/fTTT+OFF14AMI2JPDo6avrazLFLgN6cF5F5G0H36VdBOE86T/IC0pxZD+Dt73wN73//tgqAXB7er/Hu29/Bz/79/wvWxINYWI5rDMMKd+9aXd8ed+9+H1//1j+oHnFwA9794Db8x354akWFl/Hd9RHeePOv490PjjC4AesxNwHDsEpfmPn8j/wv8aHzP4Dv37uNt97/9aLcfxbALwD42yTsjwP4XQD+k5mrAgD3xvfwS79RLgf10LmP4pGHPo7vvvfruDe+D8AnT+c7H9zGG7/6X+Hf+B1/JgNIa5c19TBOF6oAxhQfgDHlJYFu4LbN0OjKNBrwyTiafxIF2QZAVPdFfqpI+K7brXxb8u/3Fl/WQAbDGEZBkU2WEPmwGkohkIVNKQc3NsNjTs/hcfQrtgxM6kZ2I9Y+gBvbntbCX2HEiFWYeUtnF48BlscJ/Ej8dO7Ri5ihMKabrhMHyfj6t8kXZDRPZeF5rIw5bIVFatMCjGmbwJyERw0aY96beBspJI7eFQBIAdILm7Sf7BWvY1FhoSvaerJt2XWdWZ3at6rnvIRPPfWUuszOsX6XGoC2HIAH8TqAw15OZwOi3KdQyCBRxKvd1kABj+997ztpGZ42eayFB1GzGcd7VYthOIfP/PC/iY999Dfjn/zif5nGNlKNfsSHP/z4dAFXAOLahNNSaBM0vn+bjT+Mp7wep8bk+x/cwj/4lZdCfnqZfgHAXwPw72GCxz9O9rfRB/e+j9v3dHj28HjngyMcvfMNPPYDP5LDa+MXhXeR2bcCY7DN3doi3y2hUXob8zlwaGT29LpUINQCy0X7m4i+zbH+6FCjXGk3ddPx7upo6BgMekzfFM7zv+QYyHge09c8xLkZ8Dj6VfAm2t3WiIAHsixPgMeUPq0vGACtASDHBK7LIRJAAkkgeDn9KoR7BmoUKDeVBpDaOMMcZ4MizU+DRZoX8yoKYJzydCU8sq5tvXs6lmsOGqm3kebnhU2Mo97GCRYlIErgROlV9E4f7hdh0dIGoLhP3cMbvNfc1zo1cDwzkgBIwovu42iPnIZBIYE/FRJdhsFkJ4BVg8eHH/34Amjcnbz3ODj4DB79gR/Bhz/0GN559xYkLX/44cfw6KM/kpdDTI2ox9H3vo53PzhSJ7lIWcAY9bcxQeJfA/AKgCvIENkihwGf/aE/iI88dIC1v4dxvIfR38N6vIvvfPdXcPTON6HdCIMb8M7dIxy4z6iTYDTP4rRvwGJM0wqMwb7mZeT5kDwaoJGGm9BIIVOApgmYCnCya2DsLxaDRGMbKMY5ws8AI8ikGIDB48p51kjLLmsNHke/wuDLr8lYYx6nVaBGrODCeMbsfRy9w+hcWpw6AuSKeCDTdurODl3u8VxmIBLIIBWBdQT1JE55UZiUNtRuW5WzmaXnMR/H7raeB0Vrn8JizLcVGGMelpcxxRvQeM9nz6WERupNpPtABkXN28iAMewXTz8f42SEoZqXct91Fsp4gnowwXGXN4HL3/4tuqtJmOllBGnDEiRmeIzDlaid/PvR3/QEHn7kAt77nj5e8Xjk8NBDj+CRRz8FDAN+9Ef/BH72H/8l5nV0bsCP/bY/Aaymps2PHu9/8F28/fa38L3vfxv/6vY/V72Um+pvY4LGPwXgL2MJNDp85OELeOKH/gCcK2czH3zsCbzxy3+14lG9AJybGgUGOhokAjooAnn8YrAtYDHkmbyRMQ8NGCHCtgDGqqdRQGMVErU4cQ48TFTUVsYQUGjG+bAsOqmItHchxqdXNMchEnEiTDCP8LgeB/jwNZkEmM7DO4/R5c8Lek/2nVe9j2MAw8G7YBs+ZwePAiC9x+girHqs/Mj26TeNI9TQ9QSHCD9uBPwKgxtxF2FsZtrPXdCxy3kKG3E3eUgnTWFh22VbNuYxeiI3cC+t5Y2Elq5qArEkvYTEKcwGRZo364IWsBjzpt4/6mHM6TkwxvOrAaPWPa1B41pCJPE2RmiksOgDDMa/SXFf80QSm5ocjZc/+dZviV0npQcTHFuV3vDb7VmbZXQ9s31qymCSw2MapgSe1gNwg8Nve+pp/PKNa3j/7dvw3guAbD0R0WVmnWQYwPL++2/hH/z9v4Af+Nin8f3v/zq8XDzcj/i5X/ob+MQP/l68/f1v4+23v427995pKId+3B88+B0Y/Rq33vpl1eKPY/I0/uXw979BCY+DO4+Hzj+C9z44QryKDz30Mfy+3/7v/f/bO9ffOLI7Pb/VvIiSeGk1NTdbOyM25cD22Due1sjrXc1ms5EMJ8gVG3KUXQRxEnvIT0kWWqwJ/gMZSEgm+ymBqAUWiyBAaHU2GeRLBuwBgmCUOJbIseNdbZKVWuOxdufKZkujsSRK7JMPdelzTp1Tdaq6ySZb7wM02HVudarYVfXU79QFGDJcqu95KE48h/37DuHe/Qbku8Y9FPyIavEohC6cuhTCLIp+evsfnyiLQd1ItKJykjB6aptGYZTb3y5pTBFIuR/q+jakAfFjSpZjjC6SIvgNe+q0gBe9QUMEf8McQD6ISg1a5FEettaveTRFH0O59KXSU6KPYdmW8IwC2RIDUloogb5ERu9GTpDIh2JAeluM9GDqIDr5EOEQt1kmAbSFUkBLC75rUgmoDx9/mGU/a8B0Y4lJDNt5dkE0pZnE0Dgt4pHFcP56dNGvl10Yw/kmSeNWq2CMNCZJozw0HUljmKevXDnaKLzwkCDloSMR3E3D1MDu60+voThmIdyfQjrmAIhe56b9uEJBjCKMIt6Gckzz9LbVYWtRCMQz2jDbn+HxEp7/uwu4++FN3Pnz/4v3/7h9o4c3MAhhezC4tHBDI2MYGBzG/c+0yKVXwP4Dkzj21d/Ag583sG9fEZ5XwO2NOm43buL2xk3LULnA5uan+Nmfv41CYQijB5/Gk2NfwejBZzB28Bkc2P8krv7o3+DePVXI4j0rYP/+En7xi78JALi89jrub95WyvwdqNc4/mdtGgA8bxAt8RCPth5goDCErdYmPM/D5sO7eOfP/j1e/PI/xP59xfhSeAV87cvfxo+u/SHuPdhAwRtAS/jv8X7x+W8Dg23hVEVJFUQ/vy2G+rQsilFbemQxKivJZsGQZhJGY16KMIZ9zSuNntZ3qO1aJRNqnoLL8cgUdYw2QqkMLFFHqPIIT6jRxpzyaIs+FqQtIJJIg0BG5SWBBILXCQZpfrlAIkUgg17w3fMjkY8QvmdZkkeoz4WUZTKSS0kmlTKBUALAgBSmkh8dpKc/DIa8dZIeSJ5053Haw7dNYhhL1x6fI6eZJFHuk3w9YTzNLIthu2FaWEcXQ7kNlyhjmjRutQpGaVSijLI0RpIIe7TRhiyV0L7vFfgcRwWKowXTMSZ1c7GKZfuLKU8WQ1kGvXAj9bdwQ55W3vMw+kwZo09NYf3mKjY/2/DnkyqNfm8ebd7F1Au/hff+5L/iwc8b8LwBCLGFkQOTeP4b38HIgUOAmI6eITnxRBkQwPvv/RD1a28Yb6bxCoM4OvVX8ezRX0N4aG2/qxp44Wv/GD/+8R/g3j1fyLZaj6JH77QFrYSvfeXbEEMD8ATw4le/ix+s/Z4ydPw8VEl8I5h+Pvj+l6b+Bj7/9Nfx/kfv4P/ceAPh3iuMkt6738A7f/rv8I3KP4vmL+8fRw4ewi+99M9x+9P3cO9eA/v3lzAx/hy8AfVsPDYsbU0LvtgkUS7vqW1YI4tRWa0tiwzahFGul0cYTfM1CWS0jMZy5h11pt23UR6lGSsbuL8lqidrbXmMLNC8dUeboSeJoResKy+aFqkCKYJtQx7CLkgCKF8D6UtfIRBDSRg9AYhCUF5PRxSFjIRU+LJmkkkAVqEE/MhmiCyaelpUXr7uBtkfUWTCdJ1kTCJjj+fxjHm6HPpt2QXRnK4OQStphsiinK7f0CLLYjstvzAmRRqV760EabRFG/XvGsZhasMZ966L7old2Kce8/iJY54fQGh3cjOeJeqopKnfTVFG9zQt+hjmeXGBBIDWo83si1kYwKPWA3ztr/0uPl1/F/c//QT7Dx7G2ORRf+4ilC2vfZeZAPaPPxnlxRAC44fLEEMDUd/kYOa+gyWc+OWzuN38Ke79fB37D0xiYuwXcOfOe7h3bx37RyYxMfGcf+1hsHj7B0v4pa//Nt555/fxYPMOCt4A/oXh5pk3gs+B/U/g80d+GZ7n4cDYE/C8Qux6xfCd3M3P3kMxGHqOryBgYnIKE5iKklpyOZMYAqocRmXtkuint39gsWsWo+9yea1Niwjao5JaX5KEEeb8xDQkfE/CIKVZ8ESw1ZjqShLZ3nqT5VF4iJ6m5AVSKD1dKRZ93BKwCmR47ZkukABi10ACgByF9Kd1ifSjjo/CssG1LTaR9J/z2J5flA71bTS6OMrf5eigUkcSxCSRlOedB9P7ns2P6bGIovQjtF3/mCaIcvu6DLrk2WSxPa0+PidNGAFkksZWq6Be0yg6kEYdPY0C1hc8fuKYFV0aZbszIDyoz1zUvofCKYK2wusW4cGPaniWaKKy4QpVFLU6n314E1sP72deVNHawsj4ExCDBYw9WcbYk+VoXuHOJjw2hPtMTwiMPXkUIwdLuGcY4h45WMLYpC9ikVsOSO0IfwHGn5jChGgL2fjkFMYDQRPa+hbwMDJ2GN94eQG3b7eFc9/wOP73j/8A9+9tRI8n2r+/hF988Z9ADPuxjc8ebFjfye0VBvDZ5gbGB8vqejFJh/aOapMUxtO1v1BFELBLotKWImDmYWj5u0k2Y20Z6xn6YZFDUz3j/AzzjH8X5uhkJ0RnXPIGrX53kccw13a6F96d7W/v7TfI2AQyrCkLJAAlCrklEEUVdYmUI5FRuhaNDEXSzw+GtoOHeLeFUc33y6hSKeebxFJPt5XR83SSnumY9paZlraxxq9tjAuhXlYtY5bDWJ5BEsMyep4ePYzKGWQRQCy6GKWJeIQR0vfMUcY80qgT5mlpidFGiV0b2dut/eoRFEeZ6Fgg4j9+z3coT55GPOqomKGH6LpEoP09kkYh5Qs1X/HTsD2TQKKdF+bfv5v0XEf5gCdtDV4B+0YncfCpo/4+IcjyhCd9DyVOtKeDI/yXXn4V196+GB/i/pXvQAz7hx45SumvZmlJhdQbAWCgvf49gfh2KwnnuBQBfOlXfwd3mj/Fvc/8aOl40Y9WhrMeGbc/uki0tjAydhitofjBySiPeppJCPX0QkJZgyCq0545L00U5e96PZP0QWonRQyN6dr8rH1Ok8ZuiqMj/jbuJo++JEKLPobpqkACiA1hA1AkciuQRy8ouxX8DSOUUVQRfl6UjkASbUPRgFIOiAtjWB7B8xijNEUa7XIZL5ssiqbrGJNkUkeXvpC0m2T86bgMAtojeyxRSV0M5bJJgqj+VW9wCfN0UTSmSxIY5usP9HYVRr/NnNIYIkukMQ/qtAnL/zK13g6ya4W2Rzxe4pjxny88yw9Gcy7JfZS4RVgmdMl2Gf+L5piRnOoiGEmVSSDDRqXI4HDRLkdeoeC/FWZwCK2tR4BoAZ4fwfvCN+cgBguS1AUH0nA5JJlUp4HhiRJe+Ou/i08/eRcP7n6CkdHDGCsd9YeYw/oD7XXihQ8Cl9YTAPVBqyKWLb2j27azCWTycFsmhVR87PBRjBwoxV+1GEZHDwfibBqqNsw2FgCxyaOUp0ff4mmemmaTrygvQRRN9V1kUa7nIptJwmhoyyiNBpQy0Mp78pkc/O0CCH5X7V+N9HyCoICcr38HEiOPQWlPhGIYbPVCFUhAFchQDOVrIAGkSqR893Mok0kiGZb1/xaUoW8/LR4d1KVSLi/nt+vHH6GTXL6N6bE73R6qBuKP6tGveYzJZAaBlMvqUqimqTfV2ERSF8XwrxxBtMliVF8TQpMwQpu2CaNfDsnSKIuiLohQpzu6tpHCtit5vMQxL5LdGaOOQpuW5TEgkkPDd0UIw3QpLRJIxMUSiEvkgc9NYXi8hAfNj7XlKGB4fBL7xg/jznvX8Lmv/y38xQ//C0rTx/Hcr/59VfKC9qIhcKgyGeZFyyAADBQw9nQZYyi3ZVdI274cqTRJo0D4WDfjDkORTR3nHYyHL5/8Lq79j9/HfT06erIdHQUyyKNeLCnf+HgeQ1mDICp90mVOK5skivHvBlmUv2fJs/bb0helTWFOTyHaVhzLq5XCTqpiqctjtKF7iKKPIhBBPz0egQQgXQMpyWEwfw9IlUi5zpZo71N0kVTSBKwyCQzEhBFIFku9vq2unq63121plDFf6xhPs0US9TZsQ9qmYWxXkZSvUTSVlWUwSrPk629+iT/I2/6IHVkYo3RAkkP1eGIcnjZJo1wn+OvpaVnYTdLIu6oVKI42gmGp8LggIxAc/0OZBNoRRk0eIdWPynltAQzrRQdMWRSlcurGKP2ODXkoFDD1t+fx//7Dv0JrM3i1YGEA+8YnUf6bc7i//j7uvHcN9+98BAAYGNkPDIZnqO3FhzYdHUChllGjiEgo46lptrJRnpqgnLkmobejVRueKOGF8AagMDo6eVQZ0rbOyiCT2cTRJd0ghxmmrRFKB1HUy2YWSW15kuRSiRzKZfV2vPi/NBMC8ahjNENNHqWNNJLHQBqj6GOwA/BFry2Q/jC132z0LzRIJBAKph9R9Lz26VA4NO2XEdGltLIAyhFJeXF0IYxHIM2y58npDt/1+knD0nGR7K482iKOpqHs+JC1Pm0ewnaRSPkRNUkiKQz1bZKo12tF++R4ZFFON0UX29MApPq6MEbzloUxKBOTxKzSGPvbXhfxfT92FRyqVqE4uiKJYnR8McljQCiP/ncvdqyKTYdneppAhuKZJIpCSg+OcRg6VMLEF17Axp/8AABQ/MKL+IXTvwkPHgbHihg6OIHbN38CAHj08F480qf9lYVQl8owzSSWcZGUXjBoKqvkefZ8E2kFPHVi9OkyRlGOqio+axVHy6xT5dFLyIunWyVMLucgkvG31khlLHKXK9/UV5ucKmXM0qjUR7yuE7ITuqRFG1t7WgQbVCiQYb9iAglpH2CIQgI2iVTTwgO5TSS34Bll0jgttQHDdxdhBOJiF683oE3DPm3YSHXxzIrtPdcmqUyXx3QZ1MtZ65iijoY2TJLoT7fbjJWRyplk0f+u5mURxrC+McoYfZem5YVTdqQJeQG7XRpJHIqjTihtElHUUZNHpXwoj5JBtouYo4/KtCyQWr4cGEmSyCg/nA4PJMP78Nlf3IAYCDo3UEDp+W/gwx++CQDYengfreBmFH04GpA2bKlvprR0aQzkUktX5mHIk/tlxXVn4yge1mFqSxtG0bQJoiHfFn1MlTNlOkES9elE2dT6YUhL7Y9TmkgdUjdFG61SrxeSf1QCiG5wCab9bddrF5AXRpmrXSCjjSFsS/p5y+9lj7okSSSkyKOe5k+bRbIFWGUSQEwgbWny0pryYmVN0cKcwpk0nzzYbpbRH1adJpN6O7H6SWUt5Uwyqaap5UySaMo3vulFyzcNR7fzpPKKXLbLGaOMUbpdGj29rPxX6seegTKrQHFMIrI2OQ1tUQyOF7o8hkkhImgrEqfwmCZJYWxoOpRGaA1KG2FMzoQqdeHDrYtfPoHGj97GJz9+GwP7RjA8cRjjXzkRieP9jY9w98M6Djwz5V/MnyqFCUPSUj/0dKGVkUk/64y/mWc7SN2fWfJdxLEbImmTQ6WORRhdIpSpZWBIzzxfkVzGsGzxdWn/McQ2W+lkTnmuo5QebYhRmtfemKQ0Idoz8LxgWSRhjPolPy8zyvIP3p60/G1ZDEUwTBdSels4W9G0iK0WPfKofzfJpV5XxqmMNu0yNN0tgbTJYogufaY6SfJnzE+rbxBCU54uh/K8TeXiUmgRRQCmyKKaL81DaPkuwii1qaZJJ0uO0rhXoo0cqlahOJoIDypAdJBQAhiaPALtHTuASAj13ZZfRQTfJYFE+7hlksqwG4C0Xcl9NJURQDgofKD8RTR+9DY++O9vwBscAra2MDhahDc4BPHoITabH+PmH/1bDE1M4uhvzGF4rKS0p84Yxp2GMJRLGpbWV4ycZNuZOG+7JnvPQko96/HKkO4WiTScnBi+J0b55LIJeZllMmd9kyzmqm9Iy4Qihwi2ryR5jOaqzVQSyGDjDp8m1b5kRZJI+QxOv2Y1mFdUzAtHJGRJTJNJT23aa9+BrYijtCQuEURzVDGWZCybNUKplDXPwgnbfsEkli4yaS6T3E6qUDrUlU+s9eiinG8SxTC9vb9NkcWgjN5GXmEE+lcaARH/ATzmUByB2KiWUzn5oCMdU2DYrhSnlA4qsQhk2JZJGMMN2muny7KJdrPRRPh2lI/+2xtRI+Kh/0aZh3fWpU4JCLGFzeYnePc/LeHYP1rwr7tKEjgtzySZ4bC0LRopl/XLCT0pdWeS5Uww0+hIqjzajqbu7aVJZVJEMlEc5XSDdKVKoinPQUptspi1P3qkLrWvMroIymF7aXuJ5NEwD2UDjHUA7TYDidT771nXXYJIQjrwhpKdIJNyM/53YfneLrOl5ZnKa0trxCWK2ImA5sEkeyGmY36a+Pn17PKXVC/etvu8zfIoF1aFMkkUlbbTZFErkyiMhjr9K43EBMXRhnzskMa+0uQRUHfWkJuBIT0USC9s3CKR6jEltoNQuhmUD18D+PB2w22ZRQsPb6/j5x/cxIEj5XRBlPKFKV/LS2vLtBNOO6Y4PyUhizTCQVAS8rNEJG3pSdJok8VEGbP1y0EEbe2Z6wqnPiaKp6me0meRnA9lk20jbVeRPCoSKLUpHwiV4WpE26lJIuVRiDSRFEBbBL1wWtoOwiFxaZ0okqUIonRQjkmctm6ShvkT8/y/+hNiO5XR7bzGEcgvfH5a/rqu9U1iqJdTT6bNkqjUEbayCbKYlK53JE0YY99zSuNuEEqB3dGPXQTF0RVNHsMkkw2mCaRdDuMSGc0HUlmpsaRrCKP3MRcGAMMr9owUBvDg9ifY/1xZ67S+EObpjmVTqy8s6V3BVSZTyuWVzEyCmSSAaXJoK5NBOs35Ip7mUi+pTEJ+poixPFOTHEry6M/X8OOySWSsfSlPOalMFkllmWIy2S4opDpCPnMV0tMawmbCYe9oGUxSl74i06KA1oB7hmsabSLaKbaTSbvc5RfGpPn5mY6CmlDPdm14TBKlelZRlL9nlUXpu/H5jEZ5VNvac9IYwGscVSiOScin+oCyww7/GKOPgFkgpfa0Y4lRIsNZGkUyOpBI/dODEcHrLGxvkTHS2sLQ5GGzPCC+LRs3KINMpsqh6bjturHayuURDTgKSk5ZdJqHIS+LnFoFzbVciiRmrptSDtD+hUnSmGEPrm47mjxq83MSSLkj8o86atdrl7eJpL4swYRRJqV5K0IJT0mX6ytSYgy7Zjhfcl3XSrn48ri06eCyVlIfuJBF+DLIJeDgNkmRUJd9p1zfImTGiGWSKCppCf00iGCiMCb00eU4kZpOdg0UxwBFAmX0U3rAPfoYVpU3PE0iI1EM0pR25P2+cvGL1nGpW3IRIVqAV8BQcRIP1z8yd07GK2Do0CRGnp0y7+9MZ+Fw2ylY3S5NKJPKdkCm6JVD2VzRsAzzShpmtk3nE0hHQUxqw6FvgOE34SqglvaUhvV8XR7lcsr2Jx2Q5bM8U99MB2JFFr14HUt+0nqOpDDaQcTLKrsn5WxWw8tyXFbrp8pdxhtfunFto4mk6x2tc8wVTey8P9Z2koaz9fw0cXMQu1i+SRYT27K3u1ejjAq7/M0x1WoVjYZ/SdqNGzcwPz+PcrnsXK/ZbGJ9fR1nzpxBpVJJrUdxdEWPVBiij3Jy7OAUTiZIZNSOLpKmMlHbWmRSQrRa8AYH8NTf+y3cWvo9wPPgDQ1BbG1haLwIAHh4pwmvMADR2sLwoUl8/h/MR2+RieZhQQ64qDM2FLZEFGP7roT59WTTdRTCbotoUrmOJRJQ9uZZpS+PJAKW/18m+c3+C1B+Y7I8hvMyfQ+mjRIJ2EVS77BLVFLuaPRdkwZlMi6P8UtitKhjpxj8w1bQJINCaiNevpOOxUk9vlvyrXLnsvpynDVmHd6O9aMTkUxqO/juJIsp7fdTlHE3D1XXajWsrKzgwoULAIBms4lTp05hdXU1sV61WkW5XMbMzEyUNjs7i4sXL6JYLCbWpThKWKOOIbboY1gZ6rYTi0K6SGQ4H4tIyrM0RialeQnRgucV8Oiz2wCA4q/8GvY9+RSGJg9j5NkpAMD9927i4fonGCo9gZFn/ec4mlaBab0I60RSwXZ7TsKZ1nZetkP0kOsY4j4PV5E0Hbw7lUOHOlFdc3JC6MnQRtIy2doxRRNhkUe5owZp1BfC02aaKJJyH9OiktH8EoTSVlZu1vr70Xca24MSFY1lWuadKfqZkaxihhwyl4UsC2rdD8bOEOzTSf21iKBVFhPqmOaVSRjT8nYLu7iPCwsLOHfuXDRdLBZRLpdRrVYVKdS5cOECVlZWlLQzZ86gVqsl1gMojjFS5RFIFsiwESBZIvX5au3ZRFJpVxdIuRseANECCgU8uPUeAGDsxePY98znlPmOTJUxMtW+EcZ4jRfi203qOrLsuDJFKZPSu8U2CWRIx0PYCSva2raL9Nnqb5ccOuab+5RjHRiaUORRbjdFGl1E0j95yyGT8vwdJNEu3647rS6TFo30LPPeiRCOqzxlyXNtvxOy7AuzDoPrv+MuyaLflsP8XfOIE81mE2tra7Fh6XK5jOXl5UQBLBaLmJ+fjyKVAHDlyhXMz8+nzpfiaMBJHoF4NDFK1yoLL77/T4tGxto07H4NBzRlPxCI472f/RTe0DCGnn4K+mtdDde1p2OKcBoLGVPt6zah0W4cZzLv5zPOdFuOI92MRNrKdlMOuxmdNa3/LOtY26Zil0bEri9BXNz0tAQ6kkm5P8a+WM64bDLaCxJ/F5aOd7vbOU9onepmLdcNsvxfHcTNS/qN6dOOoppZGF3ydxEegNRX3vaI8LrGUqmkpE9OTqJWqyXWXVxcxPHjx3H16lVcvHgRV69exfT0tNO1kRRHC6ZjSiI2idQbcY1GGtKMv12TUIa0WvA84MGtn2HfkSPwBgdiRZz2S7aDVQKuNwu5ZaQIZwrZhTHHTHbguJ0uWtnzMsuh43J25DEJQ5uZMcgjYBFIfd6W7c2aZyyeQyZhSMt6DZ7rxtJN4UyaZ8Z3v+fCZZG3czh6J8gQjYxJoqlc2jTgLou2+lnydyutXnfATLPZzJUHAJVKBaurqzh16hSOHz+Oubk5JfqYBMUxBWOkMA2TBNoacIlGphCLTobprRa27t4FAOx79jn1+OjefPYoD1L2wTYvSFm3uU/6Mh4PtvU6xW6ScZTKuW6e4eSsZD0LyBANdzkJMwqkMQHpMhn2r1syGc6nkxOFTv5JebYz07C6a5vdGrbuxg9zt4pNkpNnOalwTuuiLLqW6XPu3r2LI0eORNNnz57F2bNnO2ozjDjmodlsYnl5GTdv3sT3v/99zM/Po16vx657NNEzcez09vGs9bpF2nHFiKtIGqKRSjHbftGSJ1rt06SRZ5+ND4Xb+tQJpr4nJcQX396fborZTkQhtwHnf1MH0uF8/N2pWw27se4t24hh8zPUtWQkCaUtMmkSTM988LddbxybZ971081/X9btNWmIvpskRhjdmrCKmcvsu7SNpPYhq9R1KotJbWctswfoxlD16Ogobt26Zc2vVqvOEb9Lly6hWCxGQ9SNRkO5E3p9fT31zuhXX30Vly5dAgDMzc3hlVdewalTp2LXPZroiTjmvX08b73tJrNM2gTJEI10mof1gNcWx33PPWcu1+nBxwFbRDScr3HWaRKZlaxRxy7Msqtsw/C50/Gwl8+h6HbkMyWKl7D5uXWgWyIZpKfJQiQlOf5FuWVI2V+5lTXKU5Z2spKyPpyWvUs/+/b7x7vQWCeiZk03d6yj6GKWcnsBgR1ZnpmZmdS7mXXCoJk+LN1sNhMDamtra7HrIovFIt566y2cOnUqdb6F1BLbwMLCAmZnZ6Np+fbx7ajXC4Snfqx40ieWJ9RPyjxin+AsaWBiAoMTE+nz385PwZ4nvPa2afx0MF/h0r42r07mpyyv6ZO3vTz/LyT/PtptCvtHZ6d+L3L/stKFKBOQbbX4bdtWMOI/tKzphjKe8HJ/3DeI4NMKPqY0PV37eK2U/rRy9Mc2n27MK2V5Mn/S/p9Z2kn7fdjylbrm32ji79vUjq1Mhm2MdEaxWESlUokNWdfrdZw5cyaxnmmYO3SqNHZcHNNuH+92vd1CxxIJZDiCBWz5Ecfw+sZefYzL5ypE4frL+bGuXxdZ2Q7p2SaZSl33Sh8cf0PdlLndRBcObJlF0tQHFyEwttuFT9Y208grTgGdSHAkw659cS3jsl526v+VdT7GfPNvMfk3nNCeXq6fEaLzzzaxuLioDC03m000Gg0lelmv15WgW7lcjpxK5vz581hcXEyd544PVee9fbyT2853G9HoRdJvKdy+035vlvE1IQRamw8AAAOjoxBCwOvmaxpizzaxoxdLfASQvrzbLSs52ndc7N2D63DzXluuTghXSZeW2XqzTTS/hI0+qS/bsT24HsPyHuuybNMu+0CdPP1Kq9Ot47qtne3atpykzj5zXsPoxm5+c8zMzAwajQbOnz+PYrGI1dXV6NrFkHq9jlqthmazGV37uLKygoWFBSwvL2NycnJ3v3Iw7+3jndx2vlsRnsMP0lUgo/ICDxsNfLh0EVvBevn0f/0A96//GZ6aexVDmnh3RFLnE3ZWieLselDphAw78T0niSFZ9nR7dRm7gUBXl99JIG3/G5e+JJ10udTpZlmXNpJkOMuydtqPbrUv/2OzbGN5/m+u7SWWozR2hV36HMeQubm5xPzTp09jY2Mjli6/cSYLPYs4bne9119/Ha+//no0PQrg5m//Tq557yWEEPjSl74EIf9IWi2IjQ2M/sc/wrVr17obeSSEEEK2kSP/8l/3ugtEYsevcZRvH5dJu308a72zZ8/i1q1b0Wd0dLSzju8RLl++jHfffRePHj1S0h89eoR6vY7Lly/3qGeEEELI3sNrdf7pJ3ZcHPPePp633uPG9evXMTQ0ZMwbHh7G9evXd7hHhBBCyB5mF98c0wt2XBw7uX08T73HjWPHjmFzc9OYt7m5iWPHju1wjwghhBDSL/TkOY55bh93rfe4c/LkSUxNTWFwUL18dXBwEOVyGSdPnuxRzwghhJA9yHY9QmmP0pM3x+S9fdyl3uOO53l488038a1vfQs3b97E8PAwNjc3US6X8eabb/LGGEIIISQD3XjlYD/hCfF4rJEjR44kviey3xBC4PLly7h+/TqOHTuGkydPUhoJIYTsOXp5/B4ZnsBfrnT+RJZrt5b6xkF6EnEk24/neXj55Zfx8ssv97orhBBCCOkTKI6EEEIIITb67HE6nUJxJIQQQggxIniNo0ZP7qomhBBCCCF7D0YcCSGEEEJsMOKoQHEkhBBCCLFBcVTgUDUhhBBCCHHisYk4fvDBBzhy5Eivu7EnuXv3LkZHR3vdjT0J111+uO7yw3WXH667/GzXuvv444+73mYmeFe1wmMjjk8//XTfPHxzp3ncHp7eTbju8sN1lx+uu/xw3eWnX9cd76pWeWzEkRBCCCEkMxRHBV7jSAghhBBCnHhsIo5nz57tdRf2LFx3+eG6yw/XXX647vLDdZefvlx3Aow4anhCcI0QQgghhOiMDI3jr3zxn3bczh9v/GHfXP/JoWpCCCGEEOLEYzNUTQghhBCSGT6OR4ERR2KlXq/j+PHjve4GISQHS0tLqFarve7GnqLZbPa6C2QX4gnR8aef6PuIY7VaRaPRAADcuHED8/PzKJfLPe7V7mZtbQ3Ly8vRd5KdpaUlNJtN3LhxA/V6HRcuXODvzpGlpSUA/kH8ypUrWFxcRKVS6XGv9hb1eh0LCwu4ePFir7uy61lbW1NOkIvFIhYXF/G9732vh73aW4TbLOBvt3237vpM/Dqlr8WxVqthZWUFFy5cAOD/oE+dOoXV1dUe92x3U6lUUKlUUK/Xcf78+V53Z89x/vx5zM3NoVgsAvBPXqanp7GxsRGlETMLCws4ceIEZmZmAPjb8PHjx3Hjxg2KdwZqtRpKpVKvu7FnWFlZQalUQrFY5O8sI7Ozs5ifn8fp06cBAIcOHUKxWMTc3FyPe0a2i74eql5YWMDs7Gw0He4UOHxDtpPl5eUoyg0AMzMzKBaLeO2113rYq71Bs9nEyspKNP3SSy8BYOQ7C9VqFa+88gpPUjJQKpVQqVQojRmpVqtoNpuRNALAW2+91WfSKIBWFz59RN+KY7PZxNraWmxHUC6Xo2FYQraDer0eE51yuUz5ceDChQvRCAEAXL16FQA4VO1IeI0epZHsBHpwBujTbVWIzj99RN8OVYcRH324ZnJyErVarRddIo8JGxsbsbR6va6clRM3zp07h3PnzjES5MjS0lL/XV+2A9RqNVy9ehWlUglXrlzhtfCO1Ot1lEql6BpH3kfweNC34ph0dxzvnCM7ydraGprNJhYXF3vdlT1DEInzrAAABM9JREFUtVrF8vIyKpUKRciRarXaZ0OEO0N4CVN4Xe3p06cxNTVlPAEkbcIRlCtXruDcuXNR+vT0NFZXV/sn6s03x8To26Fq+RozQnrJ7OwsVlZW+mdHugPMzMzg0qVLmJ6exvHjx3mylwKHqPMjSyPQFkneGOjGiRMnlOlKpYKFhYUe9Wab4FC1Qt9GHMMh6kajoexM19fXuXMlO8b8/DwuXLjAYeqczM3NYWFhAQsLC8q1j0SlVqvhypUrqNfrUVq9Xsfy8jLq9TqjthkJh6yJnXA4Wh+WLpVK0bXJpD/pW3EMf8x6pKLZbPL6C7IjLC0tYXZ2ltKYgdnZ2dg1jeVymdclpzAzM6NEzQDgtddew5kzZ2LpROXQoUO4dOkSt9OMhAGYer3enzfEyPTZXdGd0rdD1cViEZVKJTZkXa/XcebMmR71am/CYcLsVKtVlMtl5WAkPySXxFlbW0O1WlWiZsBjcmAiPeOll16KHvsUcvXqVXzzm9/sUY/2DqdPn45tr41GI7Y+9zyi1fmnj+hbcQSAxcVFZXir2Wyi0WjwDDyF8K0T8/PzAPwo0MLCAgXSkbW1tehZhLVaDbVaLXqTDLET3ggjyzZvLMpOrVbD/Pw8ms1mNMxP7OiPkwlP+nijUTrnzp1THm/XbDZRq9WUm2X6Al7jqOAJ0WdLpBEesIvFIlZXV7GwsMCharJtNJtNTE1NGSXx0qVLPGlJodlsYmlpCevr65icnOQrB8mOEN4Is76+jmazyetpM1Cr1aIb2W7cuNF3x9iRwTH8+pHvdtzOTx5dwq1bt7rQo97T9+JICCGEEJKHkcEx/PrnvtNxOz9pVftGHPv25hhCCCGEkM7ov6HmTunraxwJIYQQQkj3YMSREEIIIcQE3xwTg+JICCGEEGKjG+Lodd7EboHiSAghhBBio9WF5zAOdN7EboHXOBJCCCGEECcYcSSEEEIIscFrHBUojoQQQgghNiiOChyqJoQQQgghTjDiSAghhBBio8WIowwjjoSQPcv8/DwOHTqE48ePK+8Hr9frqNfrvesYIaRvEKLV8aefoDgSQvYks7OzmJ6exltvvYUzZ87g1VdfjfJqtRrK5XIPe0cIIf0Jh6oJIXuOarWKxcVFVCoVAEClUsH58+ejqGOpVOph7wghfYMQHKrWoDgSQvYclUolFlGcm5tDrVZDo9HA3Nxcj3pGCOk7eFe1AsWRELLnMA1DF4tFNBoNRhsJId2lG2+O6SN4jSMhpG9YXV2Nhq8JIYR0H0YcCSF9Q6PR4E0xhJDuwqFqBYojIaRvOHHiRK+7QAjpMwSHqhU4VE0I6Qvq9TqjjYQQss0w4kgI6QvW1tZ4fSMhpPtwqFqBEUdCSF9w5coVRhwJId1FwH+OY6efPoIRR0JIXzA9Pd3rLhBC+g4B9NkrAzuFEUdCSF/Ah34TQsj2w4gjIYQQQogF0WdDzZ1CcSSEEEIIscGhagUOVRNCCCGEECcYcSSEEEIIscChahWKIyGEEEKIDQ5VK1AcCSGEEEIMfPWl5/Gn7//Pjtt55plnutCb3YEnBB+JTgghhBBC0uHNMYQQQgghxAmKIyGEEEIIcYLiSAghhBBCnKA4EkIIIYQQJyiOhBBCCCHECYojIYQQQghx4v8DC4urlpBFtb4AAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "version=1\n", - "it=0\n", - "gamma={}\n", - "beta={}\n", - "values={}\n", - "out=opt.minimize(getval, x0=(.7,1), method='Nelder-Mead',\\\n", - " args=(backend_sim,1,version,None),\\\n", - " options={'xatol': 1e-2, 'fatol': 1e-2, 'disp': True})\n", - "print(out.x)\n", - "f = pl.figure(figsize=(10, 6), dpi= 80, facecolor='w', edgecolor='k');\n", - "pl.plot(list(values.values()),'x-')\n", - "\n", - "f = pl.figure(figsize=(10, 6), dpi= 80, facecolor='w', edgecolor='k');\n", - "pl.imshow(-np.array(Elandscape_v1).reshape(n,m),interpolation='bicubic',origin='lower',extent=[0,gamma_max,0,beta_max])\n", - "pl.colorbar()\n", - "pl.xlabel(r'$\\gamma$')\n", - "pl.ylabel(r'$\\beta$')\n", - "pl.plot(list(gamma.values()),list(beta.values()),'ko-')\n", - "pl.plot(out.x[0],out.x[1],'xr')\n", - "\n", - "j = execute(createCircuit_MaxCut(out.x,G,1,k_cuts,version), backend_sim, shots=1024*2*2*2)\n", - "plot_histogram(j.result().get_counts())" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "jupytext": { - "formats": "ipynb,auto:light" - }, - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.3" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Bowtie MaxCut.ipynb b/Bowtie MaxCut.ipynb deleted file mode 100644 index dedfb85..0000000 --- a/Bowtie MaxCut.ipynb +++ /dev/null @@ -1,336 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from qiskit import *\n", - "import numpy as np\n", - "import pylab as pl\n", - "import networkx as nx\n", - "from qiskit.visualization import *\n", - "from qaoa import *\n", - "\n", - "from matplotlib import rc\n", - "font = {'size' : 16}\n", - "rc('font', **font);\n", - "rc('text', usetex=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "V = np.arange(0,5,1)\n", - "E = [(0,1,1.0),(0,2,1.0),(1,2,1.0),(3,2,1.0),(3,4,1.0),(4,2,1.0)] \n", - "\n", - "G = nx.Graph()\n", - "G.add_nodes_from(V)\n", - "G.add_weighted_edges_from(E)\n", - "\n", - "pos = nx.spring_layout(G)\n", - "nx.draw_networkx(G,pos=pos)\n", - "k_cuts=2" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "depth=1\n", - "createCircuit_MaxCut(np.array((np.pi,np.pi)),G,depth,k_cuts,1,True,\"depth1\").draw(output='mpl')" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- " '11001': 4.0,\n", - " '11010': 4.0,\n", - " '11011': 4.0}" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "costs=listSortedCosts_MaxCut(G,2)\n", - "costs" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "Aer.backends()\n", - "backend_sim = Aer.get_backend('qasm_simulator')" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0, 0.5, '$\\\\beta$')" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "n=12\n", - "m=24\n", - "beta_max=np.pi\n", - "gamma_max=2*np.pi\n", - "\n", - "circuits=[]\n", - "for beta in np.linspace(0,beta_max,n):\n", - " for gamma in np.linspace(0,gamma_max,m):\n", - " circuits.append(createCircuit_MaxCut(np.array((gamma,beta)),G,1,2,1))\n", - "job_sim = execute(circuits, backend_sim, shots=1024*2*2*2)\n", - "Elandscape_v1,_,_ = measurementStatistics_MaxCut(job_sim.result().results, options={'G' : G, 'k_cuts' : k_cuts})\n", - "f = pl.figure(figsize=(10, 6), dpi= 80, facecolor='w', edgecolor='k');\n", - "pl.imshow(-np.array(Elandscape_v1).reshape(n,m),interpolation='bicubic',origin='lower',extent=[0,gamma_max,0,beta_max])\n", - "pl.colorbar(orientation=\"horizontal\", pad=0.2)\n", - "pl.xlabel(r'$\\gamma$')\n", - "pl.ylabel(r'$\\beta$')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "from scipy import optimize as opt" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "def getval(x, backend, depth=1, version=1, noisemodel=None):\n", - " j = execute(createCircuit_MaxCut(x,G,depth,k_cuts,version), backend, noise_model=noisemodel, shots=1024*2*2*2)\n", - " val,_,_=measurementStatistics_MaxCut(j.result().results, options={'G' : G, 'k_cuts' : k_cuts})\n", - " global it, values, gamma, beta\n", - " #print(x)\n", - " it+=1\n", - " gamma[str(it)] = x[0]\n", - " beta[str(it)] = x[1]\n", - " values[str(it)] = val\n", - " return -val[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: -3.869385\n", - " Iterations: 18\n", - " Function evaluations: 36\n", - "[0.76350676 0.3064146 ]\n" - ] - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "version=1\n", - "it=0\n", - "gamma={}\n", - "beta={}\n", - "values={}\n", - "out=opt.minimize(getval, x0=(.7,1), method='Nelder-Mead',\\\n", - " args=(backend_sim,1,version,None),\\\n", - " options={'xatol': 1e-2, 'fatol': 1e-2, 'disp': True})\n", - "print(out.x)\n", - "f = pl.figure(figsize=(10, 6), dpi= 80, facecolor='w', edgecolor='k');\n", - "pl.plot(list(values.values()),'x-')\n", - "\n", - "f = pl.figure(figsize=(10, 6), dpi= 80, facecolor='w', edgecolor='k');\n", - "pl.imshow(-np.array(Elandscape_v1).reshape(n,m),interpolation='bicubic',origin='lower',extent=[0,gamma_max,0,beta_max])\n", - "pl.colorbar()\n", - "pl.xlabel(r'$\\gamma$')\n", - "pl.ylabel(r'$\\beta$')\n", - "pl.plot(list(gamma.values()),list(beta.values()),'ko-')\n", - "pl.plot(out.x[0],out.x[1],'xr')\n", - "\n", - "j = execute(createCircuit_MaxCut(out.x,G,1,k_cuts,version), backend_sim, shots=1024*2*2*2)\n", - "plot_histogram(j.result().get_counts())" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "jupytext": { - "formats": "ipynb,auto:light" - }, - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.3" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Depth scaling and heuristics.ipynb b/Depth scaling and heuristics.ipynb deleted file mode 100644 index 842c68e..0000000 --- a/Depth scaling and heuristics.ipynb +++ /dev/null @@ -1,250 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from qaoa import *\n", - "from plotting_functions_QAOA import*\n", - "import networkx as nx\n", - "from qiskit import Aer\n", - "\n", - "# Global Variables\n", - "NUM_SHOTS = 8192\n", - "weighted=False\n", - "backend = Aer.get_backend(\"qasm_simulator\")\n", - "\n", - "\n", - "# Updating figure params\n", - "newparams = {'figure.figsize': (10, 7), 'axes.grid': False,\n", - " 'lines.markersize': 10, 'lines.linewidth': 2,\n", - " 'font.size': 15, 'mathtext.fontset': 'stix',\n", - " 'font.family': 'STIXGeneral', 'figure.dpi': 200}\n", - "plt.rcParams.update(newparams)\n", - "\n", - "\n", - "%load_ext autoreload\n", - "%autoreload 2" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Importing the regular graph\n", - "\n", - "The graph can either be unweighted (all weights equal to one), or weighted (each weight is drawn from a uniform distribution in the interval [0,1]).\n", - "\n", - "NB! ALL of the cells should be ran again on a slightly more beefy computer.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{(1, 2): Text(0.4058672267773923, -0.4911281098680106, '1.0'),\n", - " (1, 0): Text(0.21573208213394152, 0.3489020811564408, '1.0'),\n", - " (1, 3): Text(0.646880867780462, 0.44734294874130476, '1.0'),\n", - " (2, 5): Text(-0.4319396056915979, -0.6995110593022428, '1.0'),\n", - " (2, 4): Text(-0.024806117445413056, -0.5878620804635135, '1.0'),\n", - " (0, 5): Text(-0.6220747503350487, 0.14051913172220862, '1.0'),\n", - " (0, 3): Text(0.10924671322748036, 0.7785012496337669, '1.0'),\n", - " (3, 4): Text(0.21620752355765677, 0.35060897814580183, '1.0'),\n", - " (4, 5): Text(-0.5151139400048723, -0.28737313976575635, '1.0')}" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "d = 3 # 3 regular graph\n", - "n = 6 # # nodes\n", - "decimals = 0\n", - "G = nx.random_regular_graph(d,n) # d*n must be even\n", - "\n", - "addWeights_MaxCut(G,decimals=decimals)\n", - "\n", - "plt.figure(figsize=(10,6))\n", - "pos = nx.spring_layout(G)\n", - "labels = nx.get_edge_attributes(G,'weight')\n", - "nx.draw_networkx(G,pos)\n", - "nx.draw_networkx_edge_labels(G,pos,edge_labels=labels)\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Let us first see how the error scales with increasing the number of layers $p$. $r$ is the approximation ratio defined as the ratio of the respective cost functions for the MaxCut configuration found by the QAOA, and the actual MaxCut configuration found by brute forcing the problem.\n", - "\n", - "In this case we only use 3 random initializations for each $p$, and choose the best parameters. " - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.0 %\r", - "100%\n", - "The optimal cut is equal to: 7.0\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "p_list, H_list, avg_list = scale_p(3, G, backend, depth=3, decimals=decimals)\n", - "\n", - "costs = costsHist_MaxCut(G)\n", - "MAX_COST = max(costs)\n", - "print(\"The optimal cut is equal to: \", MAX_COST)\n", - "r_list = H_list / MAX_COST\n", - "\n", - "plt.scatter(p_list, r_list)\n", - "plt.plot(p_list, r_list, linestyle=\"--\", alpha=0.4)\n", - "plt.hlines(1, np.amin(p_list), np.amax(p_list), linestyles=\"--\", alpha=0.4, label=r\"Max value of $r$\")\n", - "plt.ylabel(r\"$r$\")\n", - "plt.xlabel(r\"$p$\")\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The INTERP heuristic uses the optimal parameters at depth $p$ to find good initial guesses at depth $p + 1$. In order to compare the two strategies, we run the two algorithms $K$ times for each $p$, and plot the best approximation ratio, $r^{opt}$ found in each layer.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.0 %\r", - "100%\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "compare_methods(3, G, backend, p_max=5, decimals=decimals, num_shots=8192)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Lastly, it is interesting to study how the optimal parameters change as we increase the level of depth. The main finding is that they are correlated, and this correlation is exactly what makes the INTERP heuristic work.\n", - "\n", - "In this case we study $M$ different graphs(all of the same type), and use $K$ tries to find the best parameters for each graph." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "100%%\n", - "Max cost: 7.0\n", - "Best approximation ratio, r = 0.9666050502232143\n", - "100%%\n", - "Max cost: 7.0\n", - "Best approximation ratio, r = 0.9319719587053571\n", - "100%%\n", - "Max cost: 7.0\n", - "Best approximation ratio, r = 0.9854038783482143\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "gamma_beta_func_of_p(4, backend, M=3, K = 20, heuristic=False, decimals=decimals, num_shots=8192)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/ER10uw Max 2,3 Cut_onehot.py b/ER10uw Max 2,3 Cut_onehot.py deleted file mode 100644 index 22c1bf3..0000000 --- a/ER10uw Max 2,3 Cut_onehot.py +++ /dev/null @@ -1,190 +0,0 @@ -from qiskit import * -from qiskit.tools.monitor import job_monitor - -import numpy as np -import matplotlib.pyplot as pl -from mpl_toolkits.axes_grid1 import make_axes_locatable - -import networkx as nx -from networkx.drawing.nx_agraph import graphviz_layout -from qiskit.visualization import * -from scipy import optimize as opt -from qaoa import * -import os - -import sys -sys.path.append('../') - -from qiskit_utilities.utilities import * -#from classical_maxkcut_solver import * - - -from matplotlib import rc -font = {'size' : 36} -rc('font', **font); -rc('text', usetex=True) -pl.rcParams["figure.figsize"] = 12,8 -pl.rcParams["axes.titlesize"] = 24 -pl.rcParams["axes.labelsize"] = 36 -pl.rcParams["lines.linewidth"] = 3 -pl.rcParams["lines.markersize"] = 10 -pl.rcParams["xtick.labelsize"] = 36 -pl.rcParams["ytick.labelsize"] = 36 -#pl.style.use('bmh') - -numV=10 -G = nx.read_gml("../data/sample_graphs/er_n"+str(numV)+"_k4_0.gml") - -#pos = nx.spring_layout(G) -#nx.draw_networkx(G,apos=pos) - -IBMQ.load_account() -provider = IBMQ.get_provider(hub='ibm-q') - -beta_n = 12 -gamma_n = 24 -beta_max = np.pi/2 -gamma_max = np.pi -optmethod='Nelder-Mead' -shots=1024*2*2*2 -rerun=True - -maxdepth=3 - -depths=range(1,maxdepth+1) - -outstr="" -outstrbest="" - -max_val = np.array([12, 16]) - -backend = provider.get_backend('ibmq_qasm_simulator') -#backend = Aer.get_backend('qasm_simulator') - -alpha=None -if alpha == None: - circuit_version=2 -else: - circuit_version=1 - -for k_cuts in [2,3]: - - #max_val, label = find_max_cut_brute_force(G, k_cuts) - #max_val, label = classical_maxkcut_solver(G, k_cuts) - - outstr+=str(k_cuts) - outstrbest+=str(k_cuts) - print(" k=", k_cuts) - name="ER10uw"+str(gamma_n)+"x"+str(beta_n)+"_v"+str(circuit_version)+"_k"+str(k_cuts)+"_onehot_alpha_"+str(alpha) - Elandscape, gammabetas, E, best = runQAOA(G, k_cuts, backend, gamma_n, beta_n, gamma_max, beta_max, optmethod=optmethod, circuit_version=circuit_version, shots=shots, name=name, rerun=rerun, maxdepth=maxdepth, onehot=True, onehot_alpha=alpha) - - shiftg=gamma_max/(2*gamma_n) - shiftb=beta_max/(2*beta_n) - - pl.figure(figsize=(20,10)); - pl.clf() - pl.imshow(Elandscape,interpolation='spline36',origin='lower' - ,extent=[-shiftg,gamma_max+shiftg,-shiftb,beta_max+shiftb], aspect=1) - pl.xticks([0,gamma_max/2, gamma_max], ['0', r'$\pi/2$', r'$\pi$']) - pl.yticks([0,beta_max], ['0', r'$\pi/2$']) - pl.xlabel('$\gamma$',loc='left') - pl.ylabel(r'$\beta$') - pl.colorbar(shrink=0.75, pad=0.05, orientation="horizontal") - - - #pl.plot(gammabetas['x0_d1'][0], gammabetas['x0_d1'][1],'xw') - pl.plot(gammabetas['xL_d1'][0], gammabetas['xL_d1'][1],'or') - - pl.tight_layout() - pl.savefig("pics/E_"+name+".png") - pl.close() - print("saved", "pics/E_",name,".png") - - #num_shots, av_max_cost, best_cost, distribution = getStatistics(G, k_cuts, backend, gammabetas, circuit_version=circuit_version, shots=shots, name=name+"_best") - - for depth in depths: - outstr+=" & "+"{:.2f}".format(E[str(depth)]/max_val[k_cuts-2]) - outstr+="\\\\ \n" - print(outstr) - - for depth in depths: - outstrbest+=" & "+"{:.2f}".format(best[str(depth)]/max_val[k_cuts-2]) - outstrbest+="\\\\ \n" - print(outstrbest) - - #pl.figure(figsize=(20,10)) - #pl.clf() - #for depth in depths: - # pl.semilogx(num_shots[63:], np.array(av_max_cost[str(depth)][63:])/max_val[k_cuts-2],'x-', base=2, label='d='+str(depth), linewidth=2,markersize=14) - #pl.ylabel('r') - #pl.xlabel('num shots') - #pl.legend() - #pl.grid(True, which="both") - #pl.tight_layout() - #pl.savefig("pics/"+name+"_avE.png") - #pl.close() - - #pl.figure(figsize=(20,10)) - #pl.clf() - #for depth in depths: - # pl.plot(num_shots[:36], np.array(av_max_cost[str(depth)][:36])/max_val[k_cuts-2],'x-', label='d='+str(depth), linewidth=2,markersize=14) - #pl.legend() - #pl.ylabel('r') - #pl.xlabel('num shots') - #pl.legend() - #pl.grid(True, which="both") - #pl.tight_layout() - #pl.savefig("pics/"+name+"_bestE"+str(depth)+".png") - #pl.close() - - #pl.figure(figsize=(20,10)) - #pl.clf() - #for d in depths: - # if d==1: - # col='r' - # elif d==2: - # col='g' - # else: - # col='b' - # sty='' - # if not d==1: - # sty=':' - # pl.plot(np.arange(1,d+1),gammabetas['x0_d'+str(d)][::2],'x'+col+sty,label='depth='+str(d)) - # sty='' - # if not d==1: - # sty='-' - # pl.plot(np.arange(1,d+1),gammabetas['xL_d'+str(d)][::2],'o'+col+sty,label='depth='+str(d)) - #pl.xlabel('depth') - #pl.ylabel(r'$\gamma$') - #pl.legend() - #pl.tight_layout() - #pl.savefig("pics/"+name+"_gamma.png") - #pl.close() - - #pl.figure(figsize=(20,10)) - #pl.clf() - #for d in depths: - # if d==1: - # col='r' - # elif d==2: - # col='g' - # else: - # col='b' - # sty='' - # if not d==1: - # sty=':' - # pl.plot(np.arange(1,d+1),gammabetas['x0_d'+str(d)][1::2],'x'+col+sty,label='depth='+str(d)) - # sty='' - # if not d==1: - # sty='-' - # pl.plot(np.arange(1,d+1),gammabetas['xL_d'+str(d)][1::2],'o'+col+sty,label='depth='+str(d)) - #pl.legend() - #pl.xlabel('depth') - #pl.ylabel(r'$\beta$') - #pl.legend() - #pl.tight_layout() - #pl.savefig("pics/"+name+"_beta.png") - #pl.close() - - - diff --git a/ER10uw Max 2,3,4,5,6,7,8 Cut.py b/ER10uw Max 2,3,4,5,6,7,8 Cut.py deleted file mode 100644 index 020c69d..0000000 --- a/ER10uw Max 2,3,4,5,6,7,8 Cut.py +++ /dev/null @@ -1,194 +0,0 @@ -from qiskit import * -from qiskit.tools.monitor import job_monitor - -import numpy as np -import matplotlib.pyplot as pl -from mpl_toolkits.axes_grid1 import make_axes_locatable - -import networkx as nx -from networkx.drawing.nx_agraph import graphviz_layout -from qiskit.visualization import * -from scipy import optimize as opt -from qaoa import * -from maxkcut import * -import os - -import sys -sys.path.append('../') - -from qiskit_utilities.utilities import * -from classical_maxkcut_solver import * - - -from matplotlib import rc -font = {'size' : 36} -rc('font', **font); -rc('text', usetex=True) -pl.rcParams["figure.figsize"] = 12,8 -pl.rcParams["axes.titlesize"] = 24 -pl.rcParams["axes.labelsize"] = 36 -pl.rcParams["lines.linewidth"] = 3 -pl.rcParams["lines.markersize"] = 10 -pl.rcParams["xtick.labelsize"] = 36 -pl.rcParams["ytick.labelsize"] = 36 -#pl.style.use('bmh') - -numV=10 -G = nx.read_gml("../data/sample_graphs/er_n"+str(numV)+"_k4_0.gml") - -#pos = nx.spring_layout(G) -#nx.draw_networkx(G,apos=pos) - -IBMQ.load_account() -provider = IBMQ.get_provider(hub='ibm-q') - -beta_n = 12 -gamma_n = 24 -beta_max = np.pi/2 -gamma_max = np.pi -optmethod='Nelder-Mead' -circuit_version=2 -shots=1024*2*2*2 -rerun=False - -maxdepth=3 - -depths=range(1,maxdepth+1) - -outstr="" -outstrbest="" - -max_val = np.array([12, 16, 16, 16, 16, 16, 16]) - - -for k_cuts in [2,3,4,5,6,7,8]: - if k_cuts<=4: - backend = Aer.get_backend('qasm_simulator') - else: - backend = provider.get_backend('ibmq_qasm_simulator') - - #max_val, label = find_max_cut_brute_force(G, k_cuts) - #max_val, label = classical_maxkcut_solver(G, k_cuts) - - outstr+=str(k_cuts) - outstrbest+=str(k_cuts) - print(" k=", k_cuts) - - options={} - options['G']=G - options['k_cuts']=k_cuts - options['version']=circuit_version - - options['name']="ER10uw"+str(gamma_n)+"x"+str(beta_n)+"_v"+str(circuit_version)+"_k"+str(k_cuts) - Elandscape, gammabetas, E, best = runQAOA(createCircuit_MaxCut, measurementStatistics_MaxCut, backend, gamma_n, beta_n, gamma_max, beta_max, optmethod=optmethod, shots=shots, rerun=rerun, maxdepth=maxdepth, options=options) - - shiftg=gamma_max/(2*gamma_n) - shiftb=beta_max/(2*beta_n) - - pl.figure(figsize=(20,10)); - pl.clf() - pl.imshow(Elandscape,interpolation='spline36',origin='lower' - ,extent=[-shiftg,gamma_max+shiftg,-shiftb,beta_max+shiftb], aspect=1) - pl.xticks([0,gamma_max/2, gamma_max], ['0', r'$\pi/2$', r'$\pi$']) - pl.yticks([0,beta_max], ['0', r'$\pi/2$']) - pl.xlabel('$\gamma$',loc='left') - pl.ylabel(r'$\beta$') - pl.colorbar(shrink=0.75, pad=0.05, orientation="horizontal") - - - #pl.plot(gammabetas['x0_d1'][0], gammabetas['x0_d1'][1],'xw') - pl.plot(gammabetas['xL_d1'][0], gammabetas['xL_d1'][1],'or') - - pl.tight_layout() - pl.savefig("pics/E_"+options['name']+".png") - pl.close() - print("saved", "pics/E_",options['name'],".png") - - #num_shots, av_max_cost, best_cost, distribution = getStatistics(G, k_cuts, backend, gammabetas, circuit_version=circuit_version, shots=shots, name=name+"_best") - - for depth in depths: - outstr+=" & "+"{:.2f}".format(E[str(depth)]/max_val[k_cuts-2]) - outstr+="\\\\ \n" - print(outstr) - - for depth in depths: - outstrbest+=" & "+"{:.2f}".format(best[str(depth)]/max_val[k_cuts-2]) - outstrbest+="\\\\ \n" - print(outstrbest) - - #pl.figure(figsize=(20,10)) - #pl.clf() - #for depth in depths: - # pl.semilogx(num_shots[63:], np.array(av_max_cost[str(depth)][63:])/max_val[k_cuts-2],'x-', base=2, label='d='+str(depth), linewidth=2,markersize=14) - #pl.ylabel('r') - #pl.xlabel('num shots') - #pl.legend() - #pl.grid(True, which="both") - #pl.tight_layout() - #pl.savefig("pics/"+name+"_avE.png") - #pl.close() - - #pl.figure(figsize=(20,10)) - #pl.clf() - #for depth in depths: - # pl.plot(num_shots[:36], np.array(av_max_cost[str(depth)][:36])/max_val[k_cuts-2],'x-', label='d='+str(depth), linewidth=2,markersize=14) - #pl.legend() - #pl.ylabel('r') - #pl.xlabel('num shots') - #pl.legend() - #pl.grid(True, which="both") - #pl.tight_layout() - #pl.savefig("pics/"+name+"_bestE"+str(depth)+".png") - #pl.close() - - pl.figure(figsize=(20,10)) - pl.clf() - for d in depths: - if d==1: - col='r' - elif d==2: - col='g' - else: - col='b' - sty='' - if not d==1: - sty=':' - pl.plot(np.arange(1,d+1),gammabetas['x0_d'+str(d)][::2],'x'+col+sty,label='depth='+str(d)) - sty='' - if not d==1: - sty='-' - pl.plot(np.arange(1,d+1),gammabetas['xL_d'+str(d)][::2],'o'+col+sty,label='depth='+str(d)) - pl.xlabel('depth') - pl.ylabel(r'$\gamma$') - pl.legend() - pl.tight_layout() - pl.savefig("pics/"+options['name']+"_gamma.png") - pl.close() - - pl.figure(figsize=(20,10)) - pl.clf() - for d in depths: - if d==1: - col='r' - elif d==2: - col='g' - else: - col='b' - sty='' - if not d==1: - sty=':' - pl.plot(np.arange(1,d+1),gammabetas['x0_d'+str(d)][1::2],'x'+col+sty,label='depth='+str(d)) - sty='' - if not d==1: - sty='-' - pl.plot(np.arange(1,d+1),gammabetas['xL_d'+str(d)][1::2],'o'+col+sty,label='depth='+str(d)) - pl.legend() - pl.xlabel('depth') - pl.ylabel(r'$\beta$') - pl.legend() - pl.tight_layout() - pl.savefig("pics/"+options['name']+"_beta.png") - pl.close() - - - diff --git a/Error controlled MaxCut.ipynb b/Error controlled MaxCut.ipynb deleted file mode 100644 index 40bb58a..0000000 --- a/Error controlled MaxCut.ipynb +++ /dev/null @@ -1,366 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from qiskit import *\n", - "import numpy as np\n", - "import pylab as pl\n", - "import networkx as nx\n", - "from qiskit.visualization import *\n", - "from qiskit.providers.aer.noise import NoiseModel\n", - "from qaoa import *\n", - "from pylab import cm\n", - "\n", - "from matplotlib import rc\n", - "from scipy import optimize as opt\n", - "from collections import defaultdict\n", - "\n", - "SAMPLING_E_ATOL = 2e-2\n", - "SAMPLING_E_RTOL = 1e-2\n", - "SAMPLING_DELTA_V_RTOL = 1e-1\n", - "MIN_SAMPLES = 256\n", - "MAX_SAMPLES = 32768\n", - "SAMPLING_CONF_IDX = 1\n", - "EXACT_SAMPLES = MAX_SAMPLES*4\n", - "\n", - "BETA_MIN = -np.pi/4\n", - "BETA_MAX = np.pi/4\n", - "GAMMA_MIN = -np.pi/2\n", - "GAMMA_MAX = np.pi/2\n", - "\n", - "CIRCUIT_VERSION = 1\n", - "CIRCUIT_DEPTH = 1\n", - "\n", - "font = {'size' : 16}\n", - "rc('font', **font);\n", - "rc('text', usetex=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.0 %\r", - "Max cost: 6\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "k_cuts=2\n", - "V = np.arange(0,5,1)\n", - "E =[(0,1,1.0),(0,2,2.0),(2,3,1.5),(3,1,1.1),(3,4,0.4),(4,2,1.0)]\n", - "G = nx.Graph()\n", - "G.add_nodes_from(V)\n", - "G.add_weighted_edges_from(E)\n", - "\n", - "pos = nx.spring_layout(G)\n", - "pl.figure(figsize=(10,6))\n", - "nx.draw_networkx(G,pos=pos)\n", - "\n", - "V1 = np.arange(0,)\n", - "costs=costsHist_MaxCut(G, k_cuts)\n", - "max_cost = max(costs)\n", - "print('Max cost: %d' % max_cost)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "backend_sim = Aer.get_backend('qasm_simulator')" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "def getval(x,history_ref,backend,depth,version,noisemodel,E_atol,E_rtol,dv_rtol,min_n_shots,max_n_shots,conf_idx):\n", - " circuit = createCircuit_MaxCut(x,G,depth,k_cuts,version)\n", - " \n", - " raw_data = defaultdict(float)\n", - " [E_list,v_list,n_list] = sampleUntilPrecision(circuit,backend,noisemodel,min_n_shots,\n", - " max_n_shots,E_atol,E_rtol,dv_rtol,conf_idx, measurementStatistics_MaxCut, measurement_vars={'G' : G, 'k_cuts' : k_cuts})\n", - "\n", - " history_ref['gammas'].append(x[0])\n", - " history_ref['betas'].append(x[1])\n", - " history_ref['expectations'].append(E_list)\n", - " history_ref['variances'].append(v_list)\n", - " history_ref['n_shots'].append(n_list)\n", - " \n", - " return -E_list[-1]" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "opt_history = {\n", - " 'gammas': [],\n", - " 'betas': [],\n", - " 'expectations': [],\n", - " 'variances': [],\n", - " 'n_shots': [],\n", - "}\n", - "x0 = (0.3,0.3)\n", - "out = opt.minimize(getval, x0=x0, method='COBYLA',\n", - " args=(opt_history,backend_sim,CIRCUIT_DEPTH,CIRCUIT_VERSION,None,\n", - " SAMPLING_E_ATOL,SAMPLING_E_RTOL,SAMPLING_DELTA_V_RTOL,\n", - " MIN_SAMPLES,MAX_SAMPLES,SAMPLING_CONF_IDX),\n", - " options={'rhobeg': 1e-1, 'disp': True})" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "max_reps = max([len(x) for x in opt_history['n_shots']])\n", - "Ess = np.array(np.array([x + [x[-1]]*(max_reps-len(x)+1) for x in opt_history['expectations']]))\n", - "vss = np.array(np.array([x + [x[-1]]*(max_reps-len(x)+1) for x in opt_history['variances']]))\n", - "nss = np.array(np.array([x + [0]*(max_reps-len(x)+1) for x in opt_history['n_shots']]))\n", - "\n", - "first_Es = Ess[:,0]\n", - "first_vs = vss[:,0]\n", - "first_ns = nss[:,0]\n", - "\n", - "last_Es = Ess[:,-1]\n", - "last_vs = vss[:,-1]\n", - "last_ns = np.sum(nss,axis=1)\n", - "\n", - "first_stddevs = np.sqrt(first_vs)\n", - "first_stderrs = np.divide(first_stddevs,np.sqrt(first_ns))\n", - "last_stddevs = np.sqrt(last_vs)\n", - "last_stderrs = np.divide(first_stddevs,np.sqrt(last_ns))\n", - "\n", - "gammas = np.array(opt_history['gammas'])\n", - "betas = np.array(opt_history['betas'])\n", - "its = list(range(nss.shape[0]))\n", - "n_its = len(its)\n", - "\n", - "Es_exact = np.zeros((n_its,))\n", - "for it in its:\n", - " circuit = createCircuit_MaxCut(np.array((gammas[it],betas[it])),G,CIRCUIT_DEPTH,k_cuts,CIRCUIT_VERSION)\n", - " job_sim_exact = execute(circuit, backend_sim, shots=EXACT_SAMPLES)\n", - " [E_exact],_,_ = measurementStatistics_MaxCut(job_sim_exact.result().results, options={'G' : G, 'k_cuts' : k_cuts})\n", - " Es_exact[it] = E_exact" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Sample counts')" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure(figsize=(10,6))\n", - "pl.plot(its,Es_exact,'g-',label='Exact mean')\n", - "pl.errorbar(its,first_Es,yerr=first_stderrs.flatten(),fmt='.k',label='Initial mean estimate')\n", - "pl.errorbar(its,last_Es,yerr=last_stderrs.flatten(),fmt='.b',label='Corrected mean estimate')\n", - "pl.plot(its,first_stddevs,'k--',label='Initial stddev')\n", - "pl.plot(its,last_stddevs,'b--',label='Corrected stddev')\n", - "pl.legend()\n", - "pl.xlabel('Iteration')\n", - "pl.ylabel('Cost')\n", - "pl.title('Optimizer history')\n", - "\n", - "pl.figure(figsize=(10,6))\n", - "pl.bar(its,nss[:,0],label='Rep. 0')\n", - "for i in range(1,max_reps):\n", - " pl.bar(its,nss[:,i],bottom=np.sum(nss[:,0:i],axis=1),label='Rep. %d'%i)\n", - "pl.legend()\n", - "pl.xlabel('Iteration')\n", - "pl.ylabel('Shots')\n", - "pl.title('Sample counts')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - ":24: UserWarning: FixedFormatter should only be used together with FixedLocator\n", - " ax.set_yticklabels(['%.2f' % (y/n_iterations) for y in yticks]) # Normalize y-axis\n", - ":41: UserWarning: FixedFormatter should only be used together with FixedLocator\n", - " ax.set_yticklabels(['%.2f' % (y/n_iterations) for y in yticks]) # Normalize y-axis\n" - ] - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Relative error confidence')" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "n_iterations = len(its)\n", - "\n", - "abs_errors = np.array([abs(Es_exact[it] - last_Es[it]) for it in its])\n", - "rel_errors = np.array([abs_errors[it]/Es_exact[it] for it in its])\n", - "\n", - "abs_binsize = 0.06*SAMPLING_E_ATOL\n", - "rel_binsize = 0.03*SAMPLING_E_RTOL\n", - "abs_n_bins = int(np.ceil(max(abs_errors)/abs_binsize))\n", - "rel_n_bins = int(np.ceil(max(rel_errors)/rel_binsize))\n", - "\n", - "abs_bounded_count = np.size(np.where(abs_errors <= SAMPLING_E_ATOL))\n", - "rel_bounded_count = np.size(np.where(rel_errors <= SAMPLING_E_RTOL))\n", - "abs_bounded_pct = int(100*abs_bounded_count/n_iterations)\n", - "rel_bounded_pct = int(100*rel_bounded_count/n_iterations)\n", - " \n", - "pl.figure(figsize=(10,6))\n", - "pl.hist(abs_errors,abs_n_bins,label='Absoloute error distribution')\n", - "_,_,patches = pl.hist(abs_errors,abs_n_bins,cumulative=True,histtype='step',label='Cumulative distribution')\n", - "patches[0].set_xy(patches[0].get_xy()[:-1]) # Delete last point which is at y=0\n", - "pl.axvline(SAMPLING_E_ATOL,linestyle='-',linewidth=0.8,color='k',\n", - " label='Tolerance (%d\\%% confidence)' % abs_bounded_pct)\n", - "ax = pl.gca()\n", - "yticks = ax.get_yticks()\n", - "ax.set_yticklabels(['%.2f' % (y/n_iterations) for y in yticks]) # Normalize y-axis\n", - "ax.margins(x=0)\n", - "pl.xlabel('Absolute error')\n", - "pl.ylabel('Frequency ratio')\n", - "pl.xlim(0,max(SAMPLING_E_ATOL,max(abs_errors))*1.1)\n", - "pl.ylim(0,n_iterations)\n", - "pl.legend(loc='center right')\n", - "pl.title('Absolute error confidence')\n", - "\n", - "pl.figure(figsize=(10,6))\n", - "pl.hist(rel_errors,rel_n_bins,label='Relative error distribution')\n", - "_,_,patches = pl.hist(rel_errors,rel_n_bins,cumulative=True,histtype='step',label='Cumulative distribution')\n", - "patches[0].set_xy(patches[0].get_xy()[:-1]) # Delete last point which is at y=0\n", - "pl.axvline(SAMPLING_E_RTOL,linestyle='-',linewidth=0.8,color='k',\n", - " label='Tolerance (%d\\%% confidence)' % rel_bounded_pct)\n", - "ax = pl.gca()\n", - "yticks = ax.get_yticks()\n", - "ax.set_yticklabels(['%.2f' % (y/n_iterations) for y in yticks]) # Normalize y-axis\n", - "ax.margins(x=0)\n", - "pl.xlabel('Relative error')\n", - "pl.ylabel('Frequency ratio')\n", - "pl.xlim(0,max(SAMPLING_E_RTOL,max(rel_errors))*1.1)\n", - "pl.ylim(0,n_iterations)\n", - "pl.legend(loc='center right')\n", - "pl.title('Relative error confidence')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.3" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/Error controlled sampling.ipynb b/Error controlled sampling.ipynb deleted file mode 100644 index 24f63cb..0000000 --- a/Error controlled sampling.ipynb +++ /dev/null @@ -1,263 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from qiskit import *\n", - "import numpy as np\n", - "import pylab as pl\n", - "import networkx as nx\n", - "from qiskit.visualization import *\n", - "from qiskit.providers.aer.noise import NoiseModel\n", - "from qaoa import *\n", - "from pylab import cm\n", - "\n", - "from matplotlib import rc\n", - "from scipy import optimize as opt\n", - "from collections import defaultdict\n", - "\n", - "SAMPLING_E_ATOL = 2e-2\n", - "SAMPLING_E_RTOL = 1e-2\n", - "SAMPLING_DELTA_V_RTOL = 1e-1\n", - "MIN_SAMPLES = 256\n", - "MAX_SAMPLES = 32768*4\n", - "SAMPLING_CONF_IDX = 2\n", - "EXACT_SAMPLES = MAX_SAMPLES*2\n", - "\n", - "CIRCUIT_VERSION = 1\n", - "CIRCUIT_DEPTH = 1\n", - "\n", - "font = {'size' : 16}\n", - "rc('font', **font);\n", - "rc('text', usetex=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.0 %\r", - "Max cost: 6\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "k_cuts=2\n", - "V = np.arange(0,5,1)\n", - "E =[(0,1,1.0),(0,2,2.0),(2,3,1.5),(3,1,1.1),(3,4,0.4),(4,2,1.0)]\n", - "G = nx.Graph()\n", - "G.add_nodes_from(V)\n", - "G.add_weighted_edges_from(E)\n", - "\n", - "pos = nx.spring_layout(G)\n", - "pl.figure(figsize=(10,6))\n", - "nx.draw_networkx(G,pos=pos)\n", - "\n", - "V1 = np.arange(0,)\n", - "costs=costsHist_MaxCut(G, k_cuts)\n", - "max_cost = max(costs)\n", - "print('Max cost: %d' % max_cost)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "backend_sim = Aer.get_backend('qasm_simulator')" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "c = 1\n", - "100.00%\n", - "c = 2\n", - "100.00%\n", - "c = 3\n", - "100.00%\n" - ] - } - ], - "source": [ - "n_iterations = 256\n", - "n_conf_idxs = 3\n", - "\n", - "beta_min=-np.pi/4\n", - "beta_max=np.pi/4\n", - "gamma_min=-np.pi/2\n", - "gamma_max=np.pi/2\n", - "\n", - "betas = np.random.uniform(beta_min,beta_max,size=(n_iterations,))\n", - "gammas = np.random.uniform(gamma_min,gamma_max,size=(n_iterations,))\n", - "Ess = np.zeros((n_conf_idxs,n_iterations))\n", - "Ess_exact = np.zeros((n_conf_idxs,n_iterations))\n", - "its = range(n_iterations)\n", - "conf_idxs = range(1,n_conf_idxs+1)\n", - "\n", - "for c in conf_idxs:\n", - " print('c = %d' % c)\n", - " for i in its:\n", - " circuit = createCircuit_MaxCut(np.array((gammas[i],betas[i])),G,CIRCUIT_DEPTH,k_cuts,CIRCUIT_VERSION)\n", - " E_list,_,_ = sampleUntilPrecision(circuit,backend_sim,None,MIN_SAMPLES,\n", - " MAX_SAMPLES,SAMPLING_E_ATOL,SAMPLING_E_RTOL,\n", - " SAMPLING_DELTA_V_RTOL,c, measurementStatistics_MaxCut, measurement_vars={'G' : G, 'k_cuts' : k_cuts})\n", - " Ess[c-1,i] = E_list[-1]\n", - " \n", - " job_sim_exact = execute(circuit, backend_sim, shots=EXACT_SAMPLES)\n", - " [E_exact],_,_ = measurementStatistics_MaxCut(job_sim_exact.result().results, options={'G' : G, 'k_cuts' : k_cuts})\n", - " Ess_exact[c-1,i] = E_exact\n", - " print('%.2f%%' % (100*(i+1)/n_iterations),end='\\r')\n", - " print()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - ":31: UserWarning: FixedFormatter should only be used together with FixedLocator\n", - " ax.set_yticklabels(['%.2f' % (y/n_iterations) for y in yticks]) # Normalize y-axis\n", - ":43: UserWarning: FixedFormatter should only be used together with FixedLocator\n", - " ax.set_yticklabels(['%.2f' % (y/n_iterations) for y in yticks]) # Normalize y-axis\n" - ] - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Relative error confidence')" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "for c in conf_idxs:\n", - " abs_errors = np.array([abs(Ess_exact[c-1,it] - Ess[c-1,it]) for it in its])\n", - " rel_errors = np.array([abs_errors[it]/Ess_exact[c-1,it] for it in its])\n", - "\n", - " abs_binsize = 0.06*SAMPLING_E_ATOL\n", - " rel_binsize = 0.03*SAMPLING_E_RTOL\n", - " abs_n_bins = int(np.ceil(max(abs_errors)/abs_binsize))\n", - " rel_n_bins = int(np.ceil(max(rel_errors)/rel_binsize))\n", - "\n", - " abs_bounded_count = np.size(np.where(abs_errors <= SAMPLING_E_ATOL))\n", - " rel_bounded_count = np.size(np.where(rel_errors <= SAMPLING_E_RTOL))\n", - " abs_bounded_pct = int(100*abs_bounded_count/n_iterations)\n", - " rel_bounded_pct = int(100*rel_bounded_count/n_iterations)\n", - "\n", - " pl.figure(1,figsize=(10,6))\n", - " pl.hist(abs_errors,abs_n_bins,label='Distribution, c=%d' % c,alpha=0.6)\n", - " _,_,patches = pl.hist(abs_errors,abs_n_bins,cumulative=True,histtype='step',\n", - " label='Cumulative, c=%d' % c)\n", - " patches[0].set_xy(patches[0].get_xy()[:-1]) # Delete last point which is at y=0\n", - "\n", - " pl.figure(2,figsize=(10,6))\n", - " pl.hist(rel_errors,rel_n_bins,label='Distribution, c=%d' % c)\n", - " _,_,patches = pl.hist(rel_errors,rel_n_bins,cumulative=True,histtype='step',\n", - " label='Cumulative, c=%d' % c)\n", - " patches[0].set_xy(patches[0].get_xy()[:-1]) # Delete last point which is at y=0\n", - " \n", - "pl.figure(1)\n", - "pl.axvline(SAMPLING_E_ATOL,linestyle='-',linewidth=0.8,color='k',label='Tolerance')\n", - "ax = pl.gca()\n", - "yticks = ax.get_yticks()\n", - "ax.set_yticklabels(['%.2f' % (y/n_iterations) for y in yticks]) # Normalize y-axis\n", - "ax.margins(x=0)\n", - "pl.xlabel('Absolute error')\n", - "pl.ylabel('Frequency ratio')\n", - "pl.ylim(0,n_iterations)\n", - "pl.legend(loc='center right')\n", - "pl.title('Absolute error confidence')\n", - "\n", - "pl.figure(2)\n", - "pl.axvline(SAMPLING_E_RTOL,linestyle='-',linewidth=0.8,color='k',label='Tolerance')\n", - "ax = pl.gca()\n", - "yticks = ax.get_yticks()\n", - "ax.set_yticklabels(['%.2f' % (y/n_iterations) for y in yticks]) # Normalize y-axis\n", - "ax.margins(x=0)\n", - "pl.xlabel('Relative error')\n", - "pl.ylabel('Frequency ratio')\n", - "pl.ylim(0,n_iterations)\n", - "pl.legend(loc='center right')\n", - "pl.title('Relative error confidence')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.3" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/ExactCover/ExactCover 14 5.ipynb b/ExactCover/ExactCover 14 5.ipynb new file mode 100644 index 0000000..566477e --- /dev/null +++ b/ExactCover/ExactCover 14 5.ipynb @@ -0,0 +1,523 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "e429c1ea", + "metadata": {}, + "outputs": [], + "source": [ + "#run: pip install openquantumcomputing\n", + "import sys\n", + "sys.path.insert(0, '/home/franzf/OpenQuantumComputing/OpenQuantumComputing/')\n", + "from openquantumcomputing.QAOAExactCover import QAOAExactCover" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "a25b06d2", + "metadata": {}, + "outputs": [], + "source": [ + "from qiskit import *\n", + "\n", + "import numpy as np\n", + "from tailassignment_loader import *\n", + "\n", + "import matplotlib.pyplot as pl\n", + "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", + "from qiskit.visualization import *\n", + "\n", + "from tqdm import tqdm" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "5a113cdc", + "metadata": {}, + "outputs": [], + "source": [ + "instances = 14\n", + "flights = 24\n", + "solutions = 5\n", + "\n", + "path_to_examples = \"tailassignment_samples/\"\n", + "\n", + "FR, CR, best_sol = load_FR_CR(path_to_examples + f'FRCR_{instances}_{flights}_{solutions}.txt')" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "ba34f8b6", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "params={'FR': FR}\n", + "params['usebarrier']=True\n", + "qaoaec = QAOAExactCover(params=params)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "8a71822c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[0. 1. 1. 0. 1. 0. 1. 0. 0. 1. 1. 1. 0. 1.]\n", + " [1. 0. 0. 1. 0. 1. 0. 1. 1. 0. 0. 0. 1. 0.]\n", + " [0. 1. 1. 0. 1. 0. 1. 0. 0. 1. 1. 1. 0. 1.]\n", + " [1. 0. 0. 1. 0. 1. 0. 1. 1. 0. 0. 0. 1. 0.]\n", + " [0. 1. 1. 0. 1. 0. 1. 0. 0. 1. 1. 1. 0. 1.]\n", + " [1. 0. 0. 1. 0. 1. 0. 1. 1. 0. 0. 0. 1. 0.]\n", + " [1. 0. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 1. 0.]\n", + " [0. 1. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 0. 1.]\n", + " [1. 0. 1. 0. 0. 1. 0. 1. 0. 1. 0. 1. 0. 0.]\n", + " [0. 1. 0. 1. 1. 0. 1. 0. 1. 0. 1. 0. 1. 1.]\n", + " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 0.]\n", + " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 1.]\n", + " [0. 1. 0. 1. 1. 0. 1. 0. 0. 1. 0. 1. 0. 0.]\n", + " [1. 0. 1. 0. 0. 1. 0. 1. 1. 0. 1. 0. 1. 1.]\n", + " [0. 1. 0. 1. 0. 1. 1. 0. 0. 1. 0. 1. 1. 0.]\n", + " [1. 0. 1. 0. 1. 0. 0. 1. 1. 0. 1. 0. 0. 1.]\n", + " [1. 0. 1. 0. 0. 1. 1. 0. 0. 1. 0. 0. 1. 1.]\n", + " [0. 1. 0. 1. 1. 0. 0. 1. 1. 0. 1. 1. 0. 0.]\n", + " [0. 1. 1. 0. 0. 1. 1. 0. 0. 1. 0. 1. 1. 1.]\n", + " [1. 0. 0. 1. 1. 0. 0. 1. 1. 0. 1. 0. 0. 0.]\n", + " [0. 1. 1. 0. 0. 1. 1. 0. 1. 0. 0. 1. 1. 1.]\n", + " [1. 0. 0. 1. 1. 0. 0. 1. 0. 1. 1. 0. 0. 0.]\n", + " [0. 1. 0. 1. 0. 1. 1. 0. 1. 0. 0. 1. 1. 0.]\n", + " [1. 0. 1. 0. 1. 0. 0. 1. 0. 1. 1. 0. 0. 1.]]\n", + "solutions:\n", + "00000000110000 0.0\n", + "00000011000000 0.0\n", + "00001100000000 0.0\n", + "00110000000000 0.0\n", + "11000000000000 0.0\n" + ] + } + ], + "source": [ + "import itertools\n", + "print(FR)\n", + "nL=FR.shape[1]\n", + "print(\"solutions:\")\n", + "costs=[]\n", + "for s in [''.join(i) for i in itertools.product('01', repeat =nL)]:\n", + " costs.append(-qaoaec.cost(s))\n", + " if qaoaec.isFeasible(s):\n", + " print(s, -qaoaec.cost(s))" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "24da8ffe", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "max_val=max(costs)\n", + "\n", + "pl.figure(figsize=(25,10))\n", + "_=pl.hist(np.sort(costs), bins=200)\n", + "min_ylim, max_ylim = pl.ylim()\n", + "max_ylim *=1.025\n", + "mean=np.mean(costs)\n", + "pl.axvline(mean, color='k', linestyle='dashed', linewidth=2)\n", + "_=pl.text(mean-1, max_ylim, 'mean = {:.2f}'.format(mean))\n", + "_=pl.xticks(np.arange(0, max_val, step=25))" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "a4fcccfa", + "metadata": {}, + "outputs": [], + "source": [ + "qasm_sim = Aer.get_backend('qasm_simulator')" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "112c880a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Calculating Energy landscape for depth p=1...\n", + "Calculating Energy landscape done\n" + ] + } + ], + "source": [ + "qaoaec.sample_cost_landscape(qasm_sim, 1024, angles={\"gamma\": [0,np.pi,30], \"beta\": [0,np.pi/2,20]})" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "411cbd19", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "f = pl.figure(figsize=(6, 6), dpi= 80, facecolor='w', edgecolor='k');\n", + "_=pl.xlabel(r'$\\gamma$')\n", + "_=pl.ylabel(r'$\\beta$')\n", + "ax = pl.gca()\n", + "_=pl.title('Expectation value')\n", + "im = ax.imshow(qaoaec.E,interpolation='bicubic',origin='lower',extent=[0,np.pi,0,np.pi/2])\n", + "divider = make_axes_locatable(ax)\n", + "cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n", + "_=pl.colorbar(im, cax=cax)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "becf35c6", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "f = pl.figure(figsize=(6, 6), dpi= 80, facecolor='w', edgecolor='k');\n", + "_=pl.xlabel(r'$\\gamma$')\n", + "_=pl.ylabel(r'$\\beta$')\n", + "ax = pl.gca()\n", + "_=pl.title('Variance')\n", + "im = ax.imshow(qaoaec.Var,interpolation='bicubic',origin='lower',extent=[0,np.pi,0,np.pi/2])\n", + "divider = make_axes_locatable(ax)\n", + "cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n", + "_=pl.colorbar(im, cax=cax)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "9bb7d8d6", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 50%|████████████████████████████████████████████████████████████████████████████████████████ | 1/2 [00:03<00:03, 3.12s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 1 )= 147.66796875000006\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:11<00:00, 5.91s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 2 )= 195.6679687500001\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "maxdepth=2\n", + "for i in tqdm(range(maxdepth)):\n", + " qaoaec.increase_depth(qasm_sim, )" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "ede41c0a", + "metadata": {}, + "outputs": [], + "source": [ + "hist=qaoaec.hist(qaoaec.angles_hist['d1_final'], qasm_sim,1024)\n", + "bins={}\n", + "for key in hist:\n", + " c=-qaoaec.cost(key[::-1])\n", + " bins[c]=bins.get(c,0)\n", + " bins[c]+=hist[key]\n", + "bins=dict(sorted(bins.items()))" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "f44ac51e", + "metadata": {}, + "outputs": [], + "source": [ + "bins_class={}\n", + "for c in costs:\n", + " bins_class[int(c)]=bins_class.get(int(c),0)\n", + " bins_class[int(c)]+=1\n", + "bins_class=dict(sorted(bins_class.items()))" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "696d524e", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for i in range(1,maxdepth+1):\n", + " hist=qaoaec.hist(qaoaec.angles_hist['d'+str(i)+'_final'], qasm_sim,1024)\n", + " bins={}\n", + " for key in hist:\n", + " c=-qaoaec.cost(key[::-1])\n", + " bins[c]=bins.get(c,0)\n", + " bins[c]+=hist[key]\n", + " bins=dict(sorted(bins.items()))\n", + " max_val=max(costs)\n", + " min_val=min(costs)\n", + "\n", + " pl.figure(i, figsize=(25,10))\n", + " w=np.array(list(bins.values()))\n", + " c,d,_=pl.hist(bins.keys(),bins=200,weights=w, alpha = 0.5, color= 'r')\n", + " pl.clf()\n", + " pl.title(\"depth=\"+str(i))\n", + " a,b,_=pl.hist(np.sort(costs), bins=200, alpha = 0.5, color= 'b')\n", + " w=np.array(list(bins.values()))\n", + " pl.hist(bins.keys(),bins=200,weights=w/max(c)*max(a), alpha = 0.5, color= 'r')\n", + " min_ylim, max_ylim = pl.ylim()\n", + " max_ylim *=1.025\n", + " mean=np.mean(costs)\n", + " pl.axvline(mean, color='k', linestyle='dashed', linewidth=2)\n", + " _=pl.text(mean-1, max_ylim, 'mean = {:.2f}'.format(mean))\n", + " _=pl.xticks(np.arange(min_val, max_val, step=50))\n", + " pl.xlabel(\"cost\")\n", + " pl.savefig(\"animation\"+str(i).zfill(3))" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "6c96a550", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pl.plot(np.arange(1,maxdepth+1), np.array(list(qaoaec.costval.values())),'o--')\n", + "pl.hlines(0, 1,maxdepth, linestyles=\"solid\", colors=\"black\")\n", + "# pl.ylim(-0.01,1)\n", + "_=pl.title('Cost')\n", + "_=pl.ylabel('cost')\n", + "_=pl.xlabel('depth')" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "3d62f3ba", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 5.97it/s]\n" + ] + }, + { + "data": { + "image/png": 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CDQAAMBXCDQAAMBXCDQAAMBXCDQAAMBXCDQAAMBW3h5tZs2YpIiJCPj4+io6O1ubNm6/af8aMGWrRooV8fX0VHh6up59+WhcvXrxO1QIAgMrOreFmwYIFSkxMVFJSkrZt26bIyEjFxcXp1KlTJfafN2+enn/+eSUlJWnv3r368MMPtWDBAv3lL3+5zpUDAIDKyq3h5q233tKjjz6qYcOGqXXr1po9e7Zq1Kihjz76qMT+GzduVJcuXTR48GBFRETorrvu0qBBg6452gMAAG4cbgs3RUVF2rp1q3r27PmfYjw91bNnT6WlpZW4ze23366tW7faw8xPP/2klStX6p577in1fQoLC5WXl+ewAAAA86rmrjfOzs6W1WpVcHCwQ3twcLD27dtX4jaDBw9Wdna2unbtKsMwdPnyZT3++ONXPS2VnJysKVOmuLR2AABQebn9gmJnrF+/XtOmTdN7772nbdu2acmSJVqxYoWmTp1a6jYTJ05Ubm6ufcnIyLiOFQMAgOvNbSM3gYGB8vLyUlZWlkN7VlaWQkJCStzmxRdf1COPPKKRI0dKktq1a6f8/Hw99thjeuGFF+TpWTyrWSwWWSwW138AAABQKblt5Mbb21sdO3ZUSkqKvc1msyklJUUxMTElblNQUFAswHh5eUmSDMOouGIBAECV4baRG0lKTEzUkCFD1KlTJ0VFRWnGjBnKz8/XsGHDJEkJCQkKCwtTcnKyJKlv375666231KFDB0VHR+vQoUN68cUX1bdvX3vIAQAANza3hpv4+HidPn1akydPVmZmptq3b69Vq1bZLzI+fvy4w0jNpEmT5OHhoUmTJunEiROqX7+++vbtq1deecVdHwEAAFQyHsYNdj4nLy9P/v7+ys3NlZ+fn7vLAQAAZeDM93eVulsKAADgWgg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVAg3AADAVJwON6mpqRVRBwAAgEs4HW569+6tpk2b6q9//asyMjIqoiYAAIByczrcnDhxQqNHj9bixYvVpEkTxcXFaeHChSoqKqqI+gAAAJzidLgJDAzU008/rfT0dG3atEnNmzfXk08+qdDQUD311FPasWNHRdQJAABQJr/rguJbb71VEydO1OjRo3XhwgV99NFH6tixo7p166Yff/zRVTUCAACUWbnCzaVLl7R48WLdc889atSokVavXq2ZM2cqKytLhw4dUqNGjTRgwABX1woAAHBNHoZhGM5sMGbMGH322WcyDEOPPPKIRo4cqbZt2zr0yczMVGhoqGw2m0uLdYW8vDz5+/srNzdXfn5+7i4HAACUgTPf39Wc3fmePXv07rvvqn///rJYLCX2CQwM5JZxAADgFk6flkpKStKAAQOKBZvLly9rw4YNkqRq1aopNjbWNRUCAAA4welw0717d509e7ZYe25urrp37+6SogAAAMrL6XBjGIY8PDyKtZ85c0Y1a9Z0SVEAAADlVeZrbvr37y9J8vDw0NChQx1OS1mtVu3cuVO333676ysEAABwQpnDjb+/v6QrIze1a9eWr6+v/TVvb2/ddtttevTRR11fIQAAgBPKHG7mzp0rSYqIiND48eM5BQUAAColp59zU9XxnBsAAKoelz/n5tZbb1VKSorq1KmjDh06lHhB8W+2bdvmXLUAAAAuVKZwc//999svIO7Xr19F1gMAAPC7cFoKAABUes58f/+uWcEBAAAqmzKdlqpTp85Vr7P5byU9vRgAAOB6KVO4mTFjRgWXAQAA4BplCjdDhgyp6DoAAABcokzhJi8vz37xTl5e3lX7cpEuAABwpzJfc3Py5EkFBQUpICCgxOtvfptQ02q1urxIAACAsipTuFm3bp3q1q0rSUpNTa3QggAAAH4PnnMDAAAqvQp/zs25c+f05ptvasSIERoxYoSmT59e7lvAZ82apYiICPn4+Cg6OlqbN2++av+cnByNGjVKDRo0kMViUfPmzbVy5cpyvTcAADAfp8PNhg0bFBERoXfeeUfnzp3TuXPn9M4776hx48basGGDU/tasGCBEhMTlZSUpG3btikyMlJxcXE6depUif2LiorUq1cvHT16VIsXL9b+/fs1Z84chYWFOfsxAACASTl9Wqpdu3aKiYnR+++/Ly8vL0mS1WrVk08+qY0bN2rXrl1l3ld0dLQ6d+6smTNnSpJsNpvCw8M1ZswYPf/888X6z549W2+88Yb27dun6tWrO1O2HaelAACoeir0tNShQ4f0zDPP2IONJHl5eSkxMVGHDh0q836Kioq0detW9ezZ8z/FeHqqZ8+eSktLK3GbL774QjExMRo1apSCg4PVtm1bTZs27ap3aBUWFiovL89hAQAA5uV0uLn11lu1d+/eYu179+5VZGRkmfeTnZ0tq9Wq4OBgh/bg4GBlZmaWuM1PP/2kxYsXy2q1auXKlXrxxRc1ffp0/fWvfy31fZKTk+Xv729fwsPDy1wjAACoesp0K/jOnTvtf37qqac0duxYHTp0SLfddpsk6fvvv9esWbP06quvVkyV/8tmsykoKEgffPCBvLy81LFjR504cUJvvPGGkpKSStxm4sSJSkxMtK/n5eURcAAAMLEyhZv27dvLw8ND/315zrPPPlus3+DBgxUfH1+mNw4MDJSXl5eysrIc2rOyshQSElLiNg0aNFD16tUdTom1atVKmZmZKioqkre3d7FtLBaLLBZLmWoCAABVX5nCzZEjR1z+xt7e3urYsaNSUlLUr18/SVdGZlJSUjR69OgSt+nSpYvmzZsnm80mT88rZ9QOHDigBg0alBhsAADAjadM4aZRo0YV8uaJiYkaMmSIOnXqpKioKM2YMUP5+fkaNmyYJCkhIUFhYWFKTk6WJD3xxBOaOXOmxo4dqzFjxujgwYOaNm2annrqqQqpDwAAVD1lCjcl2bNnj44fP66ioiKH9vvuu6/M+4iPj9fp06c1efJkZWZmqn379lq1apX9IuPjx4/bR2gkKTw8XKtXr9bTTz+tW265RWFhYRo7dqyee+658n4MAABgMk4/5+ann37SAw88oF27djlch/PbZJqVfeJMnnMDAEDVU6HPuRk7dqwaN26sU6dOqUaNGvrxxx+1YcMGderUSevXry9vzQAAAC7h9GmptLQ0rVu3ToGBgfL09JSnp6e6du2q5ORkPfXUU9q+fXtF1AkAAFAmTo/cWK1W1a5dW9KV27l/+eUXSVcuOt6/f79rqwMAAHCS0yM3bdu21Y4dO9S4cWNFR0fr9ddfl7e3tz744AM1adKkImoEAAAoM6fDzaRJk5Sfny9Jevnll3XvvfeqW7duqlevnhYsWODyAgEAAJzh9N1SJTl79qzq1Kljv2OqMuNuKQAAqh5nvr/L/ZwbScrIyJAk5moCAACVhtMXFF++fFkvvvii/P39FRERoYiICPn7+2vSpEm6dOlSRdQIAABQZk6P3IwZM0ZLlizR66+/rpiYGElXbg9/6aWXdObMGb3//vsuLxIAAKCsnL7mxt/fX/Pnz9fdd9/t0L5y5UoNGjRIubm5Li3Q1bjmBgCAqqdCn1BssVgUERFRrL1x48bMzA0AANzO6XAzevRoTZ06VYWFhfa2wsJCvfLKKxo9erRLiwMAAHBWma656d+/v8P6//zP/6hhw4aKjIyUJO3YsUNFRUXq0aOH6ysEAABwQpnCjb+/v8P6H//4R4d1bgUHAACVRZnCzdy5cyu6DgAAAJco90P8Tp8+bZ8os0WLFqpfv77LigIAACgvpy8ozs/P1/Dhw9WgQQPdcccduuOOOxQaGqoRI0aooKCgImoEAAAoM6fDTWJior7++mt9+eWXysnJUU5Ojj7//HN9/fXXeuaZZyqiRgAAgDJz+iF+gYGBWrx4sf7whz84tKempmrgwIE6ffq0K+tzOR7iBwBA1VOhD/ErKChQcHBwsfagoCBOSwEAALdzOtzExMQoKSlJFy9etLf9+uuvmjJlin2uKQAAAHdx+m6pGTNmqHfv3sUe4ufj46PVq1e7vEAAAABnOH3NjXTl1NSnn36qffv2SZJatWqlhx9+WL6+vi4v0NW45gYAgKrHme9vp0ZuLl26pJYtW2r58uV69NFHf1eRAAAAFcGpa26qV6/ucK0NAABAZeP0BcWjRo3Sa6+9psuXL1dEPQAAAL+L0xcU//DDD0pJSdGaNWvUrl071axZ0+H1JUuWuKw4AAAAZzkdbgICAorNCg4AAFBZOB1umCEcAABUZuWeFfzUqVMOs4IHBQW5rCgAAIDycvqC4ry8PD3yyCMKCwtTbGysYmNjFRYWpj/96U/Kzc2tiBoBAADKzOlw8+ijj2rTpk1avny5fVbw5cuXa8uWLfrzn/9cETUCAACUmdNPKK5Zs6ZWr16trl27OrR/88036t27t/Lz811aoKvxhGIAAKqeCp0VvF69evL39y/W7u/vrzp16ji7OwAAAJdyOtxMmjRJiYmJyszMtLdlZmZqwoQJevHFF11aHAAAgLOcPi3VoUMHHTp0SIWFhbrpppskScePH5fFYlGzZs0c+m7bts11lboIp6UAAKh6KmziTEnq169feesCAACocE6P3FR1jNwAAFD1VOgFxQAAAJUZ4QYAAJgK4QYAAJgK4QYAAJjK7w43VqtV6enpOnfunCvqAQAA+F2cDjfjxo3Thx9+KOlKsImNjdWtt96q8PBwrV+/3tX1AQAAOMXpcLN48WJFRkZKkr788ksdOXJE+/bt09NPP60XXnjB5QUCAAA4w+lwk52drZCQEEnSypUrNWDAADVv3lzDhw/Xrl27XF4gAACAM5wON8HBwdqzZ4+sVqtWrVqlXr16SZIKCgrk5eXl8gIBAACc4fT0C8OGDdPAgQPVoEEDeXh4qGfPnpKkTZs2qWXLli4vEAAAwBlOh5uXXnpJbdu2VUZGhgYMGCCLxSJJ8vLy0vPPP+/yAgEAAJzhkrmlcnJyFBAQ4IJyKh5zSwEAUPVU6NxSr732mhYsWGBfHzhwoOrVq6eGDRtq586dzlcLAADgQk6Hm9mzZys8PFyStHbtWq1du1ZfffWVevfurfHjx7u8QAAAAGc4fc1NZmamPdwsX75cAwcO1F133aWIiAhFR0e7vEAAAABnOD1yU6dOHWVkZEiSVq1aZb9byjAMWa1W11YHAADgJKdHbvr376/BgwerWbNmOnPmjO6++25J0vbt23XzzTe7vEAAAABnOB1u3n77bUVERCgjI0Ovv/66atWqJUk6efKknnzySZcXCAAA4AyX3ApelXArOAAAVU+F3gouSf/617/UtWtXhYaG6tixY5KkGTNm6PPPPy/P7gAAAFzG6XDz/vvvKzExUXfffbdycnLsFxEHBARoxowZrq4PAADAKU6Hm3fffVdz5szRCy+84DBRZqdOnZgVHAAAuJ3T4ebIkSPq0KFDsXaLxaL8/HyXFAUAAFBeToebxo0bKz09vVj7qlWr1KpVK1fUBAAAUG5Oh5vExESNGjVKCxYskGEY2rx5s1555RVNnDhRzz77bLmKmDVrliIiIuTj46Po6Ght3ry5TNvNnz9fHh4e6tevX7neFwAAmI/Tz7kZOXKkfH19NWnSJBUUFGjw4MEKDQ3V3/72Nz300ENOF7BgwQIlJiZq9uzZio6O1owZMxQXF6f9+/crKCio1O2OHj2q8ePHq1u3bk6/JwAAMK/f9ZybgoICXbhw4aoh5Fqio6PVuXNnzZw5U5Jks9kUHh6uMWPG6Pnnny9xG6vVqjvuuEPDhw/XN998o5ycHC1btqxM78dzbgAAqHoq9Dk3R44c0cGDByVJNWrUsAebgwcP6ujRo07tq6ioSFu3brXPTyVJnp6e6tmzp9LS0krd7uWXX1ZQUJBGjBhxzfcoLCxUXl6ewwIAAMzL6XAzdOhQbdy4sVj7pk2bNHToUKf2lZ2dLavVquDgYIf24OBgZWZmlrjNt99+qw8//FBz5swp03skJyfL39/fvvw2ozkAADAnp8PN9u3b1aVLl2Ltt912W4l3UbnS+fPn9cgjj2jOnDkKDAws0zYTJ05Ubm6uffltRnMAAGBOTl9Q7OHhofPnzxdrz83NtT+tuKwCAwPl5eWlrKwsh/asrCyFhIQU63/48GEdPXpUffv2tbfZbDZJUrVq1bR//341bdrUYRuLxSKLxeJUXQAAoOpyeuTmjjvuUHJyskOQsVqtSk5OVteuXZ3al7e3tzp27KiUlBR7m81mU0pKimJiYor1b9mypXbt2qX09HT7ct9996l79+5KT0/nlBMAAHB+5Oa1117THXfcoRYtWthvw/7mm2+Ul5endevWOV1AYmKihgwZok6dOikqKkozZsxQfn6+hg0bJklKSEhQWFiYkpOT5ePjo7Zt2zpsHxAQIEnF2gEAwI3J6XDTunVr7dy5UzNnztSOHTvk6+urhIQEjR49WnXr1nW6gPj4eJ0+fVqTJ09WZmam2rdvr1WrVtkvMj5+/Lg8Pcs1eTkAALgB/a7n3FRFPOcGAICqp0KfczN37lwtWrSoWPuiRYv0z3/+09ndAQAAuJTT4SY5ObnE27CDgoI0bdo0lxQFAABQXk6Hm+PHj6tx48bF2hs1aqTjx4+7pCgAAIDycjrcBAUFaefOncXad+zYoXr16rmkKAAAgPJyOtwMGjRITz31lFJTU2W1WmW1WrVu3TqNHTu2XLOCAwAAuJLTt4JPnTpVR48eVY8ePVSt2pXNbTabEhISuOYGAAC4XblvBT9w4ID9OTft2rVTo0aNXF1bheBWcAAAqh5nvr+dHrn5TfPmzdW8efPybg4AAFAhnA43w4cPv+rrH330UbmLAQAA+L2cDjfnzp1zWL906ZJ2796tnJwc3XnnnS4rDAAAoDycDjdLly4t1maz2fTEE0+oadOmLikKAACgvFwyI6Wnp6cSExP19ttvu2J3AAAA5eay6bYPHz6sy5cvu2p3AAAA5eL0aanExESHdcMwdPLkSa1YsUJDhgxxWWEAAADl4XS42b59u8O6p6en6tevr+nTp1/zTioAAICK5nS4SU1NrYg6AAAAXMLpa25+/fVXFRQU2NePHTumGTNmaM2aNS4tDAAAoDycDjf333+/PvnkE0lSTk6OoqKiNH36dN1///16//33XV4gAACAM5wON9u2bVO3bt0kSYsXL1ZISIiOHTumTz75RO+8847LCwQAAHCG0+GmoKBAtWvXliStWbNG/fv3l6enp2677TYdO3bM5QUCAAA4w+lwc/PNN2vZsmXKyMjQ6tWrddddd0mSTp06xSzbAADA7ZwON5MnT9b48eMVERGh6OhoxcTESLoyitOhQweXFwgAAOAMD8MwDGc3yszM1MmTJxUZGSlPzyv5aPPmzfLz81PLli1dXqQr5eXlyd/fX7m5uYw0AQBQRTjz/e30c24kKSQkRCEhIQ5tUVFR5dkVAACAS7lsbikAAIDKgHADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMhXADAABMpVKEm1mzZikiIkI+Pj6Kjo7W5s2bS+07Z84cdevWTXXq1FGdOnXUs2fPq/YHAAA3FreHmwULFigxMVFJSUnatm2bIiMjFRcXp1OnTpXYf/369Ro0aJBSU1OVlpam8PBw3XXXXTpx4sR1rhwAAFRGHoZhGO4sIDo6Wp07d9bMmTMlSTabTeHh4RozZoyef/75a25vtVpVp04dzZw5UwkJCdfsn5eXJ39/f+Xm5srPz+931w8AACqeM9/fbh25KSoq0tatW9WzZ097m6enp3r27Km0tLQy7aOgoECXLl1S3bp1K6pMAABQhVRz55tnZ2fLarUqODjYoT04OFj79u0r0z6ee+45hYaGOgSk/1ZYWKjCwkL7el5eXvkLBgAAlZ7br7n5PV599VXNnz9fS5culY+PT4l9kpOT5e/vb1/Cw8Ovc5UAAOB6cmu4CQwMlJeXl7Kyshzas7KyFBISctVt33zzTb366qtas2aNbrnlllL7TZw4Ubm5ufYlIyPDJbUDAIDKya3hxtvbWx07dlRKSoq9zWazKSUlRTExMaVu9/rrr2vq1KlatWqVOnXqdNX3sFgs8vPzc1gAAIB5ufWaG0lKTEzUkCFD1KlTJ0VFRWnGjBnKz8/XsGHDJEkJCQkKCwtTcnKyJOm1117T5MmTNW/ePEVERCgzM1OSVKtWLdWqVcttnwMAAFQObg838fHxOn36tCZPnqzMzEy1b99eq1atsl9kfPz4cXl6/meA6f3331dRUZEefPBBh/0kJSXppZdeup6lAwCASsjtz7m53njODQAAVU+Vec4NAACAqxFuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqRBuAACAqVSKcDNr1ixFRETIx8dH0dHR2rx581X7L1q0SC1btpSPj4/atWunlStXXqdKS2e1GUo7fEafp59Q2uEzstoMd5cEAMB1VVm+C6u55V3/y4IFC5SYmKjZs2crOjpaM2bMUFxcnPbv36+goKBi/Tdu3KhBgwYpOTlZ9957r+bNm6d+/fpp27Ztatu2rRs+gbRq90lN+XKPTuZetLc18PdRUt/W6t22gVtqAgDgeqpM34UehmG4dYghOjpanTt31syZMyVJNptN4eHhGjNmjJ5//vli/ePj45Wfn6/ly5fb22677Ta1b99es2fPvub75eXlyd/fX7m5ufLz8/vd9a/afVJP/L9t+r8H0eN///v+n24l4AAATO16fBc68/3t1pGboqIibd26VRMnTrS3eXp6qmfPnkpLSytxm7S0NCUmJjq0xcXFadmyZRVZaomsNkNTvtxT7C9Tkgxd+Ut96Ys96nJzoLw8PeTp4SGf6l72PgVFl0vd9+/p+2uRVUaJVUke8pCvd/n6Xrxkle0qWbiGdzW39/Wt7iUPjyv/nAovW686JOpMX59qXvL0vNK36LJNl202l/S1VPOSVzn6XrLadMlael9vL09V8/J0uu9lq01FV+lb3ctT1cvR12ozVHjZWmrfap6e8q7mfF+bzdBFF/X18vSQpdqVn3fDMPTrJdf0vV7/7vkdUba+/I64wpW/I6w2Q0lf/HjV78IpX+5Rr9Yh9voqmlvDTXZ2tqxWq4KDgx3ag4ODtW/fvhK3yczMLLF/ZmZmif0LCwtVWFhoX8/NzZV0JQH+Xpt/OqsTp85etc8vpwvUZuIySVK3ZvX0/p862V/r9Ne1unip5B+oTo3q6OPhUfb1bq+t07mCSyX2bRPqpwV/jrGv93rra4dhwf/WtH5NfT66q339/pnf6vDp/BL7NvD30drEWPt6/N/T9OMvJR+3OjWq65vn7rSvD/1os7YcO1diX5/qntoyqZd9/Yn/t0XfHDxTYl9J2j0lzv7nxAXbtWbPqVL7bn6hh/0X3V+W7NIXO34pte+GCX9Q3VoWSdJfl+/R/B8ySu27amw3NaxbQ5L05pr9+vi7o6X2XTbqdt0cVFuSNGvdIb3/9eFS+372aLTaNQyQJH307U96a+3BUvt+NKSzoprUvbLd5mN6ZUXJ/0YkadbDHRTb/Mpp3aXbftaLn/9Yat/pAyIV1zZEkrR6d6aeWbSj1L5T72+jB25tKEn6+sApjfp0e6l9X+jTUoOiGkm68m9l+D9/KLVvYq9mGt61iSRp1885GjRnU6l9n4htqlF33ixJOnTqvPrN2lhq36FdIjT+rhaSpJ/PFqj3374pte9DncM16d7WkqSzFwp1xxvrS+17X2SopvVvJ+lKqIh6JaXUvne1DtJb8R3s622TVpfal98RV/A74j+q2u+I0pw4VaDUncfs9ZXHb9/bZTrhZLjRiRMnDEnGxo0bHdonTJhgREVFlbhN9erVjXnz5jm0zZo1ywgKCiqxf1JSkqEr4ZGFhYWFhYWlii8ZGRnXzBduHbkJDAyUl5eXsrKyHNqzsrIUEhJS4jYhISFO9Z84caLDaSybzaazZ8+qXr169uFGV8nLy1N4eLgyMjJccj0PSsZxvj44ztcHx/n64VhfHxV1nA3D0Pnz5xUaGnrNvm4NN97e3urYsaNSUlLUr18/SVfCR0pKikaPHl3iNjExMUpJSdG4cePsbWvXrlVMTEyJ/S0WiywWi0NbQECAK8ovlZ+fH/9wrgOO8/XBcb4+OM7XD8f6+qiI4+zv71+mfm6/FTwxMVFDhgxRp06dFBUVpRkzZig/P1/Dhg2TJCUkJCgsLEzJycmSpLFjxyo2NlbTp09Xnz59NH/+fG3ZskUffPCBOz8GAACoJNwebuLj43X69GlNnjxZmZmZat++vVatWmW/aPj48ePy9PzPswZvv/12zZs3T5MmTdJf/vIXNWvWTMuWLXPbM24AAEDl4vZwI0mjR48u9TTU+vXri7UNGDBAAwYMqOCqnGexWJSUlFTsNBhci+N8fXCcrw+O8/XDsb4+KsNxdvtD/AAAAFypUswtBQAA4CqEGwAAYCqEGwAAYCqEGwAAYCqEmzLasGGD+vbtq9DQUHl4eJRpos7169fr1ltvlcVi0c0336yPP/64wus0A2eP9ZIlS9SrVy/Vr19ffn5+iomJ0erVpc/fgyvK8zP9m++++07VqlVT+/btK6w+syjPcS4sLNQLL7ygRo0ayWKxKCIiQh999FHFF1uFlec4f/rpp4qMjFSNGjXUoEEDDR8+XGfOlD6HFaTk5GR17txZtWvXVlBQkPr166f9+/dfc7tFixapZcuW8vHxUbt27bRy5coKrZNwU0b5+fmKjIzUrFmzytT/yJEj6tOnj7p376709HSNGzdOI0eO5Eu3DJw91hs2bFCvXr20cuVKbd26Vd27d1ffvn21ffv2Cq60anP2OP8mJydHCQkJ6tGjRwVVZi7lOc4DBw5USkqKPvzwQ+3fv1+fffaZWrRoUYFVVn3OHufvvvtOCQkJGjFihH788UctWrRImzdv1qOPPlrBlVZtX3/9tUaNGqXvv/9ea9eu1aVLl3TXXXcpP7/kyVUlaePGjRo0aJBGjBih7du3q1+/furXr592795dcYWWZYJLOJJkLF269Kp9nn32WaNNmzYObfHx8UZcXFwFVmY+ZTnWJWndurUxZcoU1xdkUs4c5/j4eGPSpElGUlKSERkZWaF1mU1ZjvNXX31l+Pv7G2fOnLk+RZlQWY7zG2+8YTRp0sSh7Z133jHCwsIqsDLzOXXqlCHJ+Prrr0vtM3DgQKNPnz4ObdHR0caf//znCquLkZsKkpaWpp49ezq0xcXFKS0tzU0V3ThsNpvOnz+vunXrursU05k7d65++uknJSUlubsU0/riiy/UqVMnvf766woLC1Pz5s01fvx4/frrr+4uzVRiYmKUkZGhlStXyjAMZWVlafHixbrnnnvcXVqVkpubK0lX/X3rju/DSvGEYjPKzMy0TyHxm+DgYOXl5enXX3+Vr6+vmyozvzfffFMXLlzQwIED3V2KqRw8eFDPP/+8vvnmG1Wrxq+OivLTTz/p22+/lY+Pj5YuXars7Gw9+eSTOnPmjObOnevu8kyjS5cu+vTTTxUfH6+LFy/q8uXL6tu3r9OnaW9kNptN48aNU5cuXa46BVJp34eZmZkVVhsjNzCVefPmacqUKVq4cKGCgoLcXY5pWK1WDR48WFOmTFHz5s3dXY6p2Ww2eXh46NNPP1VUVJTuuecevfXWW/rnP//J6I0L7dmzR2PHjtXkyZO1detWrVq1SkePHtXjjz/u7tKqjFGjRmn37t2aP3++u0sphv/9qiAhISHKyspyaMvKypKfnx+jNhVk/vz5GjlypBYtWlRsCBS/z/nz57VlyxZt377dPg+czWaTYRiqVq2a1qxZozvvvNPNVZpDgwYNFBYWJn9/f3tbq1atZBiGfv75ZzVr1syN1ZlHcnKyunTpogkTJkiSbrnlFtWsWVPdunXTX//6VzVo0MDNFVZuo0eP1vLly7VhwwY1bNjwqn1L+z4MCQmpsPoYuakgMTExSklJcWhbu3atYmJi3FSRuX322WcaNmyYPvvsM/Xp08fd5ZiOn5+fdu3apfT0dPvy+OOPq0WLFkpPT1d0dLS7SzSNLl266JdfftGFCxfsbQcOHJCnp+c1v0RQdgUFBfL0dPwK9PLykiQZTLlYKsMwNHr0aC1dulTr1q1T48aNr7mNO74PGbkpowsXLujQoUP29SNHjig9PV1169bVTTfdpIkTJ+rEiRP65JNPJEmPP/64Zs6cqWeffVbDhw/XunXrtHDhQq1YscJdH6HKcPZYz5s3T0OGDNHf/vY3RUdH28/j+vr6OvzfLxw5c5w9PT2LnVMPCgqSj4/PVc+1w/mf58GDB2vq1KkaNmyYpkyZouzsbE2YMEHDhw9n1PcqnD3Offv21aOPPqr3339fcXFxOnnypMaNG6eoqCiFhoa662NUeqNGjdK8efP0+eefq3bt2vbft/7+/vafz4SEBIWFhSk5OVmSNHbsWMXGxmr69Onq06eP5s+fry1btuiDDz6ouEIr7D4sk0lNTTUkFVuGDBliGIZhDBkyxIiNjS22Tfv27Q1vb2+jSZMmxty5c6973VWRs8c6Njb2qv1RsvL8TP83bgUvm/Ic57179xo9e/Y0fH19jYYNGxqJiYlGQUHB9S++CinPcX7nnXeM1q1bG76+vkaDBg2Mhx9+2Pj555+vf/FVSEnHWJLD91tsbGyx378LFy40mjdvbnh7extt2rQxVqxYUaF1evxvsQAAAKbANTcAAMBUCDcAAMBUCDcAAMBUCDcAAMBUCDcAAMBUCDcAAMBUCDcAAMBUCDcAKq0//OEPGjduXIW/j4eHh5YtW1bh7wPg+iDcALhhvPTSS2rfvr27ywBQwQg3AADAVAg3ACqF/Px8JSQkqFatWmrQoIGmT5/u8HphYaHGjx+vsLAw1axZU9HR0Vq/fr399Y8//lgBAQFatmyZmjVrJh8fH8XFxSkjI8P++pQpU7Rjxw55eHjIw8NDH3/8sX377OxsPfDAA6pRo4aaNWumL7744np8bAAVgHADoFKYMGGCvv76a33++edas2aN1q9fr23bttlfHz16tNLS0jR//nzt3LlTAwYMUO/evXXw4EF7n4KCAr3yyiv65JNP9N133yknJ0cPPfSQJCk+Pl7PPPOM2rRpo5MnT+rkyZOKj4+3bztlyhQNHDhQO3fu1D333KOHH35YZ8+evX4HAIDrVOi0nABQBufPnze8vb2NhQsX2tvOnDlj+Pr6GmPHjjWOHTtmeHl5GSdOnHDYrkePHsbEiRMNwzCMuXPnGpKM77//3v763r17DUnGpk2bDMMofSZzScakSZPs6xcuXDAkGV999ZUrPyaA66Sae6MVAEiHDx9WUVGRoqOj7W1169ZVixYtJEm7du2S1WpV8+bNHbYrLCxUvXr17OvVqlVT586d7estW7ZUQECA9u7dq6ioqKvWcMstt9j/XLNmTfn5+enUqVO/63MBcA/CDYBK78KFC/Ly8tLWrVvl5eXl8FqtWrVc8h7Vq1d3WPfw8JDNZnPJvgFcX1xzA8DtmjZtqurVq2vTpk32tnPnzunAgQOSpA4dOshqterUqVO6+eabHZaQkBD7NpcvX9aWLVvs6/v371dOTo5atWolSfL29pbVar1OnwqAuxBuALhdrVq1NGLECE2YMEHr1q3T7t27NXToUHl6XvkV1bx5cz388MNKSEjQkiVLdOTIEW3evFnJyclasWKFfT/Vq1fXmDFjtGnTJm3dulVDhw7VbbfdZj8lFRERoSNHjig9PV3Z2dkqLCx0y+cFULEINwAqhTfeeEPdunVT37591bNnT3Xt2lUdO3a0vz537lwlJCTomWeeUYsWLdSvXz/98MMPuummm+x9atSooeeee06DBw9Wly5dVKtWLS1YsMD++h//+Ef17t1b3bt3V/369fXZZ59d188I4PrwMAzDcHcRAPB7ffzxxxo3bpxycnLcXQoAN2PkBgAAmArhBgAAmAqnpQAAgKkwcgMAAEyFcAMAAEyFcAMAAEyFcAMAAEyFcAMAAEyFcAMAAEyFcAMAAEyFcAMAAEyFcAMAAEzl/wMkNy9fIHc8wAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sp=np.zeros(maxdepth)\n", + "for i in tqdm(range(maxdepth)):\n", + " sp[i]=qaoaec.successProbability(qaoaec.angles_hist['d'+str(i+1)+'_final'], qasm_sim,1024)\n", + "pl.plot(np.arange(1,maxdepth+1), sp,'o--')\n", + "pl.hlines(1, 1,maxdepth, linestyles=\"solid\", colors=\"black\")\n", + "pl.ylim(0,1.01)\n", + "_=pl.title('Success rate')\n", + "_=pl.ylabel('success probability')\n", + "_=pl.xlabel('depth')" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "1ed37e8a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pl.plot(np.arange(1,maxdepth+1),qaoaec.angles_hist['d'+str(maxdepth)+'_final'][::2],\"x-\",label='gamma')\n", + "pl.plot(np.arange(1,maxdepth+1),qaoaec.angles_hist['d'+str(maxdepth)+'_final'][1::2],\"o-\",label='beta')\n", + "\n", + "_=pl.title('Parameters')\n", + "_=pl.ylabel('parameter')\n", + "_=pl.xlabel('depth')\n", + "_=pl.legend()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b781c7c4", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "291bca4d", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bde1dbfc", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ca8f3a6d", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a7049786", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/ExactCover/ExactCover 4 2.ipynb b/ExactCover/ExactCover 4 2.ipynb new file mode 100644 index 0000000..6865569 --- /dev/null +++ b/ExactCover/ExactCover 4 2.ipynb @@ -0,0 +1,735 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "04beb305", + "metadata": {}, + "source": [ + "run ```pip install openquantumcomputing``` as a user or ```pip install -e .``` in the [OpenQuantumComputing](https://github.com/OpenQuantumComputing/OpenQuantumComputing) folder as developer" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "a25b06d2", + "metadata": {}, + "outputs": [], + "source": [ + "from openquantumcomputing.QAOAExactCover import QAOAExactCover\n", + "from tailassignment_loader import *\n", + "\n", + "from qiskit import *\n", + "import numpy as np\n", + "import matplotlib.pyplot as pl\n", + "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", + "from qiskit.visualization import *\n", + "from tqdm import tqdm" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "5a113cdc", + "metadata": {}, + "outputs": [], + "source": [ + "instances = 4\n", + "flights = 3\n", + "solutions = 2\n", + "\n", + "path_to_examples = \"tailassignment_samples/\"\n", + "\n", + "FR, CR, best_sol = load_FR_CR(path_to_examples + f'FRCR_{instances}_{flights}_{solutions}.txt')" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "ba34f8b6", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "params={'FR': FR}\n", + "params['CR']= CR\n", + "params['usebarrier']=True\n", + "qaoaec = QAOAExactCover(params=params)\n", + "qaoaec.createCircuit(np.array((np.pi,2*np.pi)),1).draw(output='mpl')" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "218ddc52", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[1. 0. 1. 0.]\n", + " [1. 0. 0. 1.]\n", + " [0. 1. 0. 0.]]\n", + "[0.5 0.1 0.1 0.1]\n", + "solutions:\n", + "0111 0.30000000000000004\n", + "1100 0.6\n" + ] + } + ], + "source": [ + "import itertools\n", + "print(FR)\n", + "print(CR)\n", + "nL=FR.shape[1]\n", + "print(\"solutions:\")\n", + "costs=[]\n", + "for s in [''.join(i) for i in itertools.product('01', repeat =nL)]:\n", + " costs.append(-qaoaec.cost(s))\n", + " if qaoaec.isFeasible(s):\n", + " print(s, -qaoaec.cost(s))" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "955d4d06", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "max_val=max(costs)\n", + "\n", + "pl.figure(figsize=(25,10))\n", + "a=pl.hist(np.sort(costs), bins=100)\n", + "min_ylim, max_ylim = pl.ylim()\n", + "max_ylim *=1.025\n", + "mean=np.mean(costs)\n", + "pl.axvline(mean, color='k', linestyle='dashed', linewidth=2)\n", + "a=pl.text(mean-1, max_ylim, 'mean = {:.2f}'.format(mean))\n", + "a=pl.xticks(np.arange(0, max_val, step=1))" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "a4fcccfa", + "metadata": {}, + "outputs": [], + "source": [ + "qasm_sim = Aer.get_backend('qasm_simulator')" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "383c5700", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Calculating Energy landscape for depth p=1...\n", + "Calculating Energy landscape done\n" + ] + } + ], + "source": [ + "qaoaec.sample_cost_landscape(qasm_sim, 1024, angles={\"gamma\": [0,2*np.pi,30], \"beta\": [0,np.pi,20]})" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "fbd00aaf", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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hMHJuV7eeffbZuPjii/Gzn/0Mu+++u09fvnw5HnzwQb+9YcMGLF/e8pkbHh4pgaJTynvsMmBpdTQo0nBYiWeZsMW0XaVbIoWE1poyR7bNozWTkmCzaK/1/xS227QQdOHuxDwwSTqHphTyLI1AlJQNCRjX0a4N5TBYY4sXO01CJUBpO7enz+ulDMnULVHCThWIqf3U2h1XkvfaYvixAIbzIFQ6Cc0qJJ988kn8y7/8C/bZZx8AwC233ILdd98du+22W1DutNNOwzHHHIP3ve992HPPPXHttdfizDPP7NZpm/XjysATAbJ0LlEDnAJFI0AycDoKgBd5aayOynVWzqa8Ra2N0gtVCvEVVh1HkZMj2Fs0jWLjjQC4DrTWNO1JXqXqabI6krFtQ67ceM27lPpAnB+AMuVNjulF5gCp52egmLJrksApCZW22S9he6LBl7ZzovwmkGjrLN5IzaRmFZJPPfUUTj/9dDzzzDMYDAZ40YtehNtuuw3GGKxatQorV67EypUrsf/+++Oqq67C0UcfDQA47rjjcNFFFxX3E69mrUHZxpsEK5sLgZaET4NyChjduCPUTXmVQVY0oCqeaUImMVKoIcpWC5gEUM7QNWWFr0Gy11oT2ZDco+C5R0uA2PRr3DZJ83Ulj5Jul3jcmkcZVCXt+qkGfpGk6pP8mQqh5cKfwmBshDTXThvIBH0mbUxlZpTyINt6yqVe8UzaJm2zrIXiSS6435OcXrIE+13xHgDsXGLQsab+HGxbBLAzzIuUAJkIlRZ7jAoYJc9ShKECQZOAoxryTEjyLsc5ezQodrFNUqm9vFxyn6KyJNzKylBoWgpAms/BmBgMAehQ5NsiYKgNiT6kNoS0IOQq2q83neq32Htk+5CFqmhHwsau0u5tUpARPchyj7qtsnO3JR4t0fo/vwpbf/mk395z72l8/d69uxlH9P8dZbFp06ax2xlHC/KNO2OrZH4oBUghvSsY/WYwODLYknw5rTssQ4BYkl5SPpbW38x4kVVfeTDaFkDVExw0fIoPY4Zeo60hZQzZNnW5IHTZwuWJyma8x5RH2ValA3UpGHmbpXBk/4eRA+VzQp3v1bR6BZ5hsffcoq8SiV55Iq/Ejucx1c4IUeO/JH1cLWhITuL6bxpjDfN0yeOk4BoXjgyCHIopIIZpsleqqi6vXovjvJZDsGkmVAJAKaBSVo+U9YvEqhPP0PQaghb1/tomzziP0tgQmCnxcDt16izNZ96eqTvocsg1L1LIz3rEiHZBbaMIjhyMuYF9zP2XlDyNWz7u0ToEK5VtKX6c1ZuPgj4sgFE/Jzn/VbyKXPQUM5W0UG4GkF3gWApGNZ2YOlCAmZPmIU7ixVODFna0kbtIo0VJLE2ci7SGlUHQlvVtN2UbgDbAM+5OLQXLunzjXRJgKkp53i7Pw1JaYCNtBwdA324VZm27gEaCgARHPnALtmiDfNIeTW284KBeOq0zLNvYkLFJ816z0MzY9bydhCe5dQJtjKcFDUlNM3KDI0CzCJAtPMc2cHTtDVhZ/rkqI+/SiF7MwlVorcHUDACuq2fJQU5tkyDPIRrwQ4BhuG0DcDrQhsB04VfyeyDWVCtDKSxdWJgtM80+UJM6Tt6eRP0SQObgSD8rcJwYGFlfgddIL5uU59Nl0UvpjURJm8q+52Co5WftL7QlCcQMJI2N7bAwGGGQMW770K8lJCemaF6IfDRheltAlniPbeDo/h8ENqavsKkghCcM2In6o9zFCx3OnWWs2q8DGdWUkBaFiJLHiJYNgWwC18bAgnzXbu7SWBiyjliD5YyK768wEGbhGNTLzK9FbRe0kfEa0wO66bxCM7JPK9/Fw8sBtgSeOZhqEiAXpLNjmvPIjXInNhlPcu61YCE5Z+Fwepa68Jrfrv+bBUBqcKRgbBXmNLbVHMPUHBx/a03SK5aeBeVhV35M6D5bhB5m+BlNeFVMMz786ecq4bZdXtWJB3qKldJ+lngVNjEfSYEEAkdtcFY8NNHjaAtGZk+J1yiCMQUdbmMmvTT0mVKq/xSMUn23Dvdm+pW9cdv6GI4WyCMgCxKS0VjOvLi5lDSXJD3KoZWRwqaSB0nzOSDbzku6AX2m5g67SAJ26oUIFJ7O24xDqjaqOyA3B3QKT/JMuS3Zlb5Be5BB6Qp2UPCISZRJ8qIBUU6PP2e8xhQASH0VaEJ7qtfI5yv5JZUDD1XiNC8BZfFlIrRV7EnmIJ7rT2vbEs+QH2/BPq1tC+B5uzDwsjD2YibkBqwJSH3soaCODNXy/sYFJC+XG/hnSymPz4lDsKkbz7dOer9m/DipA3wdyuUDoAMJ/UzzUMOxCxiVsjGgEnVLwRilmYRHSfdNsJWpyMuT2mhx79jFk9T67gJ5NVQa3HDEn9scx7pkPye5kGSsfsPtJUGzEKQ8rFeiLnUkjewMzP0VSLN9puBBPb5xRW3k4VaebxmUrDVKmqsQt0fLgtQRC6pGU5sAcOAlACnCkdnban5RgGobKGrl1XAqH9QTA3oxcIRyrWGVUqr9VH8a5FLtB+XlMrkbi+yx5N3bfk5y+1GXM7gQfnJdE/bJ2qrmqMKsFBBpeZ4WzIuRbpoVlnzerALJgKVld6kDfGbT49TgKK9o1cuMC0f3f5wGgOT7NrnXxwEZDdzafgplKBBL4ShBKDgATVKreUXyfxsohunyPCMf3JODeQKeuX3L1YnqlSq7/zZMV+zjKvIylWOUO14RmJW+Rrb3JBemJEB2TUsBs84Lqrg0BkH3OAEFHy0D1CFDNIP7wKVZgxEsBqQ9X6ZlmLGLpzbpecycDZMGIy2TAiNP555jJzhy75CL72sADMWTBGBGAhxLF7sIQE4BtaunqJWJ0mla4aCf2q8UDNt6U0mJ7TdALJ6blLY1u1JQF/axFaAFbvae5PagCQzQxhpEv68Xwc+ttmi2Lcir6Cxga8hVnxE+NF7X8Q+eJ0DJDHFWRvs8siaYERjVZQekbJsXAXT1DIfCophJSH25gdBN/G7WMo/RCpDKeoyADMY6vRSMonfIDY0MF7xIWsYS75HDkQNHahfKIMmBKOVZJY20XwRFrU3Eacm5ykS7Ul66bMdzuyvUU7AT8nNlAvuVvkq8V9ZjPyc578XPCm2MtyQvEyot8x6b7epXIOo2BVBWZoWgpKZaUqppXNqZ5mH2Zn8thrZ6HH2ABrZDS4Bl9UcmgPSzjrmVnXGFpvy4c6SaXSkYVvXSniL9nPIW20AxLNcSiupde8KD5PVzYIQrE9dPelWiXZDrBdAaA4hCn+JgngNjps/S0GcJnHKP6pTcALQFlgjtFFhT9kRlw4ZcnrSbwz7cOo81Ca8lB0jBe/TbFlVh5xEyUFa5ljRbD5QEXiDdcVi6Z++kt7wYwzxQNOe7qecjaYh2mDlUusemk04LsTp48j7bvWQ9n8dtawtE9znlKZYAMWhTg2IKiNwTFD8LwPSDadprNCS9Kh+3Aegh06gO+V/0EtsCUQRAvo2cV1YGTgGIhZAqknIM03ODVq+bsCftRfI8K+elICvIAtjah1sXllykE0AIxBpyDcBInttGnSaBEhXkDPMGKSzpS62Nmy5yEIRLJ+/yDAApAxMAeeFAA8URzc/N70lpBWFXCqkAgNaId5wl85bq4hwpTZlzrLb1MhOZUxQApwJRgl0qjysaRE2YlgIj4jxAB2KZh1cwrynBJjUAp4DM28/1lcxvru9W3qdgf6lSwO86P5mCnpyfqy/ZLSQKScNZCrc+++yzOPPMM/HP//zP2HHHHbF06VJcc801OPDAA4NyGzZswAEHHIBDDjnEp61btw4HHHBAsv1fD0i2Ce/RkCsBoqnnGcWFORIomQH0ZdPuJ5Ic7MIHyJt2ODD9rlhvVG1mY3PFQwdCU3uWMjQDC42+iKftz2KFnqEDtF5GexF5qg8pPf6FDhmWreYSC0Om0iMeEfBK83gZ9ll92F+BXwqMRqgflOfpxNaJAbEQhEG+1l/9f96bLIdi1nvldgniMznxPlixfxnuTUPtgMnzy2Dny7dYxGBhZtWTvPDCC3HSSSfBGIOPf/zjWLVqFe68886o3M4774z77ruvVdsLG5LSuFMKTALI6DNtm4MyzBQNKgFmVdxdHWSAJ5s2ALrxVaswKwVnCCH5h5l178vbLKgMlGlISjaU9JOzU/Mii+YQGUidV9bka6Bq6RGKg34CpkJfKiRqOzm0DP2cBFoLGKbShbQyz1Soz9JlLyxuuysUk2WRAA0/33k+3y/WPgViqScpLcDxeRLgUkBsvRgpLj9bj4C84AUvwMknn+y3jzzySFx99dUTa39hQlKLTmljcH1S+5Cr5E1aNGFXCZS+sGCIhyJJroFoWVvB7wJye2lzHCymAaiHpwROILjKuFdZ9KgBdDhyBbBM9BuVzfRVYmfgPbIyyblDycMMYJIBZGAEN6AFBEmb4sAoAYfPAVpyOdABmENxgnOHOWBJdXMeZFCmyDYZijmv07cpfrbZfS9Rej+saq84J0nhl4K3eL20sbqdLOZuTvJjH/sYTjnlFDHvV7/6FY444ggMh0O8/vWvx7vf/W5MTaXtnFVIznTsWFOx9xhVROPZaaAEdFhaIU/yFAFPR59iSMMSPAJ3sMlv9rVZuOPa4qtfs9I8sagcty3eSPXdxrmPEzM2WpoXh0mDOikYSiCMBlchL/m5KZ+ChAzIhBdJy1Iogm4n3lqTSiNKgq4Uhok+kuFCAYZqfzkIqnm2vE4bSeHSXP8jxPtM6vHP8bGTjdRsbz1mCu0MO7+RpdGWLVuwbNkyv7169WqsXr1aLb9mzRqsX78e3/jGN6K8vffeGz/+8Y+xdOlS/PznP8cb3/hG/Mmf/Akuu+yypA2z7knOZOzYqegLVspE3qQCSgCw0pnh6npjeOOssOIt5tJskM7aqc98S8FoiLUmqKwrutDkOtL1F70liNgl7XdqhavotYp3xgmPU4Ob5BXmQKgM9NnnCYVtGY6F8FRtdPtBt4WwqwRPwd6xYVgCFxGSMgxKPcqUTXGeAFv1s5X7LJAG/sDzHTV5kfcY7YsAXCB6TqotyKP7fkmpZ7mswdbR+HjZaaedsGnTpqKyV199NW6++WbccccdeOELXxjl77DDDli6dCkAYLfddsN5552HL37xi/MLkjMdOy6W9N3aJj0Apc+UmhFgSdop6rjo5DX6WS5CttkRG6WV9KfYVggmXzSyWb8pKL6GRRsydomDcQsQsjqSd+LTNZtKAErbSuRnQ6+Knclt2q4Ah4nAMAMmdd+09ML+Iu9Ma7sEimofBWewUIQC0bcjwpyBmUBQP2ZChzkz+c0rABstKKj/Tzw/ZjG7P5W1du1a3HjjjbjjjjuwZMkSsczjjz+OXXfdFYsWLcJzzz2Hm2++GYcddli27Tmdk5x07Nhr3PAqmhMv8iql7iwDkHRuJuqXyYgftSJBAodV7vgkBvh2StRrHaMiKrVHHTykMGrTbj4MmZgn5J8hHIUOIAhtSHiaCryKvaoC0LQrY+U6mbRiz1Hah1S/JXYInmIyDMrslZR9EbkGZcADMQnmFBzbvFoLAH1ywxoTtkenixAmc20dzc6c5KZNm/DOd74T+++/P44//ngAldd477334j3veQ/22WcfXHzxxbj77rvxnve8B1NTU9i2bRtOOOEEvPvd7862P2eQnFTseO3atVi7dq3fHj333HiGuROAw1J6OJJANagrSH5CcIJKhG1FpvA06cTnFbX9Sw0QKtA7HI9UP1JeMBAqYMlBkA9MvG1tMNfs4gAVbOwCjShf6icFRAWuPK3UKyz1JsU8ZR/ltKbfIo/S1282kv1b1oc0NyjU51LvCQuAKHu/9UawcCfsRD4fpQtdn9cPsgahDZGHSduAmbXnJJctWwar3IS8//3v959PPfVUnHrqqa3bnxNITjJ2zCdypxVXu7XoMWfRzgCY/LsJCqZBkHSmMnemYUNC9cDxVDxKsd+wMW0ORa6btytSW6+2MF+1u3TBi0tToUDbzhwzzdYMKJKeFlN2nk4DorKv8hxfNxDmIJROkwCht5/yBqP6kPLYPmrzg0JfYttUwvsU1X3mIBZgqEGftxe0K4gPU806BuPbtQbAMCxgaCdC05P66bq51qxDciZjx61UCiEhvOBPTnFuMwFQIa0dhIQOlatSXpvTIUwp9Nsa7pO4Vkq+L2lgkPJLBvXSZwQ12xL25uoWzcvxuoUQKYOlAMOWICwLb8qDbAlAs6HRqH4MW5+Xe4wiOlbkMQ3u+Sl9RG1SaUAUvV3tmJEN5eXG0nVbPYlGMgbNfLy/7KmTwMGZUP9aug6a6dhxkUrhWFK+dCCUyrZcyJHoqaSQXjQHFl5GsWmcKcZilfaRuhEpgV8OpkxdIgK57zw16E4WljYPQyEt60UCIpjKw6g0LQahvM3gLswXFi1mSYGYQlHpV+2His8TprxD6aYit3q18GUAQT1j/GIcD88amrZ5gwlKAlPVoeo9ydaa6dhxUpMe3JMDY8LzkgaERF5UP2dLl/MyMejGF1/cwYwcwzHKZ+cGkwO7UoaW6/rdpOzMtZ0DpdSXBg8NdhlYZqHUAvbZUGUOhM4maXUo7avkuxLGJNFTpH3w/gTvT2wv1bcGWclblfrSwJhauEOnDa1FE0qtr/OhDYFZ25maj3TqPcn5rMzAVTxnFOTpJ0XJnX2XsF/U9iQBJdkjbCfDSKUAaNP3mCr5bruGDNV2Mv1pykNSHkDVNpT+S/ZX/yyAsPimohCAkb02TiuEoRqGBZK//Zadp6T9MiCKoVDWhtwnK6A+1mHlz4AKwOLXyg058Kz7bT0VmFVa3b76rKTpPcntTUV33kAZiFIXlJSegWGTng4FFtmSUslA27FMZ2B0vaFp0Y56zBKDdR6Q7QbEUpu63pTk2g3y1JsCG+ZpnwEZQtp5mgG/NCco3iAkQKzOEbLjkYSHVlaCYioUSuzQJI9HCgwFEKb3o93JGC10H9UpA7ePBJgWCJa8DsPj4NsAsK33JOevWg/YLcOjgAJD8rkEiFKZbD3en6C2IcCJzo8JZVLpnbz6XN1UO7kBu+X+d/WE28IlyiuRNujz/lQwxsCRj49+w1C0KEbMd2k2TpM8Lm6L9j07pUKQqQUztJ8Sz6+gD82m+Lh2bDclshDHbbt+PSyBBph6x1HKsPcktxOpg3ABGCUozhQQtbaEtBKIR+WotHIl+ya1WwjKnPc1bvgy21YSmIm0VHob5Y5Jro+u/fL2IkgmYGiFkKvyAH3y+y0FIJBdMdrlucE285F62/w42fB/p8KH9+VFRB3AyJXrn89DeoMIMCksjQnbzAITgAW2zdLLBGZaCxOS44CRfNYeHE8DL/PWFg2SiMvw8lLfubBg0C7kMjrk4wF8LK8yVV75zsb1npJtSQNhlJ5vf6x5YRXK4zQaKxvepd85haGQTsvLbYcJ2rxg1ivVvp8SECbmc5OhSm3VqATEUaK9Nt9fW093XPG2HTQJIFVYFtpmMbuvpZtJLUxIOinufis4SoNJALHE21kyUNTu3OM7+Yw9wra0f6XPpXUJ+XbJG2thiqZM+Rz0UqAaaz64xJ42gzk3JbPaMBsS5ZCKznMb25t6OF7rS7zxygNQbLvDM4OtPMocEFMLako07qKbllLPkRHUVa7hfGRjV351q+k9yXmtScORA0v4zT61LFh+0I68rbUrw5IMaso+Fs85Fm/rcMuGKKU0QB1kJhnaTLaZA5RQp80vtavSBnelz6aw3FBq8FLbj77nxMPy0jmQsXcsL1Bot3hVqNiWYGRuYcykFtSUaNz6hd9/dJ4UgpK2lQNlv7p1O1NqzlF9HZkARxWMAhRpftZTzKRXbdm0l0n3KQUlJa3ta8dSA1J5/zpwqcYGUskArpVT645lEWk/McinqkkvYCoZlxKLYdLnQwIQicG9JAxaujpUvsFJgLAUZC3aUAE6KXVZfCPV7fJ+5EnURfXVbrOz8+7WmdavDSS9+F0pTdfAx+CYAmOxRyjAMAnFEtByO8DaSuZLbcUDp7QdtE/LpZb22zgvaHsSKh24qUpDiONIaK/IMxPf0WtYfhvKCv1TOJY+D5jpdizPrzSv7crQtqtLJ7Ggpq20x0j4s4kaGOkcY04pnvEXoBcCtPckt3fxQVqDkDV+zkYEJTIQ08ALqU0BihpMeX009X1/QNw/4sFOzhPAqj3QLR1PrR8guYR/kmrzTFxRHWDyCyqE/jQoR2OOMeShblouPziJXqEGQ+n7buPpecMyoGlxbNXvqUMfrYGaeQZyxkX7l4AZ/eK5kEZFARncdDWfo3OqwEnsITmf5a7U3K9wAIHnhnq7gqLgPY4ScGSfy4GpgFFIiwAmATP6rICQD3xuv2n7aMoFbfJ2gVbPruWW609arQZunz4jpgSSn9/TOzYDPmi5A4rqFxrYrzNop7/qvVlaxirfaQYgVG0Wpkzi+88AsZt32WJ/cxozhClqZMtASbNpngRIDY4cjMmfyurDrduHCCzd7yYni/q/BpB+5Z8GrRFEiKWB2RKMQh1qMx3AkjB0n7Wl/VJbQH7xhga/CXgmMyH1PJiNEFquLwksbqwhP1Vk6v8BBkMyYBrIXmVR+NN/V/Q7SrTBy0qayeM7Ex7iJEKs2nwhzyvpR12dKoBSqVcKSF+uwMusE8JN27+Wbn7LfTcl57QAKRGQbgn4KM4v8yRtlC5CNgHG8H8CoAieVvYMC2CoepldAZh7ADs38DKVzodIKg7RdWpcmjAsaLekDPsdPz6QGaAZzEbhQGZSF4E25yZ9J7nFKgWh0nFWfrZ+xAVoD8WSOlpaZBBZGUq327bD25PEAamUFQGZg2OUr/QvpG8b9Z7k/JeLSBkbfrsW8RoHDxpDPEp42EhgTHmZPGRZ6jWaURqMWSiyNBGI7JcNVBgGIO4OwWigZYBsM3hq3lFR3UlBctywWYnHJfXB4UgHspHLt6RM2X61fdxhxsKlCRUf8bkEIy/PvUjtvBnnfEoBUvIgS+CogTEK9+uqhpnek5y38m+qt2hAmazQVIxgSL0xkqZ5gbnQqAjAUVgn9FBjMBZBkQJuZHUgEs8wAB1tVwKhBjr6v5TH4NplcDXjDCpdQDnJwS3VTy4c5+FYp4/0gc4I9bJ2zMQcXqm0cCH3yErVNpTaIs0o+2hbzg12hqN0rCYMRwpGX4Z2W2D7sJ+TXBgytvlfWyhjRjogQ2/SivVbeY4evJYBMwSjGD4lnqK8yMfKHqIGxBzwUnkSDFld0xaUwoUZDUxSNW3gHiPcVdJvsrmWMPH9BV5j/X+d528eaH5Vu0VHHUE4jidpTNzmQIBjbmAex9aZ8I5Tc3htwqcl7bPtseA4IGUMwrwS+2v1nuRCUAAxQz4zkPHPEiCj+Ty5Le4RxuHbQjhqYKTAY2DkYVMHRc1DlKFH22eQGwlp1oYwlOq0ERtADJ+vc8oNcG36FUJaPsLQ1hso9WSjN5yEA24SmpLNbdX2xqILUFLzdq5/uh/SMUr1W7oyVUtX2i+6QdIAGT1KkWmrhSeaXGxD4UjBSUOqzmuUwEjqxc/mkv+Jhv2c5HYu7oXRzzbMl8OgJG8kzBXSzxAASet46FrSVwNH97mLx5gEI/MGW0GRe4Ek33BYpiA6avFw3GAgLxDpsiiipN9BfZFzIAYLIFrCKAXnABasHIWitQ003SA3YLZ1eR1PKejahIxT/fNwZC482aavNo9upEK63L6cNO8udc7k9lmKoESwFcpqYKz/F71GAYw83CqFX/mRsTCwvSe5/cqfA+SbjeCI0Ivkf4E3mABkdsUqBySdnxxyTzL2GiMwgpQL8gSPMQFGNXTaxlOU0kcj/9nSQScFDz8H14CtzbykLRncJI1GYT/+Tj14cj+s08ajbeNVuh+3pZ6i83SMgRk6wNgKmJJ3Nm74UFMbuM7EHB2XdC7lvM5U/9KxLG1Hg2NB+FVcHJN6VlEKpdIy0lwj9xoFMNJy8iKe2ExYYDia0Pc5x5pVSD777LM488wz8c///M/YcccdsXTpUlxzzTU48MADo7K33XYb3vWud2E4HOKQQw7BZz7zGSxevLi4r3A+MH7nahRq5cBEU57DlAPK15HAGNgkA9LDrIaTGbp8Wt7CDBNwtPHCm8hr5BAsBSNPGxeMvgzx5pJeAaJBxJc2QkjHFnqntE9pQDIDWNdTDR5jDDAcssGPQrMQGG08aN4HUN8QWW+XDMy6DFA+hzqp8HFJ2+OEIVMaGB2UbdXWu+X9SGDUwqRUuQf3ORBpnSjEithjrPM9GOv6Lr/5v9mPwMMEQjgKu7BQfipr1oPGF154Ie6//3784z/+I0455RSsWrUqKrNlyxacf/75uOWWW/DAAw9gn332wR/90R8V98HhFImDktZTAcfKczgm+pLqBo9lOG/SQTeAYAXLIkA6KI4szHBU1RnZBlIj1GmjOM17lyPfDoajMM3W7Y5slI7hKCw/HPr/7WgEay3ssE63I2A0DOuNXJ/D5s+ljUg52o+1VTv8j5fV/nLtj2pbbVPW2uoP9M8dT/fHxfNpGd6W9EfbiPq2jYef+DMj+S8+X4W+U3LzWuJNhpHz6Tb9PDDNn9aG9sfF20mJ9sv/pgbVX6kdhtX3aU0blv5NVZ6b/5sy1R+tV9e1g0HzN1XXpX91WTswsNNVmdH0AHaqTpsaVLCrP9tBVc9OGdhpg9FUXWfKwA7g+7DTgzqt3p4C7FRlr7dDAOJwNBj7bz5oVj3JF7zgBTj55JP99pFHHomrr746KvfXf/3XOOyww/Cyl70MAHDJJZfgxBNPxEc/+tF2HVqEtzsWUag1CKkySSHY3EJBEdAMek0a81oB8MdBPPgIICvwIYSjh6YltruBVPAS+VxjxnOsbGNpGc/R0jaddxf1Q4ARDdr1qhxpsBvGSapKFunwPtwF6q/TUZDuVrcb4sE1dTt4srlyrv3RqBoMmffo37pC052kbfexPjaipzmOB5VK7zI/lwtja2HlcRbGUE0J5VJhWJLW9u017eYbXRnmWRqhTB1K9eWIx+jLDRrv0jr2mbAO0Jz/KbUJMsxnzemc5Mc+9jGccsopUfrGjRux3377+e0VK1Zg8+bN2LZtG6anC0zm148GOv4lUmiNIwJeqT3RS3X2cGgGUK1gmAKkOu8YhEQFaAJlc45B2x0AWQRHpo7P3pXORRoHGaeBqewzgxg+emfdoDKJkUQDpWZbia2Zgb+VUqHUVMi1TZvj2gQBTlpVBY7Jl4ALodbsK+Ki8q6sAERSlodQfVkGuyiUmgCjHbA02i//jHoo6xfujKc1a9Zg/fr1+MY3vjFWO2vXrsXatWv99ui555pMNxdJxQE54S/S1ueiBfK/XEQGSPEXNZwHR52AkkFV8iBd+oiVcxrneTLfBvOgRqxvsU6czuFWskinCIjOC1PqjvWSgmiAVG61+TFq26fULg1XltjGB/dSaLWxtcUD74ACqJS3knLWW9nZvq56qinHKzlvKNST3sWbBKLb5o9omLhe4C3W9XJgDNtD0F5kL9F8CZeOqzmB5NVXX42bb74Zd9xxB174whdG+cuXL8ftt9/utzds2IC9995b9CJXr16N1atX++3pJUvib815dZpBufHVkDKUgLaBotaGlO9ftk48CWsMuUMtsKmNOHQ4OGdKdAGF21eXZgaVt+ZXrpIbhpbgyAKSgkkBpdonfbTCLRKiD+8HAyBrVxz4JzBwCF5JyQKR1nBMeYCJdlP52Z9cKg5/Cmm58yB3PMb1TqmyXqQrpxybwEsTgFj3IT6eQYFY9xFB0dXhEKRgpO2YuH82kxWpD7d21Nq1a3HjjTfijjvuwJIlS8Qyv/u7v4u3ve1t+MEPfoCXvexl+MQnPoEzzzyzdV9a6JTOR+YbQQRIBzlr6hdIU1giYKjvg5bl7Qa/UBL0V4GF5vt22oiF9UIgc3iRsq7/galCru5icuG6AZo6QP0c4wgw1a9UWN9uDUTaF9DM+wHAoHAeT/A8KeBEYCbAFMDRA5HA0JA0CY6u7VKvS0ovHU1yUEx9RqHHKHmlBfuWBIwWSuzSVkI8yqK2U7hyNCnpO9M8QgmEAgSDOjRd8BD9dhsg1v9HUKTpAQzD0K33OLmdkqzBqPck22vTpk145zvfif333x/HH388AGCHHXbAvffei/e85z3YZ599cPHFF2PnnXfGJz/5Sbz+9a/Htm3b8PKXvxyf/exnW/XFF8R0UQNDAPX56GHoThZUhTwUSbemTqChV+pZ+nZdAXfSWgNj6ocPDKp3dVoLixqQAwAjA5cC92kA2JFLAzCwsCMGxEEVcrU1yIKFHhSU/Fg4FnCW+V+fcNvuAfxmAXhVd6puG/DzkVMU3sQ1SM1BumLKYx6RfSkFIAi9xCI4cg+h7eIXv++FUEgN5nSgLXzpdRtPNPm7gpJtSnqrH+9tG1FIHceCkGaYL7dlEt9ZVEcAnvpqt8TbbMSQaW13GyACAhT9Z9Y+a4+3Hf8AOCItEEdydiG5bNkyNTT2/ve/P9heuXIlVq5c2amf5Dxk5pujYPTwYv97eLk6NVw4KCkgqzoV5IL6puqI5lewrLw31zamquffLAyqF1jbdqCkOzmoQ7w8HYih5wDqvcrKeBOFUeudcot/pqY8BIwLd9ZfTDChLz7PliCdBFXaDg/DUZhKz1RKUCTpSTBGdRNwaqPUqklXpBSEfFurJwFx3NWYmg2pNN+mmqVLCQcn4SXYkerbQljnoNURjqP4tholzBov1GnaLQZiCrQMinK69DlzPJ39/csEti9JX1cKhBSIxoFx0IzfdoBqYYxryz1sPiJN1OU9OA0ab5DAFh6IAEYGmKpeKCCBsnourgKl80Kte13eSAClg7Al9nqw1dCtH9Y31Kt0S95tbT0LxVpjCQSbzyDpwXykb6u2wYGTDqgegAOSpNzVcLiqYE24KhIQqb0lUHSDSyo8Oa5KQ7e5xylKPMM2XmQKzFDAkXgkoyjMmiqSg10G5qVh3qyH1AGAQRoQQovWFaBHvUOfR+EW5Antl0KRtyHsl98XsJvh7VgLG5Jt/H0OSEAIrSIGZe2dVjA0lZdGgOTLjJq6rpwZNbANQGlrI2qKGmurE3VU2zJA9Zyg84wdLEEY5YCmwNJDESAeXn0syB0gLyM9T2lJXvC4yICU57CT5isEIEareVW4hu1pcBVfMweEc4s0fMqhYdjLxaX/Xd2UxgWpCKU0BFpDUzhWqTBlqYch2iJIHWPbwk6DFssbR7kbgmjRDa8jfE6FSnl+EQzFfLJd0G5kN7edaNR7kgtEftKxgaI4b1gXd6B0z0BaAsMKUBR2secJD00CVN+XaV5m7t1YCwzJ55HxdhkLBksHxvp/W/VhLfzbeYw1Hl4cih5IBG4WhniTaMpxAPqH0hkU6WMu1Pvzc4tS7MomtqdiL1KCK08vCUGmPEQKTwmirM1Wc28lSkFl4sB0dYT9MZk6JfZK9igSvTsNetpAnnvP6AQ9/xz4qjKKzYGXzsqm4AZACsEm5xFbty+0QduS0ntPcp7Lsv9TRQkUATR8qtMi4IE4nvXLTwKPclA34EHReHrhCwNMk0hBNwKscS8zNzUQa1gaNAAcNbC0IzQ/3UXSfN8W1UQ/ASbc/IqDpr8S/N4Hz6MZN5fJATgCMEUgK3mPI1u9yio48MqXk4CkGdlw3jEJVCYFDEnPUMkTf1mBfW797F9KuYFcyY/GqZT3VwLA1Dwbb0Prp1SsShZ8ks0atMa1TRO3WQBf1KcGdwGE4TbP17YVEJa0Qe0TDpPKQTf+LAAtTEhmwKg+20jhCAZKg9CDJGAM0kC3a5S6MiD1QOqbGl61F1mBr06rYWmtqSOmtvZW4b1gawEzMLDW1r8cUpcf1I057xJoAOuBR3ZfernAFJpIK60gAFLM9+3J34X6cgTlWU5LbZP6kdJFb8QN9gLgDPk1dg5CCslEflVGsKvgfaKtBu1U0ZJ5woTHqQ/kRkhj7Y7xgvKUjanBW7SLhSjjvibs7aTArsKQ37gkyrcFYQkYaV8ZYIt5ivo5ye1VNbfc5wqEzRpRIANKV1+Bpa/kt+tOuFdZs6vyFl1Hjafn83waYAcWZmTqz1Wa8eHWGpgD94sn9W8Ojur/nQdpTR25tQ24SGjVr9wj4dAAQ/WGh9vIBum0PRVg9P3eLCuCpgJL3o5Ylyn7TsxCAMarDhVPKgfM0gG6pfepDvyiJ6DYDmZzZoFJnJ41M63IFgYBbX4uSNPaGtO2lDTg5ewogFPn0Giun9TNjtR/ofrVrduD3IDepo47wUg95xC697EmYQm2bVCFYG0TNq28xqacD5kSD9Rv1/OWpp5P9HAc1R4l8W4jYFIP06JeyUo+c+Ah5lC8cIYcWrda1RLYBVATDm8OZGy+MVhunwmtWmJfpNScXA5+AhSiEF8bDyywQ7GXqdPArj4SwW1IDOxAYpBNAHbsOdh0P20XqjRtjWlXSuJNiF4mvcAoTi8Jk6YAmYUvSxe3eTsuLU5SEievmf4JxoUHSerRaflU3JskdHSOYPO2G+Rh6TxEAYIOlm4RjiVtub8GlAyYA+cJ1m0PDLGl9jAHoX1mRNrxx6baueBF6BCe/fKwaq6IEFjkECbAGL0FJegDslidNCiVNiQl4CDNa2lvOtHTXL281xXl5WztKnGQy8M6gpzm2Yl5xdbl7dDgV5ctCU1WaTPs1RTCJHusclBL7Kcags3VL7VNknIzkkicEV144YU46aSTYIzBxz/+caxatQp33nlnUMb9BOPf/u3f4mUvexne/va344/+6I+yvy618CDJ5L8maTA1TXo1T9ksXqFfbwBLI3iNtC0OS1eWLLLxsCLwoj+PRUEZQM+FTaOf0zIewj7MSuyr8ht3zz272RgueHgFt4vxSxsScONS3qqjvgjC5wv1cqAsAUUp7Arnx4I+WgJoXCWB0NLb0csUAL/jfpV7UUYukwLBJKW0rfZZeIyyYdgCCLbxJIsBr0krO0sLd2b6JxgXLCRbXRs14BwoAVSwJGD0nmO9HTw2SL01Dkvb1Ak8RjRlukDT1I+C0N+ZDEBKAYv4M8A9tPiI6YtqhEM4cjufLte0m4ewlFb0vt2MSsOJVVnZY5IWhGQXtOQG7xn0dkohNulyaZuUClmvMEzLzb1F9Xh3Lc+prhGANvDU57mFtrTjUHocM7Z01hwt3Jn0TzAuSEhGX41lmQ6IFF4UhCCwNHD0DEOxDD50m4JQCqeCp7v2CMjovKQGTQ9j9/wjTUdTp/rMvEvp2PC84IrSR5LkICPmya/2ku0pB7XQjW5WScgxAVMpjFrqAYltC/23kjsemTbazIu28ohydVq00znMKLTZJszaeuFXULmkg3R2cfizAJDFi3YK7CqSBPoJeJJbtmzBsmXL/Db/1SeuSf0EI9WChGSpAlDyPLrhHsMwtKLPagdMmg7EoVv+mUHOrYZNQtP3Y5D2HukuJgYIC5RcSdk7cskDzXqPTb8TveMPm87XSwHUD0zx3f+MQbL0WIyxj8V5qTZTynl7GS+9zfxaiZIvSNfqTOCmIFeu+OYrAcgu5xut0zqCY81EPMmddtoJmzZtKio7yZ9gpFr4kJS+XNOkBycCLwO5nLiC03l+Li3jWQbOLQEmf/ubHnJlniPxNkH6oe0HnUYeW8o90LNKlAdholzb/ic1mJfCJRPSKvN2Cuzh3bY4Jm09wrHfodqhbusFLEI7sxbd6wLgcW8gMsej63lJlRsC2oKy1S/yjKmZ/AnGhQ9JTfyEsMpJwtK459nAzDJvMQFN9r+PlNHyQlrkLUZpxrcZgbEkjDkmDLnaQK99yNZVzNvRefBsE1ZMeJOT9niaxlqWbzMwTho4HY5lLq91mFgyq/AYFreZKqfdsHftV/McWwKyZN+Cx7wStrRueAKa6Z9gXPiQnMTJ7aSBlIZI/bYN5x8BwJoQpKQugLi8S9O8QxumRdtB39xokzzruyyQKQ7PRMBu31epHUXqeC2XDOCtwq2aLRP6nloDcQbHuNYh7ZTGsHPcU6/UxrFhnDuPUuce6bzTTVoOkFDyZ8mTnOmfYFz4kMyo1UWSOIF9BFcCIPE2IZVzzdiwuDujgxAtC7vSfN5OKxhNGFRJtfUktWZyF/hM38jmPDMtFJZpI6mZ+p7aeHqpZqQARZf9n4CXOHF17bsAMsX9iYAUINgyJCtKMbr4Wp3NMWUG9WsBSfW7muAdtAefIQktvQIrfIhCsEEolayAJWV077HMjplWa1hPIqTaZYDrEuYtmUvrao9vuDAtpQJPLmg+kRdEPjLdpoE5/kk5pxAVNKkoSeeoBT0fpYaFaSeepxbJ7Jv5dXot3YYNG/B3f/d3OPnkk7F48WL8+Mc/hrU2WJo7n1QMxVR4Rzu7S8DHz+gxLpQIgKDQtAyacX+TDmVOVBNesTIvBsg282tSeU0lUYFJgBItPL9xz6358H1J0uxqu79dPciUUueXVKYkxC91w298Ouz7r5Un+YY3vAEvf/nL8d73vheXXnop/ut//a9YsmQJ9t9/f9x4443Ye++9Z9rO9mpzp0/PiNRJVRi/j86OlPfY8sQNvUoSjg3Sy9ucERUPpE1mq7F3kuHLUpUe01wIFhjvzoU0lns7UbFKbJ4nmjHPrIMmMn3R9bwqvcFvMc+bBKNQMdh/od15fYPeQkWQHA6H+MxnPoN7770XRx11FO666y4cddRRuOmmm/D2t78d69atK+7wHe94B2699VY8/PDD+N73vodDDz00KnPnnXfipJNOwsEHH+zT7rnnHuy44475DgzUOylAAGNqErzrQgKm5LnCz6RUyIs2Zr1PmQ6vdgxfttJMzKu19XJm8oocd0SVbOt8zNzE9QRhOQ8hqXnKUXKbfR335kq69x1n3m5CNzVdVgAnzREjUnFMPXuOzPVJNCEVQdIYg0cffRS/8zu/g2XLluGoo44CUHmYf/zHf9yqwze84Q247LLLcMwxxyTLHXzwwbjvvvtatd0YHG6Kd1k8js/+z3mZ4nZHG60A7HzIx/r/XFLyWUetuXHgMhvXQJs+ZgKU5GZkRtV6xYulpwAb0Lp9MeK5MFvjnACgYD+sXlZNo5rU+oOSGxJrkuZ0BmjpjWPb71GZLqI3374PG7Y1bxYDzqCKIHnFFVfgiCOOwCmnnIKrrroKDzzwAF760pfiZz/7GR599NFWHb7qVa/qZGgbJU8aCkEJjBxYany/8AwomYdK9lk4eFrA5s7K5J10izN6JgdO8XiFtiWfdZ8kKNlxFleZd71bHuf1QRIwSL4dZzJsEp76OB4EdVj875JqdMhsO00KkJk+TUASvZxo5jin7Thz3bzv6u6kAaM1vi3/jDjdl1T4dhZfJjCTKoLkqaeeiiOOOAK33HILbr/9dnzwgx/EL37xC+ywww5YunQp/tf/+l844ogjsNdee03MsAcffBCHH344pqamcO655+KSSy5p14ASxgw8Rw2OETxbeHo5WyLPVeq3DqPmYFkZV943t4En5wbCCcOxDeyCQ1EyYE9o3s8ncWAW1Jm0LB/MwOzKzCG10mxMKInHWcgnP1ge1Zs0XHJKeLSZV7/m20ul5TTO1y2B3iIAZpXkaDnD4eR5puJHQPbdd19ceumluPTSSwEAv/jFL/D3f//3+Pu//3tcf/31uPDCC7F58+aJGHX44Ydj06ZN2GWXXbBp0yacfPLJ2GOPPXDGGWdEZdeuXYu1a9f67dFzz+meI9mGScPRSulUbcKwGiQpDEl/hkG5CJaSiXw7unGI21J/mKGw33F+yIL3QbejX7aapVUBERxtKk/e+dTgmTte8e9MmzivTsuCfAy1ida1lnaM+Y1AtL96G0WatDdf6mLx+uL2DNzkaG0SB9jWUDQwjdfo/xeAmTLh18mTlLTrrrvida97HV73utdN0h4ACH4petmyZTjrrLNw1113iZDkb4WfXrKEhUVJYcl7ZJ6l5Wm+bkFIVIMlH+w5EE2Y56sZK3uVLo93lymjQSdVju6GpsGYwJL3pUkbGLncuP3mNAqAZEg6xHQOqdEEvctgTBag6J2thD1Be1KAoaO5nTyoqI08/BsWMUgmblxKpd10he0xj5bY0pRnZaMGmX2qZ2rjsrxe211N/WA5CatWmwSWqgFEvJjFrERXZkPz8mUCmzdvxp577onBYICnn34at912G84///xWbaQerA0Ayb1H7jlGIM3DUvT8mIfoy9RQdED0P3ZQfza+zbjtEHrkM+l+wOrTzwOlLQk+2iAyNiAT7Q2U/eN9TgqWEtR0UJo4X2mn68Ct2SIBWwKnZIu3aQL2TGq/eFsc+JZB0VqT8KIt+Xd8GQVWEQyV++TQtrh89Vm4QYjKFJmri0OVQtFSuxgs3Qr6FJEV237tPcmuuuiii/DVr34Vjz76KF73utdh5513xvr167Fq1Sr/Xr1169bhmmuuwfT0NLZt24bTTz8d5557bnEfEwGkBEcORgI1Dk81ZMqg6PIoFCVAuuocehx4zbYERXfCh22VwEgD0WCMq1cCr9RnkAaaPzNX4cj/onK9jRiIHJJuIBwhLsM/d1UK0vRIamAvtSUHv5HylbeBpvvupTpW2TcKzRxIpbbH8ngL5qmDPPI5WOsq2mTJTrqBirQy7n4w8PHQKWhoNQFLY0k5CthCZ3N7lbHam2G3U00vWYJ933cl8/Cq/8Q5yBQgxfLEo8vNIxIoNfm2GIoDn2cDCHJQDgSI0jI8zYGGwzMHpSovBtM4nlzKK3R9N3Y1fU9JgE1clSP1So41DGA0IJ9DEHJQNf+TOgo0u0iCbls4awM7LyfZyo+u6qWy9LbzxxEk/XYIxRREq/91m0qBnhsdO7fTMpQc9VNySFNwjeZ56zS+zcoYnlZr07s/gG2/eNJvL9plCV5y2XsLjEzrX675k+Lfk5wpzctw69jSAEnTSgGpwZGBkXuKVVmrhlCjz4ihyIE4IOVAyrvPA2MDAA5YHkDBM1LhGHprMaAAGVK+TstbyBiUo6APyXuUwDyl/OzAEAMxXVIImBh2Qz9gD4LypfldpYGPgzkF5Vbh5DGhWyrNo+R9WvqZQJQC1LWT80RztndxG0qOQxhSDvebho+tNTCEV7AGBlYAbaYfeo3Yeozyx8TlUbtrt9B7h7bxKH0W8SgTNmTztiMtTEg68fOWhkylcglAJuFIQ6hoytN5xLZg5FDUgCjBcAAbwIRDkoKPg4hDMQUqqi7eJIeaFGp1ZWjelNu3CVyFEryGgvcINLClnmOc1sCKA5O3N669GpB5uRwsUx6wNPeaDeeyY6p9TyWLZagd1LOkdllik43KhW1KIWvfr2hNe6UXTIVQjEPI1n92Xpu3K+CZicYy/1N7DI6urrXGh1kdMGNYElACdfkYlFVWbAPVGAGmeaWFDcla0TnLvUiuHCAlOLbwGIEQjlODNBglKHIgBiD06daDkEKQw5EClUMpgBOBGofiVMH8YApqtL4r52FIw6zEEw7qZ4a4YcaT4/OQwwAyVd6QeWtDOwg+V2UlcNZlmEfr0ktvMCQvl3uwfF80cNI6mtebCydLNxjSTUDb+WwJ8AEUiZ0SPKkHyT1PV67abvpMzY2WisIpF9am3m1VtvIUHSApMB39DLWf9uX7dwmkb0Pg6Rc1NUB0C3KsNtFIvyICysrJtOm3O/WQnOeSvMhkeRZ2rdNSgBwQODoYApPxGqcGo2IwalCMt0cRCCUwTplRDCpyxgdAawkrrR6v6z1ZbhvovOT4C3eGERxzXmQNTJjgs8sbBp5kDNVxJQE3BeNxwsc0LwTosNOiJBWWJF33coktzLvUwCl5nP6zNZgK+pDCvuOM8nHdkYX/ZjwcjfW2NYC0gcfp4AlTgdTDuC5jSJtVgmVsC8EcwrLyFI1JgNKFXV1nDJTa7verWxeKJJhSWHJADmLvsetcozG2AliB1zhtRioYFw2GWShSIA6MDeDHodgAioVeBS8uFTLl0uYMXb++DYSh3gaUsUcp1afKgYl7mBQkFDYeGGi8Su4xDjGoQEmg6foI2lVsykF/KEIu9uqGQvi1BKoVXMJwcbVdQTHntfI+gRQY0/uqLZga2RGxNbSXQ9OlufIOmlM1mIBqvJ8S7AbaeZKpxUmuHdqP8xRHdVi1sreCDvUmTbTNYEi6De7vSb8OZBIsJwFKfccTeduRFi4k6ferKQIk/Rx6hs6D5IAcDGwWjlMDi5TXqMFxejCKvMZp/zn0GBtQpsFIoeiAOEVCruHnOAwLUO9SX22aAmLOi+TtTzFI876TEs6BEWRIDQXQ0PJDyXP0eUYFaAio8b1JCcK87SQ8MyHieHsQAbLpaygCJqWS8LKDYWhv6NlSr5ZCUwImTAjSKdCwq/Hnb7AvBXYWiXh2IShNDUhgZK0Cy4pEhmybAI6NvYH/WJdzn4EQlrYeHzkoc/shgjJRfCFo4UKSi8XxI/HbMCDwKv0cpAJI/xmx5zg1GI0NR+pNOjhOD4aB17jIDFUwLjLDJBRd+SptFIBK8+gksLk6XJqXpIGPgzHlvbaVtto1gIwR4GJCKFVzkhSMaXjStlKSjhWtJ3mFUjg4uW0HHhzNvlQh4tAzNtE2bQeQ5yY15RZbpeZNp00N7fp8HFIoGgfA2ks0iIBprMFU7YnRkC0Nu06Rvif5sgQKX++AmQaMpbBE0AqUtBCYPpXAknqVFJT1OlrWvom7CnZEVh9u3R5U4k1yee/R/e9mvevp7gwgGyDGc45TGTg2MBwG2zEQY8/RAdLBzkNR8Bg5GB0UORA5DNt6eHywl+YrNfjJcLTi55xSi3aCvPpjGHKtBlwRQoaA0lRpDXwG/nMAqMLzkXvbUhh46D2kEHxBGJjbzuzh86kjE86lOmgOMcA0RlGoltozKdG2B852AkZn7wAVMCUPkwJzhGq/XNsOhqMamgC8t+n2W7MnZWtK7rqy1mBQh3udB2uNBUbVlTOAwcid+659f3MvUcl5pc1Y5R4hcenOA3TeqEHtVRKvUAWlDbpB5HGmdr/3JLcfGfa9lles/yPADOce04B0i28073FKnGPUQ6uiJwkGSedRMjhW+ToYqZc4BSsC0YMrBUkWqnXiUCuBX+PZUgi3v/JSno4E0BGx3XuNDiZg3qQZBOD0QOLgBAKgSUqGkP0AzoFIIGcIPEE8X2efYeFVM2xAST57YMJUx9uQhUimgW+1zxU8x1G0WIeGiFkYdIDKrikz9J5kBRZTHR3qQXLvEs33knqLEp+jdN6nZGPrlck1IKeMxYCEhKcGI+9BVsBMgRJwK18NS5dgmQKlD71qMlVfIRjLBtTek5zP0uaeS0VPfEP+czF9w4CJEJBSeNWvVlW8Rwc9abXqIgLLRWQBzxRGmB6MRO9x0WBb4DkuMttUOEpgpAAUQclgKINS9/zCR0tkCDZeLaub/vYAIDlsUzAuoul0vgXVQLioLr8IbrAa+e3q/2HlNbo003htTbl4flNSyTyrh2R950ZDwQ0Mqac4wKIaKItA4F3njTDyNo5gvSfjvkMKzKqdEDKLMMzaTO2M9od4c6jtcOfGyBoM6jnHKePy3BxkZYcGS2AA2Oo8c7Cs2rR1u+HxrI6h7kHyz/ScLAnLDoyNPVQ05/LIeZioI1AJj7LxFOm2DaEIxGkMlFUh5zm2DLvmQGnRe5LzXiVw5GUCOIafmxcDsM9o5iCdB9kGkG1WrXYB5CIzjLzHJk2GYwkYtZWvbTxButgnLANSBmJ6iTTkDJRb50X1IOU09CCgoc0GkFNurs5YklaHBU0Dn0W1l+ZazUla2ETre/jauu0KJVhUw8/BcAiLRXX5Ke8BN9GAKTRzpwNYjDCqPbVqkAbggen6p99fm7lID1i6T2gAOfTtk4VAhn3jbjGPGcDhrQlhczDaZnWubSDlQp3NcQ3PhSBPAKiHWVCuTIModBmDEoCHpQOlAxq9Uafwa2DYDpTVywRaKmBmGpS9J7k9iEPQTX4XXtt8WXflOdLPNihH4UdDrEkPss1jHWMCcpHZJnqPFI4A4u06TAuApVmWxrYzXmEJDOlCiqpc+ssbkkGP1qVoGghNuOvZ1Rnaxv4RKvsr2FSD7wDWD5wDGO9duPCgg8yUH62G2RcaVP3Lw9YwWBg1CMoOMcKghkxj54iUGwRwHNlB7ZnZ2pesQDJlGCztAFNmGHo1ibnSnDhgp0A8zLrdoW08yRCKrr9q32AGNbBGAAclQK79JgQ7gCUeWxwudXnN52Hzud5XDbYpuXL+jVkMls5q6k0O0EQ2Ks+SLf4RgKila2WbSi28SRptcaB0eVy9J7l9qTCMHtcT6lB4uotK+s1D52HSehyIrhwPsTbp4aMeFHpuDhJonnes6o0CcNHVqilAcu9R8xxTcGyet4y9xLZQpEAsHYoHxoh39g385Ct3CjFIfTvW2WADYNJBwKW5gXgKNazqgbbK667G2xhgynmHZlR5gjXMPBzrxUQurfKkHAzDdJiqPQpLmAFgR2L71I5qv/Oe8dADqfFIweDItx0sHRS9x0vSNFA6mIU3ye7bJJ4zGxA8IMFh6cpyW+N9lcBJ2wIaaEnlOAi1sKv0Evk4TYcifRFBJ2/SIlu59yTnsSIgRh4lxBNcbU9KY/ADwrtS/jn6NQ00nmFQjkARQPCIR1MmDF/KcCTeH1u5mlIXQHLPkXuNA9823X/SZ9C/Dsapgi+t8o5ieU9R8USH1kaep2/HhwTrgQr1vtHQE5WWPglxqGBE+iOg8X0PSB34+cjK/qrcEIPqO7MjP/C5OUAKSx/eREs4knrRyGndQpxR9vEYBxEKEw6W6twLQVm1X0cAqEduZE84AKh4uowazxSxPYAOy3DlbnMOjQA/aDlvMndXn/UQZ0J8cE2Bsvckf33UkqlZSSvi4p+ksuChLf7uVPqIRfA5c3amvEi9P+nxjBDWlR3lgEyFUrsAkpYb8uPJyvG9nfILYZz9jWfpwWhiUA7pAFwPmi6dDpj8O6Gh1zbvnW3abrwy52kFaQQ6rk61L6MyUAKNVwn40Kf3LktEAUTgzu13x41/biutrv9e6u+DvjFIm/9tQr7OfpfnvlcdlFW75eFYrc7A2MBWKtlzDOcmJy4KRP5ZKt5D8tdbdPk1fQdjibdG5z5K1bZ8SkOYCFBuyUZYbuBBWQ0cI1J/fHuGiEHZ2BOCzUGvFJad7JnA7TgHJSAPmKXHj89jSm/XmYSCkGYdep2iHil5fKTkZQ4O2s5WejzoZ64SQJbAJwjtIgSodI1K4ByRkG+VrnuJXVSyry7kOnQhf9O861XTjAOysHgPyXms6BzJbafasvG8JAVk8y5I8jwVubD8eyJNODCO2ByVfyatUNHSeQaxah5pFOXR8s3cwiiwzdWXoEg/O9g3Xkp150sXuTSLEFAfj3B2yHlr1SIOMo8pzC1W5ce78qThncORBhKD1a42TGvevGNIeRPkAfKgWrKIRyvP36LDX3RQ2TQQ6+Y0pXgvjbcqH//4JqDc46QvgwfIYy2W719s10g49lV6vJI2JcnLzImDWLOLp/Gf63KvzkvBN7ghVxT/XmaYTn+z0pdRW+ONS0YlGqic7QWhBQlJSf68aAVIE8w9hi8Z5s8n2QCQA3JSj1DdAdLPgLuQR8EdqlsAVF0wAz/3U4F2gAEZwivQjdC8Vqvabh4WcHNK9XJ2O6oXZaAOs4WgdEvop+pnAZvFEAAwihdbAH55fTAQszBM5TGy8JVLJ3MygefI5gib8uPfJUseYw6MND18x2vt2dE07+3JXmDcd4n3FENPexVd88YcATwgz1MGNg+C/XEKw7Y6+Np4WfSFBcE+EljKr8KToRneHHQ/P9rWVX+SjLVDt61wvqTkfhOT/pj0WBJAXf3Q8/hNc/We5PagyIPMfGs15KLPiMOr/oXDAQyr9y4O6r4kb3JgyUVjyIo1uFBKPeNlGs+sAlnzIHVVtwGggyX8QGhjCLrjUQDKaq5lFLTpVg5WO1u/Qst7qs5rbDzLKbiHtokHaizxHN2gWm1Tr7I6ZiGsPPjZ1ayFa1PiS05yUKzqtPcatVBp0HcibCqVl16WrsFRe8esy2vqy4CUlAKl9Ko6/kso/BdR/KvvEL83lraZA6T0I9cjAUilIBR/yFrw9rQft+blUj8kHfxQdJ2ueZZSqJVeEvqPOgtlgDDsVsN4Ygtuekh20zve8Q7ceuutePjhh/G9730Phx56qFjuU5/6FD784Q9jNBrhhBNOwCc+8QksWrRILCuqxHMsuV4sGmD6O67Qe6RekLX14DoaYGpQv+tyNAAG7pkvBD9UOvLLQFA9d2cBtzSketaugabzJunzYwNLgdhAbREQQdDNMY4w8g+Yx5/dasapelCrt2395J0Z1Z6hS6shWIdsG88qXtxDH9zeinixEp0r2mrzb9rhIG2rHBCrMrqnCOhQlMKjUl6YrsFHr58CY5DOgEpfwl7lm6A8rZO3j98M5AEZgBHhO2JpmyVwDOwncBsHjkFf7Ptyb/zhsOPHQnuVHS3LQ6+likOrtN8wjYZZA0DS8hF5Be8yt83UPwLSUW94wxtw2WWX4ZhjjlHLPPTQQ7jyyivx3e9+F3vuuSdOOeUUXH/99Xjb295W1gk711pHKTwUm7bcR/qbbrb+vRnrQqyoQFA921TB0E/8U1ASMG7DoP4SRtg2GmB6MPKg3ApgkUdwtZ5yGsMAlFsxFS4EIqD0rxiD8QtzRjBFsARQA5J6HCPATmHKPXMH+Ifcp6zBVjRg24ra03RzkbDYiuYzlbN9qw3zXXkNprw8VzjnG6sLDDUQVmX0eUAOGMmDFD1HoVwAshQwBTBSW2YCjGE/FMjhO2FLf3WE91UCRymflsmJz3NSqDlA0rIckJLXGNjGynmPEqEXyUOtkncqeYj0cxKQUn0Bll09wj7c2lGvetWrsmVuuukmrFy5EnvttRcA4OKLL8aaNWvKIQnIoVYD/6f+onat4AdOLX0jhTvx3DJri9FogAHzGgcwGI4GsMbKHiUGFWQHI2xD9d7JaQyxbTTwz1VOAx48A2uAQeXDDWz1tpcBLKbsqKKBHVXARPMowsAOMDKjIlhuxRQGtn6fq3UvHBhUHl39uAhQA9IOak+wgeZWTAUgrABZBUOnMPLpgAA1Gy/FT730vBSmKaVCpSUeoTSfJ5XjZYE8+Err8To5KFZlQjBqP8Hl+1DuMFP7rMGx6lf2HlNw5GAM9qMlHEu8NQ1smgcZQS8TguVwBOIwKwUklUUDTeoxUigGgGR9ioDk/aS8yDYeR+9Jzpw2btyI/fbbz2+vWLECGzduLG/AeX/u+2xzS0O8R+5R+hi+8yCbMy4CZQXHJvTqFwDVeSNT/W4kRgOM3AsCBsDAVs9HTjt42urngBYNhtg2mqrLjjAF42E5HA38L384r9LBcmsNseBXQeo+mv+bFxVM1Q+PO2ACINC0HpoA/CMj0k9cwTb5Pi8BQhmUSrvsfbFie+ChXu75xCDkHlD1OQwdSvWBPMBK6qj1CrxO9ae0WLtDAZylIJT6oraIHmQhHPmPPDd2l0FP/1HoeP9yi2a0eUj++5Qun8MxF3oN6pI0DZA+HfECntaAjDxMYltdJ1gFqw2dBUNq70nOE61duxZr167126PnngtvdnwYEuUrWwNQVp+tBQwcNKt3Go5GBoNBU4mCcgBgOKq9UVP9FM4QzR1j8zq7ymu0lm4bjIaD5ldBYDEaVnUWDYYenByW9HV19LN/UNvaAJhVf+T3JQk03dtK/K+G+IfJm3RXn4ZUnaQfDh7YDDTJ7WvqB5hDUCZeopC4SEtXiAJ6eNOnTRB2vr5YVmqTAyAOnaZ+pDnVX85OzXt0fQerVRNw5BDi+6WuIi3wLHm5nCcpeX6a90jhmAy5St4k2aaepRZiTXmQ4XbdsJXDq1W5JpEDEqxs0AAtSyVdZxYwo8QFuB1pXkJy+fLlePDBB/32hg0bsHz5crHs6tWrsXr1ar89vWRJ9YHexgTQVDq1LM+6V/2aGpDut76N/1cDpTH1a4FrGFah3TrdWJ8/Gk5VMKt/JWQ0qrw/U3uZbtu9vm56MPKwrF5fN0D0EnRSvgGZjbYdLAHEnqaDpl98MwrrCgADJM8xvkikB9HV35Z0ICdve/F57qYCcR5vh0qDYMnjE7wNLg00mkemLSZJ/ZyWDFoOPDkUnJozLZmv0+pQEPJtDkZnXwPKEIw5yHlbBIhKdSIvUjvmUblmH3jIVYMjhZ3UrmVpEhxdOvcem/TUNoq9R18mgGrz2ZfrAsiSvO1I8xKSp512Go455hi8733vw5577olrr70WZ555Zlllg9B7pOm1rJuf5LKuIKtvAfpO/KqICUBZ/SqIIb8zaQJYWmsxGIxgXboASw9MWNihIS9EH2DajLwH6tJCQMbABJp3xAIQwQnAe5wBLClAI2DSOUI9REolPYSeg+0UsY/3N0XsA0IvVfJinSI4tpjHo/VSSr2DNPeAfc7T6bICdlw4AlI42UR5/DnHMISaBmNqTlGzUwujapCSjm3qpQOpsKo4F0nSgJARUtlwe468R18vLC8CkisDwdla3VryxMSdd96Jk046CQcffLBPu+eee7Djjjtm2591SF500UX46le/ikcffRSve93rsPPOO2P9+vVYtWoVVq5ciZUrV2L//ffHVVddhaOPPhoAcNxxx+Giiy4q70TzHEvDrU7Em0TjV8KOjG/L5ZCHDV1lVI+JmAiGzW9OovntSWP985QDw35SCxbbTLXytfm1kJEKzGqBTfgrI9X/DXwGBHo0NOvKS+AEEMCTSnoHppPk1WkLdXgYdcBAGc2HJkAqKbXCMzdfV/wGmVLwtD4h020n5ykTMAjaKLBdBKQAxcqmEIw0LDqyJoKi5BXmbC6BojTPmWuDgkx63IMCjc4v8rpaGvccaTvSXOO4c4++DINfMSBZWznN1pxkyRMTAHDwwQfjvvvua93+rEPyuuuuE9M/+clPBtsXXHABLrjggm6dSNeS+/5T35zPIt4kFFD6vPq5R2OrdT7+zz1HCdGzdGFYN2dJvcuBCX+P0qUNbQXDKjw7CIAJUt7DLgFJnt82XOuU8tqcpFWnEWS5Z8g8RrqtgZSmpcRXT1YDuexR0jRNk36PKlAGq8CGzFwpz2/TvgSs1POMfC6Ph1ElWHIbUx617BHmgZgLvYpgS4RU+crUqK6YhiBNgqNLz4ZWAdV7FOFIC0mA5BAcA5DA7HmSJU9MjKN5GW6dqEpv1mvQVZ9dxTwoDarnJK01ESwBF35twrBVGjByHiUgepeo06cGoxiYtgGk4WBkXqITzQ/+V0GZDts6lUCJ15HSIs9R8FxLQUrTqFKrMIFmsYn7TNX1lylmWhrs4tW8+rxlTmWQpCHX2FvUoCitBM0vrlH2WQFiCo4lzzSWgjEFRZoelUcejvxzNrRKMoq9x+B/AZCSfDnhO5tnc5IPPvggDj/8cExNTeHcc8/FJZdcUlRvYUJSucZELzKIkNZg9HyMQQlb/36bQTP/aeo01xwBLvUuHSArCDbgdMB0PVJoDuuFQNSjlLxMCj3pR6G1z5onyn8AWgrfVp/LbxelhTzUy+QQ5iFgnpYKAUveq7SwJNi2Rg21ptLG1SR/4SUFNC2/ySsMJyurSin8UlDkYJSeg9RtLPcwS2DIy2ngo+FUaUVq9blpU3qwX5qv1MOoOhx9Gnha2HiR9xjks3Saxj/zclx2Mqtbt2zZgmXLlvltvlCzVIcffjg2bdqEXXbZBZs2bcLJJ5+MPfbYA2eccUa27sKEZIkCOCIGpVe9bVHTrvElAfdSczQvK7CuTF3beZdowOk8yxCaiKDpTErNYw5YuQFpi4oPxNyTDOZAC8O4Wts5RfORFLrMs6X5qUVIbWzJhQh9uVn2HlMvQyiZZ43SBZjl6qSkLZRJhU4dFDUgSp6ktF0i/uB9p/eqCl6e206BkXuJvB8KRd5vWzjS9uYlIBGunxxHO+20EzZt2jR2O4sXL/afly1bhrPOOgt33XVXD0kuY03oTTZOogDKugCBY3MGGu9JGsdQQ+rX3qVr2zrP0pqmK2MDaAINJJvPDTR9GmJourxSQLpdpnkpr5SHc11e2Ef7CYgyL7cJpWpzqYAMWkldXmc20+IedtebkNxil0mAkvejwc4t1nFlpHwg7eF1tYlvR/DMgEyyL1ysE7YrhU953yEc5TzxnavjwlEsqwCSKgXIUk0uQDK2Nm/ejD333BODwQBPP/00brvtNpx//vlFdX+tIAkgeLm4B6b0ZTqvkBagXmMNT+u3jQecr2YIEGHINgEnCFudPcZG4OTepoOkq68Bkm8D8GCl+QPSHg/punI5UGr95SQCMhEOlmzgi5NS0sDYZl5sEtK8e2A8b12CmJg3xj5KC2VSwLQzdKw5AFNt8yNY4lGmPEYORc1LlNpP5edeSN7We+Rtxg3G5Schw39uZ4ZU8sTEunXrcM0112B6ehrbtm3D6aefjnPPPbeofWOtbT+qzWNN77oEy9Zc0alu4GUa9j8A8e09LswKlobGmZRebGDENFYfpCxpk3uc4f+kWWVgpenco9Q8VMPgxOtRdZ1j431I86zBAiUB1qUerTaw888zpRJA8n3p6lFqc36Tg2Q8+GvA1MKRkzjmKQimvEk5P0zXvEXNG5TytPwgXaoDnkcNZ221BaTgccahVcRix+vHl38Q237xpN/e4YVL8Mr/70qhYjs9fM+fTiTcOo4WpifZEfuGDiK2hmbtBAaepUU0B1k14CBan8y+OYMoQB/QzDZmm9oSY9l2U1byPKMmEwOqVI5CNvBa63IUlA2w5L7azAuKoWAByDwsDMgwldoSvY3C+aqUUvuZa0cNNYMf4+7Hln+eVGiTt5vsh8EFkMOaVLR+LjLRBn7SOhLp3CidV9TDpDGgNFBWCYKHqeYzY2jb4v7FbTSZch8TkUX/WrrtVqnvzQGxloOm9XOTPgPBc0UMjqL3iTAvMMOwE9TUC31IlmV90BCu2EwKknxbgK0GTS1NapcO6KXwoXVoHxzIEiwlGzSlvI5STQqS3CuXjkEpLIue/Zshr7nUk0t5eF2VW1kq9S0p4lciRFrmRdLG0t5r9I1qYM0BUgjb6p10lDv/UsdzYTBygUKy5MvRylAYOg45b5F7l0DsYQIMUAI4uaI8V8c2Zgbun/M66WDKwavsIOexITvjQRS2YYAApHGoN9wO2+42EGptc++Wl5fs0JSyy1qTbKekj1T74WM6YRqfX+Yh7qZeaEPkRQnp0uMIMyEtfKnla2ltpHmrJe2mz4W4XHKxjS8swzoFQ61fXtFq4JPsEMvl+y+SPweFKE7vSW5nUqEonSA2/Gia/0VgAuEIRkOwuf6TomC0QnIDNxuV4zSUewh2Xwjb0jnXBpQySIMytL46CMjp4XxtDEsJyuFnsVlVqVl5qa0ui5Pcvmo3Ehz8paHtXH9APL8W5+sHbFLPcIph1Qm0G3ljBfN/4/SRW2gT5QUNcVtLOtdtCfJVr1PwNGdJEzp15lwLE5KpL0e4WKIv05qwmK0LUWACfgUqTZO7rAe8DheqbQM9o2VIZTnMmrqWNkPA6NM5TCWQZlQyaFEoR/0h3FMRzhNSFA2fUNu5xVdROqlbGuqVPKrk/FjG1ji9/FiUemttpcF/kksS1XalY8ry4jrd+xbbEOcsFU8zUVe1LTO+aZqt19LNtBYmJCWxk0G8tiVnzWeROzIfj0fRCWQkcJUOTinoaVlF6eTCEoHpPnNCOJeaHFIJpCmlLlpSP2pLgrNkM8YEWdRWbINSNJI25jRtu2OnAZJvt9uvNissc4q94HyZnF1dxQFYujBGVJtjWugtJhfYdJE4XmW8R16v7XEZS1ZeKbUdamFDsshr1OoK9Vxz1NMsOA9yQC5KT3bQLp0flgDESWDW/xgCVgMFpAl1uTgpnCO74v6KukiV0cK3CTC3UQMTk/WUOUgjmxR1mh9LiHcphcVdqbYh78qu9nUmsV/uJR/FxdX+4wKplafiSapdO+IcbqJMbpzLeafjyvae5PyVhTpCBuffGOGPqK2ULSX9A8lRfSzmCJXTUVnqYSpZFIwBLF1+ZsgpPfbc83XjTQSqiPrdxBdc+f6EMtqxKZQVgMdXMFcfm5sDXj7s30U3ZENy4b6cl+MfSfIJ1T/aDcRM+Sji6ZL0IpWGSr4/ej7kIJUDY2kY2NLvXulLKd/l+cZk2XG1QB7BX3iQFJT0HqWbYU02DSS1H3riC3eb0nabQSZV1mq5BR1I0Vm3K4YN6NawCmmj0tuaEa5vkD6DskJDyRsIIYGOORyIIpBb9im0I8FRuiHwMBX7zt2YFHgiqeqSh2jos7xsUM9BvaTPguuxKWvUPFWpaIRBMVDElaYlodCMuizsaQVGrXyXMoJ6T3I7kQ6ugjJae6lQq1vFyPuRHBAFmK3CsymZeOgcaxqCtufgSNOVQTJqpuvdPmvXRI2Z4L9UXbWPYOAUvOXofwfsgjBsznvXVjBTOLbYX1GFXkxsog2ru303Tb6FiULGPjzukjN3otl5uwwE2oBfg3qrhSol3mLK2xtXM+0tdgUkANN7kvNfJYNxpxBoqh0JijxNKRvZk7ODlS8Ju04iDGYJJCgco/RkIx06ltpV3BSpeckR5Nt0MVJT3gT7Rv9vPGu9TTmUx/u1YaLaXpu7jxbK3j0V3DA4IHqA1udcwIhuZ6D83F8H71GrTr/HgOpKo9nwK3f729tXpEmHTydpY+9Jzl9lPTENVoB40iXHHqldmm7r+hIopTAsb1PaVmyilse7Ueh1FFwkEhD8o6HMsMDz09ruuPpQraZBWgMiyQvAyNujYGQAsEKoNNkfEOyXSX0/hWnpm6REHlA+OEpvlXLbATBr6FNPsusdWklkJQcL8RiSC9atSjUsvzT0UrKiNLVYZpLHpk3+TMmif5nAdqUSQGrAktoQ0nJgpFCUoCnalOg75zSQ614vkGg/1UcOLrSMyrFW10/Yitp2AppcHurMmKSXHHiNRpyPix6LoWXAv5PCGxdt/GfpkVPd4nhUDWbsoHX9/tpmx/h5EXmbHQbNklWYJc3yMvTLoPZZIZ+WaWNLq9WmzLZSzWcO9eHWbnrggQdw9tln44knnsAuu+yCz3zmM/it3/qtoMydd96Jk046CQcffLBPu+eee7Djjju277AFINt4c4bnBR4i3zZyemADS5dsEJQC2ViPCibqpj1WUmacwTihZNtQbEoAxQarScPyzmsMxswaAGqaS5A8ykncNbCxvdlfAbo5b7bQHG2Fr3H7acAWOhEXUnjcpVilHmNbUdtqpzeApkV4EEq/HnERT6JM0rgWmsRxGWfAkJrrPcluuuiii3DhhRfinHPOwU033YRzzjkH3/72t6NyBx98MO67777xOiuBXmahDSBc1xp46z9D2o7SNSjmvEUO6QJPMjI7cR11XSykAatjBLVIOQ+ZZ5eWl+Ydq7HTKJ4lgWdUJ0zLK/XlpNMjD1VZRMSdvTYKOWyi45AFpjeiowGp+qVtSjcPdO7QP0YD2dNsY1cuzJpsa0I3Am3Vpt+CC7hf3dpBjz/+OL7zne/g61//OgDgtNNOw9vf/nasX78eBx544GQ7S4UQJUByeGltaeHRhOcoh14Fu1J9JOwoVckl0Galb6qDzpd5QdipxJONbGGwEBvjbQnQDD/X54+hgLVyWQiQ0myXjrlUVt33+IuI++5IKwpH15Ux4f4bVK9srD2y6FEaob3keRZdK4mzK3X+UFss4u+ee4G0LFhZxbYqTbGvC8znq+IJ9rhM70m21yOPPIK9994b09NVt8YYLF++HBs3bowg+eCDD+Lwww/H1NQUzj33XFxyySXlHSkDfQgcBkh+HUsepQSphOfI2+dw5F5kCRBLwrFt1hvweoFK79q7XtQdARwl5zzZ1PXMPMCgruQJqsB0nxuvky7wCedA5X1pJc1DrMFE4RPwgH/o6OQYPxdZ9+88SBdmdflA+I5j344CICgQ7OJBunx6z0APlgbN6ERo2a9UblxelH5PKaDPsvpHQGZQhx9+ODZt2oRddtkFmzZtwsknn4w99tgDZ5xxRlR27dq1WLt2rd8ePfdcWEAKa6YAWRIOjfJM5FXK4Ve5zVQfWn4Olp0chZR3q/QzjkpsbLtiM4qQCYDjToPoHdG69H8HBT4AM2g2q30baGb3p0TC6uHoRoHvD83nHpTOKqFv+EWrsKYJOddpFJY0vwlfNn0Xvey/Cxi1dtSbLEOKKV5mUzjdh7Ld5ocNgl8Won12vfYmeVPbtt9hD8nW2nfffbF582Zs27YN09PTsNZi48aNWL58eVBu8eLF/vOyZctw1lln4a677hIhuXr1aqxevdpvTy9Z0mQmIKQCUqsjgDEqV+o9ZvoI8jL7kQVbF2l2KH22aa+tous5N3glvMZgsSIDX1B2TGgG4NLa6iwj76+wQld7dlOKlCXNYl6pg4ipG7P1xeMPpZTvvEsJAFziOadb6J3B5E7kT8LgDa7UyyxvorYnbCfZhuGbBNqlx6utZsXbtL0n2UVLly7F4Ycfjs9//vM455xzsG7dOixbtiwKtW7evBl77rknBoMBnn76adx22204//zzyztKDew0JFqLAlKFHpr6QRr5Pzf32BqQYv8FeR2V9BxFb7XEFWzfbxvv0dJfm5Y8PEugYYV0XrclNK0J23UsoPlBHWEf2kqGvfF5hgFJ3E9qi/IdWXKsguisQbW6n8DQhVldGDaCZd1g8N0WQyeRya9jbT9KOqbnBxCGZkuUA6IEJ+27MFX/AahzwJR2q8T+mQAxAIwWxsqdWQ+3XnfddTjnnHOwZs0aLF68GJ/+9KcBAKtWrcLKlSuxcuVKrFu3Dtdccw2mp6exbds2nH766Tj33HM79ScBrtkuBGTqEZGgHGlXAiT/XABIbm/Up1a/jVJ9+Xbzd9Wlg1lOYjss7NSAzyIEH6UVaU+CpmQeBwKpQyHqwKMB0+cz4Fo+MLaVUfbHsjzLoAlEnpxoSwAJoR+X5/bHhtWcPxl8Xdp3UaI2x0o5b0y0zx1I3bZv8ZriO84Ib9ln03ilXb3a1l5j2/IpLQxGwli7QHziWtNLlmDf910JQIKRsLAGzbY8j6h7jlF6Dl5aPk/X2k+lK/WLJUJPuYvlfSXbKO8vrChUUbwxeX7RiGXz9RQbeL6yHaRLbVKVeAOp46DZwutp+wyIX1CqnaBvcj9CbaELlrK2lajLCCX1we+RC46F2lbQkJQWV4pgLWWo3+2Eh+lx4CfU/fHlH8S2Xzzpt1/wG4tx3G/+wRidVPqnJ/4CmzZtGrudcTQvF+5MQnHoUDhpARGQvA73CotA1cG7C+76W6oYkJn2cx5jbjFP8Rxmyg7FwwnmnmyYzkODxlrRq+ReTVxP7iO4qWJZ0u64cysKx7Z1YqQbj1SfmaYjT46HQAGQF/I1n5xnLKQb1B4lKcN8ySLbSqRdH6qTJnVMvVpaX72byVicAaKk8DyjJyQgQSgKvY4r6fi0rZsr04db5680YJSeY2JolLWXCpnmxEN3dBCWwnpSWbUcwvYk2yWJ84spAJZ4jbltTeNcwDMhAbIesAo8nSKoKoOg2rXmbVKg83wN9ooYM4NBO9hP+j/tWAOl+4eGeYUbQY1NbZigemkFsNT6am6g0l/YONGS4EaN12XHe+KgdP0Arc7J8rYnbOscaUFC0ssDzMRps2kGB52UNhugLBgwG6NZ1dk+bkp4Lgo1qmkmSkuHHTuYqHiiEVRI8yq0MqAQPSXuEbM+xfk4hPl8O/JwFFA2EBTairxO5imx/Z2Vc0u6OdHuaNxmG7tyZTVYB+eMcAcxW5oBWJr+EZB5rtT3M4PfnQRElw6Qc5BDjtk3DigB1i7dX8XlscaE3qRgf7QqEi3LpAYp6eKcaTiyPsU7+g4wjaCC5nMSei36oG2qaey4R31rgAvaY6BM2OIXGrPzVITATHowCRuT/U1qXMiNPbl9bhltmKgm2XfvSc5j0e9GWpmaUn2h0wGlBE6qJ8js4bBMjY2JG/5kuVy70YXg7XbHirs/oe1VGbnTaH5Lu+ik9BS0DEvz2yYqU+oxFkFRSWvdLi+eg84MKupb+C5K7JPKsHuruCy/k5ptWGa8x1mJNM0lBEs0EfssMOznJLdfCVeyNfV5QUFXj/pFoGTy134hLIM6WltaOepFSqEz1l7QvgDM4Fcx6CMWQRlEElmojppCmpCXXLmag2IhLEtsKl2hOhb4SmCcKS8qN+gV9Nt6v/j1whubgbBip2M/187OfPUsx715seg9yQWjROgpC0paTQitATq4RO9MMSWCoGEhPdo282j53FXSJoT1q7JGpKy00CcK4/Edc5vCtZP2zGQoJkOwQr8zAaEuIdocsNvY1AX+pcCv0iY30IVzuJMB5Ux745Pa/c4Aj66dGVi8k7MBsR1F6j3J7UCau0M8LAoiH2algy5qUAJ+AYLoMbE+kkvVrVDGhoO+tnpSAibAylMoMujTHU/NUeXnHyXisPKCqkczhKq8vTZAFPKCfN5m1Ldqrqxc+RIYzzQY29YTj6tl2+H/EwVUobe0vUBxJjXroAS6wdL2kNyuJC4qsfW1SeCSmt/zsDTwVyuHF+1PWzghhUeDcy8DzMBr5OUZePnn4Jk9ns+BCzlfUumjDbagUDzvGG7n8oohUppfoLYeaefwbRsvsKQN1QsvBKRygxIakMkv0EKHY3LOlt38VuXHA6X20vVsm5koUaDek9wOpK0+oCcdBSVRwDcRajEwcx5YKjyaCsvyAUlceEF22ScLkLSsjFTXsnReTlKw2x2vXTFUqgzKKXCK7VHN8IDbakBXIaWX69Rnor1OcBTygOxp0knzApBSmRZ2tV6oJd1YCKAE8mBr8yskUtlk+2qWRT8nuR3Ks0y4O/MLOlOw5G35TCuELunZzPqtG45Cr6k8wSbevstrDUENoGJn+UGl66WRXXRTAMq5WjEqSrFFhWEJ5LvuX6pt8oV2hSPAvvcU8GlnBYSas5XAOdOkG+I2bbM6kTdJxykIn329lp2XXKCJ9os8WIvJvHFnHlzPCx+SwoNpwSIcIA1L7unR65qctPG8XnMiiQBlNvibLg5NyWsULi4qKdSrmJb2GKVrwc6Mt+CVAp80YGtllfxidd3Jkr5KvMcJDw7xMcuDMZcHpG/YJCWBlwjLqs+XjqmJhVkLQsrqozekrghKkHL8M0iaZFOJ3VIbCc+5GMqTgOTU+E2Mq4UPSSd2lQmOXiDqbYnAdPnUS+SNSRc2ddc8GBk0eR90FwRjbfRBK5DfzoZNOw4qQRg4dY1pIKzzsuG+LpCcjahQxi7Ns2slcWohbisH5iQ0o/YzNmWPPfMmtdCNSy49j8ZVl69gXFACfhwIp3EUWLrtnL2l+6KVy/Wh3vTMxoU181qYkEx9qYLb1QaYMKSM5EmyslG3xLbGO7XsDpLU4eXbqAs02XhVEn4dx5RIEiQ1T7IYkkLvBQdzHC8jfSMQNpyci8x2pLer9x9/VsOsWr1UWltJYdeCUOasAbONCkEJyDfbPFqlwhKQPcqUXZNUzusEJrNwZx4Qah6YMINKhXV8GTZgBWRjcKMOIINe0FXKm2R3jHE413qz+KKgSYhfZ4FN0nZbb7Ltxcj3qxUkbVxWalOUBM5sie4qAEzbgT6KLJQYrHqv4f9WSRfrIrqM0iZIN3zBggGeJ9gptCnZ1VltAMRVAEqAHQfFUwy/3uigtbSrw8GRBozCY2P7R0C2YyXPFeEuX1q9yk7uoJZyURtWT1y4E9xBYjx3RlCJcx3M34r5hQ2XKgdKbcWlVFZrU5Ni9yQOe/HqWqGcNC7xAuIAixaOcyEYs6FgG//cllaU56mw1BrJHJg2sMx+x+OCUmtTscHy/ui2kcq2g566vwmoR2AW77KlinbBPAIymGsDZkrWtP8DUJ0s0Z/1f3Zgw3oDofyg/mPp1lTnl63t82XrdqL2pLa1voQ/O5X/k8vZ5m9gMZpq/uzAsvza9kT7Wbt8G2Gfvq8Bs3XA6pJ+fFvk+4n+TJyv2ijVT/0l9l3tn5+L3B6eT85v6XyT7BLPG1e+PieDc9Wfj825j4HNXh/SNZiSUC1UdIHyfGd8y3ZLlbv++F9Olv0JNtPHv8A/27istp9RGe1PskvopyonDZqKRqPx/wr0jne8AytWrIAxBvfdd59a7lOf+hRe+tKX4oADDsAFF1yArVu3FrW/ICHZNeSiwjM1KEjg5ANwi8EpGKDYgCcOgAkYpAAqAosP9MKgnwKb9EcBG4CW/gnADYAo7JMImVLIaQBTvv/iv1Qb2rHXIE7PKQ47Ds/6PJLPVfkvGAuFc685v0medG3Q+iD12HWVU8mgnxycM7DkbU44QNNdGWCKZYQ6/PgV1W3zB+VY0js3vmvD4dh/JXrDG96Au+++G/vtt59a5qGHHsKVV16Ju+66C+vXr8djjz2G66+/vqj9Ptyak42vSbm6ftXxkAWv7xeBmbRpJeG7yIo2++rKKvZEi9UmNPCooVJpv1ieGgrM7He8L+HOiquVC6V/T9IonmhIWPVJw2xS1eIFhSb+7OHI0zRbybXBF5mln/UoMI/thxqWlcKxSrfzBoyaqH3C7iXDsaXtouw4BH3xz4VtzNbq1le96lXZMjfddBNWrlyJvfbaCwBw8cUXY82aNXjb296WrTvrnuQDDzyAo446CgcddBCOOOIIfP/73xfLdXWNVdE76a71yMBRFqZ1eeEtmOqhQr67T3oEKU8iE4JTw3KSx8b3mXk0UR9KPdU7Yu1FYUWax0OBA+tDgW37b/p2bZDowCARJQjaCssH3/cgtC97nBJhWR7JiM4jft6kzmWy3bTTAFI8R6F/HoOHRVI9TM2rnCuVHAfVJadlyJ9rOvLikN7X0vq5viRPNCdrgeFw/L8JaePGjYGnuWLFCmzcuLGo7qxD8qKLLsKFF16IH/7wh7j88stxzjnnRGXGcY0DlYCxBEaZNpPnfDTIhLD0ZRCWS52L0TktDXxskBXjMcJfBAYOMTqwOjukY8bm1CQQFsOeAYnPj0Xw1uyQ+o2Ok/SXO25yPQ3W6nkm2CcdgyJYQmhDOF+aczAEpC/H2xHaiNtibU5QxaCcr9JszQGTSFxIVwo8xPliW1JfbQANwI7s2H9btmzBsmXL/N/atWvTnc6AZhWSjz/+OL7zne/g937v9wAAp512Gh555BGsX78+KEddY2MMLr74Ytx4443lHUlw08q1aY+X19KRAKb/rICSfU6c+yIcwzbzA7n+R8BZMMAX2ZnYL21/IsiT45OFjvT9Svns2CVvdBJ9FN0oSeApsZXtN90WzyXt3Gb20vriOcjaicZwpRxXkmPqiSOrCJRz6U1qKoW5BMscKBWJQJX6SvSngtJtK7ZMYk5yp512wqZNm/zf6tWry3acafny5Xj44Yf99oYNG7B8+fKiurMKyUceeQR77703pqerqVBjDJYvXx65veO4xsXqevNZMPhwqaDk+Zlyan+pgU9oSw2hqu3boK5qg3CdZW5y47oa7Fmf2ZsLZR/T+8ns1+qUlpFgpQCsJAJHbSwab0tALNihpds2fZdKBJ6STjTv5xdnQh1BqdWPwTjJLxaAHY3/NyGddtppuPXWW/Hoo4/CWotrr70WZ555ZlHd7X7hztq1awMXfPTLX2LrR/90Di2aWW3ZsgU77bTTXJsxY1rI+7eQ9w3o92971zj7N/XMM8H2Ia/8Lfy/zfeMbdPee++dLXPRRRfhq1/9Kh599FG87nWvw84774z169dj1apVWLlyJVauXIn9998fV111FY4++mgAwHHHHYeLLrqoyAZj7ey9YO/xxx/HgQceiJ///OeYnp6GtRZ777037r77bhx44IG+3Ec/+lE8+OCDuPbaawEAX/va17BmzRrcfffd2T6WLVuGTZs2zdg+zLX6/dt+tZD3Dej3b3vXQt+/rprVcOvSpUtx+OGH4/Of/zwAYN26dVi2bFkASGA817hXr169evWalGZ9det1112H6667DgcddBA+/OEP49Of/jQAYNWqVbj11lsBIHCNDzzwQLzoRS8qdo179erVq1evSWnW5yQPPvhg3HNPHKv+5Cc/GWxfcMEFuOCCC1q333X10/aifv+2Xy3kfQP6/dvetdD3r6tmdU6yV69evXr12p406+HWXr169erVa3tRD8levXr16tVL0YKBZOk7YbdHlf4UzPaqZ599Fq9//etx0EEH4d/8m3+Df//v/330FqbtXSeeeCJe8YpX4NBDD8Wxxx6L733ve3Nt0sT16U9/GsYY3HLLLXNtykS1YsUKHHzwwTj00ENx6KGH4stf/vJcmzRRPffcc3j729+Ol770pTjkkEP8G9F61bILRMcff7z99Kc/ba219itf+Yp95StfObcGTVB/+7d/ax955BG733772e9973tzbc7E9cwzz9ivfvWrdjQaWWut/fM//3P76le/em6NmrB+8Ytf+M8333yzfcUrXjF3xsyAHnroIfvv/t2/s0ceeaT9q7/6q7k2Z6JaqNed0x/8wR/Yt7/97f7627x58xxbNL+0IDzJ0nfCbq961atehWXLls21GTOmF7zgBTj55JNhTPVarCOPPBIbNmyYW6MmrCVLlvjPTz31lN/XhaDRaIRVq1bhz//8z7HDDjvMtTm9WuhXv/oVPvWpT+GDH/ygPyfdz0n1qrQgIFn6Tthe24c+9rGP4ZRTTplrMyaut771rdh3331x5ZVX4i//8i/n2pyJae3atTj66KPx27/923NtyozprW99Kw455BCcf/75+OlPfzrX5kxMDz74IHbbbTesWbMGr3zlK3HsscfiG9/4xlybNa+0ICDZa+FozZo1WL9+PT70oQ/NtSkT1+c+9zk88sgj+MAHPoDLL798rs2ZiP7pn/4J69atwxVXXDHXpsyYvvWtb+H//J//g+9+97vYY489cPbZZ8+1SRPTtm3b8PDDD+M3f/M38Z3vfAd/9md/hje+8Y147LHH5tq0eaMFAcl9990XmzdvxrZt2wAA1lps3Lix+KdQes0PXX311bj55pvx13/913jhC1841+bMmM4++2x885vfxM9+9rO5NmVs3XXXXdiwYQNe+tKXYsWKFfi7v/s7XHjhhbjmmmvm2rSJyY0jixYtwh/8wR/grrvummOLJqfly5djMBjgzW9+MwDgsMMOw0te8hL83//7f+fYsvmjBQHJ0nfC9pq/Wrt2LW688UbcfvvtwfzdQtCTTz6Jn/zkJ377lltuwe67747ddtttDq2ajH7/938fmzdvxoYNG7BhwwYceeSRuP766/H7v//7c23aRPSrX/0KTz75pN++8cYbcdhhh82dQRPWHnvsgde85jX4m7/5GwDVD94/9NBD+Nf/+l/PsWXzR9v9T2U5XXfddTjnnHOwZs0aLF682L8TdiFI+ymYhaJNmzbhne98J/bff38cf/zxAIAddtgB99577xxbNhk99dRTOP300/HMM89gMBjgRS96EW677bYFtXhnoeqxxx7DaaedhuFwCGst9t9/f3zuc5+ba7MmqmuvvRbnn38+Lr/8cgwGA1x33XV48YtfPNdmzRv1r6Xr1atXr169FC2IcGuvXr169eo1E+oh2atXr169einqIdmrV69evXop6iHZq1evXr16Keoh2atXr169einqIdmrV69evXop6iHZq1evXr16Keoh2avXHOpnP/sZli9fjq985Ss+7bbbbsMJJ5wwh1b16tXLqX+ZQK9ec6xbb70Vf/EXf4FbbrkFW7ZsweGHH47bbrsNBx100Fyb1qvXr716T7JXrznWYYcdhu9///sAgCuuuAJvectbekD26jVPtGDe3dqr1/aqfffdFz/96U9x99134xvf+Ab+4R/+Ya5N6tWrV60ekr16zQMddNBBOOOMM/DlL38Zv/EbvzHX5vTq1atWD8leveaBXvayl+GQQw7BscceO9em9OrVi6ifk+zVax7o8ccfxxlnnDHXZvTq1YupX93aq9c80NKlS/H9738fL3rRi+balF69ehH1kOzVq1evXr0U9eHWXr169erVS1EPyV69evXq1UtRD8levXr16tVLUQ/JXr169erVS1EPyV69evXq1UtRD8levXr16tVLUQ/JXr169erVS1EPyV69evXq1UtRD8levXr16tVL0f8Pwv8e0FB37hQAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "f = pl.figure(figsize=(6, 6), dpi= 80, facecolor='w', edgecolor='k');\n", + "_=pl.xlabel(r'$\\gamma$')\n", + "_=pl.ylabel(r'$\\beta$')\n", + "ax = pl.gca()\n", + "_=pl.title('Expectation value')\n", + "im = ax.imshow(qaoaec.E,interpolation='bicubic',origin='lower',extent=[0,2*np.pi,0,np.pi])\n", + "divider = make_axes_locatable(ax)\n", + "cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n", + "_=pl.colorbar(im, cax=cax)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "4b7a095d", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "f = pl.figure(figsize=(6, 6), dpi= 80, facecolor='w', edgecolor='k');\n", + "_=pl.xlabel(r'$\\gamma$')\n", + "_=pl.ylabel(r'$\\beta$')\n", + "ax = pl.gca()\n", + "_=pl.title('Variance')\n", + "im = ax.imshow(qaoaec.Var,interpolation='bicubic',origin='lower',extent=[0,2*np.pi,0,np.pi])\n", + "divider = make_axes_locatable(ax)\n", + "cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n", + "_=pl.colorbar(im, cax=cax)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "764615ec", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 10%|█████████████████▌ | 1/10 [00:00<00:04, 2.20it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 1 )= 1.0079101562500001\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 20%|███████████████████████████████████ | 2/10 [00:01<00:06, 1.27it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 2 )= 0.6412109375\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 30%|████████████████████████████████████████████████████▌ | 3/10 [00:03<00:08, 1.24s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 3 )= 0.6564453124999999\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 40%|██████████████████████████████████████████████████████████████████████ | 4/10 [00:05<00:10, 1.75s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 4 )= 0.6349609375000003\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 50%|███████████████████████████████████████████████████████████████████████████████████████▌ | 5/10 [00:10<00:14, 2.91s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 5 )= 0.68896484375\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 60%|█████████████████████████████████████████████████████████████████████████████████████████████████████████ | 6/10 [00:17<00:17, 4.33s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 6 )= 0.4034179687500001\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 70%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍ | 7/10 [00:30<00:21, 7.21s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 7 )= 0.53681640625\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 80%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████ | 8/10 [00:42<00:16, 8.43s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 8 )= 0.66552734375\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 90%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌ | 9/10 [00:55<00:10, 10.02s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 9 )= 0.47822265625000016\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [01:10<00:00, 7.10s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 10 )= 0.33779296875000003\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "maxdepth=10\n", + "for i in tqdm(range(maxdepth)):\n", + " qaoaec.increase_depth(qasm_sim, 1024)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "b548a68b", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "hist=qaoaec.hist(qaoaec.angles_hist['d'+str(maxdepth)+'_final'], qasm_sim,1024)\n", + "plot_histogram(hist)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "07299158", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "hist=qaoaec.hist(qaoaec.angles_hist['d'+str(maxdepth)+'_final'], qasm_sim,1024)\n", + "plot_histogram(hist)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "24e089d8", + "metadata": {}, + "outputs": [], + "source": [ + "hist=qaoaec.hist(qaoaec.angles_hist['d'+str(maxdepth)+'_final'], qasm_sim,1024)\n", + "bins={}\n", + "for key in hist:\n", + " c=-qaoaec.cost(key[::-1])\n", + " bins[c]=bins.get(c,0)\n", + " bins[c]+=hist[key]\n", + "bins=dict(sorted(bins.items()))" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "641a1129", + "metadata": {}, + "outputs": [], + "source": [ + "bins_class={}\n", + "for c in costs:\n", + " bins_class[int(c)]=bins_class.get(int(c),0)\n", + " bins_class[int(c)]+=1\n", + "bins_class=dict(sorted(bins_class.items()))" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "95be5060", + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for i in range(1,maxdepth+1):\n", + " hist=qaoaec.hist(qaoaec.angles_hist['d'+str(i)+'_final'], qasm_sim,1024)\n", + " bins={}\n", + " for key in hist:\n", + " c=-qaoaec.cost(key[::-1])\n", + " bins[c]=bins.get(c,0)\n", + " bins[c]+=hist[key]\n", + " bins=dict(sorted(bins.items()))\n", + " max_val=max(costs)\n", + " min_val=min(costs)\n", + "\n", + " pl.figure(i, figsize=(25,10))\n", + " w=np.array(list(bins.values()))\n", + " c,d,_=pl.hist(bins.keys(),bins=10,weights=w, alpha = 0.5, color= 'r')\n", + " pl.clf()\n", + " pl.title(\"depth=\"+str(i))\n", + " a,b,_=pl.hist(np.sort(costs), bins=10, alpha = 0.5, color= 'b')\n", + " w=np.array(list(bins.values()))\n", + " pl.hist(bins.keys(),bins=20,weights=w/max(c)*max(a), alpha = 0.5, color= 'r')\n", + " min_ylim, max_ylim = pl.ylim()\n", + " max_ylim *=1.025\n", + " mean=np.mean(costs)\n", + " pl.axvline(mean, color='k', linestyle='dashed', linewidth=2)\n", + " _=pl.text(mean-1, max_ylim, 'mean = {:.2f}'.format(mean))\n", + " _=pl.xticks(np.arange(min_val, max_val, step=1))\n", + " pl.xlabel(\"cost\")\n", + " pl.savefig(\"animation\"+str(i).zfill(3))" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "b420c329", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pl.plot(np.arange(1,maxdepth+1), np.array(list(qaoaec.costval.values())),'o--')\n", + "pl.hlines(0, 1,maxdepth, linestyles=\"solid\", colors=\"black\")\n", + "pl.ylim(-0.01,1)\n", + "\n", + "_=pl.title('Cost')\n", + "_=pl.ylabel('cost')\n", + "_=pl.xlabel('depth')" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "2d2b1b32", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 23.57it/s]\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sp=np.zeros(maxdepth)\n", + "for i in tqdm(range(maxdepth)):\n", + " sp[i]=qaoaec.successProbability(qaoaec.angles_hist['d'+str(i+1)+'_final'], qasm_sim,1024)\n", + "pl.plot(np.arange(1,maxdepth+1), sp,'o--')\n", + "pl.hlines(1, 1,maxdepth, linestyles=\"solid\", colors=\"black\")\n", + "pl.ylim(0,1.01)\n", + "\n", + "_=pl.title('Success rate')\n", + "_=pl.ylabel('success probability')\n", + "_=pl.xlabel('depth')" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "e4ba6f7d", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pl.plot(np.arange(1,maxdepth+1),qaoaec.angles_hist['d'+str(maxdepth)+'_final'][::2],\"x-\",label='gamma')\n", + "pl.plot(np.arange(1,maxdepth+1),qaoaec.angles_hist['d'+str(maxdepth)+'_final'][1::2],\"o-\",label='beta')\n", + "\n", + "_=pl.title('Parameters')\n", + "_=pl.ylabel('parameter')\n", + "_=pl.xlabel('depth')\n", + "_=pl.legend()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9cc0fed2", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "769d6842", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/ExactCover/ExactCover 6 3.ipynb b/ExactCover/ExactCover 6 3.ipynb new file mode 100644 index 0000000..8df86b4 --- /dev/null +++ b/ExactCover/ExactCover 6 3.ipynb @@ -0,0 +1,736 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "e429c1ea", + "metadata": {}, + "outputs": [], + "source": [ + "#run: pip install openquantumcomputing\n", + "import sys\n", + "sys.path.insert(0, '/home/franzf/OpenQuantumComputing/OpenQuantumComputing/')\n", + "from openquantumcomputing.QAOAExactCover import QAOAExactCover" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "a25b06d2", + "metadata": {}, + "outputs": [], + "source": [ + "from qiskit import *\n", + "\n", + "import numpy as np\n", + "from tailassignment_loader import *\n", + "\n", + "import matplotlib.pyplot as pl\n", + "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", + "from qiskit.visualization import *\n", + "\n", + "from tqdm import tqdm" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "5a113cdc", + "metadata": {}, + "outputs": [], + "source": [ + "instances = 6\n", + "flights = 24\n", + "solutions = 3\n", + "\n", + "path_to_examples = \"tailassignment_samples/\"\n", + "\n", + "FR, CR, best_sol = load_FR_CR(path_to_examples + f'FRCR_{instances}_{flights}_{solutions}.txt')" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "ba34f8b6", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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8p/ILT1dxBM9n9joAAN7izNCKZx4Af/bZZ7V48WKnj3cmORYXFyfp7JxjJ0/an1K+5ZZbdP7559c8cAAAakHFE215uGXLlkmSEhMTK90mNTVVUtkEWXWGT6xqGMYOHTqoX79+jgdchfj4ePn4eGUe062axA7U4FvmV7jub6OkeuXznWXUCzz776wJlW+XfVqau6T88h83bNFTk8ZXM1rnWf2C9MbUvQ7v1zV2qL55xlbp+lZN2+vrOWefFs44dkCP/9/lmjzuGXWNHepMqKXiE+JVUOTdN5TqguD6URpz/4+Vrj/XdVDTayDj1+OKju5czWhRG1p2n6g+V75Y4Tp3tIOLv1ii+6+4uZrROo92sHI9Js5Wm77XVLjOVW2AVHkdmPnwP7R31RvVjNZ5ztQBIz9/ybj/CydNmlTtbdPT7ZNJfvnll9qyZUu193vvvfccjKrm3FEHTufn6Jn5k3TT6Nka3/82TX9tiN756gHdduHzDsfrCZ+/5Fl1wJUm3HCXQkLrKT0jXdHR0eVem4HZ3wPOv/z5mv09qOvn/+dhDv9s+PDh6t27tyT7CEyPPPKI02VVlhxLS0vTjBkz9Nprr0mS7r///tJ7dRXh3hcAoCYiIyO1ceNGp/b1ygTZwYMHJUmtWrWqcH1RUZHWrFkjqWyCLCEhoXT/oqIi+fmVf3tSUlLKbFvbzvwhipqxhP9a6bp6QVL9ao6K5ONT/W3/KL8g3y2T0gb61/7wTnkFuXrkvYvVv8OFunjg1BofL/3IEeUV5rogMlQlLK/qPzaqex04ew2UlBQzMbPBQltVPsahO9rB06dP0w5Wwl3tYNucnErX1XYbIEknTmR5RR1w9ecvGfd/YW5u9cs8M1RSXl6eQ/sZ0fa7ox14/bPpioxorQsH3C6LxaIZl7+nKS9008BOE9SlzWCHjuUJn7/kWXXAlUp+H1KypNj+XebPr83A7O8B51/+fM3+Hnj6+d9+++2lv8+cObN0pCRHVZUck6Q33nhD06dPV3x8vIYPH66EhAQlJSVVeCzufQEAjOKVCbJTp05JKjtP2B/Nnz9fmZmZCgsLU+vWrUuXd+/eXVarVfn5+dq4cWOFvcFWr14tSerbt2+5dVdccYUyMzPVsGFDXXjhhZo9e7YaNWpUo3Np1qwZT9G4QP2wym+UZFfjgd16gfabgiUlUnYVw9RVdixfFSkqKurcBdWQ1e8cXUBcYNX2hdqXvk1pmUlasa18r7y379mpJg1aVvt4zZo3pweZG/gH1aty/bmug5peAyVFeW65BlC5sJCASte5ox3097HRDlbCXe1ggH/l61zVBlR1rJAgf6+oA67+/CXj/i8MDq5+IunMUOSBgYEO7WdE21/bdWD97q+0Ytt8vfG3n2SxWCRJzRvF6qbRs/Xs/Bv0+vSfFGQNqfbxPOHzlzyrDriSj69v6b9RUVHlXpuB2d8Dzr/8+Zr9Pajr519SUlJpwikyMlLjx9tHt0lLS3N63rFzJcckyWaz6dVXX9XcuXMlSTfffLPuvffeCo/HvS8AQE1ERkY6va/FZrNVPpaIh+rQoYN27dqlf/3rX7rjjjvKrEtPT1fPnj2Vnp6ugQMHlia8zhg3bpy++OIL3XjjjXr77bfLrFu5cqWGDBkiq9Wqw4cPq0mTJpKkLVu2aN68eRo8eLBCQ0O1du1aPfXUU2rZsqU2btxY+sdkdZ06dap07rScnByFhFT/D2xULK9Quv8jydnKPmuC/Yn5rFxp1ieO7z+4rTSxl5OFO6C4QFpe8QhqdVbiNMnXanQU5vDwwnPf2K5MTa+BDs2lWyof9RZu8OtJ6QnnpxaocR0Y100a3tH58quLdrByP6ZI89Y5t29NP39JmjZCatPEuX0dQR2oPkfmktqxY4cuvfRSLViwQB07Vv9ibteunTOh1Yin1QFP+Pwlz6oDrvTkyx8qO+eU6oWG6IE7ri732gzM/h5w/uXP1+zvQV0//z/eU/qzCRMmaNGiRZKk2bNn6/7773f4+NVJjp0RERGh336zj2Sxbt069e/fv8Jjcu8LAGAUr3w8Y/jw4ZKkp59+ukz37Q0bNigxMVGZmZmSpG7dupXbd+bMmaUTlr7//vuly1NSUnTTTTdJkm699dbS5Jhk73k2Z84cjRs3TkOHDtX999+vDz/8UDt27NC8efNq4xThoEB/qXHVHWhqVXSEcWUDZxhZD7kGjNco1N4WGqUFdcBwRn4GFosURR3waAkJCVqzZo3bhhlH3UMdAADP17Nnz9Lf161z/MkpR5JjknTs2LHS+3Jdu3atcCoTAACM5JUJsnvvvVcNGzbU4cOH1bFjR3Xu3Fnx8fHq06eP2rRpo/PPP19S2fnHzujXr59mz54tm82mSZMmKSYmRt27d1e7du2UnJysvn37avbs2eeMYdy4cQoJCXF6cji4XsuGxpXdysCygTNa1WzE15qVzTVgOIvFuM/BYiFJWhc0DZesBt2TiAyXArgf4tH8/f0VEREhf38DM+0wFHUAADxf9+7dS3/ftGmTQ/s6mhz7czlBQUEe36sYAOB9vDJBFh0drVWrVmns2LEKDAzUgQMHFBERoddff11ffPFFmadXKnLvvfdqyZIlGjFihE6cOKHdu3crISFBTzzxhL7//nuHxtw/My8BjNe79bm3qQ0tG9pvSgJG6xkjGdEihQZKbZsZUDDK6d3GmHI7RklVTIEGN/H1sbcDRuhjUN2D6xw6dEi33367Dh06ZHQoMAh1AAA8X0TE2afWUlNTq72fs8kxSTp8+HDp7w0aNHAgWgAAap/XPsvbvn17ff755+WW5+Tk6MCBA/Lx8VGnTp0q3X/kyJEaOXKk0+UvXrxYp06dUp8+fZw+BlwrPlJqHGafh8edBjEKDeqIRmFS++bSziPuLbd/rOTn694yUbGuLaVPNkmn8t1bLu1g3TEwXlqb7N4y/X1JkHmDkydPavny5eXm94V5UAcAwPNNmTJFDRs2VECAY0+vTZw40ankmCS98847+u6775SXl6effvrJ4ZgBAKhNXpsgq8yOHTtks9mUkJDgUE+wqlxzzTVq06aNevToodDQUK1du1Zz5sxRt27ddOWVV7qkDNScj0Ua0k5asMF9ZdYLlLq1dF95wLkMaefeBJm/rzQg3n3loWr+vvYEydKf3VdmZLiUEOm+8lC16AgprqmUfNR9ZfZqTQ9CAACAumDbtm1O7ffSSy8pIiJC11xzjUPJMUnas2eP9uzZ41S5AADUNq8cYrEq27dvl1T58IrO6Nixoz755BNdd911Gj16tN555x1NnjxZK1askNVqdVk5qLkBcVKMG+dhuryvcfO9ABVp28y9Q6yN6So1CHFfeTi34R2lJvXcU5bFIl3Zz/6AAuqOy3pLfm76BlgvUBrXzT1lAQAAoPY8+uij6tGjh0PJMQAA6joSZC5w//33a/v27crOzlZhYaH279+vuXPnKjyciafqGh8f6S/97b0oHJF9WsrKtf9bXb1ipE7RjpVTlyzZ8K5GzLBozc+fGh0KXGxiLyks0LF9nLkGWjeShrR1rBzUPquf9Jd+js9H50wdSGzn3ocSXKGgME+PvHexJj2doFvndtV9b4xQWqabxySsZU3D7clrRzjz+Uv2B0U8sfdYQVG+Xvpkqq5/Ol6Tn+us2f+5xuiQUEfw/QgAYGYnT7p5zgoAAGqZ6fq21EaCDJ6laT3pir7S//1Q/X3mLnGsjOb1pYm9HdunLsk4dkBf/fim2rfsZ3QoqAUhAdL1g6TXlklFJdXbx9FrIDxIumagPSmNuqd1Y+nCHtL/Nld/H0frQGwTabSH/lc7pu8t6tNutCwWiz5d8y/N/fhmPXfbCqPDcqmh7aQDmdJPh8+9reT45y9J57f33AdF3v7y77JYLHrv3iRZLBYdy84wOiTDNW3aVPfdd5+aNm1qdCiGMfv3I+oAAAAAAG9jugTZsmXLjA4BdUCv1lJ+kbRgvWRz8bGbhUu3nS8Fe+jomiUlJZr78c264+KX9Ppn00uX55zO0uTnOim/8LQah7dQYXG+Mn7bp2E9r9X0y94yMGI4I66pdONg6d1VUmGxa49dL0i6bZjUMNS1x4VrJbaXCoqkr2phnuzWjaXJQx3vrVsXWP0D1bf9mNLX7Vv204Lvn5XkXe2gj4903UDpnZW1My/hoARpfHfXH9cdThec0pL1b+s/M1Nlsdj7WkbUs0+k5011wFGNGjXSpEmTjA7DMHw/og4AAAAA8D6mS5ABZwyMt/ekmf+jdLrANcds10y6dqBnDid1xsKVc9UxZqASonuWWR4aVF/nd7tKQQFhumbEQ9qw52vNW/ak1938MZMOUdKU86V/r7EPneYKLSLsvdMahbnmeKhdIzvbh9v8ZJPrEqU9WtnnHfOW+Rc/Wf1P9e94kSTvawf9fKWbhkifbJRW73XNMX0s0ugu9rnuLB4691x6ZorCgiM0b9mT2rz3WwX4B+naEbPUI36Y19UBR5w4cUJr165V//79TTmMON+PqAMAAAAAvI+X3L4CnNOtpX2epPk/1uwJ+kB/6eKeUt82nntDUJL2Z/ysVdsXau7tKytcn3xkqyYMmiZJ2pu6SXHNPbR7AErFNpHuG2sfam9divPH8fWRRnWWzu9g/x2eY0C8FB8pzVsr7fvV+eOEBkqX9Za6tnRdbEb7z3dP6khmsubc+l3pMm9rB319pEv7SF1aSvPWScdPOX+sqAbSVf3t/3qy4pIiHT1+UK2adNDNY2YrOW2L7ntjhN66Z4cahDX1ujpQXampqbr77ru1YMECr0uOTHupv9IyK84Sv3r3Fp3KO8H3I3l3HQAAAABgTiTIYHrhwfahwHYdkVYn2f+t7rCL9QKlfnHSwAT7nEue7ud9q3T0+AFNejpeknTsZIZeWHCLjmWna/yA27TvyFbFRdlv+uxN3aT+HS80Mly4SJDV3uOnb6z9Gth6SCqu5txkgf5SnzbSeQlS43q1GydqT+MwaeoI+3xUa5KkvUerv2+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+ "text/plain": [ + "
" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "params={'FR': FR}\n", + "params['usebarrier']=True\n", + "qaoaec = QAOAExactCover(params=params)\n", + "qaoaec.createCircuit(np.array((np.pi,2*np.pi)),1).draw(output='mpl')" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "8a71822c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[0. 1. 1. 0. 1. 0.]\n", + " [1. 0. 0. 1. 0. 1.]\n", + " [0. 1. 1. 0. 1. 0.]\n", + " [1. 0. 0. 1. 0. 1.]\n", + " [0. 1. 1. 0. 1. 0.]\n", + " [1. 0. 0. 1. 0. 1.]\n", + " [1. 0. 0. 1. 1. 0.]\n", + " [0. 1. 1. 0. 0. 1.]\n", + " [1. 0. 1. 0. 1. 0.]\n", + " [0. 1. 0. 1. 0. 1.]\n", + " [1. 0. 0. 1. 1. 0.]\n", + " [0. 1. 1. 0. 0. 1.]\n", + " [0. 1. 0. 1. 1. 0.]\n", + " [1. 0. 1. 0. 0. 1.]\n", + " [1. 0. 0. 1. 1. 0.]\n", + " [0. 1. 1. 0. 0. 1.]\n", + " [1. 0. 1. 0. 0. 1.]\n", + " [0. 1. 0. 1. 1. 0.]\n", + " [1. 0. 1. 0. 0. 1.]\n", + " [0. 1. 0. 1. 1. 0.]\n", + " [1. 0. 1. 0. 0. 1.]\n", + " [0. 1. 0. 1. 1. 0.]\n", + " [1. 0. 1. 0. 0. 1.]\n", + " [0. 1. 0. 1. 1. 0.]]\n", + "solutions:\n", + "000011 0.0\n", + "001100 0.0\n", + "110000 0.0\n" + ] + } + ], + "source": [ + "import itertools\n", + "print(FR)\n", + "nL=FR.shape[1]\n", + "print(\"solutions:\")\n", + "costs=[]\n", + "for s in [''.join(i) for i in itertools.product('01', repeat =nL)]:\n", + " costs.append(-qaoaec.cost(s))\n", + " if qaoaec.isFeasible(s):\n", + " print(s, -qaoaec.cost(s))" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "bbe8089d", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "max_val=max(costs)\n", + "\n", + "pl.figure(figsize=(25,10))\n", + "a=pl.hist(np.sort(costs), bins=200)\n", + "min_ylim, max_ylim = pl.ylim()\n", + "max_ylim *=1.025\n", + "mean=np.mean(costs)\n", + "pl.axvline(mean, color='k', linestyle='dashed', linewidth=2)\n", + "a=pl.text(mean-1, max_ylim, 'mean = {:.2f}'.format(mean))\n", + "a=pl.xticks(np.arange(0, max_val, step=10))" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "a4fcccfa", + "metadata": {}, + "outputs": [], + "source": [ + "qasm_sim = Aer.get_backend('qasm_simulator')" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "112c880a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Calculating Energy landscape for depth p=1...\n", + "Calculating Energy landscape done\n" + ] + } + ], + "source": [ + "qaoaec.sample_cost_landscape(qasm_sim, 1024, angles={\"gamma\": [0,np.pi,30], \"beta\": [0,np.pi/2,20]})" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "411cbd19", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "f = pl.figure(figsize=(6, 6), dpi= 80, facecolor='w', edgecolor='k');\n", + "_=pl.xlabel(r'$\\gamma$')\n", + "_=pl.ylabel(r'$\\beta$')\n", + "ax = pl.gca()\n", + "_=pl.title('Expectation value')\n", + "im = ax.imshow(qaoaec.E,interpolation='bicubic',origin='lower',extent=[0,np.pi,0,np.pi/2])\n", + "divider = make_axes_locatable(ax)\n", + "cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n", + "_=pl.colorbar(im, cax=cax)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "becf35c6", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "f = pl.figure(figsize=(6, 6), dpi= 80, facecolor='w', edgecolor='k');\n", + "_=pl.xlabel(r'$\\gamma$')\n", + "_=pl.ylabel(r'$\\beta$')\n", + "ax = pl.gca()\n", + "_=pl.title('Variance')\n", + "im = ax.imshow(qaoaec.Var,interpolation='bicubic',origin='lower',extent=[0,np.pi,0,np.pi/2])\n", + "divider = make_axes_locatable(ax)\n", + "cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n", + "_=pl.colorbar(im, cax=cax)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "9bb7d8d6", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 10%|█████████████████▌ | 1/10 [00:01<00:11, 1.33s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 1 )= 10.298828124999998\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 20%|███████████████████████████████████ | 2/10 [00:04<00:19, 2.44s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 2 )= 10.130859375000002\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 30%|████████████████████████████████████████████████████▌ | 3/10 [00:09<00:24, 3.57s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 3 )= 9.669921875\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 40%|██████████████████████████████████████████████████████████████████████ | 4/10 [00:16<00:29, 4.92s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 4 )= 9.400390625000002\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 50%|███████████████████████████████████████████████████████████████████████████████████████▌ | 5/10 [00:24<00:30, 6.13s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 5 )= 9.296875000000002\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 60%|█████████████████████████████████████████████████████████████████████████████████████████████████████████ | 6/10 [00:37<00:33, 8.34s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 6 )= 9.574218750000002\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 70%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▍ | 7/10 [00:56<00:35, 11.72s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 7 )= 5.863281249999998\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 80%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████ | 8/10 [01:13<00:26, 13.46s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 8 )= 8.617187500000002\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 90%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌ | 9/10 [01:43<00:18, 18.58s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 9 )= 8.757812499999998\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [02:20<00:00, 14.10s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 10 )= 11.976562500000002\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "maxdepth=10\n", + "for i in tqdm(range(maxdepth)):\n", + " qaoaec.increase_depth(qasm_sim, 2*1024)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "fb39857a", + "metadata": {}, + "outputs": [], + "source": [ + "hist=qaoaec.hist(qaoaec.angles_hist['d10_final'], qasm_sim,1024)\n", + "bins={}\n", + "for key in hist:\n", + " c=-qaoaec.cost(key[::-1])\n", + " bins[c]=bins.get(c,0)\n", + " bins[c]+=hist[key]\n", + "bins=dict(sorted(bins.items()))" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "033178ec", + "metadata": {}, + "outputs": [], + "source": [ + "bins_class={}\n", + "for c in costs:\n", + " bins_class[int(c)]=bins_class.get(int(c),0)\n", + " bins_class[int(c)]+=1\n", + "bins_class=dict(sorted(bins_class.items()))" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "95510dda", + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for i in range(1,maxdepth+1):\n", + " hist=qaoaec.hist(qaoaec.angles_hist['d'+str(i)+'_final'], qasm_sim,1024)\n", + " bins={}\n", + " for key in hist:\n", + " c=-qaoaec.cost(key[::-1])\n", + " bins[c]=bins.get(c,0)\n", + " bins[c]+=hist[key]\n", + " bins=dict(sorted(bins.items()))\n", + " max_val=max(costs)\n", + " min_val=min(costs)\n", + "\n", + " pl.figure(i, figsize=(25,10))\n", + " w=np.array(list(bins.values()))\n", + " c,d,_=pl.hist(bins.keys(),bins=10,weights=w, alpha = 0.5, color= 'r')\n", + " pl.clf()\n", + " pl.title(\"depth=\"+str(i))\n", + " a,b,_=pl.hist(np.sort(costs), bins=10, alpha = 0.5, color= 'b')\n", + " w=np.array(list(bins.values()))\n", + " pl.hist(bins.keys(),bins=20,weights=w/max(c)*max(a), alpha = 0.5, color= 'r')\n", + " min_ylim, max_ylim = pl.ylim()\n", + " max_ylim *=1.025\n", + " mean=np.mean(costs)\n", + " pl.axvline(mean, color='k', linestyle='dashed', linewidth=2)\n", + " _=pl.text(mean-1, max_ylim, 'mean = {:.2f}'.format(mean))\n", + " _=pl.xticks(np.arange(min_val, max_val, step=20))\n", + " pl.xlabel(\"cost\")\n", + " pl.savefig(\"animation\"+str(i).zfill(3))" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "6c96a550", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pl.plot(np.arange(1,maxdepth+1), np.array(list(qaoaec.costval.values())),'o--')\n", + "pl.hlines(0, 1,maxdepth, linestyles=\"solid\", colors=\"black\")\n", + "# pl.ylim(-0.01,1)\n", + "_=pl.title('Cost')\n", + "_=pl.ylabel('cost')\n", + "_=pl.xlabel('depth')" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "3d62f3ba", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 10.72it/s]\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sp=np.zeros(maxdepth)\n", + "for i in tqdm(range(maxdepth)):\n", + " sp[i]=qaoaec.successProbability(qaoaec.angles_hist['d'+str(i+1)+'_final'], qasm_sim,1024)\n", + "pl.plot(np.arange(1,maxdepth+1), sp,'o--')\n", + "pl.hlines(1, 1,maxdepth, linestyles=\"solid\", colors=\"black\")\n", + "pl.ylim(0,1.01)\n", + "_=pl.title('Success rate')\n", + "_=pl.ylabel('success probability')\n", + "_=pl.xlabel('depth')" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "1ed37e8a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pl.plot(np.arange(1,maxdepth+1),qaoaec.angles_hist['d'+str(maxdepth)+'_final'][::2],\"x-\",label='gamma')\n", + "pl.plot(np.arange(1,maxdepth+1),qaoaec.angles_hist['d'+str(maxdepth)+'_final'][1::2],\"o-\",label='beta')\n", + "\n", + "_=pl.title('Parameters')\n", + "_=pl.ylabel('parameter')\n", + "_=pl.xlabel('depth')\n", + "_=pl.legend()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b781c7c4", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "291bca4d", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bde1dbfc", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ca8f3a6d", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a7049786", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/ExactCover/tailassignment_loader.py b/ExactCover/tailassignment_loader.py new file mode 100644 index 0000000..7158a4f --- /dev/null +++ b/ExactCover/tailassignment_loader.py @@ -0,0 +1,60 @@ +import numpy as np +import os, sys + +def load_FR_CR(filename): + + if not os.path.isfile(filename): + print("File not found.") + raise IOError + + # Matrix in file on format + # C_1: index of ones in row 1 separated by comma + # C_2: index of ones in row 2 ... + # ... + # C_R: index of ones in row R + # best state + + file = np.loadtxt(filename, dtype = str) + + R,F = filename.split('/')[-1].split('_')[1:3] + R,F = int(R), int(F) + + FR = np.zeros((F,R)) + CR = np.zeros(R) + best = np.zeros(R) + + for r in range(R): + CR[r] = float(file[r].split(':')[0]) + indexes = file[r].split(':')[1].split(',') + for ind in indexes: + FR[int(ind), r ] = 1 + + best_str = file[R].split(',') + best = np.array([int(i) for i in best_str]) + + return FR, CR, best + +def npy_loader(filename): + """ + Loading the examples saved on npy format. + + Parameters + ---------- + filename : string + filename + + Returns + ------- + FR : array + Constraint matrix + CR : array + Weights + + """ + matrix = np.load(filename) + + # The costs are saved in the last column + CR = matrix[-1] + FR = matrix[:-1] + + return FR, CR diff --git a/ExactCover/tailassignment_samples/FRCR_11_16_4.txt b/ExactCover/tailassignment_samples/FRCR_11_16_4.txt new file mode 100644 index 0000000..cece8ec --- /dev/null +++ b/ExactCover/tailassignment_samples/FRCR_11_16_4.txt @@ -0,0 +1,12 @@ +5:2,8,9,10,11,15 +8:0,1,3,4,5,6,7,12,13,14 +5:8,9,10,11,15 +2:3,4,13 +4:0,1,2,5,6,7,12,14 +1:0,1,5,6,7,12,14 +4:3,4,7,8,15 +7:0,1,4,12,13,14,15 +3:2,6,9,10,11 +15:3,5 +6:2,6,7,8,9,10,11 +0,0,0,0,0,1,0,1,0,0,1 diff --git a/ExactCover/tailassignment_samples/FRCR_14_24_5.txt b/ExactCover/tailassignment_samples/FRCR_14_24_5.txt new file mode 100644 index 0000000..1f39756 --- /dev/null +++ b/ExactCover/tailassignment_samples/FRCR_14_24_5.txt @@ -0,0 +1,15 @@ +3:1,3,5,6,8,11,13,15,16,19,21,23 +2:0,2,4,7,9,10,12,14,17,18,20,22 +9:0,2,4,7,8,11,13,15,16,18,20,23 +14:1,3,5,6,9,10,12,14,17,19,21,22 +3:0,2,4,7,9,11,12,15,17,19,21,23 +8:1,3,5,6,8,10,13,14,16,18,20,22 +2:0,2,4,7,9,11,12,14,16,18,20,22 +5:1,3,5,6,8,10,13,15,17,19,21,23 +6:1,3,5,7,9,11,13,15,17,19,20,22 +10:0,2,4,6,8,10,12,14,16,18,21,23 +1:0,2,4,7,9,11,13,15,17,19,21,23 +13:0,2,4,6,8,10,12,14,17,18,20,22 +11:1,3,5,6,9,11,13,14,16,18,20,22 +4:0,2,4,7,9,11,13,15,16,18,20,23 +1,1,0,0,0,0,0,0,0,0,0,0,0,0 diff --git a/ExactCover/tailassignment_samples/FRCR_4_3_2.txt b/ExactCover/tailassignment_samples/FRCR_4_3_2.txt new file mode 100644 index 0000000..b2db5bf --- /dev/null +++ b/ExactCover/tailassignment_samples/FRCR_4_3_2.txt @@ -0,0 +1,5 @@ +0.5:0,1 +0.1:2 +0.1:0 +0.1:1 +0,1,1,1 diff --git a/ExactCover/tailassignment_samples/FRCR_6_24_3.txt b/ExactCover/tailassignment_samples/FRCR_6_24_3.txt new file mode 100644 index 0000000..3a7600c --- /dev/null +++ b/ExactCover/tailassignment_samples/FRCR_6_24_3.txt @@ -0,0 +1,7 @@ +4:1,3,5,6,8,10,13,14,16,18,20,22 +2:0,2,4,7,9,11,12,15,17,19,21,23 +3:0,2,4,7,8,11,13,15,16,18,20,22 +7:1,3,5,6,9,10,12,14,17,19,21,23 +6:0,2,4,6,8,10,12,14,17,19,21,23 +1:1,3,5,7,9,11,13,15,16,18,20,22 +1,1,0,0,0,0 diff --git a/ExactCover/tailassignment_samples/FRCR_8_24_4.txt b/ExactCover/tailassignment_samples/FRCR_8_24_4.txt new file mode 100644 index 0000000..50f58d8 --- /dev/null +++ b/ExactCover/tailassignment_samples/FRCR_8_24_4.txt @@ -0,0 +1,9 @@ +2:0,2,4,6,8,10,12,14,16,18,20,22 +1:1,3,5,7,9,11,13,15,17,19,21,23 +6:0,2,4,7,8,11,13,15,16,18,20,23 +8:1,3,5,6,9,10,12,14,17,19,21,22 +7:0,2,4,7,9,10,13,15,17,19,21,22 +5:1,3,5,6,8,11,12,14,16,18,20,23 +3:0,2,4,7,9,10,12,14,16,18,20,23 +4:1,3,5,6,8,11,13,15,17,19,21,22 +1,1,0,0,0,0,0,0 diff --git a/Fourier analysis.ipynb b/Fourier analysis.ipynb deleted file mode 100644 index d13db03..0000000 --- a/Fourier analysis.ipynb +++ /dev/null @@ -1,343 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Fourier analysis\n", - "\n", - "This notebook demonstrates the typical spatial frequencies found in QAOA." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from qiskit import *\n", - "import numpy as np\n", - "import pylab as pl\n", - "import networkx as nx\n", - "from qiskit.visualization import *\n", - "from qaoa import *\n", - "from pylab import cm\n", - "\n", - "from matplotlib import rc,patches\n", - "from scipy import optimize as opt\n", - "\n", - "# Sampling parameters\n", - "SAMPLING_E_ATOL = 1e-2\n", - "SAMPLING_E_RTOL = 1e-2\n", - "SAMPLING_DELTA_V_RTOL = 1e-2\n", - "MIN_SAMPLES = 256\n", - "MAX_SAMPLES = 32768*32\n", - "SAMPLING_CONF_IDX = 3\n", - "LANDSCAPE_RESOLUTION = 12\n", - "\n", - "# Other parameters\n", - "WEIGHT_DECIMALS = 1\n", - "CIRCUIT_VERSION = 1\n", - "CIRCUIT_DEPTH = 1\n", - "\n", - "font = {'size' : 16}\n", - "rc('font', **font);\n", - "rc('text', usetex=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.0 %\r", - "100%\n", - "Max cost: 3\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "V = np.arange(0,6,1)\n", - "E =[(0,1),(0,2),(2,3),(3,1),(3,4),(4,2),(0,5)]\n", - "G = nx.Graph()\n", - "G.add_nodes_from(V)\n", - "G.add_edges_from(E)\n", - "addWeights_MaxCut(G,decimals=WEIGHT_DECIMALS)\n", - "weights = [G[i][j]['weight'] for i,j in G.edges()]\n", - "\n", - "pl.figure(figsize=(10,6))\n", - "pos = nx.spring_layout(G)\n", - "labels = nx.get_edge_attributes(G,'weight')\n", - "nx.draw_networkx(G,pos)\n", - "nx.draw_networkx_edge_labels(G,pos,edge_labels=labels)\n", - "\n", - "V1 = np.arange(0,)\n", - "costs=costsHist_MaxCut(G)\n", - "max_cost = max(costs)\n", - "print('Max cost: %d' % max_cost)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "backend_sim = Aer.get_backend('qasm_simulator')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Calculate the typical maximum frequencies and use this to choose the number of sampling points." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "gamma_typ_freq: 0.25\n", - "beta_typ_freq: 0.78\n", - "landscape_n_gamma: 753\n", - "landscape_n_beta: 18\n" - ] - } - ], - "source": [ - "(gamma_min,gamma_max),(beta_min,beta_max) = parameterBounds_MaxCut(G,decimals=WEIGHT_DECIMALS)\n", - "gamma_period = (gamma_max-gamma_min)*2\n", - "beta_period = beta_max-beta_min\n", - "\n", - "gamma_typ_freq,beta_typ_freq = spatialFrequencies_MaxCut(G)\n", - "\n", - "landscape_n_gamma = int(gamma_period*LANDSCAPE_RESOLUTION*np.ceil(gamma_typ_freq))\n", - "landscape_n_beta = int(beta_period*LANDSCAPE_RESOLUTION*np.ceil(beta_typ_freq))\n", - "landscape_delta_gamma = (gamma_max-gamma_min)/landscape_n_gamma\n", - "landscape_delta_beta = (beta_max-beta_min)/landscape_n_beta\n", - "\n", - "print('gamma_typ_freq: %.2f' % gamma_typ_freq)\n", - "print('beta_typ_freq: %.2f' % beta_typ_freq)\n", - "print('landscape_n_gamma: %d' % landscape_n_gamma)\n", - "print('landscape_n_beta: %d' % landscape_n_beta)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "99.99%\r" - ] - } - ], - "source": [ - "gammas_landscape = np.linspace(gamma_min,gamma_max,landscape_n_gamma)\n", - "betas_landscape = np.linspace(beta_min,beta_max,landscape_n_beta)\n", - "\n", - "E_landscape = np.zeros((landscape_n_beta,landscape_n_gamma))\n", - "circuits=[]\n", - "for i in range(landscape_n_beta):\n", - " for j in range(landscape_n_gamma):\n", - " beta = betas_landscape[i]\n", - " gamma = gammas_landscape[j]\n", - " circuit = createCircuit_MaxCut(np.array((gamma,beta)),G,CIRCUIT_DEPTH,CIRCUIT_VERSION)\n", - " [E_list,_,_] = sampleUntilPrecision_MaxCut(circuit,G,backend_sim,None,MIN_SAMPLES,\n", - " MAX_SAMPLES,SAMPLING_E_ATOL,SAMPLING_E_RTOL,\n", - " SAMPLING_DELTA_V_RTOL,SAMPLING_CONF_IDX)\n", - " E_landscape[i,j] = -E_list[-1]\n", - " print('%.2f%%' % ((i*landscape_n_gamma+j)*100/(landscape_n_gamma*landscape_n_beta)),end='\\r')\n", - " " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "First visualize the landscape to predict approximately what is the frequency support." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure(figsize=(10,6))\n", - "pl.imshow(np.array(E_landscape).reshape(landscape_n_beta,landscape_n_gamma),\n", - " origin='lower',interpolation='bicubic',cmap=cm.jet,aspect='auto',\n", - " extent=[gammas_landscape[0],gammas_landscape[-1],betas_landscape[0],betas_landscape[-1]])\n", - "cbar = pl.colorbar(orientation=\"horizontal\", pad=0.2)\n", - "cbar.set_label('Cost')\n", - "\n", - "pl.xlabel(r'$\\gamma$')\n", - "pl.ylabel(r'$\\beta$')\n", - "pl.title('Optimization landscape')\n", - "pl.savefig('fourier_landscape.svg')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Show the frequency spectrum and the predicted support." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "E_landscape_mean = np.mean(E_landscape)\n", - "Efreq_landscape = np.abs(np.fft.fft2(E_landscape-E_landscape_mean)*landscape_delta_gamma*landscape_delta_beta)**2\n", - "gamma_freqs = np.fft.fftfreq(landscape_n_gamma,landscape_delta_gamma)\n", - "beta_freqs = np.fft.fftfreq(landscape_n_beta,landscape_delta_beta)\n", - "\n", - "Efreq_landscape = np.fft.fftshift(Efreq_landscape)\n", - "gamma_freqs = np.fft.fftshift(gamma_freqs)\n", - "beta_freqs = np.fft.fftshift(beta_freqs)\n", - "\n", - "pl.figure(figsize=(10,6))\n", - "pl.imshow(np.array(Efreq_landscape).reshape(landscape_n_beta,landscape_n_gamma),\n", - " origin='lower',interpolation='bicubic',cmap=cm.jet,aspect='auto',\n", - " extent=[gamma_freqs[0],gamma_freqs[-1],beta_freqs[0],beta_freqs[-1]])\n", - "prediction_rect = patches.Rectangle((-gamma_typ_freq,-beta_typ_freq),2*gamma_typ_freq,2*beta_typ_freq,\n", - " linewidth=1,edgecolor='k',facecolor='none',label='Prediction')\n", - "pl.gca().add_patch(prediction_rect)\n", - "pl.legend()\n", - "\n", - "cbar = pl.colorbar(orientation=\"horizontal\", pad=0.2)\n", - "cbar.set_label('Power')\n", - "\n", - "pl.xlabel(r'$f_\\gamma$')\n", - "pl.ylabel(r'$f_\\beta$')\n", - "pl.title('Fourier landscape')\n", - "pl.xlim(-3*gamma_typ_freq,3*gamma_typ_freq)\n", - "pl.ylim(-3*beta_typ_freq,3*beta_typ_freq)\n", - "pl.savefig('fourier_2d.svg')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now sum over each orthogonal axis for 1D plots." - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "gamma_power = np.trapz(Efreq_landscape,axis=0,dx=landscape_delta_beta)\n", - "beta_power = np.trapz(Efreq_landscape,axis=1,dx=landscape_delta_gamma)\n", - "\n", - "pl.figure(figsize=(10,12))\n", - "pl.subplot(2,1,1)\n", - "pl.plot(gamma_freqs,gamma_power,label='Spectrum')\n", - "pl.axvline(gamma_typ_freq,linestyle='-',color='k',label='Prediction')\n", - "pl.axvline(-gamma_typ_freq,linestyle='-',color='k',label='Prediction')\n", - "pl.xlabel(r'$f_\\gamma$')\n", - "pl.ylabel(r'Power')\n", - "pl.title('Gamma power spectrum')\n", - "pl.legend()\n", - "\n", - "pl.subplot(2,1,2)\n", - "pl.plot(beta_freqs,beta_power,'-+',label='Spectrum')\n", - "pl.axvline(beta_typ_freq,linestyle='-',color='k',label='Prediction')\n", - "pl.axvline(-beta_typ_freq,linestyle='-',color='k',label='Prediction')\n", - "pl.xlabel(r'$f_\\beta$')\n", - "pl.ylabel(r'Power')\n", - "pl.title('Beta power spectrum')\n", - "\n", - "pl.tight_layout()\n", - "pl.savefig('fourier_1d.svg')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/Generic MaxCut 14.ipynb b/Generic MaxCut 14.ipynb deleted file mode 100644 index 90dcfcc..0000000 --- a/Generic MaxCut 14.ipynb +++ /dev/null @@ -1,527 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from qiskit import *\n", - "from qiskit.tools.monitor import job_monitor\n", - "\n", - "import numpy as np\n", - "import pylab as pl\n", - "\n", - "import networkx as nx\n", - "from qiskit.visualization import *\n", - "from scipy import optimize as opt\n", - "from qaoa import *\n", - "import os\n", - "from matplotlib import rc\n", - "font = {'size' : 16}\n", - "rc('font', **font);\n", - "rc('text', usetex=True)\n", - "\n", - "import sys\n", - "sys.path.append('../')\n", - "\n", - "from qiskit_utilities.utilities import *" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Let us import and draw the graph" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "k_cuts=2\n", - "numV=14\n", - "G = nx.read_gml(\"../data/sample_graphs/w_ba_n\"+str(numV)+\"_k4_0.gml\")\n", - "pos = nx.spring_layout(G)\n", - "nx.draw_networkx(G,pos=pos)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Draw the histogram of number of solutions for value of cost function" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "100%5 %\n" - ] - } - ], - "source": [ - "costs=costsHist_MaxCut(G,k_cuts)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "cost of optimal solution(s) = 17.158916153194056\n" - ] - } - ], - "source": [ - "max_val=max(costs)\n", - "print(\"cost of optimal solution(s) = \", max_val)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure(figsize=(25,10))\n", - "a=pl.hist(np.sort(costs), bins=200)\n", - "min_ylim, max_ylim = pl.ylim()\n", - "max_ylim *=1.025\n", - "mean=np.mean(costs)\n", - "pl.axvline(mean, color='k', linestyle='dashed', linewidth=2)\n", - "a=pl.text(mean-1, max_ylim, 'mean = {:.2f}'.format(mean))\n", - "a=pl.xticks(np.arange(0, max_val, step=1))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Only 3.44% of all solutions have a cost of 14 or higher" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "There are 564 solutions with cost 14 or higher, which is 3.4423828125 % of all solutions.\n" - ] - } - ], - "source": [ - "num_good_solutions=0\n", - "for i in range(0,costs.shape[0]):\n", - " if costs[i]>=14:\n", - " num_good_solutions+=1\n", - "print(\"There are\", num_good_solutions, \"solutions with cost 14 or higher, which is\", num_good_solutions/2**numV*100, \"% of all solutions.\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### There is only 1 optimal solution (modulo symmetry)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "There are 2 solutions with maximum cost = 17.158916153194056 , which is 0.01220703125 % of all solutions.\n" - ] - } - ], - "source": [ - "num_optimal_solutions=0\n", - "for i in range(0,costs.shape[0]):\n", - " if costs[i]>=max_val:\n", - " num_optimal_solutions+=1\n", - "print(\"There are\", num_optimal_solutions, \"solutions with maximum cost =\",\n", - " max_val ,\", which is\", num_optimal_solutions/2**numV*100, \"% of all solutions.\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Calculate the energy landscape (this takes time)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "Aer.backends()\n", - "backend_sim = Aer.get_backend('qasm_simulator')" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "version=1\n", - "circuits=[]\n", - "n=12\n", - "m=48\n", - "beta_max=np.pi/2\n", - "gamma_max=np.pi\n", - "job_string=\"w_ba_n\"+str(numV)+\"_k4_0_\"+str(n)+\"x\"+str(m)\n", - "\n", - "if os.path.isfile(\"../data/sample_graphs/\"+job_string+\"_Elandscape_v1.npy\"):\n", - " Elandscape_v1 = np.load(\"../data/sample_graphs/\"+job_string+\"_Elandscape_v1.npy\")\n", - "else:\n", - " for beta in np.linspace(0,beta_max,n):\n", - " for gamma in np.linspace(0,gamma_max,m):\n", - " circuits.append(createCircuit_MaxCut(np.array((gamma,beta)),G,1,k_cuts,version))\n", - " job_sim = execute(circuits, backend_sim, shots=1024*2*2*2)\n", - " Elandscape_v1,_,_ = measurementStatistics_MaxCut(job_sim.result().results, options={'G' : G, 'k_cuts' : k_cuts})\n", - " np.save(\"../data/sample_graphs/\"+job_string+\"_Elandscape_v1\", Elandscape_v1)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Define function for the optimizer" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "def getval(x, backend, depth=1, version=1, noisemodel=None):\n", - " j = execute(createCircuit_MaxCut(x,G,depth,k_cuts,version), backend, noise_model=noisemodel, shots=1024*2*2*2)\n", - " val,_,_=measurementStatistics_MaxCut(j.result().results, options={'G' : G, 'k_cuts' : k_cuts})\n", - " global it, values, gamma, beta\n", - " print(x)\n", - " it+=1\n", - " gamma[str(it)] = x[0]\n", - " beta[str(it)] = x[1]\n", - " values[str(it)] = val\n", - " return -val[0]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Run the optimization using Nelder-Mead (derivative free method)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[0.7 0.25]\n", - "[0.735 0.25 ]\n", - "[0.7 0.2625]\n", - "[0.735 0.2375]\n", - "[0.72625 0.24375]\n", - "[0.69125 0.24375]\n", - "[0.665 0.25 ]\n", - "[0.7109375 0.2453125]\n", - "[0.695625 0.246875]\n", - "[0.713125 0.246875]\n", - "[0.7175 0.25 ]\n", - "[0.704375 0.253125]\n", - "[0.7065625 0.2515625]\n", - "[0.70875 0.25 ]\n", - "[0.7065625 0.2484375]\n", - "Optimization terminated successfully.\n", - " Current function value: -11.219496\n", - " Iterations: 6\n", - " Function evaluations: 15\n", - "Optimal value= [0.7 0.25]\n" - ] - }, - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "version=1\n", - "it=0\n", - "gamma={}\n", - "beta={}\n", - "values={}\n", - "xin=(.7,0.25)\n", - "out=opt.minimize(getval, x0=xin, method='Nelder-Mead',\\\n", - " args=(backend_sim,1,version,None),\\\n", - " options={'xatol': 1e-2, 'fatol': 1e-1, 'disp': True})\n", - "print(\"Optimal value=\",out.x)\n", - "f = pl.figure(figsize=(10, 6), dpi= 80, facecolor='w', edgecolor='k');\n", - "pl.plot(list(values.values()),'x-')\n", - "\n", - "f = pl.figure(figsize=(10, 6), dpi= 80, facecolor='w', edgecolor='k');\n", - "pl.imshow(-np.array(Elandscape_v1).reshape(n,m),interpolation='bicubic',origin='lower',extent=[0,gamma_max,0,beta_max])\n", - "pl.colorbar(orientation=\"horizontal\", pad=0.2)\n", - "pl.xlabel(r'$\\gamma$')\n", - "pl.ylabel(r'$\\beta$')\n", - "pl.plot(list(gamma.values()),list(beta.values()),'ko-')\n", - "pl.plot(xin[0],xin[1],'or')\n", - "pl.plot(out.x[0],out.x[1],'xr')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Pick the best solution and its parameters along the optimization path" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[11.21949597377502] (0.7, 0.25)\n" - ] - } - ], - "source": [ - "tmp = max(values, key=values.get)\n", - "x_best=(gamma[tmp], beta[tmp])\n", - "print(values[tmp], x_best)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Calculate the average and maximum cost for the optimal parameters found with varying number of shots" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "num_shots=[]\n", - "bins_states={}\n", - "max_cost=[]\n", - "average_cost=[]\n", - "max_sol={}\n", - "for i in range(4,14):\n", - " ns=2**i\n", - " num_shots.append(ns)\n", - " jv1 = execute(createCircuit_MaxCut(x_best,G,1,k_cuts,version), backend_sim, shots=ns)\n", - " bins_states[ns], mc, ac, max_sol[ns] = bins_comp_basis(jv1.result().get_counts(),G, k_cuts)\n", - " max_cost.append(mc)\n", - " average_cost.append(ac)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Calculate the average and maximum cost for random solutions with varying number of shots" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "import random\n", - "bins_states_rand={}\n", - "max_cost_rand=[]\n", - "average_cost_rand=[]\n", - "max_sol_rand={}\n", - "for i in range(4,14):\n", - " ns=2**i\n", - " tmp_states={}\n", - " for j in range(0,ns):\n", - " s = random.randint(0, ns - 1)\n", - " binstring=\"{0:b}\".format(s).zfill(numV)\n", - " y=[int(i) for i in binstring]\n", - " c=cost_MaxCut(y,G, k_cuts)\n", - " tmp_states[binstring]=c\n", - " bins_states_rand[ns], mc, ac, max_sol_rand[ns] = bins_comp_basis(tmp_states,G, k_cuts)\n", - " max_cost_rand.append(mc)\n", - " average_cost_rand.append(ac)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Plot comparison of random solution and QAOA" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure(figsize=(10,5))\n", - "pl.semilogx(num_shots, max_cost,'x-', base=2, label='QAOA')\n", - "pl.semilogx(num_shots, max_cost_rand,'x-', base=2, label='random')\n", - "pl.legend()\n", - "pl.ylabel('max cost')\n", - "tmp=pl.xlabel('num shots')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Small comment on the result above: This shows that QAOA produces \"good\" results with a very high likelihood. Randomly choosing 2^13 solutions should give a good result as well, given, that there are only 2^14 solutions in total" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure(figsize=(10,5))\n", - "pl.semilogx(num_shots, average_cost,'x-', base=2, label='QAOA')\n", - "pl.semilogx(num_shots, average_cost_rand,'x-', base=2, label='random')\n", - "pl.legend()\n", - "pl.ylabel('average cost')\n", - "tmp=pl.xlabel('num shots')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.3" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Generic MaxCut 21.ipynb b/Generic MaxCut 21.ipynb deleted file mode 100644 index ca8a199..0000000 --- a/Generic MaxCut 21.ipynb +++ /dev/null @@ -1,541 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from qiskit import *\n", - "from qiskit.tools.monitor import job_monitor\n", - "\n", - "import numpy as np\n", - "import pylab as pl\n", - "\n", - "import networkx as nx\n", - "from qiskit.visualization import *\n", - "from scipy import optimize as opt\n", - "from qaoa import *\n", - "import os\n", - "from matplotlib import rc\n", - "font = {'size' : 16}\n", - "rc('font', **font);\n", - "rc('text', usetex=True)\n", - "\n", - "import sys\n", - "sys.path.append('../')\n", - "\n", - "from qiskit_utilities.utilities import *\n", - "from qiskit_utilities.download import *" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Let us import and draw the graph" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "k_cuts=2\n", - "numV=21\n", - "G = nx.read_gml(\"../data/sample_graphs/w_ba_n\"+str(numV)+\"_k4_0.gml\")\n", - "pos = nx.spring_layout(G)\n", - "nx.draw_networkx(G,pos=pos)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Draw the histogram of number of solutions for value of cost function" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "file_name = \"w_ba_n\"+str(numV)+\"_k4_0_costs.npy\"\n", - "if not os.path.isfile(file_name):\n", - " ## we could run the next line, but it takes several hours\n", - " #costs=costsHist_MaxCut(G)\n", - " ## therefore, we just download\n", - " url = \"https://zenodo.org/record/3730499/files/\"+file_name\n", - " downloadfile(url,file_name)\n", - "costs=np.load(file_name)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "cost of optimal solution(s) = 25.23404480588015\n" - ] - } - ], - "source": [ - "max_val=max(costs)\n", - "print(\"cost of optimal solution(s) = \", max_val)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure(figsize=(25,10))\n", - "a=pl.hist(np.sort(costs), bins=2000)\n", - "min_ylim, max_ylim = pl.ylim()\n", - "max_ylim *=1.025\n", - "mean=np.mean(costs)\n", - "pl.axvline(mean, color='k', linestyle='dashed', linewidth=2)\n", - "a=pl.text(mean-1, max_ylim, 'mean = {:.2f}'.format(mean))\n", - "a=pl.xticks(np.arange(0, max_val, step=1))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Only 3.94% of all solutions have a cost of 20 or higher" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "There are 82532 solutions with cost 20 or higher, which is 3.9354324340820312 % of all solutions.\n" - ] - } - ], - "source": [ - "num_good_solutions=0\n", - "for i in range(0,costs.shape[0]):\n", - " if costs[i]>=20:\n", - " num_good_solutions+=1\n", - "print(\"There are\", num_good_solutions, \"solutions with cost 20 or higher, which is\", num_good_solutions/2**numV*100, \"% of all solutions.\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### There is only 1 optimal solution (modulo symmetry)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "There are 2 solutions with maximum cost = 25.23404480588015 , which is 9.5367431640625e-05 % of all solutions.\n" - ] - } - ], - "source": [ - "num_optimal_solutions=0\n", - "for i in range(0,costs.shape[0]):\n", - " if costs[i]>=max_val:\n", - " num_optimal_solutions+=1\n", - "print(\"There are\", num_optimal_solutions, \"solutions with maximum cost =\",\n", - " max_val ,\", which is\", num_optimal_solutions/2**numV*100, \"% of all solutions.\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Calculate the energy landscape (this takes time)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "Aer.backends()\n", - "backend_sim = Aer.get_backend('qasm_simulator')" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "version=1\n", - "circuits=[]\n", - "n=12\n", - "m=48\n", - "beta_max=np.pi\n", - "gamma_max=4*np.pi\n", - "job_string=\"w_ba_n\"+str(numV)+\"_k4_0_\"+str(n)+\"x\"+str(m)\n", - "\n", - "if os.path.isfile(\"../data/sample_graphs/\"+job_string+\"_Elandscape_v1.npy\"):\n", - " Elandscape_v1 = np.load(\"../data/sample_graphs/\"+job_string+\"_Elandscape_v1.npy\")\n", - "else:\n", - " for beta in np.linspace(0,beta_max,n):\n", - " for gamma in np.linspace(0,gamma_max,m):\n", - " circuits.append(createCircuit_MaxCut(np.array((gamma,beta)),G,1,k_cuts,version))\n", - " job_sim = execute(circuits, backend_sim, shots=1024*2*2*2)\n", - " Elandscape_v1,_,_ = measurementStatistics_MaxCut(job_sim.result().results, options={'G' : G, 'k_cuts' : k_cuts})\n", - " Elandscape_v1 = -Elandscape_v1\n", - " np.save(\"../data/sample_graphs/\"+job_string+\"_Elandscape_v1\", Elandscape_v1)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Define function for the optimizer" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "def getval(x, backend, depth=1, version=1, noisemodel=None):\n", - " j = execute(createCircuit_MaxCut(x,G,depth,k_cuts,version), backend, noise_model=noisemodel, shots=1024*2*2*2)\n", - " val,_,_=measurementStatistics_MaxCut(j.result().results, options={'G' : G, 'k_cuts' : k_cuts})\n", - " global it, values, gamma, beta\n", - " print(x)\n", - " it+=1\n", - " gamma[str(it)] = x[0]\n", - " beta[str(it)] = x[1]\n", - " values[str(it)] = val\n", - " return -val[0]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Run the optimizatoin using Nelder-Mead (derivative free method)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[0.5 1.3]\n", - "[0.525 1.3 ]\n", - "[0.5 1.365]\n", - "[0.475 1.365]\n", - "[0.45 1.3975]\n", - "[0.45 1.4625]\n", - "[0.425 1.54375]\n", - "[0.375 1.57625]\n", - "[0.3125 1.681875]\n", - "[0.2875 1.828125]\n", - "[0.20625 2.0434375]\n", - "[0.175 1.96625]\n", - "[0.15 2.1125]\n", - "[0.271875 1.78953125]\n", - "[0.384375 1.65140625]\n", - "[0.22734375 1.88753906]\n", - "[0.33203125 1.73011719]\n", - "[0.25351562 1.84818359]\n", - "[0.30585937 1.76947266]\n", - "[0.26660156 1.82850586]\n", - "[0.29277344 1.78915039]\n", - "[0.30839844 1.82774414]\n", - "[0.32666016 1.84685059]\n", - "[0.303125 1.86671875]\n", - "[0.32402344 1.86633789]\n", - "[0.32929687 1.82736328]\n", - "[0.30966797 1.85687988]\n", - "[0.31621094 1.84704102]\n", - "[0.30576172 1.84723145]\n", - "[0.31884766 1.82755371]\n", - "[0.3090332 1.84231201]\n", - "[0.31557617 1.83247314]\n", - "[0.31394043 1.83493286]\n", - "[0.31230469 1.83739258]\n", - "[0.31262207 1.84467651]\n", - "Optimization terminated successfully.\n", - " Current function value: -17.030687\n", - " Iterations: 17\n", - " Function evaluations: 35\n", - "Optimal value= [0.31621094 1.84704102]\n" - ] - }, - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "version=1\n", - "it=0\n", - "gamma={}\n", - "beta={}\n", - "values={}\n", - "xin=(.5,1.3)\n", - "out=opt.minimize(getval, x0=xin, method='Nelder-Mead',\\\n", - " args=(backend_sim,1,version,None),\\\n", - " options={'xatol': 1e-2, 'fatol': 1e-1, 'disp': True})\n", - "print(\"Optimal value=\",out.x)\n", - "f = pl.figure(figsize=(10, 6), dpi= 80, facecolor='w', edgecolor='k');\n", - "pl.plot(list(values.values()),'x-')\n", - "\n", - "f = pl.figure(figsize=(10, 6), dpi= 80, facecolor='w', edgecolor='k');\n", - "pl.imshow(np.array(Elandscape_v1).reshape(n,m),interpolation='bicubic',origin='lower',extent=[0,gamma_max,0,beta_max])\n", - "pl.colorbar(orientation=\"horizontal\", pad=0.2)\n", - "pl.xlabel(r'$\\gamma$')\n", - "pl.ylabel(r'$\\beta$')\n", - "pl.plot(list(gamma.values()),list(beta.values()),'ko-')\n", - "pl.plot(xin[0],xin[1],'or')\n", - "pl.plot(out.x[0],out.x[1],'xr')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Pick the best solution and its parameters along the optimization path" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[17.030686515430567] (0.3162109374999995, 1.8470410156250017)\n" - ] - } - ], - "source": [ - "tmp = max(values, key=values.get)\n", - "x_best=(gamma[tmp], beta[tmp])\n", - "print(values[tmp], x_best)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Calculate the average and maximum cost for the optimal parameters found with varying number of shots" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "num_shots=[]\n", - "bins_states={}\n", - "max_cost=[]\n", - "average_cost=[]\n", - "max_sol={}\n", - "for i in range(4,14):\n", - " ns=2**i\n", - " num_shots.append(ns)\n", - " jv1 = execute(createCircuit_MaxCut(x_best,G,1,k_cuts,version), backend_sim, shots=ns)\n", - " bins_states[ns], mc, ac, max_sol[ns] = bins_comp_basis(jv1.result().get_counts(),G, k_cuts)\n", - " max_cost.append(mc)\n", - " average_cost.append(ac)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Calculate the average and maximum cost for random solutions with varying number of shots" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "import random\n", - "bins_states_rand={}\n", - "max_cost_rand=[]\n", - "average_cost_rand=[]\n", - "max_sol_rand={}\n", - "for i in range(4,14):\n", - " ns=2**i\n", - " tmp_states={}\n", - " for j in range(0,ns):\n", - " s = random.randint(0, ns - 1)\n", - " binstring=\"{0:b}\".format(s).zfill(numV)\n", - " y=[int(i) for i in binstring]\n", - " c=cost_MaxCut(y,G, k_cuts)\n", - " tmp_states[binstring]=c\n", - " bins_states_rand[ns], mc, ac, max_sol_rand[ns] = bins_comp_basis(tmp_states,G, k_cuts)\n", - " max_cost_rand.append(mc)\n", - " average_cost_rand.append(ac)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Plot comparison of random solution and QAOA" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure(figsize=(10,5))\n", - "pl.semilogx(num_shots, max_cost,'x-', base=2, label='QAOA')\n", - "pl.semilogx(num_shots, max_cost_rand,'x-', base=2, label='random')\n", - "pl.legend()\n", - "pl.ylabel('max cost')\n", - "tmp=pl.xlabel('num shots')" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure(figsize=(10,5))\n", - "pl.semilogx(num_shots, average_cost,'x-', base=2, label='QAOA')\n", - "pl.semilogx(num_shots, average_cost_rand,'x-', base=2, label='random')\n", - "pl.legend()\n", - "pl.ylabel('average cost')\n", - "tmp=pl.xlabel('num shots')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.3" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Generic MaxCut 26.ipynb b/Generic MaxCut 26.ipynb deleted file mode 100644 index 6c09fb2..0000000 --- a/Generic MaxCut 26.ipynb +++ /dev/null @@ -1,570 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "%load_ext autoreload\n", - "%autoreload 2" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "from qiskit import *\n", - "from qiskit.tools.monitor import job_monitor\n", - "\n", - "import numpy as np\n", - "import pylab as pl\n", - "\n", - "import networkx as nx\n", - "from qiskit.visualization import *\n", - "from scipy import optimize as opt\n", - "from qaoa import *\n", - "import os\n", - "from matplotlib import rc\n", - "font = {'size' : 16}\n", - "rc('font', **font);\n", - "rc('text', usetex=True)\n", - "\n", - "import sys\n", - "sys.path.append('../')\n", - "\n", - "from qiskit_utilities.utilities import *\n", - "from qiskit_utilities.download import *" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Let us import and draw the graph" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "k_cuts=2\n", - "numV=26\n", - "G = nx.read_gml(\"../data/sample_graphs/w_ba_n\"+str(numV)+\"_k4_0.gml\")\n", - "pos = nx.spring_layout(G)\n", - "nx.draw_networkx(G,pos=pos)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Draw the histogram of number of solutions for value of cost function" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "file_name = \"w_ba_n\"+str(numV)+\"_k4_0_costs.npy\"\n", - "if not os.path.isfile(file_name):\n", - " ## we could run the next line, but it takes several hours\n", - " #costs=costsHist_MaxCut(G)\n", - " ## therefore, we just download\n", - " url = \"https://zenodo.org/record/3730499/files/\"+file_name\n", - " downloadfile(url,file_name)\n", - "costs=np.load(file_name)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "cost of optimal solution(s) = 38.11808904821565\n" - ] - } - ], - "source": [ - "max_val=max(costs)\n", - "print(\"cost of optimal solution(s) = \", max_val)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure(figsize=(25,10))\n", - "a=pl.hist(np.sort(costs), bins=2000)\n", - "min_ylim, max_ylim = pl.ylim()\n", - "max_ylim *=1.025\n", - "mean=np.mean(costs)\n", - "pl.axvline(mean, color='k', linestyle='dashed', linewidth=2)\n", - "a=pl.text(mean-1, max_ylim, 'mean = {:.2f}'.format(mean))\n", - "a=pl.xticks(np.arange(0, max_val, step=1))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Only 0.6% of all solutions have a cost of 32 or higher" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "There are 406966 solutions with cost 33 or higher, which is 0.6064265966415405 % of all solutions.\n" - ] - } - ], - "source": [ - "num_good_solutions=0\n", - "for i in range(0,costs.shape[0]):\n", - " if costs[i]>=32:\n", - " num_good_solutions+=1\n", - "print(\"There are\", num_good_solutions, \"solutions with cost 33 or higher, which is\", num_good_solutions/2**numV*100, \"% of all solutions.\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### There is only 1 optimal solution (modulo symmetry)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "There are 2 solutions with maximum cost = 38.11808904821565 , which is 2.9802322387695312e-06 % of all solutions.\n" - ] - } - ], - "source": [ - "num_optimal_solutions=0\n", - "for i in range(0,costs.shape[0]):\n", - " if costs[i]>=max_val:\n", - " num_optimal_solutions+=1\n", - "print(\"There are\", num_optimal_solutions, \"solutions with maximum cost =\",\n", - " max_val ,\", which is\", num_optimal_solutions/2**numV*100, \"% of all solutions.\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Calculate the energy landscape (this takes time)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/franzf/.local/lib/python3.8/site-packages/qiskit/providers/ibmq/ibmqfactory.py:192: UserWarning: Timestamps in IBMQ backend properties, jobs, and job results are all now in local time instead of UTC.\n", - " warnings.warn('Timestamps in IBMQ backend properties, jobs, and job results '\n" - ] - } - ], - "source": [ - "#load IBMQ account\n", - "#IBMQ.save_account('yourAPItoken')\n", - "IBMQ.load_account()\n", - "provider = IBMQ.get_provider(hub='ibm-q')\n", - "\n", - "backend_sim=provider.get_backend('ibmq_qasm_simulator')" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "version=1\n", - "circuits=[]\n", - "n=12\n", - "m=24\n", - "beta_max=np.pi\n", - "gamma_max=4*np.pi\n", - "job_string=\"w_ba_n\"+str(numV)+\"_k4_0_\"+str(n)+\"x\"+str(m)\n", - "\n", - "if os.path.isfile(\"../data/sample_graphs/\"+job_string+\"_Elandscape_v1.npy\"):\n", - " Elandscape_v1 = np.load(\"../data/sample_graphs/\"+job_string+\"_Elandscape_v1.npy\")\n", - "else:\n", - " results = read_results(job_string)\n", - " if results == None:\n", - " for beta in np.linspace(0,beta_max,n):\n", - " for gamma in np.linspace(0,gamma_max,m):\n", - " circuits.append(createCircuit_MaxCut(np.array((gamma,beta)),G,1,k_cuts,version))\n", - " job_sim = start_or_retrieve_job(job_string, backend_sim, circuits, options={'shots' : 1024*2*2*2})\n", - " job_monitor(job_sim)\n", - " success = write_results(job_string, job_sim)\n", - " results = read_results(job_string)\n", - " Elandscape_v1,_,_ = measurementStatistics_MaxCut(results, options={'G' : G, 'k_cuts' : k_cuts})\n", - " Elandscape_v1 = -Elandscape_v1\n", - " np.save(\"../data/sample_graphs/\"+job_string+\"_Elandscape_v1\", Elandscape_v1)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Define function for the optimizer" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "def getval(x, backend, depth=1, version=1, noisemodel=None):\n", - " global it, values, gamma, beta\n", - " job_string=\"w_ba_n\"+str(numV)+\"_k4_0_Nelder_Mead_\"+str(it)\n", - " results = read_results(job_string)\n", - " if results == None:\n", - " circ=createCircuit_MaxCut(x,G,depth,k_cuts,version)\n", - " job_sim = start_or_retrieve_job(job_string, backend_sim, circ, options={'shots' : 1024*2*2*2})\n", - " job_monitor(job_sim)\n", - " success = write_results(job_string, job_sim)\n", - " results = read_results(job_string)\n", - " val,_,_=measurementStatistics_MaxCut(results, options={'G' : G, 'k_cuts' : k_cuts})\n", - " print(x)\n", - " it+=1\n", - " gamma[str(it)] = x[0]\n", - " beta[str(it)] = x[1]\n", - " values[str(it)] = val\n", - " return -val[0]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Run the optimization using Nelder-Mead (derivative free method)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[0.5 1.3]\n", - "[0.525 1.3 ]\n", - "[0.5 1.365]\n", - "[0.525 1.365]\n", - "[0.5375 1.3975]\n", - "[0.5125 1.4625]\n", - "[0.50625 1.54375]\n", - "[0.54375 1.57625]\n", - "[0.565625 1.681875]\n", - "[0.534375 1.828125]\n", - "[0.5328125 2.0434375]\n", - "[0.59375 1.96625]\n", - "[0.5625 2.1125]\n", - "[0.56484375 1.78953125]\n", - "[0.50546875 1.65140625]\n", - "[0.57167969 1.88753906]\n", - "[0.52753906 1.73011719]\n", - "[0.56064453 1.84818359]\n", - "[0.53017578 1.88677734]\n", - "[0.55617676 1.81384277]\n", - "[0.52990723 1.79378418]\n", - "[0.55296021 1.83458374]\n", - "[0.57476196 1.82030151]\n", - "[0.54447174 1.82616913]\n", - "[0.55456848 1.82421326]\n", - "[0.5436676 1.83135437]\n", - "[0.56386108 1.82744263]\n", - "[0.54871597 1.83037643]\n", - "[0.5471077 1.84074692]\n", - "Optimization terminated successfully.\n", - " Current function value: -26.131194\n", - " Iterations: 14\n", - " Function evaluations: 29\n", - "Optimal value= [0.55296021 1.83458374]\n" - ] - }, - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "version=1\n", - "it=0\n", - "gamma={}\n", - "beta={}\n", - "values={}\n", - "xin=(.5,1.3)\n", - "out=opt.minimize(getval, x0=xin, method='Nelder-Mead',\\\n", - " args=(backend_sim,1,version,None),\\\n", - " options={'xatol': 1e-2, 'fatol': 1e-1, 'disp': True})\n", - "print(\"Optimal value=\",out.x)\n", - "f = pl.figure(figsize=(10, 6), dpi= 80, facecolor='w', edgecolor='k');\n", - "pl.plot(list(values.values()),'x-')\n", - "\n", - "f = pl.figure(figsize=(10, 6), dpi= 80, facecolor='w', edgecolor='k');\n", - "pl.imshow(np.array(Elandscape_v1).reshape(n,m),interpolation='bicubic',origin='lower',extent=[0,gamma_max,0,beta_max])\n", - "pl.colorbar(orientation=\"horizontal\", pad=0.2)\n", - "pl.xlabel(r'$\\gamma$')\n", - "pl.ylabel(r'$\\beta$')\n", - "pl.plot(list(gamma.values()),list(beta.values()),'ko-')\n", - "pl.plot(xin[0],xin[1],'or')\n", - "pl.plot(out.x[0],out.x[1],'xr')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Pick the best solution and its parameters along the optimization path" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[26.131193655960185] (0.5529602050781245, 1.8345837402343763)\n" - ] - } - ], - "source": [ - "tmp = max(values, key=values.get)\n", - "x_best=(gamma[tmp], beta[tmp])\n", - "print(values[tmp], x_best)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Calculate the average and maximum cost for the optimal parameters found with varying number of shots" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "num_shots=[]\n", - "bins_states={}\n", - "max_cost=[]\n", - "average_cost=[]\n", - "max_sol={}\n", - "for i in range(4,14):\n", - " ns=2**i\n", - " num_shots.append(ns)\n", - " jv1 = execute(createCircuit_MaxCut(x_best,G,1,k_cuts,version), backend_sim, shots=ns)\n", - " bins_states[ns], mc, ac, max_sol[ns] = bins_comp_basis(jv1.result().get_counts(),G, k_cuts)\n", - " max_cost.append(mc)\n", - " average_cost.append(ac)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Calculate the average and maximum cost for random solutions with varying number of shots" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "import random\n", - "bins_states_rand={}\n", - "max_cost_rand=[]\n", - "average_cost_rand=[]\n", - "max_sol_rand={}\n", - "for i in range(4,14):\n", - " ns=2**i\n", - " tmp_states={}\n", - " for j in range(0,ns):\n", - " s = random.randint(0, ns - 1)\n", - " binstring=\"{0:b}\".format(s).zfill(numV)\n", - " y=[int(i) for i in binstring]\n", - " c=cost_MaxCut(y,G, k_cuts)\n", - " tmp_states[binstring]=c\n", - " bins_states_rand[ns], mc, ac, max_sol_rand[ns] = bins_comp_basis(tmp_states,G, k_cuts)\n", - " max_cost_rand.append(mc)\n", - " average_cost_rand.append(ac)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Plot comparison of random solution and QAOA" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure(figsize=(10,5))\n", - "pl.semilogx(num_shots, max_cost,'x-', base=2, label='QAOA')\n", - "pl.semilogx(num_shots, max_cost_rand,'x-', base=2, label='random')\n", - "pl.legend()\n", - "pl.ylabel('max cost')\n", - "tmp=pl.xlabel('num shots')" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure(figsize=(10,5))\n", - "pl.semilogx(num_shots, average_cost,'x-', base=2, label='QAOA')\n", - "pl.semilogx(num_shots, average_cost_rand,'x-', base=2, label='random')\n", - "pl.legend()\n", - "pl.ylabel('average cost')\n", - "tmp=pl.xlabel('num shots')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.3" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Generic MaxCut.ipynb b/Generic MaxCut.ipynb deleted file mode 100644 index fba303b..0000000 --- a/Generic MaxCut.ipynb +++ /dev/null @@ -1,299 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from qiskit import Aer, execute\n", - "import numpy as np\n", - "import pylab as pl\n", - "import networkx as nx\n", - "from qiskit.visualization import *\n", - "from qaoa import *\n", - "\n", - "from matplotlib import rc\n", - "font = {'size' : 16}\n", - "rc('font', **font);\n", - "rc('text', usetex=True)\n", - "\n", - "import sys\n", - "sys.path.append('../')" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "G = nx.read_gml(\"../data/sample_graphs/er_n5_k4_0.gml\")\n", - "pos = nx.spring_layout(G)\n", - "nx.draw_networkx(G,pos=pos)\n", - "k_cuts=2" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'00000': 0,\n", - " '11111': 0,\n", - " '00010': 2,\n", - " '11101': 2,\n", - " '00100': 3,\n", - " '01000': 3,\n", - " '10111': 3,\n", - " '11011': 3,\n", - " '00001': 4,\n", - " '00011': 4,\n", - " '01100': 4,\n", - " '01101': 4,\n", - " '01111': 4,\n", - " '10000': 4,\n", - " '10010': 4,\n", - " '10011': 4,\n", - " '11100': 4,\n", - " '11110': 4,\n", - " '00101': 5,\n", - " '00110': 5,\n", - " '00111': 5,\n", - " '01001': 5,\n", - " '01010': 5,\n", - " '01011': 5,\n", - " '10100': 5,\n", - " '10101': 5,\n", - " '10110': 5,\n", - " '11000': 5,\n", - " '11001': 5,\n", - " '11010': 5,\n", - " '01110': 6,\n", - " '10001': 6}" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "costs=listSortedCosts_MaxCut(G, k_cuts)\n", - "costs" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "good_solutions={}\n", - "for key in costs:\n", - " if costs[key]>=5:\n", - " good_solutions[key] = costs[key]" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "optimal_solutions={}\n", - "for key in costs:\n", - " if costs[key]>=6:\n", - " optimal_solutions[key] = 100" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "Aer.backends()\n", - "backend_sim = Aer.get_backend('qasm_simulator')" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "n=12\n", - "m=24\n", - "beta_max=np.pi/2\n", - "gamma_max=np.pi\n", - "\n", - "version=1\n", - "circuits=[]\n", - "for beta in np.linspace(0,beta_max,n):\n", - " for gamma in np.linspace(0,gamma_max,m):\n", - " circuits.append(createCircuit_MaxCut(np.array((gamma,beta)),G,1,k_cuts,version))\n", - "job_sim = execute(circuits, backend_sim, shots=1024*2*2*2)\n", - "Elandscape_v1,_,_ = measurementStatistics_MaxCut(job_sim.result().results, options={'G' : G, 'k_cuts' : k_cuts})" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "from scipy import optimize as opt" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "def getval(x, backend, depth=1, version=1, noisemodel=None):\n", - " j = execute(createCircuit_MaxCut(x,G,depth,2,version), backend, noise_model=noisemodel, shots=1024*2*2*2)\n", - " val,_,_=measurementStatistics_MaxCut(j.result().results, options={'G' : G, 'k_cuts' : k_cuts})\n", - " global it, values, gamma, beta\n", - " #print(x)\n", - " it+=1\n", - " gamma[str(it)] = x[0]\n", - " beta[str(it)] = x[1]\n", - " values[str(it)] = val\n", - " return -val[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: -4.767456\n", - " Iterations: 33\n", - " Function evaluations: 64\n", - "Optimal value= [0.40680664 0.34160156]\n" - ] - }, - { - "data": { - "image/png": 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IDB47pt0aNW/Km9HzBqpcL7+I9I0xZrO1tjLb5fCrtNf0BmtkQzW7wba86yP+brfWdlhrH/HGGmOw1q4O/r8IuMezbB4Qtr6IiIiISCyZGrLsGmPMjUAjUAFc41lWCzwNrHZnBBPcxcH/3wg8Yq3daYzZGWy+ADAlYjsiIiIiIjFlJOkNjsTgjsawPmJZ1Hi9wba7K4KTd368Dm4iIiIiInHpMcQiIiIi4ntKekVERETE95T0ioiIiIjvKekVEREREd9T0isiIiIivqekV0RERER8T0mviIiIiPiekl4RERER8T0lvSIiIiLie0p6RURERMT3lPSKiIiIiO8p6RURERER31PSKyIiIiK+p6RXRERERHxPSa+IiIiI+J6SXhERERHxPSW9IiIiIuJ7SnpFRERExPeU9IqIiIiI7ynpFRERERHfU9IrIiIiIr6npFdEREREfE9Jr4iIiIj4npJeEREREfE9Jb0iIiIi4ntKekVERETE95T0ioiIiIjvKekVEREREd9T0isiIiIivqekV0RERER8T0mviIiIiPiekl4RERER8T0lvSIiIiLie0p6RURERMT3lPSKiIiIiO8p6RURERER31PSKyIiIiK+p6RXRERERHxPSa+IiIiI+J6SXhERERHxPSW9IiIiIuJ7SnpFRERExPeU9IqIiIiI7yWc9BpjrjbGTAr+/3xjTIMxZpMx5rNpK52IiIiISArkJ7FurbW2JPj/h4FrgA+A1cDUVBdMRERERCRVkkl6DYAx5gzAWGt/Ffy7pMcoEREREZEsSybpbTDG/BCoxqnddRPgnekomIiIiIhIqiTTkW0hToL7b9ba7wTnFQPLU14qEREREZEUSjjptdbuD/53lmd2EbA3lQUSEREREUm1ZEZv+CEwBZjnmb0TuDfVhRIRERERSaVk2vQuttaWGGNCSa+19s/GmLI0lEtEREREJGWSadPbHByn17ozjDGXAM2pLpSIiIiISColU9N7DfAIMNkYcwPwOZz2vbN6jBIRERERybJkOrL92VpbCdwEjAXusdaWWGtb0lU4EREREZFUiFvTa4w5Hdhprf0g+Peo4KKHPOuMAnDXEREREREZiHpq3tCIM1LDs8G/W/C05w0ywXl6KpuIiIiIDFhxk15rbSDi7+L0F0dEREREJPWSGaf3/BjzJseaLyIiIiIykCQzZNk9Mea1x5kvIiIiIjJg9DpkmTHm6uB/iz3/d5Wj9rwiIiIiMsAlMk5vZfDfMZ7/uzqAhakskIiIiIhIqvWa9Fpr/x7AGFPs/l9EREREJJckPE4vcLVnrN4wGqdXRERERAayvozTayLW0zi9IiIiIjKgaZxeEREREfG9npo3xGzKEIuaN4iIiIjIQNZT84YWYjdniKTmDSIiIiIyoPXUvEHNGURERETEFxIevaGn5g5q3iAiIiIiA5lGbxARERER39PoDSIiIiLie4k8hjgk2MRhHlAG7LDW/jotpRIRERERSaFA76s4jDGXAh3AtUA5sMQYs9cYMzNNZRMRERERSYlkanpXA9XW2mfcGcaYCuARYGpPgcaYMuAynHbCFcBqa21HnHUrgGKgCKgGaq21O5PdjoiIiIiIK5mkd5834QWw1jYaY/YnEPuwtXYWgDGmAbgXWBhn3WeAydbaDmNMMXAPTvKb7HZERERERIDknsh2jzHmBpyaXdc8YFNPOwjW3La7fweT2Xk9hEz21N6249T69mU7IiIiIiJA357I9t2Ivy2wpIftlOG0BfZqN8aUuc0WwjYW3lzhWmB5MtsxxiwGFgOceOKJ1NfXO8FlZYwcOZKmpiYASkpKmDFjBi+88AIA+fn5zJkzh8bGRj74wBl2uLKykt27d7Nr1y4Apk6dytChQ3n11VcBOO644zjppJPYsGEDAEOHDuXss8+moaGBDz/8EICqqirefvtt2traAJg2bRp5eXm8/vrrABx//PFMnjyZF198EYDCwkKqqqrYuHEjBw8eBODss8+mubmZ9957D4BTTjmFo0eP8uabbwIwfvx4JkyYwMaNGwE45phjqKys5MUXX+TQoUMAzJkzh61bt/L+++8DcOqpp3Lo0CG2bdsGwMSJExk3bhwNDQ0AjBo1ioqKCjZs2MCRI0cAOPfcc3nttdfYu3cvADNnzuTAgQPs3Om8/JMmTaK4uJjGxkYAxowZw8yZM3n++eex1mKM4bzzzqOpqYl9+/YBUFFRQXt7Oy0tLXqf9D6l7H2Kxb0W5ML7NDFG+Zuamnz3Pul80vuk9yn8fZL0Mtba9O7ASUKrrbULPfN2AAuttY1xYty2u1hrV/R1O5WVldY9SURk8Ngx7daoeVPejJ43UOV6+UWkb4wxm621ldkuh18lPHpDP7TjdErz6nHMX2vtzmCy22GMebqv2xERERERgeTH6T0dqCQi+bTW3t5DWFQThmBMVO2sW8Pr1u4Cv8RpS1yWzHZERERERLySGaf32ziPJP4ccBPOWL1/zycjK8QUTEpDNbLBBHa9929jTFHwzzLCH2lcBnQEa3573I6IiIiISDzJ1PR+B5hkrf3AGNNgrf37YLK6NoHYa4wxN/LJ+LrXeJbVAk/jjLm73hhTFGy/C05CfUGC2xERERERiSmZpNdYaz8I/n+nMWamtbbJGNNrg+tgLa3bDGF9xLKFEX97h0Rbneh2RERERETiSaYj22pjzCXB//8IeM4Ysw1oTn2xRERERERSJ+GaXmvtdzz/bzTGzALKIp/SJiIiIiIy0CQ7esMonKewlQE7rbW/SkupRERERERSKJnRGy7FeSLatQRHbjDG7DXGzExT2UREREREUiKZmt7VOE9ECzVnMMZUAI8AU1NdMBERERGRVEmmI9u+yPa7wdEU9qe2SCIiIiIiqRW3pjfYftfrHmPMDTg1u655wKZ0FExEREREJFV6at7QAljARMz/bsTfFliSwjKJiIiIiKRU3KTXWlscb5mIiIiISC5JasgyAGPM6ThDlu2w1jalvEQiIiIiIimWcNJrjBkNPAOMxnkKW5kxZh9wgefxxCIiIiIiA05SjyEG7rHWTrXWfs5aWw48HJxERERERAasZJLeedbae70zrLUrgMrUFklEREREJLWSSXqbjTGf9c4wxpyP09RBRERERGTASqYj2+VAgzHmaWAnMAW4IDiJiIiIiAxYCdf0Wmt3BocxW48zdu/TQJm19n/SVDYRERERkZRIZvSGq62190W26xURERERGeiSadP795FtekVEREREckEySe81wGpjzNeNMZOMMaPcKV2FExERERFJhWQ6sj0T/Pf/C/5rcdr2WqAklYUSEREREUmlhJPeYCc2EREREZGck0zzBhERERGRnNRj0muMOd8Y8ztjzDZjzFPGmJmZKpiIiIiISKrETXqNMZcCq4F7cB5M8SjwrEZwEBEREZFc01Ob3h8B1dZa9zHDfzbGNOAkwWemvWQiIiIiIinSU/MG40l4AbDWNuI8flhEREREJGf0lPTaOPP3pqMgIiIiIiLp0lPzhhJjzNUx5hcbY27wzrDW3p7aYomIiIiIpE5PSe9mnA5sseZ/zvO3BZT0ioiIiMiAFTfptdZWZ7IgIiIiIiLpoodTiIiIiIjvKekVEREREd9T0isiIiIivqekV0RERER8T0mviIiIiPiekl4RERER8T0lvSIiIiLie0p6RURERMT3lPSKiIiIiO8p6RURERER31PSKyIiIiK+p6RXRERERHxPSa+IiIiI+J6SXhERERHxPSW9IiIiIuJ7SnpFRERExPeU9IqIiIiI7ynpFRERERHfU9IrIiIiIr6npFdEREREfE9Jr4iIiIj4npJeEREREfE9Jb0iIiIi4ntKekVERETE95T0ioiIiIjvKekVEREREd9T0isiIiIivqekV0RERER8T0mviIiIiPiekl4RERER8T0lvSIiIiLie0p6RURERMT3lPSKiIiIiO8p6RURERER31PSKyIiIiK+p6RXRERERHxPSa+IiIiI+J6SXhERERHxPSW9IiIiIuJ7SnpFRERExPeU9IqIiIiI72Uk6TXGlBljbjTGzAv+W5RAzNMx5tUaY6wxZp8x5mljTFlaCiwiIiIivpKfof08bK2dBWCMaQDuBRbGWtEYMw8oA+bFWLzJWmvSVkoRERER8aW01/QaYyqAdvdva20HsRNad/l6a+1qoCPdZRMRERGRwSETzRvKiE5g2/vYNKHMGHNZsJlEbSLNJEREREREMtG8oTjO/KI+bGt1sKYYY0w78DBQ7V3BGLMYWAxw4oknUl9fD0BZWRkjR46kqakJgJKSEmbMmMELL7wAQH5+PnPmzKGxsZEPPvgAgMrKSnbv3s2uXbsAmDp1KkOHDuXVV18F4LjjjuOkk05iw4YNAAwdOpSzzz6bhoYGPvzwQwCqqqp4++23aWtrA2DatGnk5eXx+uuvA3D88cczefJkXnzxRQAKCwupqqpi48aNHDx4EICzzz6b5uZm3nvvPQBOOeUUjh49yptvvgnA+PHjmTBhAhs3bgTgmGOOobKykhdffJFDhw4BMGfOHLZu3cr7778PwKmnnsqhQ4fYtm0bABMnTmTcuHE0NDQAMGrUKCoqKtiwYQNHjhwB4Nxzz+W1115j7969AMycOZMDBw6wc+dOACZNmkRxcTGNjY0AjBkzhpkzZ/L8889jrcUYw3nnnUdTUxP79u0DoKKigvb2dlpaWvQ+6X1K2fsUi3styIX3aWKM8jc1NfnufdL5pPdJ71P4+yTpZay16d2BMZcB11prqz3z9gEXWGsbe4jbZ60d08u2bU9tfCsrK617kojI4LFj2q1R86a8GT1voMr18otI3xhjNltrK7NdDr/KRPOGnbFm9pTwxmKMqTDGbE5NkURERERkMEl70htMbkNNHIJtedd7/06wbe5O4B5P3DzgkdSVVERERET8KlNDll1jjLkRaAQqgGs8y2qBp4HVEBrtYR5QZIypBZ4OjujQYYzZGWyzCzAlYjsiIiIiIjFlJOkN1va6zRnWRyxbGGfdFTG2sz5ynoiIiIhIb/QYYhERERHxPSW9IiIiIuJ7SnpFRERExPeU9IqIiIiI7ynpFRERERHfU9IrIiIiIr6npFdEREREfE9Jr4gMCFVVVRQUFFBQUMCXv/zlfq9/aeu9TNv6L0zb+i8se/dX6SiyiIjkECW9IpJ1VVVVvPLKK2zfvp3t27ezdu1ali1b1uf1L229l/eOHODNk77Hs5P+D48feIUVK5zn3SxbtoxAIBBzqq+vT/ehiohIlijpFZGs27RpE0888QSlpaWUlpayaNEi7r777j6t39raStOhd1h5/CUAjB9SxMyhJ1JbWwvAypUraW5uDpuWLl3KsGHDmDt3bp+PIZM11a2trUyfPp2CggICgQBVVVV9LreIyGChpFdEsqqurg5rbVjCOX/+fA4ePNin9deuXQvAWSMmhZZ//phT2LdvX+hvN1kuLS0FYNWqVWzZsqXPx5DJmmqA8vJyZs2aRVdXF83NzTQ2NrJgwYI+l19EZDBQ0isiWdXW1kZ+fn7YvPHjxwNOjWZ/1wcYVzAKa23MZRUVFSxatCiUAPdFJmuqAe6//37WrFkDOAn8uHHjePnll/tcfhGRwUBJr4hk1e7duzl69GjYvMmTJwPQ3Nyc9PqLFi0CoO1wR2j5Cx9tA6KT4hUrVrBv375QAtkX2aiprqmpCdvmO++8EzpuERGJTUmviGTVuHHj4tbCuslsMuuXlpYyOlDI/3prNQB/+qiF/z7wGkBUbe6qVas488wz+1P8rNVU19fXs2DBAgKBANOmTWPlypV9PgYRkcFASa+IZJWb8Hlt2LABiE5SE13/vz61GIBpW/+Ff/zLb7lw5AwKCwvDYlpbW2lra+O6667rV/mzVVPd1tZGc3Mzw4YN48CBA3ETZhERcSjpFZGsqqmpwRhDXV1daN66desoLi7u8/rjhxSxufxG3jzpezw16R/4U2cLl1xySdh23GYEkU0FkpWtmuqamhq2bNlCZ2cn4LRNFhGR+JT0ikjWnXnmmaEa1/r6etauXcuVV14ZWt7a2hqW5Pa2/uMfvBL6/7J3f8X+7oNR7XZffvnlqGYGfZGtmmqvRYsW0d7ertpeEZEeKOkVkazbuHEj5eXlFBQUUF1dzaJFi8LaqC5ZsoRrrrkm4fX/64OXKd/6T5Rv/SdePfQur069OWqf27ZtY9SoUf0ue6ZrqntKbPszAoWIiN+ZeD+z+UFlZaVtaGjIdjFEJMN2TLs1at6UN6PnpUpVVRXbt29n79691NfXU11dzXXXXRdKxFtbW9mwYUOoKUVv699xwqVcNOo0wKmpfurDLRzs7gI+6cB26623cuONN9La2kp5eTnl5eX9GmtYRLLPGLPZWluZ7XL4lZJeEfGdTCe94CSyjY2NgNPcwNucYsGCBdTX14fa3/a2/twRU3m+c7tT7iFjeWrSP4SVv66ujuuuu459+/aRl5dHRUUFGzduTOfhiUgGKOlNLyW9IuI72Uh6UynXyy8ifaOkN73UpldEREREfE9Jr4iIiIj4Xv/H6xERyaJr7oqe952Ml0JERAY61fSKiIiIiO+ppldEJItUUy0ikhmq6RURERER31PSKyIiIiK+p6RXRERERHxPSa+IiIhQVVVFQUEBBQUFfPnLX075+iLZpqRXRERkkKuqquKVV15h+/btbN++nbVr17Js2bI+r19SUoIxhkAgEJoWLFgAwLJly8Lme6f6+vp0H6oMYkp6RUQEUE3fYLZp0yaeeOIJSktLKS0tZdGiRdx99939Wr+mpobu7u7Q9MQTTwCwcuVKmpubw6alS5cybNgw5s6dm87DlEFOSa+PZPKGVV9fT0lJCYFAIBSfyf23trYyffp0CgoKCAQCVFVVJRXvR9lOWLL1+fv5sgLq1yjh6q9M1vRFGj58OMOHD0/5MUli6urqsNaGJZzz58/n4MGDKVk/FjdZLi0tBWDVqlVs2bKlT+UXSZSSXp/I9A2rurqa5cuX093dzW233UZdXR2bN2/O2P7Ly8uZNWsWXV1dNDc309jYGPeGOhhkO2EJBAJZ+/xVLriN7ZsfVOLbT5ms6fOaPn06p512WsqPJxdl64vjV7/6VYwxYcvHjx8POBUMkdra2sjPz+91/XXr1vV6/QCoqKhg0aJFoQRYJG2stb6dZs2aZQcLY4x97rnnQn/X1NTYwsLCPq9fXFxsa2pqYsauWbPGFhcXh80DbCAQyMj+3TJ4jR8/3o4fPz7u+n6Xyfff6+STT7azZ8+2QNY+f1ffae2Ek+dbE8i3V9/p/L39pH+MmgYqt8zeKdPlX7NmjXVuBz3PS2b9RD5DtbW1tri42F5//fU9fl4Gg9mzZ9vCwkLb0tJiW1pabH5+vr3++uv7vH5xcbEFrDEmNM2fPz+0PD8/39bW1lprrf2rv/orC4S9Xy0tLVHntev666+3xpiweZHrFxcXR5Uv1uehtrY2aluDGdBgB0D+5NdJNb0+kOmfpmpqanj00UfDtgfQ3d2dkf27ZfB65513WLRoUcLxfpKNnyYBVqxYwfvvv09JSQlA1j5/AEXjpmO7jyRV/oHm8Tur+PmyAn6+rIBl7/6q1/VT2Twl0Zq7ZNfvrabv5ptvjnovB6tM1rTX1dUxatQobrzxRgAuvPBCANauXRu1n8mTJ0fNGzduHE5+Fs1d/9FHH2XLli2h8lVXV8fc/qpVqzjzzDPjHqdIKinp9YFs3LC8CUtbWxvGGAoLCzO2f3B+nluwYAGBQIBp06axcuXKqHUGg2wnLAcOHIhalsnPH0DH7i3kFRSSqx6/s4r2d1/h8pu3c/nN2/nvA6/xg/d/F3f9ZJqzRLaXjdVzfvny5Rw5ciSs57ybvDQ3N0dtc/fu3Rw9ejRsXqz1Dx48GOqo9PTTT4cl51VVVZSXl6vjEtmvuHDPvyNHPvniuGHDBoCYTQ7c9b0i1587d25YbHFxcdj2wTnf29rauO666xIqt0h/Ken1gURvQMmu39MNy2vr1q1Ya7n11lszuv+2tjaam5sZNmwYBw4ciJlgDQbZeP+9CUtnZ2fUPjL5+TvQ3srbbzxJxedvjbk8F/zlrU18/ponGFlcysjiUi4cOYMH92+Ku36itYKx2svG6jk/Z84cIPrLBKSnpq+uro5Nmzbx5JNPxj3GwSTbFRfuL2cFBQVhscXFxTHLW1NTgzEm9CtfrPUjy71t27awihH4pGY58pc7kXRR0usDidyAkl0/0Z+mAP7jP/4DIPRTWab2X1NTw5YtW0JJV0VFRcxt+l2m3//IhKWnXveZ+Pw98qPpnHreUmZeEP35ywXbG+oAy4lT54bmnTtiKh/b2M01Eq3lc5ufuAmtV2TP+T/+8Y9R66Szpm/VqlVYa5k8eTKBQIA77riDgwcPEggEeuwA6VfZrrhwE1Q3ka6vr2ft2rVceeWVYet4k9wzzzwzVEMbuX5dXR3Tp08P/XJQX1/Ppk2bWLJkSdh+X3755ajkXSSdlPT6QCI3oGTXT+SnKXB62cdqj5Wp/bsWLVpEe3t7Ttf29rXn9k033RS1LJnXf/r06f1KWNxYb8KSyc/f5E9fwlkX527Tlo/2t2EC4Tf+cXkjAWg73BG1fqK1fIm2l62oqOBLX/pSrzV3Xv2t6du4cSPW2lBb05qaGgoLC+nu7h6UzZSyXXExffp0rr/+ek477TQKCgqorq5m0aJFYe/FkiVLuOaaa0J/b9y4kfLy8pjr19TUsGTJEqqrq0O1zEuXLo16b7dt28aoUaN6eGVEUktJrw8kcgNKdv1EfpoqKSlh/vz5/OEPf8jo/ntKbHN1yJv+DDm2c+dOgLCfL72vZ2SbTvf1v+WWWygpKeHAgQOsW7eOvLy8UNL9xS9+MWx/sRKWM888k7y8vNBQRw888EDoppbI+z9lypTQ/m655ZY+f/7mfnlN3NcpFxw8sBvbHV5rN7GgCIBdXR1R6ydSy5doe9kVK1awb98+1qxZ02PNHSRW0zdkyBAKCgrIy8tjypQpvdb0uV/cHnzwQQ4fPhy2LJGxuP3ycIxsV1xccsklrFy5ko0bN9LV1UVXVxdr1oSfV0888URUU6ae1l+5ciVdXV10d3fT2dkZ88vMxo0b2bt3b9R8kbTJ9vAR6ZwG05Bls2fPDg3j9Nxzz0UNX9PS0hI2zFdP669Zs8YWFhaGhp557rnnrDEmbHvjx48PG34mk/t/7rnnbGFhYWi4HXc4nJNPPrmvL1/W9XfIsZKSktBwUd7X0x1SbNiwYWGv/4gRIyxg8/PzQ7H5+fm2paXF3nXXXRawCxcuDG0v8v33Dpd00UUXWcAOGzYsav/WWltYWBh3/y0tLfahhx6ygK2oqLDWJv/5GwhDfvXHmRfWWiCs/M9P+qYF7POTvhlV/tra2qjhwtzhotzzzBhjW1parLW2x+HAxo8fb2fPnh36e/bs2TY/Pz/m8FLz58+P2o53/ZKSkrAhqgKBQGiorMLCwqjht2J9hrzreMvgnuPeIbdmz54dGqawpaXFGmNC14RcZIwJO0dqamqihoZMZn33/Xe5r7dXokMTSuagIcvSOmW9AOmcBlPSa23/bliR619//fU2Pz8/5g3LHY8z1pSJ/btlKC4utsYYm5+fH3bjzjWpHCPV+3p6x0ANBAIxX3/ve+dNok8++eTQGJ+xXn9v0l1TU2Pz8vJC74X3/XST7sj9G2PsySefHFp/0qRJYcv7+vnLxaR3bs2aqKR35fGXWCBm+Xt7/93Xwk04vX97X8eZM2eGxteOPP9aWlpC748xJub51dLSYsePHx96DyM/Q/0dq7mnsbhjjSHr/SKdi7JdcSEDg5Le9E5ZL0A6p8GW9Epuqq2ttfn5+WHznnvuuVDNXV/Xz8/Pt88991yPNX2zZ8+2Y8aMSfmDCdxyxnrwQLJJfm9yvab36jutBWPn1qwJlf+ikafZ0YHCuOWPrOVza+tjPaggVvI5e/ZsW1BQEIqJTLB6q2WNnJeOh1tE8iZtsWq7/fCQg4FQcSHZpaQ3vZPa9IpkWTp6biczBurRo0fTMlxSvI5UyQ7PNBgc+6kz+eOvnfax72yr578PvMalo04PLW873NFje9q9e/eycOHCpB5scN5555Gfnx9z/fvvvz/URrO0tJRx48bx8ssvh5Z/4QtfYNy4caGHHaRryK1kxuIeP348Ts6QuzLVprampiZuUpCsa+6KnkQGKiW9IlmW6p7byY6B2t3dndGkO9kkfzC4aOlGRo8t5+fLClj3b9VcOHIG3z3uc6Hl//f938btOX/BBRcA8Mtf/jK0PJEHG3zwwQehnvOR6/f2xMM33ngj7IEC6RpyK95Y3G5ZIsekjZwnIuKlAfIkq+LVCtz7rUyWIrtS3XP78ssvx1obSiLcBDkQCEQNG9T8Hhw6EsBaG/Ze3BIcvKE/SXe8BDbZJH+wuGjpxtD/v3P3rWHLfj6hhilvhs/buNFZf8WKFdx8881hy7y1ppE1gG4tqxsfub77mauvr2fFihU8+eSTYbWs3qe2lZSU0N6+j7yCYWGfIe/529cht8BJvt0EfMKECVRUVLB3715KS0spLi4O/e2OHgG5O4KLiKSfanoHuVg/TeXqz1N9Hec21vr19fWUlJQQCATSPhxSqoecS3YMVGPyoub1J+nu7cED3nj383blzU78939dmrOfv2zJdC3rSy+9BDjjNe/du5er7+ymuzt6KKz+DrkVKXIs7sbGRsB5itiSJUtYtGhR1LB2mZaNa5Bfrt8imaCkV3yhP+Pcxlq/urqa5cuX093dzW233caDDz4YuuksW7Ys9GhP72SMIT8/v083vOLi4rA2mg899BCdnZ2hG97FF1+c8NOQkpU/ZDhggk8Gc6Qz6Y4V//Yb6xgyPPb+pGfpeLABxH/ioZuw/uEPfwitWzn/+wD9/gy5Y0Xn5+fHPYfcpLi0tJTy8nJnv9u386tf/YpLLrkktF4iSWNraysTJkwInYf9eRpctq5B9y0Nn97ZVt/nYxDxOyW9MmA8fmcVP19WwM+XJZ80vvTSSzzxxBOhjjxz587ljjvuiHvD27RpU9j63o48dXV1jBo1KvRY5RtvvJEvfOELoZ9PV65cGXq0pzuNGzcOgB07dvTphrd///7QwP7V1dV0d3fzT//0T6Eb3uOPP87Xvva1ULy3TednP/tZrLVJPcnK7Rz0l7deonN/G2B5/kFn++9s698jSBPhjX9nWz07/ryWk85MPF4+kY4HG0Ty1rK6jzX2rnvsp2YD8IdH/wHo28Mt6urqMMawfft21qxZQ11dHeeee24odtWqVZx88smh+PLy8tA59Nd//dccPHgwdB5Cz0mju83y8nI+/elPhzqDPfPMM32uqU32GvTSSy9x7LHHUl5ezuTJkxk9enSfrkGLvudMp563lLyCYWGPsxaRCNkePiKdk4Ys612s4Z6uvjPz+z/2U7NtXkGhXfS9Frvoe9FDKEXyDmx/5513Rg1sHwgEQsPvuEMZuUP6RA6NVFhYGBq+yeUd/9NaZ/gf4gzn444Z+tBDD4Xm9WeMUncMYq/58+dHDVNm7Sfj4Pa0r5543/NjPzXbmkC+NYH+D5fkFe+1mD37k/2Vz6rp8+fPD0OW9af8sYY868+DDWINkxf5+ffGX33nJw/YcD9DfRlyi4hxd88555zQ+MKxxuLGM/7wySefnPQ5dPLJJ4fG/XXL4n24RiauQd5h4bzrW5v4NejqO61d9L0WawL5dtH3WjJ6/Xb3n637hx+hIcvSOqmmVwaEv7y1ic9f8wQji0sZWZzYkEturcrhw4cxxoTVkowYMQJwanMia0m8wyVNnz6d0047LfQoXbe9YOSoA1u2bInbXnDGjBkAYb3bE+k9792Hd/2ampqoob6mT58e9QjRFStW8P7774dq3vrroqUb+frKLr6+sv/DJXmtWbMmKtaNd/eX648SzrbIIc/6U1Pf3NzM8OHDWbFiRSg2spb1iiuu4LrrrqO1tZUD7a00PnUrE06eH/oMJTvk1v333w+En3ff+MY3AGd0ka6urrCOd+6xWOs0o9myZUvS51DkCBQ9/foTS3+vQYFAIGxYuDFjxoTWj3wtoOdr0K9XVjDljEWMLFYnPpGeKOmVrHPaAdqwn+WSSRp3796NtTbshrd69Wrgk4453hue25HHmzQGAoGw9b1aW1t58sknufXWW6OWrVixgo8++ijlY5QmcsOLNw6uDD6RQ54tWrQorLnLkiVL4g55Vl0dvv7cuXO59957qa2tJRAIUF5eTkVFBVu2bAnFr1mzJvSz/C9vK+eEKXP5wrVP9Ln86Rjnt6dzKHIECmMM1tqwNs3pvgY5lXqf2Lt3b9j6Xj1dg5qeWcHhzn364iiSACW9knUf7W/DBPp+w/O243PXP/vss4FPOuZ4b3huR55YSWOsjj/Tp09n6dKlofZ1XqtWreL4449PS+957zFF3vDccXDr/mcuv9sMh4+o9/Zgl8qa+pqaGvbu3RuzltUb393dzddXdvUr4YX0jUDhijyHIkegqK2tBeAzn/lMKCYT1yDvwzemTJkStr5XT9eg136/imM/dWbU/FyUytEvvKZPn57KYkoOU9IrWXfwwG5sd99veN6OOe763o45kTc8d33vwxPc7UV25CkpKeGSSy6J2UmstbWVtrY25s6dG1VrE3kcXsn2to+84SX78Il08tOQd5Id19wFv9/qnBOxPj/pOIciR6DYvXs34CSzkdtJ5zXIOyxce3t7aH2v3q5BnfvbmPFX10UtyzWpHv0CPhnB48CBA1Hxbg2/dwSeBQsWpPy4ZGBR0ptCmfyWmslxZNOtcOQ4nD4p0RK54XmfHuWu7x0uKV4tybXXXhv6f3d3d9TwSiUlJcyfPz9ue1W3fd6FF14YtSxVvedj3fC84+DetzTAq8/fwdGug9y3NMCfHuv7kEu5zjv6x7J3f9Xr+pHnX7zzMdb519raSmFhIcYYjDGMHTs27n7ixU+fPp2CggLuWxrg8TurEjxKfxoxOn0jUMQ6hyJHoIhVU+tKxzXIHbINCA0L9/HHH4fmecueyDWovLIm5vJc0p821bHWr6qqYsGCBXzwwQdxt1FTUxMaWrG7uzv0WG3xLyW9KZLpb6m9DceTS1Jxw3N/GiwtLQ3rmOPe8K677rpQ55dVq1YBsHTp0tDDE44ePUp7e3voPZgwYUKPNxuAl19+mfz8/JQ/XMIV74bnHQf36ju7KZ9VQ15BIVff2c1ZFyc+bJmfPH5nFe3vvsLlN2/n8pu3898HXuMH7/8u7vqR519dXR2NjY1h5+Pll18e9/ybNGkSXV1dtLS08Pvf/569e/dGJUc9nb/l5eXMmjWLrq4uFn2vmT1vN/LkPdmpZRoINfVO0pa6saJd8c6h0tLSsHjvNcW95qTzGgTRnQkPHTqEtTaUdCd6DYpsGpaLeuvc25f1N27cSGdnZ2h8aRFQ0psymfyW2tsYjrkmFTe8s846KzSwvdsx5/777w/dNLwdedykcfbs2eTl5WGMIS8vD2udsW7r6upoa2sLjRvqnby2bdvGqFGjgN7HrU12nNtEbnjyicjRPy4cOYMH92+Ku37k+QfOY5rdv0ePHs3DDz/cYy3R+vXrKS0tZc6cORQWFtLS0hJa1lst0/333x96b0cWl1I4chzt777chyP3D+8IFJk4h7wjULg1vzNnzgwtT+c1qLW1Naoz4UknnQQ4SXMy16CCYaN6fF1zQTo6MiZi3bp1atowyCjpTYFMf0tNdEirXJKKIZe++c1vhjrm1NfXh93weurIc8UVVzBkyJDQ/Jqamrhj/EXGuz2ue+oND8n1nk/0hieOWKN/nDtiKh/b2OdD5Pnnfq4OHz4cWufHP/4xQMzzz13fe/5Gnuu91TJ5fw4H6Nz/DmWnL4q57mDhHYEiE+eQdwSK8vJyRo8eza5du4C+J92JXoPcYeEuvfRSurq6Qr8wuMPCJXMN+upte/v92mdbujsyxnPw4MHQQz6efvrpnP21VBKnpNejr21yv/rVr0YlJO63zliPpU3Ft9RkxnDMBakccilbSWNPveGT6T2f6A3PNffLa7hqRfQ4uINFrNE/xuWNBKDtcEfU+pHnX1tbG3l5ecAn5597Ph46dChuvLfn/ac+9amw+ES48fctDVB03LRB2zTFq6/j/Pb1HHJHoOjq6qKjoyNjX1wTGRYuF7nt6pO9h951111xr2/z5s2L2l6yHRljefTRR9myZUvo153q6uqc/bVUEqekN6g/bXKvuuoqrLVh63/rW98CnItf5PZ2797NkSNHwnqOfvaznwWcdmHJXjDy8/NZt25d1BiOySbx/XkMcKz1k91/qoZcSjZpjPfwBMkNsUb/mFhQBMCuro6o9SNribx/u7VE7o0zVtLrru/tee+ul0wtkxufVzCMw4cOcKA98YRZ0iOTX1wTGRYuWX1NOlNxDfe2q0/2Hup+WfCuf/755wOxH+3ufin13kMnTZoEEPoi0lt5586dy+WXXx46vi1btkT9WprsPUwGPiW9Qf1pk+u2xfKu39TUBDjtvCK35/YU9vYcdduS1dfXJ33BKCgoIBAIhIbdiVwea3vucC33LQ0EJ8NfdjWEOgL1tyNeMl8ifnHjcH5x4/C4+0onb+ed40qrCOQVEMhL/w3DT6NvZFtPo3+4ya9XZC2Rt+d+ZC3R0KFD48bX1NSEet7Hi++JG+/W0v96pTrc9FeqR9DJxDiwqepI2J+kMxXX8L+89VKoXX2y91C3kugnP/lJaPnOnTsZOXJkzHuy2zzonHPOCd1DS0pKABKuuDr99NPDjq+lpSXsF6BE76Ea8iy3KOml/21y3W+d7vredl/nn38+q1evDtterJ6/bpI8Z86cUCJ955130tTUxEcffRS1vnvBqKio4NJLL+VLX/pS2AXmpZdeYsyYMZx//vk89dRTMS9ANTU1XH2nMwIAGBYseSbUEcjd/5QpU0JPFoq1/3hfEhLZP8AjP5xO8QmnRc1fvnw5U6ZMibv/3iQbH9n7/8EHH6SoqChufCI3jMbGRk488UROPPFE/vM//zNsuTv6xtfv6OaML9xGXd2DTK38cthNL9OvQa7Gxxr9o+Fjp23m+CFFUcsiz7+eeu6/8cYbvPfee2H7j3X+xmq7u3z5cpqamqLiYyk7fRGHO9tTWtubK+9ff+O9X1o3//kVLr3JOSf7ew6feOKJbNq0iRNPPJF//ud/TnqEnUy/ft7OnN57SCau4YWjTgAIa1e/f/9+Dh48GHP/se65U6ZMoaurC4BbbrkFIPTQjtWrV3PmmWeG3ZPz8vJoaGgAnPdh7969LFy4MHQ8Pd1D6+rqaGpq4gc/+AGlpaUxf6FJ9B6qIc9yS+6PdZICvbWxjRyyJnL9mpqaUC1Aa2sr9957LwBFRUVs3ryZWbNm8dWvfjW03F3/scceIxAIhGqd3J7Cy5cvp7OzE2stM2bMoKmpiUceeYTLLrsM+OSCcemll4Y6StTV1YWS7b/5m78B4LXXXgNg1qxZXHjhhXGT+MiOQC/95pP9u+UvLi6O2n/kl4Rk979ixQo6P3yfk6YvoP3dV0LzX/rNcvI71rN58+ZQvHf/XrFqRZKJd/3lrU0s+MazjCwu5aXfLGfMmDF0dnbGPH5wbhjPPvts6LPhXhDdn+leeuklpk6dGnry08SJE/npT38aGh3CHX3jmrtg5gU38u72enb8eW3oUaLLly9n/frkjsFrMMWXV9ZQX/cVtjfUhcYrfeGjbYwOxG7jXlNTw1e+8hXq6uqoqakJnY8jRowIrfODH/yAvLw8ZsyYwbvvvkttbW1o/3PmzAn13HdrnNybpvt5cMsfKz7WNcU1sjj2/GTl0vuXqnjvOfyzn/XvHF6+fDnvvvsuv/nNb5gzZw6zZs3i7LPPDjvH3aT540NdfHy0MOxaVPxuZo8/8hruvYdk4ho+ZtwpfLh3Z1j533zzTQB+/etf88UvfjFs/7Huuffddx+f/exnyc/PDzU3ckdEmTVrVuhR8e75M3r0aPbv3x/WV+OXv/xlaP/Nzc1Yazl06BCHDh3CGMPs2bPDmpF8+9vf5vrrr2fYsGHMnz+fdevWJXX8kntU00tqeo66zROam5v54x//CMDf/d3fUVRUxPLly3nwwQfDtpeXl8dHH31Ec3MzX/rSlwA47rjjAFi9ejW33XYb4DwpbOTIkfzwhz8M7ct9apC3Z7A3SX/mmWfIy8ujqKgotH/3ZPZ2tFm3bh33LQ1QX/dl4JMLxxsvfrL//fv3s3z58qj99/QlIdH933zzzcy7MnwUCnf/Dz/8cFi8d/+9STY+8obxxourueWWW/j4449jxvf2y4B743jyySdDZbj88stDowPEGn2jaNx0bPcn7clWr+7fazDY4iNH//jvA69x6ajTQ8vbDnf02PMePnkqX319Pa+//jpf+9rXyM/PJxAIcPXVV/Ptb38b+OQcdjs1rV27ljfeeCNseCu3/G68t/xuz/0VK1YAcKC9ldd+v4qi405O+PXpTa69f/2NjzyHV6/u3zn805/+FHAePOPG79q1K+YIO2MnRNfyZ/r4Iztzeu8hmbiGH+kKb+u8evVqfv7znwPQ3t4etf+e7rnr168PNSvy7n/YsGFA+D15yJAhtLS08J3vfAcgVPm0evVq7rvvPsBJnO+55x4qKipCCa97/F1dXXR3d9PZ2RkaAjTZe6iaNuQWJb0k3xM01vqPP/44ABdccEHoJxq3RqCyspKtW7eGbW/9+vXMnDmT8vJyHnroIcBpi9TY2EhHR0fo56CmpiY6OjpobGykqsp5apN7k/b2DHY7wj311FMcPHiQ7u7uUNkqKyvZtm0bEH7BOHjwIIu+18xJVV8HLPVrvsyeXY0cPtgRegZ9c3MzlZWVNDY2huJ6umAluv+qqirKy8vDfg4DQvsvKysLi/fuvyd9iffeMNz4M844A3AucJHxvd0w3Npdbxnc9869YEaOvtGxewt5BYWhMnR09O81GGzxkaN/XDhyBt897nOh5f/3/d/22PO+pqaGT3/60xQUFDBv3jwAfvGLX/DSSy/R1tbGd7/73VCt09y5c3nggQc4fPgwxhj+9m//lpKSktDwde45XF5eHoq/9tprQ+WP7Ln/y9vKGTuhgstuSk3P/Vx8//obH3kOd3T0/Rz+7W9/S2dnZ9jyysrK0Pvf2wgd2Th+b2dONz6T1/D8gk/6ZLj7d0c0mTx5ctT+e7rnfvTRR1EdSCsrK3n11VfDyukdfcGtUFi7dm3o/Ev38YOGPMtFSnpJ7pGWva3/1FNPhWpsXUVFRaH/u9ubO3cu//M//0NXVxc/+tGPADhy5Ajt7e2UlZXx7//+74DzLXXHjh2hbbuxQFiPYPeCPGLECIqLi8MuKN79R14wRhaXMvpYpyPejj+v5VBnOyNLysLWd+M7OjqAni9Yiey/rq6OTZs28eSTT0bFR+7fG+/uvyd9iffeMNx4b01/ZHxvvwy4NfFebkeXV155JWrZgfZW3n7jSSo+f2uoDN4bXiLH4DVY472jf6w84ZKwZT+fUNNrz3v37yeffJKysjK6u7tD55d7Drr7r6mp4ciRI6Hle/bsCW3XPYd7i3d77n99ZRcXLe1/z31Xrr5//YmPPIfLyvp+Dr/xxhuMHj06bLn3GtbbCB3ZOH5vZ87I+ExcwwuGjowqv/ceGrn/nu6hQ4cOTfgeGvkYae89NJ3HDxryLFcp6SXxR1omsn5HR0eoBshd7m5n9OjRofW9tQXuBaCwsJCOjg7a29vDLhhufHt7e9j6Xt4Lxscffxy2zHscsS4Ybkcg232Ewwc7ONSZ3v2vWrUKay2TJ0/mvqUBXn3+Do52HXT+/8KPOdTZHjPe3X9P3PInE++9YUTGT548OSq+t18G3J/hvNz33vsZcD3yo+mcet5SZl5wY6gMkWVN9jUYzPH95Z6Dfd1/f+P7K9uvfzbiI89h73rJnsPDhw/n8OHDYcu917DeRujIxvF7O3O68Zm8hr/9hvPT/31LDa++8GPa29vD7qGR+0/lPfSau2Ddy87x5BUU8qM1mb+Huuvk8gOiBgslvUGpeoxsUVERHR0dYcvdk8nt9FJXV8f06dNDzRTcE3Du3Lmh+FhJt/t3TxeMoqIiOjs7o5ZD+LdVb9Ltdv4xeQUMKSzi8MH07t99DHB3tzNyRPmsGvIKCrn6zm5OPfebHD7YQSzxvoR4ueVPJt57w3DjY9X0u/G9/TIwceLEqOV/+tOfADjttPCRKv7j5hImf/qSsAcTDCksilujk+hrMJjj+8s9B/u6//7G91e2X/9sxEeewx0dfT+Hp06d2mOHpXidEPtT/v7Gex/l7sZn+hoOhiHDizn13G/S0dERdQ8Fp1mfK5X30OHB9/+EKXMzcvwQ3cxl27ZtOf2AqMFCSW9Qqh4j655U3uUXX3wxAP/6r/8KOCfckiVLqK6uxpgA8z63gMKRx/PM8xv513VOvPeCsXOn0yv2t7/9bWj/8S4Y7v69y90erX/3d38HRF8w3tnm/BsweQwdnv7998Tdv5e7f+8FJ5Xx3huGG++9YEbG9/bLwMKFC4Hwoesee+yxqDKUlJTwqenzQyM29OcYFN93kWOkuudgovvvb3yqZfv1z/Vz2I3xLnfjE0las/X6uZ05s3UNzysYxuix5ay75wsAYfdQd//ueLyQunvofUsDPHWvcw99/62NGTn+yHtofX09mzZtYsmSJXFfHxkYlPR6pOJpPBUVFRQVFdHY2Bha/rOf/SzUOca1cuVKurq6uPrObq5a0UnNP7/L6LHlPH6X0+Gpuro6dMFoaGigpKQkoaTb3f/dd98dWr5kyRKOP/740PZiXTBOPe96ik/8dEb235OxEysYUlgU1umgoaEh6vVLdbx7wxg7sYL8ocfw0EMPhS6YDQ0NzJkzJ6GafnA+A3l5eXzjG98ILX/qqadCHTsAJkyYwPz50QmvewzuZ6ivr8Fgju8vlT83473n8DHH9P0cdq9hp5xySmi522k4suZyIB2/25kzm9fwi5Zu5Oo7jlBUVMT1118fVX4/3kPdkRuWLl2a0D1OsktJbxosXryY5cuXA843zNraWq699tpe49yOOJ8+/8bQCBBu/L/9278l/AhMd/8bN27kzTffZNKkSWFPuoHoC8ZZF6/M6P695n55TeipVAAnn923168/8d7e/0cOfcSxxx7LypUrQ/EffvhhQhdMlzuIvTsawPDhw0PL6+rqaGtro66ujvuWmrDJ1dfPkOJTQ+XPvXjvOfzRR/07hxcvXswJJ5xAeXk5+fn53HHHHcyZMyfsHF+wYAGBQIC/vPUSnfvbuG9pgMfvrMra8buvwddXdnHjjdm9hg+G43fvoe6QZ0p4c0NGHk5hjCkDLgMagQpgtbW2I9l1k9lONtXW1oaepgPOQNmJDkoOMPtvail+t+/xg33/fY339qCPjF+8eHHU+t5BziPV1tYC8Mgjj0SVwX0gAsR/5Gh/X8PBHt9fKn9uxrvn8L3fIio+mXPY3f8jjzxCaWlpzHj36VuxzuFcff0Un5p4GbhMvB6sKd2JMZuttbOC/y8C7rXWLkx23WS2A1BZWWndxxSmS7yk5d5vKX4wxPdXtsuf6/HxtvGdu2+Nmjflzeh58eL7u//BXv5ciu+vbJdf8dmNT7VgnlOZvRL4W9preo0xFUBonBVrbYcxJmbjpJ7WTWY7IpmS7aRZREREEpP2ml5jzGXAIm+NrDFmB1Btrd2Z6Lo4zRl63Y4xZjHg/g41DXgz9UeVkLHAnl7XUrziFa94xSte8X6K749Sa+2xWdq372WiTW+8MV6Kklw3oe1Ya1cDqxMoV1oZYxr68xOF4hWveMUrXvGKz714GbgyMXpDO9EJbrwEtqd1k9mOiIiIiEhIJmp6d8aaaa1tjDE77rrGmFiL4m1HRERERCQk7TW9waQ0VCMbHHZsvffv4EgMPa7b23YGoP42sVC84hWveMUrXvG5Fy8DVKaGLKsA5hF77N2HgaeDbXF7WzfuMhERERGReDKS9IqIiIiIZJMeQywiIiIivqekV0RERER8LxOjNww6xpjJwLXAaOC3QAPwvrW2O8ntGNuH9ifav/av/Wdv/yIiMjCppjfFjDFnAP8P2AccAn4M/A74qTGmKoH444wxpwO4N1wTb7w27V/71/4H2v5HGGM+b4x52BhzlzFmnjEm6fHETVAf4rT/Qbz/gVCGwb5/GeCstZpSOAEPAudEzDsH+AXwMfAszmMG48V/BegG3gJ+BEyKsU6B9q/9a/8Dcv93B/d1BfAAsAN4KbitT8WL88RfAEyJmBfoLU771/4HShkG+/41Dewp6wXw2wTcBlwcZ5kBfg58pYf4KcB/AF8EngeOAk3AN4Ci4Do/Ak7R/rV/7X/g7B8YCrweY/6FOM0suoE7gPw4+w4Avwmu9wawDCj2Lg/+WxgnXvsfxPsfCGUY7PvXNPCnrBfAbxNwPvAucC9wdozlpwAvEhwuLsbyzwDf8Pw9DPhm8ATsAp4Obj8vTfs/J8v71/Hr+HPy+IFjcJLqmLVJOAn1w8BJsZYH1/kGcD3wt8ArOEn3C8CXPOs8R4yaJ+1/cO9/IJRhsO9f08Cf1KY3hYwxBdbaZ4HPBmf9ozHmPmPMEuM8QQ7gbOAPNnjmxIj/A7A62Jwo31r7sbX2x9bak4ExgAXWWGuPxogPBPd/Hs431VuNMfcaY/4+kf0DWGv/iPPzkFueZPav49fxD9rjt9Z+CHQAzxtjfmiMmRaxfAfwMvCFWPsOygces9Y+ZK09DTgR54a70hiz3xjzMrDJxuiUF9z/vuD+f9DH/Qf6uX8df5aOX69B9o9fBj49nCLFjDGTrLUtxpgxwBzgNOBk4AxgOM63zDuttbvjxJdaa1sj5uXjvFddxpha4G5rbUuM2EBwvaPGmOOB2cH9TwNOB0b0tP9go30TeTIH94+19khP+9fx6/gH+/EH1/8c8HWcWuJ3cNoTrsNpU7wW+Adr7fYe4gM4N95ub1mMMeOBV4EKa21zD/Hn44xeMQxoAzYls3/PMVtvcp/E/nX8WTz+4LqD+jXI9vHLwKWkN0WMMWcBlwPVODVCj+C0DdoOtAOHgWnW2pcTiC8Oxj4O/Mlauy+4zhDgAmvtuiTKNRIYCXyA0ynn1QRi4t3884D51tr/7qX8On4d/6A6/uDyiUCXtfY9Y8wUoBKnOcUpwJk4neMettb+JE78BOCItfa9iPlDrLWHg/9/3Fp7UZz4fIJJgjFmKs6j2mfgJP2zgV297D8vGG898wxOU44jCexfx5/F49drkP3jlxxgB0AbCz9MwP8Ai4L//yuc3qOvA38CbuCTLxjxGtB74+fgtEt6DdgMLE9g/6uB7xCjt3mC5Y8Zj/Ntu9e2Szp+Hf8gP/6bcGqQ3gG2AP+I05TihODyIfQ8aoQ3fitOZ7k5wFDPOmOB6UkeV1FwGproawO4SX/k/LHADB1/7hy/XoPMHb+m3JiyXgA/TMDxwPrg/wMRy2pwbt6/6iH+hB7ir8D5OSVufHC9f8WpzTqC0/j+fwOjIta5kvgdgBKJvypWvI5fxz/Ij38KsB44Ofj3pTg37+04bQGv8Kwb60ZaFhF/CfCfwfg/euPjlP1Y4AngH4CSGMtjdtpLJB4n6e8tXsefxePXa5D949eUO1PWC+CXCWeYo6/FWZYXXP6FNMZ/H5gd/P+3cGrZjgDPAJ8HpgJP9zP+dzp+Hb+OPyr2/wD/J/h/45l/DLAUaAG+1cO+/3cP8d9KIL4Ip83kO8Ey/x7ny0KeZ50JwCX9iB8PXKrjH3jHr9cg+8evKXemrBfALxPwZaAR51vpN4j+mfR2YEEa488DjomYNzEY9xZOb/aL0hj/JZzHvf4BWNKH8vc3/jPA8H6Uv7/xev8H6fsPlOI89S1qiLTg8pnAo8SogUpR/BDggeD/xwD/ArwNHAzGTQf+CfibfsZfqOMfeMev1yD7x68pdyZ1ZEuhYKeZa3EazhcDH+G0VdyD87PJHGvtwX7Ef8Za+3EC5QgA2PBer6/j9DhNW7wxZhzOE61Ow/nm/CHOwP6JHn9v8Ykef6gzQzLl72+83v/B9/67nVxwbogXATtxngr3rLX2fc96rwCV1tpDaYgvAM6y1r4QsWwmzhjDl+J05hsep/z9jQ8A38P5Sbo5WP7nkih/n+ODywqCy15Mtvz9jc/2++/Zhj4DWfoMSG5R0ttPwQThMpxvqutwxigcB0wCPgWcC7wP/LO1ti2N8Z/C+abcChywTu/VfJwaqjKcgbX/JdXxnm0ErDOk0wicn4LLccY3nIMzbmLM8qcw3tiIsVONM25rtzGmPIHy9yle7//gfv8j1p+BMwLFFGA0Thvh14BC4ERr7dfTGR9xPNYGL+7GmNOAG621X0lnvDHmdJykZQowKtny9zc+uA03iTzal+PvT/xAef+D29JnIAufARn4lPT2gzFmKPAkzrfzUcBcYBvO4w4ft70Mj5Ti+JHAZ3HaPv0OeMha+4pn3cLIWrYUxOcB4621b/VUzh7Kn/L4GBdrN3EZbq3tTHG83v/B/f4bnC8o38AZlu13OD+HHofTNGISTrORB3Dez1g1XKmMXw+8Za39ILh8qLX2kDHmSpzB9F9LZbxnO/kEEwRjTDHOF5ZSnC8tn8WptYsqfwrjo4aZCs5337veyt+n+Gy//3G2oc9A+Py0fgYkB9kB0MYiVyfgYuCHnr9NcN5jON9Q1wOnZDj+IuBXnvieHrfY3/hTcGrhNuF0Nojs7W6Agh7iZ/Qzvsf9J/D+9bh/vf96/3uJr8b50vBDnITlXeApnE45JyQQP6+f8d79PxWMfw74NnC8Z714I1bM62f8CcCxybxm6Y4nRk974g+T19/4rL7/+gxk/zOgKfemrBcglyfgOuAbcZaNxhmr9Ds+ji/AecLV93HaXh4BnsVp/1QQXOcC4vfKT2d8fgbis/36Zzt+sL//G/B8KcDpaf53OEM0HcYZBq0IYg93lKb4K4F6oAv4CT0k8imI/wFOzeQLOG2xCzzLAu7nKIPx+Z5lecF/R6YxPqvvvz4D2f8MaMq9KesFyOUJZwiUncBKYtTI4Qxk/XtgjE/jTwR+GvH3j4D3cDph/RvOMDBTfBqf7dc/2/HZfv2zFo/T5u8XxB+ofxrwXzid72ItT3f8SemMD64zB6jDeajALpxHvD4KzPWsczcwrp/xxw20/Wf7/ddnYGDsX1PuTVkvQK5OfFITdUbwpHkBWAUsIjisCs5PJ6/1M/7VAbp/91vwKO/2PMs/Hbx4tPczfu8A3b9bC3EazhiyLwA/xumIksjrn2h8vNc/2/t3+wMM7+Prn2h8vNc/q/sPrrMYp6f5t3HaBkcuvxh41Mfxi4C/9fx9Ks6T9D4AdgP3Aa/7OD6rr/9AKAPO9aI/r2FOx2vKvUkd2frBGDPKWvuBMWY4sABnLMGTcHqf5+O0Ffwva+3jfo6PmJeHk1AcMcbMx2mb9v98Gu92chiHM8rC6Tiv3RScn857e/1yPd5YzwXE0+vZWmuPJvD65Wy8MSY/+Bn5XziJQwDnSW5/ANZZa7uMMd8GOq21/+rD+Lzga1SIUztmbPgQb5U4bdNvs9be7cN4Y621wc/IN3A+Ny8HX78nE3j9+hU/UMoQ3I77WcqznhFQensN/RIvuUVJbx8YY0YDC3Ge2DIW+CXwNPAXdxWcmqIN1tq/+DT+cpwHChyLc2F4AqdW8EBwnTzgb3AeL/uhn+IjthVKnIwxY4PbO4zTyeola+3ueLF+iQcnS4yx7BKcp5j1+PrlYnzw81Fgrf3YGDMZ50vDqThfGk/GqSnaCHw38ouVT+IDwfjIEQm8vfD/A+cpWu1+jHeTZGPMNOAsnF9NpuI0TThAL69ff+IHQhm88d55BIcfDP6d0GuYi/GSm5T09oEx5jacIaZW4wytcg1O7dhOYK219v7gevnuyePj+CnA1TgXyjbgQWvtfT28fH6I/yLOU3setdbu72ndwRRvIob78nH8Z4D/hfPT7z6c5kG/D/7/Y5wxRadaa58eBPH7cToD/g7YYq09HFxnJM5jox/2W3w8xpjjgeE4HSKnWmufSTQ2FfHZKkO888Y4Y25faK1d6+d4yTF2ALSxyKUJ52fALTHmj8J5csvbwJ/wDPcySOJH4jx/fRfwIvE7DuR0fHDdm3Ee2nAUp5fzQoJtZD3rfAYoHETxkUP8RD3W1w/xOD8Bb8F5bPRonEcmPwO8gdMG+PPez9ogiP97nF+JtgL/DcyPd974JD6A0/chNMJIMlN/4wdCGXqKJ8ZwX36L15TbU9YLkIsTzjAnV/Ww/KfAVxXv2/hLgGXAMJzxLd8FOoH/xHnULjhDAQ1VvL/icX7+fSjG/PHBz9V+4K4ePjt+jT8RZ+i3DuBOH8cPwRnP9ghOrfivgQtirPc36YgfCGVIIv4iYiSQuR6vKbenANIXm4CbjDHPGWO+ZowpiVj+FHCO4n0bvw941lr7sbX2JmvtCThD3xwBfmuM6QLesXGeHqT4nI7fCVjjdHIJsda2WWu/i/PAixOMMVPj7Nuv8e9Ya2/BaRd8ol/jrdP8YSswHadJ1F7gV8aYPcaYnxljxhtjzsBJmFIePxDKkGB8BU7SbP0WLzku21l3rk44g3jfAjyE87PgT3CGwJkd/LtK8f6ND24jQIwnFeE84KBS8f6Mx6kRfDP4OflrIpqB4HQM/bTi/ReP08n30hjzP4fTGbYTp+nMmemIHwhlGOzxmnJ7Uke2JBljTsIZ2eBZnPZh5Tg9Xafi1A4eA9wKPGFjvLiKz/n4qcH4euADa21XcH4eTgJ12BhTB3zFRvQMVnzux3u2cxrwNeBTOJ+jt3CGeurGSapOVbx/44PbCOvp75m/CyhNd/xAKMNgj5fco6Q3CcaYu3Dafo0DKnA6PD2GM6zV1uA6YWP9Kd7X8ZuB3+CMZbstuE4AZ5D3XYr3V3xweT6fjOM7Ducn0nKgDDgfp+nMndbanYr3bXx3ZDJkPhn390ycX4l+mo74gVCGwR4vOc4OgOrmXJhwxrPdwCdP8BqNM6j7s8A7wK9whniB2I3nFe+/+GuA9TiPrf01UJbk50fxuRNfQPzRLPJi/V/x/o4nesQTgzPcV9R++hs/EMow2OM1+WPKegFyZQLOA34cZ1kZTs/vexQ/KOMnAw8q3tfx1Thfjh4CPhdnnXzFD754Pnmkd9ye/v2NHwhlGOzxmvwxZb0AuTThtPn6F2KMYQsMxfmp/AzFK17x/ooHjscZz3YNzugPe4GfATM863wJ+CvFD+r489IRPxDKMNjjNfljynoBcmnC6dn/CPASzvie1cAwz/I/AMWKV7zi/RWP81jmFZ6/L8BpD3wYZxis63Dagype8SmPHwhlGOzxmvwxqSNbkowxx+AMc1MFTAKOBT4EWnFuoFcqXvGK91+8MabAWttljAlYTycYY8winBrkTmvt6YpXfDriB0IZBnu85D4lvX1kjBkOlOLcNM8Atllrn1C84hU/KOINTjvAo8G//x5otdauU7zi0x0/EMow2OMlNynpFRHpJ2PM5cBj1nnak+IVn9H4gVCGwR4vuUFJr4iIiIj4XiDbBRARERERSTclvSIiIiLie0p6RURERMT3lPSKiIiIiO8p6RURERER31PSKyIiIiK+9/8D4KT/rozGLCUAAAAASUVORK5CYII=\n", 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" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "it=0\n", - "gamma={}\n", - "beta={}\n", - "values={}\n", - "xin=(.7,1)\n", - "out=opt.minimize(getval, x0=xin, method='Nelder-Mead',\\\n", - " args=(backend_sim,1,version,None),\\\n", - " options={'xatol': 1e-2, 'fatol': 1e-1, 'disp': True})\n", - "print(\"Optimal value=\",out.x)\n", - "f = pl.figure(figsize=(10, 6), dpi= 80, facecolor='w', edgecolor='k');\n", - "pl.plot(list(values.values()),'x-')\n", - "\n", - "f = pl.figure(figsize=(10, 6), dpi= 80, facecolor='w', edgecolor='k');\n", - "pl.imshow(-np.array(Elandscape_v1).reshape(n,m),interpolation='bicubic',origin='lower',extent=[0,gamma_max,0,beta_max])\n", - "pl.colorbar(orientation=\"horizontal\", pad=0.2)\n", - "pl.xlabel(r'$\\gamma$')\n", - "pl.ylabel(r'$\\beta$')\n", - "pl.plot(list(gamma.values()),list(beta.values()),'ko-')\n", - "pl.plot(xin[0],xin[1],'or')\n", - "pl.plot(out.x[0],out.x[1],'xr')\n", - "\n", - "jv1 = execute(createCircuit_MaxCut(out.x,G,1,k_cuts,version), backend_sim, shots=1024*2*2*2)\n", - "\n", - "plot_histogram([jv1.result().get_counts(),optimal_solutions], figsize=(10, 6), legend=['approx',r'$=$ 6'])" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "plot_histogram([jv1.result().get_counts(),good_solutions], figsize=(10, 6), legend=['approx',r'$\\geq$ 5'])" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.3" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/House MaxCut.ipynb b/House MaxCut.ipynb deleted file mode 100644 index 87ded90..0000000 --- a/House MaxCut.ipynb +++ /dev/null @@ -1,336 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from qiskit import *\n", - "import numpy as np\n", - "import pylab as pl\n", - "import networkx as nx\n", - "from qiskit.visualization import *\n", - "from qaoa import *\n", - "\n", - "from matplotlib import rc\n", - "font = {'size' : 16}\n", - "rc('font', **font);\n", - "rc('text', usetex=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "V = np.arange(0,5,1)\n", - "E =[(0,1,1.0),(0,2,2.0),(2,3,1.5),(3,1,1.1),(3,4,0.4),(4,2,1.0)]\n", - "\n", - "G = nx.Graph()\n", - "G.add_nodes_from(V)\n", - "G.add_weighted_edges_from(E)\n", - "\n", - "pos = nx.spring_layout(G)\n", - "nx.draw_networkx(G,pos=pos)\n", - "k_cuts=2" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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jllu219keZU41d+5cq0tIGox1/C677DJJ0t69e7s9L5YG2dn3ufzyy80vFgAAAACAXnBkkywYDConJ0cej0elpaU9X+AA48aNs7qEpMFYx2/+/PkaP358m33/OjNt2rQeG2SSdOzYMV1zzTW67rrr+qNcAAAAAABi5rjllpKxAX+se4qdLRAIKBgMKhKJKD093TWz0IBEeffdd/Xuu+/2eN6qVatUW1urp556qssGmWQ8YWTXrl1mlggAAAAAQFwc2SSLl9/v5yl6JqmrD6usokh1DWHdc2uRRo+g4Yi2/vjHP1pdAgAAAAAAMXPkcks3an2KplNUHwhpob9E37+7XE9ULLO6nF5x2lgDAAAAAID+l1Qzyexs1apVVpfQK9MnnpmRNzQ1XaF9QW2r3qBjTREdaWpQ1nXz2pxjJ04bawAAAAAA0P+YSWYT9913n9UlxGXN+kLdM6dIY0ZO0eTRs7XQX6Lbbsi3bYNMcu5YAwAAAACA/sNMMpuorKy0uoRObdoZaPM67XyPfGOMhyas/rhBlpbqkWQswRwzcooaj0cSXGXv2HWsAQAAAACAdWiSoVtdzQgrqyjW6wdCWrO+UJkZozRvZoEkKS3Vo7r6cCJLBAAAAAAA6DOaZIjLvJkF0cbY2cfO/h0AAAAAAMAp2JPMJnbv3m11CUmDsQYAAAAAAO0xk8wm1q5dq7lz5yb8c4cMT/hHWvq5knVj7USTJk3q9TXht+okSd7LMtt83d+fCwAAAABAX9Aks4kHH3zQksbN1bMS/pGWs2qsnWjFihW9vuY7RaWSpB8W5rX5GgAAAAAAO2O5JQAAAAAAAJIeTTIAAAAAAAAkPZpkNrFy5UqrS0gajDUAAAAAAGiPJplNTJgwweoSkgZjDQAAAAAA2qNJZhMzZsywuoSkwVgDAAAAAID2aJIBAAAAAAAg6dEks4mpU6daXULSYKwBAAAAAEB7NMlsYsuWLVaXkDQYawAAAAAA0B5NMgAAAAAAACQ9mmQAAAAAAABIejTJbCIQCFhdQtJgrAEAAAAAQHs0yQAAAAAAAJD0aJLZhN/vt7qEpMFYAwAAAACA9gZZXQCstXejdPRg4j93yHDp6lmJ/1y438KFC7V9+3ZLPnvSpElasWKFJZ8NAAAAAOgbmmRJ7uhBKVJrdRWAebZv366qqiqrywAAAAAAOAzLLW1i/vz5VpeQNBhrAAAAAADQHk0ym1iwYIHVJSQNxhoAAAAAALRHk8wmpk+fbnUJSYOxBgAAAAAA7dEks4lDhw5ZXULSYKwBAAAAAEB7bNyPLtXVh1VWUaSqnWt1z61FamyK6MiH9Ro6OEPzZhZYXR4AAAAAAIBpaJLZxPjx460uoYPMDK/mTMvXvtqtmjMtL3r8ocdyVFZR7NhGmR3HGgAAAAAAWIvlljaxbt06q0uIWWa6V3trt1hdRtycNNawr3POOcfqEgAAAAAAJnJlk6y4uFiBQECBQEDFxcVWlxOTJUuWWF1CTKprQzrWFNED/tVWlxI3p4w1EuOqq67Svffeq9WrV+svf/mLnnrqKT322GNatGiRJk+e3Ok1M2fO1N69e5mVCAAAAAAu4romWWFhoTwej/x+v/x+vySptLTU4qp6Vl5ebnUJXWpsiii0L6jQvqDWby7R9Ik5Skv1SDKaZvevmKyyCqMZuXp9oVavL1RjU8S6gntg57FG4mRlZenpp59WdXW1Vq1apXvuuUef//zn9bnPfU5f/epX9cgjj2jr1q3atm2b7rrrruh1M2fO1J/+9CddeeWV+vrXv27dHwAAAAAAYCrX7UlWWlqqw4cPR19nZ2crNzdXeXl53VyF7qSleuQbky1JGjNyiu5edqWefMgY49EjfPr+3eVasS5f82YW6OqRUzV9ot/KcoFuDR48WD/5yU907733SpI+/PBD/d///Z9efPFFVVdXq6WlRSNHjtSUKVN0xx13yOfz6fHHH9dXv/pV/fKXv9Svf/1rDR48WGvWrFFhYaHFfxoAAAAAgFlc1SQLhUIdjnk8HoVCIUUiEXk8nsQX5TJpqR41NkVUXRvS6BE+ScYG/1dd6tOKQL7umVNkcYVA14YMGaKnnnpKN954o06ePKkf/OAHevTRR/XBBx90OHf16tX69re/rbvvvlvFxcW69dZb9fnPf14DBgzQmjVrlJeXp5aWFgv+FAAAAACA/uDIJlkoFFIwGJTX6402wQoKCtTQ0NDhXK/XK0lqaGiwdZOsqqrK6hJilpnuVV1DWKNH+FRXH1Zmhld3zVqs+1dMji7DtDMnjTXMk5KSonXr1unGG2/Um2++qS9+8Yt65ZVXur3mxIkTWrNmjSKRiH77299q4MCBOnLkiP71X/+VBhkAAAAAuIzj9iQLhULKzc1VQUGB/H6/wuGwysrKJEmRSKTL67p7zw527dpldQkd1NWHVbmjTJdkeLV+85l93RbeWaLKHWXatDOgzAyjCRmqDuqeOUVavd7+y8/sONbofwsWLNDs2bP13nvvKSsrq8cGWauZM2fq17/+tQYOHKj3339fQ4cO1Y9+9KN+rhYAAAAAkGiOm0mWm5uroqIzS/pqamqUnW3sl+XxeDo0w1pfxzuLrHXWUUpKSlzXS9KiRYt6PGf58uU9nrd8+fK4a+jKj++t0HWjsjp9LzPDq9xOlk/6xmRH9yiTjGZaZrpXo0f4tH5zSXR2WXeqqio19a6Zfaq9M3Ye63gU/rBEkpG/s7+2MzvWnJ6ermXLlkmS8vLy9MYbb8R0Xesm/a17kC1fvjzaqC8tLdXWrVvbnF9VVWX5nxUAAAAA0FasK4EcNZMsHA4rFApFm2KSFAwGNXv2bEnGD8LttS7BTE9PV2lpqUpLS5Wfn9/p/mXovdC+oB5+LCfaFPONnq2HH8tRXX3Y4sqAM77+9a/rggsu0F//+lf94Q9/iOma9g2yvLw8vfbaa/rpT38qSZo/f35/lgwAAAAASLCUFgdtrBMIBLRs2TJt27YteiwlJaVNR3DYsGHav39/dOZY66yP1atXq6GhQdnZ2QqFQsrJyVFNTU2Pn5mVlSVJqqysjLvuPXv29HjOuHHjtHv37m7PGTt2bNw1dGXrb6VIrem37ZFnhDTly+bf185jHY/vFBnLXH9YmNfmazuzuuasrKwO+869/PLLmjRpkr70pS/pj3/8Y4/36KxB1vp9xuv1qqamRk1NTfJ4PDp58mT0uhkzZvTpewUAAAAAwDqOmknWugl/q+Li4jazyiRjKVUwGIy+DgaDys/PVzgcVnl5uSTJ5/MpHLbXTKelS5daXULSYKyTS2pqqq699lqdOnVKGzZs6PH87hpkkjGjdc+ePUpNTdU111zTn6UDAAAAABLIUXuS+Xw+zZs3T6WlpUpPT9eWLVuiSy1bFRUVqbi4WIFAILrUMi/PmMXS2lALBoMdmmtWmzt3rtUlJA3GOrmMGzdOAwcO1Kuvvqrjx493e25PDbJWL7/8ssaOHatrr72WpdsAAAAA4BKOapJJUkFBQfTrZcuWafHixd2ec7bWJZglJSXRWWV2EcsSQJiDsU4uH3zwgUpKSvTmm292e94nP/nJmBpkkvTUU0+psbFR+/fv74+SAQAAAAAWcFyT7GyhUEg+n69X1xQXF2v16tVxP+0SgLPU1NTo3nvv7fG8d955R9/97nc1YcIE5efnd/v0k9/85jf6zW9+Y2aZAAAAAACLOWpPslbBYFA5OTnyeDwqLS2N+bpAICC/3y+Px9Nm3zL0Xl19WCsC+Sosna3qWpabwR0effTRbmeQAQAAAADcy5EzybKzs3u9p1jrUy7T09MlGUsvz35KptVan6LpFNUHQlroL1FjU0SPBHK15G57LV/tjtPGGgAAAAAA9D9HNsni4fP5dPjwYavL6NKqVausLqFXpk/0R78empqu0L6gtlVv0LGmiI40NSjrunltzrETp401AAAAAADof45cbulG9913n9UlxGXN+kLdM6dIY0ZO0eTRs7XQX6Lbbsi3bYNMcu5YAwAAAACA/pM0M8nsrrKy0uoSOrVpZ6DN67TzPfKNMZa6rv64QZaW6pFkLMEcM3KKGo9HElxl79h1rAEAAAAAgHVokqFbXc0IK6so1usHQlqzvlCZGaM0b2aBJCkt1aO6+nAiSwQAAAAAAOgzmmSIy7yZBdHG2NnHzv4dAAAAAADAKdiTzCZ2795tdQlJg7EGAAAAAADt0SSzibVr11pdQtJgrAEAAAAAQHsst7SJBx98UHPnzk345w4ZnvCPtPRzJevGGokxadKkuK4Lv1UnSfJeltnm60R8NgAAAADAejTJktzVs6yuADDXihUr4rruO0WlkqQfFua1+RoAAAAAkBxYbgkAAAAAAICkR5PMJlauXGl1CUmDsQYAAAAAAO3RJLOJCRMmWF1C0mCsAQAAAABAezTJbGLGjBlWl5A0GGsAAAAAANAeTTIAAAAAAAAkPZpkAAAAAAAASHo0yWxi6tSpVpeQNBhrAAAAAADQHk0ym9iyZYvVJSQNxhoAAAAAALRHkwwAAAAAAABJjyYZAAAAAAAAkh5NMpsIBAJWl5A0GGsAAAAAANAeTTIAAAAAAAAkPZpkNuH3+60uIWkw1gAAAAAAoL1BVhcAa+3dKB09mPjPHTJcunpW4j8XsKuFCxdq+/btCf/cSZMmacWKFQn/XAAAAACwG5pkSe7oQSlSa3UVALZv366qqiqrywAAAACApMVyS5uYP3++1SUkDcYaAAAAAAC0R5PMJhYsWGB1CUmDsQYAAAAAAO3RJLOJ6dOnW11C0mCsAQAAAABAezTJbOLQoUNWl5A0GGsAAAAAANAeG/ejS3X1YZVVFKlq51rdc2uRGpsiOvJhvYYOztC8mQVWlwcAAAAAAGAammQ2MX78eKtL6CAzw6s50/K1r3ar5kzLix5/6LEclVUUO7ZRZsexBgAAAAAA1nJlk6y4uFher1eSFA6HVVBg/2bOunXrrC4hZpnpXu2t3WJ1GXFz0lgD3Rk2bJjGjx+vwYMH6/jx49q9e7fef//9Ls//+7//e+3du1evvfZaAqsEAAAAAGdw3Z5khYWF8ng88vv98vv9kqTS0lKLq+rZkiVLrC4hJtW1IR1riugB/2qrS4mbU8Ya6Myll16qpUuXqrq6Wg0NDXruuef09NNPa9OmTTp06JDeeOONNn9R0ConJ0dr165VRUWFhg8fblH1AAAAAGBfrmuSlZaWKi/vzNLA7OxslZSUWFhRbMrLy60uoUuNTRGF9gUV2hfU+s0lmj4xR2mpHklG0+z+FZNVVlEsSVq9vlCr1xeqsSliXcE9sPNYA10555xztHTpUu3fv19LlizRVVddpaamJr300kt6+umn9cILL6ixsVGXX365/u3f/k3V1dV65JFHlJqaqpycHD3++OMaNGiQSkpKdPDgQav/OAAAAABgO65abhkKhToc83g8CoVCikQi8ng8iS/KBdJSPfKNyZYkjRk5RXcvu1JPPnRYkjR6hE/fv7tcK9bla97MAl09cqqmT/RbWS7gOsOHD9ef//xnTZ48WZJUVlamVatW6bnnntPp06ej5w0YMEBTp07Vvffeq69+9atatGiR5s6dq4svvliDBg3Sww8/zExKAAAAAOiCI5tkoVBIwWBQXq832gQrKChQQ0NDh3Nblxw1NDTQJDNBWqpHjU0RVdeGNHqET5Kxwf9Vl/q0IpCve+YUWVwh4C4ZGRmqqKjQ+PHjFQ6H9fWvf13PPvtsp+c2NzfrxRdf1Isvvqif/vSnevLJJ3XZZZdJkh599FEaZAAAAADQDccttwyFQsrNzVVBQYH8fr/C4bDKysokSZFIpMvrunvPDqqqqqwuIWaZ6V7VNYQlSXX1xu93zVqsUHUwugzTzpw01kBpaanGjx+vV155RdOmTeuyQdbeqFGj9MlPfjL6etKkSUpJSemvMgEAAADA8RzXJMvNzVVR0ZnZSjU1NcrONpYCejyeDs2w1td2n0W2a9cuq0vooK4+rModZbokw6v1m888/GDhnSWq3FGmTTsDyswwZuqFqoO6Z06RVq8vtKrcmNlxrIHO+P1+3XHHHTpy5Ihuu+02HTp0KKbrzt6D7Mc//rHee+89zZgxQ/fee28/VwwAAAAAzuWo5ZbhcFihUCjaFJOkYDAYbZqlp6d3uKZ1CWZ6eroCgYC8Xq+CwaCys7Pl8/l6/MzWWUd9mYGxaNGiHs9Zvnx5j+ctX7487hq68uN7K3TdqKxO38vM8Cq3k+WTvjHZ0T3KJKOZlpnu1egRPq3fXGK8zvB2uO5sVVWVmnrXzD7V3hk7j3U8Cn9oPHQiJSWlzdd25sSaJXvW/d3vfleS8dTet956K6Zrzm6Qte5B9uKLL6q8vFyFhYUqKSlRc3Nz9PyqqirL/5wAAAAA0J9aWlpiOs9RM8lCoVCHxtbZTTOfz9dhNlkkEpHP51NDQ4OWLVsmn88nn8+nwkL7z3hygtC+oB5+LCfaFPONnq2HH8uJLsMEEJ8bbrhBn/rUp3Tw4EH94he/iOmazhpkkrRu3Tq9/vrruvzyy/WFL3yhP8sGAAAAAMdy1Eyy1k34WxUXF7eZVSZJeXl5CgaD8vuNJywGg0Hl5+fL6/XqmWeekWQ01mbPnh3TZ86YMUOSVFlZGXfde/bs6fGc5cuXKy8vr9tzHnnkkbhr6MrW30qR2viv943J1sox26Kv580s0LyZBT1eN2NGllpWxdbJ7Q07j3U8vlNkLHNtaWlp87WdObFmyfq6s7Ky2uyXd8stt0gynmR58uTJHq/vqkEmGX+Oxx57TEuXLtUtt9yi9evXR9+bMWNGn76/AQAAAIBbOKpJ5vP5NG/ePJWWlio9PV1btmzp0OwqKipScXGxAoFAdKlla0PE4/EoGAyqpqZGJSUlCa+/O0uXLrW6hKTBWMMJJk+eLEl68cUXezy3uwZZq9b7tN4XAAAAANCWo5pkklRQcGaW0rJly7R48eJuz2kvOztbkUhE+fn5tmqUzZ071+oSkgZjDSdofTJlTU1Nt+fF0iCTpNdff73NfQEAAAAAbTlqT7L2OtujrLtzg8GgJKNRVlpa2sMViTVu3DirS0gajDWcICsrS+np6dq6dWu352VmZvbYIJOk/fv3KyMjQxMnTjS7VAAAAABwBUc2yYLBoHJycuTxeGJudm3dulWhUEiS8cRLj8fTjxUCQN+cOHFChw8f1qlTp7o977/+67904403dtsgk6Tm5mY1NDSoqanJzDIBAAAAwDUct9xSMmaCtd+wvyd5eXkqLS1VIBDQhg0bopv4Iz519WGVVRSpriGse24t0ugRsc3oA2C+F154weoSAAAAAMDxHNkki1frBv6tT760k6ysLKtL6JXqAyEt9JeosSmiRwK5WnJ3udUlxcxpYw0AAAAAAPpfUjXJ7GzVqlVWl9Ar0yeeaTQOTU1XaF9Q26o36FhTREeaGpR13bw259iJ08YaAAAAAAD0P0fuSeZG9913n9UlxGXN+kLdM6dIY0ZO0eTRs7XQX6Lbbsi3bYNMcu5YAwAAAACA/sNMMpuorKy0uoRObdoZaPM67XyPfGOM/eBWf9wgS0v1SDKWYI4ZOUWNxyMJrrJ37DrWAAAAAADAOjTJ0K2uZoSVVRTr9QMhrVlfqMyMUZo3s0CSlJbqUV19OJElAgAAAAAA9BlNMsRl3syCaGPs7GNn/w4AAAAAAOAU7ElmE7t377a6hKTBWAMAAAAAgPaYSWYTa9eu1dy5cxP+uUOGJ/wjLf1cybqxBrozadKkXl8TfqtOkuS9LLPN1/39uQAAAADgRjTJbOLBBx+0pHFz9ayEf6TlrBproDsrVqzo9TXfKSqVJP2wMK/N1wAAAACA3mO5JQAAAAAAAJIeTTIAAAAAAAAkPZpkNrFy5UqrS0gajDUAAAAAAGiPJplNTJgwweoSkgZjDQAAAAAA2qNJZhMzZsywuoSkwVgDAAAAAID2aJIBAAAAAAAg6dEks4mpU6daXULSYKwBAAAAAEB7NMlsYsuWLVaXkDQYawAAAAAA0B5NMgAAAAAAACQ9mmQAAAAAAABIejTJbCIQCFhdQtJgrAEAAAAAQHs0yQAAAAAAAJD0aJLZhN/vt7qEpMFYAwAAAACA9gZZXQCstXejdPRg4j93yHDp6lmJ/1wA5lm4cKG2b99uyWdPmjRJK1assOSzAQAAALgTTbIkd/SgFKm1ugoATrR9+3ZVVVVZXQYAAAAAmILlljYxf/58q0tIGow1AAAAAABojyaZTSxYsMDqEpIGYw0AAAAAANqjSWYT06dPt7qEpMFYAwAAAACA9miS2cShQ4esLiFpMNYAAAAAAKA9Nu5Hl+rqwyqrKFLVzrW659YiNTZFdOTDeg0dnKF5MwusLg8AAAAAAMA0NMlsYvz48VaX0EFmhldzpuVrX+1WzZmWFz3+0GM5KqsodmyjzI5jDQAAAAAArMVyS5tYt26d1SXELDPdq721W6wuI25OGmsA0oUXXmh1CQAAAACSgCubZMXFxQoEAiotLVVxcbHV5cRkyZIlVpcQk+rakI41RfSAf7XVpcTNKWMNuElKSopmz56t//zP/9RTTz2lHTt2aPv27Xrqqaf0gx/8QNnZ2UpJSelw3f3336+9e/cyAxQAAABAv3Ndk6ywsFAej0d+v195ecYSwdLSUour6ll5ebnVJXSpsSmi0L6gQvuCWr+5RNMn5igt1SPJaJrdv2KyyiqMZuTq9YVavb5QjU0R6wrugZ3HGnCblJQU5efnq7q6Wk8//bQWL16sz33uc5o4caKuu+46fe5zn9N3v/tdbdiwQfv27dM999wTbZbdf//9+vnPf66LL75Yn/70py3+kwAAAABwO9ftSVZaWqrDhw9HX/v9fuXk5EQbZui9tFSPfGOyJUljRk7R3cuu1JMPGWM8eoRP37+7XCvW5WvezAJdPXKqpk/0W1kuAJsYOXKkfvOb3ygrK0uS9MYbb+iJJ57QSy+9pP379yslJUVXXnmlrr/+et1111266qqrtHr1an35y1/Wxo0b9YMf/ECSNH/+fP2///f/LPyTAAAAAEgGrmqShUKhDsfS09MVCoUUiUTk8XgSX5TLpKV61NgUUXVtSKNH+CQZG/xfdalPKwL5umdOkcUVArADr9eryspKjRw5Uu+9957++Z//WeXl5Wpubm5z3vbt2/Xkk0/qe9/7nubNm6dHH31Ut9xyi2655RZJRoNs5cqVVvwRAAAAACQZRy63DIfD0X3HgsGgCgsLJUkNDQ0dzm1tjHX2np1UVVVZXULMMtO9qmsIS5Lq6o3f75q1WKHqYHQZpp05aawBJ0pLS9PTTz+tkSNH6rnnntOECRNUVlbWoUF2tubmZj3xxBP6yU9+Ej323nvv6Ve/+lUCKgYAAAAABzbJQqGQcnJyVFBQIL/fr3A4rGAwKEmKRCJdXtfde3awa9cuq0vooK4+rModZbokw6v1m8/s67bwzhJV7ijTpp0BZWZ4JUmh6qDumVOk1esLrSo3ZnYca8BNfvSjH2nUqFF6+eWX9YUvfEH19fUxXXf//ffrhz/8oSTpwIEDuvjii6OvAQAAAKC/OW65ZW5uroqKzizpq6mpUXa2sV9WZ8spW5tj8S61bJ111NlT12K1aNGiHs9Zvnx5j+ctX7487hq68uN7K3TdqKxO38vM8Cq3k+WTvjHZ0T3KJKOZlpnu1egRPq3fXGK8/rh51pWqqkpNvWtmn2rvjJ3HOh6FPyyRZOTv7K/tzIk1S86s2441X3PNNbr33nt18uRJ3X333WpsbIzputZN+iVjieXf/vY3bdmyRd/61re0cuVK7dmzp835VVVVlv9ZAQAAADhDS0tLTOc5aiZZOBxWKBSKNsUkKRgMaurUqZKM/cfazxhrXWaZnp4ePVZcXGz7mWVOEdoX1MOP5USbYr7Rs/XwYznRZZgAksv9998vSVq9enXMszbbN8hWrlypHTt26Be/+IUk6b777uufYgEAAADgLCktsbbTbCAQCGjZsmX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" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "depth=1\n", - "createCircuit_MaxCut(np.array((np.pi,np.pi)),G,depth,k_cuts,1,True,\"depth1\").draw(output='mpl')" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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KdEmKhmarguUqnF6msuJKrauvkiTdPu+B2DFAOpk9e7b+8z//U/n5+ZKkXbt2qb6+XqFQSK2trcrMzNTll1+uwsJClZSU6B/+4R9UWlqq+++/X1dffXUsILvxxhsJyAAAAACgD7YLyYAeWZkuefK9kqT8CbN054pL9JPl7ZKkvPEePXhnnVZvrFBZcaUmTSjQ3Gk+M8sF+jV//nxt3LhRY8aM0csvv6yvf/3reuaZZ0467mc/+5m+853vyO126zvf+Y5uu+02Pfzww5IUC8ief/754S4fAAAAACzBkhvThEIh+f1+BYNBGYYhv99vdkmO1NjYaHYJccvKdKmjM6J9B0Kx53Jz3Lr0Qo9WByvkyfOaWN3grDTWSK6CggIFg0GNGTNGa9eulcfj6TMgO144HNbnP/95/fa3v40996Mf/YiADAAAAAAGYLmQLBQKqby8XJWVlfL5fAqHw6qtrTW7LEd6+eWXzS5hSHKz3WppC0uSWlqjX2+f94BC+4y0X2JptbFGcowZM0ZPPPGExo4dq0AgoK9+9as6evTooOf17EF27bXX6p133pEkffnLX9b06dNTXTIAAAAAWJbllluWl5eruro69ri5uVleb+pmAfXM4MnIyEjZPdLVkiVLBnx91apVcR2TbN/7ymZNn1jU7+strWE17KjV+Tlu1W+p0fw5iyRJiz8b0C9eDEhSbGllaJ+hhfOrta6+SuXzq/u9Zo/GxgYV3F586j/EcQYbQ8m8sU5E1XejY5yRkdHr+3SXjnXfd999mjx5snbt2qX77rsvrnNO3KT/xhtvVFlZmb7+9a/r4Ycf1nXXXdfr+MbGRtN/TgAAAABIpe7u7riOs1RIFg6HFQqFeoVihmH0Cs0GUlNTI0natm2bKioq5PF4UlInzJWb4+4z8PLke2N7lEnRMC0326288R7VbwlEH+e4h7NUoF8jRozQV7/6VUnSN77xDb333nuDntNXQPb8889rx44d+sIXvqBrr71W06dP144dO1JdPgAAAABYjqVCslAodFKwdWJoNtC5brdbXq9XoVBIpaWlam5uHvS8wsJCSVJDQ0NCNVvZ7t27B3x91apVWrRo0YDHrFy5MpklSZK2PilFDpzaNUJ7DT36yyr5K34jSfLklejb60v14J11AwZlhYVF6l4bXwIdr8HGWTJvrBNxf3U0jO7u7u71fbozu+6ioqJee89dd911uvjii7V//349/fTTg57fX0AmSUeOHNETTzyh++67T3feeWevkKywsNCRv98AAAAA4ESW2pPM7e4dXvj9/riXWobDYdXV1UmSPB6PwuFw0utzmoceesjsEhLmyfdqzeJtsb3IyoortWbxtrSdSWblsUZirrrqKknS//zP/wwa1g0UkPX41a9+JSn6QQAAAAAAgJNZaiaZx+NRWVmZampqlJ2draamJpWUlPQ6JhwOKxgMKhAIqK2tTVVVVSopKZHP54sFaoZhpHQfM6dYsGCB2SU4BmPtPFdccYUk6Q9/+MOAx8UTkB1/nWnTpiW/WAAAAACwAUuFZJJUWVkZ+37FihV64IEHer3udrtVWVnZ67geLpdLkhQIBGKzypC4ng3FkXqMtfM899xzOnr06KD7hz344IODBmSS1Nraqscff1xHjhxJRbkAAAAAYHmWC8mO19ceZYPx+/1at25dLDADgHS0bt06rVu3btDj/vVf/1VFRUX63//7f/cbkEnSsWPH9KUvfSmZJQIAAACArVhqT7IehmGotLRULpcr9omV8QgGg/L5fHK5XDIMI4UVIl21tIa1OlihqpoS7TsQMrsc4JS1t7erqKhowIAMAAAAADA4S84k83q9Q95TLBQKqby8XNnZ2ZKiSy+3bduWivIco6ioyOwShmzf6yEt9gXU0RnRymC5lt5pjWW3VhxrAAAAAACsxJIhWSI8Ho/a29vNLsNW1q5da3YJQzZ3mi/2/ZmZ2QrtNbRt3yYd6YzoUGebiqaX9TomXVhxrAEAAAAAsBJLLrdEerj77rvNLiFhj9ZXaeH8auVPmKWZeSVa7Avo5tkVaRmQSdYeawAAAAAArMAxM8mQfA0NDWaX0K9ndwZ7Pc4a65InP7pEd93fA7KsTJek6BLM/Amz1PFuZJirjF86jzUAAAAAAHZASAZb6m9GWO1mv/a/HtKj9VXKzZmosuJKSVJWpkstreHhLBEAAAAAAKQRQjI4SllxZSwYO/65478CAAAAAADnYU8yJGzXrl1ml+AYjDUAAAAAAKlFSIaEbdiwwewSHIOxBgAAAAAgtVhuiYQtW7ZMCxYsGPb7jjtv2G9p+r3NGmsMnxkzZgz5nPBfWiRJ7otye32f6vsCAAAAgB0RksFyJs0zuwIg+VavXj3kc+6vrpEkfbdqUa/vAQAAAABDx3JLAAAAAAAAOB4hGRK2Zs0as0twDMYaAAAAAIDUIiRDwqZOnWp2CY7BWAMAAAAAkFqEZEhYYWGh2SU4BmMNAAAAAEBqEZIBAAAAAADA8QjJAAAAAAAA4HiEZEhYQUGB2SU4BmMNAAAAAEBqEZIhYU1NTWaX4BiMNQAAAAAAqUVIBgAAAAAAAMcjJAMAAAAAAIDjEZIhYcFg0OwSHIOxBgAAAAAgtQjJAAAAAAAA4HiEZEiYz+czuwTHYKwBAAAAAEitUWYXAAzVnmekwwfNufe486RJ88y5N5BuFi9erO3bt5ty7xkzZmj16tWm3BsAAACAPRGSwXIOH5QiB8yuAsD27dvV2NhodhkAAAAAkBQst0TC7rnnHrNLcAzGGgAAAACA1CIkQ8Luvfdes0twDMYaAAAAAIDUIiRDwubOnWt2CY7BWAMAAAAAkFqEZEjYW2+9ZXYJjsFYAwAAAACQWmzcD9tpaQ2rdnO1Gndu0MKbqtXRGdGhd1p15uk5KiuuNLs8AAAAAACQhgjJkLApU6aYXUKfcnPcmj+nQnsPbNX8OYtizy9fX6razX5LBmXpOtYAAAAAANiFbZdbGoahiooKs8uwtY0bN5pdwpDkZru150CT2WUkxGpjDfQnIyND+fn5uv766+X1ejV9+nSddtpp/R4/duxYLVmyRCNG2PavKwAAAABpwnbvOkKhkPx+vwKBgNra2swux9aWLl1qdglx23cgpCOdEX3Dt87sUhJipbEGTpSRkaGPf/zj+slPfqK3335be/bskWEY2rRpk7Zv367Dhw+rsbFRn//85zVmzJjYeWPHjtVPf/pTrVy5Ut/73vdM/AkAAAAAOIHtQjKPx6PKykoVFBSYXcqgjnVJO/4i/fwPUv12adcbUle32VXFr66uzuwSBtTRGVFor6HQXkP1WwKaO61UWZkuSdHQ7KurZ6p2s1+StK6+Suvqq9TRGTGv4AGk+1gD/Zk8ebJeeOEFPf300/r0pz+tcePG6bXXXtMzzzwjwzC0Z88ejRkzRnPnztX69eu1d+9eeb3eWEB2ww036M0339Sjjz5q9o8CAAAAwObYk8wke/8qrf+ddPjd4558WcrJkv7hOml8tmml2UZWpkuefK8kKX/CLN254hL9ZHm7JClvvEcP3lmn1RsrVFZcqUkTCjR3ms/McgHb+dznPqcf/OAHGjNmjN544w09/PDDeuKJJ/TGG2/0Ou6ss86Sz+fTfffdpyuuuEKbNm1SOByW2+3Wm2++qXnz5umVV14x6acAAAAA4BSWnEnWs6QyGAzKMAz5/X6zSxqSV/8mBTZLHe+e/FrbEelhQ3rr8PDXZWdZmS51dEa070Ao9lxujluXXujR6mCFPHleE6sD7OeOO+7QD3/4Q40ZM0aPPvqoJk+erBUrVpwUkEnS22+/rR/84Ae68sor9U//9E/q6uqS2+3WkSNHCMgAAAAADBvLhWShUEjl5eWqrKyUz+dTOBxWbW2t2WUNyS93RJdV9rWysrtbeu996TcvD3tZQ9bY2Gh2CUOSm+1WS1tYktTSGv16+7wHFNpnxJZhpiurjTWcLT8/P7Y88v7771d5ebkOHTo06HmnnXaarrvuOo0YMULd3d0644wzNGnSpFSXCwAAAACSLBiSlZeXq7q6Ova4ublZXq91ZgG1H4kuteweYO+xbklb/yQd/WDYykrIyy+nZ5LX0hpWw45anZ/jVv2Wmtjziz8bUMOOWj27M6jcHLckKbTP0ML51VpXX2VWuXFJ17EG+vLYY48pMzNTjz/+eK/f1wM5cQ+y73znO5KktWvXyuVypbBaAAAAAIiy1J5k4XBYoVCoVyhmGEbcb8KCwaDcbrcMw5DX65XH4xn0nJ4ZPBkZGYkVfYLzL52jsn9+YdDjPuiScj4yQR1tB5Jy30QsWbJkwNdXrVoV1zHJ9r2vbNb0iUX9vp6b41b5/JN7wpPvje1RJkXDtNxst/LGe1S/JRB9/PfwrD+NjQ0quL044dr7MtgYSuaNdSKqvhuQFP1v5vjv050V607HmgsLC3XNNdfozTffjKu3pZMDsnnz5mnXrl0qKirStddeqy996UtauXJlr3MaGxtN/1kBAAAAWEP3QDOVjmOpmWShUOikYOvE0Kw/4XBYK1askMfjkcfjUVWVOTOHjr7zdvzHdg6+PAmJCe019O31pbFQzJNXom+vL40twwSQmLvvvltSdAbY228P/vuur4DslVdeUXd3d+wfQHquCQAAAACpZKmZZG5371k+fr8/7qWWbrdbv/nNbyRFg7WSkpK4zissLJQkNTQ0xF/oALq7pe/+Qjp4qO89ySQpI0OadL703hACtVTYvXv3gK+vWrVKixYtGvCYE2d/JMPWJ6XIKU6w8+R7tSZ/W+xxWXGlyoorBz2vsLBI3WvjS6DjNdg4S+aNdSLur44uce3u7u71fbqzYt1m11xUVHTSfnnXX3+9JGn9+vWDnt9fQNbjl7/8pVpbW3XppZfqoosu0l/+8pfYa4WFhUn7vQwAAAAAksVmknk8HpWVlammpkbBYFBNTU0nhV3hcFh+v1+BQECGYaiqqkqGYUiSXC6XDMNQc3OzKisHD0RSISN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- "text/plain": [ - "
" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "depth=2\n", - "createCircuit_MaxCut(np.array((np.pi,np.pi,np.pi,np.pi)),G,depth,k_cuts,1,True,\"depth2\").draw(output='mpl')" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'00000': 0,\n", - " '11111': 0,\n", - " '00001': 1.4,\n", - " '11110': 1.4,\n", - " '01000': 2.1,\n", - " '10111': 2.1,\n", - " '01010': 2.9,\n", - " '10101': 2.9,\n", - " '00010': 3.0,\n", - " '01111': 3.0,\n", - " '10000': 3.0,\n", - " '11101': 3.0,\n", - " '00111': 3.1,\n", - " '11000': 3.1,\n", - " '01001': 3.5,\n", - " '01011': 3.5,\n", - " '10100': 3.5,\n", - " '10110': 3.5,\n", - " '00011': 3.6,\n", - " '11100': 3.6,\n", - " '00101': 3.9,\n", - " '11010': 3.9,\n", - " '01110': 4.4,\n", - " '10001': 4.4,\n", - " '00100': 4.5,\n", - " '00110': 4.5,\n", - " '11001': 4.5,\n", - " '11011': 4.5,\n", - " '01101': 6.0,\n", - " '10010': 6.0,\n", - " '01100': 6.6,\n", - " '10011': 6.6}" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "costs=listSortedCosts_MaxCut(G,2)\n", - "costs" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "Aer.backends()\n", - "backend_sim = Aer.get_backend('qasm_simulator')" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0, 0.5, '$\\\\beta$')" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "n=12\n", - "m=24\n", - "beta_max=np.pi/2\n", - "gamma_max=np.pi\n", - "\n", - "circuits=[]\n", - "for beta in np.linspace(0,beta_max,n):\n", - " for gamma in np.linspace(0,gamma_max,m):\n", - " circuits.append(createCircuit_MaxCut(np.array((gamma,beta)),G,1,2,1))\n", - "job_sim = execute(circuits, backend_sim, shots=1024*2*2*2)\n", - "Elandscape_v1,_,_ = measurementStatistics_MaxCut(job_sim.result().results, options={'G' : G, 'k_cuts' : k_cuts})\n", - "f = pl.figure(figsize=(10, 6), dpi= 80, facecolor='w', edgecolor='k');\n", - "pl.imshow(-np.array(Elandscape_v1).reshape(n,m),interpolation='bicubic',origin='lower',extent=[0,gamma_max,0,beta_max])\n", - "pl.colorbar(orientation=\"horizontal\", pad=0.2)\n", - "pl.xlabel(r'$\\gamma$')\n", - "pl.ylabel(r'$\\beta$')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "from scipy import optimize as opt" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "def getval(x, backend, depth=1, version=1, noisemodel=None):\n", - " j = execute(createCircuit_MaxCut(x,G,depth,k_cuts,version), backend, noise_model=noisemodel, shots=1024*2*2*2)\n", - " val,_,_=measurementStatistics_MaxCut(j.result().results, options={'G' : G, 'k_cuts' : k_cuts})\n", - " global it, values, gamma, beta\n", - " #print(x)\n", - " it+=1\n", - " gamma[str(it)] = x[0]\n", - " beta[str(it)] = x[1]\n", - " values[str(it)] = val\n", - " return -val[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: -4.255823\n", - " Iterations: 16\n", - " Function evaluations: 36\n", - "[1.08783264 0.42189941]\n" - ] - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "version=1\n", - "it=0\n", - "gamma={}\n", - "beta={}\n", - "values={}\n", - "out=opt.minimize(getval, x0=(.7,1), method='Nelder-Mead',\\\n", - " args=(backend_sim,1,version,None),\\\n", - " options={'xatol': 1e-2, 'fatol': 1e-2, 'disp': True})\n", - "print(out.x)\n", - "f = pl.figure(figsize=(10, 6), dpi= 80, facecolor='w', edgecolor='k');\n", - "pl.plot(list(values.values()),'x-')\n", - "\n", - "f = pl.figure(figsize=(10, 6), dpi= 80, facecolor='w', edgecolor='k');\n", - "pl.imshow(-np.array(Elandscape_v1).reshape(n,m),interpolation='bicubic',origin='lower',extent=[0,gamma_max,0,beta_max])\n", - "pl.colorbar()\n", - "pl.xlabel(r'$\\gamma$')\n", - "pl.ylabel(r'$\\beta$')\n", - "pl.plot(list(gamma.values()),list(beta.values()),'ko-')\n", - "pl.plot(out.x[0],out.x[1],'xr')\n", - "\n", - "j = execute(createCircuit_MaxCut(out.x,G,1,k_cuts,version), backend_sim, shots=1024*2*2*2)\n", - "plot_histogram(j.result().get_counts())" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "jupytext": { - "formats": "ipynb,auto:light" - }, - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.3" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/MaxCut classical branch and bound algorithm.ipynb b/MaxCut classical branch and bound algorithm.ipynb deleted file mode 100644 index bcd9235..0000000 --- a/MaxCut classical branch and bound algorithm.ipynb +++ /dev/null @@ -1,264 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "%load_ext autoreload\n", - "%autoreload 2" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "import matplotlib.pyplot as pl\n", - "import time\n", - "\n", - "import networkx as nx\n", - "import os\n", - "from matplotlib import rc\n", - "font = {'size' : 16}\n", - "rc('font', **font);\n", - "rc('text', usetex=True)\n", - "\n", - "import sys\n", - "sys.path.append('../')\n", - "\n", - "\n", - "from classical_maxcut_solver import *\n", - "from data.graph_generators import *" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "57911131517192123252729" - ] - }, - { - "data": { - "text/plain": [ - "Text(0, 0.5, 'solution time [sec]')" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "t=[]\n", - "num_threads=1\n", - "max_vert=30\n", - "for num_vert in range(5,max_vert,2):\n", - " print(num_vert,end='')\n", - " G = er(num_vert, 0.6*num_vert, True)\n", - " tin=time.time()\n", - " branch_and_bound(G,num_threads)\n", - " t.append(time.time()-tin)\n", - "pl.plot(range(5,max_vert,2),t,'x-')\n", - "pl.title(\"Erdos Renyi weighted\")\n", - "pl.xlabel(\"vertices\")\n", - "pl.ylabel(\"solution time [sec]\")" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "57911131517192123252729" - ] - }, - { - "data": { - "text/plain": [ - "Text(0, 0.5, 'solution time [sec]')" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "t=[]\n", - "num_threads=1\n", - "max_vert=30\n", - "for num_vert in range(5,max_vert,2):\n", - " print(num_vert,end='')\n", - " G = er(num_vert, 0.6*num_vert, False)\n", - " tin=time.time()\n", - " branch_and_bound(G,num_threads)\n", - " t.append(time.time()-tin)\n", - "pl.plot(range(5,max_vert,2),t,'x-')\n", - "pl.title(\"Erdos Renyi unweighted\")\n", - "pl.xlabel(\"vertices\")\n", - "pl.ylabel(\"solution time [sec]\")" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "591317212529333741454953576165697377818589" - ] - }, - { - "data": { - "text/plain": [ - "Text(0, 0.5, 'solution time [sec]')" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "t=[]\n", - "num_threads=1\n", - "max_vert=93\n", - "for num_vert in range(5,max_vert,4):\n", - " print(num_vert,end='')\n", - " G = ba(num_vert, 4, True)\n", - " tin=time.time()\n", - " branch_and_bound(G,num_threads)\n", - " t.append(time.time()-tin)\n", - "pl.plot(range(5,max_vert,4),t,'x-')\n", - "pl.title(\"Barabasi-Albert weighted\")\n", - "pl.xlabel(\"vertices\")\n", - "pl.ylabel(\"solution time [sec]\")" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "591317212529333741454953576165697377818589" - ] - }, - { - "data": { - "text/plain": [ - "Text(0, 0.5, 'solution time [sec]')" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "t=[]\n", - "num_threads=1\n", - "max_vert=93\n", - "for num_vert in range(5,max_vert,4):\n", - " print(num_vert,end='')\n", - " G = ba(num_vert, 4, False)\n", - " tin=time.time()\n", - " branch_and_bound(G,num_threads)\n", - " t.append(time.time()-tin)\n", - "pl.plot(range(5,max_vert,4),t,'x-')\n", - "pl.title(\"Barabasi-Albert unweighted\")\n", - "pl.xlabel(\"vertices\")\n", - "pl.ylabel(\"solution time [sec]\")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.8.3" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/MaxCut/CVaR.ipynb b/MaxCut/CVaR.ipynb new file mode 100644 index 0000000..1f00a25 --- /dev/null +++ b/MaxCut/CVaR.ipynb @@ -0,0 +1,254 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "f4edc85e", + "metadata": {}, + "outputs": [], + "source": [ + "#run: pip install openquantumcomputing\n", + "from openquantumcomputing.QAOAMaxCut import QAOAMaxCut" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "81310eb6", + "metadata": {}, + "outputs": [], + "source": [ + "from qiskit import *\n", + "import numpy as np\n", + "import networkx as nx\n", + "\n", + "import matplotlib.pyplot as pl\n", + "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", + "from qiskit.visualization import *" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "eaa8c8a1", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "numV=21\n", + "G = nx.read_gml(\"../../data/sample_graphs/w_ba_n\"+str(numV)+\"_k4_0.gml\")\n", + "pos = nx.spring_layout(G)\n", + "nx.draw_networkx(G,pos=pos)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "75d8e6d2", + "metadata": {}, + "outputs": [], + "source": [ + "# Initialize QAOA object\n", + "alpha = 0.1 # value for CVaR (Conditional Value at Risk)\n", + "params={'G': G, 'alpha': alpha}\n", + "qaoamc_cvar = QAOAMaxCut(params=params)\n", + "params={'G': G}\n", + "qaoamc = QAOAMaxCut(params=params)" + ] + }, + { + "cell_type": "markdown", + "id": "fabaeff8-5594-4e7e-b620-1c9354761229", + "metadata": {}, + "source": [ + "min cost is precalculated" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "9e337fd3", + "metadata": {}, + "outputs": [], + "source": [ + "mincost=-25.23404480588015" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "f10939f8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Calculating Energy landscape for depth p=1...\n", + "Executing sample_cost_landscape\n", + "parameters: 2\n", + "Done execute\n", + "Done measurement\n", + "Calculating Energy landscape done\n", + "Calculating Energy landscape for depth p=1...\n", + "Executing sample_cost_landscape\n", + "parameters: 2\n", + "Done execute\n", + "Done measurement\n", + "Calculating Energy landscape done\n" + ] + } + ], + "source": [ + "# Evaluating the QAOA circuit with uniformly sampled angles for gamma and beta, just to see how sampling measurements from \n", + "# the circuits roughly looks like.\n", + "qaoamc.sample_cost_landscape(angles={\"gamma\": [0,np.pi/2,10], \"beta\": [0,np.pi/2,10]})\n", + "qaoamc_cvar.sample_cost_landscape(angles={\"gamma\": [0,np.pi/2,10], \"beta\": [0,np.pi/2,10]})\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "1b4a83aa", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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nb4//cNc6lxpb1qOhfNxek+MYAinnRVhJU/uoSoRGY91yCddbOVw7aR4tVGh82L81VtRIwnMgDzYoC806gVkWloOaQy3RR9W6UZ/nAa9YBmpcwFKzpGtBolxtQ242ysn2IUysK+4xhROLRu2c52TWIKBZAzDrBLW3vZj2a67XmBtsevGQ0VeDj/ErM7ik/uvzQCFbBrBNhIntOnryiM6LKgDjEy0EE6kWnpwqgLNRYEphWRecfW1J8/V+5EVLtR9TXv6loMSoB33d4MYcswbG+5y8cFdGuVC/gjJ6m6LDm8jbFHddMuxb2721evagzzFNQ8zxxtTC01ZFt1kVZLUDU9oHV9+XnrXnzxa1UaV87RCMHOswXcSCkkJPLyC5iAcOQq2wU7JiYjcrAWJTLtZq32woon5Mu31Sd8SJ2sJTVwWHFQUkCdAkwKwCywjIez8Dg5gvrRmCjYelq9aNVZnbGAPuUQTa0FP1BAe6zsMkCRmLANtkmNgYSIT69bCGCmrDtpNFdYNTkCZxmWWAKRoPBVmiGtunL50bg1N/ABBsCJRD5T6JsYgfOyeZm2PviwyFcMOWUQTZGudmQ4AVwzWmHEretmNkyOoHNeLusEm18Kx7brMM3GKBGWxPMAaiSPWwr+RKxKtWBygoM7JznjErQO0MezMUTvTdMxmoG3w4QcjJOh3SfQXnZH39BMYBoJnbdiLvjaVU+efbKmgyLBjqDHoAA1XT4EzMNJVY9RJlnOFuvtWmtp2VzcsnVvnE/FMw/+x8dIg6HbMflQCqo4px638d5baZtdFh2rLyqfroEH++Pri+Osr5I/eB+pOOyzNG0V8dbQiPWVFW30/3zzhmnvfPOw6mb+95EWpbHz91Pur7wLWffX4q/tmfLeezlinUVkxZrp6m0H7X+ecqQVdV/6tDq1atwrx58zBlyhRcfvnlRt5nPvMZHHHEETjyyCNx1FFH4ZprrhG3O3mdZ+h9YfJrcZsxTtPbTqBP3xh97RJjJNug6nnKSvKCn5eK7lZcJqZcT6ruewdKXjsS6iBSbYXm3Zx83hF6nWBiVifzg/OlfD6SwGkRmo8NHGhvbmg+VLC4KXFeBFR1vpRrp2bV4zyrD3LhwoVYu3YtLr30Uifv8MMPx/e+9z3svvvu2LRpE44++mj8/u//PubMmRNsd/LBs8LFtcxcog9KUhCKy/nGFgHz4D5Q4+DSuPpUv4K2RPmC91gMujKf/3q+MMfJmE8LxSF7ojinv1kcTH2Qtfvm5vk84eLYULHbNl/f+/Qf33wvdxIHwc23m7cfwYck/ydSoWM6wpo/fz4AoNNxA62vfe1r89ezZs3CS17yEmzatKmFp6M+glMMTbsdCTRLALMSLGO/IFB9cG2F0gN5QQjW6UTrUFl3GrLkZd20M2ep2LwCQAz4fBfoulysMQ462wcsr4v1gpB/33zONXhfaCjf6lp69jhNNnmOM4Mar2FWcNu2rZg5c2a+vXz5cixfvrxyu5T+/d//HU8++SQWLlwoKj854FkxTNcYOOuCZiwwvS7UzPPul90uVZ9L86SzQKziRiWKAVu/v7VHPYQ8lO9xl0afdJssYA33KASszzE25Qh9cGWqDASsWdOSc403/CJVOp2JygqoZc5y2rRp2Lx5s7fM8ccfj/vuu4/MW79+PWbNmhXs5+6778b//t//G9dccw122WUX0dhGG54x750UnDEurEloVgCmpB9vW0RZKTRJMJZxoz5VCQeX6XfQz0nzhECLMnq+8EorgSwDRcWBj3Ovnrb8zrb8PCwbHo4Eq/90qQDWcON8KD1ySE2cwf1abbtu3bpK9e+991688Y1vxKpVq/DKV75SXG804Rl98aOTY8AZ7TYjYEa6zAhgxoPbA8rgl4cKTpRSneFfX3vS+lXL1y2F8D753ItKeNjGQFb6fmSs87XNOVimLSdP6GBZuOaAt9uh21dMelanlGP1ueqsaakrtbtr4pwd9OegpO677z6cfPLJ+MIXvoA/+IM/iKo7uW9VARoFp7GMO9HqUHXt/ATmUvfE+tPbN5bma/XzfPrPWGrOtGHcaqC9Lm5f6P3lt39oZbnbDPTjFLpdRG/LvvWCvK2EaSfUnj1erj7XX6KQdPrzJ7q9hnovJPtJtUu1kxBtcLeL6OLOR/Y2JOs8SzznXOjcY9PpcXO357D7IPicidvhPh/aMY2+haTE2KtoXHUq/9WhNWvWYObMmbj22muxYsUKzJw5E+vXrwcAnH/++fh//+//4c/+7M9w1FFH4aijjsItt9wianc0nadUzMlRGpwRYdqgG/Xl6R+u2HY9dX2vlaQ8pVLh3gi36evf48hEN7aXDcdWvOg4sg9hqP3sTSbGn6/stNvI6xD9UnOcRjlPXb2+z7nmZZkyWTrRhi9EzIaHKVdJOkdFO02i3di3nTscskVGgXOzNz7ptKN3friEFBJ0h8SbLV68GIsXLybzbr311tLtTl549hucJMCIPKYe2ZcAmL563OtoUEaFeYlPaQWgsiCpOO+ZxIKzbmBSEg7Jd+sDuVsqcTIUdQGnwrPUhTymrj2oEGC9X5bcNkKLm8iwsASsHFSNF0X9mPnV0H2twVNNAlejMzlkWxXqOzzPP/983HjjjfjFL36Bu+++G0cccQRb9tlnn8XRRx+N5z//+fjBD35Q3yCk4PTUKwNObx41NrseB01JHaJP0lnGwpIFcaTjtMqTUIyc//QCMPBel37kWt2Lh6QrY1FAk9xvxnEqApxQxP5b5UgHawMu5D4p2DTtXh3guRAkHWuMWyUSucVBZKrPeSr/dUq8gteo0IxG/fF8fYfn6aefjgsvvFC0qumiiy7CK17xCvz4xz+ubwAx76ekbCw4KdAF65RwmjYMfQ4zBMygY2Vg6isH4gItWGzEApEsSxcl+5I1KVK0ayWkPKFXsjw8+0u4PhK0BBCdceT1rPa1MiKwGv353SEJRsoJUulcfaOu22YlqJKiC1FQZc+7AFQBAVi9HXhU4pSua85yWNV3eJ5wwgmicuvWrcOGDRuwfPny+uDpOWlKhWspcHpdoJVutx3rNEPAJMt6oJrX8bUT5zoTJp3q24GOFIgEYLzcDAEpEn5NPBg80a5W4p/WYq6cZMQwIdKp+nbn9qbtXOtyrXpf0jlXPV3qWn1g5aDqtG9BlRwD0z/lUhPQ70USfWoGevIrsccfqW7rPPuvp59+Gu973/tw4403YsOGDd6yK1euxMqVK/Pt7nO/owvWDU6qfr/AKXWZMQ7T61RlMGVB6YOkk8eMiy7utuepy/YhbY8tH1VcrMIdSsrSV1aliP3pnTgGf2zAwerbghvrXCu6Vr1tsfOMDQnbdcu4Vae4207inNyIIBhRUCU0U0OhWqnjpE+TVoyGEp4XXHABli1bhn333TcIT/txTVN3m+4WqnIScODUlotzdUqBs4zblEJTCkzvPGkAlvo1h4FkLCBdR0o4TdKl9geeZev4pFQihnJalgOnW5ZaHGRC0LzsU2ClAVi0B2htRoSDobfdJFjLQHUYgQo69Js3HwKr3myNsFSo5/F8w6yhhOftt9+Or3/967jkkkvw7LPP4sknn8Thhx+Oe+65J76xwAkRdJ1kmwQ4WbhZ6UT5ym6zbmgy6WJYcqDUwWsPyQCtBVOfc2XKcOVkeWxWqfZixcGQLkv3TcGXatcGrAPKOsBqtJ/+z4FVGYCSg9WILnNgLQPVuoFKANABKgU8DoIK5JfJbGyNzYFmfXvUznkOQD/5yU/y17fddhs+8IEPlFttWxWclOukTtQy4PQ4SKq+N0QrgWZVYFrlKFdJgdJIYgAZgmM4XwZTrqwkzygnKlVBRPjUJ0VeIRWRrtwpTKuMm89vNwFWN8QMq4zrRp151tACphhA1g1Uwmk6QE1QYWFS3igP1d4YY8OyTnPe+sNzn2dT6js8ly1bhhtuuAFbtmzB6173OkybNg33338/zj77bCxatAiLFi2q3okopCJvQzTP2QQ4PeVMsEZCsyowY2HJgDIRAjQWplyaPT5bHSk8aw7RcqKhaKrLhWzhjtN2o7YTteGll8/GkmhA4hyr6y57de39ysojKw+jvF6Jday9Mj7HGnSrTr7dfiRQQ5OHZYAKuA61rEJgzcslvs1Jr0SpmF+TG35N3W06Dnj/xcFyUtfpnedMzPK1gJOCcShEWwWaZYEpgKUElBwkY2BqjwPgQViH8+z06SLSlVzfuBW2Vrr9CxeOWXIcqL1N54Wda8LmORfnwBjpOnY+3z/ZqK+9YN2SZanytkL1QbhTT1lvemwZQptXfAw7nvxNvv2ivZ6HK793eLnGNJ3/qseCv6oyKA1l2LZpxbjOIs1zVpHle33p2xHgZN1mDDQpIFIusyQwOVhSEJRAki0DUzYYJWHctB6ZLIKm1JXWqbHe//6fdqLCs0DXokoHfkB27VYZB5pu669dd2vWM52tUS52bhXg3WqvTtCpWk6adKk+h8o5zkG4UypkjAoOVRH9VlC7YGgyiPsCR6SLw7UYEDg5pxmAZl3AdLcjQKrtig+QNuwoKFJALONGQ3WbVlclGPP0zd2iYrsSu1zXglViQU/v3wAginrhsK6y8qDVM8FktxMdAu7VcaCqh2Lt9izYGX1reTZQncVJXLiXesqCUc9Tlrr42EkU7JT5xSevas0vO+1Q7VdUt10wNFqq4jq5UC+5wIdoTwxOJkyrqHSrPR80qdAsCU0PMG2nSDlHDqRGnjb8DpFvv7YB6QI07D5ZeJKpsrpNy+85QYLTBq4LzgRjhpMs8nWoKqodrY28HGJBKYOv3Q60/Y2ZVzVYZ8FOB6EB1AQOmEl3CljzkxGADL+72qYApp6muB+Y90I1MKTJrkkFTxKczInjhayvnYROqwWcPrdJtO/MaTLQpFymz2Fy7tIL0l56CJQdoo1MXF07T+/PV0aaR/XXDymVeMdFhXMpp2pfOB2XmYPThqreLg1VH1ABOSh98LXLUvm2I0xBWADV61Ct8CrnTs37KfVzUWvDdqZSmNrjcCSAqdVdXo0qmn/nCJz3xOItiRTasO3kksR1Wv+bC4p6aVabpcGZl7UAabVFus1IaBouswQwQ7Ckwrgdq65e3peut0/lUcDh50H9F49BOU5d3JznGJE3BgsURBkDAUzoFlY7JnD1tun6EpealaNcatZPmdW/lEv1OlQH+EU5FqaJ0Jn6YOqoAkzBlI8AHtVFCK4+jQfDfBNbkwaetblOSvq3dT3Nhp3eft3gtLYNN1kCmhQcqwLTB0sWoNpud5gydn0qn00LxKIG4Th1+dxnF25elwzRmgDK6nihCsB0pJoztJyqDSupSwVAQtXnPqnQb1bW51KjHSrnTss4Uy1dSQGpYLyPQQo65T1t+5qL6HKya9LAMyiP63TKeFyn/douE9oWgzPht0m3mYMLYmhSLtMHzDKwpEDJQdIHSMd9UvfJTTD3aYPQzhuz9tEGrQ1Xuz3bKVJQNcCZVjLSbZgCcICa3XJTBqjZthSohltOuHJmvwruOZi9zsoZDt2AoV5e+5IiAKndt59W9nlQAqZA2BmUASZ5irYPSRgJxbhOcX2iHTs6Y4drjdAvke8Fp+NMGbdZAZqcy6SAKXWXHCx9oORcqPHa+sSGnCcHQO886KBXSCT+X6awnSMVwtXTOlZbXW2SWi+XQVUEVA+M2fQIh5r1J51LlS5OYsO9dn0U/5d2pdaXCdN8lnClxpHQKwTEARWhvgJiqraP55vgEp0TnFP0lJW4znRbufmck/Q5Tr2uD5w6vJLiwpCB0145a0OSg6YNO70sBUwOlnqaD5YcKH3zoD4nardj1rPvcqTb7KcyWFGXn+wWACdkaz1ZomvDz3KhmXM1IAkXmHbY1gfUvIdEaU5UWU6UdqhpOybwnPrW8UkMkJkO1azDvY9cGQ2UBhCTPJeEaU2uVDmgs76l203oZVXiXjvsOnb3vvO8BFgV2p8km7zKv1ln21SZ4iXrOrN8C4b5PKeTToDTAKzrSHVwOnObhNu0FwIZkPRAk3KZlMPk3KUElhJQSt0oBcUyDlSSX6d06NF543S6sd0hgWi3r0OVAqoDU72sBdSYcG9Wr0zINy1nAjUGplyolysDA4g67DQ1CFK737DLtM4dCqZZMa4pozvJuT+YL5mD1EjDk/3CVPYLkcR1UtCz2sjB6aTXAM4cjPC6TTtE62z3urChqbtMKiQbAqYElhQcpZCUhGtZgAYuAE0DNHebHDjBLBCy6uiAlUKVAmrInXYNyIVhCqCaO83zei+1OnXB1BQFW20eNADSuuZJoawnPFl5rgu1twmYOoO2uq3BNLZh2wkqcaTBdoMACTZvPapvrY3cddqO1EiPAGcOpCLdCNNqzk93m1SINgRNzmVSYVkfMG34ed0nA0oOkrELh2ig8qHbTL4n/dSh0NJ+6oktVGiMm8tMt5WT5wOqW7YAajaHyrnTqLnTtIKbHulOq8JU4kqzT3wIpAnMcdbhSL0gNXr3iTmPOYca0YSu9j7PSSzqWiZ2nb008npogJDp3ANO8jYUDZx5tgVOLkRrLwSynSYHTcplUg6zg6I9Ow92G9mFmQClFJKu+3TByIFQskiobgcqcZwAMGaFa8dVAv2hEvlcKAg3iaIPvT/OpWZAtetJ3KnTlwVFpdyx6Meh6txpDEypkCQFSquE9loGUqUKZDbmSG2XKZ37zKnuOa/tCxlxrbMT/M9knvgaSXh637Oy7ydTj3SdVN0MpMQJSq6spcBptMmDkwvTUguCMrdpLwSyw7McNKm5ThuEZF5JWEohacNR6kCptkKKcaSUu/T9SktXdZyxk6FaJAZcdbDqbdhA5cK2nWRcDFMnfAsLkEMIUzOUHQdS85YYCmw6EJVTyni0HwFSpQNOFZ9n5cAwEqTOQFDzvOfk0kjCs4yi5kepb12GC1W869TLJwJwGvXoOU4HnIkdjtVAaUETMEO0IWhyLrMKMCVhWxOkNCTdudBmHWiobbpdeSjLBmImCsB6SNdecNTVXo8bcOo45bnVtro7zerm5ZLEbYcI80qdqV5Wb8spA0TDtEsAUK9HhXczyUFqeshsPPbtL2lRF6QiN+oDqdVGmkucz1yY1v0OEC2FNmw72iLB2PtgEnlsyJbK18vprpNykaExZnCMACc3vxlym/ZCIMppctAk0yOB6YMlB0oOrHYdux5Xx8yr9xs3tVLWFnebCnWLih3SpUK5nOscS8ZJh2qEdWG6Sz3Uq48z1pkCHphqZdN94352Te5Ms3eYAqkuqSOlHSefZ9xnmpVX+v2mFcK6NgQJ1+m4Umq/OHdqS/iRaH9VpZUp/SQk8wOuU2tHHK4tAU5qNa0NTmpBUJZuLwSygSqBZllg+mApcaB6ebtckea+e2POr1q6qhumAPFwA+vcyb7B6+ClAGsv/EnbGs/dZicx50VjYGo7UxuMephXhzwH37St3v6Gwrx62SQc5jW/XLj1fCClQrvG++MFqTQv6aUop1SakRQ1sv50+CqzWX3xXSxI8/YAZt/gXswqONJR0uSCZ9k33VfP5yQ519kHcNrQRK+cDU4bmsjyIYOmAUstzwfMMrCUhGp9t6xQYKRAKIGjBLJSjaPj7TMFEnFfp3XSpe3Qt6fooeIshCuBZAim1JwptQApZvERQMOULcvAlHKlZUFKhXXLQ1TP112l60ZDc6NOT7EgzftzR2v+Zmm5L4zjI07ZyQVPRlHznUx6DsimVAGc1GpaCpxciNYGn+00OWj6HKYNzNhwLQdKG2zuvKfccTbhMp0+KDBqJ6TuQvU5JHs+MGsnnRM0y3MhVkAOyXQsRTlJiLcYK+9K89dMiBcAOq5pI11ptn9OvgekhnPP0zQ3a8+jZ+leN0qBsrdlwKpESFfvj3OjvYJBkFJjz+d8ERR9b2zRfBu2nUzKTlYOjvo2QMM1d5r6a6U5zJKu0zdsBpxpHr8wiAIn5zbthUA2UEPQ5FxmyIXGwNIEr995khANLPpp8lm3upN0wrZ5qNUN27qg1JwgA9TQfKUEknaZtC3XlUrmSgGQUMzFuFIpSHU5oV19jFkZow3TjVJtc26UAqUvj4QoND8rgGhaDogCqT486lrDuIsQYFvnOaqSvq8J8zq2HWlZCpwB12lU18M7tpPsZIDzg5Nzm745TT6vKFMWmBQsOVCGIGkDkgNiCKSSNihxz/scs7b1p7MYc5054MxyOiizfB2oukPNYGo7U8oZSiCpz6tmWKGca7E/OiC7eS0RSFHATQpS37Nxszp6ed1d5lEWBqLkquA6IaqFWo09YEK6jhvVK2bfF2yQOo1bw+xDBGYiavLCs6w4V6q7S4+ibk3p9RcXrjXnOGPnN223SYVopdDUoVgWmD5Ycq4zBEgKjHVAVCIbkrZyGFqrcnNoWmVtsOpQ5Z2nIp0pNW+qu1Jq8ZEPpFyZNK+5RUc+kPrCujZEqblRDqJ629XnRd04tXHfpiSkC2tu1HajvQqJNUYWpraCPE3asO3IqE8RBDZkqwOTE+U6jfzwPGdeVC+rpemgM1wpA04uRGukRUIzFpgh56kDTodgGYjq4+Fk/45mWVFhLb1v/eKTQZNypDpYdfjqLlV3qK7zLGBaXPhpV2o6SRNJtNssoh12CNjnMPXwLoh5Ukr5aFz2OGWKUWt5dkjX2UMeosWj/Xgnqpeh3aZyXGfx+Y2EKOxyxX46jlSrZMM0a9uRAK7D8mzbVatW4ZOf/CTuu+8+fOpTn8J5552X5/3d3/0dPv/5z2NsbAzj4+N417vehfPPP1/U7uSBZ6z0k806UWoLYsS6Tq1eaIFQ5iaBDJrmtp4fAqfEbZaFZgiYlLuUwNILUephCcy7GvOkoVj5fm4MMB/Hl4E2G48NVhKaXHpSOFM7zFsGpFTYNjucEtimfWjlnYu19h4IQrsGIClQkKPR0nvtKa19B4x5XX84t6tBjQvnmpA089LXIMEagmi2D3o5AGGQ5hV7WaSD9kuBn6LotxYuXIi1a9fi0ksvdfIWL16MZcuWAQC2bt2KI444Aq9+9atx5JFHBttt4VlWursUl7VCtkQZx3VS4Vq9mgecdrjWN7+ZQ4sBpw+a6XbXgSYN0wKSIWBS7jJrRwRQ+4EJ9qKPCIhy5esQB0xAg6ZV3garDlXdperu1E7PwrycK6VAqod3fSAtO0cKwAGjdI40ExmuJWEOs4zZDBvO1cuGIGrMn6J3t4gDo8JV+iAamhM1bnMBvCFdblUtC1NzCBNK8+fPBwB0Ou7X1d133z1//cwzz2DHjh1IJEuN0cLT+SUVFoa+49mDIhuyZeshBybVHgVK+kEIYXDaC2d0cAIFgELg1MtngByz0tL27fR4aEqAycFSh2AIolSZomxzzjPvQ+vbfqSZ/mzZovy4EfLVQaLndZJukQ4tjJZ9qYEJUr1HDqQAANUbb2IhxIKZz5GKymjlaNH9ekqmjjCPUdJlghC1nKi5Deg/6A2rTd3VFm7SDc3aebEQBWDW1cbCgTStY+67cztKhJkclrBtSNdddx0uvvhi3H///bjsssswb948Ub1JD0+v7BOljiiEBWsjXQNilmb/UgrAz3MCPDht16nX07dD4LSdJeU2Y6BZBZgSWIbcpvThCbaqQpV77qe9ajbvL+ma93mCB2oIprEgdWFZjNVebGQv+ClO3HDIlsRXyAnp9fSLNVO+Voha5RwXakGw6nxo8dp0qTEQ1Xc3P8sZkKZ14ch3f6cuaqV0rLZt24aZM2fm28uXL8fy5cuNMscffzzuu+8+sv769esxa9Ysbx+nn346Tj/9dGzcuBFvfvObcfLJJ+OQQw4Jjq2FZ6RKRS30kK2TR6QHXKeeRj3oXXofJw1EPzipcCwVuqUWAZWBpgSYcscZuI3FA8T6V91qbpP4hm7fvwm4YM3GlC/8AQ1NEyrFceRAChusiTlHqi82ytUvNyqBKNEvVzKDKPXYQdtd6nOYCvXNh1IulIckv6ioLEQBBqRaXV1kVNN2rEhqeTD8tGnTsHnzZm+ZdevWVe4HAObOnYvf+73fw9e+9rUWnnWI/PIk+UKVQdEHzMRMs1fYur/PaQKzKOd3lL55zmyOc0qngNmU3jwZB07ObXILgULQlAKTAiPvOOnbWOw8vR9dHaGzjP2BbPonycy+utpFJxvruOEye21ZIdY0r+vANH9oPGxXSIM0nw8FAdaAG83Sm3KjdBlKspCus0K3ogsNhXJ1QHK3tvggyYVyRRAFyHlRe7eNM9p3ftfgLAet++67D4ceeigA4LHHHsO3vvUtnHbaaaK6LTwpieBozms6853Sdh2IZi5TS+q5Tn3bhigVrs3T4QenvQgICIMz5DabgKYfojQsQ6CkIOkDYtVwLfe4PbOP4hdSMnWSrgFVAMZVzrj1hIGp7SgpkBZt027UXmhUx9wouRTHgVmxICp/fzngGW5xMBCNvbXFt6DI50LtfMADUSDoRold56NtgS+OdYRt69CaNWvwwQ9+EE8++SRuuOEGXHbZZbjpppuwYMECfPazn8V3v/tdTJ06FUopvP/978cf/MEfiNpt4dkHeUO2gW3KdebZiRmuBeCEa4t02e0ovlDtmLUNwACn7TYp9xmCJgdMKo28jUVLC4HShqQPjE2stNXHQ91QbodHxzDuB6q+O7ojzCGW9UtAU+hGqbJSNxqGqJYXgKi/jKkMovl9pkSI1nGLNYZyQy6Uuq3FDuVyLhRGuSJfT09fm3kcRNMy1rwnfViDU1jOl70BafHixVi8eDGZ9/d///el223hKVHZL1BU2DYDKRWy1erpz6blXGcm3XXq27rrzNLrAqe9KCjkNnVQkq8DLtMGJucui7Z5ULpznzQYJQ9DiJkL9a0+1EOrxtjQRdcTstWBqsN0DN28v9wVGvduZu0XoV0urJsrANyyEJWEdGlASsoQ5RtwoVUBqrdXdi5Uz09fE/OcAYgCtPOlNBy+cnBq4dmUpGcWFbKlsgKu0w7XZvX1cK2uquC05zcpcHJuU+I0Q9AMAZODpfTeTh8UpfOhTj2tTe5buTHPmI9l3IEqF7I13Ck1kZU98IAAaRiO0nJxELWdoTl2GpBp6Fj17intFveaWq6RlgvRqi40b7nBMG6MC01f06HcLC+rnyaY86K67GuH3o5P1Pz+KKmFp1TC8yCfBw3Vzxyovp29TIjt/DXtOu3tjlHfDddmZesEpx2mlbhNHzR9YdmywLRBGbtYqK5Vt7ozdPon5jdtqDpAJUK2FEiNfhMbcllbg4GoMa8JlQNSzwuHc13IciFaA9geFzqsYVygAKTEhQICiAJekOZF2C8mxXiHZc6zKbXwjJD3dKFCtHoet524Idv8ZVKEbJ0ftfa4TnuRUJZGPa82Uww4qYVBVJjWdpux0OSACRSAG7PK6G3q7dr19Ta4fKqNOsWFatM+Xbi6c5zuLShpulbJBiQA44pMlRkSiGbt1AFRXyg3OBeatai11S+AAvIwLrR893XvcBDlqPwiw0qIAOKoPxi+73t3/vnnY+7cuUiSBD/96U/JMt/+9rfxe7/3ezjssMNwxBFH4KKLLoKS3pnbtGy3mPjPJ2WffJ6yvpBt8bpI51ynvd2x0qhwrS7fHKfejg3O/LUGyxA4x6Awlo+j67Q5hq7WTvE3lqj0D1mdrtaGKv4Sun5Hazf/0+tpf3a9uv+mYpzs93nJuDNGdvz6eI1jkR1Dlf859UEfd/t4stva+2y/78a207457+6m98aAItqRz7Un5hcsab7+ZbL4PBT9cGX0z2HxuSj+Eq6O9nkx2nC2YWzbn2O9Lfs2tfT/4trg3MbGXD/sPL0d9gl12Rd6+28Squ/O8/TTT8eFF16IV77ylWyZPfbYA1dffTX2339/PPvss3jd616Hq6++Gm9/+9v7N1DfF6wAMNk2fCClQriaK9VPdG6Frd6UA0xYYPWEazlRi4N0xwkQLrP3WneY9GvTzWZtpW2YLtMsbzpXvZ5e104nH9FHhGvrfjgCK/awW99vWYept0U4Up8bbdCJjhsh2N52z3mNoWs+Q5dN77KhXPvWFelcKBfGpRYTSeZBgcLN1e1AodeF6UDhvOYWCvldqF42P004NypU+2PYNeuEE04IllmwYEH+euedd8ZRRx2FBx54oMlh1a/QeUPC0vONj2vG+pZJzXVm0kGpKyZcKwnVUouCbLeZvQasW1k0cEpCs2NaP3meAJhSUMaEbI0FQbEhKw7STveSUK1enwBcEJKhfBei2cPp05W7BTSbD+Vq86SJEoVxpfOg3G+PUgBNx9BcCFcfhxSgbrobqtXBGIJo/taIPhJJO+c5aG3ZsgXXXXcdvv71r1drSCEItNrea+8cJ8AtBjKq6C4zKcrat6NkZfTQDjfXmYn6lZS0bBw4i3px4JS6TRua1FwmvXAoDEwblDEPizfrMfOkVt3Qo8qM2zV0Oa7OrkWUo0Dqc6MlIJreA6qKX3QpMR86brjG8i7U5zKpfGoeVLKQaFQACvgXDHEQLfLJZEejPuc51PDcunUrTjnlFFx44YU4+uijyTIrV67EypUr8+3uc7/r1/BoJe5FWFKWmu+05yfsfKCYK0lfx7lOcbhWmxfVy+mrasuAM8Ztck6zY0FXL6Pn+8ro7euSPE1I4kzHkQTbSgFBlLEvQBwkCZCm7s8E4rgFvRSCKaBy0CBdmJQ5SBtgY+iWcqFG6FZzpTlES7hQLowbAqieD7jusowD1cs0CdD8bUY5gNLbrqMMQXSya2jh+dRTT+Gkk07CokWLnKfo67Kfsj91t+l9GB0t8hxjJ9651+7FmFogoL/WXWi2nb8GdY+nfJFQByYss/YpcOblIsFJzW1WgabIhQphKQ3bUu0VPwcmacOtbwM1c3u5CJB2oZXxQNSFXtam3IVm44txoTZAq86F6mFcAFEONMvn7vPMyqbt+p9IRJXhABor7jaW7O2pE6AAD9E0Tzb+NKA+2tAdSnhu27YNJ510Et7whjdgxYoV0fUTVS4EW7ZeWtlNEq20NWDoplPu04al3rztLPXXmcu0t/0gpec5dXDm9bTFQSFwSt1mGWhKgOk887Zk2Jarm46DeLgBJzLEZfVvhBALSI73AJS2o1cwIVYWopwLpeZCTUerHBcqCeOWXUykz3PGABTg4ZgeRf9CI18Zn2OUuk+jLgFQO899LQeoXd5W6P5OXaP+kIS+B6WXLVuGmTNnYvPmzXjd616HAw88EABw9tln48YbbwQAfPrTn8add96Jf/3Xf8VRRx2Fo446Cn/1V3/V76HWK/2kC5xT1HJ1ap7BvrdTr89BlNoGYLjOWBlhW33hTklwdiwAc+C0byXJbokw8pKivaz9vH8Ut3dk43XL07ev2HXZYyOsH+pbHzt3a052bPTj1YF2G0tCuXzT2dvz0dytLWlZ+suOfVuL0W7ev/3emre0mO0qpj+zbf12FemtLHqe3U9Hbwfu5yxTYvVBlbHbTqx06S0sVJvGd27m88tNAXF1vLerUO3Li46MEjU0N1DWo6m7TccB778YAOEiiVBpXqZ3Aqmkl6fn9/4UtNfZwp/sdcdMS7dV0Zb+uqPytKT3OulYP3CdKHS0tPS1dltJp5vDc6yTXnASAFM6XaOcfn/dlPyCq2+7K2yndsbFrpOb53TdpxuqDYVpgxd6IjxLP1BePtdJPqpPGLqNFedK7XR74YWery9EysoZ+XlY08xz0q26RVtZfsKU7+QOKCurj8MeU75thVv17fy1024SSNfbsNLy8Wf9JWxeVyVOX3rbbl76v1KJ0YadZ6dnZxVXRneEmQNVTFmgCBro9czXMGQ7Ti4kKyHEg+d+Atuf+H/59q4zdsXpXzsjXDGgb516S/D3PAeloQzbjrQCbpKsQjhRSk6YForMI7e1uc4yGhQ47XSzHUn4Vg7LMq6cUnbBo/pJFxcpY5ub99QXIhnzoxqwivnFrA0uTAujLhL5YiIkHSukWoRtyy4kKhPC1SVbJCRfQKTLm8eEbylJw7c+lQ3f2nnUdpGe/h9rs9pbVUZJCkMZX8ihSICVDuG6UNR3i5rr5Lfdpwdl6VLXac9zGm3DdICx4KwLmj5g0vOdzDxmRRc6rt3WYCsFgglODqQhiBqLi6w5z2xRkQ1XE4rKAGwVgOoLiSQABRC9iAjQYMjMcery5ZFzmom7+tYu74NdU4uHjDxo34U8IPRB0L8P6f8SiCqM/oKhkb4RpyajIOioTJ3qg6PnKvh27Xke39xnWdnznGmaysGp92OPqyw4i/k1dz6TmkPUXxdtmI9bs8tQ85vZY+N8f7Z8bfr6t8fP71eXzNePWweBdOL46nOgVNls/PYY9HbsNs2+teNgj8tp1zen6LbnlCmZR/dH5HnmPm3Fzn1SCvXjuybEXkPSfG/2pNFIw3NCiDoR8w+Om9UhPkzch8d+MIJPvpCtxHVS0sO1xTjMhx/4QrVZup4WXOBiAcZO44Cp5zlQE4KRPHYCsPpAapeh9tGBJLoswMoC1DjGBEB9i4iKfWLeO+NLFbOgyAMwH1SpBUKSPLq/MJi9C3s8wC0jbsV9uF4dfYfaSfK54yp/w6yRD9smirn9pBfCZfMnoDoMLH1hW8pp2iFbifS5zlC4NkvT61IXbwqcHDSzdsw81/HYx4MM2TJgpMLbZZT/eLXVT5cM0xbbelhXD+nat4cU+XQI1QnVCkO4vjlQAE5oVQ+p6uFbfSy6qPlPO/THhW+NdpjwbZrnzm8W9SLnN315MOc+KeXhXhBPYdTEPTghJN+j+bhyvjS6Lp836k8YGu29q6ImQr4lIZ3Pf5J5/jAT9zrdLrc4SKoMwLrscK3p8MqBk3Obbp7rMou+CUeYKOPP2A8i/BoK81LtGseLcaT68dTz7NfUvG5dDtRsw3SgejnKBXKO08jzuDoufGuU8bhPuy+z7biwa9nPjORLaBWHWpebrVOj7jxbeA6JqJ8T4svK5mV8ip3vDC0UohYMFe26rtO40DOvRRdwb/gyDB4fMPXyEiiS+x6AKtWfD6L2FwB7n+oEqL0fdvvFeN33qajnhm8lbfpgmvcbCUpfvTq+SA4jwKoo5oEIk1GTD57t+UDKd/GQPONVb4cL91LuLa9HLBBK6xRpPnBm2zY4ObepAyoETGP/Sv45x8ID0qIvF6J5HrFPdQDU3Ff5/Ke5b545SAEwKfnyvBD1wZcK2Qu/mPralSzQaXLecxik0LsntuLfMGtSwFN0fg15iIBS6INOhc5i26/yIefCa7br5BYIURdtp5x3RacMmno9N5zrh6BUvnYkELX3Td8/u600r5yTEkG1pPv09We2xTvgsqHbuuarufGQeQP6pj4sV7I2bNsqrNjPyIDPCXeBEO8eqsqGY9G+csoV4+Mv2KFxUeAs2jUBpdfhHCbZRxL3R0kKUXLsjAO186lVuGS6B5TFWHhY+dynLuqLjp1HqU4Ixc57mnWH0+XZqmuU7a+p+DXyq21LSaFZwDXdfkXFXCSk83/kBVbgjshQIQuHcuDURYZYK75Xev1x6zBYP7KVjylbiWqsFEWxQlQvU6xudVewOmPRVsDyZczVt1QeJX3lbZ7mWW1K9k306csr+7CBYdFEH79Po7pfmSY3PIccYsMo6v5O6sEIZF3PvFqar7yra7Myelpd4HRcYOC8kIRsqKPBgbSDagC162X/c7eGcLev0PtKQdG8dcXcRwq6bjnq6T5l5btlZZhVFTBNuUPxT495vju38JyIIqCYKG1a0wNNo1wfxjVqCoVVYxeKSNtl+yPAGXKbFDjLXIL1OhxIqwI0r1uTg6FAWYyXB2wVUV8CqH1s1YzKAFjyiL5Rh+dwfy3rkybIVMaEEXV/p65QqJe6NcVsX+Y6OcdptGX064Kz6kKhUDtUf5zoucX6Q+yhsuJQvXCxUVOSuk7p707GwqCf8KfGJv11FV89Ny/+AfGjqtF0nkD9Lq9h16hU9tDmRLz8vKuSxlYR9luSC7KvjG+eVhKqLeM2x5j0cU8dco7T40C5OUafM+NCt0W++eShOqQ740FICjbp/krBF4IWl9eUK4u9GsS4zhhoZreqjLJGF56AA7zSIVkJOIckJJs9Lsx93UEnSS/rXSR9WUZf9r49UduW67TTuYeyZyoLTg6YXBkfSI06ibuYaBRVN7zqlhjCDY6P+11P+zc9Y9tLX8vLmulRXQIT4FaTqhpteMZKJd4YbgLtJKoK06yvEtBVxDh1UMaq23tupr7NLZgZVx0g6YogMt772akyolbZlmqnxDGhH2pQsn/QALXnN335klW0wGBXblKuM7SqtygnGzM130rtL5VGja+Ku4wt58tTgjJkPY+LlQBW8mPYVUK0ow7Pds7TJ8WzlEpvKoKancBU802ttgtd+MZVh3URTX5oqt78D/hdZ53grKv+sEkKu5DqdqHUOUvVpYErBbOsXNW8MgpdH3QQNg3OyaDRd56cs8vSGwy3JiqBsokacLd6mWweVKpsDpQP3dqv9bodjCXjTnshNzuOBOi50fT/Yk7N5xiruNJRkbO6tmLoVnoxziDjgxcFSOlKW6qc2IUG+sj2UW9PDjliXEJHKnW4uRsk2pDMd0pDtpJ5ValiwUmWJ8qNuvMcfXiWlWiekwAhB0ci3VkkJABrAUj/vYj2z1vRbZnAHCdg6QvhNqlxwfjrVhOuM0Z1zXlm4Mv+z6AhcYzcbSp8XzLYUeMzy1Fgiw+MVQnZSgEprSvJKxuytdsu6zpjwBm1uAijD8/JEbbVToaYMGxs26XyuWoR3zRDJ6meb5e1LyzUhWEcndo+CF3VoV2N58JuuozROWV9vlvPI2FTc7jEByoKqKSz08qRIVTSkcr2TR9f4ZwTJy3UTj9Ctt38Swvfv+TzVJfr9IVrfWX1OuXuBU0q/9WhVatWYd68eZgyZQouv/xyssz//M//4PnPfz4+8IEPiNsdnSvRAOWAlwOm8uR75jU50R8U+lulfiGxP7j2RYYD1LjqVLpocy6liRvvJ4vGPRdqn3xuNHeuOrB85XWICUO2IaeZvfadt3yav79uvn9u21R/XeJzJF2kY4dfjfJMmdgFSj7X6XOctjO1wVknwAaphQsXYu3atXj7299O5o+Pj+Pcc8/FH/3RH0W124ZtCTX6lCFbglBtFta1/weKMK7eAjdX6btdhVpxi6SDDrFWNFtxC9XJF/BQc6ZFWQCqS6587aLjPJBcMh8aG9aVlO/C/TY5juqhW2q1rb13esiWc53jxAXe7csfsqVAVoDK7ybztLzNTqCcP8JgjzFtp7zrpCBHAZLal9C4feWkcJW4TulcJwVOiTOlxLnNmPKUhuU+z/nz5wMAOh36S/pll12GN77xjdi2bRu2bdsmbndyf+Wvc0pN6j4F+WXDM1R41v5pH18It6s6bhhX+e/X0sOw40h622mYV7Ji12nPqtM1Lpxx4V52zMYYwuWl92qWrSsagwdEZRcKSV2nnRceFwU7f+i9CdeZf9lo0HX6nGUZ11lW1DVDMs8pdZuZM41Zgcv9zFjM37Zt2zBz5sz8b+XKlfIBCPSTn/wEt9xyC97//vdH1508zlNbAOR1lpwTrPKgBD3deJ0Y93r6Vtfmi4u0tGzRkH7fp/7UIX3RkO/hCYD549WpKzU1jk7PPQaOQUBpO+jdK6qsPNMd6tv66t2u5njzMff2KauTOetx7XiUdZ9p3VRSF8pBM7S+WDrX6QWfYKGQDUmf6xwnwEe5zvHeF6e0XELUkbvOLgHxkOvsktAl6nigSn8BdVf21jnXGbvC1nadMfOcIXD62hmEpk2bhs2bN3vLHH/88bjvvvvIvPXr12PWrFlk3vbt2/Gud70LX/rSlzA2Fh9fGk14xt5+EiifwzZfHZtl1DwOo27C3q6iAzIDJ5VmS4eiHdp1w7i9Gyms0K0ess3/B4CEXqdZwBLe0C2U+dQhPXSrw9IEavEIOh8UdYAWfRaQHLdWLnMATfssZH/cQi7TF6q186Xh2uLWDT84fben5PATznWO57BMnHLG/hkOlAKRC2fSgTIRFTvN6NsDN73vcNsukO3yytMGledbYVsmXGvXjQVnNDSFLrlf86Xr1q0rVe/hhx/Gz3/+c5x88skAgN/85jdQSuHJJ5/EVVddFaw/mvAEqoFL2A7lYO006b2evttVqLlObqiZMjgqlaQwYB7TB4V8rjP9YNL3ewLhn+nqWvd7QnW994lm94ga0EQ6hmwetA73afeZu3H4AQr45zWk4VzKbVYBpx2ujQUnCUmPE6XAV4yLdoa+cK25f4RbJMKn1H2d1CpsDpB1hmv1qQzqvk7fAqCqi4Rs2XCtCk4WmiXGV9cK/aY0e/ZsPP744/n2Rz7yEWzbtg1/+7d/K6o/ueY8AyEI8apZowxxgnAnjZ6ef7MkisGT5/lGW+Z1um2eBuPaxcZIz+Yye6tuY1fJdpHOqabtdIg8exz0PBkV/uOAQl00x40Ltd4fNeZwqJUTV3eYwGnAz0rrd7hWX81ddZFQ3eFaO89II9qwodhkuFa66t6eswyttoVKir9IKVS/TaUu57pmzRrMnDkT1157LVasWIGZM2di/fr1ldsdXecJ1Oc+q/YTzE+c59z6VtjqH54uVNS8J5Lek216J2bmDMd7eaYTLUK3nIvs9twjADec23OfaX33YfC6U63iPrnwrXT+03aggOuyKQh2PHm2ODCb+5yVpV1YU+Ac174I2eDMFoHp7aVfrijAuo5QH5szTg6WgZCqDc6u0U7IWZYL1+puU4cd5Uq5dqlwbZ3g9N0bHuU2PdCaiLeuLF68GIsXLw6W+8hHPhLV7mjDUyIGbLG3qzjlYxcPZUnEHGfxJKIiTwdkJnveMwvXxoRus3zAhWUK3xSkQEf8gPhM4xZQ9cf3FXkFZPW50CzEm8IyHd8YlAPQbJzO2AUABVyIAny4ug5oZuMoyhNOigxjDg849Ydo6P2G5jltcOrRDL09P5iIULLS6njcaBcuEKmFRz7Y2XW5PC5cq7/uNzil0CwFTEW77VHS6MOzJjiW6osDJTUmIz8pBsjNjWqvMzhm93vyK2vN1wCcVbepMy1cK5iFQ5mMBUSA133az7rlVt4Wv9yi8m3f4iE6rZj/BOA4UPSOl56f7nMqPWBnA9A39+u77SQWmnoZM2Q58cBptEe5zIh5ThucKXQJUE/Aec5hAacEmKFZrUGv1G1aow9PqSh4VW2H2s7TXUDaodkEuutMG3FCuFZ9LnTbUchX5Wah26ycDsw8Da77zD/slvtEDjtXXSJ8m23rzrl4wDzQQbeAci98qwM1azN9AH2ipVl46jVvLyICQLpQwIUoQDw4QXhqcM40BpoA7zbTPDk4uVW15tylDb1mwGm4TKHjlIKTWiBEuVEqFKuHgCXgJPO0/0Pg1F1nU+CsA5plrobD8pCEpjT54FlyHjSbkgS021WYdsT3kfbaMEK1ZChXh2Vxv2cGSP0h8VzoNstznCb034EkgClwn5lyR2EAlf7YdXv3jWZA7Wih2QyggDn/KQEoNQequ9ACjq4LLfozf8Ksjt9+se+19D1TuGm3SaYPEJz5MRhScGaKBae9X6EFQmQZK702cAqgKQamwKWOoiYHPCOASYLPM3+ZAFDQgJjnFWnk7SpOW0V559dWtLT0dXzoNgVN8WPJjqNM7HAtUMZ9xi4eShcqFQBN08z5z7oBCoB0oZn0cG6eFvndm3owQb6/2bG0gSqAZppfHZxUmNZso3jalG9Vrb5yOgTOsnOc/QJncXxdEJYBp9JfB8Cpry4NgZMKxYZvVYGW4X4h0MWe6ZGQnIiLi2I0OeBZRSWdqlPXfg3kgKDLJDnJFRQBU1notgMYeZkT1R2lOQ8adp8pNBF0opl0R2mHbwuHac5/xgI0GykHUP24+yAKwAFpvg8lFLpZnwrP2ukht0nmCcO0dvv2AxDKgFOyqnbYwMk5zn6BM5PEcYLJo6GqVzDbMODqtE7XiVG7YGiEFVo0FLWoKHOhdnkOjkAYkHpVRd+yooduOz0HnLks/X8AnsVCvV56sOokrvtM84pVuply4Hrcp/4wg+wxf9T8ZxmApgfCXIWbpeVjAIIQpWQ70rKi75ktD830df/cZpZHhWmzdkiIWqFZEqKKuvVEdjtK1VW1drvDPsdJh2J9eSjEuE0Smsw573/qkCdvRNUJF6lX559/PubOnYskSfDTn/6ULXfVVVfhoIMOwgEHHIBzzjkHO3bsaG5Qdb7ximgvtn3l/zAoRX+AAPObsr3dRfravKi4v9WZXvgS46Kjt5ddSPXX+oMT8v97LkT/324nu6hnF8TMzdgXfWMVKIi0vL/sL7HSEyMEOg7zAdR6eg4AJOQfJ195vW27bzvPP/ZOfoz0vHFVHMsu6PTseGbjyd/r7JgxbtM3v2mDMx+X5TCHDZzZOPsNzq6qB5x6mNcLTpXkMNTr6H0Z5Rx3WvzFSq9b9m+Y1Xd4nn766bj99tsxZ84ctsyDDz6IFStW4Pbbb8f999+PLVu2iJ41KBb3ptT4ZtlTnIl+UhqvtX45l8N9a9Q+sNkHM5P+Yc627UUMeqhL3/bDtPjFlLIAtR/jFgNQY2ELlaY5pfR//WJLQ9TYfwKkerm0Xz9UubpcH+5Y6oWmfZzsLxvpMU6Istb7ZPWfnxs2RHvvP7WidlyZ5419XOwHvdvgzNMqglOvGwKn/b5VAaeeVwWcyMvaeRY4rTazfhxw6ps+eCnmjyqmhuMJQ02p72HbE044IVjmuuuuw5vf/Ga85CUvAQC8+93vxsc//nGce+655TuOnbtUCX27Si9Jf0B8AoZ7dhvcvKdeVgEKxXNuVaLS9lVaOAvdohfmBdIPXwcwFg5lc515iDbbRnrbiv3QhDzciWz1rR6uzVoowreAufp2HMXr9KlGWeiXX0A0hm46PiuEm5YvQrjp8emYxy4PBXfctLzPbI+09bJWOJcU9yVKeP5wcz3OilsdyJorl85pAnR41kj3hGjTfHolrb4fMYuC0r71Lz3l3WbWVpX5zbw80S4XylXWl0onj4EeVYab36wKzqDbBJEPTQQwSVUwFMMOv6oayjnPhx56yHCmc+fOxUMPPTTAEQHsnGaenxSFrHpGGjfvifQEpm5Z8a26BWAsHMoe1wf0oEqulDVX3mZAtJ86ZAIz3eYeGq/f7jKWpHOSY0k3CNB04NYcqJ2m183Hq6WjN1Y7zYFoundGntEGL+N4CUTNpdppFDDT1x02v05o2uUpaJp16bnNrD61KCjPc9pMyLSszSphWrv9foFTujBIL2dMSyo3FEvVo9xmUdgFp8M/CrhGPpGmtdcq1VDCEwCSRH+D+a8/K1euNH4gtfvc7xodV0j5/aA2MJ20AprOKtsehJUCEiTkoqKson7Pp9R9AsjLZNIXFuVjJYBZPAO3cJ+mWzRvXwkBNF/oY93GYtwHmh8jxoVm7eouFHAharwHhBvNy1S/s5OCZ9fqhwKmXs7IbxCaWb4PmvZ2rNu0+6DT7LZoOFJONMvjoFhmRa2TR4DTF6ZNt2FsG64Ubl76P51O56EQVR5uvlPPKWj2UVYxXzYnooYSnrNnz8bGjRvz7V/84heYPXs2WXb58uVYvnx5vj11t+lRq2SpsuLn1PpEOFXnfk8njJsYcONW3WbQLLbD7lP/H72usqcOAXqIVQNHD6D6Q+O58K0PoGk6fQ/ouBpL76FMkMNyXPUe5Zel5e2CaKs4fuPI7h81IVqkI6/Xhf5IP5iPDrRhiizMHYaqDchMbsjWhaVdzgajnt9vaFJOM21PBs1sm05zoZn1RblNLi8UpnXzLNAR8FVEm775zX6FaZuCJgvMEuHbYV/wU1VDCc/TTjsNr3zlK/EXf/EXmDFjBj7/+c/jjDPOaLZTBpCVn4GrO8ysH8ADTTN0q4DiFhYg6D6dpwtlO4HCndpPHSp2FqBvR3HDt1EABQy3mZahYAoXlvluelyodTwzWI5jrHi4gRPm1erq9UHANEtXY8GHJXC3vuiwBMLABHiXaeQ1FJ61t33QtLf5cGz83KYkr99ukytTR5g2ym0aZczxufkwRYSFHVWBn6ruXIddfYfnsmXLcMMNN2DLli143eteh2nTpuH+++/H2WefjUWLFmHRokXYf//98dGPfhTHHXccut0uXvOa1+Css86K6if4pCDOTUpdpoKxaMhbhyujg5UJ3Wbb2cIhwO8+iwuCAnXfJ4DefaFJ7j4NTCQUUAFq/lMKUCN0a0MTgG8elHOhRToPUaMPO6Rr5Gn19f0mlH2tIB9y75E3ZOsBpp4vBWZaRrYQyKzvQjPblkAza5uCZtafL0SbpffbbdplqoZp+7koiHSbHDQlLpMD5oiDsIwS5ZtQnICautt0HHj+xQCY9ztxX+fltP+LNJW+Tqzyvb98fjOrk/TmKztuWpqujLaQqPS6rpVJOirfThKVGq4ePNNtlf7fy+/k22mZTqLQ6XTRyfJ7eWO919l29roDhbFO19juJNp2npamj7HbaZ0xFHWz10DqBjtQxv9AGg4d69XPnF36unj2bvY6rZu97rWLbh5SzernbWv1MuV9WAC0f2809pF8nJyQrQVSCTD1tDKh2bR8s9DM2qagmW37oJmX8eRldX1uM1RmIq6mrew2fU6TOs2FsMz6+OX7L8WOX/+/PH3qi3bHAVf+qagNn7ad/wVs3ry5cjtNaCjDtkOrmLnP3kmVAO68p56Zl03M0G1gO7OAhftNsg56ZZLcfWbhW2UtHspRkcC8DzUBuPnPWAfaxVgKymwU2nxnV6V5afvp/Ge3B1GoTjEvqbppO73VWOM9N0s50WxuMguxZmW7Sv9x7SKsC2i/pKKVycoBLlSlsiGZHg95uFZP7ycw9XbKhmft9H5Cs+iTcYeBuc3sf9/cprndB2gCjtsMQtPnNJ0wLn1hq2KtRsqVEWrhKVUMOJ26PdKE6hPzoQoJkmz1ba+tBDAgmRW27/sEwC4eAvyrb+sEaFrXnAfNwamHcYF8O1+gY4VyKYimjya05kSztoC8/Ry6ehm9HGDOk2bHsFffdqqcdPjp4mCp19HTbaBl+5CW6z80fQuBuHQJNO183+0nRbs8NO0yvrnNLL9fbrPULShWOb3taKcpgKb/MXzyi2A75zmBVWWxT+xzbY35SurhClk5wIRoBlY9XRW3peTFeu7TfmiCDs38ZM3mOQHn1hV9sRBQfNC5+c/KAAVALiQCvC40rdeBsyK3154O0WxcGUTHMZY+K9dyowAcR5oeAxOOxupcTZlTzZT/WHfgW1HQgdYMzCyNuuVFunKW3B4CaJr/+xcEARPcbRpg5N1mNDStCxv/gITRhl9VjTQ8pcpBybhLdvERkK90za7tusnMz0mrLhm6hVY5S+9t508cyoqpYuUtoH+bLXbAvnVFD992tW7t8G0dAB1HgjEk6KheCNYTxh1HemHLXGhXjaGjemDTwJmWzn7Q2g3nZqC03agNUgA5TMeVGbalgJruFe04Q78nYztQG6L8E4ZMWOptxTpMKo16sAG7HQFMvW0JNENApYDoc5r6/7HQBCBeEKRvV7lvs2qIloKm1GXSD0fwwLJMDHbE47aTD55Vwq89xTrapBd+zanqjInIy9xnNtepsqGbK28B3YUC9i+u6OHbbPWtng/UC9Cu6jlCwoWOK22VqrFNh3LHNYimgzbDuRlEs3akIAVAwjRNN4EKuCtpuTlQymEWbZhvPAXLtA05MM20+uYy9T7qgKZv9azRRs1O086X3H6StTHoBUG1QTPkMqkLmQR6gTLKHtMIavLBUxcHUl8Ytip8c2PZc5+JnUeBFMbcJ+C6TzCLh3SA6ttZ+LZ2gIJIU50UYJYLTdtIt3PoZuBED1IBiFIh3bxd7Xg786MAC1Noe0k9GCEDrETuLSq2G+VhqZefaMA0yg0Ymlm+BJpuHRh5/YKm3nbt0IwB5oi7xyqa3PCsW3m4Vv8Xftjm7CMgDct9Asbcp2/xkL36FgCy3/y05z/rAGhXjaGbZGHabPxaGDdRrAst5i+LUO6YBVE9nOuCUw/v0m4UgOFIkbeL3r5rq2+1Y6aDjHpwAiXunk8KlHY/5pOHEiKtGjCptGGEZpnwrDefCK8ORYhWh6XtNo287AWc8hw0gy6TDN0SaVz9gEbrJkhXIw/PWhcNUa5ToXB8XD8WVPP2QTyur5fjc59Z+Ja6dcW0f+lcKRW+rQOgXZUY94LajrOrEnRUYoRxUwimkDXnP2FsZ050zArnZq/HdZBmF87eASy2zYVAGUzR2+cMHhxQM+lONUbUqlvKVQK0s0zTaThSaXU5TDqvfy5TUq7sQw7INjzQHMhioIpOk3WZUlhKL5jE+IzsshfeCaKRh2ddskGas6Lq+ZGddFQ7tvu0Fg8pIHefevhWB6jqOdq6AVqsjpW5UDvNqO9xohlE9YVFhhu1Qard+mI7VON5tlR/gAHUTJSTtOc9ffOdVBtSWFJpBkBLAlNP67fDpPoeNmiS5Yi8WhcDeZxmCJpel+nkecraquIeW3hOMvkcpKQMF7qF5T5JWLql89eWQ83cpx6+tW9vAbQPXY0AzRwnFcbtInFcaBG2TdOK+U/TieoQ7aoE3STpOcRiYZEDTntbddDVnlxkrNa1VtjmzrQX5k3TC6Bm0m/tyRSCZXacnHoEKNN0F5Z6uu0u0zHGAbMJhykp04TLJPMbhKadX+VZtJWdZhmXKQFmCJQjHoaNVQvPnrwhWmXBy5YkdEvUAbSFQ4Bxe0q+nRVXMN2nFr41AKqcwRevKwA0c31KKeO2mQygGRBz0CRwwrbpLSyq5zh5iJrOs/dgBxT3gWZpEpBmjjTdn3S/MpgCJlDT/TShqIO1jHzPtLXzSbdpAYZKs2GZthU3f2m254chl6+XqQuYvrJNQLP28CxQDZqh0KwNQV8o1VfWl0bJga974WvnPEdRMZAL1Y0FZkxdy4k64dsMoBZkufnPtJk4gOYPpdegSLnQjrYgyEgLQFQP5+b3h0Khq+A4Txuk+twoBdJ0/7IvAgRMiXs97VW23Mpa+ylEoQcl+CBKhWH1sXsB2oC7NMo2AExf2bpdZpZmbttOcTALgWKhKXKZscDkAEc50xgpT9sjoskJT10BgOmOlJz3pOpyodsE7j2fKuA+fWHevD83fFsHQMd77QF0GHdcJY4LtedCzRAvoN8HqodzqXTKjdph3XRsBUiBIszKudKsTj6/qQE1rd91oOk8ss/zdgA0TB2AEqDU032wTPuQuUu97xgYDhqYZJkaXSbVTl+hqZ1StUKzDDCrwpJqsoE2h0ktPMuKgG4CxIVuY/vzuU9i/rMKQDMwUmFc3VlmLtR2m8a9nXa+BsusTPYzaZlDzdJtNxoEqZFeuNJ0HwvY6g9972qg1KGa5QNhWHJyn2GbsPllYUnn0bA08hh36SsTs+iHLkM4w5Iu01d2IkCz1HxmXcCsArYRd5RStfCUSiXFvCcVfgVcmGou0/WSeorQffZe1w1Q9ICVhmcBlfTACTOMqwPQngvtaPOIRjl9QZCTlzCh23RfbZACwFgGwN6VRXefADCWPQbQSs/6Bqxn+1pvWse6Mtj5saKfa+tCUh8fwLnHxJPXDCyNNAaWenkK7HU6TF/ZWGBSZWp7IhAFwTpCs1JgVoFlXXAccci28NSUh2Ep5oTq6GJg6sgA5OAACqCUCzXCtr3x6guK9JCtEYI1IJywbjSfL+0B1nGkGZwDrhRAMVfaywNghHqzMvrzam1XWlaO+7ROGO5+TxuWeloZWOrlYkKxvn6p8nq9KsAEijM+BMw0zeyzqsuk87IMPzRF85kkYAlgOq8FZexynHyAqwi/Nmw7AqryoAS7vtEW4UDzB8XbUjb+So4pZ2E9AFUZAJkwbg5OFC50XHehMMO2IohqsMsdKONGAd11qiBIAcKV6sDUHg3Y1VZa6WXSvnhwUreuZPvJyXefJ+U43TLUPCgNwiZgKS1vw5IrXwWYZpq5TZYFXWZg85lVXWYVYFKnbgCSSajNIdeqVavwyU9+Evfddx8+9alP4bzzzsvzPvKRj+Dv//7vsc8++wAADj/8cPzTP/2TqN1JAc9GRIVuCQeaIitxb3XR82LcZ3a/ZAWApsBMoZgCrvhmkAFUqWKVbeZC9ZW3DkSzbWPeM4UogCIdIEO6OWBRwCkPB9uOFDBCu1n7mbgQb1pOA6Z23HWo2uUcaW+lsTLZI7nb5OZAwxCUrJo10kgIVnOWwXIRsKTS9Kc/NQFMMq2fLjMWmLGwZEApAmSsEx2SsO3ChQuxdu1aXHrppWT+mWeeib/927+NbreFZ4wUAUEQq3ABd+GQslDJnasqInxLtC8DaK8j4rXStnQXms6Lgg3l6k5Uh2gWlrVX52bl0znTAnI6SA2gMrB0YGrBVi+Tlku0csXhs2Fpz33qMh4g74GiLrucvfLWB0q9fmw53wIfva6vvP66LCyNNvT97iMwfXkhYBrjZlymbwGQePFPVWAKYMmCsgzsvHUEQO6D5s+fDwDodMIPNolRC0+AdY3cex8K3TqhXBDnu85GDoh6exxAs/lPrUzwIQq52zQBmjrSYif1xURJoshQbgiiSWKGZfWQrg1JCUgzGOvhXSAM0zSPAaoW8i3qgFQ2r+qTDcY83XpzqXnK9HXi1PHNaerlyoZgubp1wBJw3SVVxzd/yfVRBzCN8oN2mQ0Ak4SlD3p1OcYhcZ4hXX311bj11lvxohe9CCtWrMCJJ54oqjd54cnA0Zkf7ZVjFwYlWj1o2wi4Ty1dX5Wbp2X40xnnA2gPimwIV2smK0GFcbNS2VxoYkE0f2CCSvJVufaDFBSKC5wd0s3TemPXw7p6eRukaV43L6P/D/DOVK8HVfxiSkd7A3ZYbRl1bOX3hprlx30XNxBO03aiQkepl/WBr25Q6q8pl0gBLVSnDljqr2koVgemWdZqZxDAjIUlB7F+ALSitm3bhpkzZ+bby5cvx/Lly40yxx9/PO677z6y/vr16zFr1iy2/Xe/+9246KKLMHXqVHzve9/Dm9/8Znz/+9/HnDlzgmObvPAsK5WQ85es+9QdpgNMFJkwy6fJ1G9+MgDtdcDNgebtWWHcwm260NRDufqvs2Rl7HBuBtjiKT3mvGiWT4V10XOSNmSN/z0w1WGdlpU7T8B9CEKHu3BZ7ejyzX36XGdatzwo9fohh0iCq0FXyfbpcYZGHfjL1Q5MI8/cwdJh2bqBWQaWZQDqG4+knRoAPG3aNGzevNlbZt26daXb32uvvfLXxx13HBYsWIAf/OAHLTybFOlEAdONwjx/DIdJwTWzuEa6Nf8JeBxoum0DFCqFX+5Cs8H3IJjlqF65HJoqXT2caJ/3PFcV4dzxXrlOYoZx9TnOrJ4O0uzn2HwgTSgwemDKlU3La6+1N4+CIes84YI2k899UqFcCpJOOgnN/rpKI58Zv29FbJrupklhqb/2hWP1fAkwjf4YYBrlJS6TgpzUgdqSAlMKLhagMkASyz38koJ3gNq8eXPubDds2IAf/ehHmDdvnqhuC0+fsit+739R6DZx0w3OATn8DDeqrPlPI70aQNFr1w7jZgNOAGcu1Jj/tLZ1J5pBFEAPohkYi5CuDlL9sX8cSAHaQdpzqK7bTPKylMM0QMpANU/zgZC5isQ4T7s8/7o8KEN1qoKSS6dcJVevDCxD+b6Hsht9kuWtvsi2zG2jXEPADLrL0LavT5QAI9eHnl2D86xDa9aswQc/+EE8+eSTuOGGG3DZZZfhpptuwoIFC3DRRRfhhz/8IaZMmYKxsTH83d/9HQ4++GBRuy08M+mwC5ZNSUrBkpz71PqggQkTwA4MpQCFsZ3NuWZh2cyFIkk7JudCe/uU11HFfKjuRPXw7rhKkPSAlqVnbjQdpjk3CsBwpAAcEIZgOq6K13YZ47XqaK8t98mA1ZdmDFood6WtvU3fniJd+crVCwGvzDylmw4y3TdfyZVNX8vy9fRYWBp1mnCYnGOk4FUGliVB6QXkkICuCS1evBiLFy8m81avXl263RaehNiQLCcKvBTTbEBmIFHauZvADe/mzNRnMEEsIsoTje3chfbAmbvQDK69UK7qOcKe9zTmQw3n2XOYBlj1XRaC1A7t6odNAlP9WbXpuIp2jHLam2k6TtMdkA7UE76ViAzXWieLxIFK3aReNjRHqafXAUqunxgQSspwDxcQzV9qBXxzmEYdCTCNNHp8TjnrtTcU64VnBCj7CdARBjIw2eEpcZtZGd1ZZtDyuU/dXfa4pQPVBmQ/AJrVR+ZC9ZweHHOIqsJtZk6Ucp46WLM03c3mq3QZkAKFC7Vhmm0DPEwBxnkSQNXL2uWp7bSdmG9RrqhQrs+Jhtyk/joUdgXcLyO+emUW9Oh92GXqAKWdTsHSGANbz6pDulWinwaBWdpdSmEpTZO0FSuV0MdhhDS54WlLAtNQXb0N3W1C/4DrZcoBNG0mT7AI3tvuuca0v3RbQeWgRA9qaWiXgWjelsrLJ1n5nvMECgC6cNW+MzAA5GA6rpW12zJ+Lo0oz0FSd5d66Dern3iuHGwY1xI396msdKkD7QckY5ykr7w9z9UoKLUyFCiNemy7bpoXiE25ywhn6ZyGEZAUncI1OcZaIDzEmjTwjA3F+hYHed2nXV93m0AeKs15qDvHEECNDtIPosyFokhTBEQzJ6qQu00kSeGYs51h3ajrPoECinpoN5sjTZv1wzRbvQto8NQ+kTZQAfNiT7lUG5AOEBUPyezZt9zTh0K/wBKa+4yBpJ7eZMjVV76Km7TzYkDp1mX6IMA4UHdZApYiR0mUqTy/OeKusQ5NGnhWktSRWu6TCuna5YIAzYtaEMzzOID2yub90lBlnSisOVEU+Zwb5UCahXsBGE5Vh2neJiiYFgfScKd5mgtU/UjpLlVvHzDdqp7mc6BlZIMD4AEJ8F8IyBWrA4KktBz7AHS7HOhyUaD01vXAMiYfRH4Vd+mDZVlQeuEpB2Olj0HrPEdcUjBa5Vn3aQHU6KMHEWWnwQNQrowmJ4yb16NdpwFVzolmZRWQrc7NQ7pAAc2sjwiQAjRMs/85Z5rugulO0zTt4kOUddJhigqzSkO0ElHt+8bAgU7PG3pIAhbEGEg65fR0q1hZWOrly+aT/RYv889Bw7CUz236L2pRp3fZj8KIu9cWnrY06LHO0anDAFRvwwIoAH8It8jKVQzFytEcYspAAqIZBFO7Z4Ix34diTImWn4MUWvkkAFIUx65gmx7StaGpl4GR11VaPe0Dmc9vamX1PsaRPv0ob1mbG9Xr2/mA+8CDGJj67vd05j09kJrIgLTH4zpOuqDj0CWQtNun2ha5wT7DMhaUEZCsHLaNLT/iLpNSC88yst2ntJzlShO4AE2rFdbT8o5AXpzKyfKtUG5eSauTA94Ga5qWPzQhc6M2SHXw5rQzR2TD1HamRlU9nGvl2fmZjGNCQBWA5T7NQ6LsBKt9XfqPZFMg9QEz788Bpz+/6flIfzm9kAeysOQFnLUpcJKhsYhAWCcs9fQaYVkWlCwk64Rn1ldshREHagvPgELuUxq+lQLUXCTU67RgadFvnktDNNHDsUYGaIgyYdrCjfpBWiw0Ql5Od6X5mLKDZuc5LlUO1KxMJg6qgAk+07EWByg03zkefxkh5zx9LpQDpL3dj0U79nikLpJqRwxJO98HFwkoif6cciFYel9n57ivf719Po8aa/y8picPJUAY0XZ0uQmqFp6AC0UCksE6QHWAasoZZ4Vxs671uukm5SALiObh3CxPh6hdjwnTQquSt581YaU7rlTLy3dVaQt58pWzSf6aCvdCC+umZVSwjF6um8NaGQP3vd2x85/esC2VVgKO0nJNO0gvHMk++bxQGLMUTNkyxcvaFviw7cvHKp/TJNIghGIVqMXUbeE5OgqGWSX1dGjaUASqARRmOucuLabmaU5Zp48eAI2wrd5gVpYAKZNOulKtuQKyhXtE7ijdL/2JXtkIv2r7yr6mnahdzi7L1clkw5AqRzlLSRnpfZF22UYX6liFBwbIMuUF9YYalqHtrB6dLANWTVCreUH6hFPf4blhwwYsWbIEjz/+OKZPn44vf/nLOOyww4wySilceOGF+PrXv46xsTG86EUvwpVXXokDDzywfwP1uU8iLxagWTNGGxm/CBealudw6i9rj5t1o1kDZUCqVQvCVGnl7J1nrmvGBU8AVdOJZtswRIVs6XRbcd/AOLB6Q6hWfilADiK8SrTdGCCp8vZnR+xW6f6iYekZexlQknvuOz0FQOsb9Mo4lQmkvsPz3HPPxTnnnIOlS5fiuuuuw1lnnYU77rjDKHPjjTfiP/7jP/CjH/0IU6dOxcc+9jF86EMfwtq1a5sbmA+W8LhWrV4QoEaDfhcKBCDaA1ii1dXbKtITLZ1wozEgzXYSIGHnhHj1fAJyxvHUea2FX8307Ljo30AS7bhk7aviOBFXCj0cDKuOu1N2Hb9CvyQhcZ+Nzz320zmWrRNRP+oXR6RwiwWlz1GGxg9C3HnEOVEpEOsGp6e9UXemfYXno48+irvuugvf/OY3AQCnnXYazjvvPGzcuBFz5841yv7ud7/Ds88+iylTpmDr1q3Gr4n3TRZQQ+Fbt4wFUL1swIVyoVwY3ZrYELvRGJDqDXhhquUZDjR7XeQpu10tG1ozdhnSqWbD59igEufiZAI6S6NBW5tIaBJpnnqlQ6vD7hwlbSASkva2FG4OmMPt+cO0VntWURI+ZQApOXX7CTPV5/4GoL7Cc9OmTdhnn30wZUrabZIkmD17Nh566CEDnqeccgpuu+027LXXXnjBC16AfffdF9/97nfJNleuXImVK1fm293nfld+gJT7rBGg2aYNQ8eFauJCuTC6tiAacqN6HR9Iobej3OPDwZQApjdUqzVj7JhZhIeq3a5u37Ndsq+7unu1OhCaTJHY64fIgdr5Mvc4IeBIpDlwFPXtH0sU2Ko6VGs7CEryC4KbxpUV5UnarkF1fmYmitzfSyL0i1/8Atdccw22bt0KAPjlL3+JzZs3l+rQXqhh/+oFANx111347//+b/zyl7/Er371K7z2ta/FeeedR7a3fPlybN68Of/rPG8nf/9Nhi30D07oW6r+zaz3OlFWvp4H7QRV5l9WL+kmaV8qIfJ65Xv/J12iXjcpyjjlE+PPKZePVxtDN/vTynYT909vyyqjuL/xRFYu/4P7N06X7fb+lCr/l7fBjN0eS9cei7Pd4fd3vGNsu8eYP74YjyxvnGPmuWb82W0Q55D3nLLPQWPbHUvejna+5+c8ca6a579dlmmXatP+nPU+pwl1PBTTv/0ZDdRlP/+BP/d9q/FvEkrkPE877TS89KUvxYoVK/Anf/In+PM//3NMnz4d+++/P66++mrsvffeos5mzZqFzZs3Y8eOHZgyZQqUUti0aRNmz55tlPvyl7+ME088EdOnTwcALFmyBCeffHLcnpWVgsh9Ato5o+dnEEmscrmTI1xor3z22m5KV6IVMH7QVzN5WePGXGf2X+4k6bEat6TkadrAspfULSiGq3RG7e4UMbfp1uXLKaNsYpU1dkdz524Zrt/avmexbkLiPj2DiikrKU8p1AYIx0jtrzjNHRP5dgXGFaxTxaF62w2MQ3ocqLpOPRm0BjX3OOpzniLnOT4+jjVr1mD16tU4//zzcfPNN+Ohhx7Ce97zHtYRUpoxYwYWLFiANWvWAACuv/56zJ0715nv3H///fGtb30L27dvBwDcdNNNOOKII8T9NCLyomHlMx8i01EW39Qcp2m9Nr81un/5t1y9PvXtWncLvW/42bdo5xuv7kzt+pRT1F6zjsJ2Dvkf5VIFzieiLOkuLadmuL1x19WW+dPbIvu3x0D1O27tX3BcgeMWcoxO/bBbdN5fyi1SjrE3Hqc9/dzTnR7pZK3zVFl17D7LOFT9c2Z/Fn1u1v5cWZ9NrwO1P7PEn7EPgT+fa631b5JJ5DyTJMGWLVvwile8AjNnzsSxxx4LAHjrW9+Kv/mbv4nq8IorrsDSpUvx13/919htt92wevVqAMDZZ5+NRYsWYdGiRVi2bBnuu+8+zJs3D8973vOw995744orrojctQpSIL5e0unG/KZdJjuhEqJshBPVmjCaNRyn7sg40Gt9m665GIPhTLU+zPyEGK+ix55ozsTaJ5FTNXZY3xmtrP1eUe+d8zU4Mf6zZZSWfMGXXjyocqXm+gKDCtVHSccoHL/ILXrHJi8r6j+w7XWTVPnY9qXvO1fW11ddZevWiIdzRfD88Ic/jGOOOQZvetOb8NGPfhQbNmzAQQcdhF//+tfYsmVLVIeHHHKIc2sKAHzxi1/MX++000648soro9qNkQM8SlUBCq2cARKtmAaiNLvI9J3zQZASfStuHAwMEwZs+n4a09fc4h/A3Gmjvn0g9X48VzeVMAfB06/RMVM+lBcr35sYcTH11nMu0mVALBuLGIjMfscBNQIswrRhAWSTi4K87fdbwzKOhiSC56mnnopjjjkGX/3qV3Hrrbfir/7qr/Dkk09ip512wowZM3DTTTfhmGOOwV577dX0ePsrH0Bh5jnzoFQ5wonmRXWQ6k4wz6OHaAyPcIxGOS2PhK7AXdoOlRqfCVUYB8U4Ph5A+sCatiO4OtqQzdOJNE4xV6Iq37QFAGjKKVYCUkWHGD0GTzrZuui41lGn5DH1pfva4jRMwBqmsTQg8a0qs2bNwnvf+168973vBQA8+eSTuPPOO3HnnXfiC1/4As455xw8/PDDjQ20boncJ8ADlMmLgqiWZsDSajSxzkJlb3CminLEIXdqlwsBFYRLtcGv5Zlm0IKqkeePqyXScC0Y0AbqmAOrQawbk8SNmfqBC3jafol2qHpcXWm/oTY8eew7ENFHmUVHZL0av3iw9QN1aivfqpJK3+e5xx574A1veAPe8IY31Dme4RThNEN5jnPUy+rlQyC1nFtaLAKmNuBtd6r3q4/DgLlZ1omGMlC1HbQT/uXcKplAXKMl7hMMaAX1Kit0MRNfeAcAxTqAGAtDX1u+9qLcr7B+GUhWdeYx+dJ+BqhhHFOdmlQPhrcldp+ZJBCFWyYIUo/orogPtmld6b4IOJNO0cr3HSJ9cZLhZgEHgMZ8qTMQOB3Z743TfmjRj2/g/f5kx4YsgXLhQ7ZehTlMJr0UBKuEKEu0WWkeshGXzqRz7XCaCGCaCGOsoEkNT6AEQAHaQQrLUB8QFqjMXCc9t5O4sAlBVe+TCtNSdXxgtUFsX+gD7pKGpR+wXN2iPl0+BN7a1KST6icQY91llXBkJcDSe9CMOxWm+fr31JnwGtX96mnSwxMoTuxS01uxICXKskAtE7qxx6CHVO3+JG61N1Yy/BrjWIn9CcKVSSRBWWVek2mzrEQOgr2YVwyXir9sRbQZOwZJnq/NvL7/TSkNpAbcY+nwrFCjHgKdiGrhqYkMr8aIO8ElYV6rfOjCwI6PCS3T8HOdn3s7pHKhR8LLTiCGFgrDkvBnIuJO+3ZMmBfrUhtSrRf5mHbquMiXcVJANfAF+pbm1xUCrhOMYgiOACxHHfgtPBl5w6uxkpxEVCjVV5wCDdEnOeZBAJash3JgBmjQanmB7ybWiwYkeQ9j68aArDZnWWKu1td/bJlQP9K2fIGJmuBYR2h2wgLHmVJAveGcIVQLzwiVPbHFt8Q0IGcO09MnORdq1a0EWLt7KShLLAjyz3dmDYT7ECvm/avzQl4TDAcSlhW2E1su7IqF/UnbLPN+CutPaI3qfvXUwrMPauzbpMC1cWVzBeZeuUVLvv6kc5cJ1wZzwMiwL7nBqN9fhCteOAcJwMoAaspp1fhZagSIkxmWk0wtPJtWHz8oZFg0pFB4mgMq1V+WJw15c3O7JH0R3h/hlbjJaJLcbZWcE6wbhBPcUdXpbge2QnhENer73MKziob95Cg5PhaKnna996+ykKT7j3K0UQXobqvAtNQFot/zc025S4FKX0DrPHfLtl8HEGu6RsQcx6GZahz262NFiX6SrFVPyvrrgxLV/z/Rvlt/9s9IUT8TFfyZKeqnpmL+xpk2A3/JePm/Uv14xh/KZ9v2tcnkBd9TyV/gPQmeI9xfZD/efWLOs+A5HNhf0WehzGewxHvl9D8M14wh0apVqzBv3jxMmTIFl19+uZN//fXXY968eTj88MNx2GGHYePGjaJ2W+cpUc0nR9TJNoATUzw+wYIc1kWG+ihxuwlbrZ/fxCPeryadS5UQZO3jqvEcrnyhFtav1cHWUaeuPvr0WUgwPFBduHAh1q5di0svvdTJW79+PT784Q/jW9/6FvbZZx9s3boVU6bIsNjC06ea3vw6wmODXFhRDELeh/LNi1JtyZv2t+utVKKORA0c66rnTD8WtTQSsq6gShfrBr8MDAtEyjx4pVqHfezLo/nz5wMAOh030PqJT3wCf/qnf4p99tkHALDbbruJ223hyaniG19mbqqWOagmT9gIt+jdl8CHmLzVxdOXWKpov4r6cZGufC5UdZd1O7Qa+hpUP8P2JaGUJJ+pujVsx4DQvffei/333x+vetWrsHXrVrzxjW/ERz7yEYyNjQXrtvCkVPeHjEiPhmsV6ArbqawIKAXv0YxpLxKGfYvi1vy+9C2C0WTIktHA3FmFfofFUYpU0xfHUPt1a9u2bZg5c2a+vXz5cixfvtwoc/zxx+O+++4j669fvx6zZs1i29++fTt++MMf4uabb4ZSCosWLcIVV1yB97znPcGxtfC0VeIkID9EUmBK07j6nvLBenVL0E8wnJspIsQ0NKsLe2oqxN6vyMRQTBGUUKPn+ZDsYyU16D4jbteO0rRp07B582ZvmXXr1pVuf86cOTj11FOxyy67AABOPfVU3HnnnS08o9UQOJ0yZWFbM1TFZapKGs7Vy8eMa0jg2Wh4r07oNRmSnciQ6cPYE/vXEAAo4S1W1TrGxH5vGtLb3/523HjjjVi6dCmUUrj11ltxwgkniOq28CypWqBZArJV3SvbBqc6FubEOsjYBRmDhmc/5tLqBN4AwvwUNEZOpc8D+0JQfSi6VJIMBpxD8pavWbMGH/zgB/Hkk0/ihhtuwGWXXYabbroJCxYswBlnnIEf/OAHOPzwwzE2NoYTTjgB5513nqjdRKnROqun7jYdB55/cXzFiKMQglwMNOtsiyzP1ZPUGZBqDcNWaavm49JYODTq3I0oPCRzmv0Kyw/b50BX5WPQ8DG8d/UleG7bb/LtqbtPx/5/WuI6bOnpL3wiGLYdlFrnGako2EmhWbINyXjIMky5qPy6FRvalbY5LKHHUlMCzYBuos1pDjPU+qVK3wEHEbJVo/++tfAEyofEpNATOs2q9SX5bBqEF+s6PxCRP8MmVT6H1DSwYlTXfHpNffTtnsimNeiQfZ9U6pBLF+fFjCPmeA/TedKARhKeovsEK3dibkaBrwowI0DqjlF589l2fapynBu68CWD/tRW6L4vi3T6Pb4aFPzx92FWDed5okq0o+oPeU+S7yoijSQ8gfoB6msrBMAg/CKgKQ8L+0EZG8pt5KI5ES58ZVR1v/rhUkv2E5JkHGUu6NH7N0xXeW3sfb2tquI1kBxrv75YTwCNLDwbVYRzFAOwFoeqmHSYkoCUKBedP4nVr2ew1tZvH9/LSsdGCh9hH/2+R7iUg0SJecsy85z27+VWPCfaOc8JLJH7FLzBorBpLATLltdei2ApDS970mq//WHEVNtFYpDh1GF9/0re9gTIwFj6uNW0ilsK71joDsXbORSDaE4jDc86VBYcMeCMh6ziywvTq4RxJ9pqzX5pGCAK1Ljoqen3reSPtedZgRt82fejDrdZUyi29vU3kYuEgj98L9Uk+YzrauEZI7EjFJRnyoqcZi0hXqaMnceUCZYfBg1oXMMGr4n8/nifgcwdZ8FP5dF9laNgfnzLhGPFnYTfx6jQbgMrcZ0uhvW8q0ktPEvIB5dawclAs9I8qi/dyiPzmXK2hv6JMn0YXu0XjxGFqR+QXIavQXn7Zl/6B0NWh+o3BsIi8y2BonBxUNmneNl9iTRk51ndGnl4Vll1K54flLgy7X+73WhoisO7njRfupVnjMVWEKL+/L6pT+OYKKuSB/m+2DATjUU490mBsg4Ac22TzWafFWFYWhR+rvj7t9l4yrzvzn5L2xiWz35DGnl41i3RLSseJ1nZbQbraQOSpuntgABlTW7U1lCAteExNLaPfXb2opBhHW1xIBG6SadtISCjFhcJ91UONH9J77NpBeHXaLdZ86rbUVULT4kErlMKN0mZRKny0PQ4T951KiYdpojjUMdqZk4D+dD2AUqN79cAjltt92GSvzoi6C8A3RAco8CoImBb1TF64Bp84HvEvGZtC4f07kccupMbnhIXGUjz1qXg5XWlvNssO29Ku04BLCMhSpYz6pT/JPXtQ9iHfkZpX6IUEfoThXWd9sxCwTYEDlc0FytYnBRsx5PvZ2PAsUq+CTS1cEi71o2qJjc8y0rg+uyyCQWjEDi9oPWPgXaiDJydcnS6kwewUCx7i08ZjYKTG5oFVpJhVFhM4yQTEBOFXgOQC8Ktd7zDYAtbx6Cr9VX3LQbyzFGG6gH+c6r085+H6clNA1bf4blhwwYsWbIEjz/+OKZPn44vf/nLOOyww5xyd999N9773vfikUceQbfbxaWXXopTTz2138ONnhwPhU9D4CQh6AFjGKKuyxQtPEIYlFJHSpblVCNDGgfSAHiXdPvfZ1WpDp8n+i1LA5Qe2HrqeudIvXRTAjjyBZqCI1UvOLepDVM0z0pmeKuVLzsB1Xd4nnvuuTjnnHOwdOlSXHfddTjrrLNwxx13GGWeeeYZ/NEf/RFWr16NV77yldixYweefPLJ0n3W8Zxb0QId0GXY15HgFLlNG5oelxlejauYdDjyHgdC0WCrE6r9ANAQXTia+hIhvSUjGacSBe0T0PWuZM1B2V/AKs+b7QUrXykejiEQezuEs391nDPtnGeNevTRR3HXXXfhm9/8JgDgtNNOw3nnnYeNGzdi7ty5ebl//ud/xite8Qq88pWvTAc5ZQr23HPPvo2zzltbnPArA9awO+XzRdAUuc4wLMMQpT71bpJRJxZmNX0o+xIqHeELSNTxE8x52tAzoOuDlwXZpgBbCq4e58qBVWAczfIl3W1e19dpFY3wuQ/0GZ6bNm3CPvvsgylT0m6TJMHs2bPx0EMPGfC89957sfPOO+ONb3wjNm/ejCOPPBKf+MQn+gpQici5TgY07MIdD0RD859kiFYITS8wBbCU/LwZC0XBh6oU2Or8sA7wgz8Rv7EHV5/a+0TOUyo+3we9DLJcpJFzsGxkks6IvC00r8S6SOocTxJPeXpAVUK40nOt3w/Qnwjqe9g2sU5+RZxA27dvxy233IL/+q//wj777IMPf/jDWLZsGdauXeuUXblyJVauXJlvd5/7XX2D5dxaKGwpeO2AzgfgIEQJtymEpnz+U9uw9t+BpNSRespXKuf0Xa5eUMOyyGcIxB7jsqtaGRcYcpUsXOsAK9M+OxzOEcYAtdefXd7XNlU+r5NvEHWtNoyk0KkeuiaOoPoKz1mzZmHz5s3YsWMHpkyZAqUUNm3ahNmzZxvl5syZgxNPPBH77rsvAOAd73gHTj75ZLLN5cuXY/ny5fn21N2mNzZ+UiVcZ2K7PQqiis9zwrQiV5pt09CUrM4FLFDan3Phj23750L5PLONcp/MRj/Q3RG/WvjU4ejkHhPvbSQ2nHLHaTeSlbfbYuBaF1iZk5dyq1w4l2yBAypJpQh3GmjfqOsdYAmN+Mehr/CcMWMGFixYgDVr1mDp0qW4/vrrMXfuXCNkCwBvfetbcdVVV2Hr1q3YbbfdcPPNN2P+/Pn9HGpQoZAs+dqBqNVGVXB6ISqDZgwwfW406puoB4TRsKsIsIF/Wx50/4A/PslpPAxJp3kKuMwtJMV8pAtX1rlSYCVhxrhJYtqBWzlMQZV8iAEBsZiQbLQ7zTfIQRcvA+ddqbDtMJzLDarvYdsrrrgCS5cuxV//9V9jt912w+rVqwEAZ599NhYtWoRFixZh9uzZ+PM//3O84hWvwJQpU7DvvvviC1/4Qr+HSkvgplgowgReVs91pnT97LV0hW76uhw0KWCysHQcqLlNwdH7YQ0AsBTgavwgD809mU1JsHuSlbamoyQKjNOgzIszcCXBSoxH+i7FQJUFKglJM3HQMM3L5xtuvt6XkTTip3wZ9R2ehxxyiHNrCgB88YtfNLbPPPNMnHnmmf0aVi77JCEXBcGTxuVR7RLO1HGNQnAG3WYsNH3AZL4o6H2y+QwYvR9O4Qe3NNQGdGEYJITL/vxWJnLsghU17CpXBq5isEqhyjlVQqSbFAB1UDAtFgnRMLXLO/XyBLdMGY36GqPJ+4Sh0AniyReFbO08FK6TdJaU+4wBZ8Bt+qBZGpg+UHY9eXbblmpZXBRqJ6QJ+DCCGIUe7cbK88ADu0kalPqJRNdV1MXebooAqxiqxGVd7FIFQJWGe+22qsI0dlVv/jKw86VX2o64W5288CwjwcngOjGmnnLLOm5USysFTgu+6WveaVLzna5jLTI5WJLHwNgn5kCWgWnef7iI2Vdzn+xhD3FVuu3AfuCBx8HmcOCAqxjAUicCUZZyrIqIbCR1AZWFlgVBZ7JV4E6tdsjH53ndpluOLQsEgWokS657xPawfw6qqoVnWdmAoZyjJsp16nUpN0qVDYHTPweq/OFZgcsUAdOob39thiMWjj4gCuFX6QM8onObomMiDesKnhGLcb69BMqFawRUHdcnAWrHXa3qrGolVrSWganjJjMAaud2CKTedkIgZco6dYDw+V4x1D9qauEpEeuI/NsxrtNId0BsgVcATvN14SjZEK3dHuAFpgiWIcdJwbHsg+ZjQFcjEyfC4qFS85vcfnEraJ0Ltuv2ivFYZQm4kq6VdJ/KhWUIqFTIt4Q7lcDUCc0GXKlkvjQqvEsNNLDKlv0iFPsZG/6PRiW18IxU+CJO1VH0iaQ7TNZ9WnXLgJNwm06I1qhnAZJymBQwfY7TeZCCe0DoLxSeAy74cJaG2wjdsxmc3+Tu0aSUvdXBXxtxoVaMR7aKFgDQtUDYEbhPwVyis0Ym4E6ducOEyrcatdMErtQBKbQ2cgdptaGXMcpZ48s3iHHqm4HTRRz2H52PEKkWnh6JwlskLD3tca5Ta88/92mnEeDUXaUOTiKdcps2NCmXGQSmB5ahFbp2X7aCQIwAX9/mZao61CZDZtY9mqIfes6doacw4RTTdBqs9Lyj/SWMCOdaQI2GaUKARj+HQiC1xu44PmZeMhqkJCDjQWqM0S5v1aM06nOZUrXw1OS9LUWXc/FnygQg6bhOB5iKzsvTFJFm1S3jNm1o2sDk0vK+rAuLMXb7UwxHJBw9QJR9ySn5iR+WsGwd45D+CorjTDz1NPDSt5Uo5n5NAqwEVJ3bTSiHGnCnQZg6+daw7JXj1v7YMI0O72ogdQAonCMF5CBNy5pDKnW7SuB0GnXItvCUKnAi8G5TGZAKnVBsuNbIgwk7ZbZLh3o1cMa4TQU/NI2HKVh1tTS7vtGGLmq1JHfMQkCJAc6I35qSyjoevttOjGrZm+6/WrI/v8Xdr0n0Tz/th3d5aa7fncbAtHZXqoV3g440crGRE9bVy9gwZsrlmyGYUoo1GSOmFp4l5V3ww0l3cozbJPthyjrgtKCbhWpZcMa4TQ6aVDiWWTTkzoN6HGpenzlAPjAKQVjbYp9+u9O6Qri9207kC4pU4D5PxY6NDMmSt5VYZSiAhEKmFryM86HjB5TXlUaA1HlgQWiOVN/mAMi4UWUtqqLaMNrRy2lldXHXsZjbnFrnOdllXPz5PCc94sSxAcne1pKXVUwotz5wSqFJukwOmCFYOi6VOYgMHEUwnOjhW4AfS0moJtoFPqjxAGyJBT1svwKgOjAlVqv6Q6blQeqEU508rR8dpD43aj06j3SjJSEKEG7UCNUKQGrVsTXqQIyRNHDTipPnZCLnLGNPPgOqgBFihQXcLI0BZ2K1kYEz0ceoQ7j3OlEqveh007pG/d42iDppveIv0caQdJVZt9s1t8e1Pnt/ybhK/5T11+0isevr7ep/VBm9T+7PGstQ/nFj9+0zd6w85ZJu130Psj/uWAnHYJwjvfPTPIfMv/xLYf6ntQerLWd/tfHBOm9htuvL0/sBrDHbeb7xwWzT7cM/BiD97DvPpbbKkG2BqUPUFYtqJ/avBq1atQrz5s3DlClTcPnllxt5559/Po466qj8b+edd8ZnPvMZUbut84wV8YZKv41Rq2I518n1pY+DdJ9dN83cNuc3xW7Tdpr6h84pX+Sx85/2h9Zyk/SHWpjGtMmp9ns1q7ZX98ra6PAsohykLXLWklgl6/SRJM6xc5ykEyYttt1bUnSqBNwg40gpt8f2qbnR3FESbpQK6QJpXcm8aFqWHx8gC+lmYh2prtDpUOG62LQWLlyItWvX4tJLL3XydFBu2bIF++23H9761reK2m3hWZdUvSeLscAoByURroXmcKnbUYx2ZOAMhmhZyBLQ5IAZgmVom2mHbY9SVcjVDd1Qu3U8zF3YBgk7XRxcCQACLlCVDSyqTbstG4BSkIYW8Vh5+bh8YV0KYgRE8z6EEBUtLrJCsWQIVgJRvV2tvWLcFb/EDQk8s5+z7HT8gdZ/+Id/wBve8AbstddeonZbeDIyHZMnz5buIKP7lNfxr8o100qDMxKa9PwnDcyEgyq1bdUl2wjVl+RRGqqHJTBjiXrIgel2OIVAy8JV6FijYVoFpNaiH26O1AGpvo+2G7UAxEEUsNxoHRD1ARxEeTAQJcrp4j5flaEaoW3btmHmzJn59vLly7F8+fJG+lq1ahX+5m/+Rly+hWeTUjrkoIGVyWPq2K6TXEhkz3PCrJurCjgrQlMMTCkoY8O4QBwMm3KWdWvcDzpSFVc7cL3R4Vm47s4Jz1rtWA7QW9+GDQNS78pdEljaFw3CjfpCupUh6ltYJA3l2uUhgKjWHifxl/waPj7Tpk3D5s2bvWWOP/543HfffWTe+vXrMWvWrGA/3/ve97B161acfPLJ4rG18CyrQV9XM9gpuD+BREBWXxxk1Ldf2+CUuk0bmhKXWSWMy6WF4Cj+4A/6DW5YofngDh1+BcCGZlMAmenlw7PFtrIcIAtSal7TgBQPvX5D1JgT7RCgbHA+FPBAVC9v1YlVv+Y8161bV7mNq666CkuWLMHY2Ji4TgvPKqr75NDcprlNz3W6dVUOziJd5eB0ytqvJeDkoKm/9jlNKTBFoVzmgJQJ55YpN8ri4MpBlQKqBKYiV6nCdaVutF8Q1UBGw5UeW1qnhAsltkPzoUAAonqdvAJTbgJr27ZtuO666/DDH/4wql57q4ot7st2ZDon7ypbaX8aKJ3VtUY5+raWXEJwGred6GPTgahUcUtJVp76y/qibg/w/XWJP7Jc4HaUwF8y3kXSVRPvb7yLZLzavov+qPdBPwf095lIc26RsG4XYdvw1Q3W085Z4xYS5tYPX339vGfOZbst55YQ+zOZt2V+xpzbW6g6xGfabJ+4HcWuA+S3uFA/5E3Wtf+k5WL/atCaNWswc+ZMXHvttVixYgVmzpyJ9evX5/nXXHMNFixYgIMOOiiq3dZ59lQpxKBoMBlt13gyUNJdp7MvWbhWmWWl4MzayPOhl1HRTlMUxtX6ZPPt7UB6Ipnv5NqcCEoS0T6qUEgWoPMZd+m8T1T7odCsPcepj8EKzQKW26Pq2fvhcaJZe1FO1BoPukX/TlsxLhRwQrmNuFCqTlY25EaFqv0WsJJavHgxFi9ezOafddZZOOuss6LbbeEZI8m5oAEnGGpl6+v/WwuFsvZV4FtiVs95qo8NKD0PYXDaULSBWBWascAkPqBegEg+0EPyoY8SNw9JlOOOTxCqISBmadaCnbRxCzYSGAKC0CwDUU9/UeFcBlxRoVwDlHwfvrlQCqBunjZeYpsFKKx6WVJViE7Aj1GMWnj61I83X4dhmf60+lwbTmg4e62FvOxQUC3glELTB8yysIx0pdFlJqJ8gI2FqgSmFEjt/Bg36gViBEQp98ZBVIcLB2Cr3VIuNBag2j7FAjTfN/DldNlf0qs60lFRC89I1baCrCwsRW3TrjPr1y5rvNbz6wRnyGn6IGnliWFZBaBDdX+nR7azo+QLxWb5XJgW5vFWVH9U+1VAGgrNeoEoqOODjwEsGnBeF9ovgHrHoY2V2rb71svBLWsrOC+a9yErN1HVwrPfioFmKGSrbXOiQse56zTCy8rK1/K08QAwwRjjNrnwLJVvbTvAlMLSBxUpIIfNieoXPd8+hMDKQdWTbr8PjitlwrLuHGHh9PJ8T0hXEVAKzYmydRgXygEUiHChNkABOoxbF0A11QJQpmwpDdnHpm618OyHdAAGyvkehCCrq8i6ziKhPN1uQ7l5OiRjwBkK0QZcaRCYUlhWnQONKde0IuY2g2Dl3KYEppwrDblPH0TLhGWzcmVDuRwEQwuKfC7U2Ue4LrQugOr77uRp46S27b5hlYVbPkat85zsok6ABk6K2k80a4WtmQcXWHo5CnBZPTCuUrRwyA9LFpwhaNrbsfd/hvIodYWxq6qyn8cZGqckRAvQK2Tteh5o+kDqhHYpRxkLUc5RAqJQbl0utI4wbq6GAMr1QW7bfVP14dZp1cKzMUkdZCjsmksVZcmfHBP0EbqX1HGdBABJV1kGnLHQLANMDiAhAFUBYxmHyl24pGPRAcu5SS6fgmlZkMZA1BfODYRynUUvIiAOAUCzw8aCsh6AunOj2jipbbtvSkSdoBowGcOkFp5lJQCjpA2fRABWelnPQqFMzqP8LHh37ZW3yq0ngWpkmLY2aEpDuXl9AZyaDtnGtm9f5Kh98AGVg2lZkMZA1FeXAyhTLh6IAwJopthFRBXkmxt1xp3XEQAUbj3fGEZZLTyrSmn/a+4wpPD8Z7Uzj3tyUda2z3U6/QvmOY00CThj3SblYqk8X5oPlMLjrZoGKaHEWRXpGUMOBw9QOZj6QKr/cksAmhREo11oaEHRBACocbx88592G3m9Iq328C0jEbylEG3h2SqkmG9YwQcn1OFoyTYFgPFASTTPyfYvAGcd0IwBpmfMpQFZ5fYWz8+K+cYTBKuerx8LyplSjlTiRikQWttBF8rU84ZxBwzQkKLmP416AagKVcZ9RinSiY6aWngSGlS4QX4LS8l6FEeotgjXmZZ1OwqGa5sAZ1loMhASwbLp+z4l7RMXbXvsXpiGQCoJzWZjtZ2oJBwLwoUOG0AjVDp8y7UR7G+I3KfdLpHWhm1bDYXsR/LpTxUCUIRi7TlLW1zItqTrNNLqAqfUbTrOWQZMLyxjIakaWHWbMFdybmwayLwwDYHU50Y5J1piUZAYoLoEAK1FdYVvQ23HrL5tUlXdp7ft0aZnC89+ygu1PvYFMC4ytryngi/U2A9wxkAzBMwmAFm2PwqsVEg1a0r/wuILywI8RDlHmPXtc6EMAEQAjQRj0+HbKEXUa2Sla952IHTbqrQmDTxVMrxhBMnDE8q1q6oBm7uGk+Ffy3Xa6b3/xY/Wk4Zpy0KzbmDW9S07uFjD/hFUC6YCkIogWgWgZqcyEEkAGhu+rVki9xmqF4JqAJSVYdik09SUYHivt3Vp0sBz0Cr/0Pc6+va4QMn8oS+vLDQopylpPwKc0dCUALPpUBTVvvdiq/8sDgNSAqLk3GhdAPWV1UGnu88m1Ke5T0N9ghOAcvOe/VQLz1aNql8nmP1UIZ+4+U5NZHpgrpMM1xJ9ip4QFAtOts0AMKvAUvLcWYmkQM32RQBR1oX6wrhVAMqoUvi2SUj0I3Qbs+p2Akr6APmJqhaehGoP8Q77N7BgCFOHViA/RjHh2rrB6YNmzP6UXYVbFaxUuDXP80A05EKDYcUAQCX1qkCPCxEPInQ7ETWRxz5k6vsvs23YsAHHHnssDj74YLz85S/Hvffey5Z99tlncdhhh+FlL3tZH0c42urbPIQFoEo/UB0RSq4ETqXCY+kq868JxfThGzO1n0R7zjErsRiLHVur4VYdMOXaUDX8DbH6Ds9zzz0X55xzDn72s5/hwgsvxFlnncWWveiii/CKV7yij6NrSBPg254DVUnIRXJxjJlTlZTTL+R1g9OnJmEZkgSkTQNUqkEdoxFUjHs23HBF1y3uN0FwcVPVv2FWX+H56KOP4q677sLixYsBAKeddhoefPBBbNy40Sm7bt06bNiwAX/8x3/czyG2qqoqcGz6wlsGnFWhqbruXxU1CNBRUZPzhEMVshWE9xsZbwCaReeq+t8Qq6/w3LRpE/bZZx9MmZJOtSZJgtmzZ+Ohhx4yyj399NN43/veh8997nP9HF6rYZfn2bTiBUJuRU9/JT68ElBWBWqVEHhZ9esn2MqqyYU1ZdsO1Stx9a0EQ7suNXUcGvMwfXkYsPoetrWXyFO3E1xwwQVYtmwZ9t1332B7K1euxMyZM/O/7nO/G8o3mD3p+zxWbhxD9Y1a15B/+8xV1VXWCdBBqolbT/Rrht5+DVAzYNGhy8S1Le9bXD906y8Tso39THvBKXWbeWNt2LZWzZo1C5s3b8aOHTsApODctGkTZs+ebZS7/fbbcckll2Du3Lk444wzcPfdd+Pwww8n21y+fDk2b96c/3Wet1OpsQ0L3Iamb8mZQX3YxPMlNZerW4OAU7+fZBQj+0e5JUoY0OkXeA6GJd/32mFotK1tdBgAh+qR+W6BoAOM/ZIicJ3iulK1C4bq04wZM7BgwQKsWbMGAHD99ddj7ty5mDt3rlHuJz/5CTZu3IiNGzfiX/7lXzBv3jzcc889lfsfuLsq4fpqG3MH/AUk9EGsE2BV2ipzAS/d1wBOFu6ZtpQGMb5Mg/pCMwjQxrQds2iHeqtjHGbNYmE96GvmEKvvYdsrrrgCV1xxBQ4++GBcdtlluOqqqwAAZ599Nm688cb6OgqGT2pqP6nppPa1UbF937dYMs/3wZeeMVkbvf9FT5KpAATniTn9hksM+Jqon7cj3G/r+DjHr0xkQAK3WNcZDHNGhmBLg1bbiHCdhso4TCrb6J9u30z3t0lfA5i+IzTqYdu+PyThkEMOwR133OGkf/GLXyTLv/rVr8YPfvCDpodVKIE4XGA8TKF3oikk4d+3LCGVJEgi4xh5nZhqSWLMM6pE2x8tj0svJaq+nsa1H9tv0nFDo742souUNIRrAzD2Ae9SRYfsrL5iIw26468BRN7+uNcxc50CcNYBWqMNCcSo/oj6dBjXO5T6wemRkp66E2W9Qkm1TxjyiQNpCLCefN/TiyRPNlIdIBnX+kHRl0p6Xff+D0Iz4ouCSJ0kBU0Ialk+VS5rg+2jw678TJLEXIBGtRULUMmYONXlJvVxsH1xYbfwGBzXafTJgNMpV8F10oOKajsYQakATs51kmIhljj9Bec6Y1ynRBXBKYZm1tRos7P/Ydu+qs+RO7GSiguUEvPEVwm0D2e4AaO8na6Lu7BQ6b6LlyR0G3Hx813QReFbCihJEobDoOYZQ33HgDMmXOubY24yXFsFnJ0SZb3ltTJcuJY4/FEPLaCyDScqb591nRXAqTrx4JwMag9JpKTf9lJABcpzJysDt8piFg2phLg4cxec0Lf9rB0GqiqQb7Rh5zcN0KwtCUSbhKm0D26sSYcO1WptJUliHie7Lfv4xoZTJxs4tWPEgpNynQmRBj3NHUPt4EzcMkAN0Bzx1bZt2DZGCWp/Q425QydPGH4NKfHMxVr7lPaZFGHMDopH9SWBdF/4U5JntJ8UoVI93SijhXCt9skQLmCGXzPAUHOT2QUmNG/jg1so1FsWvj64V3WbgD9UWzc4K0A5h0ADc5y1O84YcGanHjOG4HhjwWlJBEzBqTvqYdvRhycFB8Gbaper9Esr2YnG1U/SLO9cKHoAlJC0k0B1VVGHAIADyV49Ey5FvmjhkN2ODcXe/6qTpA+Kp6BYFaBAnpdBohaI5gcu4iSo05nGApPpPypMy4HNbjsGnIKyobbjQdggOFmABcAJJi0AThXsl3lN9W3n+6AZfSqr4X2QR00afXgOker6qTPVAZKuCVMF9LaUv48OgK4FzYSALOcynbas8tn/3OKhpgFq56EERAEapFnbtupeVegDpVGuJmgCcnA2fTtKwJ2WBmcTbrMsOBMizW6bHIebXQqcVDscOGv8/jdqmtxzns4J1p8+fYuFRHOlkVJJAnuRUdGn6yj4OZXEf0GjQnFUPxnMfG5EesHOL44d/zwdUoCQ86HU3GI2b6j/ccr6quuP7cczHmI/sv0Nzm1yx804vkk94JS0HzrPOjDnN4n2VJIMDTiNsQTAqfTPPuc4833U+6VfG33b5QB6XjPR/jzK2iavK3XMd9b0nXTVqlWYN28epkyZgssvv9zIe+KJJ/BHf/RHOPLII3HooYdiyZIl+O1vfytqd3LDU6oQyBLtfw5SRB3JvVtKcBLbUgkKCFJ1O1rbRj0bIO6FwEhPEuMC4dbxQFUKUP3iquezzkUOUTFI84oEUOu+HSWmH2a85L6VhWbWT6icflHvJOb76nn/yfbt9qJBSJy3LGQtWHWIPvXPEVfXOFfhfi6gtcGk1x2qjQ7TBq41Oiwl17hheUjCwoULsXbtWrz97W938j72sY9h//33x09+8hP89Kc/xSOPPIIvfelLonYnR9g2QW3fYow2e81mvy5vvNlJFkoN9J0QIVNC9rynL3TLL8xh+kp6ByhLzuZMVZaHXigWUN1e/UTrpxe+JedFuflPrYw3hGu3BfBh3GycQAEGez5ULwMYkCHDurq4OZwmAGorMH9K3qtJpfnCs/a278EEIbcpcKYTblFQhNv0tUO7UHcsVVbVhtymoQAwS2tIHpIwf/58AECHufXqqaeeQrfbxXPPPYdnnnkGM2fOFLU7KZ1n2PExr6X1qfKCPsu4TK809+l8CCj3aZXzhm+zNOviRoZ2bRdClMndisDZkCE+u1xetsO7LMth6Y406Ey5vzKKbNc7TmK/nGMQPGbE8aWOW+8ve+8qvX/Wa9JtSssOgduk2uHDt9RYinwSnMb4mD7sfrgQrSWRu0yIvwmoFStW4P7778dee+2FGTNm4NBDD8WiRYtEdSclPAemRAZeY97TBhzRZv6/pE7igtS+r1S/79PISxImHGVe5HKA6n/2BZP6H+DDfaGLsJ1HbVMg1cvZ5UGDyv9EniT+j5Gob27svi8N7PEJQy3f7ilqQVAZaErv3ewnNO3xBNwmD1NrPCjS7X5MaOv5nr71PEGIlgVmQvwJVEfYdtu2bcZPTq5cudLp5/jjj8eLX/xi8m/Tpk3eMV577bU48sgj8fDDD+NXv/oVfvazn+HLX/6yaP8mR9i2TiWoHgJOhCFdpo4Tuk38YV8j5GuEJmGuvE16O6eFb8kQqR6mBcxwrB3CzdLz/IS/jaXXVnZBDoZys76pcG6+88rdBlyA2qt1nYNoHl8vQJuSF9rM92AKtkY9Tz73GpHQ1PsJQRCIC9E2dc8mVz8Cmv50d0xNhGmlTtNRHad3DVHbadOmYfPmzd4y69atK93+Zz/7WaxatQpjY2N4wQtegNNPPx3f+c53sHTp0mDdyeM8uZPBc5K4C2oq9sX1kWRuTV6P7Tf7hpq5T+vi6Ky8tcO3Tr6dZ1606DCtlqen6w5Eb49zCnYoMFCedHRceTtdd2qSUK/kL6Sy7cWMkzoG0mPEvB/e90T/0/vh2kzkIVcjnNik0+x9HmoN0ebp8jCt4zaJ1+y+wAKnnZcQodnELadLPyb230TV/vvvj2984xsAgO3bt+Pmm2/GEUccIao7eeAplC/c6a2TFP+naYmRJp3PtMsbIDTSe+13tG2uPWrlLVGHnf+UApTLy+rp9bkwrg+injI0ZIh+qHKxoOLAZassXKX9cW2S74fnWPi2Y4+/3penTBCaBsgGNKfp7FfRd53QrHIbCpluz21adchVuMTpWAWQCYBEqcp/dWjNmjWYOXMmrr32WqxYsQIzZ87E+vXrAQCf/vSn8Z//+Z844ogjMH/+fOy11144//zzRe22YduqShAXnkj08Cvqf4RV9mEFYK+8pcK3KkmQdFQevk3L9OolWlnPClwnTJup0+ujm+hDc8O4QPGwBSuEq792wrl2GWo7H6eV1iXKZWUBOo8qB/gBWlWhcXD51Fyqc9Hkt52H+NtfNqjXMatnATrkGlPWKa+VqWv1rNV3bHjWP67QOOjXZUO0oVtXnP45SUHq+UW+fmrx4sVYvHgxmbfffvvhlltuKdVuC09OAShmIKpz/jOfy4TZtnEbTE5d0LetOLDsPXXImL8s6hbzm3DnPyUABVJIeuc5wQMWKA1RIN1vox2qbQlMAR6odt3s+PRTof4ksKTSygDT3g5As/R8pri8VqYuaFogqjSn6YxLMhb3tQ9+nNMM1SPH6ikboyZ+13iYNGnh6dyX6ZMN0gBY65IB6KR49B47dh2KWT29LR1+6MEsbbUHRwDdDN9+B2rmJ7zLzGTnSyHqPUAekJaRxEAO6tt06DYYCSiJtFIO0x7PRHaZdh8Cl+nLC7pM31i4177+pNAkTgUSmkJYTuR5zro0ueDZB+jlwIPrJHNHqb+m3GWofVX0Y7tPQwkRvs0A2uubA2gohIuulp8PTrLatldUDFFPiNY+NvYdKJST5NoItO2MaxDyjY/Li4FlaLsOYFYur5VpwGV63V2V0Kzdp5MX16dvTtOQb5xMmWB5iRT6YjAGqdGEZ42QtKFGQi6HVHy/prvkgWtAkNq/BO5Th3Qwo3CuTr/5PsgACiB9qE4GUCqMC48LlUIUMC+ovhAtUZ962HVpdyqBa9MqMf9J/gC5D5B1Oky93DAA0+6jTpfpjE06Hvp13U7T26+vHCfJZ6EN205QxQDUKusLi1LQ6us3rCx8Cx2s9i+iuOFbav7TWUBEARTIfCmKxnrOMgegFsbVFYIoUYYtB1gX5oT9+TSf+J9d6j0ikM3ujWpQF4TAxYqEJFUvtC0M405Ih2n13SgwvWOiX3vHU8JpSl0mf4dBtS+L7e95TmYFwBgMtWoQ84Vu3f897tPqzxe+zUKyeWdAAV8CoOmQVfG6txBIn29NP1A94PlcqO7UQqtutTJ6OaOsLTuEKlnsE5DoR4BDkG1ALBh1CcO2UbC0tmMBKKpTBZi++n0Ky/r6reoygZqgKQWm8PND1R1xTpKafPDUgNjIoqGkfAhXMoYsfJsjznDMFkC1kGxWNIMbBVB9DrRwlyZA0etfDx97XahvvpPbz1iQAvRin4YW96ixpL8OVHJRo8qQYXA5LIGKDlNchx7fsM5jevt18sw2o0OzZccryQe851blRUFt2HYCiwNcRXHQjYIxYNhKkftkXacLa+f2laoABdx5UBSdGi4UnlAuEBmqpUGKxPPj3XldqsHE8+soEVCMKVtWUifNlStxr6do/tJ6Xa4OPc5JBUw7r475zArArPUeT6D66vch12jDsyaR91nqMjni5LGhWwURcG1IGouHnDIa+GIAChSrcPV2oINRGfOgyMah7TwH0RR21o6NId8HEUi18nadog8LqDDrpO0w6XbvofBsCG4xIC4j6Twnk+51iXb5yo5U76cCLO0+Yh9g4ORZbZeZw7TajOq/AZcpBSY/18mktzLUwjOTBcXYW0fstqJDt1od231SbRgLgHr9VAKogvUQBA2EnAuFHKKAzI2m5QQgBRyY2nWLRpgH54fcoxeyEjV0FfLBlnUVEaAktkWwtLaH5uEFTp6ZNbTAdPL8/Xu/ZFD5TDu2yt+u0oZtW2WyXae9DSF0dbhCAxmh4j5M17WmbRHzn4kcoGlxbT7TeAhCVo5xoYAYommdXo7m6PLyOsh0R4rEnLsMhWsJoJLt6PUB/9NQ9IvQIC8IAYfKPd+YDF83Er7V+/S0VwGYAw3H2u06fZQDplPXN/Y6gOk5jaJB6Ss/2uycBPAkAKenSVbMss7PBimYvlAAiAMlHZo12yPL6O7RSOMBmg5Lc3ooIGaHcYtDYNYTQzSBCUIAGNOerQvk4VHDkTIwzdsJARVmnbwdKl0fG+BfaBQAWNVHkrEA5ORbISxYRFTFkYqcJdAfdzlksATKO0x3jJ48oDQwvaCMhSjVROs8WwEWLC2gekO33PmT5eeN8PlU+NYAqWLSdIACxipcfVFQ1lfarelCAThzoWk5GUSzNu2dJB0pYMwzsjAFwkDN6oD4EHNw1dvWFXERUHVcdSQaSOhWr+uBsASWdvvDcP8l0V9j7pLMF+YBcdDnynjKiutGtDFqauFZVRZIfdA0QrBeWLqulnpovOlEU7joacXwtIcg6PeBamCF0ablIplQbrrNQFSDWQ5SY9GQH6R5CetBCOZxIYAKOLALhWyBwLdk+6I3iG/UAkdab9jWbiMelk47fQrFRoGmAiyBasCsfQ5TCkzPqVT59pS8IQzmc9JHtfDUJXSUbMjXBmlWJt9w06nwLAdSe/6TBCgAbhFR2rTKP/BOGLfXkO5Cs/bSUCu01bPoPWO3GGyiVLENBqQJkN37aTp5le+jcazGzJAsBVTAfh/0K5QW+tVFAZZSALoDVWzIlkiPgiRAwIaBlsflDquzbBKU5HgGCMu+OMn2VpUREAG1yvUDoNXvm9TrsCtoNWa4rtNqy0pzw7X0Klw7XOu4UG0xkdmdC1EAYTdKghRFaFeDpusqizwKqABcqALu7SUUXLX0tLLn5LChGyrfpCTQZkO2RGIFUDptlpiz9OU1AstI2EXDkiwTmx8HzMqwFEIyei4e9f2Y9bBqcsCzJrGLi2y4CmCbtwcXmP75TP05tEKAQiubtaHNgwKEC9XHme+CBlGAXFiUjlWDJgFSjOngS1xXmh8zHqh5m/oAARKsdhEOsEaS73MfeyEJXUQqOlmviyDuBZVc9MMXcRqW4hCsk2e1PxFgKYFUVViK2hCMw1O2qFPtPJxsauEJDxQ5aSAMhm4zyBlw5BcApRtW3V5aDEDT6voj9YxmXZdouVA9zx0WA1FAWzlb7KvecaK7yQBMs+NiAxUgjjnMcsaFwH5vx8yLBPUN2Xs6xD7bts6LkuA5t+xFkLwwR0ASqMVVOv0M4WpYUf1SoKO+zES2UbKMWT5wHtVxyrbOc0RFuUNCORwF5e0VuZRzTDesMlZatlmsmBUCFNTrAnR0mQKUaizNZCGaFGNAz90m+XavTDY3ChSQSfTj4IFpNrheqNQAaibdpebHswj96kqI6k4dvW9OAfgOTKFhxIRwYyBp9R0FmWEAJenUGgAlELdPVcqw5TwnieA0rrSAqIXnJFMAkuwtK9xrZlv/GTHqFhNY2yKA6mW112mXvAsFaIgCKUipMGx+PPJ90uZCs1R9fhQIwzTPI4CayQGrthfWAgUSsNp4bfluKxKpiYtFhGv137dHZBILjsIQiYTMBFzYUxcoyXKDgqXn3CgFSEmddsFQK1IagXSgitynBg4jfGuV99UnV9G6Q7PKp2VtF5qXs9oDYMyJUvnGcciPTWKM2XaleVkNpjD204Jmnk+4RQKs+TAowOrywZZSw3OXUZL0xazGlS10kZTR+wo5LJ/jjBhLzaB0xkK24dYRPyu2BJglYyrKhd8nb9+Ceq1o9R2eGzZswJIlS/D4449j+vTp+PKXv4zDDjvMKPPtb38bf/7nf46nnnoKnU4Hb3rTm/Cxj30MyTBOaAvcp7PyliAX5zLZsKyCBVP9EXpEeaO7pIBaD/ZBiHrcaO4WrX0u8i2Yotd3vrjHHJ8N1ayMc6FQID/wjnO1lXVEraRl2nIGNEQqM38lveiGb2Wx26gJklR+3Y5SBK1ykJSWa8JR+iMQnjxJ/Qi1q21r1rnnnotzzjkHS5cuxXXXXYezzjoLd9xxh1Fmjz32wNVXX439998fzz77LF73utfh6quvxtvf/vbGxuVbNGTPe1Jlfe7T7yyJ0GvWBmAC1AdTuG0R3ed10m3CiWYVMqhSK2e1i5jtSPWwKwtTgAcq4EBVH7N5j6f2Ui9LQVYXdx2iFg6V+cJW5zUjsvsyc1yy21jstkL5/u1Bg7JON9lMuZJfbgLlRfUi2vGqhWd9evTRR3HXXXfhm9/8JgDgtNNOw3nnnYeNGzdi7ty5ebkFCxbkr3feeWccddRReOCBB/o5VJlsINhptvtkwejOf9rOkgSo9rroznKMII2uta05UW95F5AkSJlFQXbDyunIhCY5Z6kt1iHhmomBrC73C5DwKhG6JtT0zb2OPtiLJHkLC9XPBIOkpMygIMmWrQjKKpCseK7W5VInovoKz02bNmGfffbBlClpt0mSYPbs2XjooYcMeOrasmULrrvuOnz9618n81euXImVK1fm293nfld9oBQUBeWl7pOGq/4D1HKAZs0YZWFC1BMttraT3jYNUej7R4F0DMZxM2BqdWw+yN2s50AVcMBqlMsTtExiRawDS6eEJfZHs0MVB6DALSz8hbckSCQQ6LObpMsI9q8CJOPLNgPKYQnVFg2idZ51y563VJ4DvHXrVpxyyim48MILcfTRR5Nlli9fjuXLl+fbU3ebXss4bbGhW6n79DjHtAMBQIuiedMommfyzLlQux617dyCYn0p0Ds05iKN9N6qXaPhXl4X5kVE34GsjPW0o6wc+yFXIC+URXuRFwhtTnZCKeCeoy7KIbhRZQbxVB4g7JCJdpool5aVAZJtt8bywXqR7UTVa+FZn2bNmoXNmzdjx44dmDJlCpRS2LRpE2bPnu2Ufeqpp3DSSSdh0aJFBhxrVazDFLRFuk/DYTL5yOoTAAUBWyvNB0YqlGuU1YBoL97J3WgGUtDl9PbS8uagjJWyHqga9X0dgHCvupyQLHhR50DJxWlRD9uIVLQ7KOFGxM6oD5Ckyww5JGPa9bbNlC9bx1Ov9jqZ2ltV6tOMGTOwYMECrFmzBkuXLsX111+PuXPnOiHbbdu24aSTTsIb3vAGrFixop9DlCnCfVLhW8dVhgDKhGk5aDoOOc+jIWrXN7b1faPu5bRdqdUIe/uJ1okR9s3ERUwpwFJ1PB969yfK+LKkPIAcyByQoM/YhUQOHLlyNdwKQpdxC9UZbm1ilSvbbo3lvXUC9aLKCDSZ5zuBAYRtr7jiCixduhR//dd/jd122w2rV68GAJx99tlYtGgRFi1ahE9/+tO488478fTTT+Nf//VfAQBvectbcNFFFzU6Nnaeksqn5IOq5u6iAJpVY4CIooo77EQLVyp9O9G2LZDadbS07BjoIVIjHEo5U47KgAtWplxalgAsdQACckLGsSJCzEMhCUC9v8JClBeCozSwWkCyqgRI4fnZNPxG/VaVRPkmHSegpu42HQe8/2I3g9tL24QoPo/Lz9O0/+00qkyeTpXJ05RbnqnvLRMYs3Gi69FQe9x2e8E8M4H88sG5zNCZKThzS3+AJ/qnInBhrAUYdQFS3Fb5caVliYymAVlzHWl+X25F0XTPP16C57b9Jt/eeepuOPHAZZXbvfupf8TmzZsrt9OE2icMRSroPu1ynBslXKnjQJGGWvUHEJDt2n1rzerbVFq+zTyCz3ak2b7ZjfJ5hUPN8/PGC6eaF9cZzu2YvTN6khMtkFgyIq2mb+VNfPuOds5lL7RiWNUIyMrlWkBG9VG23XAr8T+gMMHUwtMnGwSMODBKAEqGZJ0yPQBxC36sbXjSRWBlH94OK908BnbjJAg9YDXK5Qm6rYUj6mEVXtUMytAXqX79zFMdTiPmdha2/KAAGdMmU7ZMeW+dQL1+wrHWEG1/Tumhl28WZFJKcpLlZXwf9oQu69RN0jSV9NLsbaNukl44qHLEdp7e4cuqDl3OTE/yvlUnMctbdZz2mDJsOad8wv4h4fPIP66vEn/esQ/gL2o8zHFFwhxT4r2r/D57y+l9m+eefv6xbRLnInvOli3vqZP/efLYNj2fY7Id4V9+HanjTyqlqv/VoFWrVmHevHmYMmUKLr/8ciPvkUcewamnnoojjzwSL33pS/GpT31K3O7kcJ6+9yAJ5IfUqy8K59pls76ZdCokmy8m4kK52u4kWh02DyDdpzfd80soaT7cY9prgHWZgZAsdWy9X3RIhxnzyfe/n00vtqhTwbF68iuHdNmyTOGK7dZa3lMnlFeHaxSfYyXOxcYjIgq1wa+qFi5ciLVr1+LSSy918pYvX4558+bhK1/5CrZt24Zjjz0Wxx13HI455phgu5MDnlXEwJWCZRCKMWV9oAX4UG4AlHr/2t0mRbq175J5zjTfBWo6HnPHyfAtMciocGyFUGzfANnEdaTk+MrCIh5KREYNwJsQcBS8N3XPWdYCxAn0pVCq+fPnAwA6HTfQ+uMf/xh/8id/AgCYNm0aXvWqV+Ef//EfW3j2TZzT4iAIIs0qC7OosS2BqFGfASWIfBeKgTxygDp0rR49RHfcq0+cLRaKXMBUtyqOMVpRF9rybQ3brR1l5imbBGO9c5WRJ04T51nZNofEefp0zDHH4J//+Z/xspe9DI8//jhuueUWvPSlLxXVHX14lnj/RCFYppyR5nOgAWfJuVBoRXwQzbIB2o0a7RD7Zdx+4snLCrBOURC+LepQNoMZZOADHVrlWgma0nNqWL7Fi1xQ6IBy9WqsMwxw7BMYo6BY9jwa9PlXw2rbbdu2YebMmfm2/ThWADj++ONx3333kfXXr1+PWbNmse1/4hOfwAc+8AEcffTR2GuvvfCa17wGjz32mGhsow/POkQBw1OGhK8UoIDXhXrLQ4Oo9mzY2DlNW6GQLVnGajgYhi0BSX/IteSVQ/J5b+iiJLmtpba5qqqQqBF0wwLHOkKxaTvCgrFvZQ1vfVORFvLMVdWfzzdt2rTgfZ7r1q0r3f4LX/hCrFq1Kt9+97vf7fy+NKfRhmcfogak0wQc16jnKx0onjTWhSIMPqWlkvdt9ipK5zTtLxCks9QGEg3LoJN00ypfCCrMlZZVI8DP65eoJHJJ5eqXqjcIx1iXU4w5/mW/29V9ftbV3qBdbkk98cQT2G233TB16lTcdddd+OpXv4r169eL6o42PCvIcY8e91kGoE4+IHehRB0nXR8fA9KseX0XubysAOeonT65sC3TWfh+SX++ty9ONXzgYx8EP8hVunWt3qwEoiF0jLWBMfK9rXwuDDuwhmTOc82aNfjgBz+IJ598EjfccAMuu+wy3HTTTViwYAHuvPNOvPe978XUqVPxghe8AGvXrsXee+8tanc04Tno9ywASDbE64MkivplIZoW00Bq/eyXxAySh5aCqt1IWTjGvJcVLyZlfhGlNhhWPWcrjKOWebyG4NY4GGuGYlPuv7G+m9SQPGFo8eLFWLx4MZn3h3/4h7j//vtLtTua8IyVx1VKy/kWGbGLiIAgDKPrWUPk5kbTTfPT5rhSan+Z/azbaXL1WNXwOa3l4lN2HP268NUcWmx08c0QgTHq3BiWkCylvgFWDY3zbEotPD2Srroly1sw4UK7UheqN+n0q732gjQ4/oSBJQFVu3Gik0r3UA4gBBvsYoCLiZpUnTfjTxQgNvUAgpEPxbbK1cIzVgGX6psrZeEqcKFZfTKPqO+UI4btfE4Fc6ZmfT9Ngm7UpxIXkTJh1xiVvjAO2xfwJsKQQzSvWP/DB+RlY9seSHv9kELrPCe7fLediOtwALXbssoBJSHa2/aB1M4H4j+jpFOllI+32Q9T7WGvuoZbclxlvwz00/1MGiiWPaZ9Bt9QzXvW8Xkfpv2x1MKzrCoCFAi7UKesD46B4ZZeDBRqO3AcjPZjbsUYhi+tNX5wy3xxaPpCWOrWmH6GeCP7bBSGFd6LoQJaq9rUwjOTBwKxc59sPauPoAsFZMD15WdlQq7Tu0I3oJLHJ9Rm39UgsEv/rmhd6pMbbWIusan5yb7PZ1boe0KqW/0hCRir3kRTauFZRQLXVRp6gfJ5nVCoFm4Zel6Tlg+qXL8TVoOeZx2yY9jkXF9jLrFfQByBcGzTawTaOc9WADzuUxi2JF0mEA9RSZ1eGZG7pOp62qA0ZNf8vqr2VcPDoqYhNGxArHgST8Qvj42PuYVnq0y1A5SoGwy/6mmcG7Xr9crGhGo5h8oVbcVI8uVjCA5gXx3YEMOwNqBMQJi2ilMLT10Ri1/K1nXgmNUF/BClynncaF4loixbnlNM2X6qjvH0EWjO+9BPmNZxrIY4VNredzlADckThppSC89IeRcPRa087VWpAlG9LJUGoSvV6oQuNuw4hkD9WNDRF5dInAeN91VB/Z43rPQ+D+DLwkgp4pxUNfyqyjCrhWcJ1QXQrC1ADlG2rF6ecTKlnSYzjoFqQOPw7n8fVhzXBe9hWTk6UBA2cA4N4vPR17C/dP+Uap3npFOV+Uu9Dcja0dsDBGBEJEjtdE9bZJtU/SHTMABdtCq5ioSRgVKqsc2Bh0lr2pdhOKekqnOswzD/PlHUwrOCgvd/lphDJSGatQW3vWB5oo4PpnqbEkk/bAO5GDW+mlB72UBfgwqRD4srrbONxs6/QUK2AdDVGoJvV9u28qkJgGbtAnIosguF7DpE3ejHE+lZQ+IU+tpHPxZKDcu9s8MGUjRwXIbhOJdR2XH3i2l1PCRhiNXCk1KJecsgQBHXpt424LlFhmmXDe3adfMKnkGMomusoqZg3GQfTWiYwr22Gjx+g/pSU1tItV+r0Vvn2Uoi0SP8SrrQrP28mZgQLQKulGqDHEAg36eaLzZD4chKqtSxn4Aa9rnZTBPpXJKOta8rwiexWnhyKjlfKQIo4tu2+wEEF2KmDxFMfe02oKGbZyurwLEsu5+DXMjRKGAaansiQbFuRd1u1uQ42rBtqxh5waarRoiy/QlDs74P28B+FisfQE3t9EtVxtvk3HI/NIKh0lGU6JGbdQC2DdtOYlUMs0Y5uornmQjaAlfKtduoKvYxES6sjbn7pq5PfTqmE+G9m4xq35ewWng2qKifMqsAartPIML55hWr9x3VX4RG4YPc2HzVkB6bUXjPvKpr/0bVnCm0D0mY9KoItWiAolp/er95s3W5noYfnjDyF1yBmrjHtg6N/HszqP1rcqHeQKWA9vF8rfoK0Br6o/rPm25XzY6M2uMXqYl4vPodIapRqnWerepQKYACtX9YxGHdBjTwi31T/Y/2NWJiadDnWNMqsW6hVTPq9LvDDRs24Nhjj8XBBx+Ml7/85bj33nvJcldddRUOOuggHHDAATjnnHOwY8eOPo+0fg3iR3o5qaT4a0p6H30FZ8L89bu/Ub+QD1qT/XgP+z6rbvW/IVbf4XnuuefinHPOwc9+9jNceOGFOOuss5wyDz74IFasWIHbb78d999/P7Zs2YKrrrqq30M1VdNJOkwAzVQn3IYClsOkyX6Br0ND9sXE/lIY+1e7hvS8Ul1V+W+Y1Vd4Pvroo7jrrruwePFiAMBpp52GBx98EBs3bjTKXXfddXjzm9+Ml7zkJUiSBO9+97tx9dVX93Ook1JlP9wDASYwtBeNoCbquPutIThOTcCvsc/LsJ1TrfOsT5s2bcI+++yDKVPSqdYkSTB79mw89NBDRrmHHnoIc+bMybfnzp3rlJnIGkb3qSvmgz2wecxhu1CU0SjsQxMaAmgC/Tm3Rx6gI6y+LxhKEvPdVcxTKPRyXBkAWLlyJVauXJlvj2/bim2rPlFxlP3Vtm3bMG3atEEPQ6yJNl5g4o15oo0XaMfcDw3reDu/+62xPe9lh+O+h++o3O7ee+9duY2m1Fd4zpo1C5s3b8aOHTswZcoUKKWwadMmzJ492yg3e/ZsI5T7i1/8wimTafny5Vi+fHm+PXPmTGzevLmR8TeliTbmiTZeYOKNeaKNF2jH3A9NlPF+//vfH/QQGldfw7YzZszAggULsGbNGgDA9ddfj7lz52Lu3LlGudNOOw3/+q//ikceeQRKKXz+85/HGWec0c+htmrVqlWrVqz6vtr2iiuuwBVXXIGDDz4Yl112Wb6K9uyzz8aNN94IANh///3x0Y9+FMcddxwOOOAAzJgxg1yV26pVq1atWg1CfZ/zPOSQQ3DHHW4s/Itf/KKx/a53vQvvete7otvXQ7gTRRNtzBNtvMDEG/NEGy/QjrkfmmjjHWUlyrcap1WrVq1atWrlqO9h21atWrVq1Wqiq4Vnq1atWrVqFakJCc+J9nxcyXi//e1v4/d+7/dw2GGH4YgjjsBFF13kvb+1aUmPMQA8++yzOOyww/Cyl72sjyN0JR3z3XffjVe/+tU49NBDccghh+ArX/lKn0eaSjJepRQuuOACHH744TjyyCNx4okn4v777x/AaIHzzz8fc+fORZIk+OlPf8qWG5bPHSAb87B99qTHGRiez96klJqAOvHEE9WXvvQlpZRS1157rfr93/99p8wDDzyg9t57b7VlyxbV7XbVKaecoj7/+c/3eaSpJOO966671M9//nOllFK//e1v1XHHHaf+6Z/+qZ/DNCQZc6bly5erd77znWrhwoV9Gh0tyZiffvpptf/++6t169YppZTavn27evTRR/s5zFyS8X71q19VL3/5y9Vzzz2nlFLqL//yL9Vb3vKWfg4z13e/+121adMmNWfOHHX33XeTZYbpc6eUbMzD9tmTjDnTsHz2JqMmHDwfeeQRtfvuu6vt27crpZTqdrvqJS95iXrwwQeNch//+MfVe97znnz73/7t39SrXvWqPo40lXS8tpYtW6b+8i//sg8jdBUz5v/4j/9Qp5xyivrOd74z0A+wdMxXXnmlesc73jGAEZqSjverX/2qmj9/vtq6davqdrvqggsuUO9///sHMOJCvov6sHzubElAlGmQnz1doTEPy2dvsmrChW0n2vNxpePVtWXLFlx33XU4+eST+zVMQ9IxP/3003jf+96Hz33uc4MYpiHpmO+9917svPPOeOMb34ijjjoKZ555Jh577LGhHe8pp5yCE088EXvttRf23ntvfOtb38Ill1zS9/FKNSyfu7Ia9GdPqmH67E1WTTh4AvU/H7dpSccLAFu3bsUpp5yCCy+8EEcffXTTQ2MlGfMFF1yAZcuWYd999+3XsLySjHn79u245ZZbcMUVV2D9+vWYNWsWli1b1q8hGpKM96677sJ///d/45e//CV+9atf4bWvfS3OO++8fg2xlIblcxerYfnsSTRsn73JqAkHT/35uABqeT5uk5KOFwCeeuopnHTSSVi0aNFAb4aWjvn222/HJZdcgrlz5+KMM87A3XffjcMPP3wQQxaPec6cOTjxxBOx7777IkkSvOMd78Cdd945tOP98pe/jBNPPBHTp09Hp9PBkiVL8J3vfKfv45VqWD53sRqWz55Uw/TZm6yacPCcaM/HlY5327ZtOOmkk/CGN7wBK1as6Ps4dUnH/JOf/AQbN27Exo0b8S//8i+YN28e7rnnngGMWD7mt771rfj+97+PrVu3AgBuvvlmzJ8/v9/DFY93//33x7e+9S1s374dAHDTTTfhiCOO6PdwxRqWz12MhumzJ9UwffYmrQYx0VpV//3f/61+//d/Xx100EFq4cKF6qc//alSSqmzzjpL3XDDDXm5L3zhC+qAAw5Q++23nzrrrLPyFYvDON6PfexjasqUKWr+/Pn538c+9rGBjFc6Zl3DsGhBOubVq1erww47TB155JHqD//wD9WmTZuGdrzPPvusOvvss9Uhhxyi5s2bp17/+tcHF5s1pfe85z1q3333VWNjY+olL3mJOuCAA5zxKjU8nzulZGMets+e9DhnGobP3mRU+3i+Vq1atWrVKlITLmzbqlWrVq1aDVotPFu1atWqVatItfBs1apVq1atItXCs1WrVq1atYpUC89WrVq1atUqUi08W7Vq1apVq0i18GzVqlWrVq0i1cKzVasB6oknnsDs2bNx7bXX5mlf/epX8ZrXvGaAo2rVqlVI7UMSWrUasG688UasWrUKX/3qV/HUU0/h6KOPxr/927/h4IMPHvTQWrVqxah1nq1aDVgLFizIn0t60UUX4cwzz2zB2arVkGvKoAfQqtVk16xZs/DYY49h3bp1+M53voMf/vCHgx5Sq1atAmrh2arVEOjggw/GW9/6VqxduxbPe97zBj2cVq1aBdTCs1WrIdBLX/pSzJs3D8cff/ygh9KqVSuB2jnPVq2GQI888gje9ra3DXoYrVq1Eqpdbduq1RDoxS9+MX72s5/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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Visualize expected values for uniformly sampled gamma/beta pairs\n", + "\n", + "f = pl.figure(figsize=(6, 6), dpi= 80, facecolor='w', edgecolor='k');\n", + "_=pl.xlabel(r'$\\gamma$')\n", + "_=pl.ylabel(r'$\\beta$')\n", + "ax = pl.gca()\n", + "_=pl.title('Expectation value')\n", + "im = ax.imshow(qaoamc.E,interpolation='bicubic',origin='lower',extent=[0,np.pi/2,0,np.pi/2])\n", + "divider = make_axes_locatable(ax)\n", + "cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n", + "_=pl.colorbar(im, cax=cax)\n", + "\n", + "f = pl.figure(figsize=(6, 6), dpi= 80, facecolor='w', edgecolor='k');\n", + "_=pl.xlabel(r'$\\gamma$')\n", + "_=pl.ylabel(r'$\\beta$')\n", + "ax = pl.gca()\n", + "_=pl.title('Expectation value Cvar')\n", + "im = ax.imshow(qaoamc_cvar.E,interpolation='bicubic',origin='lower',extent=[0,np.pi/2,0,np.pi/2])\n", + "divider = make_axes_locatable(ax)\n", + "cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n", + "_=pl.colorbar(im, cax=cax)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "a5d7930e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 1 )= -19.86213520703168\n", + "cost(depth= 1 )= -23.120157440115662\n", + "cost(depth= 2 )= -21.424389278341042\n", + "cost(depth= 2 )= -23.713190968703994\n", + "cost(depth= 3 )= -21.96525262869564\n", + "cost(depth= 3 )= -24.552234374693462\n", + "cost(depth= 4 )= -22.442847548450757\n", + "cost(depth= 4 )= -24.90678358785036\n", + "cost(depth= 5 )= -22.93777331032282\n", + "cost(depth= 5 )= -24.878448391630446\n" + ] + } + ], + "source": [ + "maxdepth=5\n", + "for i in range(maxdepth):\n", + " qaoamc.increase_depth()\n", + " qaoamc_cvar.increase_depth()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "76202992", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pl.hlines(1, 1,maxdepth, linestyles=\"solid\", colors=\"black\")\n", + "pl.plot(np.arange(1,maxdepth+1), np.array(list(qaoamc.costval.values()))/mincost,'o--', label='QAOA')\n", + "pl.plot(np.arange(1,maxdepth+1), np.array(list(qaoamc_cvar.costval.values()))/mincost,'o--', label='QAOA with CVaR')\n", + "pl.ylim(0.5,1.05)\n", + "_=pl.ylabel('appr. ratio')\n", + "_=pl.xlabel('depth')\n", + "_=pl.legend()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.4" + }, + "vscode": { + "interpreter": { + "hash": "07d9372282eac67c0084465121a77eae453ab4064aafb19ec3f3b305f02b3aaf" + } + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/MaxCut/ComparisonOptimizers.ipynb b/MaxCut/ComparisonOptimizers.ipynb new file mode 100644 index 0000000..062e7af --- /dev/null +++ b/MaxCut/ComparisonOptimizers.ipynb @@ -0,0 +1,389 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "f4edc85e", + "metadata": {}, + "outputs": [], + "source": [ + "#run: pip install openquantumcomputing\n", + "from openquantumcomputing.QAOAMaxCut import QAOAMaxCut" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "81310eb6", + "metadata": {}, + "outputs": [], + "source": [ + "from qiskit import *\n", + "import numpy as np\n", + "import networkx as nx\n", + "\n", + "import matplotlib.pyplot as pl\n", + "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", + "from matplotlib.ticker import MaxNLocator\n", + "from qiskit.visualization import *" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "eaa8c8a1", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "numV=10\n", + "G = nx.read_gml(\"../../data/sample_graphs/w_ba_n\"+str(numV)+\"_k4_0.gml\")\n", + "pos = nx.spring_layout(G)\n", + "nx.draw_networkx(G,pos=pos)\n", + "mincost=-8.657714089848158" + ] + }, + { + "cell_type": "markdown", + "id": "e34d181f-6e0c-416a-90d7-2c1747e7e199", + "metadata": {}, + "source": [ + "set up optimizers so that they have roughly the same number of function evaluations" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "de94a148-0dce-47c0-bfb5-173b63d67b36", + "metadata": {}, + "outputs": [], + "source": [ + "optimizers={}\n", + "plotstyle={}" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "17216bf6-6f57-4bac-9928-df33ec4d3891", + "metadata": {}, + "outputs": [], + "source": [ + "from qiskit_algorithms.optimizers import SPSA, QNSPSA, COBYLA, NELDER_MEAD\n", + "\n", + "settings = {\n", + " \"maxiter\": 70,\n", + " \"blocking\": True,\n", + " \"allowed_increase\": 0,\n", + " \"second_order\": True,\n", + " \"regularization\": 0.01\n", + "}\n", + "optimizers[\"spsa\"] = [SPSA, settings.copy()]\n", + "plotstyle[\"spsa\"] = '+-'\n", + "\n", + "settings = {\n", + " \"maxiter\": 50,\n", + " \"blocking\": True,\n", + " \"allowed_increase\": 0,\n", + " \"learning_rate\": 0.02,\n", + " \"perturbation\": 0.05,\n", + " \"regularization\": 0.01,\n", + " \"hessian_delay\": 0\n", + "}\n", + "optimizers[\"qnspsa\"] = [QNSPSA, settings.copy()]\n", + "plotstyle[\"qnspsa\"] = 'o-'\n", + "\n", + "settings = {\n", + " \"maxiter\": 110,\n", + " \"tol\": 1e-6 \n", + "}\n", + "optimizers[\"neldermead\"] = [NELDER_MEAD, settings.copy()]\n", + "plotstyle[\"neldermead\"] = 'x-'\n", + "\n", + "settings = {\n", + " \"maxiter\": 350,\n", + " \"tol\": 1e-6 \n", + "}\n", + "optimizers[\"cobyla\"] = [COBYLA, settings.copy()]\n", + "plotstyle[\"cobyla\"] = '*-'" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "26cd6c7e-ded7-4b14-9d6d-cb11938eb282", + "metadata": {}, + "outputs": [], + "source": [ + "qaoa={}\n", + "for key in optimizers:\n", + " qaoa[key]=QAOAMaxCut(params={'G' : G, 'optimizer' : optimizers[key]})" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8461f4cd-47d4-4249-b47e-dbbf081b3698", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "f10939f8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Calculating Energy landscape for depth p=1...\n", + "Executing sample_cost_landscape\n", + "parameters: 2\n", + "Done execute\n", + "Done measurement\n", + "Calculating Energy landscape done\n", + "Calculating Energy landscape for depth p=1...\n", + "Executing sample_cost_landscape\n", + "parameters: 2\n", + "Done execute\n", + "Done measurement\n", + "Calculating Energy landscape done\n", + "Calculating Energy landscape for depth p=1...\n", + "Executing sample_cost_landscape\n", + "parameters: 2\n", + "Done execute\n", + "Done measurement\n", + "Calculating Energy landscape done\n", + "Calculating Energy landscape for depth p=1...\n", + "Executing sample_cost_landscape\n", + "parameters: 2\n", + "Done execute\n", + "Done measurement\n", + "Calculating Energy landscape done\n" + ] + } + ], + "source": [ + "for key in optimizers:\n", + " qaoa[key].sample_cost_landscape(angles={\"gamma\": [0,np.pi/2,10], \"beta\": [0,np.pi/2,10]})" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "1b4a83aa", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "f = pl.figure(figsize=(6, 6), dpi= 80, facecolor='w', edgecolor='k');\n", + "_=pl.xlabel(r'$\\gamma$')\n", + "_=pl.ylabel(r'$\\beta$')\n", + "ax = pl.gca()\n", + "_=pl.title('Expectation value')\n", + "im = ax.imshow(qaoa[\"cobyla\"].E,interpolation='bicubic',origin='lower',extent=[0,np.pi/2,0,np.pi/2])\n", + "divider = make_axes_locatable(ax)\n", + "cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n", + "_=pl.colorbar(im, cax=cax)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "a5d7930e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 1 )= -6.927910043501388\n", + "cost(depth= 1 )= -6.9174477271748716\n", + "cost(depth= 1 )= -7.021253729878198\n", + "cost(depth= 1 )= -6.8742157370885\n", + "cost(depth= 2 )= -7.402594431974419\n", + "cost(depth= 2 )= -7.476097057751611\n", + "cost(depth= 2 )= -7.497841178375399\n", + "cost(depth= 2 )= -7.442152765412646\n", + "cost(depth= 3 )= -7.808307432029209\n", + "cost(depth= 3 )= -7.671007997898861\n", + "cost(depth= 3 )= -7.7242136386664\n", + "cost(depth= 3 )= -7.752831864992368\n", + "cost(depth= 4 )= -7.959783036898415\n", + "cost(depth= 4 )= -7.8612947991505715\n", + "cost(depth= 4 )= -7.834613892747666\n", + "cost(depth= 4 )= -7.897444057950619\n", + "cost(depth= 5 )= -8.099464844729063\n", + "cost(depth= 5 )= -8.00954484654466\n", + "cost(depth= 5 )= -7.988588287115011\n", + "cost(depth= 5 )= -8.073556297441382\n", + "cost(depth= 6 )= -8.199685617695694\n", + "cost(depth= 6 )= -8.154802165453955\n", + "cost(depth= 6 )= -8.0475178711278\n", + "cost(depth= 6 )= -8.169165586659357\n", + "cost(depth= 7 )= -8.200341268570526\n", + "cost(depth= 7 )= -8.215722589209197\n", + "cost(depth= 7 )= -8.043119902346062\n", + "cost(depth= 7 )= -8.21415523087245\n", + "cost(depth= 8 )= -8.246936079785458\n", + "cost(depth= 8 )= -8.277798936697781\n", + "cost(depth= 8 )= -8.037534506849287\n", + "cost(depth= 8 )= -8.308924039212496\n", + "cost(depth= 9 )= -8.313515865699632\n", + "cost(depth= 9 )= -8.286415351520148\n", + "cost(depth= 9 )= -8.10070508364371\n", + "cost(depth= 9 )= -8.305980731311186\n", + "cost(depth= 10 )= -8.339101588877446\n", + "cost(depth= 10 )= -8.337224006060433\n", + "cost(depth= 10 )= -8.19107042113644\n", + "cost(depth= 10 )= -8.324478323345417\n" + ] + } + ], + "source": [ + "maxdepth=10\n", + "for i in range(maxdepth):\n", + " for key in optimizers:\n", + " qaoa[key].increase_depth()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "bc7d5abb", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = pl.figure().gca()\n", + "pl.hlines(1, 1,maxdepth, linestyles=\"solid\", colors=\"black\")\n", + "for key in optimizers:\n", + " pl.plot(np.arange(1,maxdepth+1), np.array(list(qaoa[key].costval.values()))/mincost, plotstyle[key], label=key)\n", + "pl.ylim(0.5,1.01)\n", + "pl.xlim(1-.25,maxdepth+.25)\n", + "_=pl.ylabel('appr. ratio')\n", + "_=pl.xlabel('depth')\n", + "_=pl.legend(loc=\"lower right\", framealpha=1)\n", + "ax.xaxis.set_major_locator(MaxNLocator(integer=True))" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "b843158e", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = pl.figure().gca()\n", + "for key in optimizers:\n", + " pl.plot(np.arange(1,maxdepth+1),qaoa[key].angles_hist['d'+str(maxdepth)+'_final'][::2],\"b\"+plotstyle[key],label='gamma '+key)\n", + " pl.plot(np.arange(1,maxdepth+1),qaoa[key].angles_hist['d'+str(maxdepth)+'_final'][1::2],\"g\"+plotstyle[key],label='beta '+key)\n", + "pl.xlim(1-.25,maxdepth+.25)\n", + "_=pl.ylabel('parameter')\n", + "_=pl.xlabel('depth')\n", + "_=pl.legend()\n", + "ax.xaxis.set_major_locator(MaxNLocator(integer=True))" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "c22bded6", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = pl.figure().gca()\n", + "for key in optimizers:\n", + " _=pl.plot(np.arange(1,maxdepth+1),qaoa[key].num_fval.values(), plotstyle[key], label=key)\n", + "pl.xlim(1-.25,maxdepth+.25)\n", + "_=pl.ylabel('number of function evaluations')\n", + "_=pl.xlabel('depth')\n", + "_=pl.legend()\n", + "ax.xaxis.set_major_locator(MaxNLocator(integer=True))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cb9f1295-d287-41e0-88a6-2e8a1a7053a7", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/MaxCut/ToyExampleQOA.ipynb b/MaxCut/ToyExampleQOA.ipynb new file mode 100644 index 0000000..363eef0 --- /dev/null +++ b/MaxCut/ToyExampleQOA.ipynb @@ -0,0 +1,307 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "f4edc85e", + "metadata": {}, + "outputs": [], + "source": [ + "#run: pip install openquantumcomputing\n", + "from openquantumcomputing.QAOAMaxCut import QAOAMaxCut" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "81310eb6", + "metadata": {}, + "outputs": [], + "source": [ + "from qiskit import *\n", + "import numpy as np\n", + "import networkx as nx\n", + "\n", + "import matplotlib.pyplot as pl\n", + "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", + "from qiskit.visualization import *" + ] + }, + { + "cell_type": "markdown", + "id": "afc54384-89ef-474e-aa49-b43a9896726f", + "metadata": {}, + "source": [ + "Create a graph instance" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "eaa8c8a1", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "V = np.arange(0,5,1)\n", + "E = [(0,1,1.0),(0,2,1.0),(1,2,1.0),(3,2,1.0),(3,4,1.0),(4,2,1.0)] \n", + "\n", + "G = nx.Graph()\n", + "G.add_nodes_from(V)\n", + "G.add_weighted_edges_from(E)\n", + "\n", + "pos = nx.spring_layout(G)\n", + "nx.draw_networkx(G,pos=pos)\n", + "k_cuts=2" + ] + }, + { + "cell_type": "markdown", + "id": "062c6b9b-cbe7-4cf1-abb4-50218cc06228", + "metadata": {}, + "source": [ + "Create a QAOA maxcut instance a draw the circuit at depth 1" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "75d8e6d2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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└───┘└─────────────────┘└───┘ └───┘ »\n", + "«c0: 5/══════════════════════════════════════════════════════════════════════»\n", + "« »\n", + "« ░ ┌─┐ \n", + "«q2_0: ──────────────────────────────────────────░─┤M├────────────\n", + "« ░ └╥┘┌─┐ \n", + "«q2_1: ──────────────────────────────────────────░──╫─┤M├─────────\n", + "« ░ ║ └╥┘┌─┐ \n", + "«q2_2: ──────────────────────────────────────────░──╫──╫─┤M├──────\n", + "« ┌───────────────┐ ░ ║ ║ └╥┘┌─┐ \n", + "«q2_3: ─────────────────────■──┤ Rx(-2*beta_0) ├─░──╫──╫──╫─┤M├───\n", + "« ┌─────────────────┐┌─┴─┐├───────────────┤ ░ ║ ║ ║ └╥┘┌─┐\n", + "«q2_4: ┤ Rz(1.0*gamma_0) ├┤ X ├┤ Rx(-2*beta_0) ├─░──╫──╫──╫──╫─┤M├\n", + "« └─────────────────┘└───┘└───────────────┘ ░ ║ ║ ║ ║ └╥┘\n", + "«c0: 5/═════════════════════════════════════════════╩══╩══╩══╩══╩═\n", + "« 0 1 2 3 4 " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "params={'G': G, 'shots': 2048}\n", + "qaoamc = QAOAMaxCut(params=params)\n", + "qaoamc.createParameterizedCircuit(1)\n", + "qaoamc.parameterized_circuit.draw()" + ] + }, + { + "cell_type": "markdown", + "id": "3ae9ce75-30ca-499d-b7cf-35fc1936a9e6", + "metadata": {}, + "source": [ + "Sample the energy landscape of QAOA for depth 1 and draw it" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "f10939f8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Calculating Energy landscape for depth p=1...\n", + "Executing sample_cost_landscape\n", + "parameters: 2\n", + "Done execute\n", + "Done measurement\n", + "Calculating Energy landscape done\n" + ] + }, + { + "data": { + "image/png": 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l5ata39bB2KEJ2R122MEuT5o0CZ/4xCewYsUKHH/88ZgyZQruvPNOm79q1Srstttunoqtam1f/BLKRaEam4wQrK+9/rRbLiW/dP8l7adynyr19aTsMLRK17KqF75Q+Jgsd/rMZrR8mbpOhFlZHyup7BRTifslcMMgXVOU1kEIdgJcr4yTEUgvMQ1gYCs5EYckZNetW4ddd90VjUYDGzduxG233YYFCxYAAI466iicc845eOyxxzB9+nRceeWVOPHEE9tuq1dwDYK1AlSjswE78C3L6wTGvQR5af1t1FfVhtwYcQXrSI118AIE7S1UbKMEstH+JMKxI4hWHVtOqDbYdyldULtW6QoQ7SSkLJZr0/qG88lUwQYdsueccw5uvvlmrF+/HkcccQTGjh2LJ554AmeccQbmzp2LuXPn4oYbbsC3v/1tjBgxAv39/TjuuONw2mmnAQC23357XHPNNTj22GPR39+PGTNmYOnSpZX70Qu4VgJrCihTYdpu/bHybfi3paK7FbYusy7VM1yvC6rqeKqx1LAmwtAoU6JlZRyXCiDWsbZLAByET0q7qSHVyFioVnK5pK9Q9xa4vJzTvwo3GFuLkt2qfk92m7HjsN8pHbxWMQgjISMBfGVQTYFuaZlAuSEB65D1KuRd1a+dPgwxa1txpJRrN8xbsU9iPRKAEv1i6T0NbVfsT8r2eD5l62DjuVXaLikTsz/ftgRr166167tOHIGf/2ZitUqY/fWh2qlzqNqQDBcPOesErhXAGYVqtwHdJng7Ddcmwz2S3uuQdFI7w8TECaNVLpCdXGyrAC5yoXe+h4iytlkdQFmH+mfSSxRc6aSrMuXIQ9gcqpGqpXypL57KFSotDQ93El7P7S000xyD1tkPDAyW1ZAts1TAVoFeG2ANlS/LS25LypesTeXcdrlAelhNx8/wbsy87nq5Tq2iqkgKvxIrVzWhkySlA3Ka0gn9DKg6252SkG8wnFxF5YbgmgBWMSSsBPhGykSb5TcFwno7YWWnfskShxZaW8JdbILVkI1ZFwCbBFdhud1yUR+ex61DNdyxPyCeuZ2EtoPlS8pU9imxTsZkunYpSu1ESTTR/4q06Ki9hUgd/EuqGAYthXKHQBbrDKSJk5ZCqlwAsNenCHhj0I2KzxLgZv0RVC6puFNGvqU7VbJ9HZYfHKshG7IUwHYC10SwdgXGFftYWlclX/dU7zq4A2lBnnQI3M1x890RoNsEayw/KXJYAiRfRWq/jdj4YwzKEcBakCX48jZDytMzqU5JzTKYxuAaVbAh6DI4p9xHUOfgs7mxwonHm4ZCa/Bfnb9ZrIasZKkKNlBGAqkINA7KWB1V6k/sU8fAjQG0XWiXCJr2x5ZDMUA5OVhPhfKDbqExRsE6mtjCdoy9pqcoPQ7amH8MgNqtSOwD6WcUrjGwVvC1fYkco94sb7ITHPiWQLMsbCx1t22Vm6eFrn/t/tJS50p2eFgN2USLhoirKtEAXKuANWkCVRvK2PfR8XLRsgEfVjypH6QvoX60rXqDqj/htnyIQ1b2U1HX8kdu5Liwc0EvDfcqJ1mFQBbqS4o/ufg7HOgiiKXdISnnQDUOYB0lS8FL0rmPCF0lf4cxJRtVueLdUFGo3R8naQ2pk6d3VkOWm3gR7hCwMUCqBL8SsCZBtbTPEZh2AtEKIE9uK+bH65PKVkkDoMtgu7mvFYlwVeIApF+PmJuiUoE4PJ0y2vsXBq3yfaqAmEHP7ULRgVQ1DLjQltoQ/STVatoWjnUJvFztBpUu/DRHIbPuJ6tcYVvaMQ3gLb114Gfr2MpuWuzCT9IqgbMKXCvW76eTu/sKytmpC35auL8+QNtV0zF/v3yboJUsBtnNDVhqJbDVYiyzzXqFNMVjmJq5xcBI1LUP0qKiMGiFg1PyK+lLNyDsqVsBwB58ed0CeIPQpfBULI+mgRyu/ldFm3JM2n2dH/ZDY0z2+9//Pr7xjW/g0UcfxT//8z/j3HPPDfoqpTBjxgz7Ct8rrrgCs2fPLm2jhmyJpbzFKTXsS9Mln2S4VmkvAapR2CKSJ4A7JUxeVjZcJuArrdv0EtiK8JUIEqi/LG8wLEXJcgXp5YdkfEKaVZpxhSytO+paglQySAWJZvNU3pawG6i65G17fZX6FyCVpIA5JBPyk6CboHJttQHlSy1lvDflkHP6z8vroTEme9BBB+FHP/pR8k+l3n333Rg7dmylNmrIUiu7WAr5lQAr+cTyA+XLIa3L+yKlo8yf3w4ntCGVE7dPOKtTwBnyTVa/7lVAvKfqkpJVFV+/pKuqzrLqI/UFX/wmlfGgyRJ4mZCC1coHs+DLQRyDsKh08/7Jed0DsJuvg300/jaJ+dFxWDHPVE+O/TKVWymszIxDt8zfKxuwlt78SvaAAw4AgI5/YCZmNWTbMQkkQDpgA7CsDFfHJwzWJKiWADVt3DcA06ogjULZB72YDwbMiKIV4cf6FZzbUQGcVZCZXR+rQbksFBwGaUCtSFfXgIotyjAnmu8BSpfkwwdxDMIGpmUgdepgtGFlvHIcZKwat1/uportsf55/Q/BkkKO7cagyiVfZ1lYOQWiFY9Or+xQULJVbc6cOejr68MHP/hB/P3f/z3GjBlTWqaGbMSiz8RSE0Fh6mDLJD8GWA7TJLiWwZj31/GLQLVdmIZAGoNtAmBFeIag6aTLffC6J0LXT0uZVFlVvYYsVdWWvok8UI9Uvxj+9aDq+rgKjV7V5TpseQm2HMQBZajFNgh8Ywo4VHfeL1nhCtAW4Cu2x8uRtqT6abYH70B6UOVyOHNww83n6U4bJK092nY+Jrtp0yZMmjTJrvPfDweA2bNn49FHHxXLP/jgg5g8eXJye8888wymTJmCV199FWeddRbOP/98XHnllaXlashWtcC1TlJ6WloWoCkClud76wyuAtShGFglWHYI1WSgpsKUg5T5SQCV4OkkOWUIXFlfVSTPqyeS5vuUukQt9Sc8ykAsKtNA/SJ0uZ8HXAJPoFDiDlRNbvZP0X4JILb+QRiG/gsK2MKI1iUBOAT8oowPSgbGYic44C22ifaHp6dDt5LK5cAlaaLKBauL50H2SbWBDsPFY8eOLf2BgBUrVnTUBrUpU6YAAMaMGYOzzz4bZ555ZlK5GrLU6B1pmWsIKjyNATWYR9claDr16HIQQ8jPy4aAXKQJALT52ksr+i/kpcA0BFIOUUF9Fr4+IEPQdNPToCut036ErNElJQukves11loIwklAFfy0B894ugtbZfvLYVyANQDhGICrwNeDnamnyA+B1ElnZXh7XhkGXs3KpUDXgDEKbHI9U/k6v25xlWt9Q9BlZe3m80Oo5LDXAPqGUbj45ZdfxqhRo7Dddtuh1Wrhuuuuw8yZM5PKbnWQdUIhXa+8WPTq53ntANbAFTyd1AG2ziBWFnYGr68Mqk59YaBKyrQMpiGQcoj663G4OvlkczgQUyDbiBxH3QoVU0sJG7cCzVaBLAc6r7I94KpgfgEL5aYjh3AMwCzk7MC3FLqkXCJ8k8d88xVJ9XogzU0pvw4RukLb1scAnNRBQRlTubZKCbq0XyBlpeMt4fo6MAQe4Vm2bBk+//nP4+WXX8bNN9+Mr33ta7j11lsxc+ZMXHXVVXjuuedwySWX4LHHHsPChQuhlEJ/fz9mzZqFyy+/PKmNrQ6yxhQ9wDo0Dku6HA0FS+llgPUAigKu8MuI7Qr5SWANKVUBtErIVw5gi/wqMOWgjEHUZFF4hlRsQ6inyEuBbTlQ2z3cUlEdU7ohwHowFYEbrov70/p0xF8GbXZ1t8ykvgJ8AQ4XdgetOZzzgingJfVoR0WbdhVZ17AuEni9srrc12yfksoz4NrtUi4sOahzeJaGleHm8fCx6QP1tZZ4sGqoIaFkTz75ZJx88sli3llnnWWXDznkEPzud79rq42tFrJAF0AbKCuqWBXw4SA2eSHAShAG8wcs3IJwdcBYAlYBohy0Qaja5aKsMnkgaQ5Ai/JlapWDlOc3WDnqG00nu4ADNATUFOVaNXxc5efAUkEaS+e9K4OwA1WyTMGsGSBjIOYQ1lpVhq8LGV0AyKlYCYqU/PdC1LDlstWK4I2oXeUpZKZ0864ougnu6cNuMlg9AVC7bbrpEnSdciGwVrieDoVHeAbDtmrIAgJozUGN/I4zddaKBFZmYpiY+lMoBgDrhYu9slr2qwJXnhYDayD8G4OqC9FiWUqLwTQEUgmiDVYPTQtBl+dJgGwEbt17ESrmVhY6Dr0bVoKrCFwHmhG4htKF8gVoXR8O4Bh8JeVbCbwWgoRakuI1/x3AMrjm6jFbDYA3Fbq2jJb9yI52gJv7+iFj7fQ9qmaFdNOuNX6ttJ0hi4mHvcbwGpPtxAYdsueddx5uueUWPPPMM3jkkUew//77ez533nknvvCFL2Djxo1oNBr4yEc+gn/4h3+AUgqrVq3Cnnvu6ZS74YYbMG3atMHcjCQrFSEiVOmyOwZbCbAelDWBZg5XWh/1sfWSMnm+CFYLudzHuKvizDdKNaRSHcjm5RuOTwFUD5wBkHKIShB2lgkuQgo3Zd3JSw72VrOyl6tXUa9lgOXtUf8yqNJlzdeZTwzAMfiGVG818DKJVqZ4Q2kKMngpdE39FLB5Wz50NQsPM5/ceFjZV6oucMG3n9QnqtkQeEHygfJrHrGBtgdQhpcNOmQ//vGP44ILLsD73//+oM/48eNx7bXXYo899sAbb7yBI444Atdeey0++clPAgDGjRuHhx56qGt96jhsbCsKpHVat2LLVQDL4AoQwKbAlYZr8/RSxSqoVa5UU6BKFaoEyhhMJZAa4JXCNgDehmqBm6huK6pY7l8lRJxSRgarH6rj4I6p11gY2dTT0srz5Yo1BmBJ/UrKl4I3pHjN87gGygpwwGvqcIGW/3HUKAc3hVcgDQS6LKRbKN2s0mDI2PpHfMw2SMB10jSZVaxkNev0EcX1gV8r7Y6DZ9HTQCv0tbaOQOqgb+Vhhx1W6kOnRo8ePRoHHnggnnrqqV52yzV6UHWrSgo+kGUVWhbCxB0CVoQrqYvDlY+zKvu/SK8KVhr+laDqQDQAVAm4ZSCVQsPG18AzFhoOgTfkX6T7YO6WlY1pBdUsFICBqG8csEW7ZQpXBGwAwhSsEnwdsAbAS8vF1S488GYrJD9fV9AOoLRWOaQ1KWPySadDaVTpEug6Y7plIWMNL6ycAly/Hhf6jspVrovjx3wcK3ZL0DTqn7obMrZ+/Xpcf/31+NnPfmbTXnnlFRx88MEYGBjAsccei8WLF6PZTIzvBw6MbqnZrihiqc5eAFaCa57nKVcD14BqlULBkmINgVVSocZfymsoHQUqhy4HaUzp+vkuKJscwIGQcDefkZWtAGVUyQYuZgMeSBtsneXbegaCqraApA9iDlBPqRI/X8W6AA0pXhpqTle7moC2WM5AmvnbR2vgw67wNQkutB2QhdSvghxatnUaRRsBLmkzBFxn3BXw/SToKuJrvmp+vaSHeuI1sK9Vj8ludnvllVdwzDHH4IILLsCsWbMAABMnTsTatWsxYcIEvPTSSzjhhBNw2WWX4YILLvDKL1myBEuWLLHrA31vZgv2bKnQmdBdWzeNAJJCM+bXVcB2AFdpjLUqWI0vSJkQVMuAGlKwhY8LX8CFZ7vA5WUl61TdpszKTAWrW99Avh6Cq1veASlNz5VyTNmashJYHWhWBG8v1K43tqt05RBzUOlS6Jo7aGX6UQBPBC5ggdqOwnXSNIEoBWju4IgQAl6TV/XaqKGGxHOyg2FDFrIbN27EUUcdhblz5zrvoxw1ahQmTJgAANhpp51w+umn49/+7d9EyPJ3WW4zdpzrwA4O90DK8irNMG7HKCQFE1VsKL+HgO0ErtL4ahWw8rAwBSZVqDGgGj8JpNWA6wJSUqtNhCE6mG+ACl3EUsZoOaRluBYglUAsQbiAZstN16oUvFTxtrRCk6eXqF2jWkXoKk2gW6hZup75m3CxDkKXq1dH6VLgccDydWXqDwE3q0hUuPT6xYBs289N5X/ECVACjOlgq3PNpFZybALtzT0YjjYkIbtp0yYcddRR+NCHPoSLLrrIyduwYQPGjx+PkSNH4s0338SNN96Y/Hor0dq4Cys15R5j3rFUAay8nAdTp0xFwDbQEVwBH7YSXClYYfJRgDEEVg7OGFRjQA3B1M8v4EhhSKFZNrN4sADLLXbBSoUtX6flfF8XiIAEYh/CHMA0vwy8bjqBZEDt2vUcoO1Dt1zpxqDrKs3cP6ZyCRRhZgWXApcoXAm48IHr9c30VwRrsS3WgoDljrLVj/D0yM455xzcfPPNWL9+PY444giMHTsWTzzxBM444wzMnTsXc+fOxeWXX457770Xr776Km666SYAwHHHHYfFixfjV7/6FS6++GI0m0309/fj8MMPx+LFi7vWv+CdmbEqUHYAV35zZ0Ep1OOlUlArN30wAFsVrtLkJQpSClbqI4HVVbIuVCWghmBqfCSIpkK2yZVtJFTMfXthoZeuh8PH8XHYEGjpsvGRJkeF4dry8svAS0PNMbXbe+hqEbp0TBc6P95z2BavS6RA9lWuN5Yrrhvi5cC1EM0boS+3iABX8gEQhK6XJ12qEq+PdP9v6aZ08EcmtzzbZuw4/MXJF8uZkvI0d3RKuT4UcIADO83+e2m8vFluFJC1/g3iA5qm3XpJmgNZc33kgM2XVUNXBmyj0XImOFFg8hnCzUYBMwPhGFylUHAqWMugyoEag6n1pcqWXVFieTyfW69mHMfGaiX4SuAdCMwc9vLyg1mCcAzAFL4xVUvzXOhKcG2UKl0x7GzgSvrPx3TbmUglP0YESDOXi7zCF9bXNGLgWZTx1kma8nyKeuzh7gCXpHE/J71I8o6cEoq8ccUS5xdzxu66HU65/WPxQiV2y9zlpb/CMxRsSIaLe2mlSpVaflfWy3FZCmvHeBrzS1KxQBCwUOmAbTR0R+o1Fa4h1ZoK1lSopsA0BFEnnU+CEq40MaBK/u3aABSgBoL5EoCllwFQP0/lknNgQAwXu7AcQAMj0MqVYJ6uBiqCt+WpXVufhWcrCbqalaNjui2t0FTaApTnGYXayu9dLUxJmVSVqw0IlbZ9SlK4ef0OYJ3ZwKpQt3ma91iQAFJ/8hMLK5ubanK4di7Niu9nS7etDrJAALQkzJEM4sTQSGVjdXrHswdg7abFwG1AyvzjCrY6YJtM5ZbBFSjgKMGVqlM5zQVrClQ5UEXA0slQ5JsIpfM8arHxWsmkMdzQhWlkoA6rNBV/LrbhlLHAVQNFPilDgWzyuOq1aapIA2T4mnUJvC3dAFTLg24DSkzn0G3lBDB1mZsD057SCk2Vq1yW1yBgztinHeAWywDy0LLiwFV0olQBvWIyVVbWhpUF4HoTp4jytMCtEk5WkCdM5WWVNv4mLa+C9kMV/vT6YsqKFoCxBtBfj8lu2VZJ0RrrFVRpE5KCddbdmI3jb1QsL69IOQNYqmJNOuQQcRlgm43O1WsMrnxSU5OUM+kxsMagKgG1SaBvLAzY+GzjGFjbGqNNPP4M2EbCV7cDaDjQbWnFgMvzCyBTxWzUJgcwbZ/DtwWFkSDrWomKNwW6La3Qyve3HdPNy0sqt4WiD1zlNuCCWuVAlVSuUYc696Mql+YZ4Jr1VOBqwBnDLeBJJk056haFT0DdZi4FlGPAzfKLaou6TFkqaQPXUZMYOV6lx8m2RNtqIQu0CdoulC0qESqN5HOgRuvi9Qnq1nuDU16m14Ad0WiVwhVww8Icrly18nUJrB5kA1CVIeu/FYqm03qpNQTISs/WhiwE6bJnDB0Vyg5UA8yWVbnGzwUzVcEGSiO99Eaeptw0NWDTuPKl4G0pAbqqgG4LhdJtaYURKgcsg2tM5RZqlYSVbT0ucJUAXKNeGxy4SkeA6+a1AFHhuusGnNm2GeAadat1fs62pW7zirIuZvA3NwUKoMC14JRCxY6ihX9N0XwhYBror19GsRXaICjVti3WLw5fb7044KmKLRKJioUPVloVDxEb/zLANhstBtNy9ZqiXCW4loG1DKoSUE2aO1YbfzGFBMhujdFKCtUYH2sdyY4d/vIJA00DZgMpB8YExCMx4AGYwreVb4eFbw5es+2mffPdtKCKZQLdVg6FATTQyAcpMwjnvlqhAVfltnQjB3Gmch3ggoeHNVkuDyt3Clw5pGzGaflYbgHcmLo1/uXqNney1EYRTgbCwM3znFAxSJvUKggPjfCM9y3NtnrIdkWRDrK5ijZyYU5Qys5PzSl3rFZ+4YQ/BmuaSgoRdwDYduFKYRoDawyqDUex+n7GYmO1tD7JJNXbjnlKlRsbT82gWXzxIxWbAEVD5XkfR5L6LaQNfInybRDwxqBrlS1MOW3VpAvYHLjIJ0ox4HKFWwW4xSxmGbgNo8zbAK7WsFA3wG0hZ5+iL7/IQ8KqAK1Vt1oVDDRKk4y5UnWrjZOCC1u6DlMRPOCaftJ1C+p82bkOEdWbZqpWslu7Wfi2o243kyJ2xmNjoWcFT6E6rjyfqFSaRoEKYFABS6FooCrBlcI0BtYUqLrPy8ow9Z+blcLFoYlR6Uo2zYxS9Q/GkQoMtAzKBMQUwhTABr4ZIFW+DS54C7Vq9qsP3Rb7XrLwr6xyOXBpWLmbCpcDVwwpowCuAZIBbiH8ChVbgBeuugWccLIBq2LrNL3tUDJQANdkCsClIeUiZEyg6wAW4Zv9yCFdzy6uzbHUx3iGpDKOKV+2rhLWG6Q+GiamJr21yfh3C7CSepWUaztw5WCVoBoDKs8TH+/p9qSogDUCz8/y8PYAV+UEuk34ytbZXjTEvBh0B/IWLGQNuEjEoQy4rTykKyncDLYQFW4BSe2+CAOKQVUXk6ZQQNXkG+BSSCuibgHDQTdkTNWtzlUwH7vNFK12Qsn2Wdz8/PJgCxe20Hm0ShPYUjVrFTFIONlUWPyToGu237uHo4dV4FqoAfQnvIN7S7AastxSVGjIx7nr84/XnlqojUg4WZrwVOS560alhtZNmSBUyYUT8B/FaRewfKawpF5DcE0Fq6RUQ0D1Hufxxm0FZRu53e/Gjwk0A8/PelBlFz0KYepr4GsBStrw4RqGrqRyTX9TgWvg1tC6eGQoB26xXihTA1z+aBCHsH1rlIVqoZJD4WStFRpKR9WtiTZRdWsEJlW3FLZF6NiHbXah8WFLQVqAHQVsQ3ANpZlrAVOwTvRMCz4Rq5XsVmSbTX2mAL2Llvo+DQ+eJfkcrMbHha3/9ia/ju4A1ley7oQpwCjfNLjGwOo82hMBajefpS0LK9PwcEgRD4DqVB/GA1C2LwO68G2h8BsgcLR58KGb1Z212UQWWs6+lwK4WX8GgsC1yyqvD9n3TsdwW0rlfR3I1WyunnPgDqCBRj5ebPvMlKwBrhRObhmIGnWrGw5UJXXbIsrVwNaM31J1WzxGpH3Y5vs+BFvAh62GUbChcdusjC6DK+CGmUHyvAsDKlkN2dqSzR6XgWNmUCA+SMBusDZ4k0a1OmlSqJRBte3+CAoWqAbYVLhK0ExWtF74uDycHCpbZqEgHJ3M1AQDKmmDApjCVwKvgS7No9CFLvLLgDtA8qCzSAMNKWd1kOUcuAM6h6dRt8hCyFI4uVjP1a0FpQFrppYbMO9AbqGhCGxhQFuM3Zr9QMPMFqy2HlSCbYuGgxlsATmM7MFW55Ow6LgttIVtEUrOws+uCkZxYaPpIHkAgodtyQWvDhfX1n1LCkOraHjXmAPtsjIkX5uTqkcWUqheWgwoFVQsf5lE1p6rZk0fugXYKnANvbQi9fWL3Z4IxZWqbTv/byDcJBOdzLZZ2BkfAlYKXAAADc+j4SlcCbjQ2Y1S5tty1W1+gbftq5a7nMMWBLYWvLm6zaCdwTYDmVG7/thtBn4SSobK+m1CySwsbF56wWFrYNwObAu4CrBV5vGfdNjax/Y0nyRFQsmAH0621xkCVefaww4yK7tLjl2i/Ld02/og26ni4+Ur1CcpWp7mAhTs7rGs/uINMw58BzksbUwCbNi3eE1i9XZ8sALCYzkVAJuiXsW8AFipD/fjebE0bmX7OHQha+Zq0EkjL5CgQM1ryn1axTOyicC16Rai+cxmsw80PHULBVsOSoZtKJRMYQsGWwtXmPAwXW8VsOUq1vSJwBYacdi6M4Q82LaQHYcUtg2l0cr3Pxy4mmMvn1yVQ9nAFjmMQ7DNwsEubPkEKHfsloWTU9VshetMf2vzK9kLL7wQN910E7bZZhuMGjUKX/va13D44YeLvr/5zW+wcOFCvPbaa5g8eTKWLVuGiRMnlrax9UG2gg3aWG0M3GS5MoCl9JCyddKVN+6aYuYiEVofDAvB1lkX+hSaMczzQ8oWkAEbCxvzPFnhhvdfCoSbyoeprRvagzCFbwi6RulKwKXghC0ppCt46rbIK4etbdspnwBbZCFhq2y7BFsokDByVqYIRZPZyvk+pmO2BqpW+SJTq0UoGvlLMdjkKAZb83ILgI7f5jtbgG3WbVWM1ZLwsPOSC8C7biSp2YhpDI0x2dmzZ+Oiiy7Ctttui4cffhhz5szBunXrMHr0aMdPa42TTjoJ11xzDebMmYOvf/3rWLRoEa699trSNmrI5hYFareVILmZDLZB4Qpy3IYUqiaOZcD1ThIfuhS09JzJfoWElGHNtAva2CzYXpoUpi0LEYuvTyQhUmOpPyjgg7hNVct8jGKKlmXHSvaShYA/meVb+LTcetqArS3n5WUwNH4UtplfK1DeDyPzvKaCG0ZGUWexTkCZw9aM2bYsXKS0fIvNSzl08cYsC2IADXoeEqhm+zg/b1io2IzXAige+yHnsAvXbMcpq0hd2JrLhc7LGWD6wDXlYNso3k1MwFs0mWSh3z4eTPvwhz9sl2fMmIGBgQG88MILmDRpkuN3//33Y9SoUZgzZw4AYOHChZgwYQL6+vowcmTo5zky2zohWwbNRKh2rHRZO+2EjkUf7mtPLlmtOu40PS+ryAXA5JlxJLMMFAqxBfdCnU1IAVv3L+QDXVK+9G1CvTQpRCxZ8MUVJXCVn61N3z9lvvx7AuAcjxS4A9SXbq+9UHYBtlIZClTrZ8o0WDopz+qiIWo3XE2BTY7SfJ2D0ijYTA0jmGZgavaNFEJ2VC0JIVNVGw4hZze8ZI9GJ0dJsM3f65FHjYm6jQAXxJd+f95cj4QLY6dKdtOmTQ4MFy1ahEWLFrVd3w9+8ANMmzbNAywArF69Grvvvrtd33777bH99ttj3bp1mDJlSrTerROybZrzQoqIYqScIzeUsnkKNv9dyUpwJXeyJeOy2YlV3Jmak0rnd7YgJ6KSgMxATSc4xPKyUGMxRtoyFyU2bmpCe0B+kYu8o5dby15EXXAM5JNp7Lpzg+AD2UzXqdJup1AvA2wMmFXGsumPBdA6uerNZu+SevNFCls6w9eEmZsR2GZjomZcVhch5zydljF1U6AOaGX9BnT+nSaq2mI7GvlEphbLa8igzds2qrbYtmqq1uzlTlUtDSHTWcjapJtx1cB4bRC25oKSHx/2eV4STrMhZKJqHfBSSzgmBzockx07dmzpj7bPnj0bjz76qJj34IMPYvLkyQCA//iP/8CXv/xl3HHHHcG6FLuT0DrtvKsh202LKGB6Mygdj+aYF+vicCWQhCmXvKzczgCIhYyzExR2DCV7P2sRMqazKOndu3snDwZXCGAFAD9kXDwSYVRLo1AqTLFIcM1mrdK2CoBS+DpKzZTXjXzsL8szZXl6ty0VsO1MFPPe8mS+DxRRCNoHOyabf59c2VoYAva7sJOg0HAgLKlaDtrskaCWA9oWASoFrakra0cDumjTBXVD7KeveKky9lWtVesWlC37rGxxPlFoQ7geuKAlqS5oTZpZpucVYEFrf8DADmkQfyeEHIatyTdvkbKhZHpdAFiYON8VFLx2f/Ft9k1D+WDuga1YsaLU56677sJpp52GW2+9Ffvss4/oM2XKFKxatcqub9y4ERs3bkya+LT5g+JbiFW+3mmhDE8j6ypfp3li26F+kAPavF4t+w1L2AmGOr+TLWYo5ne1WonLLe2eKHS9hWJyhlm3E0fsusqfcyzqGNDK8TU/cZYSWhrIy5n/tF8DaJCfWnPbpL+LSn2y/hR50XS7XrTL82ha2XaUWbszscvqyZ4RLdLccWU/PTYruuzxKCmNjntLr8M0/XX9TDvujPHQe6ul3xMunrcu+k7fye2um8fHzONmLft8eJP6qOJNZqYe83y42c/0BS3K+IOlUZ+8HsXLqQx0jUbL+1Us+zOVCva95MbPTcvXG9mFR1kfbcPK5odEzEc1aB35p+F/PNPAQEt19OmG/fKXv8SnPvUp3HzzzTjggAOCfgcddBDeeOMNLF++HABw9dVX49hjjy0djwU2A2TPO+88TJ06FUop/P73vw/6fe9738Nee+2FadOm4cwzz0R/f7/Nu+222zB9+nTsueeemDdvHjZt2lS9I51cowQ4dlSXV58Kg5OCl5bVyi7bH2TWJN35KFuXhaRWRVUeYItuFO90hYVoKy9LX6JuXtpeth6CbouBEoAFrvm1Fuc/gR4FLf3xbwm05nnMboPWtBsD7QAUyXdvJJwfQheg280fvC4Ddgi0PL/6SzNk+LrvRPbr5qDN/DYfaO32lIDW/RRtctAqlQbaJgVqDloDW8X8w2D105x1AbhOvaBlXAA7H8HMyz3a/XTDFixYgDfffBOnnXYaDjzwQBx44IF45JFHAABXXXUVLr744ux7ajSwbNky/M3f/A323ntv/PSnP8Vll12W1IbSqYHlLtkvf/lL7LHHHnj/+9+P2267Dfvvv7/n8/TTT+N973sfHnzwQUyYMAEf+chH8Nd//ddYuHAhNm3ahGnTpuGuu+7C9OnTce6552L77bfHV7/61dK2txk7Dvt/8uIigX1PznVLyWl2TFYxH1X8L3xZer5sr7dCHhomTRflG8QHrg/Nz8rrwtcsg6br7NYqP5HM3SjYSQZ6Z2uX8x9qpxcDBedkb7ILwwjVck7MEfTOn6VJ7zAeoQacC1zKiynoc7Mpb36SXqtY9aUUXnpktrH4YwMlitHmScqxBJIpxqHNL2IO9LXy0vwbDeNDIwqNIp3fyITSSRkeLchuxqhfcUNl/PjNl7esi8lI3rJWTp1uve6PCjg/MpDfJHo/Hk9vKrXy6ijS3IgQbZvf2Jq6tOcDu+xEnuCna+Lr/nfTaVqREIYdLffm577tjJ9us/MO2G/p3wTLptgLC39QOiY7FGzQlexhhx0mzt6idv311+OjH/0odt11VyilcNZZZ9nnkW6//Xa8+93vxvTp0wEAZ599dtKzSikmXasqX78S/G2dsZAxOUAdxSqVcxRtybJVtso9iYhalcLGxf/iImBOZnqS04uEubDQvP5cdbaYv6tgyboQNo4pWqNquaLt0yOKcrnSzMo10Kebnqo1KtPWiUaufonihXLSB0i5lu2Hq2ppHk0LqVovT7iTH9DKfqqaVC4FsFWNRyV6YdJ7n903fwWW6Q0Ou9lxf96QqVam3HmdksqN1cEVranHpAEQlWQofGz8qQKV1KevYt10eoPd4OHhRli9qkbLfiTjP+FX9TNcbEhOfOLTpadOnYrVq1cH85599lm0Wi00Gl08kTWESQuIzjBWOnpjF28rr0qbBVOfrTzLNM/BZetZolnM/HNHDeTzlMFqdyvVWYKGAloaqpHPTtZOQ2i1Gmg0WgAUndoBABjIZ2I0YH7BtMjvbzUwotFCQxdTQlrKyO8spT+fkZkdjC3S1Qb6ADSR/6yZyh79aeoW0AAGdDHz0jwWZGeNAshmtDZhf8kln3AyoFHMTCW7J5vQZSbYZJNtWkBR1vqR2ceK7Q1bnzvJpgU6A5lNwHHqIUYuJA3lvlQim4hVrBs4dBJGFsPSAcDGVOyWaHwin5OXnWzFJDLFJ/21nH3jTwLMji/7YwcmH8hnDRcRKfMCCjrByYDW+iszOcrcmNGbCLcel1WmzwXQjRotJk+ZdFLKXA4rHHv2Zn4rsCEJWQDOdGke0eZTqUO2ZMkSLFmyxK4PvPWm6xAAaZLxskJdBpIEb3aZMLJYJnUZfJrHeShwDWgtYkkmrTdbZ4/0QDsOuqXyiQk5aLUuyrQaQA5WwJxwWe/LQKtJPgdtfyubkWmhmls/GmhoBTQGHNAW4C0e7UErvxhFZh2bWcCwF7HswtO0F8X8mV2lySMhLmzN92FgO6Cb+azarG4D3AGYVw5m+Tw9q4c+ApLtpyY4jANjm/zOvcJxK4WYy8a0+OSrKoDloWIvhFwhVBzsn3CBpqHpot/dB7+ZOS0ZB2pTaQe+0PBhavLz45LPJNY64E/WKWizuug85yzi5PxUJSnnh9P4hU0y6fipJi87fYRnuNiQhCyfLv3MM8/YB36nTJmCO++80+atWrUKu+22m6hi+cPJ24wd15P+egqWEjXVuJql5SWlS9O0W061VDYey9cNgVs6myEhgbalgIYM2lYLaDRMh+KgpZgwoDUhM1fBZip1RGPAblB/q4mWImOqWpH1zN8o2aZuWYUrqdqWbqKhG2jl474ctuaxnEy1Nu1jPQNowPzsWvaYifbUbbvANeWAQuGWAdd7XKgD6FKLzWTmyk2Ca+bXEPLjgPX6UTbZTJi9zcu6fY0Dt1vw5VB18li0wS0XVrscpkrp/AZV+SpXAi1Ru8VyXNVmDfkKNgRc18ek5V6JCnU4hXw7sSF5KzFv3jzcdNNNeP7556G1xlVXXYUTTzwRAHDUUUfhvvvuw2OPPQYAuPLKK21er4yOoXrG0kJjuHZcVRfL0bFZW0Y5Za0/SFo+pur42bFX9kGe13J9NCmjW6p4zAeAbjXsmGyrpdCi6/mYnhmjzabXN5y8frJuxlIHWg30t4oJIf2tJvrztH6df1pNeZw295fGavt0E32tZvZfN+14bZY+Iksz687yiKK8zmD7lh6BgXw816S/lef16RH5WG9Wx1t5W316RD7Om5V9y7SRTdfK6xqBt2xdWft03PgtNPEW3Dza1gAU3gIZN4ZCnzjOnX36tOtLP6Ey2f4MfwCgGHcu0ugYdEzBtuCOe5t06heb8GT8B1geBZcMfx8A7luY5PC4q+Srwzo289oZp2UXlFCeM25Lx2xJGT5Om/nC5oVmC/N8f+w2NIZrxm1bXppnOruOdPIZLjboSvacc87BzTffjPXr1+OII47A2LFj8cQTT+CMM87A3LlzMXfuXOyxxx748pe/jPe9731otVo4/PDDsWDBAgDZ66yuueYaHHvssejv78eMGTOwdOnSrvXPUaWBcLIzLktNCCE76rPMBDWbFDbWsGOxNqDbAjRRq466lRRtS2X1U0WryBhtqwE7Mzkfo81OqKzKAQDK3Fk3WkCer81JlitZrbLf7jThY6tw87vths4U64hGK1nVOmO1gKhsgUJZNMxFXbWcO/xiuRhzbRF4AMiVbKEuszQDibL0YiaypHKzMqasdlSuaXtAN0l+ZlTtwvq6F7a2JkV5IeNGMJ+DleZziMbyugFYPqvY1OPVyWYT274520CB2ma4gFlM4Tp+RO1S5ViWzhUtHafN2vdVbZaembOdIdWQZYZz2LitZFuJkB38R3g2p3mP8Bhjx4pzLimWZtdVsU59+LIqT6d1i+UUoBs6nOf8125ao0gz9bi3rPk6SS9mDObjOHmaglnX3qzDbL1lT3D7uE/DfaRHARhBHvkxIWT7yE8jf1CfPebDH+2R1/1nHN3nJovHfQD4y+QxHP4CBfpIDm3DlAXo4zxufjd+q7abv1NbZiF1JkGVl3F8egRX178AbEhBhwCb1afkZQfYSmijqK8Atf8YTyydziKX6uP5/LEeWk4LdWmWz/2zdTjrfJkClx9dsbAwz3vl3Gucx21Gvm1HvPPqzwXLp9hrn716WDzCMyTHZIeiWYWbq9XgLOMKataoUiMsHV+4y/adxkKeQq5oG2mKNoNwrkpNw3k6GkbF5ko5B6xJ08gUKxottFoqDxuZdxs37IxFq2rRglYqqmoNRLXO7r4z0Baq1gGto2Td9eynzjI/qm77UYwHu5NK8mWjLHQzL9vKllUrn93sqlxo5HlNNNFCn2464O3TRq2qPK2a0gWaFq4FMChMTXntAowBlSrfTiwE1CLfBysQntjk5HUBru56UZ8EW1MHV7ApgC22362P9pP7dtMk1UpVbSzNUbS6eBc5V7X8PeV8zNftUPv6TCN97Ha4Ww3ZTo1AlYaabVg3BFyeV2ImJBwErYJ9xaoEWig2GQoKumUGd0lNeZjY+Gd+uYsQPtY5jBsNoNUCgy6AViOHKyxs0WjZu2wRtgOKKNty2EIDTZW/mJ2FkvuRwbIMuH26aZWtXSZh5Sh0UahPKbxsoNuHZuanm2gqnddlIN0CQCdE8RAzvYgL4FUuUDmAjaUo2xQla9MEcHLf2KzhXsCVr0vq1ax7sI0A1k2jcPahS1WsTSuBSieTsThEgeKslkBr+lOkmX77sAX8yTsidEGvR+UAbnXp1YhD3WrICpYyLutZSM2yYVBbP0g6zY+oWYPOUtCqbMWqUJOfj7vaUHCD1aTzPDZOS1Vt1kGmavPxHgpYA1XdaFlVa2Grm3kouQS2urgzb6gCjm4omcNVA7rhhpPzztqyyL4AG/rV7jhXCLpG6faBhHxtmwbCOSgT1W4qeI0/ICvePjJj2fVxrZl0MOd1BC76HN5lSpanR9/3PEhw5et+vQVgpRCxKc8By8PENI+22YnatXMLyDHr+ZDxWQ5aAKKqNbDlj/tw4FJQUwuBN2i1kt2KLBGkwZBxTM0S2FogSgA2/7sBWlpvS9lx1Qy6ROO2Mija8LFRta0CpFbVKtJvkm5hO6Dy95u6sNW6kfUpAls6ZtsMwdYZny3ULQAPuPZNOkThmosCHcO1KlcV0KX1ZeByx3MBiOAFXPACQDPvYy/Am5Vx4dsHOp7bdPpkjMO4zEKP+HAAlwEV4JOiXMVK6+gErM56h3Dl6S2vfDpg5XBzGLhVIBwKCYdAC7jK17THQ8hZehy4NF0Cb9A07A8ebelWQ7abFlOzTMVSZUuhWgpaXShVAzvdyIdHFLJlDlr6lyndUlXLYQuiahlseQhZgi2FJQ8jU7gqFLALTZKy6paEk2HLFQo3S8vhqhX6rU8xjgsUStco2yaK8LJJAwoFbEELGby9VLxAEVIu4JuVohClELZp+f+U38yVQs7GOGjLgJqVCUOV+nLI0To7gasUFqbr4fS4enXbC+eHAMsB3i2TQGvaTZuxjNwfNo8afQtUVavHZLdyKw0Zp6hZA0pOS8CFKINqELQGpKQqDQXVKn7kXbVgIQdksHXCx1TVUthCy6qWwzaLxrohZAN7pfI68pnIgrI1UG2p4ie0+GxkM0HK/Lh6Q2kMIPshAgBR4AIkLKyogpUUbYP4F+kArNqlaRyyPM1ZN2V0sR5TvHw9BN4sX5jVbB7tyZUv7VNfnuePx7Y/KUoaP+QTpCSgZulhqLppLkSltCqqlbbTCVxNehW4Sm31ErBSKJleS0LhY9MvPzzs1h+CbhXT9ZhsbZI58JXMwrckbMwhSn3BfAxcjQ8E0ErhY52HhzVZdrQt8bcTngIhZApb2h+jnAlsbRi5lQWeisd+FHnsh6hcoAgl6+IF53RGckNptAaaztgtEAJudidAx3Cpb7bcIBAlj+yUgLfI88FL1/mjQ47qJeA19VkFbCZXCeA160H45srX1N2XQ9QqVjoxqoOLI+AC1Jg3VpvwvGlMqUpp7oze3oOVbqv7xqjuApZayDdF+UlvYpImQ3npTNXSdjlwMx+/7VbVQ6qzQ3DYWA1ZY5JaLcsPqVkKWvjLQdDmRqqQx3SJjxg+ViaNhof9UHFQ1abCNu+Etu1r+9+M/xZFsvQB7apa+pxtSN3aH6QmwDW7RQopA3CgCzQdGGfluBptsnxZ8fI8oFz10n7ytKx8HqKGO+5r8yDDlq7TtCy9RdLdqxmFccjsJKuEGa/yKwxV0Ed6YUUovQpUnbSKYKVtpYKTK1vJJz4W6/c/aby2R4qXqlqTx/sQChdn/lVb7952DGWrIRuxkGqV0kOgBSBCNxm0VDUa1mm4IHXKZKrW8zHLqBBCrgLbfNkoWjMubOrUth7+Uov2gQvAgW5DSJehCy+8nKX5YeBGVNn68JVULy3DFS79L06yElSvs+6A1VW7WZ3aHiDGt4+FiaWfiOvT5aHk0Evy5VByHKZeuvg4TDhNHsPtHlhjPk5bFeCa6g8UMAu99lEyPmNeUrM8D/DVML1J80LQCRGRoAKvJz7V5hkBpwVtROF6Y7IUtLkxDttlKY+O7dIThYLYgWc7sAXML8JZgBrgKgtUA1xVdFK5n6C67QJwAYjQVQRa1JfncfAW6Q27bPKzdVn1uj4GsE0BsFQVdwZfwFW+dp3U6aTRcVjdvbdCcUt9ttZ7kYUAnFD6gAC1FKi6eZL67Q5YpT5IbdMykh9fLgOs5FtmKaCV6pRmEJfBPgjixL4Od6sh2w2zABXeaRwCrUNJyKHlIltWtXQdksqtCFsotzEB3B2rWwvirPPtABe5nwEpfQl5TOkCvtrlaQZUXPUaP+PDw8ISfGPKNzbea9Jj471SOp1F3CBhZCedQdaMBXfbpDCz92PwAcDSvPD4rQ+pdqHq+LfhFwOrV74NuIbaK7NS+MEHrVSOh5G5SeBNsfoRnq3RBFVqgSj4OHkctFSO6qJaJ5kd5Yy7xXgnCFDpsgRbJcPWVqq0D1ubFw4lF+UVaasNdQsFNLLfrlWsPzHgAhChOwCyDlnpmnUOXrufUQ2+Ji/kIwFYUr7Gt13lC/iglfJ4fpOpW1p/Ny00dug9YxsAJc+TZyDHYRYbNy3zo74pKrKsL6llQ3CNleHlJCubcUz9pPpj47GVTSt2Yd1yrYZshxYFLUmTVCwHLxCAMWvPwtb4hmArwtdAUTtqVlS3gAPV8OM/qAZcTfqdEFK2xZnKtd2LQBdww8UcvDyfwpcrRxGwInyboo8M39i4bvmEKzffB24ItJL6kMZmu2Upk6Pik6XKAVYFlIMF1dTyQDpcy8qGLFUBG5OgTK2Tx3cAoAujFMPCasgmWEzNevkEtACCs46NK0hVmpan1RGw0jYt8ALKNmu/UK3uOgWgD1zQMgy4RSiY+hUwLgWu2QmkPAWuUbmmnLL9M3R0lS6gCGxzFwesbD3vRQp8izy/LPcx6zH1602sik668hVu2bivqQtwH9Nxf4s0PPMY6B1sU0CbpTE1G4Aj95UUKi2T4huDYFWlWlYfB2NVsEp1hPxiRu57PYtNeurYaiVbG7V2QJuls/CxLQBH1YJU58CWKlcCawtUVaQ5YCT9KkK1LnALyKUDt6iYAVeozwIXyqlHVLmgZXUBXQDFm6EyMNvdqYqQc1HcB6/tLgEiVb02Le8GDzlnabBp3KdTAEvq1/jIY78ygLP/LoSpD/UrfAsLPTvbrVByOHycANoSIJUpU14mFYYx4JdBsFOohtJCqjUGwW4Asp1JT1GrlWxtpVYGWgBRVUuKB2FL6qaAddQtBzJZttmkPxy47rhsHLh2nW47DSmbzlLg0naZyrXbzuEPkmbLutDNVC9A1a6BqwdemLZNl91lmsbha+rh0JQAHAotUwBXDz/LPqHJV06aAFj6CkbAh2sMqu1OcjEWBUEihGMArjKGmQrTsrLSehlQpTKhtFgouAxyXVefzDo6Hrpz79aRXXjhhbjpppuwzTbbYNSoUfja176Gww8/XPRVSmHGjBloNLJj5YorrsDs2bNL26ghy42Bk5qnZo0/ijLmmAup2izJb4CmaJ5GFS8FqAO6ol3F0rjCVbwBCXIEWAaOUV9F7h0YRD3oOnAl0M3r86BrNpr0i6vhIHjtMumL7Yp20xQFaJ7FAMzT6G7k4ecsDWxdHv816zEAA/AeO5L+G78sLTwxii/Tck5a4oU09ihQ6s+4haCQAqny9aEB0lh6J0BN9fHarFyiO6aGwGsVZ8+ejYsuugjbbrstHn74YcyZMwfr1q3D6NGjRf+7774bY8eOrdRGEmSfeeYZ/PrXv8aHP/xh7LDDDnj22WehtcakSZMqNbYlmAhaQFS1gKtQswz4ypa3Qeq0qpM0Q9sLKVzbNktzYEb7GoB0oU5VAdIAdF1FTDeIQDcQWgYYdEHr1YR6/nZYP/D6CjBq2245fLMsbXeMD9dinaa1o4Cl8LOzDh+iMQD7+a6ylfyL9BZbrwrc7j0KVAVO4qsJ2wjFpqjITkHaKUSr+IVsCAjIrBNDoCMf/vCH7fKMGTMwMDCAF154oatsS4LsvHnzMH36dFx00UX4m7/5G3zhC1/AuHHjsMcee+Daa6/FxIkTu9ah4WCeWjXmSVDBl/go8iyjpG6dqihETUZM4RofCjC4AFUk3UIypHKpj6mIQbdYZvXTdbPAgW3XlddvpeR+uP0zG6gpKR24FmULMPJ8RdajAM7TYwDm6Z0qYLNeNgYslZNUrrMt3KcCYAfz8R+bX2HCT/KEoUSA9kKFtgvOIcCptq3DkYeu2w9+8ANMmzYtCtg5c+agr68PH/zgB/H3f//3GDNmTGm9SZAdGBjAsmXLcM899+D9738/VqxYgUMPPRQ/+tGPcO655+KGG25I3pCVK1fi1FNPxQsvvIBx48bhX//1X7Hffvs5Pj/84Q+xZMkSu7527VocdthhuPHGG7Fq1Srsueee2H///W3+DTfcgGnTpiX3oVtWClvAufbbbAXv7FA0QcN/BMjUoaiPD1YKn5CCpX4idAnAReia/86ygVRA6dJlry7F8nnZAryxCVzabDDNC8A32we+Qg6p3+xfNQCbooMJYLrO6/HyOgghxx7f6HTclloZfKJgC4C6WyHcbkw0GmKcGVzrUJFv2rTJAeKiRYuwaNEix2f27Nl49NFHxfIPPvggJk+eDAD4j//4D3z5y1/GHXfcEWzvmWeewZQpU/Dqq6/irLPOwvnnn48rr7yytJ9JkFVKYf369TjkkEMwadIkHHrooQCA448/Hv/0T/+UUoW1hQsX4swzz8T8+fNx/fXXY8GCBbjnnnscn1NOOQWnnHKKXZ8xYwZOOukkuz5u3Dg89NBDldqtZBROCeYBlNflOMt3cL5bBLq8Hqr6hDS7KgGVlyfritbBwcjq85ezytw6StRu3qZV9YpAG3l5W59y2sz6rhhM2X7wtoHsMAJgnbclAbjoI4q7GAJJerMB62PuQ3wAg6SHwtCuj6xiU0FM05zycK1M1UqQTR+7TfOrou46gnEHsKwCyV5PQmrHunlDVNk6bHrs2LFYu3Zt1GfFihWl9dx111047bTTcOutt2KfffYJ+k2ZMgUAMGbMGJx99tk488wzk/qZBNkvfvGLOPjgg/GRj3wEX/7yl7Fy5UrstddeeOmll7B+/fqkhgBgw4YNeOCBB/Dzn/8cQBaGPvfcc7Fq1SpMnTpVLHPvvffi+eefx9y5c5Pb6YpVBK0xEaC0HunAksCr3XLKPqxK813wKpofgaKnYk0fUALegI/XhpTPwEvByf1k8JJOOj409Ov6ABTuSuxXeFtkAGd1kh0uANjzQQ6lCICtT55eJQwtpud1cgjTZfqrKSFVy2EqAtdLqX7xDvm3C6ZuKckq7Q+1HyFPeVlEaPsGA75D4WUUv/zlL/GpT30KN998Mw444ICg38svv4xRo0Zhu+22Q6vVwnXXXYeZM2cmtZEE2Y997GM4+OCD8ZOf/AR33HEHLr30UtvohAkTcOutt+Lggw/G29/+9mg9a9aswTve8Q6MGJE1q5TClClTsHr16iBkv/e97+FTn/oURo4cadNeeeUVHHzwwRgYGMCxxx6LxYsXo9ns/vtXpbBvOxY7XqXQsVMuAOhMtZIEUg+dUCWBVwQl4CnZUqgyWNuJVnBvEILgzBujoV9R8Qpt2DqY6qV1FOWUuw3ODYTyQW//0zFduq9Mm9rxhdntQti6UxWcpacr4Vi6k4fCQnB1AQzHqijaTt8Q1IlVBWA3VGcn0G13X9F9H2u/rH5p+7sO3iEQK1+wYAHefPNNnHbaaTbtf/7P/4kZM2bgqquuwnPPPYdLLrkEjz32GBYuXAilFPr7+zFr1ixcfvnlSW0kP8IzefJkfOYzn8FnPvMZABnZ7733Xtx77734zne+gzPPPBPr1q0rrUcp98vTOrynX3vtNVx33XW4++67bdrEiROxdu1aTJgwAS+99BJOOOEEXHbZZbjgggu88kuWLHHGdgfeerO0f0Hr9gHBrtNl7fJj3hsrJX4efI0L2fccpuZfWQgZkIHXTqjZa8+mKbvsqk0ZvrzPHL6+H1edyuujNGYd8hFVsGmnIGReht39qEQV7Kyz7bBNpEHYTaMw9fO95cLFu+hKF+742G0wa7NZ5R8e75WREz51PykVfw1iGYAHG7xDQcmuXLkymHfWWWfZ5UMOOQS/+93v2mqj7edkx48fjw996EP40Ic+lFxm8uTJWLt2Lfr7+zFixAhorbFmzRob6+Z2/fXXY99993UmRhn1DAA77bQTTj/9dPzbv/2bCFk+EL7N2HGgim+zWsU+eMcyg6uXLqQpaA/WBTBUsRoCKq+fpNFykmoUfThoIaQpBkPTJw/u2i2T/xfTBAC7/dZemxJgrQrm+VEI052rizQlqGDbX8AJiwt+ylsnbdAu0AMpCl8/zSsf8ZPWaT9CtlnHCDejxQA3oNP8GoG9a8qUQbJb4E0yjY4nPg0XG9SXUUyYMAEzZ87EsmXLMH/+fNxwww2YOnVqMFT8/e9/HwsWLHDSNmzYgPHjx2PkyJF48803ceONNybHxq3x77ab5/VgXSOkdsg1n6fTRQm0ZqIVB16xrLy0IIAT4Ev74YWL8zRPvTNAu2l0xm/hFwOw1yeTRiAs+3YI4fx/EoRpepdBbHxpW+5X7gPZKcN8WJAqCbq83ICY39uTanOEsT28JKpErVWwvy3xRSJxePYCvKk2FJTsYNigv/Hp6quvxvz58/GVr3wFO+ywA5YuXQoAOOOMMzB37lw7wenJJ5/Eb3/7W9x6661O+V/96le4+OKL0Ww20d/fj8MPPxyLFy/urFMKncExoWxbx2VZmcSbBQ9WUlnCiiQIRwCcAt+QXxl8U9WvKe+M+5K8og2yXSX9FyEsANitIwHCgf2TFI528lVezg9JO+lO//zBex6eZovlQLY+gfKSv+BT5h+zav6Rhr16K3WDlHP7I94LMx/zOkkJyMkztBPBS9vm4OVtdTLW61aU7jqcTenYoOgWZtuMHYf9T7pYzqy6F0r8o8daJK8XN9XBc0JID4WT+bKkeOW0MGSobwgo0hgx9wv6SP1LBBmHZqWyCKTTOiu2HwZxIN/2IZIfrFtQp46qJYvBdKGdUBdDB33kZEiBXTuKqypEU9uI+Ultpo5v86Jl4+TyRLVQv2Lj6dX27XNn/E/ncZuRO47DOy/4UqU6uL327ctKH+EZCla/u9iYQjpoq14ThPQqvsllpepUgr/yF2OwtWFYXlaAMD1RfTWqnPVS1Rrw42pSVK28LshlfTWrvDpFFSyWDaRTJczqrKKEpW0tu5lx/ocUMQkpS0rXPRb8MVz7/mjrW2QqL4/nw7dQmFlMpe2UEDMZkNFc216sfCzs6sxTtGnsuHPSyDnF1j0VGut6XpZP9jLQraJ2YxYE8lYi72rIVrVUYErRsy7VFTIlBCUcmJVWIC4GweTllSzzcgoaEOqKAU72Q7Kfc80PpNNtCoW0zZ/yOn0Qe23xOhHxzevkfaBtu31QAkS5L3tUyfGlO0NQrSZETfMDQAYDn3dYUgAH+sAB47XBCkcP/RgYyTL3koBa3DilhcGV0gLEXLBlPn672bgsaZuM03LoDmjlbEvKzzRUGdvlfRPrC5TbWua41ZCtYilQLINr5fzO7wKDdQQLyKserBW7GAlw4uly2FIuQyEcVMG0XBcgbNdLfHjbVZSwW28ChL1081YqUmUHIJb6F/MN3kxJoHF8XWAHFa0AX2MaSgZn4IotXd8LIEiZph3qz+rUwnbabkh1ClAWjiNzmobUrANTzW44CHi9yVEVlK4Mf1/t2vKkzcpWQ7Y2xyoCNjnPSWeF2lTDZaa0fPEJFzD/3MZiCjfLV0VxD6Bu3dGJTLRu6++rs14oYQ4wZ1sifs7mlQFTqLdySNrUayHhdqIrIJZUsQDcpOhGSPmJ/q5vVO0mALgSqFVMyfpt2hyaJozZUBhzxcqPewpfCl4ePqbgDUG3G0qX9rvt54o16tnFtRHrBLBV4BqDapeAK0UOgXahGymvXCiHVW4JiAWIUgUdU4C2/SBcO4dwJ37GBiUkTdalsWG5H9rdHpAIQmAbHf8S2NofdOD50rrT0QiYE9e9U4UfbJGwrxga9trgfVTOYujUVoDdmQ58PcAmADXBh/eVQxeoBt5KVivZ2kKWBL8SuDqqVYf9ktuz+ZFxpshBXcbYMgjzN3nxMiFgchCaPC5QtFJCmuRn+iO05YEhAGGp3SDg5PVO/DwIC32kqtWCWAQZnAtqW2Fp4hcEsVOXAM4YjAO+fLl4BKkKmPOMTsBs4crzfNg6IA60ydWkOIZNoQr44G0DugLOBR94/Q6+31hMTbd6THZrs9AXnqIgebp0vEaUqwzhsjQefmIdSulnBZNOM/fc8y8ovIwPXSXnhWDcCYgjF/l4uHjw1XAIwlJ9oW1xoagS2k8MS/N0AXghEPt5YRh726jyH3mI+PMDTodAJvi6eQGF7YGYQJ+CmB6EwrZnfSN1OuFg19lRvTlYY9At4OpDNzamG4Oud1OQW6fvd67DxbWVWyRkG1Wv3CcFrASqSYo30L/Kk6AiFjrFQrOZ/WRNIOpX6oJUBdKpv6yK/TS3UdlHhnOyGu4hhKv4GevFBC37LxXEQp5bzg2/Kie/GpCzbBX0TwZy6CCXQCz0IQjg2E2J40eOL36yMOhK4WUO3ZTQcpEHtu5eO4r7gTavKbWSrY1bFbXK/ZIAK9apw/5iX1gnuMCM3T1246BXAJ8g5TTBYkz0+ml96DitXSgu8qlADoWTQ+q0CohDYWlne/J+S2VdOA1+SNrZJgTSib84dp4K4ihECEwDIHVhCw/G5l9RfxiuEoyzPgbAavvO2qTA44e7AXAMmhS+0v7SoTyjXJGDtWjeCaZT6HqKlnxXkbHaMvDSdNO3KlYr2dqSoBMdg6WALVOvAeVa7k8apn2gBzAHraRme31XaS4SwonFla93x0zAzKEsT5zSURjnjdj1IIjFcqzPZQATIDGk1HCgv6lK2PVXDpiNlUE42C4HDMxhKgPML+9HNtxlH+qh8l6o2inD2zE7S6pLgDnLc24mDNhISNgBO1O6FrodhpbttpWAl5r0Ao2gMVGxJVsN2UQrHSPlfqmAjcG1DKxmPQDUEICTZktT6zTEXHbWBQe6838D7rqxTAH6F1LdCAGWjtmyCz7x5SB208x699Xw5oQwv0Gw6yV1GSuDcEo/s7xugZg1LoFYUMQxCEcBHPrOaKNu53zwlkLXdefQjanclNCyqVt6XpeDl+ZzS71c1Ep2azLpoAgdKBHfmMqkeTJsfeWaDNdAPl+uNHHKWFd+YDNSR8N/ZMCW4hlc8dJQbJaQ/RsolrN6lPUvg7Ebui0u+CKESJ/kkLD2y/B2WBlpvRcQDipXYVvT+iD7WRPaEdMFNczhVgZaUblKB1lkFjRXwX7EQ/n9SwWv98Xz8gnQLVG5DnDzQqLKtXkGqEV7XO1mXaCqlh1XVa1WsrUZS1OsfL0AnjhmGwKsqHKJGi4Dq6SyOcCNEYCKkI2cBN2aQKUjd7P0Qks75I0lsjecuxfgQu3yCzNXyJIyDoG4WJeVlxSWdvN9FZUSkpbW24FwT0PRDEix0Ll1C2yjn+dD2C1XAcJVAFwG307AmwJdAtN8ui9rx+12lbHcUuiSvsjvVIZnKeOztZKtrW2LKUofpDqoXh1QS3ANgl6AZ0sALTsPyiZNBf06sOgkqdRZygPa8XXz2QxmAuRSGMdATC8yBsSOj1mXx4eDY8POxTtBCQfzyTYI61EVbMuoQJnUup1NLPXzVW2R7vyX0tj+lOvXgTKFny2ni/9WEAogVUK9bridw9D1VYrWF1G6MZVrdpoiSjRF5dptlaHrdEUYm3W2h1nSaxZrJbuVWImCi47FBta9vHYBS9VrGVy5Wo1ANThZisNTutMMALbixMJSs5AJmRA65k/Hi5OiBrTNc69lCTCOgZhCl1+8G2w9NjYcgbCbL8CRtRHPL6qvBOCiS64KbhPAbftRE+qQ/yv6Lxm+wf92OQBeCbq5r6h0ve+sROUSuLp1kWMmB6683YhClzZHwevsAvaFVJlh3O1rxlC1GrLdMgFgTkQwBbAMpFS9Ouq4Clx5vyTQOhOn3CPfOxEGaWZy9D5YCY0q5d8U8M5Ttdsgd+UBGPvpMog5EJ2xYgbhjpSwd9FWbJ3mV1PBpq9V4Gfa8MuoYJnUuqv6Of8RSE+AL4cf33fO9ueQMrDSRVXudxMJ13tAJH5BlWt2Sgi4Vs2SDqkElQvI0M076ISIzQI7x1J/KIBu7pZuWzdkS1SslB5UsXBBJipU48+UZBJgRcWrHbgmg7VVlHf6BT+9NKQcmRjVi5Moeg7zX5/mcWXaoYEi359AVaRTdew9z5qDmALR9DEE4TIlzCEcHxOuoIIrANirqwR+4hhwsEwXAEy66Kx3At8IeIt2BfBK+9GDrnL9CDDdfaicNKqGqcoVw8oUuKZCD7hFRylw6XY6itWUBwMvbVs4IZMmQmnIkbIt0LZeyCYAIBkSOm1ZUrYepEOADanXEFxLwCqN3wZDx7EJUsGf4uvNbap4/pqzmgGfv0/Zux5QKFNfupGtQLq5CEuK2FxQW6TPOYTt9SsSjo4BOHPLL/YNt+te+7kfBYUiCTEFLIWGfV8wKPj/vTKBGwM+1lgKTOKX4sPr0oodyxHgFspTuTcBFLqhMjncitm5RYdSVK4HXI1C4er8OzYAtR0z7dJGjQ8DrtkfEnRJHQ54Tf22m1zNIslqJbslW4laLU2PqVgvnZU36tMDcDpgDVx5/UG4hsAq9V8cy2U7IBRq5nVJ1k34KuGMNyn2KkHc+RvNCUCjQM6BqGy9KHYQUcQcwlElTMPRti0SGg6o4NKxYHON7UIIupL6DeYV/Y3Cl9VfBb6KlYkCuiJ446o1DbpeyFlQucVNDdvPMeCCHLcqoHDz9qTwsa0rBF2nLgJekLKAHCIWkjwbApBdvHgxbrnlFjSbTQDAF77wBZxwwgmi729+8xssXLgQr732GiZPnoxly5Zh4sSJpW0MOmRXrlyJU089FS+88ALGjRuHf/3Xf8V+++3n+CxfvhxHH3009t57b5t2zz33YNtttwUA3Hbbbfjc5z6H/v5+HHDAAVi6dCnGjh2b1oEO7rLEO68UFWvKSuOdFKakbBXAumHqErh6EBZuDmx9Mkz9Wcgl60Id3TGhHaPueDofs2VXDO+tUxTIARjba0sXIOyN/wqh6BiAnfoZgIMh6BiAI/A1vg4YWJ6ttyJ86eaExn3dbS5Wo4qWwpD0X8Xq0KQOqYwHQ8W2R8f9icqVYFoJuEbh2n5q1n8CXFNO2I8WunYfSOA11wd2ztDVhOvsUHiE5/zzz8ell14KAHjuuecwffp0HHnkkRg/frzjp7XGSSedhGuuuQZz5szB17/+dSxatAjXXnttaRuDDtmFCxfizDPPxPz583H99ddjwYIFuOeeezy//fbbD/fff7+XvmnTJixYsAB33XUXpk+fjnPPPReXXnopvvrVr3bWsYrqNhTqiKpYkiZCvGXyKgKWgpOEhVPgGgSrBFUntMw2gJ0w8qsbE8685FhT4FbZA6mtuFjit+R03NOUa5FlO45KytEyAoQlJSyGpE3ZSCg6GIa2F+D8u+QhaAG+QHFxSwk/p4Se/dCyWddCnvLrkcDL/kt1F9tp/Agw2oEqKSstG0FI/UXVSvvDgGu7KZXHIAGX7hhH5ZJ0BXeDJfDS/Yb0U9cWHQJKdty4cXZ548aNUEqh1fLpf//992PUqFGYM2cOgIxjEyZMQF9fH0aOHBltY1Ahu2HDBjzwwAP4+c9/DgCYN28ezj33XKxatQpTp05NquP222/Hu9/9bkyfPh0AcPbZZ+Poo4/uDLISCBFIE/O4khPKUugRPydMrP26UgAbVK+iwpXyXbBGodqJoo29PaobYeTYjAsCoOLmPl8KKNwgVAECR9lfUsIxFVwFwFwBW3B4IeiK4ecIfE0b0rgvBVcGgKItP4/A0alHCSAl6wEYOlxQWoBmAbpgfSGo0v7TtvKv2QkvC/7uuiLlNx9wszLuTVeRQcraZQZUeppSP2qR09CxIaBkAeCb3/wm/uVf/gVr167F97//fbztbW/zfFavXo3dd9/drm+//fbYfvvtsW7dOkyZMiVa/6BCds2aNXjHO96BESOyZpVSmDJlClavXu1B9vHHH8esWbPQbDZx2mmn4eyzzwbgb+zUqVPx7LPPotVqodHo9GeEK5oOLKMAoVQmmEfrsn7lChaABWxQvbYD11A+zePLHKRVFG23xmsl2LYieTyNhH9tvldeIwhhQQmLvkoV30uKAs7Baeq34VTi0476jYWdgQy+SZOuLIh81etAJs9zx1U1y1Mkr4AbrSNFndp6BZhXgip81eqEgMlu8xUtu3EoUbj8JgMgwM07ZWCtNCkj+eRtFMoUUGZDdYnKNRtm6qBqFsyPHreJp3GnSnbTpk2YNGmSXV+0aBEWLVrk+MyePRuPPvqoWP7BBx/E5MmTcd555+G8887Dww8/jJNPPhlHHHGECFpv3kbi9WrQw8UpHZ01axbWrl2LHXfcEWvXrsXRRx+NnXfeGccff7xYR8iWLFmCJUuW2PWBt970nWIqVrM0vg4XPEEFHHyBg6BiIwCOhogFwFL16uYJ8GxL1SZAV1oHoEKqticTo4Rm+OM+1D8EZLpO37mcEF62ylYAdthPwypXkGtaCL6Ar34T4BsKO4uql4DXrU9XBi+/saCA5OFgxfpeqnYd0NJ6NPMtgGfrjUE1X47moRy4sZByEM4oTg8La9tPLZeRgGv6DHItZceAA80QeGl9VU9bHbkGJNrYsWOxdu3aqM+KFSuS6zvggAOw2267Yfny5Zg3b56TN2XKFKxatcqub9y4ERs3bhx6E58mT56MtWvXor+/HyNGjIDWGmvWrPHk9g477GCXJ02ahE984hNYsWIFjj/+eEyZMgV33nmnzV+1ahV22203UcXyO5ttxo5zHbp4Pad1hmFb/C8zrmLl8d0KgKWwlACarGoFmAYA651EVcdpOwVuBLJKnBHpp+nQYz4tts4ADKBQq44/A7CkgD0/+Oo3CF/h2V2ufJ06/VnOugUXTtD2poKCl05MAhh4DdAIeH11qlk72UXfVaIyICl0OeScZcSBaFUeElQuz4vVb/LyJjxfad0oTKNuHWXKffPTQ5n6FSmjnTJm/zvANR3TRX1c5cJ8R1zBgqxL51Gq9eL6W9EeffRR7LvvvgCAJ598Eg8++KA3ERcADjroILzxxhtYvnw55syZg6uvvhrHHnts6XgsMMiQnTBhAmbOnIlly5Zh/vz5uOGGGzB16lQvVLxu3TrsuuuuaDQa2LhxI2677TYsWLAAAHDUUUfhnHPOwWOPPYbp06fjyiuvxIknnlitIzGlmOrDfKXx1phVVbFeOQLYos2KgC0DL/3fCqSHoFpR2Sb92k8V6NLwbMhiatasxmCKAISrANjxjYWV3W0qg28QvEAOls7B6yheqqoYeCW1G1anmoV86VhmGnR5yNiDJUmn9cFRg8rxqwxclm85pYs67P711hUpT7ZRKptb6fhtALgA3VdMxRromjR6SkvjsRV5OxRmF3/+85/HE088gZEjR2LEiBH41re+ZaF71VVX4bnnnsMll1yCRqOBZcuW4ayzzsLrr7+O3XbbDcuWLUtqY9DDxVdffTXmz5+Pr3zlK9hhhx2wdOlSAMAZZ5yBuXPnYu7cubjhhhvw7W9/GyNGjEB/fz+OO+44nHbaaQCyAedrrrkGxx57LPr7+zFjxgxbR6lFIFY6W1hUp/GLeHDCU4mFVGyoPQvSBMCWqteKcBXBGgNsirqNpadarLy5Gg1oIZ2lNZRbF4ewMy5VEcBl6tfWTeBrlSGvz/WpBN4cbjHwOhde5EBraQKYBLWrXOhCATAv86D1Mpi7kFNOXzxVapdVwKdY9qATqEtUuGVQjdRtRCTtR1ixKqc/kq/ZX/nesl+lo1whA5fCW1S5KNqyy2DwNdbOdW4z28033xzMO+uss5z1Qw45BA8//HDlNpROHb3dAmybMeOw/ycvFvNCKjY4HkuBpmFBaH1smnbXaVkNUclGIWv+0zCx0w8tj8FGACuq11S4loE1pG6ldWHqfNC3HYuEjwEA0sQ5Xoavx17lGFgOhqAj8JX8qJoN1eH5ePluO/y1io4fq4v6iq9jFMZ2HYUplJV+TMGp01lWgXRp2a+HT6Cy7Up5vJ5IXbHyfn1pfXDXdakvkF+O2P72JkPRtJi/KQPBVzKW1/+Vf3bGT7cZMw4z58nX4lR79s4lpWOyQ8G2zjc+Mat8RxUAclJdFKgldVXtE51FnKUVgHXSjAXBK6RVgWtK2JgDNQDRrt4Dsrq8CXQDAzTTL99ouHUo5aphJ9SrfF+zGFC/WgKqFBs0qldQxwU0tevDVbGXbzvntOE2n0kkZ/IN4IaYKZwdpQursIPhZYVC6dLtoHU6MKmiXIV6RD+iFmkeq8f7BSLz8ZRokcfHWW3o2rjpcB1BdRvwpeoWABu/zepwFC5YeeqPooytjxzq1ujFL+W03Urk3VYP2dhYamxWcdQS/ZQTpiVtlKnYsnqpurVpDJgxwMbUa2RM1lO/Xn5LTkcApknjtAkDO977FPOiUmi46FBR3IaXIxDmAPZAKsBXuctqgKSbaiTVmwLeslBzYphZgm7mk9Udgi6FVnZ9ptual224UPbCms62wgkt+1AlQE8FbsyP7EYHihaamkBJpYeMJWjSMqSLVPXK64r0KfzsbTJw83ocsJo66KlC4Uv8XNlbYhodzy4eLrbVQ7YbFpxN3CvjoeJQW1zFmrTQemR8NQrYGFwDYPWgKp1wZQBNVbl6wF0PhY2pGwGzpoBkbXsAjsGXKl8+/ivB1ANvtpykeIlPcTOlHNeQ2qX5KUrXUX3INteO6dLwLwEqcczr8/OzuqnKSgRuROF6oKR+FjS+b0jdZj4aVt069aMAp5ZhzSHqqV7N1gM3AJK6deoFwsAlu8mJiNg8cpyyw1ZUtNQ3kjUUxmQHw7ZqyHbyJacoysG0WH9Kf4w9pDzbAaykXENw9SZBCVAt289t3Q1reWax4zLgA9NAmAOYwdcJQw8I9XDwAhl8rZ8uV7wculoXfh7MUdRnoKsUMABX5Yr5ps8cyOa6ruXQct4XZzM5cDXpHwNuASL50RQn1trQbn0ODLVTl9s2LAQpKBWkfBSwI+tufQS2AZ9oKFkqA7d9LxzsAVVQt1rwp2mmXrLdUpjYAWruICpaY2Wn5tC6hPbMtlrIioDVJfkxE+sb5KOoFZnJHAsf52UlXzGkUwZYQb0G4crB2suwsVNnytvBAjDmAB6AD16gKFsGXjPhysANkKFLfYgvha6W4Gyga4EqAxfIL6RB4LpADgLXXMghAFexXyfiwFVm20H6aeqgQCFQzH8MQTfisKR1uYqW9oGUF/NRQNHsUkWYz2Eb8OGgjNZrAE92maRWPbUrqVvAgbwHXGIWuiDtmA7w8Vnqm2hqoNxnS7CtFrJt25Z891WiaEUAdguwqXCtCtOQpY7lSn3gk5oAiC9ibYUVr3NBqwpdUy3NN1Akfpr7lQDX9itJ4ZJ8FCoqe39yAVyNApQODPJfJzLA1bZ+AjhN371MgRNXtx5sSbvK7o+8HkDIRwFKSOVRQBGmH/E6EGgnCFtznBDAerCl+5PnG3CS/WXUrRhONqcxhy4BqD3iHdoT+FLjxJZctuRrKbGtErJb7JfbUNAxNdsN4yq2zI9aKmBTwsgh326YVY3Sj+WGwCtVxMpT6DJ/55pEb1Skx4ok4FLrAnArh5SdPJC6NVG3WT02P4coWgS2KGAbUrea1OEAxZBAgq0Iy85gWwY+rw4WRm5L2bLy0XFbLaUx4IIoUQZdNzzMjlGaZw6t4IpgGvXEp9q6YHQsrcdtWCWwOfsimDhruBuA7eUJGlKvUn9MmJiWoaFd66fcsjRc3VDOfioFLv0uaXfos7B8eIDu8lCk3PgEbgC0eS9yQ/v5BsZenirUbQMFbI26RRi2WXlNlpHdRAKdwRamH4YVbj1+vlyeqk4HlmV1BGDrbkMJxFl5B7a0nkiaB1wKVpNud3x+DNiDgR0c7mKabR2M3fog27HKE+7goukV69X5hUcje22duajoIjV72XuLXmTibUsALsasOAh0+vLmshLAtvtsbfSHJySIAi44U4Brw7utoozxNxOI6MxlWs4AN/TSDFsPSeP7QimrIAYbttr84pCJhpMDNwZbUY3GYGvbzM8XOmYLAxMJljlCPTiafL88h50D24Q67H5j0I6qV15fALaykhVAGgAuQHxB/J2Dwfma6VBtqdVKdgs1TQ+UzdmOOelb7oWka3d3Npyo/eHCBtw0pfK0ksbpRbuhimcpYzOblfKhpxpwfnuti9Du5OUVjppMAS6fFEXBSX2l528pbDmcCWyLyUW6KNNq+eO2Doy1PDuZ+amWlmcmc5WcAltSXmktgti8PZnCVrOrtbmVzNpXxa8Hgfwggq0ph63ZXwySWX2kjJnsbl6eQRWy2S47DsxCyDbfwFS70PfyCZtK6mhbvcbyzNdM964H1jhwi/q1rSSmZEFcU2yLHbZjttVBtltG1aEH1AAsi5OvJLRbqR/m4mVULsRxWecF8SH1ataNj1L5jYBwIRcUErTOLv6tluxjwByzFJ+IiVBvwxzAhYwD1BYm4DR+gA9bSdWyeiuBli7TNiUQGyC22IxkYxS6FNocpkplMJZULXIQm/Fam1fA1lW1ZqmApv3B+waFoh9CznwKQBdIhl+mVYCWtki5oZ1+QMgvK+8CFWy9AKqGUelAGMiV8iTYcrAikE6Bazcm3w9OegFeatWUbLrvcLatErIparZdxSuVcyZBpNaBtJBxSAUW8IWvZvNwnm4R2HM1Sy7KulGEGJ2Lr/HnKoiB1gGfVcARNUtBa6/CLTcfCMKYwrEnoeNBtrZB61YSTLOglfwrgdYv56laJy8HZIPUYySXyTexzlYO2twnpmozWFDtm5l99aMuQGvTaT0oQJvlk7FaJ7+svMkH6weE+oqbAOMjqWIprwy2AAMuK+PUy/NIHcrptKL/ijqSTzfd23kVQ8i2SsgGjR/NzETwRs4mCzrhQp8pS+2GjE3h1GOvgWJslqlZ5wCmUAWK/jTgpllwkvU8LwMtSW8DtFlV2gUtAPeXwwmMgTTYUj9mPYNl7GUW0mscy15+MZgmANcLHUvWCWj5DUBV0AJe+DhTXJosQwwfu4AhcDag1QRyph5QCLrALoOknB8HZQZFDapqnboIPEN1hGBrfcFgSzomjr2SDQiFicXrYYrpWslu8VZJqYZuRauUydPssRsrb/1K1KwU4iOgzcoQyFOoAjkMuwRaQBj7NeHP4s1PVtVSiEqwtf1jIOUAM9ANQaxbd8spkAy8Izn6Sz1SWebv3CjQZWkCVKj+KvncYuDlZkAby2sHtMqtw4VrsZz5kONG+6ClZUTQgpy+FrpuPX4+A7jbnAddRPJEVUv9mArlbUmwtTAOqVuabirmKpZ3BvCUbLJAAETxsSXaVgtZoBy05fnyuKw/RktmQPLykpoNtOmM6VqYanemMa2bghbwoSqlcdDyPjQCd6COQmVqh6pauDe7doYrB2hM3Rp/QAZbSO1220JQDbVbBlehXDJgpbpDP6knmBcurmiOWgUEkDK1KxkHLa2HLtM6GKEU8gu/FDr2aASrqBzQmuPUnIoVQOsA3PQl4psCbLuPWfc9VRvJD/nA9JFkBFWs8aGHFa+sgtVKdmu1FJUaK8OWNThw42rWgNdkUzXrqTIFH7SkA56iNUZDx9G0/D9/86EZy5JOkjJVCzjPftpzmV94ndceCg3FLtQx+PXCoqHjDsEq1UH3ZRDCgXRhOfj7tjwtsp26BOJ+AXYzJvrAUVL++B8FIoOjUM6pgwOVjtHyEDRADtQugBZuuWAeElSt8c0TnHymYov95qZ76tZWyvzh5nnwpVZyOCiga5M/h7pt9ZBNDhtLB6XuUM0aSBI1y28zOWidsDEZw/FA6+TBDR3zMVpjjWKSigfbgKoFEmFLJzcJwHWeCSV1Zz4SNAO3we3wNfQMbBWLQSZhjLYSWHl+m3AFAoANlYul2fYTfDoxcQIXZPqwsHGhiAsfB6gGtAGSFcAkoAWHK4cyLScsk80I+9EQOvElyxDqAveRblS4HwOqBF0EfB1LuabWSnbrsdgjOFUhLC1TNes95E7Ke8/N0v61A9qstANaM8YFQIZqE4AuUbUiEJX7qI/53yS+icDNXIhPU3ospymPtyqg8vuNm10AQsXQsTghK1Wx8vXYmG8VuIaWS0BsVay0C4xa5j4S0KtYLOwMJKtZEahAujJGoA4GxyhoyfUi3LUiOkXVL4qiYhBOhK3kR9VsIB2AB+nKUT9Srn4ZRW2+5UdxO2pWmmksPTcbnW2sqoE263LmZWcdA274OAjV/A6/lZ9jdnw1z6ewzf8HlW0qcJtNZ/9kfkTpAm5+DkcRwLZ8j0/kEuUbnN1cRamK/j0GK28jVKcEWAbQKIRjFtu1vRwRCMHXWXaVcRiiFcLYhIQhdWyVNzHeNkhV1Iemh/xMfxywRvK4VXlOdmuZ+DTIg1fAypUrceihh2LvvffGe97zHvzxj3/0fO688078l//yX7Dffvth//33x+LFi+2FdNWqVRgxYgQOPPBA+3nyySc77pd3cMTu3kJmzjklL2c+Ssw3P/gMwIasbJrK/DLfvHyjqEc3lPXVZtJSU5G2lOuXl9UNledlZXTT1KOyi34svdnILsLNBqkjW9bNRtZWswFt8hsNvzytg/o1SJ3NZvYx6WZdFX1XjUbxUcr9NBvBDxoq+ROsh7fH+kP7aftOt8dsE/XzyrG+Nhthf1ZWN4qPU4Z+AHfZtMPTybJWqjjWqDpl9aZBGEW7tAwx6yNGAPykdo3eINJoEo06VV/WllRKI7yMfD3mq0m/SBmluY+7HkpXrbCv5KPy9ahvyy8jmWrpjj7DxQZdyS5cuBBnnnkm5s+fj+uvvx4LFizAPffc4/iMHz8e1157LfbYYw+88cYbOOKII3Dttdfik5/8JABg3LhxeOihh7ret6Q3N+VpMTUrllcQw8ZufjG7OKRopdBx0VQx6xiAq2qVCRPn+U3zogCTp3KlGlKwRTrMtjrqVskzi5FBOlsmIWXA87NhW01ul+lLMGweMjA5X17kpGvJ4eOuPUMbepSmaCgtLWVGcmTdmyEcUqh8PbGcAz8JmmRZ9GVwzfzcPthyMaiaiEwEuJUUVS8tSRVny1Io21O0+TVFCh9zH2+dGN09XN3StJCVKdqUSurZxT2wDRs24IEHHsDPf/5zAMC8efNw7rnnYtWqVZg6dar1mzlzpl0ePXo0DjzwQDz11FOdd0BBBmeCBd/kREBr29Cufyhs7I3PpoDW+Oc4zWAJJ3xMw0rZw/sZHO1YrULWfgy2JnJLoYq8o1oArskDCuDRH3XPYaoFkDp3pXxii7fThS+vxcpwfw7kXlkM2qGwcgqAJWUXmxFctp5YNghVXk4qUwphty9OWyrgK7Wj2Dq1BivPliUL/miC6ExvGIu+OMu5iWO8Gk6o1ytfAtpY+NhU46xL1z56bXL6y7ZBC/suBbQxGwJqdPHixbjlllvQzK8RX/jCF3DCCSeIvkopzJgxA438pvqKK67A7NmzS9sYVMiuWbMG73jHOzBiRNasUgpTpkzB6tWrHchSW79+Pa6//nr87Gc/s2mvvPIKDj74YAwMDODYY4/F4sWL7U5KMn4UEkuaBBUANf3h6UJ1hpa7A9psmahae1KqYjxIo1C1OWDLYZs31CQ+XN2yPE/hEgULwIduviyBF4Crenk5miZNXLIw7uQq0IaVqeNEVSs+t9oJTBP8O4IqLxf09/sWUq8eXLmC5YC160XTYphZsf89MumxIxnAhR+HaFTxUtDm5zmHsykGWk3g+uUwlfvw6yLpUrs2FB7hOf/883HppZcCAJ577jlMnz4dRx55JMaPHy/633333Rg7dmylNgY9XMxDdLF3y77yyis45phjcMEFF2DWrFkAgIkTJ2Lt2rWYMGECXnrpJZxwwgm47LLLcMEFF3jllyxZgiVLltj1gbfeZJ1BGmjFDYGrWO26C1rPF3TZB23hTp6XJaDN8rXtZ3Y37Ktae4usUcBWmQNbZRNw7YsCkPdDWVBqwE5O8tQtULy4nanYYD7xcR3h3tE6E8MSVCwQH58ZzBO5BLDBFz6khpNTQsxVQArEYVpWPhnEfn9jytUp0y5gzZwFUoekYj3AS3UHypbeUEUsBmAPtPDToqB1GmK+cDc1dHZ4Wyb1F+TaV9U0gIHND9lx48bZ5Y0bN0IphVZgeKldG9SJT5MnT8batWvR398PIAPsmjVrMGXKFM9348aNOOqoozB37lwsWrTIpo8aNQoTJkwAAOy00044/fTTsWLFCrG9RYsWYe3atfbT3GaU75RygEh3xhDShBPfz+PLKpCOYnKJykCrm0W6DX3nbZiJLVohU4Z2chPciVH5sm6qYnIUnRhDJsrofMKNbhIfO1knK6/Np9GAdibz5PkjGp6P49doFBOf+GeEMEGITxpqNKBHNLNPPtHK+Zi8mE8nn9S6+bbQbRLTEz5CnZp/6HfUVMWkOPL9O3Uo93syx6BYXrHyihxP5rjMj0WYiXDkmIZClqfIsUuO5axuZJPvWDl/PT9vTFshwJL/HqDJ1VCEb+Qa0La596hpPsF1LU6KgoY7AUm7dXjp0of48k+0HCnPN8r0t91Pt+yb3/wm9tlnH8yaNQvf+c538La3vS3oO2fOHBxwwAFYtGgRXn311aT6BxWyEyZMwMyZM7Fs2TIAwA033ICpU6d6oeJNmzbhqKOOwoc+9CFcdNFFTt6GDRvQ19cHAHjzzTdx4403OmO4bVnKiSSBVry7jdQVA60is44V2DK5mJiZxwScaBRlUmCb+aCAbX7h9GaiMuBmn2rQlcALduHXIygUGDhGNGW4hKATghkHdejTqT/vu/mE+psKz2azFKCawjMEUQnESvkgjsGYwpQBNQRVc8wFwUrOA9t+Alyd84uPwUqApecUPScbcNZj529qXlsWAGgSaAlseVoZVL2ZwBXgGYJv2exitFodfTZt2oRJkybZD41aGps9ezZ23nln8bNmzRoAwHnnnYfHH38cd999N/7hH/4BL774otjdZ555Bvfffz/uvvtu/PnPf8b5558f2DDXBj1cfPXVV2P+/Pn4yle+gh122AFLly4FAJxxxhmYO3cu5s6di8svvxz33nsvXn31Vdx0000AgOOOOw6LFy/Gr371K1x88cVoNpvo7+/H4YcfjsWLF/ekr22FjW1ZlWdrN5/6G1+YPPp8a3F+ZMtFfbqZZaoWijHX7A/y5mDCwE4YGcje6aqLcrYDGkDTnKCqeJ8DO5mLoU7lJtDQMgD6G6I6D4vbLZYek+D+bmNFgUAkx7mzjd06djt8XCFkGH31YKjPqWHjUP1SvanjwlIzLDzttendnCriG2mTh4NJXXKa358U9erUFwCs8zidV1bou9c+W++V8dCxk0bf/wzvguJeq8J5Xj61UHqqdRiVHTt2LNauXRv1CUU5JTvggAOw2267Yfny5Zg3b56XbyKuY8aMwdlnn40zzzwzqV6lu/EL18PEthk7Dvt/8uKwg7AnPMjqQF7oDhQ5AFLuRM16/pXQPCk0ZJdb1E87fm5ZVi/9cXfpLpiu2zZ431h7ThlN0op8D3TeCyjc1WBoKHbobu7Dugy+kfzKMA75p4ITEGc/B/sRg2WoncBYrjg2G003dTCQkjY6gquzzvPj7ZSvp9Yvr4t5JWlOu4G6Cj93PaTO27l5ePnHlzlAHL3NDpiz32erV0Ts9y98vxSyZfboo49i3333BQA8+eSTOPTQQ7F8+XKbZuzll1/GqFGjsN1226HVamHRokV46aWX8MMf/rC0jfqNT9SEO7Ok2cYkXZqBzF/6b9y9datw85OYqtq8vqKcKu5YBWVr8qyIzJVyMQlC57N/8wpbZKNox1iHraK1IDQNkDyT1ijqstVIs42NSjerFCTCIwqlM4eHyvN3KYMxMaBGQRxqU86IgjuUFVTMib5s+4MX+0iePGnKbzcOpABcYz6DDNiokVPGdlv734OkaLN0pmpNu+y6FlS3CPu1bRrB59cH0z7/+c/jiSeewMiRIzFixAh861vfsoC96qqr8Nxzz+GSSy7BY489hoULF0Iphf7+fsyaNQuXX355Uhs1ZBOsI9DCpAmP92hWpnDPq0uELeCEkYEAcDU5eQTg0pBy0UAAug3SFhWzAnxdH5LecOt2QUzqMcagTM35fqrONEhRvR3MJAUS7/5LXtHYTVCW9qmN0Hbs5RBBnxKgeumh8LMArZRx12S4krbbBmzEOgotO0ANg9bpS/Ru3wep5n6SVd2GzR1tAnDzzTcH88466yy7fMghh+B3v/tdW23UkOUWuoOLWBS0TpoPWpMNxI77MGyLMRkXqEHggpxwFpyBE4+mtYwSJ8/QEnC6Y6umMHkns0lqsQbYiWae8fWMKmMvr/JXJhoPS1f++bZo5al+ZaDtrHzZDUjpNoe+gtTQMoRtCAEVKIcqWRbHbmOq1Unz6y0d4xXSUiZF9h6oAhQJbJ3tD110WJ9D6tXZloonoRoCj/AMhtWQlUwAbUzNevkcoo5iLZRnVtBXvlVgS/MrA5ff5XLoSp1xGoQMX+LDf1HIhXBRsQdjW7/r51ibd8LBC0YCCbsymSUV3gmKPOlGILG5dgFblA9kiOO9vG4Vzvd8qV8aWB3fCCTdNAZX2kYCcKU2o9sVSmvDvHByTNWafKkPAejSdtq2IaBkB8NqyFawdkDrpBMqOqqWVJMCWy/US9pNAi5xtNClafSFELRCHjIGsgsoAaR30rXYj05L55WgXh1lLJnO+9SGOV9hyYneVTVrG013rdR+pXrTfVN+Y7ed0HPpRBu2Hhy3LYOql+77R8PCQb9YmgD/AGClfdfWzRy9xiAO2iyfnOcpwOV5IUvquwYGNv+Y7GBYDdmQCWoW6AJoSXrxLtNqsHXTyAWBA9e0T4ELmuZDF4B9WxNPd9Smo1qV4+6OjxYQ9rZPMqKMuXV21xxKrng16yJz21bFbfywfFttVXo8qayu9PSyx4KSoOrl+elVxnrbms1b0n4s3bEOjjkRtEKdScBN7VPKeapRK9na0D3QAhDDxzY9DFunCtKOlOYp3NwxNHYjhoVtB4X0AHxt33kWVcGsjBeFMgnBcVeddO6GrBNAdyVEHLIuKOXuhLB7W7bqpC3vRf0xVcvyYwq50iSqQHrVR2WqArbK91mmVkUf4wffN/MPAFcq34nVSrY2ANVAi8LXASrLF2ELV1XxHwPwmnHgKqlXA24K2ALi8UkTCfBleRoq/NNVgRNSBHOwXJsU4GH0qtZLwA5SWz0JeRurUHX0F25SFK3gVxZyToIqK1cdih3AtUKeuC5ZALRi/bHQMNxz1Gum0+NK15CtzVgqaAXfZNh6eb66BcLnBOeRB13AKl3aryB4TaXOOr+CsdVG5KSU9l9eeVu/KzmUIk2DCeLcKv0kW6+t4va38yiSqO5KgavC+VEYp5ZJgGuX8rploqq1HajWfsfvD66VbG2ORUALxFWt6CfA1uYH1G1WLKD+GPCjSpcWlhQv4MBXzPc6UPQ3GpqVygSAMRR+Cqtd66l6HGrWbpAhVq4SbP3Eago3vWxXwtQV24ymhUxQs7aakKqV6uikD2WVD+Pzu4rVkK1iAdACEVULt0wQtrlfDLhU4WZF3QZjN6Ka9531IwRf4+MDVodPuLJzJ/HcKpuU1JU3zyDhYlNbe1ZZ4cbqkjPbUrgpPolgLS8bbzfVp9JNh80MlwOEm/IU6xYXNTp/49MwOW9ryFa1EtAC1WDr+FcBLgQIKTbOWQJWpx9CH6LjOIGLXjQcxa3DO9khcx88VFXrUFQK3Zqx3M2wsujTPlhT8lP7EUxLtRLQ2ib40M9gHNKdQrZZ7jIUrIZsOyZAk1opbFnZaMg59+UHvQTdzDUOXtteoG/Bu9vSCRJCmZhFQD1kbIh3TzTnexqGG5DQ5eAx1hF4pYO6nXrK+5QM11h6qB7RMV6P2Gzk/qxrAB6KN4E9sBqynVhE1QIR2JqygAhb6yIp3LyMdKAng5fUKQKY9UvqQ1t3viWgHnQbCn3oprVxMU2xboXluVW+WLcLHBF05VAN1tsGfKv4JeVVtS4eG107Hjqd+DRM6DVMujmErUTVAoHQMC9vneVyTlnpZImEaePDNvFCoclHKZOgKnVkc9tQ7hu12H6usA1VLpRDYcw6qQ9RCKdBNdhWB9Csqrw7UvPRQun1D4bp+hGeLdRK1GdH9aK87ihwaT22gFzWqyN04pSMkZadb96vdrRbEcLATrXNMmN3sJvswn4Gyvd16YSZoWaJ2921x4MC/lXUaGW4luWV1ZtqFR/V6YlpXT/Cs0Vbr0Br6kZa/aXApfXZQuE6xLpKLqYpJ2woDF3VNvdjLUNBkZVaSR9TFai3r6sc7yVRjM1pycdQV0PL1droFVyjdXdibRwbXbEh8Huyg2FbJ2SB3oLW1G+sInCBCtAV6o8q16rjolVmCw8FG4S+dro/uvaKx7bAWaUtNTRVLbVOlV87MO4mXFPyy+ofTOvi8aAHBrpX2RC2rReyg2kV1K2xZOjS+p0K0uotbWMonNgJ1rMLUA/qbRuUzCp3rcINU+kwREJbHVmb7XY+dlu9XLsQr7KNQwKw3bYhGCnphQ36y9lWrlyJQw89FHvvvTfe85734I9//KPo973vfQ977bUXpk2bhjPPPBP9/f0277bbbsP06dOx5557Yt68edi0aVN7nRnsA1eRT0XTyv1UaiuxXd5G2acbVrXN5L6Etr/qp4t9Fq2D/lRus8J2dvzd92C/p/QxqT+RuqJlA+WqlrH5ibbFAnZgoLPPMLFBh+zChQtx5pln4k9/+hMuuOACLFiwwPN5+umncdFFF+FXv/oVnnjiCaxfvx7f+973AACbNm3CggUL8JOf/ARPPPEEJk6ciEsvvbT9Dm2uA7jiBYVb28Dr4KJW1oeugadKvytuz6D2ucO2K++HxDYr1dvBtnTLugL6krqj5dspV9avRNsiAZubbumOPsPFBhWyGzZswAMPPICTTz4ZADBv3jw8/fTTWLVqleN3/fXX46Mf/Sh23XVXKKVw1lln4dprrwUA3H777Xj3u9+N6dOnAwDOPvtsmzdsrQPQGev44tZF+Hat7Tb70dULf1W4d3gTULYdlfqaWG836kxpZ9BuahL6mqR8I2Xbthqw1vTAQEef4WKDCtk1a9bgHe94B0aMyIaClVKYMmUKVq9e7fitXr0au+++u12fOnWq9ZHynn32WbQ6mak2VA7mLvWjq0qim+DtEci7pqAG8yajzXbaUnKJdSbZYN58VbUK29vTPtSWZrrV2WeY2KBPfFL856cCg9/Uj/vwOkK2ZMkSLFmyxK73v/YKNvx0SaTE8LZNmzZh7Nixm7sbPbMtefu25G0D6u0b7tbp9v35z3921me8+y/w6Lp7OurTxIkTOyo/WDaokJ08eTLWrl2L/v5+jBgxAlprrFmzBlOmTHH8pkyZ4oSQn3nmGeszZcoU3HnnnTZv1apV2G233dBo+KJ80aJFWLRokV2fNGkS1q5d2+WtGjpWb9/wtS1524B6+4a7dXv77rvvvq7VNdRtUMPFEyZMwMyZM7Fs2TIAwA033ICpU6di6tSpjt+8efNw00034fnnn4fWGldddRVOPPFEAMBRRx2F++67D4899hgA4Morr7R5tdVWW2211TaUbNBnF1999dW4+uqrsffee+NrX/uanTV8xhln4JZbbgEA7LHHHvjyl7+M973vfZg2bRomTJhgZyFvv/32uOaaa3Dsscdizz33xLPPPosLL7xwsDejttpqq6222kpt0Mdk99lnH9xzjx+Lv+aaa5z1T3/60/j0pz8t1jF37lzMnTu3cts0dLwlWr19w9e25G0D6u0b7ralb18vTenQzKPaaqutttpqq60jG/RwcW211VZbbbVtLVZDtrbaaqutttp6ZFscZLvxbuShbCnbt3z5cmy33XY48MAD7ef111/fDL2tZueddx6mTp0KpRR+//vfB/2G63eXsn3D9bt74403cOyxx2LvvffGgQceiKOOOsp7k5ux4fj9pW7fcP3+AODII4/Eu971Lhx44IGYPXs2HnroIdFvOH5/m9X0FmYf+MAH9A9+8AOttdY//vGP9Xvf+17P56mnntITJ07U69ev161WSx9zzDH6qquuGuSetmcp2/eLX/xCH3TQQYPcs87trrvu0mvWrNG77767fuSRR0Sf4fzdpWzfcP3uXn/9df3Tn/5Ut1otrbXWV1xxhf6rv/orz2+4fn+p2zdcvz+ttX755Zft8k033aRnzpzp+QzX729z2halZLvxbuShbKnbN1ztsMMOw6RJk6I+w/W7A9K2b7ja6NGjcfTRR9u3sb33ve/FU0895fkN1+8vdfuGs40bN84u/7//9//EF/wM1+9vc9oWBdluvBt5KFvq9gHA448/jlmzZuHggw/GlVdeOdhd7ZkN1++uim0J3903v/lNHHPMMV76lvL9hbYPGN7f3ymnnILJkyfji1/8IpYuXerlbynf32DaFvej7d14N/JQtpTtmzVrFtauXYsdd9wRa9euxdFHH42dd94Zxx9//GB1s6c2XL+7FNsSvruvfOUrWLlyJa666ioxf7h/f7HtG+7f3w9/+EMAwNKlS3H++efjZz/7mecz3L+/wbYtSsnSdyMDaOvdyEPZUrdvhx12wI477ggge+foJz7xCaxYsWLQ+9sLG67fXaoN9+/u61//Om688Ubcfvvt2G677bz84f79lW3fcP/+jJ166qn4xS9+gRdffNFJH+7f3+awLQqy3Xg38lC21O1bt26d/em/jRs34rbbbsPMmTMHu7s9seH63aXacP7ulixZgmuvvRZ33HGHM75HbTh/fynbN1y/v1deeQXPPfecXb/pppvwtre9DTvttJPjN5y/v81mm2e+Ve/sscce0+9973v1XnvtpQ866CD9+9//Xmut9YIFC/TNN99s/b7zne/oadOm6Xe+8516wYIF+q233tpcXa5kKdt3xRVX6P3220+/613v0vvtt5/+0pe+ZGdFDmU7++yz9W677aabzabedddd9bRp07TWW853l7J9w/W7W7NmjQag99hjD33AAQfoAw44QL/nPe/RWm8Z31/q9g3X72/16tX64IMP1vvvv79+17vepT/4wQ/qBx98UGu9ZXx/m9Pq1yrWVltttdVWW49siwoX11ZbbbXVVttQshqytdVWW2211dYjqyFbW2211VZbbT2yGrK11VZbbbXV1iOrIVtbbbXVVlttPbIasrXVVltttdXWI6shW1tttdVWW209shqytdU2RO3FF1/ElClT8OMf/9im/eQnP8Hhhx++GXtVW221VbH6ZRS11TaE7ZZbbsH3v/99/OQnP8HGjRsxa9Ys/PSnP8Xee++9ubtWW221JVitZGurbQjbzJkz8Yc//AEAsHjxYpxyyik1YGurbRjZFvdTd7XVtiXZ5MmT8ec//xkrVqzAL37xC/z2t7/d3F2qrbbaKlgN2dpqG+K299574/jjj8ePfvQjbLPNNpu7O7XVVlsFqyFbW21D3KZPn44ZM2Zg9uzZm7srtdVWW0Wrx2Rrq22I2/PPP48TTjhhc3ejttpqa8Pq2cW11TbEbeedd8af/vQn7we0a6uttqFvNWRrq6222mqrrUdWh4trq6222mqrrUdWQ7a22mqrrbbaemQ1ZGurrbbaaqutR1ZDtrbaaqutttp6ZDVka6utttpqq61HVkO2ttpqq6222npkNWRrq6222mqrrUdWQ7a22mqrrbbaemQ1ZGurrbbaaqutR/b/AesehDapMor2AAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "qaoamc.sample_cost_landscape(angles={\"gamma\": [0,np.pi/2,10], \"beta\": [0,np.pi/2,10]})\n", + "f = pl.figure(figsize=(6, 6), dpi= 80, facecolor='w', edgecolor='k');\n", + "_=pl.xlabel(r'$\\gamma$')\n", + "_=pl.ylabel(r'$\\beta$')\n", + "ax = pl.gca()\n", + "_=pl.title('Expectation value')\n", + "im = ax.imshow(qaoamc.E,interpolation='bicubic',origin='lower',extent=[0,np.pi,0,np.pi/2])\n", + "divider = make_axes_locatable(ax)\n", + "cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n", + "_=pl.colorbar(im, cax=cax)" + ] + }, + { + "cell_type": "markdown", + "id": "811ee919-4b85-47b3-9e0a-f005016b6164", + "metadata": {}, + "source": [ + "Search for the best parameters at depth 1 and print the approximation ratio" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "5cb4fea4", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 1 )= -3.9169921875\n", + "approximation ratio= 0.9814453124999999\n" + ] + } + ], + "source": [ + "qaoamc.increase_depth()\n", + "print(\"approximation ratio=\", list(qaoamc.costval.values())[0]/-4)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/MaxKCut classical branch and bound algorithm.ipynb b/MaxKCut classical branch and bound algorithm.ipynb deleted file mode 100644 index ff605b0..0000000 --- a/MaxKCut classical branch and bound algorithm.ipynb +++ /dev/null @@ -1,272 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "%load_ext autoreload\n", - "%autoreload 2" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "import matplotlib.pyplot as pl\n", - "import time\n", - "\n", - "import networkx as nx\n", - "import os\n", - "from matplotlib import rc\n", - "font = {'size' : 16}\n", - "rc('font', **font);\n", - "rc('text', usetex=True)\n", - "\n", - "import sys\n", - "sys.path.append('../')\n", - "\n", - "\n", - "from classical_maxkcut_solver import *\n", - "from data.graph_generators import *" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "579111315171921232557911131517192123255791113151719212325" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "num_threads=1\n", - "max_vert=27\n", - "for k in [2,3,4]:\n", - " t=[]\n", - " for num_vert in range(5,max_vert,2):\n", - " print(num_vert,end='')\n", - " G = er(num_vert, 0.6*num_vert, True)\n", - " tin=time.time()\n", - " classical_maxkcut_solver(G, k, num_threads)\n", - " t.append(time.time()-tin)\n", - " pl.semilogy(range(5,max_vert,2),t,'x-',label=\"k=\"+str(k))\n", - "pl.title(\"Erdos Renyi weighted\")\n", - "pl.xlabel(\"vertices\")\n", - "pl.ylabel(\"solution time [sec]\")\n", - "pl.legend()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "579111315171921232557911131517192123255791113151719212325" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "num_threads=1\n", - "max_vert=27\n", - "for k in [2,3,4]:\n", - " t=[]\n", - " for num_vert in range(5,max_vert,2):\n", - " print(num_vert,end='')\n", - " G = er(num_vert, 0.6*num_vert, False)\n", - " tin=time.time()\n", - " classical_maxkcut_solver(G, k, num_threads)\n", - " t.append(time.time()-tin)\n", - " pl.semilogy(range(5,max_vert,2),t,'x-',label=\"k=\"+str(k))\n", - "pl.title(\"Erdos Renyi unweighted\")\n", - "pl.xlabel(\"vertices\")\n", - "pl.ylabel(\"solution time [sec]\")\n", - "pl.legend()" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "579111315171921232557911131517192123255791113151719212325" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "num_threads=1\n", - "max_vert=27\n", - "for k in [2,3,4]:\n", - " t=[]\n", - " for num_vert in range(5,max_vert,2):\n", - " print(num_vert,end='')\n", - " G = er(num_vert, 0.6*num_vert, True)\n", - " tin=time.time()\n", - " classical_maxkcut_solver(G, k, num_threads)\n", - " t.append(time.time()-tin)\n", - " pl.semilogy(range(5,max_vert,2),t,'x-',label=\"k=\"+str(k))\n", - "pl.title(\"Barabasi-Albert weighted\")\n", - "pl.xlabel(\"vertices\")\n", - "pl.ylabel(\"solution time [sec]\")\n", - "pl.legend()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "579111315171921232557911131517192123255791113151719212325" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "num_threads=1\n", - "max_vert=27\n", - "for k in [2,3,4]:\n", - " t=[]\n", - " for num_vert in range(5,max_vert,2):\n", - " print(num_vert,end='')\n", - " G = er(num_vert, 0.6*num_vert, False)\n", - " tin=time.time()\n", - " classical_maxkcut_solver(G, k, num_threads)\n", - " t.append(time.time()-tin)\n", - " pl.semilogy(range(5,max_vert,2),t,'x-',label=\"k=\"+str(k))\n", - "pl.title(\"Barabasi-Albert unweighted\")\n", - "pl.xlabel(\"vertices\")\n", - "pl.ylabel(\"solution time [sec]\")\n", - "pl.legend()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/Parameter choice.ipynb b/Parameter choice.ipynb deleted file mode 100644 index 7964eae..0000000 --- a/Parameter choice.ipynb +++ /dev/null @@ -1,455 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Parameter choice\n", - "\n", - "This notebook demonstrates how the function parameterBounds_MaxCut handles symmetries in gamma and beta to select appropriate bounds.\n", - "\n", - "First do some imports and define handy plotting functions." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from qiskit import *\n", - "import numpy as np\n", - "import pylab as pl\n", - "import networkx as nx\n", - "from qiskit.visualization import *\n", - "from qiskit.providers.aer.noise import NoiseModel\n", - "from qaoa import *\n", - "from pylab import cm\n", - "\n", - "from matplotlib import rc,patches\n", - "from scipy import optimize as opt\n", - "\n", - "SAMPLING_E_ATOL = 5e-2\n", - "SAMPLING_E_RTOL = 1e-2\n", - "SAMPLING_DELTA_V_RTOL = 1e-1\n", - "MIN_SAMPLES = 256\n", - "MAX_SAMPLES = 32768*2*2\n", - "SAMPLING_CONF_IDX = 2\n", - "\n", - "LANDSCAPE_RESOLUTION = 16\n", - "\n", - "CIRCUIT_VERSION = 1\n", - "CIRCUIT_DEPTH = 1\n", - "\n", - "font = {'size' : 16}\n", - "rc('font', **font);\n", - "rc('text', usetex=True)\n", - "\n", - "backend_sim = Aer.get_backend('qasm_simulator')" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "def sample_landscape(G,gammas,betas,landscape_n_gamma,landscape_n_beta):\n", - " E_landscape = np.zeros((landscape_n_beta,landscape_n_gamma))\n", - " circuits=[]\n", - " for i in range(landscape_n_beta):\n", - " for j in range(landscape_n_gamma):\n", - " beta = betas[i]\n", - " gamma = gammas[j]\n", - " circuit = createCircuit_MaxCut(np.array((gamma,beta)),G,CIRCUIT_DEPTH,CIRCUIT_VERSION)\n", - " [E_list,_,_] = sampleUntilPrecision_MaxCut(circuit,G,backend_sim,None,MIN_SAMPLES,\n", - " MAX_SAMPLES,SAMPLING_E_ATOL,SAMPLING_E_RTOL,\n", - " SAMPLING_DELTA_V_RTOL,SAMPLING_CONF_IDX)\n", - " E_landscape[i,j] = -E_list[-1]\n", - " print('%.2f%%' % ((i*landscape_n_gamma+j)*100/(landscape_n_gamma*landscape_n_beta)),end='\\r')\n", - " \n", - " return E_landscape" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "def plot_landscape_symmetries(G,E_landscape,gammas_landscape,betas_landscape,\n", - " landscape_n_gamma,gamma_min,gamma_max,gamma_period,\n", - " landscape_n_beta,beta_min,beta_max,beta_period): \n", - " inversion_gammas = np.arange(gammas_landscape[0],gammas_landscape[-1]+gamma_period/2,gamma_period/2)\n", - " inversion_betas = np.arange(betas_landscape[0],betas_landscape[-1]+beta_period/2,beta_period/2)\n", - "\n", - " pl.imshow(np.array(E_landscape).reshape(landscape_n_beta,landscape_n_gamma),\n", - " origin='lower',interpolation='bicubic',cmap=cm.jet,aspect='auto',\n", - " extent=[gammas_landscape[0],gammas_landscape[-1],betas_landscape[0],betas_landscape[-1]])\n", - "\n", - " # Coordinate axes\n", - " pl.axhline(0,linestyle='--',color='k',label='Translation symmetry')\n", - " pl.axvline(0,linestyle='--',color='k')\n", - "\n", - " # Inversion points\n", - " labeled = False\n", - " for gamma in inversion_gammas:\n", - " for beta in inversion_betas:\n", - " if not labeled:\n", - " pl.plot([gamma],[beta],'ko',label='Inversion symmetry')\n", - " labeled = True\n", - " else:\n", - " pl.plot([gamma],[beta],'ko')\n", - "\n", - " # Unique cell\n", - " zone_rect = patches.Rectangle((gamma_min,beta_min),gamma_max-gamma_min,beta_max-beta_min,\n", - " linewidth=2,edgecolor='k',facecolor='none',label='Unique cell')\n", - " pl.gca().add_patch(zone_rect)\n", - "\n", - " cbar = pl.colorbar(orientation=\"horizontal\", pad=0.1)\n", - " cbar.set_label('Cost')\n", - " pl.xlabel(r'$\\gamma$')\n", - " pl.ylabel(r'$\\beta$')\n", - " pl.title('Landscape symmetries')\n", - " pl.legend()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now, let's demonstrate on an unweighted graph. Note that the graph itself is constructed to have no symmetries." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "V = np.arange(0,6,1)\n", - "E =[(0,1,1),(0,2,1),(2,3,1),(3,1,1),(3,4,1),(4,2,1),(0,5,1)]\n", - "G = nx.Graph()\n", - "G.add_nodes_from(V)\n", - "G.add_weighted_edges_from(E)\n", - "\n", - "pos = nx.spring_layout(G)\n", - "pl.figure(figsize=(10,6))\n", - "nx.draw_networkx(G,apos=pos)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "landscape_n_gamma: 100\n", - "landscape_n_beta: 25\n", - "gamma_period: 1.00 * 2 pi\n", - "beta_period: 1.00 * pi / 2\n", - "99.96%\r" - ] - } - ], - "source": [ - "(gamma_min,gamma_max),(beta_min,beta_max) = parameterBounds_MaxCut(G,decimals=0)\n", - "gamma_period = (gamma_max-gamma_min)*2\n", - "beta_period = beta_max-beta_min\n", - "\n", - "gamma_typ_freq,beta_typ_freq = spatialFrequencies_MaxCut(G)\n", - "\n", - "landscape_n_gamma = int(gamma_period*LANDSCAPE_RESOLUTION*np.ceil(gamma_typ_freq))\n", - "landscape_n_beta = int(beta_period*LANDSCAPE_RESOLUTION*np.ceil(beta_typ_freq))\n", - "\n", - "print('landscape_n_gamma: %d' % landscape_n_gamma)\n", - "print('landscape_n_beta: %d' % landscape_n_beta)\n", - "print('gamma_period: %.2f * 2 pi' % (gamma_period/(2*np.pi)))\n", - "print('beta_period: %.2f * pi / 2' % (beta_period/(np.pi/2)))\n", - "\n", - "gammas_landscape = np.linspace(-gamma_period,gamma_period,landscape_n_gamma)\n", - "betas_landscape = np.linspace(-beta_period,beta_period,landscape_n_beta)\n", - "\n", - "E_landscape = sample_landscape(G,gammas_landscape,betas_landscape,landscape_n_gamma,landscape_n_beta)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure(figsize=(10, 6))\n", - "plot_landscape_symmetries(G,E_landscape,gammas_landscape,betas_landscape,\n", - " landscape_n_gamma,gamma_min,gamma_max,gamma_period,\n", - " landscape_n_beta,beta_min,beta_max,beta_period)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We see that the code finds the correct unique cell.\n", - "\n", - "The next test case is an integer-weighted graph." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "V = np.arange(0,6,1)\n", - "E =[(0,1,1),(0,2,2),(2,3,5),(3,1,7),(3,4,3),(4,2,1),(0,5,2)]\n", - "G = nx.Graph()\n", - "G.add_nodes_from(V)\n", - "G.add_weighted_edges_from(E)\n", - "\n", - "pos = nx.spring_layout(G)\n", - "pl.figure(figsize=(10,6))\n", - "nx.draw_networkx(G,apos=pos)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "landscape_n_gamma: 201\n", - "landscape_n_beta: 25\n", - "gamma_period: 1.00 * 2 pi\n", - "beta_period: 1.00 * pi / 2\n", - "99.98%\r" - ] - } - ], - "source": [ - "(gamma_min,gamma_max),(beta_min,beta_max) = parameterBounds_MaxCut(G,decimals=0)\n", - "gamma_period = (gamma_max-gamma_min)*2\n", - "beta_period = beta_max-beta_min\n", - "\n", - "gamma_typ_freq,beta_typ_freq = spatialFrequencies_MaxCut(G)\n", - "\n", - "landscape_n_gamma = int(gamma_period*LANDSCAPE_RESOLUTION*np.ceil(gamma_typ_freq))\n", - "landscape_n_beta = int(beta_period*LANDSCAPE_RESOLUTION*np.ceil(beta_typ_freq))\n", - "\n", - "print('landscape_n_gamma: %d' % landscape_n_gamma)\n", - "print('landscape_n_beta: %d' % landscape_n_beta)\n", - "print('gamma_period: %.2f * 2 pi' % (gamma_period/(2*np.pi)))\n", - "print('beta_period: %.2f * pi / 2' % (beta_period/(np.pi/2)))\n", - "\n", - "gammas_landscape = np.linspace(-gamma_period,gamma_period,landscape_n_gamma)\n", - "betas_landscape = np.linspace(-beta_period,beta_period,landscape_n_beta)\n", - "\n", - "E_landscape = sample_landscape(G,gammas_landscape,betas_landscape,landscape_n_gamma,landscape_n_beta)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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JHDBmQj8NtJP1I3z/vHOO6yEmwTcliAY5mJZtCm8bewEzWe4UUZC6L+VeUrSMxNsmamv59yPL765NfEdBneG6sTo5hAZq9Rx5PUdzsGXqUubLG9NDP/1xSmLll+eW06YYabjjZfKoAXVa69vFoZsAXAEgCuosi7cTMOZXwFYuBuhijUvQ4aBI6+Z5FjQUqRETnSuTfjumBlqukvCGJpWepP85yKMPKtYQc0DXXmoa3XQygHdQ9Y7rnAHfEBsQVw9Ankub3U/7sVG5S0f4IgHFkZLsiJpoBY1LDLAQWAnLzcFwOaBLMVOyfKQDlnDPuuAvLbIE/Dg/V8xnCORjjW4MCPNy5k4LHbRtXWmhafUvGBgJ5pYavq507KQtWez6ALp1jS41vIMtZJ0MeVZn+Y0D+V5gO3ZvGesiBwApf0xpHunYxjjIRx/tCoGVKLhDkbHuZUIsaz8k4y11Ir+bBtruXArox9qT2IBROvdzQHdoqVFsU6x06x2gnqPbyVw7HPueytgaf03cGpDy0+O64YCuiXb0W+FljQEWOpeqtzGzdAzIpHSwHBcWkpR7Si8Tcx45lxogxgYGdJQPhnybIibOMD1E+6COCtuU+oD91ejWO+gWzPf9tbtA2sJVDnp7tyl0nK7neiGdUJvScTUp/W0/akCdUmqCJldYmYWZPdtTNJRpxlylqYeNS0fhuXoWr+o8iCfolokaY6OgKGVSMP/Qj/yfXSP+L8bSyaHdiy1GvuFRc8w2AKDurlQ9oxoVn85z5qP10LkcGovQWILWCtAKWgOw+z1F6fL/gWI64ppeOo7rF1CoQaEGo5+Guy+lH9KqBi8//XbsOd4gsfejWRrannPKZOWT9UYBSsmnxfMXli8DUINyn3BzGdGcirVOllYhHplJA5hpdHDLY2bwo5Ut22F1QKNI/h115Le0NGAaXNoA0QDTpgA0DbDr1JF38mBkbS5Ns8y93Auk9GJzeecNxIENdd4LGEYT7URnVE+CFupwlgvuYmWJ7VMnkGKMOKtD5W+ihQbawaCxDOhLXdAgS3ZA5n1lgW4coFtq+o65UDcGAAwEHXSthKkj4Fxj7D/gmb6YSCtAmsE0dUKCu1CvpvR8wNhEy3XUvVjmFKDjg4JuJ/M6GGyJwsTMqP0DuuLAMT5QlO+YXx8Opo2e+DX+jEmnxdoRDmMc2SDZXFlfYvUGMG1KfQAYrCOv52gtNTA8shjkWQKslE+o22cuNHRfamAsmbnUNyXbFdJJbuuQBLoxeVSAOhvP7ial1LjWetYeHoNZV3FZ0ulkvnFZMpXlGL2Et2b/B79y1NHA0JBFU9r9Ugetgg7bdNauE0cMLsSBhQcXcVCn3FVd1NCFgkYtOMafQ+n6FMKz/Dk8ZfMkSr0LhW5eg9Y16K4CuhbUdVHEEEpslIMYoAPSoE7oF0CgYxdeUBXhGC9BTeglrh/lznKNdkVqEgJpln9tAa8JHaSMnjiwY+VSNfu0mqk3Bth1BeQuC/OLQlmKkJyXr3g3v5betK9fXZGmubKrNR6/2MHY/Q082HwA9w+2XcPOJQAx7FvCEuLAjlqiQbvfMcDuEAzD0oBv5LgQGyQl6VgedHTFxlcyLzFWxtwbAiYzqm64/QD4SNCyJFhKAiyD1gTNhLt6BBMrSpmYogmwoJ+SiUlUdgJ0zQiwk2Un4EJdvJwQYDpmKm5uu3ZfxpwYF1lPSD9OT/AddL1u2LuUWOAcXCOAMnf5CHQQ8XctA74EXui81AtZANpoOKBidNN7Rmt0gMQGBcRgtpeaAbArvte04z7lW4IQqvup+8rYK/peONsrAQ7pqG2ZOV/+yODD6YGx/kuq2KYU2H+7DQKAQrfeQG6/J24BKNNNkA8+QztPR3uIDwjzqG5SDGbd6YkPlMrZxV9aUGeB3Fqt9W6t9V6l1CQDdABwHky8ur6FOiLXuNjKcvHAf+Kxv/JYoDFsWt0aYDrHLky3p6GUsp257WSV6dw5q0d3pbpYHeyHgMEdVxyO8U2jhpzBsjio01BQNs9gv0pAiBrgIAZYPrSGB3RUB2VPxMGcyyA/qNlJUfDguAHOFiNZnRowpy0bpqJAkZdWC4jm/+fStTrooosaauiiC40a6I36XwmKKase0BGjCWI0XXl8/dBdBVUDtNZuEBBqoFgu8UQBYmP72uVTFWoefw4Hh7oAgvnVNaWQDdfxuMcciYn/PIDPHDNrOyo/2uSNrwMxS/Bb2ah6CcAI/a+AumcnJEaJNYLB/8wcXuZMHwN0viNqueNlwKZldQDAdlLMsTmmixhDCQ9UiLWT+Xaz+ZibR4xB6Uec+S7PnBkqNCTnDtBxVirFUsaADAfcTbQtsPO6oja3S0xurI7UU5vy5jUpQb83wIBhWr984oXsrGWnTICXAN0QFqO6aVvNBXq3sC/WQcf86KKAjpsZCeAOthywS9X3uBtQWDYJ6Di7Jlla7oss0+T1hn9PcVDXxgKGg7RbaAQDgKCudOrAATYAkPXGF9jIIAJ95YNt8002+aVp3za3Lya/Jf2+hS5Tg0QJdCWDyf9vs++mTB6xoE4ptRYGmG22/+8A8FnmO0crSJDP3LRSapvdPxLATcuZ/Ur+dHmkcfn1gSXUmo/3/ZvBckCtZlBGDRYcwYI7gAMXCezM0f4XNaKg0SGA0W4zYMVzajXX4YdX8ydTVw4QYCHoUmPXa3YODKwwhi7G1MEmwzFcAPQEmIvbmP11DIB6/frjMWDnGSfPPHmwErJQ2r4jow8D6BQy1KCtVj2oC/MDa44OGToP6Gr+NbmMkSK6Dpgm4HyifkhONeQR42wff4thqjIdXn/CtMwe1bLB0QaOerBpO7e2M5uQ5J26HU1bEHMAaWBH4kbTYJ15sQHu7eNTj84UpAaYM37FjqwVbXglI1PW+C6K/HWcqUgVy89BCmCAyqBlmJIljHcmMedrr5MiWOB6yVF3nTcAVuYWhrEYgNu4+dX7/3iDnPG7JOaO2JgYq2sAL4p1xBcu3AYR6k1KjMyQLJ80VyIEdsXbQ6A7jEUMYwENtDGMhaAuEbCVnXUHGRpoO/NiKcvcCd9TwYUhEAV0MnQB57LAAUvKH9SfTwM6GuTIe6XJPUzPfztGR/GBAd27KMBwCw000XZ+u+6ZqYFir3rDdVYHuksNdAZbER/48naF8lCIaMB880iHvh0JGTnu1pBiwflAMbd1htrZXibYRyyos+DtdgDR5cG01tcAuIb9v5f/f7jSXWr4ynEAQAcYGe0Aqs7AHHw/XFP+uEIAPOIsUqEkbk+yZQQY3L+6CGAIIlBHHIK6kBGTcECj62AhPbtrqUgFhRo08gAEKA9SCNB1EQEubF+COzpfphqnW17CkBUNLtQqYDDpnAcmRic1B+g8Y8ev9FmqWd3UHODpBcGdydXpp1YEvUESVpdKu/cqNB1RCJ3jPpWhmdnnVA4AiLEr5Fywc9ykH3C1NpUautDI6jUMdhSaaKGNBhYxFJpPaDTNG9sUsCMZFP8fgGuAMbIAYw4L/WBIUg7E8aDGIb9EjS8HdLLhpc6bN9CAZxpoIoFhL4r+VQ60kA5SYHYQpsOKADvyA+uHeUyJNOt5neQ2K55rMx2yBy7SVCTZOQ/lDIDL4CdfeXNj5u4I8kDgX+pIAl9nnmc6i/ViSVBH6ShgqWlMl4Pt4DJu6paO9JzJpDoyjIWgfpCvnGRXvL7INypPdtDECHUkOyVN07xcMCZ8BwQtYOH1IQX6TTJFV4QQzHu3BWlal0xd7NuR9Yjub6FZOGaY3mYIiGlwFKsrvM4sRXQzCGMBIGtApx5MqOGmdS4EuuWkHvee2KBIzqJNsf5ykCj9VkkHDTSxaL+pNhpYYG1smQn2EQvqfhHSiXVEHaDWhWenqJcjYKdh7YIwbJyWjJL2p+2t0lmfm8liQsyUUjYfSsIz0wlnEf8xeiI9zQM4vhGPU7Nm165jrgq5IhaqKzYuBNpqCABvASHwXykex1lw5xPTpFNrzuTmS89YaQd2aw7Y+S2EadpqzWeJDK9dqzF6Q7H3RO8nmEASYzHpldTgbckC4ZZN5Ih59HFAF5pSQybSM7E+K5ROUUcEgHORF+VYTCij2yEsYgHDrjGqI2dOzKLxlaBO+k0twXfUdKwDoFMvhHDgnad7rgAsPPxDctIBa3xjgE6Cmlin1EEWNL78vMlLPeyIaKMyyla4BNgB8DPCI748WaTRl4A3FYPTpW87ImLqyjpkbmolhooYOT6bkfteEdtAYjpqFE1psnMm0M+BXUx/qf6Od/BLMMAOdXQ7ET2SmRt81rUfCBBzQoBuyNYTXi9j5jJiofoxoxVYutSEAK6bTh1AG51OFnDnqZmnplzcb5Cz1UV2zd/fDt6/HExxQEe6idUhAGihgcXA9Gq+owZayDAUZraTFeuIbFukbupgLh1w35f7DoQbQ2oCC/elK4SoYsGfpRUgBehCsOtBHemSs7s0AYusAGUz2ytQZ8WYJJivAq801EETwKBWlvZ5J02WRQ3LKOkow0bCpyikAINn64oAJmSkdNAxS/qMOnfO8yh7J/mTEZxRQfphjqOgjuNH2gjAEADmx4Eiwyce41YmDvwYQ1NsmX65b5kHdDkzL4ZMHYkHQXxLGEPdu6EXz3TEN66bSJIhR6sjx4KniHcfm94S5BLeF9BnJjTfGv1kAVvnwSJpSznzvLmfd/xBh0EdtWToYg0wEDa+tO+uUWJUHY6IgbjfC+AbX/oNfKgijW8M0A1hIWAcYsCGAE0LDcxjNOgoc+qIuD5kuaUMwk4WKQK7OvOr475wUie9JKUT2hrWI4zrgDofEjmTk8Bdy7IsZJbPbOdPDNAihoN0CqCO6ogrNDyg48CuF6jjk3D4tRzYLTWTplivF8/kcMA7jAWMYN7VFQnq+EQDAitta1bkgSqkeEAnWLqUPyr7PxbjLyhX5Hkc9NHghk8GIWBSyCeKvpMAXF3hwHcU8wGDRzppsEkS9A0t2PpBzDHpImAreXvC25UY4CUZ9NfE9OTfs5+hHZRXhJUByl0hJDg2/pfmWxrCAhs0hkwdB/5tNDCMBduu/BL71P1XCnVzOe+IJKjjnXNN/O8IFw86iE1LA7oQSuggIZu8ML9y4axNzHyWBnXeMOuxqYYOWLoaAwi2TFQGWW7O1HGgQmCOAF+NXVNURfF+gIE5ukaFF6o4oPO4klgoDupi+qHSEl+pnBY0S4vAZArgBSxdP8A1ogjO5vISF6/zjB5n6PgbZrURIX/poTEC3XiGjgCeCuCEsgZ7ADCTckwDNRqMUJ3Ib0k2vtLExs1pnFGJYBTuuxQ+0rMbvPFNhbCQjS8fVVMDPCyYBg5siJkCDMBZxLDrEEm6sXYlBuq474/rmFShlY6BMaOT4mxHmkFXCKJqdZPVOwWH8RDYtQJwx0EKXUsmVZrZ2RaAjrN2udVXMAjg+onpSfpFyXrCddhhvymfPBIO7Kw/WiEGaZYGvMNYtCxUWD9IJ6HptY4WKzfVudDw6/1B6R2FL41tS0icK7YYnI2Wkzlk2fy+nwzCv4mAgYY3u8q4jHxQRICOM3bchN+y9cYUw9SPxRSISZleywaL3K1jhF/j88wBFbUryXdkJ26VT5LwOuQWgBigIzaTvxvyKCT9GKYu9OdNSQXqpMTMAAReOJjjbAs3w0I7AEJmwlDC2atS4oyd7Yg1s9i5tPxkAN8xa2di5KkCCtft/AzetX1HMW3xxNtn7nIdf4wxCpAhR4hACOayIBsFE+wF69dh04WTOOeirT7dGLALGFFzoWFDgZf8t+MxsXkT/mDHu4LMcQaLgEvmmDrPZoUMFEFc4jQ9R5USmihR0I0cDJC4OkPm4/Dm8kk0IfDjZmYE5fLnwqFDjb3XEOrXAj15VpO/QM73KWjbsUWAHWcWYiPqmG8Z76w5oOtYkyFzaq6zBhgodiqAb3y5ZMLcEm98vdmI9rkZqQjqTLPfRrPA0pmLeoA66nSWUAR2datL+E8sBVBNmUIndG7OARDEzCMd1VnQ9NCnyoNbztZxlpIAGz2bm17dM5n/lfE/bIDMakHHGBtQpxgXqbsYqOO/cqBAEpgthZ9hATR7U1rDsnUhaPH64Y7uAJxZfgFD7refDjowvVJ5YhMlZHkBu5Id1lgAACAASURBVG4yn8oSB3SxMpbNfnZ5Y2ZXPlmC++MN2XozhEWMYt6yda1AT8TKATQwMoCOWPMooxtrV2ZRrDeDYv8ADLCz7zw1AzY2ECouSUYDyHBSitGBZxlJb9S2EKAbxbz7roYLoK6NBQyBfA4PCJN1mVSgzorzA4qNGENaK2RhpPB4ZCWiRCKFSRKAmx0Z+NQFaZj7+exX7+DuvcS8H53GRVtfhrPOPdN15V+4/svYPnkFfjRzp7vbTxAgvkpAGglWpO9YDs/U0T73rYulFRJCofk1CZ4VoIDXX30Vjv614wJ9cpDjHf8NSMngQ794DVLyXaebnL3s0PMtIQGbKHTEy5G4WfrM9fEwhOZT/wb5/Z6DVKDgLf6cZzMpHQJ0HgCbtLpMC9rqlTfQYeOr4t+SBHa805UduGt8w5JzRgHw7ByJbHzpGAdDxZhjHXh/l9BsJE1soUmt7vzpqMMuBKIlP12uB15WXv5oZx2ydQTEHqoQ2yD9r/isx4bthKjjkYCWVkUgQEc68WkZBs9fb/wPC7NgJcOW0hPv1PkgIGGKDI5x02vBlGl03I0wMFRHqJ40Xee86EywMVDXgF/WiWCg0WLeE1xFJQVYU2VGyN6WzRrn7KFn9sglIQxLQuXja0DzyRLcdN+En2xDoI6+IRLDBnYcS7eAoYC9cibtMt/LFFPH/XRlmyJYTT4oJZcCIJzVDzCsgCLw5+ZiCY5jzD/VGwPq/L184pV3CQlBdUoqUMdFVhral6Y0ydIBJR22MrHIog/s2y7n0kLQ8XPGhSYF5AGwo+dwY+r42KiDOatWrQQAjI+tEF55XWuGJD87gVDKmDqFOAim+0Kbc1wV9D9jR2/4q524+fO78OEv3wRu4t7w0peilnlkyc2R4axgYuo8CDaPUmw/dzogtq4L+dJ7SNlrLTnnzbzhO9aRa5iR3r1/hdAEe93OT+NLu76Mv77p09FsECAE01HG9ET7Higb82sHQGZ15sNdREwDsgGOjao5I0XOzNT4sgZa+r/wziVmIgHCxrcWAUGxxpc6I2JjiGXgI2sJ6qhDGram16IeVLFNkRMlYixdwEDVIQPnxmL3cf1Q/lw2iFURoTJizJ83ubVc5yxNcA3AATZ+Hz8WrgnsTa8OJNRzW66BeIctQT8HclyHXGKgh67h9xSAnWfrUmZpHrNw2HbGI7ZjHsUB9x2Qr5gpd52Z5nkHnWbPChNZYoCO1w8h9XoILqQDv8mX/KY67N22HRDhzv0yZAsPoswd/P3gqMV05QdIIfhtOWaMQB0xdbGVOgp1pMwCwJncERTqVsHEjfhg0Yc8qwdtEZ9pHM4g9xsfKBLzT2CO1xvSL5+c00YDQyJczqM2+PDPTSS9S41ACthx6dnn+0S4CTbaz/Ngv+RXl4h1F2fqyG/MPI0bFfksV56Wt3KSic0DoxzGTBi4+KXMjMSySZNsqsAxRitm6ubn3ezRUDjIjZkVuc8YB01daKunmuXqCPSFgDwwj8f8HWNAleslyKwtmAgoLS9NVanQhMrrgFz/wrBzRJb6gNPedBvGOWTm124XquseCGQaGShIs3YdW3Qk2e+oGgjZFmp8oyxdJ3iGNC+SeAdzc47id0HAP9n4EmM37HylPMvAnb05qAPI9EogqFVseFMMFOABXS/pZA7YdRKMEv+NCQcLtMRUmIaf5chj9/EOKQUKzLFwcgGPM0am1yYaXu/ks8bLLwfWJHJmNJlSUz51/JebXyWojrB1kg3luuWx+6j+j+IARjEfgDoOrCkkhXdTiPigHo6UADuTX29O5eUo25dhbSSwM9eHTB2fQsEZPvqGRixLR7/DB5eQdYC8DrQHB4AMoKDd8xhlbYr5nhzwlUC8l1vHEvzkqxiTx8ofYzKT74i+owjT7XXQceDd+6T6waJhLn294aCOBkZUZ0gH/dSZWs8r/h8RF1crxdTxyQBWJn/rDEy++AxMvugMTL7wDEy+4AzsmvoLQCssHVzA5MR6bN2wHlvXT+A1Z2zEq894Ab7wiesAADP//4O46IwzceEZZ+KiM87ERWe8GK8840X4+8+aWMr/8bOf4eL1E5icWG+2jSatr3/xSwCAu//5pwiZmuIM2NCnjMew8+wMmWh9p26Ov3zjufi73V/An25/O549fgwUNG649qM4+6lrcPJKhQvWr8NP7rjdAa5LXr4RN3x6Jy65YCPWP2McF5y5Dvffu9edf/dlk1j/5HGc/DiFCybW4f6794Y6tRMubvjkTpx96hpz3YZ1+Mk/mmdcfuEWXP2GSXz3q9NYf9Q4zn7qGnOrBs4/5VR8budH3cvZPzuDt02+Ec8a/zWcvubZ+Mg1HwkA3VkbX4OP77wev7XxYjxh/DT8xrrzcO/e+4JruL8a/f7x5Ovx3PGj8Qw1jN9Z9xzcv3cv3vV7r8X2l70sqEsf/KPtuPyCLQCASzZtxA2f2IlLNm3EyeMKFzzPlP2Df7Qd6x9/JJ7/2MeyvGu8euNLsGvnx/HqjWfhKWolXrruN3H/3rvx3u1vw6njT8Sp40/EZ3d+3OVp/+wsXrvlNXj6+FNx2prT8MPbf4AaNC7e8vt4y+Rb8Y3pb+H48RPx7DWnu3f7Oxt/F3+7+0t49/Z346njT8O2ycvxmi2XgCZG1JDjyu3vx+9s3oasA9Ryv2Wdruv4FbqMvWqFrEMvQEdsHf3Ootgw828wwdTx/4NvuQ/xnVfY+DYZOJOAjjqlMcy6BpnOU0dUNEWLTTJRkn0pGYinZjZKH0Ovl2JinG0gABPeEzrKc786Au88pIcxO3oGqslAIA+wSp08N3M30QqBZZmuYlsMLMvflM7lNYyti4n3NfSzo3nd4PVjJKgXfPaw0QvVvcMyw0oRjGTNLivHTcZ88MI3BLeGM2BlrLUG+zYI6PPZnf678Uw3B74OyMwtYXAOGNgHDO4DVjx4COP5rNMh15uMkefKW9au8LYlFkqJvW85qz4TOpDifRytn2uiXeK65+xsOFj09WfElf2Aqz9DhQFzf3WlAnUAAi6kQMmj3IfusJ7GqadYohGepnAZ96nikyXCdWBVAO4kUPEMUbiMVhez+2bw1ovfjPnZOXxuz9ehoLHyyHFc953b8L39GpsumsRrz9vgsrJ/dh8+dM12XPHOKXzha3cDGvjkX+wANHDz3+zGj++4Dbf8eAbf+3eNK//0WqxcuSrKdq4cW4Xr/n4PvvfvGpsumMRrz9kAaOA9n9iFKz4whVOeP4Fb7p/B5++8K8qUKQCv2vASrBhbgTtmfoq/3fO3+MZN38Blk1eCzIkz++bwh9v/HH/5l1fgX/d+EYDG+3d8jDF4OgC/gMZXdn8ed972fXxn5n78QC/g7dd+GCtXrcJFb7kMN3/uc5if9SvU3fjxndj0ykkAwP6ZffjQH2/HFe+fwi33zAAANp24Bk9ddzJu+d8P4pXbt+Fdk69z72Nu3wzet/3t+OOp9+O7M/cAADaueSaefvJafHfmXmy94k14++QfuGe9bsurMbZqDD+auRM7pq7GuRt+Fwpd/NWuD+F9U+/C8yZOw7/MfB/fvetr7hmz+2aw7eJtmJudw1f2fBmv2z6Jv9n9d5ibnXPg/2M7b8DvvXqT8YnMYb6D3MRszHIPfIdcrKVF3wDXI6Pq1GSJWOObijllJQzyGTb4POq7X1KpDojYbBwExRpfMrt6R2/vVzfaMh3T6MEDGM4XAmDjR9wlzt2yfQEKZXw4pCdzF+mQSIpsHQG5VqJj50tBcdDmAZ0Hf/4+V19iJlSpMwncUkAtdU/ZO+BsXaKj9v5lPAbbQgBCRjGP0Xw+ACjcH5G7KcTYs8OSCA7N6hKg+ckSkunmvlw8P/K7CIG7/1+aG/3gqM2AbMsAlrklDOwHsA/AHIAHze+KBw/ZgVIIhPm3VGhX+hksxli8RLviyx8/4YIfuwO9BgDSF7M4uYYPCEZb8xg9eACjrfkA8A2z74a/m5RU5lcuMrgjp2kjAGTqS18zPi1kbqzZC5XG4PAwpqZvsQvPd1HLeODbLsYfcyQ++bUvO3Ne6NYPPP6YY7Dz5lvCReFrGrVaF0COJ/36k6Es4gxZunADuMmNlgWj9U2pYPyY+VUATjzpGbhq6r3oYACHoLFxyyZ0WgNAGzjnoq24+s2T+MkPb8fxT1kLAJh40bk4+pjVgAI2nnkebv32Tc7n7oH79uLWr0/jqc88Ccc/fS3YowMT64YzN7tj51ywFVe/ZRI/+cfbcfyz1nrFl7i3/X+7b8T87By273g7FA5hfGwFPrbrQ/hv48/CVTvegMeMDQPQ2LJlAr927FEAgHPP3Yjp6e8GJloOfknu33sP/mH6q3jqSevwlLXPQlfXcMSKcZyyYQM+seM9uPSqHbj1q9MAgFPXT4C+u4mzz8XRx1m9nHMeHrh3LzacsxlQOSY2n4P/ccVbMT87i7GxFQCAF557Np64+jgAwIvP24T7996DF24+CwDwgs1n4b3b3479s7O4f+9e/PC2O/CZm/4aCjmeN/Eb+M2J0/CN6W/jjInnunz7MvgYMSeedCLeO3U1aALJ8yaei/dfPYWrd7wBX53+B5PvM041Zeiy27VJIcsMACbzpGx0nPRqgGX7yf3pSpgr5zxd1oRFGl3uJ8VBDzW+nG0ghsE3sIsYPXgAgwdNngYANFuH0Fm1gGEMW8f5hDNzDECkJkc8DK1yyizdSyQA4EBO+tRlyNCCd+om8aE7vI+V9xEKAUEDLTQHWzhkHh4KN5NyM6MMcSLvQeIcPx7zYWRSmDUNbzINV0lgDFQ+j6EDh1DPgU52CPWRHJ3M+FoecCbbMM5h34CuLn7lcdqvawPoshgzV2QGY8t7Ub6orPRdxFbM4MJnQdP9VHeGsIDh1oIBdHN2a8H0n9Z2O9pcwvxKYqkWWT1h7UoMvMdCm5DQexU+uvJ9+/fRCf53esoFmOsooB5nefi79YMcGiz6geKwqDcDLZuvehfZEQeQH5FZYMvBc292twJ1VgKHyX5H0NwBKh6FpFQ86CqGMXHx6bhPnQ7vlTHJuKN9GIrEADq/+qdi9/DJBR7YARqnbzzdMVY1aByYncGfveVteOCuu7H/wX0ss+bn+KetK/rAaWDDizfjgfv24urLJ/HAvXtxyukTeM/OXRhdOcbKaLb52Vl88OrteOC+vdg/u69wPgTWKmDrFID7996NY1YfF5RvfGwUAHDv3vvwuLVPhgJw0jOPh7LfhlkxJIzXJmeUvnDzWbhv77145+Trcf/eu/HsifW45vrPYGTlOC56y1tw+ctehkuv2oEbPzqFV7z5Cp8hAMc/c11QV446brXJnwLGjhxnSjSFO2HdMwMwebQtD6CwctWYO/6j2+7A/tk5/Maa5wTX37v3Pig8OzCzy5f1vI2ng9eTN26/GK/c8ga8Z8fr8dG//ByueMsrPEsnYw0qoNYxbCafPOBMNnxEDcTZFQfomMPhAXg/qYJpMt5UxWaoBSNqmuHGbo8xfdT4SlbKO3hbQDcH4CAcYFc5MNxcwuIRHtj2nNnJy5XqpGNBdXsI70xT4qLoMxNSLB2TBd+JcFMbn/3q0gWtZJqhiRZoJmMTbfA1QhtoMEbU6qqeF5f84jpaEse5H12qnZYddwehD16SqYvrrc5YOqojvG4MYQGjc4egCPDXgXp+CJ1V86BQN5KpWzZDl6obQby+DrI6AdAOqxPeV5ImF3UQBj6WYKT4XfBVD3yAafneORgLYrId7Jpvh4M6wA2yBgaB0ZWhCZYAUdRHlbcrHNgBcKN+eb7kXXMWjGZ1c8kt4+/DyyhrAUibcMM4f8TULbo6E9SbJZh2JTNVdXhwAc3Ml78yvx6OxEwi3PzKJebRnrDPFpex4rc9NJtuaEr1pkM+C5ImU8SC06pCOn6CxcqxUff//OwMTh//VZw6MYEP/81NuO6re/rLoAUEF/7+Nnz+W3fhljtnsH92H278XzsLkwrmZ2ex/oRxnHr6Rnz4Mzfhuq/sCc4HklDb0auPw49u+74rs0IX9+69BwCwZvUTUOvm3oePAEuXyNauAHZ8ooTGq7e9EX931w/xrZl/w9y+GXzu2o8CAE7dsAErVq3CrTdP47tfncamV22NZy6wqvtJEuYUfx8ewabqioLG2KoxnLD2RHz7ru/gH+76Fr5719dx21234BVbzw3qWWhqN7/m3fr/z5h4DsZXrcBXp7+Dm2/+Lra+cpPXETfBduDMsApdEb+tXRxFxsxhAaBbBDAPGK4mbVazEou5lTYvqiQoTPkYycaXTLHD+YJh6DjTcADAQWDwIBwQ5ExXVA/yWEwi7AvqHaCeJ2bx9tfYl7KaIi1uPuJgl/9fF9fwAM60z/3seIgLHvus0WzbMkYyFKs/kv0tA2dl4C12LRDUFW6u5OXisfvIT0xRvbCbOggMH1wK/MM429U3sKvnnhWSwE4yePUcdeZPJ83o/B3zb7UY95GHNekU3j03xxZ98cJ9AsPqIMw3Qzp6EM78Sv+Pzi059p/YLJcWzdKWTB0fKAIwbckigAUAOu2LiSIjy8tfKj1Ok948++/dOnwYHGOOVhzo2jYFB4GhA4ecCToaNiohFahLScmozUmMqSvEqNOFS8qSCu7UZWdN2rKzVlFAwK/h5/js13BiRRgio4v9+wxrdvTq4wAF3PzF3aksFVi1W785jVu/Oe2OrRgT/nR2f84yc0cds9r44n1pd5DuyrFVeOAeM/mCzJzy4S/cfDZWrhrHH06+CftnZzE/O4s3T74Nr9y6GavGRiwrhxCw2OfXunKCidffd6a/hn+Y/qp70spV48GTL7rsLfjk+67BKc+fwOj4GCnVi6wAClAqNJGH76M32H/R5t/G/tk5fOSaD7v3+je7/w4/uP1OKHSxatUK3LP3Z6hB4+vT3yqwtxzg16Dxpu2vwvt2fAIT60/B2OhoEdSJTWntGl5iXhpomxmNsbhifMQMDQPm5mEa4P0IGuAezElPkcw70pMMuL9LrPEdxiJG5w4VGl0H8A4Cwy0+WSAy+1XqIlYu2UmXYLB6PY8ueda3lPgDydmPnPXxgVRbApx0CsCOMzac+eSrDZDeUe/4pb9cHhECLgno+gVs/YC5EssMH0hwU5pzfM8XMEB1gjpnuz84B2ZCazndyXhmUujdBjOcY0COb4N+kgRn2FITJVLi89URPqdt963IWHbhM3zdcYGaW23zzuS3MwfjX2fB3cB+CD9EBh5jE2oKQO2QTXyebUjXl6Dcfcwa72MiTag3P1jkk4WcOZrqDOmE6WWgBfcNLYfZrUCdlLJGV5VsjHUxx/ph4Pq4JrpMWBE4hgxcbDJECFQ4g4fgWBFo1KBx7Opj8d83n42Xn3Iqzj5hDf7p+9/DUceuxsiKMZmVAgMHDXzyIzuw/oRxnPXcJ2F0xRgu/P1thWuPPnY1Nrx4My44cx3OPm0N/ukf7TNGxwANnPK8CQDA+mPGcePHppLqu3HPLZjdN4vTnvRcnPyk38Qz1j4FH576I9R015lcA2Bn0zHsE59g0g109rEdH8Bp40fjRU96KkbHVuIV295s9KQ0zrn4Ynz3lpux6TUXF+nYaJ3RlsENmTq+H4tZJ+Vv9nwFd3zvDhw//nQ8efyZ+NpN38KTVh/t2DcAOG78ZPzPqc8iZorlz3n11s24efpWTL56k3ksMZklbF18plrEVCI7YgfkaLOMXYqBYSJZIi5uDWcp0eWTQrNUyNaFja+KdUYM4DWWuq7TS7KVKSnrqBlL16/wslBeyP+p4OyN+GxhDuzI9BibSSlNzZzNCtk+7lPmO2ryQ6wNtiNlZ/rjeiwDaPL65dxf8o58WTvCLL+AoQOHAoAvwV2z5Wc9ej329qkjEFOr57YOuJcTrn3r9o0/XaPZZgCyHXyX8tuUrgj8eGw2LGeMuDlW1pdMXO9Mr1w3HMSw74omCnhfXWZ+jYF+ajMA+LZkwW6LAA5FWbrw/XbYfvydeGDHt5QLQ9ieePM989U92DXZJZ0Qi3nQb3xd7X7Z3cqnrpfICpDsrHWh5y0uEfZQxPjBhdmQnb5OAoLQZ8/7MZ29+YWY0T8BrTRAWOfmPZ+HCV7hQc4Hdn0SbTRwaKkBtBQuvXKHCft1CLjuxj3e90oDF75mGy682AC3U0+bwKmnT9hlvsIsXPe3e4L/3/ORXf6aGnDpH+5wQ4/RFWP4/PfvYpNSjHzqu7ciy7qgiSMrx1bgI7uuxQAbVdfQgso10AX2fP06D1AAbLv0Qmz7gwuBLuwM2MwylD5jz504A6dObBBed17mZ2dw1OrVOHViAuhq0HJm131rT+A2duGbtuHCy94CpbpQtS5Wjo3hTr0fFE7k83tuZuBcYeu2S3Hxtje4JFaOrcRP9T434WZsbCWmdv1l0JhSnMKxsVHccddX4A3Rxndzes8XbOohozs3O4fVq4/CxPNPNe9VspmAcWzO4AAfrX/Jl06qg8xFzPzJzWcATGNLG0wlwgCAFQ+dpQMQhCcqY7xY55oJU4nzf+EdEgE56/sCADjCjKqTq2ukHx7u9wB0NcfexBXTbxwrJx1lH0Sxx4qAzRzPC8fJH4smQxg/pJhp2DjV03XDMLHIFmwgXjeTdrCFpcEjimydyyvKfeG4fx3YvvyNpVEixUCy7YDNHYJ1/ucdMq9zB4Hhg100mpyx7L+O0Lvu1nOgXrfr1BYyafXWQXPQhxYKQXgiyDGyArCLzWaVx80goRGc5z56fLDURBtqCcaHjgO7g/ahTVuGI8zx4YNdjDbnA8bc+V6SSEC3BHiz637xEoaAzkD4vhPvPvb9yAkhvYR/N5T3AlNNA0UJ5ChvdbgBQdbs+Ha1r+dX4iVlEomBOB5MF7rAzhGgU0oXFpw3t8VpJseV9elqJ02s3CeL4ye/b/7jgCVEWia4bG7XD5A+ZgpdoKaBmoqwlSxJeqgwsUYpJy1+KUvCjFv4v0Qf3HTs1sTlfnQ5is/LgVquobLQDF1kuNhtSkNrhY/v2IFzLr7Yg/uaLShF/OWZq2kD6gBwUzdnBs1TuRKLigsZVZ9Pzs6aqwyEi/nn8QHAe6/+GLZefI7zMwx0xcvRgQsuPdqax3BzIQhp0kDbgBEM+OujjS8HdXWYkfUhYGkg2elKny/joN+jsYsAO84oFs1GfsZeM2e+QGwE7UBd3ZbJmkr6MW+54tKvZFwc8xIDdLlIpn8QF8zg60O4Tuj/WDw8mqxiAFzG7g2d8gHj18cBswuJM7KIJVl+KWWMW0z49bGZrknGzlT00LzdcYAsWGmj1fYMLoGVHB6oHLS+dav8bM5+gw/T8/NOHbV6jm69A9QHwgkfgKs/tcE2srpnhPjkpSaKa670A1bCmaztku8mC8CMP2/LmSM0v5KuAL9qhwV1ag4YXuXZf+eLKEPfFN4/b1P4R8/8dUvqSy8/ui5NkhCXxUIlcSDN4z06xnqpW9QFTRzpWJ0sGYDbbC6jXUFlfi1KmemVhBinGkwnXtPOnEabkRgQ6IFKgktVOhlwrCBnsvrjsQTkcW52JfCWBQGLRaiPWpeVHyFokcWMbdGyppTQ/30coITl6aKmu3GwwiZLoGtfZwCwukk9AsDndn4UZzzmcfjn738fF112mXn3HOhzHdn6omoatVosDE0RlMt3LIXPXub3eh1w0Bi+BErvEzv/Gk8cfw6+f/uPsf3NF3rTNP3GfOvs+eGDXRFXivmTxfzqnOmVb2Qy6QA4lDCpxWnv6Mi6z+DDdD83FXGfqSbaxrRGnRHzlZJmEhz0I/OeTtYkBfMZ2x885CZGOD8pDjJs2ApThmWuTsBn8CX14cGbNN1Jc6v8DU1PXKfhBAPqtIexgEbWAgZ1qIuUX2EKnEXLGvmV95aIND/yejKEBcPiUhgNqhN8MoCtG808XCqqzCSaZfJdd/xyajShhAPgQQCDh9AYbAWmV9J/jHmjsvUqu/nl4VxaSDGAEvw7033e8t8QZ+voW6KYdWzjYT+cKT8T+S2YXmW7IgaOy2BopUSXbUuCQ8lsenBH38FAbKB4QBxrAWoJrvz9SsXU9SvUKdfE/8oDulin7xi75YC5woNj4jvz+PF+JXa9BlxwE8XAgQV3NY2cgxUJ7GJZitGGiFwrj3GyKsbcucf6gxzEuM2aXoMtZ3mxzJPqeoAUFi3+7l669TV46dbXQGsFrbVhWJVPj8ywJpN2AABbZwLg5UGkL7oSf1MiQXoIAnWgG+Lt/L2v2HoeLt76UsOwtfM4mJNLvtljag4YWTUfdFbG/JrDMXUk0RH1IjtpgV2PDjvp84IsbHz7ML/yRpczC+TLM8A7Ib6fs7RtfKlm3kI9iy83FEiKpXMdtQbqOQYGxZJm1hRXX4Z/nZSov6HLThyg8XMuL4x9S0kM/AEArZPLAzsPYxEYbAGDg6EuYiLrBh88SD+8lKQYu2g5fHw67hfVRDv0tUwwdVgCGkuH0Dyid2gKHntRsrIYJM6p6Rkja6avDbbRHAxnGfNl7+iZxM7xsB2SsZPvXZpySXLETLI+DZdWJ3ffSABa5uwxetfkW3fQzoJdGfpgmgk1QmHuvWk4pt+1JXWYNuiQ2cgEW9B5WE9LGcw+wSBnOD2gY5NGxICQ6gkAU3+OgGtnpD9dL4BXgbpeQuZXybhQoOGaTppYnfQ1aeKhiGRg+nle2LWH95qVQgnaFdZOrXUNqKMttOuFScpHpK2JD4PwyR8CiBJQkWwT5YOzdQxklZpeAWilAa3s+/eIVgN2/Vp73JpliaXjYWeK4VOoNMtRlGRp6ZhyQC4lBdAqWboYACb9HYRzauY+Q8ZcxB4SdJrc/LrALrLHOyviYE6O1MtEMlEsLckwSMduKsdwayEO6KiDYmYSLAFZJ8ImpCRmcnVbCwODbWT1jgNwFEezLsywskOicvDwJcv1CSqmG5rbeJqxtDnDY4oa/t9GGNjZmO5bGBxZwNLIYKgL0lPMlEr/034dIbCTgQac0QAAIABJREFUUnZviR7kLEY+yznaOXPAb48NHgQaR5DPZdjhR5+b5WaR+BSwoziD1kTvWbow1mJq8lK/plfSQZydLQLUaH3sdI0+WnajWfAH2TEAWAHHcg4cBIZX8pn1FpjKCTQB+09gzk6OAODbGgvq6D4hqQkjjktl60inLAhyIgPpnc/gbaJt2F0qN2fslli69P8SAlDdj1SgLiYp6p8DuhocoKvV0iCqFOwxKZBb0Vmvve5KA7qi0S08K2dfamiDSSSgs4AHtS5Qq4WTH8pJxf4kxeSlfplwMyaPyVeDLsSlA/nUSVCngZomkF7Oj/kHM4ZMGRzXtYBRk+Kded6A4jAmYJhnXx4qVX8iTawK3oOyF5lqRPsTMvQLZ+oIFGsYx+bWAoacX51lBwZbWKofUfSBgYYbObtRNcQ+ig2viN6+PHMjki1dymTUQMv4vcQaX3KGH4Q/3zIzYLNmHu1EfTkiWwDoNAYG28bhPcHIeUAXgqawXJ2g4y6wmAkJZwEWy8B9GD2wqydBQmymZ44MLTTCGaRY8H51/ZhggXJAJidO8Htikyoi5lgOnHmoCucTeHDJmxVl3eCA39YPPommn/rrzOtZjryeIetkaC0BGDTmwG7HmOYbgy3G0rWCUDFyAAMsD+THvo+CudjpJ4uDfA6+pPmV/Gzr8LNhKU6bi9Hmy+ImYBXEum64X9rEyy6pM8vxT+0lxQGjB3iKyiwHixzUHQHXzgZLpfUB7CpQJ0XOSANCMOdscl3vG2VNsACcH5x27E25+Y6LllcmbimaSnuJvKNIrXFHezpSQ5eButC/TtW60LVaqBtivspMqr3Ip34Yv6iEJkb6dfNUY+xTiqnr+skSPM24Txv/x3NrtRqgOUsHmLpSk+FSfB79xIwQTqYs2ikJgSGxdL4uxu51gJCbtxnQTZlfaXbfcHMxGI0WTIQdvkMbjaKp56aGOC39dIapeHSptOIja2t65aEQOMAjoWOGMClvdEvBHBxL1xxsoTHYdp06MTYEyrg/nS9L/Lm9TKTufpZeKryDnClJx/x+nd3nTdoNR8XQdYtooemWSRqygViHswXsG9HAiAp1wleBWK6U3dcXU+eBM58V3UAbTaoLvF4QqCMTLAMupAse+6/smeKgrw+dPFgBqTnYxlDTM1qc2SIHfS55wOj2A/TD74NkWbOtc3iGm+uLrw6yAoHvKg9CTC4RoMkiJME75G0KzaZnaH25fnQx3UjGOCKpCVhNtI1/IS/7AXj2kj6TOju25BnAavbr4UgsxABQZOgyuHVYTSfNOk8ljGYq7GB7y0OzSxL8oPx4HigMPRs+0Zte+T4tGlZD11bOzO53kWVddDjQlT52/dNLh+dqyO73foved5HP1lVdC1aIXeJghV4WO0YTWH16vbIQsmtawTBzWhROcZMrX46Mjvu0uOE0ZbMuN6lyKLcMMy7pRAA63fXlC5g6O7uvuapl12tshTPVCkwdELJ0h9hJ/n9a+jYl9dGI8xAMoUN8HmcWKHgyta80o64FqA6lKRpfqYcSlm5wZAGNwTYaGVuOK8sCwOSTWUanaiUvWR6MSxk4zZm2+P+0L01wPJ9UpjYabh1M3nnXRhbQHTzCrNUpGbuYSL86qeeO+E2lwX+FkDmT+1o20CqG6YiBOgb8ZFy3XiJXfOggQ6MJ5PUMDZh3mdVzNDK+VrFn6aT51fnqoQO5tB6XMpN6mK8GSy8uGTrGvZYzdR04UKMPAoreL4/1xywAzcD8moegDja9QpvC85QeLKbYcC456naJsDp7HqL1RQJgzvw7/0IObKVbB4WMojqUalNKpAJ1MZEjag5WagDIhFYLzWe+8wzBnTRtPhzSq4uWUJLDNp4L7jBfBDKGysrQRVeaYRULbVI2C3Y5hSlmKixQieo80+j3HVDiAIWbYPnzGIAxoE5C4tgzeYZCjSsAUP7Nh+xhkaWD+6U0UkDOn+1HDgszaxTAXZdM02D67MI1wkMsUGgTrWL4ASfU4HIAdwjA0HJzWZDAxNjHiJpE+k25GXt8BC23Dkzjy/3r0MOEk2LqRsxWG1lA0wI66oyDDjbYLUes/SwJJiUGNuj51D11mAk1dN8ummD5FcTWmTQyN7NxGIssgPUihkcWcGDkiHK/un4kBej6VAuxoamYbU20AzYlMKGRCnn96QD13KTJ2T/ZWcd8u/xvBqCNPLMgOkNgDuY+re47JIbLCr2jGEjoxdothy2KCoEUqxd9EJg/CNTrwDDzP6SNwnl4P8aW8dUFIu8xNSiUAK+fbHo99Mt0cwlNryGwcy4d0seQfqmu0/+5qTfmdcf9/orPrySUWMNLYC4zvyojZ3ffOcsZhUhCgT5Ep+8tD2gcusebfcnSpdm6MDYbLGBVFsjlqCFHxv3qsi6QZcVJJN3IA3qJLNeyVadZicN1bt0kCQ5U6FcAOrpGcpyx53E0mjKxF0243IydO2AXBjs2UKyMidPB++1fOF5L3qnDi52PIGBmY9E7tkwdDlAQYh9+oJG1+vCLkjRLQuzpXuxRP0Ij89hsTh4Gws3Yi5lgyfeFN859mPICPRTMrhqNwVbgmwh4MJVZiMc7mZj5OCYuIEVqmbQebEVs0gXBnTaa4PPyfN5C4EIdmweF9WDh9hG7P3TEIg5YkBs1wUqJ1S0O4Pph6oDSd+dDmbQCABWAfA7uOItLQK9lZsA2jvBsnc9uzCcyZHwca2s12XDXmXOc8eSTlpwvmhWascoNslSn+CBiOWbZvoQPsiwLtdgyG1rAQB0YECE9THw/z9TVkYe+usn32R/j79uVh8+XjiQ2YaSO3LCWvB3h+9SONBEwdVknRx+vw0kF6lLCZ6Zx82Kta5zdlTebeT8uZXGCnG/I2TwpYQCNh87jhen4TtznNuzOiwwTmQS1RWgG0NWQWWBXo4Y66yKvZR7wSof6VPYO51zZbc53MWTqXIgQaVKUPnUxYFcK6EhCn8kwVpwsUBHUSdaOmDot7pFg3AOyw6VGeTqxebfsAgvoHN7Vdjk1DuoOAsP5AppZuFh7aViKfhpdLolVFOJ+L/371EnToAN3NGOPGlc5qjY3+IbYZCbdQXAwR78jCFi64ZFF1zFTOg3ARXiLl+GhA91eEmPiKE95oMV4IGi+XFQDRs85MixgyPnVEbgbxTz+c+QQMDJQBHa9xgCpAcRhMHWUb9cZs7rRQNuwJ9LhnbO4gDe/2nqTdTyA62uihGXZMlZHGwjfKzcJe0DXdgODhmB8e5leAQ/y+mV7uRlegsIgDW6CXQIWl/zc9/oB4EgKDcPi+1HIm2D910GUSIypExKpI2Xvwyw9GA88HCZbHCiGMf1yY7LnwE4ODOrw7i1BWv2zjRWos1LnPkByRM2YOpVp1DIWKoN1wV3w+QK8O05JH51xFFOUuroLo6AMmlEr3MVzYgL1GnpGmaBtqMGYYHPyp7NbrdZFTj4A0q+uTGJYpBeajds/ARWDPGG4kIIPnWTuFApMXgwax2INhoBOTqjQwW/N5c1PPAnXmfX3pRm40CwbevP1K8uod9r403FrdTcHMjZRAgeBoQOHMLSS/HlE+IHD6FB/ni1THHj42WUZcuMEzzqggimW8siBX0pS7YoDdhrDIwsYzjzLQs7tvAMnYEfgqRfbY64NFdnvJBK6l3fSfJ+6KYqTz/3q/HPDSPjN3CguyzqgWHUe0Hkz7ODYPJZGVnnQewB+kM1NVLFJbfz/FABcFrALza7USTeWDoUgTrItQMjg5mYpOf7eUkBCOthLE6q8lhg5tzoHA0Fk9s7QQRvNAksoZ0hz38he0uuaUl/XHOjkPhAJcmCVZee4KZvHBmxwt45evpYpkWAuOVisB36jvSQ1cUm2Kw7Q0S/fpJ/u4UwMwiMc1CmlVgPYDOBIrfX2Pq7fBmAvgFUAoLXeeVgP5hVmBB6w1AyQCUN8kCu6siFANGqoWUDnAVQ/HJzrR91KEstnYIqwIpxn+YbJt+Efb7sTX9tzg4OdSt5NEwtgAGxNKcvO+c6EGDsX2oSYuhoE44U4iGPg7+zT1mDDizfj0rfuCDGTBIhJnBOaOD172vVMnWTouPnVF989n4cGKUqotRDQxRg+bgQP/elq4h5iz8qxMZlnfU79U9L3cEbO/3pXAT61guuD42AAyLWxvHOmbsCGbOD+POWN74A8UDweuZcaS84Kcb+vzjJAi0yTszKKm1VTZtblNryDYp+xdENHLLII+qYDi/mpScYu5pclOyIq1eEKQYwWmk5XZITk51ISACEYc2/eXEQb81jAkDO90u/wyCKWYibYGEiTg4Z+BxH8nHyHdW1iBDLwxVm6Js185SCfA39eP1rhcZ5WTDgIoMERZ9zCa8MZxsV4keHgILY2rzlXrC/+nv6+J85JmaKzkmbGvGovdLpZQLig1/xBYIWYfMJXlWiijUazHX/Pye9wwP+m6slypXTma9pPMkPHDwAJxJGfIZsU4Z4BHBawe8SCOqXUBIAxAGv6vH4HgO9prXfT/0qpzfR/ubCOjPvSwf5ylk6AupCVIarKc3a6gBpoT7nuOIQOtrMtYAkNRIMcewihxf/SPV8aJ80VKkzJJkSh97q5RlbPoVFDzsAczYitZTm6FK9OhjaR2ZS/dv/St+7AUceu9sdiRZSiiv8WTa+2PIRGuKL5fozJ6wmRSEKvRe7L5x/ETcPe54+YuvAegnZpNtYb92OG3zDXMa5YcrOpWdH8ehkRxsXfY40wn33XQNsudTUgGtEBFFtXvj8Q/utOp5345T6AIuAqaYTNbziyDtLoIJjlWmhw2S3RTlCCWxoscpbOhfdYhPeDaqPFTGUGyPpC9TK9yk45CnhLmApTRA7oPIj2cyu5GdYM+4CWe65jmlptZB0D/nW9C2AB7WbDMXTBls1j31jEBGtjtLlOVTJ1y+2s+7jOL5FFIMtoRPHOmdcNItQ4e9cPmxs805t7OeMmATyBQx5qhfvWSYDBgwWnWEIJzsyxkKGl1SjoWPgd1oN04u4RgO54tVBQo8UWsILPMD9oFrRvNLlbR6vYbAQ7scFiPbrL9fJQJBlPkn2Fxp8uD+sCtSt80Aj0BejKwPYjdu1XrfW0BWSzfd6yVQC4mwBMLuuhfF09vllfOgJ0WcDUeZDj/aMA2dlzLPOlT12PDcedgKfUxrH+uKfjS5+6Pp2nvsk6D+bCVUs9H+TXSAC6hZxZ0dqtZAWKMZxrH8rEbnXkqEEjy7pGZ3YSSYCuQqRVBHR22/Dbm3H8iWvL702VWsVMoIwVI9ZRTpSQIE5sHBb3y38FYVRYHcmCuhIGceb3wP0Cn9r5v3D+xnOjz+SG4JAXlJrg93jFh7ximE6hsLqoni78bFg+W41YOhNXqgOQ/0vQ2cZoFDaaRr23aY1JdHZaImRHrceEgKDDkyY0HpaB+7ww5qFU+GBxxP8SS0cmSL4uKs0IdZNPwNfdjIDQhPTn9F4sAHVHBNo8vAgBHR3jM2HDtHNkna6J+9cyJrbhg12M5qHpdRQHHLAbGFkMfA4LM2Fjm9QzX60jdT2QrF/UGZtLQvNrAbBxFpd31IKJKYtPV3y+nznctN8V1QsPgg+447wOcTMsDRL4pBUp0m9SgrvYjFAJ/FL/5wn98ohytAI0Z+loQXsCc86tI1YXCoNF+h1AoV1hW9mSew6gdjLjthB7bSIoekrMN5CH7YhsV0rA/3KY9kcsU7ccUUqtjRzeB2Bi2YnFRtSKs3SyYzZiOjv6vxb41nH50qeux9u2vh5LC2bNy3+792d429bXo4saXnz+y0xH2189cUKds1mn1T+Ze5cRwAsZGs06dNvdS58zZYnKWo5cyckSHdQwEK4uQZs0o/L9GNDT4liZ6TaSbghPuv4xKUYO5b9m1a9eL4IDPw/Oau75PoahBPnct45DMC1qjFdP6EOnEIKyGFsLaHBw5/eJEww4TfNbAqQpfQWYuHUaphG2I2vfidjgvYNtHKoPik5UwTe0FByUGl/7G+l8ywBZ1Ck7IbHltYLz1Olxc4g0kVCWeRLs0QVgw4FGBwVfOh/Sg1ZXWBTl8h1uA23AAii5/Fb4fNHJ5mlgF/MrCj3JMrQtY5gjd/8vYNiaYLmZuIXYygIZZ65gasFQdgijK0OWjkywo2Pz2De2otwEWwbw+jLNpaXO6omcJNFEuziJJtZRS2AHX++Sy4O5N8fXDOXwue3eNze9SrbOASCYd9lk7CkXbialCRXcnaEY1KUOHrQ45nFonteG80ur14B6N/hGOrb4BOhgfw9ZVw4Cd2oJdmDj/eqC7yloW6hNkfuJdiXSXEiGO2oBIClpbpKhX2L1JDIxIsZG92sKf8QydcuUVTAgjku/DB8A29jXO8URtQV1EtBlgnHxJjXOuoQch4LG+6/8YwfoSJYWFvHnV74Dyd7UHvZBdkMQ4FMPgRz95gF8ALuvhk0bX4WP79yF39q4FY8bfx5OPvkC7L3rfkADk5e8G1t+93LD2OUaGbr482uuxbkbX44MXRycncFlW34X63/lSJz9zDX4yQ9vd6Dukgs34ua/340PXrMd6581Dijg3W+dxPoTxnHy0QoXvGAd7r9vL6CAC16wDjd8aqcDFPNzs3j39kmsf+o4zn7OGnzyw9cEurhk00bc8Fc7ccmZG/H8xz4Gv7PuOfjZ3rsZPCFA5UHq5JvfjfGnr4d68slYt+UC7P3Z/Zj8k3djy5svD0yx29/5QWy54HIAwFkbX4NP7vwMfnfjy/Br6rE4Z93z8LO9d+P92/8Qp40/AaeNH4XdO//KQaJXbjwb1+/8BC7a+FKsUY/FS9ZN4P69d+M929+JE8ePx4njx+PTOz/p6s/87Cwu3vL7+PXxE3HKmufhB7f/EAoaW7f8Hi6fvBzfmv4mnjH+ZDx/zUnunb1641n4yu7P473b346TxlfjrZOX4fe2bA1K/rbt78PLt7xJcIzFKTH8HqeCCEMqLdbOoq3hI6Izps751Q2m/OrkwQGYOHXpETVQBGIcPDlWoI/AulKSDXBqFJ3ypcsSzKF5SMggWZZu5IgwpMdIBOBxk3av6PKy4S/tCBIsgzS9EsygN0tcIjF2ixgKvCllxxgEoGVMzMBBYLQ1jzHMYgyzBRMsRg4tn61LMXO92LrgPUkndwlZ8tA3ioO7WJ3hG3x9S7FmxaWlWi5kEI/txyeZDLn6ssBAoI/vxqGXfM/+fwnUwm9L3kegLVxqXg4GmsjrmQ/JwZKiT4ivBL3Ifersb5OVxcyq15H3KNuTyP+xNqWP4MP9SGwdXH/OaqNj/YBkHQGKbQoHc/X+fRuBRw+oG4sc2wcASqnYubTwhpe2guk1LwC70PRGpjjflZL8x333Rx9Lx5PcELFGSfaInkaw0hv8OIcUQh5gZt8c3r79z/DBqbfhp3d/CQCw432fBLrA5KvOwe4bbzazQXMg63bw8anr8crJc1FDjku3vApjq8bwzZn/wBUfmsJrz9ngzLD75/bhqrdejPn5WXzyi3tw89/txo9/eBtuuXMG3/s3jSvfey1Wrlrla6BRGqCA1567AaMrxnDLj2dw3d/vwa3fvAnvfou3pO+f2YcPvX07rvjQFL74L/8CAPjYjg8ETJjTvQZ2f/5m3PaPP8bMD26B/ufv4dp3XIlVoyux7RUXYvf0zZjdP+/Qys7rbsTkqzYBWmNm3xz+ZPs1uHpqB74/868AgBetORFPO3kdvj3zAF5zxZvxx5OvB0HkuX0zuGb7O3H11J/iBzM/AQCcvubZeObJJ+LHMz/C6654LS6fvNzVn61bfh/jq1bgX2e+j/dNvQubN7wcgMa1u/4CO6beg9+YOB13zPwUX73rNlf2uX2zePvFb8D+2TncsOermNz+evzt7i9jdnbOgfuP79yFV01uYXUiNLd2I8eo7rh3wX8RN8E6ps5uw60won1G5lduBgMQMnVD8IDO/kY6YBlfLmYOSorovPkqEv4S4byeYuliQo+vhzNGfeLCrSPwpVtkHbMPaeI7aB9QNsablPlI+Rl8JYCXdWphh2/uaTkeyLzVBQy7SRJkLKbjLQYn5DtR0jR5AMB+a4a14ESCu8GxedOyS7auHzAn2/AYsIP4ZeoJ130NQVbA5HJnd8D5izlV8s46LxlACAmWlrJapbpBZtcRCF9EFhqmGa0zxXova1QcpMnAHAVvMXeO3n04USIzus2Keib10JoPi4z59ytxtEOmbrAVeZfUhjDG37UpdQAquaZwvwOk5LtK+KVGgV4nss+PyazUYfQHz5z2kkcLqJuFnfHKRP4fiFJqq1LqNqXUbd3/tCQfny5Nje/YIbPGK3IH6DKaJBDxk5JMnQQaj3/i0dH8PP6JR6cBnZPiFdIAGAbJ4Cu2ZgFbx8Pdnn3uC3Dc6qMxNjaKc8/diL13PwBoYO2Jx2P1cUdh9+cMsLvjtp9gZt8cztm8EXfefgd+eNsdeNfU+1BDjlM3Ph+nPH8Ct35z2tWqp5x4Et767ikcbSdBPHDfXtz6rWnMz83i+GesxeiYwNsKuPnLuzG/fxaXvm0HoIDRsTG859pduPG6nZjfP+uAxsSmc3H0k56E0bExvOC8l+L+vXdDsqJOXxrYe98DmP7mrZidm8fapxyPsdFRPOmoozFx6im4+qOfAABMf/NWk/bzT3VZOuvcF+PY1cdixdhKvPi8c7BibAz/ffMmAMDGzWcDAOZnZx00OvPcl+C41cdgfGwUZ53321g5tgJnbX4Rasjxks0vctf/6PY7cMdtP8T7p94FBY0zJp6L35x4Lr4x/S1haPXvmY487aRn4R1Tf45jVj8Jx6w+Dr8x8Zv40NV/AQ2Fr05/GwBwxsRzC6ZZBDWSa8qD/AJTx9zskqDO+r80lrphA9xsFztUAL6h5Q0xHRsIO2UH6nwDGWvYctRLTYxmRuMyR+WxtloeizIQYmRd70RXjxg5It4pDzGARwGd+dJPosssAN2Yg3oh8DBj6eqRSSgmHdNhez86z9ItOs6IgJ2fb0mdfUEPxGRRh30AUHOGrePld+Bu5YE4U1cG7lJgroypS/STUs+BT12CidMdb1oMQF/fkyTECgSgGHSLAXObAnM0OKB64wcERUDn37NcGYSDtEah9HGAVw/SaAfcWtO/A1I5qxa05sMibNw6EdA5XP6sbVwxJEiHgm9ThhG2LcP+PYt6EHPHCAZCyMJvRzK8CUBXKhL08182QHRAGP0DTODRA+r2ocjWjQGA1jpqhtVa79Ran6S1Pqn2WIP/gspit4GRRdSUdtU1dHKXM2GlGTZwQQcA/MFVb8PgcLgk0uDwEN5w1TtsxpQJaRKEM9HeBBvc6bt/zsBIV3wJOQGwXALPXHeCT1HY2iZfcQ6m/uoGIAemdt6ALVsmkCHHD267A3Ozc5hYsw5nrnkaNh3/ZPzkjtvxwH17HeN26ukbnTl2w5mb8YpLrsDVl09i/VPGccm5Gw1IE6tRPHDv3nAmrAV2APDAPXtdPo9/1jqT32Bt3dCYqGw5Nr9kA6543SsweeXVGD9lPTZefAlm5+cBANtecSF27r4RADD16RtxxaWv8D51AJ7BdAMAR68+zkGksVXj9rl+gsPT1z3dcl5mtYhjVz8RFKz5yFWjAIAMXdxx2w8wN7sfJ615vtt+ePuduG/vfQV2V77v52x8PjhQ+73tr8Ondn4agML/nPos/uCKrS5X0o8uBHZ8s8ORHhNVAmCnEURFN2FNWsEWZ0g4Q8c32/gmRtRSCqABEfAiRMaTil6TouTkraIB1vXU7Fc5WDyE0bE0yyIZFx4qJuRN4h00gKCDTZuEO1FfRe5HR/sE4sjcusBYOs4vck4lGniWL6llA80eMdd1QG5cmGExtuTZuuWYYGMAj9/L3luoE/O+snqo52BlDJrFyFWXCklxmOLhVe6+paFIoGZugg1N94uOX+Vp+ewWvx0O1NoIA0tTLfQsXMjwcdM7rzcEDEHxTBMByfnigUGImIhbR4MzdQFYHEZocmVtC2+HXP3Rdtm2IkPdUxLtUqkZVtaJXsy/ZTa9rktmFIus/dKL1vp2pZQEb6sATPebhhvF85c+cgjDIwtQ/4cgEAE7w9b5FQBq0OiyTpPzIPS/6R1/63wzo/H9V74T/3Hf/Xj8E4/GG656h5skESmd2/MrJ3DhnbKfIhF01AFX6O+haR0MAoEdALrA1gs2Yfs7PojZB+dx/eemcfNX/sIClBU4ce0J+OKem7BkG/f2UhNoKdjQSBhZORZk9sJLtuHCS7dh/sAsXrt5A268bicufMM2yhJQA446bjV+fMdt3Ncf999rwNxRT1odFl7pyLJpwlPMlmXbay/EtlddiNkH57Hhotdi5+duxGUXXYiJZ5+KVStXYPrbt2L629/FtR+4MvIOegt/JofUgPFFhK0/AJz+nrH2qfjanhtcCh6Eh8WUEG90bCwAaqdNPA8rV43ha9Pfxtenv4P/ce2fgCZchKysZ+TCd+/DIms5gzmSF84acvNr0VTSjneqB/goGvAmk6F4Z1w3bFIKbBWYu47N8cPRuknTax1JZ/1OVpxF6ISVa2Bk0S0HFkwOsJ0y7xSGsOA6xgxDzOE9nCzBJdbo+zVx++u0qPM2zw11z82vxMxx/qaBdgAQAl3ygL0dmI7rCGD0yHmMZTMO3JEZdmRsHgdGBkNAl5osEWPxUv6PJD0GD3I1CeMbxUJTiPQ7/HUczgQNwX/5GeUeOstJE9KAKpcU68DHF42FBeJmvaKh2bN1BO4y5AHA4zOfKZZhiw1FcmT+nVhwp+qhuskEu0j/sDalmbfQzMgRoIXmYBtLso2w2vNArsP26wmGN92e9AOe3FNLmO6CxEyulHW+z7Y2028/8kvL1CmlViulNrND14v/NwKYWk6aZrKEti9fu8a3Bu1YOh/Wg0+ayAXvEbJ1IZ9mgN3N9/wId3bnMH3Pnfit88+DA2ecoeN+dIWVEwJtMFNa0duP5zoOo85aAAAgAElEQVT0q+IObRFKpguMrRjFxPNOwfa3fxCrxlZg7YnHI0OOl26ewP7ZOey85kMws2Bz3PyFXX6yhGB7bv3WtDHN2v9XjK8qmPmggA1nb8aK8VV492WTmJ+bxfz+WVx92SQ2Xbi1aK5lmVXuV3h/aWD6a7di+hu3/l/23jZasussD3zOR9Wpr9v3drctg/XplgEbzHLG8lgQ2+AxLRYxEIMjAbEsDSFxi+ErhJmREpzFZIZRgj2BBYnxikUIYKGAseMsJgTCSPZ4bExs7JYd2Ql2sGRJtmxkrNbtvvdW1ak6H/Nj73fv591nn7q3BROUofddZ1Xdqjrn7LPPPns/7/M+77vdr09sH1OteMf33Yo3/vO34fRLX4KdY1s954i3OOBTmfAd4PQ2zPKafRt854034PzuHv7Jm37B7f9v3vk7eOD+TwBosXNiB48+9CgA4AP3/T8I73yoifsf7vgB/Pwb/xm+4fRLcWxnu8PQNep/z9RxKuQGCdo06dw7oAfYtdAMzNIzdS6nVMwNpgZf2Y6Z1x73Wug6DVMtdNwkXOwA3qd94eP1FnKFdACFtahXo9QNvny8NK+NuHsEYLZ0Ea+bNp3SZOUYu1DNBPTr6fiXQJzFzCwrJcfgJaLY/So1EEZuD1vO2TcnhzGzdGoSYu1ZkGAW54FjT6yV+1VeZ9M9YKeNM3Ux92ofO9fH8EXuc5rXisHpKMuq5mju1PD4RwR57Nxk17tPZ7K/od+YOzF0/cUnMY6VkAFiMOcTTOdOK8dMnPQJ6SelY+p0qMYKhVkyrdD3IcwoJ7q6deB+HS7XFAVMso5QQxll/60HINoPtLESGwPcZ6ELVl57NKncvqocZmgGYwrybhTyYeVpC+qSJHmRTSh8I4DTNpkwpy65EZSHrm3b2wCcSpLkRruyxINHSzzsS5ZXRoSZt8CodELmhLR0nq2j5bI6Ds9QVr65dH8Rj4LtslI6+rXrbvWRr6H7ldkb5hVVpSywu+2W1+CuX/nXuO17XwPUQFYZ1um9Z9+FBz78UVx3/Fq89PgV+IN334vLT53ykx8FPyAB3vaWN+KVzzuOV7/4Odja3jEsXUq/s+/vfu9ZXNg9h1e/+Dl49Yufg+e98EX48Z8mfE6AI0lC/lGHB0h541vehuP/zSvxnNOvxs7WFu743lvdd2dufA3u+/d/gNte+519TX9IYfUaVGsLQ8dsh+gw33/27fjohz+Oq49fj6uPvwT/970fwDWnrkSCFt9w+qUAgBce/0r8+lt/JXomz7KluPnMLXjffb+HW2776w7AcRS0cIgMBqWldOBEqu4Fkv5BogV6mToZgE0CYkT0L7HBd9ArbPfusG703sXoTZjJkBKuddlJRxI7vAy6MlEVJkpNXFDqpxJZP1tiNJsrli7MzzYmmOSjXr22ykQyakUTFwaUvdZ9Xtmt9vWDXq1DXmVy5sx5e9hSGfUE6JUuzUl86TAAvq8QoBM3LLN0HDCRzub9mrpNwRFHBXa9rrQu1FF9J3TBAkor1m33+Md9gKuAyUsouR85Spr7zgzaJctrwIaGABfuG+y2XxGAE1CvQZ7ugczI+XAGXtxriLU8J5nfYs1eAVgz8C+BooR7BpysI3ZflZ5uC95YRPfejwx4D8cUfnbc+2jS7ugt21j68vW544VbASCD6oHA4ePd09b92rbt/QDuBxBdHqxt2zcBeFPksz9VSfMazah0g+8W9pBigCwAdjJpC5iS1GwyMWqHp3G/xuBdyON1ctQlrQUvfg+Z1j0Yk8XKGvrcsy8NAbj//a0/gwQNGlvr3z37Wxhgjdb6TG//n27F7T9yq3GhWlB347d+E9o//rDpLTWQ1IZyPrEzxS++481YYowFRigxwqocAiVw93vOeus8Aa7/xtO4/hWnfZJieU2Bu99/Vl3y1s4OfupX3qFzygEOcN39vrN2ojXX+323/x3cdvsPIXGVtldr9z39jdfj9PXXm0FiDXNttT/k7oU9nLrycpx+mQ+QAID3n/0NLDGW1Fr4W7f/bXzv7T/mqrS9s41PtruOqfyds/8OOSokqJCiwY/e/jfxY7f/DXcXTu7MMG8fsHs3OLEzw6++46cBAuN28TVs72zjAw/+PtbILQwxventZz9g77HPQdcCeHL3Aq4+dRW+8fTLAdQWyHG+wlBDZz5P4Q0C6S8O71lglySuG7ribkvA1A0JhBQokY5WaEaDYPAF/IC7hte/oGciXvdq4epgoLuYtU0PLTG9FbN1BdQgXGaFmv6lZHmFerRCltcoRqv4Kgp2E5faCmbZrQoZ5pg4fdQCY5cDjK87LGrCrvuXT8uC9B28/8q6XsXNKxO+B3pjxyBkMDnOctRuIi+JxbEX411rS3cic4+PAVvnl9jZ3u22y84ezs+mBtiF62LG3K7KgIDqn+57OQb/Lpc28QYYuzQdc3eYS5eOdRH2hjsfx5oKLOLoaNNPSgJs2lAJ+59xofe5GkPA4DV0ksZGXsUVL78RTr6CXwNYlovLUCumbjVKMSgarVcP6uI8k0G6mKSzBmyPrMMZizKuWIA3QjSCui9waiNoEpc+AOStYXXzuvP8xFbk6BxHXnOYZ4IArxtbRlCGIoPvTVW8VGAE1Hleo7Y3SQbfCeZIsBUQoN69ZrRLwg0ZZZ1wIq37VCZEBnZdd9jm0kaWCAvjPJkj9DnqtJ4OFoLC1tFTMq0/aHdL4AAaMvNApFnIXtZIshZtBp/olxMRMysXsHjuvLx2rOASX/FgM27pja0X91ZDsAsA/KNf/GXc9t2vUd+Hy+5u4ltDZ6aPOWaeNGRtBVhJHwI2rfmq1ZRhCE6Ct/yjf4qbb3udhepiaJBWDh68+XMnDtwrVk8At71HSWqAfFi3FvATps3TJYOvG4BHJZajaXcAXk7gZ1UbocaDr3K1+UmOSzjQRd2vDnTVKnv8JneU249LGJVW0KvdQnenq0JeA6MSeV47Q1FYlXDd06E1rmSSXmGICeaYY+ImeV6DNWwH7aqxEYnKdVQbV1JeuyCJEDDzRG+AXWbtoExp6WSi5/0y1BhjQUL7QFPHwRLyWQFgCgzOATvbIVu3j61iD+dnzwJmiUl3IaCM70d0kqdzcFnS+5g2DyBgpcGdCZRAvOSkFcvwlIGdP39t3a4L536VvsMJhqVevh8Yds1cuk5SLf0+xvyY/4dOt+kDHww4G2Ll6uV1drn7nfQJ+d7nNZygLIaYTpf+ecl0dkrOWbeWfiK5/yxT5/WEpZUzJF1AX43tUSLsP48ruY+oD1O8xF7l/nYMgSOWjcBOgFzYj2lccW7sI5RLoI6KAXNmATbjIjEPT4KZ41AEwCQE6titlSJ1wM5Pvf3xjKbYqVIiXztfe22dnlR5kjdoiFOWeOjpVV/icAPMChidCEkBO+R+JVTqwF1aA3mmrdgMDbKsNnl1avjBrKV9Q0CXwZ+Az5ma8yhQSE2lS+hUFD3d5lb/hX/1Ltzxc2/Gi7/m+bj3l38+Ki3sK/5nIQ/WVTP6yGhhWENgxf/1u+zZ7Srw7+13/TJ++o7/BV/74hfi1+79NbSo0aBB5u6yZm3F3Sou19RCe9bXufuTwTN1fU0jbKy1qkNXYTFamcXZeVAVxgVbUKr3KKDzbhJ9WrOPuEkO1cTZ0rd+rF4iiY5F2pYOq0OuV4x8TrcQzAgjMCRDsS+VycQkdXBgSVyaPonspMPMhHWOXkdfe/QgFAGHpW0z+X+OMVaWpRN3HAACDjW2sOd6QQfYia6O17vMAUwBPAHsXHYeO9Nd0tU9aZYN29nDemZXmBBgWCGurXKftSZoJkZSCbDr3NfWsZdeVaj1dbaBtOuVLjEJgaJ8nx2u3dQuXw/sxvD5C01f8bnouMhe7EpfoD9ZNUezhp95XZx3r4pB4bWWQwXg2ODgfReYAKOluc/2/owLEzEfYqQq1F5aY1HcyWPMjUxqNOqOF/sDOJerpEfqSYuTBwxbyH5vzAmXA0anW3fkC+G9cP/zyhqhPleMEGbrRkCbQ40pRxnnLoE6KhlpTHjwTfEM8LqnwsAAcJNyaqdzz9iIY8tM0pppgdu35fcW0LUMguTthqTD+mwijGeOKKXz+/AIhhueMVQV9CBLCiXdlOFA5e5Lar1sGO8fA3RJ41FkC5jwS2imLoYmCGxwZXV4QG+TAYnR0p256TUOvFwMqKPDuNYLswK6NmlpDVoASFq0CdCmAsaF12VAFyLZhD4Vhg+46cz34XvO/PfIjRqFjAy/P4O4lmoqtyYJoWhqbp9j6pIuqepKYFUX5QpFsXIMw7iY4zyDOcXWJXBOmA35yPqW9gpBS8fF6CZs7yaJHyen9/YYbD2zeLmAZ5dG+tW7JocdUJflNSaZNxRnxM6xhozBkQFREzc1igtWprfYAN9dDSJHXWU68TCNc5ljQbVgXCZtzdIVjnkRUCeTDTOMkvqkk06FAZ1M2NKuUwAXgNF5YGf6JHbwpGfqZNkwAXVLV9EuO+f6z9pdp2EmydnX43Z1LF2uNWjyKvcm4ZxiYR8p4F3K4XfUvpsKgzmvUS2d3nJmAyKKusRwuVb7rkYDl6xWghfCwBop7Br39xGup/lVRHziaVO/zPUHTkwt/QMW6AuYEy0mpuf8MzMFxiMgL/VigeoeEbgTY1HS/AxGK6xHI20IOvc83esZ4mNLrt3svk08nI6WI+giw307xwtZ/xG0NICYurKA0ixuTFG0uYp/8UqGyjX2MCvdQ7SFfTsNMlZuHKjzqSESgkhaU+cxWqu4JM/PHOLeS2R/OZP/tRzHszJ6RQnR1GkfZ6J+6yIfwxPLrN8En9uHLataGgBlGmmQpA1aBnVSGNQJoEt9WpK2BcyiooE0n13ADllohky1V7cJI67byOfq97Ejxw4bU6wRRGpqpI25VHVJKdC2LZrMrNirNZh86Unw3vwqge8JHnt7cN/AryHrQVwaADz/Pec4bNMESFu1li/fuk6bUGqHrGowLHgqWHUn3XBiDq3pYAAuRmUHiEnhKE1VWPtyhMIDb41AxU2WM2r4wbfQm089oCM/M8toyyLrodCd/2cgYViWsQJ2zOCESYfZneYma0rIzHpDA3I9I8Wv7L6TSW+lAJ1ReAmDAHg2YYiVYm86UbCsqzuAn+BGALYBnAN2ni3u1yf90mnZHOd2lsCuncjlWDGGbrbEYLQyWsbKgNoG8JN9mFZCATytMezGhPZ0KgF0UqcYw5t38wj2Fb+ihM9Rp3IYHiwxOoDu4zmQVWusRjXqQlKZjKNGjGZ2vbM5oyteEVCTTVhiD/jC9R6k39QqaGaFoQNzmJq2GhTeScrQdG0qpRjZUFM3mc1xfnZMjykyruzbA4XfhTrdvJu/T7dThrrOelZiaY0sJK825r7UTF3mmTo2FGVsEaORx5TRwEUeHzWtySVQBz+fZ6iQZVWwzt6c3GheQ+ZVSgaAiD5Jps/GTcdHccEm1vXKtZGvLGzbiFQ0R6WXCPOKLn90M4VzrK7nmwL3q/k53KUAzuWWVBxBRMun5bVhTdLEM25yCkf5tEDaIk0bBeraNkXbWqZPNHYN7R/zToN5xsMZul5QR5+xF7z/iMwKMgdm2brWAroaHW1gArmnLdpMDAFfJX2WrhGg+cE2OLv0y5b2Z5bOs7OwqjpJhdMiQZOkyNLaM5hpl6lTdSTtS1ECxVT0L7KsD7p6uZBt6bOoR60TIoeaoKhFHU09UEVZuph7RblyI5Oyk7VweoYpsJ7CsRahm0QmQu9G84J3AS6SjmKIUrEnGtBVygWboeuO6ejrKhMk0ZfuJVx+jY/Dm18WzK9rwKBuCCtbsfq/FTzPVCHz4E36igQuSClgImGfAI6fW2LrhAG8atmw2RzL2UgHS3T0dGsMRmbdYXNtK5RLwyOaR3DggVCPCza2RFjv8l48Ocfc8+xOy6UJNk+7Wr9dO5bWreFxsMToPAwo5moVwKAC8rpBnZdYZUNIWpOYUcT31xsjNST3HK8SIpo6Y2zUiqnT650U9vJr8Aokc0ywngIDAXUW2IUZK10JPAAeMtozSVqTUNrBfSo2rtjfp6MVhlkZbY9ojkXAADka+dJAp6uP5YGzk4hkGZBZ+Mq6XGHqaDwRN/U8kzRBBY0Lm/vPJVBnC7s9xHXkQuohK0r4oICksRNm2sLDO82dMGsXAoNwogbg9XQdXV1rU3d0uSN26xq2hlVc3qUmx/QJjBs7ideaqUuCgzf0KjM7uWDz1rhcPYNpXdNZAzR2MJdjpLyZa0rT1gPXNkHTNECWoq0tsJPgDK6XBYXmWlr6OGzRcB96L5iHgSal8mBWLF7YcQ6E/GiKBkndGkAXAXXSHkkCpG2LJhEnfsjC+rO4q20TtIk3FLyG0mskGysIEPc8bx7cAQkyC+00x4i09i7yFEgzIKu73vi2ss1qB+FkGQ7AK2C2BGYjPcjGQB2vHOAEzRWGhV/mCOhxb/Ra1P5tLNqtik5sGdocSEIBM+uUeXIamRx1zFjoKui0FLx+p2fq9jEp5xguG6xGqXPn+qnStKVwKrmdWmMlTNESFnFF50E+NtnHg1LR9XmWzuSnI1BnmcBhZn47ieSq28jUmZOaNj4H4DyQnAd2TuwS4DVtNJktsJy11m0PD87cpN4itYBuPF1AtF9yrXMATZV7nV3YPDm8a5p6hhQFjEImNwT9ovNjzV/WI8Cnwv1cQPzQMnVDrDCp5wbQXYBhpGr3Y/NMTc3zOCzWGE79CiR9RcHWOkOZSXJhE2HNejlmb1lT5zevsQTgAmZc6pvZAIPp2uvqpsCxDBjXNulwWMgDYBIQe7ZOpTUJmTopMqZEViSJpUjybeJdnPHgqxacuJjlC7F0ScqbwGOJ9JeSPguMxTCh0SWm7iILW0byIG1hDz5PndnSqkXaGpzUtoZpYT2dZ+sAHWXQLQ4ahHq6Q0oYFmA+4/x0mfm/TVHXglosEMpgIWgDrbWK1JOBnfRXCWIQF+zAr4PrwG/aoElToEk0UyeALG2RZY0FqxYmJAmQJWhqGPdt23q2j0sSvuWQkUhhJi7U6cXcrwlUu8YO53flgBiKgG0bpA08oOP0LOTDTBIDtJOs74zBp7SMXJs2ihf2blfpfamqGbvbWRzgmTofr+tc5OJ+TTT2VYXdWVZrKe6SCeZa/xIbfHN0AZ2skTryWfPDZY56LWougZsknKi5KLF4Bgx4ABbXiNSXLeopMC8mjrEIhecMyvqCJLYO9p07bVA2wPYcq8IwHZ7zKlUEoqmKAXcaROUEdONgNyP2EuhqgtilHQK6PWxhUU5QLofu2JNZhryoMcdCud3CtrAn6K4sIUzdORi27qpd7GSepRtjga1sD7uzOZr9qU5r4li6EkML6GR5LGCFOsuAkdFcLqsMqEZxF6xrGw9tTdt4pqvTd6QvMKADVJQng76wv/b1XYYC/CyN99c+v5/oEqUedP5iBKxGJbJMu41j7t+K+goA1Jm4X33PLTHEEJKuhDV1Q3r1TB0AlXFxgTHm2QTHpufNsz0FMDO6uvGBd8FGGbsSyKoaw0zSuxiYiFlrIqJDY5GDD3qYOpF0hOMB34+odk3WTBY9Kj1Dffkv5bhO1iH9QdyuJb0PmEyfS8C7YM3x+qHb0zb58H/Jsj77CXzhmldg/55/47rwxHdFy9Q1HtDZydrFBDRhel8zg3cjMk3RfJKFBDHXK/ykD2Kl9K/YDccJiDPUjXG9tHWKtkrR1imaxoA8DqJouC4hwOFgCQEpTI3XegByrsfM6OUQBiFksCydAXQpQQoHiC3Yc7quDuAyr6HWsNdRGu6fBlv4GTF1svPqiQPsP/AZLD7ySSwf+DTqJy6oRmKAJyydA3Q1bU2w2Wpvdh/7urTWTW82gZMepDWqH3CNWDeXqPctwv5ggiUUsMt884CazUX6kQBeUi24xcgleWzfthNsZFEPR+VTs6jDkLoNpVaDpe3NoVstSDOgBt8p3KoKMhE+es8H3PEfveYG7N3zbx2fEUYybtV7hn0RBuYAmBw0LsJxbN2y0g5eW9cvGgwTp/bl7zvMNefdZ2MH6PYPtrC3u4Xl7hbWu1tY74+xt7uFvXJL/Z7d0eB+wnnjaA1Yt50Dts6v1eoSLqnuzE7mncCIFoPRCpPZQmnQRAYwyeaYzBYYjGxCbI6YpU1Wk+D2iTJdzMxFtFCKcbHnanNmxjyoevye97jDfvyaG/En99zXIRiEZBgIoJNX3iShc2kY86zqe266wKWuMrdJ3jlmiGQ2ZCC3sMEyvOIIs3acmFqMAvfMbJvXydSnCbYLenlgJ2NmBQyXjVL4Ga1u2QVuO+gfUyiIZjjqrrJRB2OAtIu538zSWrCfd9m5ME1MuFqHYnX7xhP7/9qOKz6S3MyyT9xzLx695gYAuK5zc3GJqXOlfuTzOHfmJzDGEidv/jo16ApTJ6J31FAEXJIAaaqSQgQM0iGcjxJwMQ3VDQAI8RY7HVUiDQveUGeUliQBWosnMj3RO8dukrgjk29Ps2UMVCoY7Vji070I35OkDdrGsG+uvZIGSdpSe/ECVrC6xBRtavintgnYOmb7ki6Q64SdhC7XiH5OgTu78VEXTyxw8MiuXcEeaFdrrB75AlI8C4OT4wDQ2S0EwVKtxH6e+3Y1XmbtbOWr8bdCu+nbFmgTz7hKehLhjX1r+Dx0jWVw5Z6b6nTd9W2WAFmrgF2aGiMmyj0T0PeRagaMDItVF8gdxaKerVGMVgRiuno6zsXmB+AWfv3XymlfYiCI3WHquJJ+IAyIEKAXgDqOAPzUPffjE2fe7pvmkS/gsTN34gS+H8+9+blqZYAJ5tg6v/buNNuWSQ4U0xWGRakmM5/AZVMqEg10606AhG0PtWh9d2KSZMMC5gTQ7e9uAfukbcsHaEYDzPMai2JC065PadLm1GdCFyy3qbhgnzAuWJ3yZY7xdIH5bI6mmlLEYAuMShSjEsOsVDncAM+uVVmGYjQ0gRPLgdcywR4nb5WejtnhKMMbAn6WaEUCaaos0GwCeOye9+HhM//M/b9+5HF88sybsY1bcOXNVzhQWWCFolzplTg4UIJncuvSy6oGedFvEDEjK9pLAFjlBYps5YDaHBMH1aQthKmTlURYfyc9aohSrUQyx9iAuWNQz46sAQHYVaDZ/rB9ZVDCGYoCK53GkscMdquHII/YfwmGDMcEvVZLCOz8b12Ox4gmNQbo5L63IyAJgb/MEfK/bZfFbOAUuPI8feGe9+KxMz+Hds6uDl0uMXVU2vkSj7/h551dKuLlRJg6ZlyIeUkbIOQ+OFGIPToYKrAiq209AxOpVZC6gwsDOpqUWwJ0xKi5zlOnNiIsVRN+i7SfqQvZOtqyymsOedm0LLPaukQYt1axdJoj4nhdCaCwbB8DsYRbz4OpsNpBM2n3a4ydC4EdHXn/sQsO0LnStCgf+5Kqg9PVtY1uq5Cd4zYkpo7dyHw1KuTGMbqWsQPALG2o7AsZ3Dg7p2pvYHmSaZF3BmSUl9gRqKFZWIku1WfCn2Deb1HH2DoefAsPZPRpdPRetFhXSZhLalMaAwkKKIuhFjJzCpMA0C2tRT23TN1H3vBbaOZahN3OS/zRG+5R44qwdMl5GEB3oLfJQQNZ+1W0vqGuLuY6cpN1j+tVShi1J5O1pMKQiUQmFgfodkfALvS2D6z3x5jXExso4QX2HTcWJ5aVaEVmns6ZreumFm3d3LBts9YButFsjuHI80UTxdTJuqkLjKcLDEclOsvXqXbQeroQFLWhC00Yu7BvBOkpVqOUjAhzlv/8hns6faWZl3jgDe9ykMutKnHQ6D4SY+mC5bVijG5Hk1pLME2OclmgrjJIWh7WzM0Dpo5ZOZ/2ZOzcsLKU3AJjl8DnYDs1z/e2b6etgK3rFGHr6KwTLFCMIsZijKULxhpm/0MwplK81EG/lbJBk6qP1dXqVtxfNjD/mJogiTBP4MNv+KWNgA64xNR1yvrRL7pOIwOwRDIykEl2/ts/76oCAD7Z7nZYlrrONKBjligFUCdoUy3t51UHHEMoOCZwFQIIQCKQDTxL54Bd0iBNEzStZf8su5ZmAYDrVLBBCyBNE6NZ5GhYwB4HxGT2uV3lvOhuWXDKRL/nwIRmFWdF2pWn4JSuTnLSMYCTg4XnalzTbIhwtvelA/5TtA1ssI5n6RJIRDMnFWZXO0dEJ7aaev0Lp6vjLTMGTBZqHAHVH/yCQZKvbu6DJWTQZYt6BD342tfhqFRApntK0gV13K8teH1TQFvTMWZKD8C5nqxDi1oG3xkwn44c8ClR4ODRc5EGAhaPfknlv5xhz7B0LHyXtsyAZAoMT/jYQs0h9DMwANyEVFdZx/Uqerpguum0LacwmdcTzPcnGtAxy2UZu/nOGPPtsQN2ovWrssCtJu5X0dXBtjEBlePnlh22bmLZunJZYL00onwT7bpyeQCZN5J7nVvAusIQq9EQq9HKBE1I0EUOGyVdRftJVEsXc6EJPgvdaTlQ55pdBoDlo0907iEAHDx6DpIGR4yjRNzVzNQJWynnzeAYq6Tq1rvb173uUhipcjnEsFi5iFdh5FjHKSyusHRi0IimrkaOIUrnfpXnY15MMD2233HBTg58HccMtMkDwEESQ5QmB2YI5mQfoMdYXGIy84aSbH1autjyeiFLZ5p9E3PuIeRqlGIwCjwAUgrbJrZdBBDLuFKiwOrRP4meR9Xv0F/8BSvFVc9UujqJfk3rVjMsT5MSBjo0Vj+ndG8URfQPf+Q23PKy64DGMHrM8GwnX40HH/q8ObAADMZNzDzVwLV/+Ttwxz/4p05XF8KCBI1xs6bG5SrRrh5OxvgiUnwlrWfrGJzZCml2Ls6Ehizddd92C+56+7scULnu1bfgrl97l6egEhPbwZq6dBi32JJhTnUIXK99Ojr5v4UGyoqmjTnvyV/cmko6bR3dQ1Yn1uRe536iI2CZxfPu+xqpWe6NcylZts4xdQKOpXchcokAACAASURBVIiomZi6sWWaRqGurs+aPmTwBbxF7SalPosaPh/bptQd8ioTlUz+yn3Gk7QIva0rSSCHSfsxxviqk9G6TK86QQlBzFSXsD5KJux9eH1iqeMLY1GZ4bVwKhN/b0Jg1+9W9IxlAVnRYm93C83utMvQEVOHfWC5L+B26FxzKwyNRjFTJ/EuWHHDBuxTch7K9crs22RmAnAkfYnkRhSDXJLUCmun4jSLlWXraDkDG/maK0Y3LqRXbItsotcKdFFsFJRZ4Rgwc6wco6ue0e0oMH0lCHvpMLkdgEf9xrnGbYkbRTmBOgP+GwvwVmU3Bx333K6WrlD9RRheAYQels88cKFty7phJ7ABShEXrLDVfFbD2KI7fvQwdYMNrle5vyzp6BQH6LpBNL663Hu8C9Y8B1m33/B723/WU7i2Fn6yRobhVZd16xRW8dBf/AUqyWSEa++8RYmZzTJhjU9NIZOyLe2uXeh+CKwHGVYYYI0h1sixxgAVBvDJPtg5aSdR6yqViEbPRsECoUYxWzJNf3Wy7X7oJvPWBEKgSbRIn5f6okjWuk7R5Jy3rIfzsgCkbqx+0AKUN97+wzj1FZcDFZBWLbK8cV3ZQIoMbdKYlRNa60ZOu2sbyNnNaTLHObVILFsHtEmr2yZhdix0c9t3MYZOCpszgWu2TaUuZofp5dvYe+RJ7YJNExSXn6RDEGPHLB1vci7Y+yJRsMLUKVCqAZ3BfZala+3FNVZT17ZoEx/5mjjGzuzb0ctJi7fmLhjJYhOwdRmaLEGWtR7UCVtnwaRzvwajSFGXGGZ+qDeT8MIsFyYb4JkeZursADyazQ8dfAEPYOoq94yUaF8EyPW4SXhyZYtaFilfF8CAAyRY92KtaR58ZRL7qjtfiwfO3KXcaumkwEvufJVOInuw32VdpFiN1nDZYFjIEmFVRyvm9GIETr0WyLYJTU4ZARdm6EI3lBLIH4yx3h93gRwzdVLn/ZEV0U88SwerUURA8ZZAuwQWJTCuDIjDMShg19HUsU6TrklnS/NpYMxphD3yk+tqNMRqWaAZrYHlAOHi7DH20rVPboGHbMLQTaFZRwF29r2e5E2jnbrzVvzhmTejDfrKi+/8NojzbogVirr0gI3BnJzPsruY2bq4IDafLJi1kvz8VMLm2n6yXg5R5hWGhTB1Q2Q9TJ0PirFsXW3ct3WeIctqyzSNFbDD9h+b+3wMiq2r5LFlY5L6CjOwAu4HswXWs4EHcjk8e9kBe2tMZn55tZDtjuvpaHAjho41qVL6jCMeU8qsAIq1NwCYYSWjcW97pLSI0rO//M4zePTM/7HRBXsJ1NmSX/1luPzO1+OKm6/DEJ93gG6CBZK2jU/QgH+YWtbVMc/Tqska4TeHZLnldTdj3jly+nkdHQM6FumntFMDtE0a1NjWLzyRaLdEJJ8ASQ3c+M3fZEyr2kYBO27IQ4gGRh/Xtsatq6Jc6b2UFLWtamJgnWXr2jQlYNTjbu1UOxG0pEM3k8h72mT5LmmX0ckpauRYPHYO7apCMhxgcPkzMDg5hQnE19GviokLI105fJTTnEQuKVTZtQLmBK22MKtSNAmSzKc2MaEmxvlqjqNdry1Sc++bxEYZp0gSct8LLE8yZFmltXW19YSLu1ii/wBvUVc1sqyiQdi4xs7N1sDOQIM5eSVAl+4cYDJbOD0ZAxl2kxyWhBPo5qbrH3hN3i2/RFZhXCVFYwbaEHBZpm5ve+RSfQhD8eU3vwIXcAwPve5OAMDw6svwgjtvxNfcfDUKPOjGllHI0DFIsmyLWRvTi/ZZpRMrYZBEb7sQyA2ZKNbVlSiM23V/YJigGKgTd5ll6xYHY5RTVkAVPps+oDwHixJYLM2EfmyEDlu3Ve5hVmj368TmPxPXlXdTeu5ognnn+tRKpZatW1aZ74fSNmqi7okw5ohX6Q9ybaDP5LWAY+l4Tdwvu/kVOMAEj7zuJ00dr34Wnnfn9+C5Nz8XGR504HK4XGtAJxtXr7D34BgcU5fXtQJH8szoZeRyA+gsuAXg2brCAHtZ/q1G5tqnVC1eYFUXWC2HqKrM5AWcThSYk4Cbg+0U0+1G6eowBbYqoKqBJNQ52tshbSG9amwZ2/Ph8nGyf5CnbrSz59Z0lz6zqcgzFK7E4rpAplldtS95EiRyVdhNFywhfYMDhSz7v7DtxhHGNXLs3PwqLDHGl97wZtSPfD5a70ugDsDwuq/GtR+5G1vYwxBfdFF74n6tLLOFCl1QR5O30UVpfVWv3guB8D1MOByJ7Iwfw7vc2jbRWrdQU8d1rwE0MtmbiEg5ngI8tqJNQ9K82rjhQnesXh/XbwYICm8UOgk1U+fzrvlYziRJTeCurY9J8+KvPp42htozFiDBc14A7HitXDni4OQMyckdyJJrps41/co7NzuAju8BM6agz6Il4n51/cU2RJMQW+daG5wMj9PWtEjQNIbRlbQoQIM0c+uBQPIc1kg7wRLI4Po6Eni2goBdVjV2/VcvWB9ipa1q+1sAAVNnrOlJNu9oyYBAC+QmpbibhF2vPPD2rZ4g7INb8qgYYjpaeteIFBJ6m8lKp24oMcTOzd8CWFD3kod/Fc/G5zHBw+R+XejUFOI6y+1nYsW7bPre/RqLWDXNaQGdE75b9qXKVeRemFsrFoQiZ1wcjNEsh3GXawyc7wPz/QkWUx8sYVyWGZCvNbNbG0C3qM1kPj4ABpza5TwwPd9g67I9VmVhgjkkEa6ADC+Z8f2NmTpm6QqUmGOM3PYReRT1Wrgc+cqJr3O9MDszcqbxfFuIO60A2hHU5Mx60JM3f7MDddc9/C9xEk8gw+ddPUzkq+8Pzr3KeeoAzRrKHBApHAzgb3pu54wEGOUdtk5kENIezGo7bnQ5dFpHYT3nhWebXKhLsYXpyfPmGToJ4IvmXicVMKjhA5QYnQQBWGIyGF2dNRZFpyuvBOoOMxRjko6Yng6AknP06Vr18XKq9RBlAYwEzEpdhWWdAsttKEPRB58YY2B681/F6ObvxCPJ88/G6ndJU2eLnyYqp6eT7qjAi7yXwrnGGu8049cYy8bzuJJTBeCOQWIAVeQXBkPUKVCn0ehUFQEbADzR1YU1RwLc8NofxF2//i7ccOYH8YxXvBLX33ILHvzc51C3hrW77jW34K5ffZc79oXdXXznDd+L5x9/AW694Sb89B0/gdff8O0OUnzPdV+Pf3XXLzoO7J+/6edw6w1/zQG8vd1d/NBN34cXHz+Fb772hfjD++83bZdyNIFth6TFT972Q/j641fhK5MTeN0NN+GRhx4BAJzfvYDX3fRjuOz4K3Dt878D9/+HT+qb0AfyRFPnGC1p33Bn/k/f46SJsLp9WjqVp04X3yXIWd0SsCM3bNsCTdNZzwI+IEIHSjRNYlLN2K2x+kqVEse5YKF1ddJWcsERqzqr2FVC7hLR1YUaOre1xpqeStrSOWnqevQvDGCC0ucmcfsq3kvrXyTMo2UNHUftbQMH26m1qGdkVeslfQDtNhJZx1a516+RoghGM5m5hYaiUXtcWAvUl5sO2BzhKZNRiQLlsoizdIGWjrdmX0ftuaS0EZ1UVZvVBC4AuMARwMRg8uo+M+uGVayb6msspheNHbltiVsajgxbl7IBkPVP1q598sxr6jjSlXWXzELNgPk0VSCXXf/x+6Nd7ElMfxj2Fw48kTE/rDv1dQA+6bCsslHBBI8E2jrvtxo71/rcsUiGpSuXhXHTLws0yyHm+z6/Ia9wvIsdr6cTF6y0FydtDvqK1Fz0dFKjwWyxWau7s8TWzp4yFDk9kG4fracLx5WMXLB9q0jotvYmmGur0aAbST/zbbE3nYFjviWlCfebTeUSU0fFWwJmUJCJ5UKMdZHCrEyLCDwK3a+0extO1F1A50BM5DhuN6Ro29TsH4JP1gDSSgbyedMkaLLEMlCeCEICnNu9gDv+8Ztx9tffhmOjbdzwAz+Af/y2t+Hnf/zH0Ug70Hmuv+51uPrUlbj37G+iRIHX3vBaXHHqGoGdrj0ExEkbSfTrD970t3DlqWvw0Sf/CO+77/34m9/07fjAk48hQYo0bdE0pnJJ0uK1L/46XHHqGvxfn3kAOSp86L73uDb53pt+FM85dTkef/J9eO/vfgDf9K0/gCc/+x4PRtgVC/1Z45g63+Kt+mFfsfeJQXPI2PFhwmji4EiAv+udIAkGdWnI1vm0JtJfFC/aWP1mY4+VAGga1HWKNNfrgtTIUGcp0qzRwE4qmNJngfRE1jplA2lczLG3c2ByjLH2ZQRgp8VgxywFJSk/xCrnhebldfMyPvWR3SRiSTM8KJkPEKu6gp9oLMjbK/yg61k6WsBcquOMRUq1EaansElj3aQmQvfSBEvkhc6k569HVgrwK0CYdrHvg5QmnDA1ZKTMcTzYqOvMTNIhcBNAx6wUuV+xTNyE30lATNVpKyNekCWiFjXQHgCJtIdl67zb1cdRLjC3LSETvV7bYIy5ay9Oz8G6uyybIM9r1Ky9hI9+jbWNYx1FFyUTs8hw5HUEn4+tAMpCAzqVT7BnGvb3qNIMXcjaSSmggR2MFEL6bXgeAS9GTwfN7C0HWOe1Y+tC5lJ6owuGWQ5NNPJSGLOBubezCRaWrWNgtzwBjE5AAzthqmOpZipxs0sOTAmEKa0LdgxUA8qdCAvylphZt6s2FL3WkO8vlzAdUEr9xN+fLpvLx/L61MIzm1mBdrpGIuz/COYebQPrYyAA7ccU6d3cb/rKJVAHP2XKgOktarN4cmdy5omYPksdqGt6QVj3rCCdVP8vSVmloIUDHmFwRCywg4GE/V3TpDYRsYegTWJ0UwDwXX/lNE5dcQWqEvhrN9yA93zoQ2bcYi1YA9z37g/hoYcewyce/B3MMcESBf7Kjd+GT9z/CciS8+ZaOEDCX8HH738AH//IA/iX974dNVq8/PQ34utPvwIfvO89eMnp00iSxLhgW+AP3v1ufO6hz+DtZ38POSoMsMa33vhtyLHGA/d/FB/9yCfwW/fehRZrnD59PU6/8iW4770fwulvvN43qDwXzNRloqeLb937oq/BBUlI26joVvqMtY297ld9Pu2qp31aAG2Ktq3RNIn1iwMpGmjHsAFzLpDGBlqYH6f2X5ujzkXAmqF8kK88cBMJgpw/MvhKKgVm6tzzNJtjfzkEMKD1MQ2g29rZw1bmJ3AWMxs3WwVZj1QDu25AANBN3dFX4q4Sm3h1OkJRLg1TItc5NSwdW9PhSgo8WYRuozHmHrjE9FHiPrMTVFY1Nl/fUTR1uYtmVO1R5UrordqJ2ljaY2UnaiwHXTAnDJ0Aihn8JGp/u6oLtxi5TGbKMLBlbbcKBsMdOzCbi+Y8ACb1HONsAY6A3cMWhihRI4cLJtAKL6eZ8how70oUQLDKhz6SMe8C5277mj7S5qSLEheoBNMA2v1qg2nYaGBXX1g4wbQDDpywmVfjEMNI0pqw9CbiflUGm0gXoqAOQF5glddY5DWyqfmyQubAnTNgLEuHZRFE3Q4w358440dt0xlG2/uepTtn20qaQ8YbZSzWyDNPvDgesJij3BliiS3DKsPuNzOAbjZlTebCPd1SWFm3UdIhVaNVR8JnsZPEXI0pstLGGGWxb4xFwAdgWY3uvk945AJNFlbPGHWdB+USqLNFBsswv9boAB02rqOpo/ddbqU7czso0Mn0m7jfiW7Mq6pisMKeQSZqBnTsciWm7oorr8Uf/P59BFJNjc/v7gEAdk4cV1W67mue17lM5YG27fHQw4/hRX/peQ4OpGhx4uQOhCcS1Zy5Yh2ekaLBxz/yMZzfPY+XXfv1quUee+gz8OlNzDE+99BncMWp53SgVgLgYx/5OM7vXsDXXvst/igt8NB/9xjwCmzU1LUp0CSsP0tdjY+icExgs69wX2Hm1N6DqHFAzRn2mhbwoD+sSGNPXBtgZvLW+Y9hW125XeUHDDQTkw6nztyCeG5QajIg5QmZgz569C8+WlNLGcbThVmDM5+YySSvMZqZ6NitjHKRQa8KYA7rQYd57R982fUKdFkXOZ5OOcAZ9ox7aYIJiukK08qzlWti6TgtLrummBURQ9Hrwhbd9CWUp8sFZlhglzmWYqVq3Fd0KhPbC3Ld2dgx1G0Tu1SUTNIC6BjYCahjDdO+/3y1HGI11SDG9RV1PrMJY7coLagjXd3W+TW2TuxBcofKhC7gU9qXWRzW1Mk1KZZODPhi5fqQzjsWE797hq0sgJG4XOX6uS2Eqds2yalLmlmO6kZjd6Ni5sL3NVRwTcz1Knebr8X971hduikjAMsETT5EKc9R4TWMcowSBbF0SSeVyno0xnxngnk2dq5X2Z55ch84AaOrO2frLmwnL3pvTkbrv3qIJK751axAXeVY23soqW4E0LEmkwMk5HoUc0qSjliOR3NvNhuKphl9FDnn9VPGorR30TUURa/Lq3Ycpe9cAnVUJMJMrOkhSjPYBgEBIZDT7jXPjfQDMQZ2crxeyBbZS5/eRUXGdFwM6lrgq57/Ijz26EPYO7eLrS/bARrjcvu9+96Hq09dhe2dbbTtQTTCNCScmPE7deXluP9jn+yougQS+dgLn8Zk94lz7rMTJ7bxtS96Af7d2d9BjRQVcsgy7pUAQKvOv+Laa/C5hz4TqNxMzY6f2MYLX/Q1eP/Z37DJZCrklU1Jw2lFIkxdkyKoffcOxO8R1SFgMF1j8edhYyIe0MsxteYDZnfp5A2AzAC2xl5Qkqo4F5O/sCXwzy5im3SuaVK0maTekSnFAL00q731LPsl0Mtn8QAMLWWQyXYLe6hnJjpOouTGU5+QV5bQYtdrbGHtXj0duV7Fou7TvLjj0MauV7dEUrFCNt1HVgB1bpINbxp8QwbGL/Vk26Ge60hGAXbM1JEuKq+90ckgLKoTrElP1+M+Yt1YDCBWyLCqbXLf0O3Kr5zk1QZJCAic709QTpk/GwY54cyuAubW9lAXADwrYDCTA2ByYu5cboapm2FoWVvWWek+Z9xsonEcY445Js5oH6JEiSGGIwPsJCKY26ML7Iyrvs5ToGi8+1U0dhW9t0ydJKf2yZi7Gk4+X3R5sjDvKOvoxOBiNo+AVehi5PM5A4ABHei45IYF4FZ4kbZYHIxNdLQYALLJsUYDzPfH2NvusnXLE8DoJDxbJ/txsAT8a1Y1yIoKHSkDFlhkc2DHGBMAjF4yK9XqLTGwnwVjyybAlAVMd9/zo4UNuQN03qXqjcWJnSTKwhiK+2QkSuSw5AUMgXlfuRQoERS5FYW1AlBCUyZ9TJ39jvOlhcAugZrHfYCEcr3698khejr5fSvMSwzMBRq7668/jW/6lhvxd7//Juw9uQs0wH+6/z/gDa//O/ipt/6UYXSSpBsBS0URTbY9Tr/8euzsbOGv3/Q/I0GDRx/6DO5566/CMHU1ErS48tQ1+I9nP4YELT730MP47Xf+WwiP9O03vgoXdi/gLW96iwN+v/vO38R/uv+jnreyK1J83Q2vxBWnrsH/etsPY2/3SVzYPY/ffudv4X33vR/ffuOrcH73An72Tf/CgaJ3vOvdJliC04mwG8hq6Zq0G1gQhrqEd4Ghn2uqWF8Jmd4A5PkuEDcHlPaSz6G0ez5ViWjnmiZ1gK6tye0a1qcBUEvAROKAiRtIwghYCTKRCT0Ya2SwK8iidkECmXWJbO8HrhED6Dh5rI9U05n+O4PbIRY1v8aKfBsCOmHs9qYzk75EiZhn2MOsM/g6DRm1BSfGHS7X3YAI0tCpV+vOlmvvcw8qFkZSVERKThOSai/Hvvi1QNVEHQK78D0BOiyBZslw3rBUygDotL9l6gCsw+XDDuD0ULJiBCcW1kvP6zx1nnv170Ua4NLEZLVy08eWYOM2NkzdEOvY8k4i+LfC96V1vUoSXglAOYo2SrFB7HqlIBrU8GydvHKjUt3lfCp6vMp1kARvDqQVWC0LlMshVuUQi3JitoMxShsU4Vi6cLMJqfcIpAhTtze1iYhP2I2DkoSpoybKKri5WaVLEoMwm2M2NWPLJJt3AJ3vP57x5uKc3huW12M9nfo8Av4FwHPYDo8t82KCve2B2Whc2cWOG19kVQlm/A4rl5g6WzgajLVA2IdipEK3WXLFn+9yYS3EpYZ+YMeuvxr4qZ99B972S2/CLaevw4Xz53DFqefgl979m3jJi56LFnMoJBcBdYpkorY5+9634aa/8fdw1fGvwzecfilefvpleOShz0J0ht/63d+Bv//6H8W/v++9eNnpl+N1t92MBz78MRcoce/Z/xM/9vofxwuOfw1aAK/6rlfjf3zjK5UzVLDNL7z7t/Fzd7wBp5/zQgDAy06/HH//jX8XAPCes/8aP/b6H8ezj78UAHDjd53G6X/4w901Xy1WaxKgzSR6lHPUMT6L6eo0l6c0daF+UZitDbRf15lMXGdoWMTYYqlFYlytTOd13K5cPzltmphouLzrgq1zIBP3krhgmakLlvbxLjE/0U4wxwJjsAsnQ0X2q7dlhWWJicjd5BomHaZymOvVHMcsHuVdI4Wyqrewh9jySPsIWQc/+Apbx4W1ugVKI+ngSEZ5D3g3GrMyFdz5GdCxG0xe69D1ylpAVx+d8z4GXgyoSzSgC1k7PvYo+H45UCDX5ecKmDrAsHRzmJSXC5go2JPM1u3Duc98DObcTZCeqfNgj5k6udespeNxvrJGy8aEw7aNxbVuohhXABqTiDhgx1BYN/105rSWPjI6ztLpe6RdwR2mjkEe95kNejrAs3acjLh3P3fsBA0mWMEYDGIw1VXugyNCMCdlH8D+CItygr1CA5dd7OCZJ/b16hI1nTeUdSCMgDVjiqT84OvLUbu+wiydgHYBXbFysfnpdMqbzDGAoiXV3LEZW6TedWbOISlfwqhXMQhWzhDI3fX1lUugjoowC24rrZZhgLjo/WlQmC3rgE8BdszuWGB365nbcevfvh2YAMm0wjSfo8U+ZJEupMDZe+82g+rc7P6jt96KH771VneaD9x9N0bijmuAU1ddgbMfvBuLYYElRviZN/2SA3UpWrzqxm/Ht974bQFcMFnREgDHd7bwi+/4efdgiAtW3K8twZ5jO9v4B2/9OfzkW3/G/Wpg1TnbO8fwK+/4WXf8DDXStkHTtPjwH9ztsFUL4MMfvhttmqBOwgx73ZCOSMvH/w/ZNN6SyGfqKBx+EQLoDbo60eolidHXmagdv1/M7cpg07px2zpBk3PL2S3NTSLiHL5/pdDJM9mqpmlLWO+JdX8BIBF7F9SJ2zVDjRo1ShRuEGO2oa9k5Gbsy/iutTRaVycD8RwTNxHwfgLk9u3AyxGwIhyXgV/OW9hrGoo+SliocCIUTZFM3uakHfDVmxQXdlJipiEC7OQYMV1QDdLT9YG6/WAnCZKgfVYK0hdm/VdhXzIL8KjMYRZ2XwjrROk7JuUck0LYWw/eAM2Eyv0aEniTa5pjrFg8ThNj2qMb1chFgJBcU1ZMAMxR5w0Key1JBbS5cafNpyOX0sOv3+ldsIcVAZl5Xes+ETJ1gAZ8VHWz3mwY68xR0mwEIKKrky8NsGtGpUnpAgt6uJ/E2D6rteSACWGidrGDg5Ofx/REo0GdyDyE1bVVFBmCj3AWkG+MB8CAd7mnflEzcwe4P5SAg16yH7eNaxer+5VymOvVtSu1t9fWMaAzxqLUOwbqvKzDMnXBuNJXLoG6oCi2btn4MOtgIm4/9WFvSQzh2Iq6AFZpgTUGkCXDKsiSYbQcUWv0L8YllvpjpwDSBknaWJcAL95kZnKZ+CtkqCVytk9P51CfZfPkoSH3W9v6NBgCZByjBehAXdoaAE0Ds8A7MYU6ZYlPJ2wOFVt5lF3UZrGrxCYfDvPASRRtWMhp7dktxxEmQJICmf2EDtEkPp8br3Ph3a9yzKAhVIvQ+xiQYxB2JKOge76O+zWsAgO7VCJbyfEfYw9Ja+lOl5nExHWaBo7L1ET8MVOXwrtJwihY6AHYu2GNhcCRiZI+KGTpAFgmpivmBxCP8pRzq7VN+8GLsdrjVvUcYzf5CwhcYRi1qN0AXE+wWhqdFreDZ4bKbl4xdpsxmKMJWiv/DgF0vqGi7cKaLXNsz4i61pKIyACoaUBnx5Vl5HdLOJejU7qNUgzyptNXGEuIC1ZFd7rl0lYK+Id9KNwYkNfIHRBktmcRTMx9aSo8u2ZW2hD3LQogKyqsRrVJHwIDpMrMRDnu0+QsfYufq5gbtuMar+o4YOKGiwA6rru0QXgtnRsQMnWqGGqe1Ue9btcgeGa9u4W9k1sdpm632MF0+5xxv56HTqYcBkvAGyI+ZZJn7IwRaK7VByb5oKuhOjgcoApLxYCOylGDJGrk1geQO0NRu2ALMm5NBLcBdTNyvXpAJ3kAXUBP1v/8A5dAnStsy8ikMpCBd4LupAhsmJw3z9qdb3smeuFrtOPPDKQOIkl6CqDrIm5B/wAmGoB+QxGw2u2YKDzA/3J1WwBtqMtqoVLe2lp6D58CdDojXIvEYknzea1gmalIYo8Ugr1ukxKgcwn6bDsm+nfdtVHZ/RrGM8dKhKXj963GTZ3fhW2qzhe+18dVhUFaSjeN+1fIOAtTR8ZAXadoUu+CdYxdniCXtWDF/SppCIIUBOze4xQEvBIAAAehxg7Q6XQD8tuuizD3a1YC4FUTwsGXl9eKaV/EBRta1WJZZ3aABuBAXeiCdQOwXSYp4/VWISsD2GvjPGOiXeJJlV1tQBSchUVGL0CCJBK/b88o3wUw3h1lWBjEAV0FGF6tAkD5wVhbtwRW5dDmZ5Ocf0NMi6XqKzYBhQuUkEhYB3otUzc4ACbbPjeZvErdQ5ZOpk9meEVPxxGw4n4VN27o2g5ZWs/oenef6PIEm4mBwGsCC/PLOcv68tPxeTtutgDwt5V9zGN9JIfJqQcyhILXpo+pkxICuypRMgvXf/tAnQN2CfYPtrA73VFs3R620J48h+SL0MESgAZ0V5/hBgAAIABJREFUgReA9XSiVRRQ56UO3gjglWkMU9o1kGpkOtAoUnzam379JbtgOTAmNBYBWTouxyJg6kR/6DwAdlwpRivUWX7J/XrUwoO/GnyB7mTYiXow2xGXJaXF2XuiXhPNEfmTdI8TgioH3Nw+ZFu1WcQFx5xZ6tyvnKQ3SfS1KQIqYAkFJv3I7a/H99/+g6gJVcQywAmE8jUNE4p4hVkHHMVbTwEyD+48/+VxkWbq/Oq1ErN7ePRrtD4B8HJrpW5k6jggY0Pi4xgok6JcsUFdYno6+R2nWqlT1IPUTTwMjXJZC7aGB3WAD5ZQg69OFio53NiizlCrgdexWYA7ZwzQqUKuRo58Dd1qYdHC8dwxKS7qlSYC0eysUPS4ScZYlBOUS2NR57k+p1rujCc+FrnzPBIwJ+GqEr0rShzC1EnZ1CY1bKBFwLy59y5mVSDYMZMfLJjYy+UQq6JwGfFXKIDRsiOC57vpomFLs+4tM5ocBCGbXIs3yP3ScmIcFChRI1MCe8lykGFsYT1P1HFWV8CcWeDeg8Vu//SGAUdGs6bOg6wgOTQdSx031NTZz6ratF8vsIO/pwxKATgAE2X+5HPlgoXWuR0F1AFq+bi9qXa/7mIHT554HCe2l37NWsAn4g50dXKPQ/a/Rqaed15AQIxKBnAGdPXoJw8JkthUpD+wsegT6Rigz9IBGVsWmASG4swrSG1Aiqlb7dY87iuXQF1QFPKWzrnJpbaBYTPv9Q+i+qweoMhOuBi0cN+GrlfnWuNoCWJ8ItGPHWeoRlOqboxXGq6//SBpWqSpdr0KIEvUWbyL1kOwVO0jv/Utp/2YsfbVrZYSvgnbUDuDa+d+Zf4w1LclvTCvF2gysOvbyZFwiToX6DVmRKjmEHd5Q+/5t5vcr9JIDYDa56wT9aNMd01WIeUIWMnTFbhJJFGoj1bjhda9u48HZhmApRic0yPmr7PeKM88yDcmr2H0rNbThC5YqfEKe9hyljUvUB4uVF4uh2YFBgDVyLt65OhDrFDUpX8sOXVJxOXqyhGYOrkO8/us1/VqJB1dDZlKe1FbTR5P2srtKgt7WaYOA8/WsaZuWWC1zRnkhp0UOEF6Q5eIeLGE95RYcMdBELJJYQZP2DgBe+IyFaAnzF6OzSxu2K5eU1fYKbsL6MzvWUM1dltJgO6o6SkAk8ojchKzIkcF5H2HyUFGWY/LN8ZIsR5uCQ3sYqAuti3pd7J83O4U82d189XtYQsnTiyBJ2CY2ZrOE0TAeuVbrdh/vhec8sQ7PFfKmFxhGL3fSksn4I6DrjINkeMBWP3GogC8OSYEALOooSgGAa+ne5TytAd1SZLcDuAhGK872ra9a8NvbwRwA4B32I9uAvDGtm0fOsq5eLAbovQDL9Dv8ur7bGNhli5gYDZTUPRTioqUfTtAk2dvUsM3qf6qATprhCZ2VQnL4vhEyLq6bXiaBkgaIEkZGjXwzlOteAvdrwzo/FU2SJBBIJVvxf4iZ5T1FcJb5JvNg1mtq9MO5BgY7+XwIuSqYup6SpeVI1AZ638xF6qwbsKkJcHvQgmBzBfyW6u5bOoMdZaiRg5eXaLOKjO4MFMnFn0kXYV3wRqrmQcy7wrzAzDnkALMpCT6E+Xi2JDxHegOvrHCk6qwL0OsHGTwrlfvbouBuj1sYVFOsNyfmEjAvFXWvppSqwhT1wfajgjm1DWFARJAT5BEVzfmj0GRr52oxjUMoGOmbgCTv0P/ttmfoHyWh2ILTEw/kb5SmD0HdG454lrAAbF1Q+tOC5k6AFH3qwA7Q/poBo+NhdBFzyAvnKA5ajLUaIVsWGlBnU97O4Z2v/oz9pUOW2dOpEpVA4PwNubyU+9u5ehJp5tUBwo2KQzQLoapq2h/C+z2D7awNzXPzJPYwZMW2D3j5BOYnms8qJOqRfS6zMTJvZZ+Yb6vlOSD3fByd8O0JorB3OB61VHjYjB2jUXpVbI0nbhdh2SM8L0Jo+klT93iYGwjjAs0eaWMxb7ytAZ1SZK8EcCH27Z9p/yfJMmN8n+knABwGsAZAPcDeP1RAZ0UhcClYzYN2iZwrV40kHtKuyieKIoJwrVAneu1hY6WoBk+MsmbfwlicfoPeFAXqsscqPPVDJZLa5AgDa6DlWqaqWuR0vf6dwbwmVZJwpOqd36vxv5aNRm1Lq9toSNfU/Ud3B34/6Akchs1lJUvFUbn97H/A+av00yxVCvcPVyQTYqmzVAnJmBiQBNQltZIbEBPJ6O+0tUJQ+VVajUWCtSFbhI5i4iYDdjywuQqNvhWCborJmgxcz8L48Eju9gWVvcypxQsNbIIqJuZCXt/AuyP7ASYdBcCtyBhuGx0FGPoUjuaMd4pChgIy9ZTQqYuepy+CduFMgioy2H0detIaovEARmXdiJIgSOAboBAVlijE1BS1CXyzLtYh9atyhwUR7V6g2LlNHMe2Hl3uCiggE39JHd9w3+WqfehgtOvTOLTUoSA7s+s8EwumkWn8eNZzQM7V2JuV2brcni27jBQF2pEAZUGZ393y7lg9602dRfHsVdsYbp93ujqKl93B+iiaXlqFyRhrtNLOoSdC9MjZfb6yx4fZs0a3YssDNLkVdyvQ6zsnw+SkEjdUNLBa0m7caUCMMpRV7lh0jd0nac1qANwpm3bO+j/ewHcAaAP1KFt22v/NCdka0067WDxBBb1ZZjwRPpnNb+HbIscPpEvN+0a6OmU61X9Qydo4AIm2P3apGhSD8PaNBF0ppi66GWHAKGVgAgNr4SJ63O9CvwKFXHaKZnIlfcyZXIkiaP1oE87cvWZaNF7xR/6CNgjl00/TYL3botBXGZxIy7Y2P+AJmbZEmjoNea+FUBnNXN1naGxOeuc+xUZmjzB6qDFIHnCgDrRg0WSEMtUoidhP+LzwMspBwAzKPbpx/oG34xcJXL+0KJm9oXPJW6zoR2EefCV35QYQtZldJGv5ZZxu8rENtJCawZROUcpPgUmLlY6GqmwbDhPb9v2TdhRUGf/j+QrWxGYWYESEFtgNy6AvOxORGtzYR78LoHhco3h1EewuhQx8K5ZAXH8HQBnWDA7J31ShPNSQvYynKQzO1Hz93FQR4lmbZ46cUMfJYnsUYtzvxKQk/9D/tHXN++mvgHiTB0Qzx3HfST2npliB+xG2LtcM3US9Xny2HkMtuG9YzW8+zUwFMM0NqY6HpiHLJ15Bleu/WMRrCrQCIgai2FymE2GUUa/4nTJMq7I7zSoo7HlYIxmf+Jd39XR5qCnLahLkuRFkY/PwTBxf+YlRsXL4HvZ/W/BY4OfwOXPeCbG4kZTle0/bozdaZH4AIdDS9vBAZ6NQpep67heAS2YavzXBMaaJkGbahcsklol6aW3HQIo4VM2Um+vnUuQETBrLVbUjJw5jmH2uqBwM5DjFvJHS91R/Xf+lZ27XTdson5/lBKtmd11Y59J/G0EndfdzjCYJsbSHVapsI+Em3QPcd3WQFsnqPOAqWtTVIsMj3/hC/iy7C0+Tx3QYQhkOhnSZAv4VAIy4IZiZg+icvdMcqnDwTdSwkSyfQM4H1N0V8aiHjpWhl3BHKUm7401PdBLZwV1kzEliWnoeAINJuWLLfUhka+cONWf0q99KVHF0ckaAK3SCq+ps/9Xx/R+SyiWrsQQ6ykwIBdsngPjsudyua1qIKt8wIlMkX4C1e7UUBjPkzGzdOx2lePI71W7QljcQh0zBuTkf3kvLli93JPXum0q6vtIfxjE+og8gznUfT2UIQyBHPdRYevC34XsXNhfBAxS9PTe+Rn2tn0E+S6Om9ftGZ55YZ9ATHBeW3Q0eemeU5/yV2vqQkNRUtmYfYJxYcOYkvWsJqGbTEs6uL5iKLJxKRrNaH66/YmXQZgTHyo7sT972pYTMCCOy+5hOyVJcsbud6gGr6+4h9xaisce/SDw2P+Gz7/iB7DeOgm3sGaYymEAtDlQpZl6aIXhMO9NioimSW2W/0RPrAmApEWSNUgTkw6Xc7kJGGmsgL1Z51aEAmBltwrwdACnNEl9hdPEZDCQHHtFg/OZ1ymMUCJfWf3PCkAJVJX1RtsjytGGqbl2Pl49SFxuvgYcx+rhk1aumQYwuDD11+faLKXjeOijk5F4eOZ5OdczNBhGH2PnGTrP3HEsLsNec0cH9koHWCFfN8bSlHtiG6xtLLCTiOKB7zMY6vbirUZmlu6qM7gEwsyyMmiLsYBcIm73oIl8/WyfTgcV8qSy12iyL+aDL+GyZ/0THNv/oDnOAbyuzrpLJJWCTKYc1aqj1MpowmHA69zMb3voJgdgEm/NB0zdYQJ4/79m6xjsSH3CKLV5PdEsHWxbhAyijCl9uiWgfzR+KqP0RvdrVwsU3T9kX9RKraJ+Awyws++DSX5VF1hlxNaNUgxkzdTCMHWDA5M1ijGoHJnrMCh9TjrpVz6KsIJEW4dMigTchKkoQkO+jz3TTloP7FbgPlN0QF3XBesTD7MbdFNqEwBmnVlnoMPNO0kOoIZepYO3TKdhCbcogAn7J98U1tbx7/uAHbtvRVe3Cyx3t9xasLuWqROWaufYPgaiq5PzZQAKbScxeBfg5l3xouFdqD5inuuVY1nDdCb6uvTg6dMk+fGIDU7tis/pvUkwXFhD0YxpE7ePZ/+169WxdBJ5DnTAbV95OoO6nchn5wAgSZKdtm1jAO8jAHZFR5ckyVsP0eB1ihsQ6loNjMc+/UEc+9AHzQQG+DXrrgLwHACnAHwFsLwGeHh6NT6LK/F5PBufx7PxRVyGx/EsPI7L8EU8C1/CMeye38HyS8eBfY3EMQKws8T2M3axU5j4IFnmRDruHBM8gZN4vH4mzn36cuCPAHwMwCfs68MA8BkAj8CLmnOYmPHLAVwD7EyAFwD4SwC+DsDL1njh1WdxPT6E6/Eh/GX8Pp73yUeADwP4gGnZJ/4Q+HQNPA4z6E7s0Z67DQzkWC822588f4YHcS0+iyvxJZzEHrZgEoAa/dQW9rGDJ7GFfXVtJYY2Kuq4ajf5zFtlBhDI8sdyLL8kTCiONaJVsYwOc5c4FsYllhVtVYUCa2xhD5fhcTwbX8Bz8Wl8JT6Fr8XHcfUf/QnwH+19+EMAnwXwRaBd2sF3CuDZtt88D8DXAngB8MdfsY1P4avwIK7Fp/FcPIxr8FlcafpM+Uyc/+OTwJcGwJfgl2mKiZJjgzugJ+gwTQXvOwPwDABXAHguMHjeBTz35KfxlXgQX4X/jK/Cp/CV+BSegYdN8EdoVUfmCXG/+hx1Puv7EFr3It8DwAJjd5ekOKF3T9Lh8LxcpI+FRY4pbjVh67g+0kdE6+Imot0tz9Lxc6zOGyCsw3RzzHgecYTuBQY0KcvEZKrYXwkXbBFO2Iqlkzx18vna70N9ra4ylNnQM3bFENPp0rlfk5GBhBHZlLdLa39MnsyNRjN318Mb9xvmqEJ1GU/MmyIaZawoqe14/OAACAF4IbCTxMMl/IoSR3bDElBzDZUD7pYywUBEA5MLvDSYew6Y1Q3bPvbZUaNfeX+Ont4HsDvA3hVb2Ms8U+fy1m3v4sTB0uwb6OpqCUYN7l2BUrWjb229VJy57rwzpvB35rp6AiUyb4xuen7Msfz9zew9l34b7itLDCqmbn/isYGA22qzd0LK0xnU7cKybVTC/1Vp2/b+4KN7Afw9RDR4ltE7AwD5VV8OoMdy3WRRcwcXUWqeIiwxmr2TCyc4h6QeiHVAp41g7YuyqFt4S1osazmJdZt0HsBcaT5KDPXCylNgPALyAy9uVgNxcDy2ZFgXxRaz+V+/muPW0f3FVt40MdfBXvJZSY856xz6xM1+HdCjLenj7kuPxdyxpnkJnDxuUfN1qbJpAGaXReh+O2wAjljVYSZ4lTh0ew/HlrZvlX7/ls4ZusRMMa96RURe0smAr9gAaC4jErWXAyb1wGaLmkt4X4XREfBmfmMmATEKVFJQYek46S6k7QNLX54BqQZXJ3Rfh+NKLsAyd9cfy3NWSzLmGEuXd58zbiduk8644vqXjCkVvc/p/9ZcdyRXndLVca66woA6ceJyc7hC4I5zB7LbNNTLhdcW7sP7xtqB24ONwiG6GkvuxSFzxy42n6fOjzebSk332RWee2LjivShwjyHehUL7/YFAvAetnf4nseS8PujADseV/aBPTuudNdR3sJke4mRpDWpoNKaSJtxYExtgZP53AdJ9CUyN8Zin1Z3MyQK+1Rnf7q3ZizJFVM8h015RM+vADr3GrJ0BOpMHf/rDZQ4hy5btwMAPSwdkiQ53bbtffTRLoCYNk/csncBwPjFX91RJbmlWcLSR3WLZZTzhKwf3N7oIz42cOR8NAC6D9BSPuSUA2xR29dwn2VCg08gap7BiZrHB7DdksAddzBrVed17dJKhANtDOiZV52dOwS1kiRUvuvTvZgHZugmaP2IDzsuEgZ2ns3TS/poV8mK3nuLXRUeZEfwAQgs/KVNzhNa+cAGHUVocPD70FXCg/PFWNX7CfbKLewXXWC3le1huH3OeAXkXNZNwu3BFrX/TNZn5KhX78oQxqzPxbGpsEXdV3hi5rIKXL5+cDZ1UhNQyNLx4BsbOzaVvsm5p95c96O2iz/VIS5toKd/8JgSgjv7fzVQ+6yWBeptLxSfYwwU543BOIUBdRkwqM24IjXiNCdcJ/3UVupaeNwIr5EjYjVbJ5/7ibi/Scy4IiU2rvR5AaT/iAv2KHo6KXWeAXkTn3MkmEAMRSWB8OOKrosHdrE2dq+hwYfIeyDudg3HlBxqXFnvj8lYnLkx5Th2sTXdQ1EujXqEjM2QMPH5H0v3XPh0Jp4fde0I7549UqFrzTvBV76v9bGu0t5D+HFF7gQ/u579Jy3dvjaOnJH+XzNT17bt/UmShODtBID7Yr9PkuQUgHuTJDlOoG8HJsfdkUs0ooUHWZmcI1Q339MjPbBV0h38e+5IWCeXZyj6IBF467zaH0X2W9HgNMcEyykwksF3CiRT4Ng5YI+qqgZfYiGyqkaW6dQCsWuSgVU0Ldzx+XdHeRhDdost7BIFFjYBqPwf2u6yr/5eT6J9rKk7bzgpy3vRV4ef2fex3FXKKNiUpiIcRMPvcsQH202DMLF1e7tb2HvWlotSY+t6PJ0jq5ZGsF0B7ci7SQAEV5Q5YKct6pUCfCUKSDqRvnJUi3pTnjrfRJl6z2krhg7Ay9JPNplsyNJJkARZ1EcucnrpFyHoJ21UX+l8d7F1gAcATe+4AmhAFzJ16w6oa6rMjSfOWLRgDiMAM+MBGB8YyDiAS2ccd/PBGwThve0aj5JrzhwoNBjlsxw1VvRZONbImcL/ZUKOLwGmxxRm9bpGYrfwWFZlGZCtFQvnxo6KPgvGntUodQCu7mxH9ACErzm6/fywMUXSodCYwi5Y5X7FFmbYQr5dYwtrI+/IgXVhwa0tDFGNG97cL52/TktwRE8XsrSuzWsaayNFDAD//2Z21/9O2NohvJHhDVUGdIql44TfF2EoPm1BnS2/EWjibgDwVvnSArkXtW37zrZtH0qS5LaAxftuAG/8M6sNd2hOtkoPVJV1s3aHgwJwtCgWtkQPLeqmy4ALdHtCRPti2brSTbOyAPcAo+lapyDIgLGtkowhzgVAp8uqBnkRiy7rB3kyuIbXH0/46K+LJzzRMISWEA+8C5vNW4Cb/E7298Bu2HlAY0W5UxiscU4uZuo4oWZhgRDVR+og590UkeVK7KHvG3zD34aDcsDWNfsTC+q62xhz5LMawBq5ZQdWo0GnvwvLyixYqH3hwtrJ/mum4SvvkO2qsEUthdvan1fnrwrBvstTF2PpZAIL2jf6DDOQY1cr5+WicYX7Kbti1fWEOkNmVSLtceSiAJ36YPM+SwBLv5j53C57BDIUUQCTKbB14IUiA6B3lYQu/8Xg3Y+88pnZR4+jMfAW6x/mMgLWnACbjJO8DFjoBZBjAN5wY42bHDPehGSkxoxF6arM0BX+tc69x0G3TiDf6Z44DujC34S/7xtnhKlj5olcsMLUibG4hS0U2QrZdA/DzASI1DS3StHzQW2bwgM68QCY703P6QNlFbdJcH2h52wTwx0SCwDA6YK5b8rYs4eZezYcS8fjCkDz6+GQ7WkN6tq2vS1JktvtShGnADwYBD3IChLy2X12BQoAOAng3ouJfo3erJhLhN93tFF6wNUWnr3hYT6pQ8bIvk5UsUUtxzkSsAvObTeeuOaYYJ5NcGx6Xg3Cx2bAufNm1xwmWEJNSvaYZolQPejKa2gtx685dM0eHk4uE56ImRmg8cArr+wi6R6n66jZVNwgHk7II3QmaPXZCNZdyQxdvP9ESwygHfZ73i/G0skA7ITNcResLFZeZCtgNjeSBZjBl+vNKQgqZK5VQzGzZ2t9hqewdFiGDdcb9q84sPOMiQTyaGAnwR2yQsAEizLC0qnI1/46qcJjC/8v+f4E9OceXHAJwcGhp8tr9fwBfTriCFMHIC7lCPcNt8QBHQFB7ciw/qLVRWHGEQ6YGPS4obuck57UN12X5sC1u5a/95eS9b4PAV3MC8AlfL6PMq4ocMjuVWbqAN9fghyAZeblIyV8KhUgMgfFysX05cOMRWbqAhfsIrJKyxhzZEWNOi+RVbWVNXXbi8cICbxih7h8bxi6SrW8lEPHWDp+KBmS93Wkr+i5v3ZzkXh85N7KiiN752ddLV10bj+snk/z0rbtmw757k30/0P8/8WU6OAWDrb8f4ypyzQgiN3cow7AogsKS0wg3bWsegbccEAOOsyqHKIshD+x+peRBnWDwsTQwl7yOEgOGb2WSG+MDajS2WNA0B9n2DkGwKyLdpPII86JH00i0MKxQbF7woqb7ncaqLNF3ubEXErbCEaIDLzIjJtE6nhk7UtYYtb1pt9u+iywqN1i3AUDujH2MHORxsiAYSbL33RzcIWDYF+QhNn/cNDfV3K3lE98sjeX2s+UiOtXBO1yHKltJy9dn0V9aEWh3a2A7xfC2NnnSkB/xyX/pyxHDkLZWHosioixKJ6A+TTFdNSocWVrCswtWzcGkEvbcIkO0T4VCQdUScnQn6pEvpfeEGU/FQwQAyDrADo2GvvHDbO/GJSxUgf32L0PyIPO/MMubduHmKXTMNgc+yiRlACe+ngSApIOsBv0rKVsPstQAxmQZT5QyRzO1DtkWmVjQMeegUMjVo+Qo67zeW+/0c8pJ6vm/umSU9d2mUFh6cJxxXkAEtUGsfK0B3V/XsX475uu/gnQkzI9WOJGA7Q7T143DsZsjR4SKKGOczEsTex28+BbZaiLTLlh3cA7gxqAJbVLHjILwSn6GLejlvChlEG67wENB0MBc37pFZMIlPUt4blk/1DszL8JH1r5bVkAI3aHSB8B/GDM1vYIKAvJX6Xdvt5NchGPaawPhNqk8PcxV0swAEsU7DwIvTcpaSadtgv7egjqmL0LXa+aRdE6lqdSNvW5WF21Ve9ru8AEq3LYjXiNWdR9VRYQJ+OKuOaBjvtMGF3RRvUZip3/w3Nf7Cgv+s0jGQl5931gIHAQwYLTmtDYMpkCkwO/FuyYme3ImBJLWdJfwz6PweFuNHnP/7OhyIBO2LpN/T8cVzYVBcJiTJ1M9DH368jPOaF+uEYedTNG+wn3AZZy5JHvw334vYj9g3FFEhHzSgp72MLEBlABcK+xgLQQ1ImBKKydgC42lWNFjttw8u6e52ZToFHoSWDw5fPj+WdY2P/5/hhYFnpMiUS+AhZ8xlc521TtSwVAXMMgA3FkAOZoI8C7dC7KsiZt0OGWBQ2ihw680XgyXyqgqrwGYxHTv9htMgUqez7F1PUAuvA6+h6GvhI+iLGoVz9Q+u88D+Q1PQuw/sWDuizyoF5M6gH32zwFcp9cFVNoFie0qAu4KFt2CXcY2aMsERMOpsFgoL47qqvEDcAJ5vUE+5leo1D6CTOtUm9pNxar07RC6Skqt7+U8D6YKtJEG7GqL0b7opujjzVhrd0Q81qyvHeXw4oNvr3HZ0AX00YF/UMi6kOX3aFji8Jbh7sne6Pyn0qhPibuSjEWF5gA06UyFMVYXCyN6zWhKE4Fgp9SVUKApZm8TSxOaKTLRLyisYXZOmbbw3P4Yx4+J3TIgLBvjODHlhDo0bjCBqLajpDnkSqjX8N+vukxO8QDsNyfYL49UUa3MRb3VJASuytjwC5mKGrjMD62HFryypEshxESoWzGz0mG8S9coEblfj/HGKty6Fm6vhyi/39yv/6XKtxZamQ+4ogBHVtGoRvNWtTyoIdgYGO0Ux68UnkqLih/MFm2gN2xYgvbQoPvalmg2vZM3RxjEwEbDL6YAlu2gyWcyy6igTmsbGQc1NX4R7rvN+xacMyZtaYl8o7dr7KMC59DUqEctX46vjczDC9lzHf9w5zA/y/tNhJ3jo+KCyfvSGP0l3DgDV+P6kqR3xKwm++PMd/2bKeAO16Kp8tIdJnQWMKHUBvTV6Jt8hRHsRAgSYkxwSUKrJY9LB0PvkBvGzvGhTe2uHlypgm6zPR4EpMZADg0oMbnvuwaRYdFY3bLgF4jFp2pqHO/+sTeYiye63gAJlMD6PJQprBR2nHUiPiLR4SmLfxSZOaSPPs1t5HQoWaXGSVmfPvq1s8emeOsUGi9pRiGTDLw+Dwy0aIchiR5Nw8th40tfYZi3+/D/ztegFHH/brArh1XSgeAGNRxiXlyGOCxBm5TOx9WQmB3GPtvXnOvXcwklafvCyWGWNWFNRSLOKCLteEh5RKoC4rq+DLosnaBmbrAlcYWdRV0L4Bu9qGD7+EuJ9cRoz8bRF4PYesqQz37PHV2EJ6OMJouzQoash3ArGEJaOuRAF2d64dlMxgz9Phh0WB9+wIrCEvH2pfQmpYB2LhfC6xK0uflNepMDxC+aTzjpM+tXTQVMpRZAYzWfqCdwSfmBVTUn2w6XmvY6TfRssEQsJXuArq+Y/A+Ug6xql1OJUwwFl0dTPSZb5MmurNgAAAgAElEQVQuwxYbfNkltqmPuPd18IxSyXLPj5vzHT6Qh4NveD7A6E17WTqZqMTo23A+p7lkACdFnqOZ/y6MjA77XLREPKJ/tiU8KI0zkT61Koeoi9w9jysMox4ATGktUx53Iyydd59qwwzQethNBkLsu9gzHkZHy/PKhqJ6hkuu0xDDYtUZUzYVZuvlnq8Lo2dWHoAKxnUful8Lr9MNDcVDZUCmEWKV8q8X7c6n18i4sjgYYz41q7QwYzfBRI0NAFSGgLCEMy+73Vf0Gykdg/2ozOXGS9WyK3XcTP/GALox1sthN+KV9XRmp0tM3Z+muAeZrWl5iJhpIctILGpPd+edYx6p5Ec1gw4rMWDXY1U7ts4vYcP6M2wv9fVu035sObK7ZENRjChMcsbDxMzh/+HkJscK9QorNwAPaQAusDgYo6oy58LO8gp5XmM4WtmAFx3+vula/l/23j1Iuu2qD/v1nDP9mplvPn1XD8TDKLLLEMeUZSAVQ6oIKcBGBGITFEhycSwnzgVBbMtYCUhC2AEuCAqM/OIV4lAFSgUKqBgcSApiU5UEkjIPORUHQipYEgQJWbq6352Z7j4953Tnj73X3r+19tqne757/ajyrKrv657u0+ecvc/ev73Wbz22wEdasKwrhDe9N6znLblfrYsECAqMApu7LNhjANyOfG8t6gTC8yKYWcB3iTUpUj1B6mHwlc+ehE3J7XmyedOjSQrd0Ie+5phW+azbzLDbTEtr2lrVI3FoA1r0DXAqcXWWxWWFX+KiGqjSOpbFrc6buzAqVqyrP40RNg7lw0X5mYm3GvoG21k2WlZY4vYMOL1EyLoSY7FD3oYxFjxPhnSFDCxu/cAYqrliG5QJFR6myDyXXXcEW2SHke1mWuDK0DeYzrcYGu2GDV01bsgkHJuf4PRsp9ccVuqMcrya6RAT67o8qkxSTWpxdTCf8xjk+WEUu9X1Eqszzf5f4AorrBM+sCvW6y8vq/UYL9cxTG7zhNgi2C34HbBFY812MwOu53U8Ae6spd0rdeCN3bMMaLJCJ5b1AN/9Gi1qCXYv2bojuvlI0AIyMBWWRTqHvFkg7NEIaPB1LGoA6IOCIoAlVhPOntPgKxu4V6xEtCiqf4+5MT0FzQrT7GMT0LqoOoqpS+26WaDbzIKFJL9rGwxCsbdDWNjpMg36CPBDcrnyNfP1piXIsvLEoDwH1uenFPs3Ne7cyoCwH7/YWcy/t65aAeFoVW+7KVazEEMk29pIRJGNXznINkYZd2W07nv3PHfZiQVm3BnwZUljZXPqu10PuEiUo7kFTi3LL4aQZa5mHNJRYsvR0h63S81hpfqU/i3MZy2AicvU9b0oQ5Qxen6K07PboLxdUptFjHIrkHZM+60CYxkqO46kPqZl56d0PnkVJUlYOvECiHvewxXMO2AzDYodmrjTzmFPjMKV2RRn840mFWL/KryJ/WV3uvA8R6YTnlyONSAqit3ueon1q5ZpbLAHwGbGh9Nkw8bDjkMxkneKHZU1odEGqHdee40xTCkMRY/5f4J4OuBeqVOiSdtGTyBRZJj+Psvfd8aNZi3qqrwYi7p2PgW0S+SSnrLLIrGQbG31EwewFtifARNhmESpk98Iw8Dukrl2Rdck99GQmJoxF2xt8Rdr2ioA7MpMbuVhRot09n3t2h6Yb9FtZpjNO3X+pgluXQvEml1r08K7n8dA75pSR+Ona2Zq0ZZSGql/aha1fX7y/knHUo2xM4Czul5iNeOMv9JV4iU5lJe7W9DxQWYqCit2NXe5HScMvoBmMYY+ZgpKzEvv/AOOAt6g1J3omMszZPe8jambBcZFxpfdXuogy2AMRYmp8/qkKuocPOjsDtBL95roQx+ycbXFNNfAfICMKxymwBhL8WPWbS5tEGOLXf7Nof45IIM5n3xmWToxFFfXy7BI921gO9s9dm0fOKao2KXx2WRD0dZM06VTcuEfzExySexfa0Tuz/JalDH2iPJILUpcGROP6T/m99ZY3IQkrFWzSMaiYIouINyrvpHXYxi58haOCGNw5K7Xsoxon5S8NhuKXtLVHRU5lnulzogoFolxsZYRUDIxc2B1NldJEuIykXOOWpfmKXhFQvP9jbA3BVN3at4TW+dNvD6D1jYmGKyxDHWlHuw0UwfkjD/jhkYDVf3bTiBrherPj3At0bmAzN7x5JQFsCPg7TANwe6i0G2IoW1PsQMKxe6Y8jJ871tMQ3+xq0TAT/pKmIkYzJy3UDoQTzfmSuX3h8DAKoLWXeL9i2Bze73A9qmZsqjFrS0uEk6c4GdyLCD2ZkwcFLObxDjzVx9bDLjhVbbMasJYOeRyHRFhYLvZFGctMS6iyPA8Og//bs+4HIjOjLaJDW6G7ZGLAvezG6+YDAZm6mRQk6FofyPnJ6aOk5VwGWtgihcg7HwePADWFU3j1GP5C4Pc+c6WEjmG7bTXyrXfsqIqhuJOFmkZE+0k4UpS7JAxZSzEw3p6Oi8OEchKHbGd3QypbJOO0yUnZd/i4O4EhwxFiztyP/xb+/uqC3aB9eXSGIviAQgGQ+M897soWRZLrMclfNjQ/QdcaY8sMaYUcgqb8UpS5TUImpmz/57AUL9X6qJoMIjB9mw9z+lgzl6MlhGnj7OrxIvTSNLuAVBNnBawpQeOEgu+mCDXaJcq8LKj4hJKqTMjoDOAtUIoOnt2/jgAxwNo1pIXI3KXeOVc2CplgJWCr6wE3sWSkkQLqyAy+A5oE/gmhY4DUecA+ha7DYD5trCwvGLQvKAyS5vqcMk4GaivOZ7uDCljLte+OsDyWmt6jKnzZjcfY3/v/YYBZwNgc5pKOKwp82+Jldqr1YKtMLGyiHnuLa2sOAlGY+OgHVTsy5NY1KzMASCF7lQvREfEz7EwWzKg1YYig7fjeuV6ilnx9+MV23YI+NGemnGwV8bJ3Uo60L+elTj5UnBloY8nkf1fZQ9YidXdnwETMRRfgJ6PM2RWSkJc2owNYy406SvZoOlOsYjQHgT7eY+soCYlLxmKp3p8yPrRt9j1A4a+RdsOaXzVCswP1EZWJFOyhBiGMpcNybA6m6c6o3yfxfxpe6jkuRpTZxW2MalhiqfYkYK33czQXWpj8QJXWEcPgOdSzZgyKDwJl8gMXo08YDm0xtxlzugkibbwtiRckb3fxxQ77/wH4iHvlTojA01aNYnEigQyIEfrKLteNehay9CVOzyB6iIvr2oyCuBKORN2vyJbvyx9sDC2jezTmP/hweMyps4ydQTAXFndgqkNPBbFDuC4xLvV+KvFuLng2xPrIl21AYAJMNcAbMW68PjvngAYM0oukdhD01fr81NiEfVG4Om8whZZOQTA9m8G5rFjLPjKK1nWsvMIZxULU8cuWB+Ey8WSxS6+PEbKPvAac7xwH6fPrEInhXhrlrQHvJVbknEI65rvobOlVbD7TI0PHhsHMxk9Nn5E0rnE2CzG2AK+UhcVu7k9XtqXlVrF1p2d4OwyegAeozSymP2fB5yVLdwG0w/8mQ3HqDF48h2LNTxFcZDfcd3LVCokjRXksSJtB2JfBuZGFuRj4j8FF5PnROIQZT0SaZCx+SywdIwrUs7E9QBUjHutzDs3VzMC7W/HMIVwZbeZpuoEeUcjyawPz1xqz7GwschYzM9NpPQOabd03zeRVMmK7skBY2jMuGDlS2G4GIqekfgi3K4i90odiTx0CSzdzk9wKtvZdNBFQsmFll2vOji1Zhm6Ezo+iRMJ0nfurfq3u8AL2LJS9wCFRW0m9NA3GBpxJc7SvnS3Z8CpuEluUCoqtBjxXpVWwc2u0rC4s5In7fIW8drC7n3WE/gO9DwT+Hq1xRD/7idhEToSgLVFnZWc27PHIbtPAF7cbKTUdc1MuV6tm+Qod/0YgNaO5/Z6zF/Nqo791m2mMa5uke5fijvn+JcGebuvkkHz2KbSbVbfQUG3r0/gW2M/WNQ1U+ZrW1HoJscrcyPXY4VDxdMxa0pjY6Ncr54L7YCxoxjZ8MZnm8t6gun38iqM0/UEo0qdHOesKqLQyjhJHoDLxzr7Ve6b+yOWeNnOT9M80wZQuGAT/95iBo+5d70xFbGKAsCYlvFxGGIGo7dIt/TeYetqz8M+56RINjNAlLoB2VVNTN0msv9lSMcRS73H/vOrd7z3t4cpfIxV7HoAm9NQ4qPJTN05MXUioq5bCe3bkkJfrinWE1CVdh/mvcybJ/CecYJEUujSa+uylQpXRjwubTuMPs97pQ7AHmzttWnCrmZLnJ1d50kkCzRZ2rfRMuL9RK1CZ9kdIAyUndDfaTLo2CBPqhOUwXcOYMPgy4kSp0VGWZI4kLj0QHLBXs7x6HyjY+pu4u8FVGIZgtXZSVGmg/tB3meFSGedWRC2ljUrPJYNYiVLLF1xvQ59q2NeeALNzWfc58ld0qd74PaI4sjlDZRVHTo1L1SX4npdaIu/otAqscDJ72sWN5zPvd95gC5CfbbdzLC9zO4dDmrexrg6rkfHopkUPZZzskmOSbWK3SiYHaj8fgzreyeFzgLvSP/lMTLLBb2FbWElJhqLq7N5ii0qXfMHFqi0KOX78Moy2CD9QrhNKfzExNClMA+UTF1i66g0RzIUowfgbESpI8M5lHdpTPstqzskhc4u7qNsFfWHvAqrzOKVHtpupnHMoGTqQJ8ZY7FpBwxDkzDFSsYvVoQXuD27DsaiVerUuFmkeVniaavjJkWOMRT52Xi/q/3eO8YxFrebKbZnlHwSSyXp4uZ1XGGywOKKXRdq5MFdhK9xMD5TKXQTf7wcYv+P1NbulToSngCySKfMT5k8gJpEV5cl+NrBA4zQtN5EGbk/lqAYogTfOWISwIN4pMS9XIQ/rVJnmbqZTpaQ2kGPHm20m0SAfoacxXaW9zLVm0nrBWiLsHODbNLMW6ccTL8f6RO5RgFmfRNdryj/sUUNFFZ1Pm9bLIIcfJwz/ILFeXH2OMQMSV81SIzm1eU8saAydphdLOKG2j3Q2vjLyj8rtc/l+bFSOwbYsY92mxy8n5m6wNZxULPkM+cq6h3ELVZnaVtnDpWZe007hMSWI2tIWcb8KOaiptDZS9YU6XSa/Dy3mGI7P8X87FYv/sRMbchQFKOKMy3HFLqT1C90nwcDvZ0wB4spaYFfIEz2NTJTt9TY47B1qTQHpqlNV7jAzeWHsguW52KLnECh4pZnakwwxsp4ErYuNGNAb8aRxecahnifieGh2P/NrGRccsNHmV0PU1j5FIIhKcPnpzi9uc1KHZBIhs0l0vZ9manTmOLKmHGolHPzOb/a8zGe1OaHUWy6zQzdWbjfkOhxhRUWCGVNQgdOIe7VElf4+TOu2LUoz8cRLIgEi7B0XiZ99jqMx+slqRmKQHV81PpuLMbvXqkzIm6C5FKSTEYgx5BFZurm8kQpcxZ8eQCNSpogvbvP3MEFyCp0Aqq9uFzloEmuWG/BOkquKSUutRzYfHMZY2BkMRLGTs5pwFcy9jwGSuLPZApK3zP42sQJC7Qyub1klMIqs3EvFmiVSyBnxYpVbcUuCtlVkq3qq8sVHmxu5QdpN5LNJZArpy/TAqH3acwPJS3U8hifRKnDyHc1AOb3atGKSSdNZnS9oGbJhs19JlZ0XrBk65xwCa2Ic39In+t7H8IzpZCFOyUBGClYOm53bbyke0G1//PCPNUKv+CJKNVnwO0D4OrsPC3Ka2Jzs0JywAXb9mHut4DH/tcYhtF4K8GV5IJtoQoOn2PcWASHKCySIXw1u8DZg8fAI5RKHYcqzJAYKJtMJPctLB2/ynjjXSDG+q6GKdI/RcyvXaiB+jghY3HoBxdXLCud48uiy7q5wPTyuWCPkVK3jyydxRWObZbzKqkpdC8WU3jcAFnZrRiK6AOhwOsnK6W8HpYsXcCV7HbP3h/G562ZQ9wf7hr9Ims7elmvtba7eMIM6T1Td3dhsJTJu8YSq9kSy7PrkKMqTJ3ELsw4BVu70jTjUFrCTdvjth2ANoICga+qaO8oLK7wgz9H3p/SZjcx+FYAOE+CWQZfXAR39KNrzdTJghSZutXZSQJfsZil/XYzY5mI4dbyNjBlsoSehJqpaOmcjbr/nv9x0Ls3kQq2rokVwA8rCQK+vGH5GkusmjWml48xpwl6S661HBg8U/00alF7VvQ/CQC2v2XpJwGAG71LgCybQK4A35A1zVs6CUvLGWteBjmzLIfkmFhU1YxDxpb36GtAe+A5yPgXl/vq7ARn/S4bRrMYynF+SglKS8pi1NmMnvtItV9csPJn67mrKiU12h5oKUZO/p0jLs5m/2iLJxZb4n2wYsUegIeXjzGXOF2r1JFb0e6r7THaogBIRj2zMWOuN/2+xBT3HLzbyxgjN8LUecLjvkd2W8uYWJyt0PSbtKXa7SyMG9nphXfQ0QqwGZSSFFAbxx57DzoOle94XWBj0V6DJXoAxLjl7dhCrG7uwPwUMq4IOcDPX34j/eAl7bliML8WU3e061bWHmrrKLak+0AVT8bkXqkjyQqdzuy7uuywaG6T4t7NgjV9hfMK+E4L8JXzuyIK3RFukuI81pI+p1dAZ3jyMZatk2ukXSV4Ui2ju+Qcy8sVzrpd+I0sSA2AS2B/yRl7oqgI68Jg7C2+2bLqTP+J1CahBSt2iSqLOp/oJRG7uDCzIplbzdmAoV2h6QPXtjqb08bVXOtN1yI7CBh3tart52wJAhloWLmT41Ae121CBqxmQabJnS7SoI+xdqHERHaPsYKX50e5e4Iz5lU7hphcVD5UiY0SOTgPPTlmQT5CoWNDKRiLazRn15jFY7uYCHDVXJBbfkHsVGb/x+ZFCMkYwiLS7qGSSJyGVA0Ju7gzrlxTnzCeyDEeUzc0GJqcIZ4x5QJXZ+eYPXWNCceJAUmpE2bb1py0jLyMrw7lfrDC8ClDzxgMNg4rdINmkRWbnOoY4jhG126/lg7xxyMnyeR6kAtMcQFcArMuGE7dbJoNSeTC4GwghTbxOOlxiylSWMcxTJ1lj2C+F/yQfZCL9ju/lc97JA/ANm63yTF1azWPhwJXhBwICt0UM2xTe/VevVNaX/ROI161Aw9XBgdXijXIq1ggjK7tj1q/yHv173Dc/b1SZ0RiJjhYc9Zs0V92aIfIJjWztPlwWJxz6Q+7JcvYQnIiyRJ9i5xp4w+iUfEUO1bmQN8fwdRlVyIptjgPW0LN1pg+eBzs9BlU9pWwdKKkHFqIZIFHjK/L126TxVbrRwVQsIGxxiKXwGA7qVjGXGsjwgsDM3VXuIBscj/MGjSz0L4VFriOe6YyW+fVp9OFYIk98azpubqpOlAwkAKlVQ3oseMpKr0o/xyqoGPqRERh8wLyrUWd3U2ccOQXsQbi/Om1QlMTZmxeMjmSqStdaUHhxxmwjQVp+6ZRe1/aws5iMFql5Fi24YnbZ5k6XoiknRZTnLAOyaq3BvMKCzyPh5hddnjQ3wJSXi6GKtw+0EkjuW5fm1hiEV7Ygxcgf6cXdr1rS2iOxpUSU7KRkRRCZuleIrEGqWCDTUgCgO1sm9omY+dasXXaQDoo3hi27L1VOOwrYxHjCuNLzfiMHoCu0UydxF/LGhFCOySvRrtlrVEJZA+AbwhoYUwZ21pPFLs7GYie1Ng5+zd9figb916pI7HKjFS1bjBgiSbFMPAkErZlTcCr6d5y8DTNgLYN+w0yO2cHked6LQaRnYAMwPI96Hu2qGsAjBzbkLI5Y3uXWKO5HHDRXgeXCUIJk9XZCa5mF8pa1MV/64uzWF7hfV7YORuyZlHL/WqlsLSoq9ttPaFwe6wlmOsrXUBiPKR9PF6ucEGsZlbsRuWQRe1Ze4APFhIj51nV3vXkmBj/wgystN9mpmV2yHe/ZjdKdlFmAJat3spMctkoXUoAjVV9f9HAyzLW3yNKHcfdhuDvkLS0bUKf9GgUc8tKPy9I2lVfwnfT9hhaKqMQ+8cuBKMGpxQwvotSZ9m6Cq4wtqyxxHXElGWzAp66wmJ2i9OYFXw7CwlFV2QE5aQiXQfT4gegmUlRiH088ZMiWLHT/UWNGlPsasrLASk9ANNiPQr9GJW7OLbEGFiTYe25nUUSqTBmLNq/uW32lZk6Vgg5Hpf7xTUWGwwznXwm2a8WS3TZJF+hk/6xhsBoWMeRJUzsuKkbWPF8/anzHXwlzv6d/h22IO6VuigygTJ45jgh+Z6PS3FmRHXznoACwLVEASC6SlLBwyBtO6j6RZzJ4y1stzWFjpkYmGM8d0k8RpQfieXgTLULXCDsxdcnlqHpBwxtg1WzVG5FVgp58QeEocmSs5j0wm4pcquspX4ki4kB+2DMFMsTzgRZXBl8JWlghi0kYYDjO3I/MaupY4W0qyS61NoWblFYBmCvNEtN2bP44OGFGR9qPUOjnldnLGpAb+3Dip3UEZuiQ85Q1Ao9g++xz3IsS81+bsUyfwcupPu7ViYIHKNK7D9yzCGQXW0S5sAZ0dlQrDPf5f0NqU3HSKEkStvYGORgd8aXIz0AHqZc4QILrDFDF7YXvFwpj4gw25wNzPvIaqXFFrvO/cMMn1WaPPbGsjB8rPTXaGX/I/DEq1VncYyNPlmP8pjJBdslXlOvRzoGs36vFRcsj21R1Lw21pg6EQ+PLK7IoclY1CEd0vu5n8ITycXOywxijtMO825BmHKYvRRjsWmG4vz5PvwkviaGhCgywcS5KqkZikWZoMPz+V6pMyLafLaoQzq1p9QJMMkeqcLWZcDJNHpNZCGpFR3O9zWWpQMnmDl+15tjPIta/qWf5EHPQBFciluIBTttOrTNAIknYyVX4gx1X+Q+1KUsSqaOQVaUY/m+1jf6/rNid5Clq4HVEWLvsXPA11PqLCPD4DvqUusdq5qtYs9NAmiwqLWzxjaY8QGETFG9QLbE1OUT2TguXninMZCdWVZ2NfFWR+F7fcMp49Upriv31NK5j1IQJR6N23+IjbPPoQVs7IvMBcu2lErdwjUYt45SYvsk90d4FQXVhnRY41AZEM0QGRyUmGGVOu8YV7HbKwaGszlFiZ1FM6/DND3HocDZZVqYbSarVXQAXSaJFQXtRfEnu8UUT/FT4hlNxXdmj+KRAHzBEr7nEE+X1yNpsxgLQUk+V4xmKr3ijPtkLAJQzKx9thv63GurvFqFn4UzvWtMHXJYB8d1TzFLvZ+7NHOpnjRoILn3OfFCx3q7BMERStMYfhxSFFX/jOFKTbE74h7vlTqSnHafLWoZSOtkCzZgq1qyuHKh3kUBON5Cwpr8CS1OpZtEOI2K/75mUct3Vqk7YFXnzaZzOwWEtVKnWRZmGbK7hLM7p6oPvAmar5vdkTYOQo4pLCMwW3fACqspOObzQ1lP1uoXRiUodR0pdZqNkhhFW/VdFhsryaUGQLF17N6wf/PncF7le2tVyzF23HgAPDToG+2qH2PqBrRp8ZZ+5LInecHX/WIzHEM3DCr5pfasjmX4lFXNyvMYANuFTs2lvLJZAylsUu4tzFmp45izdTKQSqVEzu/1y5ihWEsiySeCn/kKaKPRHmPdr0a4XEXGlDw/vBhLayjKq2CUtIdd/8zUyN8cp8Vz14uBBnj3kxK/qwV87ZwbU/YqwmU3JARFCAZheNnlLO3SjCbXTC0vLuMksdPtHphPdDgGoOPhxtyv/N6eg89lFUZnnOTSMYKpWzBTJ7jBTJ0IK/lhjuW5xzjlxRraueKvx3n/arnXMdImGVhAaSzaV4srdg62mXn3YpTtqe8FHPsyVRY1gDTltVLHACxWJG9PlV2ONXfgsVuQeOcJG3hH6pwz0ziezganchZbJf6Fg3UFVK+i65Xd0VyQgkFamMuxeLHBTFBuJ1vVHviKpH4gha5X13AmXA2M1N97CM1di9XqkTeQZquarWnuJ1bq1mncSHKNLj3A0rRDqpUXwDfOdi5EzCwdA3ANOHIj6lY19401AEhyUksZ+2KVOAYiMQrs88wJJ1OzMHkujnCdsXg6e+4xUQyX3ZXBgi6gXVJ2kTJliRgzUjwdsbk6ID7XhtQB47qYN/dJqMum+0WkPbD1oM/gUJss++8ps6NxdXkusHIlc2AWY09DP+SaZBmPZ8pQ5EQ2SY4Ix+exxyyOxpRZUhpqrtda/3gYlPpgDFfusMpawzWXgFnG0Bdpk2y5yOxnjte1sYfV+EsV/hNxxVMwjlHqgHpSRAsfV5w+4nAWeW7M1HnPWN9CE5XfqRlzfmkT2yeHpOYtOpiExdjtxSvaGESnj47RF+6VOgDARCkOOUMrbH+TNf8BDDQ8kSyzxJl7NdZIFqOhb9G0PW1zFAaWKA5idfqu1xjo6sXT1Zi6Klun3QPMHiyjkpsyOlHGQ1kl18aLcakBnqDMWPAzGANf7gutyI3UeuPYEfU5XHCxUroS+b6kwOw2MbySJDGLoCT3VSbX2BI44SaaZlCuY1WEeN6GXUOsonEIgI9R6saYOlb+aZ9gmRdsUZdK3DY9S+t6FZHF3ot/Ss/B2TOzprTUCsna36r4KHZJSR94FjSLmV/8rNhAEiYXyEqdVTpk3uTs6NJQrGFKNgL6hCtevxxegFDihc2OtscdKEAcrt2mZ9zhCldRoWsijojiIgqL4EcZ4pKVXDbuGvW+xBT+3Raa8QTqzO5RGaSHcCWWlzmkOLC7eBqV12kcDzX2XyfiZGZXs5D5BtlYBEDFzU/LsX1M5qsI44+nyHkML42XtGeqMRZl7AOizAWlVkqXcGhF+KyN52nSb63naHwe9UcZi2Pjwv4+Jy85/yw7WmHqgMP7W98rdUYy6OSCh5bOZaVOAKdLizMXz9WbT4s06NG0OdaLJ7lH9/K9FXRxOwBzo9QBeUJ5izOzdWrQ9OleGAyyS3Fr+mSZ/ubMT44DkgWKraMGOauMt5PiNtbAN09gAihXM6lIwcqZzyvgW5tIHAS/JQCW0h5TbJNbEtAB8RJ/x+Dr3rIFh/QFAbBl6Q5lqgEaPPgf/14+szWe11EAACAASURBVDXISKxBlOPYmI3tkmLH48AqdTroe5HA1wrPE283iZ7GGX9+JwBu9ygSU6yLO52g3j9inMiim8fCDMy26KKrs6TQcYkgVmLsmBEjoCXFrsbSsZS40uNW3HHM0tUWasvWFQu2ZsxYsZOoyWwwMxuVlV2bGbzGsmBcNI6UOMrhJLaEUA1XbIZsyfybTOFahmdk/23cY/2ZeMairEEl+z+gIW9RGYPJwuOEZQdpw+lx451fQcdZDKrhiuMlkj1x0ehwKBunmxEkeAP0s2zTcTy31rQ22XnUYnCz6Jt2wDH4YaVphzKWe4wRtYajiCFdjmES75U6Eqa7GXwZaMLfrNRpILYKHw+ewz78sUQJ/1GloGaPpbNK3Rhb1wI2s0bcihJTx3vwbTFLrJ3cn3YBLIp+YOVWQFzgVBf55NhGp36b6Qv+W7NnojQP0aVErKZ1nY2A71hsHTODUs28jOXxlLoFuUhyDbICgCvXduPrPECV9nmviMfZhcj+3rGqT9py4ZW2Z4tas7HC1Il1za7acC5d++5Q9rjqJ0fptgaEN34sG5r7zACwZS9sULhZpNLetMiGoswhvje78GSjUdisEmfs4qX6oTJemkaPS20s6va37QDMO6Cd+yzdBlq8uDoyAmxsH2OszuacKhejHMvsNscYepjCLE4NU5jVqSl08ty4fzwWL+BvJR5NKfq5CPQYAxSMES5WnY1jaaOMJ26fZ1QLdt/ZYGzb0J5wcr453TZ+5WN4rLTQSRI1z5Fgb5TBPBt2s9t9pdloFFZOvtNMpt1pww+Jao9QvO384fMk75Pz+xRb57H9tv/smn0ke3iv1EXhDKGwLUlmETjOI/ydA9tZ8WCFztLeNWtJNHpRHnQGXxiyQFaCLJg37YDdPIKKgGqLEFvnxTbMoQdKUuz2OCFLha1EAV8BlgEtllhBmDq2dtl1pGuNaeDM1lZeesO5c795fcnxLXcRtS2bXaSlO+f7o8F3gM6s5MzPhvpJXK/MPlirkZNBxqQA4HkXNhOfH9gk+pBSJ5954CvfKQDeK2WXF02bfZjZuSFZxHbR9dxkK0fhZfGYOk/y6Crjow793nV1Wze320e3sWJ/EG5HnkOlUmfZOr0YZeOG2cuau9DiCktPfcK4Nog60cYMWOt6lTHiKXVsWBbsgr6G/BNjURT7aeS1WfSYWBSKbjjGx5StOY+MT1agWdEfwxTvu1xrlIxFOyZaAPNb5HqBMR4sYn3Ny+AZi+HYi7TK+H2U580xyr/L2DGueHUsawqdHGPDfxhTxkgG8hRx2wRbRbHLrvWMrTKWbcKMnIPX6lqsYdMMat7IZ/k8bVIiGbMOSbV/4axDIwb1yXxbMIfu9Q7e0b9AwlT3FlussFDgq4/TyhxbBDLB2Br0ZAx4eZDyomR/H5SVPrhg2fVac6N5il2aUIMaNLzQiKIrso0QzPfrsZTcH3IcULpdvUw1BitWCi1rYyewtZqaNgBXKrY5b1HUC4pbKjH4sqLtTSS2qnnfQd2Osp9Kti6zDjxexiw+kQQQLVBsLG7FcQ2qxdoDX/mdYuu6kVgtG/uigVbYulp9KQvAnsLLJYbGEgA4gYY/9+QoxQ4T3V9A6b6O7sa2tYtKnkOi6Fo2wRozNSXEjhMeL9JEXphs33AcqzWWuD9281vg/DS08SGCoegxDMX4gBor3L9iOHNiTbivYABJlQHbd+wJsIlXhzDF9i9jda0va5Ku1QwJH3btoN2WqV8ypkg4h+cO9zI4szt6pr7nsB4+3rJ1lqU7lkkS2c07hMLKMa60FntrhQ1KdtkfVOr2OJlvVZ1Wue+Mrdq1zko891n2EOjxzZ60sVhD731uXlPgimdYKWWwpjinPWGJFeX+U5iijSOLmyz/3Ct1k8nkPwfwmwAeAcB+v//+l/J4FlZiGizj5NkqN2M4rmSfPODlAXPowXt/832JqMkZd6Y4mW+xk8HB1jRPKsC4GaGYhWAF9K5yGbKvhjSYs6JbxkPx5LGKrhcHJ721RTkJLYPhKXS2f2rStAOm8w5bALt+AJx4hxNS6I4BX7m29IzcJ/fHFFsDSJp96Q4o/00TYkws2Az9gG4TgD0BRAuktHlPaQVQVCTvo4LrAa+nsMxvE6Nr68KFsanbzFGUShmj8cNWr1VstrR419g6Ubqthe4BsFznUB9LXNrQt3GPzwFom7Bw85wq3Em3OI0WNd+HGIzrNE5KF5Ftv12QvLlREzVeKkZJ7fdNO2A272K7W+Cc4n84pCN1FkpDMTJUJ/Fc+rqioC2Kzzwlv3ShaSMv3beDKdxOr5+twclJFyyeexZAatvtZuoouz6mWI+M7ZvQljyfrJLLc4iVURsKNJhxws+bx3zNAEgxdgBUOQ6gxBGY43qjqIwqdftoKJaYy9gKIK3E4flM1ZMMbF5ZVonXEO4fxmoWD1dUE515k5+bTmishkPEft/1A4AZUkasq9RJ/5TrsyejSt1kMvkcAN8H4KMAvnW/3/9E/Px1ALDf799z8AovQiaTybcB+Pv7/f7H5O/JZPIG+fvFHs8ig6eD3odU2BaWmuVnwUJ/ZuLpENwuhWKnGMF8vKdQAEZZaacoikiyWKVONvyebzGdd5jNtyr2Ji8+Q3oV5aM2cbwFyVfGpkqZ82Kraudw4yCc/knPsSF36rxLCzX3YXjNMQvTeaz4f8BFEq6T2Sl+1rnfyvgeLy6Tz6naUVkAZvNOKR5BtjnLiraKEil3GIjHi9XYO7E0zljJyQkDAa/ce97+i58vs3M8dljhlT4sF++KInYgE4xZQW9h9uYhBzkXyl07kIWNqBBnhdkzjuR5S9tqNbY8A1F+U1PovPaM6Hrub/izFgOGyEIpXNmcakPRdTMij5V5h5N4DlZieB7rpJqMsx6ueJ4Q+T6LZJnXjK+s3Hi4xLhSc2uLiAcAgFJaLa5YA5H7YsyNNqQ2dqlfZB6wkRiO1dhok0Fq9+99JQajjPncpu1Re6IGJSVKwqEWxb7bhCloB5zOt5jJWIkHsieEMQVAwhVpC68YqX0H+sdbk8cee3EsnZ+/T/O6ci5OZBr6FkM7aAwGNK7MO5wSi1nTBdL5R78FXrvf738fAEwmk3dOJpPXAvhXEfjCh5PJ5NMAvGG/3/+9A+d5Unlmv99/Lf39swC+FkBNSbvr8YUwC2cDUkV4cfDAQs5TU0LEOq9Nau+h8XlF2LWIBMADMDcLdDoxsTXGipxV/PWywPDfNsaQv6spudwG29ZwLn0NOd72c60fxkBYJut0vkXTNxh6f1KMAW/NRcL3qxm5MglEhJkXZiC1i8Tr39IIyPdOIGOtaucYdV4C79o2WTJWBHinsy24Bl24v/xsypi5bCx5wMtt9JgUb3EaWxwzm3FESRNSKj3ljhc6AIVRwMenuWRYzI6UOut+Hhvvx8wFEcYVj8HS/aP3S7X90bQNZtGwGdohxKMyrows0C47ZYxVMRJXMYvVY+n4+JrhbMVz61v8seyVhym233R/xn6mZ7w8X42MCR2fxef12f9Wve+QjQF+bvY3hwxr7hceJ7USQYKTY9uhiYKS7sNgj1UIWdz1pxloTdD9wfNG3Ss9c0sQHOqfgv2XPhlRuPmexmTMYMwxjZ4Cbc4TcXc63x68L+CwUveb8ma/33/dZDL5JQB/hhm6yWTyvZPJ5B/t9/v3HrzaHWQymXyq8/FzAD73pTieZfvL/xDve80fxcuf/U/x6Ok/FieQrqNlF3BPUfEUvZqrRADYfsZSs7LkvgRYRFlhVgEoB4h24fUqy2c6y+wBT3xplwAL94l3Xx7gei4AOccYU8fnrQGvfDYGwEDs76bB0LTADEVFeDXxHEXu5t0/iRfe/lcwvP8DaH7Pq/Hw2Tfj/OkvqvRBq/rS9lcNeD3hcaImdBPZqrZBUwBBXIxTyRwftPMxWzVWGKRtJljTDmF7OPO07f0PUV1R1zywmKXrm8XXLkzeb2vnGwNfOwf5/pomKjxNnEttqBnp9Vf6DfVR9+4fT5//+mv+OD7m2Tfhqac/Dw36qouIX+14H8OdcO9BOawZjK25ljCsRRvkuKbD0LRo2gHbzTSzCrHdvEhzdqvFlfpC3SSDeQxTbNsPuZ6ZwamdQ6TWx9IPtf6RflaYAhS4UjM67Fi9efdPpvfve80fxaNn/xwePv35xFCFq3Jsaq19x3g15B6KcdLk++ZwhDzu6VDCFP29PzeAElesEe2FUNjnrBVevZbUDPB0fcKQjF55LNk+qYXbHCNe/zaNo0THMZPq840YBjKP1u/+7/D8298FAJ/mX3tcHpq/U6yayH6//8rJZPIWAN9x4Fx3lUcIShnL8y/h8UqG9/0OPvTMNwIAHjz9Ba5Cp453QELEU/S8Yw/RqPw77x6SVdr0hbJSm1g21gbI9HV4X1o7WwMs9fv04zeOsYTH4hbG+lDuOVuivfq8PG6cGrfHA8D1u38Kzz/zDdivQnT88L7fwXPPfAMAJMWOFUsb72Hvy3P7WEU0L7y+dZoUkqbunqVYatMuDeQD2qOO9dyn/L2n2GnxY1hqUhsDVuoKnQZ97574t57ybV0pfRPfzPx7atBj9e6/jatn3pbb8b4P4P975luwwwkun379S4Ir4Rg7n+rjpXYdT6wh1JxFA6Cy+DRW8TcGkjVupB2BgS2ZFduumoFXE27/oTFkzx3ueXDHDgs/Q2W8OLc2prAKtqR7eN/v4MPP/GUAwMXTX6jujcMZDrXBa/cxuJLuuTGM0AG8TIotUMUSfTqtOHksPrvm7XgdU1YPie/tGe8T7jfdDp85HMNt5wcKV+y9hUNCf9y8+yfVWuTJZL/fV78EgMlk8mf2+/0PxPf/CYAf2e/3L5hjvmS/3/+4e4InlMlk8gYA37bf738vffYQIb7vZfv9/vkXc7z5be6E2RSzP/KHcPaln4+Lr/oPMFld44Nf8KZwHPbYx0yVizf+CVy88U9g+PBH8btv+AvFOR+86ctw/mWvR/dbH8KH/2TwCMtvAeDiL/5HOP+ifwO3//c/wke+4i+lz+WYB1//Jsw/91/H9j3/Fx6/+dni/A+/5S9g/pl/GJtf+FU8/7bvUt/tMcHDd70N09f9AWx+7n/FC9/8PcXvX/Z934jTT3otup/6Obzwnf81JtinNgLAq37oWZx+wsfg6kf+Rzz+nh+N32X5uB/7NuDlL8cLP/i38cIP/mS6b3l95U9/H06WC1x993+Dmx/9H4r2v/LnfxgAcP0d/yXWf+fn1bWxWOBVPxPyW57/pu/G5n/639Tvm6ce4qkf/xsAgMdv/Q5sf/FX828BtB//Krzyh78NAPDhN78Tt+/5NdX209//iXjV9wcg/d1nvhG3v/E+1XfT130yXv6urwMAfOjLvxbXP/azQKdLLQBA84kfi9mn/SsYPvK8uv/F5/wRvOwdXwkA+ODrvwL79Ub13fILPwsve8ufwoAWv/PZbyzOe/aln4/zr3oau9UaH/qCryi+P3/jF+P8jV+M7Ycf4yNv+HPquwn2uHjTv4ezL/sCdL/1ITz3J/+z4vsHf/FPY/lF/2Yx9kRe9vXPYPm5n4HuPb+Oj7z5napvJwBe8S1fjeVn/iGsfuEf4B+/7W/CIsijd70Vs9d9MlY/94v46DeXeUpPfd9/gZNP+n1Y/9TfxdV3/q3i/l7+Q9+G9hNejZsf+Wlcfc9/mz6X5//ox/46mpc/ws0P/gRufvAn1G8B4Kmf/gGcLBe4/u53Y/2jP11c/xU//24AwNV3/FdY/52/p8b+ZDHHq3/mewEAH/2m78U6jj055uSph3jVj/9VAMBzb/0ubH7xHwDIY7P9+I/B5n/5ZQzv+53iuvdyL8fK5PIC09d9spp7zVOX+Ngf/04AwIff+tfS2BNpP/5VeMUPf3v4/s3vxPY9v66+P/39r8Gj7/8mAMBHnvkG3P7Ge/X3r/sDePiutwMAnvvyt2D47Q+o72ef8Tq87Fu/BgDwj7/kz2L4yGP9/ed8Jh6846vD96//j7Ffd+r+z77ws/DwLX8aAPCBz/5Tua3x9eJLPxePvupLsVut8Vtf8OfVufcAHrzx38bZG78Ew4c/ig++4WvUegIA52/697H8sn8L/W99IOEeX/8Q7l1+/Vdi8bmfie17fg3PvflbzfUnuPyWr8HsMz8V3S/8Ch6/7a+o7yfY49G73orp6/5lrH/uF/D4m79XfQcAL/++v4TpJ/1LuPmpn8fj7/xBdW8A8IofeifaT3g1rn/kZ/DC9/xI0b5X/NhfxQc+/Q0KW/b7vYmxOiL7db/f/8BkMvkShH79WavQRTmaEbuDPA/DCjp/P/Hxk8nkGQDPFF90W+xwgh4tVlhiH7cQKw7DKRosMME1djgJ56SHtMNJsjDsw5lgj5NcLKH4Tq4pFgX/Xk3yeIUJ9rQwBTnDCnNc4QRrrBzrYI4NplhhwC1OsIMdGWxRZIUtv7/GORosscYcPSgtO8oaS0xidfOd23/BJLnFafyeFYeJikGS/hXZYaLiK+SedN8ESzC3jZQ+DFhind5Lmdg9JphgjwYDZujQownndBQ6ABje/wHsP+0PFgrtgBz0PeAEezlPlB4t1rFe2Q4nRmnax/sfMKFnwMecYIcGA6a41QpJfN+ixxQdJrR3MUuL25jRvU3jMD+9PebocIErtLjBYyeGY4YNptjiFrfUa/LrSRr7PVp6drGP9sDNcIZmWGJzu8Cwy2NDbKvr4RxTLHEbf2/BrzFzx37PYseGnks7M3fCe4kVbNCreTrBHi0GXOAKAPCC+R6Y4AQDhvfrxfBe7uWusn8cxhhj3wRNwg3hP1kmyAk5+ziay7lTZ7ImEVcaDDjBgJ1ZV05xiyVW8Tw7IOFmPreUbzrBHsCgcGWK2zR3PuTcxxS3mGKLXcSVhBnxe7m7LU5jv0wgnNR+P8H6doGhu8CueyHhCvM1Yc1ZYh9/b4mMY6SPvTO2Jp9EXLHfiwfsNK659rdnuMEUV+ixwXXCldwHU3RHYctBpk4dPJn8YQCfjtzPvwngtQB+6aXOhI0xcr/Mmqj32ZMeb36bOuHkEz8OD//f/71wM4zFJR0bO5F+d8D94rkYrJvI0tSe23Qs4SJcq+6OGIvRGNAmV4z0jw2mPaYqtyduP3uBvEe4BT2Xci0mRdrsZcX9P6/5QvTvKydT84kfi1e8938254gxG05sjdte5z7Hjq1Jq9p+XGxmPq8/lsbO5cUFulnPNE440SC8+nE6tvwDx/AdI9YFdSi42rbd+9zrC3tNafM/fM0Xo3/fB4tjJr/n4/HgN/6+67os3h+I8fTuZ8ydy+9r2MLzhHd2qCX7eOLFp3nX9pI+tsOsGCvqPg02HCoXoa7vlO04tr8b1T/lOPHmzbE4+v7XfF4VW1793p+vh6EMZf94yV2HMKU4h9P2Q7/3QgYO9c8Yrvg1GXVprG03TeOEkzPGMAXIsXwSQy5trbWT76uWpFc7Rw07uE9sX/F1vfXIrkVPxNSx7Pf7XwXwq/J3VPImAH5vzIz9lZcqYWK/3//KZDKxDOAjAD/3UhzvynKBxTd9HbabqVMqIkhtkDRtjFcYWcC9+J1agL8Vb4GSgSElEvJm2CVAeXFp3mS0waTymhbtoSn6p5bZBJT9xcKT0X7PSqFbR0mCemOQvu0XES4fMUXeLBzIfcmTNWQ+69phTz37Z/GhZ75RxTFMlnOcPfuW3BZS5ljZ9UTFIMXDygX7+Mxoq7TW5FC2YLC0u4MgxwocgKJ0gge8281Ml1px6untYgblbcyglDI7W8yARtgzX5EZi7nh937/lYZRqeiU48a2VxjaVz/7lfjtZ96p416WCzTveAdW10sXUxhP5DN5FVyxcZsS58P9YPHEiwOS71i4TdIXYVtAuxj7GbMepvC84vvoUeLKtpui20w1pnA/xf44BlfUfZlsTO7nWn02NBpXuJ/D16Xy680/Hhcck8yFg1/27J/Hh5/5yy62KCyuxDP2VNg290lTLX1xKHuyZgjLZ1Y8Zd1TdO6CK+HvodgikhX/bjPNmMKlU4ASU4BQoD+WTsm7ejSYNjqD/9D84edh56Q9R6nIlp+P4batkrDFDK989qvxgWe+eTSm7k5KnRVPyZtMJp8q9exeAvlRU2fu8xDq5sn1XgvgU+n70ePH5OQTPxaLb3orJv/Ol6HbzEIxSV58ouzi4LjFFCftgMGk7iugIMVDxHvI+bveHUD8fU8AI4qKlFO0QOyJDCPAzwYKg3jwF+qo0KX+2czK8gbhxtICHfYSDP0FZFC2iqD0p8gWebGzANy0Q7ZUGx+o2M4T4JXKcLxAc1+H9vexZEuTCnY8evqPAQA+8va/jv79H0Tze16NB89+DWZP/3E1yQEohRfwmd7SapSm+ONC2sPHpHMRKNgFOLct3MMUpfJjgcUaCFYEYBoMyUUu9aTke1bo1FySwr22yGZq5ARhu6VT7No9NrHvZvMthqYdXVw85aU2f/TClfvOLjx+39bry0lW66uf/mzscYIPvv170L//g5h8wsehecc7sPuip7G7nrqYcktKS23cx5vO3QWr2PmLizwXvlevn5gbkFfBl0NMhry3ikz4XCdYsVLHCt12M8NuM83jRMlpxhVkHB7auvHkGZtyvOA2K0UAYUvjjZe+wBXuH69IPTMuQZkLRqPIw6c/HwDw3Nv/WsqsP3v2LVhGbLHKnIctFitTPzc62WMMV1L7q+NeG83W8OdnzYaGzCk7jjxWimvEhrnUQ5KrknLHCh2PlTFMARKu3PYNhliqp8SVrHR5pYHS/UoyIq1Bth89zPD65ZBBkBLiolw+/XoMOMGH3/43qnG7d3K//rMQ2iHitQCe5x0i4neft9/vP++Y42sy/fRP2T/8pf8+gcvmehkUlo2vsMApnAhot1H4O7423iQZXxyslWbPM8UWS6wwRYcl1qqUbc0iYoAJfztuVZpgoi7Kfovrm0VepK/nfjHSll7n/PcdxplY36bmFVCmwnv9wu9F4Q195QMLPxW7R6C/kbrpQ8o4HmUbYpsAJCaqbUNJmmmjFc4xVxuD9JgSIm0TqbkPLOjWFnLbR7LB+jUu0tZEayyxGpal8r+Z6PFS25lAxs0cwPkeJ+crLM9XmM63WDYr1U6WWvkTnjten/GCXGMWeGHyFki5tmz7Jv1yhQtc4QLXNxdYXS/zImSNbAdTrHIHyML9ZJhSzHMTHpCVlIAnMl8EY8YwRV6r1xqZXzJWVtdL7K6X5Tgp+sj0F4CjdzcYqdMJaK+L18fT4u5z/1gviX4qjdrJgAsDezvl1EIXDuFKrZakYGLoxorLmhQOz7PhhT+MGQoeBvM8sufhvlnFObTGIr2XsbK6XgSFzhsrdi1KfQO9dd152EGJccUrCM7jNz0nUrIBqHIsMgb0GuOzuTyePExj5p+x9QoX6V5+c/IHf3m/33+6fZYviqn7pyH7/f7bD3z37c5nd7tGfB2im8hdhACjsAirELaIYZbJo8Rr4i2+LAy+YkG2NACyqyQrLjKw7PlLkM3uR1YmpdI7W5TDEIBFKXTXyAs0i0yiHgTAI2GNtn+jVY62xa7tsYsW+VhcY7pPNKmlDfoEJp5iZ39n924d0KR+aJ3nZBW6IQKvYnmLAtBtYjCHvi3ihEI31Fm58Fp3bzCA6/a1YGuaz8eLFG+i06iRkv+aIu+LHIBnm9wmImmsbGbA9URvXTe2MwHvhNJOsGun6KLiyyw19xXXg1LPx8wdb/cWaVUGWs1U2gWpBsC860wfwfiDX/423OIU+Jt/Kyh016c+pvAcaU/TuMfcT9Bx5wEtSDzn3XFrFiYAqYRFdnRJ2/XYsPND2uspb+xyzExmn8ahSJdYl0nAlKOVOtm+7LTspEOszQFsGcNtraxoo9oqdaK8tabfxCvTQtfD80Ik+iNxRcZMX3Ere+E/qs2OQmcVFC9kRZ5zea7w+wXWZnOusp/C5oLbVIxaFJqGrif4msaKYIrdFtPC3zx+fx6/a0+xa0NN12k8t8zecl3wVaTa/BFcsAqc7UtP0fUwhe+nVvTfyj/3St0/bdn1TR1cGFCAvInzHJVcVpKGF+vS8smDvAyGrSVrMKtiFZdjmcAAMHlSMuC6xS77JvSH9I/8Y2mRFbq0dZDzPVBOQFac20ncSL3sX3FNUWcUoMUKr2bsysB7uz1c7i9RGOo11rQ13WTgdZnebAzIb5q+KVz13tjg761CN8bSilrmMXXMznnMrz1PF+FXztNHQG54H09xEclckjHCc8pbuBl8U3+dYpjHgqbURzYGrKjh5iguAIPvoOajVeiOUXS5X2QfU1Fy1xgw/PbvYsBpXITbcgEKN68ZShr3uw2qil288YOMrjUWFb5wZXu0kKLVrODOsMUCKzW+WDx2ThYfYRQYX7KJEOZUij+1/WP3rrb/5ijxWN+YfgU0tswn6QPBFr0ri3atlWprH+fMumosylyx23yFnSFCP7CCx8+IWboU230IV+Ytdv0Qjx/cenE1ZS68lgpdLRxDQjlYadfnzO5p4a7lPfdhZrmXWKsx0pYKlowVYbvtGuR5ANr4mRiLD+Pv2lmBK2wUyfPgZ3NMvDT3p/SlVdw8XJk6WGuV2gZLpfjV5F6piyJMVFiI4CssHojMkWj+DA5Dint40UydGUQ2S4vBNzh9Vm7ChFwjg4ihlUmRCce2heIz2MWJJ1X4ce6fHg5bR98dpdQBQFaCPMXOil6sM9ugHWNrWKtzGhdiFp5UjaM4WBn6NrpGCHhrjAOCtRjGiV64+Zr5s55O4St0HDuo7gs6bpKt6in9VvomWNc8jvJ4mWKqwHcb/26p30NfNOVY8UDYKnW8KXoE5J3MAbNI1eaOVVwAKOWlpvzXFLqs1PhuaQu+bCCkexDlVtjtmqGY2MqgdMhemowp6d6bcpx4fwvDmRYnwpTUP4bFnKFTDkP2AmRW1Ko5meUX1pvZf1GE7DzajSn/ospeIgAAIABJREFUHn4IrngGY260fgUdJ8aDMRp14lbNTdmbPumik3CtlF7BFGZwRVmR5yGs5RiuiKE4iity2/0EcJQOL6bLa5dllWxIhsVMjxTI58uGouAKK3eMZ1vMMEVH4yrgSvhsoY7dCangrUG1cCAZM+f0dz/xjT5HsWPxMrNrzHmTnngZ3sJue1bs0nWgt+fcYooZOqyxKNhdK/dKHcnQtznwsmZVM5CkAeRZfXERMaDJg4YXTDuI0kJMA2jomxDoG63H7CoRN2O2rC1jo90iGWz5fbgvsZJ69ft0Lz2BirdIARl0LfAyANeUOkBPRLGyNtFlMu+cH4T+1TR6TxZnmDRLrHCOq4J1sBlp7Gbs4iK1TeelxbGIeRFrelJajbI4gf4uwFcrpLXAZmaLmEWoWdW86LICD7DrtTMgnBUZPs8WeS9k+dUKS+1SkUXILtQMwJ5yI89aJI2j2L9o0WCt+mAA78GrlTk7dwBrFA1qnNcUOlmwl1HhrSl1QxxHtv+LhUjGBSsZ/D71S1ikrbHoGTO5PVrpGhNZnFQSjxlfMm8WI21nD4AodAAUpqTnEJXqIraLMWXMoGaFjj8vGgffYJRxlvAlKnZOGRTPMyKYm+fLumDrpO0D2sTgAsACqzSHPMXKirqfGq6wbBAwkvYptutNbovP+Og5UU+WCc90m9YUqwB5BvUFrgrjIIyboMIBYXx0mGGKrRonA9rQps2sHCNjxqIN6Zjn46yxmNuW12TPuxGeDRkAfRN31Ng6rG4PVtoYb+24EfzOyrLUJGyoz+7dr0dLdgPAdwMAjqUHDcBGsQN8NokfOKAHkcr4iRNTJmjtXKy0WFcJK3WixAmTIOU7GvRJqQmLUpeGpmUd3P6xfcSg6yl2fK4xpQ7Qip1Z5LhPQsyUdq0x+C6StbgGu2DDbQSXGbMtoa8WsBbXoYVStctajeyS7gGbBSnCY6PmXmPQLWl8P+DX2+rNAoyArwCxVRJWWKR76DDDCks3RjG56e14scqdtajP6e90TNlPhyzqdBsmqNlKdtF3Sjlmhc7OK6u0aaVuiitcxD7bp+KoRV9YTKmGJ5TGosRMSYyttKPsIz9uS/pl6Nu4p6tmQWW8i6HI/VGGjcjCPE04ImOGWTsRV6nxxkqN0WRs4c89Y7Gm1FmDsc+4wmNk6BvHCBgKzJU5Y5U6YSc5rnEb+1OMRctw8bXDK7H/HqZIWwVjbaydkZqhaNuXjRztJmRht6stadJiUPPnIqYN2fVJ+mkVFRgZSysskiKT+k9iCS2p4GGKVeqEpbuGMhZtv+g12XgATPbxeD/nPuTYbou30kfsgs0eNTGeZ1hjWXhganKv1AGQqs272kJkAVjeFxMsK3aS5VgLWs2n0YyKFVuwVcdfsRtO4hfW7uLOrhFR6DIIa6tOjpcNtxv0Zf09b5Gy7lfPorZKHb+CjhXQBbSlRYucLHBA3aoWN8nStRazsmJditvIem7ju0OiwJf7x1tcfCM53bcXDynf8WtQQHL2JisnOe5N18jKyl2TfidAs4ggs8C66CeB+lkE4w5TLLHCOmZ5+oodfIWOQdiCr4gA8QbAZuICqQ4sLhMBGIBFeRGmWxTi3OelcswhDWOxU7IgZdYy9NHyMz4Fu915ZBgwjinM0PFccrwAADD0gzvm7Zy3Sq+NNRTmL5fxYFd0p4zFpQlbkGtKSIevxOnnlpU+h3U4hL1zlHLIWOydY5VCJ/80W1cUOk6LfcbaPF9WitGVdgdDMbMtwUBeQrwrPI8HaA9AIf2kHB/M9tYMZGgSwcMVaZc1FH2DMeOkjcUWA8Iy38z+B1xZKwWFEwCCgrfAEktce5gClAxdLbQDKA1FeebRWFRGHymQnJRVc8Pm94MxinrTl1vTH+sCVzjchV2vbCh68dKe3Ct1VpjetgPEA147uaLskrKhZxo/8NoEs1KzDLJC1yUALuOh8sC0gJuzISXmKgNL8OFvU7xUgx5NGzfUGnOV1NwhzNwpJgIl8AIadJVyFxe5VMOrRLKSaQhuAFFUxKoWoBaLWvpJ0k6Y8rbJEipjTblJTBBzrX3mtjnrkNvhtS28ZmequCqElbQB7Zk1sModl8dZp39iVXvKr7iTushVrLDEEis8j4f6/plZsArd8/DHDcdgGmNhMOCrGZAyqBpADjCXS1RiMJmNZTc0L9bcH6zUsUXdYYYrYvI+7lu/Er81fAI2722fzFB0cMUKhxxYGWOWpW/EMOJzcHwVh3X4C3uuV1jiSzAeWWRmNcT4xobofzUPgDefxoxF71jAwfLA1o0Z48L8Z6zd0ny5Th6A0Dc6e1Hc8jN0kDhUd8waXEkhHV4fyWfFuLFzZVDPtCbM0vFcsJma4bL5aP5b+olxJSjAZT9lpm5L/RSueo2LdE32FhTjwxqJHsNrFbyEKz6rmce3dbk2qqzMyQhZEy5nvSlaoRMF11PqppFQGdAkb4hNpqhf914AIE+emrUoCw1g3K5RLFt34IGLjLmPVOZTkm36XXjNE4jZOna/suuVF7FsDWgXbbjKNsU2VC1q21cizKyxMIvH5wH0xLMgbQGY3LAcY8Qxhsw2cNyLuACWtC8qx3T0aRJt07mOEQW+Xh9J2xyLummz2yO3ow7AFnw5eNsWWBZmThZcWWTlWgLazMowo7mILlggjA9xwXSYYY1FUnQ8t6Sr+HvuEukbsaglYcIu7CSaLcquEhm/3jZTVnnRfZmt6pwpvSamV7Mx0v+cDbzFNI0r3Q+Tcr54LIuntMh4J7bOU8S4X7TSVZYQ6RXLoA0jGe9sDHlxdXJ+wRWr0IVbLz0AzIKLoRiw8rTsH/vsrdtVXtkYsNhilTr2AABGIeLEFD3oJL6Lld1cRS1jCzPkef/nJvXmCks1PqyxWBWLk3ZOKOOAz53FMv287mjWulfzwpvfNpTDJkswrmRMuU4Go3W/yjolddkWZp4BgrHw1+ixsA5OkLAegnRYaVSzMHsqhI1X3Npis652mj0ibEDbuRWUujCXOszcJKUxuVfqrHhMnXyugpgPnaeJbFLr0LODGqx5kpEr1qPgjTBTw+DLLrV0PuhaWiwcFyETfYopZpDYhji52h63qX0oJxd/x8HfIse4XwWcvbhFpQSOK845kzG7ABaxnKVYi2wdNljGPpphjVVS7GSy16xcN73dGx8eM1Pcs2aNxuh/aaMFXxtP6ZUc4JiNzO5tU//IYnUeLcnZEBW5pnSTiOu1VOgm5fiw7lexqqVf5D27XuM5dn2jXITSX6Fry9gXeWXgTfFjKXyhT+eRfpMFmxekHA+0VvMLCPNkHYE490XI5Hvvl7wVq/0C+Naf9ueKjPWakVhh6jyG2gP8BvWM7TG2gYO98xwqC9ly7UNPrCcAAC1OcdweE9bhiY25rSl0dt5Zt6vCGM3WSayhVnjy+LBxqFap4x1XRKETxuaQG20UVzxD2CoppNh56w0zzLltfTwdt1PHgrExJbUIQ3uzKsO4InjCXhJR6mbdFkPbRFwJ1xZX45IStQpFxq7RtbAOXm94TbFxd0YsYZIuy8lX8hoNLI5v5X7P88g3FBXOKqVODMUZrnAOzg4+JPdKHYt1GTEw2IljAcTpyZ2h8L1JPMbUqXT2KDpbR7ty2VXC9YDkf5ZwTXEVsPUVGpKjybbp3IX7qsYwtOZVxMbE1Jg6IIOvx44mhqNJsVPTdFhejIT21sG61wlgtFKnA9052+tYN3khNaWVpGn7WJG8ZOk4gQbI7i4/HkwCcn2mrkPmA9j9KsxUVmKCBXku+yE83iTdedHcYnbeAU2II7vCRYrBcy1JT/H3XLCh4dmiHgFfVsTkmXF2skiOcYxWNSSMQZfUYAU6g6+OLyzjDDNbxYwDW9QtBgwfeR67XTeOKbafjjUaK2KNAe4bKeDKsnMCv3mMibEofWIL7HLZBSucXS/HS2mGKSmIJ+2AnRcTJ33micfkjzF1bCx6/W363GYZ8zjhOLPsVsweAGmrsP+B1V6mNrNH4ShsORSYX1l/MrNYVjLwDEaLPcxeu0x8bNsM20QfyG8zrgRFZsHKb3eF5c0Okx4Adtic3QJnObxD5llQ7LrUjtRWHhs2o94ycRzTPYdWBnsd2nTIPZ37O8ZOt/0Bti5nD1tDURRdwVn2AEi264AmekPWaR0+5h7vlToWz01iGagXAbiAdRtpy+lJhNm6GQGwTRvn88ugCct8B5+pC44lBt/gKoEflGwn0gZauWOreCymrga+BWs3qY7ebFFr8GVLkZW6LoHvNMWIiWJXSyX3sqPuJC0g2xtpl3EGVfkO8OPGbNZaVsBLpi60L7Mn8ntmH4TVFJC5eLzB6QtIc+C0BdrhFv2jK6yxjMc9TOArAJwMmUNMnVXq5PWcvkusVpmpJm23rMMxBUJz+3Pf6/ixbBxZRsayVaFvZ6QAOW7ommJXC1U4Qph19IRxRSWVsMJrFBdm6XKsZu4Pr+3qnpBd9NYlJwyEnE8W/xSrC5S44GEuh8LwZ8cydXx88S+4YP0klJxAkN3x7AG4UkpdZv+vUvD/FXKWNZ97VNoegNk1w+uT+Jq2P6NnyeyTCGMK4438hhOxvDJQos6LYidYU8ZjBuXuHFdYDiucPd4BNxBOAfMOaPprDJehiPfzsW+nabzZcAYcxhWPLGBcof6zitLY81BKXMVbpA30El+kCkOuxrDOLulhQN80if1fJWPgPqbuzpLiTI6xmvmzWmLAiFimxS5KQI6nU/v8VQBYlAAGzNrC3qNJrqNwnszi8ILPsS/JSmsHhP0TKcDU6yuPZQN0soR9vTP4Ilqw3BbdHzqGYaWsxeWwQhPjZ6az7CaR/fXY1aRZsR5HxcDwvdvP+M+WY3X8JBrrQqtZ1OwyYSbLusg42ywbAczUrXBxcx0Uusf6WUx64KLZYH15pZirah0lC8AWhO1zb813lTnI11IKHXcwZyODlD2TzFyCb6fGjS3JsLzZIFbPwXZ+gmEW4oKWibF0YnNquPISsHPcDhGt0I0sBOSq5mHCmGINpMzy6H4XBVDYOOv2D9gzpfEWx0zb45Zx1FOCbUyzvHp9V+tnNhatkQhUnwErProvtmZ8XGPZrUJ/tLkcisRaXpMb80V5ALjt8p5e1f61BivsNfn5WMXGstdeTJ2IxFOy8ssFrMU4unh8GzDlMYJSF5/rKYCL+RVWs0UMj1krbJF27XiNsYydNRZtSIdl/83zdvFL+okZbSmtEvcSVjXroPs9G4iZpbOxy8JeTjc7tAPQN7doz4NyJ/0mRtAxcq/UeVKz9F4C4GU5iuoFME712rTpzizs2QU3oI0WVQBgmZRiZWWLq8UCK0gQeFIimiFYje1pOXJq4Chg7PVfja3j78fi6lAGq1rr1DIuotBdPL6N9D/QnG0wnIV4OlnIbY2k2rPisiqqzfZvzxAwFvWMruldT1ym+tRZIczxXJmt44VVnruws6VVnuOm5jfQ4CuLYh8Yu4vzKyybzE6oWKEaU+eBr4gFX8tqmTbz2LbS91SBn8DXnoPP1WIg8M3MFMcZXgxXWFzf4vQGkMdz2u0wPLXCqlmoxbrBgAnoup5SV0PfWvhCRSxzeRSukAvJyyxuinGV621xv0tNS1vDTIwJy9RtoVm/GTrM5ltsvDbb/rIKmX21SqGNXfTOCft+AlsUPPQLb1Cf6/ZxVufFzTVmXTB89u0OzdkVhlkTWbqcUCTnOfpZiXjjocCaMOYkpMMailkh9ylebTBqts+ytFIWq4nPPyt22shMBnW3wkRwhTwAOIsvsx2Wr9Q7T+SEtRGmzuLLxhwHlLgCFLgiIl4YV+mWItDAyFgp+48TGTlueYlVdkffhHs6nQHALbrLdVICx9YFK/dKHUttosO899i5owG4VBLYqi7vSRjEkurNk03XKJMFlheuoLCVAOynpjfxON4mKSgMJ/MtdnYDbdtnrISxUuaBL/8O9PtDsS89UE9J5yreGnwXiArd43yueQ8A19ieTVNsAytIdwlAT+KND/PPukk0CHsZaj4KWdZWx9UJV8vPPWfAasDpEvjiBuHf4/gqbYjP5+LxLc4f5eSBRc2atKyLcqvu4xe3ABZQey5bi7pa1qfHQeY01Xort2PzwLfBoEBXXCSL69vAXt5AjfOL9harR+s0X4RZePA5n4Zt/xSGGpMEehW5g0LXtEcYHZ5xcMA1zedkBUSerxgBkrk4jbgiC7wdA1yQd4mc4ZjY8HYA5nugNfPZznmPvRevAP9GjvX6uIYpBu/TDiTIsW/MXuYyQFlhmZMBNGmBs36H4akrrJqlo9DdkSHgcUHzUH0WQzqati/u+1BGvc0m14rZOEsL6LJQrflNYjVvdlmhYw+AwNIcuLi8wsXsiozrbhxXagodbkOH9JMSd0ZYOo7ZtaJ3+MDoHGVl2pYcU3HLw5V2R/fh9RTAcr7CdGa3Jzw8bu6VOk880K1ZSayktHBZAabCw2F6AnF9n3BJcokAVbZBXQPaby/gAejSBhaAWQLYBAjo0WBBWaApvqEdsPP2XDwEwBZ8Ad3HvTn+oELn9YG2SDkWKFlFjzdBobtBVjKHsFPQ4kyCc3UsR2smvNv/7YBdOwBtmxcn20cKfPdBoWu062/sWjrA38bgacZPMp8b9O7Cy/0lrzMGX2bqhJmaxX6fAZPHwMWjXPZEMcTNEVY1AGAd/8mBD3wAVl2oXUlcJBSQ4rot1LZK8Rl4THfuB3bbdzTmu+yOlj7ZILuOzsICvrxcYdqwy77Hx73jP8R190no/k/447gmhQGwB5x6jIfEMxYLhc7Zezj8tld9Yl2mct6BFD9x+HN8lY3nHdCmRSqNm6bTHgDPC8DvrbFYM76PVersd0ZsiYrSjbbOCzMr/AAWs1ssL7NxwB4AHndF/9POITsp+WKxhN8T+y8hHeytEeUM8GMhgZLllblgDUY+hzBa+bk31L5co22ByNLdIChfbCxGpg5z4OzxDhevzPXblPdCqi/YdaBQ6FZ00ALYnB50vbK0KOs7DkyujIjMfXnPyQ3C0k1p3CyubzPWilIXw0OW8x2WMx3eIucdk3ulzsqYFS3isC5KoYsAfNLqCWJl7OEUgyiyUr2yILPSwYsdu0lE2O0qv8lZr2XpC3GVSNJAsjbmXY5/ORaAaxPJ9vMTWNQiokhkt2tHkyfH1J0y+xQyB9Lr8myD6VmXJp60+ZBC1zqbrbv9Yyzq2bxLE9+6t0Rh8cRdBGjx5UVjiA0c0KiFV36TXWy5ntJkg7xASX8N1FdRmbl4tMHF5VXKbnP7yj63pNTdArhCAGAAWIYTb5Z3AuCjZMSqlr7kgrKszEnb5jcIDAMv3HTu6eYWy7O840LVVWJ+l6Q2p1ihO7L2ZWiX75rO9+G7prUho93znsHB7Fz5XcYV6YsQX7bCCgvMYoHZGbbBAzA/ENYhf3shGbXfeK/2fXENn9Xl3Vq4BNDFzbVmtcUAQnClLS5zJmfNA+AxzgpX2shk1rxExP5P51w0XSe/WPEwpnzepfcn3LMmCbivsnEZmaZum+eOMHWi1LEb9jlg8cq8VSGzfa0k6oUbL43FHgh4cgXk4lsATn2mrqLAH+wjNX5aYnXzb60yx0ZRygbuVjluWfoGSMzl5AyYPtIx0sfEYd4rdTXxFpKCleN/WqFLBSCfwMIWKZiFg/57XlB0HEKeeFN1vD2XLPhLhM2nJRtUrMzpfJuLw1pXUQ1AazF1fAz/7bF19tj0XZ29YlCRAHelqIhSF0F4fgMsz8SNpieTSItcIqJp9CbgoTSDYRxGLOqmzfdo3VtWIfDc82PPPgUXYwBibGQuQJ0tSQv6s6EL/cL99AI9F1mwLoHTF3jByspQC5NQUyh0iCddQTN1LYDlUQod95E8D9VHXJ6oBTxXPRtB3JdTUu6WPG6YYWCl7CyMneasT2MGAH7t9V+Hm9058I1/NzexbEh+df9pPBGXvSfHWvI1xrK8NY8J1rhijcOW7kGyKzkEIMTqzlSZiyVWmM47bOZnep9oFk8RG4vV9cbPIS+AOV7c2xpTbKHudY4/fQFhjAB5nL8ALC83mJ6Rt4PGrqv4kzRtj6FtSlxhkc/mt5jOOzSNhOT06r71etDGnx4OJWGFIuOKMLWZmcvP22F5N7vMqDG2APmZR1y5eLwhdjPvalOMezsWsEfAE8EVCROKbJ3zjAdDkuQ2l3Nop+LpoJ6Dn2iUXe02jnSJdfaIeExdE9o0GwKTzQzgIblX6o6VUfC9uzV9aDInMS4kfQ5ZnMu4CavV6+/D8u65geW+hNkJTN15ArJp0wHzW2B+B1fJMYzLmMLnKX4jwkH7wrjMYIL/hX0CsqJyAywHcaN1RV96VlJjtitTLtiaUjff43S+pXi6vniGAOhZHKb8rYtIzstA61nsWpnZhoxgcU0zW8cL6AxJucn1uXJNqWJsF+B7i+x6ZaVuDWAPVVoo/T4rZYfmTuliRDFOrWKiF+2s0KWkEY+pk3NG1peNgAYDdust9rtNvoeaeJgyR8SVfJ/M/Htbntl2scgI9mRHC5s9j+fmt2xNaIKobbpfA9Jk1nBAQ0wdMTmSLCFtl35hOWToecfJ3y30M7uDrc1zlI3EKTosB4o/FYVFWG2AjMXM/vN8HL2udcG2LTA3hpIaL8H1KvMwx3hmLBPDR5IBxtvs/xMplf7efB6UmRYDTjtkY9EaRxRTh8fBWDy/5Mx6UyqJ2y+Y0gMBP15AZurkIa+B/rRqLB69FvO1R4RjUnU4UN7GMyWNsJIrTJ081xtgcX2L9jKXqzrmXu+VumPEBVz+17vg61nU3kMRJUul/x8dzKwVO88KFGC19L69FwFhOSq4YKeppo4Ew6dkCWbsvJHkge8x4GoX4SMUQ6vYtGaBXmClJ4+4X+U6jwFcZjeam3VVEX7OQ9tgN+8AzIIiwnXI0tgJwczTJrv8ZsayBsptfKQGlG23fO8xd0B46mJR10E5uu3FombAkTgyq9Q9BpY3GyzP1iq7q0HMkpatnwADvmNK3Tq4YCvP+2iFjhXDwjNu3c+azeCCuypphAGYY0Tj31wb8qDUFLk0n/bAvCt2fKixdMdKb/sHPoMprzasg5OvWEEQbLHPJ4/l8LqIHoBl8gDEuLrZ1seTYxg7xpWiwc7fRzJ1fP82IS250SQmihV/mSNt/lwSKwSXtPHGynRQtsRYFOW9YOu4b6IBcDrfJterHxOcn83BRC+6H81ma8U/fzZVrJ+NbUaHHItqwzpEqTvL34lnSMp5TCVWt7YuANCYYpQ6PPCfb2WNtv3T220g5fpGPIVOPBiZqdsGnOV+EKZOzjsPf592ehcWvkZN7pW6Y8Rj6Rh82yG5RRKdK/uRqppBeQHOpx7SdBFJyp3NtqmIt4i05hoZgH3aP3/eJADOWV4r9S+5SjwXI99rzd1hAbg/8Ds+bkS5s6yTio1i1yvT3XLvkamb3wDTs1xwkwGNr2ODaZsEvuF11/aBzdxAj5/5HifzwExYZkcmPcsAYToqKfZF+23CxRC9zHWXDwPwaYcMtJapk2cwz304fxxYiLzTQnQTSHC3/KYAX1bsRCIQH1Dgn0iqxoBmS23B3elmVy5EwjD0SG4SdMFVMmt4wR5PbgIwwtL1VVersMJStuKYOBslIwZjbYzYYyzLk5nhsuamPV+o6ad361hiBZxvgPm8DO8o7r/y75ChCHPO2jgzrnqeUxLfJbh4ymND3K8D3Y8oKd0Ks5mu51gzAJpmwDA0xlg0bB3/bB4MANmdho2S2rU4jKQmrETYLFopZM7YIRilsTLigVXoWKmTupFnyMZit8JytkrtSNtk1djb5HoV45CVuhUKD4CrwB9hxPNaNRrWoQ2ijCldju22LJ1V6qIRrJMv7pm6I2UEfNkaspbkHMC8i6602Oltn4JbOZ7uWOB1XSSGbbCTjWPojvG9s0JiQZwBW5i6XGcpUsfna2zOnf4Ys6rtZ3cZebUF3lXsdBxJKp7sLcyOUiduNE440NaXibuIa9sQ3SSzeYduMwPm21gln8q/RPZlOg/MhLBC1i2j26OtRpvtCaAAUnuvlhUQzs5TVCGMGoOwgI/0eXSTSD9K3SWORaxu/ZT+sEwdkMCYj6XukGQY+xyspJgxC8BF/whQliUrZPFO4GsBmBWJyEI0/VDuZWrFslDM0KV/tziZbzGdd/4pHGWvNufHXGyHxLK+R7HW0MXUPZfuEquUMMG7dZzOt7gVpc4quh7rOoYrNQisKnLlZxIeobM/t6Q0bfWYYPcrK3UbYLrZYTrj0hTjDJFV7Jq2B+Yx/N8U1ZY1KBiKOUOZlVBmWdnAPzQ+LPPECotkPufv8/lYCWyHIfSJ4Ar3mXwOaKXuZofFLJdKcsNf1LPskQ1FeWUGoQf60+q4uJNhdKSxyX0lz6BIGvGUOiDjb1yPjp1/oS33AgBljAqDrwUZAl9R6GoxLi9aXkq2Ip3St7JlYLPi0GGKGS7SliYzbGNc3R44n/iKXY2FcxbXAzda/t6jvFtrSeYMYGFcJl6cGCt14h7YIFHl2sodYS7MQl4qdnKjgwFfXehW7wLS+Ar+iOTFNyv4umJ8ucDyc28QwVeYOmtZi7BiHF0lUjYmMRGy9ZPbBLGiBYiBoPzSAz6CqbOL0oCG3K/IryPdyMaMxADJ4p2SRmw/WAU3sptNv0Mzy4rQoy/817DtX+2PnJrrNcZGTeedUt682nJ1RS7Hr6lXKffi9cOBPaqP+c4eY5VB8QD0aGKyhA6GX56v8Hj+oDSgRTwG/xiWbkw85c5pT84sD2NkgVUYH5ZxeSH+SBj6OHaCGy27b+W8Y8oE48psvkUXXf5hP/D8XcCULtU0kyx2DgfwnoNudrnzDLcfsMYhG0W+1yf93UdjsUM5nwSDRQGOuDJ5DCwf5TqAOawDPttahHQIrsj726DUyW/uIHfHYW0wMrakpBEPV1ipO0NS7A6tP1bulboxOWBRn8QD8xqZAAAgAElEQVTJ1IyAr9Qiu6vUwLdtaQE+UmypEnV/ZtJnDicsmGxJ56221jg5X2En2Wq1bNh8A3eXMaCuutLy7hp2h41CoZNJ1MR/BMyzbotmVmaM1a45oFXPWMZC3zfKxdG0A5bnKyxmKwq2rse+CKtm5RjrWitrWUmvuV3SdZmps5Z1j6DwzQE8gHKVSJtSyQbZ+klEuUlu6Z88TP6sLrXn8WIYKetakvjG6eY2A6+AMJdF4K2HNghs8Fk+78e/5d/FR7tPweY9qLtZHZZOFH+laFFoh/x9Fyn6h+aQxO3ZBJraeZhR4p5jKTFFJ0vI7i3sfl3MVnhc8wB4MXMv1uC1iqEj7HqV5APBmMX1bWZUBD/E/TpDDlOIYygzNnqRlnNv6ZrmJgAExW7oQ/IEe4PadsDiLOM0b0vFOwIdI7V5xM/Rfl6T9Jt+l/tY5pCHwRRTF4zFXHxY3LDFNpUAMXViJLLR6BiLzn3WJNeMbZEy6kfEKsD8Km05tX0gY2iTTpI/67WR5DHgVu6VOk+sO7HiIpnOuxCY2mTQapoBQ9sUsXVjA6codDgcG8R6eLKytT4WHMuTVvZtlN+d4wpXuEj71C2xwvJ8hevzMx+Aa67SQ2xd7beeFLin3QCs0C27VV6c2a0ogNJCLdxNv8Nslt2h/Gqvl5NQ4udNGAfT+RZNDHTu42vTDtEFs3XAN7tJAB9cjwlutuOBS04c5WKQZ+TF1UkzZwAe5c/PHuftfVJxVa4p5V6AATjcnWLu7Dg4UHxbX8Jh6/jzdEWrRLP7dRuUNM9lxKylKHtD2B7qqLicEcXuZB4Yq+Cez51gMYJd0XeWkQKqY4uFxExlTBlfPngeAtnYAPJ+qGmv4bjdHM43wPk8bL5eY+tUW+jVY/VqymANo/j+m9K9mHGl0/F01qUIZLyJmJMLU9fDZDjZgJNS+qbB0LRhT9m+AdfRE7cub/yevRQZV7jI/bHjxjuuNXhy1LlYoWOlhjGYKxPcABfDFZbNOrWpxYBUpNqeu1Dm1vGkZCwWmHL4tkfbc+D32WWf73+KTq9FnJTGrKXgyrGYQnKv1LF48S6ABt7z8O/0fI3ZPLgis8ssTkiz9upU73HQVIv5gerV+fz6gYcdIbLSwSDsWdacSTvDVp0zbO2zJIs6brd1tsZ17IujFbua8PFjbN8Blxy7XvMOB13ONLIxYrxtGS3gsw5ozrQ7l4XLAXjsxmBAeAokxT+7KS342rgXbb0/ibB78piMzHSMxARRXAdugH0PTISp490mklVNi4godW4MlAVg9eVLIyPuV59x6NXzTkWYLUNHYAvQ+2hl83j4Pz77LbjZnQHf9QvypY8pCVs2SaHTWzI1cpPK4PMWVRsraZOwXqxohs6aPCVe2YxuYZ47zJKByGVx5ucrbM7nZd9silPzTY2vZPa7aqwn3bdxR1tDcSYZnTXXPJDjdCPWhESaw3tKe5gi6wsaBGwhBU3cehIGwYYie2JeCimz749wx4uRKK80j25vgLaJ3BszdY9DOY9Qry4rdsU2lT2/sYai/H0M9t0h4agyXqzLVYSzgGfdtkwa6cw/KfIem9QO4bkfq0TfK3We1NwkSYG5xWzeYTHL25gkpg5NsEuPxNFjU8tZxhg6VRYlHdmiw1SBsHdODhbP51tjjVXYsDoydQLARbbaWHkTT9i9+qQsndk/tTXtmDLdbSeTlKUwLrbJplz4xyZUY74LEzgufA1vyZW3zGG3do612dI5e0ihaE+581xeLIcAyi7+9EXJ1m2A1Q3Q98BiQEgeMP/0VmGxRIVlvAGMu1cPuV5rMWShH3o0B0sB6fOxOqLHUINeMwt23MiY5a3MxsbvmPtVDMVYkoLZldC+Eld4AamJF29YxObRBvD187Spl8RQKPMh83j0vpXtpUSWWGGNBeFJnA/na2yoTxKm8IbsY2IxRd7zd55U3a95jHDtyxTSYZV9Wowx059JIg2PuTGxLs+syGWmLntXcmblIhlYuZSGiKd4Z7d4NuTzdxq/5L2XsGV/43yhGLv9BlhHZf0CyNuIRWPx9CYUN1dlnyQBa3SNEWXudOyg0JYXsTnAobFo3aUhpGNX4op1v8p2jILBuBsjf6/UWbGgK6/n+fX0fI3FWQ4OZ4amwwwzbBWEHRPT8FJa08z4DWixxdQFX6D01/NWMPKdZL+m/VOjcpesambruC7bsfISjUK2qHNdoE4DrihvMpEGhIXyAfKiMUAlLdTA17rt7HEMjry4yQKWN73WWXHi5vLGjADwlP5+EsPAns/5IvdHF8BXYrOVUhdr2EnwOFeAL9xhSTyrenH0PXuKzIudP5p3GoJFbV1G/B5Q44UBmGUyIbexYEkPN5xjeb7CssmZxLltGVfEG3AIU+7SHzZExO9fT+21vVYu9Dw3LKO4ih4AwZNzXGHZrPDcw1jc3DJ1NRbf+8xT7vjzIzDHelgkJq6F2XnFyxIH8niJ42i62aGZ1VkzZmZZoct9ty2eqzYW8244HI/G/X6ItXsxWDIqbPgIpnTAC7RQPjAJWOgEV9aZdZRY3eL52ZjcA4sQ/d4mkNk+DglGcTeJI2Lq2D1tjcZWcNUwlul9Q59FXGn64WiSyDTtX1yZIAKbBGGOul6Di8RuYQLkBTID8HhtOCsJNF2LGomVErHumYGggIOSBXRFzeH7sgoep1/LOS4wxRrLDLxsVYtFzVZ1DUS9fyLWsr4D46ep75I/SO4xE+OSrGq2qOMEs/FWxTVN33lB4VN1fF4UOOFEthuSrLVjxbrqn0SpYYarEAHfDXDbAesh5pF1wOKGFLu4oC2HFWZNjuOZocbUjQmXf7H/Smaq2uZa2EKt7psC4cjI9Ls8PizTywHNRqGrznE7D5xwjlDCIYwLGS/s1uxSQa8D1yIRpb+HgynubdpQDjYQQ4JDuBd2ts+K8chFzMX1xHN0QKNi6fj19HyN2/NTP7TDv+n8WjvmiBgoTyyeCPvf9INm/nlsSBcanAkRCTpGb+yanI1dY2TZtcfJbJmp2xbHyzVCt+hnBmgFXuQYfJG1Rs5V/IbZpz4YilLQ6LSLSp1xZ4sHIBXulZ1HQmMqz3SE8bchVv+ExGKKeGImrNAxcyljhw2/JyQR75U6K56LhBSXecxelMkjk044FpESgMfdJC/WQrK134XL6SMQi/vVXstacU20Qpt+CIV0G6RMNbGoRbm7aK6CVX1+WjJ17CoZs6y92Lm7um+hJ0/hJmEFzihvaM13EXQ80K39rRieFAtVbggu7B+7mxak0NlYGstsaJZ1qz4P7/P31j2iFvf4ykHvckz8MejDBL5SHGBxDTxl3a/Xt8lVkhRUL4PRPrg7iMcwjM6bA/GX/Fo8S2IUFKsrn7X09zEuQQbrAlcCSye7FDD7z5notcB6yyazEnb4vo5z45YLtmb+O0zd3zKvN+u2aPodtvNTDE2DLSVgMb4sz1d4/PCBNhatB+AurF3R5pHvAaDdh6xSUqZ4YU5xujYWinFGGBcyBkIijZ7XNZxhho7jK+1vAYDDHhYUV8f16WqYb2Us+aU2nqwCOHoemkNiKIpc3ABLUZAj6yl7BItyp2J17wQjp/r4+L5WioxDDqrS2j8Prw9JoeOxIf/k5y8y1PheqbPCAAw4LN2aNqNeJ3aFXRJSaTt8Xo89kN+JVBco85TGAFiUOKBTgMsRFnkCduC9G5OF2A8BtLADzoFlEwD3mpQ6CXJ2reqaq8ROxkMT84iJe0IlYyRuoXCTkAukoLt7hABdo9i5E9IRC77eVlHaWusUW8dxL2IcjMWriDAvKH97x3jfseIXYv+c+DyyqG/7rNS1CGCc+jAqdacdkjWdFNR2j7RXZRJh41rnM3pfMHWHXY0D2lwK6Agw5Gcsf0tMZmtjC8VQ4SSJA9d4xZd+Fj6we3U4zIZ0kKEoLJ3MKVmgwyUarLFMOMNc7jHxdKz0A1SYmc/T5vbbc2SWfxrHZzgXb3zUxfCOfF/l4tYOAVPaAWj6W+B8ha6ZKjwJyt0aF7MrPD5/la6D6SVL1LDlJV7VmDmT96eswMnY4MW5RR47NJb4XPYa3nXz1nU6kcreF+9XLLt1WGWwq1wne27ymjXGuFnPkIhVghJGtSa6rQ9JV+IsFcVuvYlKHTF2klySsKXpKmybxZD/n723i5Vty86DvtprVa1Vf2fve05333Ynvu7YYKJEMVEngGL8FLeDFCk2iRpZ4YIUFHFNAhKIB1twIyQU3RBbIkI8RLRRHvi5D0n8hmIJt0FWEoJE7FYgxsSKuk1fW7b755y7963aVbVWrbWLhznHHN8Ya66qfU6342t8p1S7atfPqlVzzfnNMb7xjTE7DLAmt/5A8flb0fz1ZaemQDeUa/Bj0Xh/EwYd8CE26iaTyY8C+DJC8QScTqefPPPezwH4AQB/Oz71bwD48dPp9OWX+lLZr3KEqauj5mVNIcgZMSbChkkTAOaF33rUGiKVdi5MwtsG8SD0GWg9+hQSESOPQdh+f+u8uCDmnKbV4wisNmiKWfSrJWEi3t9s8GJ1xqseA9rcBOvo3r/3QuMFeRAmYcaFF2dOlOAFu7Mi18d8t3zfOR2LGHwiaE5FTF3oVRIjfNkDBlFh3eR5Wygh9AZ76D31UPi/NMdMx5byAtS6XsG3jPdHCcFKKn7MgF2k39MCdQOU9ZnFVsAX9IaMUfeI9jJMd34Btcb7RICWF24nXo5fbO55Ln/bX/xBvN//Aez+SXyCjbrkLEYtHTG3Mh4kQUKaXFOkw51fjDr3WZNE8sh+ZcaiTYZdYQy6lhzFAsIAWyNvdjii7EMSUrjCRzTXWs7E365WOzysloorW9hkiTHH8FFM3OX3lGY3Ccmop/2gvTHHDiNgMYbGzaUsdGbpZmTQ+eQZZpjledHSiUHnpUGXk6esc2ejAIo7YyF6/jxjUTzhQetgN/ba97AJWFuNAMguHsFZRH7tMIadvHjesPtm91KWdqkWbRkdG4MhPHa8sfeKBl34rg9hm0wmPw7gH55Op5+S/yeTyefk/0x7CuCzAN4C8EUA/+5LG3TSRj3qwNJxGj6HSST8wIumFUxenlDnz+t8na6egBcI4CGTzHrVNixcOWOi7CNLEQfatAOAI9bXmv16g9thCPZmqn3FQBYOfP529ne7e/e86OmsaUJg3FGYxGsZ5P8lPUfnPSYqzi2sXJSUkyzYcxPDjtk6+V/Gh4barNHObegd5w23LgO03Fv+uWy/d1oUQDzrDxC86ilrYBrdK1gAOG0VZjRRYrhNYQcAPZcB7asyP4ey8yazH+NYy4e+ejsWxCnw4Va5F2bGn9vugFO/t0acOBLE0q0rZak4/MphTbvg2lCnNxTGmJVsK/u0I4v/DM8mjyti0O2xMAyN1Lj0LE7RQUvEIFzpdbnFbjk3TqJgy/pmg7ubZT4Jy2PCOUzJOYn82oXmnUUxtowjKIsyJ84wU8djB5YZtt/FteRU3yxOIDuG8n7WgTJb53enCW1mHBdujDnyS5mtk+flfzX27Ws5LOrLKwAPpr/FURSDDgi4cjoAE8KU6T1QXbcxKibOIjLXmnGEB8ZUb49Ye/y4BRB38Cjy46g8jRqGzJJKBMwYc47FhYTtR9pjHdcPpVEH4K3T6fRj9P8XAPwYgDGjDqfT6bu+mS8MsfoeKKcaeiWjrl7tsC5U+yEekZ+gMigqNGfBVCaRDaHpgpxaBpS8foaNtwpN9Kg1bOIFzXK+zOqkfuj6AL5k/EwBLOod1pWC7g1u8Vp8nA3BCsjJb8jdfGHRnD5pjOVD5nnYLMYSfSggy151xngbsDA9Um0gOeZY4++T2lBB6K6hE2/UMVuXS0zJhWcYWCUMNlxu8sJmH0Lx2jtj/GX6m8Mkwq3tG+AJZ/1tEVk6XVxmdYNDvXQgOoH9kindRxA+A7457di3KmPPzOVc+JUfl+aD5l7O6//+k38JeyyAz//vdsyLUXcTWDrJGlZc2dGh1WnUsTaujxouqvH/XEHzRxR0ZuMuGHYzWKbOsv9yTr48T3IUaT7WJbBeBlnHDd63ziKHYC85i/zYjxl+L0+pc86iC0fzHE5FcP24EMNNfGR5zmGMHPMca+aTrjjpIYcp8v/MXRU+fzHocs07eN41ttnOZcQqNex8xGBwrLIAiofB97KjCES2riFdXTTsBFfEWTRrh9w6wo90Iaf2TT7hpkQqh5Xrk6ws5UzLRwAoYiM7a3jtXE/P+VYibGbwEufxoTPqJpPJZzJPv0Bg4n7rmzc4UlFQCRVsE/CwDkoaezAzNClbLLdQD6nu85q6c1uOyeRqUKXvyWnqZNIJqPRGqhoHngwyMcp6YFk+YP2JrQmRrOSxD8FuYfUB5wy6HKjmjLszzRdYEG96hlbDaJkQ2qmLRS/9a10wbsviPMNqIa+nXm4GjB1rYnw4hRldvn459kTuLewPmbccW+M/E55Xw7DBLPT/SDKsAPAcCGaHCz3x1mczNJqpNjDgyXum3gxHLoeAfQZ89feVWnrgJZv0wOAHM/jyvX9sntZ+1S84AeVE50OGpeMIAEs65L5FSyPt5UJG6TiZrOCrkg0XKznwejrGFa+pk8aOKo/BCTtW8rgE1ncHbK5Z1qG36c0GR0mYeIyzyJgNes9jnUVquQiAyYjP6aK6gCnp9wIWV9JXn3MSu3QvxrFl9hvjHHq2jvFFmuq8h3MoF14dxj2c4+car3k2ShA/WxRAeQy4kpHuchGS/QFY8G4TFAFQWQfNp3Qd2Yjzht0cpqrFhWv/Ko2v2/A16nePJX6ceJbZtbN2wvjHftvbUwQjjtvtpQ9NJpO34ucuavDo/W8BQPHGpwBAw0UMEsTSsZhXwiSApa6rlGX6OAD2izKAfAHVTJFECzslWlTxW3UxGNO+CChIiRMR5xcMvsxyFcB6ucV6SSESuXEWLHvVPmEiB75jTF3pHo9MRBF5i2HnfUuzkDjjrovyjMk5T+kRTZg3X1jYA20uXFKkUVLEK9fljYzURapd8suNAVIwE2wzXxl8W8zsc6KpO2PcSdKE0REZUXP8bWU/UpJCwHdO/8/1PuOJjxUJfZQHG4/hNal5ACYdI48Zb+ANPxi86tzCJ1sbEaaIlk7Gi0QAuEZdD2VlZ5H5l2M3yVkcSgSsiyMGXTwnuS9PykiVw4Wex43q6eS7h+6L9Kl8ktlGOrBNSAIwrYD1tdfUbTUL9pt1FuV9GeMq9APO48uIeWOYOBonqZZjLiLQnzfo+DstA6cJEJyIxPgi72UmT9vs7DpkHUJrlPH6wuMvx+bxOtaiSpjTogLKQ7afeb+HpKvjZLYtoNufRaaubkLRe7OGsEE3j0deQHEF2fHyytvtpXWtG2CT9IpvBRtwrJvLYQqtm2EHEb02jz21D1O7yTz3AgAmk8nN6XTKGXg/D+BWdHSTyeTzFzR4YvT9JADM/ugf0jgEe3qOpVuRNx086jChArsSFtA2Jh547/YxrUeRwiTnstSyn4N41YHpeYyerkCHec7yF8C6p/9LoL4L4RIJv7JxV99scFg9NUWa02elX8/d5L058L3gvciEHOrYel2MnWd94uN37j1dZCxtd2W/15tKKlbeGbbOG3UMyOEUxj3hcGrD17wRJ0AqANCkz8qxSzTxPayR0gzGAqcamLBBV/L32Q2+jg3Mbh3z7RGza9XVzQpX1kQedwK+Esx1HnXuM4P+sOx4tn2r0S2H+zSGTyW/Vc7vBCPriL+JM17FkJnHSICwLDJfeTM5vuKPO+XznXBOKK7Oog2vspPIma8yF2aRVUxRARGIM7Mr7QNgvTxgfa2YcoP3hyHYc4WIPbPLYyaHJYxJvpWA1DMsqZ+NpKNvhgxL6DAAIVt86r/3JW0GucZ+T1evw5UEK8/e6deWmMU16VykiEsc5WQdjDPyfo+2TBrI/+m5ChbrqXHZ4D1g90SNWfVym6HFtG5x5ASsGhgydRx6JUfREAonNdKpDX7bGPv/Kvji1x0/jfmrIg6/bBj4w2jU3SKybdT8/6adTqcvuqe+AOA/wRkNXq4VLOwGgNXJsHRSHJONOkCNigV2yZCqKFziQ57A0Ds6qwsq48KAYVamfLbBDLMEvuE+p6fj7CVhAdgLKDmc4DPNauDm+g43ywC8Rth8vcXh5ull/YvP/ssZdRxe8Z/nx+Up1RkaCxaMeugI4Fue6fZz3ptPgtG9XAV899TzttSJCeOk7wrbQA29bLswa7ikB3vHcn2FJ+Oio8LG6X2VxpsagmErua4Apm5h9JvtCPgeO2BK4BvKmjQpAzYVIPbXupsjGHDC1JX2/3r4mZIKTEuz2Z1nwNe1RxlEY161tIxj0hVWV2Sa0ekGls5kkcfHEmIL56kGf7imytZ5JiA3ZgRjLmkOC8r01M8Xacz4DGwpsyLOIuNbiT4ZoWYxYqeKS5OUwHQJ3FzfDpi6FIJltk4+65k6v0PHmKPoDbwzLF3qHzdnU0a9Z/8R5sSgvYRBx0l1nHwl7L+E57nUSe4cw9cGhG9iBIeNVD01q6suCCeGbB0z/AFvxBnU+yp9QomGKOsgwy6Hu1IH00QAmlDYfFYovhZlh+PgWk+gGCLuJ+FMls19POGCC9hyKRnS9PvIekRvTgYdSh+Ru4xx/0yMulhy5IcvvO3F6XT6EQRWzrN1NwAwwtJhMpl89nQ6/Sw9dQsgp83LNiMXFv1LCVytdoal8zXaZEKVNInEp5bBHd6TL8zp6e1sORMSM+cKJbJnJfq98LzXvWjV9wKyd19nQDkNGGHquEAvANwB9RNh67YpUeIGt3EvWFeImA20gZeEcaPOPwa9Z4SpYzAz4JYJu2Yn1IX5fWnClpAQrIZKOFziK8MzCLAhwGzM8BR1Ug/GzQB8rXh5yGGWyThgGXZbX2FaPQRAybBk0k1HRP2LK+rMhm0qQOxvh6idyxl1foGWMEmmlI/8vostOgDfqvIFpolOqAT60oawXv9zfwLfwMdwx85ifRrUpfO4wuNYncRmwNblfrs3KtM4yEo6xvtDQmfCALP2aiz5ShwXYYYG5ycGHZdwKAHcAeun2+gs3pqkifXNBi9YV+cjALkC13zz8/5Azw/6I9xJ7UvPWRmHOmfo59orDjll82U+6b6uUh9V2Lnwfg3Dy9jgLFXrQI5FfMKIG4Zcc/KNIq4pZbr32l7lFys16Kpwm5QW9kGPT13MgI2M3exwxGK5TyVNqroN+wMPNJRs1LGjOM9iCkayvuV+1EHjFrPHvyVtZAzzOT32ML/lLYZBH8WanU6nL04mE2+8PQXws7n3TyaT7wTwhclk8hoZfTcINe5eqgUPoAFQAXUTvOnCGnMrZ9T1UFq7wQwVZnERF291HIDHWhI0lx1kyyMRNI+xfeJR86LPwCvGm2QvAUCLNoVPzPkxCHLGWgngGrh5doub6n0Tgr3BLb7KIdgt8l7xmGEn3yuamVyh0dL/3xlBM2Az1Qr0jwffkTZmYPFrAq6SKCAGnSTT5LPRbAkDYTZy4ZNw75NqdKnRbZr0uQYzcjY07NpQfiqA+L8a/U01w7I6hGtQAKhskQCAhof0LQGwsnRxq7A6FiBmYw0TBL3LHik5QsDXbw0V74sMAHN/DJos3A7hLtWTelQjLzrdCqAvr8zC9/qf+xPY49PYPu/xUB/DXBZcyTD/bNTJb5pjl9BEGOGG9G1jjRekNIZMnboYViy7QZ/09DlxFEvolmVjhYcFC8X4TDOxKIDuaDGFK+hXQP0CA71uKpm0Ir1uLgKQcxxyRp0v7grYawi9z7lCKe4iWYzAZWx5BOz78cscmTqKe7rtTOZ8+EweU8LmJ+O6Mf5l4ecoa6+Gm2DMHlyr0N9knZFz5/DrqQYmHILNRAEkArBvgAWtPVUDzJZNwtdZ1eavd0e63IQpT5AkHe79VxT9sn1iQWOgcX8Eu/tKzeGJPPYVKh5zmA9j+1tOE/cDAD4vL0ZD7jOn0+mnTqfTlyeTyY84Fu+HAfz4y3xhUQSL+6rs8VA3mNYt5kuZQPtBdpZMKgAosECPEgvs0SLs+9pGaJPMI2BocbOOKk2uM0kSObZCDDrJtO1pwu2wMAAsIC9CbClwyvvBpuZ1dbI10nNg+eQBN5+6JQ3MSAjWg6cPveZCJSVsiCUXwh0ZtWzMPUaQPPVG4is08aZDmCT09DzpL7VAdV7AbLOZwjWbp+P6ZkpUkPEmv1orxFXx8/b68kLLGYsCxmG8VEB9CB51vDbzKoRWfdfnQiXK0glTF0XNfL0BKOBKSeNx8M2V3vAaxFHDTu7PhFpsWYZSPyPNhUPSOJX/47k2lWWujt+4Q48XKKbPcIwlk3SbwX1yhjgKIAwMs+cL7LDHPM5xlXaM/W4brh/Hk6tynL0xGdEIm9LpOKuwwzw5jVzmokCPBfbps4bpYIOOncUKwB1w8wnrLEokoM45ixwB8KE1M87c+/kxMHQUwTjrVauxV5yGjtu0HAnBvkTzSV+CH7bszf5RmBL+L9N7xiVAOv5lLfKhVSEO2PBr3XtkLhXoE1O3wwJNFWBAmDoUNkfVBGlknMRrNTmIrq5J91lDfiuYAgxCrxln8VxGPWPCpXYpM1/6dbQxsDKmxL6Svs+y3yOH+9C10+n0I5PJ5Edj2PY7AXzJJT3IDhLy3M/GHSgA4BmAL1zKfh1rRRTJhirvu8Gep96oY/AV4ypUAl+kickFZf1FUbi4rHsB7GLvQyR6TC0OmguTsC5CBosZxOzZikctYaYlgrj5U8M+WWODr68OwKoe17+MedX8vdI8W+ebEzQzEIa+6vLh1jImA/Tx/pUNOutRa5banjYpHxYY5ibeMBA861zmK3vDDDRs2HCShIbrqvQ+Bl+vd9IwSSxPIQZdBJWyBMomgLAUwEn1pXicGPANADytWxy9UVcDOKzjESgTdnR8dCkclmtpXEuRUG50bYtSx0j+OKW5958PB6HnZezGuWFHYoH/53N/GVa7/MAAACAASURBVA0qTP/O38G0Do6UbDOYmzs++Up+W9DLtslZ5LI35vcb41S9e1OjruyDPkiY/4xWUT4vrMuODEh2FndYpOcCtpXJ8NQIgOtA7ywCwF24LZ8/YP2pDV6LBl2Kiqz2ONwgiGq8s5gbLzmjThqzdV6XB71Xh93iSoFet5AbaVN/zJdg69j44kLeGnpVhzFn1HmcEPY09z6+79L3W25SsCKMQRv6Vz13ZdYZOf+Wn6+nqJdHxZZa+TRuR0SjmKNEvXUW59iNGHWiq5MiKXMAC33dGXYBD/JJEtpP54yx08AxegyZkHMkkjFXIhm98j/rnuUcH3v4D1U7nU4/ceG1n6D/v8z/v2oLBl2Hsuwxq1pTl26BXWSktqmsiVDMgIiZA9DJUG5pkHuDji9SFnyllV0C4JwmSPV0MzNRhZ1jtk4/E963iKEd1szQmywLI4PsDsBz4LUXB9w8vR1kwa5uNtje1Fp+IPzYcaZuRd+ZM8C8Vz3C1uW0L2V/foIlsW5BN9fGjG0GA58swZo6ETZzpmv4qaqhk+9hOD3XeNz4EEmDGRbxOanuL6Cg4GuZ2xbWD04GnYBvFSq7+4SJTv4MNHWUr1k3VtScjDoBYBkcUx0P3qs+Y3j4/sy2eAxul/o4fU7uM+HWBMDxXIfGTNjZQnClqsPelTktnRp1NpzWo8Qu7v06dBbz8M2OYspWzGbTD8ewfJ7ZX2nsJIZECYtvACI3vTescDpPScJyxc0RIwB4Btx8So05YepCCJacRfkM48pjjTogjynQey6TxH2Ty5Q0xykcplww7DyjxmFSufFWgqH0jToFXM5EjmcTp8p0DXPzJ+sAQBk2wQh2AkXWIc8LMcD4I79BzbAKu2KBJ9VduH7RWeRqlUZK7TXQh9A37CwmWQevI98AgDX9wqjZ9ZgSb6WTNFktqjokpr4jj7szLatrLSk6NBJqNeRH7CeWSA0iCpn2oTXqfjtaUQYRZlH2iaXLga94SoCGMnuUaeNtGcrMr4wZB95T6roiG4I9t+l2bmswAV4x6lhPJwaEvMZMUDzoUP8irQZwB0yeIxl1nAU7X+6xXdGE8x4xG3YrhMkpobGujIu9a/4YsbGgWfqGA9rps9xoEk3kfw/sZdBHeW8217SMg/VXheFlXR0bmV0RQJABZYbzVd/51wFa6oKNeDHOGOg9+LIhKMdR9mWuIRIRNZNX7Q27tFDHscJlGCo0mNXt0EtOGpgFQprSREMkLIiP753WrVu8VBd6NkzixstYopEc08wDvxj7ccKhpAz4ynEnOCVcCY5ibr/T7cCokzkt7L+WdeCEiXFcMb9xwF4Su+C0ioxHgaGR51VLt4/IyL+XM3bX2CTDYHB+Xqcr83qJ5Cy+FnGFw9L1aofDqrYGm2fazKJNuHKYDle60d1uTmnf14w4BgAVFubPx8eTMUcgdM4wKjLS2IgUw86PG8GUouvDrg0AmsKXFVFMkTnDBgEnQMj/nB7CTqDq6XSNkRA7J0UU6NMYlXhXg5mdM9FZnGdkHfFEnKyDncURWccKka0Tw26Sx57E1A2dxYHEJUu0yH2XIntjUZjsGsJjQ/6XaBhjSg0cK517xkE60z4y6lwryj6mTzfZMIkYLyJ853IRMwJe9pU5BAvYsJnJNBpJm06CziI/OQNA8NZgFnj3MUwirY/bWIkIu8kNGA7B3qcPhgnxBEEDc3+XMta4j57LZtwCnJJxlgPeukm/76HrEUbzRM8hR1U7FBhjt4rOPceTKedRj7CA4acPr42v5hQy1MSU3qdFqWpazA4PaS3tCqAvjyjrHk2hYdO9GRFd+l577SwAC6C2BK7eM5fnLfjqgsvhtBYVDkugXiEstBFgRILMXZPCr6SBqZpgvKR9KIsdXnjgFW3UFkjXesSgC9oXmwgT+qEcjll7cUiLecomGmmflvQ49rUwtzwmKjomAa/cj+lTiyI4H6KLEs3lKmGKZnvyAizXa4EFNuDtoXTM9VDj3ffLuf65iuxhnv3X0Jtk7rOWTsqZ7DEntncWu6Ux7L8JZ/kELM6sXyI4i3fBWRSmLhl211scVq+FmnW5CIAZY0cg6qMB4KHsgUOFtCdwB3U4ATvnyXlmXJH5NFoOxxtwj8CU/GGUCBBMEaPebCfX7zDfHlH2wcg8lQ/oCmBWHrFbBqs3hMNbY5D65rWZqgmfmbWBk3Xk/Rol0uvNRiRLgPZYhGu8RJoz8zoYdVytEoi4wsTCAdQPTtaR9mYHJdJM9BrcuNfTODmOJl95zAUA+N1YXsJySiOpvAJK2i5NMIXHDI/jCmjrK+OMh+Od//KPjLrYCnRpoee6QKJlsBlqupuEgm+VBM0brJNxt0/lfUU+mqFl5b4rhlv5OO1Lrs6QoYpRJBGz1Kr3Vd/lvBdxMW9p8nYkYDXhV5lgFcLEfIFUjNiHYNc3G9yJUXdW/xISUqo6ePldV6AtezxgAWCinx3xqtnTYjBko2jQcoxLxtjrzxWwcy0wdWrQ6/7AeyzuD6hly5t4StMyVNIvuiOwAvrI2p0D3878Ml7ArVctma5s5GrpTuZ7NGtRZAOJm17WqJeHcJ1juGReAPM+5Kwehyen4Ht4wKwSpyiW/fGaFgFY+SyzdJlQSTniCUuTPuh4t4SOtwUaTzTSY2S8ag6P+EWbgDcBcDKcKzPPZSzmNJcrYuokzCZIwey/5ppqCJZLJfG40MtSpK3TcluE6fnZ/pVxxrq+gCsLMuqCs+iTryq0iZkx2k35epF1bGGLEN8hFLN6HkKwN9Wtw9wdrryzmDXqTriqW8zqBmXZx8hHGcdsdBhzyRJ0bXO4Io8znTccJ/y8GzuPZVsAEKa0iWSYY4dFv8P67ojJPRKmTKC4AoS5G5j/+eD6Aj7kauukioRDrh9zZEwoWO5MFYDSxEkUMcppGTNgo3E3rTSdQTAl9Qwb/z2oH6KzKLuNeIdRQvuAxRrvMEbyhvsml4jW5yJnyQjrz2aPDx6XRTDqeGyIYQdYli72UVOpKfs7OlHit6uxd+STJHw4YNFHo65YGPBNBRKdVz3WzuvpVEs37lEPdS/CFbFXLe/RMiw9GmwGYRQ6uGXruKxJ9KrxIgDwIImk2uHu5gBsa6ttMeB7xLQOkzMttnHyHLrIQ3eTvFfNXQQG4BGhas5rFg+poMf0XFdcTmDxhiQXHl5gh0WzQ30H3ceQw0VdrDqPI7rrJoFvrrERx+ERDXOoVz0EX8vmsc5FftsMbXpOVDsQoy4advMamN9r94vhf+pom7VesmR7Eww29Qtz9cZyRl0C3xM4G1GaCZU+oo3pUeVY3NedGCEyPtiAk/N14HtY6iIm5/Xxv/BDuMcycWaaST/U0iXxe9+gKwJr22IWDb11Mux8ZqQPwbJbM9Zku7TyzF7SfnFj1p+xpYPWOgSAedTTGUeRz0UwRYw7Zj4jpizvHkImrHMWF6sdtuwsZo26BrO6STKaGYKzvIMwy3XeWZT7wVZy6jYPGht0YtzL22oMDb5yqIfNNR/HMZiCfTDoBFe809zF0yhbtJExH3Vw4Z0ZPTfeeUaMCtZ7itGv3JniT3hPl5xFwaTd8grL1YPiylKNuv3w1EJzTF1CuqodGm1i1Mn1HMMUknTkv/KMnCM9thn558K4KeReFEBx1DGbIxgEU+J42lP/MWafax8ZddQEKFPoKFPKZI0N1s0Gs0OkUVc79EVgxxh8xbALhYhnEfi0WU5pXMzM2TW5zMiOBo54TzsssMHaGnVNNOqqYNTN0NKAoTp2JTCV0xDgFaNEQDAydXgO3NxtUzV4BuBb0cCwqJnA9yoydLNKQacvdDgeAAXgrFd9SmE5NuwABUV3cdVrlsU5p/WjSZZb9Pk7+Lu48LCwdcu7B+ADKCvBBgGxdlXToor9MOYEmLBaL/qZoLcSw16AVbLU5HOstdPc1FkyEgt0lNoRbli+MOC7WAajjgE4Mbps/HdagFhg/qpu8VBPh+ArnxVwvok3Bms3RnKtR0b7khbqk3rUGcaPxeI8mk4lMPEetSzaMoYolNTWU2NUdyjw7If/OK5wgxYaRuMEmoAtii+L+wOKLoTmsVQG1TJ1qi8csi/D0Ou5XTb8pvV8HKlvpmHXxBOpUdcs0HdFMJ6qNhmuIVJgdZzuRNO+nulrYwIWPgHgBbD+xLA26Gq5wXa1Ds4iZ8E6R1H0ix5XdgCOXQF0U+ss0pznML0PuQ763DuInnWp3WtJspxncuS7eCTqbI3jp9kFhu4OFpMFY+PvmR0eUFSD0eAugzNb+wIoeAca6yh67XbrXhNskb4SJzGNmWqB5XKr82apEQDeBTo1cgDKvo/7SpOz6CUdgitCJNQYDb/K2jHGYKarkC0xFu6uxDGCTayxP0Gd8B7lwMhPzqE8lkQSYerIlH2Mw0an91GzGYy2JtAaW02v7+NiLRmhOKK73mGBhfGqZULuME8XWwaR9wQYfHNlGfyCJMfrzYBRj1oMug3W2DcLNIcZ2kOFouzRHGbAdfB8ZLKpaqMKcX+44ppsWJVIJQhwB0w/QNq30YSnV3scVscgUgZ9NoLvrG4wX+pWWvJ7iioCcVdaAOZjxJAabxHGveAu7HBhrqB197w4lTxqzzIMAdguiqYA8f0hGMNbBMOO+y+GFOT/ogsAnDt/hmUAKZwGhMXKFhAJTIp45/IZFjp7ry9sC9Ta8CvmxqATz9HXazeN2BeWVi+ww6xucFgtLUvnDfUR8J3Wumcuj/vwlY9n6gCcZaXYoOtR6nZpPGZ4L2DRHEYmc1cs0rVISQa/+jUccUDx7b+X2MsG2TJJdwdM70MfSgitXe6xob4saZydY/99Y2cx6XNLdoKs/lLratrkiIArkS+6n2O3XaTPLVY7FMvOhNy4X9Nl4rCaT5ZYQZ3FJheC3WvChHwOMI7iItYB5GLfLUKZHgmlPXRliALkZB2A2U2CDTrTZAL4xZlf9xGAcii50T631RF8pEdC9su7h4C998gzdX34nmkFVH2Dohhm7HrjgMP0QIhSNM5QCwWvF/HcNDzPSjdm6oCwxjSoSMQ0B66jUfcknO+TFTC/G+TBy4mmiNHscMRs2YKjaFidgsaScYPXKnlugC2nwORST0i/eNZy0JKzaCUdvg0xJR7bj4saOg+EoRP8q5DKTUt/f5Qo8QpNwNd61JSldncMkypey2mP6BmqNy01htg78p7wYLEe0b34MEl+0ddadTJ5Nlhje7/GbrvAw3YBdBM8lKe4YwZQXTdZjzpoySILmQNgIAy451AA/vZhCHZR7LBZ7XEcGHWnyNKp/kx6Q9Lh+6ocB2A5TibrSNmzDKvj2bglhqE0WsB5cl8K84kzIJmfFdqgo7tDMOjuYBeQKn0QqELF9GKZZ+i49bAaj74soh5PxcxNXFABJGNZFuZdZG25pEmJkAW9xiYCSBg799dXWF4/ANdIxsuTCvigGZAbVgDfwSwHQf+y1219BGQ9gyssHYNwDVS13Y2D+yJ8NWtfaP5IeKTskkct12qsnxl82/oK0/JhCMByDUVvGPuGFy4xmL/0b/9lPKDA7/m5v6HGfmT/BVtu8D7WzQbTD6AJSXFDj9lSdVS6f7BVV0oEgFn/dM8OABl2CVNKxie7uMm9N+g2/Rqb2zWO23lw2OJ13EbGblfth46iLGZ+vHCyBMs6qGadlJFKfM9qj8PqEFh8swVhcBQ1SSd8e3Bc4m9bBgP30BU2DGvYf8v656Ij9KIdG2zUCRtFoftTOUx04jZ00TlRogmSHzHmfPi1pMfRaZ0djiiWZzCRzkFwpe8KFMveGHN7zCFbdMl5AkhSDXEURWspjRNrNlhrssQ1wtx5Evb9fXIX2P8Omez6cJIoOusshrImjZa5YaNO5iljCRt2F9j/rGFXdoFgAIj9V5Ill0HuDboexdAJcNmu7EgfljCYfmkdSqd68R2/C9oEoEnURmjeD/Uv91vVMghTVwCL+wdUlTfoOnc5x+P3HDp6yHrV1qPgz8q9n0Db+zW2tzFUIVXYywlQ1zgA2K32aIsqaR4kO7IrCqA8yhfYEKy0O6QMWLywIVi+bVZr3G1j3mTSvzTJm1ZzUsshJDamLgIAH2ZAPdXzAcyo9eGjbD9zGE2obXmedV7E1GXLMaSP2ZC4LK4COHMQ+G7jvdTl4gzK+P2Tgw3x+MaGe98VyrwcZiiWIYvZM3HM1HUoyIDX4GgIsYTv5NDr3odKogGzXoZsNTn9AQDHhVrLmkTDrmjGtS8cfh141QfMai4NNAw3yu8zjbbXS8b/aK07H7Is1LmpHoYetYwlAt/T0iaj+LHjw/N2L+mtsi88RkpgcX/AZqkLWehXq6s7+3viWBlLkmBGyjcJz3P4LBl0t+tQOsKE/mpsyjXmr4dkMZ3ZoS9OJZX7YIPuHjqfSauLD7xed6vOYr3GsY5JD9EYm672yVGUpAJfJSAY67MQBThUQD1xhl1nSkd5h3EQevXsP+uHM+x/U6m+6tLibEOwcdYejoorcpNkE9Z73oe+LDqNQPlmx31pcKVtZqgqkXVoJIAxlp1IUrolI14yb/eEKRusQ7KEiwIMnEXumugATBt1nuUb69UOBylrItgBKLZ4ZzHivLD/MpdCf/i4S0YS5XV0mezxYRRO3bAOtF0a63SXCPOe++Ua2C3rZIlw+PuScfeRUUdNul6gmZMlFtgH0bvcRFtThjpei+sdqoKXzOFixBlrPLEVfDPaLRcmkeOJB6qLc5hQEnLd3q6B21pLR7CouKyx286xu14k3Q6npRsahsOvPR3nGgF8XQh2hU3qt3m1w261iALlEig7TOsWs7o1Cxz/JumbRVGgrwu0dRvYupLq18USFTlB86BxaIXBt4NlYdxEC6Blt74ZjhdrDqRARNOqIeyZugPUqKy1X8u+H5SsydWPAkJouu8KoG7Q9wXaojIAK5o6KXdhwygaJpGdCYooHdgxI4MVPn69Ddf5GsCTAMZP7gCpFDMFLdQUKqnIdBR2KiVL3NB43FI/ZMIk01isdzzrW/sk22h/U71mQ8OOgdyImsvjMCOtocfC0i2vjJRBNDknKT5M42NQb+x+a8NpQDJ0qwaolixVb82Y8+0xXrz0x3jYqEz3zPDusFCD7nZii4vH0OlDvcD+ZoGmqmIGrJY1yXS6za4HVFcX79f9BjeFGnZpV4XVDpuuwEMZsJT1uaKFllEuyCK/aVa16LsCx3oW2DppTMoMlnfbV0ZvKUabsCzyUzlkL5hSXiWMlfk8hivhvjNuWM0snWfqfOJIA5S9SkTsNXaGR2+N/77r0VRDPZ13PJmhs1UUwnHUISDH4HqKJ9fHQArEKMB6CTxpdMPAqV9/JARrZB3BiD+wM+hLaHmt7grA6mTY/zFHsYeSLcNdajq3k8S4Iy7HlPU1yTqEYODkGmfsSuhVMPuj7NdXaGO6lwV2WDebIe1NYYMQ828SW2eXiDxLANAgOldyYLSejn5TAt8+gC+2ddhWxxt1q3B/WC2wu9byBL52WWoefOU4d/a2/nbVvei+p3vsBYC7UDeqqptUB5Czhbkv5PGsCqUJUrjE9UlRnAmNIIQnUTwMDTdZRMSwc9oxJE3duQw1m5jBLO3i/kEZOrnlMu0oq7joeozN1wQOvRr/D12B9lChLHs0y5kBWOkT2VGCRc3Cogg8in5qQfl1wo3g+jcN+GIZNDD7u5BJWMrC5hyAAspMiYN0Vbd4WE1tmIT74gYOfI8JfNmjlv7gBIdsQkDciYXZ7jGhOB+TARjVQQ19H65no65akEctUgYdyxIBsNvHhfuaF2lOHqmCET17yngyNDZyYWlfykTGy5Uz5PhYtn91m8Ek57hbhZDr7URxxYv06wmawwy7SvtBFvuucAlY4iiKswhYJ+gOePL8aBImpN/m1Q5NLeIChLBrrU5ikHXkmboewVmc1m3Q7B5sSE3K5+RkM3KM9JudZGMQfuVaj3UoT3GJZZHv4zBs2kWB2U2vqZM+FUfxIBEAq8MeJgbZcQIEdso7izssBsfiMLug+R6qs5SseikOtsEKm2KNJ9cvFFOuo7MYWccpgNIvhZIsgZ5MxyZUWWD2X5g6kdlkEiWuVjvMl/skl5E+PxcWNy3iyiVZ1KCP462trzCtHyxTJ41YutMSpGGdQ0mXPMFgTvHsq7+LGnc916kTI8UIVIWpk0l9r151LlTiGy8kgOpdHroCSLW27MBRRqgzxxFGqRUA3s6Dhu4WeaNO7m9r7D+2SJuQ61ZSs7z+pQNOh1hNXSh+MupumlusKlvHb4EdNtUai9UOXVeE7ddqWzGNWU3ul7Qg1CHJ46GmpIsYJnEKongdnfHMTB0zLnD/E4t3rDQDzGYveQ2MXRTFQJ2IsebDr3I+ci+GQiPJEnkWKfSJGv8yTh4QALjtKzSFsnQz15+SES2autzWcRp6nad8w6SrE8NuFTUwB2DfkMfJrQc081t310jlKHyYRPrCaequ6hbz5d4YLqML7JmWK92RKz+QEzWnUAl71OIIXOttg5UpHSTzMTB1J2g4Wtj/fWKeku5SFmn5SXHMSDFnGVvnwmk8VkyY3vVH6hc3d7hfJfTWosK+WeCwXQC3U4srfkxvgcN2gT1FAITtbusrTPHAX5KkHaculqC+i8d9gRQFEKOOhAFYYI92pWNXtl8TR3EOm4DFc3mGGYpiEbavO8RdDmIUgdl/HifeeDZJNIIfUmaFQ8msk6p4nOlYyzVrBmi5JOMg5ow6IIVepX/HwvThIyUZdZqgl3MWZX0JESJl6oSl20MThQBJ/tCsetHUpcx6mT/RkFkv456vCDtNmK4hra4GedsYATiz1ziHX28A3JxCuZs4j84lpnWpX5yujq/TGVmUv86yTjfVDMvqYNceHjOxT5T9n0MZ0MsGHQBcXXzH74J2/IVfxHuf/gHcvfvThj3i3QGMF+kZmCZ4RbKYykTKGRpMyYpHPRZ65TYWXhTw3WGBtq8i+E4UfL8Bfcy3LbDbaoll1kMgagVTi4bHvgF2zpiTUMny7sHWqsMuLWIzKTMwAF8Fal70DJREtg5lH71p9ah9qr4BXsQQGjAUorIgdeWer0IVbz8pf+3dv4df+PSfxf959b345U//IJ6/+zODayMOQTLovFedGTfK1PE1pRR4EMMg46QrwkIU2bq+KwzASrhDHvsadi1m2PULtM0MbWO3CBPw3WKNTbU2xguehH6a11Ffx4knMk66EEpWVyFWw1/uh7q6GwwZuhsAqyMWq10KFnvgNMCbm0Nln1g6DjXmwpa9u85m542MeNnfDjFMIhnnImX46rv/K5pf+hXs/u4X8Yuf/hy+9u7/At4VYIEd1ncHNWQ8rsj2SIeHxCrk9Lq+DUJrtFjLfW67NDkWmxKpKPV2ocz/CJbo4xohuYJDclUsvEpfGMfKsQE298BRfreUAJIIgCspJf03Kxosoo5OkiOYGZbkkgoa8ubXi7LHtG7jWFH2RZKvck506tMxSQdnRPMtsjLC4Hq27vm7P4Nf/vQP4hev/hX8wqf/LH7t3b+XrkkZDbqqac/jCeOK3OJc9M3LOtLYEGcxOgRtryydIDXjiNfU7RAwZX8/R9tXpny/zJEN1jgxpsTbJEYBnqyipMM7jJ060bJOVAjF6wc4krtFlm6x2qdfMDDWiVQYz35VXDnXGLu1JEnEdGb6WVdHTN2m0pJkgilyjA/e/Wn82qe/HwD+SPYUz57Z76LWfeU38Gtv/Re4xl/E73vzO5OxYXQvHFKTa0oLdNU3qIphssS5DCpjzI141j4bK32W4L3BDLvtXBMjckwd1+/ZAsftHLtnC4K6GDbK0N+nDthTBuqCQTgau+xVhwy/UJJhVszQF2G/zqB3adO9ZvUps7RITIFn6xoghpG8JmgsvJ3YVM+4sPbFgbCwl9K3v/zuF/F/vfU38bALcdvjV34T7731E1jiP8Cn3vwX0lUQeDNhEl89XwBL3iNMKMb0LxSSlgVaMoK7wH00hxlmVWDoJExSUn82tLgmddZhZnQ0uyoYcloSJ9x/8vrOAvCLwNaVhzPg2/WoCjXcZYFNXrUXNLvw63S1x3y5j46BFFA9k2h0ySEa8ai1j9ks1/BrW09RV8dhmISYus1yNVj0fvXdv49feeuv4xTHS/uVr+Ifv/V5fBI/hD/05pOUKDHNLcjstR+CQLyiPlCHMZ/04UOvAz2Q9MkI+y/9kfqgmcWwK4a4wtmnQMKa/f0czdJuM5U0is6w20fW99gBz6QA8Qd6v77fYr20bJ0kQojzKYaPLa3dOqauTKaIOIuJoUrjRJi5c2OlDGWfioehsxg+rNdP2Lp4k7Nj4+HX3/27eO+t/5rGytfwj9/6PJ7hc/iuN59CStnMDg/qBObCr138bnlPT6+lt6ixYgw74yiG/VKFrWuJrfOMufyeZMA3MzSHkIjSdQWK694Yc3J7/2mNp9cH4yhiGSpJJCacx0lkHTmywxGAu9WTYfKVD7/eBEdxUbCzmMtY1fkyhis+e3wsyc0TA9KPpzro8I0OU3TqMfS6wzzhsSRK9Cjw/N0v4Gtv/RWcdgeMtY+YOmqnXYMvvf0/QOpriZ9R5zwiXqzjrej66Em0dCltpqQ09gYM+BLdKyyDD5NYrzpU/04snRhxcst603KbZqHQsC/xlPcNsO+BD/po3Hm27g7GELa5lPvE2EgCCodKLFOnnlTypsoes7hH7FWsFC/9cC70mgzUS4wLhQGCR20zuX7+7f8pGXQ8Vr789n+frmuavn1vWbjcwu3GTfCo6ZxpjAAKDgq+EwqLl2gPYfG1oRK9AlzqRsE3jJfjYYbdVt8rwHuLm6FXTX024QXLGXZF95BYS7nNsUO92llGTm4fo8erA9Y3G2JW7O4s3DfnkiR41wS5RmGM+GMomHPSUYMZmqLShTkzboLuZRXZTeWd/+nb76ZFOn3XrsU/ePtnUKFJmtMUduXwK7F0CVcGabqO4QAAIABJREFUfKINFPs2SLxiWQcwSDAyn3WOYnOYBdmD4AfjiGfr4k0iAIwpPcpsqP7YhaLA+z5GAVi3fIewFSE2qRqBYAprNmc0zhi3PVPHY0rYuiIyL35/bekfXrTTWBHWMceyeDyJN9mY3Ydef+Xt/y47Vv6Pt386ffcMLabiBAq2eNauwdBR7DHc/xpeY1gGxy45igAOUzxEp481dbb4tNYjTM5irId6jPf7e47FCL6sol4X9ub0hwPDLml10+wMuFLtorOIs0yddxQ5vM39wuw/4Aw7Gie5scLH4bWZ2boUAeBxw/h6DWyup0ZPx2WofvPtv37WoAM+YuoGbf/eN5KBMY8GSTJcGHyl0WSTfS95sIwBZ3rsQ2qxeVGzN+x4MWoxQ3uYDVk6BtxwkNBukbIQ980C+4r1QJUplhm/BF0XxPH7+P/8PrJ11DfrZoNVpSESuefMKTYfOUstlOAIXyj7Dib5bTFDW87QU+FUCZP4EKz2cXjlVEavyHvUwrw4Y++01HIO0uP3772PXDu89w26zjE0cDgOjTkuCSNeJIVIgKhVNOdvQwFGSyEi8xLAYYKHcmbYugKhwLXsx9nQsrfrQzHq42EWNjlHqLK/rxvsliJoVsPu/ac1nj6NXvUzBK1TKrwNFSXriaPoZFsfyVSL0C4FqW+m2gcmS+2I1U0oWyHLAEsarHtDZs5ojccuJdTINco1Pp4wKWIuHKvATA70UhF8NfSqMobmva9nv+eD9+4SpiyanYYZJQIgmX7M8h44K9/uVZlrA0N3jG1w7L9flEYdxRxTF5OvsArPP2wXaF7nfRAyzmI0PLo+YMoewNRjSsSV1ad8skTI1A6HCbUWBW9mNNolAUsyTnlMMlvXxHkguwOM6RZD30TWsTpqodgGeVwhY2W/miZ8ZWZ4bKxs3ru1RmXOSRQDTy5xrE9njLvU3YwnRChQLUOOGiRnsW6xq+ZZUoF7c38/D9EUqom6AzBf7o0xd4vXsMUaePp14CnUoLmDso0c3qbzYonLgtyoerXD4SbSxbzWRabu6ubeOIqKK+N4AMCVMyEDLq0/j2P/eT1pUene2r74djTsNoWOdg5hdyjQvffV7Pdx+8ioc23xxjOjBzIFHzn8Kk3KHES2xYZIxtOeWQt0rkmYJNdE99IhApOwQN6w49IRch9BebeVZAlNmU4p+9SOnYIvEHQwC9YBbYOubvEJKWG7T6xbqKMW0I6hXvdK3cU+EYO1jCU2wu4ILVq0dZv6SpNHLukaiiBqZoOOjSpgYNQ1FaDsQgC/5RtPcf+VF4Pj1298LFwjNjcosSQZbpwoAQxDJO7yWoOOHQDxqOk7agCHqQFgPY565CJab6MXjUMFHGRv3Wlg65bz3KZ4IVTCAMwGKtXhklb2kkmuar4FdsOC1JyltjqivglbQc3TAq3JATmBMHvU3Ey5mwz4sgPApSXkncLQNpgFgf/yIVwjynY/PlHwZS1iiwrTNz6B41eG4Hvzxlo5i/uHIYsrY7OI/RwzQ6umRVlZZi4fqld2YcD+j5R3yTGgqW+7IoyTMUzx4S5532GS9EAylzoU+ttovBzjx48IPvPT+2Dc5SIAuryFnXt6lChQGENOJR1NcmrkeoujKDv9FIiLM+0OULo+9i0ZRJ6pA6yj4hi8pqiMQSfjuXrj42i+8rXB96zfuKHr3CueNHTPYwawRkKmeYNfpAsPnv0HjLNYlD32hZIJBfWnVFxoDhUeDjPFlDJ8fn8/x2bJG76t8D5uNAnrGYCvIYx3mWMFhsRCJyVeqBizjAsuSM2JaDUZdIVGkESM4vvFRs8uh17l+vjMcY/fXH1ARuqpPoQkLFmTohNwf32VqjJ6XGlRoXzjk+i+8hv5CxzbR+FXaleLCv/iO3/aaIHm20zBR6bB6TY52FR0Hx70zYBvor+1Hpuvgp/zqHuUaPsq6F4YfC+GXsPteFC9lcBhx95SgTTROwSjboMQMjk5pg73MKFXFbS26bFl6dRrEjmt3fQqTOACwYir6jZNKMuEeiG9MjptfaWZpjnK+wkM/S0FH1XcWuB73vkzuFqwqCqMle9+5980E7pEHxw6Ny7MWHFC5mTY+bHBxhwxUjb0qsd5iGHUtq8o/JoqewVQ6SsLvnIekV3ZN7p0Mltn+kpurgQMrxcT8qpn7hovVjtc3dwDN6eUkYabA+qbDdbXtA9qCsuzlEHCYJTp6UKNZq9ks4/ncP7YjNcyGXRcu3FXLXDMhF4317Upi8thqU++8xcwWdgSPOViij/5zr+crsrEM7k8LtwWWkX3kBhLwJfTya/gOfY/fcbtJDH4rDAMMk68pMNjDN/Hm4jsmfn0IbVTZP/FsNsD+MCXArqPujpwSL6lXTYsVig7vB84B8zSJZ2iJF2dyXzlfpH7o69f6EOvdH+qdccRFs13KPAd7/w7g7FSLGb4V9/5gfTdpRh1Mia8YedD9hdwxbN1ALKYkpzFg+4OwriSXLbE/E8NpmAbnUWXKLHFGrfVTTDoHP5yYon346qmBRdjFinPothhdbMBbg4RT07AzTEZdOtKGV5ZY846MyPsvw+9MvbnHCyOAPAOKw1m2C2vBmPm+CQkSLCmWUPdgWR47Z3/cDBefPuIqYtt+h2fxD//zpv47je/CxW+lAyPgZiZBc3imbGGwRl0uQSJQTFbWawzbUyEKa1HEUKvMqFyoOtTvQ1A12nQJH9XtkjiU+wVfDsEw27fUMJENPA4DCKiZhEsh0V+yNTJJBOmLjCQlfG8W8ziFma6KF3WLBa6M4D3qKUvxOBbAseYycg1gXoU+PY3vw93uMY/fft/xPG9r2H6xuv49nf+PH7Pm58B8Ovmmk8SINK935FDWDoB4Mw17ejWmwtBN2kHAOUUx7IPYyECou7hWWDXL7Dbzofgm5jLSQDgaqir++BZLBjKTF1Pn+UsWAqVcJ15CcGuqw36VYGm7NNm8FXcB1iNub0JkbC4W/uIDbvzodccq+X7W0Ijci+G8RobtPUVyv4BkyoUnt0trwZs5garpFlcvfmn8DHU+Maf/89walrMv+Nj+L53vh9/7M0VZvglpGx6Ds0L6yKFsYmVKbph+ZwhQxD7wrP/CVdKE0IKz1inkRe2DkVkdKG44mUdcv0zuLLbztFe60Jmwq/OlpAtooCgrYPDlPoemC+lEiAzdXu0mA1YOnEomanrURBzLM7iArOiUVwpdB6PtXQVyhgBWJkO1SbJNLE8BZ8hM/CfePP7scccv/H2f4Puva+ieuPj+J53/gx+/5tvoMAvJ8doYNBx+FUYrjOOoqcamNUN6w8cUxeO+XCYoRGDt0LEak3ACnuLC/NP5xCbFKTeVD6PeQ08iaVNnobrnMgziQCwtCNeEs69FZ3lHDs0y+B0N4e41pQdqrrFulLmn0vdMK5oH+kcSufvGDufTT9WEogjABJ+FUwJO/bsMVtuQ2mcLhj+7Chy6JUzjRdv/hBuUOKDt/8a+q/8OnLtI6MOQPVH/gB+/8//DbyOr6LErxqjw3jR7CH1CAOPmRliKMaaWZh8KZMEkiWANj095jWm5aorrEHnDTuZaLwnnjx/UBo9KVGklo4DYQmTAJGxuyejLnrYKo1VUbMUpJTafbnyA9yMng4kahVtlAPfc3WYmqLCYXlELWAnmacCPALMUfeiBTV1iyMA+Pibn0X95r+ewsghZPyc2JN4PqKJ8oydfJ88ZvAjELQMHZU16QsKp9nPqJNRYbeNfVGrkLfvCxd2xdCoi9nQm2cWfG9xg/eLGzx5+nUNlYhRJ86CrysFvdbGo45aqG5ZYFa3yaibFcEBYM2U7Amcv65ifNiiw1JgN8e4hMf5kCXfVNisht2sagHsUHQP6MurwQLlR7yAb/3f/m2U6PDHf+7H8M/hS6jwy4Ft6hsr5RBM4TFCoXm2xS5JDrgvPEvHyQBjc0ccibYXRhfncUW0dDW9fgjZk7tr3Re0Q2FD9W7lEVz5ALEeJidM3MPgiTD8Mg4YK2zKVwjdN6gSUyySDmF+S/jxQs9nxl9idOspquaICWe1c3H26ESellqcWiUd1jx/+ua/htWbfwoztFhjg9fxVRT4f9P5xAujc46dwgPUEfA3uqbh3D37L8lXZfZz7CwKQvdlYXBF9bmTrFGHrXUWtxFTbnGD+2e/iuWzBw2/imMja5UL1UstT44rSRi2RUhqmtXRqCuC/EPK4Mh+yzImuB/s9VU9nQ/BeknHpabXWHdnEfJkhzmqVYM+bsnZ1lPDZlrDbmHGzvLNH8TyzR/Er02++xdy3/uRUedaAZu1l816Zd0EM3XJo+4MMIyVHwAIfDNjJBcmOetRj4VHzjF1B5jBltLeM151SpRAqPy9AwZZWIv7AxZLFblLKFvOnesAMgDL79LSA/K86CjipvVFZfoip39J/SJHEgDuMdB/CfgeroFdoaECEVdbYbN+kL+PkyUM+DJQcoKbgLJcEzpvuWdthinb4Q1BAcADko6lIfABkMTgg7DrAICnpIHh3UnXOD37OiaSLCHzgAXaPF6IseYKecHgX6BHibLoI5sodaf2yaBbY5PY3dCvBXYZr9rvsMHNlhwYsrrhGIHDEWbYj8wdFol1llBbjyLD0tkwSYuwfdX1X/r3cI279N2pH0TS4VmXxJpCHYOOw9mMKSN6Lwkbcaie9Y4XtjdK/SK4ZMJpsGFWLsFCOl1sA8PDDEOLyrK60C3mhK0D1Fl84nBXg9uxqDnWxuHjRZ7DsvIb+4gHWhg74EuLKrB1KEcXamH6mNFtigqz6ohaiscWUOOKjLrN9RRaQFbPjBl4b1jw98pakhxBMfZ5jMh16On1wTVVLBkYeV7SwWOmDBf3iID3VR2yhkX20B6qkKA3iinqLG6wxvuR/d/EOpjLp3cq7ZBoBidQ0djlvWxNYfNo4Bfo0RYzgz1s0C2wc3NnBo4OsaTDN3GILkk6mKWTMecNuj3C/j2bYo35cpeMvjFM4VC3fPe59pFRFxsXNkxaoH6X10MxTSyTKHnVPcoiv4j43QFSmERCJDIZ3FUZq34tx0oe9ZhhlzPq6P2hrpTd5yHHvkgT426PoKtjfZCGSmzBTwFNLkjLMCdieJkIXDm8Qos9GciXklCkX4T6nhUVimWPBR5CAojbePtAWjotZzJL3pEN+6lQOGfYpX5mpk76GlCNoveK6fge8JMxyWES0L0cu0TwrIHEgiE+fvBhVw/AcVxsb9fYLReJpbvFTQDi6ymePKU9G3MZsJwsRoYMl5OQpBgxfNioE4NOtniSMdGiMv3L4aNzjbNecyESXfBzurowD/aR2ZHWosoadRusE3jLeFl89o/hKb6Kgtj/Ck0oT+G1loIpB+iOADROuNZlbvydbc6wk8/yTftFdxkweroctvBxHVMXyiVVtKjFTGJhX+jyia4OiLjShF1LIGWjYgRgTnKOWeTfJPvVFvRpzVgLXVAQntgyOdKvhr2jmZiyIY1hN8NuGbypqow7j8g1LKKObnmFXbEwbIuGX1Wcf6mVfW8NNnEK2aBjti7TrLExIl3wuCTGIwCUVR5Xtos8prBxSM7iNhp2gi2fvL4L4dfnUKZOuiTD6KqsQyUdc8faArr7hJbB2Q22jsvNH+6XsdDrpWx66W/GcpY3hRIxmr0NgFi6VdzVh3GFygLhI6PupZoM+WRsSHkK0b2MhdJoEozt4TlYVHryqIHBZMzVksoZiX0/4lHzzbM6nqk7VGiXsvtAGHzGU3IALGFYAeAFsw33WixVkiN2WKRFlOvPeaaugGfqKFHCeUbMiPpm312qkYodiurB7N7Q1ldoqpnxjmTLJ69iGmtmsc2FQQSAgYETwJc0nznF2heiNjyACwCXAOKGTA/Cysgelx58vVddA9jW2PRrbAsJv76mIdjrGIL9ANZR4Hp1sTGkcWkT8TYFfL3hJyCc86a5oLL0yVnwpWUsfJfVuMo7CrNYq1EfmLp9Gr9AYLVZR6fjxiakFEWP5h/9E9zjOYo/XIIF3gOG7pLR3w8NubMLig+pDRbGy6Gjjh2IHK7w9Qe0+OtBX7cVxSq77+VICLZDjACIpCNir0YANIGmRQvRd0nJF6oGltheiQLw8zYLtkjvu7RgJkcRsRjvEujLNoYGY/+XIZy2KzSctie2xc9t3xjnS/Raa47HBTN1/jX3E9SALM1zKQIwFro90EHKCdDVeKiPiiuSQT9m1AFpvGxv1ykLVqQLt7jBB89+Peh1OQIgpynEQuwmqS6hxaZljdknI036lF/TuoXqnAWf1Ideo+vkazyO7JkcHg9lDBwBkGiPOIshVrFL+CfjgGuEcqawFG5pUKHvQ+hbHJmx9pFRF5uvgDVDi0qMOGa22KgbWZzHvOBsGwm9AhhoPcJ9F786DJiWQ2o5j7oDgFP8ron9LfF2PAyLAiTg9UUgETdzRzTqDsDCGb7M0gmAsiclIVUuecF1yCRMMkvalzCJG8zSElzSjfuFPWAOhQFAXxWYVbbQpyzi26hfEPCVM78UJhlMar7cnsnl51w7UR/bFPtoHnk9XY6x4+/tpkA51edyBl0mVIItsLldx3CJGi23uMGnnn4dUwmVCOALCGeKEFvdSzDYZG9IYW6FZdG6hpqdxiGjnPbr0k4SwGVWSwC4h+6hLOA7xw77WPpCzoVrbrFnnfiAfoH2MMOsbvH8P/qr2OCI7/m5f59wpVGDjkvbPMLofwwz95g+CcfiNByZOzrOjaQjZ9ThhGQx+gzZ+P5dv8C+0JB0U82wLA9DCQR0GKaySYwp2xABmC01g14cBJkr4hhyMeJZWji1Rp08z2FbOQaPlRyzy6jTpnFcoK0qFBX3o4rid7Qo73F5H8/Rc/BrDmMLMIorfWkZI+MoIuMk5kKw0mpYXGHjcoypA2Jd1OAsbgrFk+QsPvt6qH8pEQBh7DKZ9fJLNClmj31kZIX9AnT3CU66EkOKI2Y5YqBjg45arpQJz59B38dxkHMWxeEQ5naHBW5xk5hM1ujuMEfbzNB3QYtcFPnvS+d59tXfhS0ZdGhCQVjxhpj+5gHvJlvRPdgthTCkS1X7khG+j4RJwuPhxUwedY6pOwBWCbcGts6z2gI4VGmLI/GuDftSAmURfr+f93sJAdAuGwKsunNEmyaSTkgOlWj2aw8NkwTjL7y+x5yWXxtOyzKY8V28aX2BLjFF6ToYAFZCXww7nrqXmjHs3Lg4xf8nOZat1PNh8B3VviBzDA6VuOMOvPsxoy6OB9HACEsXbq/h9nqFjz/dhlAJi8Llu6iLeAlhpk4KUeti3NBY0Xvuj1wpEmkpew+A7N/pt/CR3szNQwmvNaiS0cnbH1UJfHXLqbHw6w7ztP1a0RU4YQLg5JyY1iZCcHheMkm9Y9D5xT4P6tIvpu6YHEOuS2mdId8f0mMPknzlx43UvMQGAVumAJ5kx1Z7mKFZ6q4DPUq7Y0Bh4Y7LmxwbaJg63qTuJUszgk9hmRvFDSm+jYQnzPTwTEv9c8Zw5tCrDeP5kkq6iOtuI3OoPtfpZR+BLfHNA+P/1AET+t+fvux/nXMUgWF25wBXcpjCuJLDE9aHikY0ZkRvrtcq6YjG3etPv446lwGbiRYJnvA6rZrtLl0PvwaxvpLZf2kJ5/t8vxSUZMS44htfV4kA5JzFHeYJfzxT55OwQimqKFfpilFZFF+ij1psXkuRAMUP2hz7Qu0cQ+fTqLOlTKQY5sg2JHqsGMLNLdbJm/4AsV57/NSTDFs3SSGSBL4yIaNXPS3D3nxy9ke6mXBSAyz6sOE2a1iUFueM1m4QXu1QoIqhDQ3LGs7qYj+zNkpCdsz2FGDTUI06L3iXZIucR/2oRuEziaBM/emSU8iAzzoe4Iz2RcDvAE2YACyo5ow6Bl9+f6wvtWnW2FRaBX6DFW5xg49fb/OhkpGQmiyyukvLLvW/XD+taRg0U3KdVI/ivCTEa5xJkEjdemHu6HGInTJetdar03MJY2VL4Ms7Skh5h74rTEICYAXehvVnp1GuA5AVvD/mdwxajnFx5zQ8liRaYMRR3CFgyg7AInyB7DxB7J7IOljtlkJqcaxMocgEqAt67ICp6ycxjHXnCA3hC86U9NiykGVibyQCEMbm3Bi4jCm5EkktVIjPbLPtcjXqNGdXykZVBnsutQJ9IAp4LDCB1wdszjZyFnllS46jlO4YC79KM2FYDI06/hxLCRhTboHD7Rqba6pVJ4bd8lr3mGZskvXHDW12kpj957EseCLvYY1uOLUie+3GdqcBrCSKzyXvIGkIVnV0IfS6xyK+WiZDNO2LS4kkiendht06QoJKPyCNfPvIqAMwkfAk9CINwNezdSMde4EZNW1QooJpZrO5tB5UBgOgjN9gQiXw3bsbAKyHOogtDPAm8BWvugDKEjaDk07bfH8DzA5HVEtbEFQmk3jMwlpIX8uEE62MgPKYqHncaFZDIHjyFSR85r1pb9RJJSzWAcm3nvOos+fiF+lzrQw6HH9eLGo215kvAN+zYecNLB4fnbuP55DGzm0Mwb6uIdhg2MWadS9izboOAXB7DEIlnAGuXnPQvsi1ltCrAO+whtTMXHvt2sfBFo8Xb9Czlyz9zl71DvNkJABIDG+u7EDKUJPyDoCpFcdJI2XvnEW/kGaMuVwb09To/sDjx/H9yYudssJlnomJvRCcReHVSgALiz0k62ChRSosKyH7TDvCyToirnBoNVUnADvjVrMr2AGE66eMTZcMO/msD/FnoyJkEDWYxffPsu/jWod2v1QplaTJOfKZ4ZHONGL/E1uXaYxdjCuAY7lzRh2zZYwTl5i6XCRCnMUYgn0/snVi2D17eoepbJl3xllk2Q1rI+U1wCZTiJZOekAcxDZdv0yfceHu0o4Dm9uaZ/6ZrZN1iLNgd1ikMSfXSJIjpJC5MP/7ZhG2XzvM8BBregqGjrWPjDpqNk7eWyPOC0B9y7x21vAYSZC4dG56jHDpHnLh1wS+G1imLirhDovBROSNmxtUIVNNFuo6eIPeRjBMnRi+B6Bqgv6FEyZ4IWUGTr3mFqKWU3D2hl3wr0J/DMWqvo9lIS5QoM28Lkcc96pnZuINr8kjL96j38amqxqRRvsi996g86HQMaMud88edUykedgusHndh2CpZp3s1RhOMBh3XthM11iYukX0kPl1AV4uGCt1Ghu38qfrIYlGwAB8OUmC2ZocCPNxpZ6Z3Av4ymdtmGRlDLt9swj7pMZ9RPu6xSQutYYn6ZyGwYfqRxqXzbkk5j/XcjXZfAvJVxkBfJJzCKbwXhCnobN4sEKLPRbqLEZsmTsdeuoaxl1i6nxJJGlaULiDjwCoo6i6Ox8BGERpuD+SYaSJV95JDO9Tw5j30t5gBXZxLyVenYv0jDZ/GeP8t7/Ohn2znx1j6hhb5N47iv5//rzT62qyRMCXzfU3wnaEsl2YlDfJaLoBEKa0mEfCgnGFpRxs3ANqfOWu30CT2pVR1uGNu97MxZyzKGxdcCiE+Z+n85SIlKw9G2fQbbDGbrtI++mixsVtReXSfCjbZDL5TgCfA/DsdDr92CPe/6MAvoyQII3T6fSTL/N9llKNBpQHXl4Ac5Moe9wzSJ3TM7jPjulfwtudlzUAXwmTSM32aNR1Czv5DkDbzNBWUkdnrplqon0phqES+epTB9UfNmG7NN66R+pBMYgyCItnDQSNlWhW2MCW/70Wgq+b16NJrTl/DTyEe69ajFv1CV8x/Ert2GXCJBKGKoC+vEqLRzhH/S2AY3X1B48D8MsydWzYbQHcTrC9X2OztMkSW6xxf/0cy6cPeoxm5Duh4CcMC5cSEIPd6qRUzByMqHnm+vGCRMxSOb4QnlskecFjtjok5izS5zlM77V0OzHoDpOwmHYFnv2V/xjfht+In48RgMOD1T/x/TeJxiFzr4RJvho57jnDIZsRmXCFmX826qKzaHBoQkxduE9MXYwCsKzjSOdwlHMXzW4TtomqqpawQZVLMlOF/VdHsTPYYx1ERoHLc1zGR+i/cUwBkMKsms+tO9X4IsSvLO/gJtdYnCrBFTqngRnrC1TnnAvP1nmjjsdHju0Tg24F4NbWrAss3So5jK9d/2aohel3ljiTWS/rhfw+eY2dRI4EhfdZDJLPSssV7gZgdLrm+TPGva1ZJ9e/Ne9To27oKB63c+h+uuVoaJjbh9Kom0wmn0XYGfK7Hvn+HwfwD0+n00/J/5PJ5HPy/2ObnWb9cIByy/XcS/RmNpvxzOflnAYGhgiavbc0CL2SUQfYRf0ANIcZmoryFWVXiQi+kxqYQ/k+cwp91IqR+Js3CBIjLuhaGmOsWvNKw6Tec+b/hX4+y4SihIioZaqH7vZ8rBp2HILlxd2D76O8aL5MZcagc6yaZKl5I7JHYbUvcj82NuUy54y6cwAs4VfyqnfbRSpELGGS93GDZ9Uay+s73VlCvmcQglWmRDJgAaTQFYdJcmJmXqwHwJmp+O6bL2niGy+m4kiELOsqORpeV+XFzBIiCXsvR/CNdRCr7/0MXsOXUOCXUn+U3pB7JIsrv+elmncSM5qgnB4sfdY7ih0wNOrkuW7oLByQjBhhv3OyjrIJuCICkdS4rxpgdnjArOLcdC5QnQvBqiPoZRwyJmfRKOCyOdzPnssL/TNLRmAOoQAkRs6GYOfgzNdvylk8t/7QvQ29uhC7NM/85xwC7yzm8GSwBtH7k7M4xeb3rnFb3IBlHRussbl+Hsqb+GSJeJPpLr2dinlndLreWQQ0UN6QrMN2QzHcYq88mfcMec8htkgoX97FTmJwUnt3hCLtHqEZ9YvoKE7J8Q7Mf9+fT5b4UBp1p9PpZwFgMpn8SwjG3aX2lmPzvgDgxwC8lFEH2Is28KbH1vKX6MXHemZlaU2P3HGCoLkcYeq8QScz5AjgBB9eaQ8V2ms1ZPZYAPVBvepK59cUCufJu5aviFmRHOJgb2poUqlnxZOSF/zC9cNY5lE4DTE9aI1HAAAgAElEQVTSZpjBZn0BYfEemok2BMsaoG85+JJIXLzpAFi+R9w4GQvX57xq/1hazvj3xiGJ4h9ulykEy0zdLW6wvt5geR8F3HKargJ8+LmdWWg7aNjKA6/3qJvIsJxtXZkF3zHxOxv34X8ZHz2kVEWLNjGEBRbpvcHwnw+Yus3tGthOTdjpoSuw+wf/CHf4VeB7NdSczX7Osf4yTqiNaQlfhe3xCUfDjGIMDLTQmP2X2T8P/3dP7Bg7IIUcZU4lWUc07OYVML3PJ0x4x6PsJbTWJCNNrrPPZs05hjmdLr+HWy5TWtgWSbPySCbsHGCNOi5nwsloj8GWHgX68gooHwavTUoAve7MEU88tDh+vFFqMMbvOT4WBfCOYunek2N1O/c5whUJwbKs4xavYVM8x/r6RShmL2sJsY7cdN1oBn1oWboh+7/PXG/TRvZit8lX+c/7BDdxFsVRbBEK6ct4kff4rcE2zTo6ijAG8mNKFn0ojbqXaZPJ5DOZp18A+Oxjj3FyMtM0yS950zzA433/SCAGkKV4x5qP3QOkffETCoDd90FKD0iopAO6qfnMQ07UzF51FfLc5hgZNHwOjYpVeYcOCZXMnKHGHo9kpHGNOg6VeDGz9aqZ/+sNLc8wb4XK+pqUMtF9GilR4Qz4mtc4/EEAW8pbSgwNuzKcu8+MM0kSvq9z9/LYa+v89cl516DP0ObtEoLl3SWeyRY/yzv1qiVZogg19yTEUdIvUgAWz9kCrxaLlaSavEfdxz7JZb7yhtu5UIk9jtUYKVsXvncfv1fGkYwNNuz2TdS8pPptsQ+7Apv/9L/Er2CH7/u5f8saDmMsa2bxSrjyCKgOOkPChEwL+76GF0cdI598lc5VMKWDKmqn9D8Gn2v7Cm1BurrVFNP6mDBFIgCZyL09XhdkHYwLMp5knHEUgDGD5R/58GufnIlxB1qDvQASg68yj+FjDunLntLM/Ovxx7coM03GB+tWC/e8cxi1EsDMOIqjeJYz0jzjf07WMfZ5igAcUx1MW2xXnMUn90f7PTECIGur4kkwkGSNkbHATiKz/0W8PjqGbJ8n+YJrV7FMUjgGkwtDZ1GOw02qMKikQxNzZMz4gua77SI4irwdX50pQZNpv+ONOgQN3Qv33O2lD00mk7cAvAUA5RvfBsDG6su+zwOj91YYiBMAX5g4AIm8kQH3cd3YoHmWLh2LwVeepP0geIeBDkAnLIXW1MES4cZedaMetXjXxy4+RxNZWBfxrDVpgXPIusEkATAAZZ6APHnHmte9sDEnoGv3dLVsHXNHiRHNNP98YjtyRhXIo/YgXMCAvfWqSfuSY3dy40cA0QPwOeCV1x0AcyV4LkVwg9vA1jUP9jtrDKSisuC2mGGBXQK0AjZJQgx2ufI8Rsb6fKxdZPhcE0dA2Dp2NOReilRzxmtg6SaWzaox7rBdWrvZ6He4oof45jVYpfttAOxY9w5A0umyQcePyagjh6HvCjSFZv01RQUsj2lvVFTBqItcn/+hNlmtB1iDK46j/A6eOVauYSMAOd6K+yQXrhcjTSQdnDkvrgk/J/3ZJLwJUYAO4lSO44pvfVkEpi6z9iQ6gpl/ccRLvabeUQQwLJPk+97fc+i1xBCDck6j4IncbgFsJ9g0a2yrtWXq8BybYo318gUmB/qOTAQAEOJA9Gm9eY6RXNaMwJYF0sBjilmrx0qaUCddSlbi4xURxTjyIMo6OS9xFLMs3QG6Ddwj2v8fjLpcePYFAEwmk5vT6ZQ18GIixU8CQP1H/+Ap9x4AtiML+p/DIwTEfXkFYGjQvcwkBiSDz7IUhqVDMSxenJg6BlryotnIG4C2FzVT+QEB3xqYN0h1u+XXTGMYgAG47HvMipagRAFTjDRrvHXpdesJsc87Lmj2zBvr6HwoxJcVkP4UAM7tJiFncYl2Hxh0cVxM5H/WndX6+tDMfcmF+5JhN2bMsVEn7zW7CNTGo05MXWTrZk/ugkEvIFxYtpoXzlkKsQtjm9fTcRa0Gh+PRDRqfvGWZuYQrAPmDUl2IIRx2Y6xdLwQdRNwoQnDMvv1gENm8j+PH3PO3zrIHuvTniUdZoywkygmGA+uk7KEklV/mKGt2FmcqUEX2bp5ETS5UzqiScgS464DjaXGjY8+c1NNXd6ZFEdxPJPeI1B4zjqJvFdFPvBbJsyR5C1+PXsNCHcGzY0Ngyn02mk0/KqG3ahTyK95LLlk0OWwxe0brCWThlvuba43eNIdQ4a9YGala6tcJwm/cn8xU6clknTd5FIm53TZ6bzddDs3VsJ52DUFkCiyJSdYFpQyXSnj1bB0bCSLlvh3mqbuJdstYsYrNf//o1sa+lJ6YPiGbPhMelIE79yMXoWNu1zh4ZF2cfCZSXSkf0aYOv+ZzoqaU/kBAd9l0MKIVw3kkybij0TR9SgKW1qAf4edWFoYkiGIf7s8x6VJct6SvFOjghaAd2arHjsBmbHr6X5IrfsCKfrdBnBlnFSwIMFMTFzYxjmEkdCrPPbgmWvZMZL5PHvVBMAcgvV6ssVqh7I/YhJP81QjZvKyp9onsBVvVXSUUnaA9XQhVGZZ3MFPSg7Nee3LWJM52JnzLFJ4JDe2bIHqDEvHTOf4F+ebN/oZY5xh58+bf8+5VpQd1Jk6k2Q0Wrss5yQ65s7JOkSrKw7jDgtg9cJkwM5rYH4fcEUCuqlPQF8Fixfs5DGT7zHGO4z2Xj93yZFqyCDg5Cox9nNGnfQpRwJyxlzu+iXDriiA4jjEDSn7Ubrn4/9NFc7zMfvNDprHCf/aOcMO7nM8LyK2SMmk7O4sxRqz5QvUYsyLgVpyshpXR1AZjjiHgiu8trCDljXI+mJUs1aMRM/Gxo1/jotW8+sdirTebrDGrl9Ylk4kHR82pm4ymXwOwA9feNuL0+n0I69w+BcYsnU3ADDG0r1S88wceRADzwl4+Ul09qsfUXoAyHjUHoQJjP1EPAhbpbq6wxKonWH3BKFKlczrBMCFHhoAiu4BZTVkSnIGnjQ22tjThnnunJdkdS/yzczOSSJE68B1LN+Wt/YZaxzaSH2RY+aYoXPPs3aPuQQAKmi+NKnHwJf/HwNfBmA26lwIVg27VdCXFQsUyw0WCGHYrojhIkhXWP5UPGthW1j7Is8DKjDm57i/05eNtFEniJpnvzT8OjPgK8DNe3kOWDrZZ1nAtwNOJ4xXhZXmw6ze6E/jIy/p4HGZdIaeeX2VdpapyzmK8TU26rqgAeKKlYapi7d5pUaddIMvnSTnxNdVWDh5bNk3xQkJ93Njw4+Pw8dXbs+G5+R/Nuh2KRFCDTt9v3UYW9jiwzzG5P32u8q80S8lHDnkKo8js8XMIHOVSdZxqeWwosw859+f+5xh6yZp1xrvLO6wwHy5Q9EdwlZxiAZqYc9XnUVNsvM6Xb6e7Cq/SuMoU66xXpETJqqYIMaYJuuckA0p9CpJV2YHFxAhfnlC/zMx6mJpkZfORH3ksb84mUy88fYUwM9+y76kdPduqxt+3BV5Sn0AxrkJFY9xFfeuLM4MINMGk8gbc9yIpXOfZfANteqmqJdHo62bVyEEK3O7BFD6n0KnzIt6+D+voxNQ8542mzjnmmW6FCBliucA2HvMTImLgWsNPwu+8px5TOxbAmD2sjj5JL7vWIFgSLYSelx2XOrvS2ydf9/YTepRGcOuznvUWGOBPYqqB7BD0T2gL69SJi83vSrKnvhaUqEPS3hG5VXbY0CcF2y7T7DsQ6zntU81x2Jduu3E6l5g+3Lx1/5z/L7iyyjxfv48HMtvxgst3icKz8u5hPu8oZfOw3zXcHB4Q0fG+QM7iwNc4XbEYAnxuHJQTZmU9mCDDktgsgTmL1wEgA3bzHnn+pMxJvc7PZaMjQ//v2fd2FHUMkgLsGbXZ1fLZ9XoO5+xPHh9zEEELN7Q2GkqW47Jj5uL7Rxbl3tfjrmTlnEWOQTLJYICruxQrnr05RFFh1TH05+7ZWhlNygOvXbxN5eQ3YV4PWLG7GXbGLGgj0N/S9QokBZaO1UcyFTyhlk6jyuDaTZ+vr8jw6+xMPFnqA7d33J16X4AwOdf9rgDAyqjU0jP5yZSpZ7VORD+VjSjicjdpyYGXsb3dZOwbWZoKmXqdsUCT5Z3CsArYL20Rt0UpBejVnRssCnj5pk3/5x/TV73xiE3b1jp1mCsZfEAPAyt8rGGOpr8+8JjAhs/ZsQBiLXLkjEnHnUZNGg+LcR812OypF8GfC+9PhqCVfDdxtsam2D4VEBVNtGgs+PfAylgt3yS0GsRDT8Ok3yrmowHacyGcn8L0yuhNr7+Ar5aFJT6KRNyLf/wH8SqmAD4eX8yQ2MOGLL/8V72Bc5hyqv1RV6nK78ztayzQKzcWDMG4cRozhrMtKwJJWE9qYB9XP3miDpdD5d9TjuXZ3Nzv5Mfe0dxVF8IZeyFZc4ZdN5ZDJ8d4j3LO7JzPfN/j2KIKbLudMg7A7UaMtZFimtR/xJr0aUIAL8n9155v8MVCcEOC3pvscAuyCjqHYquTwaqNHb8+Dkx5Dj0Km38GnuJy2VZ1Dl8yrO7fXIaw2eVMJCM+t12brV0nPhI86nvirP7v34ojbpYpuSHEXaUkOLCf/N0On0xvuVzCIbbTwHA6XT6kclk8qMxzPudAL70soWHR5sPm8kk8mHX+JgzJnNMS4diOKFe8iokw8PXLnsMW+MbAXDfFUbUvMMcqO9MuGRSA08KJG3QnIwTPzc8I6d6iDx7kvOYxybPMB19LPQ6M6Cr1d1nhpnJNe/h5l73HvyxAqZixPFNWsYRaOupScxg1vGlPMjHXv+cRy3PZfQvwyzYldnSRqr494XtC24MwBo2UbE7b/mUW7SlXXKMyrRF2MtNBOnnlsaEr0eWPGoWMuc8amG+/+f/DbezX0H32cwizyE0ZnFFE0X3fUlhuJE+yPaLizBI7UvgQniaQ7imnTHksseBKUAc6rUtQlmTZSxrsgKwDM7iB2TUzXnPzzP4KHopeXwpKzEXhh0z7obMfZX+F0fRFi1fDLS68h16zMexdNYQK6yhL5giddwomY1vshZ5TZ1hZC+1l1lTxsKwgGZwMq7cTrBvFthUmiSxxRp73GKHRXAWC9XIslEqjfvWljHpkr6ud+NjbOwPyiSJmsZEzi6PMTlXvrdRAGUPZQylbQY5RM063Ze4Dh9Koy4ab19EKCCce/0nAPxE5rnfmibge4BOogxTx2ESy/icn8SDryv7VE/Kx/CHXoW7H/yTVafo24idaQ4V+qUuXqmsyTWUrXsCPLkHurtwiAS+nn2g9qhsozNNe/D8vpcSeg2PWZysCSDsUUuZFc5q5ePnRM9jlLukrPclMOWxIQZx+LB9Lo6jptB8rTEG6WwbY2u99iX3ntxrLPynEKzoydirXmODHfYooOUlQp/kQiVcdkALwXKYJLz+sp5Jvl3WvnD+tQ5cMezK6FEDWqNufz/Ph0gyjtXhr/5XeO/qHvjsm9oXHFZk5gWwmEIaqbaeZo0B7zSaDdpfsQ2yIkcvBZcgHxzEOouwutYUAbhGEOnGEOyT+1AyqSxo32nGk4IfKtM2hivnGF+feT+GK35xlusguCIsyzlnkY+f0/COGhl8zZmh45s39Ght0rJMNtYx0iHnG48DxpWcweEfy3suhGA5A3aFjXH6AJBxGk5WDDbrBovD2ILXjT3t45xro8x3RrZwrhk21I2dcO1n4GJNySnYLoBtbbGXjboV9eeF9qE06j4MLdUGYvAVxiWji0IZxJx2Ubbde3GRLgFfGX/0/PjYjx53ud1b6Zgde6CzrP4FK2C6BNYd0HVBYzdgLanxQn7p9+deP7fAy7GZpRMxMABSVkjxz8qEX6WeVGgzSPjPn5Ol0fMsSYKT8gooHizYMsavMFi8GXjFwMhpcgCMz9icscbAe6nlNDGeraMQLGeChm16JAzWud8yNIatqazv5HbJsBsrEurbY5wIBWFr2LGD0KNA21doDpWt8ejB91IYPBee7zBcnAlj7G4j5WBMnnUYE1t3SZNKiT6+bwe/RV4XPBnx5oSxpHClsFnC0KX7yNYBQOnD0EX+8I9tvn9exmnwhrQYqMzUjTmLgBiPBVrkGTt57McpC+1bVJZMkFuHEDHJGHunGob9l91xwveVNsNZT9be+8YGGtzjsff7+0wIdv/6wmWWh7JBvMVkOu/BtbQsK0cA5H/u31chFcbaUNIxlHdwy+1GssMiOIqH2dBRHHEWL7WPjLpzTSaSTBbp1BGmTsWcnMnotAy5RfoViYlxrRWD7qWZijRgHjr2QANIHZZALQYdMXaLDjh1wcM2Wo7MV12aSF0G1Ia/SHvyXG0nHzLR5IMZCd2jqLknSpyYUT7nc4YoT9wUoqlmWNYHHRdL2NCc9CWFTDQHVNk6o+cbVvM9H5bKedUvM9MZfAmEd9sFdss5AbCKmiV7Ve7H+o3B1uXipc+NsSajhu5LtLz3rBqjHgV6Nxa6aND9f+2dTYhkWXbf/zffy4jIzKrO6uo2SMJI7RrhlVf9sTI2hqkGYVta1agXs5EXqgYbjNFimmG80MJi6EEYI7BN9dhgYzd4phtkCSQsugVeGtRTeOONoUtjIyQha6prlNWZGZHv5fPi3nPvueed+96L/JjMijy/pjoyIl68eO/Eveeer3vv4fOd/qKg2Y4L8UIHrz8z6BbwA7MWxY1Gf56anzyBpsDZBzapTwYUF4/UtRWWVZ6CzRzFfQC3APclcBuhRlc4zKXbHXMW5e/NkfW9pSgoX/6Gp8wOmS7JanXZ0hgy6zKFXKd4PdAt4JcN4m2EZEy6hOkVCjDkyzf1HYKeHtG6lnT46LipekXLAES9kmbBHrEswG0cYCdkAKRsNIOp5CjKkg/JWhkR8X3+sSl+vrRMTRapW868o8ijdKWSjomYUcfgBkFTVUDN1gYi5QvkHYsZdst5vgvBlCgPgIv9FWIDkD1V8ar5IQ2AhgyhZGAc7i2w2DvOU7BBoThSKHPxWKG3XVoJLb0hGQ+br0CzJvl58q2/afuzsMfrchdtU8W6xDrUTczmPhXIl0HgNTtJXP0BIKbxZPugCG/NXg8K+GQPQvEKtdQKBayxjmKdelzBq6ZUCQ1iRyElm1Z2T6nsUm2RXCeMp8/KqahpDaqq0/CVvle/+dhWtPWpKqYP2gqr4xlWPEqnLQwKZHLuurQAMX1XV7PBWYviCp1CC8jKxbBJJoM6RURqqS7ofJAe4SffTv/kz9TAy25vlkXsupBy7c2EpVMqE0ZQT8h2IE+rlwwpPijTUkrasbxO15+b0mb5PtkrzHHY7mJ1PMs2hSe9UtXJWeDI7+SGJI+yLefAQgYTyLDjrwe9slpsK5Mk1isDGoRH7dbJBCh65fD5Lo7mKdpJZR7eWaQlkHSd4t/LHUViqhE9RlVTFiJp5yEyZ19xFqNzsJxheTxLk664TtEM6YmYUSfIogFkzFEnIrg3zZQwKV65Btpkz7oGUDfZIqEa4+faFv/iyTGkfNGk2VK0UO8RdoFbx7lXTRsucy9RSZVMTbeSQcY91CHoWAqrawqL71WQUrB+T9ej5a5f6f6YFcXXbeq8daUuYEsRRbkMCikaKgiPBeDUTvjG1HwQmwOrxVY2O5AbdWtR8uZKSnco0kefkxG7576w+XDOZ/x5RUzK16c+ytee185NT42m5xc0KMnvEUZd21So6hZtWMF9eTzH6fFMjzaMROp4lL6pwsxOHqkDckOG10XN81oiGcVN33ExclGN5/gS3yDwhP0tQsd0fJBLw5zFOHDvbWFv79TrE6qtO2af5cbtWGSaIY0WXs6wrlGTZJ3aadqrIDmIlNlYHfuoy8mxT79u1W3UK/NFmAgUSyubeH0102H+e+WiPrVfXmp+kjuFJGPSwaRz5sgio+oWhEPR/5Ksp5ZzjOkV0X9Ojmcx+k8L8aZ9uHeDvKQTXf4SbnjRo7ZcvGwLQ+v2jS1oLiP/gO4s8uzLkjuKMvqvOYqWfj07sYNxJbvHDhBeERZ+rTHpUcvUa496yuqk+XX1lJJMtdX8D1qjndZpZwpY7bQuRrio/uUQu8BLT5PyZZE6LKHWFqJGcbs0fi/+8ivMkDoqj7StO1DxwZMbR2myhPeml8czP9OI9lStG5zWbVw0VypgQnrZ3AjlXnXmSZNRRwaviEz46G7aj3YZ2g+/n4wpyncdhtIt0qs+9ts+kVdNNTBH2I31L0CKfgzdR76+VBuN87PfR1/jlZ2ivA6GFG+jGHZNU6Ftaj9Q9/ZLFv+EYb34rd/Evd3/DeBHqS0utrA9P81roLjBz2rMKOJC7VemXmV6UJeLf9DqDfk55N/DJ+TRuR32t1PbUxucRR45P5zvYm//eVarG3dIAHuNdEvoP9w4kdcsSyFKs4UHI5zsGJ8BkM55HY0kvigPpdFOnu/EmsRTAKeLZdQrdd1itlihqvwi16N1o0jZhqaq/J65XFY8cyT0ymEwimhdPF5r/BNDOprFaN0i6JEd5igmZ5HMca5TgGkp9amUI97rR/vi2N8oxjMdE/TKWR3FIcyoE6R1iWZJmewhVzhsKj79o4iLDHdzBax2qpEQdjkdpXha8ZEbcORd77B/2/lniAZMWZEHuoOTPT85Ihp2FKkjI45Fnug1vl2aHDhyw02POmgDFh/8S2kL/vm8oDmklKN3NAeOyaDeBha1V8BNjeUxM+ww7KXxAYS8+JN5kBe1E27UkWEcFDEVjvN18wbr6TSm9mKZbueva5E+RQEfP9/F4T5Pk+zEyRKzUCBO8VMORVWnIouOB52jgNzKZwgZPSeDrm1qtE0do7bJoJtPU76Mrb/589jZOwLwo3QfdQUsTvN9lSmSqyxLsazmrD3LCTUjA/UaJRDlQY2fhxxFnn7lhp083h/WNlXWJ6ndYO+5j9BpkTqtxKXuR1f4PfjHJJ98eaO0qf1UUiYgTSIhI4l0fdyBJ6bRtkV7mEe9AgAV1doNGHZ87KB7WWEOLI7zgII/uGfU0SQJvsc1zeie1GZKDqOmI+qRR450gpheOfpyB4d7efqVnEXAL1fCJy71L5tH54azXFyXFLNoNTB10iI/d/y77euWpqlQ163uKGpO4rq10OzSjQCPHrWockW7hxS5WYjX5yniwr0j6VkXEb9CvY53wDufGqmjlsGVb53tERhuGmiQ151R3dStbWzvn3jF+xLSlkh0ajJU2MxO2llDM+zouZZu5Z+Zmo7thdFRZQZ2XG4ENUujubwQ9dgBmPuk0gJoGzEbs9IVijRQl5j5aMziNI9q0oDFlO/JXkrnkALmu1iohnspUlcyzPhnS+fSKCngY2obu2zm3w52sRsVKXdppKxG69tEu1g3eqfVjdHgWYwaM4OOntNrp7RMyLHrG3IjtS/N7/8Bni5+iPYXb6doSVUBPI1G7UKJ4h6LiEtpCZZRwuC0jtHrPyf+bkh/7LA3dpB0DfrtqfEyJGcx1WLuJp1BziI5P7KsI/yjbEhpyZ/cmU5p09JqBCXImJP1dPQer9FdYY7VUtRb8jTlgF7RnEWu+1LtnjeEMWcLwafNrb18mA4+3NsSBl0ebOgxpAvkGDFktEG8p+kkrawjLKe13Ev7jpNhN8syAGeb3V4aR6a2h6G1L/vlIWzlAhbpj++Hv8/kKE7s8mbUCVLjr/2MI14Xxb3IQrE73/uPpxR7s3XqNuyWyagRw71DRZ7FiF/sgA7ALoADJKVLkbsdxDSJ0pHbtkJbsfVzsIuD6jZe2n+a19S1SA1Pi9Qx75anLwCAlh4hhcPrS0huYwYdr0WR6/hxBUZKsYWfadQ2Vd87irJwAKuhmi+WxYGQ3x8ZkVlqae95btTxSF0YyFaLrajA0szXkZQ9UfKouQJG4b3SOeRn6W+uiGNdXVK81PZnmIfIhl9WQEbnKOpRh0dKb6WISB5tlW2gHO3ue9SaYcfPFV9nHjWPisZFSKm98AkRWjGzwuq3/i3+tPoS+MV/FNtLjLhQf7mFFPXmRh1LvfZro6Txwu6pbhFrZtkgTO14nWipPx/713AdQlD0vy63ySaVFpBeOcBtfLm/hb2XTlO0jht1QseiRm8RZkB36FIpRNpZJne+xtORpFdkm+QR9eiIHc+8o8jbBsluAfh9m6tsYhbXK9rsf76KAumVbCWCJTtYtJ3DeVpntFSnK0sNIkOROu1Y/lj6fMmwY8bdyfMdHL2SUq/JWTyMS08NReDyyGyNRnEo6bhSJkijVLYwldygE44i7eet6RSpW9bx4c51xRuEDHmv+IwjnkID8kkDIfXKt4jpb9pcqAOoG6AeWBxYvcbCT0adKO5eQMqW3tzOX9M6bUiVrKoUNaKBG3tP8/QrkBSLGIwwR6ZM5H1rA5N/vWZyq0c7XDpffhxX6jx1FZUvH5zDfcfVzusap02LKoTJM6q+sc0jJ5SWWWGWz+4DkEXqwoKrh/Pd5O2zay1FIiZ51CVjrhd1Qa50a+V1TcmEurrVnKJ1szBTLUXq+Iw1OQNxqJwgOUH9QbiU2ogGHZvoMobWj0j5ZsYcADT1sEGnpbGloySMgKxOl5wjPjDfAro94LBKi9mOtg1O7/edXpATZSsH5wWA4xreWeTn2wmv7Qy2z+RgsS37qK5Oi9Tx6FMscdlWjRQ+813W5tJ30/ePyY631yG9Quu+rdp5P0rHxROzAV6vtE2NOkzAAeB3TBCeAV1f2g86BAxoL+798B0VeunXLkZ3SYenOt3BKK+mI0p6Ach1h3aekkGXhCkMu21Wc8lWX2CLBifXrwmn7m8pSDXaUp5yLOLPe8Z93WHKVmFDcAO+5yxSLXcp5XpGY+4cH9lsaGBegi3nIdMkC0SF04XBOd+Mva98JxkpdZd5BryxjipxUryxE0qjbgfemtjpH8suq20qNPMqptbIY/pyfwt7+6fjRt2eT5NIJSKVCR+kfLSu3+H4vylFvk0m6/Q5Sr22Td0fpElZxcYYW6oAACAASURBVA6VvGoAaipcC7nztMwhdrGcP/Ve9X44iNcf3vLRXaofSQo4rQDPfw9/IWxSjRZhK0XbpIKF+LukhLNICzKZrY7nWO6n9QzJ8OCpEgCgFZlyWaV6pza2jXyR3zZ7b83068gsNU7x3NygO3bjinfC9yTDgtVc0irxtE4dpSL3fAptCVqwdyfqFr7ryORZ9QEpGzk7v+hEkK6AQ5p8RZCecfmkhqz91FlfpHs6wC38NW7UcUOFp6NpyahKGid5bVTFDLolZpiHSDC9rxk2JZ1MnyPHhI7lbXOFedpaaqhtCL3ShJnVGv3JHiwFy/fi5pE6Go/2KfU6j/p7cuqV/10y7qTDOOZg0gLJSvAgyQVRt6yWsxhlpEl6FKmrwKP/qdaRXuPp9n4gJbWRsd87vw9/oUPZmnRLeRlOPIZH5wBm0DndSbwAzKhjpMaRFpgEGXUNUkdintHh3laWhuK1DFPC/BH2S4zVvvRTLsg70gJ+b0q8FA7gtTBM+UZlncNTPrGDca+avE965JNGwjIdaRZwHnUB0oKNjdIZ+QAjjTnZ8YaKpuk8MQJG08uPRcg7nYz9y6N15U6dX28WidhbYLF/nNoMOQWhKPzo1nY0mlOkrs7OV0yz06NmzGmeM6Ara+082me5fI6B02Nan2snRl12wppS+ZIltAZdxX7p9Bc37rw8c2OcG3aj0SnGUIpxtC9mETqX3/sZjTr63hiJWGxhe+80X5ZCRlvmu9kkGh7J5fLyjyPtBJgcxVQ/T3oFQG7UiXTswH6tVOwftwoLbf94D1jsA7iLfLCnvsL1Ciul4O2CaNEyGdUh8NfG75ZOQmmAL0XruBMajaVYc4l8wdj8hFGv6ItrpO+lR24E54vB/9g7i2QAk9yz1GtyFvmkjsFazLPolTGjruRoSrkEw2Z5PMNyPmNtfqbU1aXof4X+MlikW+TvFh175A5RUaeIkg4tQ6M5rPFvVktXNOg041aL0g3paO3Sxw+5WaQ0iY+8Ra+aFA2L1J0w5UtFwNR4cg9JWTCxbnBSt/B74gyHeim9UCyep8fMqANSpO4EWepVKl/W6WhNqdSpduK+fK/uP4e7C98JKewPZKloxMilXHstyWCFOaiuitdL0Hs8vdFXxGVDjv8tZyCvjmfDHnX2evKqq7qJa5bp31tHeXEF7AesYz9g1cgidSd7wEF1O1uNXu7TOFo3ORSlG/ocQelm7k3Ta5KeQVNn98pX2OeKTqZBlphHz5ob9Hlt4jxTwDJip6eOGmzV7egEozGj8FQadGOGXCn1ymTdwWU6YClrLgmK1BUcRTKGmkx2hRSSTB+p0eZC6okjdcoCPs3IZ7vS33ILq0yvuOz+KQpzgNs42LuFBTmLlH7lpQq3/L/jvbRen1xUN/0c3kmgvVdnyA3fkj6WNb8luZCTGCe9wNfeZqk0oN8u2GunYbBvg9NYgt8fX+Q4OostO3cwgGliDXcUeZ1uEWm4jRl0GHlfRumkM1kjlxVF6o7nWO3PY5snZ/GQ1XDK6D/9vlSnzR/TMf0MwKhOoe+bUFM3ydkkgy4+R1mvcM5goZlRF5DWO3Wio1vb2F6eeMGzvV+7PeBgf4ED3IrFnVwBp7RfnssfpG56Bc1nVr5RAVMPCsZjUJIlBdw2yQPmYfAD3MbB/o/w0v5JP/1K9S+3aNJI8rR4nRm/h2UoqvfGXEq/LhVjeKg4WpML93SzSCnf71Aq4DUjMHJQoDZDg/EhdrGzd4j58tib7MGoo3ZDnjdXwLK9ZNQNekvRnMeo46+PKWAZsTt2fsbfPEVd/JImS1RhsVDC/65L9vE8TeZ/m1kmR/qX2kKh/6xRxCyNfk6xaJzuVxr/8fvZoyKrxb/713ht93O0+HG8H2ojx3vPk8HPInXH+8DB/HbPUUzOYoraaWzRBKx4bT7iUCojkBMJ/MENUG+ntsF1yzHga+gokhGMR7mmnNLeuMNMa5Id4BbuvPQc2zz9SsYuqz+V6/Vp0WxatiNFcJJb0V+Ed1r0V+vnMZvTzkOkjhnQJWcRwNQ6LR6FTLXNu7mzSG0GAGrg5CXgYO9Wtih4chSFI9CrSXX9NjymV6a+R2OmdBalTmm8wcv36r6Ng9DeV+D1ul4ypFdmwXhvs2ABRWn96aus7eXGXUHXNvUk/TLJUeT6peQsynFnQA+PGZpm1DHyqEvoTNUuZns/9m0zCL5bAAf721nNGV+SQqZL/Ln7P/5W3eK07hcdjEWFcgWMfie6hbRCNRyiMcANOVLCqvKtY+eidaWOwizY2/tP4cijJuOOUkchrUjRG5n24IZZFTvaHDTo0zGa8qX3+TX68/S39JLGYIvaD9xDHnXhbyps1n8PXl+T7pcG4xluo95vsVOdoG5936a0K8lUKt9cAYsfZkzxapE2aXiUzqfVv8jjmQJaHs9i7SXfio1MNcKrZL+R9RzLbOCljc/5Jtd8H9yp3jSntO5X6bXBdQBLgzOnVl4PMt1+7acwmz8H8ONY+B1ngO4tksEPxCU7DvcWmWPAHcXJRkndwM9U9WzVKXU1RL9gHLlBRzN1nwNZdkE6iUpZB+3/SkslkVPjncVnuPvlcWp/tG5f+E6aNJK3jdT3AN8+fBQ4Rf95u+IO5rInR14i0m9neQqXfW5KPV0S7iT49y9Zv+Jp69neCsBzzIOv1FTkKO4gRc7zJbY0AyZzAIaidVONOhmBG3IWwY6jx+Ow7FRW/rMTnMV82z/SK4DfwUaL0pI8aUznhnIpWLJVt/43jfV0TW88bqHN1mdlIq3SJ4v7tCtwOfb0/PjaeWbUCVLNRFqDq9pr0daHmB2foq2913hYyenXvD5KN0oItZi7boqewXiED/1IHSlgvhbbLeSROu6Js5ZAii4z6MJGywf7B3jpONTUzJE6b0gr8hl7uRKUM9La2AHpeYrQzFXlq8mCog16MXPqZK3sVHLArsXrrK5uCG6I8bTBAW5jjhXqqkWzf4i6bdFUVZTlURy0k/KVkYcedQfUEyZLZJ8Rr3OFsWDH8Ug0DU6lczbe2OW1lzTgktTzS2gxw4qlX+t4rN+UJC1tImsxVUcGoXyBVHfcX1NPM/Kotzpo122/fUxlYBBcffQ7eLr952jfeS3e81God9rFbjT4AaCtvUGX2kZahJXPYkxlCflOB14m7P7jrOCyNTGYQZD6hP/zX+qRTmIxA1DFpZLoPuheD3Abu/vHWFBKkZ/7pZSO5nsk80Ga4PoEoMXKq6xt8dSb7GvaBCjSLXmxfTLqoixK+kQyYTFxmangNYgHuO2N8z1gtQjOcNArz3E77vJC7SY5iRPrujVHEcidRa3N031DfE5zlkuGYsMzAPNsHM5n0FfhNPq6ddQOKnDdzMuBcp0yFPUuIfXKJGQtHUczqumxJK8CZtTBJxL4DMZUmEqdqA0LDCevj2+TxDsRL07l6T/5w9e130RaGnJDBc2qZ14y6GhWDW8cMvV6C71OTKu/c2+Py+KL6g6qV36Evfo0Repqnlak1cDzWZ2knPzhemeUHZAr39KADPSLmYuKjDpV9hr6SmkiXCnQgEMRiF3s4iAURTeovHGHtP6fbzs8IsMn2OT3WdUtTus2eXua4pV1cdIz1gw7XlPHDbzjwmf4vTepjcuauv4SDfoaaRVazMDXUa0z5csHJZIjJ0YaCjQTFC/t7xrPpw26JSVcknH4t/rgP+L/bR2jfefXmPFLzuIRqqpFs7+M984dKL4HZn8WY4p8S5n020pu8NJvwwclklW6lxYx/apF6qThRe/J6L9sM0i65YgZKbdxG7t7R6ia59jm2fp5no7ur72WUvg8Uk8RG761FI8CS6OJtzHeTrxOqrNr7xmEU3Z8KdA2lbqoOXdI+eLkfEISAKyqVLaQAgs7wlnMjRj6njT+NPlvXfpHeoKQRgf9LY04qVf4ZxSDMK2+kMYO/18y2FPE30fpZI02tWteWsDHZj4+6DW6F7C92BhDUd2So1gjOmlD69iaUcfgSodSaLT+Fg+58oHZ19TtMOXLi1PzAbofbWCDSN2mNMnASuPaeYqGHZB3JK58tbo68X1pnbqdGKnbxSHqeYv2lQPszPtRBjJ0+fprXLkkZBl9+l5eA6EVNsvneSQmV77kURfTbGfsATx8zyMBtNvCIY4wC0YdbztLzLM9U+WC1aXorr/WAQXMPWruJUulWyM3ZPnxGmrhO+0SUGcpHlLAWqQOIGVME2PaaLTx3y+P0vJ1C8vKc2tkjTr52dEZsJIhJUuUlvOAXnNJbYO2VmvZwMwdRj4BJ0/DjjTctdbsG5iUw3UGdxSbwjEDaViqMz4U93mA214e+8DuwmdEgLD+J1vkWjqKZCj7+8i33KpZr1N1QsFRkLKRcsoM6wvWKfw7pU5Je6HejobqiumXfC/m3LAjQ1YSHYC6Bmqlrq60JAnQ7wPS0AeGjRYt+tQATZPS3Gn8WOGI6ZQWFWasTncesgDxvtD09Io2Fsm2T84PjclVmHxVVf3sA53XX/bESGiJUlSOj+lrROvMqGNks5rY4FyFTsRrK6jzHMXBWc4GnLHajvJ6WzzaQI2IIAMnrcuTpwz8DFr0vWnyqIF+AxmaKFHncqBBmyIGZNRVaIEKWO6n6fl8+5+jmDraiQM3L+7mRa70fdzTLhVEy/vncqJHGaUrKm2uhArRqBJ5Z1Y2Kw8etYyKJKPuFhuoyLArK1+A13p0uQKWdSv0vGTQ8XsfMuaIkkJpqlAnlQbXGVbgRc2J9FvL3T/8cgUkJx6p07bbE8b8xEJm3ndGla+MiGptRFO+2mvxGngbSXVCADBHP9qSMgA7sV6XZCwnk/Sjug3auoo6hQzeqm7j78L7Sxr4kgPqa32hR/+BfNcEqXfon5BH21Ro5/lsTuoDZNRVaNDOK1TzdJ3kUGqOojTQ8hmP/hfnkbo8epWXheR1dTJa13fg/D3Vw7VStfL3YEqvBu2yQmMQGftLHMS9UGk8Khl1PGVP59LSzb1r1XSKLMno3Q/6ekWrWZbfVarnbvK6dnIWeVnHUG1ogyqUc7TxuJU4F9ctQBpnibFdJGK5A/p1dZJi9F/eu3TOizV1rU2UmAp1bL5wI4+2zDDLjLpVqAlJXuew8pVUQdny1M/Y9anIzsjTJEBqJHSMFqnTOhdSmpnf4zPcidcTFbFy7NCszvSYrxRO73EvPJ8Nm0ezyrJKxxblBfQ7lXhtLAJE10v/yKjfxSGeB48aQEwJ0L1R/Uva1zM3YPoR3dBOqI3IaF0pxSHvmb82FP7nDCrgCm2VD9SkgKWMZlhFhdsnRW2pnaVBSVkOqGqzOriYWjzHlj68L4ImL8nZinIg4wZ0L0LVwbkuLGmSR+p2kTYqJ8ePr8slI/98Mo1mzKR7SPe/NSKTfNIRM2IoS6DplFLbGqupY8XdqQCe0q+3sIvDqGdXSLPiKSXt09G6o7hCHvGniTgUqaPWRv2Topwlx0/KNHcY0433iuFLjuEaEZb8e2vmDOQBBrqeo3BVZNQdhgWdtTVTOfQbRweAJtb0DIiB6y+9L8s6Smifb+iBRym9s8gnYMn9eJO8vJ6hqC0PFPD0fclJjDIJS1iVJ0kkZ12iGs7xHDUA1zeOh2Q+UM5Qwow6QVK+aZkGwHvUPNqS19X1ZzJK5VuK1vFGozUiuib6bvU8mvIlT2so/Vow7PiMIb5W3S4Oo7lEA3S6rtxb7KdJknJJy5gkz4t71GT8SA96SqpEjeSVPCUwOfU8p9TztN9Epkt5dDbVliWPWhp1NKhRSmmoRoovgKxG6zQvW7tXqUCHPOmip5gO89GXtEjqDg5B9S0cbrxL+mmSPFJXGpi8bFi6TVG+LdL2Uf61YXWXybh075osRgZB+t2zejrkWxzxbZHS7NB8Mg2vA5K6hcuh5dtQCdlQNIhfG38kOZzy9kSz6amkQ4sOD2UB2HfxGYi8+J/07AqzrGyB+gvVGXJHkZctAPneoDxSQ/edZqjLiN1I2QOSXhmM9pYMOsW4JTlLuIza7Fp9hJfepbbDjTpef8nXTNUjumwbRL5equYo+hsvGyP0fKw+mR/D2w0fexpdr/JIHdcvdG9UZ5jGJWnQz7J/Wj3l0O8i4Zm7UnlI5igOyUGTOY+UMjlN2YvWjDoGVza3WLibF2BKo44bdNo08in1O7IRSWVEA5M8V123aYDX6umeI4/UjSnfOl1Lij6lwSZOGgENwGlwIA+cvGq+WwKdgxq+3MNP64A8ZE6KmF9XyUvixdM9ZSaNofi6+HvNXpFS9vNYLyXlJI3flCaRe7+OtBkerdPSp5qxpkURyOAvnYMfV1DA6f7maHEUDToZqZNpEz7QSI+aR6a4sSt/82Ts5jcrDUqufOl6Bwc4IMlYi17IiSVyxl+UUYNb3/8AP1X9ORr4Gb9HYaClxVQ1o45HvGXEmvcJeQ812tiHqswhCX2skkZvHT+nRxeg6xTuKMrjSo5inSIbNGEhzfBN/aVFnco7Av1swa7QC329wgd2fp5+aUeecuXti2Qi206UnxysNb2hOIrTov+5kUnLwMyxjO2bTwjQ5MSdIs34B5IDkJbwqHVnkUektXuThp02qYLajTTqFGeobSs0lb/vHdCklzRe8KzODGkMSqnXvL6yX9ZRLnXhDlBNk4yEQuWzokuoznj2Rejrjqbwt9XUnQ3e8EnpUCSK9p/jx5Jy4QZdX+HoBZlAXj/XNjWquomNSDKUHkDdAIvtfpQO6Dcc7nnLlInwJHkInFKKFIGi92WkjhYV7aelU3Fqvs1LeWDnhmB/mQs9KsdnqklZ5zJDXyHxqELdgWoXhnYp4G2GCnpp2QquCGgmHl0/T9fT41CUQF6DX1tKeNYl5cvvUevtmvLl5xhRLDyqIGtfCCpcptQI96q5EcgdpnzSkS6bOijOqHwL+75Ocax6MqaIaFMY5NLJcznF41psvXoXrjpBi79gacfUNrhRl5YBmuFQ6BS5HIOcwRflXLU9Y1fTKfx7eaQrnqducFJ3wML1U68Q9y+NP1Wv5JEVPqGIonSp/im1oX4GYCc60dzITT+Frle0DEBpuQ/ZVpJBlxyR7Bg5eYmjGCxJxuPlNpR6pOWADrEbr4kcRV7+wrcTk7M9JTTrW9ZgZotOJyFMq6krHcs/I2sxlYiuv/866lVa8oin1oF8Jrc06Lhzx51Fnr6XdYZ8JvxUSuUhbdBLLZuFnoTAlqXizqE2wUTIaEoU0Yw6Rgr5phlH9DofqKjDkcHCDReucErF/TTIxecFzy1NkkgRjuw8dYu4/EDJox4y6niHWvSvJdWupD34+Htk1AHJEz5CP21E8iDZ+cc2dj4eqaNz8zXQpFdNsuFIg06T1WlJAfc8x/7v4WdA9V+XRs0sepXJUOFeZj5DliKZ5bpDrmj4b3O6WALHcz/wpouZbtRxj5p70ppRVzDsKLrVxHtfRTlw+VDhcvo7LUPBB3AA2WCdL0HRj9SR4iyRIjjKrglj8IiolIN6fC6jrbrFyX/6L3iGA7zyK3873gtfc2sl+g9fdJWietywkwvJltLJZOwOwWXDn6eTNEmvyIlXQ5HcQkmHzADwlOIMt8N7eqSOr5fJ9QnXK+m+dL1Cba6/Vpm2rElfroNtRxpvMrUWaizHHEW6BlpMl3QvOX9c/8jaQ95u8ohUfz2/ODtURpMA7ywuXNIF3FE8i1En5TLkLLLzyEhlPv5yXUKLTueGvDZec9lQalqSl0MNr0LBKRvPTGfHv5hDzmVBf0sHKsqn8yVaBeeVn92Ai1a7pnxLRp2mcHmEqa84hmfvDe0kwb+bP9+qW5xqEySAfhhc86izhYjTNHFZqOuNOlpTq8IODmOhrpQJ3waIG2jZvUap6qk5btDJSSdadCHJRp/lFffaXdQ++lJKESy6KNeYulI7t0+K8/rDCm2QSYMKu+E+VlFuAHopNp4ikSljrnwB9NKNpzxlUlK+dG/8EewYafjz51wuPSXMIs3Rq571DF8eNZFKWEb1uBI/YgZvySkaU8DpvOnGZSqNvGpgQkR0gTxlLSPhrG9VdYvj//AxGpyg/ZW/GyMFPDVPAzNvt9JJlM5NaZJESQ60TENpxqA267MmZ3GxnaJ0fImkIaOu5zR2vTogun5KKdKkEV7mIjMA3IGm1QZUY1/RK/T7Uz/TZCl1SjJ6y+0q27+b90E5WNcdpqZepZyorGOGtKxHi/6sce58U0QqyUcxXirdKeo5iw3ObtRxA0UaK7LNRKOlrw+oXcRrD7+xP00b5JHrFKlX8jIGOfvZlzjxwEKcfFUwoHib43/TenklfZQZdmQ8a7V0au3htLZjRh2DGzKUaqQ0at+oy71F/ho3cMaiAykM3qoppKHPx3V1ZKoEKEdcSl51UL5ySZWU+lnhIHrU/v7mzFgB0DNsyWih47NrZyFyL9s8vb1UZCqVr5SN9rxCg6pOM4xPKV1dLPxtsLVYpTWKJoS7pUdZMWOP1wMCeSogpeyTEzAERWDiwLBY4fQYyVDlkbbsg+IR6BtyMlInP1usqUu/RVKSbZYqSQMt7TWaopcyTcKjDtR2VpphR4u2skgDN1yaOLTzSUbDhtBoRJRelo8kJzaIV3UT74y+myIu9Jo0XqRjxPsOrwnjM6V5hIBnAIbareb0NOwcVd0GZzHolVvswJIzJAdpNhDxxY95/ekMq6hn+eA91YHWjLGSXuHHSr0yRaf0ZB3uJ+mU0Ad7sukynUKfJV2v1WslZzHtZ8o3tacSoVKK8Sg6BbnelBQND9nmS0bdkF5pkC9iLmvttPZSN7HvkZyl/gTSbyz7EDfR/Vf0S3rS8mP9khc59pJ8hhb6XYcsIkpC4HpFc6oz+QyXA7GzGhw5i7EfOUnDlFS8pCxIOXFFMGVQIkqNSD1P3eBksQSaRT/1qu0DytOtivLl35UbK2mjdoo++dqx5D1qg3JxoUf41AjvhOm7871UpUGnDc5cCWjGUSwKljO9okfklW9agT9F6YZSr3zfQelRAojKlxQPlxFFMlO7URSv4in2DLum7XvX8cb532z2XcOOlQZdySOP7eUki77w34fun1Z9z9NhuXHHB1+6d+pH3LOmPjg0MJUW7ObnHmN0kIOIxpTSSYvc2eFGDO8vPIIr27xs//Lv4oy7ShqofUdxinxiuQJF6+geZWSXHrXIy4JSjnr/TmnFNPiSTskzALkDzWe9TtEr0vHgsuT6ictlCplOIUFk/c3rky2mU6YMylKvUBaA4A61pld4RIobormc8hIgNWIX98tWHJrMqJuoV2SkLmszvq1IOSQjl8a+GWu1Sa9wR9GfXrahfJeaoXKMKfWO2nXGz6PBWBNKNYwAjrf7eoW/HxxFakdjXFujzjl3D8ADAK90XffeyLEPALwN4KPw0tcAvN913ZOp3yeNNdkg5GwaGnhyBaEtmKsvaklkKSRhPIxFbmi9ri0erQPyDsMppdIWJ8GTbHqNhu6PrxPEPUXNqOODspRFvPbMm5pl5+HfO1WW/Ro738kbVLGAPBYFc4UVonP+YlpsBzmsF6WrRcwyvwY9xZhqe/hsxlJRP4/oavTuCey+CP7ZuG9lUNrcSNEifTw9HQcpGVWm6EJaaJjXNvHonJQLlw0foLSJEtHpKSjOFvlaUnLgk21HOljFtJQc5KScmMFb1y1a0Dp1yYiRfSiXXZUZLJrxIgekUmpN+5vkweVY0klV3aBdrHBK9+s/0B8xauVfHKQbbC9WcVV+fp9czx6BUmizXtvo95dqLb3CGZflRGMOYqbxwred06bfN6VBV8rISLheqdBmbaUOfWxIr/ASIJI7/zzpxSF8+UGb2j3A2kKX6c2IplfklpUEDzAobYXui4zbvpOo6xWgnzbvOwflSSREaTyWEdIhuI7kzjjpmdOmCgZdQa+Qzl0s1YyExrU06pxz9wHcAfCViR+5C+A+gIcAHgP41XUMOiIpiVTsTQXdQB5RKHnR/P0pypcWsRzrYHTO3jnqFrPFEsdNBSBEE7jyHfKqRWpATuHmg0tSsrlBJ40xKQ/NGONy1Grq6DjuSfPXSjJRI3RINQ513QKLJVbH86SwAlOUr1wfKf4GoChTfl3Se6Rr5PfFlUvRcwztZMywQ932BhYeUcvSjDUtZdD2jRX13PDtZbFUa4N4dAGgWYxV9vvW7Nen1ziyaJ2nsFW5jCg36ruDihup5mrUcAb68iJYpHfGFLC/rzTg8vuUg3Kp32gy0eSSaoDr3LAryInk0zOMaHHnuvXGLOaIS13IFBp/ZLVRSa/0HcV0r8nI5f3FX3Nu1JWMOfnbSr0i35N6SjPoxgZqkpFWv8gjpP4xGJmKTpFpQnkdtImcXHmBtwiODC5oWSKue3lEibd7KvNom5rpinCNfG075ItcF/VKXXCCopOotxWeil4CrOXreqWU+aFz9bM/+XgxJcIGTGwf4Vykt4vHReNOMZ4pAhp07lzolRLX0qjruu5TAHDOvQWELQzGPzPVABxEptCk8uWvy8gUoBlzhXqGMJiMKV/Z8FIqOJy59lGF7cUKJwBQVz6cW/plRaqRjJlSg+EKmP4eirRospEGS24QUefM3y8ZhIDeqYaimr3C+sUyTTWnYxTlyz8/BL8fMuy0NCNdex6tyKN0/H7lIF1SEFwJa+9LAyzWrUilzb3seHL22dBeZotlFsls43W32e/AB6D0/+FICt2vlI9UwmSMZHJAPiDIGrue3Ng5huRLMqM2k0VlxN7N3Dm6+/v/Hn5GcNdLoXG9MtZvNLn0yjDEYM1LRqRsuHw0GZITNA9pZL/D87w/OEujTtErQ2t9LdnfbRhstUG5ZOxrBpmURX4evURjyHGQ15F9z0hfo2hvVksnDDp5fXqEac6et0ynzLJ7zVOw/WgdR7Z9DT6LmuuK/J7SfXC94h8LxgrQaytcp/R///JvqTmJeU2lPlaXyqI4Y3rfn7ss2zEjkddIR/li1VvTjuQzxaDzt+cKvgAAFrZJREFU329E8mhD2my8Eo1GGhpjBshYGpWfW3ptFSlZpqgzo6hqMwXcNpWv8ShuNt1m3tVQZIoX69K1DXmKWkRNdhw52NB7WkhbKu9+irUvV00BkJwyMTCFVWfyaLPjh36X0jWUvMqhNjNlYIopLIru1vo9lep2Mi84HNdT2gD4jgPyszI1LQ2niv12ZDRwJZveLzsE9FiK1pFsphQwj0Vy6R644dy/53z9Kmng0TFZX6pauN0dbKFCgyV8bVQq2p+JhL3mAHHdoRkwWqQqG1AKlPQKlwdNLqL04gmQD85Az+AHChHvKh9k83bSRoeRp9E4Q4acNigPDdSaPMfaCJcltT3pKI5FY4BhnZJfY+meKGOirwepOUIN+u1G9h8ZXJDXLnUFIY1WPot8qrFSaiv5fWuyyMsHhnQLlw3JhC9ancsm7zclZ6isS9re+daVrxZwqEUbGmJjjDrn3EMAT+FTsei67oMJxz8EgOpnfybrqN6IWWZRKU8ewSsZH0BumNDxxBTFKyl5BACiAp4vljFiAyAbiPxx/ZQAvV6aEJDSaXk9A9CvW+D3OXT/8vmQ4TpF6Wrn55RqsNTlH5TI6ZDypWvPX6t6suJog9SYxyjTY8VjlXsaYkhpSzJjrnBe3avWDTz5Gdlm6D3tnKVojPa9Y9eXnXeCbLm8Sn0JAA7/zX/GCg3u/ON3UHKO5D1qhhz/W5NRvD42WPP2NGT8FgenIIf5YoW2acUArctlSBb9wdGfh+qVk57t7x1Mx0udq50P6OslvU1Od7q1dgSMR3fpmHRdLIo3qlPya+b6l39e9iPpCGmGP30uGUQpWKG1f16W0E8vt73j+N9TjBWtPncoCyQdaqlbSp/XyhfGov8aU4IJdC3ZOF84tZSv5pRrMiqxKUbdZwCeUR2dc+6Rc+5B13Uflz4QjL4PAGD+5t/qgPzHSmtI6R1ai0qVjA/NI9DQo3T92htJpjjqFm1IDclIFD9G/i1rx0rX2iJFnoBcUQ0p2rF7Lx0/TekOGUTCcyp5TANpkbHvloYdf6/kNdLjlJpAUgwyyjnoAY54dDIqBYwbgPIYWdAskYYL70/afZcM/1IbkOlLjSlRcn8uYTgPKOJS7R3vSxUaHH//9+DQ4c4/fidzjrjDKO+vpCumyItD7WbMeODP+WfL997vH7WmT4Qs8u8uO0HZ9zNKxq52/VN0zZBxrBmIedtg1zfwVZoumRJdLhl2+XvD/agdMOjk9cQ0LL/eAQMkez7iBA0ZK6W0tCyjoOscGpP8YzpHqURHOgdDjP1WU9qZlG/RcBYOQp4ZKPcl/Ts3gK7rHouXPgHwTQBFo24IHrIeighM8Z6n/PDAmDetn0Mql6GCerX+Y0IxNdEg1dPl19OfhaV9duzcWsrFn69sKK7DWKqhdP9TBkXNsCsNqGMOwBDyGoeMu/E6wPQZzcArXsMaE3pkWxkbrPhn9Wsu94MUdZjmzRLFQS2eezh9kh2rOAZ+9ms/6sLbizTkptSMTpHFlEFpSF68JqiqW1QjkVzN4C9Fq7X7GUuf8UfJlEG6dA3DTsEEGQ0wxYgb+l5+bVz/am1+auQ/XXuehs1LHBp5cOEcE48TJQz02tSUdEmncIbkwo/RxpZ1SjrkOSXyd1OjdtrnKua4T9A3JX4iRl1YcuSdkcOedl337hnPf58mVwSeAXh96udXP/hf+JPXvoq7v/FPcfvr/7Bo6UtK6SINLTyr1ZOdFTn4TG0U4zUEeUdft4ZFUqpZGRrIphpypYF9aocdev/ow/+KZ9/6V2j/75+h+tmfxku/8Wt46ev/QP3ukpF21jTyWFogM+4mpHj63znNaJl6Lrqmqe3iLAauRCpSbTBexyGQilhGSbVTcdkvP/xtrP7H/wSWK/zJa1/Fnd/4Z9j/+t9Xr28orahxVsdGfu/QuaYWexNjjpKeUi33gaHfbmq7umxZSs6qx7/88HfxV9/6l5lu2fv6L4k2kkfmpNMo5aPVd485PGe9/kGjpWTkKQ5Q2YFOem29saY8Vq2jZ9Z1FOkzQ2M+f41fWynzxV8//PB38OW3fhMA3tC+23Vdp71+LXDOvQ/gzpCxF9az+xzAy13XPQuvPYBfp+4rE7+nAwC3u8CrH/x6NOymMNXwOIvymNKYSp5ZbxAaQetQ9P1nadTrMjTpYgpaykR7v6QUhhTalx/+Lp49/OfoDtPqmW53gTsf/IvMsOMk2ZVTT3RdpUF2aCDTJpZMvZ+hz50FXndaaiua8l7XmJNtYayubsgwGDMSxuQ7xPLD31bby6sf/DrufP0Xiudft80PsY5chj677iBYchLXaR/8c/I6SpzVGZgi69KEBH5dQ/VcQ/zVh79X1C17X/+lotxKkS2Zph7Ti3TcFIZ00NBx/jvKE1DkeaoBWQ6V+wy1obHSKPm3dj1Tyj00ztKfS+398MPfwV89/BZweAQA6LrOyWNeSKMuGHKvU82cc+4hnxjhnPsIwCdjkyXY8VEI9c/9NH72h59k75cMo8s06Pz3rhcKPusgXeqcWufSBtazoHmPPOKkfdeU85WuaaqBpBkKf/ba30P7f/60d87q534Gf/2Hf6hej7yvsfRZKVWgXfPYgDdkoK8T8dCMr9JxUxyAdfvRUERpSrRpqlEHrG80l6jRFtsL6ZaxGt2L4KKMOqBs2E2r75lm1JXOqUU3uMN6lnrbdQfnMaPurAYdAPzJa18t6paf/uF/z845ZNhJo0VLV5/XqAN0I3bouPx7+pGnIV0l/57ClLKT/PnlG3Vn/Ywmw7947e/glLWXF8aoc869Dp+ufRBe+hjA96h2zjn3DQBvd133dnh+jx37CoDPpxp04fNSCD8Y+cirAP5y6vmNM3GdZKyGuQNjbeU6c51kvElsanu5rrzI7fhFaCsvsnxfFKbKOGsvL4xRd91xzn3Wdd2bV30dm4zJ+PIxGV8+JuPLx2R8uZh8L5+LlPHWRZzEMAzDMAzDuFrMqDMMwzAMw9gAzKg7G5Pr9YwzYzK+fEzGl4/J+PIxGV8uJt/L58JkbDV1hmEYhmEYG4BF6gzDMAzDMDaAjdgmzDAM4zoRll16AuAuEPeaNi4I59wdAA/D07ewxrqkxvo45x6ddccno0xox9+E30ABAD5Ttj1dCzPqDMMwLpCwaPofscXR33fOPaDnxoXwza7r3qMnzrnPnXNmPF8CoT3fu+rr2DSCQfcRW2/3IbyB97XznNfSr+fEOXcnKO2H4d/kPWeN9XHOPbrqa9g0Qhv+Rvj3UVAuxtl5KAy4TwBYlOOCCIOhNDIeAXhPOdw4BzaeXSrfhW+3xPdxAW3YInXn4LIsbUPHPMZLw6IeF0RhEHwK4P5P+lo2mLsA7jvn7nVd9yS89gymGy6DN+GdEjPuLp4HAN4LO2LdCWnXZ+c9qUXqzselWNpGH/MYLweLelw4d+GNOM65FbWR6LruSdd1LzODDgDeBvDpVV3TJuKcewA/phkXDBvPXmevfRT08bkwo+58PADw2Dl3zzn3etd1z4SiMS4O8hiNiyVGPdhrFvU4O5pSfgpEA9q4YIJc78MckQsjyPRZ13XmkFwOpF+fBCflMYDvwQeKzoUZdWfkMi1tI8c8xsvDoh4XzjOEGa8M+dy4WL4L4KvnnTVoZPxy13WmAy6PJwAg2uwT+EDRuTCj7uxcmqVtJMxj/MliUY9z8xT9aN0dALA2fPGEpWMemUF3cYSAhRl0l4umC54B54/o20SJs3NplraR8ctWsP8TxaIe56DrusfOOamw78IGyQsnRPAfU0TJOXffoksXApVk0PO3ANwLBvTHVmJ0frque+KceyYm+1xIAMOMOkZQEu+MHPY0LMI4aGmbV66zjozNYzwba7Zj/jmLelwM3xfr0r2NfEKVcU6cc/cRjGVWD2plAxdAMIyjHMOqDve6rvvO1V3VRvJt+KwIBS3eCa+dC9v79Rw4574A8AZZ2sEI+cOu616+2ivbDILi5rNe3wrPH8E8xgslGILPLOpxMbAdJe7By9WizRdESE99obz1cdd1tpzUBRIMunfh2/EHAL5tAYuLI+iJyEUYzmbUnYPwg0SFHdZR+5F5NJcDKZiu69646mvZJILxfA9+MgoV9b/L164zDMMwrj9m1J2Ty7C0jT7mMV4OFvUwDMPYHMyoMwzDMAzD2ABsSRPDMAzDMIwNwIw6wzAMwzCMDcCMOsMwDMMwjA3AjDrDMAzDMIwNwIw6wzAMwzCMDcCMOsMwDMMwjA3AjDrDMAzDMIwNwIw6wzCMC8Q5d88594lzrgu7zNDrd8JWgoZhGJeCGXWGYRgXRNih4/3w7ysAuCF3v+u6x1d2cYZhbDz1VV+AYRjGBnFfbK/2btjizow5wzAuHdsmzDAM4xJxzj0AgK7rPr7qazEMY7Ox9KthGIZhGMYGYJE6AM79fAcc8VfWfJx6zGWcX76/7nkncpZbPcvlD31mnWMv+/xTvvcsx17G+QebYCeOSfrAiffoee91/hnk+oSey9fz1+iY4XOc9fxX/ZnreE1nv49pv9VZz997L4xP1OTobdc/fWq68lG+P/Re6bNnPf/Y96x77GVeyzrfc43kH5+yz9DfnTimdKqhS1jn2Is4/9Tv+TPgD7qu+wXx1VZT5zkE8E/Y8+3wWE98PnTMOsee5fzy+brHFiCtXSkfqcWjPEa+P+WY83zPOtdSIXGea1nnmsYep1y39pmz/A7xtaAe6jZ73KqadOi2f62q5aM/pqbnWy27jVY8hmPF61OOkY/TjmXXP3LM8DVNu7bLuv568JrWOfYFvf42PDbhmPY0PEf2CACOPt4UHuX7Q+/Jx6FjSq9POW/Ljp163qHPXMS9XqdrGvqMOOYkPG/YsSdt/lo8ht4Xj9p7pedTjjnP+ad8BgB+HXgVCpZ+NQzDMAzD2ADMqDMMwzAMw9gAzKgzDMMwDMPYAMyoMwzDMAzD2ADMqDMMwzAMw9gAzKgzDMMwDMPYAMyoMwzDMAzD2ADMqDMMwzAMw9gAzKgzDMMwDMPYAMyoMwzDMAzD2ADMqDMMwzAMw9gAzKgzDMMwDMPYAMyoMwzDMAzD2ADMqDMMwzAMw9gAzKgzDMMwDMPYAMyoMwzDMAzD2ADMqDMMwzAMw9gAzKgzDMMwDMPYAMyoMwzDMAzD2ADMqDMMwzAMw9gAzKgzDMMwDMPYAMyoMwzDMAzD2ADMqDMMwzAMw9gAzKgzDMMwDMPYAMyoMwzDMAzD2ABc13VXfQ1XjnPuvwF49aqvYw1eBfCXV30R1wyTSY7Jo4/JpI/JpI/JJMfk0ec6yOQvu677BfmiGXUvIM65z7que/Oqr+M6YTLJMXn0MZn0MZn0MZnkmDz6XGeZWPrVMAzDMAxjAzCjzjAMwzAMYwMwo+7F5IOrvoBriMkkx+TRx2TSx2TSx2SSY/Loc21lYjV1hmEYhmEYG4BF6gzDMAzDMDYAM+oMwzAMwzA2ADPqDMMwDMMwNoD6qi/AWA/n3D0ADwC80nXde+K9OwB+OTz9CgDIYzaRCTJ5GJ6+BeCTruuubZHrRTAkjynvbyITZPINAE8A3AWATW8jGs659wF8Dq87Pr+JMuCENvEsPL3Tdd13rvJ6rhrn3EcAHsH3k6f8va7rnqkfugGEMeab8H0HAD7ruu7xVV2PGXUvEM65+wDuIBhsCu8DeI86mHPuB865b2yyMpogk2/yQdw597lzbmMH7TF5TJDXxjFBJu8D+KOu6z6m5865B/T8JuCc+wTA+13XfRqeP3LO3afnNw2pN51zr2+6Lp3A6wA+UV7/GoAb01c4waD7qOu6t8Pzh/AG3teu6pos/foC0XXdp2GgKXlFbwK4z54/gY9ObSxDMgkd7p54+RGAjY1OjbWRCW1o45hwzw+FAfcJgHcv/8quByGKKQ24T7DB/WQC7/AnIfKy0bp0Ao+6rnP8H3wQ4UYadIHvwo8pxPdxxf3GjLoNouu6N0QHK3lWN4W7AO6HQYt4hr6hZ9xQnHOvKy8/Re4cbTqaDJ7AO4k3lach3QggRmC+d4XXcx3IjDeLXALwJR2PnXP3nHOvd133rOu6J1d5QWbUbSihHuTTTU0zTqHruidd170sOtnbAG5kSslQuQtRH4QbFMUMaPU/d+FT1jeVdwG87pz7IujSpzc8IgWuR0NJw43Wo8whfJ299lHIEF0ZZtRtGM65O8GrBFLhpoGYjr2Pm51WMnI0BfwUiO1l4wmD9WMRtXwduDkykASZPALwGXyt8k1PvUrevcrJANcEyvg8CQGEx/DR3O9e4TWZUbdphPDvByEs/hZPIRj4LoCvmjIyGM8QZrwy5PObwFcBvOOce+CcewCffr2xsxqdc4/gMx1vw0f3H5ou9YT28UdXfR3XAOojj8VrD67mcjw2+/UKCZ3jnZHDnnZdN1q0TUt3iBqHT5AXcV57LlIm4rzfgC/0faEMusuSx4vMBcvkKfrRujvAi23QrCujcK98lvgD6GnZF5J15BEils9IV3Rd96lz7m8A+OPLvs6fJOfoR+/CRy83jjVloukHWnnizlXpDzPqrpBQo3FRdRpvAnjfOfcBa0wvXOrkgmUCIA1QbLmGF2aphsuQx4vORcqk67rHzjmpfO/iBa8XWldGzrl7Su3pC+UQDrGmPO4C+JH4/DPn3AvdJiTn6EcbW8Kyjky6rnvinHsm+s4deIfgyhxCS79uCMFIeU80prcB3OjZSaGg9y6Az8IMpXvwcjEM4vvB8Cc2yqCZyA+opi5E/d+8qZOsgi7NdESQyZXOarwOsBrLFzaKfcF8G/lM+XfCa1eG67ruKr/fWIOgdN9Bytl/DOB7lCZgq+YDwCsAfrTpU86HZBIU0BfKxz7uuu7KFoe8TCa0kcH3N5Ep98x2lLgH72nfKIMmGLVUS/iVm7LTSImgS98Fm2x209qERtCpPwDwxotcnnCRBN0Rueox14w6wzAMwzCMDcDSr4ZhGIZhGBuAGXWGYRiGYRgbgBl1hmEYhmEYG4AZdYZhGIZhGBuAGXWGYRiGYRgbgBl1hmEYEwjrHH7knPvcOdeFx5u2np1hGNcYM+oMwzBGCOu4fQ6/5+XbAF6GX8fM1uoyDOPaYOvUGYZhDMAWsX73Mhagdc49BPC1sHm8YRjGmbFInWEYxjDfBPDEdhQwDOO6Y0adYRjGMPcxYZNv59wd59wj59wXod7uG+J9eq9zzv2AavTg95m9T5+7pHswDOMGYEadYRjGMPfA9gAd4A/h9419GcAbAN6miRShJu/Nrute7rrOAfhVAE/DHsTvAvg0vPeVy7kFwzBuAmbUGYZhDPMEwKCxFYy2O13XvQcAYbPzrwF4GGryAOCec+6+c+5O13WPbUN0wzAuGjPqDMMwhvkMPgU7xD144y/CjLZ7Xdd9DODb8KnWL5xznzBjzzAM40Iwo84wDGOY9wC8HqJxJZ4AeJO/4Jy7x95D13XfCenVlwHcBfDwEq7VMIwbjBl1hmEYA7BU6kfOuW9QhC1MdHgU0qkfA3hKz8MxjwB80HXds5B25dG+p+Lve+GcYxFBwzCMImbUGYZhjBCMtq8AeAvAHzvnOgCfAPicpVnfgI/A/XH497jrunfZad5zzn0R3nvWdd13wuufAkB4jx9vGIaxFrb4sGEYhmEYxgZgkTrDMAzDMIwNwIw6wzAMwzCMDcCMOsMwDMMwjA3AjDrDMAzDMIwNwIw6wzAMwzCMDcCMOsMwDMMwjA3AjDrDMAzDMIwNwIw6wzAMwzCMDcCMOsMwDMMwjA3g/wO8PmHG5dVxLQAAAABJRU5ErkJggg==\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure(figsize=(10, 6))\n", - "plot_landscape_symmetries(G,E_landscape,gammas_landscape,betas_landscape,\n", - " landscape_n_gamma,gamma_min,gamma_max,gamma_period,\n", - " landscape_n_beta,beta_min,beta_max,beta_period)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Some thought will reveal that the unique cell for an integer-weighted graph is the same as for the unweighted graph.\n", - "\n", - "Finally, we demonstrate how we handle 2-decimal-weighted graphs." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Weight: 0.4200000000\n", - "Weight: 0.7600000000\n", - "Weight: 0.4500000000\n", - "Weight: 0.0600000000\n", - "Weight: 0.6300000000\n", - "Weight: 0.4500000000\n", - "Weight: 0.6300000000\n" - ] - }, - { - "data": { - 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "V = np.arange(0,6,1)\n", - "G = nx.Graph()\n", - "G.add_nodes_from(V)\n", - "\n", - "decimals = 2\n", - "E = [(0,1),(0,2),(2,3),(3,1),(3,4),(4,2),(0,5)]\n", - "for i,j in E:\n", - " w = round(np.random.uniform(),decimals)\n", - " print('Weight: %.10f' % w)\n", - " G.add_edge(i,j,weight=w)\n", - "\n", - "pos = nx.spring_layout(G)\n", - "pl.figure(figsize=(10,6))\n", - "nx.draw_networkx(G,apos=pos)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "landscape_n_gamma: 5026\n", - "landscape_n_beta: 12\n", - "gamma_period: 100.00 * 2 pi\n", - "beta_period: 1.00 * pi / 2\n", - "100.00%\r" - ] - } - ], - "source": [ - "(gamma_min,gamma_max),(beta_min,beta_max) = parameterBounds_MaxCut(G,decimals=decimals)\n", - "gamma_period = (gamma_max-gamma_min)*2\n", - "beta_period = beta_max-beta_min\n", - "\n", - "gamma_typ_freq,beta_typ_freq = spatialFrequencies_MaxCut(G)\n", - "\n", - "landscape_n_gamma = int(gamma_period*LANDSCAPE_RESOLUTION*np.ceil(gamma_typ_freq))\n", - "landscape_n_beta = int(beta_period*LANDSCAPE_RESOLUTION*np.ceil(beta_typ_freq))\n", - "\n", - "print('landscape_n_gamma: %d' % landscape_n_gamma)\n", - "print('landscape_n_beta: %d' % landscape_n_beta)\n", - "print('gamma_period: %.2f * 2 pi' % (gamma_period/(2*np.pi)))\n", - "print('beta_period: %.2f * pi / 2' % (beta_period/(np.pi/2)))\n", - "\n", - "gammas_landscape = np.linspace(-gamma_period,gamma_period,landscape_n_gamma)\n", - "betas_landscape = np.linspace(-beta_period,beta_period,landscape_n_beta)\n", - "\n", - "E_landscape = sample_landscape(G,gammas_landscape,betas_landscape,landscape_n_gamma,landscape_n_beta)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure(figsize=(10, 6))\n", - "plot_landscape_symmetries(G,E_landscape,gammas_landscape,betas_landscape,\n", - " landscape_n_gamma,gamma_min,gamma_max,gamma_period,\n", - " landscape_n_beta,beta_min,beta_max,beta_period)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/PortfolioOptimization/4_asset_optimize.ipynb b/PortfolioOptimization/4_asset_optimize.ipynb new file mode 100644 index 0000000..650c8b1 --- /dev/null +++ b/PortfolioOptimization/4_asset_optimize.ipynb @@ -0,0 +1,506 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from openquantumcomputing import QAOAPortfolioOptimization, QAOABase\n", + "from openquantumcomputing import Statistic\n", + "import asset_loader\n", + "\n", + "from qiskit import *\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", + "from qiskit.visualization import *\n", + "from tqdm import tqdm\n", + "import itertools\n", + "\n", + "\n", + "from importlib import reload" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/franzf/OQC/optimization/PortfolioOptimization/asset_loader.py:41: UserWarning: FixedFormatter should only be used together with FixedLocator\n", + " axs[0].set_xticklabels(axs[0].get_xticklabels(), rotation=-30)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "reload(asset_loader)\n", + "assets = asset_loader.AssetData(4, 100, seed=13)\n", + "assets.plotAssets()\n", + "\n", + "params = {\n", + " \"risk\" : 0.5,\n", + " \"budget\": 2,\n", + " \"penalty\": 4,\n", + " \"cov_matrix\": assets.cov_matrix,\n", + " \"exp_return\": assets.exp_return,\n", + " \"usebarrier\": True #only for drawing\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "reload(QAOAPortfolioOptimization)\n", + "qaoa_portopt = QAOAPortfolioOptimization.QAOAPortfolioOptimization(params)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "qaoa_portopt.createParameterizedCircuit(1)\n", + "display(qaoa_portopt.parameterized_circuit.draw(output='mpl'))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.00048258 0.00031392 0.00078376 0.0001755 ]\n", + "[0.00056995 0.00033647 0.00060782 0.00024153]\n", + "0.0009053685866285729\n", + "0.0009053685866285729\n", + "0.0009053685866285729\n", + "[1. 1. 1.]\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "tril_cov = np.tril(qaoa_portopt.cov_matrix + np.tril(qaoa_portopt.cov_matrix, k=-1))\n", + "plt.imshow(tril_cov)\n", + "print(np.sum(qaoa_portopt.cov_matrix, axis=0))\n", + "print(np.sum(tril_cov, axis=0))\n", + "\n", + "x = np.random.rand(4)\n", + "print(x.T@(qaoa_portopt.cov_matrix@x))\n", + "print(x@(qaoa_portopt.cov_matrix@x))\n", + "print(x.T@(tril_cov@x))\n", + "\n", + "print(np.ones((3)))" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "False\n", + "-4.002333065994415\n", + "0.00039152639381967447\n", + "0.0023381735562253425\n", + "-3.998367003059391\n" + ] + } + ], + "source": [ + "print(qaoa_portopt.isFeasible(\"0010\"))\n", + "print(qaoa_portopt.cost(\"0010\"))\n", + "print(qaoa_portopt.cost(\"0101\"))\n", + "print(qaoa_portopt.cost(\"1100\"))\n", + "\n", + "print(qaoa_portopt.cost(\"1000\"))\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "solutions:\n", + "0000 \t -16.0\n", + "0001 \t -4.000341395451567\n", + "0010 \t -4.002333065994415\n", + "0011 -0.0026484871652812103\n", + "0100 \t -3.9992716588144965\n", + "0101 0.00039152639381967447\n", + "0110 -0.0016550158624220046\n", + "0111 \t -4.001965856373403\n", + "1000 \t -3.998367003059391\n", + "1001 0.0013270681176713595\n", + "1010 -0.0007997440273825873\n", + "1011 \t -4.001079698569619\n", + "1100 0.0023381735562253425\n", + "1101 \t -3.9979631746068307\n", + "1110 \t -4.0001448584652906\n", + "1111 \t -16.000420232347622\n", + "--------------------\n", + "Best sol is 1100 with cost 0.0023381735562253425\n" + ] + } + ], + "source": [ + "\n", + "print(\"solutions:\")\n", + "best_sol = None\n", + "best_cost = None\n", + "for s in [''.join(i) for i in itertools.product('01', repeat = assets.N)]:\n", + " c = qaoa_portopt.cost(s)\n", + " if best_sol is None:\n", + " best_sol = s\n", + " best_cost = c\n", + " elif c > best_cost:\n", + " best_sol = s\n", + " best_cost = c\n", + "\n", + " if qaoa_portopt.isFeasible(s):\n", + " print(s, c)\n", + " else: \n", + " print(s, '\\t', c)\n", + "\n", + "print(\"--------------------\")\n", + "print(\"Best sol is \"+ best_sol + \" with cost \" + str(best_cost))" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Sample cost landscape" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "qasm_sim = Aer.get_backend('qasm_simulator')" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Calculating Energy landscape for depth p=1...\n", + "Executing sample_cost_landscape\n", + "parameters: 2\n", + "Done execute\n", + "Done measurement\n", + "Calculating Energy landscape done\n" + ] + } + ], + "source": [ + "qaoa_portopt.sample_cost_landscape(qasm_sim, 1024, angles={\"gamma\": [0,np.pi,50], \"beta\": [0,np.pi,40]})" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def plotLandscape(field, title, interpolation='bicubic'):\n", + " f = plt.figure(figsize=(6, 6), dpi= 80, facecolor='w', edgecolor='k')\n", + " _=plt.xlabel(r'$\\gamma$')\n", + " _=plt.ylabel(r'$\\beta$')\n", + " ax = plt.gca()\n", + " _=plt.title(title)\n", + " im = ax.imshow(field, interpolation=interpolation, origin='lower', extent=[0,np.pi,0,np.pi])\n", + " divider = make_axes_locatable(ax)\n", + " cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n", + " _=plt.colorbar(im, cax=cax)\n", + "\n", + "plotLandscape(qaoa_portopt.E, \"Expection value\", interpolation=\"None\")\n", + "#plotLandscape(qaoa_portopt.E, r'CVaR with $\\alpha$='+str(qaoaec_cvar.params[\"alpha\"])) #, interpolation=\"None\")\n", + "plotLandscape(qaoa_portopt.Var, \"Variance\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 14%|██████████████████████▎ | 1/7 [00:00<00:01, 5.91it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 1 )= 0.008001757623218517\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 29%|████████████████████████████████████████████▌ | 2/7 [00:00<00:01, 3.81it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 2 )= 0.07446525947055213\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 43%|██████████████████████████████████████████████████████████████████▊ | 3/7 [00:01<00:01, 2.50it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 3 )= 0.5392266181173387\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 57%|█████████████████████████████████████████████████████████████████████████████████████████▏ | 4/7 [00:01<00:01, 2.00it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 4 )= 1.6122062260642713\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 71%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████▍ | 5/7 [00:02<00:01, 1.37it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 5 )= 0.5078199146476047\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 86%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋ | 6/7 [00:04<00:00, 1.03it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 6 )= 0.6936878676705739\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7/7 [00:06<00:00, 1.05it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 7 )= 0.15967693316080286\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "maxdepth=7\n", + "for i in tqdm(range(maxdepth)):\n", + " qaoa_portopt.increase_depth(qasm_sim, 1024)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "hist=qaoa_portopt.hist(qaoa_portopt.angles_hist['d'+str(maxdepth)+'_final'], qasm_sim,1024)\n", + "plot_histogram(hist)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-0.0026484871652812103 0011 470\n", + "0.00039152639381967447 0101 247\n", + "0.0023381735562253425 1100 156\n", + "-0.0007997440273825873 1010 48\n", + "-0.0016550158624220046 0110 31\n", + "0.0013270681176713595 1001 29\n", + "\t -4.002333065994415 0010 15\n", + "\t -4.001079698569619 1011 14\n", + "\t -4.0001448584652906 1110 6\n", + "\t -3.998367003059391 1000 5\n", + "\t -3.9992716588144965 0100 1\n", + "\t -16.0 0000 1\n", + "\t -4.001965856373403 0111 1\n", + "Classical best result: ('1100', 0.0023381735562253425)\n" + ] + } + ], + "source": [ + "sorted_hist = dict(sorted(hist.items(), key=lambda item: item[1], reverse=True))\n", + "\n", + "for s, freq in sorted_hist.items():\n", + " if qaoa_portopt.isFeasible(s):\n", + " print(qaoa_portopt.cost(s), s, freq)\n", + " else:\n", + " print(\"\\t\", qaoa_portopt.cost(s), s, freq)\n", + "\n", + "print(\"Classical best result: \", (best_sol, best_cost))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/PortfolioOptimization/6_asset_optimize.ipynb b/PortfolioOptimization/6_asset_optimize.ipynb new file mode 100644 index 0000000..5acaf77 --- /dev/null +++ b/PortfolioOptimization/6_asset_optimize.ipynb @@ -0,0 +1,580 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from openquantumcomputing import QAOAPortfolioOptimization, QAOABase\n", + "from openquantumcomputing import Statistic\n", + "import asset_loader\n", + "\n", + "from qiskit import *\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", + "from qiskit.visualization import *\n", + "from tqdm import tqdm\n", + "import itertools\n", + "\n", + "\n", + "from importlib import reload" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\Users\\havardh\\playground-win\\quantumComputing\\optimization\\PortfolioOptimization\\asset_loader.py:41: UserWarning: FixedFormatter should only be used together with FixedLocator\n", + " axs[0].set_xticklabels(axs[0].get_xticklabels(), rotation=-30)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "64\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "reload(asset_loader)\n", + "assets = asset_loader.AssetData(6, 100, seed=13)\n", + "assets.plotAssets()\n", + "\n", + "params = {\n", + " \"risk\" : 0.5,\n", + " \"budget\": 2,\n", + " \"penalty\": 4,\n", + " \"cov_matrix\": assets.cov_matrix,\n", + " \"exp_return\": assets.exp_return,\n", + " \"usebarrier\": True\n", + "}\n", + "print(2**assets.N)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "reload(QAOAPortfolioOptimization)\n", + "qaoa_portopt = QAOAPortfolioOptimization.QAOAPortfolioOptimization(params)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "display(qaoa_portopt.createCircuit(np.array((np.pi,2*np.pi)),1).draw(output='mpl'))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "solutions:\n", + "000000 \t -16.0\n", + "000001 \t -3.9961826539466863\n", + "000010 \t -3.998681291258883\n", + "000011 0.005149285769853407\n", + "000100 \t -4.000341395451567\n", + "000101 0.0034369571369659013\n", + "000110 0.000982559034333974\n", + "000111 \t -3.9952258574017137\n", + "001000 \t -4.002333065994415\n", + "001001 0.0015792261027094412\n", + "001010 -0.0009441163260390795\n", + "001011 \t -3.9970185932535003\n", + "001100 -0.0026484871652812103\n", + "001101 \t -3.998775188532939\n", + "001110 \t -4.001254291752133\n", + "001111 \t -15.997367762144364\n", + "010000 \t -3.9992716588144965\n", + "010001 0.0046114172079469995\n", + "010010 0.0020760282873837355\n", + "010011 \t -3.99402766471475\n", + "010100 0.00039152639381967447\n", + "010101 \t -3.9957643910485174\n", + "010110 \t -3.9982555407595157\n", + "010111 \t -15.994398227226426\n", + "011000 -0.0016550158624220046\n", + "011001 \t -3.9976769937961762\n", + "011010 \t -4.000237087833291\n", + "011011 \t -15.996245834791608\n", + "011100 \t -4.001965856373403\n", + "011101 \t -15.998026827771938\n", + "011110 \t -16.000542682599487\n", + "011111 \t -35.996590423022596\n", + "100000 \t -3.998367003059391\n", + "100001 0.005428075404783073\n", + "100010 0.0030563424410345874\n", + "100011 \t -3.9931353481193668\n", + "100100 0.0013270681176713595\n", + "100101 \t -3.994916846882937\n", + "100110 \t -3.997244340637117\n", + "100111 \t -15.993475024662288\n", + "101000 -0.0007997440273825873\n", + "101001 \t -3.996909719519401\n", + "101010 \t -3.9993061575996975\n", + "101011 \t -15.995402902116297\n", + "101100 \t -4.001079698569619\n", + "101101 \t -15.997228667526429\n", + "101110 \t -15.999580866397153\n", + "101111 \t -35.995716604378515\n", + "110000 0.0023381735562253425\n", + "110001 \t -3.9938010180104726\n", + "110010 \t -3.9962095025825803\n", + "110011 \t -15.992335463173859\n", + "110100 \t -3.9979631746068307\n", + "110101 \t -15.994141359638306\n", + "110110 \t -15.996505605000849\n", + "110111 \t -35.992670559056904\n", + "111000 \t -4.0001448584652906\n", + "111001 \t -15.996189103988172\n", + "111010 \t -15.998622293676831\n", + "111011 \t -35.994653308224315\n", + "111100 \t -16.000420232347622\n", + "111101 \t -35.996503471335316\n", + "111110 \t -35.9988924218144\n", + "111111 \t -63.99496242982666\n", + "--------------------\n", + "Best sol is 100001 with cost 0.005428075404783073\n" + ] + } + ], + "source": [ + "\n", + "print(\"solutions:\")\n", + "best_sol = None\n", + "best_cost = None\n", + "for s in [''.join(i) for i in itertools.product('01', repeat = assets.N)]:\n", + " c = qaoa_portopt.cost(s)\n", + " if best_sol is None:\n", + " best_sol = s\n", + " best_cost = c\n", + " elif c > best_cost:\n", + " best_sol = s\n", + " best_cost = c\n", + "\n", + " if qaoa_portopt.isFeasible(s):\n", + " print(s, c)\n", + " else: \n", + " print(s, '\\t', c)\n", + "\n", + "print(\"--------------------\")\n", + "print(\"Best sol is \"+ best_sol + \" with cost \" + str(best_cost))" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Sample cost landscape" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "qasm_sim = Aer.get_backend('qasm_simulator')" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Calculating Energy landscape for depth p=1...\n", + "Calculating Energy landscape done\n" + ] + } + ], + "source": [ + "qaoa_portopt.sample_cost_landscape(qasm_sim, 1024, angles={\"gamma\": [0,np.pi,50], \"beta\": [0,np.pi,40]})" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def plotLandscape(field, title, interpolation='bicubic'):\n", + " f = plt.figure(figsize=(6, 6), dpi= 80, facecolor='w', edgecolor='k')\n", + " _=plt.xlabel(r'$\\gamma$')\n", + " _=plt.ylabel(r'$\\beta$')\n", + " ax = plt.gca()\n", + " _=plt.title(title)\n", + " im = ax.imshow(field, interpolation=interpolation, origin='lower', extent=[0,np.pi,0,np.pi])\n", + " divider = make_axes_locatable(ax)\n", + " cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n", + " _=plt.colorbar(im, cax=cax)\n", + "\n", + "plotLandscape(qaoa_portopt.E, \"Expection value\", interpolation=\"None\")\n", + "#plotLandscape(qaoa_portopt.E, r'CVaR with $\\alpha$='+str(qaoaec_cvar.params[\"alpha\"])) #, interpolation=\"None\")\n", + "plotLandscape(qaoa_portopt.Var, \"Variance\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 10%|█ | 1/10 [00:01<00:17, 1.96s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 1 )= 2.5829933609362214\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 20%|██ | 2/10 [00:03<00:12, 1.58s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 2 )= 6.725234989402634\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 30%|███ | 3/10 [00:06<00:15, 2.23s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 3 )= 6.611086736425675\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 40%|████ | 4/10 [00:10<00:17, 2.86s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 4 )= 7.356770721480401\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 50%|█████ | 5/10 [00:14<00:16, 3.39s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 5 )= 6.259591530955283\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 60%|██████ | 6/10 [00:20<00:17, 4.41s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 6 )= 5.828438714146477\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 70%|███████ | 7/10 [00:30<00:18, 6.13s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 7 )= 2.864840185559787\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 80%|████████ | 8/10 [00:42<00:15, 7.91s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 8 )= 2.673134117383907\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 90%|█████████ | 9/10 [00:57<00:10, 10.21s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 9 )= 3.143092114770156\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 10/10 [01:14<00:00, 7.41s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 10 )= 6.161788672015834\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "maxdepth=10\n", + "for i in tqdm(range(maxdepth)):\n", + " qaoa_portopt.increase_depth(qasm_sim, 1024)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "hist=qaoa_portopt.hist(qaoa_portopt.angles_hist['d'+str(maxdepth)+'_final'], qasm_sim,1024)\n", + "plot_histogram(hist)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Classical best result: ('100001', 0.005428075404783073)\n", + "0\t\t -3.9993061575996975 101010 171\n", + "1\t 0.00039152639381967447 010100 162\n", + "2\t\t -3.996909719519401 101001 85\n", + "3\t\t -3.9992716588144965 010000 38\n", + "4\t\t -3.9957643910485174 010101 35\n", + "5\t\t -15.994141359638306 110101 32\n", + "6\t\t -3.9962095025825803 110010 31\n", + "7\t\t -4.001965856373403 011100 28\n", + "8\t 0.0013270681176713595 100100 26\n", + "9\t -0.0016550158624220046 011000 21\n", + "10\t -0.0026484871652812103 001100 21\n", + "11\t\t -15.993475024662288 100111 20\n", + "12\t\t -4.0001448584652906 111000 18\n", + "13\t\t -35.994653308224315 111011 17\n", + "14\t\t -3.9982555407595157 010110 16\n", + "15\t 0.0034369571369659013 000101 16\n", + "16\t\t -4.002333065994415 001000 16\n", + "17\t\t -16.000542682599487 011110 15\n", + "18\t\t -3.9970185932535003 001011 14\n", + "19\t\t -3.9931353481193668 100011 14\n", + "20\t\t -16.0 000000 13\n" + ] + } + ], + "source": [ + "sorted_hist = dict(sorted(hist.items(), key=lambda item: item[1], reverse=True))\n", + "\n", + "print(\"Classical best result: \", (best_sol, best_cost))\n", + "\n", + "i = 0\n", + "for s, freq in sorted_hist.items():\n", + " if i > 20:\n", + " break\n", + " if s == best_sol:\n", + " print(str(i)+\" -->\\t\", qaoa_portopt.cost(s), s, freq)\n", + " elif qaoa_portopt.isFeasible(s):\n", + " print(str(i)+\"\\t\", qaoa_portopt.cost(s), s, freq)\n", + " else:\n", + " print(str(i)+\"\\t\\t\", qaoa_portopt.cost(s), s, freq)\n", + " i = i + 1\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-63.99496242982665 -63.99496242982666 -63.99496242982665\n", + "-16.0 -16.0 -16.0\n", + "-3.995764391048522 -3.9957643910485174 -3.995764391048522\n", + "-0.0016550158624250885 -0.0016550158624220046 -0.0016550158624250885\n", + "0.004611417207942098 0.0046114172079469995 0.004611417207942098\n" + ] + } + ], + "source": [ + "def cost(qaoa_portopt, string, penalize=True):\n", + " \n", + " risk = qaoa_portopt.params.get(\"risk\")\n", + " budget = qaoa_portopt.params.get(\"budget\")\n", + " cov_matrix = qaoa_portopt.params.get(\"cov_matrix\")\n", + " exp_return = qaoa_portopt.params.get(\"exp_return\")\n", + " penalty = qaoa_portopt.params.get(\"penalty\", 0.0)\n", + "\n", + " x = np.array(list(map(int,string))) \n", + " cost = risk* (x.T@cov_matrix@x) - exp_return.T@x\n", + " if penalize:\n", + " cost += penalty * (x.sum() - budget)**2\n", + "\n", + " return -cost\n", + "\n", + "\n", + "for s in [\"111111\", \"000000\", \"010101\", \"011000\", \"010001\"]:\n", + " print(cost(qaoa_portopt, s), qaoa_portopt.cost(s), qaoa_portopt.cost_nonQUBO(s))\n", + "\n", + "\n", + "\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "qcomp", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.3" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/PortfolioOptimization/8_asset_optimize.ipynb b/PortfolioOptimization/8_asset_optimize.ipynb new file mode 100644 index 0000000..85d79cf --- /dev/null +++ b/PortfolioOptimization/8_asset_optimize.ipynb @@ -0,0 +1,813 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from openquantumcomputing import QAOAPortfolioOptimization, QAOABase\n", + "from openquantumcomputing import Statistic\n", + "import asset_loader\n", + "\n", + "from qiskit import *\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", + "from qiskit.visualization import *\n", + "from tqdm import tqdm\n", + "import itertools\n", + "\n", + "\n", + "from importlib import reload" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\Users\\havardh\\playground-win\\quantumComputing\\optimization\\PortfolioOptimization\\asset_loader.py:41: UserWarning: FixedFormatter should only be used together with FixedLocator\n", + " axs[0].set_xticklabels(axs[0].get_xticklabels(), rotation=-30)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "256\n" + ] + }, + { + "data": { + 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "reload(asset_loader)\n", + "assets = asset_loader.AssetData(8, 100, seed=13)\n", + "assets.plotAssets()\n", + "\n", + "params = {\n", + " \"risk\" : 0.5,\n", + " \"budget\": 3,\n", + " \"penalty\": 0.1,\n", + " \"cov_matrix\": assets.cov_matrix,\n", + " \"exp_return\": assets.exp_return,\n", + " \"usebarrier\": True\n", + "}\n", + "print(2**assets.N)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "reload(QAOAPortfolioOptimization)\n", + "qaoa_portopt = QAOAPortfolioOptimization.QAOAPortfolioOptimization(params)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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XcVmB7HbHePMfbPuL0nN3q1+vEerZta/R5bnN6n9Lp0471+bRyVLHIEe7l9a1rM36b6SBPaUeEc7XCAAAgLYlLy9P8+bN02WXXaZOnToZXQ4uQmGpY84pZ7hyP1BxRlq5Q5oxXrJYnK/TCGa5J/wmR9p52Lk2rlwD2YWOuemuG+h0iQAAAPAAArLzfPXVV3riiSdksVj05ptvKjk5WZKUkZGhyZMna9u2bXr66af1v//7v4bW2RpWfDJXKz6ZW2/Z2MSbNPNHrxpUkful5Eo7M51v1zFICg92rk2NTfr7NunRH0g+7eSGGAAAAPB273zl/GgSrtwPSFJqnvTVd9LIWOfbGsEM94QVZ6R3djjfztVrYP1+aXAvqVuY820BAADQugjIzjN37lzZ7Xbdc889deGYJMXGxuqNN97Q1VdfrVdffVWzZ89WZGSkcYW2gslX3KvxQ25Xja1ah49+o39sXKCTpfkK9D/bW27/d5s1+40fNGhbXVMlm61G619w0+zWreTTFM8eL+ek9G2e1L+HZ48LAAAAoKGcQkdo5UmfpkhXXNo+epGZ4Z7wq++kUxWeO16NTfr8oHT7KM8dEwAAAC3j9XOQFRQU6PHHH1dsbKysVqt69eqlxx57TKdPn9b06dNlsVi0ePFiSVJJSYk2bNggSbr//vsb7Ouqq65SfHy8qqqqtGbNGo+ehydEd47T5fETNCJhsm4Z97jm3vOhUo/s0Murf163zaBLr9QH80vr/VkyK00dQ7ro7klzL7B34+UVSRnHPH/crYc8f0wAAAAADRnxu/mxU9KhfM8f1xXefk9ot0tbWnHuuab8+7BUbq7pzAEAANoFrw7I9u3bp4EDB2rRokXKz8/XgAEDVFVVpZdeeknTp0/Xt99+K0kaMmSIJGn37t2qqqpSYGCghg8f3ug+k5KSJEnbt2/3zEkYaECfUbr28unauOdtpWQ1fr5V1ZX63Vs/0sCYJN1x7WwPV+icbenGHPdArlRcbsyxAQAA4B4hISEaO3asQkJCjC4FLqqslv7twnDr7mDUvcjF8rZ7wszjjsDS087USLsOe/64AAAAuDCvDcgKCgo0depU5efna9asWTp69Kh27dql/Px8zZ07V6tXr9aePXvk4+OjgQMdM+ampTkeJevTp4/8/BoffTI2Nrbett7uzgm/lo+Pr5at/3Wj619e9YCqzlToiduWerYwF3x33Jjj2u3S4QJjjg0AAAD3iImJ0eLFixUTE2N0KXBRbqFUZdDof5kG3Yu4gzfdExoxokit7ww8NgAAABrntQHZzJkzlZ2drUcffVQLFy5UaGho3bpnnnlGCQkJqq6uVnx8vIKCHOOpnzx5UpIUERHR5H5r19Vu6+2iu8Rp/JDbtevQJ9r/3eZ6697b8op2HPxQv0v+P1kDXJit2IOqaxxDLBolp9C4YwMAAODi1dTUqLS0VDU1bXt+JTQt28DfyYvKpRIPznvlTt5yTygZe19m5PUHAACAxnllQJaSkqKVK1cqMjJSc+c2HAPdYrFo2LBhks4OryhJFRWOO5aAgIAm9x0YGChJOn36dJPb/OAHP5DFYtGzzz7rSvltzn9d+4x8LD5atuE3dcv2pG/U4rVPas70d9StU4xxxbXQ0WLH5MhGyTFHngoAAOC1UlNTNWLECKWmphpdClyUa/Dv5O35oTlvuCeUjL0GjpdIlWeMOz4AAAAaanwcwXZuxYoVstlsmj59uoKDG3+KrTboOjcgs1qtkqSqqqZnz62srJSkul5n53vnnXe0Z88eV8puVN++feXj07IcM8AvSK897Pys00Nix+lfL9qbXN8nqr/Wv3D2SdmjhYc1b/mtun/qi7osbrzTxztX3/i+qqpuOmx0l66XjtbVM/7Z6LpHJ0sdG/9y1uloPfv3sz9sertTp6WX1jVcvmXbTs2966aWFdsGTZn9tYLDuivvaJ569hxhdDkwgNmvAbOfP7gGzH7+8M5rIDk52ant8/LyJEkfffSRdu/e3aI2S5cudbIqtKbRdy1W9MDJja5r7p6gpfcDUtP3BD+97+fK2fdBC6t1nSv3hUbeE0qeuy+84Tf7FBjSqdF17roGmvr6S1Li4GGqKMlvYbVtizf+HIBzuAZ4DcyOrz+vAdrWNWCzne0Nk5SU1OJ7tPN5ZUD26aefSpLGj2/6F/WcnBxJ9QOylgyfeKFhGE+dOqVf/epX+v3vf6/p06c7X3gjam/EW8Lq3/pDWlRUleu3S2/S6AHTdNPYhy96f3nff6+KM+VuqOzCfMKb/pp2DJLCW/jS+fi0fNtznam2KTc31/mGbUTtUEI1NTXt+jzgOrNfA2Y/f3ANmP384Z3XQHm5c7+D1o42UVFR0eK23vJaeYvKqqa777T0nsDV+wFJKio+5ZFrorXvC919Tyh57r7wQoPoeOIaOHb8uEpOtM/vC974cwDO4RrgNTA7vv68Bmi710B+vusPIHllQJaVlSVJTU6gXVlZqR07dkiqH5DFx8fXta+urpafX8OXJyMjo96253rmmWcUHx+vO++8020BWffu3Z3qQdbaNu9fpe/y9iq3IE2f713ZYP0bj6coMqJ3i/fXvUcPjzwpGBEW2uS6Uy04fEer40bIZpNOXWDugKb25WuxKTo6uvkDtVG+vr51f7fn84DrzH4NmP38wTVg9vOHd14DTY000ZTa0SasVmuL23rLa+Ut/C9w99vcPUFL7wcutK+wDiEeuSZa+77Q3feEkufuC201lU2uc9c1cKH9dO0coY5WA8f+vwje+HMAzuEa4DUwO77+vAZoW9eAzWar61wUFRXl8n68MiArKyuTdPYpz/MtX75cxcXF6ty5c70v5NChQxUQEKDKykrt3LlTo0aNatB2y5YtkqSRI0fWW75z5069/vrr+ve//+2u05AkHTp0SCEhIS3atqZK2viKWw/fwMRhd2nisLvctr9DaYfk2/SUb25z6rT0m9WNr2tq+ItzPftDx1OCpyqkZ99z/vjXTxilFb/Ocb5hG/Hb1VLxaal7t+51vS9hLma/Bsx+/uAaMPv5wzuvAWfnEjtw4IDefPNNTZkyRYmJiS1qM2/ePFdKQyv5YLf0aUrj65q7J7jY+wFJWv32a4puOBCJ27X2faG77wklz90XvrxByjze+LrWvgas/tKh1L3ysTjfti3wxp8DcA7XAK+B2fH15zVA27oGysrKFBrq6BRTm9m4omVdk9qZbt26SXKEVufLzs7W008/LUkaPHhwvXUdOnTQxIkTJUmvv/56g7abNm1SWlqaAgICdOONN9Ytr6mp0QMPPKCHH364xTfL8KyOQVJY63ewa1LvzsYdGwAAABcvPj5eW7dubXQkCbQPvQz8ndzfV+oWZtzx4dCr8enHPHbs9hqOAQAAeCuvDMgmTJggSXruueeUlpZWt3z79u265pprVFRUJKn+8Iq15syZI4vFoiVLlmjZsmV1yzMyMnTvvfdKkmbMmKHIyMi6dX/84x919OhRPfvss61wNnAXI2+Iexp4IwYAAICL5+/vr06dOsnf39/oUuAiI8ORHuGSr1fefbcvRl4D3BMCAAC0PV75K/pTTz2liIgIZWdnKzExUYMGDVJcXJxGjx6t/v37KykpSVLjAdmoUaO0YMEC2e12JScnKyYmRkOHDlVCQoLS09M1cuRILViwoG77goIC/frXv9ZvfvMbVVdXq6ioqC6Aq6ioUFFRkWy29jnGuLcZ3MuY40YES725GQIAAGjXjhw5ogcffFBHjhwxuhS4qFOIcSHFEOem5EIrGRAt+Rn0KQjXAAAAQNvjlQFZ7969tXnzZk2ZMkVWq1VZWVnq2rWrFi9erPfff79uvoHGAjJJmjVrltatW6eJEyequLhYqampio+P1/z58/XFF1/Um5Q7JydHJSUlmjFjhiIiIur+SNLChQsVERGh7777rvVPGs0a2kcK9sC49ucb09cxmTMAAADar5KSEm3cuFElJSVGlwIXWSxSUl/PH9fPRxoZ6/njoqGQQGlojOeP2zNC6sOw+wAAAG2On9EFtJbExEStXbu2wfLCwkLl5eXJz89PAwYMaLL9pEmTNGnSpGaPExcXp40bNzZYPn78eN19991KTk5WdHS0c8WjVfj7SqPipM+amJi7Nfj6SKO4GQYAAADahMtjpDW7pfIqzx1zaIwjmEHbcGW89LWHn2FNincEtAAAAGhbvDYga8r+/fslSQkJCQoMvPi7lNDQUI0bN67RdTExMU2uM0rO8UN6ceXdKi4rUGhQuJ64ban6RNUPCo8WHtaLK5OV/v1uRXfpqz//cme9dXcvjFNM1MC6Zb/9ySr16BKrrPwUPbfijrrlZRVFKq84pdX/Xdj6J9ZCExKlf2dKxac9c7zJg6QOQZ45FgAAAIALC/CTpl0u/WO7Z45n9Zeub3zgEsOY/Z6wd2fpikulrzwUkvXuLI241DPHAgAAgHNMG5A1Nbyit3t51QxNGfkzTRqRrE373tWid+7VK7/YVm+bYGtH/XTyPJVVFGvZht822EeoNVx/fXRPg+V9ogbUW/6H9x6WpY09JhccIN02Unrt89Y/Vu/O0jVNd1IEAAAAYICRl0p7sqTUvNY/1o+GS+HBzW/nSWa/J5Skm4ZJ3+a1/oOTvj7SHaMdfwMAAKDtMd2vaZ4KyOx2u5599tlWPYazTpYe06HcXZpw+XRJ0pWDfqyjhZk6Wni43nYdgztp4CVJsgaEuHysqupKbdz9d00ece/FlNwqBkRLV/Vzrs2p01JRuePvlggKkO7kRggAAMBrREVF6cknn1RUVJTRpeAiWSzS7aOkMCdGenD2fkByzIE84hLn62tN3BM6BAdId45x7n7NlWvgpsulbmHO1wcAAADPMG0PssGDBxtciecdL8pW54495Ovr+LJbLBZFRvTWsaIj6tYppsX7Ka88pYdeHiGbvUZjEm/SHdc+I18f33rbbNm/Wt06XaK46MvceAbuc9Mwx7wDOzNbtv1L61q+70A/6WfjpCh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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "display(qaoa_portopt.createCircuit(np.array((np.pi,2*np.pi)),1).draw(output='mpl'))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "solutions:\n", + "00000000 \t -0.9000000000000001\n", + "00000001 \t -0.39959493903923593\n", + "00000010 \t -0.40003838680503623\n", + "00000011 \t -0.09961497100788397\n", + "00000100 \t -0.3961826539466855\n", + "00000101 \t -0.09571981905405957\n", + "00000110 \t -0.09620838012044663\n", + "00000111 0.004272809608567463\n", + "00001000 \t -0.3986812912588831\n", + "00001001 \t -0.09831678722260051\n", + "00001010 \t -0.09870341459236309\n", + "00001011 0.0016794442803078624\n", + "00001100 \t -0.0948507142301469\n", + "00001101 0.005571563737997387\n", + "00001110 0.005139823067648375\n", + "00001111 \t -0.09441954412781906\n", + "00010000 \t 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"01011101 \t -0.39406914361545575\n", + "01011110 \t -0.39435014921544576\n", + "01011111 \t -0.894002710768081\n", + "01100000 \t -0.1016550158624252\n", + "01100001 -0.0013522162694326045\n", + "01100010 -0.0016661050159871849\n", + "01100011 \t -0.10134495058660642\n", + "01100100 0.00232300620382353\n", + "01100101 \t -0.09731642027132215\n", + "01100110 \t -0.09767542231846371\n", + "01100111 \t -0.39729649395722055\n", + "01101000 -0.000237087833283689\n", + "01101001 \t -0.09997484516477262\n", + "01101010 \t -0.10023191351528937\n", + "01101011 \t -0.39995131601039025\n", + "01101100 \t -0.09624583479161308\n", + "01101101 \t -0.3959258181912404\n", + "01101110 \t -0.39622799984234436\n", + "01101111 \t -0.8958896284055828\n", + "01110000 -0.0019658563734039625\n", + "01110001 \t -0.10170985433451096\n", + "01110010 \t -0.10195588133790268\n", + "01110011 \t -0.4016815244626206\n", + "01110100 \t -0.09802682777193805\n", + "01110101 \t -0.39771305180118266\n", + "01110110 \t -0.3980041921051616\n", + "01110111 \t -0.897672061298018\n", + "01111000 \t -0.10054268259947885\n", + "01111001 \t -0.40032723748506727\n", + "01111010 \t -0.40051644409242093\n", + "01111011 \t -0.9002826441416205\n", + "01111100 \t -0.3965904230225916\n", + "01111101 \t -0.8963172039763172\n", + "01111110 \t -0.8965515238842585\n", + "01111111 \t -1.5962599500015962\n", + "10000000 \t -0.398367003059392\n", + "10000001 \t -0.09789276426475624\n", + "10000010 \t -0.09838280904672725\n", + "10000011 0.00210978458429667\n", + "10000100 \t -0.09457192459522124\n", + "10000101 0.005960088131276464\n", + "10000110 0.00542493004871869\n", + "10000111 \t -0.094024702388396\n", + "10001000 \t -0.09694365755896117\n", + "10001001 0.003490024311193052\n", + "10001010 0.0030567999252598677\n", + "10001011 \t -0.09649116336819752\n", + "10001100 0.006864651880631345\n", + "10001101 \t -0.09264389231735248\n", + "10001110 \t -0.09312223000387276\n", + "10001111 \t -0.392612419365469\n", + "10010000 \t -0.09867293188232829\n", + "10010001 0.0017545093582082005\n", + "10010010 0.0013323263194000567\n", + "10010011 \t -0.0982218776036754\n", + "10010100 0.005083153117060091\n", + "10010101 \t -0.09443163171054159\n", + "10010110 \t -0.09489892804993683\n", + "10010111 \t -0.3943953580411501\n", + "10011000 0.0027556593628863535\n", + "10011001 \t -0.09685745632105891\n", + "10011010 \t -0.0972228189638289\n", + "10011011 \t -0.39681757981138577\n", + "10011100 \t -0.09347502466230373\n", + "10011101 \t -0.39303036641438704\n", + "10011110 \t -0.39344084235774424\n", + "10011111 \t -0.8929778292734396\n", + "10100000 \t -0.10079974402738401\n", + "10100001 -0.000381369797451514\n", + "10100010 -0.0008247288873732828\n", + "10100011 \t -0.1003879998210524\n", + "10100100 0.0030902804805961193\n", + "10100101 \t -0.09643357135760944\n", + "10100110 \t -0.09692204374811797\n", + "10100111 \t -0.3964275407499358\n", + "10101000 0.0006938424003041233\n", + "10101001 \t -0.09892834029424491\n", + "10101010 \t -0.09931487898812885\n", + "10101011 \t -0.39891870684628983\n", + "10101100 \t -0.09540290211629432\n", + "10101101 \t -0.3949673108789813\n", + "10101110 \t -0.395398962873452\n", + "10101111 \t -0.894945016799751\n", + "10110000 -0.0010796985696177597\n", + "10110001 \t -0.1007081218937842\n", + "10110010 \t -0.10108361924054354\n", + "10110011 \t -0.40069368772832203\n", + "10110100 \t -0.09722866752642045\n", + "10110101 \t -0.3967993169187254\n", + "10110110 \t -0.3972199275660706\n", + "10110111 \t -0.8967722221219876\n", + "10111000 \t -0.0995808663971458\n", + "10111001 \t -0.3992498466457943\n", + "10111010 \t -0.3995685235965152\n", + "10111011 \t -0.8992191490087753\n", + "10111100 \t -0.39571660437852674\n", + "10111101 \t -0.8953278106953133\n", + "10111110 \t -0.8956916009466214\n", + "10111111 \t -1.5952844524270187\n", + "11000000 \t -0.09766182644377852\n", + "11000001 0.0027660155477891024\n", + "11000010 0.002358844093014456\n", + "11000011 \t -0.09719495907902975\n", + "11000100 0.006198981989517183\n", + "11000101 \t -0.09331540208705302\n", + "11000110 \t -0.0937676868424151\n", + "11000111 \t -0.3932637160825976\n", + "11001000 0.003790497417419547\n", + "11001001 \t -0.09582221751549458\n", + "11001010 \t -0.0961725685742314\n", + "11001011 \t -0.395766928670757\n", + "11001100 \t -0.09233546317386332\n", + "11001101 \t -0.3918904041749156\n", + "11001110 \t -0.39228586853423875\n", + "11001111 \t -0.8918224546989035\n", + "11010000 0.0020368253931716263\n", + "11010001 \t -0.09758213016936046\n", + "11010010 \t -0.0979214398809718\n", + "11010011 \t -0.39752204060711605\n", + "11010100 \t -0.09414135963831538\n", + "11010101 \t -0.39370254126898563\n", + "11010110 \t -0.39408696428118417\n", + "11010111 \t -0.8936297910754665\n", + "11011000 \t -0.0965056050008466\n", + "11011001 \t -0.39616511748786043\n", + "11011010 \t -0.3964476068034337\n", + "11011011 \t -0.8960887644540596\n", + "11011100 \t -0.39267055905691195\n", + "11011101 \t -0.8922722976120638\n", + "11011110 \t -0.8925999002282248\n", + "11011111 \t -1.5921832839469887\n", + "11100000 -0.0001448584652826712\n", + "11100001 \t -0.09977288103841842\n", + "11100010 \t -0.10013336680114415\n", + "11100011 \t -0.3997430345378914\n", + "11100100 \t -0.09618910398817793\n", + "11100101 \t -0.3957593526294516\n", + "11100110 \t -0.39616495169276367\n", + "11100111 \t -0.8957168454976492\n", + "11101000 \t -0.09862229367682729\n", + "11101001 \t -0.3982908731744448\n", + "11101010 \t -0.39859453854113247\n", + "11101011 \t -0.8982447632023616\n", + "11101100 \t -0.3946533082243009\n", + "11101101 \t -0.894264113790056\n", + "11101110 \t -0.8946128924573304\n", + "11101111 \t -1.594205343186698\n", + "11110000 \t -0.1004202323476302\n", + "11110001 \t -0.400095052474865\n", + "11110010 \t -0.40038767649442764\n", + "11110011 \t -0.9000441417852743\n", + "11110100 \t -0.39650347133530794\n", + "11110101 \t -0.8961205175306814\n", + "11110110 \t -0.8964582548508304\n", + "11110111 \t -1.596056946209815\n", + "11111000 \t -0.3988924218143912\n", + "11111001 \t -0.8986077988661074\n", + "11111010 \t -0.8988436024896325\n", + "11111011 \t -1.5985406247049612\n", + "11111100 \t -0.8949624298266474\n", + "11111101 \t -1.5946200329465021\n", + "11111110 \t -1.594900949870614\n", + "11111111 \t -2.4945401981540805\n", + "--------------------\n", + "Best sol is 10001100 with cost 0.006864651880631345\n" + ] + } + ], + "source": [ + "\n", + "print(\"solutions:\")\n", + "best_sol = None\n", + "best_cost = None\n", + "for s in [''.join(i) for i in itertools.product('01', repeat = assets.N)]:\n", + " c = qaoa_portopt.cost(s)\n", + " if best_sol is None:\n", + " best_sol = s\n", + " best_cost = c\n", + " elif c > best_cost:\n", + " best_sol = s\n", + " best_cost = c\n", + "\n", + " if qaoa_portopt.isFeasible(s):\n", + " print(s, c)\n", + " else: \n", + " print(s, '\\t', c)\n", + "\n", + "print(\"--------------------\")\n", + "print(\"Best sol is \"+ best_sol + \" with cost \" + str(best_cost))" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Sample cost landscape" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "qasm_sim = Aer.get_backend('qasm_simulator')" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Calculating Energy landscape for depth p=1...\n", + "Calculating Energy landscape done\n" + ] + } + ], + "source": [ + "qaoa_portopt.sample_cost_landscape(qasm_sim, 1024, angles={\"gamma\": [0,np.pi,50], \"beta\": [0,np.pi,40]})" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def plotLandscape(field, title, interpolation='bicubic'):\n", + " f = plt.figure(figsize=(6, 6), dpi= 80, facecolor='w', edgecolor='k')\n", + " _=plt.xlabel(r'$\\gamma$')\n", + " _=plt.ylabel(r'$\\beta$')\n", + " ax = plt.gca()\n", + " _=plt.title(title)\n", + " im = ax.imshow(field, interpolation=interpolation, origin='lower', extent=[0,np.pi,0,np.pi])\n", + " divider = make_axes_locatable(ax)\n", + " cax = divider.append_axes(\"right\", size=\"5%\", pad=0.05)\n", + " _=plt.colorbar(im, cax=cax)\n", + "\n", + "plotLandscape(qaoa_portopt.E, \"Expection value\", interpolation=\"None\")\n", + "#plotLandscape(qaoa_portopt.E, r'CVaR with $\\alpha$='+str(qaoaec_cvar.params[\"alpha\"])) #, interpolation=\"None\")\n", + "plotLandscape(qaoa_portopt.Var, \"Variance\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "def searchBestSolution(qaoa, depth, verbose=0):\n", + " # Verbose: 0 = None, 1 = Best only, 2 = all\n", + " hist=qaoa.hist(qaoa.angles_hist['d'+str(depth)+'_final'], qasm_sim, 1024)\n", + " sorted_hist = dict(sorted(hist.items(), key=lambda item: item[1], reverse=True))\n", + "\n", + " if verbose > 1: print(\"Classical best result: \", (best_sol, best_cost))\n", + "\n", + " i = 0\n", + " best_s = None\n", + " best_freq = None\n", + " best_i = None\n", + " best_c = None\n", + " for s, freq in sorted_hist.items():\n", + " if s == best_sol:\n", + " if verbose > 1: print(str(i)+\" -->\\t\", qaoa.cost(s), s, freq)\n", + " best_s, best_freq, best_i = s, freq, i\n", + " best_c = qaoa.cost(best_s)\n", + " elif i <= 30:\n", + " if qaoa_portopt.isFeasible(s):\n", + " if verbose > 1: print(str(i)+\"\\t\", qaoa.cost(s), s, freq)\n", + " else:\n", + " if verbose > 1: print(str(i)+\"\\t\\t\", qaoa.cost(s), s, freq)\n", + " i = i + 1\n", + " if best_s is not None:\n", + " if verbose > 0: print(\"Best sol (rank, cost, freq):\", (best_i, qaoa.cost(best_s), best_freq))\n", + "\n", + " \n", + " return best_s, best_freq, best_i, best_c" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{}" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "qaoa_portopt.angles_hist" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 10%|█ | 1/10 [00:00<00:08, 1.06it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 1 )= 0.08067517405076155\n", + "Best sol (rank, cost, freq): (50, 0.006864651880631345, 6)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 20%|██ | 2/10 [00:03<00:13, 1.70s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 2 )= 0.10103095672695425\n", + "Best sol (rank, cost, freq): (56, 0.006864651880631345, 6)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 30%|███ | 3/10 [00:06<00:17, 2.56s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 3 )= 0.12079932098816727\n", + "Best sol (rank, cost, freq): (42, 0.006864651880631345, 6)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 40%|████ | 4/10 [00:12<00:23, 3.86s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 4 )= 0.11527252394282568\n", + "Best sol (rank, cost, freq): (114, 0.006864651880631345, 1)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 50%|█████ | 5/10 [00:22<00:30, 6.01s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 5 )= 0.10170289526647305\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 60%|██████ | 6/10 [00:37<00:36, 9.01s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 6 )= 0.08807727137294126\n", + "Best sol (rank, cost, freq): (36, 0.006864651880631345, 3)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 70%|███████ | 7/10 [00:55<00:36, 12.12s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 7 )= 0.1039965668251942\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 80%|████████ | 8/10 [01:17<00:30, 15.15s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 8 )= 0.09225442439271589\n", + "Best sol (rank, cost, freq): (150, 0.006864651880631345, 1)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " 90%|█████████ | 9/10 [01:45<00:19, 19.19s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 9 )= 0.13552138723821758\n", + "Best sol (rank, cost, freq): (16, 0.006864651880631345, 14)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 10/10 [02:18<00:00, 13.86s/it]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cost(depth= 10 )= 0.17989536974217735\n", + "Best sol (rank, cost, freq): (8, 0.006864651880631345, 17)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "maxdepth=10\n", + "for i in tqdm(range(maxdepth)):\n", + " qaoa_portopt.increase_depth(qasm_sim, 1024)\n", + " searchBestSolution(qaoa_portopt, i+1, verbose=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "hist=qaoa_portopt.hist(qaoa_portopt.angles_hist['d'+str(maxdepth)+'_final'], qasm_sim,1024)\n", + "plot_histogram(hist)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Classical best result: ('10001100', 0.006864651880631345)\n", + "0\t\t -0.09892834029424491 10101001 60\n", + "1\t 0.0030902804805961193 10100100 42\n", + "2\t\t -0.0979214398809718 11010010 36\n", + "3\t\t -0.09573257650909128 01010110 30\n", + "4\t\t -0.39650347133530794 11110100 21\n", + "5\t\t -0.09414135963831538 11010100 19\n", + "6\t\t -0.09977288103841842 11100001 19\n", + "7\t\t -0.400095052474865 11110001 18\n", + "8\t\t -0.10013336680114415 11100010 17\n", + "9\t -0.0001448584652826712 11100000 16\n", + "10\t\t -0.3967993169187254 10110101 16\n", + "11\t\t -0.39370254126898563 11010101 15\n", + "12\t\t -0.09997484516477262 01101001 15\n", + "13\t\t -0.09618910398817793 11100100 14\n", + "14\t\t -0.09931487898812885 10101010 14\n", + "15\t -0.0013522162694326045 01100001 14\n", + "16\t 0.005083153117060091 10010100 14\n", + "17\t\t -0.3946533082243009 11101100 12\n", + "18\t\t -0.395766928670757 11001011 12\n", + "19\t\t -0.09822012337979902 01011010 11\n", + "20\t 0.0007033929974177289 01010001 11\n", + "21\t\t -0.10170985433451096 01110001 11\n", + "22\t 0.0020368253931716263 11010000 10\n", + "23\t\t -0.10195588133790268 01110010 10\n", + "24\t\t -0.09665217985005481 00101101 10\n", + "25\t\t -0.1003879998210524 10100011 10\n", + "26\t -0.0006354768544620804 00101001 10\n", + "27\t\t -0.10134495058660642 01100011 9\n", + "28\t\t -0.0948507142301469 00001100 9\n", + "29 -->\t 0.006864651880631345 10001100 9\n", + "30\t\t -0.3982908731744448 11101001 9\n", + "Best sol (rank, cost, freq): (29, 0.006864651880631345, 9)\n" + ] + } + ], + "source": [ + "sorted_hist = dict(sorted(hist.items(), key=lambda item: item[1], reverse=True))\n", + "\n", + "print(\"Classical best result: \", (best_sol, best_cost))\n", + "\n", + "i = 0\n", + "best_s = None\n", + "best_freq = None\n", + "best_i = None\n", + "for s, freq in sorted_hist.items():\n", + " if s == best_sol:\n", + " print(str(i)+\" -->\\t\", qaoa_portopt.cost(s), s, freq)\n", + " best_s, best_freq, best_i = s, freq, i\n", + " elif i <= 30:\n", + " if qaoa_portopt.isFeasible(s):\n", + " print(str(i)+\"\\t\", qaoa_portopt.cost(s), s, freq)\n", + " else:\n", + " print(str(i)+\"\\t\\t\", qaoa_portopt.cost(s), s, freq)\n", + " i = i + 1\n", + "if best_s is not None:\n", + " print(\"Best sol (rank, cost, freq):\", (best_i, qaoa_portopt.cost(best_s), best_freq))\n", + "\n", + "\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "qcomp", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.3" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/PortfolioOptimization/GeneratePortfolioCases.ipynb b/PortfolioOptimization/GeneratePortfolioCases.ipynb new file mode 100644 index 0000000..8971889 --- /dev/null +++ b/PortfolioOptimization/GeneratePortfolioCases.ipynb @@ -0,0 +1,346 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Generate timeseries and cases for portfolio optimization" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "#from openquantumcomputing import QAOAPortfolioOptimization, QAOABase\n", + "#from openquantumcomputing import Statistic\n", + "import asset_loader\n", + "\n", + "#from qiskit import *\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", + "#from qiskit.visualization import *\n", + "from tqdm import tqdm\n", + "import itertools\n", + "\n", + "\n", + "from importlib import reload" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We generate datasets through the `RandomDataProvider` in `qiskit_finance`, and generate timeseries for 100 days for a different sizes of sets of assets. \n", + "The selection criteria is that we only want assets that do not crash, meaning that their timeseries reach 0 and stays there.\n", + "\n", + "In the following, we store the seeds for 100 valid sets of assets with $N = 2, ..., 20$." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\Users\\havardh\\playground-win\\quantumComputing\\optimization\\PortfolioOptimization\\asset_loader.py:41: UserWarning: FixedFormatter should only be used together with FixedLocator\n", + " axs[0].set_xticklabels(axs[0].get_xticklabels(), rotation=-30)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(12, 101)\n", + "[22.6123522 83.56846026 20.71079507 37.69119479 67.57089469 17.74460264\n", + " 83.59385007 33.00269779 78.81371367 0. 43.60974642 95.46294669]\n", + "(array([9], dtype=int64),)\n", + "1\n", + "[9]\n", + "[22.6123522 83.56846026 20.71079507 37.69119479 67.57089469 17.74460264\n", + " 83.59385007 33.00269779 78.81371367]\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "reload(asset_loader)\n", + "assets = asset_loader.AssetData(12, seed=0)\n", + "assets.plotAssets()\n", + "\n", + "\n", + "np_data = np.array(assets.fin_data._data)\n", + "print(np_data.shape)\n", + "print(np_data[:,-1])\n", + "invalid_indices = np.where(np_data[:, -1] == 0)\n", + "print(invalid_indices)\n", + "print(len(invalid_indices[0]))\n", + "print(invalid_indices[0])\n", + "num_valid_timeseries = invalid_indices[0][0]\n", + "print(np_data[:num_valid_timeseries,-1])\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "23378\n" + ] + } + ], + "source": [ + "valid_seeds = {}\n", + "largest_set = 20\n", + "numSeeds = 1000\n", + "counters = np.zeros(largest_set+1, dtype=np.int32)\n", + "counters[:2] = numSeeds # Treat N = 0 and N = 1 as full already\n", + "for N in range(2, largest_set+1):\n", + " valid_seeds[str(N)] = np.zeros(numSeeds, dtype=np.int32)\n", + "#print(counters)\n", + "#print(valid_seeds)\n", + "\n", + "seed = 0\n", + "max_seed = numSeeds*1000\n", + "while not np.alltrue(counters == numSeeds) and seed < max_seed:\n", + "\n", + " # Load timeseries for given seed\n", + " assets = asset_loader.AssetData(12, seed=seed)\n", + " data = np.array(assets.fin_data._data)\n", + "\n", + " # Check how many valid timeseries we've got until we get an invalid one\n", + " invalid_indices = np.where(data[:, -1] == 0)\n", + " N = largest_set\n", + " if len(invalid_indices[0]) > 0:\n", + " num_valid_timeseries = invalid_indices[0][0]\n", + " N = num_valid_timeseries\n", + " \n", + " # Put seed in appropriate box\n", + " while N > 0:\n", + " if counters[N] < numSeeds:\n", + " # put seed in this set\n", + " valid_seeds[str(N)][counters[N]] = seed\n", + " counters[N] += 1\n", + " break\n", + " # else, check if we can use seed for a smaller set\n", + " N -= 1\n", + "\n", + "\n", + " seed += 1\n", + "\n", + "print(seed)\n", + "#num_valid_timeseries = 20\n", + "#for " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "last seed for 2: 16490\n", + "last seed for 3: 17016\n", + "last seed for 4: 19309\n", + "last seed for 5: 19838\n", + "last seed for 6: 22681\n", + "last seed for 7: 23377\n", + "last seed for 8: 23358\n", + "last seed for 9: 23202\n", + "last seed for 10: 22875\n", + "last seed for 11: 22439\n", + "last seed for 12: 21757\n", + "last seed for 13: 19331\n", + "last seed for 14: 16934\n", + "last seed for 15: 14464\n", + "last seed for 16: 12095\n", + "last seed for 17: 9713\n", + "last seed for 18: 7257\n", + "last seed for 19: 4801\n", + "last seed for 20: 2431\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for N in range(2, largest_set+1):\n", + " plt.plot(valid_seeds[str(N)], label=str(N))\n", + " plt.legend()\n", + " print(\"last seed for \"+str(N) + \": \" + str(valid_seeds[str(N)][-1]))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Save and read" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "import json, os\n", + "\n", + "filename = os.path.join(\"data\", \"qiskit_finance_seeds.npz\")\n", + "np.savez(filename, **valid_seeds)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "seeds = np.load(filename)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Some examples" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "assets = asset_loader.AssetData(7, seed=seeds[\"7\"][12])\n", + "assets.plotAssets()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "assets = asset_loader.AssetData(3, seed=seeds[\"3\"][82])\n", + "assets.plotAssets()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "assets = asset_loader.AssetData(17, seed=seeds[\"17\"][99])\n", + "assets.plotAssets()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "qcomp", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.3" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/PortfolioOptimization/asset_loader.py b/PortfolioOptimization/asset_loader.py new file mode 100644 index 0000000..e555719 --- /dev/null +++ b/PortfolioOptimization/asset_loader.py @@ -0,0 +1,60 @@ +import numpy as np +import matplotlib.pyplot as plt +import datetime + +from qiskit_finance.data_providers import RandomDataProvider + +class AssetData: + + def __init__(self, N_assets, num_days = 101, + seed = 0, start_time = datetime.datetime(2020, 1, 1)): + """ + init function that initializes member variables + + :param params: additional parameters + """ + self.N = N_assets + self.num_days = num_days + self.start_time = start_time + self.end_time = start_time + datetime.timedelta(self.num_days) + + self.tickers = [("TICKER%s" % i) for i in range(self.N)] + self.fin_data = RandomDataProvider( + tickers = self.tickers, + start=self.start_time, + end = self.end_time, + seed = seed + ) + self.fin_data.run() + + self.cov_matrix = self.fin_data.get_period_return_covariance_matrix() + self.exp_return = self.fin_data.get_period_return_mean_vector() + + def plotAssets(self, figsize=(12,4)): + fig = plt.figure(figsize=figsize) + gs = fig.add_gridspec(1, 3) + axs = [None]*2 + axs[0] = fig.add_subplot(gs[0, 0:2]) + t = [self.start_time + datetime.timedelta(dt) for dt in range(self.num_days)] + for (i, ticker) in enumerate(self.tickers): + axs[0].plot(t, self.fin_data._data[i], label=ticker) + axs[0].set_xticklabels(axs[0].get_xticklabels(), rotation=-30) + axs[0].legend() + axs[0].set_title("time development") + + axs[1] = fig.add_subplot(gs[0,2]) + im = axs[1].imshow(self.cov_matrix) + fig.colorbar(im, ax=axs[1], shrink=0.8) + axs[1].set_title("Period return cov. matrix") + + def plotPeriodReturns(self, figsize=(8,4)): + fig = plt.figure(figsize=figsize) + gs = fig.add_gridspec(1, 3) + axs = [None]*2 + axs[0] = fig.add_subplot(gs[0, 0:2]) + t = [self.start_time + datetime.timedelta(dt) for dt in range(self.num_days)] + for (i, ticker) in enumerate(self.tickers): + axs[0].plot(t, self.fin_data._data[i], label=ticker) + axs[0].set_xticklabels(axs[0].get_xticklabels(), rotation=-30) + axs[0].legend() + axs[0].set_title("time development") diff --git a/PortfolioOptimization/data/qiskit_finance_seeds.npz b/PortfolioOptimization/data/qiskit_finance_seeds.npz new file mode 100644 index 0000000..b184611 Binary files /dev/null and b/PortfolioOptimization/data/qiskit_finance_seeds.npz differ diff --git a/Precision analysis.ipynb b/Precision analysis.ipynb deleted file mode 100644 index 673a8cc..0000000 --- a/Precision analysis.ipynb +++ /dev/null @@ -1,539 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Precision analysis\n", - "This notebook demonstrates the effect of the relative error tolerance." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from qiskit import *\n", - "import numpy as np\n", - "import pylab as pl\n", - "import networkx as nx\n", - "from qiskit.visualization import *\n", - "from qiskit.providers.aer.noise import NoiseModel\n", - "from qaoa import *\n", - "from pylab import cm\n", - "\n", - "from matplotlib import rc,patches\n", - "from scipy import optimize as opt\n", - "\n", - "# Parameters when sampling the entire parameter space\n", - "SAMPLING_E_ATOL = 2e-2\n", - "SAMPLING_E_RTOL = 1e-2\n", - "SAMPLING_DELTA_V_RTOL = 1e-1\n", - "MIN_SAMPLES = 64\n", - "MAX_SAMPLES = 32768*16\n", - "SAMPLING_CONF_IDX = 2\n", - "LANDSCAPE_RESOLUTION = 16\n", - "\n", - "# Parameters for error tolerance iterations\n", - "N_INITIAL_GAMMA = 5\n", - "N_INITIAL_BETA = 3\n", - "N_REPS = 8\n", - "MIN_E_RTOL = 2e-1\n", - "MAX_E_RTOL = 4e-3\n", - "N_E_RTOL = 6\n", - "N_INITIAL_POINTS = N_INITIAL_GAMMA * N_INITIAL_BETA\n", - "\n", - "# Other parameters\n", - "WEIGHT_DECIMALS = 0\n", - "CIRCUIT_VERSION = 1\n", - "CIRCUIT_DEPTH = 1\n", - "\n", - "font = {'size' : 16}\n", - "rc('font', **font);\n", - "rc('text', usetex=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.0 %\r", - "100%\n", - "Max cost: 5\n" - ] - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "V = np.arange(0,5,1)\n", - "E =[(0,1),(0,2),(2,3),(3,1),(3,4),(4,2)]\n", - "G = nx.Graph()\n", - "G.add_nodes_from(V)\n", - "G.add_edges_from(E)\n", - "addWeights_MaxCut(G,decimals=WEIGHT_DECIMALS)\n", - "\n", - "pl.figure(figsize=(10,6))\n", - "pos = nx.spring_layout(G)\n", - "labels = nx.get_edge_attributes(G,'weight')\n", - "nx.draw_networkx(G,pos)\n", - "nx.draw_networkx_edge_labels(G,pos,edge_labels=labels)\n", - "\n", - "V1 = np.arange(0,)\n", - "costs=costsHist_MaxCut(G)\n", - "max_cost = max(costs)\n", - "print('Max cost: %d' % max_cost)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "backend_sim = Aer.get_backend('qasm_simulator')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now we sample the entire parameter space landscape and find the cost value at each point." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "landscape_n_gamma: 100\n", - "landscape_n_beta: 25\n", - "99.96%\r" - ] - } - ], - "source": [ - "(gamma_min,gamma_max),(beta_min,beta_max) = parameterBounds_MaxCut(G,decimals=WEIGHT_DECIMALS)\n", - "gamma_period = (gamma_max-gamma_min)*2\n", - "beta_period = beta_max-beta_min\n", - "\n", - "# Use the weights to find the typical Fourier frequency. Then pick LANDSCAPE_RESOLUTION points\n", - "# within each sinusoid oscillation at this frequency.\n", - "gamma_typ_freq,beta_typ_freq = spatialFrequencies_MaxCut(G)\n", - "\n", - "landscape_n_gamma = int(gamma_period*LANDSCAPE_RESOLUTION*np.ceil(gamma_typ_freq))\n", - "landscape_n_beta = int(beta_period*LANDSCAPE_RESOLUTION*np.ceil(beta_typ_freq))\n", - "\n", - "print('landscape_n_gamma: %d' % landscape_n_gamma)\n", - "print('landscape_n_beta: %d' % landscape_n_beta)\n", - "\n", - "gammas_landscape = np.linspace(gamma_min,gamma_max,landscape_n_gamma)\n", - "betas_landscape = np.linspace(beta_min,beta_max,landscape_n_beta)\n", - "\n", - "E_landscape = np.zeros((landscape_n_beta,landscape_n_gamma))\n", - "circuits=[]\n", - "for i in range(landscape_n_beta):\n", - " for j in range(landscape_n_gamma):\n", - " beta = betas_landscape[i]\n", - " gamma = gammas_landscape[j]\n", - " circuit = createCircuit_MaxCut(np.array((gamma,beta)),G,CIRCUIT_DEPTH,CIRCUIT_VERSION)\n", - " [E_list,_,_] = sampleUntilPrecision_MaxCut(circuit,G,backend_sim,None,MIN_SAMPLES,\n", - " MAX_SAMPLES,SAMPLING_E_ATOL,SAMPLING_E_RTOL,\n", - " SAMPLING_DELTA_V_RTOL,SAMPLING_CONF_IDX)\n", - " E_landscape[i,j] = -E_list[-1]\n", - " print('%.2f%%' % ((i*landscape_n_gamma+j)*100/(landscape_n_gamma*landscape_n_beta)),end='\\r')\n", - " " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Prepare the initial points from which we will do the optimizations." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "delta_gamma = (gamma_max-gamma_min)/N_INITIAL_GAMMA\n", - "delta_beta = (beta_max-beta_min)/N_INITIAL_BETA\n", - "\n", - "initial_points = np.mgrid[gamma_min+delta_gamma/2:gamma_max-delta_gamma/2:N_INITIAL_GAMMA*1j,\n", - " beta_min+delta_beta/2:beta_max-delta_beta/2:N_INITIAL_BETA*1j]\n", - "initial_gammas = initial_points[0,:].flatten()\n", - "initial_betas = initial_points[1,:].flatten()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Optimization landscape')" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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CGeoR7LWx8fHynGTQ9RbGRLRtSNX/fNTqXkLaNE2fsqKPAPwKABHSZi/bBwDw8hu/sIr/RBYGUEArcFYNZgvPmPISWzAWBbGjU64p2j4KiNFxPUVs3od3bBSiaiCtB7RlbarHgXxD2v7IwuzHcQluc1g1my8XleZVs9Q7AVory+aSZXLbPG9dNCzlAeR9SKT31OIV6XWXFmq79z5dPb283G5UNBzZ6z3BoS8Ky7XeSytv1QuJ3tqbdh++8lYahuHNsthg1hcAXq+x5QGa5j3TwplSKHMFZ6WNFZrkZVsca2NFzr02vb1qnn1NW7yDpbGjAKYBjybPbhTaImXaeQTYNNtSWLi870ecwY3lzRVgK8dZaOOLG+hqVApq5+nJF1T+5SJ9+WlfiPn9zGxAq11s4I3jlXPV5rrJY+oeyi2VCX1tvVDklrr1fmz09WvdDLh2Y+fsAgt5c/D78fezdO8gbd5P7aNhGH56mqYv5uJXADRtwZEFNA3OqEdNhLPyBZX1htHjDIxlvVst3rEtIa3FXk2os0YtHqqITa9vC4hZY2QhbYQCZ0q/47AGNuplm5tFgI0uZqCwtto2hIQ/JUmeti28FNZig2iI1G7fttqzZT6yDT90uVVYqHeS/H0bV8oD67khb0SSR2mLvdGiCywyXsqWnMGIB42+t/tuW3MPNIPZ69M0/Wiaps+GYXiHABoA/DKA97J2rZWcEqBR71k4pMm9ZhyeIiFJq20NuHnj1fZryYfz1MOe9G7uef2sAaCoPatvKxxmPGgRUOQwJp2P5HEhGkItn501sBVxaJMWI3BQO4wnnE4H9TZh9ALK7wLSmotGzzVAi4cr7Rwxqh7bR7Qm4UcBcatb9dxlOJbfF7M3uGn7uvUcJwIvFKh653jVbGRbkxvXa4GH9D7eAthvAmnDMLyOM2i9NZ+/B+CHJPes3GGg5Jz9eBiG783H3wDwUc3qziK+/1kG0KrgLAJdXn0PG1b76HHNeJI0L0tk/PuinpAWygnrOH4UyDwbR+UYUKCMadFGALbFeKfqjZMLqAFY7cPGf+1Kt2u7tm27RRGgA1om6T+y4KDHIoLaPdTuQ9goE+rcEujsbU7ynkQtFN/yHGq36+Ceu17eNGm7jeim1EAd+G/p1e2pYZrkfZaeVb38xi9MP/fxXwVAIEyAtGZAi8JZK5S1eNda4CxjWzq36lbhsIStu1QUiqL5a1q/3jDmjZOdQxbyMuPR/DVpnzfiWStetsPl8XhZIXoYT+LeaxzYyheT5Ykqx1JbDbpybfMerMh8o7Ysu9r8IvWep0Ur650HZ41Xo8wcpTEzMOHt65mpi6rmXr09X9vW9llYy96vW7sdZIt+a/jWJ9M0vSHV3X+MrJT2wi/2QWNbbHBAC3nPNEirha8aWPPqe8JcJqRqlY9G/UOCtBZAa4UxbwzpUfJ4Sh40LZwZ8aaZKosOJixWRhdgI9t78K09SmoCvw8thTXNu2Z50zRl9kCLAlp2iw4PEr3+nk3pPFLHx494LTT46bFfVo98Q82zk9nGJeIBsxLi+f1Ae9w1I7rKlc+rZk8za9xiJ7vS1Ju/B1LZ8OeWq3clPVhI41ouHLg+7bJIwAS0aGizF7BF+mrHWVhrgTrp+yQKas+SNy2TA6Z5orT+W4NaFtLKoxbW5IBmAVuTSCiUAhuFtQCoLVZ+MliTVoLW77O17ldsRQAtG2aM5MJFN8HN2l+W5+bdoti811AT7WupBvIy7SNJ8zwHreYG7tktJ6i0bTJqQ4YabEbCnby9BXbRvDXrLgh3qfsxiw2luSZpmPNS5gGaB1G9QC1SJvWN2M/WZfpCaCeVSe+6npBmeelq7WjlNeFKrX0tdEXnxF//bDgyCmQ9gW3E9ccRh7WSjgCsNsstm+Pye4cCCN2CqtbzYoUWW71enpcpulAha1eaozVX7UvVSq6PAEdNUnaPRO4aGFrbsIHD8wICOiTp/dYfwujWKJIHsIh7j6x5ZLxTfBzPg5sBNSAOa1lt7U178JDGtYqlz140moMG4ApoWe9ZFNq0xxYPXKZtK9hZx1aZpVZQ097NGTvR8CQ/90Ar2i8CehGYko5pmffotYVTB+HcK7ckwRrxqlFQA3BZ9clBjUryptUo6kWT2tfeD1SzE12k4Nnjc9Pmp9nmXpJeCwtavXSR/bd424iHRXr/RMKBWkh0aXv5WnLY1ZSBJy9/kENUrXcqMo/MvmtZUAPiUCWFdLVNbWtBLbbVyAOUl9RYvGg0zFn09HhYetAA27sVOY+CVyusWfasdhmbWh2Mssz3Xw3sRd/Fmp0MmEll2TCl1KfVmxbtnw15eoAWkQZxntSxB9GrVkANwGJ7Dsmjlr6he0ARL1oU0LJwRm34ixIs2zaYRRYJeHXS9g1R+KqFPQ4Xlm2tbe1u+PJ81mFYzdtmhQIz+W3W3DSglIAxuvlsRNY9OyPAJYFapG8GMre73VPsvfwgIS2rRZhTCnFa8BSBsgh09YA1y2bLo1cnnWv9I6p3avRRxAPGzyNhT69dDXAdhTKpTgOu7COU4yyAWaJzV+tnUAOwuv0UsLqpOxCDs5a8tOv0dC9aUQ2gWZ4uPmbGi5YFs0x+GpeU+L5lrleNIuHaiKJeLm1bCz6fFhjx5qbfM1Meu+aWWpHXw/M+RhcbZF6f3B5rfbxpmffScwNpdNsNwAhzXjoMa8iIAlovUMvCmmUv+hgBMw++IgDXo4+kmpBnFMqk8h7HLZBWHiksWXW1YFbkwVhPWIM3PwJqAMpiAgBifpqlbMgzAwoSOBXV3oXACm9a49G+1lwikJdZNCB5obRcr8jeW5m/VWtOmQaStYAELIHFuseqB2aRXDZvbtaqTTpODSRqY0pjW+N742qhzh65ahlv2hb5ac8NpBVJCwYAFubk99yMQlcLqLXAGli51LaljTUGhProOVctmPVSJLQplW8FZy39bwFmFpC1wlrYE0hCn8SbxsOeXPzOBJquwLOGoki9bFN+o0c8VjXes8yeaxacZbcH0dp4uV6ZuUekj2PbjkKT3DcOcPT1qPVkSfJy3fhcvFWbLXPRJAFSBIoy3rMeIdDlLZ90b9oWetCQFn3xLoBGxQGJl0UArRXUvL7Rx2xdBMwyQHbf4YyqJ6htAWk9Q5cWoFll1nGLeJgzC2oAPG9aNB+tNaTmebMAHY60fhFAiwJOdDPc1lWdVLW5Xj239MjcSskKSXJlVkdyUe+LBUgeIPr3lrT7SKs2a71q0feCNfa5ne1Vy3jPMgsLABnWIvPwvGnZ9/ODhjRL8orO2YsWgTOpPAtrCNZ5bbzHaJ0FYpE67fxZkjR37fn09KBFQpZZG1uFNLdULagB0Lxp90E14dFl2RrQeHvu1aOKJMxHFzXE5mt/cUf2BfPGyCiaaE/lbTMRTbbn9dq8PEDyICMDhrxPZh7aXGre494iBA/Wtgh/0vlor8UtPGjXeTyHEnPQJElgxstr/km2I+DWCmi1kGbBWlrabci4wSdBe49qJzJL+ggMQpkgDVQtD1g51kBD85hJZdJjq+eMP7/e3jJJFpjxc3X+sjcN0EOevcRDndlcqkyI0QtN1sJVtL/93Oz2GU9LZAztS1KClch42Z3rJU8bHT+7OrEHqPG20XnYdmRQ6gEq2iKE6MIGy84tQa1lEYE/h+dMHNBWuWhbgVktqFl9esCa1xbCsSsKYrSjBl61gAYAvzs/1sDaKIzF7VgfEQXmpNdNgi9e7j1mYCvSFqwPP95aEnzROij1Zhj26k0DYis6vby0WkVCna2AdsBpBVhZz1c07y5jM9KmJjyXHTMzrtfOgraWrSRqQM2ap2RfkpZbpgFGCzRacK151aybwGe8e71B7dZ6riCN3qsTCHjUeoNZD1DbCtC0/qo0EAOW4JOFtAygUf0ucqAmARqfi9YGbCz+MRLgjb+ureHJCKBZ2hrGOHTRMg3OOJjxMul5LmwsV3vykCfPS+MA17qpbYu8PDBrFSftU+v98jbDjdiy6jMhwIxdbjsKJNn5SfXRpPfIeBFI0hTxLmr9sp6wDKhpf4toiDKayO/NpTeotXjTavIrnytIozod2VO3vGgRbQFqEViD81gDaKImodEToYyWa+21tu4kDFlAVUTBSmr7iIyv2Ss2JJLgY5RyBdo4nGwVrrTgzbORlQVnWpnmRYPSJvTcbxvytKSBUCTZ388/O4ltM56tbAjWsxepy+RWtYwbHd/zelmgJa2OjKxO5ONpoJbZAiILXhpkWKAYBdGauUbDn9o8MmNZ5ZJq/iY9Fr08N5BmvqAc2IA62KrpVwNmWwCaKA5mHMoiMKa1keq1Np6iHi/Ndvn7FxuPBHsWnNF+HPI4tDletiyw8X4WkEFo30MShPHyqBeNzpGWe8/30m84FwRDntpWHDWbrAL1uVbnvtc5Wx4xb6FAxtsV3dIjai+qPIjJn1179d+yTyTRP5vzpUNd7Et8iwT0XjazoFajDKgBWM3n1qDm2d3i7/ncQBrV4lZQ0UUEwLawxvtkxvMATSpTWSgKZhKoRaCND+yFHC1xSCqKgJnWn4KW1YaWUYCj7R8pZY6HjZqqATRur8enXPJ2WcyrgZgJWMwGLYuGSNlz9UKedyULtKLbY9B+kUULa1sxQOsFVEUxeIldA3IbEBNwZ8DWA9RqtpHgNnSQyENqD9WEHLPKhCgjoeAtQEkaPxNy5cqEs1/ITfHZUPSD+9TaG80CMK4IdGX/famU/x+P5Xb8kZfx+pUmnCHiiHN+15P50Tr/J6Sc1v0uK/9do/yotHnC2j4R/vF+R8WeZkPrK7U5CvZLm3/C2nNbtOwxOX8yv+7Kilft7+q9R2r/IXnutUXiWHpPNvUdwX+ArVIckvqdx3+pqT+gecjygCaFOaUFAfyfNWZNDpr1XKw23r8t9Dcf/63wPNev1/o1lKT9fWueU8vGyL014uS+d3uLv95///Ffu8yldg5enlytpM+epuwihAcJaVyhF8X7O0fgrQXUtC9h/u93frCELg/UtLleROEsC2a8nQZqHJwsQNLASgMvC56iUMfhLGpbgzsKbbz+P1Ne3wJsgiJglgE2KMfZc6nOaw+jnD/nzPFi7LWHki4SKp70E3u8mpCvF5//4P3FeSYHy8v7AtY5ZR6gWXcuiH7pZBYaeLCxNTAUUKjN8/lbP/hfFucxoFy/lpkv5Oh4W3ouLWU9Tj0hdGnD/yx99oMfmvNoHavmMxP9m7bouQx3riRc1F24ycBazZdntA2cR/U9NJHKJ8YxfeTl/JyWSe14W16nSQo18v70rWy15315PylUKtmOriTlNvn8JDm5axlZYUmtTebcW5GpnfOXXrPB671QqdAvs7Ft7QpP7UvD805FVlVaX+A1eWQRYNTmSY+XIcO1zei9Ky1pNjK7wlMb2d3knye1bklh5QBGZOf49U1N8PLTtJzFrM0eodcHD2n8BdJ+PV8UhTKrXrLTAmj/5+OzB63oH85f4C+9C/zUY93DIWoLOLNgLbsdR6ZOWq2pQRyVB2b8YyGBVqSu6C8C+C/I+e+bH/8sgF9RbATy1njzDIxFQAysPT+32tOyUl4BWJe2Xn91kYS8yjNy03UA+Pzxf4kvfnANc/7m8IsAgJ9590/i9z/+E25/qsjqyyig1Xouajar1T12+hw8T4cHS1FPiZej9Dcf/62FB+3x8KsAgD/y7h/GH338R0Jj7KpTj5y133r8Q/z9H/z65fx/Gv51AMBr7/4y/sDjf6fJtibpMxhdcbqFhmnSdoB/NvXyG78w/bMfn/+oJYvgiMPZSX464OsvX8TxeMDXX750zkn78iVctt+I5v1YoSUpDGn1hWFL+vcPB+D3TToQmnBWGjxxjiMwptXRMskGP+btsuIXgaiHy9u0VrIzKvWjUUbLRwCvAfiMlNE67RhQN84dyT/rPHIcLfPGjc4p0xdGmfhvfr+PR2A8XTxph/F02YpjXJTNx4fzFWNkOUgHHPFbw7fwL02fzOfLOu9emryNVE7b28dr0Ip40jRAqw2rasqGolr3kop60x4Pv4rH0/cWfQpErH7Mk3PpNaX1vK81HwtaJJtREKB2o54b6zlHFJlbFtKsOfwPwx/Hvzb9d+Ic+DiR55J5vlLb4+LvZXbiC8UAACAASURBVL/+tEzq99nwBz+ZpukNaewH70kLi1+HLE+Y1p+35/0iHjpvDD5WV+9ZC5xlwIxP1Av/WYp4wm6tyH5r1opSrhHnv6HjVfPCktoxt2WVcY8Wby/NiZaHPWDCmJY3bdV/ubHtfZS1dUYkvFO7ZcZ9U88bqGs6Kl+SklrgpSegRdVjheVWqyEz3rSt5qCp13YrGWlgZ+muv81uqlWI0wp5eucaVGnQlPGWWWP81LuyTVUF0CLeMw/AeF+pLS2Lhjqjv9QjocVbS4MwQIa1f18o0+zx4yCo0TIJyCTQovW8v3Yuted2aL0HaJ6NiBRwpHlpmY1taX7Kq+++Uzmpq26xp5hsw/eief1KXwtEbgFcVJmQ0x959w+LX5JtgOTDn/dlrI1ZE06r9aJpY9/q7xmZ98+/+28uzu9rXmEE6DJg/eAgLfLbeX23AeVYqrOu7ZYnLSML4F56HPO6rcKbGe9ZC6zxYwnOWjxpkaT7rGeO99E2s/W8XU+w3BuN5smVvn9aaUfHrAA1sOlFPF8WKEU9YJo3LWtPs6HNMdo2Ie/+nd94/KeAG3xpRUOWcXv5PkV0IUX5wt4qHycb9ox4rehz93LQentyauCsxYvWI8zJX9MjDpuBWjYk+drjfztse8u90rLaFw4oqnphPEDjdZY3Teqf9aZpcwwBmgZd3HsGVmYBmgdv0fw0Xs6V+VLRYMhqb40vQR6HNgmwtHOQMgT6gfXlwKeAmgc+HlhpoOQBmuUNy9qz1AJgbPFAje7qvp7t+zfdfs41koCLllk3N6da5yZdz6VVqeV7osWDxudT6znz8pZqbGb6aa+pBGotkN47X+yh68FCGhe/ufpF0vYbgA5oUW+aBXgRZeHtogyg1XrMNDiTbPByaTxLFsx5uV9SaFRyN1mQp3nZtgA13k6qd2gl4rmS+vTwTPVun7HX6EXbUrcCpdpbWUVtlC/r3l60iD0/jywCMrHk8pYcNGkefuirHvg0+/QOBpm5aLplaLEXoEW8abf0uNUucrinl7XtJd5twJPXxgO0Vi8at7MSDfa2AFqmrtZ7xp+AF6KMwhV9S2cAj7fn9+rkENUb1LL1AW+aVFbryeJta+zcA5Dybgf1rHieqHrAWVR3AWieomBUXiMtB61ldWOP1YUR4PNsZBY9RLxovRWdz31Xr9cr8pwfJKRRF3bZfqPoGLlXpwRZ0rXbg6tab5pkMwxxFMaAJVhBqKOTawW0KIRp85FkvbAa/IDVS5L6SIAntdFATZMGahklvGlSl5bherTd2itXqZ737+y1yjIKXZF8IS9MK41Vyq6P8VBvJoep9YsuC0YWwFh9M168mjyzDJz18P7x9p7nrjWnMTufiKLvnbvwpvWGzQcJaZvLgqVMuDPiQUuFOXlHDmTZxH+r7q4Ajddb8CP1j4IYbdNyd4Fd98GD1ktbJlLflXp74iKvUXYlpLebfe22GZk9ztZ9dTiLjN8jVBpto7WPhFalRRg1ygCs9HfQNkDudZN3az6WaqA6owdy6bwn8rxp5dzyvDV9DqIT4LJyxDL5Y1K77ErLzFhcEUiqcft4YUit/w5tz4J6etOANfREPVFb5ZRFxl/Pee1NA+Tk+yI6RtZL5ifbawCxLZxlQ4410NdrI9ae4Vp5TL+N9f5Y27MXi2TqeikCa7fe+uMBQpqyEKCXPA8aPZbClS1jhOolKNJASZq0BGWZMOezqN4wVT5Wkk1e9siok2zy40ZlTGlT8GzUTNfq0/D0M0CWhaZb5oZZY3vz0DxdVrL51bblNch7XFq8IBYcRYGl1iuT2cZC7h/3mmXDuBFldssH4iH8Fpi+r/uebalIqPUBQtodaItc4wgMpiSFLDN9tpC0HxlwfltGnmjvb/9M/wiAWWNqlMNvB6XZDPwY8YbNlmXH6jnGFiB4xyoerluEULk3zRqTe9FoGW9XxD2H1/L157h3eCiT/C+BQG2YkbfbAviifaTxY2P7gKbVxcHNfn73Ec6ieWo9Q62ansFLW2eNE863kEEf2GrJSYtEJrtLgqSeA3MQ4y+0BWrafLS3bdQTleln1XOgoscWxEltrHuB0nPjeYxCtQZH0XZWWcRGzRhRex3lbWTbS729cxS2OFQBa3hqBTVrnkUasFnqDWfZLTtaEvK9sGFLXlkNdEaUyenT3n8euEVCsr0XjzxEPfxnqOiF8bTehiMizhi1PLMZgGnQky2vlUS7EVCDMQ/vbZrxYHn9eJ/ojdS9OWiANpJjCdok+4IXjcOTdW6189pIY2l1klpArVPEN3pLKEnbe7zWcFTTXzvnsjaMpXPx5H05R9UrCf5a7+W65bxYkdy12ry4lvH5HKKKPP9MCDTjjYv8vbZYrNDLTi2QZ+5nCjxISOtwU+Var1okb7/GRljaxKUd83uCmQRhgA1iVpsW1XrMpH4WjD0SymrOs/aMMKcHXaPQhrfTXr4sqGU9ZNrcMlLnXgdWt8wvi4Y8pUUAvK8FalbemARsWp7ael7LL6fsa9cTzrLh1B7J/pKdFlirnUPNWNEVlhLEU2U8btG/mbXoZetVlfdFDxDSbI3jaX3vzksl+oY8t1BqjtreYUfhuGYQ2k7yhmVgjbfzxo2oJvzJ+0hwxss1uNLal/NOgMYBRzuW+tBz6djrY41jgZcFZFEgzHrlaLPOKzo1UKKAJIUm61ZexkANWK5Wy6w45TfYjn7ptWxlkO3XspmsB2Y9NpKNzEMbv2UeEWW2vtDqPGiL2MisKo2ukO6hmtcno4w37bmDNFG94KyHInMR2wy4ehElOCvlT4RjzWhpU+roBq6aR4xCjgViXrusegCZ1l4CtKi3TGujAZpmrxHQRqGt1EazK41Jz7U6z14rRAZB7YXOUKapZYVnAa1IyFMDNWD55WnlqUX2JJO+mK09rLKhUa1P9MuwZSPZ1jsGSO1atm7o4RnKQkoNHJb3hwdt3lhZT2DtPVHvq6KgtkNajXpAXTWM1Rguf+YnQhtep4GZBGrcZlEGxI6wASurViCT2ke8YVE4K+cZ4DNy0CRIg1DmebkkUNPa8nJpjKwXzWorHXsa/bSH3vujWaJQxSHMDunowKZ5GDQvWHSLDmt1pnUTbknWVh9RG9b8uL2M7R4b4rausszmNfWCsMg8Im1r98brue2HZaNGtWHrGkVA7UFCWvg2D+MJ0EKfLeIMpIEWdUJxh1QVoEneNGC9s36BLqnOAjN6Xvpy+KG2iyQQ6+E90xRZEGC15eUWbGl1lg0OaJXeM3qswVbUmyb1iQKb50mzxtXKeH9trvx40W/5AbollGnS9yhbbschbX+h5YdpydYSrGnhSMtjl9WWm9qe29hfopnkegvwakOVeQ9RXZi0dcuNzHy4Mt5Ya/wIkGbzIa1y+8fJtp44zQvthXEfJKSFVbO6k6uHR6wKyDQNzCD3cHEPGIczeiwBl2SrqAXaekqac8u+Zhk4i+S0cTtBOCtNspDG22kAx8ukfhpQ1XjSLDjrBmrLi3LLys6esjxkFqjxY9n2+cWQYE0HPfta6K3kq9l2Q1PWg5WFJA3MareHaNlnrXVsaw6Z8bLyIL8FtrPvTc+uVec5dLzVw7fQg4e0Eaf8RUPa6yw/8DpfP2JT8qhpUm0VUAPWkMRDkRKccVmwdt8UgbGMV82DsagnTQtvUmhz4Kw8tkJatF8UsixY4+0zcObVee1n8Xw0umjA8q5F88s0L5jWX2tHw560DYCVPeuLRfJylPkBS1iz+i+fYy4Rv1WevZa9yTQw67UZrTe+ph73pOy5iMBTZNuVyHvJOt865HnfAQ14dr55q5S+u33vPDPJQ+a94l7/9IQAH7Kinq27hrUa75vmFdPqvXaZECcPd2oeuQSc0WPPI5bpr7Xl7aPeNKuPNQd+bNVJfQFI+Wh3GerM5Z6tQW1Z74eApC856l2TFhho/e9S0aT2LCRpX7697qEp2Y6odvFCZk6tfbNg1ppfFwG26N+/Fvju+o4IDxrSis7JecYLXQNCFKC043KeGUNyelntTG8abSh51LLQQ5+ctNeaRJVSu6xq3qYejEXz1qK5aVpbrX05NvLO+GOtVyzS3xpTgi0PFD0w02BLBS+jTmy//mDQUGcPaKtZyRnLPZOBinvVPElQJ9m2ZK3Y6/HlpeXpFHleshoIiNy3sjYfbTl+/rpVMwfPTk/VgJnnTYt64VqhuSbHzfr7ZjelrdVzAWk3EQc1QIY1T9E+0mIDUVbos1UalJWxtHZSG0kZiLSelwZP2hhWGw3MJCiT2htw1uoNi/TX7FjtJKiKQJrU1gNHbXwIdVDqLucnM9S5haybl1NQ8kCttANsWLOkQR0FwWuZfBFpAbHMHlh6fTw0RhWFp9K/Jidsi81Ue0Fa0VZeoMgeadnbiVl1sbSDtS3p82j9uLpPHrSiBwtp6VCnJ4lHeJl0DqGfZp8rsyrUHGdA25+a74sWAa5Iu8ycarx+Wv8IqPF2ESjzQC3gNYsCVhS4LPu1Y2mQpo1h2fHmgkCbxXOdcBerOnko08tL80AN0L1f2T3J1oC2hrytPAK9vUHel2g2Yb0cezlukblF6jJ2e0FCn5uAx7ZiAbB6f2aBKLpti/UdfxRsW5s9W/PJqDt34AFD2iaSoIuXWW0sRRYK0LZWOxHWLFCLblobubsAgu1qyZXazfavAbVMuJPbNXLNaFMLeLTHGuCSbNSMkwFFel4zdwnW1LYkF81Y1Vmg7fJ4w5urA0v44qC2rF97v3iYkn7xWLd1utrIhUx7qFduVe/NZ4u9zH03t4IzPic+rx7Kzi8D8dq2K94iFQmGPGC7zsnuK9VFPIDe34A+11uEPB8cpGlfi4fDCaceW24AOohZYKbdfYnLA7CMxLsSaANroqDG88skMCvtAHkvNGmjW0/efC1bFoxZ0Ga1kTxnDpDxKbUCmnfc6zEDapH5ZefM+7ptr+/DW4Q6rTCm1CbSR8rpWZfJu74XeffhzCSIc2W/7LdY6VgbFpS+gCO2vDF6eL0im+u23k826n3V2mb20/MWqURes8xdDaL2ojZukW8W0f2YxV2pbGbLAetSr5TTepA2FphlgCy7ItSS6lV7hPPGt+VJat40YPlCaOHNlrsLWLaorBfCAjUvod+ynwhbSuKwwR89aLH6ece9Hj1Qs8bOPFfv9THbkjBncIsNrsi9ATPScs3WdbaHjMOVlFOmSbJ7i1V5VL134K8NS3m5aFnPjGS3Vl6uXZmHBxk9VJtftm67XKmsjycDnqSav7d3n1vJtp1v6N9vt6eeS0g7jEfZq1ZYhDIJBTH6amkAVhPm9Nq1eNfKc1FhrTSijTmwAbZ3jE6UtqWSNrot5R4cWWXaXKx+GqhJdoJAJoGEdlwLWNG+tUDm2a+Brpr58nKzzxziZID2wgLU9FBnVl6yP1cG1AD7vog0z+3cNraHW5G2ojN7E/WtNlr1ctD42LV2JUDrcYP1nu3t0O6tISEG9kXLHxUyKJ3b2SCk9YtoCeT+fW69ULq0WW9NqNNbzSz3eYDaJE5MeaWcF0XArGalpzcX7dGSCWuA7GED/Ns4WVt6aCDmbQMSgbcWQANSXjHJhAU6XtsoXGl9MzaygEbtRWDNmlPrPNXX0wY0CmJaqFPKRysX7sjqSe3iLe1xVo6pbW2RwGV+CrRlc8o071t0Kw6q3H0eI54o34PV4z6bvJ2Ukxa1Vet1iyizD1xr+NOT9P6QvLzrfjz/0QKyZd7ksm75IyMi2Rsrg63t4Vt6WWvuqtBDDxLSNB1GIS9tPALHR3HgKa9YJJQp9St1mVeeziUCYtJzkMrcPdYK4BRo45Ly0LQJafKWsHJFIa0CviyzUTDT+lleIa3MG+PWoObBW3Ss2raL4xig9fSiFUWX9WugVs4BfZHAtd3yS4ovMrAUDV9mVAswmiIeLAvIarx/LXujRTfYrVUWPqX8xV7StmrJruyU3tte7p+2InprSXmK17r2nEDg/BplgP7BQ9pBeUEO4wlPvYUEFpd4zNL6yhaY0kKVGlRKEBdt60IbVzT5v3jnLEVevEbw4tJgyKqLgpTXLwItUXu1sBaZYwTWrDE2gbUcoEW8aJFf6dKvcSmcqf1ql3+Nr7+UtC9eL3dNGs9SzQrPyJYHcVsjO7cBxQp91oyRyW3TACHz+m2Zy8f7tOatyYtV/P31tPzHTE5badfbS2jf8eO2KJT5+zxoSBPfaOMJx5U3bQKOgw06l7ZCWWb7DE8UzrS6CHRF2tK50+MQuGXlAVbDDde9112qbwE0etwKaNZj1mYU1rSxMvZqYbAZ1taA9oKwUIADWosXLeslO5fpKz0vc3U8XVJI1Mtdiyibg1ZUuy+ZpIx3rMbb5o2phTqjtiLzbFH7TeqX75OMJE9tFNqudfF7xa772t7lFq33M8z9/beAR08PGtKKtJusv0C9aRrEcEW30qiRB4dbAJp2zMtoeS9F7FkAJZ1rZZH+tzqOAIo3V6l/Dfhk59gKgjXAejkmgBYIb1pbbmhetFYPhAZ0km3vS4jXR3N8qLJ5OJpaYMbro3m0Wu/R6dmsCZtye9I8Izqdkh5MIeoT+cFxwiG1D6CWgxYNWWq5lVw05BdJHbD+PjW3ZtPr+oF2Lz0XkGaqbMOxKMO2MBYZS2oTfcwCWjnPHN+FIiAU6ZuxF4UZaYxWOInMV4OaWjiL2rRgKms79FgPaK25aDxHzLoBOj3mv9qt7ROsLzxar3k0NN1VrpTXH4jBU6Tvsm3sC7gct2wPIoFWt704A/ZKnfe+Ph0Poff+4RCH/1VfBdz4DwrJA+zt6ecps/I0Y6fGk7cF5N0M0oZheA3AWwC+MU3T9wPtvwfgMwCvAsA0TR9kxrNWeI7jCScOZsASmKSuvcKaEphZZRlA0/rQ+fNjqy4DZpmcvKjdCPhY7WvtbXncCmhe3xpIi87LA7UeYywe9fwzL/fsIIAaEPOieeDjgZrUtrSXxpPH8b0Xt7hzQAs06TZlKLPyxGq8eVZIMgJdql0CT73BbJWOE2xveY49UDuMJ/H5c3CLeNrUMZzwKLD2OreEPDOhycyPkFuHPG8CacMwvAngFQDfDLZ/D8DfnqbpR+V8GIa3ynl3lRWegAw0tFyqE222zAfLvLQsoFHgy4QunwUPWuTcq7sFqGl1WUDz5r8FQGn9MvYz8xYf44sDJK8ZlQZoveSt9qxZ/g8sIU5fTHBbQOsS6nOgLHKbpuwChoXNUz1g8fYcqMQf/zfS6TguvMlcx+NBBDlx1wOswU3ytFmrPSPwJoVHtTsVZFc00z7RO2g8t+HOaZp+DADDMPwSzrDm6W3mbfsIwPcBdIO01Ya2ZfHA5Zx1sPLUMqIAJUEVPZbaZB4BG7Y8UPP6e4q+XpHX9i5ALQs0Xl0GbDJzroWnVqisBTTTLrtBurg57UldGEDbcHFAi3jRrNvgSKFMKexZ2vMxPfXYeLZF2b3KuLx6C8qiSflmePPEAcqGs4wHi8JYb08aAH/nAaxve0bnonnNPJDLqCU8Cljbc1w/KxnP87mv7HnTvF9RQOP9s3lzLbo77Fc0DMPrQvHnAN5ssXsOf7Jfo3wbDglspPLaV82CMa0+AmDao3VslUX6bSXttY1CWW3/iHcsCjiRfhLkSHaitiMQVTPPqO3oc1Fty7d1kjampYAWyTeTvGcaLGXCGJGtNtYXd/lFicJbZI+qSFtL2b3KsmN5oU7vrgJWWFICJlrW6vmitlYgpYFVeW92hrnrorf1e7bUSSAX0ci8a9zbpoVHFzKqpcUI6/PlD5vs9iIeWLV60Kw80Vqbku4dpOGcg/Y5K/tiq8FeGE94CmCxeMDzotV41TRAi8KaBGi9vGdWfbZ/j3dUBFS8sbKetx5gZrVp9aJtZbsGTjPjcS1sxe8YcD6XvWeXx2AokwORdtGP3nYpupDAs9MiLeyUtRv5sulxayZexr1q0ZCkVufBmNQv4r06G+dw5rwGW4dAj+PS+0wkgdzT46Ea3pqkMSyWK5cBDkAyrFnyNpHuqa292vcR0qRw6OcAMAzDK9M0rYBtGIa3AbwNAOPP/SyAioveWChnkD1mvMzyqnHwkkCMl3Pgkso0QKPzkQAy40HT6mu8abXvrruGNH7eAmpRr1fEVo1N67imXdVzUDYyTtwtAIjDWSakmA1zSoqC2nKO9V+SUp7NVput3nRLjBnMCkBlQ5IeiIU9X5o4bNH0GOstJ/1pel9PLznVymeNgdzTxLCH8bh43bmXLSsaJrX2U9O2nYl8vr0FPVSZffFuvUcacD8h7QvMKzqJ+PlC88rPDwDg5Td+wdva3pcFYlmvmgZsGUCjc4mWcUUuCi19PWXeaTUeq4yNXsBmzaMWzmq9aN6Ylg2rvzXm6pF5xixV7HNmwVntpp3X/nWAVqSBmt6+/dd3xEZ0nJZ7Zdbs/A/I3rLySKFAC0lqoGDCmObVOibuZpJNBemVLqKl4SzaDMa1Ua7IAFtPabAGrL1rUn6natf5wUSl/TBp3S+xp+4jpH2OtTftFQCQvGgZHQ6JXwAZEIuGPzOABuTBLDqP6EUj44GLvpNa4CozVi9PGD3PzKWnt8trkz2O1Ic9eHKivyYeZvHuECC1Ba6AVi7I3kXVSkBuBbQiCdQy+z3ZtuugrvXWSdJ5S84YoCfwHy+gNq7q3FCkF4LkEJYBJ+86GLHV4k3Trgfa9V6L8lCAOz66/qgSwqW9wc3yvlnbfNDFONHPEge/aOiT790mXVOi3rSeIdB7B2nTNH06DAOHsVcB/LiHfS3B+PqmHCGGPKVwoycJxqR6CdSsMCeEdrSsVbUetSw8eXVRr1XUTgugZecTgTRrbtn5ZL1imf6LcjuPDIhvGivtb2YtBJA8Z9FfvC15ZxlZiwl6qGXzVblNHZBZKyfFcYzQpbRS8gJlkl0rx8sKQbamcGTt8R/6tbJSa7J1i+8uCq76a0qB7YXGUGeBNXXbD8O7di7LbeshgZok6XN1Xzxq9wLS5o1uXyf7oP062xft2wDev9mExgmXN7AFSRlosPLMtEeQfh6sQThv+fVW0y/rJbPqIpCRsZPxKtX012x5QOZBmlSXgasw/LEsAS1kaay8jC7t98KYgL8iM7rxbJGXEybZKOPVJvX3utl17YKArTZ6jWzkGs0dM6GMwpgWjox4+49KuSarXQb0pLqVd8vor7WtgTX37cJfX7lD1MMWhTkKa6sVo4fycAWt6L5nEqgB8mfR+uHj7YGojd9TN4G0eVuNX8b5jgNls9ofTtP06dzkLZxB7EcAME3TO8MwfG8YhrcAvAbgtzfbyJbqslR6fllq4Ezyiml1EUCTYCzram9Rq0veq5PqMxCiXZxqPE7WvCIwZdmP2MrOxernJeuvypcXHWv1l7YdBq/zFLkLwGqaiTyy6G7lFqCV4wyo9bgJumX3em6AkPPFY9m2VlbWbmdhJvFfAG3un/GGWeUSnLV6z6TyTIShJszaA9ak7y3zu0zxshkrSa/Nl1tbRYBN2+KjeNaiHjFtj0JpG4/o51IDNToeL++pYZra8+zvk15+4xemn/v4r14uOicccMIBRxxwwojT6YDT8fyPuttPx8P5jUUvGEfiTeMfeK2s5dErk863hrSIot4ar34Lb1qrJyza1/LOdQFG8jmVLpIGHHnL7eX8LwOUtNstNezsH73JecQDpikCbRogRlZPerCn2cmM2XKLJvU5BL1kVnhSkphHpuWO0WstfeTHVplU3gPUMnOwAApCXcaTVnOd9X40Rq5Nntd9Uadfm7L32i3HPP/0Oi0/hWF53PZluWXo8zeHX/xkmqY35HGfM/EvjyMj/vOeaQdctuQwV8sE1dNzFjnnY2+tDGxo9VmQ8UIJPcAoYyfUpx60gFzeV23oMWabgVLDKksriV8dP3jhXd/CxoK//AVcA6bI1hjLfnab7Eay0XtSRr1kGpSltrSIbF9h/XiNnHvtrGuqdV2xxovOocabxj1dtZ416+0VCoVyKaHncVr/ncfj5X2hhUrpFh8jD3/S9xQJf56nvn6/9b7rB9Vd5ag9N5A2sj8U1+INMZ6WoAbgspiAg5U8mB7ylNrAOC7nMM6lMg+EeqkV0GrDlJExWmypv0ATvyKF/C0g77m6mKtIzteU3aF/US+8AbM5YrLdRKhU+VVNL9xyAv9o1lvjZTdu7RkK6Z3QHwEy3s4MUWqyVlVaEYRMeocHShr0eTZqQqtc3o/KaL8WWJO+W7zwp/V9pM2X/60ptBVYm0OhUghUgrUDfSThz0U/8iJqt2c7t1szQBbY7gLUngtIs1aElC++8z3NzsdP5zfTBdSOIxaLCTKKes00KNM+INH3Vs1fuAZiMmVSueeWl9ocjTqxfzA5nqtiBWPElR+1dWnXuC9YRJELkBzWq79wte5xZpWvV4f1ed167FFmJUFnNpaN5pABMPPIQl4yL5k/AjatoKaNY5VFQE1SBtQi7aIeNQ5cWVjLXPervGlEKmzO7w/Bw1a8ahasaaAGLK+FUg4oB7VzO93Tbf2g43W3BrXnAtIkHS5wVlyrxwWoAZJ7lnjVJNE3q3TMywD5A+L9cozU0TG0c09RwOJl0VCgdx7xXq3szy9KwoulSQIt0wOVCAPWfMitfKwWL02LB4vq1r8wIyusoqu5aLteif7anKLl0QR/b9+xa13SSwboUFZzjcqEIWtBzRq3N6hFbWVDnby9B2aeVyzahpe1wNsC3BisCSHQFxZANqqgBgirQCFv3aGtBtVgTVvNLW2rc0tQe+4g7YAjcFj++hzHE47HwwLUTrNL9uJVW8iBNdpMAjVA/rAB+gfHk2ZPKov+1WtshT1nRn5WI2BZ+29lbQEQE1ejye1rsKr35Nzlnj1RkPM3mnRWeVWECP0L8NKG9zpmVn55yiT2y/3ZF4axSz8AMbmftwc6QVnUy2SdZ0Etch6xY10vW71nVr/ItTfqRauBN63cAzKtXvKiynsJ0AAAIABJREFUqQ6KwQyBRsRhraiEQgF/fzTtnrpWOkMtqPXYhue5gjTp4lv+6BKoUa1CoLPFs8jFjL9po94zr7xGlnerJqRpgRZgwlaRBV2ZECFXZDsHD6ys8FMpy3iSeu1kf7URfyP0uGH3FsrazW5/4QEbLbfErxW5LTjinrGIbW/1ZWTVZehWSRkoy4JS5DgzpjSeVRYFvh51kjhw8XJrDA3Wsh60W3jT1NBnkR4C5flqmlcNWC8qoDlrgL0/mrawwFMG1PhnvcXz9iAhLXpBPTBXKgU1TfIKFf5mw/KCF/GeSeWWrA+CBmceZC3qbODSbu9zPl5PTtvAdHWs3Cw7kytlrf7LflAk0PJAw0qi1y4IWY+Rpqudr922d6Ut9hJajzGq3rReYeL1mDE4M3+xCysxu9xGKeMta4WlaPstQC1iOwNYvX6raN60yHXcgrOol+2Woc4inubDvWrAOgQaADUAK28aX1wA6Pujnev63Sy9Zb+1iB4kpFFpiwYOh/kPKoBakQVschiUaPEhGddlAHmjBp5IjaSQYnDT0qiXi7a1crIuZYpny4KZ1jCjtxrRkwR/1tjSuNHxrA985v6UVNbeXK0et4wioUhJkVvBFB0vYyyfH1/pRW1H51Ekta0BtF5bY6x27Qdg3ssysv2FV8aPtbKMF65mDto8InY0Rb10GWlgFvGklXZHdpwFM628F5y5XjQIz4OFQAEX1ACIsCYtLtAWFQBXUGv1pmVUA2oPDtI039AynCWHUBYxbgZsltxbZVA79OK5xatvQJi3iSBvJ51HPF3e6r9WUOP95PZtoUZtvNZ9vLzVh4ANVZpOGPHi4pzatbxqbR63CNxo4HQu01/PrJfrxC6ARxxSsNbbw9eyTUYUzIDALZWAvMcsCkzSuWfTshHtEwGz6NgRO61q8aSVdhykakHNsinZ1+xEoExruzgXQqAKqAFQYU1aXEC9asByUQHVfQa1BwdpnmiuCfWmAVjFuC2V3LXSNnzT2Yb9rXquTIyAF5CHqFbvmN3H9lZRWy0700v2s5uuZsf3vDOZ/rWw0ZIsb+2Ozz1n0p5mkrJ7k1njSLDWC8q22C7D20zW3bMsshLTA6NaQIuMUTOf6PieXattpi4qLb1FqrPaSZ60Fg9aTRtNGoRZ816V8YUF6z3VJFjjoEaP+ZYdfFFBbdizB6hF9dxBWlH5AiigBugQRP/4qr3onlsVinr0Ih4wD6ZaQCrfPuZxyoBaxqMXUfa2IhGY0wChF1wtoECxKXmUdE+cr5PgIaSvlwRHkVBj+VElAZuVZ0ZtL36YETv879AL3LKA1uQ1qwUzepx95MdQymk/r2/r2FFY1NpmbFFFvkEtKMsAm1bfy4O2lSQoo8cWqEHepgOAGAKVFhZYuWpUWWBrvYNBVM8tpAFLUNt0nErvmdYvsyM89yxxoOoFaxnw6gWFGRuSsttKZD6MmR34KRjUeLPWUPb1ym5U0fCrPA8KPEvPnufVsmxlJK3cksbv5VHL3gkgugiA1lfdjDwLZrys1Ztl2fLs9ILESJ8a71qmnQVlvN6yZSXhgx3z8TIeNM1DZymbi0bPxXICasadCmiuGgB1YYG0qOD8VP27E0TU6lXz9FxBGr1gS7+sl22P9CQ/VsU+XOr4yAOHForUYI2PIUOXDUN92saAq6ZPVNmQK6D/Cot+eCPeL21cmldWC3xl/Bcv53ZOmxXioysrNWgClqkHXNmtN7RxtTF7glpRDaCFFgJY22VkwIwetz7yY20sq3/L/LT+lk2rfcY2VQSArPZHpVyykwE1CbJ6etAsMDMBTKlfHeugBqw3vwXg5qrxW0stPf3y3QmK/B/a24HacwVpVBzULGnARkOltMzsb8xn2SeXiyXZ8bxn63od3DwoqoGvSP5YSwiV98+o5sbfVnvvPpLn83xemQoGOKjhS/litPa+eZC3vodegTTZayZBkwVIHKhoW75IgM+LjyWNI4FgFCItWYAW2UIjFNLMeLhqIa3Fmxa1I/WX+nr9M3PSzr3yaNtMnhkvH412mperB3xF+3leM3OBAGxAW9keSANqY72oAMDKqwbAvAcocPWmeYp42LYCtecO0ryLcHofrYP+R8mEvLQv9YgNCwgoCOWhzZ9D1Ob6OANqdaFXqU9Gt7hpuAZmETiwVnSW4yhkSJ482atG+yxDB+sw5hKoNOCK5Kb581+OQcs5qImbWhuweK63PXtimFgBtJT3TPOc1XjNyvGW3rSsJy0DkN7YkTa38KJ5EMPbeSFPDaA8sNKgLtq/KOI1s8ozXjcvT83YTw3AwqsGQL0HKFC3iMCDtS1A7bmANCtB2NvKoXY8zVaNB0zrF/G+SfDUw8Nmt9fhznpuWyxm4KrNK7NsivvwJd5DGpzZtymJhTkjIUMpjy2yAauUg6YBWWkj1V9t1MGadHFdQqMOalLYsyX8WWx5gGbmnh0PPpzVQFrLYw2gaX17glpkLtE+WpkmzSuW7ROBpQxwWfZqwawm74zX0fFFz5llN56nBmAVAh05oLH8tKLo4oGem+F6ei4gDbBBjZZJx5Ydqf56HAMKrZ/njYr0LfUUoKIwRoEuOsdM6NRqYz3vVlDLtLFy3KJeKs07K8FUJOQZ3fIhs4iA939xNRcdgqT5a6HP0/yusr1adfliml0t9GmtHLXm584jCGgh71kEVlogzbPb4t2K9s/OW+qvldd60qLeMK195JtV8jRlYC+b4J+V5yUzc8qwBDPLtudNu8gGNQAirJlbdTBv2rnMD21a6u1Ne24gDZBBTWt3PY692C2gIfWJeNP8lZZrkDosjnXQyuaa2fDXDmpR72RtLlmr5239Je/30xYLWKFKzaO1DE3aXjHJHu8v9V16vZbz1cKZkndK8qBxEONwFIU1aUUnD69KksKw0TZ0wcRlHlsC2hZwlnmMApo3VstzgNDWKquFNatNNPdMUzThH4G6TF9rPMuDVutNs2xEc9wu7fwFBcAS1miumuVN4/lpnrfsVt40E9KGYfhjAN4H8BMAf26apr8+l38LAKZp+o3NZ9hZVkgl4q2RznUbeU+RBT1SP2o/4tWSgc2GOamNZT/6GmwRAuV9eFtPnqeSq3VVoAdn1uICqUwEBtZHWrmpjU09ajwHrbSh4Uza7ojDCtjK/+f2+RWcHJCkXDQLCjVvmjVWxpsm7YXWDGgRyIkCjmU309cbO9Mn+zyk/pEyCwaiEOfllGWkQZVnV/M6Zcbg6gFSvAxYPxdp7hDKTNiTQQ2ACGsFyqg3jcryfLV61XrI+/O9Nk3TzwPAMAx/fhiG1wD8Es7LLl4ZhuEXAbw1TdP/vPE8u8vznNTkqmVDll57CZD+3uO/jn/58b/h2tRy0OzcNBvmrOel2baeb2Qlqvca6ufrD110UUgU1CKhSd7vg8f/CH/i8e9flHGw0ux6YU7JhrUYQQJACcqk+V1/7FzbyF60JbCV14TC2rksD2xcEqhp5VbYU/Om/c7jv4RXHv+Zxet1PV570YDOgNYCZ5Y9z1YE2LL9rT7ec4DQzior5//gMfDPP9b7WTZpHX+bWu0lcdDTQCsKWJJa+gI6mEUgKgJ8FqBpbf/SY+DPPNZBDVjAGr0lIvemARC35OA3Yr/0V2DtFt60YZq0u12ePWnTNP0Ncv4xgD9JPWjDMPxXAP78NE3/+5YTjeqlN35h+uc+/vWqvt6KQ62M9pX6Z8N/Fkj9teFP4N+a/koV4B1YfU0/aUzPrvUaRCC2NgctskhDU+aDl/Gm/cHhM/zd6TVI3rKsV03rI/WPetYkIOPAp0GlVU/rTpd3jQ2Sln1tfnRsaVztOUXm/VvDt/Da9HfV5wScPWmn4/lfF0CLwEoEzjI2o5CXmU9PUOPHWhk//18H4A3l+86zJwFPa7LQyB4j4/A+lo1Im3I8snbSeWZcy1bN/EcAbwzAb0zM3vz3pHf8IXBWQO0wni6QNo6n+XyuO6y/Z87Dat/1fqQmm5P2W8O3Ppmm6Q2pznubvcLOPwPwKi2YpunfG4bhPwbwF1KzugNl9iuTwESzE1nFmNnuwgo3AsDvwT8Rx8vkoMVAzpuzHOaMg1oG2Nb2eFutzPq7WzDmwdwSKOKg9lPz308Cpwxc8TIJMq6eMXsftPW2GWsv2vXXpO1po/V8wUCRVNYizXNGn3PNSk7qbXPnMAPaoqzVg8bPa+GM2rHgKdK/R1+tfW09jDLPnteflklesFpRL1Er8EVsSG280GbE46XVeZ6x2rDnoi3zqAGgXrXlooKrN+18bm9wq+2hxr1nkjet5+IB8886TdN/OwzDn5ym6S/PRR8B+Fho+r91mc2G8l4wC86iOU8R+IhAG4ecv/P4v8enP/gfL+P9leEccvmld9/Ev/L421VQps0pushA6ysBpvd8M/XcbpEHbxHPmPUeGU/L/sdDPG/sLzz+Ev/5D766nH9z+L8AAP/Ruy/jzz7+PWd7DNIiqz2l/LGlDdvztVzBuV4scL7QLIGrlEfDhlIO2jrUWbflhbYnGn9teBmftzZ/APhHjz/AP/7BX77Y+mz4gwCA3/vun8Y//fg/EOdFvWjlHAjsgXaeZF/PF3/0QEsDGu+4x/ys8a0yqW85/0ePgX/8g2vZb8yv9TfeBX7msd1fEgcdDiERe9K3rgVsVlkPwJPmZ4EbL/egC+w8A2i/9hj4r8nf71vz3+9PvQv86cc6qDHx+29r9+OWQO08tf4hzahNM9x5aTQMfxzABOBTKazJw6J3KSncaX75MuhYPq7BhNZrx9pKx2iCvuXp+ovDf4I/O/2n4pwtjxgf0wpX8nlYr8mBzDUTIrVe73LueTVX8MxA6nAUvGzHp6syScYexRedRnr8gtP2/GH/veMT/D/HR5dyCfZ0yNJzympDklYbKXwolZeySFhSCnfSdto8+HOKhFB5ufRcrOfLn9dvDr+If3H6Dd0mC3WejmNuk1oJpiJAtQWkaX29fpG+Xr+oXamfdf73B+DnJ7lNVr1CnfTYCnvWhDWzffg/Xp6xWRPylI5pmz88AB9Pch0AK/T5wiXEOX8H0XAnC3sCMjNkHQGZdJvfHH6xOtwJ4OxRA4BhGP7QMAzfxhnYgHP48zXI3rV7oWgCuQZLvN5qT21HPVRavQZJAPDiHLqKLg7wvF15j5scJpWAkM9dAjHLa1bAqwCXBFkcqPgPpMG6IEcu1vztMn/PXlBrBIDzvCb1E3Wd90/9v09I+ZML7BXQK0BXAE7yqvFzyxMnQU5k1SYNl3JPmrUxbRnz3MtfPQngYseT5D3TknzPYyz/wNybxiXNw/P0FUDTVAVoy0nH4cl7rIG01jGjfSLHWr1Wxs+/FPpY7Ysi3q2MWvv3lOcpi/TVwpPRkCevK7LOV3YiHrVlyHNRR7bkkMKV2S06JNV45FJvk2ma/g6Av1POh2H4Qziv9PzmvPJT9LTdF3krNjVvl9b2/JiDMx+AliDFx/mj7/6reAlfpUCPjx8Zm9uRXhMNJosPg7/m4pwVCCvgRYFrsC7Q/E8buYBrin6O6Pfy/EkayLGkd/9D4NH/tyx7NLefxvNzPx7Oj6fxyfy4hLciCnFL6DrnoFFwW7aRQ5vnp2SFN5dgZm1My8GG9ik9au6LKYmGU7mkMeRVqPZebgDw6rvv2PNgXrTlRAxAu052eRyFqlZIawUtDaBqQA7GsfX5j5z/U+/6kKdJgqpeoMVho6ftVnnhSA3AwPrxc+s5a2P8u+/qdoqUOxMAeshT2zvtek28PkkL1GqgLaJQuDNs7Axt/0LZT+0uRMOdkQR/ehxNlNfaenCW8VhZ3rQ8NC3LM1AmgaIGZVp7QPaIcRC7QFh5pO936ULN2/B66yKcuUBbslz1mjg38H6HZXnxztGcdCnUKnng5FDeAVqIUwv3eSFFbksKTUZDkN5caD23JbW1xuTzlmxbz+nSzgt1erd6ioBUD1jLQlptXW3byHEG0KTPee1nvwaarD6ZkGePcKfWVwtNanXW+D1Dnhm7i/Ys7DmezFWeRVLY81KXZAmvD1dzuDMq7mm7T6oBtBo4K3Wa58wHoTVQeVBG7dA5SXai8OiFUstX2Gq80wmH42nlEQMUGDuRY/rIy61j2l6q08osaZ8nyfmjXVgtRxH/5PELzeF6PMyPj4i9q/cNwFdPZ4B7itMIvIgnM7h9jdN4WEEb9bRRbxf1tq03pL16v6gHjZZrCwYsSd4r7oWTVDx3cl39ZS0ydkYXQCuK3ii9nHuAthWktUJZSx9UHmfqanRE/huTjhnpS8ewxtO8WRFFQ5NSH82G5HGjbSHURz1qwPq1sNoLYU9tlae0gEC6r6e34W2tBy3S7z44VDeRtVjg2iYOaBlQ8oDLC4FanjRvrjEbvmeNlpVjcUECgTLqGVO9YlK5dqHWwIseW3DmvQVaLtoaZNHjGkijXjQJ3Mr5vFh0AXAj8OirJbidxqcXaDuNpwWw0ZuiA8ARV7c9DX9SOOPn5zZXKOM5XefWHO7WNjzxXDQ678hnnc6V2pPCnlS8rBoAafjTgxkJznid1k+zb/XvCWctbbwy6zhTx8XrrD9xDajdQjWwptmBYssDQw5q3I4Ech6oScfcPu8bFL/xeuQG7Je+yo9ECmzeNhxRsLuPb7dNFYEvD4p4/2jIUMo3i7XTVotac5DH8oHx+nUqPh8StixgdoGyI2To4iAVAbUIoEVhzSuvlQdaUpto31Ep449frfsMc9kjAm3H41OcPW0ysJ2HoaG9JbB5sFZg5go7OQiLSAK1Uu6p9CvAJS14iIpDmxXqXE6UbbVBH/kxWHktYPFHDQa1es9epG3GDgJl0nkNoHnl2tvCq79LZWHNAq4izV6tFw2snwZqYOdandSmeNMAWHlpXBao9dz7LKP7+DZrViYWTOsjgMbBiJZHPGIeIFn9pHnZ40Y9a3pOWfGUAVhAGSCAmQZpHLxoOS2TLsxbe9N4f8D2gFFZ3jQOVrzdV0Jb2p5DWukjgVl5PJE60n44zitRx/Pf7nh8uvKwAVh52a6esQJgVzj7Ci/NU1uu4JS8URFFYUkDNUued0wr82x6cPhUBDXh2IKnGkBrhbQWwOrVF4njTLuMvL7PAqx5j2DHmi0Y/bkNzYsGrMe0oKsW0KickCf3pnFZHjXNm9Zb9/HttZk0L1gpkzxRvF8kB0wqi4JTxuNGn4M2f2sMDmYpKAPWYCbV00cNyLz2tIwfS7lr0jlX5OId+XREPGK8/itWxsOYFMQk75nUnl78tPLZ48k9bKd5VenlF+TsZbPuCPASvgIPeUp3GKAet69nsGuVtFEtlQRgUn2LNy0sumDgUmYcR963HlhxW/cZ0iwwqwE06Xxr3Xq8Ii/8GO1fjuHY8QDP86LxMhOujPpoe8ebpm3HYXnbenrTrukanhPpORV9oT1A87xnmdCm5ykr22vY3rRtwEzMK9OgjJ5zUIt602hZFtAkUOPlkrKfL+8TwuslONOOaXtaxz1opYyHQhUQEwGvvMbcw7YKiZ7z2A7jaQFrh8u7Ze1VW8Oa5mH6CtwbR8Okkoo3T5PUT4My3ibiOYt619StN4poqBPQAYXWWf94O8mmBkXZc37MbUpjtLaJHkvn91UcVmrnbYUoI9Bm1UfCnNZ4km0N1ngfL9zJz6U+IsCtvWkUxFq8aT3kXWOeO0ijF3B+8afAdT2Pec9sWFqWvYivQh63JbD523ToYc8YnIm5ZRyktLJab5rWLgprPXLRig1v5aakDKR5W298RY45kGVAjJ4D1wsXBzvSpgDbxEKiEqx9dbkBFZ2+BGvXsKik4o3z5IGa1qfI8rbJCx0OYtu1jVG5X+dBD3VqgBEBs1pA6w1pGqxF4Cza1ivrpuwWVIPfJKIaYMuCnRXipG34fHgdrc+EO7ldKeRZzi1QA2sn9VHr1940636eRV7u2i31ICEt45KkwFPkbZVhwZAGUi/h66C3Swa6rbxmKphx75ZUJoGZBHEwyqy2pRxCeQTSIm8B7aKlnfMyK3TJ23Ov2VfCMYczDmRK3tniAqUB21GwzdoMs51HxzWsfTXz1kvzZrjUq8ahp8AaDYt+LcBdVFGPVhH9PGt9OZCV8wPWG+1qe62ZkkDtbMw+53Uc7rKA5tVloI3P99aQVqUIiGUH0b46KyBOGzriGdNALOtNi7Qvc42GO3k/rUwDMw/AIm0v9VdvWlHGm9ZDtTlsDxLSJNGLNoWpZZu1VwpYA1qP3DMKX8UOB7Jl+68VYGyEs6+gQ5YEbiDnGthxgLKgrAbSPFjjbSxZkEbhCYgtKOAhy2IjC2gcxiiQUWArz0HznAHLUCc/58BWjg/nr5vry/H0DGezV03KL/NCiC8CIVAroFQrnl+m2VoC2kZ5accRq1AnYIOXBGZSG24nCmG8vsZ2r8cIpKUlQVnU2BO/iapRGTsJbhG4ynrfpH4SqGXmo9mU+mheuXIe9ZDxeW3oTcsoes2qucvKcwNpkjTwutb74BVtZ3vTbO9ZxHMme9yWcPbSV47XzKqDU6+1Bew8NA/SJGCLQBpvp8mDtKLsik/uPePQVs4lgPO8Z1qbI7NBzzWoo7B2xArWShi0eNW+frk8L5pfdvWqeYqCWlTabZ+sei4e8sx67QDY+WjniejlUp0Gba2Adt8hjR+HFIWyKIC1fWEvxcEtAWwaXFHTUpvoY7EB2E9ZAygOeBrwecAW9ZBpbcK2Zm8aWURg6b6EPJ8rSIuQbo1nbNlv3U7KLaPeMc97loGzqpDml0o5hDKpXoM8Wg+jj9aOH1v11kXG+rNbFxBrGw0uCl30PLJ9Bj3Wwpkcxij0WZ4yfq7A2OoCx2GtVH85rwZ9GSq4Fq8U366jKAJqBZSkzywFKv7DigMWred1xXYNlF1sHpc5aWo+GqADGa2T2nhlWwJaC3DVPprSQpe8swdkkcEyXrVRaP+IjUOBLQhrEghJ3jALxPg0+WcdkK9xHhRCONbmbT2nUhb1nNFj/qi2I960WeVzGgl5ejdf19RjNeiDh7Qa71h5UTOerGt7yyNGvWmet83zvh1nACT1veBMOkeireU5Q6AdWFsIxx7QabI8bgWKAHnVJT+mksKiFKQkQNM8aiOrl2CK12mesoPSXyrjsMY0HIFx9qS9+OWTRZ7a+WmfLu9MqpfwVRWoATJA8c+0tiWHBmXX+rbL3+lkwJ0GaoAOY14bC6Z69PEgDsHHzeFM6iABVfTLMQN05T1D+3AYK+20Ng2wlvGseWXlmNrn9vgcPCCy+kp10jwy4MbltRNy01ok5Zm1pmtwPVhIayVYOWdN97Kd68/lmgcsCmAc7rgnjuacvYiv8nB2hJ6LZvXJhEWt0Kd1zmGNlkn1/E9cC2qADmhS/pgkqR+FM+79AmTPmhaq1ADN85QBaxijc+Xtub1y/jIwfHm9byjPU7OgR/osHlDvwTo/pfN4mresfC5r8kCiYzeLQ5IEb1qdBlKaXa1PBtBqAcyCOVMFZmhjDaq4wWx+WWRCERjj7WibAmvl/ZMIhWrgZQFYFKy29KRJ9rU+EUCTnrvneVvVLUOeW+alXVe8HxfnUT1YSKPyqDZzdwB9jDigSeHPFwVg47CmhTZf/PJJHM4ooEXKIbSLQhztC9IGgXZAPahJfaL13GtmJfhLop4xDmjSvmb0kT8fDZhAyiS4Amt/IH0SnrOVvry2fXQpfHqtN16Xl/D1im9PsD9TkugF7nrRs8HMCnnWKAx9Vo6aP4gOMhnw8qBOAzvtXHushTVVkufsiVBG1eJNi9jiksKZGrBRD5zUDwh51yKgptVDaJsFKw+KtL5WvQV8GqBJ8iBPuPE6YOee1ealScBW+8PuuYA0wN6/zO6X2zIjC2ied61An+c9eyQBlgRXPMSplVvAFRlH6wfWhp6DtQN8UNPaSopcrz0okz4xtIyGMOkFR9oqQ4Ky8qgBGPfGSfXaeQTWLLtl0cCsLKhJqQeWoosCpBBnGcsKedZcNNOQJ63sFNuxf1q9Va71t6BO6yedS+Npj9VwBqy9ZxaccZiyBmhZuWnZ496zUaindVq/Uj8h5FXTQM2DGAl8ALtfqc+Oa4GbBWQaREqw6T3vhGry0mjIk8JZr7DncwNpEWlhzHNdBNBobpoNaPzOAjq86blnL375dOk90zxkXphzi9AnWD1YG3oOZgPkkR+XflDaclmfEakf9YQB61AkhTAobWl7yfuledR4O9qfQtOBtdOgisMY75/Vl7iCWoVHjYc3Ne+0FMb06gs8lby465h6yPO8wCG2cW2TLLjy4MsCKg+qvHaefa09lMcIvJmyQptSGYQ6qd5SK7g9QgzWNK8a7UfrDVCLgFIEYjQQ4vK8WlHb3rjWONY8JPtBsqFbcWR1K1B7LiHNAqxlu+XdBJZ9Za+Z5lHTAM3KPxMXHnz19TL3TPKAfUmOOURp7XvBGa+DcQ7WB6wdSDk/N0Kdk/FlcPQ+L18BI/ueHihYzW0A2HcQkLxkErDxthSuaNJ/DazR+UW9ZVY74ApqBNjGy/PWQU26WHFou4LW+g+4BK9rPfWmcc+aFPKUPGsZMKPjpORBGW9XY9caJ3vOy2oALQ1ntLHkPct41Hp7zTRRAKPHwPLDr+WkATLkVYJatE6yB6WO97MgqAbOaBkfJzKn6NwcRe4+UHPD9VZQe64gjQOXJM+LpvdZA9qLzBtmQRg/Toc3qTfMgy9ernnSWuAsA2q0D8ijAWsFxCh0PbHgLPPFN+sCH1/NyfIawBVJ86UgRi8gErDx18cKXWZgreHCJaoA2vwchy9xWfUpgZp0kTqysvOvUhZeEDxitD2whC8OYiNOkDa2bfWWSXabZcEZBy8N9iw4k+DJOtfaZMEsDGi0YQbQnijHUtvekjxllneMtpUIRPO4KYoAmtTeOpbGgNC2FQAlu9I4nh1P5nOz90uL5KPxBYoF1Pg1rwXUHiyk8V/jWv6LtjiAe9GsMCe3peWkZQFEnso2AAAgAElEQVTtsgjB2pCWAlfUqyaFRSOgVlvnhT/B+mDpDePerwJjFLxMQKv9EUOgjOaAj+T4EbFNf4Rd4I17xCQIk+CMvh4S6HmesyIL3F4W2mt9eFv2eg9HejG5gtrpsIYvYB2q5J9PDnGlXRFfNEDha3m8Dmn2ALVu0uBMAzGrXQS2pGNtHlp/rSwFaJmFAV7I01tQoEmCukdCmSYOX7S/5h0rdZHQKBDKT+PTiQKYZ4tOKzp2pJyXRc75XLLP9dJ+vV/aqumcl0ZledO0nSR6gdqDhTSqdZhF94xpXjSprxbm9MolQOMLBDigmflnX7LjWu9ZTW6aB2cRMJuPp+MVqCh0cS/YBdKoF231l4zVeSoQ9run66WTwpgEb49mwBlnOBskyGJQegGv0k5L8ufi9RzkrE/4l6QN7ye1pfloZd6H6yO9jdRpLMXSxesKbtyDZiX+03Y8tFns0PIT9PAnbyv1syTBX1oWnLXYjMJZBMy0/hzKqgDNAzGt/Al7tPplJa3OtMQ/mByyrHw0z9uWGD4DLVYbC86ssay5WWV8LjDOM3a1MkXZVZwWqFn36OTXpIgeNKRJ4U3txeFtNS8atyV53Eqdlp8mb7EhLxBYba/BQaoAGveORXLPPFDrBWcJMCtAJoFYUeQSLbWvkfTVQL1ndH4F3gq4XaCNAxv3rvELJoW4Xttn9BD9G0ob9mL+zX8ADkc5P+1IvGbcg0a9Z9LFjIYYOcQVaKKhSJ4/tkmYslYROJL6eP80mxJIWWNLoOfZqgK0SBgzA2iZT7s0UQ5clrTQpORVy4KadN6gVlNW/1po8mAxC5gZdd7UFpA9apr3LANr9+SKdRvJiwNkT5l8bIc5uRdNC39KsNYN0Hh4U+vjec82XPFJ88lo6PIJBTbyN7LWckVArQbSpGCE9Zv+EYAns7ftOEPZk+PZq3Y8noHt4mErsCZ5sDh8cVjTJMGbZzur8sTpxrzCF7O0kOB0OBde4WrtQZNXR10nq+2LxsOc1MtVA2bViwOikoBIa6cBmGXbsi+BltdX6q/ZqgI03ikDYNmrgSf6iffk5ZBpiwosUJPkhDyLuV4Ao9mP2s0CWqR/dGyprfT6EEk3W5e24uDetppFBDV6kJAWudOA5WWTvGjFrn7vTtlbFgl/rrxuNYBG672cs8iigwy4JeCMe82ox4z+Rq69bLeCWnS/cF7Ov3YeCcB2HAnAUFibzxcXEQmoNACLQJyk7DWEes/4lzINex7tsCf3pp3r1+FJydNG67VwZfHISeFIDeA4zEXg7nA4Le7bGVIE0DJQZo3jwVVmfKu/C2hW/ln00yz9bOsNaNLYma9IqY+1+vMZVuuPvahHrWY8r20gL62nWhYNAA8Q0rTfG3xRAK+jIMbbaXlq0v5opZ8V5tS36kgC2ok9cgDzwpvRVZ4WlAXaFTizvGb0stv797XVDpAXzQPL37qlnQRodFE9XbtVjouHDQjAGogxfr7Vp/UIfRFBUYHBAmgHclzqSjvIYU/Lm8aPz93X4cpz/TpvzYKqaP4Yb9cl76zIAx+rzLIn/dPsabaj5RzIIrarAM365Euf4i0XDniwJoEX/wBLoEbbSDakdncgF3iceq9NxD6ENhGwo3Uq/NkrPD1FFxG06MFBWpEFZVQ81FkeJfCywpwSjPE2lpdtuc1GENC+ZGXcqxbxpGl7qll7rVXAGc0107xm/BjkHKyc10Xv5ue1sTJL+GW11EmAJl0/LFgbMYONBmhby3uhDuxR86aRi2q59nFvGs0jK+cUiLi3i/Y519tesgJskUUAHohJiw7SisKY9zfQQExrJ9nlfzOtj1XO7YW+k3oAmjYJqyyb7CBtoUFtSx/GLKjVKLHKM6NbE0AG2GqufR68LeqXeWna4gEr5NmiqHftwUIasPaAlTKtLXD9UliGMtfARSFQzjnTvWVSmJNus7FYxWkBUgTQNG+ZBnzemMUG7HYc0DQ4szxo0Ut39LIe8aRFdjmi9VFA02DtMu7xusDgcimuDWPWSBunlBcvWtSbdlx7046HdTiznNNFA1K4Ugpxam3lpxFdtSm3S+e2HUfgOAQBBna7MAgZNltB0QI1VZEctC03qG1ZMqRBVYYcvLa3+gXGZA15y+nW2sv2u6OXuZee4am3ywM2Cnk+lEk5bPzYADeyUe3qJukSLFkrMyVPmORJk6BOs82PE3AGXAHNg7PMZTxyCY98l0i/ka2F9KUPD1ZEAI3D2nEOdz4ig49zw+GWn04+Fs2NK+dHrKGsvHjl0fCmjacTcOB5aOucMOoJO5v2V2jyXLTiIZMWAUgAmPHUufLy1DLAUwNnWn/+t9LsZ0BNnZ+1ihNCWfSnlmWjpr9nO+r96t32hrlrD5ECJDBbXIiXeWnW4oEtlMlRe4h/ngVQRSTlo1EvmrTas7Tn7SwYW45FvGmnuew4f6lpgCb9416wFkCzbrJeCWgUzoAriHlw5sGal4VSc4n2FsR74FYt5e16CYFuLQpWZeCjUM8fNXADK8PZm3Ya7c1mNQjSttsodT221eAwV7vC8+ldAloUrm5tK23AA7pb6hlK9h+V4152JJtb5sm2LiCoad+o3vlowAOFNE08nyzTRspF48dZL9q57rgOc2pgpoGb5XFzwCoEaI5njW+pIQEahTMgB2r8WAM3qT6rW32mV5d+9nZ8NM5eNmwIatxbBqw8YZf6UXiUwA3LsqHUATgcT4uQp7bxLM9Ru07NvqsA9cBRrxov118Of4VnNGwqKvPGzLaVvGSWXc+bVlNe3dBrF13DvZW2BrXLNtnsnJYZqrlgaZ7zh6qFFw3L59u4eMBTNOVK003/NMMwfA/AZwBeBYBpmj4w2r4F4NsAPpyLvgPgvWmaPjPHQG5pLc87Ox8flTbrLTdK3+JFK+01cLu2X3vRBn6xPbHjCIhpgMX7ebeT4nAW9J4BNqB5oAZyHgEzfrm+q9/bWZU8toUyoJbhBO4Vs8oLgJV6fix5zrgHjcHceLouHhhPJ3WVpxeWLGXZuwNIioY0Mys8ze04JK7o4a2K2u3NNaY9fg3OfCp7fYIfCbakFZR3IQ5lHaWZzA7ltbc8bD2e1i1y1Z4R3ewpDcPwHoC/PU3Tj8r5MAxvlXNBrwJ4E8DbAD4F8F0P0Fq1XBG6DIF6HraFZ0w4jnjRAKzzfDyvmBUWtbxlXlizAtCkbTUkQJNCn8AaziQw29KLBijwpIhuyWHZ0WxS/rl8pQigJirzY4yyA++n5Z6VftKF78jqpPbs8XBcrvK0kvNrQIx74EL7nDmetS6iP7xuqbsYU5UETLce3yrPzE17T0ljjE49Lfe8aI4/vSYUGYWr1jBqJnxqSbsWaWUV0Ba6qXqgjZZylfWinW3dTm9P0/R9cv4RgO8D0CAN0zR9c/NZwQcwv/4Kcvy2UKVe8qZRLxqAtRfN8qxBqKdtJNijx54HjtsMApq0ejPqSYvA2Ra5aEUcujhcRfdJk/qXYwnsHpE6KnrPUjPsKV2kLEneNEqMnFsolHGPm1U2P5aQZyQvTZ5u/e2drPCpZqsppEll/R16eNEs8bxCaQxvLMuGqQFnb5pkwCvrCXTREKU3pmVHq9MAzfKiJcOcWrOWnLLavg/Qg3UreXlsN3lph2F4XSj+HGdPWVdNHTJ4NArmKzwBHsL0vG7Hddt5e4JBAjXA9qxZQGZ5yXgYFUo7pbwF0CC0AXQY8+CshzetfAg0ICttOJTRcml7St5Ps73S/DdRvWhc0ndewP4yLwNr2DphbUsKh0rtFGl5aZd6xRPmreqMSoayjpvWFh1vsuRDf92lN1jmg+EBWhrgtPBjK5BRG9VUGZxLxDNmtdO8Zp5LK/heuhU01YwTgb+7AL2O9/CUYMvKg48uMrjVy/IqzlBG9YXXaRiGt+d+bg5bjaS7C3BJwMZhTAuTujlqc2xwEeqkjxEvGvV8SXYisMfH4XYDgFZkec4g1EFokwE2Wl4riXFqPGjWXfq0enduljfN+vRqL4oGZrUqT5A/JvLSylYZvUDJ855ZfXahM6Bt4U2rhTHpA0PtRPLYtDJJj9gjnUME2DrB2RbetNZxIuTRSif32LuXWQV6q6fxilD2OQAMw/DKNE0SsH0M4IuShzYMw/taDtsMc28DwPhzP1s9yRrq1UKdUr/FSlAr1Kk9al60SD9g2V8qA+vDyw1pqzhpvQdokrcssjUHWF1W3t7iEnTx9ty5xPtpbek4i3YRb5r3Rar10eqiHjHLhiGalxZqv4WHayO7p2PiifX54X43CvNRCXnSTpLXK+IJi4QjLRvW34a3j4QvLVvcTg2gVcLZyMozn9EWUGsZx7If6dvSLqHMnQZkx04+F63oheqeOX2B2RtGxM8XmqbpU7ZQ4CMAv6K0/WCapjemaXrj8DM/7YY/Wu5OH81T49418Z6gkVAnfcwAHX3UbPN6CcoCXjQOaEUWtAF9AO0J+VcrzYbk3ZPmI7Xx2vN6+lrdNMW6/qNwVeZ9OGuL/YQ0tVwgnztpX3CjUmd+IVLY4EBCFSnj5963Of3H7ZR/vL1lT5qHNg4HNFrfCdCkqdFzC9isv7F2HgW1zDi9vWn3zHOmb/OVu/bdCtI+x9qb9goAKF40DMPwJiv6AoCU29Yky2Mm5ZhpfSP9FuCWCXVGHi07mu1SZoBZjSLeNF5O+9IyD9CksSP/NEVBrUX3ypFS61C6V08ipuce1mq+xCx+CdmzQE0CGw2IyrmWXB/ZwT9izyIVCbqkcXhbPlYHQNO8aLSuxitVA2qWNFbmdmq9aR29a+5G1Hekm0DaNE2fYp2D9iqAH0vth2F4DcBHwzBQsHsF5z3Wuiu62ZxULuWjafW8jRrq1BQFOkmWd42eKzayXrQiDWxaE/4lmMr0t9r3znl7ZnSDa1TxHvfSrfPItPEOmeTjHiEdq3/a41Uxl9QXdhTUJIMaXGXaZm/BZHnHLDizAI3Pt9GDJk0lG5bsBWrRMKsUks2M00t36HGriSDcypMGAL8+b1Bb9G0A75eTYRheK/VzmPMd5mX7ZQDvbTW5TAjUBC8nHArgko+mKgtv0f4aoFFvG1fSoyY11bp7kGR50SJ2ein6mY6mEzc5JnpKuxDekx+UdBUmTWHYfG+zu5bnfbD6SDZqvA+RL9qoLQAyhHjeJgvArO0qrJCm9E/rI81JGiO6grMToEW8aPzcArUI1GcBKgL4EaiLlEfAMSkvx9TcuJrJ8uCPJJddb3MjTdP0zjAM35tB7DUAv80WAZQ7DJSyH893KACAbwD4qOfqTi/0IcFWpn9r+4uy4c+MTatf1jVFFA0LjvVDbKrstpPSh8jLsnk096OPpTwKe2lpv2RrYC155aC3h9pat/KunU7GOOMEcxuO6Jufvs5a+9oPUunHH615HFnZUThWFd0/jS8EAKsD1uulpRcqGwvjY0htvKuD1NbyqFUCmgblvI31KNm1yjIwKM3RUhbYan54VGjLm6xHddMf79M0/apT96vk/DN6fgt5xHtuI1+JrK06LLmLBrLyctUiuiepO+WyXS7Z2vdAy3cUl5aeHA2Y8N/avCx8zToE90k7YOkUOBjHtI80oeiv5eyvdQDTBlcaCmMSmBVPXAu0UW+eeweD8ZTLa8m+cbXhsza89hy+pDEkQKsCNW1lJv3EUQiTQI6v/oz+bKL2tX6aDW8V6MaARssinrUI1EhQVeO1kvpE5pX5ASmde7op7fTTMzrtPmpZ5QnkgO2ZEr1ZdoWkSyY3J11ipcs2l9aGv5Gt6Wtv+gigaZfgaPtyHIa18QxrY/nu5/CVFe2TBTfPXqDuNJ4zLArwlNDl6fK4LKd1/FiSBVJW3028b1Egomp1LXt/r1ag46zEAa0LqPHJSh6zIyuP+p85/PEyWi7VeatMI3AGVG2zQc81EJL6aRCnXUOi4OfNR9KWoBaFxkrRbTii23H00HMHaRysrBWYt9A0Em+apy1ig9pFlb0zhrnoiTMHbk6Dqege4dbvbXqJlvpFZV12Ix4y6ff1I6F+FNqO7PERoHrRBg+ILC+adnHmxxqsFXkw1/mKogHa8ng9aEveWgTYNBh8gXvTQtBCJJnNhEWjY1mfewm2JDgDZEALzUUCtSIN2DxYo30BH9w0OMuCGW9j/ZRrhDN6PGL5+QXWn+eoPQ3WvDlYfSJ2e4NaVp3uNmCpbNZdq+cO0jLSQpw1L3i51Q0AHA+HyxYcyQn5eSnaRZZ6x7inbEQ4xLmCB9ZP86BxOJMut5o3zSqjtvj4niJwRss9YIsCGgczDm+XccerF22IwJcnCmGlLz/m7WgZbSN54SKeOSLNe5bxankLClqAq1rjCaCJx1lQW9kjx55nS+vHlQlVSsBmedIA3yYAPUdNgifpyWhhUOkJeOKw59mI5K1tBGflWDrngGPBjzSWBX1Re1G7XFGg08aw5vAM6wE9FVsWWEWXxUo2pLJjDTnXXsi9flro0oK4RklAxuFM+13MQc0rK7Iu0ZG5FnmhSu0yrAGaBmvSB4960QqguZP34C3rRZMu0By4tP4QjknfcreBcu9OT5q3zIOqe3F7p/EIHMk7x4KplF12rkFbZCwNviTgAjuXYEyqd+dCQU2S5CnzrgaeJB+817/Wm1ax91kE1Phn0AK0aH8+ZgSQrDGj0BUts2xpUuc3CY1vryNx3mh6biCtRlWwRXTCiOu9CY9zGTkegerQ9oi196uU0UfLu6ZdhBUNWhPFmyYBmXYsgRpvoyl7iebSskaiiwEeCeUWrPFjHuYciXHTi0blARrto3nReD9uPxLqVC7SJQJ4GnkOmvZ47ax5y6TwZyYkyu1Z7aw+qqQVnvwzSMvlwYJjJdpLn/tIEqfkPeOyAM4EtSL+5cmps+fa554/6Xibho1po8ceXGX7S8DWAmoZm16Z1Fdrc0MdDrkv8BPGlVPIv0PSA1TvvLICW62i0HcaD9eNPSlwlYvZgT1yAINQR8u4aP/rhK51wBr6qIKeNu2SmgU1fh7NSKlVLZzxOu24tJPaaB60UJhTAjbpyXkeNQ5wGrDRtrwfhOPxurIzu2jgfKfbSLgy5znrHt60JMGJBjdaf6udBmfWU/S8ZxpcWfBlgRvvY0qDG+pta/Gi1SoaRm2EMwtCNBga2T/NXqQ/WJl3bNmOPBetXrOrtdPaJvSC4zHJLhZozUUrepCQlhWFsKz3TPtDlHLJ3mK8A/CIXgQjoESBiUMdLeO/ag/kGFj+9Wm9pNmW502zvGj3VTWeNKk+k4tW2nQBNO+YPjnPiwbFhtdWOg6EOnVg4+2WwGZtucGPo56vaLuzdzxx6QzBScIWVSZHTbIRATQOZ1I/Lqu+6rWQ7lpwSzUCmWRCA4/MsQZoHgB6n+EslElzsuYSscEVeV0iKqHOsmjgjvdB87RDmiIalrTKigqMaW3Obs7TAupO4wtXb5oEWfyR150NL49pGd0IV2oPoT6gaNjzWVELmPGyjCdNArQLnJWOrYCmAZZULwFcZBwD5qZRDnVS6PJCnRyItlzZuZkioMbhKWNb6qd9pls8aR60ZVQNrgWOrFy2nqq4ZVNRFCyyAFcDaVK/zLE3F+84CmCW/YysuTeoZvuNxfc+1iFPSzukEelgxj1htreN56KV9toKz8s2HOUiKIU3Jcji3jHuaaPhUN7+Otmqd8F9ATW+xUe2L5UEXlEvWyYnrcAZoACaBFatgOYBFu8njZv1wuEMaKexX6gzmlt2ba8DW2T/tfL57SIOU/ypRABLUksItMaTxufunUvl4fCnpQZ42loZgPHOo5AG4Tja3zu2+kTtaLa4osDWQi/Mi/YC2/+s3Is3ereBmntyRvXgIG1YJZ7asiAsGwalto7MhrR44DQecBqfnt8nBcaA68WLwhZYWWkH6N40+mhdOCtVC2o112a+QlRbl1Xzg77Y5McSlGnlGpCVOs17BiS22bCgqQXQJMDy5qHZxbWM5qKdxsMl1OltvcE9ZQXYOIhJW3Z44NXLy9YMb82AwmxRabBnlVvwpQHllt8e233nbSMNsnpAmmQvA2mR/lrfKPBF7UWek1bWQ5WrOiXvWXbRAFXGm/bgIK1WFoQtAesKbjqAnRbH1DaHN4DkpfEv3bOR66N2IeUQV47po/aXbnwHqKAGAKcrUGkeLwm+ytOUYOxI2kKwGc1/89KAPSij5RFQC3nPgHqvGBJtJdB62amXzrXw6HgNc9JctAJcgL+qU4IyKtnLVgdN0X5dvWq1kj5s0rV+ZHUayGn2NCir9aJF5HkS7xLcrOdkAZYHa9GyDGS1QJpVZj1qc/H6cGVhLirR7tKLdmtFQe25hjQrqd8Lc1ohT9FrhsMqL+14ON9m4nB8ug55lkfuTbMuiBTsom/slwF8qdQFxUFtHIEjfe+Rl0nziGmAxr9rOJz1eANHwp5auQVqlzIBzkp5V++ZVOZ5wDLeNgp0ll0sw5yn8QpoBb6WwHae/BE8V23tRdMWEFh5a1JZFLasBQKHwwkn7V6dI3WLz2E5C6YkSdASCWHSdh6s0fb82iNB2X1SD2iLPLcoVPE6DcwsqNPKayAt06/10YK1zKNW5inyGl7K5DcOD3VabRZl5I2Y3QUisgDpvn78bqrIggCtTPKMnW2uPW5lrEW+2hzyBMjmpfyRe9PA6sHaeWVcL+OaC0dVvoilXDamAVfPULmZQoG1R+P5dlIjznUFwCiUaYDmwVnkOh15k/cENQpnFyDz4Azs3IM3Dc6gtBkBvETKOWjxYwnELHAjj9O4BDQa5iwgRs/LsedFW4PYFe6KpIUGxaak1u04ykX7eDwsLu7ijdaloaw3MG0fCWFKfXt4vmrBLQt49AO/RXupf019BNDocSugSbYsSPPaW/2tx+j4lu3oONG23uu0qCOhzoAXbTTu0xkJdfbYfgN4DiHN2vOMhyelMKfmJSv9gOsfh5+X9qt8tXmV5zTOv7kplEkhzHLM/3q8npdFReGMq5QfsYa40xrWLoDGgI2GQqlZyaNWJN1loHU7SqosqIl5bMxrdjmeyxdwVoxtBWel7CVWxwHMq0+A2zXMeQU0HubkXjQOa7Scet6KpPb8uEiDNk105Wkmf20cTzhqXrVeouBFzyVJSfpSndQnCmMtoU7r+gKlTrNjyYPYjC2vTQQYLGDL2MpCmlWfhTJrHr3t9tBi3PvjRYvquYO0Ig5YfttlbhlfXMDhDcDinIIZD3kCuHrTeIgz8wGX6qVwJgetHuKwNl73f9OArXjXHp2WeWvaddpi0uxUJXk3fvGgDFiCWalfbalRjjU40+o1QNJsS/0paEnetBpAm//RPDQOaFLIUlswYK3UjC4S0FaHauNEYa58drsrciXWQpianSio3SqkKYGZBWvRtt6YvdppbaLX4lZAk2xJcOSN6cFUxo42h0x/rgwYRh47q8aLtt9gvYP0bTPWnjeet0YBDKCes2XI8zR/dVwhbr7YHwqlz6C2HEw+9v5yFM4ieWcUsjjESXW83ZHZEYBtOi6BbTxevWvlB8wjsimuB029Ix2SV27hQSPfzRqUlXYDv1B4YU1ABzILjiTbVv8CXLz8JaHMKmc2l4D2ggho1It2VI5PkPrRuqVnbe1lu3rpuLJeta7yhs3E7b2kf952KxirgaZW+xag1o5R0y4KWZFjz24NaEWg6v9v73xeLTmy/P4N3at6GsbGpeoG76ahZDCmDZal0n5MV8FsvJOm/4KuohnbMNhIaFXVGGNKYG+HUs+6wSP9AWNKXhvcpVo1NKZRDV4YY9xdqsVgd5Xuq/AiM+6NjDwn4kRk5r353vt+4JGZkREn4ubP7zsnIlLbV2NHyiPVU7LVUpeFfTk91Cl5yCxTb1i9aFPDnhRpRqTQZhwSTQcVANjni9c30fbAE7C/KLopOQZhz0DtgykVapLQ0mgVa3FZDMsH4TIQbEHs9GXDgAPJ6/ymcK3PNkeaciwG4ms7To/LmYRZWN8qaVZxltrW6gj5zgRbuX5pNQLtLRgGCshhTs2LJg0wiJG8alYPXFxfuj4r8eCB9BueVXb6peZJswhAq2ir7XdmqTMlth8vtbwQ9kvtrmVpgRZvlwSaRbTlhEuruGoRZzkbOduW9dpzUiPmMqFMQA51tkxcO1dftMCVFmk5j1g5fextix/2sQjTJraNiT+Xs9u9xhb9aE/A/jCWCOIs50nTxJi0XysrCTMo6YlgAw5iJ4i2P0Dfdy1hl6Rp+XK8mRzHbea4ph6ywEiQAUOBFJapaIrTpW2rONPqyNkrDRYo5Un7rm3HHrRDmFMWaMM03YuWovdP0/NbBhG0CLT4n6/RvtLggRzadZjzjkn7pTwljhXy1NDEWO3+qfW35isJr5xIs9qcKrKkMi3lLW2ptVeyPWk53Yu277PWhzo1L1pNmJPzpCXEnq7a73PG5XNCDohDnakHTRZzB/vb/ctWHe2phS23hnTNkyatax6yQC5v2H+Gw8AHTbCFNIxFGwC8edZ53Aac9cWj0/cHwk+PCSIuFWcAVA9a3KZD5n65EdLSfdIDQ/NyIdkuibOcMJPsx9sl75klNFoQaK9wVhBocphT86Jpgk7qU5bvizYUdFNCn/sHc1JV1eCBtHqrQNmiXpjNGfaM628tmy7j/cjYl8TpFGqPQ05saem57RYbc4msnJ2SrZJIS9MsbSrZ19okkQq0Bi+ahZYwZ+3XCa6MSNPQwpbyCM9DnlA2pAMYCLB4yg2pzJhruAbsX4zXft8F8kb9pLQzpk2j8ZaQphG/jEthzrAdi7EzjF8GOQ8bkn2IbPS4s6h9yXxrg3IZ3jxTdqTHMvd+lR4kObEW56kRahZxptlDoYwm1NK2biF6zZYUaMBQRFkEmlWUSaFQeYqPTdZeM9twUyQhT6tXqLWf2TG8Y1MEW86GRcBaf1vJtpWSuLKktdiI0y3iyLJuEXgWwWYVa9Z2Wdpjbt9xP6Recvy0fjrqyos0CSmcCUBc10W3NRgAACAASURBVLxp8bpUXkIaSCD2T9uiPBBgI+QrCbB4/k2rWEOUFsoCskBLRR2ifbE4U4TZAClvnF6i9LAMpO/r3ANC86JJwizezok3TSjFeaU6cmKv1mMXiTY9vKn3QSsNDpBCoDVoXjcJSYRJYdFcfzgLITzyGgAs3rW4esmzFNJLQm3JMGd8z2vCStsv7UvTAP3+tYg2jdLvqxWEOeGVS68VbLkyFpGVq6fWTimtRVBZ1lvaVjjf2nc6AVQPGNDzpGHP9v9kLp1I85mP7qad+9N1eSSnNCBgPDea5E3r8sbhlfwF8BLXcIZX3foZcIZXeInXOIPwKeHYc5YKKCmfNbQZv+w1T9gOw1Bmuh9COc3rhigdUX4NSZzF+TWvmYZVrMX7WsKdkscsTs+JN2ldsolCmRZxFq3PJdBe9t42i4et1YsWUxqAUMIqHOP+Leehc2UOqzCL044lyGqQBFtrWe2YSOUk0t/Y0ofNuk/K1yLYrHaswmVJkVaqt0WclfK3CDTFi1bzCajSoIFcX7Q5uXQibSrSFwTGAwK2/fpQmKUdiuMwZ66zcUws1MKIz/1AAgAP/iPw4F8ZfkhOhJXEGgrblr5oSPJJAi0VZ4jS07SAxcuWlpHQRFcuX7zdItS2wINfAQ/+CcrCDMl2uh7vT+tsEWeFst+dDcUZgGqB9hLXsgKsRaBZyqS0esl+9+AvcP3BvxT3bbaZT0QFth6Df7cs4mSbpIX7LRVqc3nW4no1j9Kc3rRSXRpW8RVv/48HwA8e6OWsz4xcHbXpFls1wqVkb2mR1mKnZD+s//wB8NMHhvaUw5wt025M+aD6FJz3bV+FXytv3fqh/6Mnvxg9tuPta3i53x6uv9rnjdfTfXG5cZmuvrNoPd2Xa1tc9hpeYnt+js3uHNd+34U+3/ge4P8ngJc4eLSAsZfr9xh6u2LvF5LtdB2KbSk/knJpGUC2HedFkl5Kk8qW8kssKdQU8eT+EvD3knyaMEu3NSGHijLSOvT9c3nPLGIq52GLvVm1dnc49JVrbdsOG/zGvYub/lejPABwfr7B+a772+02e0/a+W7TjfLcbYDdFti54T0J5LeldBSWlvWSPet6bdmafXPzlQNuV7zvUi9mbl3aTrEKqNK2VQTl9lnE2VSRVmPLUsctBzzxzQIt9qJZQp2bNCyajOysGdVZCnf+xr37tff+lrSv5X+sC0UchrTkTb8aIHnTuu3u0KXetC5tN8q/gf2/9pfoQp2vcAZsXgIAXr0F4PfdqM/BhRk/aGOkMGfYPo/SJM8aMHzwSiFPLdwZl5G8Z1pYU/OgSeFL6VQGW1J+zWORbluFmrRu6Y8W+DvRPkkkaduSuNL6p1nEmZQ/2vbbLuyuiTMgeKWWF2iBFnG15AS23b0+tB8e9tmQZ3rPpNtxWkgv/YwWr1m499OlpYxmI82j5df2WWkRdDX2a4VFTV1WMZWmWcRSqY7apWV9Dhsl2xa7gFmg5aidHy1E0looaZNLLdK0A6d9/FzalkKU0rxnu+RFkhKEl5Vd34ZXOMPDf/u3+Oxnr/f73N/vlvf/DfDgzyELLk2AxaIuJ9BScZGzGfanYcz0P/Y0FHomrMfkxFhNemo7e4MrdoC85yzen+x78N+An/3XQzb3H7rl/T8GHvwzyIIJUbpFzMX503ySOMt47ubwngG2qTRKIdChGMwLNAu1/dv+94PP8X9+9pf77WfuHwMA/u79f4E/fPDno/zZsGc8ylMSZ+m1p+XRlmnZOZ/uOaEVb7cKNUC/h3NtKvHrB8B//9lh+6/7cPM/vA/8owf5stIxtAoiDauQkrbnEGi5slab1nZMFWpbAI8eAD+Pzt+7/fn76X3gzx4k5WQvqSbQagcMzI3FcQRc8nAngMGj/xCCPMcZXqr7ciFJKSR6JoY586HMeH9oZxx6FcOy5+f4e9vv8P/+Ftjsun8UnOTZQrJt3Q8hj5Qm2YWxHJK86XrMVJGWuwckD5e0LZVJ86UPo4xXzd0H/L9L8qaiTEpvGTQAyOJMsTNFnAF5L1e3fxh6rJkLrSTapoQxc5+dyoU7B+0479uZhDyDYBuFPLvC439kpO30/rIstfWaZboubWv5rfd6izesteyXDviw8X1n8eBoaSWbUrkWkdVSNqyX8tS0YQ5xJu1/1wG/8kKeeLLaoRfNItCAoUhLvWhzTGQrhTvjsr9271+9cOcOm5FSjT1r6YS2Vndl/N92CGGGUZtSmDPlJRC9EjY4718BQOc163JgtP0KZzjfnAP4Dq/eehOb3TnOd6+x2QDbbS/W0o78iLY1b1mcP6RJHq9YkEnlNE9ZKgDjfYGaAQBzizSg/OCV9rUMHAjpf6jsS8VWWJcEl5QvTkuFGZLtRJgB9eIM0D1TwHDesVYB1dmpE2hzUWNrsznfC7V9Wv8iGHjWgjctCLX4PorvzXg7pG2jpcYcHrT0GVLal/6GuA259VJdlnbW8lZjXXF91udFzoaWZhFGWltqtktLa1tqRFZrOXU9EdwzCLSUmrDnlJBnjksr0jTiA5ke1KqHMqRpOKYfzs7L0Hn6DtuHV9C/vn+Gl5s3sdnssN2e28SaJsbiB6b0AI2FVvoFgXg9FWco7EvXA9bBADWeNyl/SWxJpPusIi3Zd/+fQxdpaZkaL1vajlSsFYRZt76MOOvS2vuSWQRajLWOWq7f/+l+Pfx7pbHdno+/PrA9Pxz4MNJTEzFhG5CvSymvdv1qQigWVDsln5aGJD0nyiRBJonTVqx2/un9vEjLCdPU/hShppVrFTdaG1oE0lyCsea3WMXZn93v1xVxBqA0krMk0DRRNnVk5zm2kLxpFi5duPPs1g/9D578AgBGj2jLKM44v8WGHOqU7eVHdcp5YpvpawfoxGIYAbrZvR6HQQE51IkoLfV2xdeSlJ6KtLgOQK4nXqbrKUuM+tQoiTTtAax5yyTR1ZpeK8q0vNuyMAPGQqpLy3vANHEGyEIurafkZQt2Na9aTZta88W/JeQV29WP8ASQH+UJYP+R2p0b3h9SqDJ3/yy1zK1LlMrlbLV60o6JRcRoaVbbUvla75KlXa0iyWpvsTZkxBkAaaDAFIE2KBuJNC3c2e2zhzyvfLgzEB6o8QHqPGC70XqcPy6T/scc/xedC3WGkGsa2tyK24e0syjkeQiPhr2HV0hX7wbnm3PVswZE3rXUqxWnxZ4vSWRJoUtJ4EEpHy+R7JewPsiniLVWgRant4oxaZ8mwDKeuZEoi9J80AFJP7MuTRcdQZiFNKuQyompOcKbcT3D9sreMakuCatnTRrJOcqTDBzYbHd7ofbG9vzwBYLtrhNqkket+9EdUnU5r1krwbNl8Xxp5dO2aV661NZFeQtZxUiLzZLdkijKtWcOD9gc4rFUp0Wcad/YrBBouQ+oS9s1XrTwFrcgdcmSuCi3RxXBtRgfhHTUZpo/EIdCA/E0HKkYCy+WtD9ZzclKeYmzjJg7iLXQ3n2+RKy9AjrvWi/GwnU3Em2aCEOyvlPya/+NTw1zSvlrRVkphBFI39FzCjQpj7V8SawlNrQ+ZsBYmA1FkE1c5QYElMrH9bZ4z+R259ubkhNkFqGWskX0CbikX1oc8hyItxD2LAm17gcNhc5cSOIp3Setp1jKakJNs7E2LOJsyrmZKoZy9Wv5aj1hc7ZL+udUtFUQZ4LYkr4okPt4uhTezPVDaw1ZAnLI0zLB/aUUaRY00XbwvB3EXaATR/p293LY7gVVqf6SVy2IvliaxWUObYhfTZ1Yw6YPhfaCDQDOd/00HmeH0aFAFBpNRRuS9LAt5Ue0bA1zxmVjasKdmg0N6R6x/Ida8ojFeaSHkLV8Ji32lAGdKOuW8lcBgFT85Lxp5ak0ANnLlRNXWv6cRy1tX1xvThCmbY/RPGuWh2bsSVfzRKJs5E3bbfJCDRiLGMlT1UJOlLV40SSxlfOkbZO8qY21onmv5hJn6XarKKq13yq2WrxnUprYjro+Z8BYnGlCyzKKc799oi8MpFyE22M20hGd0nbsNQPGQixmPEHttYG9mKEoO1fzxYRBBLFXMIi1rv6xdy3YlQRbEF7b8778Lixfj0Vbd0AOYi3ncWvxoFmu/5q+K7UetlZxlqa1hDVrbWzHoUtg2K8sUOMtC3nSgS+58OOUsGRaJjeoQLIR6sjVLYnCQC4kOkyzPRZjsRaHQmOBJnnTikKt+0EdmliTtnOUPGZSmlWoxWVDu+IyJU9aXCa1VYPUPqsdS/0tQslCizgr1WsRRlra1G2tXaXjVynOtO9wWsKcLQIt16fskIejO2cnfkAP+6nFD2BZqJU+mB7XIZ08zUMme9WwTweg5B1710LeWEC+2vQXUyTewuADoBNt3bJrpyjeJJFWCpXmD5JMbV+0nC0Nq2BL0zVxJeVJ0zN2JA9ZKshiMQbInqawnRslmZa1dNCPbZW8XtY+amma1N5gR/stUrm0belvT4/fUgRvWlGoAfVCrDYkKokviziztCPOZ/WkWWxbmNOrpaXXipHcc2oOT1rOXql8qxetlKe2HQCyoU3lywEpY+FVFmgt4mwKLaM8r5xI0wRTt687HFscPpiehj930XYpNHIeiSgpLVbiaXoqwEKdqWCLBdgmKR/KvMLwQot//9725vwwWd9ZLwQFj1u3xDhUevgh6A/UcJnuL1HjRavJY6HmoVQb0sRBhAWkcGW3PAgyQBZCu2Q75Atpmgcq7M+Jnzm8ZlI7tFBqnDcnzrS2aXUdjsvYixaTet0kgscsfjZo/dKCIAveNJNQwxbYOdnT1OJFq/GMSeJKy6vVFcrH5SSBdow3z5z1zOnRmmK7xYOn2VhKpGllxLps4gzQ+ptp3rRlBZqlw/9cXDmRBoyFmuQxk4Ral2c3KCPbl/ulpaM50hBosCuJtbjuQ35ZnL0C9mkhP3Bt/xtj4nxDz9vhopXEW8nrBiSetxw1AwdK6Va7KS3hT0GgpV4w4CC+DttvROvDUCUgCxJgHLKM96XrraKsVLZUrkZMlbx25WNhb4tduM3zSExHeU4SalPCnBZSEaZ514B6sZazJdlr+V2W/nK5NGuYtEW8aPbTvLWip+Y4lcRYS12ltFL7JoizbMf+iolq92U26TtRv8hz4swa6qz1pl1JkQYMH87D0Zvj0Kalo3BcPj1ZXfrwawdDYTYUa+cYhkFDG6UvHMQh0VicxR628MXQsUCLRdxh/wZDUSiJN83rBhw8b93662i9eAh7W+M0Z72m5/CmCXdFyfvVrY/7iHV5x16uw/ZYZKXesZJnTLJnCRPWhBJzZWuFVI0HzCogw7L0W9LjlK5rxN6yGK1f2n6/0D8tFmoxg+k5rB41CxZvmuYtkwRcCYsnrcZeiak2ioKicnuK/TnFWa78HHUWyxXmYK0cECCPxFQ8XcVJbYcOiH36jAItJ9r2/VcNL6wrK9JSYq9ZEGqhwz6QF2qx92u8b6iaYy9eLNZSD9pB8I2FGXAQbakwSwVbXCalJM5y+0ch0010UcbrZ3L9sajTiMVePt/rcqZGYq9Xtz32fAGyZyvdTl/ymhenRpjIdmU7tSIopE8RZpZ9re2SymtttwjDuQghzyDQNKEGYOxVA+wetVZqRZsm4HL2gdOEOmu8ajW0eJMAe5+0Wu+V9nty/QdLHjVLudI+TZgZ5jcLWMKareJM2t6nS++pjNA6lGsPfVo891depGnhzVqhNrY79KrF3rLYsyalS4Is1B97x3JhzrRMTGhT6mGzeta0/Qf7u1H66GJXDuPA1kZJTzkbJ02dz2aclg8rpumpnZx4G9uxixzJVlpGsyl546aIH2ubrXksx0TznuWOQXrMtPIapX5pYhl1xKcQ/gSGQg2QvWpd421P8ZzQsgo1YGwjJ0pKAm2uwQM1njntGFryaek1IqaUx2K/pT6rKKv+fYWvAIhlyn3NAhZxpoU0S3OgaV8RAGzirCunCT5reXrSVA4hiqFXKxZqgZxQk+LLOe9ZvC+uKw1hduu6Fy20JRfmjC8Uixt3LMrs4ix3kUv94CzUCK0p/81o5ERXut8iurS8aVpJdMjhO11YWgVVjfAq7Z9SR0k8Tm2r5I2UsP5DJoU8U28acHhBhMEEAPR+agDG03NIODm55P1qEW1hO0cqwnJCb4q4mTNk2iLspnrR0vxTxZK1nqZ6K8KWgBq6jKkRZl2ara+ZPpAgeQcZP/OktnHC+4ajOwvEYgvA4OGa/idc4zkLSIJs3OftENoMdcbCLBVlh/1DL1rIIw0kiMvHAwckcqLLKuCG7RzaTddztLqcdXvlsqVzrIUTpbKSLauYSretQkRrZ66Mxcs0l2ibaucUbWoh9aZJQg3Q+6ntf2ss1HKMxJsi2A4NlD1d0r5cOSuSJw2Y561j9YjNVZ9mZ6oXLc1n9eBZBWGp3KDuylDlII/dOxbIDQA45CmLM6sw26dnPGjZtkwUcK3RnSsl0jQPl+Q1247S9UltJfuaWBuGVGPv3DC0OprbDLJnSxvNmYZGc9SJs+H+tLxs0945M1ArzOb0pJWEVpenLLbStBpRFee3hu20tBovnTXsKu2vyVvTplz7cnmOKdBitAEEAExetZj9yM+Y/eelSvFCQbRN8aDViqBjhDpjW3N55lpt5X6fxdYUb5oUji4KNGOo0iCmgLopMsb5DO8EQ9+y7MjPwhcE5picdm6BBlxSkSZ34B9PuzHsfyaP7EzFWrAvdQLPhTTjdC20Gn/BIJ4ot+RRS8VZmp4jvTAtHrNUwEnltTIlSjaPiUUAaf2QSiFOTRDUhPpybagbRarXJeVrEWVSHimfJmpbxKOUxyrQpPMzmA8Nw35pYRnyxGFPAIO504C8WOu2hdGf8bc/TWiPdzfM0iIoavLXetOs9bR65qTfPFfIU9tXqq/Fm1aTR/KSNYQpY2pFmUWIpbQOBLB80in3fmp55ywh0IBLKNIKDn8Acv+zoVgqe800cqIsNygByHmndI9aLNryAw5kUi+bRZRZwphWgTa142Wu3hLWc2wVWEC9YNLSc4Kmpk3WkZ9aXTlBFpexeABLdrUyc9mfItBaiD1q6cfXNwNBtlHFWpwnF0ISPW5h7rWULbD/ugGA5n5tUv4YqS9azWM156HL7Z9iu7VcyYtmKdcqsHaFHzPh4+QWrCMv91XPVo/ez0y1MVEw6XaXEWjAJRRpJUohz5xYk7xqej3ySNEtZM9ZVyYfFhyLOL0PWhzmrBE8dnGmDIHO/EdiaYfsSVvmxooph7LLwsqy3yLi4nIlEWVtS4sY08ppYnGKKNPKzVGP1SsobceUpulIvWld2lCo7esRBFss1gA5/FlNmCxXSD+ETYHBJ6l2iacNaOvvpXnPpvYds4YVa95uU35fLt3avimhR02MC/kt37tsoWbUZZ1dgyetYq4zialetCUFGnBFRFoa6gQOD9yhaJJFmNWzlgtnSqM404f+2OM0/GC71i8NGIo2yxxpGpI3ryWEWS/O5h0w0EruRVzjXS29/K31aIImZ0Nr5xShNEf+XPtr+tlN8cxZj20N0nMjFWpp3emLJQwwAOYXa+nAhYA6MGHkaUOlB6xva/ot0iD+iqHFwmjCgDYticXeLvEettoplrHkic5tRthkPV2CGJ8yU38LNZ36W1hanHU2ymmxXpiC9f12JURaIPVqAbJYA3TBlrM7TCsLtrEdmyLXviagCbcaNHElDRjIldXSWgcN1NwQlpuodG5LXpNWwWa5pkoiRLNt3V8rxHJlcuVavGSluq1tbvEA1iIOEIju7dFoz4EHPylnCNVMIUzzMUyLxFv6ks95ZyQ0Dw8w9NgFRiLQFpIbtOkU4c6BjcI5sxy/3kbtlBS1+ZYKQVraMKdQA8rirPWf+/G7qr0rTuk9V9PGKyXSYvYhiESsAfawpjxHWtwnTe5/Vt9HS/eoxb+hNMmsBc1T1jadRjk8GjPH6Jpapoo13W5dOFLKo4kcS12lultF2BRbltBi6yCI1nZYBZo11Jmuh2t6PL2PfD+kc6zNSTyJrq3ATPX3dkYiUKDYL0obTFFjQ0AMCU+1K/1uwVZtny4AgxHB1rw5lvR47dOVcL/JZuHj59o71epssQo0C3MKtC7/FSP1eo3/Ex6HIW12h945aW60zr4tdGrp83X4HeUwZ1xO+33pfGq1AwQ0Wj6tccwRnS3eqBos03eU6p1LTE4VYFpdrRP9auWtbZrD65ZrVyvpyyF3D4jetj5pbrGmffi929eHZUsd0UW7+nMg2Et/RxrWrbUn2bTYkH5fyzG22re20erNSr9BKYWyLXW35DPZsnTgn+A5rpk4XUvL2z9+N5scV0akpR6ugBSmjJki2tLyNQMP0kEFB7u6qzfXn6w0V1qapyVMGdPaGbNVDLaOxh3aqDvPLeKt5loq9dPKl60TnjXCyRp6rR0k0VrXEqKxhVSYSc8bifReCVN49EZmp/Rit3pprKJCs9fa2TzNE+zWtkdj6u+2eCwtc35JaOFE6XxqfbgkL5ZVNFnLzjHKvsYjlRNnNc/OqQJtiUFuV0akAVrfscx/IUavV6nOFluWzzh1yNNzlGzk0Lx1tUwRZscY0Rmo8eJMr6tGpM3r7akRXVM8dzVCrNWLafVOThnAYUHqlzbOU9efMg6RWu6DeD62OWnzLo29ZfE+TRxO8eTU9IPKiVOpbDqfXW2bSuIp1xl+ipjK9ttSDoHlH2Gt/tqBX1pfTQu1nxwcRs6U628G79lS76xLL9Li0CMwFE1pWkDzuE0RbLVqPncxSe2QPWrX9mVq0KbukCcJ1o/JsYdCd+2puwmXDnuN66u7hqaKxFaxNVc7W7xkKVNGsebSlzjPLf+9a+Ut3QSsQk6oaFbUl7cyP1xJ/OTEiNafaY4wW2p76b5auU8UbTbyPwDi+d7k89hHEo7zpaOUa8pa82rzheaY2k+6nNf+vlvSqXDpRZpGzctDn5qjLRRa27bSfwJp+6RRonN41UretPGNNsyfe4HFI1XjvDWUXoySzVYPz9LUeqrGA1jq+71Z0mvI2ai9b2oFWSnPkkIcaP/PXBuZrP3OWaapmXgois8WwX5OLJXsbTbLvRA1YdRurx8E0tjx3VyPQZTF8/jVsNQn+qx9Nkv2rdEj63nN2RCn06l8t6aOoxJXQqRZDkquM/3Yozb+hFSNYKsdOJCzK3+2SrpB65/EFu+h9vJomUj3UG851FsjYqwho1paXOeaQLXYzYfm60OWtflqmHMKk2G5tvBozNICbQpLzcmU2qwNqWosMZfhKeZHXIJ0EuPaDu8tgipmjk70Erk+3aW6rH02bdNc1PWbLnVNqLkPjtkd56gizTn3MYBnAG4AgPf+8znz55CEmuVhnU6boYdG66dBKOW1XKiSopdcx7UvYuvQ5RbvVVp2fLPpNnMDIPS25MO+LX2yLFjFV42HT2NOcTJl9HGNjUPetmNdW26qd1LD0i9NK1dug+UZYH/JpQOo5hBEpXu8NbRluX/WNhIvoIlfa38q6/O/RMtckZbITW1daR6r0CvZ6db146xNfTPFE3ZsjibSnHMPAfzSe/9l2HbOfRi2p+a3YHlJaSdPEmsto7mWDKPJAyPaLsbSnG6WjttW72L5ywt2rB5Ra7kcpf4JVptzeJ1q+wvK9Swfuj+VrZZ55qR5EFux2GkNWee9GcMJdNM5HMN6yU5tO3J9f1vnQ6z12rSQPkNrBXBg6tdYLJ3dLfYPaZI4aT/mFhGZu56tToCaNgHj4147T+GxqAl5Ou8bPnXRgHPuW+/929H2bQCfeO/vzJE/8NatH/o/evKL6vaVR2iVJ3mV7coXYunFPNesydZ9ehl90s3Dei4MZ/NeTZ3yo7W/Qeuks1Zy3oCWvhs1ddWUteafO+w2ByWRP2UiYOt1OOcAmhpaOjKXvmJhoXbE6lK25fLlZ1aJJQbs1Palmto37hjTFtXWW5qncWjHIiLt/frW1s0hbu+v3ftfe+9vyfmOgHPuPSH5OYDbc+SfSs13OQF5slq5zPCisIxSy4UsNRvS6NWYKfPFtE5tEGwc06vYYm+pUCcw/+8vhSfm6K9V04YlX9QWtPtpTQ/jpf9jt4Rv0s9TlW3OG0K0ek2m1NviqZQ4zG/Z7ukJ5S37Sp3UW4WU9Xjkwvy1dbfUKR3ntYawT8Wxwp030ImsmBcz5j8pcpixLNBkL844xFJ6wJZCk1O8NyXvjFWElIREWp81BGMVWacIRU/xgNXYqB0RWKL0j4Bkf666rcwhxGr/OavlmCGV0hdKJKE25wuy5KEuiZ6lBVqNrZJQq+nbOmd7asrMkbdVrB2LOUfHrpljHf3rQtpzAHDOXffepwKsKr9z7i6Au/3my9+4d381sb0kz/cB/PbUjbjk8BgvD4/x8vAYLwuP7/Ic4xj/QNtxLJH2Av0IzYh0uzl/P+rzcwBwzj3RYrtkHniMl4fHeHl4jJeHx3hZeHyX59TH+I0j1fMcY+/YdQAQvGgt+QkhhBBCLhVHEWne+6cY9ym7AeCrOfITQgghhFw2juVJA4C/cs59GG3fAfAobDjnbib7s/kzNE94S8zwGC8Pj/Hy8BgvD4/xsvD4Ls9Jj/HR5kkDBl8QuAngRfwFgX7fnXgetFx+QgghhJDLzFFFGiGEEEIIsXHMcCchhBBCCDGyzlnqMpzyI+1XhZpj1vcbvAPgiz7pIwAPvffPlm7nRcU5dxPAhwC+573/xJCf13AlNceY13AbzrnrOMxP+QGAx3wez0ft8eV1XE9/jP+033wHAAzPi6NewxdKpK3hI+2XnYZjdgPd57ruAngK4Cd8KOj036C9jv6BYMjPa7iS2mMMXsOtfBq/0Jxz3zjn1JcWr+Vqqo4veB238BDdN8FfAIBz7mvn3Mfe+8+kzKe4hi9auPNucjAeA7g3Y37ScMy89+947533/v1++hSi4L3/qj++1vn+eA1X0nCMeQ1X0nsgbibJjwDkvBC8lo00Hl9eprVaTQAAC+lJREFUx/XcwvCb4M/QeS01jn4NXxiRtvaPtF8GeMzWBc8HWTE3ANzuw8qBFxgLCwC8lhuoOr6kjV7MxqLrPXTCa8SpruGLFO681B9pXwlNx6z/dupzsJ/J3PAaPhK8huvow2hvJ8l3oE84zmu5gobjC4DX8RT6vmZfFcLJR7+GL5JIW/Qj7QRA2zF7gm4Ou2d9vkfsZzIbvIaPA6/hifThudsAfqRk4bU8AcPxBXgdN5EMHvgmk/Uk1/CFCXdi4Y+0EwANx8x7/zTpnPoYwKdzN+yKwmv4CPAanoWfA/hRph8Ur+VplI4vr+NGvPcvvPef94MFPnDOfaFkPck1fJFEGj/SvjzVx6wfSRfzAl1cn0yH1/AR4DU8jT5M9KjQUZ3XciPG48vruBLn3PX+2MY8Rjd1j8RJruELI9L4kfblqT1mfafWx727OHAd3QgZMhFew8vDa3ga/dxcT733X/XbYidqXsttWI8vr+MmbgF4KBwzkVNdwxdGpPUc6yPtVxnzMe5d6/eS/yJ+jG7uGdIAr+Hl4TU8D71guAHgSX9Mb6K7PsN+XssTqDm+vI7r6YXvJ8kxuwNgP0faGq7hC/ftTn6kfXlqjnE0szsAfA/ANzzGOv0w7h/jcMy+BPCfQiiD1/B0ao8xr+F6eu/Dt8KuL733H/V5eC030nJ8eR3XIxyz38UT2a7hGr5wIo0QQggh5Cpw0cKdhBBCCCFXAoo0QgghhJAVQpFGCCGEELJCKNIIIYQQQlYIRRohhBBCyAqhSCOEEEIIWSEUaYQQQgghK4QijRBCCCFkhVCkEUIIIYSsEIo0QghR6L/d99g5551zD6P06/3npwghZDEo0gghRKD/fuLD/u8dALEwux2+BUoIIUuxPXUDCCFkpdwOH7PuueecuwuA4owQchT4gXVCCDHinPsQALz3X566LYSQyw/DnYQQQgghK4QijRBC7NwA8OzUjSCEXA0o0gghxM51DhgghBwLijRCCCGEkBVCkUYIIYQQskIo0gghxEA/RxpDnYSQo8EpOAghxIBz7rr3/sWp20EIuTpQpBFCCCGErBCGOwkhhBBCVghFGiGEEELICqFII4QQQghZIRRphBBCCCErhCKNEEIIIWSFUKQRQgghhKwQijRCCCGEkBVCkUYIIYQQskIo0gghhBBCVghFGiGEEELICqFII4QQQghZIRRphBBCCCErhCKNEEIIIWSFUKQRQgghhKwQijRCCCGEkBVCkUYIIYQQskIo0gghhBBCVghFGiGEEELICqFII4QQQghZIRRphBBCCCErhCKNEEIIIWSFUKQRQgghhKwQijRCCCGEkBVCkUYIIYQQskIo0gghhBBCVsj21A2YG+f+gQf+LwAXUpKllFZaamlL2LfayLXJwJxNqskrNXWpw3PqvMdqy+A4+SSt23aj9ENaus+FMv1yWJW877Dto7R033T7ayhzqjbV2LOU2V8bSr7Z2+SjMsnl4tKqvbCu5Rk3e7xvDvs19Vjy5tLnbItk05q3pk0tbRHs73d5eWkxl2u+dXkM+2H9fwH/2Xv/J0LVl0+kdQLtHg4/7c1+Gf/UNK20HafV5G2xn+bR0rU0hfAk3ihmt8l+Sx6pKVqedP9SbYntW9tS0ybJfkubSsuatmyj2357Pli+sdl1m29225uwP1rfbPs8YfuNfonhslvv80LOE/bn85yLtix52tpU3/58m+Zu/5y/tb397W0q5D3vl7vo2jh/3adhsHTB7CHrYT0s0zxpurRPK1tjd+42aWWWblON3ZY21dgV2vRdnxYul+/Oh9uDPGE7WabpUlpp+5j2HwDfhwLDnYQQQgghK4QijRBCCCFkhVCkEUIIIYSsEIo0QgghhJAVQpFGCCGEELJCKNIIIYQQQlYIRRohhBBCyAqhSCOEEEIIWSEUaYQQQgghK4QijRBCCCFkhVCkEUIIIYSsEIo0QgghhJAVQpFGCCGEELJCKNIIIYQQQlYIRRohhBBCyAqhSCOEEEIIWSEUaYQQQgghK4QijRBCCCFkhVCkEUIIIYSsEIo0QgghhJAVQpFGCCGEELJCKNIIIYQQQlYIRRohhBBCyAqhSCOEEEIIWSEUaYQQQgghK8R570/dhllxzv01gO+fuh1kwPcB/PbUjSCLwfN7ueH5vdzw/J6e33rv/0TacelEGlkfzrkn3vtbp24HWQae38sNz+/lhud33TDcSQghhBCyQijSCCGEEEJWCEUaOQafn7oBZFF4fi83PL+XG57fFcM+aYQQQgghK4SeNEIIIYSQFUKRRgghhBCyQijSCCGEEEJWyPbUDSCXD+fcdQB/2m++AwDe+08y+T8EcAfAF33SRwAeeu+fLdlO0kbt+e3LfAzgGYAbfX52Vl4p/fm9229+AOBx7nzx/r1Y1J7fvgzv3xNBkUaW4CGAT7z3LwDAOfe1c+5j7/1nSv4bAG6je3A8BfATPuBXTdX5dc49BPBL7/2XYds592HYJqvj01h0O+e+cc7lXsy8fy8WVeeX9+9pYbiTLMEtdA/twDN0/7GpeO/f8d477/373vuni7aOTKX2/N5NHuiPAdxbomFkGr2X5WaS/AhA1lPK+/di0Hh+ef+eEIo0Mjv9gzq+qd9Dd2OTS0DN+XXOvSckP8dQ5JH1cAPAbedc/CJ/gfGLnVxMqs4v79/Tw3AnWZS+L8NXhj4Pd9Hd/OzzcIEwnN8b6M5rzItlW0Va6cOUbyfJdwB8lSvH+/di0HB+ef+eGIo0sghJ5/JvCtmfAHgR+rE45x6xz8O6qTi/14W058FG6NdG1kl/nm8D+FEmG+/fC4rh/PL+PTEMd5JF8N6/8N5/3ncm/8A590Um79Oko/FjAJ8u3kjSTMX5fYHeuxKRbpP18nMAP8r1M+P9e6EpnV/evyeGnjRSpB9i/+NCtufe+3theHcy0u8xus6pmv3b3vvY3f4CXT8ncgQWPr/PMf5v/DrQCb2W9pI6as5vUu5jAI9KAwF4/56Whc8v798TQ5FGivRhC2vo4haAh865z6ObWHKZAwD6DqyPnXNvJ/k5hP9ILHl+vfdPnXPpw/wGCn2cyHxUnl8A+xf/0yC+BCEW8vH+PTFLnl/ev6eH4U4yK/2N/knyX9YdAHvPi3PuZv+QCB1Z7yX5f4xuLi6yMmrPb89fJdt3kPGsktPinLuN7kX8pD+XN9Gds7Cf9+8Fpub89vD+PSHOe3/qNpBLRn/Th5v6ewB+F4fHejf7He/9HSX/Nxwdtl5qz2+U9gzdUP8XPL/rpA9nfyvs+tJ7/1Gfh/fvBaXl/EZpvH9PAEUaIYQQQsgKYbiTEEIIIWSFUKQRQgghhKwQijRCCCGEkBVCkUYIIYQQskIo0gghhBBCVghFGiHkStLPB/WFc+4b55zvl5z/iRCyGijSCCFXjn5yzm8A/BLd5JxvA7iH7pNGhBCyCjhPGiHkShFN6HlviUk5nXN3AXwUTwZKCCEt0JNGCLlqfArgGWdNJ4SsHYo0QshV4zYMH6R2zl13zj1yzn3b91f7ONkf9nnn3Nehjxu67xreDuUW+g2EkCsARRoh5KpxE11/tBL/Bd13Ct8G8D6AO2FgQd+n7Zb3/m3vvQPwEwDP++8f3gPwVb/vnWV+AiHkKkCRRgi5ajwDkBVPvQi77r3/BAC89y8AfATgbt+nDQBuOuduO+eue++f9nkIIWQ2KNIIIVeNJ+hCnjluohNzeyIRdtN7/yWAf48utPmtc+5xJN4IIWQWKNIIIVeNTwC813vLNJ4BuBUnOOduRvvgvf+sD2e+DeAGgLsLtJUQcoWhSCOEXCmi0OUXzrmPgwes7/j/qA9ffgngedju8zwC8Ln3/kUf5oy9cc+T9Zu9zZLHjhBCVCjSCCFXjl6EvQPgAwB/45zzAB4D+CYKa76PzkP2N/3fU+/9vcjMJ865b/t9L7z3n/XpXwFAvy/OTwghVXAyW0IIIYSQFUJPGiGEEELICqFII4QQQghZIRRphBBCCCErhCKNEEIIIWSFUKQRQgghhKwQijRCCCGEkBVCkUYIIYQQskIo0gghhBBCVghFGiGEEELICvn/GYG6KDJeoxoAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure(figsize=(10,6))\n", - "pl.imshow(np.array(E_landscape).reshape(landscape_n_beta,landscape_n_gamma),\n", - " origin='lower',interpolation='bicubic',cmap=cm.jet,aspect='auto',\n", - " extent=[gammas_landscape[0],gammas_landscape[-1],betas_landscape[0],betas_landscape[-1]])\n", - "pl.plot(initial_gammas,initial_betas,'k+')\n", - "cbar = pl.colorbar(orientation=\"horizontal\", pad=0.2)\n", - "cbar.set_label('Cost')\n", - "\n", - "pl.xlabel(r'$\\gamma$')\n", - "pl.ylabel(r'$\\beta$')\n", - "pl.title('Optimization landscape')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now we iterate over each of **N_E_RTOL** error tolerances. For each of them, do **N_REPS** optimization runs at each of the **N_INITIAL_POINTS** parameters space lattice points." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "def getval(x,history_ref,backend,depth,version,noisemodel,E_atol,E_rtol,dv_rtol,min_n_shots,max_n_shots,conf_idx):\n", - " circuit = createCircuit_MaxCut(x,G,depth,version)\n", - " \n", - " [E_list,v_list,n_list] = sampleUntilPrecision_MaxCut(circuit,G,backend,noisemodel,min_n_shots,\n", - " max_n_shots,E_atol,E_rtol,dv_rtol,conf_idx)\n", - "\n", - " history_ref['gammas'].append(x[0])\n", - " history_ref['betas'].append(x[1])\n", - " history_ref['expectations'].append(E_list)\n", - " history_ref['variances'].append(v_list)\n", - " history_ref['n_shots'].append(n_list)\n", - " \n", - " return -E_list[-1]" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "83.33%/93.33%/87.50%\r" - ] - } - ], - "source": [ - "E_rtols = np.geomspace(MIN_E_RTOL,MAX_E_RTOL,N_E_RTOL)\n", - "E_atol = np.inf\n", - "\n", - "opt_histories = []\n", - "for i in range(N_E_RTOL):\n", - " E_rtol = E_rtols[i]\n", - "\n", - " opt_histories.append([])\n", - " for j in range(N_INITIAL_POINTS):\n", - " x0 = (initial_gammas[j],initial_betas[j])\n", - " \n", - " opt_histories[i].append([])\n", - " for k in range(N_REPS):\n", - " \n", - " opt_history = {\n", - " 'gammas': [],\n", - " 'betas': [],\n", - " 'expectations': [],\n", - " 'variances': [],\n", - " 'n_shots': [],\n", - " }\n", - " opt.minimize(getval, x0=x0, method='COBYLA',\n", - " args=(opt_history,backend_sim,CIRCUIT_DEPTH,CIRCUIT_VERSION,None,\n", - " E_atol,E_rtol,SAMPLING_DELTA_V_RTOL,\n", - " MIN_SAMPLES,MAX_SAMPLES,SAMPLING_CONF_IDX),\n", - " options={'rhobeg': 1e0, 'disp': True, 'maxiter': 10000})\n", - " \n", - " opt_histories[i][j].append(opt_history)\n", - " print('%.2f%%/%.2f%%/%.2f%%' % (i*100/N_E_RTOL,j*100/N_INITIAL_POINTS,k*100/N_REPS),end='\\r')\n", - " \n", - " \n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Let us verify that the optimizations seem to work correctly." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Optimization landscape')" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure(figsize=(10,6))\n", - "pl.imshow(np.array(E_landscape).reshape(landscape_n_beta,landscape_n_gamma),\n", - " origin='lower',interpolation='bicubic',cmap=cm.jet,aspect='auto',\n", - " extent=[gammas_landscape[0],gammas_landscape[-1],betas_landscape[0],betas_landscape[-1]])\n", - "\n", - "for j in range(N_INITIAL_POINTS):\n", - " for i in range(N_E_RTOL):\n", - " for k in range(N_REPS):\n", - " gammas = list(opt_history['gammas'])\n", - " betas = list(opt_history['betas'])\n", - " for it in range(len(gammas)):\n", - " gammas[it],betas[it] = wrapParameters_MaxCut(gammas[it],betas[it],\n", - " (gamma_min,gamma_max),\n", - " (beta_min,beta_max))\n", - " opt_history = opt_histories[i][j][k]\n", - " pl.plot(gammas[-1],betas[-1],'k*',linewidth=0.3)\n", - " pl.plot(initial_gammas[j],initial_betas[j],'k+')\n", - "\n", - "cbar = pl.colorbar(orientation=\"horizontal\", pad=0.2)\n", - "cbar.set_label('Cost')\n", - "\n", - "pl.xlabel(r'$\\gamma$')\n", - "pl.ylabel(r'$\\beta$')\n", - "pl.title('Optimization landscape')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Finally we plot histograms for the achieved optimization ratios, as well as iterations and total shots per optimization." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "n_datapoints = N_REPS*N_INITIAL_POINTS\n", - "\n", - "apx_ratios = np.zeros((N_E_RTOL,n_datapoints))\n", - "n_itss = np.zeros((N_E_RTOL,n_datapoints))\n", - "n_shotss = np.zeros((N_E_RTOL,n_datapoints))\n", - "\n", - "\n", - "for i in range(N_E_RTOL):\n", - " for j in range(N_INITIAL_POINTS):\n", - " for k in range(N_REPS):\n", - " opt_history = opt_histories[i][j][k]\n", - " \n", - " n_shots_list = [sum(x) for x in opt_history['n_shots']]\n", - " E = opt_history['expectations'][-1]\n", - " \n", - " tot_n_shots = sum(n_shots_list)\n", - " n_its = len(n_shots_list)\n", - " apx_ratio = E[-1]/max_cost\n", - "\n", - " flat_idx = j*N_REPS + k\n", - " apx_ratios[i,flat_idx] = apx_ratio\n", - " n_itss[i,flat_idx] = n_its\n", - " n_shotss[i,flat_idx] = tot_n_shots\n", - " \n", - "pl.figure()\n", - "_,axs = pl.subplots(N_E_RTOL,1,sharex=True,sharey='col')\n", - "for i in range(N_E_RTOL):\n", - " binsize = 0.004\n", - " apx_ratios_flat = apx_ratios[i].flatten()\n", - " n_bins = int(np.ceil((max(apx_ratios_flat)-min(apx_ratios_flat))/binsize))\n", - " \n", - " axs[i].hist(apx_ratios_flat,n_bins,label='Distribution, E_rtol=%.2e'%E_rtols[i])\n", - " axs[i].axvline(np.average(apx_ratios_flat),color='k')\n", - " if i in [0, N_E_RTOL-1]:\n", - " axs[i].set_ylabel('rtol:\\n%.1e' % E_rtols[i])\n", - " axs[i].set_yticks([])\n", - "pl.xlabel('Approximation ratio')\n", - "pl.suptitle('Approximation ratio distributions')\n", - "pl.savefig('rtol_E_pdf.svg')\n", - "\n", - "pl.figure()\n", - "_,axs = pl.subplots(N_E_RTOL,1,sharex=True,sharey='col')\n", - "for i in range(N_E_RTOL):\n", - " binsize = 1\n", - " n_its_flat = n_itss[i].flatten()\n", - " n_bins = int(np.ceil((max(n_its_flat)-min(n_its_flat))/binsize))\n", - " \n", - " axs[i].hist(n_its_flat,n_bins,label='Distribution, E_rtol=%.2e'%E_rtols[i])\n", - " axs[i].axvline(np.average(n_its_flat),color='k')\n", - " if i in [0, N_E_RTOL-1]:\n", - " axs[i].set_ylabel('rtol:\\n%.1e' % E_rtols[i])\n", - " axs[i].set_yticks([])\n", - "pl.xlabel('Iteration count')\n", - "pl.suptitle('Iteration count distributions')\n", - "pl.savefig('rtol_its_pdf.svg')\n", - "\n", - "pl.figure()\n", - "_,axs = pl.subplots(N_E_RTOL,1,sharex=True,sharey='col')\n", - "for i in range(N_E_RTOL):\n", - " binsize = 0.04\n", - " n_shots_flat = np.log10(n_shotss[i].flatten())\n", - " n_bins = int(np.ceil((max(n_shots_flat)-min(n_shots_flat))/binsize))\n", - " \n", - " axs[i].hist(n_shots_flat,n_bins,label='Distribution, E_rtol=%.2e'%E_rtols[i])\n", - " axs[i].axvline(np.average(n_shots_flat),color='k')\n", - " if i in [0, N_E_RTOL-1]:\n", - " axs[i].set_ylabel('rtol:\\n%.1e' % E_rtols[i])\n", - " axs[i].set_yticks([])\n", - "pl.xlabel('Log total shots')\n", - "pl.suptitle('Total shots distributions')\n", - "pl.savefig('rtol_shots_pdf.svg')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/classical_exactcover_solver.py b/classical_exactcover_solver.py deleted file mode 100644 index 9ebfd83..0000000 --- a/classical_exactcover_solver.py +++ /dev/null @@ -1,40 +0,0 @@ -# Classical (i.e., not Quantum) algorithms to solve the Exact Cover problem. -# -# The input is a 2-dimensional array A, where aij = 1 if an only if element i is covered by cover j. -# Therefore rows represent elements and columns represent covers. -# The objective is to choose a set of covers such that all elements are covered exactly once. -# An additional input array can be provided to assign a weight to each cover. In this case, -# the exaxct cover with the minium sum of weights will be chosen. - -import networkx as nx -import numpy as np -from cylp.cy import CyCbcModel, CyClpSimplex -from cylp.py.modeling.CyLPModel import CyLPModel, CyLPArray - -def classical_exactcover_solver(A, w=None, num_threads=4): - nrows, ncolumns = np.shape(A) - if w is None: - w = np.ones(ncolumns) - assert(len(w) == ncolumns) - assert(sum(w >= 0)) - model = CyLPModel() - # Decision variables, one for each cover - x = model.addVariable('x', ncolumns, isInt=True) - # Adding the box contraints - model += 0 <= x <= 1 - # Adding the cover constraints - # Sum_j x_ij == 1 - for i in range(nrows): - model += CyLPArray(A[i,:]) * x == 1 - # Adding the objective function - model.objective = CyLPArray(w) * x - lp = CyClpSimplex(model) - lp.logLevel = 0 - lp.optimizationDirection = 'min' - mip = lp.getCbcModel() - mip.logLevel = 0 - # Setting number of threads - mip.numberThreads = num_threads - mip.solve() - - return mip.objectiveValue, [int(i) for i in mip.primalVariableSolution['x']] diff --git a/classical_maxcut_solver.py b/classical_maxcut_solver.py deleted file mode 100644 index b2ac033..0000000 --- a/classical_maxcut_solver.py +++ /dev/null @@ -1,56 +0,0 @@ -# Classical (i.e., not Quantum) algorithms to solve the MaxCut problem. -# -# All functions take as input a NetworkX graph and return the optimal solution. - -import networkx as nx -import numpy as np -from cylp.cy import CyCbcModel, CyClpSimplex -from cylp.py.modeling.CyLPModel import CyLPModel, CyLPArray - -def branch_and_bound(G, num_threads=4): - N = len(G) - model = CyLPModel() - # Decision variables, one for each node - x = model.addVariable('x', N, isInt=True) - # Adjacency matrix (possibly weighted) - W = nx.to_numpy_matrix(G) - z_ind = dict() - ind = 0 - w = [] - for i in range(N): - j_range = range(N) - if (not nx.is_directed(G)): - # Reduced range for undirected graphs - j_range = range(i, N) - for j in j_range: - if (W[i,j] == 0): - continue - if (i not in z_ind): - z_ind[i] = dict() - z_ind[i][j] = ind - w.append(W[i,j]) - ind += 1 - # Aux variables, one for each edge - z = model.addVariable('z', len(w), isInt=True) - # Adding the box contraints - model += 0 <= x <= 1 - model += 0 <= z <= 1 - # Adding the cutting constraints - # If x_i == x_j then z_ij = 0 - # If x_i != x_j then z_ij = 1 - for i in z_ind: - for j in z_ind[i]: - model += z[z_ind[i][j]] - x[i] - x[j] <= 0 - model += z[z_ind[i][j]] + x[i] + x[j] <= 2 - # Adding the objective function - model.objective = CyLPArray(w) * z - lp = CyClpSimplex(model) - lp.logLevel = 0 - lp.optimizationDirection = 'max' - mip = lp.getCbcModel() - mip.logLevel = 0 - # Setting number of threads - mip.numberThreads = num_threads - mip.solve() - - return mip.objectiveValue, [int(i) for i in mip.primalVariableSolution['x']] diff --git a/classical_maxkcut_solver.py b/classical_maxkcut_solver.py deleted file mode 100644 index 1be4331..0000000 --- a/classical_maxkcut_solver.py +++ /dev/null @@ -1,73 +0,0 @@ -# Classical (i.e., not Quantum) algorithms to solve the Maximum K-Cut problem. - -import networkx as nx -import numpy as np -from cylp.cy import CyCbcModel, CyClpSimplex -from cylp.py.modeling.CyLPModel import CyLPModel, CyLPArray - -def classical_maxkcut_solver(G, num_partitions, num_threads=4): - # G: NetworkX graph - # num_partitions: the number partitions or groups in which we should - # subdivide the nodes (i.e., the value of K) - - N = len(G) - model = CyLPModel() - # Decision variables, one for each node - x = model.addVariable('x', num_partitions * N, isInt=True) - # Adjacency matrix (possibly weighted) - W = nx.to_numpy_matrix(G) - z_ind = dict() - ind = 0 - w = [] - for i in range(N): - j_range = range(N) - if (not nx.is_directed(G)): - # Reduced range for undirected graphs - j_range = range(i, N) - for j in j_range: - if (W[i,j] == 0): - continue - if (i not in z_ind): - z_ind[i] = dict() - z_ind[i][j] = ind - w.append(W[i,j]) - ind += 1 - # Aux variables, one for each edge - z = model.addVariable('z', len(w), isInt=True) - # Adding the box contraints - model += 0 <= x <= 1 - model += 0 <= z <= 1 - # Adding the selection constraints - for i in range(N): - indices = [i + k * N for k in range(num_partitions)] - model += x[indices].sum() == 1 - # Adding the cutting constraints - for i in z_ind: - for j in z_ind[i]: - for k in range(num_partitions): - shift = k * N - model += z[z_ind[i][j]] + x[i + shift] + x[j + shift] <= 2 - model += z[z_ind[i][j]] + x[i + shift] - x[j + shift] >= 0 - model += z[z_ind[i][j]] - x[i + shift] + x[j + shift] >= 0 - # Adding the objective function - model.objective = CyLPArray(w) * z - lp = CyClpSimplex(model) - lp.logLevel = 0 - lp.optimizationDirection = 'max' - mip = lp.getCbcModel() - mip.logLevel = 0 - # Setting number of threads - mip.numberThreads = num_threads - mip.solve() - sol = [int(i) for i in mip.primalVariableSolution['x']] - sol_formatted = [] - for i in range(N): - indices = [i + k * N for k in range(num_partitions)] - for j in range(num_partitions): - if (sol[indices[j]] == 1): - sol_formatted.append(j) - break - - assert(len(sol_formatted) == N) - - return mip.objectiveValue, sol_formatted diff --git a/constrained mixers.ipynb b/constrained mixers.ipynb deleted file mode 100644 index 2af2662..0000000 --- a/constrained mixers.ipynb +++ /dev/null @@ -1,8670 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "11322472", - "metadata": {}, - "outputs": [], - "source": [ - "# import sys\n", - "# sys.path.append('../')\n", - "\n", - "# from qiskit_utilities.mixers import *\n", - "from mixers import *" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "8d9ecd99", - "metadata": {}, - "outputs": [], - "source": [ - "from IPython.display import display\n", - "np.set_printoptions(suppress=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "e9c44fec", - "metadata": {}, - "outputs": [], - "source": [ - "import matplotlib.pyplot as pl\n", - "import tikzplotlib" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "76ca88e9", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "import numpy as np\n", - "y={}\n", - "ma=16\n", - "y[1]=np.zeros(ma)\n", - "y[11]=np.zeros(ma)\n", - "y[111]=np.zeros(ma)\n", - "y[1111]=np.zeros(ma)\n", - "y[13]=np.zeros(ma)\n", - "y[14]=np.zeros(ma)\n", - "y[135]=np.zeros(ma)\n", - "y[156]=np.zeros(ma)\n", - "y[147]=np.zeros(ma)\n", - "\n", - "ns=range(2,2+ma)\n", - "for n in ns:\n", - "# x=[]\n", - " y[1][n-2]=n\n", - " y[11][n-2]=2*n\n", - " y[111][n-2]=3*n\n", - " y[1111][n-2]=4*n\n", - " if n>4:\n", - " y[13][n-2]=n+(n-3)\n", - " if n>5:\n", - " y[14][n-2]=n+(n-4)\n", - " if n>6:\n", - " y[135][n-2]=n+(n-3)+(n-5)\n", - " if n>7:\n", - " y[156][n-2]=n+(n-5)+(n-6)\n", - " if n>8:\n", - " y[147][n-2]=n+(n-4)+(n-7)\n", - "# for d in [1,3,4,5,6,7]:\n", - "# x.append(n-d)\n", - "# print(n,x)\n", - "\n", - "\n", - "pl.figure(figsize=(12,10))\n", - "#1 time\n", - "pl.plot(range(2,ma),range(2,ma),'k:')\n", - "pl.plot(range(2,5),range(2,5),'xk-',linewidth=4,markersize=8)\n", - "#2 times\n", - "pl.plot(range(2,ma),2*np.arange(2,ma),'k:')\n", - "pl.plot(range(5,9),2*np.arange(5,9),'xk-',linewidth=4,markersize=8)\n", - "# pl.plot(range(8,ma),2*np.arange(8,ma),'xk:')\n", - "#3 times\n", - "pl.plot(range(2,ma),3*np.arange(2,ma),'k:')\n", - "pl.plot(range(9,13),3*np.arange(9,13),'xk-',linewidth=4,markersize=8)\n", - "# pl.plot(range(12,ma),3*np.arange(12,ma),'xk:')\n", - "#4 times\n", - "pl.plot(range(2,ma),4*np.arange(2,ma),'k:')\n", - "pl.plot(range(13,ma),4*np.arange(13,ma),'xk-',label=r'$n\\times(T_1+T_2)$',linewidth=4,markersize=8)\n", - "\n", - "#+3\n", - "tmp=np.arange(5,9)\n", - "pl.plot(tmp,2*tmp-3,'rx-',label=r'$(T_1+T_2)+T_{O(3)}+T_{E(3)}$',linewidth=4,markersize=8)\n", - "tmp=np.arange(8,ma)\n", - "# pl.plot(tmp,2*tmp-3,'rx:')\n", - "\n", - "#+5+6\n", - "tmp=np.arange(9,ma)\n", - "pl.plot(tmp,3*tmp-11,'bx-',label=r'$(T_1+T_2)+\\sum_{i=5,6}(T_{O(i)}+T_{E(i)})$',linewidth=4,markersize=8)\n", - "tmp=np.arange(8,ma)\n", - "# pl.plot(tmp,2*tmp-3,'rx:')\n", - "\n", - "pl.plot([4,8],[6,28],'gx',label='sim. complete-graph',linewidth=4,markersize=8)\n", - "\n", - "# pl.plot(range(12,ma),3*np.arange(12,ma),'xk:')\n", - "# for items in y:\n", - "# print(items, y[items])\n", - "# if items==1 or items==11 or items==111 or items==1111:\n", - "# pl.plot(ns,y[items],'-kx',label=str(items))\n", - "# else:\n", - "# pl.plot(ns,y[items],label=str(items))\n", - "# # print(y)\n", - "pl.legend(loc=2)\n", - "pl.grid()\n", - "_=pl.xticks(ns)\n", - "_=pl.yticks(range(2,60,10))\n", - "pl.xlabel(\"n\")\n", - "pl.ylabel(\"# (XX+YY)-terms\")\n", - "# pl.title(\"all have linear depth, number of XX+YY terms, so cost is 4 times as much\")\n", - "tikzplotlib.save(\"onehot_Trotterizations.tex\")" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "d33b3b3a", - "metadata": { - 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure()\n", - "for n in range(5,16):\n", - " print()\n", - " print(\"--------\")\n", - " print(n)\n", - "\n", - " yesno={}\n", - " yesno[\"oe1\"]=np.zeros((n, n), dtype=bool)\n", - " yesno[\"oeoe1\"]=np.zeros((n, n), dtype=bool)\n", - " yesno[\"oeoeoe1\"]=np.zeros((n, n), dtype=bool)\n", - "# yesno[\"oeoeoeoe1\"]=np.zeros((n, n), dtype=bool)\n", - "\n", - " T_tmp={}\n", - " for oe in [\"odd\", \"even\"]:\n", - " T_tmp[oe+str(1)]=get_T(n,mode=\"nearest_int_cyclic\",oddeven=oe)\n", - " \n", - " T=np.zeros((n,n))\n", - " for oe in [\"odd\", \"even\"]:\n", - " T+=T_tmp[oe+str(1)]\n", - " display(T)\n", - " \n", - " if True:\n", - " \n", - " for p1 in range(n+1):\n", - " for p2 in range(n+1):\n", - " T12=np.matmul(np.linalg.matrix_power(T_tmp[\"odd1\"],p1),np.linalg.matrix_power(T_tmp[\"even1\"],p2))\n", - " yesno[\"oe1\"]=yesno[\"oe1\"] | (T12>0)\n", - " for p3 in range(n+1):\n", - " for p4 in range(n+1):\n", - " T1234=np.matmul(T12,np.linalg.matrix_power(T_tmp[\"odd1\"],p3))\n", - " T1234=np.matmul(T1234,np.linalg.matrix_power(T_tmp[\"even1\"],p4))\n", - " yesno[\"oeoe1\"]=yesno[\"oeoe1\"] | (T1234>0)\n", - " for p5 in range(n+1):\n", - " for p6 in range(n+1):\n", - " T123456=np.matmul(T1234,np.linalg.matrix_power(T_tmp[\"odd1\"],p5))\n", - " T123456=np.matmul(T123456,np.linalg.matrix_power(T_tmp[\"even1\"],p6))\n", - " yesno[\"oeoeoe1\"]=yesno[\"oeoeoe1\"] | (T123456>0)\n", - " # for p7 in range(n+1):\n", - " # for p8 in range(n+1):\n", - " # T12345678=np.matmul(T123456,np.linalg.matrix_power(T_tmp[\"odd1\"],p5))\n", - " # T12345687=np.matmul(T12345678,np.linalg.matrix_power(T_tmp[\"even1\"],p6))\n", - " # yesno[\"oeoeoeoe1\"]=yesno[\"oeoeoeoe1\"] | (T12345678>0)\n", - "\n", - " pl.clf()\n", - " pl.title(\"T_trotter_oe1_\"+str(n))\n", - " pl.imshow(yesno[\"oe1\"], cmap=pl.cm.gray,vmin=0,vmax=1)\n", - " pl.savefig(\"T_trotter_eo1_\"+str(n)+\".png\")\n", - "\n", - " pl.clf()\n", - " pl.title(\"T_trotter_oeoe1_\"+str(n))\n", - " pl.imshow(yesno[\"oeoe1\"], cmap=pl.cm.gray,vmin=0,vmax=1)\n", - " pl.savefig(\"T_trotter_oeoe1_\"+str(n)+\".png\")\n", - "\n", - " pl.clf()\n", - " pl.title(\"T_trotter_oeoeoe1_\"+str(n))\n", - " pl.imshow(yesno[\"oeoeoe1\"], cmap=pl.cm.gray,vmin=0,vmax=1)\n", - " pl.savefig(\"T_trotter_oeoeoe1_\"+str(n)+\".png\")\n", - "\n", - " # pl.clf()\n", - " # pl.title(\"T_trotter_oeoeoeoe1_\"+str(n))\n", - " # pl.imshow(yesno[\"oeoeoeoe1\"], cmap=pl.cm.gray,vmin=0,vmax=1)\n", - " # pl.savefig(\"T_trotter_oeoeoeoe1_\"+str(n)+\".png\")" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "4aeb4e78", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0., 0., 0., 1., 0.],\n", - " [0., 0., 0., 0., 1.],\n", - " [0., 0., 0., 0., 0.],\n", - " [1., 0., 0., 0., 0.],\n", - " [0., 1., 0., 0., 0.]])" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure()\n", - "\n", - "for idonotmatter in range(3):\n", - " if idonotmatter==0:\n", - " shifts=[3,5]\n", - " elif idonotmatter==1:\n", - " shifts=[3,6]\n", - " elif idonotmatter==2:\n", - " shifts=[4,6]\n", - "\n", - " for n in range(5,16):\n", - " print()\n", - " print(\"--------\")\n", - " print(n)\n", - "\n", - "\n", - " yesno={}\n", - " yesno[\"oe1\"+str(shifts[0])]=np.zeros((n, n), dtype=bool)\n", - " yesno[\"oe1\"+str(shifts[0])+str(shifts[1])]=np.zeros((n, n), dtype=bool)\n", - "\n", - " T_tmp={}\n", - " for oe in [\"odd\", \"even\"]:\n", - " T_tmp[oe+str(1)]=get_T(n,mode=\"nearest_int_cyclic\",oddeven=oe)\n", - " for s in shifts:\n", - " for oe in [\"odd\", \"even\"]:\n", - " T_tmp[oe+str(s)]=get_T(n,mode=\"nearest_int\",shift=s,oddeven=oe)\n", - "\n", - " T=np.zeros((n,n))\n", - " for oe in [\"odd\", \"even\"]:\n", - " T+=T_tmp[oe+str(1)]\n", - " for s in shifts:\n", - " for oe in [\"odd\", \"even\"]:\n", - " T+=T_tmp[oe+str(s)]\n", - " display(shifts,T)\n", - "\n", - " if False:\n", - " for p1 in range(n+1):\n", - " for p2 in range(n+1):\n", - " T12=np.matmul(np.linalg.matrix_power(T_tmp[\"odd1\"],p1),np.linalg.matrix_power(T_tmp[\"even1\"],p2))\n", - " for p3 in range(n+1):\n", - " for p4 in range(n+1):\n", - " T1234=np.matmul(T12,np.linalg.matrix_power(T_tmp[\"odd\"+str(shifts[0])],p3))\n", - " T1234=np.matmul(T1234,np.linalg.matrix_power(T_tmp[\"even\"+str(shifts[0])],p4))\n", - " yesno[\"oe1\"+str(shifts[0])]=yesno[\"oe1\"+str(shifts[0])] | (T1234>0)\n", - " for p5 in range(n+1):\n", - " for p6 in range(n+1):\n", - " T123456=np.matmul(T1234,np.linalg.matrix_power(T_tmp[\"odd\"+str(shifts[1])],p5))\n", - " T123456=np.matmul(T123456,np.linalg.matrix_power(T_tmp[\"even\"+str(shifts[1])],p6))\n", - " yesno[\"oe1\"+str(shifts[0])+str(shifts[1])]=yesno[\"oe1\"+str(shifts[0])+str(shifts[1])] | (T123456>0)\n", - "\n", - " pl.clf()\n", - " pl.title(\"T_trotter_eo1\"+str(shifts[0])+\"_\"+str(n))\n", - " pl.imshow(yesno[\"oe1\"+str(shifts[0])], cmap=pl.cm.gray,vmin=0,vmax=1)\n", - " pl.savefig(\"T_trotter_eo1\"+str(shifts[0])+\"_\"+str(n)+\".png\")\n", - "\n", - " pl.clf()\n", - " pl.title(\"T_trotter_eo1\"+str(shifts[0])+str(shifts[1])+\"_\"+str(n))\n", - " pl.imshow(yesno[\"oe1\"+str(shifts[0])+str(shifts[1])], cmap=pl.cm.gray,vmin=0,vmax=1)\n", - " pl.savefig(\"T_trotter_eo1\"+str(shifts[0])+str(shifts[1])+\"_\"+str(n)+\".png\")" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "612bf729", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "--------\n", - "2\n" - ] - }, - { - "data": { - "text/plain": [ - "[3, 5]" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "--------\n", - "3\n" - 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] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "--------\n", - "3\n" - ] - }, - { - "data": { - "text/plain": [ - "[4, 6]" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "array([[0., 1., 1.],\n", - " [1., 0., 1.],\n", - " [1., 1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "--------\n", - "4\n" - ] - }, - { - "data": { - "text/plain": [ - "[4, 6]" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "array([[0., 1., 0., 1.],\n", - " [1., 0., 1., 0.],\n", - " [0., 1., 0., 1.],\n", - " [1., 0., 1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure()\n", - "\n", - "for idonotmatter in range(3):\n", - " if idonotmatter==0:\n", - " shifts=[3,5]\n", - " elif idonotmatter==1:\n", - " shifts=[3,6]\n", - " elif idonotmatter==2:\n", - " shifts=[4,6]\n", - "\n", - " for n in range(2,5):\n", - " print()\n", - " print(\"--------\")\n", - " print(n)\n", - "\n", - "\n", - " yesno={}\n", - " yesno[\"oe1\"+str(shifts[0])]=np.zeros((n, n), dtype=bool)\n", - " yesno[\"oe1\"+str(shifts[0])+str(shifts[1])]=np.zeros((n, n), dtype=bool)\n", - "\n", - " T_tmp={}\n", - " for oe in [\"odd\", \"even\"]:\n", - " T_tmp[oe+str(1)]=get_T(n,mode=\"nearest_int_cyclic\",oddeven=oe)\n", - " for s in shifts:\n", - " for oe in [\"odd\", \"even\"]:\n", - " T_tmp[oe+str(s)]=get_T(n,mode=\"nearest_int\",shift=s,oddeven=oe)\n", - "\n", - " T=np.zeros((n,n))\n", - " for oe in [\"odd\", \"even\"]:\n", - " T+=T_tmp[oe+str(1)]\n", - " for s in shifts:\n", - " for oe in [\"odd\", \"even\"]:\n", - " T+=T_tmp[oe+str(s)]\n", - " display(shifts,T)\n", - "\n", - " if False:\n", - " for p1 in range(n+1):\n", - " for p2 in range(n+1):\n", - " T12=np.matmul(np.linalg.matrix_power(T_tmp[\"odd1\"],p1),np.linalg.matrix_power(T_tmp[\"even1\"],p2))\n", - " for p3 in range(n+1):\n", - " for p4 in range(n+1):\n", - " T1234=np.matmul(T12,np.linalg.matrix_power(T_tmp[\"odd\"+str(shifts[0])],p3))\n", - " T1234=np.matmul(T1234,np.linalg.matrix_power(T_tmp[\"even\"+str(shifts[0])],p4))\n", - " yesno[\"oe1\"+str(shifts[0])]=yesno[\"oe1\"+str(shifts[0])] | (T1234>0)\n", - " for p5 in range(n+1):\n", - " for p6 in range(n+1):\n", - " T123456=np.matmul(T1234,np.linalg.matrix_power(T_tmp[\"odd\"+str(shifts[1])],p5))\n", - " T123456=np.matmul(T123456,np.linalg.matrix_power(T_tmp[\"even\"+str(shifts[1])],p6))\n", - " yesno[\"oe1\"+str(shifts[0])+str(shifts[1])]=yesno[\"oe1\"+str(shifts[0])+str(shifts[1])] | (T123456>0)\n", - "\n", - " pl.clf()\n", - " pl.title(\"T_trotter_eo1\"+str(shifts[0])+\"_\"+str(n))\n", - " pl.imshow(yesno[\"oe1\"+str(shifts[0])], cmap=pl.cm.gray,vmin=0,vmax=1)\n", - " pl.savefig(\"T_trotter_eo1\"+str(shifts[0])+\"_\"+str(n)+\".png\")\n", - "\n", - " pl.clf()\n", - " pl.title(\"T_trotter_eo1\"+str(shifts[0])+str(shifts[1])+\"_\"+str(n))\n", - " pl.imshow(yesno[\"oe1\"+str(shifts[0])+str(shifts[1])], cmap=pl.cm.gray,vmin=0,vmax=1)\n", - " pl.savefig(\"T_trotter_eo1\"+str(shifts[0])+str(shifts[1])+\"_\"+str(n)+\".png\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c09c5b48", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "187997b3", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[0. 1. 1.]\n", - " [1. 0. 1.]\n", - " [1. 1. 0.]]\n", - "[[0. 1. 0. 1.]\n", - " [1. 0. 1. 0.]\n", - " [0. 1. 0. 1.]\n", - " [1. 0. 1. 0.]]\n", - "3\n", - "[[0. 1. 0. 1. 1.]\n", - " [1. 0. 1. 0. 1.]\n", - " [0. 1. 0. 1. 0.]\n", - " [1. 0. 1. 0. 1.]\n", - " [1. 1. 0. 1. 0.]]\n", - "3\n", - "[[0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0.]]\n", - "3\n", - "5\n", - "[[0. 1. 0. 1. 0. 1. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1.]\n", - " [0. 1. 0. 1. 0. 1. 0.]\n", - " [1. 0. 1. 0. 1. 0. 1.]\n", - " [0. 1. 0. 1. 0. 1. 0.]\n", - " [1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 1. 0. 1. 0. 1. 0.]]\n", - "3\n", - "5\n", - "[[0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0.]]\n", - "3\n", - "5\n", - "7\n", - "[[0. 1. 0. 1. 0. 1. 0. 1. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 1. 0. 1. 0. 1. 0. 1. 0.]]\n", - "3\n", - "5\n", - "7\n", - "[[0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]]\n", - "3\n", - "5\n", - "7\n", - "9\n", - "[[0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]]\n", - "3\n", - "5\n", - "7\n", - "9\n", - "[[0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]]\n", - "3\n", - "5\n", - "7\n", - "9\n", - "11\n", - "[[0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]]\n", - "3\n", - "5\n", - "7\n", - "9\n", - "11\n", - "[[0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]\n", - " [0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1.]\n", - " [1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0. 1. 0.]]\n" - ] - } - ], - "source": [ - "for n in range(3,15):\n", - " T=np.zeros((n,n))\n", - " for oe in [\"odd\", \"even\"]:\n", - " T+=get_T(n,mode=\"nearest_int_cyclic\",oddeven=oe)\n", - " for s in range(3,n-1,2):\n", - " print(s)\n", - " for oe in [\"odd\", \"even\"]:\n", - " T+=get_T(n,mode=\"nearest_int\",shift=s,oddeven=oe)\n", - " print(T)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6982d08f", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "c05b1469", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "--------\n", - "5\n", - "{'even': {0: {'i': [0, 2, 4], 'j': [1, 3, 0]}, 4: {'i': [4], 'j': [0]}}, 'odd': {0: {'i': [1, 3], 'j': [2, 4]}, 4: {'i': [], 'j': []}}}\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1., 0., 0., 2.],\n", - " [1., 0., 1., 0., 0.],\n", - " [0., 1., 0., 1., 0.],\n", - " [0., 0., 1., 0., 1.],\n", - " [2., 0., 0., 1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " even, odd\n", - "[[ True True True True True]\n", - " [ True True True True True]\n", - " [False True True True True]\n", - " [False True True True True]\n", - " [ True True True True True]]\n", - " even, odd, even, odd\n", - "[[ True True True True True]\n", - " [ True True True True True]\n", - " [ True True True True True]\n", - " [ True True True True True]\n", - " [ True True True True True]]\n", - " shift\n", - "[[ True True True True True]\n", - " [ True True True True True]\n", - " [ True True True True True]\n", - " [ True True True True True]\n", - " [ True True True True True]]\n" - ] - } - ], - "source": [ - " n=5\n", - " shift=3\n", - " print()\n", - " print(\"--------\")\n", - " print(n)\n", - " \n", - " ind={}\n", - " ind[\"even\"]={}\n", - " ind[\"odd\"]={}\n", - "\n", - " for a in [0,shift+1]:#,2*shift+1]:\n", - " ind[\"even\"][a]={}\n", - " ind[\"even\"][a][\"i\"]=[]\n", - " ind[\"even\"][a][\"j\"]=[]\n", - " ind[\"odd\"][a]={}\n", - " ind[\"odd\"][a][\"i\"]=[]\n", - " ind[\"odd\"][a][\"j\"]=[]\n", - " for i in range(a+0,a+n,2):\n", - " if i>=n:\n", - " break\n", - " if a>0:\n", - " j=(i-a)%n\n", - " else:\n", - " j=(i+1)%n\n", - " ind[\"even\"][a][\"i\"].append(i)\n", - " ind[\"even\"][a][\"j\"].append(j)\n", - " for i in range(a+1,a+n,2):\n", - " if i>=n:\n", - " break\n", - " if a>0:\n", - " j=(i-a)%n\n", - " else:\n", - " j=(i+1)%n\n", - " ind[\"odd\"][a][\"i\"].append(i)\n", - " ind[\"odd\"][a][\"j\"].append(j)\n", - "\n", - " print(ind)\n", - " \n", - " T_f=np.zeros((n,n))\n", - " T_eo={}\n", - " T_eo[\"even\"]={}\n", - " T_eo[\"odd\"]={}\n", - " for a in [0,shift+1]:#,2*shift+1]:\n", - " T_eo[\"even\"][a]=get_T(mode=\"leftright\",n=n,i=ind[\"even\"][a][\"i\"],j=ind[\"even\"][a][\"j\"])\n", - " T_eo[\"odd\"][a]=get_T(mode=\"leftright\",n=n,i=ind[\"odd\"][a][\"i\"],j=ind[\"odd\"][a][\"j\"])\n", - " T_f+=T_eo[\"even\"][a]+T_eo[\"odd\"][a]\n", - "# display(T_eo)\n", - " display(T_f)\n", - " \n", - " yesno1=np.zeros((n, n), dtype=bool)\n", - " yesno2=np.zeros((n, n), dtype=bool)\n", - " yesno3=np.zeros((n, n), dtype=bool)\n", - "\n", - " for p1 in range(n+1):\n", - " for p2 in range(n+1):\n", - " a=0\n", - " T1=np.matmul(np.linalg.matrix_power(T_eo[\"even\"][a],p1),np.linalg.matrix_power(T_eo[\"odd\"][a],p2))\n", - " yesno1=yesno1 | (T1>0)\n", - " \n", - " for p1 in range(n+1):\n", - " for p2 in range(n+1):\n", - " for p3 in range(n+1):\n", - " for p4 in range(n+1):\n", - " a=0\n", - " T1=np.matmul(np.linalg.matrix_power(T_eo[\"even\"][a],p1),np.linalg.matrix_power(T_eo[\"odd\"][a],p2))\n", - " a=shift+1\n", - " T1=np.matmul(T1,np.linalg.matrix_power(T_eo[\"even\"][a],p3))\n", - " T1=np.matmul(T1,np.linalg.matrix_power(T_eo[\"odd\"][a],p4))\n", - " yesno2=yesno2 | (T1>0)\n", - " \n", - " for p1 in range(n+1):\n", - " for p2 in range(n+1):\n", - " for p3 in range(n+1):\n", - " for p4 in range(n+1):\n", - " a=0\n", - " T1=np.matmul(np.linalg.matrix_power(T_eo[\"even\"][a],p1),np.linalg.matrix_power(T_eo[\"odd\"][a],p2))\n", - " T1=np.matmul(T1,np.linalg.matrix_power(T_eo[\"even\"][a],p3))\n", - " T1=np.matmul(T1,np.linalg.matrix_power(T_eo[\"odd\"][a],p4))\n", - " yesno3=yesno3 | (T1>0)\n", - " \n", - "# for p1 in range(n+1):\n", - "# for p2 in range(n+1):\n", - "# for p3 in range(n+1):\n", - "# for p4 in range(n+1):\n", - "# for p5 in range(n+1):\n", - "# for p6 in range(n+1):\n", - "# a=0\n", - "# T1=np.matmul(np.linalg.matrix_power(T_eo[\"even\"][a],p1),np.linalg.matrix_power(T_eo[\"odd\"][a],p2))\n", - "# a=shift+1\n", - "# T1=np.matmul(T1,np.linalg.matrix_power(T_eo[\"even\"][a],p3))\n", - "# T1=np.matmul(T1,np.linalg.matrix_power(T_eo[\"odd\"][a],p4))\n", - "# a=2*shift+1\n", - "# T1=np.matmul(T1,np.linalg.matrix_power(T_eo[\"even\"][a],p5))\n", - "# T1=np.matmul(T1,np.linalg.matrix_power(T_eo[\"odd\"][a],p6))\n", - "# yesno3=yesno3 | (T1>0)\n", - " \n", - "\n", - " print(\" even, odd\")\n", - " print(yesno1)\n", - " print(\" even, odd, even, odd\")\n", - " print(yesno3)\n", - " print(\" shift\")\n", - " print(yesno2)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "fb160291", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "f35930ce", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": "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\n", - 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure()\n", - "pl.imshow(1-T_f, cmap=pl.cm.gray)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "427039a3", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": "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\n", - "text/plain": [ - "
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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.figure()\n", - "pl.imshow(yesno1, cmap=pl.cm.gray)\n", - "pl.figure()\n", - "pl.imshow(yesno2, cmap=pl.cm.gray)\n", - "pl.figure()\n", - "pl.imshow(yesno3, cmap=pl.cm.gray)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4e9f9abc", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "95d942a8", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "228cc99c", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "ed752e72", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(['100', '010', '001'],\n", - " ['011', '101', '110'],\n", - " [],\n", - " (['011', '101', '110'], [0, 1, 2]))" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "tmp=['100','010','001']\n", - "tmp_neg=get_bitwise_negated_strings(tmp)\n", - "tmp, tmp_neg, get_overlap(tmp,tmp_neg), get_minus(tmp_neg,tmp)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "47c00718", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(['001', '111', '101'],\n", - " ['110', '000', '010'],\n", - " [],\n", - " (['110', '000', '010'], [0, 1, 2]))" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "tmp=['001','111','101']\n", - "tmp_neg=get_bitwise_negated_strings(tmp)\n", - "tmp, tmp_neg, get_overlap(tmp,tmp_neg), get_minus(tmp_neg,tmp)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "70cf7238", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(['100', '010', '011'], ['011', '101', '100'], ['100', '011'], (['101'], [1]))" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "tmp=['100','010','011']\n", - "tmp_neg=get_bitwise_negated_strings(tmp)\n", - "tmp, tmp_neg, get_overlap(tmp,tmp_neg), get_minus(tmp_neg,tmp)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "0a79cba8", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(['100', '010', '001', '011'],\n", - " ['011', '101', '110', '100'],\n", - " ['100', '011'],\n", - " ['101', '110'],\n", - " [1, 2])" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "tmp=['100','010','001','011']\n", - "tmp_neg=get_bitwise_negated_strings(tmp)\n", - "minus, m_ind = get_minus(tmp_neg,tmp)\n", - "tmp, tmp_neg, get_overlap(tmp,tmp_neg), minus, m_ind" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "5a021a9f", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['0010', '0001']" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "get_overlap(['1000','0100','0010','0001'],\n", - " ['0101','1001','0110','1010','0111','1011','1100','0000','1111','0011','1101','0001','1110','0010']\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "57fe1ca5", - "metadata": {}, - "outputs": [ - { - "data": { - "text/latex": [ - "$\\displaystyle 0.25 {{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{2}}\\otimes {1}}\\otimes {\\sigma_{2}} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}}$" - ], - "text/plain": [ - "0.25*sigma1x1xsigma1 + 0.25*sigma1xsigma3xsigma1 + 0.25*sigma2x1xsigma2 + 0.25*sigma2xsigma3xsigma2" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "H_12=get_H(['100','010','001'],get_T(3,\"leftright\",i=0,j=2),simplify=False)\n", - "H_12=simplifyH(H_12)\n", - "display(H_12)" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "8817bd9a", - "metadata": {}, - "outputs": [ - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 {\\sigma_{1}}\\otimes {\\sigma_{1}} - 0.5 {\\sigma_{2}}\\otimes {\\sigma_{2}}$" - ], - "text/plain": [ - "0.5*sigma1xsigma1 - 0.5*sigma2xsigma2" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "H_12=get_H(['11','00'],get_T(2,\"nearest_int\"),simplify=False)\n", - "H_12=simplifyH(H_12)\n", - "display(H_12)" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "e2f06adc", - "metadata": {}, - "outputs": [ - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 {{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {1} - 0.5 {{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {1}$" - ], - "text/plain": [ - "0.5*sigma1xsigma1x1x1 - 0.5*sigma2xsigma2x1x1" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "H_12=get_H(['1100','0000'],get_T(2,\"nearest_int\"),simplify=False)\n", - "H_12+=get_H(['1111','0011'],get_T(2,\"nearest_int\"),simplify=False)\n", - "H_12+=get_H(['1101','0001'],get_T(2,\"nearest_int\"),simplify=False)\n", - "H_12+=get_H(['1110','0010'],get_T(2,\"nearest_int\"),simplify=False)\n", - "H_12=simplifyH(H_12)\n", - "display(H_12)" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "0860a213", - "metadata": {}, - "outputs": [ - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 {{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {1} + 0.5 {{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {1}$" - ], - "text/plain": [ - "0.5*sigma1xsigma1x1x1 + 0.5*sigma2xsigma2x1x1" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "H_12=get_H(['0100','1000'],get_T(2,\"nearest_int\"),simplify=False)\n", - "H_12+=get_H(['0101','1001'],get_T(2,\"nearest_int\"),simplify=False)\n", - "H_12+=get_H(['0110','1010'],get_T(2,\"nearest_int\"),simplify=False)\n", - "H_12+=get_H(['0111','1011'],get_T(2,\"nearest_int\"),simplify=False)\n", - "\n", - "H_12=simplifyH(H_12)\n", - "display(H_12)" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "c1871039", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 \\cdot {{{1}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.5 \\cdot {{{1}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.5 {{{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.5 {{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {1} + 0.5 {{{\\sigma_{2}}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.5 {{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {1}$" - ], - "text/plain": [ - "0.5*1x1xsigma1xsigma1 + 0.5*1x1xsigma2xsigma2 + 0.5*sigma1x1xsigma1x1 + 0.5*sigma1xsigma1x1x1 + 0.5*sigma2x1xsigma2x1 + 0.5*sigma2xsigma2x1x1" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "H=get_H(['0100','1000','0010','0001'],get_T(4,\"nearest_int\"),simplify=False)\n", - "\n", - "H+=get_H(['0101','1001'],get_T(2,\"nearest_int\"),simplify=False)\n", - "H+=get_H(['0110','1010'],get_T(2,\"nearest_int\"),simplify=False)\n", - "H+=get_H(['0111','1011'],get_T(2,\"nearest_int\"),simplify=False)\n", - "\n", - "H+=get_H(['1001','0011'],get_T(2,\"nearest_int\"),simplify=False)\n", - "H+=get_H(['1100','0110'],get_T(2,\"nearest_int\"),simplify=False)\n", - "H+=get_H(['1101','0111'],get_T(2,\"nearest_int\"),simplify=False)\n", - "\n", - "H+=get_H(['0110','0101'],get_T(2,\"nearest_int\"),simplify=False)\n", - "H+=get_H(['1010','1001'],get_T(2,\"nearest_int\"),simplify=False)\n", - "H+=get_H(['1110','1101'],get_T(2,\"nearest_int\"),simplify=False)\n", - "\n", - "H=simplifyH(H)\n", - "display(H)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "bd60f6f0", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "70226fb0", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['000', '001', '010', '011', '100', '101', '110', '111']" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "all_states(3)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ba8c831e", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "243eb50c", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7116d2b2", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "d028b920", - "metadata": {}, - "outputs": [ - { - "data": { - "text/latex": [ - "$\\displaystyle \\left[\\begin{matrix}a & b\\\\b & c\\end{matrix}\\right]$" - ], - "text/plain": [ - "Matrix([\n", - "[a, b],\n", - "[b, c]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.25 a {1}\\otimes {1} - 0.25 a {1}\\otimes {\\sigma_{3}} + 0.25 a {\\sigma_{3}}\\otimes {1} - 0.25 a {\\sigma_{3}}\\otimes {\\sigma_{3}} + 0.5 b {\\sigma_{1}}\\otimes {\\sigma_{1}} + 0.5 b {\\sigma_{2}}\\otimes {\\sigma_{2}} + 0.25 c {1}\\otimes {1} + 0.25 c {1}\\otimes {\\sigma_{3}} - 0.25 c {\\sigma_{3}}\\otimes {1} - 0.25 c {\\sigma_{3}}\\otimes {\\sigma_{3}}$" - ], - "text/plain": [ - "0.25*a*1x1 - 0.25*a*1xsigma3 + 0.25*a*sigma3x1 - 0.25*a*sigma3xsigma3 + 0.5*b*sigma1xsigma1 + 0.5*b*sigma2xsigma2 + 0.25*c*1x1 + 0.25*c*1xsigma3 - 0.25*c*sigma3x1 - 0.25*c*sigma3xsigma3" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "a = symbols('a')\n", - "b = symbols('b')\n", - "c = symbols('c')\n", - "T=Matrix(([a,b],[b,c]))\n", - "display(T)\n", - "\n", - "get_H(['01','10'],T,symbolic=True)\n", - "# print_info2(['01','10'],T)" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "706f830e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hamming distance= (2, 0.2)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 {\\sigma_{1}}\\otimes {\\sigma_{1}} + 0.5 {\\sigma_{2}}\\otimes {\\sigma_{2}}$" - ], - "text/plain": [ - "0.5*sigma1xsigma1 + 0.5*sigma2xsigma2" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 4)\n", - "overlap with bitwise negated stringlist = ['01', '10']\n", - "minus = []\n", - "g(x)= 2*x0*x1 - x0 - x1 + 1\n", - "is zero for the following bitstrings:\n", - "0 1\n", - "1 0\n" - ] - } - ], - "source": [ - "T=np.ones((2,2))-np.identity(2)\n", - "display(T)\n", - "\n", - "print_info(['01','10'],T)" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "a17a3e40", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[-1., 1., 1.],\n", - " [ 1., -1., 1.],\n", - " [ 1., 1., -1.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hamming distance= (8, 4.4)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle - 0.375 \\cdot {{1}\\otimes {1}}\\otimes {1} - 0.125 \\cdot {{1}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.25 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.25 \\cdot {{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.125 \\cdot {{1}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.125 \\cdot {{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{2}}\\otimes {1}}\\otimes {\\sigma_{2}} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}} - 0.125 {{\\sigma_{3}}\\otimes {1}}\\otimes {1} + 0.125 {{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.125 {{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.375 {{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}$" - ], - "text/plain": [ - "-0.375*1x1x1 - 0.125*1x1xsigma3 + 0.25*1xsigma1xsigma1 + 0.25*1xsigma2xsigma2 - 0.125*1xsigma3x1 + 0.125*1xsigma3xsigma3 + 0.25*sigma1x1xsigma1 + 0.25*sigma1xsigma1x1 + 0.25*sigma1xsigma1xsigma3 + 0.25*sigma1xsigma3xsigma1 + 0.25*sigma2x1xsigma2 + 0.25*sigma2xsigma2x1 + 0.25*sigma2xsigma2xsigma3 + 0.25*sigma2xsigma3xsigma2 - 0.125*sigma3x1x1 + 0.125*sigma3x1xsigma3 + 0.25*sigma3xsigma1xsigma1 + 0.25*sigma3xsigma2xsigma2 + 0.125*sigma3xsigma3x1 + 0.375*sigma3xsigma3xsigma3" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (3, 46)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H+H_neg='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle - 0.75 \\cdot {{1}\\otimes {1}}\\otimes {1} + 0.5 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.5 \\cdot {{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.25 \\cdot {{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.5 {{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{1}} + 0.5 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.5 {{\\sigma_{2}}\\otimes {1}}\\otimes {\\sigma_{2}} + 0.5 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.25 {{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {1}$" - ], - "text/plain": [ - "-0.75*1x1x1 + 0.5*1xsigma1xsigma1 + 0.5*1xsigma2xsigma2 + 0.25*1xsigma3xsigma3 + 0.5*sigma1x1xsigma1 + 0.5*sigma1xsigma1x1 + 0.5*sigma2x1xsigma2 + 0.5*sigma2xsigma2x1 + 0.25*sigma3x1xsigma3 + 0.25*sigma3xsigma3x1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 18)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H+H_minus='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle - 0.75 \\cdot {{1}\\otimes {1}}\\otimes {1} + 0.5 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.5 \\cdot {{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.25 \\cdot {{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.5 {{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{1}} + 0.5 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.5 {{\\sigma_{2}}\\otimes {1}}\\otimes {\\sigma_{2}} + 0.5 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.25 {{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {1}$" - ], - "text/plain": [ - "-0.75*1x1x1 + 0.5*1xsigma1xsigma1 + 0.5*1xsigma2xsigma2 + 0.25*1xsigma3xsigma3 + 0.5*sigma1x1xsigma1 + 0.5*sigma1xsigma1x1 + 0.5*sigma2x1xsigma2 + 0.5*sigma2xsigma2x1 + 0.25*sigma3x1xsigma3 + 0.25*sigma3xsigma3x1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 18)\n", - "g(x)= -2*x0*x1*x2 + 4*x0*x1 + 4*x0*x2 - x0 + 4*x1*x2 - x1 - x2 + 1\n", - "is zero for the following bitstrings:\n", - "0 0 1\n", - "0 1 0\n", - "1 0 0\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1., 1.],\n", - " [1., 0., 1.],\n", - " [1., 1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hamming distance= (8, 4.4)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.25 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.25 \\cdot {{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.25 {{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{2}}\\otimes {1}}\\otimes {\\sigma_{2}} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}} + 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}$" - ], - "text/plain": [ - "0.25*1xsigma1xsigma1 + 0.25*1xsigma2xsigma2 + 0.25*sigma1x1xsigma1 + 0.25*sigma1xsigma1x1 + 0.25*sigma1xsigma1xsigma3 + 0.25*sigma1xsigma3xsigma1 + 0.25*sigma2x1xsigma2 + 0.25*sigma2xsigma2x1 + 0.25*sigma2xsigma2xsigma3 + 0.25*sigma2xsigma3xsigma2 + 0.25*sigma3xsigma1xsigma1 + 0.25*sigma3xsigma2xsigma2" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 36)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H+H_neg='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.5 \\cdot {{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.5 {{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{1}} + 0.5 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.5 {{\\sigma_{2}}\\otimes {1}}\\otimes {\\sigma_{2}} + 0.5 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1}$" - ], - "text/plain": [ - "0.5*1xsigma1xsigma1 + 0.5*1xsigma2xsigma2 + 0.5*sigma1x1xsigma1 + 0.5*sigma1xsigma1x1 + 0.5*sigma2x1xsigma2 + 0.5*sigma2xsigma2x1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 12)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H+H_minus='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.5 \\cdot {{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.5 {{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{1}} + 0.5 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.5 {{\\sigma_{2}}\\otimes {1}}\\otimes {\\sigma_{2}} + 0.5 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1}$" - ], - "text/plain": [ - "0.5*1xsigma1xsigma1 + 0.5*1xsigma2xsigma2 + 0.5*sigma1x1xsigma1 + 0.5*sigma1xsigma1x1 + 0.5*sigma2x1xsigma2 + 0.5*sigma2xsigma2x1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 12)\n", - "g(x)= -2*x0*x1*x2 + 4*x0*x1 + 4*x0*x2 - x0 + 4*x1*x2 - x1 - x2 + 1\n", - "is zero for the following bitstrings:\n", - "0 0 1\n", - "0 1 0\n", - "1 0 0\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1., 0.],\n", - " [1., 0., 1.],\n", - " [0., 1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hamming distance= (6, 4.2)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.25 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.25 \\cdot {{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}$" - ], - "text/plain": [ - "0.25*1xsigma1xsigma1 + 0.25*1xsigma2xsigma2 + 0.25*sigma1xsigma1x1 + 0.25*sigma1xsigma1xsigma3 + 0.25*sigma2xsigma2x1 + 0.25*sigma2xsigma2xsigma3 + 0.25*sigma3xsigma1xsigma1 + 0.25*sigma3xsigma2xsigma2" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 24)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H+H_neg='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.5 \\cdot {{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.5 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.5 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1}$" - ], - "text/plain": [ - "0.5*1xsigma1xsigma1 + 0.5*1xsigma2xsigma2 + 0.5*sigma1xsigma1x1 + 0.5*sigma2xsigma2x1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 8)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H+H_minus='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.5 \\cdot {{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.5 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.5 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1}$" - ], - "text/plain": [ - "0.5*1xsigma1xsigma1 + 0.5*1xsigma2xsigma2 + 0.5*sigma1xsigma1x1 + 0.5*sigma2xsigma2x1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 8)\n", - "g(x)= -2*x0*x1*x2 + 4*x0*x1 + 4*x0*x2 - x0 + 4*x1*x2 - x1 - x2 + 1\n", - "is zero for the following bitstrings:\n", - "0 0 1\n", - "0 1 0\n", - "1 0 0\n" - ] - } - ], - "source": [ - "T=np.ones((3,3))-2*np.identity(3)\n", - "display(T)\n", - "\n", - "print_info(['100','010','001'],T)\n", - "\n", - "T=np.ones((3,3))-np.identity(3)\n", - "display(T)\n", - "\n", - "print_info(['100','010','001'],T)\n", - "\n", - "T=np.ones((3,3))-np.identity(3)\n", - "T[0,2]=0\n", - "T[2,0]=0\n", - "display(T)\n", - "\n", - "print_info(['100','010','001'],T)" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "db0c1e57", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0., 1., 0.],\n", - " [1., 0., 1.],\n", - " [0., 1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hamming distance= (6, 4.2)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.25 \\cdot {{1}\\otimes {1}}\\otimes {\\sigma_{1}} - 0.25 \\cdot {{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{1}} - 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "0.25*1x1xsigma1 - 0.25*1xsigma3xsigma1 + 0.25*sigma1xsigma1x1 + 0.25*sigma1xsigma1xsigma3 + 0.25*sigma2xsigma2x1 + 0.25*sigma2xsigma2xsigma3 + 0.25*sigma3x1xsigma1 - 0.25*sigma3xsigma3xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (1, 20)\n", - "overlap with bitwise negated stringlist = ['100', '011']\n", - "minus = ['101']\n", - "g(x)= -2*x0*x1*x2 + 4*x0*x1 + 4*x0*x2 - 2*x0 - 2*x1*x2 - 2*x1 + 2*x2 + 2\n", - "is zero for the following bitstrings:\n", - "0 1 0\n", - "0 1 1\n", - "1 0 0\n", - "m,2**n 3 8\n", - "minus = ['101']\n", - "minus = ['101']\n", - "add minus = ['001', '111', '110']\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 \\cdot {{1}\\otimes {1}}\\otimes {\\sigma_{1}} - 0.5 \\cdot {{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}} + 0.5 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.5 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}$" - ], - "text/plain": [ - "0.5*1x1xsigma1 - 0.5*1xsigma3xsigma1 + 0.5*sigma1xsigma1x1 + 0.5*sigma2xsigma2xsigma3" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (1, 8)\n" - ] - } - ], - "source": [ - "T=np.ones((3,3))-np.identity(3)\n", - "T[0,2]=0\n", - "T[2,0]=0\n", - "display(T)\n", - "\n", - "print_info(['100','010','011'],T)\n", - "print_info2(['100','010','011'],T)" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "9f5c3766", - "metadata": {}, - "outputs": [], - "source": [ - "# for i in range(3):\n", - "# for j in range(i+1):\n", - "# T=np.zeros((3,3))\n", - "# T[i,j]=1\n", - "# T[j,i]=1\n", - "# display(T)\n", - "# # print_info(['100','010','001'],T,disp_d=False,disp_g=False,disp_neg=False,disp_H=False)\n", - "# print_info2(['100','010','001'],T)" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "a1b67037", - "metadata": {}, - "outputs": [], - "source": [ - "# T=np.zeros((2,2))\n", - "# str_lst=['0110','1011']\n", - "# T[0,1]=1\n", - "# T[1,0]=1\n", - "# display(T,str_lst)\n", - "# print_info(str_lst,T)" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "306d65b0", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['11', '00']" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hamming distance= (2, 0.2)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 {\\sigma_{1}}\\otimes {\\sigma_{1}} - 0.5 {\\sigma_{2}}\\otimes {\\sigma_{2}}$" - ], - "text/plain": [ - "0.5*sigma1xsigma1 - 0.5*sigma2xsigma2" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 4)\n", - "overlap with bitwise negated stringlist = ['11', '00']\n", - "minus = []\n", - "g(x)= -2*x0*x1 + x0 + x1\n", - "is zero for the following bitstrings:\n", - "0 0\n", - "1 1\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['10', '01']" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hamming distance= (2, 0.2)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 {\\sigma_{1}}\\otimes {\\sigma_{1}} + 0.5 {\\sigma_{2}}\\otimes {\\sigma_{2}}$" - ], - "text/plain": [ - "0.5*sigma1xsigma1 + 0.5*sigma2xsigma2" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 4)\n", - "overlap with bitwise negated stringlist = ['10', '01']\n", - "minus = []\n", - "g(x)= 2*x0*x1 - x0 - x1 + 1\n", - "is zero for the following bitstrings:\n", - "0 1\n", - "1 0\n" - ] - } - ], - "source": [ - " T=np.zeros((2,2))\n", - " T[0,1]=1\n", - " T[1,0]=1\n", - " \n", - " str_lst=['11', '00']\n", - " display(T,str_lst)\n", - " print_info(str_lst,T)\n", - " \n", - " str_lst=['10', '01']\n", - " display(T,str_lst)\n", - " print_info(str_lst,T)" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "bc777907", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "----------------------\n", - "\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['01', '10']" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 {\\sigma_{1}}\\otimes {\\sigma_{1}} + 0.5 {\\sigma_{2}}\\otimes {\\sigma_{2}}$" - ], - "text/plain": [ - "0.5*sigma1xsigma1 + 0.5*sigma2xsigma2" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "----------------------\n", - "\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['011', '100']" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "0.25*sigma1xsigma1xsigma1 - 0.25*sigma1xsigma2xsigma2 + 0.25*sigma2xsigma1xsigma2 + 0.25*sigma2xsigma2xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "----------------------\n", - "\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['0111', '1000']" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.125 {{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.125 {{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.125 {{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.125 {{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.125 {{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.125 {{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.125 {{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.125 {{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}$" - ], - "text/plain": [ - "0.125*sigma1xsigma1xsigma1xsigma1 - 0.125*sigma1xsigma1xsigma2xsigma2 - 0.125*sigma1xsigma2xsigma1xsigma2 - 0.125*sigma1xsigma2xsigma2xsigma1 + 0.125*sigma2xsigma1xsigma1xsigma2 + 0.125*sigma2xsigma1xsigma2xsigma1 + 0.125*sigma2xsigma2xsigma1xsigma1 - 0.125*sigma2xsigma2xsigma2xsigma2" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "----------------------\n", - "\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['01111', '10000']" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.0625 {{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.0625 {{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.0625 {{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.0625 {{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.0625 {{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.0625 {{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.0625 {{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.0625 {{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.0625 {{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.0625 {{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.0625 {{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.0625 {{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.0625 {{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.0625 {{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.0625 {{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.0625 {{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "0.0625*sigma1xsigma1xsigma1xsigma1xsigma1 - 0.0625*sigma1xsigma1xsigma1xsigma2xsigma2 - 0.0625*sigma1xsigma1xsigma2xsigma1xsigma2 - 0.0625*sigma1xsigma1xsigma2xsigma2xsigma1 - 0.0625*sigma1xsigma2xsigma1xsigma1xsigma2 - 0.0625*sigma1xsigma2xsigma1xsigma2xsigma1 - 0.0625*sigma1xsigma2xsigma2xsigma1xsigma1 + 0.0625*sigma1xsigma2xsigma2xsigma2xsigma2 + 0.0625*sigma2xsigma1xsigma1xsigma1xsigma2 + 0.0625*sigma2xsigma1xsigma1xsigma2xsigma1 + 0.0625*sigma2xsigma1xsigma2xsigma1xsigma1 - 0.0625*sigma2xsigma1xsigma2xsigma2xsigma2 + 0.0625*sigma2xsigma2xsigma1xsigma1xsigma1 - 0.0625*sigma2xsigma2xsigma1xsigma2xsigma2 - 0.0625*sigma2xsigma2xsigma2xsigma1xsigma2 - 0.0625*sigma2xsigma2xsigma2xsigma2xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "----------------------\n", - "\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['011111', '100000']" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.03125 {{{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.03125 {{{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.03125 {{{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.03125 {{{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.03125 {{{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.03125 {{{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.03125 {{{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.03125 {{{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.03125 {{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.03125 {{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.03125 {{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes 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0.015625*sigma1xsigma1xsigma2xsigma2xsigma2xsigma1xsigma2 + 0.015625*sigma1xsigma1xsigma2xsigma2xsigma2xsigma2xsigma1 - 0.015625*sigma1xsigma2xsigma1xsigma1xsigma1xsigma1xsigma2 - 0.015625*sigma1xsigma2xsigma1xsigma1xsigma1xsigma2xsigma1 - 0.015625*sigma1xsigma2xsigma1xsigma1xsigma2xsigma1xsigma1 + 0.015625*sigma1xsigma2xsigma1xsigma1xsigma2xsigma2xsigma2 - 0.015625*sigma1xsigma2xsigma1xsigma2xsigma1xsigma1xsigma1 + 0.015625*sigma1xsigma2xsigma1xsigma2xsigma1xsigma2xsigma2 + 0.015625*sigma1xsigma2xsigma1xsigma2xsigma2xsigma1xsigma2 + 0.015625*sigma1xsigma2xsigma1xsigma2xsigma2xsigma2xsigma1 - 0.015625*sigma1xsigma2xsigma2xsigma1xsigma1xsigma1xsigma1 + 0.015625*sigma1xsigma2xsigma2xsigma1xsigma1xsigma2xsigma2 + 0.015625*sigma1xsigma2xsigma2xsigma1xsigma2xsigma1xsigma2 + 0.015625*sigma1xsigma2xsigma2xsigma1xsigma2xsigma2xsigma1 + 0.015625*sigma1xsigma2xsigma2xsigma2xsigma1xsigma1xsigma2 + 0.015625*sigma1xsigma2xsigma2xsigma2xsigma1xsigma2xsigma1 + 0.015625*sigma1xsigma2xsigma2xsigma2xsigma2xsigma1xsigma1 - 0.015625*sigma1xsigma2xsigma2xsigma2xsigma2xsigma2xsigma2 + 0.015625*sigma2xsigma1xsigma1xsigma1xsigma1xsigma1xsigma2 + 0.015625*sigma2xsigma1xsigma1xsigma1xsigma1xsigma2xsigma1 + 0.015625*sigma2xsigma1xsigma1xsigma1xsigma2xsigma1xsigma1 - 0.015625*sigma2xsigma1xsigma1xsigma1xsigma2xsigma2xsigma2 + 0.015625*sigma2xsigma1xsigma1xsigma2xsigma1xsigma1xsigma1 - 0.015625*sigma2xsigma1xsigma1xsigma2xsigma1xsigma2xsigma2 - 0.015625*sigma2xsigma1xsigma1xsigma2xsigma2xsigma1xsigma2 - 0.015625*sigma2xsigma1xsigma1xsigma2xsigma2xsigma2xsigma1 + 0.015625*sigma2xsigma1xsigma2xsigma1xsigma1xsigma1xsigma1 - 0.015625*sigma2xsigma1xsigma2xsigma1xsigma1xsigma2xsigma2 - 0.015625*sigma2xsigma1xsigma2xsigma1xsigma2xsigma1xsigma2 - 0.015625*sigma2xsigma1xsigma2xsigma1xsigma2xsigma2xsigma1 - 0.015625*sigma2xsigma1xsigma2xsigma2xsigma1xsigma1xsigma2 - 0.015625*sigma2xsigma1xsigma2xsigma2xsigma1xsigma2xsigma1 - 0.015625*sigma2xsigma1xsigma2xsigma2xsigma2xsigma1xsigma1 + 0.015625*sigma2xsigma1xsigma2xsigma2xsigma2xsigma2xsigma2 + 0.015625*sigma2xsigma2xsigma1xsigma1xsigma1xsigma1xsigma1 - 0.015625*sigma2xsigma2xsigma1xsigma1xsigma1xsigma2xsigma2 - 0.015625*sigma2xsigma2xsigma1xsigma1xsigma2xsigma1xsigma2 - 0.015625*sigma2xsigma2xsigma1xsigma1xsigma2xsigma2xsigma1 - 0.015625*sigma2xsigma2xsigma1xsigma2xsigma1xsigma1xsigma2 - 0.015625*sigma2xsigma2xsigma1xsigma2xsigma1xsigma2xsigma1 - 0.015625*sigma2xsigma2xsigma1xsigma2xsigma2xsigma1xsigma1 + 0.015625*sigma2xsigma2xsigma1xsigma2xsigma2xsigma2xsigma2 - 0.015625*sigma2xsigma2xsigma2xsigma1xsigma1xsigma1xsigma2 - 0.015625*sigma2xsigma2xsigma2xsigma1xsigma1xsigma2xsigma1 - 0.015625*sigma2xsigma2xsigma2xsigma1xsigma2xsigma1xsigma1 + 0.015625*sigma2xsigma2xsigma2xsigma1xsigma2xsigma2xsigma2 - 0.015625*sigma2xsigma2xsigma2xsigma2xsigma1xsigma1xsigma1 + 0.015625*sigma2xsigma2xsigma2xsigma2xsigma1xsigma2xsigma2 + 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0.0078125*sigma1xsigma1xsigma1xsigma1xsigma2xsigma2xsigma2xsigma2 - 0.0078125*sigma1xsigma1xsigma1xsigma2xsigma1xsigma1xsigma1xsigma2 - 0.0078125*sigma1xsigma1xsigma1xsigma2xsigma1xsigma1xsigma2xsigma1 - 0.0078125*sigma1xsigma1xsigma1xsigma2xsigma1xsigma2xsigma1xsigma1 + 0.0078125*sigma1xsigma1xsigma1xsigma2xsigma1xsigma2xsigma2xsigma2 - 0.0078125*sigma1xsigma1xsigma1xsigma2xsigma2xsigma1xsigma1xsigma1 + 0.0078125*sigma1xsigma1xsigma1xsigma2xsigma2xsigma1xsigma2xsigma2 + 0.0078125*sigma1xsigma1xsigma1xsigma2xsigma2xsigma2xsigma1xsigma2 + 0.0078125*sigma1xsigma1xsigma1xsigma2xsigma2xsigma2xsigma2xsigma1 - 0.0078125*sigma1xsigma1xsigma2xsigma1xsigma1xsigma1xsigma1xsigma2 - 0.0078125*sigma1xsigma1xsigma2xsigma1xsigma1xsigma1xsigma2xsigma1 - 0.0078125*sigma1xsigma1xsigma2xsigma1xsigma1xsigma2xsigma1xsigma1 + 0.0078125*sigma1xsigma1xsigma2xsigma1xsigma1xsigma2xsigma2xsigma2 - 0.0078125*sigma1xsigma1xsigma2xsigma1xsigma2xsigma1xsigma1xsigma1 + 0.0078125*sigma1xsigma1xsigma2xsigma1xsigma2xsigma1xsigma2xsigma2 + 0.0078125*sigma1xsigma1xsigma2xsigma1xsigma2xsigma2xsigma1xsigma2 + 0.0078125*sigma1xsigma1xsigma2xsigma1xsigma2xsigma2xsigma2xsigma1 - 0.0078125*sigma1xsigma1xsigma2xsigma2xsigma1xsigma1xsigma1xsigma1 + 0.0078125*sigma1xsigma1xsigma2xsigma2xsigma1xsigma1xsigma2xsigma2 + 0.0078125*sigma1xsigma1xsigma2xsigma2xsigma1xsigma2xsigma1xsigma2 + 0.0078125*sigma1xsigma1xsigma2xsigma2xsigma1xsigma2xsigma2xsigma1 + 0.0078125*sigma1xsigma1xsigma2xsigma2xsigma2xsigma1xsigma1xsigma2 + 0.0078125*sigma1xsigma1xsigma2xsigma2xsigma2xsigma1xsigma2xsigma1 + 0.0078125*sigma1xsigma1xsigma2xsigma2xsigma2xsigma2xsigma1xsigma1 - 0.0078125*sigma1xsigma1xsigma2xsigma2xsigma2xsigma2xsigma2xsigma2 - 0.0078125*sigma1xsigma2xsigma1xsigma1xsigma1xsigma1xsigma1xsigma2 - 0.0078125*sigma1xsigma2xsigma1xsigma1xsigma1xsigma1xsigma2xsigma1 - 0.0078125*sigma1xsigma2xsigma1xsigma1xsigma1xsigma2xsigma1xsigma1 + 0.0078125*sigma1xsigma2xsigma1xsigma1xsigma1xsigma2xsigma2xsigma2 - 0.0078125*sigma1xsigma2xsigma1xsigma1xsigma2xsigma1xsigma1xsigma1 + 0.0078125*sigma1xsigma2xsigma1xsigma1xsigma2xsigma1xsigma2xsigma2 + 0.0078125*sigma1xsigma2xsigma1xsigma1xsigma2xsigma2xsigma1xsigma2 + 0.0078125*sigma1xsigma2xsigma1xsigma1xsigma2xsigma2xsigma2xsigma1 - 0.0078125*sigma1xsigma2xsigma1xsigma2xsigma1xsigma1xsigma1xsigma1 + 0.0078125*sigma1xsigma2xsigma1xsigma2xsigma1xsigma1xsigma2xsigma2 + 0.0078125*sigma1xsigma2xsigma1xsigma2xsigma1xsigma2xsigma1xsigma2 + 0.0078125*sigma1xsigma2xsigma1xsigma2xsigma1xsigma2xsigma2xsigma1 + 0.0078125*sigma1xsigma2xsigma1xsigma2xsigma2xsigma1xsigma1xsigma2 + 0.0078125*sigma1xsigma2xsigma1xsigma2xsigma2xsigma1xsigma2xsigma1 + 0.0078125*sigma1xsigma2xsigma1xsigma2xsigma2xsigma2xsigma1xsigma1 - 0.0078125*sigma1xsigma2xsigma1xsigma2xsigma2xsigma2xsigma2xsigma2 - 0.0078125*sigma1xsigma2xsigma2xsigma1xsigma1xsigma1xsigma1xsigma1 + 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0.0078125*sigma2xsigma1xsigma1xsigma2xsigma2xsigma1xsigma2xsigma1 - 0.0078125*sigma2xsigma1xsigma1xsigma2xsigma2xsigma2xsigma1xsigma1 + 0.0078125*sigma2xsigma1xsigma1xsigma2xsigma2xsigma2xsigma2xsigma2 + 0.0078125*sigma2xsigma1xsigma2xsigma1xsigma1xsigma1xsigma1xsigma1 - 0.0078125*sigma2xsigma1xsigma2xsigma1xsigma1xsigma1xsigma2xsigma2 - 0.0078125*sigma2xsigma1xsigma2xsigma1xsigma1xsigma2xsigma1xsigma2 - 0.0078125*sigma2xsigma1xsigma2xsigma1xsigma1xsigma2xsigma2xsigma1 - 0.0078125*sigma2xsigma1xsigma2xsigma1xsigma2xsigma1xsigma1xsigma2 - 0.0078125*sigma2xsigma1xsigma2xsigma1xsigma2xsigma1xsigma2xsigma1 - 0.0078125*sigma2xsigma1xsigma2xsigma1xsigma2xsigma2xsigma1xsigma1 + 0.0078125*sigma2xsigma1xsigma2xsigma1xsigma2xsigma2xsigma2xsigma2 - 0.0078125*sigma2xsigma1xsigma2xsigma2xsigma1xsigma1xsigma1xsigma2 - 0.0078125*sigma2xsigma1xsigma2xsigma2xsigma1xsigma1xsigma2xsigma1 - 0.0078125*sigma2xsigma1xsigma2xsigma2xsigma1xsigma2xsigma1xsigma1 + 0.0078125*sigma2xsigma1xsigma2xsigma2xsigma1xsigma2xsigma2xsigma2 - 0.0078125*sigma2xsigma1xsigma2xsigma2xsigma2xsigma1xsigma1xsigma1 + 0.0078125*sigma2xsigma1xsigma2xsigma2xsigma2xsigma1xsigma2xsigma2 + 0.0078125*sigma2xsigma1xsigma2xsigma2xsigma2xsigma2xsigma1xsigma2 + 0.0078125*sigma2xsigma1xsigma2xsigma2xsigma2xsigma2xsigma2xsigma1 + 0.0078125*sigma2xsigma2xsigma1xsigma1xsigma1xsigma1xsigma1xsigma1 - 0.0078125*sigma2xsigma2xsigma1xsigma1xsigma1xsigma1xsigma2xsigma2 - 0.0078125*sigma2xsigma2xsigma1xsigma1xsigma1xsigma2xsigma1xsigma2 - 0.0078125*sigma2xsigma2xsigma1xsigma1xsigma1xsigma2xsigma2xsigma1 - 0.0078125*sigma2xsigma2xsigma1xsigma1xsigma2xsigma1xsigma1xsigma2 - 0.0078125*sigma2xsigma2xsigma1xsigma1xsigma2xsigma1xsigma2xsigma1 - 0.0078125*sigma2xsigma2xsigma1xsigma1xsigma2xsigma2xsigma1xsigma1 + 0.0078125*sigma2xsigma2xsigma1xsigma1xsigma2xsigma2xsigma2xsigma2 - 0.0078125*sigma2xsigma2xsigma1xsigma2xsigma1xsigma1xsigma1xsigma2 - 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{\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes 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0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes 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{\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.00390625 {{{{{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "0.00390625*sigma1xsigma1xsigma1xsigma1xsigma1xsigma1xsigma1xsigma1xsigma1 - 0.00390625*sigma1xsigma1xsigma1xsigma1xsigma1xsigma1xsigma1xsigma2xsigma2 - 0.00390625*sigma1xsigma1xsigma1xsigma1xsigma1xsigma1xsigma2xsigma1xsigma2 - 0.00390625*sigma1xsigma1xsigma1xsigma1xsigma1xsigma1xsigma2xsigma2xsigma1 - 0.00390625*sigma1xsigma1xsigma1xsigma1xsigma1xsigma2xsigma1xsigma1xsigma2 - 0.00390625*sigma1xsigma1xsigma1xsigma1xsigma1xsigma2xsigma1xsigma2xsigma1 - 0.00390625*sigma1xsigma1xsigma1xsigma1xsigma1xsigma2xsigma2xsigma1xsigma1 + 0.00390625*sigma1xsigma1xsigma1xsigma1xsigma1xsigma2xsigma2xsigma2xsigma2 - 0.00390625*sigma1xsigma1xsigma1xsigma1xsigma2xsigma1xsigma1xsigma1xsigma2 - 0.00390625*sigma1xsigma1xsigma1xsigma1xsigma2xsigma1xsigma1xsigma2xsigma1 - 0.00390625*sigma1xsigma1xsigma1xsigma1xsigma2xsigma1xsigma2xsigma1xsigma1 + 0.00390625*sigma1xsigma1xsigma1xsigma1xsigma2xsigma1xsigma2xsigma2xsigma2 - 0.00390625*sigma1xsigma1xsigma1xsigma1xsigma2xsigma2xsigma1xsigma1xsigma1 + 0.00390625*sigma1xsigma1xsigma1xsigma1xsigma2xsigma2xsigma1xsigma2xsigma2 + 0.00390625*sigma1xsigma1xsigma1xsigma1xsigma2xsigma2xsigma2xsigma1xsigma2 + 0.00390625*sigma1xsigma1xsigma1xsigma1xsigma2xsigma2xsigma2xsigma2xsigma1 - 0.00390625*sigma1xsigma1xsigma1xsigma2xsigma1xsigma1xsigma1xsigma1xsigma2 - 0.00390625*sigma1xsigma1xsigma1xsigma2xsigma1xsigma1xsigma1xsigma2xsigma1 - 0.00390625*sigma1xsigma1xsigma1xsigma2xsigma1xsigma1xsigma2xsigma1xsigma1 + 0.00390625*sigma1xsigma1xsigma1xsigma2xsigma1xsigma1xsigma2xsigma2xsigma2 - 0.00390625*sigma1xsigma1xsigma1xsigma2xsigma1xsigma2xsigma1xsigma1xsigma1 + 0.00390625*sigma1xsigma1xsigma1xsigma2xsigma1xsigma2xsigma1xsigma2xsigma2 + 0.00390625*sigma1xsigma1xsigma1xsigma2xsigma1xsigma2xsigma2xsigma1xsigma2 + 0.00390625*sigma1xsigma1xsigma1xsigma2xsigma1xsigma2xsigma2xsigma2xsigma1 - 0.00390625*sigma1xsigma1xsigma1xsigma2xsigma2xsigma1xsigma1xsigma1xsigma1 + 0.00390625*sigma1xsigma1xsigma1xsigma2xsigma2xsigma1xsigma1xsigma2xsigma2 + 0.00390625*sigma1xsigma1xsigma1xsigma2xsigma2xsigma1xsigma2xsigma1xsigma2 + 0.00390625*sigma1xsigma1xsigma1xsigma2xsigma2xsigma1xsigma2xsigma2xsigma1 + 0.00390625*sigma1xsigma1xsigma1xsigma2xsigma2xsigma2xsigma1xsigma1xsigma2 + 0.00390625*sigma1xsigma1xsigma1xsigma2xsigma2xsigma2xsigma1xsigma2xsigma1 + 0.00390625*sigma1xsigma1xsigma1xsigma2xsigma2xsigma2xsigma2xsigma1xsigma1 - 0.00390625*sigma1xsigma1xsigma1xsigma2xsigma2xsigma2xsigma2xsigma2xsigma2 - 0.00390625*sigma1xsigma1xsigma2xsigma1xsigma1xsigma1xsigma1xsigma1xsigma2 - 0.00390625*sigma1xsigma1xsigma2xsigma1xsigma1xsigma1xsigma1xsigma2xsigma1 - 0.00390625*sigma1xsigma1xsigma2xsigma1xsigma1xsigma1xsigma2xsigma1xsigma1 + 0.00390625*sigma1xsigma1xsigma2xsigma1xsigma1xsigma1xsigma2xsigma2xsigma2 - 0.00390625*sigma1xsigma1xsigma2xsigma1xsigma1xsigma2xsigma1xsigma1xsigma1 + 0.00390625*sigma1xsigma1xsigma2xsigma1xsigma1xsigma2xsigma1xsigma2xsigma2 + 0.00390625*sigma1xsigma1xsigma2xsigma1xsigma1xsigma2xsigma2xsigma1xsigma2 + 0.00390625*sigma1xsigma1xsigma2xsigma1xsigma1xsigma2xsigma2xsigma2xsigma1 - 0.00390625*sigma1xsigma1xsigma2xsigma1xsigma2xsigma1xsigma1xsigma1xsigma1 + 0.00390625*sigma1xsigma1xsigma2xsigma1xsigma2xsigma1xsigma1xsigma2xsigma2 + 0.00390625*sigma1xsigma1xsigma2xsigma1xsigma2xsigma1xsigma2xsigma1xsigma2 + 0.00390625*sigma1xsigma1xsigma2xsigma1xsigma2xsigma1xsigma2xsigma2xsigma1 + 0.00390625*sigma1xsigma1xsigma2xsigma1xsigma2xsigma2xsigma1xsigma1xsigma2 + 0.00390625*sigma1xsigma1xsigma2xsigma1xsigma2xsigma2xsigma1xsigma2xsigma1 + 0.00390625*sigma1xsigma1xsigma2xsigma1xsigma2xsigma2xsigma2xsigma1xsigma1 - 0.00390625*sigma1xsigma1xsigma2xsigma1xsigma2xsigma2xsigma2xsigma2xsigma2 - 0.00390625*sigma1xsigma1xsigma2xsigma2xsigma1xsigma1xsigma1xsigma1xsigma1 + 0.00390625*sigma1xsigma1xsigma2xsigma2xsigma1xsigma1xsigma1xsigma2xsigma2 + 0.00390625*sigma1xsigma1xsigma2xsigma2xsigma1xsigma1xsigma2xsigma1xsigma2 + 0.00390625*sigma1xsigma1xsigma2xsigma2xsigma1xsigma1xsigma2xsigma2xsigma1 + 0.00390625*sigma1xsigma1xsigma2xsigma2xsigma1xsigma2xsigma1xsigma1xsigma2 + 0.00390625*sigma1xsigma1xsigma2xsigma2xsigma1xsigma2xsigma1xsigma2xsigma1 + 0.00390625*sigma1xsigma1xsigma2xsigma2xsigma1xsigma2xsigma2xsigma1xsigma1 - 0.00390625*sigma1xsigma1xsigma2xsigma2xsigma1xsigma2xsigma2xsigma2xsigma2 + 0.00390625*sigma1xsigma1xsigma2xsigma2xsigma2xsigma1xsigma1xsigma1xsigma2 + 0.00390625*sigma1xsigma1xsigma2xsigma2xsigma2xsigma1xsigma1xsigma2xsigma1 + 0.00390625*sigma1xsigma1xsigma2xsigma2xsigma2xsigma1xsigma2xsigma1xsigma1 - 0.00390625*sigma1xsigma1xsigma2xsigma2xsigma2xsigma1xsigma2xsigma2xsigma2 + 0.00390625*sigma1xsigma1xsigma2xsigma2xsigma2xsigma2xsigma1xsigma1xsigma1 - 0.00390625*sigma1xsigma1xsigma2xsigma2xsigma2xsigma2xsigma1xsigma2xsigma2 - 0.00390625*sigma1xsigma1xsigma2xsigma2xsigma2xsigma2xsigma2xsigma1xsigma2 - 0.00390625*sigma1xsigma1xsigma2xsigma2xsigma2xsigma2xsigma2xsigma2xsigma1 - 0.00390625*sigma1xsigma2xsigma1xsigma1xsigma1xsigma1xsigma1xsigma1xsigma2 - 0.00390625*sigma1xsigma2xsigma1xsigma1xsigma1xsigma1xsigma1xsigma2xsigma1 - 0.00390625*sigma1xsigma2xsigma1xsigma1xsigma1xsigma1xsigma2xsigma1xsigma1 + 0.00390625*sigma1xsigma2xsigma1xsigma1xsigma1xsigma1xsigma2xsigma2xsigma2 - 0.00390625*sigma1xsigma2xsigma1xsigma1xsigma1xsigma2xsigma1xsigma1xsigma1 + 0.00390625*sigma1xsigma2xsigma1xsigma1xsigma1xsigma2xsigma1xsigma2xsigma2 + 0.00390625*sigma1xsigma2xsigma1xsigma1xsigma1xsigma2xsigma2xsigma1xsigma2 + 0.00390625*sigma1xsigma2xsigma1xsigma1xsigma1xsigma2xsigma2xsigma2xsigma1 - 0.00390625*sigma1xsigma2xsigma1xsigma1xsigma2xsigma1xsigma1xsigma1xsigma1 + 0.00390625*sigma1xsigma2xsigma1xsigma1xsigma2xsigma1xsigma1xsigma2xsigma2 + 0.00390625*sigma1xsigma2xsigma1xsigma1xsigma2xsigma1xsigma2xsigma1xsigma2 + 0.00390625*sigma1xsigma2xsigma1xsigma1xsigma2xsigma1xsigma2xsigma2xsigma1 + 0.00390625*sigma1xsigma2xsigma1xsigma1xsigma2xsigma2xsigma1xsigma1xsigma2 + 0.00390625*sigma1xsigma2xsigma1xsigma1xsigma2xsigma2xsigma1xsigma2xsigma1 + 0.00390625*sigma1xsigma2xsigma1xsigma1xsigma2xsigma2xsigma2xsigma1xsigma1 - 0.00390625*sigma1xsigma2xsigma1xsigma1xsigma2xsigma2xsigma2xsigma2xsigma2 - 0.00390625*sigma1xsigma2xsigma1xsigma2xsigma1xsigma1xsigma1xsigma1xsigma1 + 0.00390625*sigma1xsigma2xsigma1xsigma2xsigma1xsigma1xsigma1xsigma2xsigma2 + 0.00390625*sigma1xsigma2xsigma1xsigma2xsigma1xsigma1xsigma2xsigma1xsigma2 + 0.00390625*sigma1xsigma2xsigma1xsigma2xsigma1xsigma1xsigma2xsigma2xsigma1 + 0.00390625*sigma1xsigma2xsigma1xsigma2xsigma1xsigma2xsigma1xsigma1xsigma2 + 0.00390625*sigma1xsigma2xsigma1xsigma2xsigma1xsigma2xsigma1xsigma2xsigma1 + 0.00390625*sigma1xsigma2xsigma1xsigma2xsigma1xsigma2xsigma2xsigma1xsigma1 - 0.00390625*sigma1xsigma2xsigma1xsigma2xsigma1xsigma2xsigma2xsigma2xsigma2 + 0.00390625*sigma1xsigma2xsigma1xsigma2xsigma2xsigma1xsigma1xsigma1xsigma2 + 0.00390625*sigma1xsigma2xsigma1xsigma2xsigma2xsigma1xsigma1xsigma2xsigma1 + 0.00390625*sigma1xsigma2xsigma1xsigma2xsigma2xsigma1xsigma2xsigma1xsigma1 - 0.00390625*sigma1xsigma2xsigma1xsigma2xsigma2xsigma1xsigma2xsigma2xsigma2 + 0.00390625*sigma1xsigma2xsigma1xsigma2xsigma2xsigma2xsigma1xsigma1xsigma1 - 0.00390625*sigma1xsigma2xsigma1xsigma2xsigma2xsigma2xsigma1xsigma2xsigma2 - 0.00390625*sigma1xsigma2xsigma1xsigma2xsigma2xsigma2xsigma2xsigma1xsigma2 - 0.00390625*sigma1xsigma2xsigma1xsigma2xsigma2xsigma2xsigma2xsigma2xsigma1 - 0.00390625*sigma1xsigma2xsigma2xsigma1xsigma1xsigma1xsigma1xsigma1xsigma1 + 0.00390625*sigma1xsigma2xsigma2xsigma1xsigma1xsigma1xsigma1xsigma2xsigma2 + 0.00390625*sigma1xsigma2xsigma2xsigma1xsigma1xsigma1xsigma2xsigma1xsigma2 + 0.00390625*sigma1xsigma2xsigma2xsigma1xsigma1xsigma1xsigma2xsigma2xsigma1 + 0.00390625*sigma1xsigma2xsigma2xsigma1xsigma1xsigma2xsigma1xsigma1xsigma2 + 0.00390625*sigma1xsigma2xsigma2xsigma1xsigma1xsigma2xsigma1xsigma2xsigma1 + 0.00390625*sigma1xsigma2xsigma2xsigma1xsigma1xsigma2xsigma2xsigma1xsigma1 - 0.00390625*sigma1xsigma2xsigma2xsigma1xsigma1xsigma2xsigma2xsigma2xsigma2 + 0.00390625*sigma1xsigma2xsigma2xsigma1xsigma2xsigma1xsigma1xsigma1xsigma2 + 0.00390625*sigma1xsigma2xsigma2xsigma1xsigma2xsigma1xsigma1xsigma2xsigma1 + 0.00390625*sigma1xsigma2xsigma2xsigma1xsigma2xsigma1xsigma2xsigma1xsigma1 - 0.00390625*sigma1xsigma2xsigma2xsigma1xsigma2xsigma1xsigma2xsigma2xsigma2 + 0.00390625*sigma1xsigma2xsigma2xsigma1xsigma2xsigma2xsigma1xsigma1xsigma1 - 0.00390625*sigma1xsigma2xsigma2xsigma1xsigma2xsigma2xsigma1xsigma2xsigma2 - 0.00390625*sigma1xsigma2xsigma2xsigma1xsigma2xsigma2xsigma2xsigma1xsigma2 - 0.00390625*sigma1xsigma2xsigma2xsigma1xsigma2xsigma2xsigma2xsigma2xsigma1 + 0.00390625*sigma1xsigma2xsigma2xsigma2xsigma1xsigma1xsigma1xsigma1xsigma2 + 0.00390625*sigma1xsigma2xsigma2xsigma2xsigma1xsigma1xsigma1xsigma2xsigma1 + 0.00390625*sigma1xsigma2xsigma2xsigma2xsigma1xsigma1xsigma2xsigma1xsigma1 - 0.00390625*sigma1xsigma2xsigma2xsigma2xsigma1xsigma1xsigma2xsigma2xsigma2 + 0.00390625*sigma1xsigma2xsigma2xsigma2xsigma1xsigma2xsigma1xsigma1xsigma1 - 0.00390625*sigma1xsigma2xsigma2xsigma2xsigma1xsigma2xsigma1xsigma2xsigma2 - 0.00390625*sigma1xsigma2xsigma2xsigma2xsigma1xsigma2xsigma2xsigma1xsigma2 - 0.00390625*sigma1xsigma2xsigma2xsigma2xsigma1xsigma2xsigma2xsigma2xsigma1 + 0.00390625*sigma1xsigma2xsigma2xsigma2xsigma2xsigma1xsigma1xsigma1xsigma1 - 0.00390625*sigma1xsigma2xsigma2xsigma2xsigma2xsigma1xsigma1xsigma2xsigma2 - 0.00390625*sigma1xsigma2xsigma2xsigma2xsigma2xsigma1xsigma2xsigma1xsigma2 - 0.00390625*sigma1xsigma2xsigma2xsigma2xsigma2xsigma1xsigma2xsigma2xsigma1 - 0.00390625*sigma1xsigma2xsigma2xsigma2xsigma2xsigma2xsigma1xsigma1xsigma2 - 0.00390625*sigma1xsigma2xsigma2xsigma2xsigma2xsigma2xsigma1xsigma2xsigma1 - 0.00390625*sigma1xsigma2xsigma2xsigma2xsigma2xsigma2xsigma2xsigma1xsigma1 + 0.00390625*sigma1xsigma2xsigma2xsigma2xsigma2xsigma2xsigma2xsigma2xsigma2 + 0.00390625*sigma2xsigma1xsigma1xsigma1xsigma1xsigma1xsigma1xsigma1xsigma2 + 0.00390625*sigma2xsigma1xsigma1xsigma1xsigma1xsigma1xsigma1xsigma2xsigma1 + 0.00390625*sigma2xsigma1xsigma1xsigma1xsigma1xsigma1xsigma2xsigma1xsigma1 - 0.00390625*sigma2xsigma1xsigma1xsigma1xsigma1xsigma1xsigma2xsigma2xsigma2 + 0.00390625*sigma2xsigma1xsigma1xsigma1xsigma1xsigma2xsigma1xsigma1xsigma1 - 0.00390625*sigma2xsigma1xsigma1xsigma1xsigma1xsigma2xsigma1xsigma2xsigma2 - 0.00390625*sigma2xsigma1xsigma1xsigma1xsigma1xsigma2xsigma2xsigma1xsigma2 - 0.00390625*sigma2xsigma1xsigma1xsigma1xsigma1xsigma2xsigma2xsigma2xsigma1 + 0.00390625*sigma2xsigma1xsigma1xsigma1xsigma2xsigma1xsigma1xsigma1xsigma1 - 0.00390625*sigma2xsigma1xsigma1xsigma1xsigma2xsigma1xsigma1xsigma2xsigma2 - 0.00390625*sigma2xsigma1xsigma1xsigma1xsigma2xsigma1xsigma2xsigma1xsigma2 - 0.00390625*sigma2xsigma1xsigma1xsigma1xsigma2xsigma1xsigma2xsigma2xsigma1 - 0.00390625*sigma2xsigma1xsigma1xsigma1xsigma2xsigma2xsigma1xsigma1xsigma2 - 0.00390625*sigma2xsigma1xsigma1xsigma1xsigma2xsigma2xsigma1xsigma2xsigma1 - 0.00390625*sigma2xsigma1xsigma1xsigma1xsigma2xsigma2xsigma2xsigma1xsigma1 + 0.00390625*sigma2xsigma1xsigma1xsigma1xsigma2xsigma2xsigma2xsigma2xsigma2 + 0.00390625*sigma2xsigma1xsigma1xsigma2xsigma1xsigma1xsigma1xsigma1xsigma1 - 0.00390625*sigma2xsigma1xsigma1xsigma2xsigma1xsigma1xsigma1xsigma2xsigma2 - 0.00390625*sigma2xsigma1xsigma1xsigma2xsigma1xsigma1xsigma2xsigma1xsigma2 - 0.00390625*sigma2xsigma1xsigma1xsigma2xsigma1xsigma1xsigma2xsigma2xsigma1 - 0.00390625*sigma2xsigma1xsigma1xsigma2xsigma1xsigma2xsigma1xsigma1xsigma2 - 0.00390625*sigma2xsigma1xsigma1xsigma2xsigma1xsigma2xsigma1xsigma2xsigma1 - 0.00390625*sigma2xsigma1xsigma1xsigma2xsigma1xsigma2xsigma2xsigma1xsigma1 + 0.00390625*sigma2xsigma1xsigma1xsigma2xsigma1xsigma2xsigma2xsigma2xsigma2 - 0.00390625*sigma2xsigma1xsigma1xsigma2xsigma2xsigma1xsigma1xsigma1xsigma2 - 0.00390625*sigma2xsigma1xsigma1xsigma2xsigma2xsigma1xsigma1xsigma2xsigma1 - 0.00390625*sigma2xsigma1xsigma1xsigma2xsigma2xsigma1xsigma2xsigma1xsigma1 + 0.00390625*sigma2xsigma1xsigma1xsigma2xsigma2xsigma1xsigma2xsigma2xsigma2 - 0.00390625*sigma2xsigma1xsigma1xsigma2xsigma2xsigma2xsigma1xsigma1xsigma1 + 0.00390625*sigma2xsigma1xsigma1xsigma2xsigma2xsigma2xsigma1xsigma2xsigma2 + 0.00390625*sigma2xsigma1xsigma1xsigma2xsigma2xsigma2xsigma2xsigma1xsigma2 + 0.00390625*sigma2xsigma1xsigma1xsigma2xsigma2xsigma2xsigma2xsigma2xsigma1 + 0.00390625*sigma2xsigma1xsigma2xsigma1xsigma1xsigma1xsigma1xsigma1xsigma1 - 0.00390625*sigma2xsigma1xsigma2xsigma1xsigma1xsigma1xsigma1xsigma2xsigma2 - 0.00390625*sigma2xsigma1xsigma2xsigma1xsigma1xsigma1xsigma2xsigma1xsigma2 - 0.00390625*sigma2xsigma1xsigma2xsigma1xsigma1xsigma1xsigma2xsigma2xsigma1 - 0.00390625*sigma2xsigma1xsigma2xsigma1xsigma1xsigma2xsigma1xsigma1xsigma2 - 0.00390625*sigma2xsigma1xsigma2xsigma1xsigma1xsigma2xsigma1xsigma2xsigma1 - 0.00390625*sigma2xsigma1xsigma2xsigma1xsigma1xsigma2xsigma2xsigma1xsigma1 + 0.00390625*sigma2xsigma1xsigma2xsigma1xsigma1xsigma2xsigma2xsigma2xsigma2 - 0.00390625*sigma2xsigma1xsigma2xsigma1xsigma2xsigma1xsigma1xsigma1xsigma2 - 0.00390625*sigma2xsigma1xsigma2xsigma1xsigma2xsigma1xsigma1xsigma2xsigma1 - 0.00390625*sigma2xsigma1xsigma2xsigma1xsigma2xsigma1xsigma2xsigma1xsigma1 + 0.00390625*sigma2xsigma1xsigma2xsigma1xsigma2xsigma1xsigma2xsigma2xsigma2 - 0.00390625*sigma2xsigma1xsigma2xsigma1xsigma2xsigma2xsigma1xsigma1xsigma1 + 0.00390625*sigma2xsigma1xsigma2xsigma1xsigma2xsigma2xsigma1xsigma2xsigma2 + 0.00390625*sigma2xsigma1xsigma2xsigma1xsigma2xsigma2xsigma2xsigma1xsigma2 + 0.00390625*sigma2xsigma1xsigma2xsigma1xsigma2xsigma2xsigma2xsigma2xsigma1 - 0.00390625*sigma2xsigma1xsigma2xsigma2xsigma1xsigma1xsigma1xsigma1xsigma2 - 0.00390625*sigma2xsigma1xsigma2xsigma2xsigma1xsigma1xsigma1xsigma2xsigma1 - 0.00390625*sigma2xsigma1xsigma2xsigma2xsigma1xsigma1xsigma2xsigma1xsigma1 + 0.00390625*sigma2xsigma1xsigma2xsigma2xsigma1xsigma1xsigma2xsigma2xsigma2 - 0.00390625*sigma2xsigma1xsigma2xsigma2xsigma1xsigma2xsigma1xsigma1xsigma1 + 0.00390625*sigma2xsigma1xsigma2xsigma2xsigma1xsigma2xsigma1xsigma2xsigma2 + 0.00390625*sigma2xsigma1xsigma2xsigma2xsigma1xsigma2xsigma2xsigma1xsigma2 + 0.00390625*sigma2xsigma1xsigma2xsigma2xsigma1xsigma2xsigma2xsigma2xsigma1 - 0.00390625*sigma2xsigma1xsigma2xsigma2xsigma2xsigma1xsigma1xsigma1xsigma1 + 0.00390625*sigma2xsigma1xsigma2xsigma2xsigma2xsigma1xsigma1xsigma2xsigma2 + 0.00390625*sigma2xsigma1xsigma2xsigma2xsigma2xsigma1xsigma2xsigma1xsigma2 + 0.00390625*sigma2xsigma1xsigma2xsigma2xsigma2xsigma1xsigma2xsigma2xsigma1 + 0.00390625*sigma2xsigma1xsigma2xsigma2xsigma2xsigma2xsigma1xsigma1xsigma2 + 0.00390625*sigma2xsigma1xsigma2xsigma2xsigma2xsigma2xsigma1xsigma2xsigma1 + 0.00390625*sigma2xsigma1xsigma2xsigma2xsigma2xsigma2xsigma2xsigma1xsigma1 - 0.00390625*sigma2xsigma1xsigma2xsigma2xsigma2xsigma2xsigma2xsigma2xsigma2 + 0.00390625*sigma2xsigma2xsigma1xsigma1xsigma1xsigma1xsigma1xsigma1xsigma1 - 0.00390625*sigma2xsigma2xsigma1xsigma1xsigma1xsigma1xsigma1xsigma2xsigma2 - 0.00390625*sigma2xsigma2xsigma1xsigma1xsigma1xsigma1xsigma2xsigma1xsigma2 - 0.00390625*sigma2xsigma2xsigma1xsigma1xsigma1xsigma1xsigma2xsigma2xsigma1 - 0.00390625*sigma2xsigma2xsigma1xsigma1xsigma1xsigma2xsigma1xsigma1xsigma2 - 0.00390625*sigma2xsigma2xsigma1xsigma1xsigma1xsigma2xsigma1xsigma2xsigma1 - 0.00390625*sigma2xsigma2xsigma1xsigma1xsigma1xsigma2xsigma2xsigma1xsigma1 + 0.00390625*sigma2xsigma2xsigma1xsigma1xsigma1xsigma2xsigma2xsigma2xsigma2 - 0.00390625*sigma2xsigma2xsigma1xsigma1xsigma2xsigma1xsigma1xsigma1xsigma2 - 0.00390625*sigma2xsigma2xsigma1xsigma1xsigma2xsigma1xsigma1xsigma2xsigma1 - 0.00390625*sigma2xsigma2xsigma1xsigma1xsigma2xsigma1xsigma2xsigma1xsigma1 + 0.00390625*sigma2xsigma2xsigma1xsigma1xsigma2xsigma1xsigma2xsigma2xsigma2 - 0.00390625*sigma2xsigma2xsigma1xsigma1xsigma2xsigma2xsigma1xsigma1xsigma1 + 0.00390625*sigma2xsigma2xsigma1xsigma1xsigma2xsigma2xsigma1xsigma2xsigma2 + 0.00390625*sigma2xsigma2xsigma1xsigma1xsigma2xsigma2xsigma2xsigma1xsigma2 + 0.00390625*sigma2xsigma2xsigma1xsigma1xsigma2xsigma2xsigma2xsigma2xsigma1 - 0.00390625*sigma2xsigma2xsigma1xsigma2xsigma1xsigma1xsigma1xsigma1xsigma2 - 0.00390625*sigma2xsigma2xsigma1xsigma2xsigma1xsigma1xsigma1xsigma2xsigma1 - 0.00390625*sigma2xsigma2xsigma1xsigma2xsigma1xsigma1xsigma2xsigma1xsigma1 + 0.00390625*sigma2xsigma2xsigma1xsigma2xsigma1xsigma1xsigma2xsigma2xsigma2 - 0.00390625*sigma2xsigma2xsigma1xsigma2xsigma1xsigma2xsigma1xsigma1xsigma1 + 0.00390625*sigma2xsigma2xsigma1xsigma2xsigma1xsigma2xsigma1xsigma2xsigma2 + 0.00390625*sigma2xsigma2xsigma1xsigma2xsigma1xsigma2xsigma2xsigma1xsigma2 + 0.00390625*sigma2xsigma2xsigma1xsigma2xsigma1xsigma2xsigma2xsigma2xsigma1 - 0.00390625*sigma2xsigma2xsigma1xsigma2xsigma2xsigma1xsigma1xsigma1xsigma1 + 0.00390625*sigma2xsigma2xsigma1xsigma2xsigma2xsigma1xsigma1xsigma2xsigma2 + 0.00390625*sigma2xsigma2xsigma1xsigma2xsigma2xsigma1xsigma2xsigma1xsigma2 + 0.00390625*sigma2xsigma2xsigma1xsigma2xsigma2xsigma1xsigma2xsigma2xsigma1 + 0.00390625*sigma2xsigma2xsigma1xsigma2xsigma2xsigma2xsigma1xsigma1xsigma2 + 0.00390625*sigma2xsigma2xsigma1xsigma2xsigma2xsigma2xsigma1xsigma2xsigma1 + 0.00390625*sigma2xsigma2xsigma1xsigma2xsigma2xsigma2xsigma2xsigma1xsigma1 - 0.00390625*sigma2xsigma2xsigma1xsigma2xsigma2xsigma2xsigma2xsigma2xsigma2 - 0.00390625*sigma2xsigma2xsigma2xsigma1xsigma1xsigma1xsigma1xsigma1xsigma2 - 0.00390625*sigma2xsigma2xsigma2xsigma1xsigma1xsigma1xsigma1xsigma2xsigma1 - 0.00390625*sigma2xsigma2xsigma2xsigma1xsigma1xsigma1xsigma2xsigma1xsigma1 + 0.00390625*sigma2xsigma2xsigma2xsigma1xsigma1xsigma1xsigma2xsigma2xsigma2 - 0.00390625*sigma2xsigma2xsigma2xsigma1xsigma1xsigma2xsigma1xsigma1xsigma1 + 0.00390625*sigma2xsigma2xsigma2xsigma1xsigma1xsigma2xsigma1xsigma2xsigma2 + 0.00390625*sigma2xsigma2xsigma2xsigma1xsigma1xsigma2xsigma2xsigma1xsigma2 + 0.00390625*sigma2xsigma2xsigma2xsigma1xsigma1xsigma2xsigma2xsigma2xsigma1 - 0.00390625*sigma2xsigma2xsigma2xsigma1xsigma2xsigma1xsigma1xsigma1xsigma1 + 0.00390625*sigma2xsigma2xsigma2xsigma1xsigma2xsigma1xsigma1xsigma2xsigma2 + 0.00390625*sigma2xsigma2xsigma2xsigma1xsigma2xsigma1xsigma2xsigma1xsigma2 + 0.00390625*sigma2xsigma2xsigma2xsigma1xsigma2xsigma1xsigma2xsigma2xsigma1 + 0.00390625*sigma2xsigma2xsigma2xsigma1xsigma2xsigma2xsigma1xsigma1xsigma2 + 0.00390625*sigma2xsigma2xsigma2xsigma1xsigma2xsigma2xsigma1xsigma2xsigma1 + 0.00390625*sigma2xsigma2xsigma2xsigma1xsigma2xsigma2xsigma2xsigma1xsigma1 - 0.00390625*sigma2xsigma2xsigma2xsigma1xsigma2xsigma2xsigma2xsigma2xsigma2 - 0.00390625*sigma2xsigma2xsigma2xsigma2xsigma1xsigma1xsigma1xsigma1xsigma1 + 0.00390625*sigma2xsigma2xsigma2xsigma2xsigma1xsigma1xsigma1xsigma2xsigma2 + 0.00390625*sigma2xsigma2xsigma2xsigma2xsigma1xsigma1xsigma2xsigma1xsigma2 + 0.00390625*sigma2xsigma2xsigma2xsigma2xsigma1xsigma1xsigma2xsigma2xsigma1 + 0.00390625*sigma2xsigma2xsigma2xsigma2xsigma1xsigma2xsigma1xsigma1xsigma2 + 0.00390625*sigma2xsigma2xsigma2xsigma2xsigma1xsigma2xsigma1xsigma2xsigma1 + 0.00390625*sigma2xsigma2xsigma2xsigma2xsigma1xsigma2xsigma2xsigma1xsigma1 - 0.00390625*sigma2xsigma2xsigma2xsigma2xsigma1xsigma2xsigma2xsigma2xsigma2 + 0.00390625*sigma2xsigma2xsigma2xsigma2xsigma2xsigma1xsigma1xsigma1xsigma2 + 0.00390625*sigma2xsigma2xsigma2xsigma2xsigma2xsigma1xsigma1xsigma2xsigma1 + 0.00390625*sigma2xsigma2xsigma2xsigma2xsigma2xsigma1xsigma2xsigma1xsigma1 - 0.00390625*sigma2xsigma2xsigma2xsigma2xsigma2xsigma1xsigma2xsigma2xsigma2 + 0.00390625*sigma2xsigma2xsigma2xsigma2xsigma2xsigma2xsigma1xsigma1xsigma1 - 0.00390625*sigma2xsigma2xsigma2xsigma2xsigma2xsigma2xsigma1xsigma2xsigma2 - 0.00390625*sigma2xsigma2xsigma2xsigma2xsigma2xsigma2xsigma2xsigma1xsigma2 - 0.00390625*sigma2xsigma2xsigma2xsigma2xsigma2xsigma2xsigma2xsigma2xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "for n in range(2,10):\n", - " print(\"----------------------\")\n", - " print(\"\")\n", - " \n", - " T=np.zeros((2,2))\n", - " T[0,1]=T[1,0]=1\n", - " \n", - " str_lst=[]\n", - " str_tmp='01'\n", - " for i in range(n-2):\n", - " str_tmp+=\"1\"\n", - " str_lst.append(str_tmp)\n", - " \n", - " str_tmp='10'\n", - " for i in range(n-2):\n", - " str_tmp+=\"0\"\n", - " str_lst.append(str_tmp)\n", - " \n", - " display(T,str_lst)\n", - "\n", - " H=get_H(str_lst,T,simplify=True)\n", - "# print(2**(n-2))\n", - " display(H)" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "945c6797", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "----------------------\n", - "\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['10', '01']" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "m,2**n 2 4\n", - "minus = []\n", - "add minus = ['00', '11']\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 1.0 {\\sigma_{1}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "1.0*sigma1xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 2)\n", - "----------------------\n", - "\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1., 0.],\n", - " [1., 0., 1.],\n", - " [0., 1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['100', '010', '001']" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "m,2**n 3 8\n", - "add minus = ['011', '101', '110']\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.5 \\cdot {{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.5 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.5 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1}$" - ], - "text/plain": [ - "0.5*1xsigma1xsigma1 + 0.5*1xsigma2xsigma2 + 0.5*sigma1xsigma1x1 + 0.5*sigma2xsigma2x1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 8)\n", - "----------------------\n", - "\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1., 0., 0.],\n", - " [1., 0., 1., 0.],\n", - " [0., 1., 0., 1.],\n", - " [0., 0., 1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['1000', '0100', '0010', '0001']" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "m,2**n 4 16\n", - "add minus = ['0111', '1011', '1101', '1110']\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.25 \\cdot {{{1}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.25 \\cdot {{{1}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.25 \\cdot {{{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.25 \\cdot {{{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.25 {{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {1} + 0.25 {{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.25 {{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {1} + 0.25 {{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.25 {{{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.25 {{{\\sigma_{3}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}} + 0.25 {{{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.25 {{{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}$" - ], - "text/plain": [ - "0.25*1x1xsigma1xsigma1 + 0.25*1x1xsigma2xsigma2 + 0.25*1xsigma1xsigma1x1 + 0.25*1xsigma2xsigma2x1 + 0.25*sigma1xsigma1x1x1 + 0.25*sigma1xsigma1xsigma3xsigma3 + 0.25*sigma2xsigma2x1x1 + 0.25*sigma2xsigma2xsigma3xsigma3 + 0.25*sigma3xsigma1xsigma1xsigma3 + 0.25*sigma3xsigma2xsigma2xsigma3 + 0.25*sigma3xsigma3xsigma1xsigma1 + 0.25*sigma3xsigma3xsigma2xsigma2" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 48)\n", - "----------------------\n", - "\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1., 0., 0., 0.],\n", - " [1., 0., 1., 0., 0.],\n", - " [0., 1., 0., 1., 0.],\n", - " [0., 0., 1., 0., 1.],\n", - " [0., 0., 0., 1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['10000', '01000', '00100', '00010', '00001']" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "m,2**n 5 32\n", - "add minus = ['01111', '10111', '11011', '11101', '11110']\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.125 \\cdot {{{{1}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.125 \\cdot {{{{1}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.125 \\cdot {{{{1}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.125 \\cdot {{{{1}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.125 \\cdot {{{{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {1} + 0.125 \\cdot {{{{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.125 \\cdot {{{{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {1} + 0.125 \\cdot {{{{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.125 \\cdot {{{{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.125 \\cdot {{{{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}} + 0.125 \\cdot {{{{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.125 \\cdot {{{{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.125 {{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {1}}\\otimes {1} + 0.125 {{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.125 {{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.125 {{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.125 {{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {1}}\\otimes {1} + 0.125 {{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.125 {{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.125 {{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.125 {{{{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.125 {{{{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}} + 0.125 {{{{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.125 {{{{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.125 {{{{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.125 {{{{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.125 {{{{\\sigma_{3}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.125 {{{{\\sigma_{3}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.125 {{{{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.125 {{{{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.125 {{{{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.125 {{{{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {1}$" - ], - "text/plain": [ - "0.125*1x1x1xsigma1xsigma1 + 0.125*1x1x1xsigma2xsigma2 + 0.125*1x1xsigma1xsigma1x1 + 0.125*1x1xsigma2xsigma2x1 + 0.125*1xsigma1xsigma1x1x1 + 0.125*1xsigma1xsigma1xsigma3xsigma3 + 0.125*1xsigma2xsigma2x1x1 + 0.125*1xsigma2xsigma2xsigma3xsigma3 + 0.125*1xsigma3xsigma1xsigma1xsigma3 + 0.125*1xsigma3xsigma2xsigma2xsigma3 + 0.125*1xsigma3xsigma3xsigma1xsigma1 + 0.125*1xsigma3xsigma3xsigma2xsigma2 + 0.125*sigma1xsigma1x1x1x1 + 0.125*sigma1xsigma1x1xsigma3xsigma3 + 0.125*sigma1xsigma1xsigma3x1xsigma3 + 0.125*sigma1xsigma1xsigma3xsigma3x1 + 0.125*sigma2xsigma2x1x1x1 + 0.125*sigma2xsigma2x1xsigma3xsigma3 + 0.125*sigma2xsigma2xsigma3x1xsigma3 + 0.125*sigma2xsigma2xsigma3xsigma3x1 + 0.125*sigma3x1xsigma1xsigma1xsigma3 + 0.125*sigma3x1xsigma2xsigma2xsigma3 + 0.125*sigma3x1xsigma3xsigma1xsigma1 + 0.125*sigma3x1xsigma3xsigma2xsigma2 + 0.125*sigma3xsigma1xsigma1x1xsigma3 + 0.125*sigma3xsigma1xsigma1xsigma3x1 + 0.125*sigma3xsigma2xsigma2x1xsigma3 + 0.125*sigma3xsigma2xsigma2xsigma3x1 + 0.125*sigma3xsigma3x1xsigma1xsigma1 + 0.125*sigma3xsigma3x1xsigma2xsigma2 + 0.125*sigma3xsigma3xsigma1xsigma1x1 + 0.125*sigma3xsigma3xsigma2xsigma2x1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 160)\n", - "----------------------\n", - "\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1., 0., 0., 0., 0.],\n", - " [1., 0., 1., 0., 0., 0.],\n", - " [0., 1., 0., 1., 0., 0.],\n", - " [0., 0., 1., 0., 1., 0.],\n", - " [0., 0., 0., 1., 0., 1.],\n", - " [0., 0., 0., 0., 1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['100000', '010000', '001000', '000100', '000010', '000001']" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "m,2**n 6 64\n", - "add minus = ['011111', '101111', '110111', '111011', '111101', '111110']\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.0625 \\cdot {{{{{1}\\otimes {1}}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.0625 \\cdot {{{{{1}\\otimes {1}}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.0625 \\cdot {{{{{1}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.0625 \\cdot {{{{{1}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.0625 \\cdot {{{{{1}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {1} + 0.0625 \\cdot {{{{{1}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.0625 \\cdot {{{{{1}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {1} + 0.0625 \\cdot {{{{{1}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.0625 \\cdot {{{{{1}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.0625 \\cdot {{{{{1}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}} + 0.0625 \\cdot {{{{{1}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.0625 \\cdot {{{{{1}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {1}}\\otimes {1} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {1}}\\otimes {1} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.0625 \\cdot {{{{{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.0625 {{{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {1}}\\otimes {1}}\\otimes {1} + 0.0625 {{{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.0625 {{{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.0625 {{{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {1} + 0.0625 {{{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {1}}\\otimes {1}}\\otimes {1} + 0.0625 {{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.0625 {{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.0625 {{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {1} + 0.0625 {{{{{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.0625 {{{{{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.0625 {{{{{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.0625 {{{{{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {1} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {1} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {1} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {1}}\\otimes {1} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.0625 {{{{{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}$" - ], - "text/plain": [ - "0.0625*1x1x1x1xsigma1xsigma1 + 0.0625*1x1x1x1xsigma2xsigma2 + 0.0625*1x1x1xsigma1xsigma1x1 + 0.0625*1x1x1xsigma2xsigma2x1 + 0.0625*1x1xsigma1xsigma1x1x1 + 0.0625*1x1xsigma1xsigma1xsigma3xsigma3 + 0.0625*1x1xsigma2xsigma2x1x1 + 0.0625*1x1xsigma2xsigma2xsigma3xsigma3 + 0.0625*1x1xsigma3xsigma1xsigma1xsigma3 + 0.0625*1x1xsigma3xsigma2xsigma2xsigma3 + 0.0625*1x1xsigma3xsigma3xsigma1xsigma1 + 0.0625*1x1xsigma3xsigma3xsigma2xsigma2 + 0.0625*1xsigma1xsigma1x1x1x1 + 0.0625*1xsigma1xsigma1x1xsigma3xsigma3 + 0.0625*1xsigma1xsigma1xsigma3x1xsigma3 + 0.0625*1xsigma1xsigma1xsigma3xsigma3x1 + 0.0625*1xsigma2xsigma2x1x1x1 + 0.0625*1xsigma2xsigma2x1xsigma3xsigma3 + 0.0625*1xsigma2xsigma2xsigma3x1xsigma3 + 0.0625*1xsigma2xsigma2xsigma3xsigma3x1 + 0.0625*1xsigma3x1xsigma1xsigma1xsigma3 + 0.0625*1xsigma3x1xsigma2xsigma2xsigma3 + 0.0625*1xsigma3x1xsigma3xsigma1xsigma1 + 0.0625*1xsigma3x1xsigma3xsigma2xsigma2 + 0.0625*1xsigma3xsigma1xsigma1x1xsigma3 + 0.0625*1xsigma3xsigma1xsigma1xsigma3x1 + 0.0625*1xsigma3xsigma2xsigma2x1xsigma3 + 0.0625*1xsigma3xsigma2xsigma2xsigma3x1 + 0.0625*1xsigma3xsigma3x1xsigma1xsigma1 + 0.0625*1xsigma3xsigma3x1xsigma2xsigma2 + 0.0625*1xsigma3xsigma3xsigma1xsigma1x1 + 0.0625*1xsigma3xsigma3xsigma2xsigma2x1 + 0.0625*sigma1xsigma1x1x1x1x1 + 0.0625*sigma1xsigma1x1x1xsigma3xsigma3 + 0.0625*sigma1xsigma1x1xsigma3x1xsigma3 + 0.0625*sigma1xsigma1x1xsigma3xsigma3x1 + 0.0625*sigma1xsigma1xsigma3x1x1xsigma3 + 0.0625*sigma1xsigma1xsigma3x1xsigma3x1 + 0.0625*sigma1xsigma1xsigma3xsigma3x1x1 + 0.0625*sigma1xsigma1xsigma3xsigma3xsigma3xsigma3 + 0.0625*sigma2xsigma2x1x1x1x1 + 0.0625*sigma2xsigma2x1x1xsigma3xsigma3 + 0.0625*sigma2xsigma2x1xsigma3x1xsigma3 + 0.0625*sigma2xsigma2x1xsigma3xsigma3x1 + 0.0625*sigma2xsigma2xsigma3x1x1xsigma3 + 0.0625*sigma2xsigma2xsigma3x1xsigma3x1 + 0.0625*sigma2xsigma2xsigma3xsigma3x1x1 + 0.0625*sigma2xsigma2xsigma3xsigma3xsigma3xsigma3 + 0.0625*sigma3x1x1xsigma1xsigma1xsigma3 + 0.0625*sigma3x1x1xsigma2xsigma2xsigma3 + 0.0625*sigma3x1x1xsigma3xsigma1xsigma1 + 0.0625*sigma3x1x1xsigma3xsigma2xsigma2 + 0.0625*sigma3x1xsigma1xsigma1x1xsigma3 + 0.0625*sigma3x1xsigma1xsigma1xsigma3x1 + 0.0625*sigma3x1xsigma2xsigma2x1xsigma3 + 0.0625*sigma3x1xsigma2xsigma2xsigma3x1 + 0.0625*sigma3x1xsigma3x1xsigma1xsigma1 + 0.0625*sigma3x1xsigma3x1xsigma2xsigma2 + 0.0625*sigma3x1xsigma3xsigma1xsigma1x1 + 0.0625*sigma3x1xsigma3xsigma2xsigma2x1 + 0.0625*sigma3xsigma1xsigma1x1x1xsigma3 + 0.0625*sigma3xsigma1xsigma1x1xsigma3x1 + 0.0625*sigma3xsigma1xsigma1xsigma3x1x1 + 0.0625*sigma3xsigma1xsigma1xsigma3xsigma3xsigma3 + 0.0625*sigma3xsigma2xsigma2x1x1xsigma3 + 0.0625*sigma3xsigma2xsigma2x1xsigma3x1 + 0.0625*sigma3xsigma2xsigma2xsigma3x1x1 + 0.0625*sigma3xsigma2xsigma2xsigma3xsigma3xsigma3 + 0.0625*sigma3xsigma3x1x1xsigma1xsigma1 + 0.0625*sigma3xsigma3x1x1xsigma2xsigma2 + 0.0625*sigma3xsigma3x1xsigma1xsigma1x1 + 0.0625*sigma3xsigma3x1xsigma2xsigma2x1 + 0.0625*sigma3xsigma3xsigma1xsigma1x1x1 + 0.0625*sigma3xsigma3xsigma1xsigma1xsigma3xsigma3 + 0.0625*sigma3xsigma3xsigma2xsigma2x1x1 + 0.0625*sigma3xsigma3xsigma2xsigma2xsigma3xsigma3 + 0.0625*sigma3xsigma3xsigma3xsigma1xsigma1xsigma3 + 0.0625*sigma3xsigma3xsigma3xsigma2xsigma2xsigma3 + 0.0625*sigma3xsigma3xsigma3xsigma3xsigma1xsigma1 + 0.0625*sigma3xsigma3xsigma3xsigma3xsigma2xsigma2" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 480)\n" - ] - } - ], - "source": [ - "for n in [2,3,4,5,6]:\n", - " print(\"----------------------\")\n", - " print(\"\")\n", - " T=np.zeros((n,n))\n", - " str_lst=[]\n", - "# T[0,1]=1\n", - "# T[1,0]=1\n", - " for i in range(n-1):\n", - " T[i,i+1]=1\n", - " T[i+1,i]=1\n", - " for i in range(n):\n", - " str_tmp=''\n", - " for j in range(n):\n", - " if i==j:\n", - " str_tmp+=\"1\"\n", - " else:\n", - " str_tmp+=\"0\"\n", - " str_lst.append(str_tmp)\n", - " display(T,str_lst)\n", - "\n", - " print_info2(str_lst,T)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f6a84111", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "af0b9211", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "09cd2177", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 33, - "id": "1af0d20b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hamming distance= (2, 0.2)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}}$" - ], - "text/plain": [ - "0.25*sigma1xsigma1x1 + 0.25*sigma1xsigma1xsigma3 + 0.25*sigma2xsigma2x1 + 0.25*sigma2xsigma2xsigma3" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 12)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H+H_neg='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.5 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1}$" - ], - "text/plain": [ - "0.5*sigma1xsigma1x1 + 0.5*sigma2xsigma2x1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 4)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H+H_minus='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.5 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1}$" - ], - "text/plain": [ - "0.5*sigma1xsigma1x1 + 0.5*sigma2xsigma2x1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 4)\n", - "g(x)= 2*x0*x1 - x0 - x1 + 3*x2 + 1\n", - "is zero for the following bitstrings:\n", - "0 1 0\n", - "1 0 0\n" - ] - } - ], - "source": [ - "T=np.ones((2,2))-np.identity(2)\n", - "# T[2,0]=0\n", - "# T[0,2]=0\n", - "display(T)\n", - "\n", - "print_info(['100','010'],T)" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "id": "fb2e2286", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hamming distance= (2, 0.2)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "0.25*sigma1xsigma1xsigma1 + 0.25*sigma1xsigma2xsigma2 + 0.25*sigma2xsigma1xsigma2 - 0.25*sigma2xsigma2xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 16)\n", - "overlap with bitwise negated stringlist = ['001', '110']\n", - "minus = []\n", - "g(x)= -2*x0*x1 + 2*x0*x2 + 2*x1*x2 - 2*x2 + 2\n", - "is zero for the following bitstrings:\n", - "0 0 1\n", - "1 1 0\n" - ] - } - ], - "source": [ - "T=np.ones((2,2))-np.identity(2)\n", - "display(T)\n", - "print_info(['001','110'],T)" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "id": "8e374302", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0., 1., 0.],\n", - " [1., 0., 1.],\n", - " [0., 1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hamming distance= (6, 4.2)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.25 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.25 \\cdot {{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.25 {{\\sigma_{1}}\\otimes {1}}\\otimes {1} - 0.25 {{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{3}}}\\otimes {1} - 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} - 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}$" - ], - "text/plain": [ - "0.25*1xsigma1xsigma1 + 0.25*1xsigma2xsigma2 + 0.25*sigma1x1x1 - 0.25*sigma1x1xsigma3 + 0.25*sigma1xsigma3x1 - 0.25*sigma1xsigma3xsigma3 - 0.25*sigma3xsigma1xsigma1 - 0.25*sigma3xsigma2xsigma2" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (1, 20)\n", - "overlap with bitwise negated stringlist = ['001', '110']\n", - "minus = ['010']\n", - "g(x)= 2*x0*x1*x2 - 4*x0*x1 + 2*x0*x2 - 2*x0 + 2*x1*x2 + 2*x1 - 4*x2 + 4\n", - "is zero for the following bitstrings:\n", - "0 0 1\n", - "1 0 1\n", - "1 1 0\n" - ] - } - ], - "source": [ - "T=np.ones((3,3))-np.identity(3)\n", - "T[2,0]=0\n", - "T[0,2]=0\n", - "display(T)\n", - "\n", - "print_info(['001','101','110'],T)" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "id": "85eb5d26", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0., 1., 0.],\n", - " [1., 0., 1.],\n", - " [0., 1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hamming distance= (6, 4.2)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.25 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {1} - 0.25 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} - 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} - 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}} - 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}$" - ], - "text/plain": [ - "0.25*1xsigma1x1 - 0.25*1xsigma1xsigma3 + 0.25*sigma1xsigma1x1 - 0.25*sigma1xsigma1xsigma3 - 0.25*sigma2xsigma2x1 + 0.25*sigma2xsigma2xsigma3 - 0.25*sigma3xsigma1x1 + 0.25*sigma3xsigma1xsigma3" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (1, 20)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H+H_neg='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.5 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} - 0.5 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.5 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}$" - ], - "text/plain": [ - "0.5*1xsigma1x1 + 0.5*sigma1xsigma1x1 - 0.5*sigma2xsigma2x1 + 0.5*sigma3xsigma1xsigma3" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (1, 8)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H+H_minus='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.5 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} - 0.5 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.5 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}$" - ], - "text/plain": [ - "0.5*1xsigma1x1 + 0.5*sigma1xsigma1x1 - 0.5*sigma2xsigma2x1 + 0.5*sigma3xsigma1xsigma3" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (1, 8)\n", - "g(x)= 2*x0*x1*x2 - 4*x0*x1 + 2*x0*x2 - 2*x0 - 4*x1*x2 + 6*x1 - 6*x2 + 6\n", - "is zero for the following bitstrings:\n", - "0 0 1\n", - "1 0 1\n", - "1 1 1\n" - ] - } - ], - "source": [ - "T=np.ones((3,3))-np.identity(3)\n", - "T[2,0]=0\n", - "T[0,2]=0\n", - "display(T)\n", - "\n", - "print_info(['001','111','101'],T)" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "id": "41b21ee2", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hamming distance= (2, 0.2)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "0.25*sigma1xsigma1xsigma1 - 0.25*sigma1xsigma2xsigma2 - 0.25*sigma2xsigma1xsigma2 - 0.25*sigma2xsigma2xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 16)\n", - "overlap with bitwise negated stringlist = ['000', '111']\n", - "minus = []\n", - "g(x)= -2*x0*x1 - 2*x0*x2 + 2*x0 - 2*x1*x2 + 2*x1 + 2*x2\n", - "is zero for the following bitstrings:\n", - "0 0 0\n", - "1 1 1\n" - ] - } - ], - "source": [ - "T=np.ones((2,2))-np.identity(2)\n", - "display(T)\n", - "\n", - "print_info(['000','111'],T)" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "id": "b23bb046", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0., 1., 0., 0.],\n", - " [1., 0., 1., 0.],\n", - " [0., 1., 0., 1.],\n", - " [0., 0., 1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hamming distance= (8, 4.3999999999999995)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.25 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.25 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.25 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.25 \\cdot {{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}}$" - ], - "text/plain": [ - "0.25*1xsigma1x1 + 0.25*1xsigma1xsigma1 - 0.25*1xsigma1xsigma3 + 0.25*1xsigma2xsigma2 + 0.25*sigma1xsigma1x1 + 0.25*sigma1xsigma1xsigma3 + 0.25*sigma2xsigma2x1 + 0.25*sigma2xsigma2xsigma3 + 0.25*sigma3xsigma1x1 + 0.25*sigma3xsigma1xsigma1 - 0.25*sigma3xsigma1xsigma3 + 0.25*sigma3xsigma2xsigma2" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (1, 32)\n", - "overlap with bitwise negated stringlist = ['100', '011']\n" - ] - }, - { - "data": { - "text/plain": [ - "'H+H_minus='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.25 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.5 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.25 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.5 \\cdot {{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {1} - 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}}$" - ], - "text/plain": [ - "0.25*1xsigma1x1 + 0.5*1xsigma1xsigma1 - 0.25*1xsigma1xsigma3 + 0.5*1xsigma2xsigma2 + 0.25*sigma1xsigma1x1 + 0.25*sigma1xsigma1xsigma3 + 0.25*sigma2xsigma2x1 + 0.25*sigma2xsigma2xsigma3 + 0.25*sigma3xsigma1x1 - 0.25*sigma3xsigma1xsigma3" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (1, 24)\n", - "g(x)= -6*x0*x1*x2 + 8*x0*x1 + 8*x0*x2 - 2*x0 + 2*x1*x2 - 2*x1 - 2*x2 + 2\n", - "is zero for the following bitstrings:\n", - "0 0 1\n", - "0 1 0\n", - "0 1 1\n", - "1 0 0\n" - ] - } - ], - "source": [ - "n=2\n", - "T=np.zeros((2**n,2**n))\n", - "for i in range(2**n-1):\n", - " T[i,i+1]=1\n", - " T[i+1,i]=1\n", - "display(T)\n", - "\n", - "print_info(['100','010','001','011'],T)" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "id": "a9f121e3", - "metadata": {}, - "outputs": [], - "source": [ - "import networkx as nx" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4725cbf8", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 40, - "id": "8fd3e9c8", - "metadata": {}, - "outputs": [], - "source": [ - "def addNode(G,s1,s2,s3=None,i=None):\n", - " found=False\n", - " if s3 is None:\n", - " for u,d in G.nodes(data=True):\n", - " tmp1=(d['list'][0]==s1 and d['list'][1]==s2)\n", - " tmp2=(d['list'][0]==s2 and d['list'][1]==s1)\n", - " if tmp1 or tmp2:\n", - " found=True\n", - " break\n", - " if not found:\n", - " if i is None:\n", - " key=s1+','+s2\n", - " G.add_node(key)\n", - " G.nodes[key]['list']=[s1,s2]\n", - " else:\n", - " G.add_node(i)\n", - " G.nodes[i]['list']=[s1,s2]\n", - " else:\n", - " for u,d in G.nodes(data=True):\n", - " tmp1=(d['list'][0]==s1 and d['list'][1]==s2)\n", - " tmp2=(s2 in d['list'])\n", - " tmp3=(s3 in d['list'])\n", - " if tmp1 or tmp2 or tmp3:\n", - " found=True\n", - " break\n", - " if not found:\n", - " if i is None:\n", - " key=s1+','+s2+','+s3\n", - " G.add_node(key)\n", - " G.nodes[key]['list']=[s1,s2,s3]\n", - " else:\n", - " G.add_node(i)\n", - " G.nodes[i]['list']=[s1,s2,s3]\n", - " return G\n", - "\n", - "def addEdges(G):\n", - " for u1,d1 in G.nodes(data=True):\n", - " for u2,d2 in G.nodes(data=True):\n", - " if not u1==u2:\n", - " if len(get_overlap(d1['list'],d2['list']))>0:\n", - " G.add_edge(u1,u2)\n", - " return G\n", - "\n", - "def remove(G,keys):\n", - " Gnew = nx.Graph()\n", - " for u,d in G.nodes(data=True):\n", - " found=False\n", - " for key in keys:\n", - " if key in d['list']:\n", - " found=True\n", - " break\n", - " if not found:\n", - " Gnew.add_node(u)\n", - " Gnew.nodes[u]['list']=d['list']\n", - " return Gnew" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "04be85b9", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1ed9704a", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "838077f4", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2344c97f", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "23782e2e", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3c11699f", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c00a4e33", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7eb4540f", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "82a0ae45", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 41, - "id": "324c4bd6", - "metadata": {}, - "outputs": [], - "source": [ - "# nodes = ['a','b','c','d']\n", - "# edges = [('a','b'), ('a','c'), ('c','d'),('d','b')]\n", - "# gender = ['f', 'm', 'f', 'm']\n", - "# colors = {'m': 'blue', 'f': 'red'}\n", - "\n", - "# style = {}\n", - "# style['node_label'] = ['Alice', 'Bob', 'Claire', 'Dennis']\n", - "# style['node_color'] = [colors[g] for g in gender]\n", - "# style['node_opacity'] = .5\n", - "# style['edge_curved'] = .1\n", - "\n", - "# from network2tikz import plot\n", - "# plot((nodes,edges),'network.tex',**style)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "234249b4", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 42, - "id": "863335a6", - "metadata": {}, - "outputs": [], - "source": [ - "# B=['100','010','011']\n", - "\n", - "# G = nx.Graph()\n", - "# for s1 in all_states(3):\n", - "# for s2 in all_states(3):\n", - "# for s3 in all_states(3):\n", - "# ol=get_overlap([s1,s2,s3],B)\n", - "# if len(ol)==0:\n", - "# if not s1==s2:\n", - "# G = addNode(G,s1,s2,s3)\n", - "# GE = addEdges(G)\n", - "\n", - "# pos = nx.circular_layout(GE)\n", - "# # pos = nx.spring_layout(G)\n", - "# pl.figure(figsize=(10,10))\n", - "# nx.draw_networkx(GE,pos=pos,with_labels=true,node_size=2500)#, node_color=color_map)\n", - "# # print(GE)\n", - "\n", - "# for u,d in GE.nodes(data=True):\n", - "# display(d)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "25d07183", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 43, - "id": "f13b2868", - "metadata": {}, - "outputs": [], - "source": [ - "def addallNodes(G,n,usei=False):\n", - " if usei:\n", - " for lst in all_states(n):\n", - " key=st\n", - " G.add_node(key)\n", - " G.nodes[key]['list']=[st]\n", - " else:\n", - " i=0\n", - " for lst in all_states(n):\n", - " i+=1\n", - " G.add_node(i)\n", - " G.nodes[i]['list']=[st]\n", - " return G\n", - "\n", - "def addEdgesFor(G,s1,s2):\n", - " for u1,d1 in G.nodes(data=True):\n", - " for u2,d2 in G.nodes(data=True):\n", - " if not u1==u2:\n", - " if len(get_overlap(d1['list'],d2['list']))>0:\n", - " G.add_edge(u1,u2)\n", - " return G\n", - "\n", - "def remove(G,keys):\n", - " Gnew = nx.Graph()\n", - " for u,d in G.nodes(data=True):\n", - " found=False\n", - " for key in keys:\n", - " if key in d['list']:\n", - " found=True\n", - " break\n", - " if not found:\n", - " Gnew.add_node(u)\n", - " Gnew.nodes[u]['list']=d['list']\n", - " return Gnew" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1dfacd6b", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 44, - "id": "824fbb97", - "metadata": {}, - "outputs": [], - "source": [ - "# B=['100','010','011']\n", - "\n", - "# G= nx.Graph()\n", - "# for s1 in all_states(3):\n", - "# for s2 in all_states(3):\n", - "# ol=get_overlap([s1,s2],B)\n", - "# if len(ol)==0:\n", - "# if not s1==s2:\n", - "# G = addNode(G,s1,s2)\n", - "# # G = addNode(G,'000','001')\n", - "# # G = addNode(G,'001','101')\n", - "# G1 = addEdges(G,key='000')\n", - "# pos = nx.circular_layout(G1)\n", - "# # pos = nx.spring_layout(G)\n", - "# pl.figure(figsize=(10,10))\n", - "# nx.draw_networkx(G1,pos=pos,with_labels=true,node_size=2500,node_color=\"tab:blue\")" - ] - }, - { - "cell_type": "code", - "execution_count": 45, - "id": "33ec1d15", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0., 1., 0.],\n", - " [1., 0., 1.],\n", - " [0., 1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "[]" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['011']" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.25 \\cdot {{1}\\otimes {1}}\\otimes {\\sigma_{1}} - 0.25 \\cdot {{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{1}} - 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "0.25*1x1xsigma1 - 0.25*1xsigma3xsigma1 + 0.25*sigma1xsigma1x1 + 0.25*sigma1xsigma1xsigma3 + 0.25*sigma2xsigma2x1 + 0.25*sigma2xsigma2xsigma3 + 0.25*sigma3x1xsigma1 - 0.25*sigma3xsigma3xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(1, 20)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "+C1\n" - ] - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.25 \\cdot {{1}\\otimes {1}}\\otimes {\\sigma_{1}} - 0.25 \\cdot {{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}} + 0.5 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.5 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{1}} - 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "0.25*1x1xsigma1 - 0.25*1xsigma3xsigma1 + 0.5*sigma1xsigma1x1 + 0.5*sigma1xsigma1xsigma3 + 0.25*sigma3x1xsigma1 - 0.25*sigma3xsigma3xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(1, 14)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "+C2\n" - ] - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.25 \\cdot {{1}\\otimes {1}}\\otimes {\\sigma_{1}} - 0.25 \\cdot {{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}} + 0.5 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.5 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1} + 0.25 {{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{1}} - 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "0.25*1x1xsigma1 - 0.25*1xsigma3xsigma1 + 0.5*sigma1xsigma1x1 + 0.5*sigma2xsigma2x1 + 0.25*sigma3x1xsigma1 - 0.25*sigma3xsigma3xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(1, 12)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n" - ] - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.25 \\cdot {{1}\\otimes {1}}\\otimes {\\sigma_{1}} - 0.25 \\cdot {{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}} + 0.75 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1} - 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{1}} - 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "0.25*1x1xsigma1 - 0.25*1xsigma3xsigma1 + 0.75*sigma1xsigma1x1 + 0.25*sigma1xsigma1xsigma3 + 0.25*sigma2xsigma2x1 - 0.25*sigma2xsigma2xsigma3 + 0.25*sigma3x1xsigma1 - 0.25*sigma3xsigma3xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(1, 20)" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "T=get_T(3,mode=\"nearest_int\")\n", - "display(T)\n", - "\n", - "B=['100','010','011']\n", - "C1=['110','000']\n", - "C2=['101','011']\n", - "\n", - "# G = nx.Graph()\n", - "# uniquepairs={}\n", - "# for s1 in all_states(3):\n", - "# for s2 in all_states(3):\n", - "# if not s1==s2:\n", - "# ol=get_overlap([s1,s2],B)\n", - "# if len(ol)==0:\n", - "# if not bool(uniquepairs):\n", - "# uniquepairs\n", - "# # display(\"no=\",[s1,s2])\n", - "\n", - "display(get_overlap(B,C1))\n", - "display(get_overlap(B,C2)) \n", - "HB=get_H(B,T)\n", - "HC1=get_H(C1,T)\n", - "HC2=get_H(C2,T)\n", - "HBC1=simplifyH(HB+HC1)\n", - "HBC2=simplifyH(HB+HC2)\n", - "HBC12=simplifyH(HB+HC1+HC2)\n", - "\n", - "display(HB)\n", - "display(num_Cnot(HB))\n", - "# print()\n", - "# display(HC1)\n", - "# display(num_Cnot(HC1))\n", - "print(\"+C1\")\n", - "display(HBC1)\n", - "display(num_Cnot(HBC1))\n", - "\n", - "print(\"+C2\")\n", - "display(HBC2)\n", - "display(num_Cnot(HBC2))\n", - "\n", - "print()\n", - "display(HBC12)\n", - "display(num_Cnot(HBC12))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "43a0c8d2", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "63f39323", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "83b646ff", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 46, - "id": "c7fc659e", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0., 1., 0.],\n", - " [1., 0., 1.],\n", - " [0., 1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "'+0.25 IIX +0.25 XXI +0.25 XXZ +0.25 YYI +0.25 YYZ +0.25 ZIX -0.25 IZX -0.25 ZZX '" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(1, 20)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "['000', '001']\n" - ] - }, - { - "data": { - "text/plain": [ - "'+0.25 XXI +0.25 XXZ +0.25 YYI +0.25 YYZ +0.50 IIX +0.50 ZIX '" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(1, 14)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "['000', '101']\n" - ] - }, - { - "data": { - "text/plain": [ - "'+0.25 IIX +0.25 XIX +0.25 XXI +0.25 XXZ +0.25 XZX +0.25 YYI +0.25 YYZ +0.25 ZIX -0.25 IZX -0.25 YIY -0.25 YZY -0.25 ZZX '" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(1, 32)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "['000', '110']\n" - ] - }, - { - "data": { - "text/plain": [ - "'+0.25 IIX +0.25 ZIX +0.50 XXI +0.50 XXZ -0.25 IZX -0.25 ZZX '" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(1, 14)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "['000', '111']\n" - ] - }, - { - "data": { - "text/plain": [ - "'+0.25 IIX +0.25 XXI +0.25 XXX +0.25 XXZ +0.25 YYI +0.25 YYZ +0.25 ZIX -0.25 IZX -0.25 XYY -0.25 YXY -0.25 YYX -0.25 ZZX '" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(1, 36)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "['001', '101']\n" - ] - }, - { - "data": { - "text/plain": [ - "'+0.25 IIX +0.25 XII +0.25 XXI +0.25 XXZ +0.25 XZI +0.25 YYI +0.25 YYZ +0.25 ZIX -0.25 IZX -0.25 XIZ -0.25 XZZ -0.25 ZZX '" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(2, 28)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "['001', '110']\n" - ] - }, - { - "data": { - "text/plain": [ - "'+0.25 IIX +0.25 XXI +0.25 XXX +0.25 XXZ +0.25 XYY +0.25 YXY +0.25 YYI +0.25 YYZ +0.25 ZIX -0.25 IZX -0.25 YYX -0.25 ZZX '" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(1, 36)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "['001', '111']\n" - ] - }, - { - "data": { - "text/plain": [ - "'+0.25 IIX +0.25 ZIX +0.50 XXI +0.50 YYZ -0.25 IZX -0.25 ZZX '" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(1, 14)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "['101', '110']\n" - ] - }, - { - "data": { - "text/plain": [ - "'+0.25 IIX +0.25 IXX +0.25 IYY +0.25 XXI +0.25 XXZ +0.25 YYI +0.25 YYZ +0.25 ZIX -0.25 IZX -0.25 ZXX -0.25 ZYY -0.25 ZZX '" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(1, 32)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "['101', '111']\n" - ] - }, - { - "data": { - "text/plain": [ - "'+0.25 IIX +0.25 IXI +0.25 XXI +0.25 XXZ +0.25 YYI +0.25 YYZ +0.25 ZIX +0.25 ZXZ -0.25 IXZ -0.25 IZX -0.25 ZXI -0.25 ZZX '" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(2, 28)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "['110', '111']\n" - ] - }, - { - "data": { - "text/plain": [ - "'+0.25 XXI +0.25 XXZ +0.25 YYI +0.25 YYZ +0.50 IIX -0.50 IZX '" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(1, 14)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.75 \\cdot {{1}\\otimes {1}}\\otimes {\\sigma_{1}} + 0.25 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.25 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.25 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.25 \\cdot {{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.25 \\cdot {{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{1}}\\otimes {1}}\\otimes {1} + 0.25 {{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{1}} - 0.25 {{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.75 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.5 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}} - 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} - 0.25 {{\\sigma_{2}}\\otimes {1}}\\otimes {\\sigma_{2}} - 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1} - 0.5 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}} - 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}} + 0.25 {{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{1}} - 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {1} - 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} - 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "0.75*1x1xsigma1 + 0.25*1xsigma1x1 + 0.25*1xsigma1xsigma1 - 0.25*1xsigma1xsigma3 + 0.25*1xsigma2xsigma2 - 0.25*1xsigma3xsigma1 + 0.25*sigma1x1x1 + 0.25*sigma1x1xsigma1 - 0.25*sigma1x1xsigma3 + 0.75*sigma1xsigma1x1 + 0.5*sigma1xsigma1xsigma1 + 0.25*sigma1xsigma1xsigma3 + 0.25*sigma1xsigma3x1 + 0.25*sigma1xsigma3xsigma1 - 0.25*sigma1xsigma3xsigma3 - 0.25*sigma2x1xsigma2 - 0.25*sigma2xsigma2x1 - 0.5*sigma2xsigma2xsigma1 + 0.25*sigma2xsigma2xsigma3 - 0.25*sigma2xsigma3xsigma2 + 0.25*sigma3x1xsigma1 - 0.25*sigma3xsigma1x1 - 0.25*sigma3xsigma1xsigma1 + 0.25*sigma3xsigma1xsigma3 - 0.25*sigma3xsigma2xsigma2 + 0.25*sigma3xsigma3xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(3, 68)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - " nearest_int dict_keys(['000,001', '000,101', '000,110', '000,111', '001,101', '001,110', '001,111', '101,110', '101,111', '110,111']) dict_values([14, 32, 14, 36, 28, 36, 14, 32, 28, 14])\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1., 1.],\n", - " [1., 0., 1.],\n", - " [1., 1., 0.]])" - ] 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"output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "['001', '111']\n" - ] - }, - { - "data": { - "text/plain": [ - "'+0.25 IIX +0.25 XXX +0.25 YXY +0.25 YYX +0.25 ZIX +0.50 XXI +0.50 YYZ -0.25 IZX -0.25 XYY -0.25 ZZX '" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(1, 30)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "['101', '110']\n" - ] - }, - { - "data": { - "text/plain": [ - "'+0.25 IIX +0.25 IXX +0.25 IYY +0.25 XXI +0.25 XXX +0.25 XXZ +0.25 YXY +0.25 YYI +0.25 YYX +0.25 YYZ +0.25 ZIX -0.25 IZX -0.25 XYY -0.25 ZXX -0.25 ZYY -0.25 ZZX '" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(1, 48)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "['101', '111']\n" - ] - }, - { - "data": { - "text/plain": [ - "'+0.25 IIX +0.25 IXI +0.25 XXI +0.25 XXX +0.25 XXZ +0.25 YXY +0.25 YYI +0.25 YYX +0.25 YYZ +0.25 ZIX +0.25 ZXZ -0.25 IXZ -0.25 IZX -0.25 XYY -0.25 ZXI -0.25 ZZX '" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(2, 44)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "['110', '111']\n" - ] - }, - { - "data": { - "text/plain": [ - "'+0.25 XXI +0.25 XXX +0.25 XXZ +0.25 YXY +0.25 YYI +0.25 YYX +0.25 YYZ +0.50 IIX -0.25 XYY -0.50 IZX '" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(1, 30)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.75 \\cdot {{1}\\otimes {1}}\\otimes {\\sigma_{1}} + 0.25 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.25 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} - 0.25 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} + 0.25 \\cdot {{1}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} - 0.25 \\cdot {{1}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{1}}\\otimes {1}}\\otimes {1} + 0.25 {{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{1}} - 0.25 {{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{3}} + 0.75 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 0.75 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} - 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{3}}}\\otimes {1} + 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}} - 0.25 {{\\sigma_{1}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{3}} - 0.25 {{\\sigma_{2}}\\otimes {1}}\\otimes {\\sigma_{2}} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{2}} - 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {1} - 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{3}} - 0.25 {{\\sigma_{2}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{2}} + 0.25 {{\\sigma_{3}}\\otimes {1}}\\otimes {\\sigma_{1}} - 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {1} - 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{3}} - 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{2}}}\\otimes {\\sigma_{2}} + 0.25 {{\\sigma_{3}}\\otimes {\\sigma_{3}}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "0.75*1x1xsigma1 + 0.25*1xsigma1x1 + 0.25*1xsigma1xsigma1 - 0.25*1xsigma1xsigma3 + 0.25*1xsigma2xsigma2 - 0.25*1xsigma3xsigma1 + 0.25*sigma1x1x1 + 0.25*sigma1x1xsigma1 - 0.25*sigma1x1xsigma3 + 0.75*sigma1xsigma1x1 + 0.75*sigma1xsigma1xsigma1 + 0.25*sigma1xsigma1xsigma3 - 0.25*sigma1xsigma2xsigma2 + 0.25*sigma1xsigma3x1 + 0.25*sigma1xsigma3xsigma1 - 0.25*sigma1xsigma3xsigma3 - 0.25*sigma2x1xsigma2 + 0.25*sigma2xsigma1xsigma2 - 0.25*sigma2xsigma2x1 - 0.25*sigma2xsigma2xsigma1 + 0.25*sigma2xsigma2xsigma3 - 0.25*sigma2xsigma3xsigma2 + 0.25*sigma3x1xsigma1 - 0.25*sigma3xsigma1x1 - 0.25*sigma3xsigma1xsigma1 + 0.25*sigma3xsigma1xsigma3 - 0.25*sigma3xsigma2xsigma2 + 0.25*sigma3xsigma3xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(3, 76)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - " nearest_int_cyclic dict_keys(['000,001', '000,101', '000,110', '000,111', '001,101', '001,110', '001,111', '101,110', '101,111', '110,111']) dict_values([30, 48, 30, 28, 44, 28, 30, 48, 44, 30])\n" - ] - } - ], - "source": [ - "B=['100','010','011']\n", - "for mode in [\"nearest_int\", \"nearest_int_cyclic\"]:\n", - " T=get_T(3,mode=mode)\n", - " display(T)\n", - "\n", - " HB=get_H(B,T)\n", - " HB=simplifyH(HB)\n", - " display(HtoString(HB))\n", - " display(num_Cnot(HB))\n", - "\n", - " HS=HB\n", - " Htest=HB\n", - "\n", - " als=all_states(3)\n", - "\n", - " pair={}\n", - " for i in range(2**3):\n", - " s1=als[i]\n", - " for j in range(i+1,2**3):\n", - " s2=als[j]\n", - " C1=[s1,s2]\n", - " ol=get_overlap(C1,B)\n", - " if len(ol)==0:\n", - " print(\"\")\n", - " HC1=get_H(C1,T)\n", - " HS+=HC1\n", - " HBC1=simplifyH(HB+HC1)\n", - " print(C1)\n", - " display(HtoString(HBC1))\n", - " display(num_Cnot(HBC1))\n", - " pair[s1+\",\"+s2]=num_Cnot(HBC1)[1]\n", - " if num_Cnot(HBC1)==14:\n", - " Htest+=HC1\n", - "\n", - " HBS=simplifyH(HS)\n", - " display(HBS)\n", - " display(num_Cnot(HBS))\n", - "\n", - "# HBt=simplifyH(Htest)\n", - "# display(HBt)\n", - "# display(num_Cnot(HBt))\n", - " print(\"\\n\",mode,pair.keys(),pair.values())" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4f972655", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "eb036793", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "636d8c78", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "771c6837", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9c639f65", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "id": "5759a74e", - "metadata": {}, - "source": [ - "# Case 1" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "id": "a745a7cc", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0., 1., 0.],\n", - " [1., 0., 0.],\n", - " [0., 0., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "array([[0., 0., 0.],\n", - " [0., 0., 1.],\n", - " [0., 1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "array([[0., 0., 1.],\n", - " [0., 0., 0.],\n", - " [1., 0., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "[['000', '001'],\n", - " ['000', '101'],\n", - " ['000', '110'],\n", - " ['000', '111'],\n", - " ['001', '101'],\n", - " ['001', '110'],\n", - " ['001', '111'],\n", - " ['101', '110'],\n", - " ['101', '111'],\n", - " ['110', '111']]" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "B & 12 & 8 & 16\\\\\n", - "000,001 & 20 & 2 & 24\\\\\n", - "000,101 & 24 & 20 & 28\\\\\n", - "000,110 & 6 & 20 & 28\\\\\n", - "000,111 & 28 & 24 & 8\\\\\n", - "001,101 & 20 & 16 & 24\\\\\n", - "001,110 & 28 & 24 & 8\\\\\n", - "001,111 & 6 & 20 & 28\\\\\n", - "101,110 & 24 & 20 & 28\\\\\n", - "101,111 & 20 & 16 & 24\\\\\n", - "110,111 & 20 & 2 & 24\\\\\n" - ] - }, - { - "data": { - "text/plain": [ - "10" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "5" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "10.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "B=['100','010','011']\n", - "Cs=get_Cs(B)\n", - "Hs, HSs, Cnots=analyzeAdding(Cs,B)\n", - "display(Cs)\n", - "\n", - "n=len(B[0])\n", - "m=len(B)\n", - "for key in Hs[0]:\n", - " tmps=key\n", - " for indi in range(m):\n", - " tmps+=\" & \" + str(Cnots[indi][key][1])\n", - " tmps+=\"\\\\\\\\\"\n", - " print(tmps)\n", - "HcapB=2**n-m\n", - "display(len(Cs),HcapB,math.factorial(HcapB)/(2*math.factorial(HcapB-2)))" - ] - }, - { - "cell_type": "code", - "execution_count": 48, - "id": "62c57612", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{0: {'B': '+0.25 XXI +0.25 XXZ +0.25 YYI +0.25 YYZ ',\n", - " '000,001': '+0.25 IIX +0.25 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'11110'],\n", - " ['01111', '11111'],\n", - " ['10000', '10001'],\n", - " ['10000', '10100'],\n", - " ['10000', '10101'],\n", - " ['10000', '10110'],\n", - " ['10000', '10111'],\n", - " ['10000', '11000'],\n", - " ['10000', '11001'],\n", - " ['10000', '11010'],\n", - " ['10000', '11011'],\n", - " ['10000', '11100'],\n", - " ['10000', '11110'],\n", - " ['10000', '11111'],\n", - " ['10001', '10100'],\n", - " ['10001', '10101'],\n", - " ['10001', '10110'],\n", - " ['10001', '10111'],\n", - " ['10001', '11000'],\n", - " ['10001', '11001'],\n", - " ['10001', '11010'],\n", - " ['10001', '11011'],\n", - " ['10001', '11100'],\n", - " ['10001', '11110'],\n", - " ['10001', '11111'],\n", - " ['10100', '10101'],\n", - " ['10100', '10110'],\n", - " ['10100', '10111'],\n", - " ['10100', '11000'],\n", - " ['10100', '11001'],\n", - " ['10100', '11010'],\n", - " ['10100', '11011'],\n", - " ['10100', '11100'],\n", - " ['10100', '11110'],\n", - " ['10100', '11111'],\n", - " ['10101', '10110'],\n", - " ['10101', '10111'],\n", - " ['10101', '11000'],\n", - " ['10101', '11001'],\n", - " ['10101', '11010'],\n", - " ['10101', '11011'],\n", - " ['10101', '11100'],\n", - " ['10101', '11110'],\n", - " ['10101', '11111'],\n", - " ['10110', '10111'],\n", - " ['10110', '11000'],\n", - " ['10110', '11001'],\n", - " ['10110', '11010'],\n", - " ['10110', '11011'],\n", - " ['10110', '11100'],\n", - " ['10110', '11110'],\n", - " ['10110', '11111'],\n", - " ['10111', '11000'],\n", - " ['10111', '11001'],\n", - " ['10111', '11010'],\n", - " ['10111', '11011'],\n", - " ['10111', '11100'],\n", - " ['10111', '11110'],\n", - " ['10111', '11111'],\n", - " ['11000', '11001'],\n", - " ['11000', '11010'],\n", - " ['11000', '11011'],\n", - " ['11000', '11100'],\n", - " ['11000', '11110'],\n", - " ['11000', '11111'],\n", - " ['11001', '11010'],\n", - " ['11001', '11011'],\n", - " ['11001', '11100'],\n", - " ['11001', '11110'],\n", - " ['11001', '11111'],\n", - " ['11010', '11011'],\n", - " ['11010', 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"metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "B & 96 & 64 & 112 & 80 & 80 & 112 & 96 & 64 & 64 & 96 & 96 & 96 & 112 & 112 & 80\\\\\n", - "00010,00011 & 160 & \\cellcolor{black!25}24 & 176 & 144 & 144 & 176 & 160 & 128 & 128 & 160 & 160 & 160 & 176 & 176 & 144\\\\\n", - "00010,01101 & 208 & 176 & \\cellcolor{black!25}48 & 192 & 192 & 224 & 208 & 176 & 176 & 208 & 208 & 208 & 224 & 224 & 192\\\\\n", - "00010,10001 & 192 & 160 & 208 & 176 & 176 & 208 & \\cellcolor{black!25}48 & 160 & 160 & 192 & 192 & 192 & 208 & 208 & 176\\\\\n", - "00010,10101 & 208 & 176 & 224 & 192 & 192 & 224 & 208 & 176 & 176 & 208 & 208 & 208 & 224 & \\cellcolor{black!25}48 & 192\\\\\n", - "00010,11001 & 208 & 176 & 224 & 192 & 192 & 224 & 208 & 176 & 176 & 208 & 208 & 208 & \\cellcolor{black!25}48 & 224 & 192\\\\\n", - "00011,01101 & 192 & 160 & 208 & 176 & 176 & 208 & 192 & 160 & 160 & \\cellcolor{black!25}40 & 192 & 192 & 208 & 208 & 176\\\\\n", - "00011,10000 & 192 & 160 & 208 & 176 & 176 & 208 & \\cellcolor{black!25}48 & 160 & 160 & 192 & 192 & 192 & 208 & 208 & 176\\\\\n", - "00100,01000 & 176 & 144 & 192 & 160 & 160 & 192 & 176 & 144 & 144 & 176 & 176 & 176 & 192 & 192 & \\cellcolor{black!25}32\\\\\n", - "00100,01100 & 160 & 128 & 176 & 144 & 144 & 176 & 160 & \\cellcolor{black!25}24 & 128 & 160 & 160 & 160 & 176 & 176 & 144\\\\\n", - "00100,10000 & 176 & 144 & 192 & \\cellcolor{black!25}32 & 160 & 192 & 176 & 144 & 144 & 176 & 176 & 176 & 192 & 192 & 160\\\\\n", - "00100,10001 & 192 & 160 & 208 & 176 & 176 & 208 & 192 & 160 & 160 & 192 & \\cellcolor{black!25}40 & 192 & 208 & 208 & 176\\\\\n", - "00100,10111 & 192 & 160 & 208 & 176 & 176 & 208 & \\cellcolor{black!25}48 & 160 & 160 & 192 & 192 & 192 & 208 & 208 & 176\\\\\n", - "00101,10110 & 192 & 160 & 208 & 176 & 176 & 208 & \\cellcolor{black!25}48 & 160 & 160 & 192 & 192 & 192 & 208 & 208 & 176\\\\\n", - "00111,01011 & 176 & 144 & 192 & 160 & 160 & 192 & 176 & 144 & 144 & 176 & 176 & 176 & 192 & 192 & \\cellcolor{black!25}32\\\\\n", - "00111,01111 & 160 & 128 & 176 & 144 & 144 & 176 & 160 & \\cellcolor{black!25}24 & 128 & 160 & 160 & 160 & 176 & 176 & 144\\\\\n", - "00111,10100 & 192 & 160 & 208 & 176 & 176 & 208 & \\cellcolor{black!25}48 & 160 & 160 & 192 & 192 & 192 & 208 & 208 & 176\\\\\n", - "01000,01100 & 160 & 128 & 176 & 144 & 144 & 176 & 160 & 128 & \\cellcolor{black!25}24 & 160 & 160 & 160 & 176 & 176 & 144\\\\\n", - "01000,10000 & 176 & 144 & 192 & 160 & \\cellcolor{black!25}32 & 192 & 176 & 144 & 144 & 176 & 176 & 176 & 192 & 192 & 160\\\\\n", - "01000,10001 & 192 & 160 & 208 & 176 & 176 & 208 & 192 & 160 & 160 & 192 & 192 & \\cellcolor{black!25}40 & 208 & 208 & 176\\\\\n", - "01000,11011 & 192 & 160 & 208 & 176 & 176 & 208 & \\cellcolor{black!25}48 & 160 & 160 & 192 & 192 & 192 & 208 & 208 & 176\\\\\n", - "01001,11010 & 192 & 160 & 208 & 176 & 176 & 208 & \\cellcolor{black!25}48 & 160 & 160 & 192 & 192 & 192 & 208 & 208 & 176\\\\\n", - "01011,01111 & 160 & 128 & 176 & 144 & 144 & 176 & 160 & 128 & \\cellcolor{black!25}24 & 160 & 160 & 160 & 176 & 176 & 144\\\\\n", - "01011,11000 & 192 & 160 & 208 & 176 & 176 & 208 & \\cellcolor{black!25}48 & 160 & 160 & 192 & 192 & 192 & 208 & 208 & 176\\\\\n", - "01100,10000 & \\cellcolor{black!25}40 & 160 & 208 & 176 & 176 & 208 & 192 & 160 & 160 & 192 & 192 & 192 & 208 & 208 & 176\\\\\n", - "01100,10001 & 208 & 176 & 224 & 192 & 192 & \\cellcolor{black!25}48 & 208 & 176 & 176 & 208 & 208 & 208 & 224 & 224 & 192\\\\\n", - "01100,11111 & 192 & 160 & 208 & 176 & 176 & 208 & \\cellcolor{black!25}48 & 160 & 160 & 192 & 192 & 192 & 208 & 208 & 176\\\\\n", - "01101,11110 & 192 & 160 & 208 & 176 & 176 & 208 & \\cellcolor{black!25}48 & 160 & 160 & 192 & 192 & 192 & 208 & 208 & 176\\\\\n", - "01111,11100 & 192 & 160 & 208 & 176 & 176 & 208 & \\cellcolor{black!25}48 & 160 & 160 & 192 & 192 & 192 & 208 & 208 & 176\\\\\n", - "10000,10001 & 160 & \\cellcolor{black!25}24 & 176 & 144 & 144 & 176 & 160 & 128 & 128 & 160 & 160 & 160 & 176 & 176 & 144\\\\\n", - "10110,10111 & 160 & \\cellcolor{black!25}24 & 176 & 144 & 144 & 176 & 160 & 128 & 128 & 160 & 160 & 160 & 176 & 176 & 144\\\\\n", - "10110,11010 & 176 & 144 & 192 & 160 & 160 & 192 & 176 & 144 & 144 & 176 & 176 & 176 & 192 & 192 & \\cellcolor{black!25}32\\\\\n", - "10110,11110 & 160 & 128 & 176 & 144 & 144 & 176 & 160 & \\cellcolor{black!25}24 & 128 & 160 & 160 & 160 & 176 & 176 & 144\\\\\n", - "11010,11011 & 160 & \\cellcolor{black!25}24 & 176 & 144 & 144 & 176 & 160 & 128 & 128 & 160 & 160 & 160 & 176 & 176 & 144\\\\\n", - "11010,11110 & 160 & 128 & 176 & 144 & 144 & 176 & 160 & 128 & \\cellcolor{black!25}24 & 160 & 160 & 160 & 176 & 176 & 144\\\\\n", - "00000,11111 & 224 & 192 & 240 & 208 & 208 & 240 & 224 & 192 & 192 & 224 & 224 & 224 & 240 & 240 & 208\\\\\n", - "00001,11110 & 224 & 192 & 240 & 208 & 208 & 240 & 224 & 192 & 192 & 224 & 224 & 224 & 240 & 240 & 208\\\\\n", - "00011,11100 & 224 & 192 & 240 & 208 & 208 & 240 & 224 & 192 & 192 & 224 & 224 & 224 & 240 & 240 & 208\\\\\n", - "00100,11011 & 224 & 192 & 240 & 208 & 208 & 240 & 224 & 192 & 192 & 224 & 224 & 224 & 240 & 240 & 208\\\\\n", - "00101,11010 & 224 & 192 & 240 & 208 & 208 & 240 & 224 & 192 & 192 & 224 & 224 & 224 & 240 & 240 & 208\\\\\n", - "00111,11000 & 224 & 192 & 240 & 208 & 208 & 240 & 224 & 192 & 192 & 224 & 224 & 224 & 240 & 240 & 208\\\\\n", - "01000,10111 & 224 & 192 & 240 & 208 & 208 & 240 & 224 & 192 & 192 & 224 & 224 & 224 & 240 & 240 & 208\\\\\n", - "01001,10110 & 224 & 192 & 240 & 208 & 208 & 240 & 224 & 192 & 192 & 224 & 224 & 224 & 240 & 240 & 208\\\\\n", - "01011,10100 & 224 & 192 & 240 & 208 & 208 & 240 & 224 & 192 & 192 & 224 & 224 & 224 & 240 & 240 & 208\\\\\n", - "01111,10000 & 224 & 192 & 240 & 208 & 208 & 240 & 224 & 192 & 192 & 224 & 224 & 224 & 240 & 240 & 208\\\\\n" - ] - } - ], - "source": [ - "B=['10010','01110','10011','11101','00110','01010']\n", - "Cs=get_Cs(B)\n", - "Hs, HSs, Cnots=analyzeAdding(Cs,B,Tall=True)\n", - "display(Cs)\n", - "\n", - "n=len(B[0])\n", - "m=len(B)\n", - "mini={}\n", - "maxi={}\n", - "for keys in Cnots:\n", - " mini[keys] = Cnots[keys]['B'][1]\n", - " maxi[keys] = Cnots[keys]['B'][1]\n", - "\n", - "for key in Hs['0,1']:\n", - " for keys in Cnots:\n", - " val=Cnots[keys][key][1]\n", - " mini[keys]=min(val,mini[keys])\n", - " maxi[keys]=max(val,maxi[keys])\n", - "print(mini)\n", - "print(maxi)\n", - "HcapB=2**n-m\n", - "display(len(Cs),HcapB,math.factorial(HcapB)/(2*math.factorial(HcapB-2)))\n", - "\n", - "indch=['B']\n", - "for key in Hs['0,1']:\n", - " for keys in Cnots:\n", - " val=Cnots[keys][key][1]\n", - " if (mini[keys]==val):\n", - " indch.append(key)\n", - "for key in Hs['0,1']:\n", - " for keys in Cnots:\n", - " val=Cnots[keys][key][1]\n", - " if (maxi[keys]==val):\n", - " indch.append(key)\n", - " break\n", - " \n", - "for key in indch:\n", - " tmps=key\n", - " for keys in Cnots:\n", - " val=Cnots[keys][key][1]\n", - " if (mini[keys]==val):\n", - " tmps+=\" & \\\\cellcolor{black!25}\" + str(val)\n", - " else:\n", - " tmps+=\" & \" + str(val)\n", - " tmps+=\"\\\\\\\\\"\n", - " print(tmps)" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "id": "08f292f5", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(568, 1360)" - ] - }, - "execution_count": 50, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "Bsum=0\n", - "for keys in Cnots:\n", - " Bsum+=Cnots[keys]['B'][1]\n", - "sum(list(mini.values())), Bsum" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "75f79d4f", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "895f2af2", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8620dbd4", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "362cdca1", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "e2cf253a", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "be1319f3", - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 51, - "id": "ba96f73f", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "text/plain": [ - "'+0.25 IIX +0.25 XXI +0.25 XXZ +0.25 YYI +0.25 YYZ +0.25 ZIX -0.25 IZX -0.25 ZZX '" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(1, 20)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "['000', '001', '101']\n" - ] - }, - { - "data": { - "text/plain": [ - "'+0.25 XII +0.25 XXI +0.25 XXZ +0.25 XZI +0.25 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"data": { - "text/plain": [ - "'+0.25 IXI +0.25 IXX +0.25 IYY +0.25 XXI +0.25 XXX +0.25 XXZ +0.25 YXY +0.25 YYI +0.25 YYX +0.25 YYZ +0.25 ZXZ +0.50 IIX -0.25 IXZ -0.25 XYY -0.25 ZXI -0.25 ZXX -0.25 ZYY -0.50 IZX '" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(2, 50)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - " nearest_int_cyclic dict_keys(['000,001,101', '000,001,110', '000,001,111', '000,101,110', '000,101,111', '000,110,111', '001,101,110', '001,101,111', '001,110,111', '101,110,111']) dict_values([50, 16, 16, 54, 48, 16, 48, 46, 16, 50])\n" - ] - } - ], - "source": [ - "B=['100','010','011']\n", - "for mode in [\"nearest_int\", \"nearest_int_cyclic\"]:\n", - " T=get_T(3,mode=mode)\n", - " \n", - " HB=get_H(B,T)\n", - " HB=simplifyH(HB)\n", - " display(HtoString(HB))\n", - " display(num_Cnot(HB))\n", - "\n", - "\n", - " als=all_states(3)\n", - "\n", - " pair={}\n", - " for i in range(2**3):\n", - " s1=als[i]\n", - " for j in range(i+1,2**3):\n", - " s2=als[j]\n", - " for k in range(j+1,2**3):\n", - " s3=als[k]\n", - " C1=[s1,s2,s3]\n", - " ol=get_overlap(C1,B)\n", - " if len(ol)==0:\n", - " print(\"\")\n", - " HC1=get_H(C1,T)\n", - " HBC1=simplifyH(HB+HC1)\n", - " print(C1)\n", - " display(HtoString(HBC1))\n", - " display(num_Cnot(HBC1))\n", - " pair[s1+\",\"+s2+\",\"+s3]=num_Cnot(HBC1)[1]\n", - " print(\"\\n\",mode,pair.keys(),pair.values())" - ] - }, - { - "cell_type": "code", - "execution_count": 52, - "id": "e7f667b9", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'+0.25 IIX +0.25 XXI +0.25 XXZ +0.25 YYI +0.25 YYZ +0.25 ZIX -0.25 IZX -0.25 ZZX '" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(1, 20)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - 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"metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(2, 28)" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - " nearest_int_cyclic dict_keys(['000,001,101,110', '000,001,101,111', '000,001,110,111', '000,101,110,111', '001,101,110,111']) dict_values([28, 46, 28, 54, 28])\n" - ] - } - ], - "source": [ - "B=['100','010','011']\n", - "for mode in [\"nearest_int\", \"nearest_int_cyclic\"]:\n", - " T=get_T(4,mode=mode)\n", - " \n", - " HB=get_H(B,T)\n", - " HB=simplifyH(HB)\n", - " display(HtoString(HB))\n", - " display(num_Cnot(HB))\n", - "\n", - "\n", - " als=all_states(3)\n", - "\n", - " pair={}\n", - " for i in range(2**3):\n", - " s1=als[i]\n", - " for j in range(i+1,2**3):\n", - " s2=als[j]\n", - " for k in range(j+1,2**3):\n", - " s3=als[k]\n", - " for l in range(k+1,2**3):\n", - " s4=als[l]\n", - " C1=[s1,s2,s3,s4]\n", - " ol=get_overlap(C1,B)\n", - " if len(ol)==0:\n", - " print(\"\")\n", - " HC1=get_H(C1,T)\n", - " HBC1=simplifyH(HB+HC1)\n", - " print(C1)\n", - " display(HtoString(HBC1))\n", - " display(num_Cnot(HBC1))\n", - " pair[s1+\",\"+s2+\",\"+s3+\",\"+s4]=num_Cnot(HBC1)[1]\n", - " print(\"\\n\",mode,pair.keys(),pair.values())" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1d8d0378", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 53, - "id": "ca80e38b", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "cost( 2 )= 4\n", - "cost( 3 )= 12\n", - "cost( 4 )= 32\n", - "cost( 5 )= 80\n", - "cost( 6 )= 192\n", - "cost( 7 )= 448\n", - "cost( 8 )= 1024\n", - "cost( 9 )= 2304\n", - "cost( 10 )= 5120\n", - "cost( 11 )= 11264\n", - "cost( 12 )= 24576\n", - "cost( 13 )= 53248\n", - "cost( 14 )= 114688\n", - "cost( 15 )= 245760\n", - "& 4& 12& 32& 80& 192& 448& 1024& 2304& 5120& 11264& 24576& 53248& 114688& 245760\n" - ] - } - ], - "source": [ - "def scost(l,n):\n", - " if n<2 or l>n:\n", - " return 0\n", - " if n==2:\n", - " if l==2:\n", - " return l\n", - " else:\n", - " return 0\n", - " else:\n", - " return scost(l,n-1)+scost(l-1,n-1)\n", - "ls=''\n", - "for n in range(2,16):\n", - " cost=0\n", - " for l in range(2,n+1):\n", - " cost+=2*(l-1)*scost(l,n)\n", - " ls+=\"& \"+str(cost)\n", - " print(\"cost(\",n,\")=\",cost)\n", - "print(ls)\n", - "\n", - "# ls=''\n", - "# for n in range(2,16):\n", - "# cost=0\n", - "# for l in range(2,n+1):\n", - "# cost+=2*(l-1)*math.comb(l,n)\n", - "# ls+=\"& \"+str(cost)\n", - "# print(\"cost(\",n,\")=\",cost)\n", - "# print(ls)" - ] - }, - { - "cell_type": "code", - "execution_count": 54, - "id": "5b51da26", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.0" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "s=0\n", - "for n in range(1,8):\n", - " T1=get_T(2**n,mode='standard',d=1)\n", - " for k in range(1,10):\n", - " Tkm1=get_T(2**n,mode='standard',d=k-1)\n", - " Tk=get_T(2**n,mode='standard',d=k)\n", - " Tkp1=get_T(2**n,mode='standard',d=k+1)\n", - " s+=np.max(np.matmul(Tk,T1)-((n-(k-1))*Tkm1+(k+1)*Tkp1))\n", - "display(s)" - ] - }, - { - "cell_type": "code", - "execution_count": 55, - "id": "5d0508d0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "----------------------\n", - "\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['01', '10']" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "----------------------\n", - "\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['010', '100']" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "----------------------\n", - "\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['0100', '1000']" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "----------------------\n", - "\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['01000', '10000']" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "----------------------\n", - "\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['010000', '100000']" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "----------------------\n", - "\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "['0100000', '1000000']" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "for n in range(2,8):\n", - " print(\"----------------------\")\n", - " print(\"\")\n", - " T=np.zeros((2,2))\n", - " T[0,1]=1\n", - " T[1,0]=1\n", - " str_lst=[]\n", - " str_tmp='01'\n", - " for j in range(n-2):\n", - " str_tmp+=\"0\"\n", - " str_lst.append(str_tmp)\n", - " str_tmp='10'\n", - " for j in range(n-2):\n", - " str_tmp+=\"0\"\n", - " str_lst.append(str_tmp)\n", - " display(T,str_lst)\n", - "\n", - " H=get_H(str_lst,T)\n", - "# display(H)\n", - " H=simplifyH(H)\n", - " num_Cnot(H)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0c756663", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "772a3f9a", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 58, - "id": "b7aa8862", - "metadata": {}, - "outputs": [], - "source": [ - "from scipy.linalg import expm" - ] - }, - { - "cell_type": "code", - "execution_count": 59, - "id": "b219f7d4", - "metadata": {}, - "outputs": [], - "source": [ - "sI=np.array(([1,0],[0,1]))\n", - "sX=np.array(([0,1],[1,0]))\n", - "sY=np.array(([0,-1j],[1j,0]))\n", - "sZ=np.array(([1,0],[0,-1]))\n", - "\n", - "z=np.array(([1,0]))\n", - "o=np.array(([0,1]))\n", - "\n", - "v={}\n", - "v['0']=np.kron(np.kron(z,z),z)\n", - "v['1']=np.kron(np.kron(z,z),o)\n", - "v['2']=np.kron(np.kron(z,o),z)\n", - "v['3']=np.kron(np.kron(z,o),o)\n", - "v['4']=np.kron(np.kron(o,z),z)\n", - "v['5']=np.kron(np.kron(o,z),o)\n", - "v['6']=np.kron(np.kron(o,o),z)\n", - "v['7']=np.kron(np.kron(o,o),o)\n", - "\n", - "# display(v100,v010,v001)\n", - "\n", - "IXX=np.kron(np.kron(sI,sX),sX)\n", - "XIX=np.kron(np.kron(sX,sI),sX)\n", - "XXI=np.kron(np.kron(sX,sX),sI)\n", - "\n", - "IYY=np.kron(np.kron(sI,sY),sY)\n", - "YIY=np.kron(np.kron(sY,sI),sY)\n", - "YYI=np.kron(np.kron(sY,sY),sI)" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "id": "8ff5ccc2", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0\n", - "1\n", - "2\n", - "3\n", - "4\n", - "5\n", - "6\n", - "7\n" - ] - } - ], - "source": [ - "pl.rcParams.update({'font.size': 22})\n", - "\n", - "samp=200\n", - "t=np.linspace(0,4*np.pi,samp)\n", - "\n", - "T={}\n", - "T[\"X_12_23_31\"]=XXI+IXX+XIX\n", - "T[\"Y_12_23_31\"]=YYI+IYY+YIY\n", - "T[\"X_12_23\"]=XXI+IXX\n", - "T[\"Y_12_23\"]=YYI+IYY\n", - "T[\"XY_12\"]=XXI+YYI\n", - "T[\"XY_23\"]=IXX+IYY\n", - "T[\"XY_31\"]=XIX+YIY\n", - "\n", - "overlap={}\n", - "overlap[\"exact_XY_12_23_31\"]={}\n", - "overlap[\"exact_XY_12_23\"]={}\n", - "overlap[\"trott_XY_12+23+31\"]={}\n", - "overlap[\"trott_XY_12+23\"]={}\n", - "overlap[\"trott_X+Y_12_23_31\"]={}\n", - "overlap[\"trott_X+Y_12_23\"]={}\n", - "\n", - "for i in range(0,2**3):\n", - " print(i)\n", - " v1=v[str(i)]\n", - " for j in range(0,2**3):\n", - " v2=v[str(j)]\n", - " overlap[\"exact_XY_12_23_31\"][str(i)+\"<->\"+str(j)]=np.zeros_like(t)\n", - " overlap[\"exact_XY_12_23\"][str(i)+\"<->\"+str(j)]=np.zeros_like(t)\n", - " overlap[\"trott_XY_12+23+31\"][str(i)+\"<->\"+str(j)]=np.zeros_like(t)\n", - " overlap[\"trott_XY_12+23\"][str(i)+\"<->\"+str(j)]=np.zeros_like(t)\n", - " overlap[\"trott_X+Y_12_23_31\"][str(i)+\"<->\"+str(j)]=np.zeros_like(t)\n", - " overlap[\"trott_X+Y_12_23\"][str(i)+\"<->\"+str(j)]=np.zeros_like(t)\n", - " for s in range(samp):\n", - " eT=expm(-1j*t[s]*(T[\"X_12_23_31\"]+T[\"Y_12_23_31\"]))\n", - " overlap[\"exact_XY_12_23_31\"][str(i)+\"<->\"+str(j)][s]=np.abs(np.vdot(eT.dot(v1),v2))**2\n", - " eT=expm(-1j*t[s]*(T[\"X_12_23\"]+T[\"Y_12_23\"]))\n", - " overlap[\"exact_XY_12_23\"][str(i)+\"<->\"+str(j)][s]=np.abs(np.vdot(eT.dot(v1),v2))**2\n", - " \n", - " eXY12=expm(-1j*t[s]*(T[\"XY_12\"]))\n", - " eXY23=expm(-1j*t[s]*(T[\"XY_23\"]))\n", - " eXY31=expm(-1j*t[s]*(T[\"XY_31\"]))\n", - " eT=np.matmul(np.matmul(eXY12,eXY23),eXY31)\n", - " overlap[\"trott_XY_12+23+31\"][str(i)+\"<->\"+str(j)][s]=np.abs(np.vdot(eT.dot(v1),v2))**2\n", - " eT=np.matmul(eXY12,eXY23)\n", - " overlap[\"trott_XY_12+23\"][str(i)+\"<->\"+str(j)][s]=np.abs(np.vdot(eT.dot(v1),v2))**2\n", - " \n", - " eX_12_23_31=expm(-1j*t[s]*(T[\"X_12_23_31\"]))\n", - " eY_12_23_31=expm(-1j*t[s]*(T[\"Y_12_23_31\"]))\n", - " eT=np.matmul(eX_12_23_31,eY_12_23_31)\n", - " overlap[\"trott_X+Y_12_23_31\"][str(i)+\"<->\"+str(j)][s]=np.abs(np.vdot(eT.dot(v1),v2))**2\n", - " eX_12_23=expm(-1j*t[s]*(T[\"X_12_23\"]))\n", - " eY_12_23=expm(-1j*t[s]*(T[\"Y_12_23\"]))\n", - " eT=np.matmul(eX_12_23,eY_12_23)\n", - " overlap[\"trott_X+Y_12_23\"][str(i)+\"<->\"+str(j)][s]=np.abs(np.vdot(eT.dot(v1),v2))**2" - ] - }, - { - "cell_type": "code", - "execution_count": 61, - "id": "dde1aac3", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(array([0, 0, 0, 0, 0, 0, 0, 0]),\n", - " array([ 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, -1.+0.j, 0.+0.j, 0.+0.j,\n", - " 0.+0.j]),\n", - " array([0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]))" - ] - }, - "execution_count": 61, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "IXX.dot(v['4'])-v['7'], IYY.dot(v['7']), np.matmul(IYY,IXX).dot(v['4'])+v['4']" - ] - }, - { - "cell_type": "code", - "execution_count": 62, - "id": "114d8a96", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "trott_XY_12+23\n", - "\u001b[32m1<->2:0.24998442368970755\u001b[0m\n", - "\u001b[32m1<->4:0.9998753933996\u001b[0m\n", - "\u001b[32m2<->1:0.9999376947588275\u001b[0m\n", - "\u001b[32m2<->4:0.24998442368970755\u001b[0m\n", - "\u001b[31m4<->1:0.0\u001b[0m\n", - "\u001b[32m4<->2:0.9999376947588275\u001b[0m\n", - "\n", - "trott_XY_12+23+31\n", - "\u001b[32m1<->2:0.9998753972813001\u001b[0m\n", - "\u001b[32m1<->4:0.3848540703520528\u001b[0m\n", - "\u001b[32m2<->1:0.9999376947588267\u001b[0m\n", - "\u001b[32m2<->4:0.2499844236897071\u001b[0m\n", - "\u001b[32m4<->1:0.249984423689707\u001b[0m\n", - "\u001b[32m4<->2:0.3848540703520528\u001b[0m\n", - "\n", - "trott_X+Y_12_23\n", - "\u001b[32m1<->2:0.42185161187299347\u001b[0m\n", - "\u001b[32m1<->4:0.2499688483499007\u001b[0m\n", - "\u001b[31m1<->7:0.4217817372339912\u001b[0m\n", - "\u001b[32m2<->1:0.4218516118729932\u001b[0m\n", - "\u001b[32m2<->4:0.4218516118729931\u001b[0m\n", - "\u001b[31m2<->7:0.24996884834989982\u001b[0m\n", - "\u001b[32m4<->1:0.24996884834990005\u001b[0m\n", - "\u001b[32m4<->2:0.4218516118729931\u001b[0m\n", - "\u001b[31m4<->7:0.4217817372339913\u001b[0m\n", - "\u001b[31m7<->1:0.4217817372339915\u001b[0m\n", - "\u001b[31m7<->2:0.2499688483499\u001b[0m\n", - "\u001b[31m7<->4:0.42178173723399165\u001b[0m\n" - ] - } - ], - "source": [ - "for case in [\"trott_XY_12+23\", \"trott_XY_12+23+31\", \"trott_X+Y_12_23\"]:\n", - " print()\n", - " print(case)\n", - " for i in range(0,2**3):\n", - " for j in range(0,2**3):\n", - " m=np.max(overlap[case][str(i)+\"<->\"+str(j)])\n", - " st=str(i)+\"<->\"+str(j)+\":\"+str(m)\n", - " if i==j:\n", - " continue\n", - " onehoti=(i==1 or i==2 or i==4)\n", - " onehotj=(j==1 or j==2 or j==4)\n", - " if ((onehoti and onehotj) and math.isclose(m,0,abs_tol=1e-7)):\n", - " print(\"\\x1b[31m\"+st+\"\\x1b[0m\")\n", - " elif ((onehoti and onehotj) and (not math.isclose(m,0,abs_tol=1e-7))):\n", - " print(\"\\x1b[32m\"+st+\"\\x1b[0m\")\n", - " elif ((onehoti and onehotj) and (math.isclose(m,0,abs_tol=1e-7))):\n", - " print(\"\\x1b[31m\"+st+\"\\x1b[0m\")\n", - " elif ((onehoti and (not onehotj)) and (not math.isclose(m,0,abs_tol=1e-7))):\n", - " print(\"\\x1b[31m\"+st+\"\\x1b[0m\")\n", - " elif (((not onehoti) and onehotj) and (not math.isclose(m,0,abs_tol=1e-7))):\n", - " print(\"\\x1b[31m\"+st+\"\\x1b[0m\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2e5b127f", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4aa38267", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.7" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/exact cover 14.ipynb b/exact cover 14.ipynb deleted file mode 100644 index e75eae1..0000000 --- a/exact cover 14.ipynb +++ /dev/null @@ -1,1251 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "%load_ext autoreload\n", - "%autoreload 2" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "from qiskit import *\n", - "from qiskit.tools.monitor import job_monitor\n", - "\n", - "import numpy as np\n", - "import pylab as pl\n", - "\n", - "from exactcover import *\n", - "import os\n", - "from matplotlib import rc\n", - "font = {'size' : 16}\n", - "rc('font', **font);\n", - "rc('text', usetex=True)\n", - "\n", - "import sys\n", - "sys.path.append('../')\n", - "\n", - "from qiskit_utilities.utilities import *\n" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1],\n", - " [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1],\n", - " [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0],\n", - " [0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0],\n", - " [1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1],\n", - " [1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1],\n", - " [1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0],\n", - " [1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1],\n", - " [1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1]])" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "FR = np.array([\n", - "[0,0,0,0,0,0,0,1,0,1,0,0,0,1],\n", - "[0,0,0,0,0,0,0,0,1,0,0,1,0,0],\n", - "[0,0,0,0,0,0,0,1,0,0,1,0,0,0],\n", - "[0,0,0,0,0,0,0,0,1,0,0,0,1,0],\n", - "[0,0,0,0,0,0,0,1,0,1,0,0,0,1],\n", - "[0,0,0,0,0,0,0,0,1,0,0,1,0,0],\n", - "[0,0,0,0,0,0,0,1,0,0,1,0,0,0],\n", - "[0,0,0,0,0,0,0,0,1,0,0,0,1,0],\n", - "[1,1,0,0,0,1,0,0,0,0,0,0,0,0],\n", - "[1,0,1,0,0,1,0,0,0,0,0,0,0,0],\n", - "[1,0,0,1,0,0,1,0,0,0,0,0,0,1],\n", - "[1,0,0,0,1,0,1,0,0,0,0,0,0,1],\n", - "[1,1,0,0,0,1,0,0,0,0,0,0,0,0],\n", - "[1,0,1,0,0,1,0,0,0,0,0,0,0,0],\n", - "[1,0,0,1,0,0,1,0,0,0,0,0,0,1],\n", - "[1,0,0,0,1,0,1,0,0,0,0,0,0,1]\n", - "]\n", - ")\n", - "FR" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "# FR = np.zeros((2,2))\n", - "# FR[0,0]=1\n", - "# FR[1,0]=1\n", - "# FR[0,1]=1\n", - "# FR" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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-       "       ├───┤                                 ░                       ░      »\n",
-       "q0_13: ┤ H ├─────────────────────────────────░───────────────────────░──────»\n",
-       "       └───┘                                 ░                       ░      »\n",
-       "c0: 14/═════════════════════════════════════════════════════════════════════»\n",
-       "                                                                            »\n",
-       "«                        ░                       ░                       ░ »\n",
-       "« q0_0: ─────────────■───░───■───────────────■───░───■───────────────■───░─»\n",
-       "«                    │   ░   │               │   ░   │               │   ░ »\n",
-       "« q0_1: ─────────────┼───░───┼───────────────┼───░───┼───────────────┼───░─»\n",
-       "«                    │   ░   │               │   ░   │               │   ░ »\n",
-       "« q0_2: ─────────────┼───░───┼───────────────┼───░───┼───────────────┼───░─»\n",
-       "«       ┌─────────┐┌─┴─┐ ░   │               │   ░   │               │   ░ »\n",
-       "« q0_3: ┤ RZ(0.1) ├┤ X ├─░───┼───────────────┼───░───┼───────────────┼───░─»\n",
-       "«       └─────────┘└───┘ ░ ┌─┴─┐┌─────────┐┌─┴─┐ ░   │               │   ░ »\n",
-       "« q0_4: ─────────────────░─┤ X ├┤ RZ(0.1) ├┤ X ├─░───┼───────────────┼───░─»\n",
-       "«                        ░ └───┘└─────────┘└───┘ ░ ┌─┴─┐┌─────────┐┌─┴─┐ ░ »\n",
-       "« q0_5: ─────────────────░───────────────────────░─┤ X ├┤ RZ(0.2) ├┤ X ├─░─»\n",
-       "«                        ░                       ░ └───┘└─────────┘└───┘ ░ »\n",
-       "« q0_6: ─────────────────░───────────────────────░───────────────────────░─»\n",
-       "«                        ░                       ░                       ░ »\n",
-       "« q0_7: ─────────────────░───────────────────────░───────────────────────░─»\n",
-       "«                        ░                       ░                       ░ »\n",
-       "« q0_8: ─────────────────░───────────────────────░───────────────────────░─»\n",
-       "«                        ░                       ░                       ░ »\n",
-       "« q0_9: ─────────────────░───────────────────────░───────────────────────░─»\n",
-       "«                        ░                       ░                       ░ »\n",
-       "«q0_10: ─────────────────░───────────────────────░───────────────────────░─»\n",
-       "«                        ░                       ░                       ░ »\n",
-       "«q0_11: ─────────────────░───────────────────────░───────────────────────░─»\n",
-       "«                        ░                       ░                       ░ »\n",
-       "«q0_12: ─────────────────░───────────────────────░───────────────────────░─»\n",
-       "«                        ░                       ░                       ░ »\n",
-       "«q0_13: ─────────────────░───────────────────────░───────────────────────░─»\n",
-       "«                        ░                       ░                       ░ »\n",
-       "«c0: 14/═══════════════════════════════════════════════════════════════════»\n",
-       "«                                                                          »\n",
-       "«                             ░                       ░                 »\n",
-       "« q0_0: ──■───────────────■───░───■───────────────■───░─────────────────»\n",
-       "«         │               │   ░   │               │   ░ ┌─────────┐     »\n",
-       "« q0_1: ──┼───────────────┼───░───┼───────────────┼───░─┤ RZ(0.1) ├──■──»\n",
-       "«         │               │   ░   │               │   ░ └─────────┘  │  »\n",
-       "« q0_2: ──┼───────────────┼───░───┼───────────────┼───░──────────────┼──»\n",
-       "«         │               │   ░   │               │   ░              │  »\n",
-       "« q0_3: ──┼───────────────┼───░───┼───────────────┼───░──────────────┼──»\n",
-       "«         │               │   ░   │               │   ░              │  »\n",
-       "« q0_4: ──┼───────────────┼───░───┼───────────────┼───░──────────────┼──»\n",
-       "«         │               │   ░   │               │   ░            ┌─┴─┐»\n",
-       "« q0_5: ──┼───────────────┼───░───┼───────────────┼───░────────────┤ X ├»\n",
-       "«       ┌─┴─┐┌─────────┐┌─┴─┐ ░   │               │   ░            └───┘»\n",
-       "« q0_6: ┤ X ├┤ RZ(0.2) ├┤ X ├─░───┼───────────────┼───░─────────────────»\n",
-       "«       └───┘└─────────┘└───┘ ░   │               │   ░                 »\n",
-       "« q0_7: ──────────────────────░───┼───────────────┼───░─────────────────»\n",
-       "«                             ░   │               │   ░                 »\n",
-       "« q0_8: ──────────────────────░───┼───────────────┼───░─────────────────»\n",
-       "«                             ░   │               │   ░                 »\n",
-       "« q0_9: ──────────────────────░───┼───────────────┼───░─────────────────»\n",
-       "«                             ░   │               │   ░                 »\n",
-       "«q0_10: ──────────────────────░───┼───────────────┼───░─────────────────»\n",
-       "«                             ░   │               │   ░                 »\n",
-       "«q0_11: ──────────────────────░───┼───────────────┼───░─────────────────»\n",
-       "«                             ░   │               │   ░                 »\n",
-       "«q0_12: ──────────────────────░───┼───────────────┼───░─────────────────»\n",
-       "«                             ░ ┌─┴─┐┌─────────┐┌─┴─┐ ░                 »\n",
-       "«q0_13: ──────────────────────░─┤ X ├┤ RZ(0.2) ├┤ X ├─░─────────────────»\n",
-       "«                             ░ └───┘└─────────┘└───┘ ░                 »\n",
-       "«c0: 14/════════════════════════════════════════════════════════════════»\n",
-       "«                                                                       »\n",
-       "«                        ░                                  ░                 »\n",
-       "« q0_0: ─────────────────░──────────────────────────────────░─────────────────»\n",
-       "«                        ░                                  ░                 »\n",
-       "« q0_1: ─────────────■───░──────────────────────────────────░─────────────────»\n",
-       "«                    │   ░ ┌─────────┐                      ░                 »\n",
-       "« q0_2: ─────────────┼───░─┤ RZ(0.1) ├──■───────────────■───░─────────────────»\n",
-       "«                    │   ░ └─────────┘  │               │   ░ ┌─────────┐     »\n",
-       "« q0_3: ─────────────┼───░──────────────┼───────────────┼───░─┤ RZ(0.2) ├──■──»\n",
-       "«                    │   ░              │               │   ░ └─────────┘  │  »\n",
-       "« q0_4: ─────────────┼───░──────────────┼───────────────┼───░──────────────┼──»\n",
-       "«       ┌─────────┐┌─┴─┐ ░            ┌─┴─┐┌─────────┐┌─┴─┐ ░              │  »\n",
-       "« q0_5: ┤ RZ(0.1) ├┤ X ├─░────────────┤ X ├┤ RZ(0.1) ├┤ X ├─░──────────────┼──»\n",
-       "«       └─────────┘└───┘ ░            └───┘└─────────┘└───┘ ░            ┌─┴─┐»\n",
-       "« q0_6: ─────────────────░──────────────────────────────────░────────────┤ X ├»\n",
-       "«                        ░                                  ░            └───┘»\n",
-       "« q0_7: ─────────────────░──────────────────────────────────░─────────────────»\n",
-       "«                        ░                                  ░                 »\n",
-       "« q0_8: ─────────────────░──────────────────────────────────░─────────────────»\n",
-       "«                        ░                                  ░                 »\n",
-       "« q0_9: ─────────────────░──────────────────────────────────░─────────────────»\n",
-       "«                        ░                                  ░                 »\n",
-       "«q0_10: ─────────────────░──────────────────────────────────░─────────────────»\n",
-       "«                        ░                                  ░                 »\n",
-       "«q0_11: ─────────────────░──────────────────────────────────░─────────────────»\n",
-       "«                        ░                                  ░                 »\n",
-       "«q0_12: ─────────────────░──────────────────────────────────░─────────────────»\n",
-       "«                        ░                                  ░                 »\n",
-       "«q0_13: ─────────────────░──────────────────────────────────░─────────────────»\n",
-       "«                        ░                                  ░                 »\n",
-       "«c0: 14/══════════════════════════════════════════════════════════════════════»\n",
-       "«                                                                             »\n",
-       "«                        ░                       ░                            »\n",
-       "« q0_0: ─────────────────░───────────────────────░────────────────────────────»\n",
-       "«                        ░                       ░                            »\n",
-       "« q0_1: ─────────────────░───────────────────────░────────────────────────────»\n",
-       "«                        ░                       ░                            »\n",
-       "« q0_2: ─────────────────░───────────────────────░────────────────────────────»\n",
-       "«                        ░                       ░                            »\n",
-       "« q0_3: ─────────────■───░───■───────────────■───░────────────────────────────»\n",
-       "«                    │   ░   │               │   ░ ┌─────────┐                »\n",
-       "« q0_4: ─────────────┼───░───┼───────────────┼───░─┤ RZ(0.2) ├──■─────────────»\n",
-       "«                    │   ░   │               │   ░ └─────────┘  │             »\n",
-       "« q0_5: ─────────────┼───░───┼───────────────┼───░──────────────┼─────────────»\n",
-       "«       ┌─────────┐┌─┴─┐ ░   │               │   ░            ┌─┴─┐┌─────────┐»\n",
-       "« q0_6: ┤ RZ(0.1) ├┤ X ├─░───┼───────────────┼───░────────────┤ X ├┤ RZ(0.1) ├»\n",
-       "«       └─────────┘└───┘ ░   │               │   ░            └───┘└─────────┘»\n",
-       "« q0_7: ─────────────────░───┼───────────────┼───░────────────────────────────»\n",
-       "«                        ░   │               │   ░                            »\n",
-       "« q0_8: ─────────────────░───┼───────────────┼───░────────────────────────────»\n",
-       "«                        ░   │               │   ░                            »\n",
-       "« q0_9: ─────────────────░───┼───────────────┼───░────────────────────────────»\n",
-       "«                        ░   │               │   ░                            »\n",
-       "«q0_10: ─────────────────░───┼───────────────┼───░────────────────────────────»\n",
-       "«                        ░   │               │   ░                            »\n",
-       "«q0_11: ─────────────────░───┼───────────────┼───░────────────────────────────»\n",
-       "«                        ░   │               │   ░                            »\n",
-       "«q0_12: ─────────────────░───┼───────────────┼───░────────────────────────────»\n",
-       "«                        ░ ┌─┴─┐┌─────────┐┌─┴─┐ ░                            »\n",
-       "«q0_13: ─────────────────░─┤ X ├┤ RZ(0.1) ├┤ X ├─░────────────────────────────»\n",
-       "«                        ░ └───┘└─────────┘└───┘ ░                            »\n",
-       "«c0: 14/══════════════════════════════════════════════════════════════════════»\n",
-       "«                                                                             »\n",
-       "«             ░                       ░                                  ░ »\n",
-       "« q0_0: ──────░───────────────────────░──────────────────────────────────░─»\n",
-       "«             ░                       ░                                  ░ »\n",
-       "« q0_1: ──────░───────────────────────░──────────────────────────────────░─»\n",
-       "«             ░                       ░                                  ░ »\n",
-       "« q0_2: ──────░───────────────────────░──────────────────────────────────░─»\n",
-       "«             ░                       ░                                  ░ »\n",
-       "« q0_3: ──────░───────────────────────░──────────────────────────────────░─»\n",
-       "«             ░                       ░                                  ░ »\n",
-       "« q0_4: ──■───░───■───────────────■───░──────────────────────────────────░─»\n",
-       "«         │   ░   │               │   ░ ┌─────────┐                      ░ »\n",
-       "« q0_5: ──┼───░───┼───────────────┼───░─┤ RZ(0.2) ├──────────────────────░─»\n",
-       "«       ┌─┴─┐ ░   │               │   ░ ├─────────┤                      ░ »\n",
-       "« q0_6: ┤ X ├─░───┼───────────────┼───░─┤ RZ(0.4) ├──■───────────────■───░─»\n",
-       "«       └───┘ ░   │               │   ░ └─────────┘  │               │   ░ »\n",
-       "« q0_7: ──────░───┼───────────────┼───░──────────────┼───────────────┼───░─»\n",
-       "«             ░   │               │   ░              │               │   ░ »\n",
-       "« q0_8: ──────░───┼───────────────┼───░──────────────┼───────────────┼───░─»\n",
-       "«             ░   │               │   ░              │               │   ░ »\n",
-       "« q0_9: ──────░───┼───────────────┼───░──────────────┼───────────────┼───░─»\n",
-       "«             ░   │               │   ░              │               │   ░ »\n",
-       "«q0_10: ──────░───┼───────────────┼───░──────────────┼───────────────┼───░─»\n",
-       "«             ░   │               │   ░              │               │   ░ »\n",
-       "«q0_11: ──────░───┼───────────────┼───░──────────────┼───────────────┼───░─»\n",
-       "«             ░   │               │   ░              │               │   ░ »\n",
-       "«q0_12: ──────░───┼───────────────┼───░──────────────┼───────────────┼───░─»\n",
-       "«             ░ ┌─┴─┐┌─────────┐┌─┴─┐ ░            ┌─┴─┐┌─────────┐┌─┴─┐ ░ »\n",
-       "«q0_13: ──────░─┤ X ├┤ RZ(0.1) ├┤ X ├─░────────────┤ X ├┤ RZ(0.2) ├┤ X ├─░─»\n",
-       "«             ░ └───┘└─────────┘└───┘ ░            └───┘└─────────┘└───┘ ░ »\n",
-       "«c0: 14/═══════════════════════════════════════════════════════════════════»\n",
-       "«                                                                          »\n",
-       "«                                        ░                       ░      »\n",
-       "« q0_0: ─────────────────────────────────░───────────────────────░──────»\n",
-       "«                                        ░                       ░      »\n",
-       "« q0_1: ─────────────────────────────────░───────────────────────░──────»\n",
-       "«                                        ░                       ░      »\n",
-       "« q0_2: ─────────────────────────────────░───────────────────────░──────»\n",
-       "«                                        ░                       ░      »\n",
-       "« q0_3: ─────────────────────────────────░───────────────────────░──────»\n",
-       "«                                        ░                       ░      »\n",
-       "« q0_4: ─────────────────────────────────░───────────────────────░──────»\n",
-       "«                                        ░                       ░      »\n",
-       "« q0_5: ─────────────────────────────────░───────────────────────░──────»\n",
-       "«                                        ░                       ░      »\n",
-       "« q0_6: ─────────────────────────────────░───────────────────────░──────»\n",
-       "«       ┌─────────┐                      ░                       ░      »\n",
-       "« q0_7: ┤ RZ(0.1) ├──■───────────────■───░───■───────────────■───░───■──»\n",
-       "«       └─────────┘  │               │   ░   │               │   ░   │  »\n",
-       "« q0_8: ─────────────┼───────────────┼───░───┼───────────────┼───░───┼──»\n",
-       "«                  ┌─┴─┐┌─────────┐┌─┴─┐ ░   │               │   ░   │  »\n",
-       "« q0_9: ───────────┤ X ├┤ RZ(0.1) ├┤ X ├─░───┼───────────────┼───░───┼──»\n",
-       "«                  └───┘└─────────┘└───┘ ░ ┌─┴─┐┌─────────┐┌─┴─┐ ░   │  »\n",
-       "«q0_10: ─────────────────────────────────░─┤ X ├┤ RZ(0.1) ├┤ X ├─░───┼──»\n",
-       "«                                        ░ └───┘└─────────┘└───┘ ░   │  »\n",
-       "«q0_11: ─────────────────────────────────░───────────────────────░───┼──»\n",
-       "«                                        ░                       ░   │  »\n",
-       "«q0_12: ─────────────────────────────────░───────────────────────░───┼──»\n",
-       "«                                        ░                       ░ ┌─┴─┐»\n",
-       "«q0_13: ─────────────────────────────────░───────────────────────░─┤ X ├»\n",
-       "«                                        ░                       ░ └───┘»\n",
-       "«c0: 14/════════════════════════════════════════════════════════════════»\n",
-       "«                                                                       »\n",
-       "«                        ░                       ░                       ░ »\n",
-       "« q0_0: ─────────────────░───────────────────────░───────────────────────░─»\n",
-       "«                        ░                       ░                       ░ »\n",
-       "« q0_1: ─────────────────░───────────────────────░───────────────────────░─»\n",
-       "«                        ░                       ░                       ░ »\n",
-       "« q0_2: ─────────────────░───────────────────────░───────────────────────░─»\n",
-       "«                        ░                       ░                       ░ »\n",
-       "« q0_3: ─────────────────░───────────────────────░───────────────────────░─»\n",
-       "«                        ░                       ░                       ░ »\n",
-       "« q0_4: ─────────────────░───────────────────────░───────────────────────░─»\n",
-       "«                        ░                       ░                       ░ »\n",
-       "« q0_5: ─────────────────░───────────────────────░───────────────────────░─»\n",
-       "«                        ░                       ░                       ░ »\n",
-       "« q0_6: ─────────────────░───────────────────────░───────────────────────░─»\n",
-       "«                        ░                       ░                       ░ »\n",
-       "« q0_7: ─────────────■───░───────────────────────░───────────────────────░─»\n",
-       "«                    │   ░                       ░                       ░ »\n",
-       "« q0_8: ─────────────┼───░───■───────────────■───░───■───────────────■───░─»\n",
-       "«                    │   ░   │               │   ░   │               │   ░ »\n",
-       "« q0_9: ─────────────┼───░───┼───────────────┼───░───┼───────────────┼───░─»\n",
-       "«                    │   ░   │               │   ░   │               │   ░ »\n",
-       "«q0_10: ─────────────┼───░───┼───────────────┼───░───┼───────────────┼───░─»\n",
-       "«                    │   ░ ┌─┴─┐┌─────────┐┌─┴─┐ ░   │               │   ░ »\n",
-       "«q0_11: ─────────────┼───░─┤ X ├┤ RZ(0.1) ├┤ X ├─░───┼───────────────┼───░─»\n",
-       "«                    │   ░ └───┘└─────────┘└───┘ ░ ┌─┴─┐┌─────────┐┌─┴─┐ ░ »\n",
-       "«q0_12: ─────────────┼───░───────────────────────░─┤ X ├┤ RZ(0.1) ├┤ X ├─░─»\n",
-       "«       ┌─────────┐┌─┴─┐ ░                       ░ └───┘└─────────┘└───┘ ░ »\n",
-       "«q0_13: ┤ RZ(0.1) ├┤ X ├─░───────────────────────░───────────────────────░─»\n",
-       "«       └─────────┘└───┘ ░                       ░                       ░ »\n",
-       "«c0: 14/═══════════════════════════════════════════════════════════════════»\n",
-       "«                                                                          »\n",
-       "«                                        ░ ┌──────────┐             ░ ┌─┐      »\n",
-       "« q0_0: ─────────────────────────────────░─┤ RX(-0.4) ├─────────────░─┤M├──────»\n",
-       "«                                        ░ ├──────────┤             ░ └╥┘┌─┐   »\n",
-       "« q0_1: ─────────────────────────────────░─┤ RX(-0.4) ├─────────────░──╫─┤M├───»\n",
-       "«                                        ░ ├──────────┤             ░  ║ └╥┘┌─┐»\n",
-       "« q0_2: ─────────────────────────────────░─┤ RX(-0.4) ├─────────────░──╫──╫─┤M├»\n",
-       "«                                        ░ ├──────────┤             ░  ║  ║ └╥┘»\n",
-       "« q0_3: ─────────────────────────────────░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n",
-       "«                                        ░ ├──────────┤             ░  ║  ║  ║ »\n",
-       "« q0_4: ─────────────────────────────────░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n",
-       "«                                        ░ ├──────────┤             ░  ║  ║  ║ »\n",
-       "« q0_5: ─────────────────────────────────░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n",
-       "«                                        ░ ├──────────┤             ░  ║  ║  ║ »\n",
-       "« q0_6: ─────────────────────────────────░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n",
-       "«                                        ░ ├──────────┤             ░  ║  ║  ║ »\n",
-       "« q0_7: ─────────────────────────────────░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n",
-       "«                                        ░ ├──────────┤             ░  ║  ║  ║ »\n",
-       "« q0_8: ─────────────────────────────────░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n",
-       "«       ┌─────────┐                      ░ ├──────────┤             ░  ║  ║  ║ »\n",
-       "« q0_9: ┤ RZ(0.1) ├──■───────────────■───░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n",
-       "«       └─────────┘  │               │   ░ ├──────────┤             ░  ║  ║  ║ »\n",
-       "«q0_10: ─────────────┼───────────────┼───░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n",
-       "«                    │               │   ░ ├──────────┤             ░  ║  ║  ║ »\n",
-       "«q0_11: ─────────────┼───────────────┼───░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n",
-       "«                    │               │   ░ ├──────────┤             ░  ║  ║  ║ »\n",
-       "«q0_12: ─────────────┼───────────────┼───░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n",
-       "«                  ┌─┴─┐┌─────────┐┌─┴─┐ ░ ├─────────┬┘┌──────────┐ ░  ║  ║  ║ »\n",
-       "«q0_13: ───────────┤ X ├┤ RZ(0.1) ├┤ X ├─░─┤ RZ(0.5) ├─┤ RX(-0.4) ├─░──╫──╫──╫─»\n",
-       "«                  └───┘└─────────┘└───┘ ░ └─────────┘ └──────────┘ ░  ║  ║  ║ »\n",
-       "«c0: 14/═══════════════════════════════════════════════════════════════╩══╩══╩═»\n",
-       "«                                                                      0  1  2 »\n",
-       "«                                        \n",
-       "« q0_0: ─────────────────────────────────\n",
-       "«                                        \n",
-       "« q0_1: ─────────────────────────────────\n",
-       "«                                        \n",
-       "« q0_2: ─────────────────────────────────\n",
-       "«       ┌─┐                              \n",
-       "« q0_3: ┤M├──────────────────────────────\n",
-       "«       └╥┘┌─┐                           \n",
-       "« q0_4: ─╫─┤M├───────────────────────────\n",
-       "«        ║ └╥┘┌─┐                        \n",
-       "« q0_5: ─╫──╫─┤M├────────────────────────\n",
-       "«        ║  ║ └╥┘┌─┐                     \n",
-       "« q0_6: ─╫──╫──╫─┤M├─────────────────────\n",
-       "«        ║  ║  ║ └╥┘┌─┐                  \n",
-       "« q0_7: ─╫──╫──╫──╫─┤M├──────────────────\n",
-       "«        ║  ║  ║  ║ └╥┘┌─┐               \n",
-       "« q0_8: ─╫──╫──╫──╫──╫─┤M├───────────────\n",
-       "«        ║  ║  ║  ║  ║ └╥┘┌─┐            \n",
-       "« q0_9: ─╫──╫──╫──╫──╫──╫─┤M├────────────\n",
-       "«        ║  ║  ║  ║  ║  ║ └╥┘┌─┐         \n",
-       "«q0_10: ─╫──╫──╫──╫──╫──╫──╫─┤M├─────────\n",
-       "«        ║  ║  ║  ║  ║  ║  ║ └╥┘┌─┐      \n",
-       "«q0_11: ─╫──╫──╫──╫──╫──╫──╫──╫─┤M├──────\n",
-       "«        ║  ║  ║  ║  ║  ║  ║  ║ └╥┘┌─┐   \n",
-       "«q0_12: ─╫──╫──╫──╫──╫──╫──╫──╫──╫─┤M├───\n",
-       "«        ║  ║  ║  ║  ║  ║  ║  ║  ║ └╥┘┌─┐\n",
-       "«q0_13: ─╫──╫──╫──╫──╫──╫──╫──╫──╫──╫─┤M├\n",
-       "«        ║  ║  ║  ║  ║  ║  ║  ║  ║  ║ └╥┘\n",
-       "«c0: 14/═╩══╩══╩══╩══╩══╩══╩══╩══╩══╩══╩═\n",
-       "«        3  4  5  6  7  8  9  10 11 12 13
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──────░───────────────────────░──────────────────────────────────░─»\n", - "« ░ ░ ░ »\n", - "« q0_3: ──────░───────────────────────░──────────────────────────────────░─»\n", - "« ░ ░ ░ »\n", - "« q0_4: ──■───░───■───────────────■───░──────────────────────────────────░─»\n", - "« │ ░ │ │ ░ ┌─────────┐ ░ »\n", - "« q0_5: ──┼───░───┼───────────────┼───░─┤ RZ(0.2) ├──────────────────────░─»\n", - "« ┌─┴─┐ ░ │ │ ░ ├─────────┤ ░ »\n", - "« q0_6: ┤ X ├─░───┼───────────────┼───░─┤ RZ(0.4) ├──■───────────────■───░─»\n", - "« └───┘ ░ │ │ ░ └─────────┘ │ │ ░ »\n", - "« q0_7: ──────░───┼───────────────┼───░──────────────┼───────────────┼───░─»\n", - "« ░ │ │ ░ │ │ ░ »\n", - "« q0_8: ──────░───┼───────────────┼───░──────────────┼───────────────┼───░─»\n", - "« ░ │ │ ░ │ │ ░ »\n", - "« q0_9: ──────░───┼───────────────┼───░──────────────┼───────────────┼───░─»\n", - "« ░ │ │ ░ │ │ ░ »\n", - "«q0_10: ──────░───┼───────────────┼───░──────────────┼───────────────┼───░─»\n", - "« ░ │ │ ░ │ │ ░ »\n", - "«q0_11: ──────░───┼───────────────┼───░──────────────┼───────────────┼───░─»\n", - "« ░ │ │ ░ │ │ ░ »\n", - "«q0_12: ──────░───┼───────────────┼───░──────────────┼───────────────┼───░─»\n", - "« ░ ┌─┴─┐┌─────────┐┌─┴─┐ ░ ┌─┴─┐┌─────────┐┌─┴─┐ ░ »\n", - "«q0_13: ──────░─┤ X ├┤ RZ(0.1) ├┤ X ├─░────────────┤ X ├┤ RZ(0.2) ├┤ X ├─░─»\n", - "« ░ └───┘└─────────┘└───┘ ░ └───┘└─────────┘└───┘ ░ »\n", - "«c0: 14/═══════════════════════════════════════════════════════════════════»\n", - "« »\n", - "« ░ ░ »\n", - "« q0_0: ─────────────────────────────────░───────────────────────░──────»\n", - "« ░ ░ »\n", - "« q0_1: ─────────────────────────────────░───────────────────────░──────»\n", - "« ░ ░ »\n", - "« q0_2: ─────────────────────────────────░───────────────────────░──────»\n", - "« ░ ░ »\n", - "« q0_3: ─────────────────────────────────░───────────────────────░──────»\n", - "« ░ ░ »\n", - "« q0_4: ─────────────────────────────────░───────────────────────░──────»\n", - "« ░ ░ »\n", - "« q0_5: ─────────────────────────────────░───────────────────────░──────»\n", - "« ░ ░ »\n", - "« q0_6: ─────────────────────────────────░───────────────────────░──────»\n", - "« ┌─────────┐ ░ ░ »\n", - "« q0_7: ┤ RZ(0.1) ├──■───────────────■───░───■───────────────■───░───■──»\n", - "« └─────────┘ │ │ ░ │ │ ░ │ »\n", - "« q0_8: ─────────────┼───────────────┼───░───┼───────────────┼───░───┼──»\n", - "« ┌─┴─┐┌─────────┐┌─┴─┐ ░ │ │ ░ │ »\n", - "« q0_9: ───────────┤ X ├┤ RZ(0.1) ├┤ X ├─░───┼───────────────┼───░───┼──»\n", - "« └───┘└─────────┘└───┘ ░ ┌─┴─┐┌─────────┐┌─┴─┐ ░ │ »\n", - "«q0_10: ─────────────────────────────────░─┤ X ├┤ RZ(0.1) ├┤ X ├─░───┼──»\n", - "« ░ └───┘└─────────┘└───┘ ░ │ »\n", - "«q0_11: ─────────────────────────────────░───────────────────────░───┼──»\n", - "« ░ ░ │ »\n", - "«q0_12: ─────────────────────────────────░───────────────────────░───┼──»\n", - "« ░ ░ ┌─┴─┐»\n", - "«q0_13: ─────────────────────────────────░───────────────────────░─┤ X ├»\n", - "« ░ ░ └───┘»\n", - "«c0: 14/════════════════════════════════════════════════════════════════»\n", - "« »\n", - "« ░ ░ ░ »\n", - "« q0_0: ─────────────────░───────────────────────░───────────────────────░─»\n", - "« ░ ░ ░ »\n", - "« q0_1: ─────────────────░───────────────────────░───────────────────────░─»\n", - "« ░ ░ ░ »\n", - "« q0_2: ─────────────────░───────────────────────░───────────────────────░─»\n", - "« ░ ░ ░ »\n", - "« q0_3: ─────────────────░───────────────────────░───────────────────────░─»\n", - "« ░ ░ ░ »\n", - "« q0_4: ─────────────────░───────────────────────░───────────────────────░─»\n", - "« ░ ░ ░ »\n", - "« q0_5: ─────────────────░───────────────────────░───────────────────────░─»\n", - "« ░ ░ ░ »\n", - "« q0_6: ─────────────────░───────────────────────░───────────────────────░─»\n", - "« ░ ░ ░ »\n", - "« q0_7: ─────────────■───░───────────────────────░───────────────────────░─»\n", - "« │ ░ ░ ░ »\n", - "« q0_8: ─────────────┼───░───■───────────────■───░───■───────────────■───░─»\n", - "« │ ░ │ │ ░ │ │ ░ »\n", - "« q0_9: ─────────────┼───░───┼───────────────┼───░───┼───────────────┼───░─»\n", - "« │ ░ │ │ ░ │ │ ░ »\n", - "«q0_10: ─────────────┼───░───┼───────────────┼───░───┼───────────────┼───░─»\n", - "« │ ░ ┌─┴─┐┌─────────┐┌─┴─┐ ░ │ │ ░ »\n", - "«q0_11: ─────────────┼───░─┤ X ├┤ RZ(0.1) ├┤ X ├─░───┼───────────────┼───░─»\n", - "« │ ░ └───┘└─────────┘└───┘ ░ ┌─┴─┐┌─────────┐┌─┴─┐ ░ »\n", - "«q0_12: ─────────────┼───░───────────────────────░─┤ X ├┤ RZ(0.1) ├┤ X ├─░─»\n", - "« ┌─────────┐┌─┴─┐ ░ ░ └───┘└─────────┘└───┘ ░ »\n", - "«q0_13: ┤ RZ(0.1) ├┤ X ├─░───────────────────────░───────────────────────░─»\n", - "« └─────────┘└───┘ ░ ░ ░ »\n", - "«c0: 14/═══════════════════════════════════════════════════════════════════»\n", - "« »\n", - "« ░ ┌──────────┐ ░ ┌─┐ »\n", - "« q0_0: ─────────────────────────────────░─┤ RX(-0.4) ├─────────────░─┤M├──────»\n", - "« ░ ├──────────┤ ░ └╥┘┌─┐ »\n", - "« q0_1: ─────────────────────────────────░─┤ RX(-0.4) ├─────────────░──╫─┤M├───»\n", - "« ░ ├──────────┤ ░ ║ └╥┘┌─┐»\n", - "« q0_2: ─────────────────────────────────░─┤ RX(-0.4) ├─────────────░──╫──╫─┤M├»\n", - "« ░ ├──────────┤ ░ ║ ║ └╥┘»\n", - "« q0_3: ─────────────────────────────────░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n", - "« ░ ├──────────┤ ░ ║ ║ ║ »\n", - "« q0_4: ─────────────────────────────────░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n", - "« ░ ├──────────┤ ░ ║ ║ ║ »\n", - "« q0_5: ─────────────────────────────────░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n", - "« ░ ├──────────┤ ░ ║ ║ ║ »\n", - "« q0_6: ─────────────────────────────────░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n", - "« ░ ├──────────┤ ░ ║ ║ ║ »\n", - "« q0_7: ─────────────────────────────────░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n", - "« ░ ├──────────┤ ░ ║ ║ ║ »\n", - "« q0_8: ─────────────────────────────────░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n", - "« ┌─────────┐ ░ ├──────────┤ ░ ║ ║ ║ »\n", - "« q0_9: ┤ RZ(0.1) ├──■───────────────■───░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n", - "« └─────────┘ │ │ ░ ├──────────┤ ░ ║ ║ ║ »\n", - "«q0_10: ─────────────┼───────────────┼───░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n", - "« │ │ ░ ├──────────┤ ░ ║ ║ ║ »\n", - "«q0_11: ─────────────┼───────────────┼───░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n", - "« │ │ ░ ├──────────┤ ░ ║ ║ ║ »\n", - "«q0_12: ─────────────┼───────────────┼───░─┤ RX(-0.4) ├─────────────░──╫──╫──╫─»\n", - "« ┌─┴─┐┌─────────┐┌─┴─┐ ░ ├─────────┬┘┌──────────┐ ░ ║ ║ ║ »\n", - "«q0_13: ───────────┤ X ├┤ RZ(0.1) ├┤ X ├─░─┤ RZ(0.5) ├─┤ RX(-0.4) ├─░──╫──╫──╫─»\n", - "« └───┘└─────────┘└───┘ ░ └─────────┘ └──────────┘ ░ ║ ║ ║ »\n", - "«c0: 14/═══════════════════════════════════════════════════════════════╩══╩══╩═»\n", - "« 0 1 2 »\n", - "« \n", - "« q0_0: ─────────────────────────────────\n", - "« \n", - "« q0_1: ─────────────────────────────────\n", - "« \n", - "« q0_2: ─────────────────────────────────\n", - "« ┌─┐ \n", - "« q0_3: ┤M├──────────────────────────────\n", - "« └╥┘┌─┐ \n", - "« q0_4: ─╫─┤M├───────────────────────────\n", - "« ║ └╥┘┌─┐ \n", - "« q0_5: ─╫──╫─┤M├────────────────────────\n", - "« ║ ║ └╥┘┌─┐ \n", - "« q0_6: ─╫──╫──╫─┤M├─────────────────────\n", - "« ║ ║ ║ └╥┘┌─┐ \n", - "« q0_7: ─╫──╫──╫──╫─┤M├──────────────────\n", - "« ║ ║ ║ ║ └╥┘┌─┐ \n", - "« q0_8: ─╫──╫──╫──╫──╫─┤M├───────────────\n", - "« ║ ║ ║ ║ ║ └╥┘┌─┐ \n", - "« q0_9: ─╫──╫──╫──╫──╫──╫─┤M├────────────\n", - "« ║ ║ ║ ║ ║ ║ └╥┘┌─┐ \n", - "«q0_10: ─╫──╫──╫──╫──╫──╫──╫─┤M├─────────\n", - "« ║ ║ ║ ║ ║ ║ ║ └╥┘┌─┐ \n", - "«q0_11: ─╫──╫──╫──╫──╫──╫──╫──╫─┤M├──────\n", - "« ║ ║ ║ ║ ║ ║ ║ ║ └╥┘┌─┐ \n", - "«q0_12: ─╫──╫──╫──╫──╫──╫──╫──╫──╫─┤M├───\n", - "« ║ ║ ║ ║ ║ ║ ║ ║ ║ └╥┘┌─┐\n", - "«q0_13: ─╫──╫──╫──╫──╫──╫──╫──╫──╫──╫─┤M├\n", - "« ║ ║ ║ ║ ║ ║ ║ ║ ║ ║ └╥┘\n", - "«c0: 14/═╩══╩══╩══╩══╩══╩══╩══╩══╩══╩══╩═\n", - "« 3 4 5 6 7 8 9 10 11 12 13" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "options={}\n", - "options['FR']=FR\n", - "options['usebarrier']=True\n", - "circ=createCircuit_ExactCover(np.array((0.1,0.2)), 1, options)\n", - "circ.draw()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "from qaoa import *\n", - "Aer.backends()\n", - "backend = Aer.get_backend('qasm_simulator')" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "depth = 1\n", - "Calculating Energy landscape...\n", - "Calculating Energy landscape done\n", - "depth = 1 rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 7.400879\n", - " Iterations: 12\n", - " Function evaluations: 27\n", - "depth = 1 rep = 2\n", - "Optimization terminated successfully.\n", - " Current function value: 7.489502\n", - " Iterations: 10\n", - " Function evaluations: 23\n", - "depth = 1 rep = 3\n", - "Optimization terminated successfully.\n", - " Current function value: 7.350098\n", - " Iterations: 106\n", - " Function evaluations: 285\n", - "depth = 1 rep = 4\n", - "Optimization terminated successfully.\n", - " Current function value: 7.400146\n", - " Iterations: 10\n", - " Function evaluations: 22\n", - "depth = 1 rep = 5\n", - "Optimization terminated successfully.\n", - " Current function value: 7.428223\n", - " Iterations: 9\n", - " Function evaluations: 18\n", - "depth = 2\n", - "P= [0.23599704]\n", - "P= [2.0201347]\n", - "depth = 2 rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 9.005859\n", - " Iterations: 62\n", - " Function evaluations: 144\n", - "depth = 2 rep = 2\n", - "Optimization terminated successfully.\n", - " Current function value: 6.467041\n", - " Iterations: 73\n", - " Function evaluations: 129\n", - "depth = 2 rep = 3\n", - "Optimization terminated successfully.\n", - " Current function value: 6.492188\n", - " Iterations: 97\n", - " Function evaluations: 231\n", - "depth = 2 rep = 4\n", - "Optimization terminated successfully.\n", - " Current function value: 9.572754\n", - " Iterations: 41\n", - " Function evaluations: 85\n", - "depth = 2 rep = 5\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "depth = 3\n", - "P= [-0.15447915 0.17193543]\n", - "P= [2.37174307 1.85785879]\n", - "depth = 3 rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 8.446289\n", - " Iterations: 33\n", - " Function evaluations: 77\n", - "depth = 3 rep = 2\n", - "Optimization terminated successfully.\n", - " Current function value: 8.414062\n", - " Iterations: 87\n", - " Function evaluations: 219\n", - "depth = 3 rep = 3\n", - "Optimization terminated successfully.\n", - " Current function value: 8.395264\n", - " Iterations: 41\n", - " Function evaluations: 88\n", - "depth = 3 rep = 4\n", - "Optimization terminated successfully.\n", - " Current function value: 8.336670\n", - " Iterations: 46\n", - " Function evaluations: 98\n", - "depth = 3 rep = 5\n", - "Optimization terminated successfully.\n", - " Current function value: 7.322266\n", - " Iterations: 91\n", - " Function evaluations: 167\n", - "depth = 4\n", - "P= [-0.03165379 0.01107571 0.21153219]\n", - "P= [3.14534065 1.66760369 2.04985913]\n", - "depth = 4 rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 7.531982\n", - " Iterations: 68\n", - " Function evaluations: 148\n", - "depth = 4 rep = 2\n", - "Optimization terminated successfully.\n", - " Current function value: 7.450684\n", - " Iterations: 125\n", - " Function evaluations: 294\n", - "depth = 4 rep = 3\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "depth = 4 rep = 4\n", - "Optimization terminated successfully.\n", - " Current function value: 7.479004\n", - " Iterations: 62\n", - " Function evaluations: 117\n", - "depth = 4 rep = 5\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "depth = 5\n", - "P= [-0.03156305 -0.00288732 0.06436897 0.21585873]\n", - "P= [3.50589296 2.57899441 1.9137407 2.02755091]\n", - "depth = 5 rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 7.503418\n", - " Iterations: 101\n", - " Function evaluations: 236\n", - "depth = 5 rep = 2\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "depth = 5 rep = 3\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "depth = 5 rep = 4\n", - "Optimization terminated successfully.\n", - " Current function value: 7.450928\n", - " Iterations: 179\n", - " Function evaluations: 502\n", - "depth = 5 rep = 5\n", - "Optimization terminated successfully.\n", - " Current function value: 7.594238\n", - " Iterations: 96\n", - " Function evaluations: 221\n", - "depth = 6\n", - "P= [-0.03184732 -0.01020374 0.02914492 0.07591598 0.22546395]\n", - "P= [3.9949623 3.25418129 2.11791567 2.08058606 2.04301179]\n", - "depth = 6 rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 7.663818\n", - " Iterations: 64\n", - " Function evaluations: 158\n", - "depth = 6 rep = 2\n", - "Optimization terminated successfully.\n", - " Current function value: 7.610107\n", - " Iterations: 53\n", - " Function evaluations: 144\n", - "depth = 6 rep = 3\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "depth = 6 rep = 4\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "depth = 6 rep = 5\n", - "Optimization terminated successfully.\n", - " Current function value: 7.723145\n", - " Iterations: 33\n", - " Function evaluations: 110\n", - "depth = 7\n", - "P= [-0.03707147 -0.0171202 0.01755224 0.02696108 0.02502577 0.31233637]\n", - "P= [3.81840949 4.64227778 3.14382871 1.76578659 1.87605579 1.84860556]\n", - "depth = 7 rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "depth = 7 rep = 2\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "depth = 7 rep = 3\n", - "Optimization terminated successfully.\n", - " Current function value: 6.601074\n", - " Iterations: 71\n", - " Function evaluations: 163\n", - "depth = 7 rep = 4\n", - "Optimization terminated successfully.\n", - " Current function value: 6.687988\n", - " Iterations: 78\n", - " Function evaluations: 199\n", - "depth = 7 rep = 5\n", - "Optimization terminated successfully.\n", - " Current function value: 6.432617\n", - " Iterations: 166\n", - " Function evaluations: 426\n", - "depth = 8\n", - "P= [-0.03746959 -0.02079373 0.00601282 0.02227587 0.02662151 0.07059805\n", - " 0.29894152]\n", - "P= [3.75633373 4.5305231 3.43600498 2.66637648 1.86546274 1.93925864\n", - " 1.88779298]\n", - "depth = 8 rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "depth = 8 rep = 2\n", - "Optimization terminated successfully.\n", - " Current function value: 6.438477\n", - " Iterations: 127\n", - " Function evaluations: 260\n", - "depth = 8 rep = 3\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "depth = 8 rep = 4\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "depth = 8 rep = 5\n", - "Optimization terminated successfully.\n", - " Current function value: 5.690186\n", - " Iterations: 196\n", - " Function evaluations: 341\n", - "depth = 9\n", - "P= [-0.03863625 -0.02442922 -0.00156588 0.01513779 0.02639142 0.04819386\n", - " 0.05449732 0.32781771]\n", - "P= [3.11519743 4.65318474 3.54673891 3.35825024 2.8387483 1.6818394\n", - " 2.05710604 1.80835832]\n", - "depth = 9 rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.866211\n", - " Iterations: 178\n", - " Function evaluations: 425\n", - "depth = 9 rep = 2\n", - "Optimization terminated successfully.\n", - " Current function value: 5.832520\n", - " Iterations: 155\n", - " Function evaluations: 291\n", - "depth = 9 rep = 3\n", - "Optimization terminated successfully.\n", - " Current function value: 5.857178\n", - " Iterations: 124\n", - " Function evaluations: 293\n", - "depth = 9 rep = 4\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "depth = 9 rep = 5\n", - "Optimization terminated successfully.\n", - " Current function value: 5.846924\n", - " Iterations: 128\n", - " Function evaluations: 279\n", - "depth = 10\n", - "P= [-0.03853162 -0.02667192 -0.00710624 0.00877157 0.02056809 0.03409896\n", - " 0.05061348 0.08325644 0.32522284]\n", - "P= [3.09656315 4.40521728 3.68653698 3.47996751 3.23237849 2.51510543\n", - " 1.85444218 2.08034107 1.8439856 ]\n", - "depth = 10 rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.835449\n", - " Iterations: 164\n", - " Function evaluations: 323\n", - "depth = 10 rep = 2\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "depth = 10 rep = 3\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "depth = 10 rep = 4\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "depth = 10 rep = 5\n", - "Optimization terminated successfully.\n", - " Current function value: 5.899902\n", - " Iterations: 533\n", - " Function evaluations: 1505\n" - ] - } - ], - "source": [ - "beta_n = 40\n", - "gamma_n = 40\n", - "beta_max = np.pi\n", - "gamma_max = np.pi\n", - "optmethod='Nelder-Mead' \n", - "shots=1024*2*2*2\n", - "rerun=True\n", - "maxdepth=10\n", - "\n", - "Elandscape, gammabetas, E, best = runQAOA(createCircuit_ExactCover, measurementStatistics_ExactCover, backend, gamma_n, beta_n, gamma_max, beta_max, optmethod=optmethod, shots=shots, rerun=rerun, maxdepth=maxdepth, options=options)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as pl\n", - "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", - "\n", - "shiftg=gamma_max/(2*gamma_n)\n", - "shiftb=beta_max/(2*beta_n)\n", - "\n", - "pl.figure(figsize=(20,10));\n", - "pl.clf()\n", - "pl.imshow(Elandscape,interpolation='spline36',origin='lower'\n", - " ,extent=[-shiftg,gamma_max+shiftg,-shiftb,beta_max+shiftb], aspect=1)\n", - "pl.xticks([0,gamma_max], ['0', r'$\\pi$'])\n", - "pl.yticks([0,beta_max], ['0', r'$\\pi$'])\n", - "pl.xlabel('$\\gamma$',loc='center')\n", - "pl.ylabel(r'$\\beta$',loc='center')\n", - "pl.colorbar(shrink=0.25, pad=0.075, orientation=\"horizontal\")\n", - "pl.plot(gammabetas['xL_d1'][0], gammabetas['xL_d1'][1],'or')\n", - "\n", - "pl.tight_layout()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[0.1634521484375]" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "circuit = createCircuit_ExactCover(gammabetas['xL_d1'], 1, options = options)\n", - "job = execute(circuit, backend, shots=shots)\n", - "successProbability(job.result().results, options)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[0.1527099609375]" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "circuit = createCircuit_ExactCover(gammabetas['xL_d4'], 4, options = options)\n", - "job = execute(circuit, backend, shots=shots)\n", - "successProbability(job.result().results, options)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[0.1845703125]" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "circuit = createCircuit_ExactCover(gammabetas['xL_d6'], 6, options = options)\n", - "job = execute(circuit, backend, shots=shots)\n", - "successProbability(job.result().results, options)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[0.1851806640625]" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "circuit = createCircuit_ExactCover(gammabetas['xL_d8'], 8, options = options)\n", - "job = execute(circuit, backend, shots=shots)\n", - "successProbability(job.result().results, options)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[0.1898193359375]" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "circuit = createCircuit_ExactCover(gammabetas['xL_d10'], 10, options = options)\n", - "job = execute(circuit, backend, shots=shots)\n", - "successProbability(job.result().results, options)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "sp=[]\n", - "for i in range(1,maxdepth+1):\n", - " circuit = createCircuit_ExactCover(gammabetas['xL_d'+str(i)], i, options = options)\n", - " job = execute(circuit, backend, shots=shots)\n", - " sp.append(successProbability(job.result().results, options)[0])" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0, 0.5, 'success prob.')" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.plot(range(1,maxdepth+1),sp)\n", - "pl.xlabel('depth')\n", - "pl.ylabel('success prob.')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/exact cover.ipynb b/exact cover.ipynb deleted file mode 100644 index 0ac32d9..0000000 --- a/exact cover.ipynb +++ /dev/null @@ -1,543 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "%load_ext autoreload\n", - "%autoreload 2" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "from qiskit import *\n", - "from qiskit.tools.monitor import job_monitor\n", - "\n", - "import numpy as np\n", - "import pylab as pl\n", - "\n", - "from exactcover import *\n", - "#from classical_exactcover_solver import *\n", - "import os\n", - "from matplotlib import rc\n", - "font = {'size' : 16}\n", - "rc('font', **font);\n", - "rc('text', usetex=True)\n", - "\n", - "import sys\n", - "sys.path.append('../')\n", - "\n", - "from qiskit_utilities.utilities import *\n" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[1., 0., 1., 0.],\n", - " [1., 0., 0., 1.],\n", - " [0., 1., 0., 0.]])" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "FR = np.zeros((3,4))\n", - "FR[0,0]=1\n", - "FR[1,0]=1\n", - "FR[2,1]=1\n", - "FR[1,1]=0\n", - "FR[0,2]=1\n", - "FR[1,3]=1\n", - "FR" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([0.5, 0.1, 0.1, 0.1])" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "CR = np.array([0.5,0.1,0.1,0.1])\n", - "#CR /= np.sum(CR)\n", - "CR" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "# FR = np.zeros((2,2))\n", - "# FR[0,0]=1\n", - "# FR[1,0]=1\n", - "# FR[0,1]=1\n", - "# FR" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "#classical_exactcover_solver(FR, CR)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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├─────────────┤ ├──────────┤ ░ ║ ║ └╥┘┌─┐\n", - "«q0_3: ┤ RZ(0.00025) ├─┤ RX(-0.4) ├─░──╫──╫──╫─┤M├\n", - "« └─────────────┘ └──────────┘ ░ ║ ║ ║ └╥┘\n", - "«c0: 4/════════════════════════════════╩══╩══╩══╩═\n", - "« 0 1 2 3 " - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "options={}\n", - "options['FR']=FR\n", - "options['CR']=CR\n", - "options['usebarrier']=True\n", - "circ=createCircuit_ExactCover(np.array((0.1,0.2)), 1, options)\n", - "circ.draw()" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "from qaoa import *\n", - "Aer.backends()\n", - "backend = Aer.get_backend('qasm_simulator')" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "depth = 1\n", - "Calculating Energy landscape...\n", - "Calculating Energy landscape done\n", - "depth = 1 rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 0.649619\n", - " Iterations: 13\n", - " Function evaluations: 30\n", - "depth = 1 rep = 2\n", - "Optimization terminated successfully.\n", - " Current function value: 0.641952\n", - " Iterations: 10\n", - " Function evaluations: 25\n", - "depth = 1 rep = 3\n", - "Optimization terminated successfully.\n", - " Current function value: 0.646637\n", - " Iterations: 9\n", - " Function evaluations: 25\n", - "depth = 1 rep = 4\n", - "Optimization terminated successfully.\n", - " Current function value: 0.642351\n", - " Iterations: 9\n", - " Function evaluations: 26\n", - "depth = 1 rep = 5\n", - "Optimization terminated successfully.\n", - " Current function value: 0.656172\n", - " Iterations: 11\n", - " Function evaluations: 25\n", - "depth = 2\n", - "P= [2.29173583]\n", - "P= [2.02039802]\n", - "depth = 2 rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 0.648982\n", - " Iterations: 40\n", - " Function evaluations: 86\n", - "depth = 2 rep = 2\n", - "Optimization terminated successfully.\n", - " Current function value: 0.640078\n", - " Iterations: 40\n", - " Function evaluations: 83\n", - "depth = 2 rep = 3\n", - "Optimization terminated successfully.\n", - " Current function value: 0.648043\n", - " Iterations: 40\n", - " Function evaluations: 84\n", - "depth = 2 rep = 4\n", - "Optimization terminated successfully.\n", - " Current function value: 0.650554\n", - " Iterations: 34\n", - " Function evaluations: 79\n", - "depth = 2 rep = 5\n", - "Optimization terminated successfully.\n", - " Current function value: 0.655886\n", - " Iterations: 32\n", - " Function evaluations: 68\n", - "depth = 3\n", - "P= [1.15593447 3.16324927]\n", - "P= [2.11279807 2.02144161]\n", - "depth = 3 rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 0.406448\n", - " Iterations: 53\n", - " Function evaluations: 109\n", - "depth = 3 rep = 2\n", - "Optimization terminated successfully.\n", - " Current function value: 0.176421\n", - " Iterations: 116\n", - " Function evaluations: 202\n", - "depth = 3 rep = 3\n", - "Optimization terminated successfully.\n", - " Current function value: 0.424255\n", - " Iterations: 46\n", - " Function evaluations: 100\n", - "depth = 3 rep = 4\n", - "Optimization terminated successfully.\n", - " Current function value: 0.391349\n", - " Iterations: 68\n", - " Function evaluations: 131\n", - "depth = 3 rep = 5\n", - "Optimization terminated successfully.\n", - " Current function value: 0.431536\n", - " Iterations: 42\n", - " Function evaluations: 90\n", - "depth = 4\n", - "P= [1.6306103 0.65332996 3.11242588]\n", - "P= [1.90443188 1.77035915 1.92798257]\n", - "depth = 4 rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 0.154490\n", - " Iterations: 166\n", - " Function evaluations: 273\n", - "depth = 4 rep = 2\n", - "Optimization terminated successfully.\n", - " Current function value: 0.148447\n", - " Iterations: 130\n", - " Function evaluations: 220\n", - "depth = 4 rep = 3\n", - "Optimization terminated successfully.\n", - " Current function value: 0.396785\n", - " Iterations: 120\n", - " Function evaluations: 219\n", - "depth = 4 rep = 4\n", - "Optimization terminated successfully.\n", - " Current function value: 0.147124\n", - " Iterations: 159\n", - " Function evaluations: 264\n", - "depth = 4 rep = 5\n", - "Optimization terminated successfully.\n", - " Current function value: 0.382561\n", - " Iterations: 124\n", - " Function evaluations: 211\n" - ] - } - ], - "source": [ - "beta_n = 20\n", - "gamma_n = 40\n", - "beta_max = np.pi\n", - "gamma_max = 2*np.pi\n", - "optmethod='Nelder-Mead' \n", - "shots=1024*2*2*2\n", - "rerun=True\n", - "maxdepth=4\n", - "\n", - "Elandscape, gammabetas, E, best = runQAOA(createCircuit_ExactCover, measurementStatistics_ExactCover, backend, gamma_n, beta_n, gamma_max, beta_max, optmethod=optmethod, shots=shots, rerun=rerun, maxdepth=maxdepth, options=options)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as pl\n", - "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", - "\n", - "shiftg=gamma_max/(2*gamma_n)\n", - "shiftb=beta_max/(2*beta_n)\n", - "\n", - "pl.figure(figsize=(20,10));\n", - "pl.clf()\n", - "pl.imshow(Elandscape,interpolation='spline36',origin='lower'\n", - " ,extent=[-shiftg,gamma_max+shiftg,-shiftb,beta_max+shiftb], aspect=1)\n", - "pl.xticks([0,gamma_max], ['0', r'$2\\pi$'])\n", - "pl.yticks([0,beta_max], ['0', r'$\\pi$'])\n", - "pl.xlabel('$\\gamma$',loc='center')\n", - "pl.ylabel(r'$\\beta$',loc='center')\n", - "pl.colorbar(shrink=0.25, pad=0.075, orientation=\"horizontal\")\n", - "pl.plot(gammabetas['xL_d1'][0], gammabetas['xL_d1'][1],'or')\n", - "\n", - "pl.tight_layout()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "circuit = createCircuit_ExactCover(gammabetas['xL_d1'], 1, options = options)\n", - "job = execute(circuit, backend, shots=shots)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from qiskit.visualization import plot_histogram\n", - "plot_histogram(job.result().get_counts())" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[0.5968017578125]" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "successProbability(job.result().results, options)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "circuit = createCircuit_ExactCover(gammabetas['xL_d4'], 4, options = options)\n", - "job = execute(circuit, backend, shots=shots)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "plot_histogram(job.result().get_counts())" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[0.9931640625]" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "successProbability(job.result().results, options)" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "sp=[]\n", - "for i in range(1,maxdepth+1):\n", - " circuit = createCircuit_ExactCover(gammabetas['xL_d'+str(i)], i, options = options)\n", - " job = execute(circuit, backend, shots=shots)\n", - " sp.append(successProbability(job.result().results, options)[0])" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0, 0.5, 'success prob.')" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.plot(range(1,maxdepth+1),sp)\n", - "pl.xlabel('depth')\n", - "pl.ylabel('success prob.')" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.1" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/exactcover.py b/exactcover.py deleted file mode 100644 index d5f144d..0000000 --- a/exactcover.py +++ /dev/null @@ -1,167 +0,0 @@ -from qiskit import QuantumRegister, ClassicalRegister, QuantumCircuit -import numpy as np - -from tqdm import tqdm # progress bar - -#import os -#import sys -#sys.path.append('../') -#from qiskit_utilities.utilities import * - -def createCircuit_ExactCover(x, depth, options=None): - """ - implements https://arxiv.org/pdf/1912.10499.pdf - FR is a matrix - r1 r2 ..... rN - f1 - f2 - . - . - . - fn - where each column indicates if route r uses flight f (entry is 1) or not (entry is 0) - - CR is a vector of route costs [c1 ... cN] where c1 is the cost of route r1 - """ - - FR = options.get('FR', None) # a_fr - CR = options.get('CR', None) # c_r - mu = options.get('mu', 1) # mu - weight of constraint - - usebarrier = options.get('usebarrier', False) - name = options.get('name', None) - - fN=FR.shape[0]### number of flights - rN=FR.shape[1]### number of routes - - q = QuantumRegister(rN) - c = ClassicalRegister(rN) - circ = QuantumCircuit(q, c, name=name) - circ.h(range(rN)) - - for d in range(depth): - - gamma = x[2 * d] - beta = x[2 * d + 1] - - for i in range(rN): - w=0 - for j in range(fN): - w += .5 * mu * FR[j,i]*(np.sum(FR[j,:])-2) - if CR is not None: - w += .25 * CR[i]**2 - if abs(w)>1e-14: - wg = w * gamma - circ.rz(wg, q[i]) - ### - for j in range(i+1, rN): - w=0 - for k in range(fN): - w += 0.5 * mu * FR[k,i]*FR[k,j] - - if w>0: - wg = w * gamma - circ.cx(q[i], q[j]) - circ.rz(wg, q[j]) - circ.cx(q[i], q[j]) - # this is an equivalent implementation: - # circ.cu1(-2 * wg, i, j) - # circ.u1(wg, i) - # circ.u1(wg, j) - if usebarrier: - circ.barrier() - - circ.rx(- 2 * beta, range(rN)) - if usebarrier: - circ.barrier() - circ.measure(q, c) - return circ - -def cost_exactCover(binstring, FR, CR = None, mu = 1): - - # Reverse string since qiskit uses ordering MSB ... LSB - a = np.array(list(map(int,binstring[::-1]))) - - if CR is None: - return - mu * np.sum((np.sum(FR*a,1) -1)**2) - else: - return - mu * np.sum((np.sum(FR*a,1) -1)**2) - np.sum(a*(CR**2)) - -def measurementStatistics_ExactCover(experiment_results, options=None): - """ - Calculates the expectation and variance of the cost function. If - results from multiple circuits are used as input, each circuit's - expectation value is returned. - :param experiment_results: Input on the form execute(...).result().results - :param G: The graph on which the cost function is defined. - :return: Lists of expectation values and variances - """ - - FR = options.get('FR', None) - CR = options.get('CR', None) - mu = options.get('mu', 1) - - rN = FR.shape[1] ### number of routes - - cost_best = -np.inf - - expectations = [] - variances = [] - for result in experiment_results: - n_shots = result.shots - counts = result.data.counts - - E = 0 - E2 = 0 - for hexkey in list(counts.keys()): - count = counts[hexkey] - binstring = "{0:b}".format(int(hexkey,0)).zfill(rN) - cost = cost_exactCover(binstring, FR, CR, mu) - cost_best = max(cost_best, cost) - E += cost*count/n_shots - E2 += cost**2*count/n_shots - - if n_shots == 1: - v = 0 - else: - v = (E2-E**2)*n_shots/(n_shots-1) - expectations.append(E) - variances.append(v) - return expectations, variances, cost_best - - -def is_Solution(binstring, FR): - a = np.array(list(map(int,binstring[::-1]))) - return np.all(np.sum(FR*a,1)-1 == 0) - -#def is_Solution(binstring, FR): -# # This implementation fails the unittests -# rN=FR.shape[1]### number of routes -# fn=FR.shape[0]### number of flights -# a=np.zeros(rN) -# for i in np.arange(len(binstring)): -# ### inverse order, because qiskit order is $q_n q_{n-1} .... q_0$ -# a[len(binstring)-i-1]=int(binstring[i]) -# return np.sum(np.sum(FR*a,1)-1)==0 - -def successProbability(experiment_results, options=None): - - FR = options.get('FR', None) - CR = options.get('CR', None) - rN = FR.shape[1] - - success_prob = [] - - for result in experiment_results: - n_shots = result.shots - counts = result.data.counts - - sprop=0 - for hexkey in list(counts.keys()): - count = counts[hexkey] - binstring = "{0:b}".format(int(hexkey,0)).zfill(rN) - if is_Solution(binstring, FR): - sprop+=count - - success_prob.append(sprop/n_shots) - return success_prob diff --git a/exactcover_unittests.py b/exactcover_unittests.py deleted file mode 100644 index d4d8cbf..0000000 --- a/exactcover_unittests.py +++ /dev/null @@ -1,72 +0,0 @@ -import unittest -from exactcover import * -import numpy as np -from qiskit import * - -class TestExactCover(unittest.TestCase): - - def test_(self): - FR = np.zeros((2,4)) - FR[0,1]=1 - FR[1,2]=1 - FR[0,3]=1 - FR[1,3]=1 - - ### inverse order of the bit strings, because qiskit order is $q_n q_{n-1} .... q_0$ - ## solutions - self.assertEqual(cost_exactCover('0110'[::-1],FR)==0, True) - self.assertEqual(cost_exactCover('0001'[::-1],FR)==0, True) - self.assertEqual(cost_exactCover('1001'[::-1],FR)==0, True) - self.assertEqual(cost_exactCover('1110'[::-1],FR)==0, True) - - ## not solutions - self.assertEqual(cost_exactCover('0000'[::-1],FR)<0, True) - self.assertEqual(cost_exactCover('0010'[::-1],FR)<0, True) - self.assertEqual(cost_exactCover('0011'[::-1],FR)<0, True) - self.assertEqual(cost_exactCover('0100'[::-1],FR)<0, True) - self.assertEqual(cost_exactCover('0101'[::-1],FR)<0, True) - self.assertEqual(cost_exactCover('0111'[::-1],FR)<0, True) - self.assertEqual(cost_exactCover('1000'[::-1],FR)<0, True) - self.assertEqual(cost_exactCover('1010'[::-1],FR)<0, True) - self.assertEqual(cost_exactCover('1011'[::-1],FR)<0, True) - self.assertEqual(cost_exactCover('1100'[::-1],FR)<0, True) - self.assertEqual(cost_exactCover('1101'[::-1],FR)<0, True) - self.assertEqual(cost_exactCover('1111'[::-1],FR)<0, True) - - def test_is_Soluton(self): - - """ - Test-matrix from - https://github.com/marikasvenssonjeppesen/Extracted-datainstances-for-Tailassignment/blob/master/data_instances/instance_8_0no_feas_sol_1_small_costs.simple - - - """ - - ind = [ [7,1,3,5,6,8,10,13,14,16,18,20,22], - [1,0,2,4,7,9,11,12,15,17,19,21,23], - [5,1,3,5,7,9,11,13,15,16,19,21,23], - [2,1,3,5,6,8,11,13,15,17,19,20,22], - [3,1,3,5,7,9,11,13,15,16,18,20,22], - [8,0,2,4,6,8,10,12,14,16,18,21,23], - [6,1,3,5,6,8,11,12,14,16,18,20,23], - [4,1,3,5,6,8,11,13,15,17,19,21,22]] - - FR = np.zeros((24,8)) - - for i,l in enumerate(ind): - FR[l[1:],l[0] - 1] = 1 - - # Only one solution - self.assertEqual(is_Solution('10000010'[::-1],FR), True) - - # Not solutions - self.assertEqual(is_Solution('10000100'[::-1],FR), False) - self.assertEqual(is_Solution('01000010'[::-1],FR), False) - self.assertEqual(is_Solution('00010010'[::-1],FR), False) - self.assertEqual(is_Solution('00101000'[::-1],FR), False) - self.assertEqual(is_Solution('10010000'[::-1],FR), False) - self.assertEqual(is_Solution('10001000'[::-1],FR), False) - self.assertEqual(is_Solution('10010000'[::-1],FR), False) - -if __name__ == '__main__': - unittest.main() diff --git a/full mixers.ipynb b/full mixers.ipynb deleted file mode 100644 index b24f3db..0000000 --- a/full mixers.ipynb +++ /dev/null @@ -1,2911 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "11322472", - "metadata": {}, - "outputs": [], - "source": [ - "# import sys\n", - "# sys.path.append('../')\n", - "\n", - "# from qiskit_utilities.mixers import *\n", - "from mixers import *" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "8d9ecd99", - "metadata": {}, - "outputs": [], - "source": [ - "from IPython.display import display\n", - "np.set_printoptions(suppress=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "a86347a4", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[31mstandard\u001b[0m\n", - "\u001b[32m1\u001b[0m\n", - "1.0 [1. 1.]\n", - "\u001b[32m2\u001b[0m\n", - "2.0 [1. 1. 1. 1.]\n", - "\u001b[32m3\u001b[0m\n", - "2.9999999999999996 [1. 1. 1. 1. 1. 1. 1. 1.]\n", - "\u001b[32m4\u001b[0m\n", - "4.000000000000002 [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]\n", - "\u001b[32m5\u001b[0m\n", - "5.000000000000003 [-1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1.\n", - " -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1.]\n", - "\u001b[32m6\u001b[0m\n", - "6.000000000000006 [-1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1.\n", - " -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1.\n", - " -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1.\n", - " -1. -1. -1. -1. -1. -1. -1. -1. -1. -1.]\n", - "\u001b[31mnearest_int\u001b[0m\n", - "\u001b[32m1\u001b[0m\n", - "1.0 [1. 1.]\n", - "\u001b[32m2\u001b[0m\n", - "1.6180339887498942 [0.74349607 1.20300191 1.20300191 0.74349607]\n", - "\u001b[32m3\u001b[0m\n", - "1.879385241571817 [0.45602686 0.85705015 1.15470054 1.313077 1.313077 1.15470054\n", - " 0.85705015 0.45602686]\n", - "\u001b[32m4\u001b[0m\n", - "1.9659461993678033 [0.25210226 0.49561948 0.72225897 0.9243028 1.0948706 1.2281539\n", - " 1.3196139 1.36613602 1.36613602 1.3196139 1.2281539 1.0948706\n", - " 0.9243028 0.72225897 0.49561948 0.25210226]\n", - "\u001b[32m5\u001b[0m\n", - "1.9909438451461687 [-0.13237707 -0.2635553 -0.39234674 -0.51758503 -0.63813599 -0.75290789\n", - " -0.86086134 -0.96101869 -1.05247292 -1.13439578 -1.20604538 -1.26677284\n", - " -1.31602822 -1.35336544 -1.37844637 -1.39104388 -1.39104388 -1.37844637\n", - " -1.35336544 -1.31602822 -1.26677284 -1.20604538 -1.13439578 -1.05247292\n", - " -0.96101869 -0.86086134 -0.75290789 -0.63813599 -0.51758503 -0.39234674\n", - " -0.2635553 -0.13237707]\n", - "\u001b[32m6\u001b[0m\n", - "1.9976644536646535 [-0.06779782 -0.13543729 -0.20276045 -0.26961005 -0.33582996 -0.40126552\n", - " -0.46576391 -0.52917449 -0.59134915 -0.6521427 -0.71141313 -0.76902202\n", - " -0.82483483 -0.8787212 -0.93055527 -0.98021599 -1.02758737 -1.07255877\n", - " -1.11502516 -1.15488736 -1.19205226 -1.22643307 -1.25794949 -1.28652792\n", - " -1.31210159 -1.33461079 -1.35400295 -1.37023277 -1.38326234 -1.39306125\n", - " -1.39960659 -1.40288309 -1.40288309 -1.39960659 -1.39306125 -1.38326234\n", - " -1.37023277 -1.35400295 -1.33461079 -1.31210159 -1.28652792 -1.25794949\n", - " -1.22643307 -1.19205226 -1.15488736 -1.11502516 -1.07255877 -1.02758737\n", - " -0.98021599 -0.93055527 -0.8787212 -0.82483483 -0.76902202 -0.71141313\n", - " -0.6521427 -0.59134915 -0.52917449 -0.46576391 -0.40126552 -0.33582996\n", - " -0.26961005 -0.20276045 -0.13543729 -0.06779782]\n", - "\u001b[31mnearest_int_cyclic\u001b[0m\n", - "\u001b[32m1\u001b[0m\n", - "1.0 [1. 1.]\n", - "\u001b[32m2\u001b[0m\n", - "2.0 [1. 1. 1. 1.]\n", - "\u001b[32m3\u001b[0m\n", - "1.9999999999999996 [1. 1. 1. 1. 1. 1. 1. 1.]\n", - "\u001b[32m4\u001b[0m\n", - "1.9999999999999996 [-1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1.]\n", - "\u001b[32m5\u001b[0m\n", - "2.0000000000000004 [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.\n", - " 1. 1. 1. 1. 1. 1. 1. 1.]\n", - "\u001b[32m6\u001b[0m\n", - "1.9999999999999996 [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.\n", - " 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.\n", - " 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]\n", - "\u001b[31mfull\u001b[0m\n", - "\u001b[32m1\u001b[0m\n", - "1.0 [1. 1.]\n", - "\u001b[32m2\u001b[0m\n", - "3.0 [-1. -1. -1. -1.]\n", - "\u001b[32m3\u001b[0m\n", - "6.999999999999999 [1. 1. 1. 1. 1. 1. 1. 1.]\n", - "\u001b[32m4\u001b[0m\n", - "15.0 [-1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1.]\n", - "\u001b[32m5\u001b[0m\n", - "31.00000000000001 [1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.\n", - " 1. 1. 1. 1. 1. 1. 1. 1.]\n", - "\u001b[32m6\u001b[0m\n", - "63.000000000000085 [-1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1.\n", - " -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1.\n", - " -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1.\n", - " -1. -1. -1. -1. -1. -1. -1. -1. -1. -1.]\n" - ] - } - ], - "source": [ - "for mode in [\"standard\", \"nearest_int\", \"nearest_int_cyclic\", \"full\"]:\n", - " print(\"\\x1b[31m\"+mode+\"\\x1b[0m\")\n", - " for n in [1,2,3,4,5,6]:\n", - " print(\"\\x1b[32m\"+str(n)+\"\\x1b[0m\")\n", - " \n", - " T=get_T(2**n,mode)\n", - " l,v=np.linalg.eigh(T)\n", - " print(l[-1],v[:,-1]*np.sqrt(2**n))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d0818dea", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "c5131d92", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[0. 1. 0. 0.]\n", - " [1. 0. 1. 0.]\n", - " [0. 1. 0. 1.]\n", - " [0. 0. 1. 0.]]\n" - ] - }, - { - "data": { - "text/plain": [ - "(array([-1.61803399, -0.61803399, 1.61803399, 0.61803399]),\n", - " array([[ 0.37174803, 0.60150096, -0.37174803, -0.60150096],\n", - " [-0.60150096, -0.37174803, -0.60150096, -0.37174803],\n", - " [ 0.60150096, -0.37174803, -0.60150096, 0.37174803],\n", - " [-0.37174803, 0.60150096, -0.37174803, 0.60150096]]))" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "-1.6180339887498947 [ 0.37174803 -0.60150096 0.60150096 -0.37174803]\n", - "-0.6180339887498947 [ 0.60150096 -0.37174803 -0.37174803 0.60150096]\n", - "0.6180339887498949 [ 0.60150096 0.37174803 -0.37174803 -0.60150096]\n", - "1.618033988749895 [0.37174803 0.60150096 0.60150096 0.37174803]\n" - ] - } - ], - "source": [ - "n=4\n", - "T=get_T(n,'nearest_int')\n", - "print(T)\n", - "display(np.linalg.eig(T))\n", - "for k in reversed(range(1,n+1)):\n", - " val=k*np.pi/(n+1)\n", - " vec=np.sin(val*np.arange(1,n+1))\n", - " print(2*np.cos(val),vec/np.linalg.norm(vec,2))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "fe3d798e", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "76f3da9a", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(array([-2., -0., 0., 2.]),\n", - " array([[-0.5 , -0.70710678, 0. , 0.5 ],\n", - " [ 0.5 , 0. , -0.70710678, 0.5 ],\n", - " [ 0.5 , 0. , 0.70710678, 0.5 ],\n", - " [-0.5 , 0.70710678, 0. , 0.5 ]]))" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "T=get_T(2**2,'standard')\n", - "np.linalg.eigh(T)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0374f492", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "ef209dc1", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0., 1.],\n", - " [1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hamming distance= (2, 0.2)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 1.0 \\sigma_{1}$" - ], - "text/plain": [ - "1.0*sigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (1, 0)\n" - ] - } - ], - "source": [ - "T=get_T(2**1,'nearest_int')\n", - "display(T)\n", - "\n", - "print_info(['0','1'],T)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "c72f0c7e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0., 1., 0., 0.],\n", - " [1., 0., 0., 0.],\n", - " [0., 0., 0., 0.],\n", - " [0., 0., 0., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hamming distance= (2, 0.2)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 \\cdot {1}\\otimes {\\sigma_{1}} + 0.5 {\\sigma_{3}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "0.5*1xsigma1 + 0.5*sigma3xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (1, 2)\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[0., 0., 0., 0.],\n", - " [0., 0., 0., 0.],\n", - " [0., 0., 0., 1.],\n", - " [0., 0., 1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hamming distance= (2, 0.2)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 0.5 \\cdot {1}\\otimes {\\sigma_{1}} - 0.5 {\\sigma_{3}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "0.5*1xsigma1 - 0.5*sigma3xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (1, 2)\n" - ] - } - ], - "source": [ - "T=np.zeros((4,4))\n", - "T[0,1]=1\n", - "T[1,0]=1\n", - "display(T)\n", - "\n", - "H=print_info(['00','01','10','11'],T)\n", - "T=np.zeros((4,4))\n", - "T[3,2]=1\n", - "T[2,3]=1\n", - "display(T)\n", - "\n", - "print_info(['00','01','10','11'],T)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "31202667", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "d0b83076", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[0., 1., 1., 1.],\n", - " [1., 0., 1., 1.],\n", - " [1., 1., 0., 1.],\n", - " [1., 1., 1., 0.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hamming distance= (16, 8.799999999999999)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 1.0 \\cdot {1}\\otimes {\\sigma_{1}} + 1.0 {\\sigma_{1}}\\otimes {1} + 1.0 {\\sigma_{1}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "1.0*1xsigma1 + 1.0*sigma1x1 + 1.0*sigma1xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (2, 2)\n" - ] - } - ], - "source": [ - "T=get_T(2**2,'full')\n", - "display(T)\n", - "\n", - "print_info(['00','01','10','11'],T)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "1e494d16", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[32m3\u001b[0m\n", - "Hamming distance= (24, 24)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 1.0 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "1.0*sigma1xsigma1xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 4)\n", - "\u001b[32m4\u001b[0m\n", - "Hamming distance= (192, 192)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 1.0 \\cdot {{{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 1.0 {{{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 1.0 {{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {\\sigma_{1}} + 1.0 {{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1}$" - ], - "text/plain": [ - "1.0*1xsigma1xsigma1xsigma1 + 1.0*sigma1x1xsigma1xsigma1 + 1.0*sigma1xsigma1x1xsigma1 + 1.0*sigma1xsigma1xsigma1x1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 16)\n", - "\u001b[32m5\u001b[0m\n", - "Hamming distance= (960, 960)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 1.0 \\cdot {{{{1}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 1.0 \\cdot {{{{1}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 1.0 \\cdot {{{{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {\\sigma_{1}} + 1.0 \\cdot {{{{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1} + 1.0 {{{{\\sigma_{1}}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 1.0 {{{{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {\\sigma_{1}} + 1.0 {{{{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1} + 1.0 {{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{1}} + 1.0 {{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 1.0 {{{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {1}$" - ], - "text/plain": [ - "1.0*1x1xsigma1xsigma1xsigma1 + 1.0*1xsigma1x1xsigma1xsigma1 + 1.0*1xsigma1xsigma1x1xsigma1 + 1.0*1xsigma1xsigma1xsigma1x1 + 1.0*sigma1x1x1xsigma1xsigma1 + 1.0*sigma1x1xsigma1x1xsigma1 + 1.0*sigma1x1xsigma1xsigma1x1 + 1.0*sigma1xsigma1x1x1xsigma1 + 1.0*sigma1xsigma1x1xsigma1x1 + 1.0*sigma1xsigma1xsigma1x1x1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (0, 40)\n", - "\n" - ] - } - ], - "source": [ - "for n in [3,4,5]:\n", - " print(\"\\x1b[32m\"+str(n)+\"\\x1b[0m\")\n", - " T=get_T(2**n,mode=\"standard\",d=3)\n", - " #print(\" ---\", T_sum_Hamming_distance(T))\n", - " print_info(all_states(n),T,disp=True)\n", - "print(\"\")" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "a9c1112c", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[31mstandard\u001b[0m\n", - "\u001b[32m1\u001b[0m\n", - "Hamming distance= (2, 0.2)\n", - "#sqg, #cnots= (1, 0)\n", - "\u001b[32m2\u001b[0m\n", - "Hamming distance= (8, 0.7999999999999999)\n", - "#sqg, #cnots= (2, 0)\n", - "\u001b[32m3\u001b[0m\n", - "Hamming distance= (24, 2.400000000000001)\n", - "#sqg, #cnots= (3, 0)\n", - "\u001b[32m4\u001b[0m\n", - "Hamming distance= (64, 6.399999999999993)\n", - "#sqg, #cnots= (4, 0)\n", - "\u001b[32m5\u001b[0m\n", - "Hamming distance= (160, 15.99999999999996)\n", - "#sqg, #cnots= (5, 0)\n", - "\u001b[32m6\u001b[0m\n", - "Hamming distance= (384, 38.400000000000276)\n", - "#sqg, #cnots= (6, 0)\n", - "\n", - "\u001b[31mnearest_int\u001b[0m\n", - "\u001b[32m1\u001b[0m\n", - "Hamming distance= (2, 0.2)\n", - "#sqg, #cnots= (1, 0)\n", - "\u001b[32m2\u001b[0m\n", - "Hamming distance= (8, 4.3999999999999995)\n", - "#sqg, #cnots= (1, 4)\n", - "\u001b[32m3\u001b[0m\n", - "Hamming distance= (22, 14.799999999999997)\n", - "#sqg, #cnots= (1, 20)\n", - "\u001b[32m4\u001b[0m\n", - "Hamming distance= (52, 37.60000000000001)\n", - "#sqg, #cnots= (1, 68)\n", - "\u001b[32m5\u001b[0m\n", - "Hamming distance= (114, 85.19999999999997)\n", - "#sqg, #cnots= (1, 196)\n", - "\u001b[32m6\u001b[0m\n", - "Hamming distance= (240, 182.3999999999998)\n", - "#sqg, #cnots= (1, 516)\n", - "\n", - "\u001b[31mnearest_int_cyclic\u001b[0m\n", - "\u001b[32m1\u001b[0m\n", - "Hamming distance= (2, 0.2)\n", - "#sqg, #cnots= (1, 0)\n", - "\u001b[32m2\u001b[0m\n", - "Hamming distance= (12, 8.4)\n", - "#sqg, #cnots= (1, 2)\n", - "\u001b[32m3\u001b[0m\n", - "Hamming distance= (28, 20.8)\n", - "#sqg, #cnots= (1, 12)\n", - "\u001b[32m4\u001b[0m\n", - "Hamming distance= (60, 45.60000000000001)\n", - "#sqg, #cnots= (1, 44)\n", - "\u001b[32m5\u001b[0m\n", - "Hamming distance= (124, 95.19999999999996)\n", - "#sqg, #cnots= (1, 132)\n", - "\u001b[32m6\u001b[0m\n", - "Hamming distance= (252, 194.39999999999978)\n", - "#sqg, #cnots= (1, 356)\n", - "\n", - "\u001b[31mfull\u001b[0m\n", - "\u001b[32m1\u001b[0m\n", - "Hamming distance= (2, 0.2)\n", - "#sqg, #cnots= (1, 0)\n", - "\u001b[32m2\u001b[0m\n", - "Hamming distance= (16, 8.799999999999999)\n", - "#sqg, #cnots= (2, 2)\n", - "\u001b[32m3\u001b[0m\n", - "Hamming distance= (96, 74.4)\n", - "#sqg, #cnots= (3, 10)\n", - "\u001b[32m4\u001b[0m\n", - "Hamming distance= (512, 454.4000000000005)\n", - "#sqg, #cnots= (4, 34)\n", - "\u001b[32m5\u001b[0m\n", - "Hamming distance= (2560, 2415.9999999999927)\n", - "#sqg, #cnots= (5, 98)\n", - "\u001b[32m6\u001b[0m\n", - "Hamming distance= (12288, 11942.400000000083)\n", - "#sqg, #cnots= (6, 258)\n", - "\n", - "\u001b[31mrandom\u001b[0m\n", - "\u001b[32m1\u001b[0m\n", - "Hamming distance= (2, 0.2)\n", - "#sqg, #cnots= (2, 0)\n", - "\u001b[32m2\u001b[0m\n", - "Hamming distance= (16, 8.799999999999999)\n", - "#sqg, #cnots= (4, 10)\n", - "\u001b[32m3\u001b[0m\n", - "Hamming distance= (96, 74.4)\n", - "#sqg, #cnots= (6, 86)\n", - "\u001b[32m4\u001b[0m\n", - "Hamming distance= (512, 454.4000000000005)\n", - "#sqg, #cnots= (8, 584)\n", - "\u001b[32m5\u001b[0m\n", - "Hamming distance= (2560, 2415.9999999999927)\n", - "#sqg, #cnots= (10, 3210)\n", - "\u001b[32m6\u001b[0m\n", - "Hamming distance= (12288, 11942.400000000083)\n", - "#sqg, #cnots= (12, 17806)\n", - "\n" - ] - } - ], - "source": [ - "for mode in [\"standard\", \"nearest_int\", \"nearest_int_cyclic\", \"full\",\"random\"]:\n", - " print(\"\\x1b[31m\"+mode+\"\\x1b[0m\")\n", - " for n in [1,2,3,4,5,6]:\n", - " print(\"\\x1b[32m\"+str(n)+\"\\x1b[0m\")\n", - " T=get_T(2**n,mode=mode)\n", - " #print(\" ---\", T_sum_Hamming_distance(T))\n", - " print_info(all_states(n),T,disp=False,disp_H=False)\n", - " print(\"\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "362a0823", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "829b0fee", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[1., 1.],\n", - " [1., 1.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "2\n", - "Hamming distance= (2, 0.2)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 1.0 + 1.0 \\sigma_{1}$" - ], - "text/plain": [ - "1.0 + 1.0*sigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (1, 0)\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[1., 1., 1., 1.],\n", - " [1., 1., 1., 1.],\n", - " [1., 1., 1., 1.],\n", - " [1., 1., 1., 1.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "16\n", - "Hamming distance= (16, 8.799999999999999)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 1.0 \\cdot {1}\\otimes {1} + 1.0 \\cdot {1}\\otimes {\\sigma_{1}} + 1.0 {\\sigma_{1}}\\otimes {1} + 1.0 {\\sigma_{1}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "1.0*1x1 + 1.0*1xsigma1 + 1.0*sigma1x1 + 1.0*sigma1xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (2, 2)\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "96\n", - "Hamming distance= (96, 74.4)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 1.0 \\cdot {{1}\\otimes {1}}\\otimes {1} + 1.0 \\cdot {{1}\\otimes {1}}\\otimes {\\sigma_{1}} + 1.0 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {1} + 1.0 \\cdot {{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 1.0 {{\\sigma_{1}}\\otimes {1}}\\otimes {1} + 1.0 {{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{1}} + 1.0 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 1.0 {{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "1.0*1x1x1 + 1.0*1x1xsigma1 + 1.0*1xsigma1x1 + 1.0*1xsigma1xsigma1 + 1.0*sigma1x1x1 + 1.0*sigma1x1xsigma1 + 1.0*sigma1xsigma1x1 + 1.0*sigma1xsigma1xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (3, 10)\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.],\n", - " [1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.]])" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "512\n", - "Hamming distance= (512, 454.4000000000005)\n" - ] - }, - { - "data": { - "text/plain": [ - "'H='" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/latex": [ - "$\\displaystyle 1.0 \\cdot {{{1}\\otimes {1}}\\otimes {1}}\\otimes {1} + 1.0 \\cdot {{{1}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{1}} + 1.0 \\cdot {{{1}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 1.0 \\cdot {{{1}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 1.0 \\cdot {{{1}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {1} + 1.0 \\cdot {{{1}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {\\sigma_{1}} + 1.0 \\cdot {{{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1} + 1.0 \\cdot {{{1}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 1.0 {{{\\sigma_{1}}\\otimes {1}}\\otimes {1}}\\otimes {1} + 1.0 {{{\\sigma_{1}}\\otimes {1}}\\otimes {1}}\\otimes {\\sigma_{1}} + 1.0 {{{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {1} + 1.0 {{{\\sigma_{1}}\\otimes {1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}} + 1.0 {{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {1} + 1.0 {{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {1}}\\otimes {\\sigma_{1}} + 1.0 {{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {1} + 1.0 {{{\\sigma_{1}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}}\\otimes {\\sigma_{1}}$" - ], - "text/plain": [ - "1.0*1x1x1x1 + 1.0*1x1x1xsigma1 + 1.0*1x1xsigma1x1 + 1.0*1x1xsigma1xsigma1 + 1.0*1xsigma1x1x1 + 1.0*1xsigma1x1xsigma1 + 1.0*1xsigma1xsigma1x1 + 1.0*1xsigma1xsigma1xsigma1 + 1.0*sigma1x1x1x1 + 1.0*sigma1x1x1xsigma1 + 1.0*sigma1x1xsigma1x1 + 1.0*sigma1x1xsigma1xsigma1 + 1.0*sigma1xsigma1x1x1 + 1.0*sigma1xsigma1x1xsigma1 + 1.0*sigma1xsigma1xsigma1x1 + 1.0*sigma1xsigma1xsigma1xsigma1" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "#sqg, #cnots= (4, 34)\n" - ] - } - ], - "source": [ - "import math\n", - "def possibilities_full(n):\n", - " val=0\n", - " for i in range(n+1):\n", - " val+=i*math.comb(n,i)\n", - " return val\n", - "for n in [1,2,3,4]:\n", - " T=np.ones((2**n,2**n))\n", - " display(T)\n", - "\n", - " print(2**n*possibilities_full(n))\n", - " print_info(all_states(n),T)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "d4611550", - "metadata": {}, - "outputs": [], - "source": [ - "import tikzplotlib" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "e2aeaecc", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as pl\n", - "fig=pl.figure(figsize=(12, 12), dpi=200)\n", - "pl.imshow(1-get_T(2**4,mode='standard',d=1), cmap=pl.cm.gray)\n", - "# tikzplotlib.clean_figure(dpi=1000)\n", - "tikzplotlib.save(\"Tn4_d1.tex\",dpi=1000)\n", - "fig=pl.figure(figsize=(12, 12), dpi=200)\n", - "pl.imshow(1-get_T(2**4,mode='standard',d=2), cmap=pl.cm.gray)\n", - "tikzplotlib.save(\"Tn4_d2.tex\")\n", - "fig=pl.figure(figsize=(12, 12), dpi=200)\n", - "pl.imshow(1-get_T(2**8,mode='standard',d=1), cmap=pl.cm.gray)\n", - "tikzplotlib.save(\"Tn8_d1.tex\")\n", - "fig=pl.figure(figsize=(12, 12), dpi=200)\n", - "pl.imshow(1-get_T(2**8,mode='standard',d=4), cmap=pl.cm.gray)\n", - "tikzplotlib.save(\"Tn8_d4.tex\")\n", - "# pl.xticks([0,2**7,2**8-1],[\"{0:b}\".format(0).zfill(8),\"{0:b}\".format(2**7).zfill(8),\"{0:b}\".format(2**8-1).zfill(8)])\n", - "# pl.yticks([0,2**7,2**8-1],[\"{0:b}\".format(0).zfill(8),\"{0:b}\".format(2**7).zfill(8),\"{0:b}\".format(2**8-1).zfill(8)])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6426c65d", - "metadata": { - "scrolled": false - }, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "2566119c", - "metadata": {}, - "outputs": [], - "source": [ - "def getT_test(n,wrap=True):\n", - " T=np.zeros((2**n,2**n))\n", - " for i in range(2**n-1):\n", - " T[i,i+1]=1\n", - " T[i+1,i]=1\n", - " if wrap:\n", - " T[0,-1]=1\n", - " T[-1,0]=1\n", - " return T" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "1cc5a5ca", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": "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\n", - 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as pl\n", - "T={}\n", - "TF=getT_test(3,False)\n", - "for k in range(9):\n", - " T[k] = 1-(np.linalg.matrix_power(TF,k)>0)\n", - "\n", - "TS=0*TF\n", - "for k in range(9):\n", - " fig=pl.figure()#figsize=(12, 12), dpi=200)\n", - " TS+=np.abs(np.linalg.matrix_power(TF,k))\n", - " pl.imshow(1-(TS>0), cmap=pl.cm.gray)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "acfc2c8f", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "4bc78438", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(array([[0., 1., 0.],\n", - " [1., 0., 0.],\n", - " [0., 0., 0.]]),\n", - " array([[0., 0., 0.],\n", - " [0., 0., 1.],\n", - " [0., 1., 0.]]))" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "T12=np.zeros((3,3))\n", - "T12[0,1]=1\n", - "T12[1,0]=1\n", - "T23=np.zeros((3,3))\n", - "T23[1,2]=1\n", - "T23[2,1]=1\n", - "T12,T23" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "055cd64a", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(array([[0., 0., 1.],\n", - " [0., 0., 0.],\n", - " [0., 0., 0.]]),\n", - " array([[0., 1., 0.],\n", - " [0., 0., 0.],\n", - " [0., 0., 0.]]),\n", - " array([[0., 0., 1.],\n", - " [0., 0., 0.],\n", - " [0., 0., 0.]]))" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "T23_2=np.matmul(T23,T23)\n", - "T12_2=np.matmul(T12,T12)\n", - "T23_3=np.matmul(T23_2,T23)\n", - "T12_3=np.matmul(T12_2,T12)\n", - "np.matmul(T12,T23), np.matmul(T12,T23_2),np.matmul(T12,T23_3)" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "a3786ae5", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(array([[0., 0., 0.],\n", - " [0., 0., 1.],\n", - " [0., 0., 0.]]),\n", - " array([[0., 0., 1.],\n", - " [0., 0., 0.],\n", - " [0., 0., 0.]]))" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.matmul(T12_2,T23), np.matmul(T12_3,T23)" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "b27d7789", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(array([[0., 0., 0.],\n", - " [0., 1., 0.],\n", - " [0., 0., 0.]]),\n", - " array([[0., 0., 0.],\n", - " [0., 0., 1.],\n", - " [0., 0., 0.]]),\n", - " array([[0., 1., 0.],\n", - " [0., 0., 0.],\n", - " [0., 0., 0.]]),\n", - " array([[0., 0., 1.],\n", - " [0., 0., 0.],\n", - " [0., 0., 0.]]))" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "np.matmul(T12_2,T23_2),np.matmul(T12_2,T23_3), np.matmul(T12_3,T23_2),np.matmul(T12_3,T23_3)" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "df80bfd0", - "metadata": {}, - "outputs": [], - "source": [ - "from scipy.linalg import expm" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "cf8b39ba", - "metadata": {}, - "outputs": [], - "source": [ - "pl.rcParams.update({'font.size': 22})\n", - "\n", - "samp=200\n", - "t=np.linspace(0,4*np.pi,samp)\n", - "\n", - "T={}\n", - "ov0={}\n", - "ov1={}\n", - "ov2={}\n", - "ov3={}\n", - "for i in range(0,3):\n", - " for j in range(0,3):\n", - " ov0[str(i)+\"<->\"+str(j)]=np.zeros_like(t)\n", - " ov1[str(i)+\"<->\"+str(j)]=np.zeros_like(t)\n", - " ov2[str(i)+\"<->\"+str(j)]=np.zeros_like(t)\n", - " ov3[str(i)+\"<->\"+str(j)]=np.zeros_like(t)\n", - " for s in range(samp):\n", - " eT0=np.matmul(expm(-1j*t[s]*T23),expm(-1j*t[s]*T12))\n", - " eT1=np.matmul(expm(-1j*t[s]*T12),expm(-1j*t[s]*T23))\n", - " eT2=np.matmul(eT1,expm(-1j*t[s]*T12))\n", - " eT3=np.matmul(eT2,expm(-1j*t[s]*T23))\n", - " ov0[str(i)+\"<->\"+str(j)][s]=np.abs(eT0[i,j])**2\n", - " ov1[str(i)+\"<->\"+str(j)][s]=np.abs(eT1[i,j])**2\n", - " ov2[str(i)+\"<->\"+str(j)][s]=np.abs(eT2[i,j])**2\n", - " ov3[str(i)+\"<->\"+str(j)][s]=np.abs(eT3[i,j])**2" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "f5acdcc5", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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95Xl2G+G2PS14enixor28nhxaRH2NA4f9jVueR0R43f42PD28hEgFx4j86uI87DbCKwebdbunFIcNuGNvK565vFSxLofz4QQuzIZxZ4GjlFcNNuPs9CqWIpWZoyqdzeH4WBA3D/gKOv/mAR+Woilcmotsf7IFYYzhyeFFvGJXM+y27dNj3LmvFalsDs9rlENIBH55YQFHe7xocFXpdk8pDhtwx94WpDI5PDu6ZHRRDOH4mJIo7sb+wqIvb92tjGaeGqnM+nopsIxYKotbChQHft4zI5VpbY0uRjG1HMetBY6Cr+/xwmEjPD9ameKwGEni3MwqbtdpIZojxWEDjvZ6YbdRxWbTfG40CFeVHdd0NRR0/mF/I+prHHhyqDKn4p5RRfGmAsWhu8kNv9eFZy5Xppg+OayI4qt2FyYOLqcdh/wNeK5CxYEP1m4e0C5VxkZIcdiA2moH9nd4Klocru9tRFWBXhF2G+GmAR+eH6vM+nrm8hL2tXvQVLv1+sx6bh7w4dnRIHIVmMvrudEgOhtq0Ovben1mPTf2NeGlwAoS6cqb6n1hIgSn3VbwYK1cSHHYhKM9XpyaXEamwvz3V+JpnJ9dLTqh1/U9XowuRhGKpjQqmTlJZXI4MR7CLbsKsxo4twz4sBxL48KspnklTcnJiWUc6fUWlY77hr4mpLI5nJpc1q5gJuXEeAiH/A0bRt1riRSHTTja14RYKltxjfeF8RAYK3y9gXOdGshUaY334mwYiXQOR3u9RX2On19p9TUfTmBqOb5l4NtG3NDXBCJU3LpDIp3F6cAKjhX5fJUDKQ6bwBtvpU0tHR8PwmEjHOku7mE87G+AjRR/7ErixcAyAODabVwy8+n1udHgqsJL6ucrhVMTywCAIz2NRX2uwV2FvW0ePF9h7fHs9ApS2Ryul+JgHjobatBeX4PjFfYwvhRYwZ42z6YpMzajttqBve31ODlRafW1jKZaJ/zezZILbwwR4bC/oeKSFp6cXIbDRjjYWfz8+WF/A85MrVRUfAhfjL6+R4qDaSAiXN/biFOTldPZMcZwZmoFh3a48HVddyNenFyuqEXWFydXcNjfsKPtLK/1N+LSXLii4mlOTSxjf0c9aqqKnz8/1NWAYDSF6ZXKybN0anIZPU1utHiqdb+3FIctONjZgMlgHCvxysgnP7UcRyiWxjX+nYnDkZ5GrCYyuFwhealiqQyG5sPbRvluxrXdjcjmGM5OV4b1kM0xvBRYLnpKicO9dU5XkLV1dnoV13TVG3JvKQ5bcLBT+VLOTVfG3tJnppRGV4rlAACnp5bLVCJzc2ZqFTkGXLtDMeWfq5SppcsLEURT2R2L6f6OethttPacWp3VRBoTwdiOpuDKgRSHLeBfSqWM7E5PrcBuI+xr92x/8gYMNNfC6bDh/ExleHjxxeSddnat9cq6VqUsSp+bUQZZBzp2NhKuqbJjsLUOpytEHPig9ECntBxMR4unGq2e6oqxHE5PrWKwtW5H88GAslfynrY6nJ+pjPo6O72K9vqakuaDD6mLrJXA+ZkwquyE3a11O77GNV2Vsyh9Vu13DkpxMCcHO+vXviQrU+piNGd/ez3OTa9WROM9P7OK/R07s7I4+9s9GF2MVkTk7/mZVexu9cDp2Hm3c6irAUvRFGYqYFH67PSKOkDVfkvQjZDisA0HOxswvBCxfOOdW00iGE2VHKJ/oLMeS9EUFsLWztCayuQwshDB3vbSRnV72+uRY8DwvPUztJZDTPnibCUM2M5NrxpmNQBSHLblYGc9sjmGixaPlL44p/x/e3e43sDZr84nn7P41NLlxQjSWVZyZ7dP/bzVI/EXI0nMh5M7Xm/g7GlT6uvSnLXrK5HOYmg+IsXBzPDFIKvPo19SOyfe+HbK/vbKEAc+WNhXouXQ56tFtcOGCxavr/MlLkZzPDVV6Gp0WV4chucjyOYYDnQY46kESHHYlm6vGzVVNstvzHJxLowWT3VRmUU3osGtNF6reyzxxdWBltqSrmO3Efa0edYsN6vCxWF/ieIAAHva6ixvyXPx29O288X7UpHisA02m+JdMTRv7Yfx4mwYe0u0Gjj7OzyWHwlfmF3Frpa6gtOab8Xedo/lxfTCTBjt9TXwljj4AIA97R6MLESQtnDG5KH5CKrshL7m0gYfpSDFoQD2tHowZGHLIZtjGJoPl7zewBlsUzxwrNx4L8yEyzIKBoB97R4sRpJYtPA2q0PzEQyWaRS8r92DdJZhzMKR+ENzYfQ315Zl8LFTpDgUwGCbB7OrCcum0ZgMxpBI58pmOQy21iGTYxhfsmbjXYmlMbuaKJuYcpGx6lRJLscwPB/BYGt56ouvi1l5Ku7SXASDZWqPO0WKQwHweb9hi04t8Ua2p0ydHQ9ysqp7Jp9iLNd88KBaX0MW7eymluOIp7MlBb+tZ1dLHWx0xYnCasRTWUyGYthTJjHdKVIcCuCK+5w1OzveyAbL2HgBWHYqbmRB+b/4/1kqLZ5qeKodGFmwpqU1rNZXuaaVaqrs6Guutaz77/B8BIwZuxgNSHEoiK5GF1xVdsu6zw3NR9DV6EJttaMs16utdqCr0YUhi1oOw/MROB02+L2F74G8FUSEXa11lrW0htVBwu4yiSmgrANy0bEavJ+R00oCYLMRBtvqLDsSvrwYwa4yWQ2c3Rbu7EYWohhoroXdVvweDpuxu7VuzSKxGkPzYTTXOcviqcQZaKnFxFLMkk4Pl+bDcNpt6POVZ/CxU6Q4FIhV3VlzOYaR+Sh2leivn8+g2tllLbjxz/B8+cV0V0sd5sNJrCas5/QwNB8p23oDZ1eL4vQwEYyV9bpmYGQ+gv7mWjgM9FQCpDgUzK6WOsytJhFNZowuSlmZXU0gns6Wbf6cM9hWh2Qmh0DIWo03kVYWC8s5RQJcWcQfsZi1xRjD8Fz5PJU4uyxaXwBweSFacnBlOZDiUCADajDKqMV8qy+ri6Dlfhh3t1pzUXp0MQrGoIHloNS/1abi5sNJhJOZslsO/Hm12q6D6WwOE8GYFAeRGFBHilZ7GPk8d7lHwtwSsZqY8s673PXV0+SG026znMdSuT27OPU1VWjxVFvOcpgMxpDJMQw0G+upBEhxKJhenxtEylaHVuLyQgR11Y6yb2De6HbC666ypJgSld/Sctht6Gt2W85y4IODfg1GwgPNtZZ7vrglr0V9FYsUhwKpqbKjq9G19uVZhZEFZTGaqHyeN5z+5lqMLlqrsxtZiKKr0bXj3fK2YqC5znKDj9GFKKodNnTUl3/Dml0W9PC6rLaXXdJyEIuBljrLTZNcXoisTZmVm/5m69XX2GIU/RolQ+trrsVkKGYpD6+xJaW+bGV0++UMNNdiOZZGMJoq+7WNYnQxCl+tEw3uKqOLIsWhGAaaa3F5IWKZLTBjqQymVxJld2Pl9De7LeXhxRjTVhx8bqSzDNPLcU2ubwSXF6Po82lTX7ssmKZlZEG756tYpDgUwUBLLaKpLOYtsgXm2KLiZqpVWuB+1TQes0gCvqVoCuFkRrPOrle97viSNdx/M9kcJpZims2f96v1ZZXnCzCPGysgxaEouAeBVdYdeKPSqrPrt5j7L08RrdXIrleNiLVKZze1HEcmxzSrry6vC3YbYcIiYrqaSGMxktRsmrdYpDgUQf+ab7U1zNg1cdBsDl3p7EYtIqZc5LSqr/b6GjgdNstE/XJPogGN6qvKbkNXowvjFqkvrQcfxSLFoQg66mvgtNssM1IZX4yhua4adWVKuJeP2+lAR0ONdSyHpSjsNoLf69Lk+jYbobfJbZlNbPigQMvOrtfnxoRFLK0xtV/RypIvFikORWCzEfxNLsuM7EaXopon9+rzWccXfWwxhm6vS9PduXp9tZZZcxhdjMJT4yh5X/Kt6Glyr3WqojOp9ivdTdoMPopFikOR9Da5LdN4x5eimu9R29dca5k59MuLOtSXz43xYBQ5C7izcjdWLWJoOL0+N1biaazExE9YOL4URYunGm6nNpZ8sUhxKJJeXy0mgjHh3VljqQzmVpOaWw69PjeWY2nhs40ypmx7qrXJ3+tzI5HOWcIjbjIYQ0+T1s+X6uEVFH8AMr4UQ6/G9VUMUhyKpLvJjUgyg5DgIxVu/fRq3NnxzmFS8Km4+XASsVRW88XCK+6sYnd22RxDIBTXQRyU61vBmtdDTItBikORcGUXvfHy8mvd2VlFHHj5e3RYowHE7+ymVTdWrTu7Hou0x2Qmi5nVhObPVzFIcSgSPlIRfVF6dFGfzq67yRoju0l1X4ruMm0NuhmdjTVw2Ej4dZo1MdVYHNxOJWmk8M9XMA7GrvQvZkCKQ5Hwzk50d9bxJSWHS32NtjlcGlxVaHBVCS+mgaCS0kIrN1aOw25DtwWcHiZ0srQA1UlE8OdLLzEtBikORVJTZUdbfbX4D2MotiZ0WtPrc4svDqE4muuqNcnGmo/inim25TARjMFhI3Q0aO+W2eurtcRgDQB6mswR4wBIcdgRvU3iP4yBUFzzUTCnu8kt/ppDKKab/3mfz42JJbE94iaCMfjV9BZa0+tzY3Y1gUQ6q/m9tGI8GIPbaUdznXYxIcUixWEHdDe5hXady+aUzJ9+jefPOT1NbgRCcaFTUStiqpelVYtwMiN0KuqJoL6WKb+nqEwsKZ5KWsaEFIsUhx3Q61NSUYs6UpkPJ5DOMt1Gwj1NbmRyDDMrYqaiviKmOlkOzTwBn8CdnY5umT0WcHrQs74KRYrDDuAjFVGnSibXFlf1bbyiTsXNriaQyTHNPZU4osc6rMTTWI6ldevs+gSvr1yOYSIYM5WnEiDFYUeI7p4ZUN0y9RoJr4mDoGIaCOpbX36vC0TiWg580KRXZ9foroKnxiHs8zUfTiKZyUnLwQr0it7ZhRTLoatRn86uo0Hx3Re9vvSaQ6922NHZ4BI22+iVBHL61BcRodcnbgK+K26/5vFUAqQ47IimWifqqsUdqQRCMbR69HHLBBTf/S6vuNlseQBcZ2ONbvfsaxa3sxvXWRwA7kEoppjy6TAz5VUCpDjsCCJSA5XEfBgng/otrnJ6BHZnDYTiaKuvRrVDHzEFFH93UcV0IhiD112leYDlenp8ikdcJpvT7Z7lYiIYg42ATp0s+UKR4rBDepvEDewKLMd0W4zmdItcX6GYbovRnO4mF4LRFKLJjK73LQdGJJDr83GPuISu9y0HE8EYOhtdcDrM1R2bqzQC0etzYzIUFy7vfiabw8xyQvcNRXqb3AgJmrrbCEuLizdf7xCJiWBM9/lzHlksopPI+JL5PJUAKQ47prvJjVQmh9lVsUYqc+EkMjmmu+UgqjtrJqt8x3rXFxcj7lkmCplsDlOhOHp0HnzwHE4iBqeaMcYBkOKwY0SNypzU2S2TwxcnRVt3mFlJIJvTL2CQw6exRKwvPVJ159Ner3jETQlmaYUTaQSjKVPlVOJIcdghveqXKdpImE9T6G45iCqmazEh+tZXc50TNVU24aaVJgzwVAIAu43Q2egStr7ktJKF6GysgV1A3/1AKAYifd0yAaC+pgqNbvFSd18RU30tByKC3+sWtrMzYpqkq9El3DQcz1agt8NDIUhx2CEOuw3t9TWYWhar8QZCcbR5anR1y+SI6OEVUN0M9Ug9nY/f61qzXERhIhhDlV2fVN35+L3iWQ5czPSetiwEKQ4l0OUVcaQS030UzBHRnTUQiqO9vsYQN0MRO7uJJcVNWo9U3fn4vW41FYU4CTEDoTjqqh1ocOkXE1IoUhxKQMTGq+c+Dvl0N7kxJVjqbj1TdefT7XVjJS6W++9kyLjBB7/v9LI4HoS8PZopVTdHikMJ+L1uzK0mkMqIEZXJ3TL1XizkdHuVQKU5gdx/J0Mx+A0y+ddiHYLiDECmDBRTEd1/AwaK6XZIcSgBv9eFHANmBYnK5G6ZRo/sRHHP5HEshlkOTWJ1drFUBkvRlHHPV5NYgYOMMUPFdDukOJSAaCMVo9wyOVfqS4zGO7MSB2P6eypx+Pc0KUh9TRnk2cVp81TDYSNh2uNqPINwMiMtByvibxRrpGKUWyanSzBxMNrN0OuuQq3TLkxnF1g29vly2G3oaKwR5/nSeV+VYpHiUALtDTWwkTiWQyAUN8wtE1D2KWirrxaovoxtvDzWYVKQNQejAizX428UJzbEDPW1FVIcSsDpUGIdAoLEOgRCMcPcMjl+r1sY3/1AKA67jdDRoG/A4Hr8ArlLB0IxOO02tNRVG1YG0eoLkJaDZREpitVIt0yOSO6/k6GYsoud3bhmwt1/GTO/++9UKI7OxhrYDIhx4CgehGLEOpg5xgGQ4lAyfq9LmGRfAQMD4DjdXreSnE2ATVmMjAnh+L0uhJMZrMTNH+tglsEHIEasg5ljHAApDiXT5XVhZiWOtMk7uzW3TINTA/u9LmQF2ZTFiE1+8hFpX4dAKK7bvuSbIZIHoZljHAApDiUjSqzD7EoCOQPdMjmidHaJdBZzq0nTjITNHhuSSGexGEka/3wJEutg9hgHQIpDyYjS2Zll8UuUwK5pg90yOd2CPF88AaVR0eScNk817ALs62D2GAdAikPJiGLGcg8ho6dJOhpcIDJ/Z8fLZ1SqEU6DuwqeGofpny9eX12NxtaXw25DR0ON6evL7DEOgBSHkhGpszPaLRO44v5rdndWMzVexf3X3M+X0dHR6xHBI87sMQ6AFIeScTpsaPOYPyqTp5420i2T0y2A+28gFEeVndBWb6yYAkC3AL77gVAMDps56ksE93KzTPNuhfE9hQXwe12YWjZ/4zXLgyiC++9kMIbORpch+xLkw6OkzRzrEAjF0aHujmg0fq8Lc+GEqWMdzB7jAEhxKAsimLGTwbjh8+ccvwDuv2aIceD4vS7E01mEYuaNdQiEYmu5xozG73WDMWDGxLEOZo9xAKQ4lAW/yQO7kpks5sIJ83R2TW7kRGi8punszO/0MLVsLjEFzL0OaCZLfjOkOJSBLjWwa9akm9jMLCfU1NOysyuEeErx2TfLvr5md5dOZswRE8Ix+/MFGLspUqFIcSgD/GE06zy60am68+le26fAnI2Xrx+ZpfF2mbyz46kqukzyfLXXK2sfZhXTlXja9DEOwA7EgYjeTURPENEKEUWI6DgR3U9ERV2LiL5ORGyLnwvFls0ozD6yW4txMMmaw5VU52atL3OJaYOrCvU1DtPWl5ncWAHzxzqI4KkEAI5iTiaiLwD4MIAEgMcApAG8BsDnAbyGiO5ljBXrIvAUgOENXp8p8jqG0dmouO+ZtfGuuRl6jEulvJ4quw0dDeZdxA8EzSWmgLndM83Y2ZnZScQsAYPbUbA4ENHboAjDLIDbGGND6uttAH4J4K0APgLgc0WW4SuMsa8X+RlTYfZNbLiboRliHDhmzrsfCMXhdBi7L0E+fq8LY0tRo4uxITzAst0EMQ4cv9eNJ4cWjS7GhphtmncziuktPqEeP8aFAQAYY3MA7lP//Hix00tWoavR3CMVs3jecMy8w5lSXy5D9yXIh1sOZox1mFo2T4Alh8c6pDLm8yAMhGKoddrR6DZvjANQoDgQkR/AUQApAN/Nf58x9jiAKQDtAG4uZwFFwe91ryUfMxuTwZhpPG843U3mDVSaDMVMs7jK8XtdiKXMGetgRrfMrkaXEuuwYr42yfe9MHOMA1C45XBEPZ5ljG1W28/nnVsodxLRZ4joy0T0V0R0l4jWh9/rwvRyHNmcuUZ2iXQW82HzuBlyzByoZIZNa/Ixs3tmIBQ3oZia10nETAGWW1HomkO/ehzf4pyJvHML5X0bvHaOiN7FGDtd5LUMw+91I5NjmFtNoNPgDU/WY5bU0/ms7VMQiqGvudbg0lwhmswgGE2ZztJa39kd9jcaW5h1pDI5zK0mpJgWQSAUw419XqOLsS2FjtDr1ONWK2IR9egp8JqnAHwUwEH1+p0A7gbwIoADAH5BRF2bfZiIPqi60R5fWFgo8JbaYdaoTLNmf+w26aYsZq0vs8Y6mGUTqXw6GswZ67ASTyOcyJju+dqIQsWBT46Vbc6EMfa/GGP/wBg7xxiLMsZmGGMPA7gRwG8AtOLKIvhGn/8yY+wYY+xYS0tLuYq1Y8zaeK/EOJir8bZ5quGwkenqy4xumYB5Yx3W6stE1jKgxDq015svWzKPCTHbNNxGFCoOYfVYt8U5/L3wFudsC2MsBeAB9c83lnItPeF755otSpqnnm71mMfNEFADlRrN13jXNvkx4cjOjLEOgWVzWlqAOd2lzTr42IhCxWFMPfZucU533rmlwKOjN51WMhs1VXa0eKrN13hDcdOkns6n2+s23d7Ik8EYqh02NNc5jS7KVZizs4vDRkrUu9kwo7u0WactN6JQcTipHg8S0WaSd0PeuaXgU4+RLc8yGX6vCwGT7esQCMVMOQoGzBnFauZUymaMdQiEYmirr4HTYT4HQzPGOgRCcbiddnhNHuMAFCgOjLFJAC8AcAK4N/99IrodgB9K9PQzZSjXO9Tj81ueZTLMaPZPBs3rNuf3ujEfTiKRNk+sQ2A5Zqq0GesxY6zDlIndMv1e88U68JgQMw4+8ilG7vk6wKeJaDd/kYhaAXxR/fNTjLHcuvceIKILRPTAuuuAiK4joruJyJ73uoOI/hiKFxMAfLaI8hlOV6MS65AzSaxDIq2knjZz4wVgquBBc4up+ZwezBgTwjFjrIOy74U56yufgsWBMfY9AF+CEgV9mogeIqLvAxiC4nr6QygJ+NbTAWCvelxPH4CHAMwT0TNE9F0i+jmUOIq/V8/5GGPskeL+HWPxe11IZxnmwuYI7DL7/KbZ3FlXE2msxNOmrS+zdXaZbA6zq4k1ZwyzYVYxNWt95VNUVlbG2IeJ6EkA9wO4HYAdyuLx1wB8ab3VsA0vQknQdyOURe4jUNxkAwD+EcAXGGMniimbGVi/r0NHg/EPQMCkbqwcszXeQNC8nkqA+dylZ1cTyOaYaS0tnhreLB6EVwYf5qyvfIoSBwBgjH0LwLcKPPf9AN6/weujAP6w2HubnfUju2N9xpYFWL8vgTk7u1ZPDarsZBqPErO7GZot1sHslqnZUsNPmby+8jGfi4HArKWEMIl7ZiAUg9NurtTT67HbSM1ma5b6MmeqkfWYyekhIEBAV5eJPOJEeL7WI8WhjNRU2dFcZ55YB54QzUypp/MxU2c3GYrB7bSjqdZ8MQ4cM8U6BEIxEF3Z7MqMmK2+ACkOFUt3k3liHUTI/mimWAczxzhwzBTrMBmMo81Tg2qHffuTDcLvdWN21RyxDlOhOFxV5h58rEeKQ5kx00g4EIyZfn6zu8mNxUgS8ZTxsQ6BUNy0i9EcM8U6BELm2yckH7/XhRxTEgQaDbfkzTz4WI8UhzJjln0dYqkMlqIpISwHAJgy2NpijKliKkZ9mWGqxMwxDhxT1dey+Z+v9UhxKDM81mHe4FiHKUEWv67s62CstbUazyCcNH8qZbPEOvAYB7M/X90mqS9eBrPX13qkOJQZszTeteyiJk0FwVlrvAZ7eJk1tXk+Zol1mFkxd4wDh8c6GF1fkWQGyzHzBlhuhBSHMmMWM3ZSEM+I5rpqOB02E4gpry9zN16zxDqsianJ66uK7+tgcIoWUSz59UhxKDM8ND5gcGBXIBRHtcO8MQ4cm43gbzTeY0kkH3QzOD2YPQBuPeaoLzEGH+uR4lBmzLKvQyAUE8YzosvrWhuJGkUgFIen2oEGl/lTKZvBdz8QjJl2H4d8/F6X4Sk0RBp8cKQ4aIAZ9nUQwS2T091k/MhuMiiOmJoh1iEQiqPdpPs45OP3ujCzEkc6a1ysQyAUQ02VDT5BYhwAKQ6aYAYzdlIAt0yO3+tCMJpCNJkxrAwiuGVyzBDrEAjF4Te5swPH73UbHuvAs7GKMPjgSHHQAKNjHSLJDEICeUbwchq1rwNjTIiALo4ZnB4mQ2INPgAYOnUp0uCDI8VBA4yOdZhac2MVo/F2G5ywMBRLI5rKCtN4jXaXTmV4jIOsr0JRNvkRoz1ypDhoAH8YjUpFLZpnhNGNV7SEaEbHOsysxMHYFVE3O+0NNSAy7vmKJjMIRlPCtEeOFAcNMNrs5yNwUTq75jonaqpsBtaXWJ4kRsc6iOTGCgBOhxrrYNDzxadLRXm+OFIcNGAt1sHAxuuqsgvjGUFE8HvdhllafC66R5AFVsBYpwfRBh+Ase6sXJTMvO/FRkhx0IArsQ7GjFRESD2dj5HuvxPBGJpqnfDUmD/GgWNkrEMgFIfdRugQIMaBY6SYihjjAEhx0IxuA/cpmFQD4ETCyH0dJoMx0+egysfIWIdAKIaOhho47OJ0H0bGOoiSrSAfcb5dwTBqpMIYw0Qwhl7BOrturxvLsTTCCf199yeCMaGmlABjYx0mBcsuCiiBljkGTBvgLj0l2D4OHCkOGmFUrMNKPI1wIiPkSBjQf50mk81hKhRHjyBuvxwjnR4CIfNvIpUPF/8JA9ylRawvQIqDZvi9bmRyDLOr+sY6jC8pD3+vr1bX+5bKlc5OX3GYWUkgk2MCWg7GiGkyk8XcalKY1CycXp9SXt4+9GRSjY4WDSkOGsE7m/GlqK735SMj8To7Y0bC3PNGNEvLqFiH6WVlsCPatFKbpwZOu033QMtwIo1gNLUmTiIhxUEj+MOg98M4sdbZidV4m2qdcDvturuziiqmRsU6iOjGCqip4Ztcuk8rrVnygj1fgBQHzehoqIHDRrqbsRNLMbR4quF2OnS9b6kosQ76u2dOBGNw2AgdDWJ1doAxTg9rm0gJ2Nn1Nrl1b49cTHuk5SDhOOw2+L0ujBtgOYg2CuYY0dlNqNlr7TaxPEkAY2IdJpZicDps6KgXJ8aB09PkxmQwpqv777iglikgxUFTeny1mNDbchDQjZXTbcCmPyLGOHCMiHUYW4qi2+uCTUAx7fHVIqxmLNaL8SXxAiw5Uhw0pKfJpeuCdCqTw/RKXOjOLpzIYCWuX+MV29JSYh2Woind7jm+FEOfYJ5wHCPcWSeCUWGfLykOGtLbVIvVRAbLMX0abyAUA2NimrCA/h5Lq4k0QrG0sPXV16yveyYPsBRx/hwwRhzGl2JCeioBUhw0pUdn32r+0Iv6MHKLR691h0mB54OBK7EselmnC5EkYqmssNOWa+KgU32lMjlML8eFrS8pDhqyFnij00hFVLdMztqOXTrVl6gxDhy/1wUbAWN6DT64W2azmNNKLqeSEFMvy2FqOY4cU9Y6RESKg4boPVKZWFI2MW/xiJXgi9PgqkJdtX6++xMCuxkCQLXDjs5G/da1xgT22ef0Nrl1Ewf+vYhqyUtx0BC306HrSIUvroqW4ItzJdZBP3FodFehXkBPEk6fr1ZHyyEKG4mzyc9G9DS5dfMgXJvmFVRMpThojJ6BNyJ73nAU90y96isufH31+ty6Wg6djS44HeJ2G91NbsysJpDMZDW/1/hSDC51bxcREfdbFoQenz5m7JonSZOY85scbjno4bsvcowDp89Xi+VYWhePuPGguG6snF6fG4zp4/QwviS2JS/FQWN6m2oxu5pAIq3tSGUxkkIslRUu9XQ+fq8LkWQGyxoHKmVzDIFQTLjsovn0NXOPJe0HIONLUWHXZzh6urNOBMWuLykOGnNlpKLtw3jFjVX0kZ3a2WnceGdXE0hnxUvVnU+f2vmMaTy1tBJPYzmWXrufqPTolBBT1E231iPFQWP0inWYCCqdg+jTJP1qYNfYoradHV+UFF0cupvcINLh+VqrL7EHHy111aipsmleX/PhJBLpnLQcJJtzZV8HrRtvHETipVLOx+9VOjutR8KiB8Bxaqrs6Kiv0VxM+ffBo7JFhYgUjyWNLYdxCww+pDhojK/WiVqnXfOHcSIYQ3t9DWqq7JreR2tqquzobHBp3tmNLkVRZSd0NoqXXTSfXl+t5mIqeoDlenqatE+IaYVpXikOGkNE6PHVau5uOBGMCj+lxOlvrsWoxo13dEGpL4dd/CbQ16y9u/TYYlTIfUI2glsOWnrE8ZgQEbcH5YjfMgRAj6jM8SWxF7/Wo4fv/thSFAOCpoHIp9dXi6VoCqsJ7Ty8FDdW6zxf8XQWC+GkZvcYD4ofEyJuyQWi1+fGZCiOXE6bkUo4kcZ8OIn+Fmt0dv3N2vru53IMY0tR4X32ObzT1nKqZHwpKvxiNKdfHRRc1nDqUuRsrBwpDjrQ43MjlclhdjWhyfXHFpVOYaC5TpPr6w3vtEc1arxK3EnOMmLK57W1WneIp7KYW01axnIYaNH2+QJgiYBUKQ460K9xZ3d5MQLgykMvOloHdvHF7n6LWA69GrtLi56gMJ/OBmW6R6v2uBJLIxhNrblli4oUBx0YaFFG9JcXIppcf3QxCiJreJIAQHeTkopaOzHlbpnWEAe304G2+mrNPLz4+o9VpuFsNkK/rxaXF7SprxE+WBPckpfioANt9dWoddoxotHDOLoYRVejS3g3Vg5PRa2VOIwtRlFTZUN7vfhurJxeX61mlgO/ruhz6Ovpb67F6KI2gzUuOqJb8lIcdICI0N9Sq9kC2OWF6Noim1XY1VK3Nl1WbkYXlcVom03MhGgb0edza7bmMLIQga/WiUa3U5PrG0F/Sy0mgjFksrmyX/vyQgQOGwnvWi7FQScGmus0mVZijGF0MYpdLWKbsPnsaqnDyHxUEw+v0SXriWmvrxbz4SSiyUzZrz2yELHc8zXQXIt0lmmSnfXygpJwr0rwGBqxSy8QAy21mFqOlz0760IkiUgyY7nObldrLeLpbNk9vNLZHCaWYparL/7/aDEVN7IQxa5Wa9WXlh5Llxcjwq83AFIcdGOgpQ6Mlf9hHFXnN63W2fGR6kiZra3xpSgyOYbdreI33vXw/2d4vrz1FYymEIymLGc59Kudd7mnerM5hrHFGHYJvt4ASHHQDf6wlNtDgj/clhWHMnd2vPO0mjj0+Wpht1HZxYFPhVpNHLzuKjS4qso++AiEYkhlc5aoLykOOrEWlVnmh3FoLgJXlV3oHC4b0VznRH2No+weXrzztELjXY/TYUOvz112cRixqDgQEQZb6zQQU2t4KgFSHHTD7XSgs6Gm7Gbs0HwYu1vrLOV5AyiNd1drXdlHdsPzEXQ1ulBbLX4CuXx2t9RhuMz1NbIQhdNhQ5fgqeA3YrCt/OLAn9cBC4ipFAcd2dVah6H5cFmvOTQXwWCb+A/iRuxq0UAcFiLYZbEpJc7u1jqMLUaRLqN75sh8BAPNypSV1Rhs9SAYTWExUr4EfMPzEXjdVWiqFd/tV4qDjuxp82B4PoJsmdwzVxNpzK4mMNjqKcv1zMauljrMrSYRLlO20VyOYWQ+it0WGNVtxO7WOmRyrKzBcFZ0Y+XwQdXQXPkGIJfmwtjTZo32KMVBR/a2eZBI58q2fy03iQctPBIGgKEymf7TK3HE01nLLUZzyu2xlEhnMRG0hufNRvBB1XCZrHnGGIbmItjbLsVBUiR8pHJprjwP45B6HatOK+1VR2CXZstTX1b1VOKU2/13eD6CHAP2tteX5Xpmo62+Gp5qBy6VyXKYWUkgnMxgUFoOkmLhD035xCGCmiob/F6xw/Q3w+91we2044IUh4KorXagq9FVtueL17tVRsL5EBEG28q3DnhRrfe9UhwkxVKnNt6LZRqpDM0r88FWXCwElOyZe9o8uFgmcTg/E0arp9oSi4Wbsbe9fPV1cXYVTofNMvs4bMRgq6ds03Dcwt1jEUteioPO7G33rE0HlcrQXNiy6w2cfe0eXJwLl2W/3/Mzq9jXYc0pEs6+dqWzS2ZKT9NyYVZ5vqywz/ZmDLbVYTGiRIGXyqW5CFo91ZZJUGjdb92kDLYp7pmluhsux1KYXklYvrPb2664Gy6U6G6YzuYwPB/B/g5rmPybsb+jHhnVK6tULs6GLTulxNmnrqecn1kt+VpW8lQCpDjozt42D9JZVvLGLOfUh/lABYgDgJKnSi4vRJHK5rDfoourHC5+pXZ2oWgK8+Ek9llcHHh9nZsurb5yOYbh+YgUB8nO4SOVcyU2Xv4w77e4OPD6KlUcLswq9bXP4pZDn68WTodt7f/dKVcWo639fPnqqtFeX1NyexxdiiKezlpKTKU46MxgWx2cdhvOljhSOTezilZPNVo81WUqmTlpqnWixVNdssfSuZlVVNnJsgFdHIfdhr1tHpyfKa2+LnIxtVBntxkHOutLthzOTK0AAK7paihHkUyBFAedqbLbsK/Ds/Yw7ZRz06s42GntUR1nf0d9yWJ6YSaM3a0e4TdgKYR97Z6SLYez06vw1TrRavHBBwAc7KzH8EKkpL1Wzk6vwmm3WSrmyPotxYQc7GzAmamVHXvgJDNZDM9HcKBCxOFwVwMuzYVLarznZ1YtvxjN2d9Rj8VICvPhnW+UdHpqBYf8DSCyppv0eg501CObYyWl0TgztYJ9HdYafFjnPxGIQ10NWE1kdrxF4dBcBJkcw4EO65iwW3HI34Bsju14XnhuNYH5cNLyi/ccblHu1DqNp7K4NBfGYQtNkWwFH2Sdnd5ZfTHGcGZqxVJTSoAUB0O4pqu0xsvnRyvFcrjW3wgAOB3YWX29OLkMADjS01ieApmca7oaYCPg1OQOn6+ZFeQYcFitd6vT7XWjrtqx46nLQCiO1UQG13RKcZCUyJ42Dxw2wpkdjlROTi7DU+NAb5N1I1fX01avLLy/tENxODW5DIeNcNBijXczaqsd2NPmwSlVFIuF1/Mhf2XUl81GuKarHi8Glnf0+SuL0dYarElxMICaKjsG2zw77uxOToRwXXej5Tb42QwiwuGuBpyeWt7R518MLGNfhwc1VfbyFszEXNfdiBcnl3e0rnU6sIK2+mq01ddoUDJzcqTHi3PTqzta1zozvQKHmurFSkhxMIjruhtxanK56L0dwok0Ls6FcX2PV6OSmZND/gYMz0cQTWaK+lwux/DS5Mra1FSlcG13I1bi6R3t7fDS1AoOdTWWv1Am5voeLzI5tqMB24nxEA501ltu8CHFwSBu6PMinMgUnUHzxckVMAZc31tZ4nDY34AcU7xoiuHyYgThZAbXdjdqUzCTwsWw2Kml1UQaIwsRHK6QKSUOX496YSJU1OdSmRxOTS7jWG+TBqUyFikOBnFDn/IwHR8LFvU5/vBeV2Gd3dGeJhABz40WV198UfZIhdXXnrY6uKrsRYvD8bEgGAOO9VXW4KO5rhq9PjdeGC9OHM5OryCRzuEGC9aXFAeD8HtdaKuvxvEiH8aTEyEMttahwVWlUcnMSYO7Cvva6/Hs6FJRnzs+FoSnxmGJDd+LwWG34bC/AcfHixPTZy8H4bTbKm7aElCmlk4WuU5zfExpv0elOEjKBRHhWF/T2sNVCLkcw8nJ5YpsuABwU38TToyHkMoUntH2qZFF3Dzgs+yeF1vxil3NODu9iuVY4emofzMaxLXdDZabPy+E63sasRBOYjJYePzR82NB9PncaPVYb/FeioOBHOv1Ymo5jqnlwh5GpaGncfMu681vFsLNA01IpHN4qUCXw8lgDJPBOG7d5dO2YCbl1t0+MAY8M1KYtRVJZnBmagU39Vdmfd08oPzfTw4vFnQ+YwzHx0M4asH1BkCKg6Hc2K88VIU23l8PLQAAXjXYolmZzMyNaqf1bIHrDk+PKI381t3NmpXJzFzb3Yhapx1PjRTW2Z0YDyGbY7hpwJqd3Xbsbq1DR0MNfn1poaDzL86FEYymcGO/NS15KQ4GcqCjHm311fjlhfmCzn/80gIOdtajuc76ydA2oqnWib1tnoLF9KnhJbR6qi27Z/R2VNltuLG/CU8PF1Zfz4wswWEjHK0wTzgOEeG2wRY8NbKITAGbcf272m7v2NuqddEMQYqDgRARXr2vFb++tLDtPHo4kcYL4yHctqcyrQbOHXtb8OzoElbi6S3PY4zh6ZElvGKXryKSx23GrbubcXkxipmV7acuHz03i5sGmuB2OnQomTm5bU8LwolMQV5e/35+Hoe6GiwbLCjFwWBeva8N4WRmW5fWZ0aWkMkx3FahU0qc3zrYjnSWbWttvTCxjMVIsuLF9Hb1/3/03NyW5w3PhzGyEMVdB9v1KJZpeeXuZtgI204tBaMpvDARwqv3WdNqAKQ4GM6tu31wOmx4bJvO7pGzc/BUOyrW5Occ6W5Eq6caj5yd3fK8h16cRrXDhtcdaNOpZOZksM2DvW0e/PjU9JbnPXJWEY/fOlDZ4tDgrsL1PV48cnZuS5fWxy/NI8cgxWE9RPRuInqCiFaIKEJEx4nofiLakdCU+3qi4XY68IpdPvz8zOymqTSiyQx+dmYGd1/bAaejIqplU2w2wm8dbMOvLi5smgcnm2N4+PQMXr2vFZ6ayooH2Yg3XdeJ4+OhLb3ifn5mFtd1N6K9wZpTJMXwliNduDgXxpmpzbO0PvzSLFo81ThksTTd6ymqpyGiLwD4JoBjAJ4A8CiAPQA+D+B7RFSUc3S5rycq7zzWjanlOH51cWPr4eHTM4ilsnj7Ub/OJTMnb7imA/F0dlPr4dnLS1gIJ3HPtZ06l8yc3H24AwDw8EsbWw/D8xGcnlrB66+pbKuBc8/hTjgdNnzvxOSG708tx/HvF+Zw71G/pZNfFiwORPQ2AB8GMAvgMGPsbsbYWwEMAjgP4K0APmLU9UTmtQfa0FZfjW88M77h+987EcBAc23FBr/lc8uADwMttfjyry9vaPp/67kJ1DrtuNOiXiTF0uurxbXdjfj285MbWqf/368vo9phw71y8AFAmVq662A7fvTiNJKZq63Tf352AgzAu2/q0b9wOlKM5fAJ9fgxxtgQf5ExNgfgPvXPjxcxHVTu6wlLld2G/3hjDx6/tIDRxejL3ntuNIjnRoO491h3RXvdrMdmI/z+bQM4O716VcDSuelV/OSlGfzurf1wOSvC8CyI+24fwOWFKH5wcuplr8+tJvCDk1N4x7Fu+CrURXoj3nmsG8uxNL717MTLXk+ks/j28xN4zb5W+L3W3k+loI6XiPwAjgJIAfhu/vuMsccBTAFoB3Cz3tezAu++sQdupx1/+v3TyKmju0w2h0/+6Aw6G2rwO6/oNbiE5uItR7rQ6qnGZx699DI34L//t4uor3Hg924bMLB05uOug+041NWAzz566WWj4c89NoRMLoffe5Wsr/XcutuHVw024zP/dgkL4eTa63/3yEUsRlL4z6+0fn0VOio/oh7PMsY2W9V6Pu9cPa8nPK31Nfjzew7imctL+Myjl7CaSOMvf3IOF2bD+OQ9Byra93wjqh12/Lff3o+TE8v4bz84jUQ6i0///AIeuzCPD92xq+ISE24HEeFPXr8XU8tx3P/Nk4gkM/jqk6P41rMT+MCt/ejxWXsUXCxEhL9400EkMln88XdOYSGcxI9fnMZXnhzFe2/uxS0VkJKl0B6nXz1uPCmuwO2v/i3O0ep6luDeY378emgBn//lML74q2HkGPC+W3or3vd8M958XRcuL0TxuceG8N0TAQDAe27qwe/ftsvgkpmTVw224K/efBCf/PFZXPNnjwAAXnegDZ94436DS2ZOBlrq8Gf3HMRfPHQWN/31L5BjwL52D/60QuqrUHHg+QeiW5wTUY+F7JVX8vWI6IMAPggAPT3WWBgiInzuXUdw77Fu/PLCPF67vw2vHKzMvECF8oevHcSBznpcmAmjs7EGbz/ql2szW/DeW/rQ11yLZy8H0ddci7sPd1RkxtpC+U839+Km/iZ889kJHOlpxF0H2ysmY22h4sCfnuI3pNXoeoyxLwP4MgAcO3asXOUyHLuNcPuelrXIVsnWEBHuOtgurasieNVgS8Umb9wJg20e/PmbDhpdDN0pdM2B72W5VQYz/l4h+16W+3oSiUQiKSOFisOYetzKZaY771w9ryeRSCSSMlKoOJxUjweJyLXJOTfknavn9SQSiURSRgoSB8bYJIAXADgB3Jv/PhHdDsAPJdr5Gb2vJ5FIJJLyUkz08QPq8dNEtJu/SEStAL6o/vkpxlhu3XsPENEFInoAV1P09SQSiUSiDwVHVjHGvkdEX4KS2uI0Ef0CQBrAawDUA/ghlIR56+kAsFc9luN6EolEItGBosJuGWMfJqInAdwP4HYAdgAXAHwNwJeKHeWX+3oSiUQiKQ+01YYWonDs2DF2/Phxo4shkUgkQkFEJxhjxzZ8zwriQEQL2DoVx1Y0A1jc9iyJ6Mjv2frI77h4ehljG0ZEWkIcSoGIjm+mnBLrIL9n6yO/4/Ji+b0SJBKJRFI8UhwkEolEchVSHNTkfRLLI79n6yO/4zJS8WsOEolEIrkaaTlIJBKJ5CqkOEgkEonkKipWHIjo3UT0BBGtEFGEiI4T0f1EVLF1YhWI6OtExLb4uWB0GSXbQ0R7iegPiOhBNUdbTv3+3l7AZ2X7LpGK3LWeiL4A4MMAEgAew5WcTp8H8BoiupcxljWwiJLy8BSA4Q1en9G7IJIdcR+APyj2Q7J9l4eKEwciehuUB2cWwG2MsSH19TYAvwTwVgAfAfA5wwopKRdfYYx93ehCSHbMGQB/C+A4gBMAvgolB9umyPZdPirRxPqEevwYf3AAgDE2B2WkAgAfl+anRGIsjLGvMMb+hDH2HcbYSIEfk+27TFRUBRGRH8BRACkA381/nzH2OIApAO0Abta3dBKJpBRk+y4vlTatdEQ9nmWMxTc553kAXeq5T+tSKolW3ElEhwHUAZgD8CSAR2UqeMsi23cZqTRx6FePW2Vwncg7VyIu79vgtXNE9C7G2GndSyPRGtm+y0hFTStBGUECQHSLcyLq0aNxWSTacQrARwEchPKddwK4G8CLAA4A+AURdRlWOolWyPZdRirNciD1KHOGWBjG2P/KeykK4GEiehTA41Dmmz8BxWtFYh1k+y4jlWY5hNVj3Rbn8PfCW5wjERDGWArAA+qfbzSyLBJNkO27jFSaOIypx94tzunOO1diLXh0tJxWsh5j6lG27zJQaeJwUj0eJCLXJufckHeuxFr41GNky7MkIiLbdxmpKHFgjE0CeAGAE8C9+e8T0e0A/FCiK5/Rt3QSnXiHenze0FJIyo5s3+WlosRBhc85f5qIdvMXiagVwBfVPz8lfeHFhIiuI6K7icie97qDiP4YihcTAHxW/9JJdEC27zJRkZv9ENEXoYTSJwD8AlcSc9UD+CGAt8vEXGJCRG8B8AMAQQCXAASguC0eguLSmgPwCcbY3xhVRklhENH1uNKhA4obsgfAEJTvFwDAGLs573OyfZeBihQHQEnpC+B+KJ2GHcpC5dcAfEmOKsSFiPqhZPK8EcrCpA+Ka2MAwBMAvsAYO2FcCSWFQkR3QEmWtyWMMcp/Tbbv0qlYcZBIJBLJ5lTimoNEIpFItkGKg0QikUiuQoqDRCKRSK5CioNEIpFIrkKKg0QikUiuQoqDRCKRSK5CioNEIpFIrkKKg0QikUiuQoqDRCKRSK7i/wcBK6b15ZzM0QAAAABJRU5ErkJggg==\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "for i in range(0,3):\n", - " for j in range(0,3):\n", - " pl.figure()\n", - " pl.title(str(i)+\"<->\"+str(j))\n", - " pl.plot(t,ov0[str(i)+\"<->\"+str(j)])" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "61b05894", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "for i in range(0,3):\n", - " for j in range(0,3):\n", - " pl.figure()\n", - " pl.title(str(i)+\"<->\"+str(j))\n", - " pl.plot(t,ov1[str(i)+\"<->\"+str(j)])" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "937be7b9", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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miaF5s4tiCseGtURxt/RlF315+25tNvPoYGnW1/PjC0RXU7woS3HQr3t8sDStraG5CBMLMW7PchZ8Y7cfj0vw1FBpisPc8gqnJ5e406CNaB0lDptwU48ft0uUbDbNJ4eCVJW5ua6zLqvrDwfqqa308MiF0lyKezwjirdmKQ5dDV4C/ioev1SaYvrIRU0UX7o7O3GoKndzKFDHkyUqDvpk7bb+4qXK2AwlDptQXeFhf7uvpMXhxp56yrL0inC7BLf2N/LUcGnW1+OX5tnX5qOhevv9mfXc1t/IE0NB0iWYy+vJoSAddZX0NG6/P7OeW3obeH58kXii9JZ6nxkNUe52ZT1ZKxRKHLbgpm4/z44tkCwx//3FWIIzU0s5J/S6sdvP0FyEUGS1SCWzJqvJNE+PhHjRruysBp0X9TeyEE1wdqqoeSUtyfHRBY70+HNKx31zbwOrqTTPji0Ur2AW5emREIcCdZtG3RcTJQ5bcFNvA9HVVMl13mdGQkiZ/X6Dzg2ZQKZS67znpsLEE2lu6vHn9D39+lKrr5lwnImF2LaBb5txc28DQlBy+w7xRIoT44sczbF9FQIlDlugd95SW1o6NhLE4xIc6cqtMR4O1OESmj92KfHc+AIA11/DJXMjPY1e6qrKeD7z/VLh2dEFAI501+f0vTpvGXtbfTxVYv3x1OVFVlNpblTiYB066ippq63kWIk1xufHF9nT6tsyZcZWVFd42NtWy/HRUquvBRqqywn4t0ouvDlCCA4H6kouaeHxsQU8LsHBjtzXzw8H6jg5sVhS8SH6ZvSN3UocLIMQght76nl2rHQGOyklJycWObTDja8buup5bmyhpDZZnxtb5HCgbkfHWV4fqOf8dLik4mmeHV1gf3stlWW5r58f6qwjGFnl8mLp5Fl6dmyB7gYvzb4Kw5+txGEbDnbUMRaMsRgrjXzyEwsxQtEE1wV2Jg5HuutZiie5VCJ5qaKrSS7MhK8Z5bsV13fVk0pLTl0uDeshlZY8P76Q85KSju6tc6KErK1Tl5e4rrPWlGcrcdiGgx3aj3L6cmmcLX1yQut0+VgOACcmFgpUImtzcmKJtITrdyim+vdKZWnp0uwykdXUjsV0f3stbpdYa6dOZymeYDQY3dESXCFQ4rAN+o9SKjO7ExOLuF2CfW2+a1+8Cf1N1ZR7XJyZLA0PL30zeaeDXUuttq9VKpvSpye1SdaB9p3NhCvL3Ay01HCiRMRBn5Qe6FCWg+Vo9lXQ4qsoGcvhxMQSAy01O1oPBu2s5D2tNZyZLI36OnV5ibbayrzWgw9lNllLgTOTYcrcgt0tNTu+x3WdpbMpfSoz7hxU4mBNDnbUrv1ITibfzWid/W21nL68VBKd98zkEvvbd2Zl6exv8zE0FymJyN8zk0vsbvFR7tn5sHOos475yCqTJbApferyYmaCWvwjQTdDicM1ONhRx8XZZcd33umlFYKR1bxD9A901DIfWWU27OwMravJNIOzy+xty29Wt7etlrSEizPOz9BaCDHVN2dLYcJ2+vKSaVYDKHG4Jgc7akmlJeccHil9blr79+3d4X6Dzv7MevJphy8tXZpbJpGSeQ92+zLfd3ok/tzyCjPhlR3vN+jsadXq6/y0s+srnkhxYWZZiYOV0TeDnL6Ofj4zOOmdb6fsbysNcdAnC/vytBx6G6up8Lg46/D6OpPnZrSOr7KMzvoqx4vDxZllUmnJgXZzPJVAicM16fJ7qSxzOf5glnPTYZp9FTllFt2MOq/WeZ3usaRvrvY3V+d1H7dLsKfVt2a5ORVdHPbnKQ4Ae1prHG/J6+K3p3Xnm/f5osThGrhcmnfFhRlnN8ZzU2H25mk16Oxv9zl+Jnx2aoldzTVZpzXfjr1tPseL6dnJMG21lfjznHwA7GnzMTi7TMLBGZMvzCxT5hb0NuU3+cgHJQ5ZsKfFxwUHWw6ptOTCTDjv/QadgVbNA8fJnffsZLggs2CAfW0+5pZXmHPwMasXZpYZKNAseF+bj0RKMuzgSPwL02H6mqoLMvnYKUocsmCg1cfUUtyxaTTGglHiiXTBLIeBlhqSacnIvDM772I0wdRSvGBiqouMU5dK0mnJxZllBloKU1/6vpiTl+LOTy8zUKD+uFOUOGSBvu530aFLS3on21OgwU4PcnKqe6a+xFio9eCBTH1dcOhgN7EQI5ZI5RX8tp5dzTW4xBUnCqcRW00xFoqyp0BiulOUOGTBFfc5Zw52eicbKGDnBRy7FDc4q/279H9nvjT7KvBVeBicdaaldTFTX4VaVqosc9PbVO1Y99+LM8tIae5mNChxyIrO+iqqytyOdZ+7MLNMZ30V1RWegtyvusJDZ30VFxxqOVycWabc4yLgz/4M5O0QQrCrpcaxltbFzCRhd4HEFLR9QF10nIY+zqhlJRvgcgkGWmscOxO+NLfMrgJZDTq7HTzYDc5G6G+qxu3K/QyHrdjdUrNmkTiNCzNhmmrKC+KppNPfXM3ofNSRTg/nZ8KUu130NhZm8rFTlDhkiVPdWdNpyeBMhF15+utvZCAz2KUcePDPxZnCi+mu5hpmwissxZ3n9HBhZrlg+w06u5o1p4fRYLSg97UCgzPL9DVV4zHRUwmUOGTNruYappdWiKwkzS5KQZlaihNLpAq2fq4z0FrDSjLNeMhZnTee0DYLC7lEAlc28QcdZm1JKbk4XThPJZ1dDq0vgEuzkbyDKwuBEocs6c8Eoww5zLf6UmYTtNCNcXeLMzelh+YiSEkRLAet/p22FDcTXiG8kiy45aC3V6edOphIpRkNRpU42In+zEzRaY1RX+cu9ExYt0ScJqb64F3o+upu8FLudjnOY6nQnl06tZVlNPsqHGc5jAWjJNOS/iZzPZVAiUPW9DR6EUI76tBJXJpdpqbCU/ADzOu95fi9ZY4UUyEKb2l53C56m7yOsxz0yUFfEWbC/U3VjmtfuiVfjPrKFSUOWVJZ5qazvmrtx3MKg7PaZrQQhfO80elrqmZozlmD3eBshM76qh2flrcd/U01jpt8DM1GqPC4aK8t/IE1uxzo4XUp0192KcvBXvQ31zhumeTS7PLaklmh6WtyXn0Nz0XoK1IytN6masZCUUd5eA3Pa/XlKqDbr05/UzUL0QTByGrB720WQ3MRGqvLqfOWmV0UJQ650N9UzaXZZcccgRldTXJ5MV5wN1adviavozy8pJTFFYdGL4mU5PJCrCj3N4NLcxF6G4tTX7scmKZlcLZ47StXlDjkQH9zNZHVFDMOOQJzeE5zMy1WWuC+jGk87JAEfPORVcIryaINdj2Z+47MO8P9N5lKMzofLdr6eV+mvpzSvsA6bqygxCEndA8Cp+w76J2qWINdn8Pcf/UU0cWa2fVkImKdMthNLMRIpmXR6qvTX4XbJRh1iJguxRPMLa8UbZk3V5Q45EDfmm+1M8zYNXEo2hq6NtgNOURMdZErVn211VZS7nE5JupX9yTqL1J9lblddNZXMeKQ+ir25CNXlDjkQHttJeVul2NmKiNzUZpqKqgpUMK9jXjLPbTXVTrHcpiP4HYJAv6qotzf5RL0NHgdc4iNPiko5mDX0+hl1CGW1nBmXCmWJZ8rShxywOUSBBqqHDOzG5qPFD25V2+jc3zRh+eidPmrino6V09jtWP2HIbmIvgqPXmfS74d3Q3etUHV7oxlxpWuhuJMPnJFiUOO9DR4HdN5R+YjRT+jtrep2jFr6JfmDKivRi8jwQhpB7iz6m6sxYih0elp9LIYS7AYtX/CwpH5CM2+CrzlxbHkc0WJQ470NFYzGoza3p01uppkemml6JZDT6OXhWjC9tlGpdSOPS22yd/T6CWeSDvCI24sGKW7odjtK+PhFbT/BGRkPkpPkesrF5Q45EhXg5fllSQhm89UdOunp8iDnT44jNl8KW4mvEJ0NVX0zcIr7qz2HuxSacl4KGaAOGj3d4I1b4SY5oIShxzRld3unVcvf7EHO6eIg17+bgP2aMD+g93ljBtrsQe7bof0x5VkismleNHbVy4occgRfaZi903poTljBruuBmfM7MYy51J0Feho0K3oqK/E4xK236dZE9Mii4O3XEsaafv2FYwh5ZXxxQooccgRfbCzuzvryLyWw6W2srg5XOqqyqirKrO9mI4HtZQWxXJj1fG4XXQ5wOlh1CBLCzJOIjZvX0aJaS4occiRyjI3rbUV9m+Moeia0BWbnkav/cUhFKOppqIo2Vg3orln2ttyGA1G8bgE7XXFd8vsaax2xGQNoLvBGjEOoMRhR/Q02L8xjodiRZ8F63Q1eO2/5xCKGuZ/3tvoZXTe3h5xo8EogUx6i2LT0+hlailOPJEq+rOKxUgwirfcTVNN8WJCckWJww7oavDa2nUuldYyfwaKvH6u093gZTwUs3Uqak1MjbK0qgmvJG2dino0aKxlqj/TrozOa55KxYwJyRUlDjugp1FLRW3XmcpMOE4iJQ2bCXc3eEmmJZOL9kxFfUVMDbIcmvQEfDYe7Ax0y+x2gNODkfWVLUocdoA+U7HrUsnY2uaqsZ3XrktxU0txkmlZdE8lHbvHOizGEixEE4YNdr02r690WjIajFrKUwmUOOwIu7tnjmfcMo2aCa+Jg03FdDxobH0F/FUIYV/LQZ80GTXY1XvL8FV6bNu+ZsIrrCTTynJwAj12H+xCmuXQWW/MYNdep/nu272+jFpDr/C46airsm220SsJ5IypLyEEPY32TcB3xe3XOp5KoMRhRzRUl1NTYd+ZyngoSovPGLdM0Hz3O/32zWarB8B11Fca9szeJvsOdiMGiwPoHoT2FFN9OcxKeZVAicOOEEJkApXs2RjHgsZtrup029iddTwUo7W2ggqPMWIKmr+7XcV0NBjF7y0reoDlerobNY+4ZCpt2DMLxWgwiktAh0GWfLYocdghPQ32DewaX4gathmt02Xn+gpFDduM1ulqqCIYWSWykjT0uYXAjARyvY26R1zc0OcWgtFglI76Kso91hqOrVUaG9HT6GUsFLNd3v1kKs3kQtzwA0V6GryEbJq62wxLSxdvfb/DTowGo4avn+uRxXZ0EhmZt56nEihx2DFdDV5Wk2mmluw1U5kOr5BMS8MtB7u6syZT2m9sdH3pYqR7ltmFZCrNRChGt8GTDz2Hkx2DU60Y4wBKHHaMXaMyxwx2y9TRNyfttu8wuRgnlTYuYFBHX8ayY30Zkap7I221mkfchM0srXA8QTCyaqmcSjpKHHZIT+bHtNtMWF+mMNxysKuYrsWEGFtfTTXlVJa5bLesNGqCpxKA2yXoqK+ybX2pZSUH0VFfiduGvvvjoShCGOuWCVBbWUa9136pu6+IqbGWgxCCgN9r28HOjGWSzvoq2y3D6dkKjHZ4yAYlDjvE43bRVlvJxIK9Ou94KEarr9JQt0wdO3p4jWfcDI1IPb2RgL9qzXKxC6PBKGVuY1J1byTgt5/loIuZ0cuW2aDEIQ86/XacqUQNnwXr2NGddTwUo6220hQ3QzsOdqPzmpu0Eam6NxLwezOpKOyTEHM8FKOmwkNdlXExIdmixCEP7Nh5jTzHYSNdDV4mbJa628hU3Rvp8ntZjNnL/XcsZN7kQ3/u5QX7eBDq/dFKqbp1lDjkQcDvZXopzmrSHlGZulum0ZuFOl1+LVBp2kbuv2OhKAGTTP61WIegfSYgEyaKqR3df8dNFNNrocQhDwL+KtISpmwSlam7ZZo9s7OLe6Yex2Ka5dBgr8EuuppkPrJqXvtqsFfgoJTSVDG9Fkoc8sBuMxWz3DJ1rtSXPTrv5GIMKY33VNLRf6cxm9TXhEmeXTqtvgo8LmGb/rgUSxJeSSrLwYkE6u01UzHLLVOn02biYLabod9bRnW52zaD3fiCue3L43bRXl9pn/Zl8LkquaLEIQ/a6ipxCftYDuOhmGlumaCdU9BaW2Gj+jK38+qxDmM22XMwK8ByPYF6+8SGWKG+tkOJQx6Ue7RYh3GbxDqMh6KmuWXqBPxe2/juj4diuF2C9jpjAwbXE7CRu/R4KEq520VzTYVpZbBbfYGyHByLnaJYzXTL1LGT++9YKKqdYuc2r5vo7r9SWt/9dyIUo6O+EpcJMQ46mgehPWIdrBzjAEoc8ibgr7JNsq9xEwPgdLr8Xi05mw0OZTEzJkQn4K8ivJJkMWb9WAerTD7AHrEOVo5xACUOedPpr2JyMUbC4oPdmlumyamBA/4qUjY5lMWMQ342YqdzHcZDMcPOJd8KO3kQWjnGAZQ45I1dYh2mFuOkTXTL1LHLYBdPpJheWrHMTNjqsSHxRIq55RXz25dNYh2sHuMAShzyxi6DnVU2v+wS2HXZZLdMnS6btC89AaVZ0eQ6rb4K3DY418HqMQ6gxCFv7GLG6h5CZi+TtNdVIYT1Bzu9fGalGtGp85bhq/RYvn3p9dVZb259edwu2usqLV9fVo9xACUOeWOnwc5st0y44v5rdXdWK3Vezf3X2u3L7Ojo9djBI87qMQ6gxCFvyj0uWn3Wj8rUU0+b6Zap02UD99/xUIwyt6C11lwxBeiyge/+eCiKx2WN+rKDe7lVlnm3w/yRwgEE/FVMLFi/81qlIdrB/XcsGKWjvsqUcwk2okdJWznWYTwUoz1zOqLZBPxVTIfjlo51sHqMAyhxKAh2MGPHgjHT1891AjZw/7VCjINOwF9FLJEiFLVurMN4KLqWa8xsAn4vUsKkhWMdrB7jAEocCkLA4oFdK8kU0+G4dQa7Bi9pO3Reywx21nd6mFiwlpiCtfcBrWTJb4UShwLQmQnsmrLoITaTC/FM6mk12GVDbFXz2bfKub5Wd5deSVojJkTH6u0LzD0UKVuUOBQAvTFadR3d7FTdG+laO6fAmp1X3z+ySufttPhgp6eq6LRI+2qr1fY+rCqmi7GE5WMcYAfiIIR4hxDiYSHEohBiWQhxTAhxrxAip3sJIb4shJDb/Hc217KZhdVndmsxDhbZc7iS6tyq9WUtMa2rKqO20mPZ+rKSGytYP9bBDp5KAJ5cLhZCfBb4IBAHHgISwCuAzwCvEELcI6XM1UXgUeDiJu9P5ngf0+io19z3rNp519wMfealUl5PmdtFe511N/HHg9YSU7C2e6YVBzsrO4lYJWDwWmQtDkKIN6MJwxRwh5TyQub9VuBnwJuADwF/nWMZviil/HKO37EUVj/ERncztEKMg46V8+6Ph2KUe8w9l2AjAX8Vw/MRs4uxKXqAZZsFYhx0An4vj1yYM7sYm2K1Zd6tyGW0+Gjm9cO6MABIKaeBD2T+/Eiuy0tOobPe2jMVq3je6Fj5hDOtvqpMPZdgI7rlYMVYh4kF6wRY6uixDqtJ63kQjoeiVJe7qfdaN8YBshQHIUQAuAlYBb698XMp5S+ACaANuK2QBbQLAb93LfmY1RgLRi3jeaPT1WDdQKWxUNQym6s6AX8V0VVrxjpY0S2zs75Ki3VYtF6f1M+9sHKMA2RvORzJvJ6SUm5V209tuDZbXiaE+EshxBeEEH8uhHi1Ha2PgL+KywsxUmlrzeziiRQzYeu4GepYOVDJCofWbMTK7pnjoZgFxdS6TiJWCrDcjmz3HPoyryPbXDO64dpsefcm750WQrxdSnkix3uZRsDvJZmWTC/F6TD5wJP1WCX19EbWzikIReltqja5NFeIrCQJRlYtZ2mtH+wOB+rNLcw6VpNpppfiSkxzYDwU5ZZev9nFuCbZztBrMq/b7YgtZ159Wd7zWeD3gYOZ+3cAdwPPAQeAnwohOrf6shDifRk32mOzs7NZPrJ4WDUq06rZH7sseiiLVevLqrEOVjlEaiPtddaMdViMJQjHk5ZrX5uRrTjoi2MFWzORUv6VlPJvpJSnpZQRKeWklPJ+4BbgV0ALVzbBN/v+F6SUR6WUR5ubmwtVrB1j1c57JcbBWp231VeBxyUsV19WdMsE68Y6rNWXhaxl0GId2mqtly1Zjwmx2jLcZmQrDuHMa8021+ifhbe55ppIKVeBT2T+fF0+9zIS/excq0VJ66mnW3zWcTOETKBSvfU679ohPxac2Vkx1mF8wZqWFljTXdqqk4/NyFYchjOvPdtc07Xh2nzQo6O3XFayGpVlbpp9FdbrvKGYZVJPb6TL77Xc2chjwSgVHhdNNeVmF+UqrDnYxXAJLerdaljRXdqqy5abka04HM+8HhRCbCV5N2+4Nh8aM6/L215lMQL+KsYtdq7DeChqyVkwWDOK1cqplK0Y6zAeitJaW0m5x3oOhlaMdRgPxfCWu/FbPMYBshQHKeUY8AxQDtyz8XMhxJ1AAC16+vEClOutmdentr3KYljR7B8LWtdtLuD3MhNeIZ6wTqzD+ELUUmkz1mPFWIcJC7tlBvzWi3XQY0KsOPnYSC5yr+8DfEoIsVt/UwjRAnwu8+cnpZTpdZ99QghxVgjxiXX3QQhxgxDibiGEe8P7HiHEH6F5MQF8OofymU5nvRbrkLZIrEM8oaWetnLnBSwVPGhtMbWe04MVY0J0rBjroJ17Yc362kjW4iCl/A7webQo6BNCiB8KIf4JuIDmevo9tAR862kH9mZe19ML/BCYEUI8LoT4thDiJ2hxFP8zc82HpZQP5PbPMZeAv4pESjIdtkZgl9XXN63mzroUT7AYS1i2vqw22CVTaaaW4mvOGFbDqmJq1fraSE5ZWaWUHxRCPALcC9wJuNE2j78EfH691XANnkNL0HcL2ib3ETQ32XHg74DPSimfzqVsVmD9uQ7tdeY3gHGLurHqWK3zjget66kE1nOXnlqKk0pLy1paemp4q3gQXpl8WLO+NpKTOABIKb8OfD3La98DvGeT94eAP8z12VZn/czuaK+5ZYH15xJYc7Br8VVS5haW8Sixupuh1WIdrG6ZWi01/ITF62sj1nMxsDFrKSEs4p45HopS7rZW6un1uF0ik83WKvVlzVQj67GS08O4DQK6Oi3kEWeH9rUeJQ4FpLLMTVONdWId9IRoVko9vRErDXZjoSjecjcN1daLcdCxUqzDeCiKEFcOu7IiVqsvUOJQsnQ1WCfWwQ7ZH60U62DlGAcdK8U6jAVjtPoqqfC4r32xSQT8XqaWrBHrMBGKUVVm7cnHepQ4FBgrzYTHg1HLr292NXiZW14htmp+rMN4KGbZzWgdK8U6jIesd07IRgL+KtJSSxBoNrolb+XJx3qUOBQYq5zrEF1NMh9ZtYXlADBhsrUlpcyIqT3qywpLJVaOcdCxVH0tWL99rUeJQ4HRYx1mTI51mLDJ5teVcx3MtbaWYknCK9ZPpWyVWAc9xsHq7avLIvWll8Hq9bUeJQ4Fxiqddy27qEVTQeisdV6TPbysmtp8I1aJdZhctHaMg44e62B2fS2vJFmIWjfAcjOUOBQYq5ixYzbxjGiqqaDc47KAmOr1Ze3Oa5VYhzUxtXh9lennOpicosUulvx6lDgUGD00ftzkwK7xUIwKj3VjHHRcLkGg3nyPJTv5oFvB6cHqAXDrsUZ92WPysR4lDgXGKuc6jIeitvGM6PRXrc1EzWI8FMNX4aGuyvqplK3guz8ejFr2HIeNBPxVpqfQsNPkQ0eJQxGwwrkOdnDL1OlqMH9mNxa0j5haIdZhPBSjzaLnOGwk4K9icjFGImVerMN4KEplmYtGm8Q4gBKHomAFM3bMBm6ZOgF/FcHIKpGVpGllsINbpo4VYh3GQzECFnd20An4vabHOujZWO0w+dBR4lAEzI51WF5JErKRZ4ReTrPOdZBS2iKgS8cKTg9jIXtNPgBTly7tNPnQUeJQBMyOdZhYc2O1R+ftMjlhYSiaILKask3nNdtdejWpxzio+soW7ZAfe/RHHSUORUBvjGalorabZ4TZndduCdHMjnWYXIwh5RVRtzptdZUIYV77iqwkCUZWbdMfdZQ4FAGzzX59Bm6Xwa6pppzKMpeJ9WUvTxKzYx3s5MYKUO7JxDqY1L705VK7tC8dJQ5FYC3WwcTOW1Xmto1nhBCCgN9rmqWlr0V322SDFcx1erDb5APMdWfVRcnK515shhKHInAl1sGcmYodUk9vxEz339FglIbqcnyV1o9x0DEz1mE8FMPtErTbIMZBx0wxtWOMAyhxKBpdJp5TMJYJgLMTZp7rMBaMWj4H1UbMjHUYD0Vpr6vE47bP8GFmrINdshVsxD6/rs0wa6YipWQ0GKXHZoNdl9/LQjRBOG687/5oMGqrJSUwN9ZhzGbZRUELtExLuGyCu/SEzc5x0FHiUCTMinVYjCUIx5O2nAmD8fs0yVSaiVCMbpu4/eqY6fQwHrL+IVIb0cV/1AR3aTvWFyhxKBoBv5dkWjK1ZGysw8i81vh7GqsNfW6+XBnsjBWHycU4ybS0oeVgjpiuJFNML63YJjWLTk+jVl69fxjJWCY62m4ocSgS+mAzMh8x9Ln6zMh+g505M2Hd88ZulpZZsQ6XF7TJjt2WlVp9lZS7XYYHWobjCYKR1TVxshNKHIqE3hiMboyja4OdvTpvQ3U53nK34e6sdhVTs2Id7OjGCpnU8A1Vhi8rrVnyNmtfoMShaLTXVeJxCcPN2NH5KM2+CrzlHkOfmy9arIPx7pmjwSgel6C9zl6DHZjj9LB2iJQNB7ueBq/h/VEX025lOSh0PG4XAX8VIyZYDnabBeuYMdiNZrLXul328iQBc2IdRuejlHtctNfaJ8ZBp7vBy1gwaqj774hNLVNQ4lBUuhurGTXacrChG6tOlwmH/tgxxkHHjFiH4fkIXf4qXDYU0+7GasKZjMVGMTJvvwBLHSUORaS7ocrQDenVZJrLizFbD3bheJLFmHGd196WlhbrMB9ZNeyZI/NRem3mCadjhjvraDBi2/alxKGI9DRUsxRPshA1pvOOh6JIaU8TFoz3WFqKJwhFE7atr94mY90z9QBLO66fgzniMDIftaWnEihxKCrdBvtW643ero1Rt3iM2ncYs/F6MFyJZTHKOp1dXiG6mrLtsuWaOBhUX6vJNJcXYratLyUORWQt8MagmYpd3TJ11k7sMqi+7BrjoBPwV+ESMGzU5EN3y2yy57JSVbmWENMoy2FiIUZaansddkSJQxExeqYyOq8dYt7ss1eCL526qjJqKozz3R+1sZshQIXHTUe9cftawzb22dfpafAaJg7672JXS16JQxHxlnsMnanom6t2S/ClcyXWwThxqPeWUWtDTxKd3sZqAy2HCC5hn0N+NqO7wWuYB+HaMq9NxVSJQ5ExMvDGzp43Opp7plH1FbN9ffU0eg21HDrqqyj32HfY6GrwMrkUZyWZKvqzRuajVGXOdrEj9v2VbUJ3ozFm7JonSYM91zd1dMvBCN99O8c46PQ2VrMQTRjiETcStK8bq05PoxcpjXF6GJm3tyWvxKHI9DRUM7UUJ54o7kxlbnmV6GrKdqmnNxLwV7G8kmShyIFKqbRkPBS1XXbRjfQ26R5LxZ+AjMxHbLs/o2OkO+to0N71pcShyFyZqRS3MV5xY7X7zC4z2BW5804txUmk7JeqeyO9mcFnuMhLS4uxBAvRxNrz7Eq3QQkx7Xro1nqUOBQZo2IdRoPa4GD3ZZK+TGDX8FxxBzt9U9Lu4tDV4EUIA9rXWn3Ze/LRXFNBZZmr6PU1E14hnkgry0GxNVfOdSh2540hhP1SKW8k4NcGu2LPhO0eAKdTWeamvbay6GKq/x56VLZdEUJoHktFthxGHDD5UOJQZBqry6kudxe9MY4Go7TVVlJZ5i7qc4pNZZmbjrqqog92Q/MRytyCjnr7ZRfdSE9jddHF1O4Bluvpbih+QkwnLPMqcSgyQgi6G6uL7m44GozYfklJp6+pmqEid96hWa2+PG77d4HepuK7Sw/PRWx5Tshm6JZDMT3i9JgQOx4PqmP/nmEDjIjKHJm39+bXeozw3R+ej9Bv0zQQG+lprGY+sspSvHgeXpobq3PaVyyRYja8UrRnjATtHxNi35LbiJ5GL2OhGOl0cWYq4XiCmfAKfc3OGOz6morru59OS4bnI7b32dfRB+1iLpWMzEdsvxmt05eZFFwq4tKlnbOx6ihxMIDuRi+ryTRTS/Gi3H94ThsU+ptqinJ/o9EH7aEidV4t7iTtGDHV17WLte8QW00xvbTiGMuhv7m47QtwRECqEgcD6CvyYHdpbhm40ujtTrEDu/TN7j6HWA49RXaXtnuCwo101GnLPcXqj4vRBMHI6ppbtl1R4mAA/c3ajP7S7HJR7j80F0EIZ3iSAHQ1aKmoiyemulumM8TBW+6htbaiaB5e+v6PU5bhXC5BX2M1l2aLU1+D+mTN5pa8EgcDaK2toLrczWCRGuPQXITO+irbu7Hq6KmoiyUOw3MRKstctNXa341Vp6exumiWg35fu6+hr6evqZqhueJM1nTRsbslr8TBAIQQ9DVXF20D7NJsZG2TzSnsaq5ZWy4rNENz2ma0y2XPhGib0dvoLdqew+DsMo3V5dR7y4tyfzPoa65mNBglmUoX/N6XZpfxuITtXcuVOBhEf1NNUZaVpJQMzUXY1WxvE3Yju5prGJyJFMXDa2jeeWLa01jNTHiFyEqy4PcenF12XPvqb6omkZJFyc56aVZLuFdm8xgae5feRvQ3VzOxECt4dtbZ5RWWV5KOG+x2tVQTS6QK7uGVSKUZnY86rr70f08xluIGZyPsanFWfRXTY+nS3LLt9xtAiYNh9DfXIGXhG+NQZn3TaYOdPlMdLLC1NTIfIZmW7G6xf+ddj/7vuThT2PoKRlYJRlYdZzn0ZQbvQi/1ptKS4bkou2y+3wBKHAxDbyyF9pDQG7djxaHAg50+eDpNHHobq3G7RMHFQV8KdZo4+L1l1FWVFXzyMR6KsppKO6K+lDgYxFpUZoEb44XpZarK3LbO4bIZTTXl1FZ6Cu7hpQ+eTui86yn3uOhp9BZcHAYdKg5CCAZaaoogps7wVAIlDobhLffQUVdZcDP2wkyY3S01jvK8Aa3z7mqpKfjM7uLMMp31VVRX2D+B3EZ2N9dwscD1NTgbodzjotPmqeA3Y6C18OKgt9d+B4ipEgcD2dVSw4WZcEHveWF6mYFW+zfEzdjVXARxmF1ml8OWlHR2t9QwPBchUUD3zMGZZfqbtCUrpzHQ4iMYWWVuuXAJ+C7OLOP3ltFQbX+3XyUOBrKn1cfFmWVSBXLPXIonmFqKM9DiK8j9rMau5hqml1YIFyjbaDotGZyJsNsBs7rN2N1SQzItCxoM50Q3Vh19UnVhunATkPPTYfa0OqM/KnEwkL2tPuKJdMHOr9VN4gEHz4QBLhTI9L+8GCOWSDluM1qn0B5L8USK0aAzPG82Q59UXSyQNS+l5ML0MnvblDgockSfqZyfLkxjvJC5j1OXlfZmZmDnpwpTX071VNIptPvvxZll0hL2ttUW5H5Wo7W2Al+Fh/MFshwmF+OEV5IMKMtBkSt6oymcOCxTWeYi4Ld3mP5WBPxVeMvdnFXikBXVFR4666sK1r70enfKTHgjQggGWgu3D3guU+97lTgocqUm03nPFWimcmFGWw924mYhaNkz97T6OFcgcTgzGabFV+GIzcKt2NtWuPo6N7VEucflmHMcNmOgxVewZTjdwt3jEEteiYPB7G3zrS0H5cuF6bBj9xt09rX5ODcdLsh5v2cml9jX7swlEp19bdpgt5LMP03L2SmtfTnhnO2tGGitYW5ZiwLPl/PTy7T4KhyToNC5v7pFGWjV3DPzdTdciK5yeTHu+MFub5vmbjibp7thIpXm4swy+9udYfJvxf72WpIZr6x8OTcVduySks6+zH7KmcmlvO/lJE8lUOJgOHtbfSRSMu+DWU5nGvOBEhAHIO+lkkuzEVZTafY7dHNVRxe/fAe7UGSVmfAK+xwuDnp9nb6cX32l05KLM8tKHBQ7R5+pnM6z8+qNeb/DxUGvr3zF4eyUVl/7HG459DZWU+5xrf17d8qVzWhnt6/Gmgraaivz7o9D8xFiiZSjxFSJg8EMtNZQ7nZxKs+ZyunJJVp8FTT7KgpUMmvSUF1Os68ib4+l05NLlLmFYwO6dDxuF3tbfZyZzK++zuli6qDBbisOdNTmbTmcnFgE4LrOukIUyRIocTCYMreLfe2+tca0U05fXuJgh7NndTr722vzFtOzk2F2t/hsfwBLNuxr8+VtOZy6vERjdTktDp98ABzsqOXi7HJeZ62curxEudvlqJgj5/cUC3Kwo46TE4s79sBZSaa4OLPMgRIRh8OddZyfDufVec9MLjl+M1pnf3stc8urzIR3flDSiYlFDgXqEMKZbtLrOdBeSyot80qjcXJikX3tzpp8OOdfYiMOddaxFE/u+IjCC9PLJNOSA+3OMWG341CgjlRa7nhdeHopzkx4xfGb9zq6RblT6zS2muL8dJjDDloi2Q59knXq8s7qS0rJyYlFRy0pgRIHU7iuM7/Oq6+PlorlcH2gHoAT4zurr+fGFgA40l1fmAJZnOs663AJeHZsh+1rcpG0hMOZenc6XX4vNRWeHS9djodiLMWTXNehxEGRJ3tafXhcgpM7nKkcH1vAV+mhp8G5kavraa3VNt6f36E4PDu2gMclOOiwzrsV1RUe9rT6eDYjirmi1/OhQGnUl8sluK6zlufGF3b0/Sub0c6arClxMIHKMjcDrb4dD3bHR0Pc0FXvuAN+tkIIweHOOk5MLOzo+8+NL7Cv3UdlmbuwBbMwN3TV89zYwo72tU6ML9JaW0FrbWURSmZNjnT7OX15aUf7WicvL+LJpHpxEkocTOKGrnqeHVvI+WyHcDzBuekwN3b7i1Qya3IoUMfFmWUiK8mcvpdOS54fW1xbmioVru+qZzGW2NHZDs9PLHKos77whbIwN3b7SabljiZsT4+EONBR67jJhxIHk7i51084nsw5g+ZzY4tICTf2lJY4HA7UkZaaF00uXJpbJryS5Pqu+uIUzKLoYpjr0tJSPMHg7DKHS2RJSUffj3pmNJTT91aTaZ4dW+BoT0MRSmUuShxM4uZerTEdGw7m9D298d5QYoPdTd0NCAFPDuVWX/qm7JESq689rTVUlblzFodjw0GkhKO9pTX5aKqpoKfRyzMjuYnDqcuLxBNpbnZgfSlxMImAv4rW2gqO5dgYj4+GGGipoa6qrEglsyZ13jL2tdXyxNB8Tt87NhzEV+lxxIHvueBxuzgcqOPYSG5i+sSlIOVuV8ktW4K2tHQ8x32aY8Na/71JiYOiUAghONrbsNa4siGdlhwfWyjJjgtwa18DT4+EWE1mn9H20cE5butvdOyZF9vx4l1NnLq8xEI0+3TUvxoKcn1XnePWz7Phxu56ZsMrjAWzjz96ajhIb6OXFp/zNu+VOJjI0R4/EwsxJhaya4xaR09w2y7nrW9mw239DcQTaZ7P0uVwLBhlLBjj9l2NxS2YRbl9dyNSwuOD2VlbyytJTk4scmtfadbXbf3av/uRi3NZXS+l5NhIiJscuN8AShxM5ZY+rVFl23l/eWEWgJcONBetTFbmlsyg9USW+w6PDWqd/PbdTUUrk5W5vque6nI3jw5mN9g9PRIilZbc2u/Mwe5a7G6pob2ukl+en83q+nPTYYKRVW7pc6Ylr8TBRA6019JaW8HPzs5kdf0vzs9ysKOWphrnJ0PbjIbqcva2+rIW00cvztPiq3DsmdHXoszt4pa+Bh67mF19PT44j8cluKnEPOF0hBDcMdDMo4NzJLM4jOtfM/32rr0txS6aKShxMBEhBC/f18Ivz89ecx09HE/wzEiIO/aUptWgc9feZp4Ymmcxltj2Oikljw3O8+JdjSWRPG4rbt/dxKW5CJOL1166fPD0FLf2N+At9xhQMmtyx55mwvFkVl5e/3pmhkOddY4NFlTiYDIv39dKeCV5TZfWxwfnSaYld5TokpLOrx1sI5GS17S2nhldYG55peTF9M7Mv//B09PbXndxJszgbIRXH2wzoliW5SW7m3AJrrm0FIys8sxoiJfvc6bVAEocTOf23Y2Ue1w8dI3B7oFT0/gqPCVr8usc6aqnxVfBA6emtr3uh89dpsLj4lUHWg0qmTUZaPWxt9XHD569vO11D5zSxOPXDpS2ONR5y7ix288Dp6a3dWn9xfkZ0hIlDusRQrxDCPGwEGJRCLEshDgmhLhXCLEjoSn0/eyGt9zDi3c18pOTU1um0oisJPnxyUnuvr6dck9JVMuWuFyCXzvYys/PzW6ZByeVltx/YpKX72vBV1la8SCb8Rs3dHBsJLStV9xPTk5xQ1c9bXXOXCLJhTce6eTcdJiTE1tnab3/+SmafRUcclia7vXkNNIIIT4LfA04CjwMPAjsAT4DfEcIkZNzdKHvZ1fedrSLiYUYPz+3ufVw/4lJoqsp3nJTwOCSWZPXXtdOLJHa0np44tI8s+EVXn99h8ElsyZ3H24H4P7nN7ceLs4sc2JikddcV9pWg87rD3dQ7nHxnafHNv18YiHGv56d5p6bAo5Ofpm1OAgh3gx8EJgCDksp75ZSvgkYAM4AbwI+ZNb97MwrD7TSWlvBVx8f2fTz7zw9Tn9TdckGv23kRf2N9DdX84VfXtrU9P/6k6NUl7t5mUO9SHKlp7Ga67vq+eZTY5tap//nl5eo8Li4R00+AG1p6dUH2/j+c5dZSV5tnX7jiVEk8I5bu40vnIHkYjl8NPP6YSnlBf1NKeU08IHMnx/JYTmo0PezLWVuF795Sze/OD/L0FzkBZ89ORTkyaEg9xztKmmvm/W4XILfu6OfU5eXrgpYOn15iX9+fpL33t5HVXlJGJ5Z8YE7+7k0G+G7xyde8P70UpzvHp/grUe7aCxRF+nNeNvRLhaiCb7+xOgL3o8nUnzzqVFesa+FgN/Z56lkNfAKIQLATcAq8O2Nn0spfwFMAG3AbUbfzwm845ZuvOVu/vifTpDOzO6SqTQf+/5JOuoq+e0X95hcQmvxxiOdtPgq+MsHz7/ADfh//ss5ais9/Ns7+k0snfV49cE2DnXW8ekHz79gNvzXD10gmU7zb1+q6ms9t+9u5KUDTfzlv5xnNryy9v7/eOAcc8ur/JuXOL++sp2VH8m8npJSbrWr9dSGa428n+1pqa3kz15/kMcvzfOXD55nKZ7gv/zzac5OhfnY6w+UtO/5ZlR43PzJr+/n+OgCf/LdE8QTKT71k7M8dHaG99+1q+QSE14LIQT/8TV7mViIce/XjrO8kuRvHxni60+M8ju399Hd6OxZcK4IIfjPv3GQeDLFH33rWWbDK/zguct88ZEh3nVbDy8qgZQs2Y44fZnXzRfFNXT7q2+ba4p1P0dwz9EAv7wwy2d+dpHP/fwiaQnvflFPyfueb8Ubbujk0myEv37oAt9+ehyAd97aze/dscvkklmTlw408+dvOMjHfnCK6/70AQBedaCVj75uv8klsyb9zTX86esP8p9/eIpbP/5T0hL2tfn44xKpr2zFQc8/ENnmmuXMazZn5eV9PyHE+4D3AXR3O2NjSAjBX7/9CPcc7eJnZ2d45f5WXjJQmnmBsuUPXznAgY5azk6G6aiv5C03BdTezDa860W99DZV88SlIL1N1dx9uL0kM9Zmy2/d1sOtfQ187YlRjnTX8+qDbSWTsTZbcdBbT+4H0hbpflLKLwBfADh69GihymU6bpfgzj3Na5Gtiu0RQvDqg23KusqBlw40l2zyxp0w0Orjz37joNnFMJxs9xz0syy3y2Cmf5bNuZeFvp9CoVAoCki24jCced3OZaZrw7VG3k+hUCgUBSRbcTieeT0ohKja4pqbN1xr5P0UCoVCUUCyEgcp5RjwDFAO3LPxcyHEnUAALdr5caPvp1AoFIrCkkv08Scyr58SQuzW3xRCtACfy/z5SSllet1nnxBCnBVCfIKryfl+CoVCoTCGrCOrpJTfEUJ8Hi21xQkhxE+BBPAKoBb4HlrCvPW0A3szr4W4n0KhUCgMIKewWynlB4UQjwD3AncCbuAs8CXg87nO8gt9P4VCoVAUBrHdgRZ24ejRo/LYsWNmF0OhUChshRDiaSnl0U0/c4I4CCFm2T4Vx3Y0AXPXvEphd9Tv7HzUb5w7PVLKTSMiHSEO+SCEOLaVciqcg/qdnY/6jQuL489KUCgUCkXuKHFQKBQKxVUoccgk71M4HvU7Ox/1GxeQkt9zUCgUCsXVKMtBoVAoFFehxEGhUCgUV1Gy4iCEeIcQ4mEhxKIQYlkIcUwIca8QomTrxCkIIb4shJDb/HfW7DIqro0QYq8Q4g+EEPdlcrSlM7/fW7L4rurfeVKSp9YLIT4LfBCIAw9xJafTZ4BXCCHukVKmTCyiojA8Clzc5P1Jowui2BEfAP4g1y+p/l0YSk4chBBvRms4U8AdUsoLmfdbgZ8BbwI+BPy1aYVUFIovSim/bHYhFDvmJPAXwDHgaeBv0XKwbYnq34WjFE2sj2ZeP6w3HAAp5TTaTAXgI8r8VCjMRUr5RSnlf5RSfktKOZjl11T/LhAlVUFCiABwE7AKfHvj51LKXwATQBtwm7GlUygU+aD6d2EptWWlI5nXU1LK2BbXPAV0Zq59zJBSKYrFy4QQh4EaYBp4BHhQpYJ3LKp/F5BSE4e+zOt2GVxHN1yrsC/v3uS900KIt0spTxheGkWxUf27gJTUshLaDBIgss01y5lXX5HLoigezwK/DxxE+807gLuB54ADwE+FEJ2mlU5RLFT/LiClZjmIzKvKGeJgpJR/teGtCHC/EOJB4Bdo680fRfNaUTgH1b8LSKlZDuHMa8021+ifhbe5RmFDpJSrwCcyf77OzLIoioLq3wWk1MRhOPPas801XRuuVTgLPTpaLSs5j+HMq+rfBaDUxOF45vWgEKJqi2tu3nCtwlk0Zl6Xt71KYUdU/y4gJSUOUsox4BmgHLhn4+dCiDuBAFp05ePGlk5hEG/NvD5laikUBUf178JSUuKQQV9z/pQQYrf+phCiBfhc5s9PKl94eyKEuEEIcbcQwr3hfY8Q4o/QvJgAPm186RQGoPp3gSjJw36EEJ9DC6WPAz/lSmKuWuB7wFtUYi57IoR4I/BdIAicB8bR3BYPobm0poGPSin/u1llVGSHEOJGrgzooLkh+4ALaL8vAFLK2zZ8T/XvAlCS4gBaSl/gXrRBw422Ufkl4PNqVmFfhBB9aJk8b0HbmGxEc20cBx4GPiulfNq8EiqyRQhxF1qyvG2RUoqN76n+nT8lKw4KhUKh2JpS3HNQKBQKxTVQ4qBQKBSKq1DioFAoFIqrUOKgUCgUiqtQ4qBQKBSKq1DioFAoFIqrUOKgUCgUiqtQ4qBQKBSKq1DioFAoFIqr+L9SeZkPZXJkCQAAAABJRU5ErkJggg==\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "for i in range(0,3):\n", - " for j in range(0,3):\n", - " pl.figure()\n", - " pl.title(str(i)+\"<->\"+str(j))\n", - " pl.plot(t,ov2[str(i)+\"<->\"+str(j)])" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "f44dd820", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "for i in range(0,3):\n", - " for j in range(0,3):\n", - " pl.figure()\n", - " pl.title(str(i)+\"<->\"+str(j))\n", - " pl.plot(t,ov3[str(i)+\"<->\"+str(j)])" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "34312da4", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "b2efe674", - "metadata": {}, - "outputs": [], - "source": [ - "def multiple_formatter(denominator=2, number=np.pi, latex='\\pi'):\n", - " def gcd(a, b):\n", - " while b:\n", - " a, b = b, a%b\n", - " return a\n", - " def _multiple_formatter(x, pos):\n", - " den = denominator\n", - " num = int(np.rint(den*x/number))\n", - " com = gcd(num,den)\n", - " (num,den) = (int(num/com),int(den/com))\n", - " if den==1:\n", - " if num==0:\n", - " return r'$0$'\n", - " if num==1:\n", - " return r'$%s$'%latex\n", - " elif num==-1:\n", - " return r'$-%s$'%latex\n", - " else:\n", - " return r'$%s%s$'%(num,latex)\n", - " else:\n", - " if num==1:\n", - " return r'$\\frac{%s}{%s}$'%(latex,den)\n", - " elif num==-1:\n", - " return r'$\\frac{-%s}{%s}$'%(latex,den)\n", - " else:\n", - " return r'$\\frac{%s%s}{%s}$'%(num,latex,den)\n", - " return _multiple_formatter\n", - "\n", - "class Multiple:\n", - " def __init__(self, denominator=2, number=np.pi, latex='\\pi'):\n", - " self.denominator = denominator\n", - " self.number = number\n", - " self.latex = latex\n", - "\n", - " def locator(self):\n", - " return plt.MultipleLocator(self.number / self.denominator)\n", - "\n", - " def formatter(self):\n", - " return plt.FuncFormatter(multiple_formatter(self.denominator, self.number, self.latex))\n" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "afb3c2c6", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "standard\n", - "nearest_int\n", - "nearest_int_cyclic\n", - "full\n", - "overlap_10-11\n", - "random1\n", - "random2\n", - "random3\n" - ] - } - ], - "source": [ - "pl.rcParams.update({'font.size': 22})\n", - "\n", - "samp=200\n", - "t=np.linspace(0,4*np.pi,samp)\n", - "\n", - "vecs={}\n", - "vecs['00']=np.array([1,0,0,0])\n", - "vecs['01']=np.array([0,1,0,0])\n", - "vecs['10']=np.array([0,0,1,0])\n", - "vecs['11']=np.array([0,0,0,1])\n", - "\n", - "n=2\n", - "\n", - "T={}\n", - "y={}\n", - "overlap={}\n", - "for mode in [\"standard\", \"nearest_int\", \"nearest_int_cyclic\", \"full\", \"overlap_10-11\", \"random1\", \"random2\", \"random3\"]:\n", - " print(mode)\n", - " if mode == \"overlap_10-11\":\n", - " Tm=np.zeros((4,4))\n", - " Tm[3,2]=1\n", - " Tm[2,3]=1\n", - " elif mode == \"random1\" or mode == \"random2\" or mode == \"random3\":\n", - " Tm=np.random.rand(4,4)\n", - " for i in range(0,4):\n", - " for j in range(i,4):\n", - " Tm[i,j]=Tm[j,i]\n", - " else:\n", - " Tm=get_T(2**n,mode)\n", - " T[mode]=Tm\n", - " y[mode]={}\n", - " overlap[mode]={}\n", - "\n", - "states=['00','01','10','11']\n", - "for i in range(0,4):\n", - " i_str=states[i]\n", - " for j in range(i,4):\n", - " j_str=states[j]\n", - " for mode in [\"standard\", \"nearest_int\", \"nearest_int_cyclic\", \"full\", \"overlap_10-11\", \"random1\", \"random2\", \"random3\"]:\n", - " y[mode][i_str+\"<->\"+j_str]=np.zeros_like(t)\n", - " overlap[mode][i_str+\"<->\"+j_str]=np.zeros_like(t)\n", - " for s in range(samp):\n", - " eT=expm(-1j*t[s]*T[mode])\n", - " v1=eT.dot(vecs[i_str])\n", - " v2=vecs[j_str]\n", - " y[mode][i_str+\"<->\"+j_str][s]=np.abs(np.vdot(v1,v2))**2\n", - "# overlap[mode][i_str+\"<->\"+j_str][s]=np.abs(eT[ind_i[j],ind_j[i]])**2\n", - " overlap[mode][i_str+\"<->\"+j_str][s]=np.abs(eT[i,j])**2\n", - " \n", - " \n", - " \n", - "# marker=['o','p','*','v','s','x']\n", - "# markersize=[10,10,10,10,10,10]\n", - "# # fillstyle=['top','bottom','left','right']\n", - "\n", - "# count=-1\n", - "# for i in range(0,4):\n", - "# i_str=states[i]\n", - "# for j in range(i,4):\n", - "# j_str=states[j]\n", - "# count+=1\n", - "# pl.figure(count,figsize=(12,6))\n", - "# ax = pl.gca()\n", - "# ax.spines['top'].set_color('none')\n", - "# ax.spines['bottom'].set_position('zero')\n", - "# ax.spines['left'].set_position('zero')\n", - "# ax.spines['right'].set_color('none')\n", - "# # pl.xlim([0,1])\n", - "# pl.ylim([0,1])\n", - "# ax.xaxis.set_major_locator(pl.MultipleLocator(np.pi / 2))\n", - "# ax.xaxis.set_minor_locator(pl.MultipleLocator(np.pi / 12))\n", - "# ax.xaxis.set_major_formatter(pl.FuncFormatter(multiple_formatter()))\n", - "# pl.title(i_str+\"<->\"+j_str)\n", - "# mi=-1\n", - "# for mode in [\"standard\", \"nearest_int\", \"nearest_int_cyclic\", \"full\"]:\n", - "# mi+=1\n", - "# pl.plot(t,y[mode][i_str+\"<->\"+j_str],label=mode,marker=marker[mi],fillstyle='none',markersize=markersize[mi])\n", - "# lgd=pl.legend(bbox_to_anchor=(1.04,1), loc=\"upper left\")\n", - "# pl.savefig(\"snf_\"+i_str+\"<->\"+j_str+\".png\", bbox_extra_artists=(lgd,), bbox_inches='tight')\n", - " \n", - "\n", - "# for i in range(0,4):\n", - "# i_str=states[i]\n", - "# for j in range(i,4):\n", - "# j_str=states[j]\n", - "# count+=1\n", - "# pl.figure(count,figsize=(12,6))\n", - "# ax = pl.gca()\n", - "# ax.spines['top'].set_color('none')\n", - "# ax.spines['bottom'].set_position('zero')\n", - "# ax.spines['left'].set_position('zero')\n", - "# ax.spines['right'].set_color('none')\n", - "# # pl.xlim([0,1])\n", - "# pl.ylim([0,1])\n", - "# ax.xaxis.set_major_locator(pl.MultipleLocator(np.pi / 2))\n", - "# ax.xaxis.set_minor_locator(pl.MultipleLocator(np.pi / 12))\n", - "# ax.xaxis.set_major_formatter(pl.FuncFormatter(multiple_formatter()))\n", - "# pl.title(i_str+\"<->\"+j_str)\n", - "# mi=-1\n", - "# for mode in [\"overlap_10-11\", \"random1\", \"random2\", \"random3\"]:\n", - "# mi+=1\n", - "# pl.plot(t,y[mode][i_str+\"<->\"+j_str],label=mode,marker=marker[mi],fillstyle='none',markersize=markersize[mi])\n", - "# lgd=pl.legend(bbox_to_anchor=(1.04,1), loc=\"upper left\")\n", - "# pl.savefig(\"orrr_\"+i_str+\"<->\"+j_str+\".png\", bbox_extra_artists=(lgd,), bbox_inches='tight')\n", - " \n", - " \n", - " \n", - " \n", - " \n", - "# for mode in [\"standard\", \"nearest_int\", \"nearest_int_cyclic\", \"full\", \"overlap_10-11\", \"random1\", \"random2\", \"random3\"]:\n", - "# count+=1\n", - "# pl.figure(count,figsize=(12,6))\n", - "# ax = pl.gca()\n", - "# ax.spines['top'].set_color('none')\n", - "# ax.spines['bottom'].set_position('zero')\n", - "# ax.spines['left'].set_position('zero')\n", - "# ax.spines['right'].set_color('none')\n", - "# # pl.xlim([0,1])\n", - "# pl.ylim([0,1])\n", - "# pl.title(mode)\n", - "# for i in range(0,4):\n", - "# i_str=states[i]\n", - "# for j in range(i,4):\n", - "# j_str=states[j]\n", - "# pl.plot(t,y[mode][i_str+\"<->\"+j_str],label=i_str+\"<->\"+j_str,marker=marker[mi],fillstyle='none',markersize=markersize[mi])\n", - "# pl.legend(bbox_to_anchor=(1.04,1), loc=\"upper left\")\n", - " \n", - "# for mode in [\"standard\", \"nearest_int\", \"nearest_int_cyclic\", \"full\", \"overlap_10-11\",\"random1\",\"random2\",\"random3\"]:\n", - "# ymax=-1000*np.ones_like(t)\n", - "# ymin=+1000*np.ones_like(t)\n", - "# for i in range(1,4):\n", - "# i_str=states[i]\n", - "# for j in range(i,4):\n", - "# j_str=states[j]\n", - "# ymax=np.maximum(ymax,y[mode][i_str+\"<->\"+j_str])\n", - "# ymin=np.minimum(ymin,y[mode][i_str+\"<->\"+j_str])\n", - " \n", - "# count+=1\n", - "# pl.figure(count,figsize=(12,6))\n", - "# ax = pl.gca()\n", - "# ax.spines['top'].set_color('none')\n", - "# ax.spines['bottom'].set_position('zero')\n", - "# ax.spines['left'].set_position('zero')\n", - "# ax.spines['right'].set_color('none')\n", - "# # pl.xlim([0,1])\n", - "# pl.ylim([0,1])\n", - "# pl.title(mode)\n", - "# pl.plot(t,ymax,label=mode+' max')\n", - "# pl.plot(t,ymin,label=mode+' min')\n", - "# pl.legend(bbox_to_anchor=(1.04,1), loc=\"upper left\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "cc4534df", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "e01d93d7", - "metadata": {}, - "outputs": [], - "source": [ - "# fig, axes = pl.subplots(ncols=2,figsize=(24,6))\n", - "\n", - "# for ax in axes:\n", - "# ax.spines['top'].set_color('none')\n", - "# ax.spines['bottom'].set_position('zero')\n", - "# ax.spines['left'].set_position('zero')\n", - "# ax.spines['right'].set_color('none')\n", - "# ax.set_ylim([0,1])\n", - "# ax.xaxis.set_major_locator(pl.MultipleLocator(np.pi))\n", - "# ax.xaxis.set_minor_locator(pl.MultipleLocator(np.pi / 12))\n", - "# ax.xaxis.set_major_formatter(pl.FuncFormatter(multiple_formatter()))\n", - "# axes[0].set_xlabel(r'$\\beta$')\n", - "# axes[1].set_xlabel(r'$\\beta$')\n", - "# axes[0].set_ylabel(r'$|\\langle 00|U_M(\\beta)|11 \\rangle|^2$')\n", - "# axes[1].set_ylabel(r'$|\\langle 10|U_M(\\beta)|11 \\rangle|^2$')\n", - "# axes[0].set_title(r'$|00\\rangle \\leftrightarrow |11 \\rangle$')\n", - "# axes[1].set_title(r'$|10\\rangle \\leftrightarrow |11 \\rangle$')\n", - "\n", - "# marker=['o','p','*','v','s','x']\n", - "# markersize=[10,10,10,12,10,10]\n", - "# fillstyle=['full','none','none','none','none']\n", - "# legend=['standard','nearest int','c nearest int','all-to-all']\n", - "\n", - "# mi=-1\n", - "# for mode in [\"standard\", \"nearest_int\", \"nearest_int_cyclic\", \"full\"]:\n", - "# mi+=1\n", - "# axes[0].plot(t,y[mode][\"00<->11\"],label=legend[mi],marker=marker[mi],fillstyle=fillstyle[mi],markersize=markersize[mi])\n", - "# lgd=fig.legend(bbox_to_anchor=(0.9,.75), loc=\"upper left\")\n", - "# mi=-1\n", - "# for mode in [\"standard\", \"nearest_int\", \"nearest_int_cyclic\", \"full\"]:\n", - "# mi+=1\n", - "# axes[1].plot(t,y[mode][\"10<->11\"],label=mode,marker=marker[mi],fillstyle=fillstyle[mi],markersize=markersize[mi])\n", - "# pl.savefig(\"snf_00<->11-10<->11.png\", bbox_extra_artists=(lgd,), bbox_inches='tight')" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "13916c3e", - "metadata": {}, - "outputs": [], - "source": [ - "# fig, axes = pl.subplots(ncols=2,figsize=(24,6))\n", - "\n", - "# for ax in axes:\n", - "# ax.spines['top'].set_color('none')\n", - "# ax.spines['bottom'].set_position('zero')\n", - "# ax.spines['left'].set_position('zero')\n", - "# ax.spines['right'].set_color('none')\n", - "# ax.set_ylim([0,1])\n", - "# ax.xaxis.set_major_locator(pl.MultipleLocator(np.pi))\n", - "# ax.xaxis.set_minor_locator(pl.MultipleLocator(np.pi / 12))\n", - "# ax.xaxis.set_major_formatter(pl.FuncFormatter(multiple_formatter()))\n", - "# axes[0].set_xlabel(r'$\\beta$')\n", - "# axes[1].set_xlabel(r'$\\beta$')\n", - "# axes[0].set_ylabel(r'$|\\langle z_0|U_M(\\beta)|z_3 \\rangle|^2$')\n", - "# axes[1].set_ylabel(r'$|\\langle z_2|U_M(\\beta)|z_3 \\rangle|^2$')\n", - "# axes[0].set_title(r'$|z_0\\rangle \\leftrightarrow |z_3 \\rangle$')\n", - "# axes[1].set_title(r'$|z_2\\rangle \\leftrightarrow |z_3 \\rangle$')\n", - "\n", - "# marker=['o','p','*','v','s','x']\n", - "# markersize=[4,4,4,4,4,4]\n", - "# fillstyle=['full','none','none','none','none']\n", - "# legend=['$T_{Ham(1)}$','$T_{\\Delta}$','$T_{\\Delta,c}$','$T_A$']\n", - "\n", - "# mi=-1\n", - "# for mode in [\"standard\", \"nearest_int\", \"nearest_int_cyclic\", \"full\"]:\n", - "# mi+=1\n", - "# axes[0].plot(t,overlap[mode][\"00<->11\"],label=legend[mi],marker=marker[mi],fillstyle=fillstyle[mi],markersize=markersize[mi])\n", - "# # lgd=fig.legend(bbox_to_anchor=(0.6,.95), loc=\"upper left\")\n", - "# mi=-1\n", - "# for mode in [\"standard\", \"nearest_int\", \"nearest_int_cyclic\", \"full\"]:\n", - "# mi+=1\n", - "# axes[1].plot(t,overlap[mode][\"10<->11\"],label=mode,marker=marker[mi],fillstyle=fillstyle[mi],markersize=markersize[mi])\n", - "\n", - "# # axes[1].legend()\n", - "# # pl.savefig(\"snf_00<->11-10<->11.png\", bbox_extra_artists=(lgd,), bbox_inches='tight')\n", - "\n", - "# tikzplotlib.save(\"snf_00<->11-10<->11.tex\")" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "9ccbd726", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.plot(figsize=(12,6))\n", - "ax = pl.gca()\n", - "ax.spines['top'].set_color('none')\n", - "ax.spines['bottom'].set_position('zero')\n", - "ax.spines['left'].set_position('zero')\n", - "ax.spines['right'].set_color('none')\n", - "ax.set_ylim([0,1])\n", - "ax.xaxis.set_major_locator(pl.MultipleLocator(np.pi))\n", - "ax.xaxis.set_minor_locator(pl.MultipleLocator(np.pi / 12))\n", - "ax.xaxis.set_major_formatter(pl.FuncFormatter(multiple_formatter()))\n", - "pl.xlabel(r'$\\beta$')\n", - "pl.ylabel(r'$|\\langle z_0|U_M(\\beta)|z_3 \\rangle|^2$')\n", - "pl.title(r'$|z_0\\rangle \\leftrightarrow |z_3 \\rangle$')\n", - "\n", - "marker=['o','p','*','v','s','x']\n", - "markersize=[4,4,4,4,4,4]\n", - "fillstyle=['full','none','none','none','none']\n", - "legend=['$T_{Ham(1)}$','$T_{\\Delta}$','$T_{\\Delta,c}$','$T_A$']\n", - "\n", - "mi=-1\n", - "for mode in [\"standard\", \"nearest_int\", \"nearest_int_cyclic\", \"full\"]:\n", - " mi+=1\n", - " pl.plot(t,overlap[mode][\"00<->11\"],label=legend[mi],marker=marker[mi],fillstyle=fillstyle[mi],markersize=markersize[mi])\n", - "\n", - "# pl.legend()\n", - "\n", - "tikzplotlib.save(\"snf_00<->11.tex\")" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "cfc32366", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig=pl.plot(figsize=(12,6))\n", - "ax = pl.gca()\n", - "ax.spines['top'].set_color('none')\n", - "ax.spines['bottom'].set_position('zero')\n", - "ax.spines['left'].set_position('zero')\n", - "ax.spines['right'].set_color('none')\n", - "ax.set_ylim([0,1])\n", - "ax.xaxis.set_major_locator(pl.MultipleLocator(np.pi))\n", - "ax.xaxis.set_minor_locator(pl.MultipleLocator(np.pi / 12))\n", - "ax.xaxis.set_major_formatter(pl.FuncFormatter(multiple_formatter()))\n", - "pl.xlabel(r'$\\beta$')\n", - "pl.ylabel(r'$|\\langle z_2|U_M(\\beta)|z_3 \\rangle|^2$')\n", - "pl.title(r'$|z_2\\rangle \\leftrightarrow |z_3 \\rangle$')\n", - "\n", - "marker=['o','p','*','v','s','x']\n", - "markersize=[4,4,4,4,4,4]\n", - "fillstyle=['full','none','none','none','none']\n", - "legend=['$T_{Ham(1)}$','$T_{\\Delta}$','$T_{\\Delta,c}$','$T_A$']\n", - "\n", - "mi=-1\n", - "for mode in [\"standard\", \"nearest_int\", \"nearest_int_cyclic\", \"full\"]:\n", - " mi+=1\n", - " pl.plot(t,overlap[mode][\"10<->11\"],label=legend[mi],marker=marker[mi],fillstyle=fillstyle[mi],markersize=markersize[mi])\n", - "\n", - "pl.legend()\n", - "\n", - "tikzplotlib.save(\"snf_10<->11.tex\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "e9047914", - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "3b00bfdd", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "pl.plot(figsize=(12,6))\n", - "ax = pl.gca()\n", - "ax.spines['top'].set_color('none')\n", - "ax.spines['bottom'].set_position('zero')\n", - "ax.spines['left'].set_position('zero')\n", - "ax.spines['right'].set_color('none')\n", - "ax.set_ylim([0,1])\n", - "# ax.xaxis.set_major_locator(pl.MultipleLocator(np.pi))\n", - "# ax.xaxis.set_minor_locator(pl.MultipleLocator(np.pi / 12))\n", - "# ax.xaxis.set_major_formatter(pl.FuncFormatter(multiple_formatter()))\n", - "pl.xticks(np.arange(0,5)*np.pi,['$0$','$\\pi$','$2\\pi$','$3\\pi$','$4\\pi$'])\n", - "pl.xlabel(r'$\\beta$')\n", - "pl.ylabel(r'$|\\langle z_0|U_M(\\beta)|z_3 \\rangle|^2$')\n", - "pl.title(r'$|z_0\\rangle \\leftrightarrow |z_3 \\rangle$')\n", - "\n", - "marker=['o','p','*','v','s','x']\n", - "markersize=[4,4,4,4,4,4]\n", - "fillstyle=['full','none','none','none','none']\n", - "label=['$T_{2\\leftrightarrow 3}$','$T_{rand}$','$T_{rand}$','$T_{rand}$']\n", - "mi=-1\n", - "for mode in [\"overlap_10-11\", \"random1\", \"random2\", \"random3\"]:\n", - " mi+=1\n", - " pl.plot(t,overlap[mode][\"00<->11\"],label=legend[mi],marker=marker[mi],fillstyle=fillstyle[mi],markersize=markersize[mi])\n", - "\n", - "# pl.legend()\n", - "\n", - "tikzplotlib.save(\"orr_00<->11.tex\")" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "id": "43f324d9", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig=pl.plot(figsize=(12,6))\n", - "ax = pl.gca()\n", - "ax.spines['top'].set_color('none')\n", - "ax.spines['bottom'].set_position('zero')\n", - "ax.spines['left'].set_position('zero')\n", - "ax.spines['right'].set_color('none')\n", - "ax.set_ylim([0,1])\n", - "\n", - "# ax.xaxis.set_major_locator(pl.MultipleLocator(np.pi))\n", - "# ax.xaxis.set_minor_locator(pl.MultipleLocator(np.pi / 12))\n", - "# ax.xaxis.set_major_formatter(pl.FuncFormatter(multiple_formatter()))\n", - "pl.xlabel(r'$\\beta$')\n", - "pl.ylabel(r'$|\\langle z_2|U_M(\\beta)|z_3 \\rangle|^2$')\n", - "pl.title(r'$|z_2\\rangle \\leftrightarrow |z_3 \\rangle$')\n", - "\n", - "marker=['o','p','*','v','s','x']\n", - "markersize=[4,4,4,4,4,4]\n", - "fillstyle=['full','none','none','none','none']\n", - "label=['$T_{2\\leftrightarrow 3}$','$T_{rand}$','$T_{rand}$','$T_{rand}$']\n", - "mi=-1\n", - "for mode in [\"overlap_10-11\", \"random1\", \"random2\", \"random3\"]:\n", - " mi+=1\n", - " pl.plot(t,overlap[mode][\"10<->11\"],label=legend[mi],marker=marker[mi],fillstyle=fillstyle[mi],markersize=markersize[mi])\n", - "\n", - "pl.legend()\n", - "\n", - "tikzplotlib.save(\"orr_10<->11.tex\")" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "id": "c6eb6aa0", - "metadata": {}, - "outputs": [], - "source": [ - "# fig, axes = pl.subplots(ncols=2,figsize=(24,6))\n", - "\n", - "# for ax in axes:\n", - "# ax.spines['top'].set_color('none')\n", - "# ax.spines['bottom'].set_position('zero')\n", - "# ax.spines['left'].set_position('zero')\n", - "# ax.spines['right'].set_color('none')\n", - "# ax.set_ylim([0,1])\n", - "# ax.xaxis.set_major_locator(pl.MultipleLocator(np.pi ))\n", - "# ax.xaxis.set_minor_locator(pl.MultipleLocator(np.pi / 12))\n", - "# ax.xaxis.set_major_formatter(pl.FuncFormatter(multiple_formatter()))\n", - "# axes[0].set_xlabel(r'$\\beta$')\n", - "# axes[1].set_xlabel(r'$\\beta$')\n", - "# axes[0].set_ylabel(r'$|\\langle 00|U_M(\\beta)|11 \\rangle|^2$')\n", - "# axes[1].set_ylabel(r'$|\\langle 10|U_M(\\beta)|11 \\rangle|^2$')\n", - "# axes[0].set_title(r'$|00\\rangle \\leftrightarrow |11 \\rangle$')\n", - "# axes[1].set_title(r'$|10\\rangle \\leftrightarrow |11 \\rangle$')\n", - "\n", - "# marker=['o','p','*','v','s','x']\n", - "# markersize=[10,10,10,12,10,10]\n", - "# fillstyle=['full','none','none','none','none']\n", - "# label=['$10 \\leftrightarrow 11$','rand','rand','rand']\n", - "# mi=-1\n", - "# for mode in [\"overlap_10-11\", \"random1\", \"random2\", \"random3\"]:\n", - "# mi+=1\n", - "# axes[0].plot(t,y[mode][\"00<->11\"],label=label[mi],marker=marker[mi],fillstyle=fillstyle[mi],markersize=markersize[mi])\n", - "# lgd=fig.legend(bbox_to_anchor=(0.9,.75), loc=\"upper left\")\n", - "# mi=-1\n", - "# for mode in [\"overlap_10-11\", \"random1\", \"random2\", \"random3\"]:\n", - "# mi+=1\n", - "# axes[1].plot(t,y[mode][\"10<->11\"],label=mode,marker=marker[mi],fillstyle=fillstyle[mi],markersize=markersize[mi])\n", - "# pl.savefig(\"orrr_00<->11-10<->11.png\", bbox_extra_artists=(lgd,), bbox_inches='tight')" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "id": "79107243", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig, axes = pl.subplots(ncols=2,figsize=(24,6))\n", - "\n", - "for ax in axes:\n", - " ax.spines['top'].set_color('none')\n", - " ax.spines['bottom'].set_position('zero')\n", - " ax.spines['left'].set_position('zero')\n", - " ax.spines['right'].set_color('none')\n", - " ax.set_ylim([0,1])\n", - " ax.xaxis.set_major_locator(pl.MultipleLocator(np.pi ))\n", - " ax.xaxis.set_minor_locator(pl.MultipleLocator(np.pi / 12))\n", - " ax.xaxis.set_major_formatter(pl.FuncFormatter(multiple_formatter()))\n", - "axes[0].set_xlabel(r'$\\beta$')\n", - "axes[1].set_xlabel(r'$\\beta$')\n", - "axes[0].set_ylabel(r'$|\\langle z_0|U_M(\\beta)|z_3 \\rangle|^2$')\n", - "axes[1].set_ylabel(r'$|\\langle z_2|U_M(\\beta)|z_3 \\rangle|^2$')\n", - "axes[0].set_title(r'$|z_0\\rangle \\leftrightarrow |z_3 \\rangle$')\n", - "axes[1].set_title(r'$|z_2\\rangle \\leftrightarrow |z_3 \\rangle$')\n", - "\n", - "marker=['o','p','*','v','s','x']\n", - "markersize=[10,10,10,12,10,10]\n", - "fillstyle=['full','none','none','none','none']\n", - "label=['$T_{2\\leftrightarrow 3}$','$T_{rand}$','$T_{rand}$','$T_{rand}$']\n", - "mi=-1\n", - "for mode in [\"overlap_10-11\", \"random1\", \"random2\", \"random3\"]:\n", - " mi+=1\n", - " axes[0].plot(t,overlap[mode][\"00<->11\"],label=label[mi],marker=marker[mi],fillstyle=fillstyle[mi],markersize=markersize[mi])\n", - "lgd=fig.legend(bbox_to_anchor=(0.9,.75), loc=\"upper left\")\n", - "mi=-1\n", - "for mode in [\"overlap_10-11\", \"random1\", \"random2\", \"random3\"]:\n", - " mi+=1\n", - " axes[1].plot(t,overlap[mode][\"10<->11\"],label=mode,marker=marker[mi],fillstyle=fillstyle[mi],markersize=markersize[mi])\n", - "pl.savefig(\"orrr_00<->11-10<->11.png\", bbox_extra_artists=(lgd,), bbox_inches='tight')\n", - "tikzplotlib.save(\"orrr_00<->11-10<->11.tex\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5435a352", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "dd2c3897", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b1877a1e", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f23a620a", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a0b86486", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a6787077", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5daa70e7", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 38, - "id": "ed752e72", - "metadata": {}, - "outputs": [], - "source": [ - "Id=np.array(([1,0],[0,1]))\n", - "Xd=np.array(([0,1],[1,0]))\n", - "Zd=np.array(([1,0],[0,-1]))" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "id": "e4490f35", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(1+0j)\n", - "{'0': array([1, 0]), '1': array([0, 1]), '+': array([0.5+0.5j, 0.5-0.5j])}\n" - ] - }, - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 39, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "samp=200\n", - "t=np.linspace(0,4*np.pi,samp)\n", - "\n", - "vecs={}\n", - "vecs['0']=np.array([1,0])\n", - "vecs['1']=np.array([0,1])\n", - "\n", - "# gamma=np.random.rand()*2*np.pi\n", - "# gamma=4*np.pi/3\n", - "# vecs['+']=1/np.sqrt(2)*np.array([1,-1])\n", - "\n", - "# eZ=np.cos(-gamma)*Id+1j*sin(-gamma)*Zd\n", - "# vecs['+']=eZ.dot(vecs['+'])\n", - "\n", - "\n", - "vecs['+']=1/np.sqrt(4)*np.array([1+1j,1-1j])\n", - "print(np.vdot(vecs['+'],vecs['+']))\n", - "print(vecs)\n", - "\n", - "marker=['o','p','*','v','s','x']\n", - "markersize=[10,6,8,12,10,8]\n", - "# fillstyle=['top','bottom','left','right']\n", - "\n", - "n=1\n", - "i_str='+'\n", - "mi=-1\n", - "pl.figure(figsize=(12,6))\n", - "# for mode in [\"standard\", \"nearest_int\", \"nearest_int_cyclic\", \"full\"]:\n", - "mode=\"standard\"\n", - "mi+=1\n", - "yy1=np.zeros_like(t)\n", - "yy2=np.zeros_like(t)\n", - "Ttmp=get_T(2,mode)\n", - "for i in range(samp):\n", - " eT=expm(-1j*t[i]*Ttmp)\n", - "# eT=np.cos(-t[i])*Id+1j*sin(-t[i])*Xd\n", - "# print(eT)\n", - " v1=eT.dot(vecs[i_str])\n", - "# v2=vecs[j_str]\n", - "# y[mode][i_str+\"<->\"+j_str][i]=np.abs(np.vdot(v1,v2))**2\n", - "# print(np.vdot(v1[0],v1[0]))\n", - "# print(v1[0]*np.conj(v1[0]))\n", - " yy1[i]=np.abs(np.vdot(v1[0],v1[0]))\n", - " yy2[i]=np.abs(np.vdot(v1[1],v1[1]))\n", - "pl.plot(t,yy1,label=mode,marker=marker[mi],fillstyle='none',markersize=markersize[mi])\n", - "pl.plot(t,yy2,label=mode,marker=marker[mi],fillstyle='none',markersize=markersize[mi])\n", - "# print(yy)" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "id": "e045d2e1", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[0. 1. 1. 0.]\n", - " [1. 0. 0. 1.]\n", - " [1. 0. 0. 1.]\n", - " [0. 1. 1. 0.]]\n", - "[[0. 1. 0. 0.]\n", - " [1. 0. 1. 0.]\n", - " [0. 1. 0. 1.]\n", - " [0. 0. 1. 0.]]\n", - "[[0. 1. 0. 1.]\n", - " [1. 0. 1. 0.]\n", - " [0. 1. 0. 1.]\n", - " [1. 0. 1. 0.]]\n", - "[[0. 1. 1. 1.]\n", - " [1. 0. 1. 1.]\n", - " [1. 1. 0. 1.]\n", - " [1. 1. 1. 0.]]\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 40, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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\n", 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\n", 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HgV7AJD+0a2vtbXIHt0NRuobEDDCHgatKyxc3GDo2LcQWDffvg3klcPtX2rLz/qItVxRFUZRuxNfe49G1t5lSyqpm1vmmwbrtMaj29mgHt0NRuobhc7Q0EID4gdptqKSFJI7QShxmfdHRLVEURVGUoPM1GO9Xe5vTwjoHG6zbJkKIXsDc2ocfdlQ7FKVLSZ8Jx3do91+fpaWHHN4SGmkhBoM2AVDWF9qkRIqiKIrSjfgajEfW3la0sE557W1UWxsjhDABbwLRwCop5af+bocQ4rbaMohb8vPz29pURelcbNEw5gYwh8MjxVp6yP37QictZMDZUHkC8n7s6JYoiqIoSlD5GoyL2lsZqIbUegWYAeTS9ODNdrdDSvmqlHKclHJcjx492roZRel8CrIgbgAIcep1g21AbeGkfas6th2KoiiKEmS+BuNltbeRLayjP1fWwjrNEkI8C9yCVrJwhpTyWEe0Q1G6rMIsiO/f0a1oWkQPiOwFqx+HjS91bA10RVEURQkiX4Px7Nrb1BbW6dtgXZ8JIZ4Gfg7kowXie5tZNaDtUJQuy+2ComytZzzU6DXQhUELwjM/7tga6IqiKIoSRL4G43qpweFCiLBm1hnfYF2fCCGeQpuJswA4V0q5oyPaoShdWnEOeFwnK6mEkkWzYfB5MPsFkG44876OrYGuKIp/edyw8UWYP0xd+VKUJvgUjEspc4HvAAtwZcPnhRDT0GqCHwM2+rpzIcQTwP1AEVogvq0j2qEoXV7hfu02PgR7xhMzwJ4MqVPAFAZZX3ZsDXRFUfxHv/K181PthHvHJ/DcaPjbYBWYK0qt1sxS+Xjt7ZNCCG/3mhCiJ/BS7cMnpJSeOs89LoTYJYR4nAaEEH8CHgSK0QJxX3uyW90ORen2CvZpt6GYpjJ8DuxYDGYbpJ0BWatCpwa6oijto1/5+unHUFUCrmrtCpjHAzuXqJQ0RQFMvq4opfxACPEy2pTzPwohPgecaNVP7MBi4IUGL0sC0mtvvYQQlwC/r324D7hHNF3hYZeU8gk/tENRureCLLBGQ0RCR7eksfSZsPJ3Wu1zXWUhXPaPjmuToij+kZihDdBedCnkbjq53BIJl/8LfnhPC9jv3d5hTVSUjuZzMA4gpfyZEGIdcBcwDTACu4B/Ay+3ojc6rs79cbU/TVkDPNFwoR/boSjdg15JJRTLGtqitZrnAPm74cUJMOPh0KmBrihK63ncsPkVOLgRDqwBZxX0GAp9J0DOBig+CO/fAGNvUilpSrcnpAx06fDQNW7cOLlly5aOboaiBN4zIyB5AlyxoKNb0jIp4e/Doc9YuOqNjm6NoihtUZAFi3+m3XfVwNEGWagRPeC8v8DHt2lX7AwGmPoATLwdDMbgt1dRgkQI8a2UslEHdGtyxhVF6YxcNVByKDQrqTQkhDYb5/41WjlGRVE6Hz1PvO9ELRC/4Cntape9jxaIV+RrgThATQkMvUTljyvdmgrGFaWrK8oG6QnNSipNGXC29gV95LuObomiKG2RmAFhsbBlAYy4UuvxtveBpJFaStq8EojuC2f/AQadD9+/BbNfVCVNlW5LBeOK0tWFciWVpvSfrt2uflzVJVaUzmj4HNj0MjjKYcovtWUNKyQlZmgB+cXPao+/+Zcqaap0WyoYV5SuTr/sG9+/Y9vhq6oisERA7tdaXWJ1+VpROpf+Z8GJ2om0X5miVUo6vEWrnKTTS5rak7T7370BP/5HlTRVuqVWVVNRFKUTKsyC8HjtsnFnsGg29B4L2Wuh92iYuwzW/12VP1OUUKdXUFnzFCDhp4thwFlNr9tUSdODm+CKfwejpYoSUlTPuKJ0ZR437P8Kaso6T7pHYgakTAIk7FulVVpQl68VJbTpM23uWALmMO3q1ponm7+ipZc0nVei/SRPgMieYIkKbrsVJQSoYFxRuir9y7H0EKRO7jzpHsPnwLEftaoLOz/VlqkZORUltOkVVCbdCWVH4ZLnWzcgc+JtULgf/jaw83QcKIqfqGBcUbqqRbO1S8RuhzbN/NxlnaNaQfpMLb+0Il/LKW0q31RRlNCSmAH2ZPhuEUSnaCfPvl7RKsiCr/8JRgvYe3eejgNF8RMVjCtKV5WYAUazdj+uf+dJ99AvX//0Y+3xVW9pj9WMnIoSuobP0QZgHvgKhs/WJu/x9YrWotkw+HyY9hvtqtjFz3WOjgNF8RMVjCtKVzV8Duz6r3Y/tp9225nSPdLOBFuM1kumKEpoS58JuZvB44QNz7fuipbeqz7yKu3x7v92jo4DRfETVU1FUbqq9Jnw33u1+/+srWgQ0QMu+0fHtak1jGYYchHsXAouB5gsHd0iRVGaY4vWJuzK2QC/2q1difOVXuZw5FVaBaVd/4XwBG25onQDqmdcUboqWzSMug6s0fBIsVaxoLOlewy9RJuN88Cajm6JoigtcVbDvs9hyIWtC8RB6zg49I3Wm35kq3b/0NdqnIjSbahgXFG6ssIDEJsKQnR0S9qm/3QwR8LqJ9RsnIoSyg6s0WbcHDKr9a+tW+bwzo3asrP/0Lk6DhSlHVSaiqJ0ZUXZ0HNoR7ei7UoPg9kKR7+Ha96FtU9rOeSzX4T4AR3dOqWTc7lcFBYWUlJSgsvl6ujmdG6VkTDzA3D2gZ0727EhARd8DNLUzu0oSmAYjUbCw8Ox2+1ERUUh/NDZpYJxRemqPB4oztEuG3dWi2ZrU2tv/0Are6Zm41T8xOPxkJubi9VqJSUlBYvF4pcv1W5HSqg4DqXVYIqHHuntvxJXYtdKm/YarFVlUZQQIaXE7XZTXl7OiRMnqKqqomfPnu3+7FBpKorSVZUd1WqMx6Z1dEvaLjED+k/TZuX74b3OU55RCXlFRUWYTCaSkpKwWq0qEG8LVzWc2AuVhdpj6YGCvdry9rDZAQl5mVB+XAv4FSUECCEwmUzExMSQmppKRUUFZWVl7d6uCsYVpasqytZuO3MwPnwO7F4OGXO0sow15Z2rPKMSssrLy4mJiVFBeHsUZGmBszUKENBjMFjt7Zusx1UNpUe17ZnDoLrYPwG+oviZ0WgkLi6O0tLSdm9LBeOK0lUVHdBuO3MwrldZ+G4ROCvg8T5qNk7FL6qrqwkPD+/oZnRuJpuWPlZTBpZIMJi0x6awtm9TD/DDYsFZBXED2x/gK0qAREZGUllZ2e7tqJxxRemqirJBGCG6b0e3pO30KgtSwvNjIKo33PTfjm6V0gV4PB4MrS3Bp9QXFgtVhVqvdVSstqyqSFveVnqAb7Jp23ZWtD/AV5QAMRqNuN3tr/ClPokUpasqyoboZG3ynM5OCBh1LeSs08o1KoofqBSVdrLZwVHbK1h2VKsR7qyszfluo7BYqCoGa6T2uKa8NsCPaW9rFcXv/PUZooJxRemqirI7d4pKQyOv0W7/e5+qOa4oocBggvA4wABJI7XZM3uN0Ja3lc2u9YYf+1F7XH6s/QG+ooQ4FYwrSldVeKBrBeOuGm020ez1cPHzWr3xhRepXFJF6Ug15WAJB+GncMJg0gL63qMhsicgoOew9gX4ihLiVDCuKF1RTRlUnuhawfii2TBwBrhrwGjSao4POldbrihK8Lld4KqqraYSAJYoQIKjIjDbV5QQoYJxRemKinK0264UjCdmwICzISwONr+iao4rSkdzlGu3lsjAbN8SUX8/frBw4UKEEMydO9dv22yP7OxshBCkpaV1dFOUDqSCcUXpivQa43H9OrQZfjV8DuxeBhP+T7vN36NqjitKR3KUs/C9TxG2qMAEtwYjmMO1K32K0oWpYFxRuqKuMOFPQ3rN8TVPao9fHK9qjitKR6opB5M1sPuwRmkDONVgbaULUyMiFKUrKjqg1ehuT73fUKPXHAdYei9sfRPuWK8tV5QQl1NQwesbcliy7TCFFQ7iIixcMrIPN05OJTU+oqOb1zpSQnmeli8e6OqQlkggT8sbVxVVlC5K9YwrSlfU1coaNnT63eB2wMe3qTKHSsj7cvdx5ry0AZvZwId3TmbPny/gwzsnYzMbmPPSBr7cfbyjm9jI7t27ufHGG0lNTcVisRAVFUVaWhpzLr2ED197AaqKSJt4ETfd8xsAXn/9dYQQ3p+6aSs7duzg4YcfZvLkyfTu3RuLxUKPHj248MILWbFiRZP79+Z2334PZeWV3P/AA/Tr1w+r1UqfPn248847KSwsbPK1UkoWLFjAmDFjCAsLIyEhgUsvvZQffvih2d/X6XTyxhtvcM0115Cenk5UVBTh4eEMGzaMBx98sNl9paWlIYQgOzubxYsXc9ZZZxEbG4sQgu+//9673tq1azn33HOx2+1ERUUxZcoUPv7441P8FZTuQvWMK0pX43HDke+1QU8bX4KJt2u5l11NWCwcWAtXvQkbntNKHc5+EeIHdHTLFMUrp6CCX72/jX/eMI6xqSevVKXGR/DAzCHMGJrI/y3awsc/mxwyPeQ//vgjU6ZMoaysjCFDhnDxxRcjhODw4cP8b+VnVJWXcfnlc7jionPYtD2L9es3MCCtL2dMO9u7jTPOOMN7f/78+SxYsIChQ4cycuRI7HY7+/fvZ/ny5Sxfvpynn36a++67r8m2lJSWMuXSmzl8LI+pE8eSMWQQ6zZ9wyuvvMLXX3/Npk2bMJvrT2x211138fLLL2M0Gpk2bRo9e/bk66+/ZuLEidx0001N7icvL48bbriB2NhYhgwZwqhRoygtLWXLli089dRTfPDBB2zevJmEhIQmX//000/zwgsvMGHCBC644AJyc3O9M7y+++67XHfddXg8HkaPHs2QIUPIysrisssu4957723V30bpoqSU3fZn7NixUlG6lBP7pPzXuVI+Ei3l+zdKueB87efEvo5umX/NHy7lp7+U8hG7lOuekdLtlvKrv2nLFcUHO3bsCMp+Hl2SKZ9cvrPFdZ5YvlP+8dPMoLTHFzfddJME5GOPPdboubLsbXLDFyukPL5Lyvzd8rXXXpOAvPHqy5rd3urVq+WBAwcaLd+0aZO02+3SbDbL3Nzces/p2wXkhTPOlGV71klZWSRl/m55+MevZN++yRKQb775Zr3XLVmyRALSbrfLzZs3e5e7XC55zz33eLd544031ntdaWmpXLJkiXQ4HPWWV1ZWeo/HHXfc0eh3SE1NlYA0mUxy6dKljZ4/fPiwjIyMlIB8+eWX6z337rvvSoPBIAGZmpraxJFTOoPWfJYAW2QT8ajqGVeUrmTRbBh+GeRuhn7TYMyNsP7v2vJ7t3d06/wnMQP6ToKSQ7Dmr3Da1arMoeJXj36ayY4jpe3ezrc5RQzvbeeqf2xsdp1qp5sdR0vZfrikXfsa1tvOIxcPb9c2QOslBrjgggsaPRfZI5nTIyO0CieRPU4+YbQ0u71p06Y1uXzixIncfffdPPbYY3zyySfcddddjfcXEc6CF+cTGWEEISB+EL2tdu6+8Sc8+Of5rFq1iuuuu867/jPPPAPAvffey4QJE042z2jkr3/9Kx9++CFHjhxptJ+oqCguvvjiRsvDwsJ44YUXeOONN/jwww95+eWXm/xdbrrpJi666KJGyxcsWEB5eTnTpk3jjjvuqPfcVVddxfvvv89HH33U5DaV7kMF44rSlSRmaBPiAMSmdt1a3MPnwI7FcP7j8NIkWPVHqCzQlitKCHF5JFZTy8OzLCYDTrcMUotObcKECSxbtow77riDP/3pT0ydOhWrtbZqis2unQQjofz4yTkNjOZmtwdQVlbGf//7X77//nsKCwtxOBwA7N27F4A9e/Y0+bqxIzPolZwGJbm1gzijwWhhSHo6QL3A2uVysX79egCuv/76RtuyWq1ceeWVPPvss822c+vWraxatYrs7GwqKirQOjPBYrGQn59PUVERsbGNB8ZfdtllTW5vzZo1zbYH4Kc//akKxhUVjCtKlzJ8Dmx8Qbsfk6rdZi7uekFq+kxY+Tt4Yaz2+Ps3wRQGR7/XgvKumievBI0/epgBxv35M/565cgW88FzCiq4/OWNvHf76X7ZZ3vdf//9rF27llWrVnHeeedhtVoZNWoU06ZN4/rrr2dEvyQoPQQ9h0PsNu1FovkTjk8++YSbb7652UGQAKWlTV+FSElNg+pSMIednImzqgh7Qi8AqqurveueOHGCmpoaDAYDqampTW6vucl1ysvLue6661iyZEmzbdTb2VQw3tz+Dh06BEC/fk3P+aAm+1FAVVNRlK4lfSYU1Jb/e34MzIvumrW49TKH80rgtq/AYNaC70te1AZyLrwICrI6upWKwiUj+/DeN7ktrvPuN7nMHtU7SC06tfDwcD7//HM2bdrEvHnzmDp1KpmZmTz11FOcdtpp/PEvj2v/c6bmU1N0hw4d4pprrqGwsJDf/OY3/PDDD5SWluJ2u5FS8o9//APA2wPdkMFsBWcFOKu0QelHtmp1xy3+Hez60EMPsWTJEoYNG8aSJUs4cuQIDofDm9OblJTUYjvDwsL82h6le1HBuKJ0JbZoGDZbS02ZV6L93L+va9fifu86GHKR9kVdmgtzl8Ggc7U8eUXpYDdOTuXdb3L5Nqeoyee/zSnivW9yueH0pntWO9LEiRN55JFHWLlyJQUFBbz22muYTCbmPfkMu3OO+bSNpUuXUlVVxeWXX87jjz/OiBEjiIqK8lYa2bdvX8sbEAYtzU6/0peQrj1u4spXQkICVqsVj8fDwYMHm9xcdnZ2k8v/85//APDee+9x8cUXk5SU5K3SUlFRwbFjvv2+DfXp06fF/Ta3XOleVDCuKF1NUc7JL67uIDEDBs+EflNh2QNaqkpXzJNXOqXU+Aie/slI/m/RFp5csYucggqcbg85BRU8uWIX/7doC0//pOU0llBgsViYO3cukyZORErJD7sPeJeDlq/dFD01pW/fvo2eq6mp4cMPP/SxAbXHx1nR7Comk4nJkycD8NZbbzV63uFw8MEHH7S6nW+//XazPeKnog9ebao9LS1XuhcVjCtKV1Ocow3e7C6Gz9FSU654DSIT4d3r4Ku/wsGNajIgJSScld6Tj382GYfLw+Uvb2TIH1Zw+csbcbg8fPyzyZyV3rOjm1jPSy+9xO7duxst379/P5k7MgFI7T8QONnzu3Pnzia3NWTIEAA+/PBDb5UW0ALje+65h/379/vWKKMFDCZwVLa42s9//nNAq22+ZcsW73KPx8ODDz7I4cOHW2zniy++WG/5li1beOihh3xrYxNuueUWIiIi+PLLL/nnP/9Z77kPPvhADd5UADWAU1G6FlcNlB6BmJSObknw6IM5/1p3sh8BVyyEr19RkwEpISE1PoI/zBrGH2YN6+imnNKrr77KXXfdRf/+/cnIyCAyMpJjx46xbt06HA4HV88+nwmTpwIwadIkevXqxXfffce4ceMYPnw4ZrOZKVOmcNNNN3HJJZcwevRotm7dyqBBg5g+fTo2m43169dTUlLCz3/+c5577rlTN0oIrXfcUd7iapdeeim33XYbr776Kqeffnq9SX8OHz7MnXfe2WR5wocffpgrr7yS3/3ud7z//vsMHTqUI0eOsG7dOq6++mrWr19PTk5Oq49lnz59eOWVV7jxxhu57bbbeOWVV0hPT+fAgQNs2rSJe++9l7///e+t3q7StaiecUXpSvSSY90pTaXuYM7ovlqddSRkfgDXvAvWKHhhvOolVxQf/fnPf+b222/HbrezYcMGPvjgA/bu3cu0adN4f8FzvPXK096cbavVyooVK7jooos4cOAAb775JgsWLPCW9DOZTKxZs4YHHniApKQkVq5cydq1a5k6dSrffvsto0eP9r1h5ghwO8DtbHG1V155hVdffZWMjAzWrVvHihUrGDp0KBs3bqxXe7yuK664gi+//JKzzjqL3NxcPv30U0pLS3nmmWd44403fG9jE66//npWrVrFjBkz2LNnD59++img5anrPflK9ybamgfVFYwbN07WvYylKJ1e1hfwxhyY+19IO+PU63c1b1+tpa1UnoD//RbM4RDRAyJ7ape4QfWSK4CWVjF06NCObkbnIiXkbQervWNS4WrKoWAvxPaHsC48KF3pVFrzWSKE+FZKOa7hcpWmoihdiT4BR3fqGa9Lnwzomndg7XxtlsDSI5B+IZzzKLx/vdZLfu4fAQmbXoZJPzv1/dPvVrXLFcXtAI8LLOEds39zOCC0QZwqGFe6EBWMK0pXUpyj9QDbQ6dmcVDp+ePz6nxRCyNsfhm+XailrPQYAmue0J4741envj/zSfhuEWx+BVzVMOWXKjBXuh8poeyodt/l0B4LEdw2GAxgtkFVEVQWale8InoEvx2K4metzhkXQlwrhFgrhCgRQpQLIbYIIe4SooXpt5reTroQ4hdCiDeFELuEEB4hhBRCXHGK1y2sXa+5n12t/Z0UpcsoPgjRyd03UKybPz7nVa1H/Pd5EBanTeNdcRyOZ4LRBtGpsOpRSBoFSWO0+71Og57DtPu9x0LfyVq6i8cF0gMej5pUSOl+XNVwYq+WJoLQZsIs2KstD3Y73C6thz4mBaqLO6YdiuJnreoZF0K8CPwMqAZWAU5gBvACMEMIcaWU0tcRUncCv2jN/htYDzQ1W8DRdmxTUTq37lZjvCV6L/mfEk4us0Vrgbk1CopzAQnZa08+f3BjbW65hAOrTy4//C3E9QdLJFz3AXxwk5buct6fVS+50vUVZEF4vDYtvdECCYOgPE9bnjg8uO2wRGhBuMEE8R3UDkXxM5+DcSHE5WiB+DFgqpRyb+3yROBLYA5wN/Csj5vcDvwV2AJ8CywApvnccviXlHJhK9ZXlK6vOAfSL+joVoQGvZccYNt7J3PJ9fv2PhCVBOXHtF7vqCTti11K7X7ZEa1qQ1E29EiH7HVQUwp/HQjhcdBnjNZLrkonKl2dyQZGM7iqtKBcCC0oNwV5CniT7WQw7qzQctc7oh2K4met6RnXq94/qAfiAFLKPCHEncBq4DdCiOellJ5TbUxK+a+6j4XK+VKU9nFUQkV+96ox7qumcslbozBLy001xmuXyUsPQ8JguO4/sOE5WDQb7t3u3zYrSqgIi4XKAu2k1Vwb+FYVacuD3Y6qopOT/0R0UDsUxc98CsaFEMnAWMAB/Kfh81LKNUKIw0AfYBKwwZ+NVBTFB8UHtduYtA5tRkiq20veWtUl8PxY7URHZwqD/V/Csvuh70ToNcI/7VSUUGSzQ0mudr/4oPZjMAW/vKHNrp0Ie1xQVaj9dEQ7FMXPfO0Z16vyZ0opq5pZ5xu0YHw0wQnGzxJCnAZEAnnAOuAzX3rlFaVLKq4ta6i+mPyruXSXzx+FdfNh56cg3dqkQip/XOmKDCYIT9BOSJNGdlz1EoNJO/EtO6ZVduk14uT8AYrSifn6Lu5Xe9vSXLAHG6wbaDc0sWyHEOJqKeWPQWqDooSO7l5jPBiaSnepPAFjb1b540rX5qzUUlRCIaXUXFvn3FmlDcZWlE7O13KEkbW3FS2sU157G+j/jO+BnwPD0drVG5gFbAOGAZ8LIfoEuA2KEnqKc7QBTpE9O7olXVfd0onRfeGs38OAc+C7hXD+YzDoXC1/XFG6Eim1wNfcQZP9NKS3w9FSSKIonYevwbh+KiwD1RBfSSmfkVI+L6XcIaWskFIelVL+F5gAbAJ6cnKwaSNCiNtqa6Nvyc/Pb241Rel8inO0wZuh0HPVHSRmaMf7igVaucTlD2pVWFT+uNLVuB1aKpY5RKqWGE1gtGq99YrSBfgajJfV3ka2sI7+XFkL6wSMlNIBPF778MIW1ntVSjlOSjmuR48ewWmcogSDqjEeXMPnaPnjYTFw7qNw6GvY9BIMu7SDG6YofqYHvaHSMw5aWUOHCsaVrsHXYDy79ralb/q+DdbtCPrsmypNRelePG44sQdyNmgDCT2+zr2ltFn6TDj0jZY//sld2rJjP8Jnf1B/A6VrcVYBQpuKPlSYw8Hj1HrtFaWT8zUY31p7O1wI0dx1qvEN1u0I8bW35S2upShdSUEWLDhPmxJ6xOVquvZgqZs/fs93WtoKQPJ49TdQuhZnpTYeRfgaMgSBJUK7Vb3jShfg03+WlDIX+A6wAFc2fF4IMQ1IRpudc6M/G9hKP6m9/aYD26AowbVotjYbJMCAGTB3mRpIGGyLZkPGZTD2Jti9HC55Xv0NlK7BO3gzRPLFdaYwQHS5vPHp06cjhGD16tUd3RQliFpzmqvnYz8phBioLxRC9AReqn34RN0630KIx4UQu4QQj+MHQohRQohZQghjg+UmIcR9aFVWAP7uj/0pSqeQmHGyxyo2FQwGbap3NZAweBIzwJ4M0x/S/hbf/Ev9DZSuwe3UJtkJpXxx0D7nzLYOr6iyevVqhBBMnz69Q9vRnHnz5iGEYN68eR3dFKUFPlfLl1J+IIR4GbgT+FEI8TngBGYAdmAx8EKDlyUB6bW39QghxnAyiAetLCHAY0KIX9fZ76Q666QBHwOFQog9wCG0Uooj0EoceoAHpZT/8/X3UpROb/gcbfIZODmAM3OxtlwJDn0w58irtB7yrW9BwT4Y8ZNTvlRRQpaUUH5Mu++u0R6HUrUmczhUFsKx7VpJ14geodW+Nli0aBGVlZWkpKR0dFOUIGpVApiU8mfAdWgpK9OA84F9wN3A5VLK1oxYsgMT6/zo9ckHNVhe1zbgWWA3kAJcXNuOSuA1YIKU8qnW/E5K4JQ5yrh/zf2UOTqkwE73kT7z5IQ/T/XTBhQe3qIt74JC8n1VdzDnD++BowwObgqJv0FIHq8Q5/a4yS3Lxd2dB+G6quHEXqgp1R47KqFgr7a8gQ45Xq5qqCkHpFZStLq42faFouaOWUpKCkOGDCE8PMSuRHSwrv4/2erRGFLKt6WUU6SUdillhJRyrJTyxaamoZdSzpVSCinl3CaeW137XIs/DV5zQEr5SynlZCllHymlTUoZJqUcJKW8WUr5bWt/H8W/6n7xr85dzYrsFazOXd3BrQpddY9Xm4MmWzT0mwqJI7TBhPNKtIGFtuhTv7YTqvu+CplAs+5gznkl0Hei1lNn6fjZAdX/YeuVOcoorSnt+PdVBxLmMETPdDCF8d7SLzj9khuJTBtNVEw8M2bMYN26dd51Gx6viooKnnrqKcaPH4/dbicsLIzhw4czb948yssb11coKyvj1Vdf5dJLL2XgwIGEh4cTGRnJ6NGj+ctf/kJVVVXjBhZkIXoNR/QZAwIWLP6KiTOvxh6bgBCC4uJi76o7d+7klltuoV+/fthsNmJjYznnnHNYsmRJk7/7kSNHuPvuuxk4cCA2m43w8HBSUlKYOXMmr776qne96dOnc9ZZZwGwZs0ahBDen1OlrTT3HmsuZ3zu3LkIIVi4cCH79u3j2muvJTExEavVypAhQ3jyySfxeOqHYUIIHn30UQAeffTReu3rbGkrXf1/MoSGRitdQd0v/pXZK5nSeworc1Z2dLNCVt3j1a6gqThHyxfvBuq+r0I20Jzwf1C4H/42sMPLHNY9XiFz8hLiSh2lRFoiKXWU+rdHzuOGjS/C/GEd/r7w1cN/+SvX3vkAFouFi2aeR3LvJL744gtmzJjBxo1avYa6x+vQoUNMmDCBBx98kJycHE4//XTOO+88ioqKePTRR5kyZQpFRUX19rFt2zZuv/12Nm7cSO/evbnkkks4/fTTycrK4ve//z3Tp0+nurpBj7fpZJnFe375a267/XasNhuzzjubsWPHImrTVd59911GjRrFv//9byIiIpg1axannXYaa9euZfbs2Tz88MP1Nnv06FHGjh3Liy++iMvlYubMmVx88cWkpKSwadMm5s+f71135syZnH/++QAkJiZy4403en9mzmz5qljdY9Ya33//PWPHjmXz5s2cddZZTJ48maysLH7zm9/wi1/8ot66N954IyNHjgRg5MiR9do3atSoVu23I9T932vr8eoshJQdPqlmhxk3bpzcsmVLRzejSznt9dOQtRO1mgwm3rjgDeaumEuNuwYAs8HMdz/9riObGFLuWXUPTo8Ts8GMW7pxepzYTDaeP/t53zciJTzWW6vkMfOxwDW2A415YwxOjxPQ3kOvnf8at6y8xfu+Egh+uPGHjmziSQVZsPhOOLIVegzVJicBmP0ixA8IShMaHq+bMm5iYeZCHLU1mY3CyPc3fB+UtoSqnTt3MnToUO/jHQU7qPt92CeyD0cqjtRbNjxheNt3WJAFi3+m5TRPewDW1GZUBvF90Rp6MBsXE83KJe8z9szzoCALjzWaO+77Lf/85z+ZNG0S//rgXwDYrXZKa0q57sLr2PbNNq695Vr++dw/vekWVVVV3Hbbbbz55pvceOONLFy40LuvQ4cOsWfPHqZPn47BcLKPsLi4mGuuuYYVK1bwxBNP8OCDD55sYGUhIkKrZhxtj2LlZ58zYUA8hMVCeBwAP/zwA+PHj8disfD+++9zwQUXeF+emZnJBRdcQG5uLl988YW3h/uPf/wjjzzyCLfffjsvv/yy9zgA1NTUsHnzZqZOnepdtnr1as466yymTZvWYgUUt8fNrsJd9Zal2lM5WHbQ+x4TQvCzy3/GmjVr+PLLL+v1rs+dO5fXX38dgEceeYSHH37Ye6y++uorb/uzs7Pp27ev93Xz5s3j0Ucf5ZFHHul0veGZJzLrPe4Z3pP8qvx6x2tY/LCmXhpUDT9LWiKE+FZKOa7hcp8HcCpKc+p+8ZuEiTR7GvtK9uHyuLjmv9cAMLn3ZGb1n8X0vtM7sKWhoe7xas6I17UqHD6dvFTka+W9unDP+Jqr1rA6dzXv7HqHH0/8yPXLr/c+d9uI21i4Y2HrjlkgLZoN426CQefBF3+Cu76GXUu15fduD0oT9OP1yb5P2JK3hVd/eBUDBsKMYfSO7E1SZKMx9d1eemw6ZY4y8irzcHlcuJffT9qJfYB2sieEAGM7Jr059A1E9dKq7nz1NGCA0kPw0ulabXp/6DUCLnjCP9uq9eivb2fsgB7ayaXBhCE2lT//+c/885//5LtN3yE8AmmQlNaUsm7VOrZ9s42R40by7HPP1st7DgsL45VXXmHlypW89dZb/P3vfyc2NhaA5ORkkpOTG+07JiaG5557jsGDB/PBBx/UD8Ztdu/dB+68gQnJ5kafg3/5y19wOBw888wz9QJxgOHDhzN//nyuvPJKXnjhBW8wm5eXB2i93qLBYFCr1VovEG8N/WpUlCXKe/9oxVHMBjNmgxmP9JAc1fgYNDR+/HgeeeSRem2bOnUq559/PsuXL+fLL7/khhtuaFMbQ02kJZIadw1Ot/Z9ebzyOGaDGavZSrQlmqgQSAP0FxWMK+2mf/H/Z89/2Hp8KyWOEmxGGxJJjbuG0xJOY1b/WVw84OKObmpI0I/XkqwlfH30axLCEiioLkAgcEkXsdZYhsYP9f3kRR+8GdN1g/EoSxQXD7iYRZmLMAojF/a7kP9l/w+Hx0FOWQ69I3rTO7J3aJzw6WUO+0+HL/4M2z+CuH5BLXOoH6/Pcz7HXTuu3oOHKncVDo+Db459EzonLyGksKYQl8flfaz3wNlMNqrcVVQ4a8voCYgwRbRu45YIMFpPVvsQQntsaeV2gmzWOVO197TR7F3Ws2dPYmJjKC4qJj8/n15JvYizxfHVZ18BcNHsi6h0Na7/HRERwbhx41i2bBnffPMN5513nvc5KSXr16/nq6++4tChQ1RVVSGl9P4N9uzZU39jhpPhy2UXng0Jg+sdS4/Hw4oVKxBCcMUVVzT5u02bNg3Am24DMGHCBF566SVv4H/uuecSEdH+v1GpoxSbyUaZowyTwYTJYKLaVY3JYMJitFBUXUSlDzXTL7zwwkYnCQBDhgxh+fLlHDlypN1t7UgNr1A15PQ4SbAkUOYsU8G4otSlf/EvP7AcgPcvfp8rllyByWDieOVx9hbvZdn+ZXx16CsePv3hLvUP1Bb68dqWv41NRzfxyORHeP675xFCEGYKI7Mgkwv7Xej7yUtxbTDehXvGAXYV7mJX0S7ibfGsP7KeWFssJTUlrMpZxYSkCaFzwle3zGHaGZD5sRaMD78saE0oc5Tx27W/5atDX2lBo9CCHZfHRW5ZLonhiQyIGRAaJy8horimmCpnFUIILEYLx6feh0QLBnuG96S4phiL0XKyR85gPPVG69r2nva+uOadk8vevhqm/lp7r4SolL596wXiuojICIqLiqmpqcHlcXG88ji5ObkAPPaHx3jsDy2nzOXn53vv5+Xlcdlll7Fhw4Zm1y8tbT5XOLVPklbtpU4wXlBQ4H1Nz549fW7LT3/6U1auXMnbb7/NnDlzMBqNZGRkMHXqVK6++momT57c4rbqqhtYCiG8910el/ekz+VxUVJT4nM+dHMlD+127UpBo9z6Tka/QlVcU0yFs4IoS5T3JFj/fzxReQKnx0mUOYoYW0zHNthPVDCu+IXT42TT0U1EmCO4fMnlONwOwkxhzM2Yy2vbXyO3LJecshymJk8NjYApBCw/sByzwcwf1v/Bm/tswECNu4Y3Mt9g3eF1vp28FGVrtzFdty5tmaOMu1fdjVEYOSf1HK4cfCW//PKXGIQBl3Sxu3A3FqMlNN5b6TNh5e+0Moe6iuNw2avNv8bPVueuZvWh1QCcm3Yu1w+9nr9/+3d2F+2mxqW910Lm5CVEnKg6AYBBGIg0RxITGUNeZR4VjgpKHaVYjVbsFnvbv/ybel9E9IDL/tH+xgeQwXoywK0bXOpjg+ryuLVqHuMnjyc5NRmDMGAxWDAbzI16c1NTT3Ye3HrrrWzYsIEpU6Ywb948Ro4cSUxMDGazGYfDgdVqbbGNYRGRjWbidLu1K0JGo5Hrr7++qZc1/fsaDLz11ls89NBDLF26lPXr17N+/Xqef/55nn/+eW6++WYWLFjg07b0wLLEUUKVswqP8HjHB9UdEOyRHhLCEsgpzfEGntkl2c22ryszGozE2GKodFVS4awgISyBKlcVNpONnuE9OVh6EKfHSYQ5glJHqQrGFaWudYfW4fQ4mdJ7CnePvptPsj7hWMUx7h51NysOrKCwupDJvSezMmdltw8Ayhxl/Gr1ryh1lDI+cTwPTniQ+1bfB8Dfpv2NW1feSk5ZDruLd/t28lKco32ph/jl7vZ4b/d75FXmMT15Or+f9HsAhsYPpVdEL7bmbeVA6QFMIkQ+zvQyhwDl+fD0YBh/a1BLTX6490MA+kb15U9T/gRo6ShxtjhySnMoryxn+YHl3f5/seEl8fiweAqrCymoKqCgqgDAm07gMXra9+Vf933RmZjDvHfr9lp6nzaaibREEm2Jpn9af9aznvMuOY+bbr+JeFv8KY9XRUUFy5Ytw2g0snTpUmJi6q+/b58Px8wc0WgmzoSEBMLCwqiqquKFF14gMjLy1NupIyMjg4yMDEBLeVm2bBnXXnst//73v7nqqqvqpdg0Rw8sASqcFUSYIxAI7Ba7N3e8qEZLT6lwVmA2mDHWXnHpG9W3hS13faWOUoQQHCw7iMlgotxRTrnjZFlMk8FEqaPUO8gzVAZztlXXPsVSgqLMUcafN/2ZWGss88+aT3pcOg+Mf4DVuasZ++ZYjlYcpcxZxnmp57HxyEZGvD6CEa+PYMwbYzq66R1ide5qNh7diMVg4bmznyM9Lp3/XvZf/nvZfxkaP5R7x95Ltbua4fHDfSsLWZTTpfPFAd7Z9Q4GYag38HX+9Pk8MP4Bbsy4kQpnBRf0uyD0yvZF9oC0M7W88QBXrhrzxhjv/9bW41uxW+zkVeZ5l605tIaJSRP5/cTfI5EUVhcGtD2dQXpsOn0i+2CuTcNICEvAbNCCyz6RfYiyRHmvTBkNxiZzdbu8OsG4HlxajSd7qi0GLXUnxhbDlLOnAPC/Jf/D6Xb6lHZRUlKCx+MhKiqqUSAO8NZbb526jZZwbYbQOvn+JpOJc845B4APPvjg1NtogcFgYNasWcyePRvQSjF6d22xAOByuZp8LUBRTRFSSiqdlTg8Dkodpd5jGWuNxSiMlDvKsRqt3k4FY2vToJrhS/tCjcvjwu1xYzVaSbOnEWmOJMoSRZ/IPkRaIjEIA2WOsnr/q+mx6R3d7HYJka4kpTP7NOtTjlcdZ2qfqZgNJ3ML9YGKn2Z9ytfHvmb9kfUkRSSFzkC7DrJ0/1IEgh7hPYi0nOytaVhlJcwU5j15gRYG2hXnQJ+xAW93sDU8HlcOvpIlWUsaHY8ZfWcQZ4vjnz/+k12Fu0IvFWr4HFj6Szj2IySdFrDd1P1/23R0E+elnceWY1vq/b9FWaKQUvLKD68Qbgrn/jX3d+txHHpAdLzqOEZhxGQw1UtH0Xs1q93VSCm7Z2+lKazRorpBtlM6vVcMZl48k9NGn8aWDVt45FeP8Pt5v9fm2q5j//79LF++nLvuugvQ6nPHxsZSVFTE22+/zbXXXutdd8WKFfXqejfLXFu1xVFZr8rKww8/zIoVK/jFL36BzWbjqquuqndC5fF4+PLLL3E6nd664IsWLSIjI4MxY+p3FhUUFHgHetZNsenTpw+g9eC7XC5MpsZhlZ4fnhKVQpmzrN7nmt4DXOWqwmq0egdc+4vevp07d/p1u4Gkv7/6RPbBZrLRy9Sr3vMuj8s7+FU/EezsVDCutNt7u98DtC+suvSBigAHSg6w5dgWTutxGuennR9awVIQ1A0sjcKIRJJfmV8vsNSDqaX7l7KjYAdb8rbQN6ovfaP6Nn/y4nFDyaGgDg4MFv14/Hv7v9lXvI+rh1zNN8e+aXQyZzaauWzQZfzrx38xLnFc6KVCDb0Elt4HK38PBfvg9Lth4u2tHwB4Cvr/W25ZLhuPbmRir4mcqDzBeWnn1TseQgguHnAxr2x7BSD0Tl6CzOVx4XQ7MRlM7Crc5b38XfcLPtoSzbGKY9S4arCaWs5f7nIa/L5SStzSjUALaiNMEd4ANzU6lf8u+S/nX3A+77/+Pss/Ws7IkSNJTk7mxIkTHDx4kD179pCYmOgNxo1GI7/73e/49a9/zXXXXccLL7xAWloaWVlZfP311/z2t7/lscdOMX+CXsvfWT8YHzduHIsWLeLmm2/mmmuu4Te/+Q3Dhg0jKirKW9v8xIkTPPjgg95g/KOPPuLGG2+kT58+jBo1ipiYGAoKCli7di0VFRWceeaZzJkzx7uP1NRURo8ezdatWznttNMYO3YsVquV9PR07r//fkD7n4swRxBh0X7q0p8rqSnxXqHxp/PPP5/w8HA++ugjpk6dyoABAzAajVxyySVccsklft9fe7k9bo5XHsditNS7AqMrdZR6U8tq3DVdJm9cBeNKm9QNLgWCYXHD2Ja/rcle3JXZK5FIimqKOFByIPSCpSCoG2h/m/ctGXEZlNSUNOq11I9Ltaua745/R5QlquWBdqWHtUuzXbCSin48PtjzASaDiYExA0mzp9ULLhv2no9IGMHbu94OrbJ91cVgi4LcTXD1u/DVU7BzScAme1mRvQKAxzY/RkJ4QpP/bxf314LxVHtqt/x/rEsfMBduDqdHWA+Ka4obzQNgt9g5VnGMYkcxjioHvSN6+y2NIOQ1SM2pcmklBw1Cy3LtEd6j3hWD5ORkvt78NY+/8DirlqwiMzOTzZs3Ex8fT58+ffj1r39dL5gF+NWvfkVaWhp/+9vfyMzMZPv27WRkZPDmm29y3XXXnToYN5i0MpGOxqUBr776asaPH89zzz3HZ599xpo1awDo1asXY8aM4aKLLqpX+lBvy4YNG9iyZQtFRUUkJCQwZswY5s6dy3XXXYfZXD9o/uijj3jwwQdZs2YN77zzDm63m2nTpnHfr+7jUPkhalw1xEbENtn0vlF9kVJS7izHKIxNBqDt0atXL5YuXcof//hHtm7dyrp165BSkpycHJLBeHFNMW6PmwhLRJNpYUII7YqyA+2ksIukjqkZONUMnG1S5ihjde5q3t/9Pt/nf88fJv2BN3a80Si4BLhv9X1EmiP5eN/HjE8cT4wthvnTfbj02AV9tOcj5m2cx9yMuRwoPtCo1xK0WTkPlx9mb/FeYqwxjOo5qvkZOQ+shddnwU8Xw4CzAv8LdIDxb4731uKND4unT2Qf7/HQ34dL9y/lm2PfMKHXBA6XH27yfdhh/p4BvUfBzk/httXQaySs/ztseS0gkwBNe28aHunhX+f9yzuQWv9/a3gSnWJP0Xp8u+EMufqseYfLD1NWU0Z6XHqLX+wHSg7gdDtxepz0iezTJXrjmiWlllYVFgsx9VNz8iryKKgqID0uvcUTkpzSHGrcNYSZwoJz8lKUDTVlWk30EAnQiquLOVx+GIDBsYNb7Pk+VHaIcmc56bEtvw+7un1F+6hx1xBhjiAtOq3Z9Xx9HwaDmoFT6TB6r+WWY1v4Pv97xvcaz9pDa5sMLvVA4OtjX2O32rttIA7w8b6PkUg+2P0BvSJ7NdkraTaamdR7ElajlcPlh+vl4TfSxWuMH6s4RrW7mrEJY3lowkPe4FJX92pCdkk22/K3MTZxbGilQiVmQL/psHMp7P0Meo8Ge5+ATALkcDuocFZw5eArtYHUcQ/Ue77uFZpdhbvIKc0hOTKZFHtKtxzHIaWk3FHebC9cXXrveLg5vMtcGm+W2wHSXW/wJmgpBIXVhYSZw04ZAEWZoyh3lON0B6ketDkcqoogLxMie2oVpjo4qC11lHqvIJwqBSXKEkVJTQlVrirCzeEtrtvVNKxqZDVZqXRVtlgpJcIcwYmqE1S6Kju+w8UPVDCutMuGoxswCANzV8wlPiy+xUve43uN58vcL/FIj/cDqrspd2qlmZ476zm+OPRFvcBSp5+svPT9S7yy7RUenfxo8xssygFhgOiuObDs27xvAXhg/ANNBpe6ldkr8UgP5c5yskuyQyv1Qp8EKGkk7FsF0x6AzMXacj/blr+NGncNE5MmNvl8w1SowupCoq3R3bbmeI1bm7Am0tx82buGgUK4KZyC6oIuU1KtSc4q7bZBMF5UU4RHelruIKgVZYniaMVRLEZL4E9eXNVQWVsdKDxeSw2rLtbmXjDZArffJjQ30c+p3i8RZi2XvMxRRkF1QbdKhWo40Y/dYqekpqT+JFsNhJvDEUJQ7ixXwbiilNWUkRSexLNnP9uo17Kh8b3Gs3jfYvYW7SU9rnOXIWqr3pG98UgP45LGMS6p0ZWqesYkjkEi+f7495yZfGbTKxXnaL2sARj4Ewq25G0hyhx1yrJVZqOZSUmTWJy1mF6RvXwKFoJGn+ylonaWv3nRAZvsZdPRTRiFkXGJLb+3Vmav9JaAPFJ+JLROXoLEIz3eFIKWgvG6E7dUOCtweByYDeYWA4VOTUqo1CZAoqZc63Gu7WHW64u7PM2XyWt48mIQBsqd5YE9eSnIgvA4KKsGPBA/CMrztOWJw/27r1Oo+3755e2/9ObXGwzNT4AE2sRHvUf0psRREryrCSFCr2pU466hwllBmCmMald1i5NsGYSBCHME5Y5ycj25nf7kRQXjSpuVOkqpcFUwN2Nui72Wugm9JgDwzbFvumUw7pEeth7fynmpp54sAuC0hNMwCRPfHf+u+WC8i9cY33JsC6MTR5/yQ3b+9PlIKfnq8FckhifylzP+EqQW+kCf7CVnA7x2AfxkEQyb7ffdlDnKeH/3+wyJHVKvZGZT9FQo/WpCSJ28BEm1qxpc2uQhLaUQ1J24pdpVTZVTmw2wXbNxhipXNRQd1G4NZqgpYUfNiXpzbZqN5hZTCOrNOumqotpVjcVoCezJi8mmDeA027RBnEKA0dJkWcZAq/t+WfzuYp9fN336dNLHpHO88niXm13SV3oHweHyw01WNWpID8YdbkenP3npnrkCil9sz9cGn43sMdKn9XtF9KJvVF82HNkQepOzBEFWcRZljjJG9xzt0/rh5nCGxg/lu7wWBtQV53TZfPETVSfILs1mbKJvNdSFEIzsMZJt+dtOvXJHSB4PligtVSUA/pf9P4priukR3uOU6+oTJk1ImkCpo5Snpj4VkDaFsiq3lorh62A5vfax0+PE4Xb4NKFNp1OQpZUGFEZtRt/4QaRb4+jjOXn1INIc2eJkK3owGm2JxmLQJpypWw86IL2XYbFQVazNxOms1Hr3q4ogLMb/+/KRPjtk5olM9hbtJackByllkz+ZJzIZP2s8xyuPA1qKj341IfNEJjsKdnTY7xFMbunGIAzeiX5O9b+pp/ZYTdZO//+ognGlzbblb0MgGJHg+0C08b3G882xb1iRvYLVuasD1rZQtPX4VgCfg3GAMT3H8OOJH73VLrw8blj3DJQdhbI87XEXs+7wOgCGxfl+SXtUz1HklOaE5uySRjP0nwZZXwRkNs6P9n4EaHm9vjqtx2lUuarIKs7ye3tCUd1ZSh0uB6ClXPgS9AghvAPrLEZL16x4YbJpZQI9Di1fXAiMRisxxjBvfWybyYbVaD1lcF3qKMUjPQCBP3mx2cFZoaXXSA8c/b5RzfGOIKUk2hJ9ysBSnwlWDy71VKiuMrukrwRa2UKbyebtvGvKjoIdZJ7IZH/xfkCbBbazn7yoYFxps2352xgQM+CUl8TrGt9rPNXuakb2GOnbVO9dyNbjW4m3xbdqFr8xiVopup99/rOTVxIKsuC1CyHzY+1xcTYsvEhb3oUszVoKwLHK5schNKSf6Gw7HqK94wNnQEkunNjjl83VDS53FOzALMzsKtzlXTbmjTEtvv60BG1G0B9O/OCX9oS6NVet4bEzHmNy78ne4MjXoKdvVF96R/QGtIC0S87GGRZ7ciCkXtGjtoe5pKYEgOMVx71TurdErwdtFEaMwhjYkxeDSatO1GOI9jgmRXts6LhM3B5h2hWqSEtki4ElnLyaEGONwSiMVLuqfTrh6UqcHq1saJgPqUX6yUukJRKDMFDlqur0Jy8qGFfaxCM9/HDiB59TVPSg4aG1DwEwKWmSd6p3X4KGzq7MUcaqg6sYkTCiVV9KY3pqx+XrY1+fvJKwaDYMPg/O+p32+OLnYNC52vIu5McTPxJjjWHVQd/TOobFD8NkMPF9/veBa1h7DJih3fopVaVucGkymBjZcyRJEUlM7j2Zx854jDVXrWnx9X2j+hJjjeHH/B/90p5Qp1eTmdV/FgKB2WBuVdBjNBixmqxUuaqC1OIgs9lB/90Ks+DIVm8Ps97LnWJP8SmFoG9UX3pF9CLMHAaC4Jy8mGxadakmJv8JNj0NypfgUlfqKAUBlc5Kn054upJqlzaDty/Hq24qlNloxuVxecckdNaTFzWAU2mT7JJsyhxlPgfjdesbf330a/aX7CcpIqnR1OZd1Sf7PmlT/dgYWwzhpnAsRsvJiheJGWBPhpKD2kpx/bTe1gDUrQ62hjNq/iT9J7yz6x2fZ9S0Gq0Mix/Gt8e+5f419/Pw6Q+HVrWL2FSIGwDf/hs2vgCn3w0Tb4c2fnnowaVHeth0ZBND44eSW5rbZL3/pgihpZn9kN89esZ1K7NXMsc+B5d0eYMeXwd/hZnCKHOUIaXseqkqBhPYYrTJc3pl1HvKYrRgEAbCzeGt+hwLM4VRXlkenJK2Qmg9+s4QCMZdVRgNxlYNjhZCYDPaqPBUEGYMw4MngC0MLZUu7W/W2pMX/SSxxl3TqQe9qp5xpU02H90MwMDYgT6tX7dHKtYWy56iPaTZ07z1jUMqYAqAT/d/CkBeZZ5P69dNP6hx1+BwO05eSXBmMub7v0DxQa2CQGQvrW71sEsD9wsEid7TOzROm81savLUVvX0AozqMYrMgszQHJdQkAWOCjiRBRfNh51L/JJi9EnWJ3jw8NHejzhccbhVKWCn9TiN/SX7u9WAaiEEEkmMNcanXt66wkxhuD3ueieNXYqzslF9cSklVS6tikxr2Yzaa/Sez4CzhGt10j0dG8hWu6oJM4W16r3VN6oviRGJgJbe0iVToZpR7arGZrK16oRNCOEdWNxcycjOQgXjSpvoX/YHSg607nW1k7PklOZwqPxQl84brxtQ7y7cjdVoZfuJ7T6l5tRNP4i1xVLpqiTeFq8FpRP/wJr8Slj/LLhr4I+xcHiLVs+6k9NP2lKiUgBtCunWnrSN6jkKl3RxWsJpoff+WjQbBpwNeMBkgbnL/JJipAc6806fx6SkSa3qjTst4TQkkp9/8fNuE5DfMuIWQKsMcqp83ob0nrsumari8WhlDRsE4y6PC7fH7Q2sWyPox8scAciT6TYdwCM9WnDZhuNlNVoRiOCdvIQAKSWVzspW9YpD7TiOyN5aeVKDuVOfvKg0FaVNdhTsIMYaw2c5n3HJgEt8fp3ZaCYjIYM1h9YwKGYQLtn85BGdXd3UnG/zvmV4/HAKqwt9Ss2pO1PiR3s/4kTVCWKsMSdnShzyE3h1OoTFwU8/CsrvE0xb87diMpi4ZPElp5zZVdcwxWVy78m8lvmazykuQZGYASmT4If3IHu9Fpjb+7Q7xWhi0kR2Fuzk7JSzmdmvdSdlGT20dIQteVtYnbu6W0z+s7twN/HEt6mn12q0IoSgylVFtDU6AK3rQK6mZ97UA+nWBkuglTU0GozBCy71FBpHpVaesQO0Jv+5IYMwYDVZqXZ3n2C82l2NR3qwGq1ter3NZOv0x0sF44rPGgY7lw++nPd3v9+qYGf+9PnkluWy5tAaJiRN4IrBVwS0zR1JD6illGw+uplBsYPIq8jzOZ8XtCsJehWDY5XH6gelRTnQ2/cyiZ1JpbOSxLBEn2Z21dU9+dl8dDO55bmhNy5h+BzYsRh6j9ImAQItxWj4nHZtdnfhbvrF9MNitLT6tXaLnXBTOFajtdvMxLmzcCdTzVPbNNmRQRiwGW1UuirJLev8M//V42w6GNcDnbacvAghCDOFeQc0BpzRrE1Y5KwATl1zPxDac/IC2nHusuMSmlBUrZVj1fO/W8tmtFHhqAjOuIQAUcG44jM92Hlr51tkFmRyetLprD20ttXBjl5PdU+Rf8q7hbpP93+KW7pZun8pvSN7tyrg0WdKrHRVeqs/ANoAq6rCLjn7ptPtpNpVzVXpV/k0s6uu7tWEXYW7yCrOIs2e1qqTn4BLnwkrfwcV+drjedEQ0QMu+0e7Nru7aLd3hltf1T25NggDZqPZOy4BQuRKQoDsLtzNjKQZbQ50wkxhFNUUUSWrOv3Mf/U4q7RqJA16KKtd1VhN1jYHOjaTLfiDODuooorb46agugCjwYipjaUVbUYbxZ5iXB5Xi7PDdhXlznKg7alMNpMNiaTGXdPmE6COpoJxxWd6sLPpyCYyCzIZFDuoTcGOQRgYFDOo2wTj+iXL34z/DXuK9/jUy6ubP30+APmV+fx44kfvY4pytNsuOPvmgdIDuKSLwbGD2/T6ldkrkVKyq3AXbo87tHp7bdFw/z7YtQzevUbLGU+b0q5NFlcXc7zyeKtr69a9krCrcBeF1YUkRyaTYk8JnSsJAeDyuNhTtAdTn7Z//YWZwiisLiTcHN6pKzg04qzyTvZTV5WryjshTVuEGbUA6WDpQfpG9Q38lQRLONSUwLHtENlTO+ENUg9zmaMMp9uJzWRr88mefgWi2l3dZYPxHQU7kHUmPwszhXkn7gHtisqweN8mfPMer9pBs51R5+zPVzrUlrwtGDBw1dKrWl25QTc4djB7CvfU+2fsqvSg5uzUs3lg/AMnA+pWGBQ7iMPlh6lwVmgLimuD8S7YM66fpLU1GDcbzd4P8WHxw9qUihBwKZO024Mb2r2p3UW7ARgc17rjVbfCkT5gNs4W1+UrHOWU5lDjrmnT+0Kf+e9w+WGgi01bLmsHPTYoW+j0OHF5XO0KcvTXVjgrAj9I2FWtTVQEEJEA1cVQsFdbHgQlDi2tsK0pF9OnTyfSEsnX67/umoOEazWcdTTcHN7miXvOn3E+GT0y+OLLL+otnzdvHkII5s2b58+mB4QKxpVWq3JVERcWx6vnvtrqyg269Lh0ypxlreol7qz2Fu8lMTwRu6XtUzMPihkEwL7ifdqCoq4djJsMJlKj2/a7zZ8+n5+P+TkA0/pOa9PJT8CFx0HP4Sfzxtthd6EWjLd11rmV2Su9AdKRiiOhV4HGz3YW7gRoU49jwwDC6XF2+pn/vFw12lTyDfLFK2trdrdlPILOZDAhhMBkMAV+IpuCLK1Wui5+EFjtAZuhePXq1QghGD9lPJknMr0dJk6Ps10naWaD2S+DXkM1INUn7tFn8LYare2eddThdvi7mUGj0lSUVpFSIpFMS57WqnzehvRezz1Fe0iKTPJnE0POvqJ9DIod1K5t6K/fW7RXm2ipOAcskVpQ18XsLdrLgOgB7erR7h/dH4FgX9E+zk0914+t86PU02Hbu+B2gbHtH8W7i3YTb4snPiy+Ta83G81M7jOZ/Kp8bUa7ULyS4Ee7C3djMVgwidYfcz2AAK1TosZVg9VoxW6xd/5UFb0XtkEPeGmNFjy3pa56w1QEg8HQ5lQEn5lsYLJqee+OSi09xWhp9Hv5m9VoJdISSZWrCrd0YzKYvMFla64yLVq0iMrKSgyxBqpd1V1vkHAD+vsrryIPk9HUrrQvh9tRb9Dr3XffzdVXX01CQoK/mhswqmdcaZWC6gKKa4oZGOPbZD/N0V+vX2LvqpweJ/tL9nt7ttuqd2Rvwk3h7C3aqy0oytF6xbvgSPs9RXvanKKis5lspNhT2Fu810+tCoDUyeAoh2Ptm/1yT9Ee0uPa3iM7f/p8Hhj/AEPihhBhjgjNKwl+UuYoY0nWEu1krR3/O6WOUgSCCmdF15i2XEqoOKHdd5Rpj2tVuioRQlDuKG/1ZvUrCZGWSIwGIw63I/BXEsJioapYK2vorNB+l6oiCIvx/77qMBlMRFuiMWDAKIzYjLY29fKmpKQwZMgQYqNicXqclNaUdun6//osoyn2lFZPwNXUtuqeNCYkJDBkyBAVjCtdj54m4evMm83RP4y7+iDO3NJcnB5nu3vGDcLAwNiBJ4PL4pwuOXizpKaE45XH2328QDvh86b1hKKUydptO1JVnB4nWcVZfglqBsQMIKskq0uP4/jy4JcUVhe2Ox9eCIHVpFUcCTeFtyqAKHOUcf+a+0MnwHJVw4m92uBNowWqS9hRsAMhBEIIXB4XXyz5gktmXEJ4RDgRkRFMmjqJdevWNbvJiooKnnrqKSZNnERKzxSGJA7h4ikX8+JTL1JTWdMoSC0rK+PVV1/l0ksvZeDAgYSHhxMZGcno0aP5y1/+QlVV07nTehsBFixYwMSJE7H3SkMkDKD4WA54XHD0e3ZmbueWu39Fv379sNlsxMbGcs4557BkyZImt3vkyBHuvvtuBg4ciM1mIzw8nJSUFGbOnMmrr77qXW/69OmcddZZAKxZs4bYsFjS49MZmjCUKy+8sk0nadOnT0cIwZb1WwCtY6HUUcrcuXMRQrBw4UL27dvHtddeS2JiIlarlSFDhvDkk0/iaTDrqBCCRx99FIBHH33Ue7zam7ZSUFDAww8/zOjRo7Hb7URERDBo0CDmzp3Lhg3a51l2djZGo5G4uLhm/35Op5MpQ6aQ0SOD7L3Z9Sbgqqio4G9/+xunn346MTExhIWF0b9/f6688kqWLVvWbNsOlx/G7XEDp07R2blzJ7fddhsDBw4kLCyM2NhYTjvtNH7961+Tk5PT5uPTFipNRWmVrGIt7669PeOg9Zp09WB8T7H2+/njeA2KGcSqg6uQHg+iKAf6TWv3NkNNewdv1jUwZiCrc1dT465p82QSAWVPgrj+WjA++e42bWL7ie04PU5S7Cntbs7AmIFUOCs4VnGsy6aOfbr/UwCKa4rbtZ2+UX0pc5Rx0HmQGGsM4Q0GPbZkde5qVmSvYGry1NCo8lOQBeHxUFGjpb7FpJBefnIszwtPvMCrf3+VsZPGcvb5Z7N3x142r93MjBkzWL16Naeffnq9zR06dIjzzz+fHTt20KNHD04//XSkSbLtu228/NeX+WLZF/znv/8hJjXG+5pt27Zx++2307NnT9LT0xk3bhwFBQVs3ryZ3//+9yxZsoQ1a9ZgszVd5/yee+7hpZdeYsqUKcyaNYs9e/YgEgaCM493P/+OG//vZzgcDoYPH86sWbPIz89n7dq1rFq1ij/84Q/88Y9/9G7r6NGjjB07lmPHjpGamsrMmTOxWq0cPnyYTZs2kZ2dzW233QbAzJkzsdls/O9//yMxMZEzZ5zpHUcwOH1wm3p59Rz9Y5XHSCGFSEskBVUFFFcXA7Bq0yp+8YtfkJCQwFlnnUVeXh7r1q3jN7/5DYcOHeL555/3buvGG2/k+++/Z9u2bYwcOZJRo0Z5n6t7vzW2bt3KRRddxNGjR4mLi2P69OnYbDZycnJ45513AJg8eTJpaWlcfPHFfPLJJ7zzzjvcfPPNjbb14YcfcjzvOJPOnMSwYSfTlXJycjj//PPZvXs3kZGRnHHGGURHR5Obm8vy5cvJz8/nwgsvbPb4lTnKTpnqsmjRIv7v//4Ph8NB//79mTVrFk6nk3379vH000+TkZHB3Llz23SM2kRK2W1/xo4dK5XWeWT9I/KMd86QHo+n3dt6YesLcsTCEfLeL++VpTWlfmhd6Hn+u+flaa+fJqtd1e3e1ps73pQZCzPk8fxdUj5il3LjS35oYWjx/o4Vx9u9reUHlsuMhRlyV8EuP7QsQD6+Q8o/J0r59BApN7wopdvVqpc/uuFRmbEwQ/5z2z/b3ZQtx7bIjIUZ8qvcr9q9rVAyetFombEwQ2YszPDeH71otPz868/l9vztMvNEZpu2W+Oqkdvzt8vCqsJWve7uz++Wt6+8Xd696u427dfvTuyTsuy4lIe/k7IsT1tWUSABCcjo2Gi5esNqmVOSI4uqiqTb7Zb/93//JwF5zjnn1NuUx+ORp59+ugTk3XffLSsqKqSUUh4sPSizjmfJWVfOkoC84tor6r0uNzdXrlq1Srrd7nrLi4qK5MyZMyUgn3jiiUZN97YxOlpu3ry5/pMet9z22XvSYrHIyMhIuWzZsnpPb9++Xfbt21cC8osvvvAuf/TRRyUgb7/99kbfc9XV1XLNmjX1ln355ZcSkNOmTZNOt1Nuz98u8yvzmznYpzZ12lQJyHeWviO352+Xh8oOyT2Fe+Tl117u/X0feeSResdqzZo10mAwSIPBIA8ePFhve4888oj3Ne1VWloqk5OTJSDvuOMOWVlZWe/548ePy7Vr13off/755xKQzcVaZ555pgTkP984+fnldrvl6NGjJSBnz54tCwvr/3+VlpbKzz//vN6yadOmSUAuXLxQ7izYKXNKcqSUzf/uX3/9tTSZTNJoNMp//etfjf7OO3bskDt27PDtoNSu7ytgi2wiHlU940qrZBVnMSBmgF9mBRscOxiJ5LOczzir71mh0UvkZ3uL9pISleKXnlm9t3jv4U3avHJdrJJKmaOMN3e8SbQlmoSw9uf46Xn6e4v3tiunOmAKsuDgZi09YOYT2mDOnUtg9osQP8CnTWw6ugmB4Pv879vdHP3qTVZxFmcmn9nu7YWKuvXUdxbspKimiKSIJKxGK30i+zSbsvLk10+yq3BXi9uudFZiMphOWWnk27xvkWjpPwLBiIQR/HjiR+8ESwLB2MSxrf/lGhgSN4QHJzzYuheFxZ6chErv4ddLAwJ3PXAXiYMTvbnxMbYY/vznP/PPf/6TtWvX4nQ6MZu1Qb8rVqxg48aNTJo0iWeffRaDQcuE7RvVF6LgT/P/xKbVm1j8/mKKXigiNjYWgOTkZJKTkxs1LSYmhueee47BgwfzwQcf8OCDTf9uDzzwABMmNJj0Shj4ywsLcTgcPPPMM1xwwQX1nh4+fDjz58/nyiuv5IUXXvCmm+Tl5QFar3fD7zmr1crUqVObPZQ17hpAm7SnrQTaPiPNWp69fmXPYtDeY+PHj+eRRx6p17apU6dy/vnns3z5cr788ktuuOGGNu+/JQsWLODQoUNMmjSJl156qdHx6dGjBz16nJz1dMaMGQwbNoxvv/2Wr7/+ut7faPv27axdu5aevXoy+9LZ3uVLlixh69atpKWl8c477xAWVn/gbVRUFDNmzPA+3lGww1vBxoMHgfAOEj5eebzJ3+Mvf/kLLpeLBx98kFtuuaXR80OHDm3FUfEPFYwrPpNSklWcxYX9m7481Fp6cDkwZmBoTcziR/uK9/ktEPQGlyd+YDJ0uZzx1bmrOVR+qN2D63Qp9hRMBhP7ikI0b3zRbBg2Gza+AB63NgHQ+r9ry+/d3uzL6s6cKRAMiB7ApqOb2j1zZrRVOwkK6Tz7Nqg7M+v+4v30COtB/+j+hJnC2l0BRQjhHYDWkpE9RlJSU0JBdQEOtwOL0YLFaMFqtBJviyfaGt2udrSLzQ4ludr9gtoxKXVmjpx23jRS7CmUOkq977uePXsSGxtLUVERBQUF9OrVC8Cby3v55Zd7A/G6Yu2xDB81nDWfreGbb77hvPPO8z4npWT9+vV89dVXHDp0iKqqKm+vIcCePc2nNF522WWNlnk8HlZ8sQ4hBFdcfnmTr5s2TUv127hxo3fZhAkTeOmll7yB/7nnnktEhG8THunBuD86XyqcFSChylmF1WT1HvsLL7ywyc/HIUOGsHz5co4cOdLufTdnxYoVANxyyy0+f0bffffd/OxnP+Oll16qF4y/+OKLAFxxwxVEWE8eX30f1113XaNAvCnpsene420URlwel/f/q6lywm63m88//xyAW2+91affIRhUMK74LK8yjzJnWbvzn+sGEwAZCRksP7C8y03DXemsJLcsl1n9Z/llezG2GOJt8bx9bAOXCUFUF+sZ/1/2/zAIg99qxZoNZvpF9wvd4DIxA3qN0GYHPLQFxt8C9j7ashbU7endfHQzQ+OH4pIuekf2bvfMmQNiBnjHhXQ1K7NXUlxTjEu6OFxxmOq4lms4+9LDfKjsEJXOSp8nXPo061NW5qzk+bOf555V97R69uKAMJi0OtzOSkgc3ujplJQUws3hjfLi7XY7RUVFVFefPI779+8H4P777+f+++9vcbf5+fne+3l5eVx22WXewX9NKS1tfjBkamrjz8KCggJKy7RBsj0TE31uy09/+lNWrlzJ22+/zZw5czAajWRkZDB16lSuvvpqJk+e3Ox2alw1GIQBk6H9oZU+SLjSWUm46eSxT0lpenyI3a4FnnX/Hv6mD2ocMmSIz6+54YYbeOihh3jvvfeYP38+cXFxlJWV8eabb2Iymbjyp1fWO3lp7T6MBqP3eNe9jbZEe2fmrOvEiRNUVFRgMpkYOLD9Y7n8RQXjis/0L+kBMb5dQm9O3WBiy7EtHC0/SlJEkl+CiVCSeSITiSQ5qvHl17aKtcWyr3gfq2N7cLE10m/b7Sh1T8wsBgse6eFY5TG/nZgNjBnID/ntKx0YMMPnwI7FkDweDn2jLctcrC1vgd7TW+OuYcORDfSP6U+Zo8wvgd2A6AF8vO9jPNKDQXStYlsmgwm3dHN237NJjGg5OPOV1WilpKYEt8ftU/m6ldkrOVJxhGnvTSM+LD50rgg6KxtN9qMLs/hen9vt1qpYTJs2jbS0tEbPO9wOKp2VRFmj6gXQt956Kxs2bGDKlCnMmzePkSNHEhMTg9lsxuFwYLW23NPcVA+q3haj0cj1V1+p1R73gcFg4K233uKhhx5i6dKlrF+/nvXr1/P888/z/PPPc/PNN7NgwYImX6unlPjjyl7P8J70COtBjjOHaGu0d6Kppq44hLKIiAhuvvlm/v73v/Pvf/+bX//617z++uuUl5cza84sevf2Xw11fdZTp9vZ6cqNqmBc8Zm3rGE7e8brXjbOKs7iQOkBhsUNC41eIj9aun8pACeqTvhtm9WuagSwMjKKrnCk6p6Y7Svex/HK4/QI60G/6H5+OTEbFDOI5QeWc++X9/LHKX8MrSne02fCyt+dzNedF631kl/2D59evjRLe38t+HEBSZFJfgnsBsQMoMpVxdGKo/SJ7NOubYWa3036HZ+//zljE8dy7dBr2blzZ7u3qffoOdwOwgynDlrNRjMTkyYye8BsPsn6JDRmIPa4we3QKqo0Qc9V9kXfvlpZuiuvvJK77rqr0fOVzkoOlBwgxZ7i/V+sqKhg2bJlGI1Gli5dSkxMTL3X7NvXtitbCQkJhIWFUVVVxQtPPEJksu+9uQAZGRlkZGQAWsrLsmXLuPbaa/n3v//NVVddVS/FRlfjriHS7L9OEn0sgp7+0tFSU1PZtWsXu3fv5owzzvD5dXfddRfPPvssr7zyCvfddx8vv/wyANfcco23RGjdfQDs3t36OUjCaid20md8bUpCQgLh4eFUVlaSlZXFgAHt61z0l851iqV0qJ0FO7WZ6/xwCQ60XiK3x83xyuPklud2uWm4vz72NQLBd3ntS7kZ88YYRrw+ghGvj+BY5TEksMHo8i4b88YY/zS4A+gnZrP6z/J+iQ2IGcCs/rO4eMDF7Q6e9RPHzw9+zurc1e1srZ/ZouH+fXBDba3j6z/UHtt8yx+udmuXo/885c9MSprkl5kz6w7i7Gr2F2spFP2i+/ltm3ow7muwpE+wlB6XzgPjHwiNCZactTWgm+kZP9Xg1Lr0QZL/+c9/mnxeP151p3kvKSnB4/EQFRXVKBAHeOutt3zef10mk4lzzjkHgA8+/rhN29AZDAZmzZrF7NnaQMNt27Z5n7NYtOPjdDm9+cr+YjaYMQhDu4JxvX0ul6vd7Tn//PMB+Pe//92q+QgGDBjABRdcQFZWFr/97W/ZsWMHw4cPZ9SkUY3y6/V9vPnmm61OuYkPi8ditGA2mr31yhsyGo3e98W//vWvVm0/kFQwrvjs+/zvcXgcfgtqzEYzwxO0HMX02PQuMQ133cD5SPkRBkQPYOPRje0KnNdctYbHzniMyUmn08Og5cDFYGBy0uk8dsZjrLlqjb9/jaBbmb2SE1UnEAjyKvP8dmKmT06lDxIOSX3GAELLG2+Fyb0nYxRGpiZP9Vtgp6egPfvds6EzKY2fHCg5APg3GLcYLQghvCdGndIpgvHWDEa89NJLGTt2LGvWrOGOO+6gsLCw3vNGg5GjB4/y6ssnJ85JTEwkNjaW4uJi3n777Xrrr1ixgvnz2/6+fvjhhzGbzfzid4/x7it/RZbl1Ztd1OPxsGrVKu+gQdDqT3/3XeMOlIKCAu9Az7opNn36aFeQ9u3bh8vlajJPua2EEFiMlnaNo9Hb548rQbfeeiu9e/dmw4YN3HPPPY2C5fz8/GYng7rnnnsAePLJJwG47Y7bkFI2en/Nnj2bUaNGkZ2dzXXXXUdJSUm958vKyli1alWzbbQarac8efnd736H0Wjkb3/7GwsXLmz0/K5du9i1q+VKSv6mgnHFJx7p4WiFltvtr6Bm/vT5/HLMLwE4M/nM0Oglaidv4Nx7MkII0uPTSYpIYnLvyW0OnKMsUVwcM4xZh3YyoEb7kIl0u5l1eBcXxwwLrdSLNjIbzViNVobEDfFLL69+UnThR1rlnxEJI9h4pH0nRQFjjYKew07mjfsouzSbvlF9MRv9dxIbbY0myhzFnqI9oXcloZ32l+wn3BROYrh/8sXBP8FSh3NWaoM4m/mfa00wbjAYWLx4MSNGjOAf//gHaWlpnHnmmVxzzTWce+65pKenc+7Yc3nmqWe8rzEajfzud78DtAoakydP5tprr2XixIlccMEF3HfffW3+1caNymDR84/hdLq45s4H6Dd8LBeeO52rfnIFU6ZMITExkXPOOYfVq1d7X/PRRx8xduxYkpOTmTVrFtdffz0XXHABqampZGVlceaZZzJnzslxHampqYwePZrjece5bNpl3HHzHdx666389a9/bXO767IardS42t4zfv755xMeHs5HH33E1KlTuemmm7j11lubnX20JVFRUXzyySf07NmTF198keTkZGbPns1VV13FpEmTSE5Obra3+bzzziM9Pd27nSuuucL7+9VlMBj46KOPGDhwIB999BF9+/blwgsv5JprruGMM84gKSmJP/3pT822Uf9/bKnnfsKECd6ZVG+66SYGDhzIVVddxaWXXsqIESMYOnQomzZtatWxaS+VM660qGHlk6vSr+LlbS/7bYBdij0FgzCQXZLd3qaGBD3twuF2sOHIBtLsaVQ4KtqfD79oNiuTUzguIhDlhzhhCWelNZKLT1EGr7OYP30+U9+dyrD4YTww/oF2b6/hIOHjlcdDe5Bw8jjY8Ql4PODjAK0DJQdIi07ze1NMBhOR5sjQGVzoJwdKDtAvup9fBtfVZTPaqHRV+nWbQeWs0nrFmzkurU1LTE5O5uuvv2bBggW8//77/Pjjj2zevJn4+Hj69OnDHT+/gzNnnomU0vu3+NWvfkVaWhp/+9vfyMzMZPv27WRkZPDmm29y3XXX8dhjj7XtdyvI4uprrmX8iME89+anfLZ6PWs2fgMSeiUlMWbMGC666CKuuOIK70v0tmzYsIEtW7ZQVFREQkICY8aMYe7cuVx33XXeuuq6jz76iF/86hesX7ee9959D7fbzbRp005ZUcYX+iDh1qSF1NWrVy+WLl3KH//4R7Zu3cq6deuQUpKcnMwll1zS6u2NGzeOH3/8kb///e98+umnfPbZZxgMBnr37s21117L7bff3uTrhBCcc8457N69mxtuuAFTmAkqm35/9evXj++++47nn3+eDz/8kLVr1+J2u+nVqxezZs3ipptuarZ9VqMVKWW9uKUpN998M+PHj2f+/Pl88cUXLF68mIiICFJSUrj//vs5++yzW3dg2km09g8shLgWuBM4DTACu4DXgJellKcuuHpyO+nATGA8MA4YDAjgSinlB8Fox7hx4+SWLa27NNzdlDnKWJ27mjd2vMHOwp0sumARD69/uF5Q096e2Ys+uoghcUN4evrT/ml0CLhpxU1sydtCpDmSpMgk+kT24fmznz/1C5vz9tXcF+6mlzmKbw+tIz86iVG2nsyvMsE17/iv4R2kpKaEM949g1+P+zU3Dr/Rb9v9NOtTnvnuGcwGM4NiBoXuIOHv3oAld8PdWyBh0ClXd3vcjH9rPNcPu577xra951BX96TbKE6WCtMv93aFcqPnfnAu4xLH8fiZjwPaZXt/TO5xvPI4+ZX52C12ekf6rzJEUEgPHP0BIntoZTXryCnNweVxtbt6VkOFVYUcrTjK4NjBfr2q06SCLG1So9IjYImAuH5QWQhVxRDf36+7CtTxKq0pJbcsl/4x/b0DFDsjh8NBSkoKeXl5ZGZmYutjo8pZRZ/IPu2u919XU4OEA601nyVCiG+llOMaLm9VmooQ4kXgLbTgeS3wGVoQ/QLwgRCiNZ9CdwLPANcB6YDP3RV+bofSAr2nt3+09sGVZk8jzZ7mtwF2AGnRaRwoPdDu7YQSPYh55PRH/DO4bvgc5leZeCCsP8OcLpx4mF9phGGXtr+xISC7NBuAVLt/a6frg4QPlx/mUPmh0M0bT679bPYxVeVI+RGcHif97P7Jf66bXhVjjaHGXUNCWEK70qtCSaWzkmMVx7yfY/6kz7ZY6ijtfHn2zmpAQhNBnl6mz9/06hlBqRASFqsF3pZIcFRo+eJVRRAW49fduD1uKpwVfh28qQu1iipt9eKLL5KXl8fMmTMZNmwYNa4ajAaj30sQdtbj5XMwLoS4HPgZcAw4TUo5S0o5BxgE7ATmAHe3Yt/bgb8CVwEDAZ8+7QPQDsUHW49vxSAMXPrJpRyuOOzXoKafvR8HSw/i9rj9ts2ONi1Zm9nNb4Pr0mdqgdpXfyXN4aC4ppjiI1u05V2AnqaUZk/z63bNRjND47Uei6FxQ0N3kHBCujbxio/BuH7y6q/BiHWr2uhVCOJt8X496e5I/j5edekBq9Vk7XS1jXHpgzfrT+jjkR6cbmdAgkv9eOVV5gX+M99mB2cFVBeBxwlHv9dy5G2NZ2ZsjxJHbRpJ2zJJWuQNLtuRN95Rdu/eza233sqFF17Ir3/9a0xmE7c+eCuZJzLxSA9Rlijv1PWZJzLZUbCj3fs0GUwYDcZON46jNclgD9XePiil3KsvlFLmCSHuBFYDvxFCPO9LmoiUsl6Wfyvy+PzaDsU3Va4q4mxxvHLOK36vj9svuh817hqOVhz16wQ5HSmnNIfE8MRGs9a1mV4G79Wz6Gc1AcfIvuEDRvlYBi/UZZdmYxIm+kT5t7b1/OnzySzIZN3hdZydcjbnpJ7j1+37jcGgVVXxsaKKXhnE3ycvK7NXegPKoxVHu0zeeCDKGu4o2FEvjzfcFE5xTTGZJzIB7TttWPwwv+3P76SEygLtfk2pNilO7fewHsgEomfcKIwYhIFqVzVljjK/pig0YjBpM9o6qyB/F8SkNFtPvT1KarSKHw5P/QBw7ty5Pm/j1ltvbbJ2t0EYAjJIeNeuXTzxxBM+r/+3v/2NhISEVu3j6NGjLFiwAKvVysiRI3n0j49y5qQzKaopotJZSZgpjEpnJRajhWhLtN9O+n2pqBJqfArGhRDJwFjAATQqICqlXCOEOAz0ASYBzc9p2w6h0o7uyGw0MylpklYfN679A+zq0gehHSg50GWC8ezS7IAMrqPoAP2GzITiYxwoOcConqP8v48OkF2STXJUckB6rvWAVU+FCVl9xsLa+fD0EJj8c5h4OzSTf3yg5ABxtji/BzJmo5kpvadwtOIocba40L2S0EoHSg5gFEZSopqeSrwt0mPTKXOUUeIoocJZgcvjwmww+z2wCAhXNRQd1G5NVqgu1n5iUsBko6q2x9xfc0rUJYRAIDAKLUUhoMG4zmQDYYSacr8F43VPxvTOxBp3Tb2Tsddff93n7U2fPr3ZiXQCEVweO3asVe2bN29eq4Px6dOnNznwtNpdTaWzEqvRitVoxW6x+/V9YDV2vqtUvv6nja69zZRSVjWzzjdoQfBoAhcEh0o7upVKZyXHK4/7vRdOp/dWZZdmcyZnBmQfwSSlJLs0mwv7XejfDVcVQVURvROGYi79ukvl2WeXZgfs/RVhjqBnWM/QrthTkAW7lgISTr8Ldi7Rfma/CPGNB4QdKDkQkOOlp1NtPb6VKEtUlyg3CoEpA2k0GL0BRLWrGofHEZDAIiAKsrSgtLwKLFEQnQzledryxOGUO8oBrYdcn4a9vRpeSTAKozdFAQJ8JUEIsEZC7e/lD3VPxqpcVbilu9HJWFsroDRkNVopc5SRW5ZL7wj/DBJuLlAOhnKn9nfILcvFZDD5/aTMYrTg9rhxeVwBOaEMBF9zxvVrezktrHOwwbqBECrt6FZySrXD7e/BdbpYayx2i9176b2zK6wupMxR5v9gqVA7Psb4gaTaU0M7uGwFt8fNwdKDgbmSUCs1OjW0e8YXzYYhtekgHjfMXQaDztWWNyG7NDsg+c+6kD9erVDmKGPjkY0Bu+pW6ihFIqlx1eDwODpHj5zJpgWo0nOyrKHR4h3IWemqRAjh1wGp6bHp9InsQ6QlEqPB6A1eIy2R9InsQ3psut/21SRLJLgd2o8f6Cdj0ZZoBFq9eavRSrQlmhhbjF+r6ujpQqU1nXCQcBOklAgEqfZUIs2Rfi832tqZcUOBr8F4ZO1tRQvr6Kecgbw21+52CCFuE0JsEUJsyc/P92vjuir9SzlQwZIQgn7R/brMl3/AjlehlvdKbD/S7Gld5uTlaMVRHB5HwHrGQUtV0U8qQ1JiBiQMhphUOLJVyyG399HyXRsori6msLowoMF4mj2NoxVH601b3lmtOriKcmc5BhGYOe6EEN6KKmGmML8HFgERFqtdaQPv4M0dlUfJlFVknsjE5XERZgrz6+C6usGrxaANSjQZTAEJXptkqe3hr/Ff7zhoJ2Nu6cbpcQbsZEwfxGkz2TrHyd4pWIwWrCYrYaYwekX0anbq+rbSg/FjFcc6TWEIXz+d9E+XjrmmcVK72yGlfFVKOU5KOa5Hjx5+albXll2ajUD4Nd+yoX7R/bpMcBmwKwlFtccnNo206DQOlR065cQGnUGgT/ZA+1sU1xRTXF0csH20y/A5sGMx9B4NR2rreWcubrJ0pX68Ah2MA6F9AuOjT7M+BbR64IHQN6ovPcK17xK7xe73wCIgbHbQq3Oc2A1HtpLu8tAnIolIs9bnZTPaAtJzrQevoKXBBC24NIeDMGglDv1IIJBSYrfY/d7Lu6NgB5knMr3fjZHmSL9XH+kIgSqbqTMbzAiEd5BwZ+BrMo3+20S2sI7+XCB/81BpR7eSXZJNUkQSNpMtYPtIs6exeN9iyhxloT3wyQfZJdmYDWZ6R/T274YLD0BUEljC6RfdD5d0cbjscECD2GAIdBoU1B+XMMo2KmD7abP0mbDyd1BRe7VuXjRE9IDL/tFo1Z0FOwHoGdYzYM3R31M5pTmkxwU4fSAA6k5ipA9CzSrOqjdz8Fvj3vLb/vTAotOUUzOYtPQUCfQYDGgz58UAbiTlznKsRitOj9PvOfBCCCItkRRWFWIymIJ3JUEIrXfcj3njAIkRiZQ6Sgk3hxNni/PrtuvmpZc7yjvXIOFmeMtmWv1fNlMnhEAIgUEYgjdIuJ187RnPrr1t6dtS7w7IbmGd9gqVdnQrOaU5AQ2U4GSwdN/q+zrNmWxzskuzSYlK8f9l18L9EHdy8iWgS1xNOFBygChzFPE2/5cc0+nv35BNhdJLV96o9eJy3Yfa4yZKV649vBaAPUV7AtYc/SpYyB6vU6g7iZHe09srolfAJjHSy/V1mhxVKbVyf5bGpVdLHFqZvrzKvICkXfSN6ktSRBIWowWzwRzcKwmWCK2CzLHtUH5cOw7tFNAykHVSe4wGIzWemoDlpQdLII+XfiVBr2NuwNBpriT4Goxvrb0dLoRobj7W8Q3WDYRQaUe3oVcGCXTvqx6Mbzq6idW5qwO6r0AL2PEqPACx2nHSt99ZgyVdmaOMz3I+o29U34D2kPWJ7IPJYAr9Qa9JowBxMlWlCTsKdhBuCuezg58FrBnh5nASwxM7bZpK3UmMbCYbcbY4BkQPCNgkRkIIrEZr5+kZd1XXDt5sHIzrFTb6RvUNyOA6XdCPl6tam40TICJeK+VYsFdb3g76CZieBx8IpY5SkFDlrOo8g4Sbof/NAzGhVMNBwk6PM7iDhNvBp2BcSpkLfAdYgCsbPi+EmAYko82KudGfDQzFdnQnBdUFVDgrAt4znhyVjECQHJkculOW+8DlcZFbluv/wYiOCig/BnFaMG632Im3xXf6YHx17moKqwsDmj8I2kCxvlF9Qz+4tNkhYZA2iLOOMW+MYcTrIxjx+ggKqwsZmziWjUc2epeNeWOM35uSZk8L/ZOXU1iZvZLimmJKa0r9PnNwQ4GYmCVgnJXabRPBeLg5HIMwEGGOCMjgOp3FaMHhcQSvvF5BFoTFAAI8HogfpM16W5DVrs063A4MwhDQEnpCCKwm7TMy3BTeOQYJNyOQJy91ryTo6Wlmg7lTXElozfDyx2tvnxRCDNQXCiF6Ai/VPnyi7qyXQojHhRC7hBCP4z+tbofSdnoaRD97YAaL6UGGHkyk2lMDHmQE0pHyI7g8rgAM3szWbuNO/h36RvXli4NfdOq0nuUHlgNQXFMc8H2l2jtJub7eo+Fw/Z5xPe1iUtIkJJIhcUNIikgKWNoFaFdfDpQe6LBaxP5gNpqRUjI1eSqTkiYFdBIjPcfa0xm+ehyV2iQ4psYnwQ63A4vREvCAz2q0IqUM3iB0kw2MVi1VpaasUTnHtqpx1wT8ePWN6ktCmDbhTow1pnMMEm6Gw+3wTlkfKKWOUu//YVAHCbeDz6dyUsoPhBAvA3cCPwohPgecwAzADiwGXmjwsiQgvfa2HiHEGE4GzwB6tf/HhBC/rrPfSX5oh9JGek9ioNJU1ly1htW5q1m6fylbj28lrzKPpIgkekf2Zlb/WUzvOz0g+w2UnYXa4LrE8ET/blgva1ibMw5ab29xTTGrc1d3qinLmxpcl1ueW29w3Xc/bT5No6362fux4fAG3B53SPeQ0HsM/PAelB4Fu/bRqaddnKg6waajm0iLTiPNnsZ5aecF7G+fak+lzFFGUU2R3wemBcsfJ/+R0985ndN6nMYtI24J6L70y+4OtyOgg939wll5sr54AzXuGsJNjXvM/U0/XnowG3BhsVqaijUKyo6C26mVdwyLbddmHW4H4U1cYfC3uscrGPsLFD3vPZCEEESYI3C4HZiN5k5xJaFVhVellD8DrkNLFZkGnA/sA+4GLpdStqagox2YWOdHT+Ib1GB5oNuhtCC7JBur0UqviF4B2X7d3M6EsAQOlh4k1Z4asNzOQFt1cBWgzSzmV4V6WcOTPeNF1Vqd4GX7l/l3XwFWd3BdjDUG0CqDBLKXF7Tg0uFx8PMvfx7aVxN610403ETe+Gc5Wp74k18/GfC0i65Q3tDbmRDAGva6TjPRiPQ0O3jTW+kiCMFx0CvQ2OzgrNACcYC87dpJic3e5k16pAenJzjHy2LQet87TSpUM/QrL4HUN6ovvSO1mUotRkunuJLQ6lkQpJRvSymnSCntUsoIKeVYKeWLTaWFSCnnSimFlHJuE8+trn2uxR9/tENpmzJHGcsOLKNPVJ+ATZihW5m9EofbgcPjIKc0p9PmjX9//HtMwsS6I+v8u+HC/RAWx5gPzvam8Bws0yab3Xxsc6dK66l7AqZPtT0gJnCD63T61Z2vDn0V2oOEe43QUggONw7Gq93aYLNnz3o24GkXegDbmfPG9bSkQI95gZNXeUI+WHJWAbLJfPGmKl188sknTJkyBbvd7i0Z9/3337dp19nZ2QghSEtLa1SBJi0tDSEE2dnZbdr2KRlM2v9W0ijt/yssTnvcjlzvQFYGaUgIgcVgCf2TvRa4PC7cHndwroTQAYOE2yFwIw6UTm917mryq/L9n3LRBLPRzMgeI1mZs5IBMQMCHvz7U920C4FgSNwQb947+CntougAxPVjzVWfeNN6DpYe5FD5IewWO+lx6Z0urWdl9koKqgswYOBY5TFW5qwMaLqNHpD1i+4X8H21iyUceg5tNIgTYFSPUeRX5jOu1zjG9RoX0Gb0juytVaDpDHn2zcgpzUEg6GsPfM+Y0WDEbDCHfrDUwuBNve16cLl161auuOIKAM4++2ySkrS0qbi49qctdVgFGiG0VJWaMq20YTtSGLyDEYMUXHaqQcJNCObJC2jHq9zPdeUDRQXjSrNWZK9AIIJySX/+9PnkV+azMmclE3pN4Nqh1wZ8n/5SN+9989HNDIodRJWryr9574X7oe9Eb68ywP+y/8exymOEm8O9vcqdidloxmKw0C+hHyN7juRYxbGA7KfuyRJARnwGK3NWBjxHvV2SRkLmRzB/GJx+N0y8HQzGoNT81xkNRpIjk1matZRbR9za6VLGQOsZ7x3ZO6hf/nWDpexrr6PqO9/fW2FjxpD2tv8mI2pESqgs1O5Xl2gTS9UJRhsGl4sXL8blcvHb3/6Wv/zlL35vjsVoocLp3xkxfWK1a6UNXdVa7nwbecv0BbCsYV0Wo4VyZzlSyk6RB91QsE9erEYrxZ7i0B8nhArGlQbqBi4WgwWJ5HDF4aAELglhCYSbwjtdjqoeINe4a9hwZAP9ovtRWlPqn8F1HjdsfBGKD0LcQO2xwcjK7JUcrTiKlJLC6sLQ7ultxtPTnub0d05neMJwHhj/QMD2U/dk6du8b8mvyg/tQcIFWZCzQUsnuOgP8N3rsHMJzH6R7NJsJiVNOvU2/CTMFEZ2aXanGySsyynNCUq+uM5itFBSU+INlsJGZBA2IoPEhx465WvzHn8cCGCA5aqGooO1AWi4FoxWF0NMilZpBC24NBvM3iuTubna2JdBgwYFpElWo5WSmhLcniAP87LWnljWlLU7GA90ZZC66lagCVZA6096MG4UwTle+kmSw+0gzNC+qjmB1nlyAZSgqDe4rnYK2YSwhIAPrgPtsmVadFqnC8Z1S/cvBWDBjwv8M7iuIAteuxC2f6g9LjkICy+CgizMRjMTkyYyNnEsRmEMaO5woOg17AMdLNXNUY+xxmiTMtnTQneQ8KLZMPAc7b7JCnOXwaBzqVw0m+OVx4MaXJY7yxEIVmZ3vjEcUsqgXkkALVjySA+5Zbm4PW7ibrmF4sWf4Dx+vMXXOY8fp2TxJ8TfGsCKLwVZYIvSBnBa7U3W2a5x12A1WZk3bx5CCF577TUAbrrpJm+++Ny5c1m4cKH3flNWr16NEILp06e32CRvBRpPkFMvTBbtf6umfSXvglEZpK66FVU6I/0qSLBSR7zHyxP6x0v1jCv11E2DWLB9AccrjzMgegAX9b8oKD1jqfZUfsj/IeD7CYQal/YP/+jkR/k+//v2p10smg3jboLEDHj7J3DJ83BwIyyazfx7twPwzLfP8N3x73hy6pPtbX7Q6TXsgxVcrsxeicvjoqC6gEhzZOheTUjM0CqqGC1aRZWMy8Deh4M9B4IrK+DBZd2rYyaDCYlkw5ENoZ3W04RgTVhWl/7lX+Yoo8xRRkzPnsRcOpvCBQta7B0vXLCA6EsvxdSjR+AaZ7KdnP7dEt6ozraUUivTZwpn1KhR3Hjjjaxbt46srCymTJnCwIHatB5nnHGG35oU9Ioq9XYeBRUFcGw7RPZslLJzKlJKHC4Hdmvbq7G0VoceLz9wuB0YDUZKHaXezr5AqltuNNSpYFxp0srslZyoPIFAcLzqeNAClzR7GisOrAhK+SN/OzP5TDILMpnWdxrnpZ3X/g0mZoA9+WRZw/iBWrpKrxHeVfpF98PlcXG47HDAasEHij4wMFjtNhvNDIsfxtrDaxkSNyR0e5eGz4Edi7W//5HvtWWZi8nuMxJyAh+M103rOVBygKMVR4mxxTAwZmBopvU0Q68CE8wrCXqwZDVZvQFH3C23sP/iS4i75RbMPXs2eo3eK95/6aeBbVxYrDaLL0BtFaO6dbZdHhce6cFqtHLppZdy6aWXMnfuXLKysrj11lvr9YIvXLjQL03qsJ5eVzXUlANSC8KbSNk5FYfHgVu6g3pV0iiMGIUxdD+7mrCjYEe9icNirbEU1xSTeSIT0K6ID4sf1tzL28UgDJiNZhWMK52X2WjGZrLRK6IXE5ImBGxwXUOp9lQkktyyXAbEDAjKPv0lu8TPg8X0oMzeG6zR2pdG5mJteS09kM0uze58wXhJNjajLWA17BuaP30+uwt3s/bwWqb3nc75aecHZb+tlj4TVv4OKvK1x/O0v31O+ukApNhTArr7ulfH/rv/vxytOIrdYu90g4T1dLfU6LadvBx77DFqdu7yad0KV6W311kAHoOZculih7cn2kj2lT/BktL4b+c4eBBhs3H4vl+1qZ11WYcOoddvf9v0kza7djIPkPejdmswQax2fII9uA7wTiNfXF0ctH0CWmpOWByU54F0aSk75Xna8sThPm2ipKYEAHcQpzURQnS6iirpseneycMqnZXYTDbMTjMWo4VoS3TA0wStRmunOHlROeNKk+ZPn49buhkaP5QHxj/A/Onzg7LfzlzbWM9F9pv0mXDoG/jmX1BTAo/GwOEt2vJanfl45ZTmkGJPCWoZS33yh5A+XrZouH8fzK6doPiub+D+feRU5tErohdh7Zy+21crs1eSX5WPQHgrHXUmOaU5WAwWeoUH/mQv3BSG1WjVBvIJgUQiEBgNRqxGK2G9k3GdOIF01A+ipMOB68QJzEmNJqn2P2EEYYDweC0NqvfoenW29Rr2pnbU3W4LozDi9Di905cHhcmm5YxbIqC6tFHKji/0KmPVrupAtbJJnSW41BkNRmJsMd7PLavRitVoJdoSTYwtJuCDXy0G7eSlbu98KFI940qTyh3lnKg6EdR8SzjZ69fZahvrg8XGJPpx0h09KJs/DNLOhMv+0WiVaGs0cba4Tne8QPsbD44dHNR9hpvD6RXRq3MMEq47E2ePwUGvDKIPEpZSUuYs63SDhLNLs0mxp7T5y77ZHuYWFFcXk1eZh0EYCDNasVvs3txYrVoK9XLH8x5/nLBRo0h86DdtamOruGpAuk+mqDRQ7tQG1VW7qrH5mKrhD3oQLglisBQWC1XF2mds6WFwVtdL2WlOw5QLgEpXZVBSLnQWowVXjYvc0lzvLJOdgf7+yi3LxWQwBTVv3CM9uDwuzMbQ/QxTPeNKk/RgpZ+93ynW9K8oSxTxtvjOESzVkV+VT6Wr0v8nL44K7csiYWCzq6TZ07yDITsLp9vJobJDQQ0udan21M5x8tIjXStBd/g7pJQcKD0Q1JPj+dPn88D4BxgSNwQpZdCujvlLsE9eAEodpUikdzbhUsfJah0NK6sEpYJKXY7aet6WpoPxalc1BmGo1+a28nha7uV2epxknsgk80QmLo9Le01tUL6ncA87Cna0uw0tstnBWfvZCpC/U5sMydbyYMz02HT6RPYh0hKJQRiwGC2YDWYiLZH0iexDemx6YNvNyTSiUkdpUOYA8ReP9CCEINWeSqQ5Mmh10r2DXoNdsaeVVDCuNOlAqRbcBbtnXN9nZwvGAzZYrGCfdhvffJ3fftH9OkdwWUdueS5u6aZfdHBP9kD7G2WXZIf8ZUsMRm3ynyNbKa4ppsxR1iEnL2nRaeRV5lGpz9zYCRRXF3Og5ABJEUFI/6hDCIHNqPUqhxnD6gUc5jqVVSBIFVTqclZoqSqmk2NadhTs8AbFbo+bCHME5c5y77LimuImN2WxaAFheXnTJepyclr+/DYbzN6gVu/ZFbU11ntF9Ap8UGswaSk6vUdrdcbN4fVSdpqjp1xEW6KB4Kdc6PuEk4OEOwuLwYLNaCPMFEaviF7elMGA77eTlINUwbjSpJzSHAzCEPDBYk1Ji07rdMGltzKIv4OlE3u124SWg/HC6kLvgKLOIKdE+7LuiOCyX3Q/ypxlFFYXBn3frdZ7DBz7gZxirRZ0R50cAxwsOxj0fbfV4n2LkUgqXcE9gegb1Zee4VrFFLvV3ijg0HvHq3fsCG6vOGg945aIeuX79J7eiNrUFZvJVq+nVw86G+rTpw8Au3Y1PcB12bJlp2yOHtQ2HPBut9qDm3phi9F6xVsxKLLUUYpHeih3lje6AhIo+olTVu1nQaQ5st6JU8CvJrRTR1VIMxvMCAQFVQXBn1yqFVQwrjQpuySb3hG9O+SfJ9WeSmF1Yac6688u1SqDJEYk+nfDBfsAAXH9m11FD2g7U6qKfvLS1koX7aEHl53ihK/PGHBVs+ugNtlWj7Ag9aLW4R0k3BmOVy19sOn+kv1B33dLPXF673jOTTcHt1fc7dLK+TVIUdF7evVgvGFPb3OpBOPHjycqKorMzEzeeeedes+99NJLfPDBBz41q9RRiktqaSpBzRmvy1Z7wlHte2eG3taEsISgpVzUTZERCC0HOsgpMm3lkZ4OmzVUCG0gtcPtCOm0HhWMK03KKc3pkEAJ6vTElXaenrjskmxS7an+rwxyYi/E9G1xyua65Q07i+zSbOJscdgtwZswQ6cHl50iFap2EOfa3K8A2F20O+hN8A6qDuUKNGiTFY14fQQjXh/BzoKdAGQWZHqXjXnDj4OrW6BPj95c+bm4W24hbMSI4PaKO1vOF9c7Po6WH/Wppzc8PJyHH34YgOuuu44zzjiDK664gv9n76zjozjQN/6d1Wzc3ZEEEkII7gFKcW2pULerXPVq17vqtVe7lspV7mrX0lKnaLHi7g4JEDeIy0bX5vfHZJfdkEBkd5Pf58PDh89mN7Mzs5PZmed93+d93ri4OB5//HGeeeaZdu2WIAi4K91RyVUWmYrToXABuVpq6GwnfF18AXBTujlNcmEtkZHJZNK0VCdLZDoL83fBmdNKW8Je/RCOwlUyfhWXQBRFcmpynN68aYaZLL2x740eHclaI6cmxzESgvJzl9WLA4S5h6GQKXo8WbJGTrWdbSA7gBC3EFQy1f+P4+UbC2ovTtcVoFFo2Ji30em7oFFoCHEL6fHBy7Ybt/H6mNcZFToKjVKDp8qTELcQRoWO4vUxr7Ptxm1O25fLeUErAwOJ/OJz52XFRRFqmz3rdRf90G0XkV6L9Ixsd6b3qaee4ssvvyQpKYmDBw+yadMmevXqxc6dO5k2bVq7di3CI4Jgt2CnurdcAkEAjRfoaqVpnLUlrR4ja3QnuTQTykZDo9MkMl1Fd3jYW/dDmAda9WRZz1Vrw6u4BCX1JTQYGrpFnwrSBVpA4HjZcbbmb+3xg0b0Rj2FtYVMi2nfDajdEEVpCEXkyMsuppApiPSI/H8jU9HqtJwsO8nU6KlXXtgBkMvkRHpG9vhKgmUsfagXgknH8OAR7Cna0y1j6aM8o3p88GI9rOh0+WkiPSPxVftybfS1Tr+GqGVqi5Vbt8LQCJV50qNcLc0raKq+ZNKki8IFk2jCVemKq9LV8vrXX3992Wmbd999N3fffXerv2utQTo6OrrV11UyFRsObyDeL96pcwcA6dg0Nid9ND7tmsbZZGxCJsiQC87PRpubhOtMdbgqXJ06dKizMAcvKpnzyLh52FC1rppGQyMGkwGFTGGpJjh62FBHcTUzfhWXwNljyltCJVehlqvxd/H/fzFoJF+bj0k02T/Tqz0vZWv82rY1NCPaM5qs6iye3vZ0j68mrM1ei86k61arqf8P9obmTO9IdSAgEu/du9syvdGeUlN1j3egQRpWVKur5UzFGQrrCrvlGqKSqzCYDN3fMFaeKdn1iaL06NcH1J7S61ZoMjahVnSfhEAtVyMiSsGns1GeCRpvkCklL/Y2jpE1dEYdarnaafZ81ojwiMBf4w9Icyac5UrSFTQZmyzyLWfBWtZjzsgrBEWPlfVczYxfxSUwl6OdLSOwZAIBGTK83b27LRPYEaRVSPrUQE2gfVfcDicVM6K9otlasJWcmhzGhY/r0dWE37N+B6CgtqDb9iHaM5ptBdss2ZKeCHOmtyJ7O3sK1xGz7ytyQvpwbcwMp/99o72iqdXXUt5YbiECPRWCIGAQDdzQ5wbkMjkX6i44fR+svY01MudMTG0VChdABEwXnVRaTJoURckX3Toj7myYyZKZ5DoVChfpmGh8oK4UTIYrTuNsMjZZml67A9ZNwt25H+1Ft/xdm1Gjq7FUD/QmvdOGDXUUPfMudBXdiuzqbDQKjcWiy1nYduM2tuZvZXXWak6WnaSwrpBgt2DC3MOYGTuT1IhUp+5Pe7ElfwsgWb8NZ7j9VlzeTMavoBkHya7PJJpICUxhQ+6GHkfGrQMtM/k9W3G22wKtaK9oDCYDRbVF3WLf2W6UZ7I+/w+QwbtergTVFrJh56vM8kkAv15O2w2Lo0p1To8n4/cn3c+W/C0MCxnGpMhJ3bIP1uRS04ER63aHxgdqi5t3yl16bDFp0qynVcu6LzNuTS49cLJ8wDyN0zME6kqk49OkbXMap9FkxGAydGszolKmRBCENvsSehJEUaTJ2ISXunWbTEfD3CRsMBqQy+TdUs1oD66S8au4BDk1OUR6RDpdu2et+SxrKONs5VlC3EKYGTuzx5FLaxwrOYZSpmR74XYWxC2w34rLMqTR1Z6hbS5iTXIB5vWex2v7Xutx1QTrQOtU+SnqdHWEuId0W6BlJpcv7nqRf0/6d4/TD1qweA5NQb6gr+QDTT82Rw3kQt4OWDwHnjjptN0wS9Zya3IZEjzEadvtDMx2ht3VgA49aNCIiydUNbtSFTefLzIF+FzsB+qO5rqWuJIDjUPh4ilN4ixt9kyvKbzkGFnDLK/rzuMlCAIquar7z692wCgapWCvm4IXs4ynwdBg87yn4SoZvwobaHVaDhUfYmTo5ZsGHYkNORss0/7ytfk9PtMrIJDgl2B/SU35OSn7eZlI3kxyl2csZ/+F/VTrqglxCyHUPbRHVROsA62zlWeJ8IwgyiOqW5rr4CIZP1RyqGc3CQclkuSporS8hiElWQxZ8D2oo0C/wqm7EewaLDnQ9HCdPUjJBLkg79abrkyQoZQpuz9zKcik64erP3iFt7pIT7CdA7qPXJqncQLUlUF1vuRi1IZ8raccL7VcTaOhsVv3oT3oCcEeSMerJzvPXG3gvAobbMzdSIOhoVsbtZRyJSNCRwAQ6haKUqbstn1pC9Y2aoIg0Ne3r/2b68rOXVEvbia5c3vPRSlTkl2dTbRntKWa0NMyvhtyNlDTVEOBtqDbmutAmv6nkCkIcg3q2U3CCfPIrjhDjNoXys5AUy2cWg795zp1N+QyOWEeYfye9XuPbxDOrs4m3CMcpbx7rxtqhbr7M5e6ehBNFyUqraDJJDmDdHfvhFqu7v7gReMNyKC+vM1Fegq5NNtnmkRTt+7HldBTgheVXGWRGPVEXM2MX4UNVmWtAuiWpiczFqUuQhRF1uesJ9Y7ludHPN9t+9IWzCS4Tl/H7qLdxHrFUtFQYZ9Mr8kIu/8NVbmSk4rJCFfo/N6QswGFTMGKjBXEeMf0yGoCSKROb9Izt/dc3FXuTj/PWlY0gtyCenaTcNxUsg+/yoSyEolUvREGbgEw/79O3xVXhSvZ1dk9u5IA3TojwRoqmYp6fT2iKHafTtUcOF2GjJvHlHe3llYlu+hA021OFzKF5DleXwGNNeAeKH3frI6NzqhDKVM634KxBcwaf71R361OOFdCo1HK3nf78TI3VRt13R54toaet0dX4XRYExRzFjqjKqNbCYogCMR4xfR472yzM8h/j/2XYPfgrpPg8kxY/hDoJX0bVXnw9QyY8/FlG/aUciVh7mGU1JcwImREtwZTl8NjKY+xKW8TQ4KHMLvXbKdv31q7frz0OIXawh4p6zGjWoAKmUDMqCdh5d/h2n/CqIe7ZV+0Oi0CAutz1vdYMm40GcmtzmV06Oh2Le9IoqySqzCJJgyiAaXQTVn6plppeq+87Vt9k6GpW51UzOgRDjSGxuZrrwiurXuOm4OXboMoQl0pqroSkAs01ZWgbqiWAgeaBzy1EkR0F8yS01pdbbe6mJjPryajfc93e6kIrpLxq7AhKGnlaVQ2VRLiFkK4R3i3EpRYr1h2Fe7qlm23F+aS5Ztj32Tvhb1dJ8GL58CQuyTN4i93wvzPIGvLFRv2FqUu4uuTX/PuoXe5P+n+butcvxLMzXWxXrHdsn1r7XpxXTGZ1ZnE+8YzI9b5doHtgTkYjQlMAs9wKDri1O23dMEREXt0JaGorgidSUeM15Uz43K5HL1ej0rlGGJlvvkXaguJ8IhwfrbXZAJdnUTK2lpENKE36btdcgG2Ta/d5kBTngmufpJMRVcnOVnVFkuvByV0uzOIZYiTAGr3IGgoQddYBW6B0lwKkHoD6suvOLjIWdAZdchl8m63FDQ70NhbOqbT6VAouk6lr5Lxq7AhKJlVmQS6BhLrFdttzXVmxHjFsDxjOVqdtsdpn80YEjyE7OpsxoSPYVzEuK6vMChRIl3lGdJz/75QdvZig9FlYHa8yKnJYWDAwK7viwNgJpfO9rBviQ05Gyzl0zxtXo+V9dgcr9BkKHIu8bUO1LOrszlfdx5vF296e/fukZUE85TQ9pxfHh4e1NTU4O/vGKtGM7ms09eh1WmdT0T0dYAI6stLVKD79bxgawfZbTB7jrsFSK4qujobz3GzRtvpfUzN2XBqCqWBRB4hyMszUCjlNAkCaIukCasyBdQUQVACVGRDSRp4hjk9S366/LRNxthH7UNVUxWnyk4BUuW7v19/p+2PeZtmnb29IIoi5eXleHl1PTi72sB5FRZsyNlAVVMVlY2V3dpcZ4ZZ99mTpSpZ1VlEe0XbTw+XMA9OL4eSdCmroXZvd8OetRd0T0V2dTaBmkDcL6NhdQaUciVDg4cCEOYe1iObhAGya7JRypSEuodCWApUZEk+yE6COVCfGTuTXt6STMpd6d5jG4QtlYR2ZMZ9fX2prKykrKwMnU5n96Z18zmllCmd7+IgiqBt9hfXN0rPW4E5S9gTyLjZgaaqsar7JpeaPcdd/UCQS1nxhsrmxk6oaqoCcO4IekOj1MzfWCUFC7paqZlbNKISRXQyGSBIPSX6emlo0YUTktxG6Sq9r/yctB4nIc4njjD3MIscRKPQoJQpcVe5E+YeRpxPnNP2xRpqedebqkVRxGg0otVqKSgooKmpCV9f3y7v29XM+FVYoJApMJgMTImegp/Gr9t1x+YbanZ1NkkBSd26L20huyqbgYF2zELHTYUNf5eyIAAve7W7YS/MIwyFoOjRwUt2dTYx3t3fXLcodRFGk5G12Wvp69OXp4c+3d271Cqyq7OJ8oySGo5CU6QXi45CrwlO3Y8NORsoqS9BQKC0obTHVhJyanLwUnvh49L6wBZrqNVqIiMjqaioICcnB6PRPgTrfO15RC6SX7NLyDmkIV4CAiHuIXbZVqsw6qGhQnqUyUGoBtJA4wstHGZqdDXU6moRXcUeMR68tL4UvUmPVq3tHh27aIKa8yCeu/iaIJNmPQjFlv2rlFdSqXFwUCyKEvFuqAKFWtoPfT0gSM+NOqrkChoRaZSpwRwgGJoufhaFWpKwNGkhM/+yMyscgeqmaur0dRg0Bmr1tbjIXahX1nOe807dDzNqdDXU6erQu+m71Csik8nQaDS4ubnh4+ODTNb1ZNxVMn4VFjw99Gk25m1kcNBgboi7obt3h3CPcBSynksu6/X1FNUVMc9rnv1W6uIFT5yG10Ng1CNwzcvtfqtSpiTCM6LHekGLokh2dTYzY2d2964AkrNLtGe0RcfeE5FTnUMfn2Z7y9Bk6bHosNPJuFKuZHjIcNRyNUW1RT23klCd3SEnFbVaTUhICCEh9iPH4bpwi7TnWMkxvF28LdUNs7THoRWF9xIheSFs+xeMfQImPA+73oOd/7uk7+TW32/lWNkxXh/zeo8Irp5Y+gTn684zLmwc/570727aiwTpobEaFiWSEuqNvpm3yQU5MmTIZDJLhtUhfRPmRn5BkPTf5ZkSuR50G5xZA/VlAHzt6cG7fj5Mqqvn1dJyPKwrIEpXibzHTgAXbzi7Fia9BMPvv6I7l70we/lssquz8VH74O/qT5h7GP+e2F1/V1iVuYq/7fwbK+au6La+pbZwlYw7GDkLb6HhcPu/qJqUFKK/X+LAPWob3d1cB5cer+8B+C9ptJ4Z7s7jZSa9dj9eFZlSqTGwfZo662P2FgDnSKNfm8t31zErbSilVl9LrHf3XgStj9erza/1xOOlN+rJ1+YzOWpy8474SI29TmjibPk9vK/58SJdW0saa9t8f3cds5yaHMaEjXH6dsH2mPUGHrf8prr5MQPYTkHzM4cdo6BEKROKCWLGg0wm6YZb6TvJrM7EW+3dLZWO1u6N71l+2njJd9Lp51RdGbh4sC03n61j/sTq/M0cEXVEeEagE3CsA9PiOZByhyQx2fORZE2ZfAs5b6+i4YIKkDLcw4GfMQAqCrg0oNT0iiOaLZLkZth9kLZS+n8Fdy57ocHQgKvClc+v/ZwVmSucXm1veY71Bn4Gmt6YQVory3cnn7hKxh0MzYBENAMSCXruOXLL6/hmdy4rjxVSUafD103F7IFh3DEqiig/N4rfeAPoPiuizKpMAIs2tDvQ8njdv/5RiupzqM38S487Xg4LXkpOS4+BbRPEjgZ5sqSBxP38Y7ces47oee2N/4/HK1+bj1E02h6v0EGQt8/h2275PTz615fJKq3l05EBqIOXEVr9GiVVGqob9DyStprYAHeS33y5W7+X52vPU9ZQJunruwHWx+zMDTdhOn7ssss3HD5MWrz0HbcrCUiYB5v/ITX6RTZPUj61XHodW4ccgLm957I2e63THXLMx8v1yYdJW3A9HmfyLru8w45XW1g8B5IX4rH7Y2ZVlsOYFzi0+yV6lWXT0GuCYwwOTEbY9x+oLYEDn0ua9eTb4Nxa2P9fNJ6eaDwhaKyavFt28O/9p1hX/QSmxiAUoj/Xhb3InYN9iFwyluIdTSDUSusVjZC7B+5eB/s+vaI7l73go/Yh1iuWON84nvF9xuHba4mW17EvdqWxvPIudCVT8Wi6tkfxiatk3MHwvecesmbNJj11LpXPPMWC0iwWWC/wHdSDTZRW8c03gPOjtOzqbHxdfNult7QnWiNKFd8sBqwzJU9JD9/BkYBYct5+h5DlK4hdvcpp+9kSWVVZyAU5UZ5R9l1xSZqUyfDv2+Yi1heZnDO5VN90PY9c+zRF3mloQn9ljPodnpo0CoVMxsm/vUJ6sZYLe9K69ZiZg5fuGMjS5vHyzEITvoSR6ld5dtKkHnW8zMGLTbAXmgInl0o3a/dAh23b+rr1xMYC7rhmHlPfeQLv5GdYdGEZqIsxidF8MTOGkE1H2LDwPV75ZDfvXRPebcdsWcYyAGqaumfktfUxO6TzwW1ECGm3DWVTwRr8ZEmU1ojU5d9CpFjHh3/8C+8ffyW6b5T9SUCfa2H5A5Ks4bVmW0OrvhOzQ87Sc0s5VHyIRL9EjpYcdbrXvs3xEmIJHu3H+uvcOFy6F3chjOrzY6mvTHb88WoLQYmSteHIB2HHu6xR1dEkGtmqlhHebHBgVzJulqYYdVLjfm2xVAkb+wTM/Qi+vwnf1GvIevYLbnRr4rHbJ3J3AdwNQGHz/+uoA9JQApKUrOKM1Cyv8S8gOvx5iBjWLneursIkmsiuzmZw0GCHb8sal+MTC5v/w2rpfw/iE1fJuIOhDAxENmU6h976kGvGDMXXYzT7BxfztwubudkwmOVFN1FWb+Te4yvoE+TBsH/9o9uitMyqzG7JWraMXvc/9QLnSmrpW5lPQkXOJcvHlWbBXfMxAufGXrQT7I7gJcIjwv5jt0vSpMmbl5mq1pIsPZ8yjjnpmxlHAe5nDMDj6F4GHRDb/J+7tnbrMcuuzsZN6Uagq+NIZFto63jF/vNeXjy0BJm6lAX/2ct714TT5+h2gv/zHdteeZdZU2egCGjbp9mRSK9MB8BfY2W9F9LcLPzJCBj7lMP0n9bXrc8/eJ3BUT6cOzWDik/XwjxYOEZNovtQtj32NyKmzeCxG0YyJreSbY/9rduO2Zb8LQCcrTzr9G2D7TEb/+JfcH/wNvq43MomcT3BLjF8M/05imua2PH438gaNJ7XfjrLe9fU258EVGZJRHzef2HgTZf82uyQc6biDIeKD9HbpzfRntFOsbJtjSgF3jWfac0/D7KMlcgFcjH0P84Go49jj1dbMDtbXfclnPwNXekpUMDDoZO44B1iP8mFORu+4QUIHwKVuVLzrYsXVGSRM2cyDWXme4FUbfn0w7ZXdzowgDOefegT6M2Eewbin7eW4pwkKTN+8Es4sxYMDbDnE4fqx4tqi2g0Njq90t4Wn/h8wBz83FWoot5Fayrk9TGvM+znk8Rqm9j41ofdeq2Hq9aGTsGyuElMyjtIn9mjqfp5CXv2b8WnIZhs43G2B77L6dv8mV50hOVxE5n3yW627UmjevkK/O69x2n7KIoiWdVZ9PJyvkTF9557qFq+gm170pj3yW6Wx09ketFhRk4cgnbOFG54TsENT/Tmk0feRqty5eEJT6BVufLKnf/CdddB+qWn4XvH7WgGOD7at0ZWdZZjgpeS05eVqEALsnT7EDImzuea/EMEJCTw+1CB/Uv/StbPm1nZexxr4lK5ddqL3X7MzM113TF2u63jNfDlt/j5DQOPPbeIJUseJfCu+Rirq3G9eRbT0rdi+Ol70uL7Wf7nLLzFafu877wkR9l/Yb/0QnkmbHpF+rnXNZL28+sZ0usOgPm6laTRW55fk3eMaL0XWdVZJGn0TMo7yLK4iQCXPHcGUr5NYcA3AxjwzQDOVZ5Djpxjpccsr6V8m+LQ7ecsvMXm/DD8/APT0rfiunA2pupqQu65gZ/fbOKlF5ZSP3oIAc88wDX5h8iYNI/Pbx/Cobc+RLA3CTi7XnLe6D35sovtKNwBwBNbnnCala1mQCK+d9xOv/Q0XHcd5JXb30ar1HDrtBf5PTmQVQPCeeIf/XjoH8GcmBiNf0Kc449XW4ibCgUHpGb6ymxmVpYDMO7kWp4xuLNo3L+6vo3yTPjfdEhbBT7RkL9PclBZ8BX8NQ/m/RdNr/BWj9nDE56gVq3iz4/4cMNTIfzlpeGcnz6SEePGM73wOMvjJjJ/kyf1p/dR/cPX+HlJf2+0RTD+rw6/fpgrob29eztk/W2hLT6R9vgQlj44ChM6/KsEVu5eSvXyFfS97UanX7daw1Uy7gT8nF3PxsQGPv7kMbb0Fln4vY4/b9VxQiUw1OUCH71xF5sGNHBGr3b+BacZ5Y3l1OhquqW5riVROqNX4zZrNjIB3P/YwWvfGHjr+wz6rPsM5bSZfBdehnLaTI7VKboteNGb9OTV5NlfL66rk4Y1tKN505os/Zxdj+vMWTRW1DH5sEjovR+watFXXFNwiOo5N7HaP7tbj5lWp+VIyREiPCKcsr3W0PJ4qadOp76imjNRavYMDODMNddTp3bjrlkvs7zXWNbEpTJvwXvdFrxkVGXgpfa6SJIWz4G4aeAfLzV23bkG+kyWXrcDWhLLWa/ei6q+loxx422ev/1OOTfd/TMZ48ajqq9l1j/uJS2+3yXPnRHAbLtxG6+PeZ1RoaNQyVXEeMcQ4hbCqNBRvD7mdbbduM1h24ZLyeW8BYtYEzee5b3GcvfMl2mSKznQz48fpnijHzsRk16P66zZ/JzV4Ljg5cxaCB8Gbn6XXazB0IBGruHzaz9nRMgIpzjktCRKxxqUKKfPZLV/NjXXvsLk9FL+siiH2cvLGbBfcgxx+PFqCy5e8HQGvFwNjxwm080LlUkkYuTj9iOyi+dIsqLek6XGfRdvyUVr9RPS708tx/eu21s9Zt+Fl5E+wIfXv6ji5R/PE52Ri8+2g8gEAbfZszmjV/PeHeP5z4kpCPNuRREcBmOeAFd/OPwN3LbcrtePljD3oDm72t4an9g0oJGPnp7A3OXDuXFtMe9/rmfw8gOs6FvDR69fx8bEBn7OanDqfrbEVTLuBFTU6bjjtRVMPSFwPCUAowySjpbw/Dd6ZlUEMfWkwO3/XEllva5bsksg6Z+h+5xUrIlSRZ0Ol9lzKP9tOUJ9PZElEFQBkzIy2OYZg3blSuKfeAid0dRtwUu+Nh+DaLB/8FJ6BhCvmBkHLAS84ssvMVRUkLV9P+LWTSiM4K9t5M/7v8MwZAi7Msq6/Zitz1lPk7EJk2hyyvbg8uTy2+8eRfztZ+RF+cTlNjHyWClxG3+lKLQXGoWc+WXHmf3mMzTpjU4NXqwzvVqdlnFh4yzj5wf4CqRkfysN/yk6LNmeteGS0Rm0JJbT577Dw/P/IWXh5r/K8thLXUrSUiY0L/cqNUpX/jz/NabPfcdpAYz1UCJRFOntLUkunDWUqCW5bNKbmPPms8wvPcaIohOojXqGpJVz8/oqlDs2o0tPx/DT93z73SOOCV5qiuDCceg75YqL+rj4kByYLDXXDX2GRamLOr/ddqIlUWoyGOn3xJ+pWbmSnP3HUBj0BGh1XHtYD7W1lC9dimbOPCrrdVR8+aWFmDsdi+eQ4RtBjElEfuhruOn7rhFZkxH2fCz1fhz6Wmq47TcH5ArY8Q5U50szJgoPohyxoNVjVrVsGTGny/FsEAkrh0eWXKBKJad63TrCH/zTpXwiKBEC+sGcj6Tq677/2PX60RIZVRkEaALwUnd9OmVH0ZJP3PHaCqacUvPG10qmHjZxYlBfBmeKnBgUx9R0jYV/dSeuknEnwNdNRZ1bMAEThzHjcDVbBglk9pITUm5k4eeFqBLjqHcNwsdV1W0XnMxqKYrtLjJuTSx9XJUcfuZmBKOBnAAwyCGzlxsGGYz78S02RtYw6o9p+Liqui14OV0uOZ4Euwbbd8Ulza28LTLjLYllWnw/vv3uUQw//0DFN4v5Yc3LRF6Q/oYyQGkUkZnAdHAfsw+uxGvuXEqU7t12zFZlShrPwtpCp23zcuTyi/7TASiLiacyxIs8fzAhEJ6XzvyDy/GeOxdVYCB+7s6tVpkzveamp6SApIuZ3sg5bFP0lci4eTR2O6eztgctiaWLUs6rd08g4qbreaPwD+Zm7eT32NHkpPRGBMp8Aog7vJXkyhz+ozhN5M3X89rd43FRyp1efVmTvYZGYyPbCrY5dXpwS3Lp565CGRiIOHIsdx9ZRn5QDCaFnAJfqPP0BGD5xNu4ZdqLjglezq6THuOmXXYxk2giqyqL3j7OlRCALVHydVNRrHRHNnY8T+z4kmoXT1RqJaLZ19tkQrtwAat/e5KKbxZbApmW10KHy8eCEsk01tErZCiUZ8D3N8H5E9L3cM8nErluL8zSlBO/gNoDqvPAKwImvQhPZ0LfaTDvMykj/3QGuHhdcswOnc6nsVGPR6NIxYjhHO4FermcgMpGqo0yLshdL+UTZg183DSImwHb3oJjP9jt+tESWVVZ3WZja80nfN1UnDiSj6nRQGi5jp9u7cfk/iNIHx7GwN0CAfMXWPhXd+IqGXcCZg8M46cD+fg+8Tyh5xrZnSASVGjk12kGZCaRnPN6fjyQz42xGqqXr7BEtc5EVlUW7kp3pzXXtSSX1sTyuyWP0bdIRAZEl4J7EySk1/HtdQGo9ZCU6cI8j0+ZkxzabcHLljypWSxPe3k7rg6j5LQ08tjXtrTXklj+8q+lTJ/3DtPnvsO2mGGYgB39x9N7+zZ0chl1aigPdEFp0jEp7wDy2fP58UC+U4+ZdZb3eNlxQGquc5aety1y6T9rBrelb+BUQC9eSl6IS3k9EWVgGDMMg1zOhILDaG68yXK8nBm8mDO9CX7S4JE+Pn0uZnpHPo1H4WFY0+ws9F4CFB6UtK12QEtiefOwSHZmlOF640247dtBicaHohvvIb9Kum2c8faixM2Xxw98j2nd7wTcdy87MspYODzS6dUX8wCWRwY94jTJhRnWRGn2wDB+3H6O8/sOIhNN+D3/AopJYwmrAKGxgXTfSCbuWMpzJTvtG7yYM63rngMXH8kF5DIo1BbSaGx0up4XbInS7IFh/LDxFEXb96A26pG98AqqyEjq1KCTy8hMGY9BkLG37wjWxqcyY947TJ/3Dr/8a6lT5WO18dO5oK+hd/houPZVKNgH6atg6L3tk6yY/z6L+sPnE8ErDCpywKADtZeUCf9osCUb3vI7bXPM+gdgfOpRdHIFepmCxCefYPxJUBmNyAHP+moaxw7j2+8esQ1gbnyZtFeOSsHLx3ulgUDZO2DjSx0PKK4AURTJrM7slh40kNQIEQ/dT9XyFdwQ40rFBx/QoHLBqBIo8Wsk7+dv2ZWsZOy5s/jde4/lWt+duErGnYA7RkXx44F8jpt82dwviOnpbugUcPsKGQICEQUZzH58HjP/cS/G6mpyUlNZ/duTTo38s6qziPWKdVpzXWtay4ULP2B5r7FUqD0o1vhw7tu1rOwXR51GhijAoFw4GBmOX30DBSs2c1sft24LXo6VHkMlU7GtwM6a1JI0CIi7pMP9UmIp4/qUcO4fH0uo0IgALB++m4m/TARMuOjAr04gPVJEhsh/3p3Ldxducuoxs9bzuincUMgUhLg7T8/bFrk8nVWMymTg18Sp3Dt3OBdcPBGBU4ZMimPikYkia//2Fj8dyOf2kVHdEvC12lxn1rD+vRhkCkn/2Zw5sxesiaX5urXmHx8gQ8QlaQBHzxQyMjeLQl8YlpfFdwNnEVhfQbm7H8fqFZZj5uzqy4yYGQCkRqQ6TXJhhjVRumNUFC6ffUBgVQmZcYO58Osy3D18EYESNxWlf/oLbvoG4o9ut1/wYs60nlouESqFGr6ZeVlyeK5KGvfeHWTcmijd3tcN/Q/f4ldTRkb8MGpWrsZUeB6NDgRR5MLk+egFOUMyDjD/7b9y39hYrk8Jx0Upc2r1JTNQIpW91r0A6/4qvWgySNfrBd9IGe6PhtqSWjMB/1df+HAQnF4Jk1+V+oJOLgWPYPjTFnhOatQkbrpNNrytY5ZycjsB9ZXk3fcUO3qPpGTxT4gCNLgpWNFrDKWuPqT5RLEmbjzLeo1j4cIPLu19mXSDlI0XjTDkHrs3c16ou0CDocFpTiotk3u/L3uK7NRUTNXVzHr1XvoXpePVWItLo5FHPsjG3c2Ha0+q2d7f9rrVnbhKxp2AKD833r1hIPctPsjhQU+TfEzH2VAQgc0Pvkq9Qs2h8CS0KldunfYi8xe8x1MPfea0yF+r03K09KhTm+taksu+QR5MHxDCuDmp+DZpOZA8gceWnuJQ3yZcG0w0qCBlXynD8qT5dU/sWUzDnKlODV6sM70l9SUk+ide1PPaK9NbktZq82ZLYvnM1HgentibA79vp0/Wcaqj43gsdzIzNvbhvJcSBDifGMuAbJETEa5MOKLm9aSf0Pz2vY1kxZGw1vPKZXJ6efUixjPGaXpeuJRc7l6zg5ijO6kKjeEp9xK+WLGfUG0lRhnEHS4jOPske+JGkXBsO6+MCSLUWNctAV+D/uLkuksyvUoXCEpwyCROa2IZ5efGs1FGkvdvYF/8aDxPH+VfpVsxifD+LA0iIg8q8jHIlXgVZfPaO7/y7g0DifJzc3oAc67qHBqFhjD3MKdszxrWREmZfY5J2fv4vfcYjs3/E0G7N1KzZj1GGYRV1/PjWS1lQRHIjQbWbjlun+Bl8Rzoe63U+GfSw9yPr6hnzqjKALpnwJtZmuI9dw6qn79lUs5+DgX349i8ewjZv4WmISNBJlDko6Dk11+pCIpAYTJy7NAZfjlUwMMTe/PM1HinVl8yG4oB6P3A/osykunvQNZWeK8/FB2VZgCcXiER77djLxJwTNLfpSofVj0q2U66+oNOC/7NwVALudnlyGWv7z8FIPGjV5iavhXjqmXoXOS41Bk4EJLAD30m0q8ylym5+/nLl/9g2oAQ4oLcbYMX1SpIuR38+sKRb+G2ZXZt5jTLXp11frVM7j314GfMX7CIW6e9iF4mp16u4s75b7DlqXcBcE1OIXZ3AYeTn+G+xQct163uxFUy7iRMiAtk2UOjCI2NYFt4fwbkgiiA/+5NrI8dyaCC46jGT+DTR6egUshIjvB2WuS/JmsNOqPOqc11Lcnlv28exNoT56n+7jsaFGoWxmr4aGEKd+wqptpFgdoARgH+/thgDs28E4B6pYtTgxdzpndkiDTVrp9fP/s5N5iMsP1fku1UQ2WrJcOWVnMRPhruPPU7lWp39tz4MJH7tzM1Kxe/WoFtiQLB+0+hMkJSfj2+DY30XjiXim8WU/HNN9SPHnKJ9tJR1ZcNORuoaaohuybbqXpeuJRc3n1yNVVqd/be+gRuW9fzSc1OBEHG1gFyFEYo8ZJTOPV65KIJ2R/rqPjyS6cFL9ZwV7kzJHhI2811oYMkMi6Kdt2uNbHUl5Tgsm4FDQo1eQvvZ3NQIpodm9geM4xs71C293PHdfsmdkYn0ahQc0vpYSbEBaIvKXF6AHOu8hy9vXsjE5x/S7Mml3kvv4ockdFPPQB+/hS7+aJvbGJzvB+iIPJJzU4C6yupVrlR/+F79gleghLBMxxO/iqRvJjUKzbmZVRlEOYehpvS8QSkNUli/eghVHyzmOolS/BprGHYhdNc/8b9qEwGZFv/YHPvIPxr9cwoOEhoTQnVKleaPv6Qd68fYCFNzqy+ZFZloparpWDPrL0edp80TMkjFOpKJKlJVa6U+a6vkGQg2vNS1q3mPGgLpWz6vZvA2ATVBZIspRVpSlvk8qUREg/YPHIulat38MMzn2JEQN4kUuMKd55YybSn7qVBoaZOpuJUg4J1Jy/w4c2DbIOXmAHgHQXT3pD2+fC3dm3mtEzzdpJMpWVyLznSG5VCzj9n9EFuMlLhF0Kj2hX/jaswIlCybSdrQlMIiw1n2UOjmBDn/NkXLXF16I8TEeXnxr8WDGRr6AtkvXY9KrWa+BM7Cfzrqwivb+VofhUffneI929KZkJcIPNTwp0yROP37N8BKKgtcNg2WsOyuElMWf04/TV6lH4+POlbRUxJNpvHL2DiylWMTk2lqKyBv425n1tyviL+vIG/nw7hEa94/iPIafD05dNHp3Df4oOW4MWREwDNmd6yhjL2nN9DnE8chdrCrg/LME9e02ml55U5Uslwzsfgd/Fi9nN2PfOaiWXQc89xcPlGep8/R9oN91MXEEqO0pvQ+gtsHuDFqjF1JGc3YnRVUxwfSPj+WkQBDkQM5KN+MxFFuH5wOA9P7O3wIVMiIgbRwO1xtyMi2m9YRjtQUacj4rH7yZ0zh4ax19Cn6Cwnp99CXWAYG2NrmbRxPduSBX4eI2dMuozY0kZiP/gLALG//Y8K84q++YZvgbTvLq7bUQOT9EY9OdU5jA8f3/ZCoSmSC0NFls050lVYE8viT/9D+Im95CcO58UbhnL+xErq6kOZ9d6LfLz2FVZMKiYpDwb1VlDgMYyYU3upr61H2w0BTEZVhtMmR7YcXPMtUN88SdksLvB94BauNy/g5sb3yUnIFFu5ZuN6tvQehTEgmMl7fsNdrEVfAtXLVxCxYgWVHx7q+A4lzJOaAbO3w+A7JUeOU8ul19tARlWGU7OW1kNY/r0pg6WHpXvN1+tfw13fgPfGbbj/7xNqd++mrkrLT8nDMHisYvIhHTmuIaQNT2X65u+oTT8B/aSmeesAxtGD1jOrMon1ikUuk0ukecPfJRJthtoD6ssl2Yc5qVVXevH3PtGSHCRvD4QNgqgx0t9n4I2tbq/lkLJpicEUVDVwfc1pDIKcKKGBh384wuelG5ApFKT5+7M09QIv/niesMYC8mSgqa/m1beW8O4TNxHl50aosQ5F3kGW3fA+zyT0lQKKm76X9mX7v6SBYgMWtLo/HUV6eToqmUo6Xk5Aa0PKrukfxKG//J1QZITVlfPFKA9UP+0kZ+BoakvKGP3C44wfcWXXMmehw2kEQRAWCoKwQxCEakEQagVBOCgIwp8FoXMpiY6uTxCErwVBEC/zP70z++FMpI5OYPUNGpaPk7Ja7m+/Qr5HEAPPHeDr+X0tUZojI39rycWJ0hMAnKk447TmOrDNWgL4rPyJclcfyqfMZ11YCrn3P0iOTzinguL4x/wB7BzgimLTOj4cH4ggk+FZfoGnP9vM+zcl8895A5xWtlyXIzkWvHvwXftkes1l5sF3Ss9v+aXVkmHLrOX5ZStpUKiZ+vR9/HWYP7GGajwHD2J5SjCuQRH8/VYNXlVG+uwt4kBwP/zrKqkflYqXRsmb1w0gwEPtlOrLbf1vA2B02Gin63mtyeWFN98EYNjdN/LCzP7M7jULQ6APx2YOokqjYUuSQEGIisOpYWxdcC0AuyJTpKaxue/w1as/OkU6ll2TjUE00Nenb9sLhTV/P7soVblc1lL7ww+46hvpe3Q7afH9qPrlV+R+fvyU1UCAOpJi10aM3u54rd9H36M7cNU3kjtksNOrL2UNZVQ0VjhN/9wya/nlP35k+tx3+Mu4hwHIikrAdddBfO+4HXX/fuinzKRCHskv42XU+KqZNTCQ2U/cAcDxxb92vfoSNxXy9krZ1v3/bbMJ0Ay9SU92dbbTjlfLrGWgp5o3rxtAH0MVgQ1VKEUTT765lJJffqO2oIjHxj7CvTOnsmKEDFNiDL0M1dz39K00KFQU/bZS+gxOrr7YBC/W/uPzPpO03s8VQO9rYNa/IXIkxIyXHqf9S3pdVwd/vABn1lzx7wOXVo7/OW8Ar40LJj5tP4fiRtDrxB7+O8IdxcZ1nBs0jlcn/4lTMXJy/HzIuf8BNsUMp0zjzc2ZWy18wqb6Yh5o9Io35O6UMvu5u+3WDH6s7Bg6k46t+Vvtsr72oGXleICbyDU5+zjUdzjrI4bAXx4C4LtBcxj563c9iohDB8m4IAgfA0uAIcAO4A+gL/AR8KsgCB0Kg7q4vl3AN638X9aRfegu9NUEcsbbgGbGTLwDfYn8x8u4GHXkffu9ZRlH6i6tm+s0Sg1uSjenNteBLbksPnqSyLw0KsdO5sX5yTzw+qOoZDD2iw8wiSK3DBrO92MkxwTxiYfYFTkIJSYerj3plODFGg36BgQEPp38qX2cG8xl5uLT0oXeK6LVkqE1sSz97HOCj++lID4FVw+pzO09fz6y9z9Fr3+Au5JupspLz5nksRSpgxiTdxgT4Ht0L8v/PJobh0Y6TXd5puIMAHE+cQ5Z/+VgcTK65x48MtMp8I8kKrEP+pISmjZtpf/SFSjcxuGuCGT5CPCtMJCwr4wtlfGIgFKlcHrwYh7n3sfnMo4YAfGS607h4baXaQfaIpbT577DBTdfGuQqVFv3Wojlb5rTfFe8gCrNUgAM/ZLICRL4fYhAhTtc8OKi64WTAhiz/vmyx8uOaItcTs0/QKNMQVhxDo+9+hMlv/yGNjuXxxjAiPB+VLkLPH2LgZr16wkL9iYvKAaXrRss51KnHR1cvCA0GXxj4aWqNpsAzcivycdgMjiNjLfW73Lj0EjurTmOUZCxI3oIf9v0ETlKL84OSuXrJ6dyQ9IQqtwFNj05He/582j48XsK4lIIOr4XfZPOqfKx87XnKa4vJtwj/NJfmknty15wdi2s/LNkfTjnY+lx7dOQsVHKkrsFSFM1r/D3MaMluWTVcpSikbwp17EuLMVCLn9ImMqK+2cgGlVkPToSlUzggTcfp3LcZGLy0ykrKL40eLEOKF6ulnTwJgN8PLzLziqiKFJUW0Swa3C3SRIB9n70FWqjnlF/e5SHP3sFnwBfNDNnkWFw6XZ9eGtot0xFEITrgIeAC8A4URTPNb8eBGwB5gEPAx84aX1fiKL4dXv3v6ehr09ffmoqRH3bNTRu30Lvwf3ZEhiNcs8O4DnLl6fTpcsrwCy5ADhZdpI4nzg8VZ5dl1x0ANbkMve1N/BAJGae5IpQs2I5vrfcQkVwFD6uRQwNS2DJWdBNHoP3ibPcu/gd1t3+Z8J2rsWgfx6FUuG0smWkZyRymZwB/gMY4G8HcmHWINYUQUiyNMyllTKzmVg+cc89nJsyDc+mehqnTrGcK7GrV/Fu8w09zscXgAPjB3DnsX14piRxuqyBlNO7CHa9GOMmafQXS5dd/ySt4mzlWfxc/PDTXH4ioD3QUkJgLrpmIGUewsvySIu/mBFJf+Bh9lwjEBogUojA9iQVfbNFntr2OfkeQSTmHOOHj94hPloKVCb1C3K4dOxc5TkUMgXRXtFtLyRXQnBSlzPjLcvhNw2N4M3rBvDRbwfxr6tElMt58s2lvLr9N0yiiVXTn+O2XpBWu5GDxQf5Z6APi6ogsFpgX1g0qZnZ1N46Ha9KJX+dFk9ueb3D5WPnKp3rDNJaSby2qoYz+Uc52nsoVTK1RC5dfWlMGMjXT07FYDIw93d4doUceW0DGePGE9m8PiNwbuw4Zjc/T3vq4rbaJYWqLoScnZD6V+nacQV0h5OKtSQRoKmhkch9m8nuM4g/ffEmRU89jfrESdZfM58FzUTJRfDh17M/c+/tX1E8/2Z8broXr1N7Ofr9crxaXO8ciaXnpMCzTld36S/NpBagsRr+PVgi3u8nSq+5BcAjhzrleGQtS/R76mn8tvxOZmwSLz44Df11g8m96WZMQ4aTYXAhxt8DmSGY3W5lLLhlIdXLlxM7dwby9b9w5KdVJOlK2w5eyjOlmQXGJogYLjmrpK28RCZ5JaR8m4LepLc8v77v9Xx+4nMGfCPdI5UyJYdv61ry4HKwliT63nMPqt3byQuKYcqIZPQlJZjq6oj4y2MO4VP2QEcy4881Pz5rJs4AoigWAw82P/1rB+Qq9l7f/yv0CZaGehytOIL33DlUfPkluuFjiCzO5nxmntMi//U569HqtJwuP+305jrrrKXr6WOUu/rQf9wQC7m0zhaZS/YFNw3DVFeHKIq4zpyFT0MNJzbvcWrZMr0inThfO2Z546ZCwX44fxSyt1nKmDlv/GZT4l/w9HXMenweGePGIzTUAxD4zstkjBuPsbqa9AcetrgzmI/X5ppsNLPmoOkXj/dtt+HVqGXP4ovFI2e4XpytPGvf43UZtObHfuNN7/Nt/LWYgCa1K4ovvgVPL3JGTma90ZekcF8mRI5DJVOxaVQQIbV6AgcNwO+xR3E1NFGwYrVl/c6ovpytPEusV+yVKy6hg+D8sS5lsdrKWj4uz0WByN6IZJus5Td/mcszY25hfp/5KGVKkkfI2TswkPOuXgzLLUIA3NKOO7X6klGVga+LL/4af7uvuy20zFru/XoproYmBtxzCw9/9gpBgwYQqavk34M3MXP1COauGQOCQLqfO5uS5dS6wGs3yhCBpX1SmTb3HW686f2O+WebrfM+GQGIkDC/Xft+qvwUAAEa500sbpm13LN4GV5NtfgvvBllYCAu/eJxnT3X5joU5O5LnamMtAfux1Rdjf9/JScM97dewlhdLQUwj8/j+qeuc6gUaku+NFPCHPS1iZbZ5nZmwNuCdeX4xNK1+DTU4DrzYqLMQi6b73fRnr04W3EO37ulyk3f/tGUufli2LDu8tWXxXMgYS4MuFEaGrXg6045q5ir7f18pWTH0OCh9jM4aAesk3v5775PREkO+uHS1ODuasTvCNpFdAVBCAcGAzrgl5a/F0VxG1AIBAMjnL2+/4/oHT0BgH3Z+y1lz14TRgFw8puful66bCf0Jj0iIncn3u3wYRkt9anW5FJuMuJXX8mZ/gmtkssw9zAwqTmgK7AEL4Oum45RkJG/er3TvmxVjVUU1xcT7xNvv5W6eMEtv0o/L/jachHXDExulVjOmPM21UoNBpn8EmJpdmdwV7kT5h5Gk6zAckEfnDqUahcPav7YCDhHd2kwGcioyri8/tmOaM2PfcWfR3HN+WOkB/VmQ+QQKh/8ExsD+hNybA/Xvf1Xvpv1Cc8Oe5Z433jyZGo8Zt+Apl88KQvnUuIRgG71Ssv6nRG8nKs8177jFZoM+jp4N75LpeVLyuGA+46NFPqFc9fidy3EMvua+Zby7oacDShlSrYVrmfNSDUh9TX4pwzkgncwiad325SBHR3AmJ1UnImW5FK3eiUlngGkzJpgQy7rql618tp3ZeckFSPSRfb28uaxZQrKXDwZfuE0fzwxllWPjGm/f7bZWzxtFWh8QeUu2ea1wyd6//n9AOw5v8dux+NKaNnvUvPHH1S5eDDs+qltXoeMYhMCArvcGsgZMRk8PMmK6o8JuHfmS50LYNoJ656qzKpM1DI1R0qPOLWnyppcNnz5GUZBxqDrpcmqrd3vrumVTJOoZcsdszBVV5M5PhX/ugqic09dPnhZo5ZkkuOfAaMO9n7aKWcVc7XdbC8a5xt3cWCZE6xsrZN79WvXANBn/vRWk3s9Ee3NOg9qfjwlimJbd6EDLZZ19PomCIKwSBCEzwRBeFUQhCn/n7LoHl6RBBtF8urzON6gxHvuHHyO7qHUwx/3ddL4cmeY0c/rLUkhJkROcHhzXVtZyzeG3ApAk8qlTXIpE2T4qaLYX3jKQrjcZUbyw/rgfnC3075sZyol/XNfXzuTS7PcIPTi6d4asVz1yBg+SgAvfQNHAvteQiytLZrifOJQai5YLuhVX/+P4vhBhJw9ikFvcEoAk1Odg96kdxoZby3TW5+WTkh1Me7TpvHEl6/impSEIIDbrNlE97343YrzjcOkLCT8wT9RtXwFxrIyqkdPJCr/DOWFJU4JXqqbqimuL76y/rk8E/b9R/o56cYuDe1oSSwzDp0isjiLpgnXtpm1VMqVxHrFIooiBcZY0oeHoekXT/3EaUReyCLzSJplWUcGMNVN1ZwuP02Up3MHdtj0uxw7TVTBGapHTUQmk9mcJ1V1covXfrBbMJnKMk4PC0Iw+uM6YBCNs64nXFuC/uxZovzc2l9JMDd9T/8XVOXAxBfanc3Mqs7Cz8XPqVXQlv0uIWePUdIvBblCbnMdcu37NwvhvVB/ARGRNeNq8T/6BxtjawgpOo0MmOjWyKYnx3UsgOkArHuqlDIlfXz6ODXLC7bk0qsgk8LgWHwC/dokl8PCpfkUxwO0nBiaCB6eFN0nOUN9PGhB28FLUpIkk/TvLXmdH/hScuex8j3vCI6WHEUpUzL9t+lOrbZbhis2KNG6uFOv1NBnWJLl/Oopw33aQnvJq3k2d+5lljHPBY+5zDL2XN/twBPAfcDzwDrghCAIjp2La0f0lbtRrakn785rqfhmMZWLvyVAW4Z3TRkV33yD65RRLFkiuRs4qgyXVpGGQqZwih9oW+RyTu1ZqtTu/BE57LLkcmhoAsWN2RyrV1iy46YRowmpPI9s/ASnfNnSKySzHrs3IxYdBY2P5P3ajNaIZZSfG/rNG2mUq5j75aI2iSVI5FJUlvHd/nOWY+89NAV3XT0nlq5xSgBjbkZ0FhmHSzO9mT8uwyDIGHzrdSgDA4l7723GFp24JFMb7xuPIG/kpKHWcn5FTrsGGSLHVmxwSvBiLoVf8XgtngP9ZoPSHQwNcOeaTg/taJm1TP9ZqgQMuuPGNgOQRamLuCvxLkyYqCtP5rpXFlO1fAUD50wGIO2n5YDjqy/LMpZhFI0YTAa7r/tysPEWf+NNZIhEzZA+e2vnyYacDTQZpQb075KNjMzJJu69t0m5/3aMgoyMHy9Kx9pVSTA3fR/8CuRqGHD9ZbOZ1pneBkMDU6On2n9g2WVgTSyrlv6Gu64er9TxlxDLub5fWEhwoKb52u/vw+lhIQhNvRH6D6JJpmBI7lF6BXh0LIDpAMxZ3ukx09Gb9CT4Jzg1ywsXyeXWU4XIRBEvNzVAm+TSXB3aPzGS2BNpbAzoj8fXn9IoUzC0Kqvt4OWJFy42oZ76TbLY7YKzSq2+ljD3MD6b/JlDq+0tK+31o4ewZMmjuE4ZhXdNOa76Bs70T7C4O+XfemuPGO7TFtrbwOne/NhKB4MFtc2P7TlLu7K+o8AhYBMSmfcEUoB/AgOBjYIgpIiiWNiO/ehW9HENYWddBpnhdShCg8msi2Nsxl5cDU28MeIOdoYMwNdNxeyBYdwxKsohftDpFen09u6NUu44eYoZrTU+1dfWE5NxjPxBY3n83Rc488QzCNWtk8vBIf1Zl7eMgttuxq1UitVim3+nX7kc15XLWQLUL4E0q/fZ0w/6bOVZAjQB9m9GLDpysXnTCi0bnwx6A4FH95DfN5lBvaKJe+9tjFNnsGzhPZc0YEoBg8gvxw8ytf91hM+dg0tlEVpBRsNXXxBqdUFf9tAo+36eZpypPINCpiDWK/bKC9sJ1o1PAc8+i/eBHeRGJzAgPAho25/YrGtffGgPi5obG+PvuJPjKlfqN22kuiDd4U1jx0uPAxDiFnL5BYMSJded8BTpRiqTdXpohzWxrPjyS+SH9lHoH0G/PpEUv/FGmwFIPz9JG+rhWWx5P5vXUegXjuygJIVwdACzPns9ALk1l8vr2B/WzdSlEyZRq9IwKHV4q83UIFUSRoeN5qczP3FB7kn6cBfCm+cF7I1OwGv/Dsu629WInjAPTvwMObsgaQG4+V/WW3zbjdvYmr+VH9N/5HjZcVKCUthVtItQ91Bmxs50uEf7HaOimPfJbib1C6IpIBSvvAwGzruWii8/syGWyx4aRZTfEEDqZyptKMVF4cKhkddwz79/oP+6L1n3p6cIPLobg96AQilRGEc1oq/MXIlRNLI6azWh7qFsyN3gMIODls3nIFnN0Xzr8so4ZdN8nr9mB+9+8T/mrRlr0zgZFTuA7UmFKHX7yAwHravAkDMnCdHIcXV35Zmp8baN6OGxF5tQAZbcCDnbJGeVUY/C8PuhnX7hlY2VNBobua7PddLAMl/HWSm09K//ZncuK48VEn/mAH8/8C07w5IYWHKOnb1G0DvAjYRQT/r0gOE+baG9mXEzQ7DXuLdOr08UxfdFUfy3KIqnRVGsE0XxvCiKvwPDgL1AIBebQy/dsCD8qdnL/GBpaWlbizke5Zn0KcvBJAhkTAgl/NQFFiafosA/FK1Sw5zaDM6+No2lD45ySBkOJAui9Ip04n3tqH++AlpmLQ//th6NoYmA6ddeNmsJF7OFlfGNpI+Zwrr4VLRKDbUKFw4ExTNj3jvcduuHDtEQmmH35k0AfSOUnLaRqJjRUkJwZM1WvBu1eEyZAlxeAmCW0lw/Ukb+rbdS8c1i6n/9GblowifvnFOqL5ZmRCcEe2ZYZ3qzt+0lQFuGYsw44PKZ2j7efRAQ2J57zCIdq/7may70HUhY+mE85sxxePVlZ9FOAE6Xn778gmYHnogRcOEENGkvGandXlhnLSt/W054wVnqk1pvpLZGuHs4HkoPIkOqLmY9l6+gMT6R8MJzVJ3Lckj1xTrLm1Yhhd2nyk85Vc9rzloeq5VhQEDv4W1xdGota7kodRHPj3ieCI8I9Dp3SyVBX1KCYvRYArWlZB870/5KQtxUyN0jVUWOfHdF72pzpjfaMxqARP9Eh2Z6L5e19MnLQAZcGDemzazlhpwNnK87j0k0UdZQxram/ZbroPuUKXg3ajm65qJUxFFSqHq91Cj/yshXHN5T1ZqM87ZbP+RAYBwFbv6s6jMOrVLD2vgJnBs7k4SJI5gQF2gjqXGRu5Bbk8uGEYGMTJfh9Y+/02fuS2gMTRxZflEu0mb1pTwTagpA3wB9p3RY/mb+PpoDdUeitUr70gdHsaApG63Klbp7HibLP4qhD9xK/PEdxDz8gMP3qStoLxlvHg1oyWi3BvPvtJdZxlHrQxRFHfBG89Ppl1nuM1EUh4iiOCTAgYNhLoeUb1MYsHouf3WVGq7GRQ9hS5KCxZnlPH9XPkfimog4ewTRYHBYGQ6gtKGUisYKp5LxluSyfN0G6pUuDJ57scTb1kXVrKP9KrmcPke3M+T+W8nyj+Jk36EMLM3g8NOjHRq86I16sqqz7C9RKTklebyGJl/yq0sG/WzYIkkubphxxRu3Zdy1qoiECcM5N3Ym6+JTaWq+odw940WHBjBanZYDFw44NSsOtpnesg8/BKDP9EnA5TO1rkpXor2iSYyp5b7FB/khdjwVvy3HI64PLkY9Pwjh3Lf4oENLnekV6XiqPK+sszT7G29/W5r490b4FQeJtAVrrWV9/AAUiARPGn9FraUgCMT5xqHUFFne7z13DuFiPUrRSNY/XneIVtOafKjlasLdw52u543yc+PdGwby6vvLURv1eGorqD15ioplK/ih1/g2z5N+vv1QuBbZVCJ6T5MI0ZnfN7W/kqB0lRq/Y1M75Nyx/8J+5IKcm3+/2aF63raI5W1TXgDglF9Mq8TS8vHkSoaHDGdS5CQMJgM6PZbrYPKkERgEGUV/SC4njpRCDQ4ajEqmYmLURIf3VLVGLr9dOIDksgyqBg5DfesdrZJLc6A1M3Ymga6BnKs8R5HMj5qJwxi8MY+R182iXulC2dqLf+s277OL50DifIgeB2fWwq2/dUj+llYukXFncIrWZJyh7kpC0w9zvv9gHl84lj5ff8WB/3zr8EGA9kB7yXhO8+PlrqYRLZZ15vrMME/fDOvAe5yObTdu43V5GCPco0AUOV95jg0jAplwQuCt+mBirnkGD109R9dtt7zHEY4EZv2zM8m4NbnUFRcTmHaYwrhBqDUuV7yoeqg8UMvVKAICODrYjwP//Y4+X39Fwi3XoTIZOLFys0ODl8zqTAwmg/2PVyvNm2a0lBC4nDhEYUgvPH29rnjjlgky+vr0Ja08jW+HlNL3mBTA5PhKwyue8alwaPXl96zfaTJKjgjOhHWm1+3MSco13sQMjGtXV328Tzzl+hx+OPElU166B7Q1BC9dDMC0b15nyZJHCZ4z3ibr19VKgnWmV6vTkhqRemU9r9lG7a/5IMhg/F87baNmJpb3LT7IiRoTItAryv+KxBKkDFiONoO3FyRaAhj1iSM0yRQoD++/4vs7A2vyYRSNDAgY4HA9b8tMb1p8P4LnjOfNDZLdnlzXRP7110NNNVNevJsfTnxpQy7N6O/XHxQVLN532kK+IsP9KXfzwbRr25UrCWY7w3f6gLYIhnUs26fVawl2DXa4nretrOVroTUA5M299bJZy0Wpi3hm6DOMCRuD3qRHUzfLch3ULf2ZwuBYXI5LftGOlEKdKj8lBZwOzIib0Rq5LN22E6XJSNTMKTx246jLkssNORswmAwYRANGeTHrxiioWr4Cea2WwrhBBJ46iMlkuvx91tyLMO4pqC2GY993SP6WVpFGmHsYXurO2Tl2FC0r7UfXbMNdV4/3JCn54qxBgPZAe8m4ebJEgiAImjaWGdpiWWeuzwyzkLf2skt1MzxUHswacBezGwx4InC8No/zsgAaBrgy+Fw4I26Yi14mp2jNH5b3OKIMZ45inTkZ0ZpcZv3zLbwbanAZLrlXtnVRtSYreqMeN6UbnyeVMTZnK4+vHsuftX+lXulCxcZNlvc44kt4tOQoQOuT2LqCoiPg6idpgFvAVkKwjLCSXPSDhrbbrqmvT1/SK9NZVrmVojEJHPjvd0R8+y0Vrt4oDuxDIZc5LIBZnSX5cxfVFXV5XR2BOdN7pEbEBMg8PZDJZO3qqo/zjaOwthBNUj9877id3tu3IRs+kjzvEE76xTqkkmDO9A4KlIKxwUGD25/pdfGEoATIa79NXVvEcsmSRxl2Zg8CUHLrrVckliBlepuMTUQH1VkFMFrUJgMKo54pL97tkAAGYFXmKpqMTWzL3+Zw14a2Mr0n/WI45x3Oqhe+QDZ8JH12bMf3jtvxHpTc6nr6+0mOF0tP7rdUEiq/+oryfoMIzz6F+6xZbZ+fLe0MFS6w6/12Swjq9fU0GBqY3Xu2pOd1YKa3zebz3bsod/Ph8SdvalfW0ny8UnrX2UihTP0SCSvJpezUGYc1optEE2kVaZZ9cAZaksvKjZupV7qQPH08cPn7mlKuZGToSADkJh+q3VwuJnGGj8C7Ucu5/ccvH7yY5W8x4yB8KOz8AE7+1m75W1q5c49Xy0p70do/0MvkpFhZQNrwJnMwu6h/lyeN2hvtIuOiKOYDhwEVF4faWSAIwnggHGma5hXvCvZenxVuaH48cNmlegLiprKhPg+ZychhsYFY+RFWDaqlaudpNIYmCsL64HZKikMcVYZLr0gn0iMSd9Xl1EL2hTW5NGzdDEDctAmXJZfWZWlPtSf52nwq1N6cHhbC23kj2bxwO4W9BxJ46iBGg/TlckTwYh7+kFWVZbd1AlB0rNXmTbCVENT26S9NkZw0rt12TXG+ceiMOgYHDubTuCbpQu9mpCxhCKGZx2lqaLQsa48AxjpwOlUmDRdJq0hzqp7XnOl9+/1lKE1GPKtK2yUhgItVonf6ZlC5bDm7M8u5uffNZPUeRL+KHPY9NszulQRzptcs5xkYMLBjmd7IkVBwEIztcxRpi1jec63UarN55Lx2EUu4eLzSKtLwHjTQEsBog6SA9bHZjpNC1RskPe/fhv/N4Xre1jK9Xy/oR7+KXJoGDQM/P27ufTO7Msouez6YB6JMH2KwkUJ594lFaTLyoym47fPTbGc48XmoyIRrX5Wet1dCUJGGSTSR4JfQpWPRXrQklk0NjYRlnqA8YTAymaxd15te3r1Qy9UEB5baSKEiDDXIEMn955sOs63Lq8mjTl/ntOMFtuTSaDASePoQhX0GonK56KTS1n1tUeoiXhr5Ev4afyI8Q+klPmQ5b/uOTAYgd/nvlw9ezPK3V7ylx+o8yGufs4pWpyVPm2c5x52BljJOt1NHKAjvi4eP56W8yTqYnfNRl+xgHYGO+HKb9dhvCYJgmbAgCEIg8Enz0zdFUTRZ/e4NQRDSBUF4g0vRmfUlC4IwUxAEm9ZeQRAUgiD8BXi0+aX3OvC5ugcuXij7TmWAVy8QBM7rkqlKmIz3vLnSF3FgCiFlBZQXljikDKfVadlVtItYb+fqeW28QN28aFC6EJXY57Lk0rosHekRiUk0YdS74nfP3fhuPYFLVQOasWPxbqjh7P5jDgteTpefxl3pzh95f1x54fbAZISd70PxCUn320qUbi0hOK2VOp6jgzyvSCzNpPgfe/4BwMzYmaSrTvNHQh0fPJnKyqjtuBqaOGbnJigbPa9CTaAmkFC3UIfqedvK9L668QMA5E2N7ZIQwEVHlS0NRykak2DJ7A27cQZy0cTpVY6TQu0p2oMMGXevv7tjmd7IEdLwn+IT7Vq8LQnB80FSe07NiHHtIpYAMV4xqOVq0irSLOvdnVnOS0NuB+B+11KHSaGGBg9FISiYEj3F4Xre1jK9Zdt2IhdNxM64pt3ng7eLN2HuYejk+TZSqMAfvgBg2vfvtF1JWKOWJAOb/gFugZB8S4ckBObgOMHfOeSyZdby6O9b0Ria8J0oDbxrz/VGIVMQ7xtPft1Zy3Xwh9jxKI4coFGuRHXsoEOkUHBxUqkzM73W5PLsui14N9SgGTMWaF9SThAEEv0TMSpzbYIXzY5NlHgE4LF1w+WDF+spoi9VQWCiZJ35yYgrZpLNsldnNG+aYV1pL/zgI8LKCzAlSQmfS3iTOZid9CLs/Q/M+0+n7WAdgXaTcVEUfwU+RZqKeUIQhFWCIPwGnAP6A8uBj1q8LQSIa360x/qigVVAiSAIewRB+EUQhHVIFofvNi/zrCiK69v7uboTi1IX8bfkRwBIdfexiWTDBichQ+T0LysdUoZbm72WBkMDKplzR8OayeWf/rcfhbYGpcnQ7qzlhpwN1BkkN0y5upLllbstZbi4qakA5Pyx3a7Bi3Wmt6qpinHh4+zjz2uO0k80D6CtKYKvZ5Bzw3VtSgiGntuHAFy4ZeEViaWZFI8IkSRABbUFmPTeFM4extQ0F15d+C16Qc6FjVsB+1VfbPS8JiMDAzuY5e0E2sr0nvKN5qxPRLslBAD+Gn9UMhUBmoCLlQSNnqRrx1CndKFqm+P6OLQ6LUFuQR3X80Y0DynO29uuxduSEBj37aHMzZdn77u23YGGQqagr09fTpad5G9p/8I4eTKH3vqQ1x6eTrmbD6ojBxwmhTpRdoI+Pn1wUbh0aT3tRctMb/W27dQpXUiaPBpo//nQz7cfp8tP21QSZMNHkusdxmm/6LYrCUlJ0qCn/H0w8e+gcuuQg87J8pMEuwXjr/HvymFoN1pmLYs3bkUvk5M855oOXW8S/BJIq0hjXB8/GymUi1GPwmhwmBTqdPlp1HK1UxNW1uSy+rP/AhA//WLw0p772gD/ARTW5fHq/F421Zf6iBi8qkr4PnJ0+4KXiiwwNkF9mRT4XSGT7MzmTTOsK+11v68CIGzi2NYr7WY9/IlfIGcHuPp32g7WEejQxEpRFB8CbkGSmIwHpgAZwMPAdaIodkiA04n1HQM+AM4AkcCs5vfVA/8Dhomi+HZH9qG7ERY5Hl+jEVGVYxPJBmWcoEGhQr7iV4eU4VZlSifuhboLdllfRzAhLpB3B2twNzRyIqA3p2++jbWhKWhdvVj20Kg2s5ZKuZJRoaMIdQ/FTanhfJXOEryE+HtQ6uGPuM++0zhb6nmHBg+1j3ODOUpPkTKI3Por9JmMRkxrlVje3UEJgZkUz+41Gw+VB0dKjqAwBTGw70wCrluAfMXvFIb2QnNSkkLZu/qyKnMVjcZGdhXucriet7VM7zc39Ce+Mg9d8tB2SQisgy6DyYC7yt2mkjD85xGc7zUA/9OHMZmkYp09pVD1+nrqDHXM7tUJPa9XGHhFdkg33pJY6hqbCM06SUX/lHZLCMzo59uPtPI01uWs4z+9fCxSqPL+KYRmnUTX2GRZ1l4BjEk0carsFEkBSV1aT0dgnek1mUz4px2hqHcSSrX0fWnv+dDfrz/52nw+6JdnI4XK7j2QuIo8Djw+wraSsOsk1b/+hJ/Xbmk4GMCqx65oZ9gSp8pOkeiX2JVD0CG0bD7XnDpCYWhvPHw8O3S9SfBPoMHQQE5NTqtSqEcdJIU6XX5ammLshOZNM6zJpXtGGmVuvkTEx3ZopLv5b+zrU8yyh0ahdfNmXVgKQWeOIgB1RUWXvc9asHgODLwJfHvB2XVw5++XzSQfKzuGWq5GLVd39uN3GNaV9mrvIAyCjISJI1qvtCfMk4YanVoGcdNB7d5pO1hHoMPj40VR/F4UxdGiKHqKougmiuJgURQ/tpaTWC17pyiKgiiKd9ppfdmiKD4uiuIoURTDRFF0EUVRI4piH1EU7xZF8VBHP093Q1CqSRI0pDcV25ThalauoiwwEq8LeXYrw1kTjpNlJwGptORIPW9rEoK0+H4EPX0/AIMupOOhb2Ba+hauf+o6xEf+1Oa6zB32w4KHIVfoKDp3gyV4qfjySyrjkgjPOY3H7Nl2C17MpDbGUxoEmxKUYp9MrzlKLzwslZy9IsAzDN/J/VuVELwUKuljtcPHtFtCAFI1QSEoOFxyGHf3Gn5K+91CXsW+/QgpzXNIE1SdXqpgPD/ieYfreVvL9Jbv3INcNBE9dUK7MrIt+xJya3IxGbwslYTNE5eiGjEK3/oqso6ctrsU6lT5KUyiqfPkMnKElBkX2ze6oaWE4MQfu3A1NOE9fgzQsUAj3i+eRmMjgwMH2/hBe48bi6u+kRMbd1uWtVcAk1OdQ62+lkR/55FL60xvxqZd+NZXoR4uNcx15Hwwyx5WVe+0kUINuW4qctHEqTVbLJWExXP88H3rFtzilCgGTQVECOgHjxxut50hQHVTNXnaPKdJVODS5vPQ0jwMSSkdIpaARbN9qvyUjRTq5cG3AfCgh/1doaqbqjlScoRe3o6fTG0NM7k8qhUwAXJ36X7fkZHu5r/xqfJTiI/8ieufuo6p6VvRGKXz8rovX75krkSrlQTzYLGxf5FmGWRsumwm+UjxEZqMTWzN32qPQ9EuWMs4G2vrEAQBXUZG65X2uKlSwqKhEk7+2uFg1tHoMBm/CvtjgHskWYKBwVEqGx1hRFEGMlG0WxnOmnCo5CpC3UIJdXesnrfNQQZB8eS7B3Yqk5EUkESNrornZgfYNkH1ikJpMjrED3p30W5kgoy71t1ln0yvuWs9dzdEjZSaN08tRzl8QasSAt3+vVRqvHjmT1M7VOpXypUWgpccFE9hpe6iH7S+BjkiuW+8ZffqS3JgMiqZiqnRUx2u54VWXAi276RBoSLpWolcXikjay2vifKMwiSakItulkpC0+If6dMshcpYv83ulQTz5M0k/06S8YihkhXZu3HtcgloKSEo2rgNIwJJs9svIWjZlzAtZhpG9RnuDvqZvJ8W83btGxgRKNwoXVfsGcCcKJP08QP8nVdits70Vn78MQB9p3VMQgAXNbXRntE2UqgBU8bQKFdRuX2nZdm4lbchyxP5bcrLcHIZ9LpGmrjZQZ2reYiUM5sRrbOWdX0TkQGhE8Z0iFiCdJw0Cg1Hio/YSKFefWQGlRpPFEcP2l0KtfTsUoyiEZngXIpkJpf//GB5h5vPzfBSexHpEcmJ0hOX3H9zfcI4HtC7fZUE8z0q6UaJlO94R8oqt5JJrtfXU9pQSoRHhEOroJdzggqpLUNuMrbdH+TiBX2uBY0PPF/aoWDWGbhKxnsABgRJ439PZm2wKcM19ZUyKO+PuM0uZTgz4ZgRMwO9Sc/goMEO1/O2JiH44e4hJJZlUdNvYKcyGQMDBgKgcS+wKcO5/vYDALKsjPaV4TqAGl0NoW6h9vPnjZsK+XulbvXTK2yi9JbE0mgwEpx5ktK4pA5LCBalLuLlUS8DMCx0IB9MfM8SwCiPHUQnU6A6av8mqKOlR0n0T3Ta5M2WmV7v04cpiuqHWiPpidubkd2Qs8GS1Ve5VNlUEsJDfCh388G4e6fdKwnHSo8R5RmFt4t3x99cngmHv5V+TrqxXS4BLSUEipNHKQqMwifQr93E0rovQUAgqzoLmdGHmJgRGKaM4T918ygKjER5wv5SqBNlJ3BTuhHjFdOl9XQENv71Z09SofEiakCfdmd6zcHL+J8km7por2gbKdSopaMpjOqH16mLbr4V53xxG5tMn5xPQFcLU17rlM71cIk0Zj3K0zGTY1uDjX99nQwRiAnx6RCxBJDL5PTz7ce+C/sukUKV9R1IUMYJi4sW2EcKtS5nHQC5NbmdXkdnMSEukFtU0nTwrREp7ZZxWiPRP5GT5Scvuf/mRifQrzybI0+PvXIlweys8qo/VOdLvQp5e20yyeZzevj3wwG4N/Fe+/RUtYG2kntvD1kIwKpbnm1bxqmrg/TfpWBC4dxeufbgKhnvAUjsNRVBFDmRv92mDHdPyp+oVbowuSnfrmW45ZnL0Zv0bM7f7HA9b2sSgtqjx9EYdQSMG92pTEYvr164Kd04VnrMpgznrpds+qbs/KV9Zbh2oqyhjHpDPTfE3WA/f14XL5jSbCj0wC6bKL0lsUzbeQiPpjrcR40COl7q99f4E+4ezpGSI0yIC7QKYAYjE03UyVQdutBfCU3GJtLK0yxBkzNgnenN23OIwJpSZIOlUQUdyciavXp7efXCXaW2qSRUfvUV5X0GEJZ9Eo85c+xWSRBFkeOlxzt/vBbPgf5zQOUJjdVw55orugRYE8uqZcsJK8ygITG5QxIC674Eb7U3B4sPEuwaiWvTMIY8+U/qV61F37sfYeczqcnOtWsAc6LsBIl+iU7NXJozvcdqZRgFAcHdvd3+9WBbmXRVuHKu8pxNU/XmiUuRDR5KUE0JhWdzpL/FqTpCo84xVdwJE56DwH6d0rluL5Aajw8VO1fJab7ehJzPolTjTcZd93SYWIIkvSjUFjIqdJSNFMp11Eg8m+pI333YsmxnpVDWMs6zlWdRyVScKDvRLTLOxNVScD0pY3e7ZZzWSPRPpKS+hL+cfNVSSfj89iEkzpqE0mQkbePOK1cSrJ1V/n5BklOGDrLJJJvP6QgPaUbGpKhJDp2G25YT1BzxPLVKDWLK0LZlnGfWgr4eBlzipt0jcJWM9wB4hCQTYzBypNzWkeCzu4ZxIaY/gRkn7VqGq9VJM5HeGPOGw/W8cKmEoHDzDgASm7vEO5rJkMvkDPAfwLHSY5dEyjsTU2mQq5g95y27NfQcKzkGYGnitBtydkoXtkBb66yWEoLcDVsB6D9jYqdL/cmByRwtOYooijYBjEI04aWr4/qnrrNbAJNWnobepGdgoPPIuHWmt/g9ydk06ppxQMcysua+hNFho9Hqq3kn9S0bKZRnbBRqo4Ef5JF2qyQU1RVR3ljeeYmKWdsZNVI6p2SyK2ZPrSUEDQnJKDHhP2ZkhyUEIFUTZIKMs5VnUagr2H1hsyWACTXUojQZyXr1dbtJocobykkrT6OvT99Or6MzMGd6X/lgJSqjAc/qsg5JCKylUKHuoRTWFiIXfWykUJGTJBu79HWbqXjtUbyialHWShITNr/WaZ1rRlUG/hp/p0sI0uL7UT96CJHV5wlsqOowsTQT5G9Pf4sJE7f3v91GCvWRTrIvzWm+RnZFCmUdLClkCvr79XcosYTWM7133LSIBrmK33uP6fT9yyzf2pq/9WIlQaMnaVoqBkFGydaLUqh23X+VGhj5EGRtgX/1tkjhzOe0UqbEXemOl9rLodX2tpygfM8c50JMf56dkXApPzIP+lnxZ1B7Qfgwu+6TvXCVjPcEyOQMkHtyVFdhW4bT6FEMHkqAtoy80xdLzl0tw/Xy7oWfix+pEalO0fO2zPTKjh2i0D8CvzApK9KZTMbAgIGcrTyL5o6FNpFyVVwSGqOOH8Z52q2ScLjkMGq52v5+s7m7IXKURJ6s0FJCIB49zAXvYEJ6RXa61D8ocBDljeUUaAtsbgBFr0va1/dG3WE3RwLzpFJnZsatM72aU8eoU2qIH9XxZjEzUoJS0Jl0BPiV2kih3FdKVpSCHaVQ+87vA6C3d+8rLNkGzNrO2PHSMJiq/CtmT60lBIfqFIhAr6jADksIQKomDGmW2vXyjiIp3NcSwKhPH8OIgHz/XrtJoX5I/wGx+Z+zMSEukDs0ZQBsjxjUKQnBhpwN6E1SYsJFU24jherdN4J6pZrwdR9Qvf0EfilKTIKCArf+HW7atM706ow6rutzXbdICN4ceisAv977jw5fV8wEOSVQ2tfcmlwbKdS/m+ZxwSsI8YiU8e+KFMpMLK+JvIYmYxPDQoZ1i4zz9X5yNEYdcVNSO33/Ms9LCHcPt6kkePh4UhjSC5eTHawklGdKEg9BDj4xNlI4nVFHTnUOCpmC8T+Nd3i1vWVyL/dUBgG15SiGSJVQG35kthA+9RsYdZId6OJZPWbQjzWukvEegiSvXtQJIoP1JjIaV+E6YyYVX35J9GQpu3dm3VbLsl11JDhUfIjBQYMRWpn46AhYZ3prsnMJK8ygrn8y0PlMxsCAgZhEE4+feMWmDHf3Q9cBcGFLO8pw7cSRkiMk+ieikttRZ6a9IBGn6NGX/KqlhCAkN42auAGdJpYgZcYBjpQesbkBPHO8iXqFmmubCuwmhTpaepQIjwin+RmDbaa3SaZA7+aBXCHvVKYXsNz8DxUfspVCGSQp1NRtP9qtkrA+RxqLUFBb0KH3WWDWdq7/m/T8/cR2ZU/NEoKA89lUqj3Ie+ChTkkIFqUu4vWxr6OWq4nwjOC7WZ9YApj14YNBEKhWuNhNCrUpbxMAWdV2noTbAm1lehOW/w+ACZl7OyUhUMqVjA0bi4fSA383TxspVPU3X+Md1IAu34jXQF/k+kIe5jnckuZ0uGnTTGT7ePcBIDUitVskBPOEC9Qr1Kji+3X4umImyNf3vR4XuQv7zu+7RApVF9OXkNx0GgoK7SKF+i3jNwB+TP+xW2ScDQf2YUJg1PzJHb5/mQOwYUuGISDgr/G3qSRM/GQQuqQUQkvyqCwpb//9d/EciJsG456Ggv0w7W2LFO5k2UlMmBgYMNB+PVWXQcvk3tlmbhRzjdSLYcOPzBbCSTdJg/Vu/qFHDfqxxlUy3s0wf3le1UruANeGT+SCSxl3B/9C3k+Lefjo3VSr3WnYJ2XPuupIUFRbxPm68wwOGmzXz3E5WGd6s199A5XJgP+4i/rnzmQyzA4hBy4csKkk+IUFUugfgez4xci/K5WEBkMDaeVp9peo5O6SHqNGXfIra2KpGzQMV6MOz5FteKe2E729e+Oh9GD/+f0tpFAjOB8Vj3/GCbtIoWqaathRsMOprg1wMdP77MfrcdU34l5X3WEXAmv4uPgQ6xXL4eLDl2T8dvcbS53ChVl2kkKdKDuBp8qTjXkbO/PRL2o7X6oCtwAYcEO7s6e+MiMxZblUDR1D8PDBPPr5K7wws3+HM9cquYqkgCQOXjgISH+PF2b25+HPXqHRxx/PxlqeGBPe6Yy4dZY3qzoLfxd/DhUfcqiet7VM7+03v0e9Qs362JGd/rsvSl3Es8OeZUToCPRiI+9PWMR9iw/yY8xYKn/5CVf3RhR6I56eabwp3MMNN92OT3B0h5s2zUTWQ+WBQlDQz7dft0gIvNOPcz6qH8/OTOz0dWVDzgbUcjVb8regcqmykUIF04SroYnM1960ixSqpqkGuSDnP5P/0y0yTvmxwxT5h1sqxx25f1lLbTxUHpwuP41g9LZUEr6pmEvI+NHIETm1tgMD8sxWvCMekKQe296ySOEOXDiAgMA/x/zTfj1Vl0FLGWfDvn1Uq93pOyLpUn4UlCjt56FvpO9PyMAeNejHGlfJeDdj243beL1WZKQqAEEUydRXYjAG0Mc3FEO8wNcV8yjplYDfuROYTKYuOxKYG3icScatM73y/bsxIpA4dXyXMr1eai9cFa74qH1synAAdf0HElZwjvpayZu7K5WE/ef3YxAN9p8qlrsbVO4QfKmUw1pCsLtBGqDQKza008QSQCbISApMYs/5PZdIoWQpQwmqLqHoXJ5l+c4GML9l/IbOpHPq4AczJsQF8mffGgD2hCV2SkJgjUGBgzhachTvu++yyfhVxCXhZmjkl4l+na4kWJNLrU7LlOgpXZcQCALEjIesrZf4jbeV5S0YORyFaCJ251rqdu7k3NhxnW50HhI0hDOVZ9DqtJbtZYwbj1tFCUpM5I8Y3uo+tGd7ZpIxMmQkiDA6bLTD9bytZXrfHKDC1dBEzLXju1xBGhY8jAt1F+gTqmPVwmDmFTyHIdxEVYYGgJK6AG6/9U7pvO3kcBJRFDlZfhIXhQsTf5nodAlB4dkcgmpKkA2WZEydva6YLVpFRPr79bWRQrmekzT14q7tdpFCuShcGBI8hAH+A5wu46zX1hFWmEF9c+UYOnb/su5LiPaMRmfS4evibVNJiBvUF51MQdXmze2//5qlcBofGPlnSF8tEdz+czlQfIC+Pn3xUjvHItA6uVf+xRf4nztBSe9Em2ZqCz9KmAeHvobiEzDkHouFcE8Z9GONq2S8m+Gh8mCWTyKzgkfiZxLZWZlOsGskMfo+DJnYn/pVa9EkJuBbX0Xm5q5Nl9TqtHxy9BPcle708enjoE90KWz8ZlWu1Ll64uXv06lMrzWJaTQ2YhSNl5Th/MaMQmUycHLDzi5XEpZnLAekIRB2Rc4uiBgOckWrvzZLCHwLsqhRunLhyb90iVgCJAckU1JfwvDg4TYBTFSzFCpt7WbLsp0NYH7P+h2AwtrCDu9fR9AWuYz/WmreHJtzqFMSAmsMDhqMVq/l0eMv2Uihbn9gPgCFWzsvhTKTS3MfwrjwcfYhl7GpUFcCJWk2L7el5/25zwT0gpyfX/22y43Og4MGYxJNHCk5YrM91mzBIMhYGj+p030JZpIxMHAgJkyMCRvjcD1vqxKC/VKFcuT8a7ssgRsWLDWS7dv1Jvo75lL3RRnys3owSPLB+t1QM+MG6dz+xzHSbny5w1Ko7JpsdEYdCf4J3SIhSFu7BYDoya1ICDqARamLeG3MawD09ultK4WKGIIRgXKlW5elUOUN5ZytPMuIkBGden9nYJ3pPfXr7zaV487evzbkbKDeICWjDPJSm0pCww/fUxjWm6Bje9t//zVL4V72gq2vS68VHkTXeyLHSo4xNHhopz9/R2EzTGrpb/g0VKMeOrz15F7cVChqrpKvfrzHDfqxxlUy3hOQMI8N+VuQy9UUiU3IVCWk1e6loPd0vOfOIVJbAkDFJx93qQy3NX8rBbUFhLuHO9USzJzpffiLHbjV1+Cqq++0hMC6DOfr4kuNrgbB5GFThhswPRWjIKN42y67VBJcFa7sKNzRmY9+KUxG2PY2lKaBTH7Z4Swhbgp6lWRSmjSsSxICcwDz8VGpWXNWr1k2AcyjJ+9Dq3Kldm/npFAtLcE0Co3DLcHaIpfFGh92hyXZxUUnJUja791Fu20qCUHRoZz3CUU4ctCybEczfmZy6a32RkBgWLCdmsViU6XHrK02L7el5x1Rk0NBUDQaD/cuNzonBSShkCnYXbibjxOKqFy2nG170rhlyQmy/aMZXJnV5b6EtdlrAXh93+sOz/ICLO+bypSc3SR9Owp2f0TAwTXIvUwEFiyF3f8m6dtRTMnZTa5vNSzqD7s/gt3/btfPMZ9Pxd8E+y/sRxOswLdvLf1uKSPg8yc5HJWM1tWVggUhXZJC7SnaA8DLI1/uFglB3d59aNVuxI0c1OXEiK+LL/G+8ZaGZxsplJcvnk21PHtNry41Bx8oPgBcDJScAetMr/7H7zAKMhKnXgxeOnP/Mlu0JvonIgjYVBIqfluOPCoat8ZalgQMat/919rm8OVqmPg8GHWc/Hw0jcZGhgTa/xrfFqyTezWRUlKxz9TU1pN7RoNUJRx638V970GDfqzRelruKpyLuKko977CGF0DSz3dCS47h7dMwR07fZkfF8+U356g2sUdt/QT/HDToyzuZBluddZqAEsnvzMxIS6QFyJ1yBHZG9yfhptvY2evEdS5erHsoaR2fxYziQFYk7WG3Y27cVW5NJfh5pI1azbBf3qQwsAoXI7sp7qpktjVq3i3I04a36bYHKOZMTP5I+8PBnwj3QCVMiWHbzvc1tvbRnkmLH8IGiqk5zWF8PUMcta50XD8dKtv0QC9Dm2lDjg3Vspga1JSiP5+Sbs3u+3GbWzN38qKjBXsu7CPs5Vnmx0JYjFMEfi6IpyjMZn4nTnWKSmUef2rMlex/8J+xoSN4VzlOULdQ5kZO5PUiNR272t74XvPPWTNmk166lye2FjATUMj+HhCMJ7fVVI+cgHlzWTvvWvCCVm+gtjVqzq8jVC3UFRyFZ5KT7ZV7ueR5oxf0HPPoe0/kKi9G2lqaEStcbHJ+D3TgW0cKTmCRqFh2m/T8NP4sSF3g+X87hS8I8C3l0TGRz5kedkmy/vB6wyO8qGmopqwklyyJl/HM1PjmdQviG2P/Y1ZnWx01ig0DPAfwLaCbRTUFpA6ZihHm7dXWDKIiI3LqK/WEuXn1entVTVW4a/x5z/X/IcVmSu4UHehw/t5RZiMsO8/sPMDFtaJ0M+LivJk/De9gdd5D+oTQmHLPwGoyEvBLyaNqMrvYNKzsO1NaR1jnrzizwIwtBH2qYx8PEzPwiXu1M1bgGbTG5T2uouU3KNEDLmdpWNG8dOB/E6dz3uL9hLhEUG4R7g9j1CbaCkh8Dt7nOKY/sgVcsrsMPRpePBwvk//ngZDA8W330vDYek6bL57ZCYnt/ne9lw3953fh7vS3f7OWZeBOdP7xD33ULr4O877hZPo72MJXjp6/wIsAdf/Tv6PRYcW8e6sl2gc5c7iPbmsC0th3N4tCEBTZhbLnrq9Y1yiPBPOrkcrV/KalyuIRoZs/hfMiQW/Xh389B2HtYzz2VojiQj4y/QULlvB+qfek/jR9YlEnf0atr4puagMvtPh+9VVXM2M9wS4eLHo/tO8fMPv9NbpUATE8f4DaXz758kXp0vqGjAgUKN271AZzjpruf/CfgDytHndMsgg5t0XABhRcKzLEoINORsoaShBhgwd5TZluIovv6QpcRChJTlopk3vcCXBnH03NyGmRtrJhcDc2R07ERQucO8m6DMZjZjWapb3637TAPj5+S+6lOU1BzBzes/B18WXLflbLnEkcEnoj19dJbk79ndYCmVe/6DAQRhFI6kRqd0iIajZsxeAxJkTuiQhMH9nkhYnYTAZWpVC+Ywehdqo5+TG3Z3O+OXW5NJgaCDBz84SgthUqUHYaBt0t9TznlizDbloIqi5JG6PyYVDgoZQUFvAiJARNqPeg8aNQS6aOLHu4neno9uraqyiRlfDgr4LHJflNVuhpa0C0YDGVE9gn1KqNu2lLkePaBTo5Xka9PXoaxqp3puBf99KXMUG2PQyKDSg8YNNr0BAfwgbIv0cPuzizxpfMOihScuwhkYqFHKWBblREWfCbdkvhFDGAypJbpV2Rt5pKZTepOdA8QFJZ+8k2EoIluFXV4ly6LAu9QdZY0ToCPQmPUeKbaVQTT9L8rjvBszotBRKq9OyJmsNyQHJKGTOy1OaM737LjQiiCbcNFKg0pWGfTNGhUrf7d1Fu21coVwNTQDMXfZhx12hmp1Vtg65kXMyI8EuPnj1meJUh5IJcYH8+qfhRBVnUeARQPotd1hknKsWBjNh951weqXkj672hDVP9Ug7Q2tcJeM9CQHxjNXDodo86vR1Nl8epcmIi8nAgmdv6NCXx1rW4SJ3wVXhSqh7qNMHGdx264dkeIVxPKC3XSQESrmS4SHDuTHuRnQmHf1C3WzKcIF9opABSxu9O9zQYyaXXmovBATGho21D7k0d6RnbpRcVJQa8AzDd3L/ViUE4+pyKfQJQ+Pv12UJAUgBjEKmIF+bj6AqsQlgImolKVTphx92+gZg1ou/c+Adp0gIWpLLhgMHqFa702eY5LTTWXLZUgpV2VSJYHJvIYWagAmBoi07O11K3lEgSZ9eGf2Kfcll9FhpdPqieMtwDrhUz1u+czd6mZzEyWOArjU6mwOYz098DsDsXrNtRr0/pn0OvSCnfPtuy3s6ur095/cgIjI67FI70C7DPBjko6FSytrFB+or8JXVItOIeMc0UHguDBFwiVDDqEepqB6DV28DDYOuY5swVAqwPUNBkEn/zx+VhqQgQuam5p+RvJrDB4NXOMObXZpiUfPepCFU5HqiT30X5Tsl1Kjd0B4+btnFjp7P+4r2Uaevs9iaOgPWEgJttCQh6DV5nF2IJUiWowqZgu2F222kUHevyCTfK4QR1dmdlkItP7ecekM93mrvTu1bZ2HO9P7no6XIAM/Swi45QVmjr09f/Fz82FO055L78qnQeLI9QzoevDTfx9YpjMhEEUVDNXiEOMyhpK3kXtP44Xjp6ojUltgk9/T33CAlvcY+CbXFMOPdHmtnaI2rZLwnQSZjjE9/DIjsK9pn8+XR/u9XAL5KntuhL4+ZWE6LmUaTsYnxEeOJ8Yxx+iCDr+b1Jba6CFnKELsM4jFPSlwQJ422vS5+is1wFtmX/8GIgCo3q1MNPaIoSnpxpSvTfptmH3KZMA+OfgflGRA3XXrt1HKUwxdckuUNdpUTVniOuv5JdvFKBymAGRcmSV0CXH1tdITinl1oVa5o0k90+gZQ3lhOoCaQz6/93CmWYNbk0mQy4XfuBCWxCciahyh1llxaOxLE+8ajkClwU6ltKgnuMiNFAZGoD+/rdMZve8F2YrxiLKOk7YLyTNjzkfRzr2tshnO01PO6njxMQWgf3Lzcu6znNQcww4OHIyBwrPSYzaj3dVN+ozCsN5rmYSMd3Z5Wp+WDwx/gofQg0S+xw/t3WZiz4Sd+BY035O2FjA0QOZJc92TWhj2O77gIxNJGTD4KlCnXoc9Jo3pfNn7XTeFC8QXCvNQwcKFExgPiIOUO6D0J+lwLybdIj32mSOXywHhSZAUM8JUx3ZgFokhYfRXZqqP8niTywZeLGPrDUIpjE/A7dxKTyQR0/Hz+5aw0oKqx2RvfGbCWEGTVmjABQS6CXYglgKvSlYEBA9mSt4VllVspGpNguW42JAwkvDADo07XqWrCiswVABQ3FHdq37qCCXGBzBHPoxfkbIoc0mUnKDMEQWBU6Ch2F+3mo4RCS/Ay75PdXIjpT0zNeXY9MKjdwUvK2Lu/YAAAc8NJREFUtykM0J9iwNHX2HNhPyZBoFgwMuDYGwzQnXRqf9B/E2cD8PNTH9vyoCh/Kem1+0NwD5KcU3qonaE1rmrGexgGxU7B7fRZtmSuZGuCkYWv7W/WxRbxrpsfo2tzeeO1f1JY1dAhHeEvZ35Bb9Kzo2AHIe4hXdemXgat6VO3ffETgYj0npLKAjvoU82I9YolzD2MbQXbGPbKCq4/bKvlnnBkPfWj15PWynsvpyE8XXGaJmMTg4MG85fBf7GPPjVuKvz+hPTzmqek/24BMP+/LIsLZ8rqx+nfnOU9uWkPrkY93qOkEnOSRo8i7yDLbni/Q5pka5izrmerzmIwGfhx1ifkjqqz6AgnndmBQSZD6+LRIR0/SP71tfpa7k+6X8ry+nZ2L9uPijodEY/dT+6cOdQMHYtvfRXaoVJXv5nsRaxYQeWHhzq1/g05GyipL0FAoEk0S6EWEN4shWpIHETslhW43nyzJeO37KFLfeNbQ72+noPFB1kYv7BT+9YmFs+BIXeByQCV2XDXOtj1Hiyeg6/bexY9b+H7/yasLJ/MmVI1rauNzta9HFnVWfyR+wdyU3DzqPc4mhb/iCF5MJGrf6CsoBjjt191aHtb8rZQWFtIkn8Scpm8w/t3Ccy68D0fg64OosfAuY3ScfOJhaTr4cgSwo1NRGW9gskgIIjBuFEPh76i4rAnXpGgOLcEiy/VoZ2X26INtgkCW101rHZ347iLC0e9Amioc6FwdhT3vHWce99cyt78Nfil7Sf72Bkiw/w6fD4fKD6Au9Kd7YXbLUkLZ2BCXCBLHxjB+V//TpF7IHW33NGp/qC2MCJkBB8f/ZhhwcP4tLGR57eeoL9GT+2oEbjsXsepzXtJmZEKXPm6ad0fJBNkeKm9OF56vOv9QZdBzsJbLFp3a5hDzGvPShWzaelb4KktiCkp0IEeoZYYFTaKVVmrWK7bxgSrPg7ZaTXs+o0z67eT+qeb2tXHse3GbWzNWsvq7S9zQmFELggEGo2E6w3MjJhA6rldUjVu+P2SQYEd0Fp/0NIHR3Hsjv9R7OGPJjzUlge9fS8c/BLy98HUN0GhkuwME+bZZX8chatkvIdBGTOeEYf+xZaiXVQbG22aoArODCT82G4wmSyRf3tJbXljOQpBwX8n/5d1Oesc0/hkhWVxk2zIZdWuPXgoVCROlCyj7EEuQYr8UyNS+eXML+z3DmTkrTcR8fxL5JbXsfKJV5iwfzU3z/gHah8vZg8M445RUUT5uVH8xhtI9ejWsSl3E3JBzltj38Lbxds+5NLFC4KTJAnBA7Y37p+z65ln1SBYtGUnsc1+7ECnGwRbw4SICXxw+AMu1F1AfORJmwBGaTRy/TMLqIcOBTBb87cCOKRZsy1YN4vlfPQRnkDf6ZOArpNLuCiFuibyGj459gl9g1Xct/ggt/cdz5R3nsD/xjuRbxH5VefX4abqzfmb0Zv0ljHydoNZCtV3Cmz/F9SXW7JCs90vNoqdnTwFGRA2eXyXGsVawiyFKq0rxc1NwU9pv3PLPW+RNWs24U/8Hdnq7zn90wqCO7i9ZRnLANCZOp61vwTmRmpBgBmL4OfbJN/kiGEw830poNn2NgByQKf248ELD/AU/6OuwYva61dSseYeqVnsTC3v3jCww5lLD2AWQOYqatN/5HjZceSij03w0mfaXHSLP+Lc2s24CzXtOp9bNp8vjF/I0nNLHUYu2yKWAD6AT5MWsA+xbPnZJkZO5M2id/gjoYk/nkxl5Rg1nyJQuGWHhYxf6bppbj5fmbmSfef3MT58PMdLjzu0+VwzIBHNgESCnnuO3PI6vtmdy4Z95/jvr8/xc8K1yO/8U7vvU+2BuWcg0iOST+OaLMGLOGE4JxUqqnfvhT/dBFz5vuyh8mBW/A0YFEoO7HmVSZGTaKzM5tpzu5h1djfM+Uj67qSthDkf26Whs7Xknr5JR1luGgXJoy/lQcMXwLa/Sm9e91fpf3PSqyfjqkylpyEgnjFGOdXGRgYFDLJpgvIYOQI3fSNp2w9YFm+PjtBgMlCnr2Ny9GSSApKcPsgAwCPtGEWR8ahcpGEwXdGntsS48HHoTDr+nZBPtZU8pq5/MnJEPkoUOqwh3JS3iSFBQ/B28e7y/llQVyZF62aJihVaSgiURw5QFBCJX1hglyUELTExUjpX1mav5YBPJe633kS/9DSqP/8RgM9TruuQFEqr0/LZ8c+I9Igk2iu6y/vXXlg3i7mdPUm5qw/RSX3t1ixmlkLdHH8zckHOuKjBNlIoxTefYwJUORkdLiUvPbsUgCpdVaf2rU2Yh3PEz5TGP59daxlyYa3nrfYOkPTiqcPtpucFKYCZEDEBF7kL/q7uNqPegzKOU69Qo1j5a7u2Z918fqTkCABZVVldbz43N1LP/xy2vCa5LWj8oKYIghIk67O+02DeZ/ByNarnspgqVmIQZHaVEIAUvDQYGxAQkKvL+Cntd4vMLyLUlzI3X0y7trf7fDbLhXp79wZgWsw0hw5HaktC8EmSlIX85YkPutwfZIb14Ce5IGdHwQ4bKdTKmb9RFBCBotlytD3XTXNFJ9ozGhHR8rOzZZzPhjYgQ2T09VPsIuOEi9+f1J9TERDwUHnY9HGM+GUkRRFxeKQfs7ynvfdlc6V9Z+FOCsvT2eAbLN3f/PrAnWvsrtFu2R+UtuMgrvpGPEZeTO5NyjtIrm8NfJgCJj1Meb3H2xla4yoZ70FI+TaFAYuTeMVTIqyDcw9xTnXS8uV5VSYR6LxN2y3vac+XZ/+F/VQ1VTElaopjP4AVrMll3p5DhFRdQJZiKyGwF7kcGjQUuSBHHRjM0cF+Fg3h44/Oo0mmoGrXng5pCE+UniCrOsv+jWLnNkgEKW7aJb+yzvKe/+gTws9n0jBQypraI8trjVivWKI9o1mRsYIP++dZApiHthRT6urD2NrcDjVBrc1eS3ljOdGe0V3et47ATC6P1IiYAJm7u80UNnuQSwBvF2+GBg9lfc56sm+fbGmq9tA3IAMmHFrboaZqURQ5XnocPxc/NuVt6tK+XQLzcI7/jpWer3zEMuTCWs+rr6lFBjSdO2c3PS9IAcxzw59jUtQkKnVlvJv6tqUvoXrFSspCovAqLmjX9qwbaeWCnHjf+K41n5ubNOtKoeCgpBOvzIXrvwaTDqoLyBkT2+qQncRty1GIJq49u6PLTlDWUMqVjAgZwfSY6RhporCywRK8VH71FRXxAwnPPoXH7NntOp/N5FJv1KNRaBgYMNCh5LIt//rJTfmUufniEhlhF2IJFz/brF6zCPcIZ8/5PchF3+ZqwgKaFv9IQ9IQwosyqKmo7tB1c0PuBhSCgme3P+vw5vPWnKBMhw7QJFcybk6q3XqErL8/XmovTpWfwmTwsAQvmycuRRg8lJCqCxSezenQfbmsoQylTCn1B6n8UXpHgkwGv/9FqjjZWaPdMrmXt0mS8iRMlxJLFR8twj9exK9yB3gEg0wJp1f0eAcVa1wl4z0I227cxuvJjzNKD2qTiU0+AfgbRAqHuTD1tJpls3/jvE8IHJIy4+358mh1Wl7d8yoaucYxLgRtwJpcXnjnXQBip18D2I9cmiP/lO9SEBExGA18nlTG2JytPL56LKOWjqYwIg7300ct72lPJeF/p/4HgErWdeJrgzNrpK7zkORLfmWd5dWuXIlcNBE8cZzdsrwtMTFyIlnVWcT1HnExgLljKJVxSYTlpiGIYrsDGHOWV6vX2mXf2gszuXzr/eUoTUY8q0vt5kLQEpOjJpOvzeegbxVVc8ZYMoGbh87AiMCCma9esZJgbZmoM+m4K/Eu9hTtsa/NqNVwjpx9iaT9GEral0rSkkeQFt+P4DnjWbLkUQIbKpGbjORffz3UVDPlxbv54cSXXcryWmNa9DRqdDWYNCf5154XmfLSPaCtITL/LDJEprx4N0uWPErwnPFtBjBm8pUcmIzOpGNu77mdJ5bWloUDb4IzayWf/zkfQeI8iBoD8z5DM+O+SzK99y54CyMCP/e71i5OUNYwV19u7X8rIiZuTJxi4wrl3ScWpcnID6aQdp/POdU55GpzcVO6kfpzqkPJZWvEMtzLheDs01TEJfHMtH52IZbW2JCzARkyTKIJtabYppoQMmQgCtHEiR+Wt/u6WdZQRkVjBXG+cU6ZUgqXZnrd045SGN4XF1cNYB+bUetG9P5+/ZELcmSCzCZ4iW2W9Z1etbFd92WtTstftv6FqsYqZvWaRaJ/Is8kPcginStMeklKOB3/ye4j51tWjoXDBzjvE0JQdKh0j1yxAv+bZvMv/XVQfBImvyJJ9Xq4g4o1rpLxHgQPlQezNr/HTL9kYvQGspvKKREjGRExlIDYJpoW/4h2wGDC889QV13bri/PprxNFNQW0Me3Dy4KF6d9Fmty6Zp2nCoXD/qOSLIrubSO/P1c/ChvKqfCxY3Tw0J4O28k227chjgwhdCKQkryzgPtqyTsLdqLu9KdvRf2dnrfbGAyws73IW01eEdK2fEWsJEQ+ARiEGQkTR1r9yyvmRB+dfIrRERSI1NtApiN4bvxaKrjzJ4jlve0dmOwlhCkV6bjpfLidPlpp/vXB88Zz2sb3wdA3tToMHJplvYcmBSOyx97LZlAbbMU6pMB8itWEsznq7/GHwGB6/te71gJQXKKNNXxtzdtJAQfJEvNfKvufAHZ8JH02bEd3ztux3tQst22PSp0FB4qD747/R1H/KqpmjOG3tu3oesntal9OvSmdkuhlp1bhoDAf4/9t/PE0ixNmfORRMQBRCP8fLvNiOzWMr3PhTUgR2TE9dfaTULQEgl+CUR7RpOu3WwTvAT+KGUCpy15+4rBixlmfX1qeKpTyGVLYpm++zAeunrchktTLO1BLK2hlCsZEz6GeJ945HKTjRQqNP8MTXIlwq8/tOu6qdVpefCPBwH455h/OmVKKdhmekvyzhNaUYSYPNjye3vKODfkbKCsoQyZIENQVvLj6dWW87xXrzAqNZ7otm1p1315a/5W/sj9gwZjA9NjmuWW5mrcumel58vuh+xtsPElG2vVrsAmuffJp0Tkp6MdYFU5TvZH6xvBi8olUsJryN3/LxxUrHGVjPc0BCWygTqMcgUCIFeXsLQ63+JFHTQsBZXJwLHv2xf5/3JGsrcy22M5C2ZyeVQrYERA9PC0u4SgZeQf5BqEiB6/e+7Gd+sJXKoaiLw2FYATK/64bCXBmlxq9VpujLvRPllLc0bu2A+ACI3VFqs5a1hLCJpqahEEAUNWlt2zvNa6S4WgYF32OirUPpYA5pE7vgcg54+LxLC1G4N5PSmBKZhEk8OJJbStTz3hF0uGdzirXvjC7uTSfF5M+HkCAgJ1Xiq2JMKBT65DH/kXlgW/i06moLIdUigPlQfDQ4ZT0VBBmHsYbko3x0oIHvsbVTluFG363kZCME2XT6XGEwYO4ubeN7Mro8yuxBIkwjQpchInyk5QOHsYLn/sZXdmOXcNuo9KFw9Sa3PaJYXS6rQU1xcT6xXbNcvMoERQe8GSBdIwpAd3wbz/Sv0bVprS1jK9xsMHaZIpGDuna8OkLgdBEJgRO4OjpUdtghfZ8JHkeYVwwr/XFYMXrU7Lk1ufZHnGclIjUnlp1EtOIZctJQS5f0gyyn7TJgD2JZZwsZqwsN9C6gxaHky5hbt+f5TFMUOpWbWakqAovC7kteu6uTV/K+mV6YS5h9HL2/HTI82wzvSeWiJVFqOa71X2lnGaG9GfGvIUIiYKtWU2UqjSuGTCM463Swq1IWcDvi6+qGSqi83nVtU4blkKCJLn/pxPbKxVuwLr5F7N8hUoTUaCrkm9mNy7+w7EXR8QTzZMe0ua4WHn7LyjcdVNpachYR7KYx8ywj2a/mVnWOEOpvoLPOYXw3OzpuFWmEGZXAk/L7EhtdaWai3tmlzkLpyrOudQu6aWMJPLN97/jX+aDMhryi0SAsvIWjtJCDbkbOB83Xm0Oi2Cop4lpX/wfrP9XMLTz3BA7U7d9m1U1Ba2WUkwd9W/d+g9yhrKuK3/bWzK29T1rnqz1VxlHlTlw31bYN+n5Fw3k4YWhjbBgLXPQP711wMw5cW7mZY0kLgXfuzcPljB2oKurKGMY6XHMOqj8LvnJnwf/YiYJwPZ5RWI6cA+oG2LQPN6VmSsQEDgln63kFmVybXR1zrMMrM1i6tvFw5AvySX9LEzwM+Pm3vfzHsZZR0aGX45mM+L1VmrOVNxhtyaXNaO8OKNz6ro/+hfGTtwNjt+uAO3FlKothwJfj7zMyZMKGVKxv80Hj+Nn8NsRpXBIbimhGH8Yz+ff/BvBscEYjQYOZ95kpK4ZJ6Z1o9J/YPtYjFqjZauFyOTprMl8RCmT65Df42ck71MJGWctJFCteYKpdVpuXf9vZhE08WsZUddjcwWhnl7pKE7ogh3rpYaNTe92qrdWUsnKLdTRykK70uyuytgPyeolpgRO4OPj37MoWsimfTBXnbPLeeJ3jfzJ/3vjDqykcNPj6ZaVLZpabs1f6ulajC/93w77tnlYW0x6nvPPZgO7qPYK5B+faPtYjHaFq6NvpY39r/BgapfeeW3g8QXSI2bEdoaQLpuTgFYcqkzlNkV6rdzv0nPFRq77tuVYJ3pLV/9G9UuHgwdL1US7N0jZA7EjCYj/zv1Pzw8fbjr90e5LeYOZr77d7ynX4fq6HZ+FEP4tpX7svX3WSVXYTKZEBFJ/jYZaMEnVj8OvSZKQ65qi6VmzmZrVZ442enPcMeoKOZ9sptJ/YJo8gnE40I+SdNTqfjwfbyGR2Pa8zr+jeXSwj/fLj3+P3BQscZVMt7TEDeVRRv+DnUnKVTIWekWSpDQwPaGs6gjRvOnj36iJDiasKIMfug1vlVSayYQP5/5maOlR1nYbyGb8zY71K6pNYurYOCfzT9bJATYl1zCxcj/uWHPcff6e8mqyOHjBE8WvrYf33vuobjfIEJPHaQq7xS92rBT81B5kBKUQllDGWHuYfhp/Ij2jO46uQxKBLdA2PWBVM5TuYJnGJqoADRTptnYW608VsiQkzt47OgvrLrzBeakbaTXO29R/sUXdNXeqiU25GxARJRcHFwusLxyN/9sDmCqk4YRvWsdtVU11LVxY9DqtDy/83kOXDiAh8qD61dd71BiCa1bXO36biW+opGoyRO4wY7+9WZYBy9KmZL0inQuGLXUTBjG4I15eAz1wJSUQtjqJZTmnycgIqRNO7XyhnL+d/J/+Ln4MSZ8DHN6zbGPf/1lsH/YNBL/8zlJ34yAKU9xRjcEr6ZatCPsazFqDfP1Z1XmKg5cOMDSc0upHhHIa58V0//Rv0JJFV6nPuLs3qP0GzO4zf3YkreF0xWnCXUPJcE/oeM7YrYwBMlirbCZDH45WXps42ZtbTMqu/VOwsoLyBx1q+X39rQZBVuyIyBQ4yFnSyKW4GWXScb4w0ZOrdvO6IWz2wxeNuRswMfFhzpdHWPDx9phz9qHSyQEuWnkjJkK2J9YWsNN6cbkqMn8nvU7E3uHcqyvnOte/o7T9/8ZVdpJPh16E6vDh+DrprKxtV10eyJG8QiLvxmAXJAjR06eNs+pySpzpvfRO+7E+5vFZCUMR66Q29VmtCXkMjnze8/nk2Of8I/fDJbgJfAnqUdq6ndvMxUuCV6WAA39o/nvg5GkV6RT0VhBiFsIMV4xl/KJoEToN1tyKFr9OAT2s4tcxLpyvKhaiyAImI5up+rn73C5zpeMRk/6UQmhyXDdF3axVHQ2rpLxngZzyceoJ+xfvRmv9GWXvJZ3lyiIyJFGTbcn8h+QksKShUbkgpy7Eu4iqyrLoVnL1rxTVx4r5K9rFqEyGUl/5CXmbPjSIeTSugQ7PWoev+csZVnlVqZNGEHFl1/iOX487kd3oEse1eZwFq1Oy30b7gOk6N9uWcuEebD3Y0meknKH9Nqp5fjedTtZz35x6SCDe7+jQuMlSQj0AXbN8lpDKVcyMnQkQ4KG8OOZH/+vvbOOjuJq4/Bzd7O7cScJ8QSHBEgIbsGhuFPaQo0KXwstpV6oUC9SoUoVKrgWt0Bxdw/xQNw9u/P9Mdl0CYEGiAHznJMzm93Zyc27OzO/+9olIiWFr5upGfv+Aeo+MwXtP39z/I8V1LnBjSEsJoxtMdsA6OrZlfHNxle5sITrvZbJO//BSmVGYD95ZdGq8loaoy/ZhdmgzuXPkEyem/UXunFj8HmgF/z9B8eXbaDr2P439ATOPTaXQkMhg+sP5sVW8uJPVbo4Uko49RMXYeebR2qED65nV2P5zy/kAU36l3QhqGRhCddOYNIK0jiTcgZh5klmd3kCUzh0NNk/zSViY1ipGC9vHEsvyqsO22huM33HGJXKS5dX4+v7MRTlwqFfbuqlM/X0xuqtcAd8S4rPq8LTaxp9uZh2keisaNa1s+XjHzJoOuk1Wg/oQfyiXiSH7YKx8qqDxu/5E72KSPttMSAXnBcbihFCELQgCKheYfniE09woXdftIZi3Hr3qFJhWTb6Io0dTL1J39J9SXfSB8N3MRCadZnZ70+7boG8/uetCJ87mdapWzh89TDdvLsRnh5epc6qshg9vY2SI2gIuJXMU8qmcVZ0EbGKMrTBUL45/g0J3rYUNLRj+Du/c/nl14g4H0W2WscrXf533eTF2Ou8u5cfB64coKN7RzQqTfl6wthadcQv8EMoLHxIThnJTb6lxYBu5Ny7JnL8pHwNzf0jBUvnAsSsj+U1PO7QC19TKDnjtZTgP9sSWNeWsOI0igxFaAObsKGNGU89r+asp7zPjfpBWz88ht12CZxOOY29zp7BqwZXebum8gqffh3ZhMZp0RQEtS5NIaiK/FRTng1+FIQERU7MqZ9L6vKVNGzsgwTszxA3zCFcdWkVMVkx2Ovs6ejRsfIKnxr1hYQz8uP5g0qLxTTtRl6Xm+phq8Mt/BTJjVtWSRcCU4x5l88FPYeF2pLEnBxWpIWR1q05HnEXyTPTIcqkQpnmEa6PWI9GpcHR3JEPO39YI4VPANanjhLn1QjLkhSCys5PNWKMvvzY50cw6DguRbOlWTFnv/yQZqGtSbOwIy9s+w09gZIksSFiAxZmFlxOv1ypY7sh8wezqTgIxwHtSD+WRFG/n0iM0qKylfBs5Ffpuall2RS5CYNkQC3UGDRXWNNe4sqSv7CxEVy1d4P9e4Brc2TzPaaW1mkcTzqOpZklkZmRt1a7YdrC8OImWYiHPA7tnq2Ql87U02u5djmplvY07Sq3Za0KT69p7Uszp2YEOAWQYJFLSmhLcn79A3MbK+I8G2J1+t+iauP3PCd9RmkRu1atRSVUuFm5VWntRlmuKT63c6ZIqGnZP7TSi89NMa190al1/HhlGYeCbBm8y46nmkwjsX5HPC+fumaBPOP1VNV3AA+0HoskSUhITAqaVOW9xcti9PQeW7YePWB58UyVdYKCf2tfei3thQoVq9upqLcnhu5LujOi+0EON0mgcWoUBya3va6OI33lSr5uFscvp3+hWCrmVPKpG+sJYzHnzPqQGSv/pFyCAV/cUv74f/WvXz3hXcz9rGnw8SgcG+dj4VsHWj951xVtmqKI8VrKjtE7+LDeaNrn5qERar5uGkeXkwbq27Tgvb6PcNXaka7pl8ovglq1mm8DrqJCRU+fntVSUV9e4VPKP7tRSwb8H+hRZYVPRowXmwErBqBCxQeLUnh31hHIyiTz2QkIoOOxLTfsSODw4kyAUlFZaeIyJ1legKDH9OsWICjbheDMjgPYFOZi01H2hlR2F4LysNPZMbrxKNBFIfL9mVM/l8zVa0jyqCf3g/brXHpjGLquc6ko2hu/lyJDEVmFWVXaQaUspoVPMfuO4J4aB62qpn+9KcbJS4BzAEHWD5Gvz+NcvyaYb96HPjmZpIDWeFw8TnqZomrTdobZRdlMCJzA3iuV3M7wRrgGkKl1JT1oNPY+OVz58C2srqQh1XMAqjaFAP6dwLwU8hJCpeeEFFs6gckKbo93zDnSrqZcMw7tlTdp7tychg4NMUgGHmn6yK0VBpu2MAwcCdH7QGsNbUr6gVegqMvo6bUa+xB2aQmkNQxEpVJVWZtRI5siNxGfE090VjSoivk6IBrf3RH8c3w1UkgbPFJiib8Yfc33PD2vkJ2xO/G38ye7KJvHAh6jgX2DGhGWE347iJSRjkpAUXh4lQlLuLbneKBzIOkF6axobU73czkkJezCon0bbApzy10gb3HD9jy1+SkOJRzCXmfPYxsfq3Jn1Y06QY06uxk1ILKzqqwTFFzbeczN2o0rFvnsbq5l8C5b/G2a0v6Bt1FLBk6v3X7d5CWuUwAr0sKIy47D386fn/r8dGM9YVrMaeclp6wgwfm1MG51hRcDulH/+t45l0m0caa142mc2sZi2Pc1GRHmOH0wX/a432VFm6YoaSq1FButDQPbvgQHf6TA1objJLO3hQUBq7NRPZ5AekAQvgf/obig4LoiKPuW1mRYF+Jn58Nb7d4CqjgcXkLZFIL0HbuwNtMR2Evub15VKQRwbag3MiOSi25xXHbXcvmB5vT84zzRNiH0OLydh/tNRzg5M6iFByvSHqZYKmL8Fj0ShfTy6cvO2J2Vmzt45DcQamh5/eIvprmprq+/TvSGbdQDAgbJOa1VkUJgStlQ78wVV/CKlHuFe2fJ3vw+7zxZmgp17SLWxcT4WvHl0254WHtUW3jX1GsZ8fEn2AGNhvcHql5cXmMvCRLNVYQFwNaXQjnpI3jtoIHcpu1KPYG/T2hOytkuBDoHMvfoXFRCxfhm41kdvrp6QuLNhvJwwgLmJ41mcitzLi3Zj0qS0PbsX6UpBEaME1lJkvjxyApS8iKJHdQa84/24fXah6i3reDYr4vwMBlHUKMUDiSfQKfWYaWx4qnmT3E+9XzFU+yMqSkhj8MP3QAhh66/kXPkK1LUZUwhqBeZTlPAQyt3oqrqFALj5GVwvcGMWP4sEZokzrV1Q/PLb7R6bDbFy3/lxKJVBKmzS7/nto4X2BC5AY1Kg0alYdnFZVVeu1GhFIIqqg8qy6bITWQWZqJVablimcqBIEtsl2wl8xl5gh61YRuBPeTl4I3X0yUJB9EX70Ut1PT27c3IhiOrPMWuvDTO7XvP8M3yafwe2B+7IUOrLI0Trk0d2xS1iSH1hvBn5tfMmZfJqiunyew+BjszHek7dsITcutT4/16xgMNqGNRh5S8FL7v9T1uVm4V0xOuAfJKwO4tYet7UJQPajM5YvUfKSvl1QflZufiFXkGq4ZqGuh3U2BpT+qRbOx8szH7RS5+vduKNk1RxHhtRmPBJmcPsvOS0ZqpWdS6mNnzLrIyIpz0VsMx31fIR98/ydT/fUfXRV2xyixkVqSeKb3U2Gntic+Or9aiFFNxWefVV3E8c4R4/wBamcsrilaluCx7sXF/ejD1n/uKA6HZvDk8j16pLvQ4DMOtljDkyW/5+1gahuTB2OuW0OWUxNQnNfwR/CIX0y5WjlAyhsr3fAXOjeWLRBnKdiHQ7dtJtJs/TbzrVmkXAiOmE5hzqec4USeJc67mHOrpycAFlwiIhj8De7G0SwqWmaNp2SieAzlfY6u1Zdi6DAbX74OfbWaV1iKUxTQ/NWlBNxLsXAhtFVAt4tLUXieTzvLYN6doHCu/1v+gBID53p3Qp4MsTP6ApwHYSAcgzs8G7SPayikMrgiN+lJ/wxtMPSBPhjXmLhTlqfEZPZHkr76vUmFppOyEr8jWnbCAI+hXv0oHKzCs+gqLQQ/y9MH3OXKkB8Ehx3EudiY5Pxk3Kzd6Le11a+LSNQBs3GHl/yAjBh5bB+nR8mp8D/5V7lvKE5emwtL8wG7ONm5S+nvMun+Y9eMvlerpBXnyErwgmAVnFkCJ0/F034YMf3cnjzcbw3QnyN3+DenZtvzxZhs0+8/h4nYelc6T2OxYevr05Jnmz9SIsFx9PI5eh9cx7uwGVj//KUMOrKgyYWmKcQLzZts3GbfuSRaGFDDnRzULE3dh6+qL+sBysgonoU9KJn7pX3iuXEnhumdRAw3sG1Sbs6q8TlCTrJMB6P3oUParK78TVHkYoy8nkk6QbqkhLLCQp0+4srXJNnr5Ncb+3E4y8jPotqQbYzflIzWD89ozkCfXn/VaKjuKKqQnjPnjD/4F+VlyVxWVRhbhZ1fLP4O/vmGx5TXOPYOe+O/fQKcvwqq+A0gCVVoySTGepIzvgqu09a7MEzdFEeO1mZRwNAVZtM3N5b2Ax3gmYhk7AmDCMQcOD0mglUqF5bGjhMWE8Xqb14l6/23+aW5GhhX83G0O7+19r1qLUkzFZVLTVjjnpJLb8RGgagqfysN4sfku7wRDW2gJ3nqe7GEBFHkkk2Zpgevpc4TnHOCVvgM5XhRL0EIVOwIM+Pi1wMvWq3KEkrGLQ15qyQI/BjlXrsyF51ov70w8k2OIGPkkUPVeXrh2AqNVaSl+0JKub6xmU8dsZgxrxgd/RdA26TgrbVN5vstQFp7ZB8U2qLIz6HpK4sWuO9DkuFSpF64sRq9lGycVdQwGtPZ2QNV7LeF6e0mNYlhb9wLobeh6JpMsM2vUkoHnni/ALPUh6ridR9Jc5WpuHC/sskNCqvJ2htcLSy1w7cTkQsi/K/FWlbA0YjqBOZpwgp6frSydwAA45ED2gr+YugBgE/xu+u5wznnCO4+k42vre/M/VNrCcJ+8gE9OEvT9BHw6wO4vy21haKQ8cbnqWCyzl79NuL0HydZOhEYeZFe9dtSvY0Uzd1saVGIKgSlGey05v4qjV0+yNnMPdVvoGHfEkv2N0hm6R2JjUDYr0sKAMMyEBqnIgEqo2BK1hS1RW6rc8VKesFz2bAfODf+cKBdfRL0GPJha9cISrp3ACBWkWEFEB1/cVuxlRzMD47YZGPZtJ/oe0mNoamD+tsGoddDQviERmRHV5qwqz9O7+vuPSbOwo3O/9nRVqSq9E1S541BruJR+CYNkABWsaif48qdkfmm5G3X9Ap6+aOCRLzszrfMLeMz6jE8neyCRgJe1J0IIvGy8Kq4nGvWFTW/KdVJGDEUQvg2GfAvbP4C5raH3++V6yUude3Nn4+pzFGlfEqjAVXcK4gyk5vTFfFBTtmUWENrg7swTN0UR47WZ+YOZ3XIswVF/siBmGZjBqvYq5sxL5pegfZz1lmh9QeKFf96gl01rxpyCF5+U0Of70NqtdfV54EowFZfhc7/ERqgIeVjud1sd4hKuvdgsayMxe55EWNc4duVcpHH9AtpckHhy5+u8sesNHHMEk08XMWWCmoykY6UXZgR3ZjNjqDw8DAqy4ZldchFZmSrva7y8PXqhBgIeHFItXl5TNkVuYkfsDiQkzAIFoTsTkCaO59ihWQzblYhNrppZx95FLdRgpmfwXgPbAyBSk4EqLeu/hdIdcEOvZYnr0iHqYrV4LU0xTvh+CUrm7bnwzthsPFJ1nPe3Z/S2WLyT1ES7/MnVIhVSoQGHHEHgwRSmTFCTU6Chv3//KvNc3shr6XfpOO/t+wmtRxFFSWZc9vOl2KUZzdztq0xYwk0mMAYN3U8UY1Fk4P2BXhytr0etTQVVMQ3tm1JgyOHBjfn42/uz68FZN899Nk5+hYA2E2Dnp/LzG16Vf/4jdF2euJwdbIXLH+mkDn+YrAZBXP4ukdbPPIzr21Pw+7DqxKWpvYqKVIz6/ASNr2QABaX79DpqoNdR4yJuxde8P6+pLw0WLq6y8UH5wjIp5gqeVyO43P/BG7ZerCqME5gv9i0kTR/OnCYRzJ6nZ85DNkAWA0870+l0Iu9OdAbSUAkz5vaYy1Obn6pWZ5Wpp7eooBD3S8eJa94elUou3avKNE4js0Nnk1WYRVhMGG9u/g29w1W2Nkul/16JDV1s0W9Ip9d5JwoiFnKitRPnVQkIg475/ebz3t73bk1PGPPHAf4cI0+IdTawaqLcacXCEdyD5KjV/u+gOB86TAIk2PctQ/JD8W7nReQbK3B4piGZEQLnOgWozc0oqj+KjI+24LXxc7p8MwaaPlNFFqs+FDFem3ENAMd67EgKIix+D9PNm5NufYmwQEH/vYXsbip4dp2E/xWJulv3ERYAGdYCNdGVJyxvAaO4fOHxx7H7bQHR3o0J9HCpVnFZ9mKzI/AMoTvT+K2nmqP1BN1PSDSJljjtKxi4t5idzVVkWOqoa+XEiAYjSMxLJDU/9c4G4RoAhTkQuVOe9as1YOtB5Dpz8r7/VziOLNleAow+gZxhAyi5fHHumedY1PLJKkshMKJRaxjVaBSulq4szpnPhz8kM+XoTBzrw4hd0CHSho1Ns9FLeuyzJbqckvhoYiAfdnqEUK/QKi0Su5G4fG7zt/hmXuWARyChUdXjtTRSOuHTGAgLhNATEh8+qMcu+wqjt0HIRYloF4GEAQQM2lvM2bbuvNr3hSq31428lmef/wPMJLyCUth3qBkhQTmkr9yA3+LfqmwsphgnfMeaGpg9T+LdscV4phhoGAdtY2I5EfCvV+xC+hnss6HFYS2N132A2X/Zyzj5bToE5nUHlwBoOhCO/l6h0HV54nLN1Bk4I+jw8FCG+rpzuN3P1SYuQbbX6fR9hHsWE+4pQIKupyRUBjjjLfh05LVeRIHg+zNt8bevVy1Fm2Xrg44v24AHEr79ewPVIyyNGCcwydkFzD76Hm+t0GOdD9N+kutfeu2MB+DjmUkl7ygm/aPuyFO2S1gEZ2PzZ9XfI03TOKMaBmNTlI99t66lr1d1jZARo71WHo3jQM43rGqnYva8Yla0zeKEn6DliavoimDKBDUgQFVA9yUlTQRuV0+YpqysswAbN0g8C0lFYG4jL8ZVXAg7Ppb37/QSL2z9BM1xNfYNbUhceRLLbAvUrRxAC6l/rsTOFyy+a0iQyk72wt/lKGK8NlPyBbbp+AIDf17NMR8nLhbF0mR4Z1ze2cCbjwiK1NDjqIG2FyWOzX4Us+glaFU2PNH8wcoRljehrNfSKC7Dkdv0+EafvcZrWV3i0nixeWnxMeIH2/L4x8fY3MmME/ULydUV0OU0ZNe1JfRUOj6r1/DT6td4vssjlTdpaTYE1r8q5662ltNOOL0Si8BALLo3vEZYLj0cg0VKAr9u/ohCtQbL73+meMpzRDZrw5m0okrvQlAeph1jvtmSzJk2W3j1gj1vt7pMmpWegHPZ7Ag0R6vW8ml0U861jSAyO7haJnnlicv5DwZQ/OcFzrfrg67P8GrzWhoxnfD9kreAN747RfHYB1goNnKxrp5WFw383dkcczNz3qw/EZfPP2L+5P58WQ32Kk9Y6ov15J3ZR5aPG1rHbJo90YDfluoY3i4Js7WPQsOqz7U0nfAdOPQDoSfy+POpAIbMP03IRYl1w+qSVJiCmTBDkgSDdxdzNNiBgIoIX9cA2fu9eBwgwZjfIWb/LbU4KysudQf2EOvqRzNf2XFQneIS/rWXs68VAS/8yIwHNXgkQ7JdAV1OSdSRbElX5yFJaor10MDghPmW/Tht+LAaRnd98Xne9u2kW9jSpou8RHp1CUtTjiTvwM3Sh3C3SOKcJdqe07MrQEvfQ4W8Nk7FeesWaGzOYaZSozVTU9fKjTGbcunmVT0pDqZpnIleF1BrzGk9egBQfWmc12B9HNJcmLriKtb58MNX+mtenlfmd5ktRAY/hO+ff5Tz2k0om7KSGQ86O9kbnplZspMAB1/Q2cLWdxFqGyjKxLFeLpfWuGIQ4OqbR9Gj+8j4qzv+n7/AJ3mdKCw2MM3c7kZ/+a5BaW1YmzH27PxZ9jYk5m0n05CD/uvNWOdLfDFPj0YPPU9I2ORB52d/5c+Pcvj1g6t0Hj2H4Y/+wYRn1hM59vpOHpVBeb1AR4/5nOX1ulAkVBSYW2L24wKwtSOyfS826h2rRVyWjs/hNBdVaYQFwOB9Biyt7Ylu1pF2Z2H4PjgWYs+wXY+i0aZXblsrlRby0yErHj5wK+0t7vjiW9e1a1rzfCemmscBsNMriLRnn2JLnabUPb6X4Z++VqntrSpCvvYo2zpb4bbzLD7F9uxvqiP4ooRToTlueTrMNu1mc2dL8rVH//tglUB5LTMTNm1DY9DjP2wAk0d3oMGvP3PwuwVV0jLzRhgnfBG5QZxr68Fjx+1pYN+As42caHAF3PMssDSz5PLXszgcbMuO/IP/fdBKomzLzBObdyPlCzRtW0LzUdieXUfPmEOcCGxZbT15Z4fO5q12bzGh+QTOdxlDt1OwrNPXXGzmikMOfGT7FrZaW4JcgpjfZg7dzhayJqTuzQ9qLJKO3gcb34SEUzD8Z3D0u+UWZ6b96+MvRuOVGElRm3+dBlXVv/5GGO31aNcXyezWls5HbGj4/XbOtfZGq4dp+f/DTmdH27qteK/NN3TYZOBM67rV9v03bTGaeOIsPhePkBjS5ZpVJKuqf/2N0Kg19PLrTOsXv6TdOdjXUEunY7LECYy2Z+2D3+NgYYuLtjGFMc/QqLARjfZfrbI1L8piTOO07NcPn9MHiW3eHksb+V5YXWmcptiZWxDq3YlLtkHsCXYmx1xQ8NlcJGBjoBX9hsxk1KTmzHz/hdI1TBzHj8Mi8DauGaYtD4f+AI0egNejoV536PMBONUncpsLZ78t4OznSZxdWJfoP6w5v9CdS6vcwCBQSXDpN4lLXbqiz9Nz/vP1ld6/viZRPOO1GdOcq2N/odnzFg3qdOKiTR7xLc/Q6lwef3c0Z8zWPGYN1LG3sQUqgw3uVh780GfuNatnVQXleS1XPtueK6ve5pRnM2LNHQh99in2e7ek8/G9NFm4FN+G1Scu69paY6H3pecbr1A85HG67c0BEgBot0eOGHT8x7h3DGf514tvERx867N/gx72fQtb3gZLJ3jxDGjMS1/WwHVeS4BzB3YRW8eHZ+Z/xvkXX0FkgNXAQfg2rP6LjFatwcunBVaDGtN71w62tNTQ92ABLY9l45utxXrQQHy8bTlR0vqwOijrtczavBlzcxta95GX/K5ur6Up+dqjbO5kQePZC8h8xppdTSUGhUGrI9mcaWtBjzNmbJjRi8KLF6ptTNe1zFyznvpC0Ng9FjrOJHXeMuyDnElPDoNOT1XbuIzsKDhIQCtb9r7Sl32dzBirgi0LJ+MwzA+NWoPDsjDUg0ZyOaH9jQ9imifeeAAcWyA//8dweXuLLc5MvZaXr+TgCzQZK9e71IjX0oRvGuXz2rZU3tk8kGTXItItIWLjJzg8Vg+NWsOAOj6cuZjGxqmfV9uYTOuDLk97GzuDnobjxwA1Iyzh2gjfgrZ1ITWNSJ9CbDIErS+k8/i2AThbOuFhbc+HHQazY/J+rAeMrJIJTHm1LguA3JICZTOg4eHt/0aO1WoahG2vlhohI0Z7RfpGkTy6P3sbWNB22vOk2QlCInLxGvox9uZOxBfuY+g3/szp6Vk5BbllveQX1oNVHSyC22GRFo1rH3eytHWIj4ngSkYuB2P8GLB7D5KZwO718WR+saJaI8fVhSLG7xYChjF701sQf4L8lumcWa5mt58b/XemUqSCVhEqxjzzNWFx6zkaH1G69G9VVrOXFxI/vGYbjnkZFAwewMhRfWtUXH7f5wuGfrOHnDaNyfWwRaMyw27BPHJ7jCLbXM2kAZ+RkVeEg6WGoUGe1y3/e0sYxUFuChiK5eKUBUOu66BSVljGnLuMd8JlwoeMQ+PiQqM5n6Lv258VY5+odmEJMNzzTcxzVZifmU7Xk5l0lRdJZPymfCAfWM1Di+Ah4OwXdzh5qSCm4tLmuUl4XjhGTFBnzDTy5asmQuJGTCcvww7sYHX/OoR7OdPtSAJNhRrHocMYFvI8fxzcW21jMhWW1g89jMuerUT5N6NZ2lGKPg4iI8IF/8b7sTZY1UiuZWGRIGdUL/q+tY5doQ6c9Cuk03E1hgkhZCbHVkz4GvPEPdvI51nDB8CzFRz+9bZanBnFpe2gQbguXEKEV2MeCJK/3zUlLo1cNAiiOzbk05gGTG1xmmMNi2l7qogk+1YkGFKq5ftfVlwahWUuUJog8OTDnC15aB4YyOJqFJZlWRNcl1e/S8Bq0fcsm/Miw7Zn8KH/dHZzmKs5V6t8Al9ercuKo7Gk5Rbx/p55NEmNxGboUBrOeJvLQ4eBEFXeZvRG+DbyYXdbD0RSMaJxPbbXjeXB9Wm8rnmaU17xXM25yvvtQyqvZsLUyZifAV+1gpwkHHVruXzUBUe3k9hYGGgENAIaxoWTpTFH66Mn/uNF7Ksh515Vo4jxu4WMWDDTQdJZzId8i+vZOYRmJKNu2oTLeivanDtCE5dG9Kwnr+h3OCqtWgqOyorL2OWr8VGZETJ2MBpHuxoVl6Urw80/xJOj36bbzJdI3nIZG70Kp6xCbHPSmfVYVxq4WLPoYMydTWDmD4YWD8KxP+Uc1qd2wJ4vruugUtZrefKPFfgBTcfIrddqUljCv60D+9ZvinVxMVZtWrMrW0vTZT/yj08IHwePQZJgRCtPnutev8qjL3CtuDxZqMOjuAD3YYOAmvdamk5eupzMpMvuzNLXXLZHkcpv8NtvLADOmrTtq8zJS1mhtBaIWCE/ju7dG3vAPvwUZ8M1gBtqZyfUlslES+44ftMe2j930wU4KhurjMcZFtKBQovtvP1xdMmzBQx6QvZu64HI0FD+Bs4uf6n0fdfYzDVA7lm8eJycZzrsOzi/vsJpNzcTlxaAX8y5a+pdalJcZkWP5YFpIUQNHszK/63mmDiOxbFJBB9wIXTcBCJeHVTl3/+y4vKrrZdYdiQW//Q45obNIcKzMc0W/Y75D1+Sc/AgWQ2a1oiwNHI56RFsB9bHdlkYY576hcLtw8hYc4xX3pOvqgkffVSl19lyo8b/68jRoxepv/ICWxp3peOq1exoEozLuXNsnzqbH6tgpdKKEtdlOn1mvUDTDX/RyEzH5Y2dKFp/mFd+ngPI19kqmbyYCHMNoNK9x1cnrtDVuNBPVg5X2ncktnl7Hvj8XXJqOHJclSg543cL8wdD81Hyao5XjvNH/9mo4qFB4CmcR43AsriAgwv/Lt29OpZSh2tzLQvzC3A5uofoRsHYOv7b/7k6cy3L0q2RCysmdiDFzZcIB09s33+NPd4tUQOTiaBnE9frlv+9rdxj12ZwaStkX4WBX8grjdl6XCcOTHMt8+OvYLVxFdGu/vi3bFxjuZamGCcwL4gAsiOjSFy8lKVp5kiA2lyHnYWGj4cHUsdGx9Bv9rBj79nSJcIri7JLR69dMZWI0FAMGRl4/DUPAOvXJ3G2cRMudekKOl2NeS3Hd/Bh4cEYsuo3RdekCY7jx6Ha9A8FKjPirJ3pP3QmDwyZyc8zFt553uUNKFu7MfXZHxg2cjYP95tOsVCRZGGPbsd+6u/cgdBpsekQQo6ZHS04Dz2my4tv/Npfju5UA6XLzXcNBa0Wv23bSLJ24qKzL1laSx7uN51hI+cwdeIP19usNE98D2ybIXdhGLtYvqnfQp54WZv99N5CHhgyk3/cm1OgMuNCx35Y7j6E4/hx6Jo2KRWXNZGfavTaq3RaLnXpivXrkwDw/HG2nD+bkSFPXpa/dM15U5m1QmWXJ3ex1fHx8ED6xB6iSKhwT45m8oxFJC5ZTlZEFJMJrNEUAtPrrLeHE9Gu/lhuWE1xUXG1XGfLq3XxcbJCE7YZNRKZfQax06819u+/QYS9Bymu3qyY2KHaa4SMmN7HbR3tiGkYhMuR3RQVyPaprvt42XqXA3+twbK4ALehg0sjx53jT1a5rqkJhCRJNT2GGiMkJEQ6dOhQTQ+jYhj7dEb+A8f/YoSYyczEbVhkRuH4wxYOte1EsncDBq6WPUcJH31EZn4xD2rac+itnpU2jPJy4W6KWo3v1q0EfHmY8A8fqLRx3A5ffLeWnl++Sr1lS9jxzEuoi4vouXtz6etFiYmc6dufjVM/55WxHW9yJBOMi41sex+KcmVx07nEm/fnGCIXpZJ3PqbCY1S7uKBbsY7h3+6t1M/tVolKyeHA1GmYnzmOa24amTorbArzcFy3iQaejoBJ9KWFOw3enVZpf1v2tFPqhZv4+xEuJ2fTKuoobx5YwObQ0Qz+4GXc9TmE9+qF3eAhzO/woFxVP6BppY2jomw/n8iM33by+fqPEMC0rv/jvc1zQG/gf0Pf5blhbYhKyWXhwRg58vLCY/j/vabSIlZFiYlcHjiIq5//wotbYukX4MbfJ67wQQsL6r32FFHuDXij2/PMS9qEVdgmvIYXspg2PMpaRPBD0H+OvDreoV+qZRW7qJQchn6zh3n9fbF6dAQ5XXuz9CqMO/k3ed36UPzKdCbMP8SA5nVZf+rqvzZbMBezf94EJMjLgORz1x7Yqg48f1gW5v9BWZuNae2Fqz6H4Knj2N+4IyGRR3in60Rm7PwWg2TghX5vMH185xoRS++tOYO5RsXDu/8kY9Uq6m/ZzJrvl9Dkj7nkmul4qter5Fo74F/Him8eCr4mWuX6+muVNo6L099jjYnXMj83jxPtOnHBowlJOhs6hu8nwdKR/GYtaPPZezWayxvy/maWPduBwqH9KE5M+u83lFCZEatP/9hd4m1ei8ZF/t5s6dgLvZmWPjvWknfmLJdHjGTLC58y+amavTf6v76WM5NDiOjRA/TldVEpn8pOTwx5fzN/Fe7F1kKD6+uvs2bQQzhHX6T1wT2YacyqTNdUJ0KIw5IkhZR9XklTuVsw9ukc+CWcXc2U3Hm4N3Mj/MtkUlu0kEPRF45cE1oFWMCflRoeLxuu7PP5Tiw0akbtX0L36COkW9nRYNVK/F1tS3PhasprWZYFyVoeGDGKjJUrkXr1w+P3bzi5bT+B3dsCt5EiYswTL86D4iJAwNb35B+Qi1JCHsGinfY6YWmZnc5vG94n1dwWj/Ub8FYVEN6rFzahocyvwVxLIz5OVizqOZy+x3ZgGxRIcafe2M5+n/j1m2kwYTRQdYWTZUO8/QLciE3PY2jKKQpUZvgXZcpiLmkTVhLED32ERX9H1FhIvFsjF/xf6seBK3swP3OcN7bOZY93EF0jDjK56CIjWo8AqLKFUMqr3ejZ1JUjU97AS6jxzrzC9+2sMZu8gfOtupIgnaVtu04Igwsc/AmCxpUbxakqStPHFh/nnRad8dm6gX5vf4p08m9Oxmfyxe+H+XxMS7o1cmFYsOe/Nlv7KLR6FBLOyK0Lh34PmXG3NYkoz2Zr3/gEM8lAfM/BbN+s5o2tc4ksEZe/vtS3xsSlMXWsx9BHsFq1ihMzPuNjh678oDIj39qObyf1YcL8Q7T0sq/SWqGyKYn7fl+Fa2Eu/uNGM7pHW+Knvozu5Ck29hzGyBouqjNGXx7uGkrGqlX4rlvHwSGjydRa4ZKdzLM9pt5wAlNZXJeSuG0/HimxRD3yPwAyV61EO3I0CxK1TK60v3p7GKMvuoYNAfBZsoTtnXsj6Q2cqtuIvGKJJW2Hk1dkYOMLnSvNXuWlixUDqUDqb/OpX/L8RWMkscS5VxMpiVWN4hm/WzzjJoUORgxqHZEbHMHKBdufFhLd7wHOeAWQpLMhr8hww5PnTrwlZT1Kng4WBHrY0TtyPy7fz2JL73H8UieEL0IscZ4yAb8Vy/kikhrzWppS6bP/OQEQOBLO/g15qfCMHLUwFQc38lq+41dM4w9fItKrMW92mVjqtcz5bRkTSoRlTVeJG70UhG2pdu9SWS/cynUHaDDlUfY170aHiENkf/g52slPEdmqK+82HMysUS1qLMRr5NM/dtN35iRsAwPwnDWTzWOexCIrnS77tqNSqW4v8nILf9vUC5eZmsHFLl056deSNLUFncL3odUX89G4j5jbORXn6PXyktTfdpRrUZz8IWAktBhdqeO6GVEpObz6wzZeX/AGhSoz0izscMpLx3L1Bpr4uwH/RquSxofSM+s3sHaD9Cjo+Q50ehGOL5RX8Hvwr1v++6Y2Uzs780+7UHJtHOi3dRVFiYnET32Z9JOn2Pjyl5X+ed0q288n8tLi47xzYRU+h3dQ9MUP6F58GlFcxAsDp/Pmkz3o1silUqNVtxoFVbu4ILr1rBVey/KiL38ma3jy6AqyO3RDmvZ++dGXO4hY3c1RY2P05Xlvicjhw0mePY/fF4Xxwr7f0essqL9xPe/tTeR0XAYxaXmVFuErGwX917m3lNYJZ3HIz0KzaBXNm/mUOvfU8+bXeOT4TlA843c7phXISRco+LYLakMRdd+cQuSUORh+Gs2u+i3pcW4/WFpRb91asktOnsr0lpT1KDlbaxn69W46b1pCrsaC4S4GOjwSQsKYUdRp0JDTFq4sOnioxryWppSd/Z9p1Jp6K+ezbPx0rPbvvOkE5hqMqSnZiXDgBzAY4OElYOt+nYfxRl7LiGefI0tjgW9a3DVey3f/jqg17ZqMhZMRK5dhN3Ikx1QO+C36geWjX2ZbkS0frvmI1we+QYTBnLCXQyvVu1TWCydWLsUgBHF9R7JhtYFOUyYC8FezvqyYUPMTFyjxhA0cjIWFhtjJL+AbJ7czPN+0Wek+WmDge09y9r1r33urE5iyN37jckKXuvy7op8l0Pbi/pI/rEU9YCCXis1xbjUY9rwHn5jkP6dHwdVTcjegairm9HGy4pLeHIv+A9FuXIt1ltx2lAe6lXblANlmHt/+zVmcgCLAHYszu/Dt9KKcJ95s6H/+rfKEUlmbuQBkJnG2cRMsgoOxCAzA0q9+jRVTm2KsfXn1h3xeP7wD6cWJ7PQJoevl/TydephujR4EKjdaVTYKGvpZGP6qXD5a8xG/BA9n0v7fOT30cUZ89DJXpk0jY/UafJ59qlZ4LcuLvgz/6HOkoyuIiE7k4xtFX+5AWN44arwU18Is2scc41T/hxk5681aFzUujb40CcGqfkOy3nuHJxb8Tu7QpehVZpzOM2PDqausmNiB5OzCSovwlY2CNnS1IdDDjkHBo1BNfZ49zbvz9fILfBEdi/O5c7JzrxZEjqsCxTN+t3jGTZkTQKZXd6xP/UZy43Gk/hFNRnI8Af2yCf9LTbZDHXR/LWfC/EPXnjy36S251Rm/pl49CsPDmTN6OofNnGuF1xKun/1fef8rtDPeIN3SnnrF6fitXv3fs39jaoq+AFIuQUGW3Nlh1Hy5heFt5InrhUAv1Hw07iM+mdCtVghL+DfvUvv5x2SsWk3cl/ORXnoOycwM755dsbXSETFqAk/8dggLrfqOvCW37FXSalH37c9Y2+61xkNijLxEDR6MTe/eoNVybt12zIry2fe/dwmd8yrP9phKis6Wxzv6XddK81YiVmU9SqZC6Z2+U3h9y9fkWtvRa8c6Et5+WxZKGzde74VLCZeLN7OuQLe3IHyr/HyZlpxVRWm0qndv7AYP4tSOg1hmZ7DtlTk4Hf+FnmvDSO5XhziNA6PMdoLGkoT9ZiDANSizwnniZe31254oft4dgWN+Jt9v+4x8tZZCnSWdw9aTNmc2htw8sjZtwmvVqlrhuTQS8v5m/szYjn7jWiisePHh7USrykb18gr1/DQ+BO8/v+XKspVkaa145YHXmNXXD9enx2A3ZAiFk1+pVV5L0+iL2qBHTcX1zq3a7EZR4zfbOnO5R08ydFZMGTSdme0dal3UGP6NvrQuTmLyohno6ten8NKlCr//diOiplFQZ2stQ7/Zw5sH5tPg0lHshg8jecKLJIwZhX8dK3K++qVU19SW++StciPPuCLG70YxXlLMGXNmD17nf+WPvFEErdqFzq6YwoyKBzsqevKUF0qacGIVhcUGlrUfyZubv6ROZhLbpn1L689ewSs9jmh7D6b0fKnUw1wbKA1djgvB6rnHuJycQx1VMdYpVyt8DAvnQnwfdoeMOJD08qIjeWn/7mBVh4T8R8BMe0N7Pb/vd1pePoLbuo0YfvqWjHXrUfXoXauEJfw7eXkx2JFLPXqxzacVbbNjsLoaW+Fj3O53zFRcHnVtRMfY4yR/9h2hA7v864UrT1zWIMbJi/kPX2LIzSVz02ZOjHqWgHkf39JxKmKzGwklv0U/cGnTDhwTYpjWazKTx3a5uVCaEwDB4+DUCshNgkfXwrm/q62Ys+yE79RTr9Nk7ruIRlrsLLWohZ46TeJQ6/NZSF/q9n6bupMexv9pf8wmLL3psW91ghdlVxeLz7+m7guPYdO7NypLS/Kfer5WictrJy+DSe3eH559jAONOvBHs743jVZVZLJ3qzbTN2vOjgIrukcfpsHWLcw6nFJrxKUR4wTGsG0T2i6hZG/cwKUmbTn16EusPh7H8L1L0Jqpmdd88C2ndN6OvaLjU2utsDTer2ZvmY13WhwxDu7Y5GeTZu/C0Skf37G94N5x7t0ulSbGhRBjgWeB5oAaOAf8AnwrSZLhNgZ2W8erjHHctWL8+CK5mHP07+T9MgTz6J2Eb3ShIN0M7FSIXAMFKnPMC/IrfMiyAuBWT5gEK0fE3B9xfe4RpPx8PBcvpuUfkRUXSsbUj71fQ7uJgCSvZlmRx7fQJ7ns7N+yWzdyt28n3saFLJ0VjZMjKvw/WzTxw3fFOji+kMipM8mLyanwe5Ms7JG++Rm3SeNBCLxXr65VwhKunbxcmT4d38M7cBw6mMSVa8CgJ/ybxbyxORJLrRpVWgrfbp3J7LHvlnr3b3aBvtXvV4a1AxMHv8ucnp611gtnOnm5PHAQokt3/r6YRtsrZ3DISMT8+1/4MdWK4zHpJGTmk5pTyJMnVtHA1aa0+0Rl2qxCQsnYpcm9pewhlwCPIIjYCT3ervKUlbITvmjvOvjFRaPPr/jfvNHkpewE78DUaVxMzGZe4GCcrLW42pgTZJbNqLlTUSOh7zuQLRGZDGjoADu24f/3mlonLstOXhK+X8jOT75mxLmtt3Scitrs1e+3MeWvt3m258sYHJwQ2dl8u+FDJK0WFy9XLAICSVmxkshWodR9791aJy7h3wlM5MCBCOBo00602L/+lo5haq9bPQ/z1RoyzG1wLczGsktncrZurdXC0v/1tZx42I+YUaNQWVhwuG0/grYuuaVj3Kme0CNYPv1nWn81rdY6926XShHjQoivgYnIS/FtRU7g6wHYACuAkZIkVbgy7naPV1njuGvFeDnFnHlpZkRudkVlaUVKUzccDlwium59Gn03l7xh/W+pYLEiXPVuhI23B+a7tpNt44BF9x5sPZ/EA4YrOLRvd2OPUnmie/dX8rLxNnUh+BHYUCJEOr0Eu2bd/HHfT+DIfDnMXpwPHSbxX+I9tcVTdAmrx49bZmCXnokBFSpJQu2oJ8OvEfUeDSX5lXno8yp3IRuDnQP6zEzyLG0w79mrYvaqYYyTF/OMVH7c+AFWXbqQs3UrEpCms8WpIPM/j3G7JHrUQ5d8FduCHGyHDSPh6ans+99LtdYLZzp58fzzOw6ei8fr5D6s2rSmMGw75z0ao8/Lp1lqZJWNoUCtwSBU2Pj7YN2ixX8LJePE/sG/4OJm+OtBeQXZlmMh9bK8TxWmrBhtNn+wE9q3HkcfXoBtI3Myz+ah0hjQ2EJBctVNBrI0FqgNeixVErZ9+5C8NYzYwHaENPYgduzTtU5clhetajXrfdSjBmFVkIPzkuWcnfo6LlHnq2wMErC8/zMMX/s9Vj26k73zH57o+yYFtg61UlyaRqzS9uxnnXClQ+xxLPOyMe/3APoD+yC54gXqFcLJGcvVGzg3fBTeVy+zLPRhBu5cCEjE2dWt1cKyPHu1jzuJTU46onsvtHWcidt7GNfoSv6OqdWc6zyQxmErOe3sT53PZt6+c68Wc8diXAgxHFgKXAW6SJJ0seR5V2A70AR4QZKkL6ryeJU5jrtWjJvy5xg+uOjFy447SdtyhcxsD1KtDLjlJJIbZ05S/UCyU9LIb9qcGT59+TptB6l79nHapT56gwFLfSEd4k+yq24gRVodAHoDrGnSne/Wvc8Wr1bMDRrJy6eW0TniEA22bmbN65+QlZlL/cvHcMrLQGVljd/v8zk/9mFA0GzTemYfSqRl3EJ6Zy77b9EtzOSODuZ28qI5nq2hKB+idoNHK1nAXzkGXm1BrYHIXdCwL6i1ELFDLpzMS4OiPDl1BG4u3g/8QFb8eczM/IlcmIGNVz55qSqKM80QagnP3tnEbLTG2r8Ih1ZZ5BzVkZ2oI9/FHAvyoRiKY9XYeOahMpPIQ8fqgna0iz/Dbo/m5Kp1rGgYys+bPkT7wAB+ajOGRkt+oNm5fdgV5iKsrPD7fcE19qptwtIUY9rI1FPL6HZpLzF2dSmWwD/zChn1m9Hq52+41LMX4UFdeK5uX546uYrA5HBOuzTAYDCgVsmTmqaJ4ZxxkUWdWWEBneNPlNrr9+AhvHRiGe3CD2C9bA1HPv0Sm2MHcM1JRWOmxn7oEJyff47z3XvWai+ccfIyrqEVHT94HpsunZF2bifawQPvhAhiPBrQomd7XF9/nXMDh5CUXcC4ds8x4cSt22xe4CB+2/sVLrbmmP+8gPNDR+CTHM3foQ8yIGxhxYRSORN7EKCzgd4z5E5B4dug9/tV4yU36Lm4Zib+Rz9md04AzuvTsfYsJidSAgRqRz2H6z/A4B6xxP6exJUiC8a3e56nTq4q99plai+9AdQCmiZd4qRzfeY1H8T8fXOpY6Oj4crl7B84Avvws5x08sPc358Gx/9BdO1G5o5/2PPWXOafz6514rK8aFWjbVu4+Obb8E8Yp3yac8nMjsZuNgS/MomsYQPZ36AtswKH88iR5bdssx8CB/FV/HrqH/uHqB5D8Vm/iIQ6Xuy386Nl0kW8Mq6wvX4HZgYMK02LqW2YTmDO9O6HEGD7wSfkTnkeA4Id/m3Q2tpwYfiTPLl/IQXr/+bxPm8y7Py2cu1V9jw0E9AsKRzHTu14WNuer+M34H4wjPNdBhIYtoKzDVsTKSzp72OJYdtmPBctqtXCsjx71Zn9OanPPg1IvNz/dYbGHcTeQsPAj17lYo9e7PRrzcyAYTx3dAk9Yw7zdP+3GHRma+l17GY2+59dF6ZFbcTx2D5cc1LRq80omL+MHTPm1Hpn1e1wIzF+Kytwvl6yfdUogAEkSUpAThcBeE0IUdFj3u7xKnscdzfNhjLC9izf+s3F8YHW6BNTsY9Ip87YUCQd1Ll0gpBmETQ6vJlpmjV4G/7EPyOOhHahrA/oSbfow5xvFMLvTfrQO/oQvaIPsrRBKK18HFAJgQBeCLInJPo4Yb4hnP5wJgGndmN9NQb7gmyu2tTBzEFHxrRhWDpZEO/thOGn9ozdP4Qu+r3Q7Q3Y8THs+EQueizKg6yrsO5lMHeQ+3Pnp8kiPPm8LA4ubZGFOEDiWblQEiD+iLzoERJcWA9nV0F+OiSekT3j+elQkC13N9n6Dlg4gZ0XbH0X3JqDeyvY+AakRZIsHNCqY3BsmE+O1pbifDMsXPOR9HBlpwX2frnkRpuRmW+Fzq+IgnQNh1v0JqaJJ1mRFuT7WPNVo+HER7mQGmXLr036c6FRa7pFH2Z9sx6Ya9QIBFvOJhKizaHNqR3YF+aSaOWI8PAkY+VKdF5ebPVpw/Fcsxpb3a8i+DhZ4WStpf+st9G4u2Pwr49nUSZRfgHYXTrNngefYKt3KzxP7MXTkMP+hu2olxHP0SbtWdqgW+n3ak7QqNLHfzTpc4293u/iRvOIo2z3CSHp889puG8TnjnJXHD05mJQF9I3bOTqJ5+iEoIPXDoxoQaXjr4Zxq4XWVb2bPZqRVbYDgqLDSzt+CDFKjVecRdJ+uMvdv79D1mR0dimJ+KQl3lbNnPMz8Q+M4mcyCiOPv4sPsnRnGzYBkNsHNF2bmRv3cp2nxCuqq1uvLqfsUvTOxnQsB8M/QEmHwMHP1gzWT7fXJrI7QO/DIKZDWHvN1BcKEe3ZjeVfzf8R+TNuHLm7KawZy7s+Qo+awhfBtEgeRt6h3qEWJ7DwTuDnEgJMzs9Wtsi9Klqgg5toOj4ETKvZmKfkYRjfuYNr12m9lraIJSjTTtQLyOefQ3b4ZCXiW16ItkR0SwfNQH78LNE1WtOw9wkVvt1oLDYQFbYDjZ7hZBlaVejKyLeiNIuIfMP8WGdTqgEXP3kU8Txo8S4+BAYdQJfVSHNTu4iZe5cwnxDaB5+hPe7uN6WzTwNOXid3M95azd81i9Crzaj1dez6Bt/BMm/Plp3d/rPno6Tta7WnYtGjKvknsjTsM23DVpPLyyOH6TA2Q01Es6iiJZndtPO3sCWcwmohMDcTHVDe5U9DxPad8c/I45PDPXxNOTge/YgWfWbEhC2gjQ7Z/p+/SE9Yg5zKaMIx4ceItXNp1Z0ULkR5dlLtW8XxXU9AXjy2EoWe7Un4NRuTn8wkzDfEFpHHeOFIAcAVELQytvhmuvYzWwW6qyi3qHt2OekYwDUvfvR3MueHlEHKIiJxenJJ1h4j3ZQMaVCnnEhhCcQAxQC9pIkXbcmqhAiFvAAOkqStKcqjlfZ47gnPOP5Gei/CEadlwxAwhFbchK1WLkUkl+oJTdSA2rQOhSjsdeT79keceokOBTgGWzg8lId0d6udOkay8mVdiAgcHAGO/b44qhVYX8hkkgvT47hx5iHPMmb8RdFKjUavQGLFgXkndECKoSZFqHPx7VvBipLgU5ngc7CGnISwcpFbgNYnHvt2B3ryV7ylEtg4wYNestLc9t5yR44G3dZpEuSvF/2VZAMcgeFzHgwFEHmFWjUDy6Hyd69ui3kDiexB8HWEwqzICdZLrQsp5SgKE/F5fUu2HgXI0QxaUmWkA6WTSAPa04Xu9LGJoWiyFSsnXNxbJJN+BpXdL7FHHpjFVYvT0ZCkPH5TyS+PZ2esUcomL+MjdM+Y1hTJ4o3byK/SI+lvoBVDULpHb0fM0CnUSMheKjTi+BUO3MHTTH1lhzr2Q+7Pn2wtrMics1GHDKSONm+H2q9nkup+fQLrIs4foQ1wg3f6W9h/8LjpTYyfWxqrx3vzSa/yECrR4bh+c4LqIDLnR/A49BOPh79Np13raDbpT213gtnSo83lvJN3DpsvT1ZeDKJ/oFuJO/ai8OVKDI1lmj79AW1mvWnrjKgufst22zjtM/oVd+B4l3/YJ+TRrJnPdos+JFz/QdypVEQ9RPCMfvuZ0Ysvlgxj5JpysqcZuAeBOfWg1QMOltQmcnnkZ0XpIbL52/PtyHsk5uniZUXEZMd3zLFRaDPpwAzCh3bcnV+BJcadMb3zG7SA5tgf+g0uWot9OqHSqdl/amr9JnxMtpHhrPVuxUu77x7Q3tFvvc+A6WrSC2C+ftEPL0bOZO3bx/OqVdIdvWhfu8uZBfq+ft4PGMC65AZHctEzwFs/WBYlX0vKoOy0art9Tuwq91gXv/rLTT6IrJ1VuiK8ilYsJwt02ei06jpOn3KLdts8/FYmmXH45MYgQGBuv9AHJztyUjLIn3DRoK3bqjVUT0jxogVKcn88c9sVAJyi/SoiorQGorJ1lhw1qUeIZnRqEK7s/xMyk2/Y2XPw1J7nYilSW4CnlfCMUNi03Mf8GDW+XvGXqK4GJ2+iARrZyz8fTE/dYzCBcvYMn0mtqKYDnEniWzahogcA26vv/6fNituGkjE3iPUT40hw8IOh4JMokJCCWnsTtre/axTudP1iw9qZRT0drnTPuNBJdvT5QngEg4ii+Ag4KYi+A6OV9njuPsxt0P9ajjbzyei+utBNtZrziOxOymKyEFCwsYrj/xULYXJGgqSNYjLRzDvaEbBPhXpGLD1zcUvJg6V10jsc+TuBCqvkdSLXIpr30xS7Tvjs+ckLYMukP6TNUgCrSjGo0c2OXFazPyLyE0wQ5+Zj3mDYqws8tFggIIcKJAnCAgBHi0hNQLsPKHZcDj+p/xYkiD0Ndj+Aez8VN4/6Vz5/+uN2HNRFujd3oSLm2Th0PLh64W8QQ+N+oIkod/2AZ/kD2NsrwZknJmHjbWOzHNZ5LmaYZGdT95ZCTRZBOizyFVJeIcmE72zDoaAhzgbnIXH8X0McFRxJicVAXS3yeFk/EkutuhM8/nf0jdyP/ulQELyc7EE1g2fxAh1EsfqdMP89DG8sxLZ0qATuTYObLwLLjL/9qF1ZYtXK8ZpVWStWUOGbwB2J5IJ3LueXLWOBpIeTZyW9Y+9Sc957xNok3ONjcqzV/BfP9Lj8j72uDTGecYrCCDCL5AQf2cy3QdxqdicOUHu5OTKXrhfFl+s9fYC6Nq+Kas0AbwY7EjHHn1x/+B3pI3rONiwHa0u7CN33RqOeDenX+wptIla1j8xnZ5fT/9vmzXviO9n7zMg4giFUWZYFRcgAUdGPkvDX3/BomcvHDdsxLfkxl9hj1KjvrDpTXinpE1gRixYOslecKGWF7ZCQH6m/HzqZUg4LUekivOhMA+2fyiL7FaPyec0gFCBVASZEqybKkfEcpLkyTQC7H0gP52iYoFN6m7Me6gwrN+Bta+EY6NAlmsb0XXPcvI2b+CIR1P6xZ/BeemvHArqTIfj+25qrxPRh9ny9Fv0+WkGA/ILKYpU46wvRAJODXoE18VfUffnn+mw4hHqzNvA/MMphBbfch+Casc0WlX07OMMC/LgFyywGD6C7MhotAf3YiYZuPzBR8TYefH02XW4rJjPvgrZ7BBbh0yg5/Jv6KcvRgDn6reiQeQJIuPTUO3agVWvXizzDkFdEtWrDetI3AxjxKrP5ztZ5xlCz4v/EGvjRn5wc7z12RSdPEFI3CkynOryT44NvaI34H4TexmvXW1XLKBH9CG2Dp5Az5Xf0re4CBWQauuEg7MDmg1ryUg6fe/Yq6lsL+n8BWxPHMKAIGb9JnZ7B/PxP9+gfWAAnxpa8N22mTS8gc1ClvxCr6iD7AnuQae/V9AEiRN1G5NiboenszXuR3aTdlp2Vv3eaTS/19IoaGVTUc/4JOALYKUkSeWusCCE+AKYBMySJGlqVRyvssdxT3jGTUjePZ/jm37l2LFG9LsYRrKNLb79IG95BroQPfn7VUh6Y/aO/LlrrIrRF6mQ9AJhJj8nFQuEGtRaA0U5apBKXFhCQmdfSFG2Bu/uycRsd8a7WzKR25yxcChC092BHFtnGhAjL37TbKi8IqVRdDfsI9+gr8lPNaGCPYOvodyc14ogSm1g9I5b180nK8YC315JRG11RudYSF6ieek78tRazPWFxNi4YFuQg6W+kBwzHRJgXVxAoVBTrFJhXyhHAHLNdBTaO2GXkcSbPafwyZ7vqPvzz5wd8zCuQYGsGPAMWZZ2tdpDYoppMee8sFnYdu1C6vqNRLbqSlJCKsUG6BJ7tNThma/WoEIiVy3nWhrtBWBVYi+DENgU5SGAbDNzcqzscAgKpGj3bmzMzfBes4bOn2znzz2f18ruFjfDNL935+Q3GNC8LrYWGo6s3oa7uURmoYR1ehLmenlho0yNJQDmhiJyS75XVsUFpTazLspDArQlKSFFqNjhFUSIhw0OqVfYanCiV8mNf/6xRHp//fHte5RMveR/joFmQ+Dwr/K5GXsIinLklLPbwbmRXOeREg51GkHgCDiziqjePxL51SC8uzzEwln7GNfShewtW9hapymdcmPJyC/GIjMNq2K5S1S2mTmSEOgMxdd8r3LNdICEZXEBkgQ6QzEABmCrVwit3CxwykgkIimH4EE9yMwrZM2Jq3edB65s956xHSaz+9XuRA0cSHZeEQXWtlhlpqA16DEgX/ESLBzQ6QuxKjkXBRKWxYXkqrUIwKooD7OSCKIE5OssebfTU3SNO0Z9GzU+h3fg2K8PmTv/4cnQl2pt0eaNeG/NGexy0xm89nuSjp6gycI/iHv8caa3Hs/0rV+hR6Ax+f8TLBww1xdiYSgqsdG/9srSWuKZnXTNEmf5WnNmt3mE5w/8wcHnZ9Bpzqv3pL3cvv2WiEfGo9brMcPk+2KmI0Vng31xLtpi+TpmQL4/5qk15Kl1uOalldqsUK1BquPCSx2eZe6Wz1g9eSZNv3y71Fll2j7xXuFOc8atS7Y3692WXbK1qcLj3fE4hBBPCSEOCSEOJSVVcgV1DePcajBtNZeZ1Hghlk75uOam4yolY989hKQrNqAxQ2jgfJAX2MunQ7qtDdn2Fkh6Qa61jjwrLZJeUOxoTqatJQiBxgX07irQCJwHORPr48qVM42wa2pOckojzvo3xHmEGxewx8PJBrq8DGkRsPF1uHoCzq+Tc7z/fkEWzVZ14LVoOU/V9OflS7cmxOHanNdb+kmHdzKIej6eIR6rWeUTSnycIwVo+LDFMlTDHmK5ZVewsMSg07GkfiiZlrZIQnDVwoEoG1c0+iJirZyJt3RCoy/irLMvh10aY1CpyQ7pyFPdp2JXkI3d4ME8vud37IYM4eqipeyq147kGZ8z/3x2rc0TLw+jt8TB2521dYO4ulFupxbRsS8d08JZ0iAUYWWFQatjcf1Qznk1RaMvJsralWjrOqX2irNylu3l5Mt+t6ZIKhWFbToyscdLWOZlUTjhea5YOqLx9CRRY81DETuwGzKk1ufWl8U0v/dQ+/7krFmNeafO+KTFcmDQk5hnpfNGh6fQa3XozTTsc2tKnJMHGn0R0VZ1iCmxk9FmZgY9++oGsKxeFyS1Gvshg/k1oD/qIwfYOvApOl0+gEWnTqRv3MTqJj3uLK++UV851esdO/ncXfG0nE427Afo8yFobWDAHPDtDF1eAfdgsPeGkCcgeLwcnWrzlJyq4lQf/LrK+7u1kDuzmJlD5ylyYfaKp+H8Ony+cqe9LoLxuxxZ06QH6Rs3YdmpEx0uH+SfB1/APDuDid2nkNs8BINKxe66AVxw8Cq1UWyJvaKt6hBtVQeNvpjTvi1YXD8Ug1aH2tqaVfU7ozl+mH+6jcEnLRZdp07krFnDofb9a20dwo0wze21HzKYhyN2kqCxRuPpSbyVE5qv51FopuW9tuPJ9PBHEirC7T2IMzkXZTsVEWXtSoS1K2rJwJ7AUL5uPgRhZYWVVk22QUW/+KNc7tgXCbi6aSt/uwXh6FW3VubV34zxHXz47UIOKTM+Z1e9dlxZtFS23cGl2A8fjpmVFdPaPUGKV30koeKSvSdRNq5oiwuJtXImyspFtpdtXeKtnJCEILaOD182HwaWlljqNATFnsBh6BAS1Jb3rL1SZsxgnW97sn9aRK6ZOaccfUl39kAr6YmydSOlrl/puXil5P4YYetOuL0HkkpFhHdTXu70LDpLcyxyMul/ZA2OQ4cwOsQLt9w07EOCUT80jofaet815+OdUtE0FeNEprJWCLrd493xOCRJ+gH4AWTP+O0ep1ZibkfKs6cZ+s0efvq5Ic4v9yT9aCGOTdaSFuWKnV8uKrVEm4xzZOVZYtutBdlx4VhqtejMdORYGxCAzlyF1kPLlYx80kMa4T86lKKXv0Rq05yPCxrSx38HBZvScBozgvQvljCw31nMUg2EAkQAEZvl8dyOp7ua8XGy4puHgnnsagIP2BYQaWZD2/3r8J0xlR6hPVAPGEiRWov1kUjqUIjjiBEkHEvAz9kK83QdMQYXQNDKzRILe1+uJufgOHwYqg0bebSOnvUewUh12/BAxlL5xj/pRQ6NeeeuDb2VtdeODDX9449gO2wIU1cvwWzAYPIK9WhOxNO4RUPMLQqJK7FRa1eLf+3lamFir+Gkb9jIY64GVH3789KS48zMTaUgJoNty8IIjTrEX2PHMf8utJlxAjN32yXWuQfTc+IkEuw8sD9xAPshg5m0eRW6ocPJK9STcyIev2A/zC+YEXsDmznau5ORnIPDsGGkb9jIE65Xr7vxb/Nti6NXXb55KPj2bWWc5MK10aePvUt2EPD3i/LDyH+uTROTJAgYIae5SJK8DsD2D+TORwBXj8vbCyW9nk2uE1pgQUoOE/84wtq6QXTbuBUtkKC2xH7IYMYf2Y5l4kXshw+n8FgCOs86mDupS20U4mpxje2aNvQn6tRV9AOGoDVTMXXzEhyGDsH+xAHC7TzInjiJLd6t8fD35KPu9e+q75bpZG9cw650WzyJdcvDCI2Jxa2gmKlLjjOrzwA6nb2AfVYK9iOGk3osATtfL8zT//1etXa1KD1H27rqCPavQ8KpqxT1GYCFmYqpmxfjOHQI/eOPsMm/DV3t9Gzw6cWvd/L9qiFMbdakfX+6LXwHly8/p95v8/nDvQ1mnsl0TTyNU0YS9iOGk3YsAXtnz2uu9W1czVHb+5KYnINjl0BYv4H6GXEU9R2IeVEhPdauwW/BZ7R56zNiW4fiW5x1z9kr9bcF7OzVn0Vb4vm5e08abtmA3cq/OTXra1LiM+ga5IHawlB6Lga7WWJm70tqcg6OnYbD+g10E0co7PVAqc2cnvyMDW99hr59D1RvvsH8+YdYMbF5TZug2qioGM8q2VrfZB/ja1k32edOj1fZ47jnMJ48Tyw8ztChP9F31ovEPL8Y3d9Ps8m8K0saduSzVR9i75eLs+0mMnfJs3T37skUbXMufRy1zRlboN4Dm5F2biYVVxwS9/Gh70YSIm3JcdBy9YvF2PvlkmdtR9oTe/F2r1uD//nt4+NkxbTxXRi32I6h3jr6znqR48eHohOCveEp/NaoF1/ELiO6dTfyhz5Ct5Wj0MSocP/rd7qNfggJcF/0B1kPPoyvXiL+vcUkxqQTeigMm+Vr2DRtJpft7+4bvymm9mqiLaBjyQXa57f5zFI14IIwY1bsGlTx4P7ntTa6mb06HwqjyS+fMPm1jznctCM5+UV0/moa2/zbkmtpx4qJze9Km/k4WfHZyBbs8HyRy2+8wbYuo5i4ehYuj39O0eK/7thmfr98UrU3flNhXhZTof73C+XvU47ovhk3myB37d6TyJBQXG5yHpo+zh77MH0lmNyiD43VhTyf9hd1enajwaQX+WbQFLrvXEzHaS/QtV2T27VOjWKc7M3fG8VW79Z0/nIaa/3bYqNTMzlpHy0+ehXzSrCZ0ZGwe8w7/FSovesmxaaUN0FOtPfAYccmen3yGtnDB/6nvcqeh70PhjGp1UDGX95IK5Xg6LFLuOzdysapnzM9Kv+es1eygwdDE44S3b0N7kfMSVEJ5u28zF6nNsze/xG5sYdo9Oft2+zdu9DxcqdUNE0lsmR7s/iwV5l9q+J4lT2OexLjyYOTMzt8W2OY8j+2eLeiyYWDPN/GG0mtY5GhB8EWC8l2b0C4tTfLxx4l3NqLS6WPvZH8mvBL/8N8dmokF1v1JCXBjSHpc0i+4s6GJ+dy1Kkp517fhM20yLtWiBu5mc1ebe2MWqXifEIWj66+jMrdg3gLR5ZnWnHVypGrVk4sz7QizsIRlbsHj60K53xCJmohSIqKp+XZPZwdN5nLzj50nPYCn428+y8yRnu5+3uxzj2Y8xMnEengid/B7bw0pgMW3l7EmV9vo/+y19Fjl/A8GEZS/1GsbdYTbUAgk398j2kDmt71Nuvavgntl/6OXUDTSreZy96tHO0xinGNH2L6+GrMsbyVNLFbSEMrnfA1foij3Ufisncrx4+HoxLiP89D08ex5o5YensxdUwHfA+GEengyYWJk1jnHoxdQFPaL/39rhXiRnycrJg2oCmT5r2LNiCQtc16kth/FF4HwyrdZh7+nnddqkV5GCfIHd96kcvOPpwZN5mWZ/eQHB1fIXtddx6qBK+2dqLJxcNs9WqFNOV/7PBrDY5O96S9Ip+cQqfLBzi94yAp6zcSHtQFqxV/8WC/YMy9yr+O3W82u1UqKsaPlmybCSEsbrBP6zL7VsXxKnsc9yzGC/TkH9/DLrglRY88yU6/NjhMn8Imz2C6XDmJf1oc6oQr1M1N5adfNuCWm4p76eMUCqJjWLs8jAFXj7EwoB+r3Vryxta5bPRoRYqrzz1xIzOlMmxmlhCPb1osna+cYrNncOkFJt+73j1pr7IX6AeuHGHezxvIj4m5gY0qZi8cnfjlpX60/Os3zOrUqel/tdKoapvdSzex8ibIFTsPr7+Ozft5PQ9cPUrkk1PuqUmxKRoXF1r+9Ru/vtRXsVkFMU6QC7zr3aK9rj8PHadPYadfa4oeeRK74Ja8+OOMe8KJYIrRXimuPmzybMUbW+ey2jWIxQF9GXDlKGuXhd3kOnZ/2qyi3MoKnIeBYGC8JEnzy7zWFQhDXhXTQ5LKaehcScerzHHca91U/ouixEQuv/waq/o8gWbx73QM38923zYIJEIjD97w8a567ch58jkeaWCF6rP3cf/ow3tKIN2MO7GZftRDDNr4E/VmfnLP2ysqJYf5e6Ow/vGrCtvofrYXKDa7FW73PCzvOjauvc99cbNXbHZrKNf6W6MoMZErb7yJ4ZW3WHAh55auY/erzeDG3VSQJKlCP8AI5MLJK0B9k+ddgNMlr00u856PgHPAR5VxvDt5X3k/rVq1ku5XChMSpKgnnpSKEhMr9FhBsVlFuFUb3e/2kiTFZreKYq9bR7HZraHY6NZRbFYxgENSOXq0wp7xEkX/DfKS8/nAFqAI6AHYAiuBEZIk6U32/xUYD/wmSdKjd3q8O31fWe43z7iCgoKCgoKCgkLNcKcrcAIgSdJEIcQu4H9AV0CN7Pn+GfhWqkB6SmUcr7LHoaCgoKCgoKCgoFAT3JJn/F5D8YwrKCgoKCgoKChUB3e6AqeCgoKCgoKCgoKCQiWjiHEFBQUFBQUFBQWFGkIR4woKCgoKCgoKCgo1hCLGFRQUFBQUFBQUFGoIRYwrKCgoKCgoKCgo1BD3dTcVIUQSEFVDf94ZSK6hv60go3wGNYti/5pH+QxqHuUzqHmUz6DmuV8+Ax9Jkq5bcvS+FuM1iRDiUHntbRSqD+UzqFkU+9c8ymdQ8yifQc2jfAY1z/3+GShpKgoKCgoKCgoKCgo1hCLGFRQUFBQUFBQUFGoIRYzXHD/U9AAUlM+ghlHsX/Mon0HNo3wGNY/yGdQ89/VnoOSMKygoKCgoKCgoKNQQimdcQUFBQUFBQUFBoYZQxHg1IoQYK4T4RwiRIYTIFkIcEkL8TwihfA5ViBBCI4ToIYSYJYTYJ4S4IoQoFELECSGWCiFCa3qM9ytCiA+FEFLJz9SaHs/9ghDCQgjxihDioBAiXQiRK4SIEEIsEUJ0rOnx3esIITyFEF8JIc4LIfKEEPlCiItCiO+EEP41Pb67HSFEIyHEZCHE70KIc0IIQ8k1ZkQF3qvcpyuBW/0M7vf7tFlND+B+QQjxNTARyAe2AkVAD2Au0EMIMVKSJH0NDvFepiuwueTxVeAwkAM0BYYDw4UQMyRJml5D47svEUK0Bl4BJEDU8HDuG4QQfsAmoD6QCOwACgBfYDBwHNhdU+O71xFCBAHbAHsgFthY8lII8DTwkBCijyRJe2pmhPcEzwKTb/VNyn26UrnVz+C+vk8rM71qQAgxHPkEvwo0lyRpgCRJQ4EGwFlgKPBcDQ7xXscALAO6SJJUt8T+oyVJCgTGAHpgmhCiW42O8j5CCKEDfgUSgFU1O5r7ByGEFfINrz4wA/CUJGmwJEmjJElqA9QFFtfkGO8DvkYW4vMAf0mShkiSNATwA34GrIFva2x09wangM+A0cjf9R3/9QblPl3p3OpncF/fp5UCzmpACHEIaAWMlyRpfpnXugJhyBcAD0mSDNU/wvsbIcSPwBPAz5IkPVHT47kfEEJ8guwVH4Ts9RgPvCxJ0swaHdg9jhDiI+A1YL4kSeNrejz3G0IIcyCv5Ne6kiRdLfO6OxBX8quVJEm51Tm+exUhRBiy53WkJElLb7CPcp+uQiryGfzH++/p+7TiGa9ihBCeyCd4IbCk7OuSJO1Avvi6Ae2qd3QKJRwt2XrW6CjuE4QQbYGXgD8lSVpT0+O5XxBCaIEJJb9+XJNjuY/RA8Ulj8tLzTJ6x3L4V7QrVDHKffqu4J6+TytivOoJKtmeliTpRhfXg2X2VaheGpRsr9ToKO4DSjyDvwGp3EZOp8Id0QpwAmIkSTorhOhQUkD7vRDiXSFE+5oe4L2OJElFyLnIAO8KITTG10oev1/y60+SErauTpT7dO3nnr5PKwWcVY9fyTbqJvtEl9lXoZoQQrgBj5b8uqwGh3K/8AHQCBgjSVJyTQ/mPiOwZHtRCPErcmqQKdOFEMuAR24iSBTunInABuQoRb+S9AiA1oAD8AXwcg2N7X5FuU/XYu6H+7Qixqse65Jtzk32yS7Z2lTxWBRMEEKYAb8DdsBWJWWiahFCdABeAFZKkrSohodzP+JYsu0CqIGZwHdASslz3yDn72cCj9fEAO8HJEm6XHIuzAf6cW3Y/RCws8SDrlB9KPfpWsr9cp9W0lSqHmNeoBJyrH18h9y2KgZ4uIbHck8jhLAAfkEWehNreDj3K8brvRlyGsTLkiSFS5KULknSamAI8nVqvNLruuooEeKnkDtMDAacgTrI9ncAlgkh7sn2bbUY5T5de7kv7tOKGK96skq21jfZx/ha1k32UahEhBBfIFdmXwV6lO1qoFDpfAg0BKZIknRP5vzdBZheX+aVfVGSpEPIvX1VQGg1jem+QghhD6xE9q72lSRptSRJKZIkJUuStAroi1y4OU0I0eDGR1KoZJT7dC3kfrpPK2K86oks2frcZB+vMvsqVCFCiFnAJCAJ+QS/WMNDuh8YitxHdrwQIsz0B1mAADxb8tyPNTbKe5tIk8cRN9jH+Lxb1Q7lvqU/shd8nyRJl8u+KEnSJWA/cvQitHqHdl8TWbJV7tO1hPvtPq3kjFc9xnY8zYQQFjcojGpdZl+FKkII8SkwBTlPtpckSWdqeEj3EyrkPrM3wr/kx75aRnP/ccTksRPyTa4sziXb7HJeU7hzvEu2GTfZJ71k63iTfRQqF+U+XYu4H+/Time8ipEkKQb5JqgFRpZ9vWQxAU/kMMze6h3d/YUQ4mPkLgVpyCf48Roe0n2DJEm+kiSJ8n6QWx2CvOiPkCSpZQ0O9Z5FkqQ4ZK8ryDmY1yCEcACCS349VPZ1hUohvmTbyrStoZGS51qV/Hqj6IVCJaPcp2sP9+t9WhHj1cNHJdtPhBD1jU8KIVyQOxgAfKys6lV1CCFmAK8ie516SZKkeDcU7kc+KNlOF0K0ND5Z0v/9W+SOBYdRBEdVsR7IRfaQzxFC6IwvlDz+EjkdIg3YWCMjvH9R7tM1zP18nxbKugLVgxDiG+BZIB/YAhQhe6dskQt6RkiSpK+xAd7DCCEGAatKfj0EnL7BruckSVJWJqxmTHpevyxJ0swaHs49jxDiM2Aq8mqD+5FDwW0A41Ls3e71/MyaRAgxHvgJub1kPPLkRyB7xOsCBch9+FfW1BjvdoQQwfwroAGaIhfNXkRecAwASZLalXmfcp+uJG71M7jf79NKzng1IUnSRCHELuB/yHmzauAc8DPwrTLbrlJMcy9DSn7KYwfKMuEK9ziSJL0shNgDPI+8mqAl8oIms5E9f+XlkitUEpIk/SaEOIncc78z0LvkpThkkT77fsiRrWJsgbblPH/TDjXKfbpSudXP4L6+TyuecQUFBQUFBQUFBYUaQskZV1BQUFBQUFBQUKghFDGuoKCgoKCgoKCgUEMoYlxBQUFBQUFBQUGhhlDEuIKCgoKCgoKCgkINoYhxBQUFBQUFBQUFhRpCEeMKCgoKCgoKCgoKNYQixhUUFBQUFBQUFBRqCEWMKygoKCgoKCgoKNQQihhXUFBQUFBQUFBQqCEUMa6goKCgoKCgoKBQQ/wff0w5/G7xynMAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "samp=200\n", - "t=np.linspace(0,4*np.pi,samp)\n", - "\n", - "vecs={}\n", - "vecs['00']=np.array([1,0,0,0])\n", - "vecs['01']=np.array([0,1,0,0])\n", - "vecs['10']=np.array([0,0,1,0])\n", - "vecs['11']=np.array([0,0,0,1])\n", - "\n", - "gamma=0#np.random.rand()*2*np.pi\n", - "vZ=1/np.sqrt(4)*np.array([1+1j,1-1j])\n", - "vZ2=1/np.sqrt(4)*np.array([1-1j,1+1j])\n", - "vecs['++']=np.kron(vZ,vZ2)\n", - "\n", - "marker=['o','p','*','v','s','x']\n", - "markersize=[10,6,8,12,10,8]\n", - "# fillstyle=['top','bottom','left','right']\n", - "\n", - "n=2\n", - "i_str='++'\n", - "mi=-1\n", - "pl.figure(1,figsize=(12,6))\n", - "pl.figure(2,figsize=(12,6))\n", - "pl.figure(3,figsize=(12,6))\n", - "pl.figure(4,figsize=(12,6))\n", - "for mode in [\"standard\", \"nearest_int\", \"nearest_int_cyclic\", \"full\"]:\n", - " print(T[mode])\n", - " mi+=1\n", - " yy1=np.zeros_like(t)\n", - " yy2=np.zeros_like(t)\n", - " yy3=np.zeros_like(t)\n", - " yy4=np.zeros_like(t)\n", - " for i in range(samp):\n", - " eT=expm(-1j*t[i]*T[mode])\n", - " v1=eT.dot(vecs[i_str])\n", - "# v2=vecs[j_str]\n", - "# y[mode][i_str+\"<->\"+j_str][i]=np.abs(np.vdot(v1,v2))**2\n", - "# print(np.vdot(v1[0],v1[0]))\n", - " yy1[i]=np.abs(np.vdot(v1[0],v1[0]))**2\n", - " yy2[i]=np.abs(np.vdot(v1[1],v1[1]))**2\n", - " yy3[i]=np.abs(np.vdot(v1[2],v1[2]))**2\n", - " yy4[i]=np.abs(np.vdot(v1[3],v1[3]))**2\n", - " pl.figure(1)\n", - " pl.plot(t,yy1,label=mode,marker=marker[mi],fillstyle='none',markersize=markersize[mi])\n", - " pl.figure(2)\n", - " pl.plot(t,yy2,label=mode,marker=marker[mi],fillstyle='none',markersize=markersize[mi])\n", - " pl.figure(3)\n", - " pl.plot(t,yy3,label=mode,marker=marker[mi],fillstyle='none',markersize=markersize[mi])\n", - " pl.figure(4)\n", - " pl.plot(t,yy4,label=mode,marker=marker[mi],fillstyle='none',markersize=markersize[mi])\n", - "# print(mode,np.vdot(v1,v2))\n", - "pl.legend(loc=7)\n", - "\n", - " \n", - " \n", - " \n", - "\n", - "# count=-1\n", - "# i_str='++'\n", - "# for j in range(4):\n", - "# j_str=states[j]\n", - "# count+=1\n", - "# pl.figure(count,figsize=(12,6))\n", - "# pl.title(i_str+\"<->\"+j_str)\n", - "# mi=-1\n", - "# for mode in [\"standard\", \"nearest_int\", \"nearest_int_cyclic\", \"full\"]:\n", - "# mi+=1\n", - "# pl.plot(t,y[mode][i_str+\"<->\"+j_str],label=mode,marker=marker[mi],fillstyle='none',markersize=markersize[mi])\n", - "# pl.legend()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6c89adf7", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4533f61e", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 41, - "id": "d028b920", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[1, 2, 1, 3, 1, 2, 1, 4, 1, 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "n=8\n", - "x=[]\n", - "for i in range(2**n):\n", - " j=(i+1)%2**n\n", - " s1=\"{0:b}\".format(i).zfill(n)\n", - " s2=\"{0:b}\".format(j).zfill(n)\n", - " d=hamming(s1,s2)\n", - " x.append(d)\n", - "# print(s1,s2,d)\n", - "import matplotlib.pyplot as pl\n", - "pl.figure(figsize=(16,4))\n", - "pl.plot(x)\n", - "print(x)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "706f830e", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.7" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/maxkcut.py b/maxkcut.py deleted file mode 100644 index 627ede7..0000000 --- a/maxkcut.py +++ /dev/null @@ -1,579 +0,0 @@ -from qiskit import QuantumRegister, ClassicalRegister, QuantumCircuit, execute -import numpy as np -import math - -import sys -sys.path.append('../') - -from qiskit_utilities.utilities import * - -def binstringToLabels_MaxKCut(k_cuts,num_V,binstring): - k_bits = kBits_MaxKCut(k_cuts) - label_list = [int(binstring[j*k_bits:(j+1)*k_bits], 2) for j in range(num_V)] - label_string = '' - for label in label_list: - label_string += str(label) - return label_string - -def kBits_MaxKCut(k_cuts): - return int(np.ceil(np.log2(k_cuts))) - -def cost_MaxCut(labels, G, k_cuts): - C = 0 - for edge in G.edges(): - i = int(edge[0]) - j = int(edge[1]) - li=min(k_cuts-1,int(labels[i]))## e.g. for k_cuts=3, labels 2 and 3 should be equal - lj=min(k_cuts-1,int(labels[j]))## e.g. for k_cuts=3, labels 2 and 3 should be equal - if li != lj: - w = G[edge[0]][edge[1]]['weight'] - C += w - return C - - - -def validcoloring_onehot(s): - num_ones=0 - for i in range(len(s)): - num_ones+=int(s[i]) - if num_ones>1: - break - val = True - if num_ones!=1: - val = False - return val - -def validstring_onehot(s,num_V): - if len(s)%num_V!=0: - raise Exception("inconsistent lenght") - l=int(len(s)/num_V) - vale = True - for i in range(num_V): - ss=s[i*l:i*l+l] - val=validcoloring_onehot(ss) - #print(ss,val) - if not val: - break - return val - -def getcolor(s): - for i in range(len(s)): - if int(s[i])==1: - return i - return -1 - -def binstringToLabels_MaxKCut_onehot(labels, num_V, k_cuts): - l=int(len(labels)/num_V) - label_string='' - for i in range(num_V): - ss=labels[i*l:i*l+l] - label_string+=str(getcolor(ss)) - return label_string - -def measurementStatistics_MaxCut_onehot(experiment_results, options=None): - """ - Calculates the expectation and variance of the cost function. If - results from multiple circuits are used as input, each circuit's - expectation value is returned. - :param experiment_results: Input on the form execute(...).result().results - :param G: The graph on which the cost function is defined. - :return: Lists of expectation values and variances - """ - - G = options.get('G', None) - k_cuts = options.get('k_cuts', None) - if G == None or k_cuts == False: - raise Exception("Please specify options G and k_cuts") - - cost_best = -np.inf - - expectations = [] - variances = [] - num_V = G.number_of_nodes() - for result in experiment_results: - n_shots = result.shots - counts = result.data.counts - - E = 0 - E2 = 0 - for hexkey in list(counts.keys()): - count = counts[hexkey] - binstring = "{0:b}".format(int(hexkey,0)).zfill(num_V*k_cuts) - if validstring_onehot(binstring, num_V): - labels = binstringToLabels_MaxKCut_onehot(binstring, num_V, k_cuts) - cost = cost_MaxCut(labels,G, k_cuts) - cost_best = max(cost_best, cost) - E += cost*count; - E2 += cost**2*count; - - if n_shots == 1: - v = 0 - else: - v = (E2-E**2)*n_shots/(n_shots-1) - expectations.append(E/n_shots) - variances.append(v) - return expectations, variances, cost_best - -def createCircuit_MaxCut(x, depth, options=None): - - G = options.get('G', None) - k_cuts = options.get('k_cuts', None) - version = options.get('version', 1) - usebarrier = options.get('usebarrier', False) - name = options.get('name', None) - - num_V = G.number_of_nodes() - k_bits = kBits_MaxKCut(k_cuts) - if version==2: - if k_cuts==2: - Hij = np.array((-1, 1, - 1,-1,)) - elif k_cuts==3: - Hij = np.array((-1, 1, 1, 1, - 1,-1, 1, 1, - 1, 1,-1,-1, - 1, 1,-1,-1)) - elif k_cuts==4: - Hij = np.array((-1, 1, 1, 1, - 1,-1, 1, 1, - 1, 1,-1, 1, - 1, 1, 1,-1)) - elif k_cuts==5: - Hij = np.array((-1, 1, 1, 1, 1, 1, 1, 1, - 1,-1, 1, 1, 1, 1, 1, 1, - 1, 1,-1, 1, 1, 1, 1, 1, - 1, 1, 1,-1, 1, 1, 1, 1, - 1, 1, 1, 1,-1,-1,-1,-1, - 1, 1, 1, 1,-1,-1,-1,-1, - 1, 1, 1, 1,-1,-1,-1,-1, - 1, 1, 1, 1,-1,-1,-1,-1)) - elif k_cuts==6: - Hij = np.array((-1, 1, 1, 1, 1, 1, 1, 1, - 1,-1, 1, 1, 1, 1, 1, 1, - 1, 1,-1, 1, 1, 1, 1, 1, - 1, 1, 1,-1, 1, 1, 1, 1, - 1, 1, 1, 1,-1, 1, 1, 1, - 1, 1, 1, 1, 1,-1,-1,-1, - 1, 1, 1, 1, 1,-1,-1,-1, - 1, 1, 1, 1, 1,-1,-1,-1)) - elif k_cuts==7: - Hij = np.array((-1, 1, 1, 1, 1, 1, 1, 1, - 1,-1, 1, 1, 1, 1, 1, 1, - 1, 1,-1, 1, 1, 1, 1, 1, - 1, 1, 1,-1, 1, 1, 1, 1, - 1, 1, 1, 1,-1, 1, 1, 1, - 1, 1, 1, 1, 1,-1, 1, 1, - 1, 1, 1, 1, 1, 1,-1,-1, - 1, 1, 1, 1, 1, 1,-1,-1)) - elif k_cuts==8: - Hij = np.array((-1, 1, 1, 1, 1, 1, 1, 1, - 1,-1, 1, 1, 1, 1, 1, 1, - 1, 1,-1, 1, 1, 1, 1, 1, - 1, 1, 1,-1, 1, 1, 1, 1, - 1, 1, 1, 1,-1, 1, 1, 1, - 1, 1, 1, 1, 1,-1, 1, 1, - 1, 1, 1, 1, 1, 1,-1, 1, - 1, 1, 1, 1, 1, 1, 1,-1)) - else: - raise Exception("Circuit creation for k=",k_cuts," not implemented for version 2 (hard coded).") - - # we need 2 auxillary qubits if k is not a power of two - num_aux=0 - k_is_power_of_two = math.log(k_cuts, 2).is_integer() - if version==1 and not k_is_power_of_two: - num_aux=2 - ind_a1=num_V * k_bits + num_aux - 2 - ind_a2=num_V * k_bits + num_aux - 1 - - q = QuantumRegister(num_V * k_bits + num_aux) - c = ClassicalRegister(num_V * k_bits) - circ = QuantumCircuit(q, c, name=name) - circ.h(range(num_V * k_bits)) - - if usebarrier: - circ.barrier() - for d in range(depth): - gamma = x[2 * d] - beta = x[2 * d + 1] - if version==2: - for edge in G.edges(): - i = int(edge[0]) - j = int(edge[1]) - w = G[edge[0]][edge[1]]['weight'] - wg = w * gamma - I = i * k_bits - J = j * k_bits - ind_Hij = [i_ for i_ in range(I, I+k_bits)] - for j_ in range(J,J+k_bits): - ind_Hij.append(j_) - U = np.diag(np.exp(-1j * (-wg) / 2 * Hij)) - circ.unitary(U, ind_Hij, 'Hij('+"{:.2f}".format(wg)+")") - else: - if k_cuts == 2: - for edge in G.edges(): - i = int(edge[0]) - j = int(edge[1]) - w = G[edge[0]][edge[1]]['weight'] - wg = w * gamma - circ.cx(q[i], q[j]) - circ.rz(wg, q[j]) - circ.cx(q[i], q[j]) - # this is an equivalent implementation: - # circ.cu1(-2 * wg, i, j) - # circ.u1(wg, i) - # circ.u1(wg, j) - if usebarrier: - circ.barrier() - elif k_is_power_of_two: - for edge in G.edges(): - i = int(edge[0]) - j = int(edge[1]) - w = G[edge[0]][edge[1]]['weight'] - wg = w * gamma - I = i * k_bits - J = j * k_bits - for k in range(k_bits): - circ.cx(I + k, J + k) - circ.x(J + k) - Cn_U3_0theta0(circ, [J-1+ind for ind in range(1,k_bits)], J+k_bits-1, -wg) - for k in reversed(range(k_bits)): - circ.x(J + k) - circ.cx(I + k, J + k) - if usebarrier: - circ.barrier() - elif k_cuts == 3: - for edge in G.edges(): - i = int(edge[0]) - j = int(edge[1]) - w = G[edge[0]][edge[1]]['weight'] - wg = w * gamma - I = i * k_bits - J = j * k_bits - - for k in range(k_bits): - circ.cx(I + k, J + k) - circ.x(J + k) - Cn_U3_0theta0(circ, [J-1+ind for ind in range(1,k_bits)], J+k_bits-1, -wg) - for k in reversed(range(k_bits)): - circ.x(J + k) - circ.cx(I + k, J + k) - if usebarrier: - circ.barrier() - circ.x(I) - circ.ccx(I,I+1,ind_a1) - circ.ccx(J,J+1,ind_a2) - Cn_U3_0theta0(circ, [ind_a1, ind_a2], J+k_bits-1, -wg) - circ.ccx(J,J+1,ind_a2) - circ.ccx(I,I+1,ind_a1) - circ.x(I) - if usebarrier: - circ.barrier() - circ.x(J) - circ.ccx(I,I+1,ind_a1) - circ.ccx(J,J+1,ind_a2) - Cn_U3_0theta0(circ, [ind_a1, ind_a2], J+k_bits-1, -wg) - circ.ccx(J,J+1,ind_a2) - circ.ccx(I,I+1,ind_a1) - circ.x(J) - - if usebarrier: - circ.barrier() - elif k_cuts >= 5 and k_cuts<=7: - tt={} - tt[0]=[False,False,False] - tt[1]=[True,False,False] - tt[2]=[False,True,False] - tt[3]=[True,True,False] - tt[4]=[False,False,True] - for edge in G.edges(): - i = int(edge[0]) - j = int(edge[1]) - w = G[edge[0]][edge[1]]['weight'] - wg = w * gamma - I = i * k_bits - J = j * k_bits - - for k in range(k_bits): - circ.cx(I + k, J + k) - circ.x(J + k) - Cn_U3_0theta0(circ, [J-1+ind for ind in range(1,k_bits)], J+k_bits-1, -wg) - for k in reversed(range(k_bits)): - circ.x(J + k) - circ.cx(I + k, J + k) - - if usebarrier: - circ.barrier() - - n=2**k_bits-k_cuts+1 - for fi in range(n): - for fj in range(n): - if fi==fj: - continue - itt=-1 - for apply in tt[fi]: - itt+=1 - if apply: - circ.x(I+itt) - jtt=-1 - for apply in tt[fj]: - jtt+=1 - if apply: - circ.x(J+jtt) - circ.mcx([I,I+1,I+2],ind_a1) - circ.mcx([J,J+1,J+2],ind_a2) - Cn_U3_0theta0(circ, [ind_a1, ind_a2], J+k_bits-1, -wg) - circ.mcx([J,J+1,J+2],ind_a2) - circ.mcx([I,I+1,I+2],ind_a1) - itt=-1 - for apply in tt[fi]: - itt+=1 - if apply: - circ.x(I+itt) - jtt=-1 - for apply in tt[fj]: - jtt+=1 - if apply: - circ.x(J+jtt) - if usebarrier: - circ.barrier() - - if usebarrier: - circ.barrier() - else: - raise Exception("Circuit creation for k=",k_cuts," not implemented for version 1 (decomposed).") - - circ.rx(-2 * beta, range(num_V * k_bits)) - if usebarrier: - circ.barrier() - if version == 1 and not k_is_power_of_two: - circ.measure(q[:-2], c) - else: - circ.measure(q, c) - return circ - -def createCircuit_MaxCut_onehot(x, depth, options=None): - - G = options.get('G', None) - k_cuts = options.get('k_cuts', None) - alpha = options.get('alpha', None) - version = options.get('version', 2) - usebarrier = options.get('usebarrier', False) - name = options.get('name', None) - - #W=np.zeros(2**k_cuts) - #for i in range(k_cuts): - # bs='0b' - # for j in range(k_cuts): - # if i == j: - # bs+="1" - # else: - # bs+="0" - # ind=int(bs, 2) - # W[ind]=1 - #W = W/np.sqrt(k_cuts) - - num_V = G.number_of_nodes() - - num_qubits = num_V * k_cuts - - q = QuantumRegister(num_qubits) - c = ClassicalRegister(num_qubits) - circ = QuantumCircuit(q, c, name=name) - if version==1: - circ.h(range(num_qubits)) - else: - for v in range(num_V): - I = v*k_cuts - Wn(circ, [i for i in range(I, I+k_cuts)]) - #circ.initialize(W, [q[i] for i in range(I, I+k_cuts)]) - - if usebarrier: - circ.barrier() - for d in range(depth): - gamma = x[2 * d] - beta = x[2 * d + 1] - # the objective Hamiltonian - for edge in G.edges(): - i = int(edge[0]) - j = int(edge[1]) - w = G[edge[0]][edge[1]]['weight'] - wg = w * gamma - I = k_cuts * i - J = k_cuts * j - for k in range(k_cuts): - circ.cx(q[I+k], q[J+k]) - circ.rz(wg, q[J+k]) - circ.cx(q[I+k], q[J+k]) - if usebarrier: - circ.barrier() - # the penalty Hamiltonian - if alpha != None: - for v in range(num_V): - I = v*k_cuts - for i in range(k_cuts): - for j in range(i+1,k_cuts): - circ.cx(q[I+i], q[I+j]) - circ.rz(gamma*alpha, q[I+j]) - #circ.rz(alpha, q[I+j]) - circ.cx(q[I+i], q[I+j]) - if usebarrier: - circ.barrier() - if version==1: - circ.rx(-2 * beta, range(num_qubits)) - if usebarrier: - circ.barrier() - else: - for v in range(num_V): - I = v*k_cuts - ## odd - for i in range(0,k_cuts-1,2): - circ.rxx(-2 * beta, q[I+i], q[I+i+1]) - circ.ryy(-2 * beta, q[I+i], q[I+i+1]) - ## even - for i in range(1,k_cuts,2): - circ.rxx(-2 * beta, q[I+i], q[I+(i+1)%k_cuts]) - circ.ryy(-2 * beta, q[I+i], q[I+(i+1)%k_cuts]) - # final - if k_cuts%2==1: - circ.rxx(-2 * beta, q[I+k_cuts-1], q[I]) - circ.ryy(-2 * beta, q[I+k_cuts-1], q[I]) - if usebarrier: - circ.barrier() - - circ.measure(q, c) - return circ - - -def find_max_cut_brute_force(G, k_cuts): - if (len(G) > 30): - raise Exception("Too many solutions to enumerate.") - num_V = G.number_of_nodes() - k_bits = kBits_MaxKCut(k_cuts) - maxcut = [] - maxcut_value = 0 - for i in range((2*k_cuts) ** num_V): - binstring = "{0:b}".format(i).zfill(num_V * k_bits) - labels = binstringToLabels_MaxKCut(k_cuts, num_V, binstring) - max_bin = int(max(labels)) - if max_bin>=k_cuts: - continue - cost = cost_MaxCut(labels, G, k_cuts) - if (cost >= maxcut_value): - maxcut = labels - maxcut_value = cost - if i % 1024 == 0: - print(i / (2*k_cuts) ** num_V * 100, "%", end='\r') - return maxcut_value, maxcut - -def listSortedCosts_MaxCut(G, k_cuts): - costs={} - num_V = G.number_of_nodes() - k_bits = kBits_MaxKCut(k_cuts) - for i in range((2*k_cuts) ** num_V): - binstring="{0:b}".format(i).zfill(k_bits * num_V) - label_string = binstringToLabels_MaxKCut(k_cuts, num_V, binstring) - max_bin = int(max(label_string)) - if max_bin>=k_cuts: - continue - costs[label_string]=cost_MaxCut(label_string, G, k_cuts) - if i % 1024 == 0: - print(i / (2*k_cuts) ** num_V * 100, "%", end='\r') - sortedcosts={k: v for k, v in sorted(costs.items(), key=lambda item: item[1])} - return sortedcosts - -#def costsHist_MaxCut(G, k_cuts): -# num_V = G.number_of_nodes() -# costs=np.ones(k_cuts ** num_V) -# k_bits = kBits_MaxKCut(k_cuts) -# for i in range(k_cuts**num_V): -# binstring="{0:b}".format(i).zfill(num_V * k_bits) -# label_string = binstringToLabels_MaxKCut(k_cuts, num_V, binstring) -# costs[i]= cost_MaxCut(label_string,G, k_cuts) -# return costs - -def costsHist_MaxCut(G, k_cuts): - if k_cuts!=2: - raise Exception("k_cuts must be equal to 2") - num_V = G.number_of_nodes() - costs=np.ones(2**num_V) - for i in range(2**num_V): - if i%1024*2*2*2==0: - print(i/2**num_V*100, "%", end='\r') - binstring="{0:b}".format(i).zfill(num_V) - y=[int(i) for i in binstring] - costs[i]=cost_MaxCut(y,G, k_cuts) - print("100%") - return costs - - -def bins_comp_basis(data, G, k_cuts): - if k_cuts != 2: - raise Exception("bins_comp_basis not implemented for k_cuts!=2") - max_solutions=[] - num_V = G.number_of_nodes() - bins_states = np.zeros(2**num_V) - num_shots=0 - num_solutions=0 - max_cost=0 - average_cost=0 - for item, binary_rep in enumerate(data): - integer_rep=int(str(binary_rep), 2) - counts=data[str(binary_rep)] - bins_states[integer_rep] += counts - num_shots+=counts - num_solutions+=1 - y=[int(i) for i in str(binary_rep)] - lc = cost_MaxCut(y,G, k_cuts) - if lc==max_cost: - max_solutions.append(y) - elif lc>max_cost: - max_solutions=[] - max_solutions.append(y) - max_cost=lc - average_cost+=lc*counts - return bins_states, max_cost, average_cost/num_shots, max_solutions - - -def measurementStatistics_MaxCut(experiment_results, options=None): - """ - Calculates the expectation and variance of the cost function. If - results from multiple circuits are used as input, each circuit's - expectation value is returned. - :param experiment_results: Input on the form execute(...).result().results - :param G: The graph on which the cost function is defined. - :return: Lists of expectation values and variances - """ - - G = options.get('G', None) - k_cuts = options.get('k_cuts', None) - if G == None or k_cuts == False: - raise Exception("Please specify options G and k_cuts") - - k_bits = kBits_MaxKCut(k_cuts) - cost_best = -np.inf - - expectations = [] - variances = [] - num_V = G.number_of_nodes() - for result in experiment_results: - n_shots = result.shots - counts = result.data.counts - - E = 0 - E2 = 0 - for hexkey in list(counts.keys()): - count = counts[hexkey] - binstring = "{0:b}".format(int(hexkey,0)).zfill(num_V*k_bits) - labels = binstringToLabels_MaxKCut(k_cuts,num_V,binstring) - cost = cost_MaxCut(labels,G, k_cuts) - cost_best = max(cost_best, cost) - E += cost*count/n_shots; - E2 += cost**2*count/n_shots; - - if n_shots == 1: - v = 0 - else: - v = (E2-E**2)*n_shots/(n_shots-1) - expectations.append(E) - variances.append(v) - return expectations, variances, cost_best diff --git a/maxkcut_unittests.py b/maxkcut_unittests.py deleted file mode 100644 index f5ada46..0000000 --- a/maxkcut_unittests.py +++ /dev/null @@ -1,150 +0,0 @@ -import unittest -from maxkcut import * -import numpy as np -from qiskit import * - -class TestMaxKCut(unittest.TestCase): - - def test_kBits_MaxKCut(self): - self.assertEqual(kBits_MaxKCut(2), 1) - self.assertEqual(kBits_MaxKCut(3), 2) - self.assertEqual(kBits_MaxKCut(4), 2) - self.assertEqual(kBits_MaxKCut(5), 3) - self.assertEqual(kBits_MaxKCut(6), 3) - self.assertEqual(kBits_MaxKCut(7), 3) - self.assertEqual(kBits_MaxKCut(8), 3) - self.assertEqual(kBits_MaxKCut(9), 4) - - def test_binstringToLabels(self): - - num_V=1 # for the case of one vertex - for k in [2,3,4,5,6,7,8,9]: - num_qbits=kBits_MaxKCut(k) - fo='{0:0'+str(num_qbits)+'b}' - for i in range(k): - i_binstring=fo.format(i) - self.assertEqual(binstringToLabels_MaxKCut(k, num_V, i_binstring), str(i)) - - num_V=2 # for the case of two vertices - for k in [2,3,4,5,6,7,8,9]: - num_qbits=kBits_MaxKCut(k) - fo='{0:0'+str(num_qbits)+'b}' - for i in range(k): - i_binstring=fo.format(i) - for j in range(k): - j_binstring=fo.format(j) - self.assertEqual(binstringToLabels_MaxKCut(k, num_V, i_binstring+j_binstring), str(i)+str(j)) - - num_V=3 # for the case of two vertices - for k in [2,3,4,5,6,7,8,9]: - num_qbits=kBits_MaxKCut(k) - fo='{0:0'+str(num_qbits)+'b}' - for i in range(k): - i_binstring=fo.format(i) - for j in range(k): - j_binstring=fo.format(j) - for h in range(k): - h_binstring=fo.format(h) - self.assertEqual(binstringToLabels_MaxKCut(k, num_V, i_binstring+j_binstring+h_binstring), str(i)+str(j)+str(h)) - - def test_getcolor(self): - - self.assertEqual(getcolor("00"), -1) - - self.assertEqual(getcolor("10"), 0) - self.assertEqual(getcolor("01"), 1) - - self.assertEqual(getcolor("100"), 0) - self.assertEqual(getcolor("010"), 1) - self.assertEqual(getcolor("001"), 2) - - def test_binstringToLabels_MaxKCut_onehot(self): - - num_V=1 - k=2 - self.assertEqual(binstringToLabels_MaxKCut_onehot("10", num_V, k), "0") - self.assertEqual(binstringToLabels_MaxKCut_onehot("01", num_V, k), "1") - - k=3 - self.assertEqual(binstringToLabels_MaxKCut_onehot("100", num_V, k), "0") - self.assertEqual(binstringToLabels_MaxKCut_onehot("010", num_V, k), "1") - self.assertEqual(binstringToLabels_MaxKCut_onehot("001", num_V, k), "2") - - num_V=2 - k=2 - self.assertEqual(binstringToLabels_MaxKCut_onehot("1001", num_V, k), "01") - self.assertEqual(binstringToLabels_MaxKCut_onehot("0101", num_V, k), "11") - self.assertEqual(binstringToLabels_MaxKCut_onehot("0110", num_V, k), "10") - self.assertEqual(binstringToLabels_MaxKCut_onehot("1010", num_V, k), "00") - - k=3 - self.assertEqual(binstringToLabels_MaxKCut_onehot("100100", num_V, k), "00") - self.assertEqual(binstringToLabels_MaxKCut_onehot("010100", num_V, k), "10") - self.assertEqual(binstringToLabels_MaxKCut_onehot("001100", num_V, k), "20") - self.assertEqual(binstringToLabels_MaxKCut_onehot("100010", num_V, k), "01") - self.assertEqual(binstringToLabels_MaxKCut_onehot("010010", num_V, k), "11") - self.assertEqual(binstringToLabels_MaxKCut_onehot("001010", num_V, k), "21") - self.assertEqual(binstringToLabels_MaxKCut_onehot("100001", num_V, k), "02") - self.assertEqual(binstringToLabels_MaxKCut_onehot("010001", num_V, k), "12") - self.assertEqual(binstringToLabels_MaxKCut_onehot("001001", num_V, k), "22") - - - def test_validcoloring_onehot(self): - - self.assertEqual(validstring_onehot("00",1), False) - self.assertEqual(validstring_onehot("01",1), True) - self.assertEqual(validstring_onehot("10",1), True) - self.assertEqual(validstring_onehot("11",1), False) - - self.assertEqual(validstring_onehot("0000",2), False) - self.assertEqual(validstring_onehot("0001",2), False) - self.assertEqual(validstring_onehot("0010",2), False) - self.assertEqual(validstring_onehot("0011",2), False) - self.assertEqual(validstring_onehot("0100",2), False) - self.assertEqual(validstring_onehot("0101",2), True) - self.assertEqual(validstring_onehot("0110",2), True) - self.assertEqual(validstring_onehot("0111",2), False) - self.assertEqual(validstring_onehot("1000",2), False) - self.assertEqual(validstring_onehot("1001",2), True) - self.assertEqual(validstring_onehot("1010",2), True) - self.assertEqual(validstring_onehot("1011",2), False) - self.assertEqual(validstring_onehot("1100",2), False) - self.assertEqual(validstring_onehot("1101",2), False) - self.assertEqual(validstring_onehot("1110",2), False) - self.assertEqual(validstring_onehot("1111",2), False) - - self.assertEqual(validstring_onehot("001100",3), False) - self.assertEqual(validstring_onehot("001100",2), True) - - def test_validcoloring_onehot(self): - - backend_sv = Aer.get_backend('statevector_simulator') - - for k_cuts in [2,3,4,5,6,7,8]: - q = QuantumRegister(k_cuts) - c = ClassicalRegister(k_cuts) - circ = QuantumCircuit(q, c) - Wn(circ, [i for i in range(k_cuts)]) - circ.draw() - job = execute(circ, backend_sv) - result = job.result() - outputstate = result.get_statevector(circ) - sv1=qiskit.quantum_info.Statevector(outputstate) - - W=np.zeros(2**k_cuts) - for i in range(k_cuts): - bs='0b' - for j in range(k_cuts): - if i == j: - bs+="1" - else: - bs+="0" - ind=int(bs, 2) - W[ind]=1 - W = W/np.sqrt(k_cuts) - sv2=qiskit.quantum_info.Statevector(W) - - self.assertEqual(sv1.equiv(sv2), True) - -if __name__ == '__main__': - unittest.main() diff --git a/mixers.py b/mixers.py deleted file mode 100644 index 5705cf3..0000000 --- a/mixers.py +++ /dev/null @@ -1,538 +0,0 @@ -import numpy as np -from sympy.physics.quantum import TensorProduct -from sympy.physics.paulialgebra import Pauli, evaluate_pauli_product -from binsymbols import * -from sympy import * -import itertools -import math - -X=Pauli(1) -Y=Pauli(2) -Z=Pauli(3) -I=1 - -def all_states(n): - return [''.join(i) for i in itertools.product('01', repeat= n)] - -def hamming(s1, s2): - return sum(c1 != c2 for c1, c2 in zip(s1, s2)) - -def get_T(n, mode, d=1,i=None,j=None, shift=1, oddeven="both"): - if mode=="leftright": - T=np.zeros((n,n)) - if isinstance(i,list): - if not len(i)==len(j): - raise ValueError('mode "'+mode+'": lenght of index lists must be equal') - for ind in range(len(i)): - T[i[ind],j[ind]]=1 - T[j[ind],i[ind]]=1 - else: - T[i,j]=1 - T[j,i]=1 - elif mode=="full": - T=np.ones((n,n)) - for i in range(n): - T[i,i]=0 - elif mode=="nearest_int": - T=np.zeros((n,n)) - for i in range(n-shift): - if oddeven=="even" and i%2==0: - continue - elif oddeven=="odd" and i%2==1: - continue - T[i,i+shift]=1 - T[i+shift,i]=1 - elif mode=="nearest_int_cyclic": - T=np.zeros((n,n)) - for i in range(n-1): - if oddeven=="even" and i%2==0: - continue - elif oddeven=="odd" and i%2==1: - continue - T[i,i+1]=1 - T[i+1,i]=1 - if not oddeven=="even": - T[0,-1]=1 - T[-1,0]=1 - elif mode=="random": - T=np.random.rand(n,n) - for i in range(0,n): - for j in range(i,n): - T[i,j]=T[j,i] - elif mode=="standard" or mode=="Hamming": - ispowertwo=(n & (n-1) == 0) and n !=0 - if not ispowertwo: - raise ValueError('mode "'+mode+'" needs n to be a power of two') -#def T_full_standard_mixer(n,d=1): - T=np.zeros((n,n)) - log2n=int(np.log2(n)) - for i in range(n): - for j in range(n): - s1="{0:b}".format(i).zfill(log2n) - s2="{0:b}".format(j).zfill(log2n) - if hamming(s1,s2)==d: - T[i,j]=1 - else: - raise NotImplementedError('mode "'+mode+'" not implemented') - - return T - -def T_sum_Hamming_distance(T): - val=0 - val2=0 - n=T.shape[0] - for i in range(n): - for j in range(n): - if not math.isclose(T[i,j],0,abs_tol=1e-7): - s1="{0:b}".format(i).zfill(n) - s2="{0:b}".format(j).zfill(n) - tmp=hamming(s1,s2) - if tmp>1: - val2+=tmp - else: - val2+=tmp/10 - val += tmp - return val, val2 - - -class PauliStringTP: - def __init__(self, excludeI=False): - self.excludeI=excludeI - self.items=[] - def get_items_PS(self,tp): - if isinstance(tp,Pauli): - if not self.excludeI: - self.items.append(tp) - elif not tp==I: - self.items.append(tp) - else: - tpL,tpR=tp.args - if isinstance(tpL, TensorProduct): - self.get_items_PS(tpL) - else: - if not self.excludeI: - self.items.append(tpL) - elif not tpL==I: - self.items.append(tpL) - if isinstance(tpR, TensorProduct): - self.get_items_PS(tpR) - else: - if not self.excludeI: - self.items.append(tpR) - elif not tpR==I: - self.items.append(tpR) - -def HtoString(H, symbolic=False): - ret='' - for item in H.args:### go through all items of the sum (Pauli strings) - if isinstance(item, Mul):### remove float - if symbolic: - fval,_,item = item.args - else: - if len(item.args)>2: - fval,tmp,item = item.args - if not math.isclose(fval,0,abs_tol=1e-7): - raise AssertionError("Encountered imaginary part that is not close to zero, aborting!", fval, tmp, item) - else: - fval,item = item.args - if math.isclose(fval,0,abs_tol=1e-7): - item=None - print("depug: close to zero", fval, item) - ret+=f'{fval:+.2f}'+" " - if isinstance(item, TensorProduct) or isinstance(item, Pauli):### go through Pauli string - tps=PauliStringTP() - tps.get_items_PS(item) - for p in tps.items: - if p==1: - ret+="I" - if p==X: - ret+="X" - if p==Y: - ret+="Y" - if p==Z: - ret+="Z" - ret+=" " - return ret - -def num_Cnot(H, symbolic=False): - sqg=0 - cnot=0 - for item in H.args:### go through all items of the sum (Pauli strings) -# print(type(item)) - if isinstance(item, Mul):### remove float - if symbolic: - fval,_,item = item.args - else: - if len(item.args)>2: - fval,tmp,item = item.args - if not math.isclose(fval,0,abs_tol=1e-7): - raise AssertionError("Encountered imaginary part that is not close to zero, aborting!", fval, tmp, item) - else: - fval,item = item.args - if math.isclose(fval,0,abs_tol=1e-7): - item=None - print("depug: close to zero", fval, item) - if isinstance(item, TensorProduct) or isinstance(item, Pauli):### go through Pauli string - tps=PauliStringTP(excludeI=True) - tps.get_items_PS(item) - tmp=len(tps.items) - if tmp==1: - sqg+=1 - elif tmp>1: - cnot+=2*(tmp-1) - return sqg,cnot - -def get_g(binstrings): - n=len(binstrings[0]) - x=binsymbols('x:'+str(n)) - expr=1 - for bs in binstrings: - tmp_expr=0 - for i in range(n): - if bs[i]=='0': - tmp_expr+=x[i] - else: - tmp_expr+=(x[i]-1)**2 - expr*=tmp_expr - return x, expand(expr) - - -def convert_to_ps(bs1, bs2): - n=len(bs1) - - for j in range(n): - if bs1[j]=="1" and bs2[j]=="0": - tmp=1/2*(X-1j*Y) - elif bs1[j]=="0" and bs2[j]=="1": - tmp=1/2*(X+1j*Y) - elif bs1[j]=="1" and bs2[j]=="1": - tmp=1/2*(I-Z) - else:# bs[j]=="0" and bs[j]=="0": - tmp=1/2*(I+Z) - if j==0: - pauli_str=tmp - else: - pauli_str=TensorProduct(pauli_str,tmp) - return pauli_str - -def get_overlap(binstringsA, binstringsB): - overlap=[] - mA=len(binstringsA) - mB=len(binstringsB) - for i in range(mA): - for j in range(mB): - if binstringsA[i] == binstringsB[j]: - overlap.append(binstringsA[i]) - return overlap - -def get_minus(binstringsA, binstringsB): - minus=[] - indices=[] - mA=len(binstringsA) - mB=len(binstringsB) - for i in range(mA): - found=False - for j in range(mB): - if binstringsA[i] == binstringsB[j]: - found=True - break - if not found: - minus.append(binstringsA[i]) - indices.append(i) - return minus, indices - -def add(binstringsA, binstringsB): - add=binstringsA.copy() - mA=len(binstringsA) - mB=len(binstringsB) - for i in range(mB): - found=False - for j in range(mA): - if binstringsA[j] == binstringsB[i]: - found=True - break - if not found: - add.append(binstringsB[i]) - return add - -def get_bitwise_negated_strings(binstrings): - n=len(binstrings[0]) - m=len(binstrings) - - binstrings_neg = [] - for i in range(m): - tmp='' - for j in range(n): - if binstrings[i][j]=="1": - tmp+="0" - else: - tmp+="1" - binstrings_neg.append(tmp) - return binstrings_neg - -def get_negated_strings(binstrings, mask): - n=len(binstrings[0]) - m=len(binstrings) - - binstrings_neg = [] - for i in range(m): - tmp='' - for j in range(n): - if mask[j]=='1': - if binstrings[i][j]=="1": - tmp+="0" - else: - tmp+="1" - else: - tmp+=binstrings[i][j] - binstrings_neg.append(tmp) - return binstrings_neg - - -def get_Pauli_string(binstrings, T, symbolic=False): - m=len(binstrings) - - pauli_str=0 - if symbolic: - for i in range(m): - for j in range(m): - tmp_ps = convert_to_ps(binstrings[i], binstrings[j]) - pauli_str+=T[i,j]*tmp_ps - else: - for i in range(m): - for j in range(m): - if not math.isclose(T[i,j],0,abs_tol=1e-7): - tmp_ps = convert_to_ps(binstrings[i], binstrings[j]) - pauli_str+=T[i,j]*tmp_ps - - return pauli_str - -def simplifyH(H): - for i in range(10): - H = H.expand(tensorproduct=True) - H=evaluate_pauli_product(H) - return H - -def get_H(stringlist,T,simplify=True, symbolic=False, verbose=False): - H=get_Pauli_string(stringlist, T, symbolic=symbolic) - if simplify: - H=simplifyH(H) - if verbose: - print("#sqg, #cnots=",num_Cnot(H, symbolic=symbolic)) - return H - -def print_info(stringlist,T,disp=True,simplify=True, disp_d=True, disp_g=True,disp_m=True, disp_H=True, disp_neg=True): - n=len(stringlist[0]) - m=len(stringlist) - - if disp_d: - print("Hamming distance=", T_sum_Hamming_distance(T)) - - H=get_Pauli_string(stringlist, T) - if simplify: - H=simplifyH(H) -# T+=eye(len(stringlist))*d -# m = Matrix(T) -# P,D = m.diagonalize() -# display(P) -# display(D) - if disp_H: - display("H=", H) - print("#sqg, #cnots=",num_Cnot(H)) - - if m<2**n: - stringlist_neg=get_bitwise_negated_strings(stringlist) - overlap = get_overlap(stringlist,stringlist_neg) - if not len(overlap)==0: - print("overlap with bitwise negated stringlist =", overlap) - else: - H_neg=get_Pauli_string(stringlist_neg, T)+H - if simplify: - H_neg=simplifyH(H_neg) - if disp_neg: - display("H+H_neg=", H_neg) - print("#sqg, #cnots=",num_Cnot(H_neg)) - - minus, m_ind = get_minus(stringlist_neg,stringlist) - if len(minus)<2: - print("minus =", minus) - else: - S = T[m_ind].T[m_ind].T ## .T is the transpose - H_minus=get_Pauli_string(minus, S)+H - if simplify: - H_minus=simplifyH(H_minus) - if disp_m: - display("H+H_minus=", H_minus) - print("#sqg, #cnots=",num_Cnot(H_minus)) - - if disp_g: - x, pen = get_g(stringlist) - - g=lambdify(x, pen, "numpy") - - print("g(x)=",pen) - print("is zero for the following bitstrings:") - l=len(stringlist[0]) - if l==1: - for y1 in [0,1]: - val = g(y1) - if val<0: - print(y1,"=",val) - if val==0: - print(y1) - elif l==2: - for y1 in [0,1]: - for y2 in [0,1]: - val = g(y1,y2) - if val<0: - print(y1,y2,"=",val) - if val==0: - print(y1,y2) - elif l==3: - for y1 in [0,1]: - for y2 in [0,1]: - for y3 in [0,1]: - val = g(y1,y2,y3) - if val<0: - print(y1,y2,y3,"=",val) - if val==0: - print(y1,y2,y3) - - -def print_info2(stringlist,T,simplify=True): - n=len(stringlist[0]) - m=len(stringlist) - - all_strings=stringlist.copy() - - H=get_Pauli_string(stringlist, T) - print("m,2**n",m,2**n) - - if m<2**n: - first=True - for mask in reversed(all_states(n)): - if first: - first=False - #continue - stringlist_neg = get_negated_strings(stringlist,mask) - minus, m_ind = get_minus(stringlist_neg,all_strings) - if len(minus)<2: - print("minus =", minus) - else: - print("add minus =", minus) - S = T[m_ind].T[m_ind].T ## .T is the transpose - H+=get_Pauli_string(minus, S) - all_strings = add(all_strings, minus) - break - - if simplify: - H=simplifyH(H) - - display("H=", H) - print("#sqg, #cnots=",num_Cnot(H)) - - -def get_Cs(B): - n=len(B[0]) - m=len(B) - Cs=[] - als=all_states(n) - for i in range(2**n): - s1=als[i] - for j in range(i+1,2**n): - s2=als[j] - C1=[s1,s2] - ol=get_overlap(C1,B) - if len(ol)==0: - Cs.append(C1) - return Cs - -def analyzeAdding(Cs,B,Tall=False): - n=len(B[0]) - m=len(B) - - Hs={} - HSs={} - Cnots={} - - if Tall: - for indi in range(m): - for indj in range(indi+1,m): - ind=str(indi)+","+str(indj) - Hs[ind]={} - HSs[ind]={} - Cnots[ind]={} - - T=get_T(len(B),mode="leftright",i=indi,j=indj) - display(T) - - HB=get_H(B,T) - Hs[ind]['B']=simplifyH(HB) - HSs[ind]['B']=HtoString(HB) - Cnots[ind]['B']=num_Cnot(HB) - - T=get_T(2,mode="nearest_int") - - - for C in Cs: - s1,s2=C - key=s1+","+s2 - HC=get_H(C,T) - Hadd=simplifyH(HB+HC) - Hs[ind][key]=Hadd - HSs[ind][key]=HtoString(Hadd) - Cnots[ind][key]=num_Cnot(Hadd) - - else: - for indi in range(m): - Hs[indi]={} - HSs[indi]={} - Cnots[indi]={} - - T=get_T(len(B),mode="leftright",i=indi,j=(indi+1)%len(B)) - display(T) - - HB=get_H(B,T) - Hs[indi]['B']=simplifyH(HB) - HSs[indi]['B']=HtoString(HB) - Cnots[indi]['B']=num_Cnot(HB) - - T=get_T(2,mode="nearest_int") - - - for C in Cs: - s1,s2=C - key=s1+","+s2 - HC=get_H(C,T) - Hadd=simplifyH(HB+HC) - Hs[indi][key]=Hadd - HSs[indi][key]=HtoString(Hadd) - Cnots[indi][key]=num_Cnot(Hadd) - if m>4: - for indi in [m,m+1]: - print(indi) - Hs[indi]={} - HSs[indi]={} - Cnots[indi]={} - - T=get_T(len(B),mode="leftright",i=indi-m,j=(indi+4)%len(B)) - display(T) - - HB=get_H(B,T) - Hs[indi]['B']=simplifyH(HB) - HSs[indi]['B']=HtoString(HB) - Cnots[indi]['B']=num_Cnot(HB) - - T=get_T(2,mode="nearest_int") - - - for C in Cs: - s1,s2=C - key=s1+","+s2 - HC=get_H(C,T) - Hadd=simplifyH(HB+HC) - Hs[indi][key]=Hadd - HSs[indi][key]=HtoString(Hadd) - Cnots[indi][key]=num_Cnot(Hadd) - - return Hs, HSs, Cnots diff --git a/plots.py b/plots.py deleted file mode 100644 index 99fb7b3..0000000 --- a/plots.py +++ /dev/null @@ -1,51 +0,0 @@ -from matplotlib import rc -import matplotlib.pyplot as plt -import matplotlib as mpl -import numpy as np - -fontsize = 24 -newparams = {'axes.titlesize': fontsize, - 'axes.labelsize': fontsize, - 'ytick.labelsize': fontsize, - 'xtick.labelsize': fontsize, - 'legend.fontsize': fontsize, - 'figure.titlesize': fontsize, - 'legend.handlelength': 1.5, - 'lines.linewidth': 2, - 'lines.markersize': 7, - 'figure.figsize': (12, 7), - 'figure.dpi':200, - 'text.usetex' : True, - 'font.family' : "sans-serif" - } - -plt.rcParams.update(newparams) - -def plot_H_prob(qaoa, SP, C, savefig = None): - - best_cost = np.max( qaoa.vector_cost(qaoa.state_strings) ) - - fig, ax = plt.subplots(figsize = (14,7)) - - ax.set_ylabel(r"$\overline{\langle H_{\mathrm{tot}} \rangle}/\min \limits_{\mathbf{x}} \langle H_{\mathrm{tot}} \rangle $", color = "black") - ax.hlines(1,1,qaoa.max_depth,color = "black", ls = "--") - ax.plot(np.arange(1,qaoa.max_depth +1, 1), C/best_cost, color = "black", ls = "-", marker = "o") - - ax.grid(ls = "--") - ax.set_xlabel("Depth, $d$") - #ax.set_yscale("log") - - ax2 = plt.twinx() - - ax2.plot(np.arange(1,qaoa.max_depth+1,1), SP, color ="blue", marker = "o") - ax2.hlines(1,1,qaoa.max_depth,color = "blue", ls = "--") - - ax2.tick_params(labelcolor = "blue") - ax2.set_ylabel(r"Probability $| \langle x^* \vert \gamma \beta \rangle |^2$", color = "blue") - - plt.tight_layout() - - if savefig != None: - fig.savefig(savefig) - else: - plt.show() diff --git a/plotting_functions_QAOA.py b/plotting_functions_QAOA.py deleted file mode 100644 index 6dac1db..0000000 --- a/plotting_functions_QAOA.py +++ /dev/null @@ -1,52 +0,0 @@ -import matplotlib.pyplot as plt -import networkx as nx -from qaoa import* - -def gamma_beta_func_of_p(p, backend, M=5, K = 20, heuristic=False, decimals=0, num_shots=8192, k_cuts=2): - fig, (ax1, ax2)= plt.subplots(nrows=2, ncols=1, sharex=True) - for i in range(M): - G = nx.random_regular_graph(3, 6) - addWeights_MaxCut(G, decimals=decimals) - MAX_COST, max_config = find_max_cut_brute_force(G, k_cuts) - print("Max cost: ", MAX_COST) - if heuristic: - params, E = optimize_INTERP(K, G, backend, p, decimals=decimals, num_shots=num_shots, k_cuts=k_cuts) - else: - params, E, temp = optimize_random(K, G, backend, p, decimals=decimals, num_shots=num_shots, k_cuts=k_cuts) - r = E/MAX_COST - print("Best approximation ratio, r = ", r) - p_list = np.arange(1, p + 1, 1) - ax1.scatter(p_list, params[0::2]/np.pi, label=r"$r = %.2f$" %(r)) - ax1.plot(p_list, params[0::2]/np.pi, linestyle="--", alpha=0.4, color="k") - ax2.scatter(p_list, params[1::2] / np.pi, label=r"$r = %.2f$" % (r)) - ax2.plot(p_list, params[1::2] / np.pi, linestyle="--", alpha=0.4, color="k") - - ax2.set_xlabel(r"$p$") - ax1.set_ylabel(r"$\gamma/\pi$") - ax2.set_ylabel(r"$\beta/\pi$") - - ax1.legend() - ax2.legend() - plt.show() - - - - -def compare_methods(K, G, backend, p_max, decimals=0, num_shots=8192, k_cuts=2): - """ - Uses K tries to find the best approx ratio for both INTERP and RI. Does this for all integer p, 1<= p <= p_max - """ - costs = costsHist_MaxCut(G, k_cuts) - MAX_COST = max(costs) - p_list = np.arange(1, p_max + 1, 1) - E_heur_list = np.zeros(len(p_list)) - E_ran_list = np.zeros(len(p_list)) - for i in range(len(p_list)): - params_heur, E_heur_list[i] = optimize_INTERP(K, G, backend, p_list[i], decimals=decimals, num_shots=num_shots, k_cuts=k_cuts) - params_ran, E_ran_list[i], temp = optimize_random(K, G, backend, p_list[i], decimals=decimals, num_shots=num_shots, k_cuts=k_cuts) - plt.plot(p_list, E_ran_list/MAX_COST, "-o", label="RI") - plt.plot(p_list, E_heur_list/MAX_COST, "-o", label="INTERP") - plt.xlabel(r"$p$") - plt.ylabel(r"$ r^{opt}$") - plt.legend() - plt.show() diff --git a/qaoa.py b/qaoa.py deleted file mode 100644 index 4e381cb..0000000 --- a/qaoa.py +++ /dev/null @@ -1,234 +0,0 @@ -from qiskit import execute -import numpy as np -import os -from scipy.optimize import minimize - -import sys -sys.path.append('../') - -from qiskit_utilities.utilities import * - -global g_it -global g_values -global g_bestvalues -global g_gammabeta - -### same as getval -#def objective_function(createCircuit, measurementStatistics, params, backend, num_shots, options=None): -# """ -# :return: minus the expectation value (in order to maximize MaxCut configuration) -# NB! If a list of circuits are run, only returns the expectation value of the first circuit. -# """ -# -# qc = createCircuit(params, int(len(params)/2), options=options) -# if backend.configuration().local: -# job = execute(qc, backend, shots=num_shots) -# else: -# job = start_or_retrieve_job(name, backend, qc, options={'shots' : num_shots}) -# res_data = job.results -# E,_,_ = measurementStatistics(res_data, options=options) -# return -E[0] - - -def getval(gammabeta, createCircuit, measurementStatistics, backend, depth, noisemodel, shots, options): - global g_it, g_values, g_bestvalues, g_gammabeta - g_it+=1 - - circuit = createCircuit(gammabeta, depth, options=options) - - if backend.configuration().local: - job = execute(circuit, backend=backend, noise_model=noisemodel, shots=shots) - else: - job = start_or_retrieve_job(name+"_"+str(g_it), backend, circuit, options={'shots' : shots}) - - val,_,bval = measurementStatistics(job.result().results, options=options) - - g_values[str(g_it)] = val[0] - g_bestvalues[str(g_it)] = bval - g_gammabeta[str(g_it)] = gammabeta - return -val[0] - -def runQAOA(createCircuit, measurementStatistics, backend, gamma_n, beta_n, gamma_max, beta_max, optmethod='COBYLA', shots=1024*2*2*2, rerun=True, maxdepth=3, options=None): - - repeats=5 - gammabetas = {} - E = {} - best = {} - name = options.get('name', "None") -### ---------------------------- -################ - depth=1 - print("depth =",depth) -################ -### ---------------------------- - print("Calculating Energy landscape...") - gamma_grid = np.linspace(0, gamma_max, gamma_n) - beta_grid = np.linspace(0, beta_max, beta_n) - - data_path = "../data/sample_graphs/" - - Elandscapefile= data_path + name+"_Elandscape.npy" - if not rerun and os.path.isfile(Elandscapefile): - Elandscape = np.load(Elandscapefile) - else: - if backend.configuration().local: - circuits=[] - for beta in beta_grid: - for gamma in gamma_grid: - options['name'] = name+"_"+str(beta_n)+"_"+str(gamma_n) - circuits.append(createCircuit(np.array((gamma,beta)), depth, options=options)) - job = execute(circuits, backend, shots=shots) - El,_,_ = measurementStatistics(job.result().results, options=options) - Elandscape = -np.array(El) - else: - Elandscape = np.zeros((beta_n, gamma_n)) - b=-1 - for beta in beta_grid: - b+=1 - g=-1 - for gamma in gamma_grid: - g+=1 - options['name'] = name+"_"+str(b)+"_"+str(g) - circuit = createCircuit(np.array((gamma,beta)), depth, options = options) - job = start_or_retrieve_job(name+"_"+str(b)+"_"+str(g), backend, circuit, options={'shots' : shots}) - #print("error message = ", job.error_message()) - #job.error_message() - e,_,_ = measurementStatistics(job.result().results, options=options) - Elandscape[b,g] = -e[0] - if not os.path.exists(data_path): - os.makedirs(data_path) - np.save(Elandscapefile, Elandscape) - print("Calculating Energy landscape done") - - ### reshape and find parameters that achieved minimal energy - if backend.configuration().local: - Elandscape = np.array(Elandscape).reshape(beta_n, gamma_n) - ind_Emin = np.unravel_index(np.argmin(Elandscape, axis=None), Elandscape.shape) - x0=np.array((gamma_grid[ind_Emin[1]], beta_grid[ind_Emin[0]])) - - ### local optimization - #cons = COBYLAConstraints_MaxCut([0,gamma_max], [0,beta_max], depth) - global g_it, g_values, g_bestvalues, g_gammabeta - g_it=0 - g_values={} - g_bestvalues={} - g_gammabeta={} - - for rep in range(repeats): - print("depth =",depth, "rep =", rep+1) - options['name'] = name+"_opt_"+str(depth) - out = minimize(getval, x0=x0, method=optmethod, args=(createCircuit, measurementStatistics, backend, depth, None, shots, options), options={'xatol': 1e-2, 'fatol': 1e-1, 'disp': True})#, constraints=cons) - ### pick the best value along the path - ind = max(g_values, key=g_values.get) - gammabetas['x0_d'+str(depth)] = x0.copy() - gammabetas['xL_d'+str(depth)] = g_gammabeta[ind].copy() - E[''+str(depth)] = g_values[ind] - best[''+str(depth)] = g_bestvalues[ind] - - while depth < maxdepth: -### ---------------------------- -################ - depth+=1 - print("depth =",depth) -################ -### ---------------------------- - - ### interpolation heuristic - inter0 = INTERP_init(gammabetas['xL_d'+str(depth-1)][::2]) - inter1 = INTERP_init(gammabetas['xL_d'+str(depth-1)][1::2]) - x0 = np.zeros((2*depth)) - x0[::2] = inter0 - x0[1::2] = inter1 - - ### local optimization - #cons = COBYLAConstraints_MaxCut([0,gamma_max], [0,beta_max], depth) - g_it=0 - g_gammabeta={} - g_values={} - g_bestvalues={} - - for rep in range(repeats): - print("depth =",depth, "rep =", rep+1) - options['name'] = name+"_opt_"+str(depth) - out = minimize(getval, x0=x0, method=optmethod, args=(createCircuit, measurementStatistics, backend, depth, None, shots, options), options={'xatol': 1e-2, 'fatol': 1e-1, 'disp': True})#, constraints=cons) - ### pick the best value along the path - ind = max(g_values, key=g_values.get) - gammabetas['x0_d'+str(depth)] = x0.copy() - gammabetas['xL_d'+str(depth)] = g_gammabeta[ind].copy() - E[''+str(depth)] = g_values[ind] - best[''+str(depth)] = g_bestvalues[ind] - - return Elandscape, gammabetas, E, best - - -def INTERP_init(params_prev_step): - """ - Takes the optimal parameters at level p as input and returns the optimal inital guess for - the optimal paramteres at level p+1. Uses the INTERP formula from the paper by Zhou et. al - :param params_prev_step: optimal parameters at level p - :return: - """ - print("P=",params_prev_step) - p = params_prev_step.shape[0] - params_out_list = np.zeros(p+1) - params_out_list[0] = params_prev_step[0] - for i in range(2, p + 1): - # Next line is clunky, but written this way to accommodate the 1-indexing in the paper - params_out_list[i - 1] = (i - 1) / p * params_prev_step[i-2] + (p - i + 1) / p * params_prev_step[i-1] - params_out_list[p] = params_prev_step[p-1] - return params_out_list - - - -def sampleUntilPrecision(circuit,backend,noisemodel,min_n_shots,max_n_shots,E_atol,E_rtol,dv_rtol,confidence_index, measurement_fun, measurement_vars=None): - """ - Samples from the circuit and calculates the cost function until the specified - error tolerances are satisfied. This may include several repetitions, either if - the number of initial shots was too small, or if the variance estimate changed - to a large degree since the last repetition, meaning that the required shot - estimate was inaccurate. - - :param circuit: The circuit that will be sampled. - :param backend: The backend that will execute the circuit. - :param noisemodel: The noisemodel to use, e.g. when simulating. - :param min_n_shots: The minimum number of shots to be executed. - :param max_n_shots: The maximum number of shots to be executed. - :param E_atol: Absolute error tolerance for the expectation value. - :param E_rtol: Relative error tolerance for the expectation value. - :param dv_rtol: Relative change in variance tolerated without repeating. - :param confidence_index: The degree of confidence required. - :return: Lists of expectation values, variances and shots each repetition. - """ - - E_tot = 0 - v_tot = 0 - n_tot = 0 - - E_list = [] - v_list = [] - n_list = [] - - n_req = min_n_shots - v_prev = v_tot - while n_tot < n_req and np.abs(v_tot-v_prev) >= dv_rtol*v_prev: - v_prev = v_tot - n_cur = n_req - n_tot - experiment = execute(circuit, backend, noise_model=noisemodel, shots=n_cur) - - [E_cur],[v_cur],_ = measurement_fun(experiment.result().results, options=measurement_vars) - E_tot = (n_tot*E_tot + n_cur*E_cur)/(n_tot+n_cur) - v_tot = ((n_tot-1)*v_tot + (n_cur-1)*v_cur)/(n_tot+n_cur-1) - n_tot = n_req - E_list.append(E_tot) - v_list.append(v_tot) - n_list.append(n_cur) - - E_tol = min(E_atol,E_rtol*E_tot) - n_req = int(np.ceil(confidence_index**2*v_tot/E_tol**2)) - - if n_req > max_n_shots: - print('Warning: need %d samples to satisfy tolerance %.2e, but max_n_shots = %d.' % (n_req, E_tol, max_n_shots)) - n_req = max_n_shots - - return E_list,v_list,n_list - diff --git a/qaoa_OOP.py b/qaoa_OOP.py deleted file mode 100644 index 8c54b02..0000000 --- a/qaoa_OOP.py +++ /dev/null @@ -1,374 +0,0 @@ -import os -import sys - -sys.path.append('../') -from qiskit_utilities.utilities import * -from qiskit import execute -from qiskit import transpile -from plots import * - -import numpy as np -import scipy.optimize as optimize - -import itertools - -class QAOABase: - - def __init__(self,options = None): - self.options = options - - self.params = dict() - self.E = dict() - self.best = dict() - - self.reset_bookkeeping_params() - - def reset_bookkeeping_params(self): - - self.g_it = 0 - self.g_values = dict() - self.g_best_values = dict() - self.g_params = dict() - - - # ----------------------------------------- - # Methods a child would have to implement: - - def initial_state(self): - raise NotImplementedError - - def createCircuit(self): - raise NotImplementedError - - def measurementStatistics(self): - raise NotImplementedError - - def cost(self): - raise NotImplementedError - - def getval(self): - raise NotImplementedError - - # ----------------------------------------- - - def get_depth_and_numCX(self): - """ - Calculating the depth and number of cx-gates for full connectivity - and 1 layer. - - Depth is here a bit ambiguous, but the returned depth referred to - denotes the length of the critical path of the circuit, not the depth - in the qaoa algorithm. - - Returns - ------- - depth : int - Length of the critical path of the one-layer circuit - - """ - # createCircuit modifies self.qc, so save this temporarily - if hasattr(self, "qc"): - circ_tmp = self.qc - temp_save = True - else: - temp_save = False - - # create a circuit with self.q number of parameters, all ones - # set usebarrier to False when calculating the depth - usebarrier = self.options['usebarrier'] - self.options['usebarrier'] = False - - qc = self.createCircuit(np.ones(self.q)) - - self.options['usebarrier'] = usebarrier - - # Transpiling circuit - basis = ['cx', 'id', 'rz', 'sx','x'] - new_qc = transpile(qc,basis_gates = basis, optimization_level=1) - - depth = new_qc.depth() - num_cx = new_qc.count_ops()['cx'] - - # If the circuit was temporarily saved when making the circuit, - # swap it back again. - if temp_save: - self.qc = circ_tmp - - return depth, num_cx - - def interp_init(self): - """ - Interpolates the current parameters to the next layer - according to the procedure INTERP explained in - https://arxiv.org/pdf/1812.01041.pdf - - Returns - ------- - x.flatten() : array - array of length (self.depth)*(self.q) with the parameters for - the next depth of the algorithm. - """ - - x_prev = self.params[f'xL_d{self.depth - 1}'] - print(f"P = {x_prev}") - - # Minimize needs one-dimensional input, but the interpolation of the - # parameters can be done with a multidimensional input - # - # gamma_1 gamma_2 gamma_3 ... - # beta_1 beta_2 beta_3 ... - # ... - # The resulting flattened vector will be - # gamma_1 beta_1 gamma-2 beta_2 ... - # Which is what we want for the createCircuit method called in get-val - - # Hacky way of not having to refer to self.depth here - p = np.size(x_prev) // self.q - - x_prev = x_prev.reshape((p,self.q)) - x = np.zeros((p+1,self.q)) - - x[0,:] = x_prev[0,:] - - for i in range(2,p+1): - x[i - 1,:] = (i - 1)/p * x_prev[i-2,:] + (p - i + 1)/p * x_prev[i-1,:] - - x[p,:] = x_prev[p-1,:] - print(f"P_ = {x.flatten()}") - self.params[f'x0_d{self.depth}'] = x.flatten() - - return x.flatten() - - def save_best_params(self): - - # Find the best value along the path - ind = max(self.g_values, key = self.g_values.get) - - # Save params - - self.params[f'xL_d{self.depth}'] = self.g_params[ind].copy() - self.E[f'{self.depth}'] = self.g_values[ind] - self.best[f'{self.depth}'] = self.g_best_values[ind] - - def get_energy_landscape(self): - """ - Calculates the energy landscape given the simulation arguments - specifying the number of parameters and their upper and lower limits. - The method calls the scipy function brute which performs a grid search - over the specified ranges. The brute method also does some additional polishing - in the end. - - Returns - ------- - Jout.T : array - Array holding the energy at each point of the grid searched through - x0.flatten() : array - The parameters minimizing the energy found using brute force. - - """ - - print("Calculating energy landscape ...") - - ranges = [] - for i in range(self.q): - - step = (self.params_ul[i] - self.params_ll[i])/self.params_n[i] - - ranges.append(slice(self.params_ll[i],self.params_ul[i],step)) - - x0, fval, grid, Jout = optimize.brute(self.getval, ranges, full_output = True) - - print("Calculating energy landscape done.") - # Flatten the parameters according to fortran ordering - self.params[f'x0_d{self.depth}'] = x0.flatten() - - # Transpose energy landscape to be in accordance with the ordering used in the - # runQAOA function used previously. - return Jout.T, x0.flatten() - - def simulate_init(self, **simulation_args): - - # Unpack the simulation arguments: - - self.backend = simulation_args['backend'] - self.optmethod = simulation_args['optmethod'] - self.max_depth = simulation_args['max_depth'] - self.repeats = simulation_args.get('repeats',1) - self.shots = simulation_args.get('shots', 1) - self.noise_model = simulation_args.get('noise_model',None) - - # Give lower and upper limits (ll, ul) as arrays rather than - # separately giving max and min for each variable, so that it is - # easier to change the number of variables later on - # Aslo, provide the number of steps for each variable as a similar array - - self.params_ll = simulation_args['params_ll'] - self.params_ul = simulation_args['params_ul'] - self.params_n = simulation_args['params_n'] - - self.q = self.params_ll.size - - assert( self.params_ll.size == self.params_ul.size == self.params_n.size) - - def continue_simulation(self): - """ - Boolean function, providing a critetion for continuing the simulation loop, - may be overridden by a child. - - """ - return self.depth <= self.max_depth - - def simulate(self, **simulation_args): - - """ - Simulation function for doing the QAOA algorithm. - - Parameters - ---------- - simulation_args : dict - Keyword arguments, must contain: - backend - optmethod - max_depth - params_ll : lower limits for each parameter to do brute search over - params_ul : upper limits -- " -- - params_n : number of points -- " -- - - - """ - - self.simulate_init(**simulation_args) - self.depth = 1 - - # Calculate energy_landscape - global optimisation - - Elandscape, x0 = self.get_energy_landscape() - - while self.continue_simulation(): - - - # Reset the current book-keeping variables for each depth - self.reset_bookkeeping_params() - - # Local optimisation - - for rep in range(self.repeats): - print(f"Depth = {self.depth}, Rep = {rep + 1}") - - # No need to keep track of the optimisation result, as the getval-function - # is required to update the member variables g_values, g_best_values, g_params - # among all iterations, so that multiple repetitions can be performed and compared. - # - # The function save_best_params() will ensure the best of each repetition will - # be used further. - - _ = optimize.minimize(self.getval, - x0 = x0, - method = self.optmethod, - options={'xatol': 1e-2, 'fatol': 1e-1, 'disp': True}) - - self.save_best_params() - self.depth += 1 - - # Extrapolate the parameters to the next depth - x0 = self.interp_init() - - return Elandscape, self.params, self.E, self.best - - -class QAOAStandard(QAOABase): - - def __init__(self,qubits,options = None): - super().__init__(options) - - # If a start circuit is provided, use this in self.initial_state(qubits) - self.start_circuit = options.get('start_circuit', None) - self.qubits = qubits - - def simulate_init(self, **simulation_args): - super().simulate_init(**simulation_args) - - # Only create state strings array if using the statevector simulation - if "statevector" in self.backend.name().split('_'): - self.generate_state_strings(self.qubits) - - def generate_state_strings(self, qubits): - """ - Generates an array of all the state strings in increasing order. - Useful for toy examples. - - This should only be done when using the state-vector simulator, - so do a call to this function in the simulate_init function. - - Parameters - ---------- - qubits : int - number of qubits in circuit. - - """ - - self.state_strings = np.array([''.join(i) for i in itertools.product('01', repeat= qubits)]) - # Flip the state-vectors to be in accordance with the ordering in qiskit: - #self.state_strings = map(lambda x : x[::-1], self.state_strings) - - def initial_state(self, qubits): - # Save current circuit and registers as - # member variables of the object - # Use |+>^n as initial state - - q = QuantumRegister(qubits) - c = ClassicalRegister(qubits) - qc = QuantumCircuit(q,c, name = self.options.get('name', None)) - - # If provided with a start_circuit, use this instead of |+>^n - if self.start_circuit is not None: - qc.compose(self.start_circuit, inplace = True) - else: - qc.h(range(qubits)) - - self.q_register = q - self.c_register = c - self.qc = qc - - def getval(self, params): - """ - Objective function to use in the minimizer. Saves in each iteration the - parameters and the function values in the member variables whose name starts - with g_ , i.e. what previously was the global book-keeping variables. - - Parameters - ---------- - params : array - Array of parameters to feed into the circuit: gamma_1, beta_1, ... , beta_p - or even more parameters per. layer. - - Returns - ------- - -val[0] : float - Value of hamiltonian for these parameters. - - """ - - - self.g_it += 1 - - circuit = self.createCircuit(params) - - if self.backend.configuration().local: - job = execute(circuit, - backend = self.backend, - noise_model = self.noise_model, - shots = self.shots) - else: - job = start_or_retrieve_job(name +"_"+str(g_it), - self.backend, - circuit, - options = {'shots' : self.shots}) - - val, _, bval = self.measurementStatistics(job) - - self.g_values[str(self.g_it)] = val[0] - self.g_best_values[str(self.g_it)] = bval - self.g_params[str(self.g_it)] = params - - return -val[0] diff --git a/recursive_decomp.py b/recursive_decomp.py deleted file mode 100644 index e4fab99..0000000 --- a/recursive_decomp.py +++ /dev/null @@ -1,39 +0,0 @@ -import numpy as np -from tailassignment_loader import * - -def decompose_problem(FR): - - F, R = np.shape(FR) - - routes_per_flight = np.sum(FR, axis = 1) - fmin = np.argmin(routes_per_flight) - min_routes = int(routes_per_flight[fmin]) - ones_ind = np.where(FR[fmin,:] == 1)[0] - - compatible_routes = np.zeros((min_routes,R), dtype = bool) - covered_flights = np.zeros((min_routes,F), dtype = bool) - - for r in range(min_routes): - current_route = FR[:,ones_ind[r]] - covered_flights[r] = FR[:,ones_ind[r]] == 0 - - for r_ in range(R): - if FR[:,r_] @ current_route == 0: - compatible_routes[r,r_] = True - - return ones_ind, compatible_routes, covered_flights - - -if __name__ == "__main__": - - instances = 6 - flights = 24 - solutions = 3 - - FR, CR, best_sol = load_FR_CR(f'../data/FRCR_{instances}_{flights}_{solutions}.txt') - - ones_ind, compatible_routes, covered_flights = decompose_problem(FR) - - print(ones_ind) - for r in range(len(compatible_routes[:,0])): - print(FR[covered_flights[r,:],compatible_routes[r,:]]) diff --git a/tailassignment_oop averages 7r high interlaced.ipynb b/tailassignment_oop averages 7r high interlaced.ipynb deleted file mode 100644 index 7cf35ef..0000000 --- a/tailassignment_oop averages 7r high interlaced.ipynb +++ /dev/null @@ -1,4621 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "e429c1ea", - "metadata": {}, - "outputs": [], - "source": [ - "%load_ext autoreload\n", - "%autoreload 2" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "a25b06d2", - "metadata": {}, - "outputs": [], - "source": [ - "from qiskit import *\n", - "from qiskit.tools.monitor import job_monitor\n", - "\n", - "import numpy as np\n", - "from qaoa_OOP import *\n", - "from exactcover import *\n", - "from tailassignment_oop import * \n", - "from tailassignment_loader import * \n", - "\n", - "import os\n", - "\n", - "import sys\n", - "sys.path.append('../')\n", - "\n", - "from qiskit_utilities.utilities import *\n", - "\n", - "from qiskit.visualization import plot_histogram" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "d463d2d9", - "metadata": {}, - "outputs": [], - "source": [ - "from matplotlib import rc\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib as mpl\n", - "# from tqdm import tqdm\n", - "\n", - "fontsize = 24\n", - "newparams = {'axes.titlesize': fontsize,\n", - " 'axes.labelsize': fontsize,\n", - " 'ytick.labelsize': fontsize,\n", - " 'xtick.labelsize': fontsize, \n", - " 'legend.fontsize': fontsize,\n", - " 'figure.titlesize': fontsize,\n", - " 'legend.handlelength': 1.5, \n", - " 'lines.linewidth': 2,\n", - " 'lines.markersize': 7,\n", - " 'figure.figsize': (12, 7), \n", - " 'figure.dpi':200,\n", - " 'text.usetex' : False,\n", - " 'font.family' : \"sans-serif\"\n", - " }\n", - "\n", - "plt.rcParams.update(newparams)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "50c7c80a", - "metadata": {}, - "outputs": [], - "source": [ - "def averageQAOA(qaoa_type, options, simulation_args, num_route, num_sols, num_arr):\n", - " flights = 24\n", - " max_depth = simulation_args.get('max_depth',10)\n", - " SP_all = np.zeros((len(num_sols), max_depth))\n", - " C_all = np.zeros_like(SP_all)\n", - " SP_avg = np.zeros(max_depth)\n", - " C_avg = np.zeros_like(SP_avg)\n", - " per_cent_best_cost = np.zeros((len(num_sols), max_depth))\n", - " for i in range(len(num_sols)):\n", - " print()\n", - " print('Now using', num_sols[i], 'solutions, set number', num_arr[i])\n", - " FR,CR = load_giorgio(f'./data/tail_assignment/Our_routes/Giorgio_routes_cost/FRCR_{num_route}_{flights}_{num_sols[i]}_{num_arr[i]}.npy')\n", - " CR /= np.amax(CR)\n", - " mu = np.amax(CR)\n", - " options['FR'] = FR\n", - " options['CR'] = CR\n", - " options['mu'] = mu\n", - "\n", - " qaoa = qaoa_type(options)\n", - " Elandscape, gammabetas, E, best = qaoa.simulate(**simulation_args)\n", - " SP, C = qaoa.simulation_statistics(plot = False)\n", - " best_cost = np.max( qaoa.vector_cost(qaoa.state_strings) )\n", - " optimal_solution = qaoa.best_cost_string()\n", - " state_strings = qaoa.state_strings \n", - " for k in range(1,max_depth+1):\n", - " qaoa.depth = k\n", - " circuit = qaoa.createCircuit(qaoa.params['xL_d' +str(k)])\n", - " if qaoa.backend.configuration().local:\n", - " job = execute(circuit, backend = qaoa.backend, noise_model = qaoa.noise_model, shots = qaoa.shots)\n", - " else:\n", - " job = start_or_retrieve_job(name +\"_\"+str(g_it), qaoa.backend, circuit, options = {'shots' : qaoa.shots})\n", - " optimal_ind = np.where(state_strings==optimal_solution)\n", - " per_cent_best_cost[i, k-1] = (np.abs(job.result().get_statevector())**2)[optimal_ind]\n", - "\n", - "\n", - " SP_all[i] = SP\n", - " print(-best_cost, -C)\n", - " C_all[i] = C/best_cost\n", - " SP_avg += SP/len(num_sols)\n", - " C_avg += C/(len(num_sols)*best_cost)\n", - " print(C_all, C_avg)\n", - " print(SP_all, SP_avg)\n", - " return SP_avg, SP_all, C_avg, C_all, per_cent_best_cost\n" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "ba34f8b6", - "metadata": {}, - "outputs": [], - "source": [ - "num_routes = 7\n", - "\n", - "options={}\n", - "options['usebarrier'] = True\n", - "\n", - "\n", - "beta_n = 20\n", - "gamma_n = 25\n", - "delta_n = 25\n", - "\n", - "beta_max = np.pi\n", - "gamma_max = 2 * np.pi\n", - "delta_max = 2 * np.pi\n", - "\n", - "optmethod = 'Nelder-Mead'\n", - "shots = 1024 # no need for more shots when using the statevector simulation\n", - "rerun = True\n", - "max_depth = 20" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "a4fcccfa", - "metadata": {}, - "outputs": [], - "source": [ - "Aer.backends()\n", - "backend = Aer.get_backend('statevector_simulator')" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "a60f7e98", - "metadata": {}, - "outputs": [], - "source": [ - "simulation_args = dict()\n", - "\n", - "simulation_args['backend'] = backend\n", - "simulation_args['optmethod'] = optmethod\n", - "simulation_args['max_depth'] = max_depth\n", - "simulation_args['repeats'] = 1\n", - "simulation_args['params_ll'] = np.array([0,0,0])\n", - "simulation_args['params_ul'] = np.array([gamma_max,beta_max,delta_max])\n", - "simulation_args['params_n'] = np.array([gamma_n, beta_n, delta_n])\n", - "simulation_args['shots'] = shots\n" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "c35f45c9", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'usebarrier': True}" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "options" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "28ce097d", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'backend': StatevectorSimulator('statevector_simulator'),\n", - " 'optmethod': 'Nelder-Mead',\n", - " 'max_depth': 20,\n", - " 'repeats': 1,\n", - " 'params_ll': array([0, 0, 0]),\n", - " 'params_ul': array([6.28318531, 3.14159265, 6.28318531]),\n", - " 'params_n': array([25, 20, 25]),\n", - " 'shots': 1024}" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "simulation_args" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "a187660b", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Now using 3 solutions, set number 1\n", - "Calculating energy landscape ...\n", - "Optimization terminated successfully.\n", - " Current function value: 8.963195\n", - " Iterations: 53\n", - " Function evaluations: 99\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 8.963195\n", - " Iterations: 25\n", - " Function evaluations: 42\n", - "P = [0.31272002 2.66767357 1.60230999]\n", - "P_ = [0.31272002 2.66767357 1.60230999 0.31272002 2.66767357 1.60230999]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 8.526213\n", - " Iterations: 226\n", - " Function evaluations: 349\n", - "P = [0.29086231 2.71981502 1.32307298 0.43549713 3.03781181 1.82586034]\n", - "P_ = [0.29086231 2.71981502 1.32307298 0.36317972 2.87881341 1.57446666\n", - " 0.43549713 3.03781181 1.82586034]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 6.282966\n", - " Iterations: 343\n", - " Function evaluations: 500\n", - "P = [0.24944413 2.65151026 2.3535837 0.31595663 3.27593798 1.93719992\n", - " 0.92980669 2.82633449 0.99452538]\n", - "P_ = [0.24944413 2.65151026 2.3535837 0.2937858 3.06779541 2.07599451\n", - " 0.52057332 3.12607015 1.62297507 0.92980669 2.82633449 0.99452538]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.082704\n", - " Iterations: 1169\n", - " Function evaluations: 1629\n", - "P = [0.35224696 2.42708402 1.88534226 0.19027849 3.36683307 1.87029456\n", - " 0.36976876 2.92281452 3.23016691 1.16438265 3.47992329 1.13096187]\n", - "P_ = [0.35224696 2.42708402 1.88534226 0.2307706 3.13189581 1.87405648\n", - " 0.28002362 3.1448238 2.55023073 0.56842223 3.06209171 2.70536565\n", - " 1.16438265 3.47992329 1.13096187]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.090901\n", - " Iterations: 2133\n", - " Function evaluations: 2824\n", - "P = [ 0.33205669 2.28264146 2.03174697 0.21641351 3.3906482 -0.26720304\n", - " 0.40641187 2.9596506 7.04200959 0.00776959 3.333015 -0.79576901\n", - " 1.75265985 3.09536527 -0.2569942 ]\n", - "P_ = [ 0.33205669 2.28264146 2.03174697 0.23954214 3.16904686 0.19258696\n", - " 0.33041253 3.13204964 4.11832454 0.24695496 3.10899636 3.90689815\n", - " 0.35674764 3.28548505 -0.68801404 1.75265985 3.09536527 -0.2569942 ]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.660090\n", - " Iterations: 1873\n", - " Function evaluations: 2418\n", - "P = [ 0.36558252 2.18352739 1.94688645 0.23597067 3.65307405 0.0130428\n", - " 0.32965703 2.94497673 1.69318126 0.09451728 3.41487154 1.66277558\n", - " 0.38748628 3.00698832 -0.35514757 2.58556301 3.066184 -0.59906509]\n", - "P_ = [ 0.36558252 2.18352739 1.94688645 0.25757264 3.40814961 0.33535008\n", - " 0.29842824 3.18100917 1.1331351 0.21208716 3.17992414 1.67797842\n", - " 0.19217362 3.27891047 0.99013453 0.7538324 3.01685427 -0.39580049\n", - " 2.58556301 3.066184 -0.59906509]\n", - "Depth = 7, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.590065\n", - " Iterations: 1242\n", - " Function evaluations: 1624\n", - "P = [ 0.37524039 2.215986 2.05210621 0.23067407 3.60060473 0.26968012\n", - " 0.07011344 3.06250758 1.48166431 0.15202109 3.14652083 2.60959175\n", - " 0.15210785 3.13826142 1.40565152 1.05726709 3.37884554 -0.37609063\n", - " 2.73378363 3.11115147 -0.57154475]\n", - "P_ = [ 0.37524039 2.215986 2.05210621 0.2513264 3.40280206 0.52431242\n", - " 0.11598791 3.21624962 1.13538311 0.11691781 3.11051515 2.12619427\n", - " 0.15205827 3.14298108 2.09361736 0.41072477 3.20699974 0.89658234\n", - " 1.29676945 3.34060353 -0.40401265 2.73378363 3.11115147 -0.57154475]\n", - "Depth = 8, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.459274\n", - " Iterations: 2866\n", - " Function evaluations: 3642\n", - "P = [ 0.35622399 2.26958622 1.98254044 0.20091759 3.31814231 0.30192913\n", - " 0.11505256 3.34877684 1.32600348 0.14212948 2.95672733 1.71368253\n", - " 0.15569128 3.11818189 2.14584038 0.39928601 3.32187992 1.11711958\n", - " 1.29799666 2.84461712 -0.6415186 2.64590202 3.33287181 -0.44279479]\n", - "P_ = [ 0.35622399 2.26958622 1.98254044 0.22033089 3.1870728 0.51200555\n", - " 0.13651882 3.34111821 1.0699849 0.13197563 3.1037459 1.56830289\n", - " 0.14891038 3.03745461 1.92976146 0.24703931 3.19456865 1.76007008\n", - " 0.62396367 3.20256422 0.67746004 1.46648483 2.90564896 -0.61667812\n", - " 2.64590202 3.33287181 -0.44279479]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.578549\n", - " Iterations: 3858\n", - " Function evaluations: 4792\n", - "P = [ 0.31372204 2.2986719 2.3199472 0.14344668 3.27086943 0.69534473\n", - " 0.0861013 3.48831769 0.79574606 0.20434842 3.05353958 1.92414228\n", - " 0.12911757 2.73571835 1.31484399 0.25586189 3.5415213 1.71410607\n", - " 0.44456836 3.10751708 0.76463577 2.17191341 2.86703789 -0.68327156\n", - " 2.50199185 3.33802232 -0.62983935]\n", - "P_ = [ 0.31372204 2.2986719 2.3199472 0.16236617 3.16284748 0.87585611\n", - " 0.09884472 3.43999585 0.77343466 0.16493271 3.19846562 1.54801021\n", - " 0.1625535 2.87697223 1.58564323 0.18544838 3.093853 1.4922938\n", - " 0.31876405 3.39685323 1.39761597 0.82842282 3.05407726 0.44287858\n", - " 2.20858879 2.91936949 -0.67733465 2.50199185 3.33802232 -0.62983935]\n", - "Depth = 10, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.573377\n", - " Iterations: 1908\n", - " Function evaluations: 2350\n", - "P = [ 0.25995873 2.62326097 2.29949183 0.11459644 3.08076706 1.28457162\n", - " 0.09715039 3.37908592 0.61310267 0.13982643 3.12218143 2.02375691\n", - " 0.22461737 2.77373148 1.6109861 0.22194795 3.65212571 1.48794833\n", - " 0.29017251 2.85619754 1.43636704 0.76098355 3.30720094 0.28135676\n", - " 2.26258548 3.17528278 -0.73670934 3.10929467 3.23366851 -0.68649524]\n", - "P_ = [ 0.25995873 2.62326097 2.29949183 0.12913267 3.03501645 1.38606364\n", - " 0.1006396 3.31942215 0.74739646 0.12702362 3.19925278 1.60056064\n", - " 0.190701 2.91311146 1.77609443 0.22328266 3.2129286 1.54946722\n", - " 0.24923777 3.33375445 1.46731581 0.43141582 2.99149856 1.08986395\n", - " 1.06130393 3.28081731 0.07774354 2.3472564 3.18112135 -0.73168793\n", - " 3.10929467 3.23366851 -0.68649524]\n", - "Depth = 11, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 0.27500097 2.67547024 2.44225628 0.00952938 3.0738543 2.24747039\n", - " 0.13080038 3.33186156 0.52708257 0.14054269 3.24195262 1.73765285\n", - " 0.22438319 2.67233767 1.08181701 0.22813003 3.23245971 0.92165734\n", - " 0.20229015 3.48169877 1.42045398 0.33834541 2.87252474 1.1675282\n", - " 0.82222524 3.17553784 0.09840671 2.6001531 3.33913926 -1.34440552\n", - " 3.57515822 3.1462026 -0.54193342]\n", - "P_ = [ 0.27500097 2.67547024 2.44225628 0.03366316 3.03763757 2.26517819\n", - " 0.1087511 3.28495115 0.83988035 0.13788569 3.26647324 1.40749732\n", - " 0.19389573 2.87947038 1.32030277 0.22642692 2.97785878 0.99445719\n", - " 0.21638463 3.34575019 1.14838309 0.25176479 3.26018094 1.32848097\n", - " 0.47031263 2.95516468 0.87594961 1.14548485 3.20528355 -0.16392279\n", - " 2.68878993 3.32159957 -1.27145351 3.57515822 3.1462026 -0.54193342]\n", - "Depth = 12, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.793890\n", - " Iterations: 3109\n", - " Function evaluations: 3776\n", - "P = [ 0.23619473 2.64222178 2.7590199 0.03746439 2.99586786 2.09512363\n", - " 0.14216408 3.45577469 0.80390242 0.13272681 3.18050852 1.45657934\n", - " 0.2412875 2.95747381 1.45979178 0.13536542 2.88552777 1.61075582\n", - " 0.21388778 3.56076768 1.12777979 0.29246391 3.16094001 1.12658791\n", - " 0.48264541 2.95991103 0.26932047 1.54540558 3.31978916 -0.11833412\n", - " 2.45323509 3.07242524 -1.44271353 3.05571854 3.0551821 -0.49122231]\n", - "P_ = [ 0.23619473 2.64222178 2.7590199 0.05402526 2.96639736 2.15044832\n", - " 0.12471414 3.37912355 1.01910595 0.13508613 3.24932506 1.29341011\n", - " 0.2051006 3.03181872 1.45872097 0.17949962 2.91550529 1.54785414\n", - " 0.1746266 3.22314772 1.3692678 0.24662784 3.39417282 1.12728317\n", - " 0.35585774 3.09393035 0.8408321 0.74833545 3.04988056 0.17240682\n", - " 1.6967105 3.27856184 -0.33906402 2.50344204 3.07098831 -1.36342259\n", - " 3.05571854 3.0551821 -0.49122231]\n", - "Depth = 13, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 1.945163\n", - " Iterations: 5423\n", - " Function evaluations: 6430\n", - "P = [ 0.33563718 2.42548978 2.38002998 0.06809098 3.08239758 0.85172961\n", - " 0.10210807 3.39876498 1.04745238 0.1597891 3.2077856 1.64182148\n", - " 0.11099075 3.02950442 1.58241673 0.11593745 2.96375471 1.66805552\n", - " 0.1835754 3.18501682 1.68849833 0.16316833 3.51821934 0.69642753\n", - " 0.25214452 2.80239429 0.60354771 0.75375984 3.25864036 0.25761338\n", - " 1.4625044 3.22103548 -0.4737451 2.61334928 3.14474182 -1.99431448\n", - " 3.28058982 3.24597872 -0.6747418 ]\n", - "P_ = [ 0.33563718 2.42548978 2.38002998 0.08867146 3.03186621 0.96929118\n", - " 0.09687467 3.35009307 1.01734118 0.14647809 3.25185777 1.50465938\n", - " 0.12600563 3.08436017 1.60069511 0.11403487 2.98904306 1.63511752\n", - " 0.15235788 3.08289585 1.67906318 0.17415675 3.3388026 1.2306195\n", - " 0.19738994 3.24290201 0.66070452 0.40648769 2.9427777 0.49710637\n", - " 0.91731628 3.24996231 0.08883834 1.63955746 3.209298 -0.70767885\n", - " 2.66467547 3.15252927 -1.89280889 3.28058982 3.24597872 -0.6747418 ]\n", - "Depth = 14, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 0.30005294 2.46689965 2.37308252 0.14312549 3.04286466 1.12501664\n", - " -0.02086666 3.37422002 0.87942262 0.1524036 3.25744984 0.90387954\n", - " 0.10925437 3.17251724 2.10004605 0.17034071 2.82459513 1.0519851\n", - " 0.1822353 3.04856761 1.04098618 0.17450393 3.58952741 1.34455993\n", - " 0.29288589 2.94562868 0.84577685 0.50189992 3.1437454 0.28833011\n", - " 0.31306297 3.20086258 0.09333706 2.05034783 3.19407072 -0.62542743\n", - " 2.91518879 3.11268661 -3.23261087 3.31266096 3.19609836 -0.5398306 ]\n", - "P_ = [ 3.00052944e-01 2.46689965e+00 2.37308252e+00 1.54334590e-01\n", - " 3.00172430e+00 1.21416420e+00 2.56079154e-03 3.32688354e+00\n", - " 9.14507479e-01 1.15274260e-01 3.28247202e+00 8.98638773e-01\n", - " 1.21582724e-01 3.19678370e+00 1.75828419e+00 1.48524160e-01\n", - " 2.94885302e+00 1.42629259e+00 1.77137617e-01 2.95257940e+00\n", - " 1.04570001e+00 1.78369612e-01 3.31904751e+00 1.19277306e+00\n", - " 2.25239054e-01 3.31357081e+00 1.13079575e+00 3.67533758e-01\n", - " 3.01638465e+00 6.46688729e-01 4.47946505e-01 3.16006459e+00\n", - " 2.32617808e-01 6.85338294e-01 3.19940718e+00 -6.06839023e-02\n", - " 2.17389654e+00 3.18244442e+00 -9.97882210e-01 2.94357966e+00\n", - " 3.11864460e+00 -3.04026942e+00 3.31266096e+00 3.19609836e+00\n", - " -5.39830599e-01]\n", - "Depth = 15, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 3.15940879e-01 2.51646320e+00 3.06780116e+00 9.91193352e-02\n", - " 2.96658511e+00 8.55513362e-01 2.55139419e-03 3.40809922e+00\n", - " 8.58700209e-01 1.64497814e-01 3.28795989e+00 1.03381050e+00\n", - " 9.79325996e-03 3.21405198e+00 1.57698071e+00 2.23495462e-01\n", - " 2.78412584e+00 1.27512746e+00 1.87322823e-01 3.05352404e+00\n", - " 8.54151791e-01 1.83735049e-01 3.35000175e+00 1.02910454e+00\n", - " 3.65866184e-01 3.29592820e+00 6.73025051e-01 2.29407133e-01\n", - " 2.79068712e+00 4.66557073e-01 4.24918569e-01 3.36754094e+00\n", - " 2.94391921e-01 8.81784327e-01 3.15014326e+00 -7.47509959e-02\n", - " 2.48339237e+00 3.00848188e+00 -1.44577389e+00 2.67065286e+00\n", - " 3.20942993e+00 -2.31079966e+00 3.60289402e+00 3.08294775e+00\n", - " -4.79403830e-01]\n", - "P_ = [ 0.31594088 2.5164632 3.06780116 0.1135741 2.93657699 1.00299922\n", - " 0.01542712 3.34923067 0.8582753 0.13210853 3.31198776 0.99878844\n", - " 0.05104781 3.23376075 1.43213532 0.15226139 2.92743455 1.37574521\n", - " 0.20179188 2.94576476 1.02254206 0.18540934 3.21164548 0.94745993\n", - " 0.26872958 3.32476742 0.86293411 0.31128256 3.09383176 0.59043786\n", - " 0.29457761 2.98297172 0.40916869 0.54674944 3.30956822 0.19595381\n", - " 1.20210594 3.12181098 -0.34895557 2.50836043 3.03527495 -1.56111066\n", - " 2.73280227 3.20099778 -2.1887066 3.60289402 3.08294775 -0.47940383]\n", - "Depth = 16, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 0.30179839 2.46676016 2.49462184 0.13977146 3.16958229 1.32571057\n", - " 0.01816059 3.38078825 0.95631957 0.10746889 3.11772503 0.96668236\n", - " 0.05946233 3.14547374 0.05728796 0.10957026 3.09881897 1.5648927\n", - " 0.14270721 2.86868907 1.15440807 0.18137861 3.2259849 1.303632\n", - " 0.26511192 3.45950431 1.0858684 0.43781569 2.77185895 0.83125874\n", - " 0.37252442 3.33455464 0.29338765 0.46697126 3.17013041 0.15020842\n", - " 1.17891779 3.02643134 -0.62149884 2.60599863 3.26850056 -0.86801266\n", - " 2.60709731 3.1224333 -2.54607257 3.3144191 3.07736186 -0.35020693]\n", - "P_ = [ 0.30179839 2.46676016 2.49462184 0.14989815 3.1256559 1.39876752\n", - " 0.03336195 3.3543875 1.00249345 0.09072358 3.16704938 0.96473934\n", - " 0.07146397 3.13853656 0.28463656 0.09391153 3.11339858 1.09376622\n", - " 0.13028085 2.95498778 1.30833981 0.16445987 3.06966798 1.23834653\n", - " 0.22324527 3.34274461 1.1947502 0.34066982 3.15865947 0.97447667\n", - " 0.41333146 2.98286983 0.62955708 0.40203906 3.28317207 0.24864414\n", - " 0.6449579 3.13420564 -0.0427184 1.44649545 3.07181932 -0.66772018\n", - " 2.60613596 3.25024215 -1.07777015 2.65130492 3.11961634 -2.40883097\n", - " 3.3144191 3.07736186 -0.35020693]\n", - "Depth = 17, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 0.34879402 2.41050512 2.4358758 0.11017122 3.08797352 1.21245919\n", - " 0.02687605 3.45004599 1.00210229 0.09454975 2.99388338 1.16805917\n", - " 0.07158193 3.40359242 0.20929476 0.055198 2.99209205 1.13375358\n", - " 0.16129313 3.04237748 1.09502618 0.19643315 2.89192617 1.0987076\n", - " 0.16551501 3.41938367 1.38747827 0.33268572 3.23019559 0.92494474\n", - " 0.31537238 2.83571596 0.36441765 0.43633385 3.41060002 0.28756353\n", - " 0.47915995 3.08841293 -0.05961261 1.60501839 3.04423262 -0.77796612\n", - " 2.73054568 3.1675373 -1.34140878 3.03293629 3.22824337 -3.71328431\n", - " 2.86771427 3.11984642 -0.36894602]\n", - "P_ = [ 0.34879402 2.41050512 2.4358758 0.12420785 3.04812244 1.28442487\n", - " 0.03667548 3.40744923 1.02685016 0.08260733 3.07438266 1.13877267\n", - " 0.07698612 3.30719029 0.43488638 0.0600168 3.11312157 0.86185392\n", - " 0.12384779 3.02462968 1.10869467 0.18196373 2.95387671 1.09719172\n", - " 0.18006473 3.17116838 1.25158619 0.24418358 3.33035399 1.16981543\n", - " 0.32555669 3.0677628 0.69413947 0.35806466 3.03861622 0.33729267\n", - " 0.44892976 3.31583911 0.1854529 0.74406782 3.07801756 -0.22863697\n", - " 1.80364085 3.06599227 -0.87739718 2.76612105 3.17467919 -1.62045296\n", - " 3.02321735 3.22186708 -3.51655853 2.86771427 3.11984642 -0.36894602]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.145283\n", - " Iterations: 7957\n", - " Function evaluations: 9225\n", - "P = [ 0.32923266 2.51668676 2.47116027 0.09543151 3.00855023 1.17224777\n", - " 0.03465995 3.50177365 0.99705413 0.08451595 2.94978687 1.65905593\n", - " 0.07343639 3.37476516 0.44699638 0.07514957 3.04145109 0.76488142\n", - " 0.14135364 2.96976845 0.6991315 0.20636324 2.94483017 0.86282627\n", - " 0.09686127 3.38677112 1.44419167 0.27644367 3.31996142 1.1794213\n", - " 0.33811719 2.84247598 0.66330497 0.32705115 3.23619683 0.25009577\n", - " 0.39439497 3.23374413 0.13212281 0.72071278 3.09313246 -0.27493414\n", - " 2.06085838 3.10037813 -0.85793001 2.52059381 3.26268593 -2.13276698\n", - " 3.18698066 3.01763292 -2.79542643 3.17390181 3.21096896 -0.30615866]\n", - "P_ = [ 0.32923266 2.51668676 2.47116027 0.10842046 2.98122448 1.24440958\n", - " 0.04141234 3.44697105 1.01652009 0.07620662 3.04178467 1.54872229\n", - " 0.07589852 3.28032554 0.71634295 0.07467368 3.13403834 0.67658002\n", - " 0.11928561 2.99366267 0.72104814 0.18108173 2.95452839 0.79916719\n", - " 0.14552881 3.19035292 1.18580705 0.18665247 3.35336627 1.31180649\n", - " 0.30385412 3.10774567 0.95003626 0.33381373 2.99558965 0.50261251\n", - " 0.34949909 3.23537926 0.21077145 0.4850388 3.19468534 0.01905143\n", - " 1.01852291 3.09474261 -0.40448877 2.13748095 3.12742943 -1.07040284\n", - " 2.59463679 3.23545781 -2.20639581 3.18625406 3.02837381 -2.65713378\n", - " 3.17390181 3.21096896 -0.30615866]\n", - "Depth = 19, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 2.49258372e-01 2.53262891e+00 2.86111829e+00 1.10611371e-01\n", - " 3.05155734e+00 1.03350544e+00 8.35930497e-03 3.38598036e+00\n", - " 7.80840837e-01 5.44388530e-02 3.15876024e+00 1.51843853e+00\n", - " 1.38260507e-01 3.30606742e+00 5.86895506e-01 4.33298014e-04\n", - " 3.06520906e+00 6.74423037e-01 1.36463364e-01 3.03431480e+00\n", - " 9.98475813e-01 1.48166916e-01 2.96668069e+00 4.80292751e-01\n", - " 1.12499847e-01 3.05601470e+00 1.05687269e+00 1.82452465e-01\n", - " 3.49904461e+00 1.29691801e+00 3.40125698e-01 3.07727678e+00\n", - " 6.29424019e-01 4.16586422e-01 2.98264532e+00 4.59004826e-01\n", - " 3.88873265e-01 3.31013987e+00 4.30729244e-01 4.33597496e-01\n", - " 3.17194339e+00 2.21360434e-02 1.42092134e+00 3.03572033e+00\n", - " -4.44193892e-01 2.13113032e+00 3.19743369e+00 -1.05929680e+00\n", - " 2.70516798e+00 3.14506842e+00 -2.91802570e+00 3.10693460e+00\n", - " 3.03501955e+00 -2.82919353e+00 3.27577410e+00 3.16475940e+00\n", - " -3.21307877e-01]\n", - "P_ = [ 0.24925837 2.53262891 2.86111829 0.11790858 3.02424532 1.12969559\n", - " 0.01912268 3.35077794 0.80743711 0.04716313 3.1946371 1.40197573\n", - " 0.12061384 3.27505538 0.78300983 0.03670362 3.12859284 0.65138948\n", - " 0.0935065 3.04407088 0.89614336 0.14385508 2.99159852 0.6712023\n", - " 0.12751756 3.01840038 0.81410219 0.14931701 3.28918834 1.18321233\n", - " 0.25713979 3.29925985 0.98073664 0.37231969 3.03743196 0.55766857\n", - " 0.40637631 3.10330121 0.44858751 0.40299671 3.26649888 0.30169981\n", - " 0.69341956 3.13609522 -0.10058236 1.57043902 3.06976525 -0.57368924\n", - " 2.22176784 3.18916549 -1.35278031 2.74745921 3.13348433 -2.90867495\n", - " 3.11582089 3.04184797 -2.69719955 3.2757741 3.1647594 -0.32130788]\n", - "Depth = 20, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 1.727342\n", - " Iterations: 6504\n", - " Function evaluations: 7510\n", - "1.4444444444444444 [8.96319455 8.52621283 6.28296593 4.08270355 4.09090119 3.66008968\n", - " 3.59006463 3.45927379 2.57854881 2.57337692 2.36291787 2.79388967\n", - " 1.94516271 2.3340464 1.90267237 2.01326881 1.90853752 2.14528349\n", - " 1.72188166 1.72734175]\n", - "[[6.20528854 5.90276273 4.34974565 2.82648708 2.83216236 2.53390824\n", - " 2.48542936 2.39488186 1.78514917 1.78156864 1.63586622 1.93423131\n", - " 1.3466511 1.61587827 1.31723472 1.39380148 1.3212952 1.48519626\n", - " 1.19207192 1.19585198]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]] [0.62052885 0.59027627 0.43497456 0.28264871 0.28321624 0.25339082\n", - " 0.24854294 0.23948819 0.17851492 0.17815686 0.16358662 0.19342313\n", - " 0.13466511 0.16158783 0.13172347 0.13938015 0.13212952 0.14851963\n", - " 0.11920719 0.1195852 ]\n", - "[[0.17030757 0.16850299 0.24687602 0.45514832 0.45145637 0.56268179\n", - " 0.4723914 0.62266371 0.8026945 0.81119819 0.87005395 0.73125403\n", - " 0.9110609 0.83507433 0.90935654 0.90735586 0.92006095 0.88620215\n", - " 0.96581763 0.96554472]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]] [0.01703076 0.0168503 0.0246876 0.04551483 0.04514564 0.05626818\n", - " 0.04723914 0.06226637 0.08026945 0.08111982 0.0870054 0.0731254\n", - " 0.09110609 0.08350743 0.09093565 0.09073559 0.09200609 0.08862022\n", - " 0.09658176 0.09655447]\n", - "\n", - "Now using 3 solutions, set number 2\n", - "Calculating energy landscape ...\n", - "Optimization terminated successfully.\n", - " Current function value: 6.782327\n", - " Iterations: 132\n", - " Function evaluations: 232\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 6.782327\n", - " Iterations: 20\n", - " Function evaluations: 38\n", - "P = [ 0.32439412 1.96339572 -0.99871401]\n", - "P_ = [ 0.32439412 1.96339572 -0.99871401 0.32439412 1.96339572 -0.99871401]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.208312\n", - " Iterations: 311\n", - " Function evaluations: 473\n", - "P = [ 0.26217972 1.80424272 -0.35129935 0.5078583 1.85254454 0.03671439]\n", - "P_ = [ 0.26217972 1.80424272 -0.35129935 0.38501901 1.82839363 -0.15729248\n", - " 0.5078583 1.85254454 0.03671439]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.219960\n", - " Iterations: 366\n", - " Function evaluations: 528\n", - "P = [ 0.20012525 1.94093528 -0.26535981 0.43799293 1.75022651 -0.22456591\n", - " 0.5090615 1.76665699 0.04166658]\n", - "P_ = [ 0.20012525 1.94093528 -0.26535981 0.3587037 1.8137961 -0.23816387\n", - " 0.46168245 1.75570334 -0.13582174 0.5090615 1.76665699 0.04166658]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.679552\n", - " Iterations: 81\n", - " Function evaluations: 135\n", - "P = [ 0.18654845 1.87528474 -0.24305847 0.37668902 1.81654489 -0.24293966\n", - " 0.46659591 1.71168275 -0.14271432 0.54750157 1.71263381 0.04303803]\n", - "P_ = [ 0.18654845 1.87528474 -0.24305847 0.32915388 1.83122985 -0.24296936\n", - " 0.42164246 1.76411382 -0.19282699 0.48682232 1.71192052 -0.09627623\n", - " 0.54750157 1.71263381 0.04303803]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.324722\n", - " Iterations: 156\n", - " Function evaluations: 231\n", - "P = [ 0.16464461 1.93285681 -0.24646962 0.3622098 1.7844019 -0.23047211\n", - " 0.40619753 1.7514643 -0.20423048 0.51389541 1.69142211 -0.09825361\n", - " 0.59388251 1.67947866 0.04437041]\n", - "P_ = [ 0.16464461 1.93285681 -0.24646962 0.32269676 1.81409288 -0.23367161\n", - " 0.38860244 1.76463934 -0.21472713 0.44927668 1.72744742 -0.16183973\n", - " 0.52989283 1.68903342 -0.0697288 0.59388251 1.67947866 0.04437041]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.972413\n", - " Iterations: 1057\n", - " Function evaluations: 1395\n", - "P = [ 0.15609241 1.87925784 -0.49260073 0.35000062 1.84695576 0.24350808\n", - " 0.40163896 1.72400226 -0.31004419 0.47007855 1.73367493 -0.29459646\n", - " 0.57941146 1.66976503 -0.11631075 0.63824295 1.65773143 -0.03718116]\n", - "P_ = [ 0.15609241 1.87925784 -0.49260073 0.31768259 1.85233944 0.12082328\n", - " 0.38442618 1.76498676 -0.12552677 0.43585876 1.72883859 -0.30232032\n", - " 0.50652285 1.71237163 -0.23516789 0.58921671 1.66775943 -0.10312249\n", - " 0.63824295 1.65773143 -0.03718116]\n", - "Depth = 7, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.794555\n", - " Iterations: 200\n", - " Function evaluations: 298\n", - "P = [ 0.15172502 1.93394388 -0.44220037 0.32177942 1.81536762 0.12372942\n", - " 0.3810854 1.75594358 -0.12932338 0.43097898 1.71801787 -0.29957178\n", - " 0.51152272 1.6947149 -0.24352584 0.60401109 1.66203173 -0.10551066\n", - " 0.64232736 1.645698 -0.03840131]\n", - "P_ = [ 0.15172502 1.93394388 -0.44220037 0.29748594 1.83230709 0.04288231\n", - " 0.36414083 1.77292188 -0.05702258 0.40959602 1.73427175 -0.22660818\n", - " 0.46549773 1.70803088 -0.2755521 0.53794797 1.68537685 -0.20409293\n", - " 0.60948484 1.65969834 -0.09592361 0.64232736 1.645698 -0.03840131]\n", - "Depth = 8, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 1.690816\n", - " Iterations: 214\n", - " Function evaluations: 324\n", - "P = [ 0.13800065 1.92586171 -0.43213112 0.30711742 1.83451563 0.04344176\n", - " 0.35971461 1.77006362 -0.05884196 0.41791864 1.73436051 -0.22628098\n", - " 0.44985795 1.69559604 -0.27223865 0.54427688 1.68112968 -0.20634549\n", - " 0.63025481 1.65664488 -0.10153944 0.6510978 1.62712077 -0.03879132]\n", - "P_ = [ 0.13800065 1.92586171 -0.43213112 0.28597782 1.84593389 -0.01600485\n", - " 0.34656531 1.78617662 -0.03327103 0.39609213 1.74774918 -0.16349135\n", - " 0.4338883 1.71497828 -0.24925982 0.48526505 1.69017116 -0.24752872\n", - " 0.56577136 1.67500848 -0.18014397 0.63286018 1.65295436 -0.09369592\n", - " 0.6510978 1.62712077 -0.03879132]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.549618\n", - " Iterations: 2320\n", - " Function evaluations: 2871\n", - "P = [ 0.13070469 1.96690965 -0.37162686 0.27454446 1.78473138 -0.01672886\n", - " 0.32057151 1.81513823 -0.04202008 0.36593126 1.70481279 -0.41847365\n", - " 0.41853567 1.7459968 0.30065686 0.44445993 1.66279077 -0.02667867\n", - " 0.50101017 1.68426398 -0.34673702 0.60493873 1.64702245 -0.1674458\n", - " 0.65830428 1.64021225 -0.04535442]\n", - "P_ = [ 0.13070469 1.96690965 -0.37162686 0.25856226 1.80497341 -0.05616197\n", - " 0.31034328 1.80838115 -0.03639981 0.35081134 1.74158793 -0.29298913\n", - " 0.39515593 1.72769279 -0.0189567 0.43005756 1.70901634 0.15517441\n", - " 0.46331001 1.66994851 -0.13336478 0.5241054 1.67598808 -0.30689453\n", - " 0.61086824 1.64626576 -0.15388009 0.65830428 1.64021225 -0.04535442]\n", - "Depth = 10, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.496278\n", - " Iterations: 647\n", - " Function evaluations: 859\n", - "P = [ 0.12473528 1.91587636 -0.36995342 0.26174075 1.81233608 -0.05780648\n", - " 0.30649706 1.77112144 -0.0424133 0.35054253 1.74430337 -0.34865061\n", - " 0.38835137 1.70931205 -0.02028243 0.441177 1.70658688 0.15938624\n", - " 0.45200131 1.65387801 -0.14956891 0.54830255 1.67387797 -0.30868876\n", - " 0.63891632 1.6369477 -0.0586031 0.65210927 1.62352903 -0.05100309]\n", - "P_ = [ 0.12473528 1.91587636 -0.36995342 0.24804021 1.82269011 -0.08902118\n", - " 0.2975458 1.77936437 -0.04549194 0.33732888 1.75234879 -0.25677942\n", - " 0.37322783 1.72330858 -0.1516297 0.41476418 1.70794947 0.0695519\n", - " 0.44550672 1.68550334 0.03580418 0.48089168 1.659878 -0.19730487\n", - " 0.56642531 1.66649192 -0.25867163 0.64023561 1.63560583 -0.0578431\n", - " 0.65210927 1.62352903 -0.05100309]\n", - "Depth = 11, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.465081\n", - " Iterations: 294\n", - " Function evaluations: 438\n", - "P = [ 0.11432101 1.9321558 -0.3582844 0.2522788 1.81811521 -0.09058005\n", - " 0.29547136 1.77229365 -0.04645384 0.33971912 1.75173742 -0.26712699\n", - " 0.3738043 1.72652287 -0.15446207 0.41325009 1.70733031 0.07016692\n", - " 0.44906139 1.68711033 0.0362368 0.47690329 1.65959016 -0.20104971\n", - " 0.57103437 1.66009976 -0.25980259 0.64149764 1.63423885 -0.05828043\n", - " 0.65220339 1.61788157 -0.05169853]\n", - "P_ = [ 0.11432101 1.9321558 -0.3582844 0.23973719 1.82848254 -0.11491681\n", - " 0.28761817 1.78062484 -0.05447678 0.32765155 1.75734366 -0.2069434\n", - " 0.36140969 1.73569179 -0.19543113 0.39532018 1.7160542 -0.03193717\n", - " 0.42952795 1.69813941 0.05474414 0.45918571 1.677103 -0.0500492\n", - " 0.5025754 1.65972914 -0.21707322 0.58384587 1.65539777 -0.22316219\n", - " 0.64247089 1.63275183 -0.05768207 0.65220339 1.61788157 -0.05169853]\n", - "Depth = 12, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.415530\n", - " Iterations: 1773\n", - " Function evaluations: 2170\n", - "P = [ 0.09689657 1.91763265 -0.20981375 0.21964768 1.82587227 -0.14970917\n", - " 0.28371434 1.77371329 -0.06658276 0.33238924 1.77014105 -0.25428671\n", - " 0.33020815 1.7115467 -0.31013622 0.33312117 1.69659557 -0.03994147\n", - " 0.37155408 1.67532036 0.00805047 0.43372271 1.6855827 -0.05807163\n", - " 0.46105634 1.64834027 -0.30297311 0.54643959 1.65747133 -0.23532715\n", - " 0.62912391 1.6285535 -0.08224117 0.64079645 1.61570558 -0.06820161]\n", - "P_ = [ 0.09689657 1.91763265 -0.20981375 0.20941842 1.83351896 -0.15471789\n", - " 0.27303656 1.78240645 -0.08043716 0.32022052 1.77103411 -0.20736072\n", - " 0.33093518 1.73107815 -0.29151972 0.33190741 1.7028252 -0.15252261\n", - " 0.35233763 1.68595797 -0.0159455 0.39745768 1.67959634 -0.0195004\n", - " 0.44283392 1.67316856 -0.13970546 0.48240215 1.65062304 -0.28606162\n", - " 0.56022031 1.65265169 -0.20981282 0.63009662 1.62748284 -0.08107121\n", - " 0.64079645 1.61570558 -0.06820161]\n", - "Depth = 13, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.397398\n", - " Iterations: 609\n", - " Function evaluations: 818\n", - "P = [ 0.08536073 1.92130049 -0.21123564 0.20492231 1.83032587 -0.1551606\n", - " 0.265166 1.77990317 -0.09448599 0.31677471 1.76254531 -0.2290803\n", - " 0.33803143 1.73167472 -0.29865307 0.33369698 1.69828525 -0.14241063\n", - " 0.35503242 1.68190821 -0.01576668 0.39456789 1.67414495 -0.01979939\n", - " 0.44552738 1.66859128 -0.14074149 0.47494475 1.64315449 -0.268527\n", - " 0.56145517 1.6429204 -0.21009618 0.63282328 1.62174235 -0.08204178\n", - " 0.6477425 1.59916452 -0.06952003]\n", - "P_ = [ 0.08536073 1.92130049 -0.21123564 0.19572526 1.83732392 -0.15947407\n", - " 0.25589774 1.78766051 -0.10382055 0.30486501 1.76655097 -0.19802007\n", - " 0.3314909 1.74117336 -0.27724606 0.33536408 1.71112735 -0.20250388\n", - " 0.34518529 1.68946684 -0.07421774 0.37327956 1.67832517 -0.01762793\n", - " 0.41416769 1.67200893 -0.06631558 0.45457888 1.66076458 -0.18006011\n", - " 0.49490869 1.64310047 -0.25504296 0.57243488 1.63966223 -0.1903955\n", - " 0.63397091 1.62000559 -0.08107857 0.6477425 1.59916452 -0.06952003]\n", - "Depth = 14, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 0.01547177 1.72080732 -0.83584443 0.11152703 1.85320389 -0.77197364\n", - " 0.15676095 1.69934189 -0.31051537 0.21717961 1.72653077 -1.62428669\n", - " 0.31415118 1.79045869 -1.19801299 0.34038488 1.73323003 -2.30653505\n", - " 0.36396548 1.74562215 0.51828542 0.13734966 1.59502871 0.04354591\n", - " 0.37818041 1.72162285 -1.47748579 0.46375172 1.69558348 0.00593585\n", - " 0.5153487 1.66563761 -0.19456375 0.59133549 1.65435206 0.54113699\n", - " 0.6520662 1.622769 0.36505998 0.62022816 1.63045542 0.04845758]\n", - "P_ = [ 0.01547177 1.72080732 -0.83584443 0.10466594 1.843747 -0.77653584\n", - " 0.15029897 1.72132218 -0.37643798 0.20423275 1.72070458 -1.34276426\n", - " 0.28644501 1.77219357 -1.31980548 0.3310157 1.75366883 -1.91063431\n", - " 0.35385951 1.74031124 -0.69235192 0.25065757 1.67032543 0.28091566\n", - " 0.24056284 1.64928334 -0.60832482 0.40874159 1.71232307 -0.94769235\n", - " 0.47849371 1.68702751 -0.05134975 0.53163158 1.66321927 -0.03691359\n", - " 0.6000113 1.64984019 0.51598313 0.64979206 1.62331803 0.34244552\n", - " 0.62022816 1.63045542 0.04845758]\n", - "Depth = 15, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 0.03684835 1.96828914 -1.20873558 0.17137257 1.90223319 -2.08367735\n", - " 0.05730993 1.59603565 0.10767099 0.24065133 1.78533373 -3.40126853\n", - " 0.2748636 1.73888046 -2.18475699 0.30966934 1.75999628 -2.50878836\n", - " 0.31422566 1.70198496 -1.78338777 0.35650748 1.72987269 -1.37130472\n", - " 0.34625437 1.69393984 -1.23858724 0.40500279 1.70531367 -0.98171695\n", - " 0.44793507 1.67765829 -0.15781838 0.4534314 1.64887818 -0.08510087\n", - " 0.48857658 1.63757867 -0.39536005 0.55750413 1.62474831 -0.63655012\n", - " 0.5779879 1.6236585 0.05215222]\n", - "P_ = [ 0.03684835 1.96828914 -1.20873558 0.16240429 1.90663692 -2.0253479\n", - " 0.07251828 1.63686199 -0.18450879 0.20398305 1.74747412 -2.69948063\n", - " 0.26574033 1.751268 -2.50916007 0.29806743 1.75295767 -2.40077791\n", - " 0.31240313 1.72518949 -2.07354801 0.33677596 1.71685841 -1.56361014\n", - " 0.35172269 1.71310402 -1.30936989 0.36975374 1.69848937 -1.13583912\n", - " 0.41931355 1.69609521 -0.70708409 0.44940076 1.66998359 -0.13842704\n", - " 0.46046044 1.64661828 -0.1471527 0.49776692 1.63586795 -0.42751873\n", - " 0.55886971 1.62467566 -0.59063663 0.5779879 1.6236585 0.05215222]\n", - "Depth = 16, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 1.022240\n", - " Iterations: 1321\n", - " Function evaluations: 1705\n", - "P = [ 0.03946379 1.95487467 -1.19020552 0.15664938 1.88824394 -2.07918298\n", - " 0.07149722 1.60236963 -0.18497619 0.20214726 1.76432647 -2.75720813\n", - " 0.27369996 1.75276083 -2.51434078 0.30303907 1.75164928 -2.44164383\n", - " 0.31471398 1.72085925 -2.08131831 0.3338603 1.71645702 -1.60789796\n", - " 0.34118491 1.70506433 -1.34512975 0.36803836 1.70335154 -1.13569654\n", - " 0.41447497 1.68110307 -0.68765559 0.44811014 1.6669401 -0.13897143\n", - " 0.4603114 1.6357904 -0.1489278 0.51311119 1.63946579 -0.42184046\n", - " 0.55976184 1.62242262 -0.58313555 0.57753044 1.61225463 0.05180412]\n", - "P_ = [ 0.03946379 1.95487467 -1.19020552 0.14932528 1.89240836 -2.02362189\n", - " 0.08214124 1.63810392 -0.42175204 0.17765038 1.73395957 -2.27491464\n", - " 0.25581179 1.75565224 -2.57505762 0.2938706 1.75199664 -2.46436163\n", - " 0.31033589 1.73240551 -2.21644038 0.32548379 1.718383 -1.81501936\n", - " 0.3375226 1.71076068 -1.47651386 0.35293329 1.70431499 -1.25350272\n", - " 0.38545209 1.69500836 -0.96768118 0.42498596 1.67667714 -0.51619179\n", - " 0.45116046 1.65915267 -0.14146052 0.47021136 1.63647954 -0.20009893\n", - " 0.51894252 1.63733539 -0.44200234 0.56087238 1.62178712 -0.54345182\n", - " 0.57753044 1.61225463 0.05180412]\n", - "Depth = 17, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 0.989319\n", - " Iterations: 5366\n", - " Function evaluations: 6286\n", - "P = [ 0.05076867 1.97784985 -1.18164855 0.15143047 1.82492938 -1.90755827\n", - " 0.0887441 1.6566417 -0.34719966 0.18207837 1.73505114 -2.52366523\n", - " 0.25126491 1.7437503 -2.01050811 0.28404084 1.73337116 -2.4341074\n", - " 0.3309573 1.74526659 -2.39965508 0.33670325 1.71782466 -2.09387674\n", - " 0.33529447 1.71307323 -1.58089543 0.3380935 1.69624652 -1.30911399\n", - " 0.361339 1.69050977 -0.87865415 0.40431404 1.66494202 -0.70734754\n", - " 0.46525413 1.67804989 -0.12007072 0.45016972 1.61816511 -0.21394064\n", - " 0.55896169 1.64818557 -0.16355392 0.65178034 1.62067208 -0.44334364\n", - " 0.67965391 1.61120946 0.04988414]\n", - "P_ = [ 0.05076867 1.97784985 -1.18164855 0.14550919 1.83392471 -1.8648577\n", - " 0.09611897 1.67644025 -0.53077126 0.16560761 1.72121418 -2.13958307\n", - " 0.23498573 1.74170344 -2.13125096 0.27440086 1.73642384 -2.30951938\n", - " 0.31439855 1.7410682 -2.41181472 0.33433727 1.72912428 -2.21978547\n", - " 0.33595743 1.7153092 -1.8222984 0.33661166 1.70515478 -1.45299828\n", - " 0.34766517 1.69388433 -1.13186582 0.37650666 1.68148586 -0.81819299\n", - " 0.4222376 1.66879728 -0.53461906 0.46170486 1.66395935 -0.14215776\n", - " 0.4693683 1.62346284 -0.20504887 0.56988153 1.64494869 -0.19647036\n", - " 0.65341996 1.62011545 -0.41433025 0.67965391 1.61120946 0.04988414]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 0.973834\n", - " Iterations: 1599\n", - " Function evaluations: 2045\n", - "P = [ 0.05270028 1.97879652 -1.16405993 0.13715572 1.81596414 -1.90856571\n", - " 0.09387239 1.66737019 -0.53908476 0.16300998 1.73246392 -2.20194707\n", - " 0.23614499 1.74305877 -2.13063676 0.27697276 1.73754484 -2.35479125\n", - " 0.31134814 1.73901582 -2.42455444 0.33319263 1.72561731 -2.24928733\n", - " 0.33935877 1.71875876 -1.85958336 0.33826189 1.70307954 -1.49993623\n", - " 0.34676307 1.69171398 -1.18823838 0.37454041 1.67950458 -0.82650191\n", - " 0.42784672 1.6650836 -0.55087359 0.47819713 1.66360827 -0.13841482\n", - " 0.47995923 1.61946679 -0.20043401 0.56415969 1.64202314 -0.190164\n", - " 0.64205121 1.61452828 -0.40350147 0.65723453 1.60750486 0.04953926]\n", - "P_ = [ 0.05270028 1.97879652 -1.16405993 0.13246376 1.82501039 -1.86720428\n", - " 0.09868165 1.68388063 -0.69124931 0.15148705 1.72161496 -1.92480335\n", - " 0.21989276 1.74070436 -2.14648349 0.26563171 1.73907649 -2.29252611\n", - " 0.29988968 1.73852549 -2.40130004 0.32469755 1.73082784 -2.31744676\n", - " 0.33661826 1.72180701 -2.03278512 0.33881033 1.71091915 -1.67975979\n", - " 0.34204019 1.69802818 -1.36140385 0.35756537 1.68696588 -1.04756308\n", - " 0.39230918 1.67469758 -0.7346258 0.44183295 1.66467378 -0.43630171\n", - " 0.47858871 1.65379905 -0.15219686 0.49399264 1.62322618 -0.19872234\n", - " 0.5728143 1.63896815 -0.21386816 0.64289472 1.61413809 -0.37833254\n", - " 0.65723453 1.60750486 0.04953926]\n", - "Depth = 19, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 0.05383976 1.97833168 -1.58029231 0.12220778 1.73430629 -1.80467095\n", - " 0.08016236 1.6823455 -0.6717016 0.16046217 1.72717062 -2.17982688\n", - " 0.22431627 1.76107189 -2.55461574 0.25225658 1.73417997 -3.06121098\n", - " 0.28193736 1.72689384 -2.32843259 0.30254221 1.72203039 -2.77588006\n", - " 0.32895402 1.72289907 -2.31755689 0.34530722 1.72640265 -2.27679606\n", - " 0.32811071 1.68917411 -1.45815703 0.33222911 1.69163138 -1.15478943\n", - " 0.35191339 1.6652686 -0.8482813 0.43142477 1.67908219 -0.57664932\n", - " 0.47663144 1.65989431 -0.13650146 0.48888392 1.62551889 0.06275188\n", - " 0.59760081 1.6358343 -0.22347705 0.65959691 1.6195121 -0.20644558\n", - " 0.6527166 1.60978139 0.06654986]\n", - "P_ = [ 0.05383976 1.97833168 -1.58029231 0.11860946 1.74714973 -1.79286155\n", - " 0.08458819 1.68781506 -0.79096153 0.14778325 1.72009297 -1.94170184\n", - " 0.21087331 1.75393478 -2.47571283 0.24490387 1.74125679 -2.92789645\n", - " 0.27256448 1.72919472 -2.55983629 0.29495095 1.72382219 -2.61103099\n", - " 0.31783326 1.72253331 -2.51053506 0.33756097 1.72474306 -2.29610382\n", - " 0.3371615 1.70876808 -1.88901968 0.32984477 1.69020875 -1.3304233\n", - " 0.33948122 1.68191878 -1.04186538 0.37702225 1.66963079 -0.76250278\n", - " 0.44332126 1.67403275 -0.46082093 0.47921091 1.65265738 -0.09455339\n", - " 0.50604975 1.62714764 0.01755784 0.60412672 1.63411618 -0.22168426\n", - " 0.65923478 1.61899995 -0.1920774 0.6527166 1.60978139 0.06654986]\n", - "Depth = 20, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 0.950058\n", - " Iterations: 1608\n", - " Function evaluations: 2075\n", - "0.9285714285714285 [6.78232723 4.20831158 3.21996038 2.67955152 2.32472243 1.97241296\n", - " 1.79455456 1.69081594 1.54961832 1.49627794 1.46508125 1.41552997\n", - " 1.39739759 1.23014625 1.0619735 1.02223964 0.98931894 0.97383434\n", - " 0.95735817 0.95005802]\n", - "[[6.20528854 5.90276273 4.34974565 2.82648708 2.83216236 2.53390824\n", - " 2.48542936 2.39488186 1.78514917 1.78156864 1.63586622 1.93423131\n", - " 1.3466511 1.61587827 1.31723472 1.39380148 1.3212952 1.48519626\n", - " 1.19207192 1.19585198]\n", - " [7.30404471 4.53202785 3.46764965 2.88567087 2.50354724 2.12413704\n", - " 1.93259722 1.8208787 1.66881973 1.61137624 1.5777798 1.52441689\n", - " 1.50488971 1.32477289 1.14366376 1.10087346 1.06542039 1.04874467\n", - " 1.03100111 1.02313941]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]] [1.35093332 1.04347906 0.78173953 0.57121579 0.53357096 0.46580453\n", - " 0.44180266 0.42157606 0.34539689 0.33929449 0.3213646 0.34586482\n", - " 0.28515408 0.29406512 0.24608985 0.24946749 0.23867156 0.25339409\n", - " 0.2223073 0.22189914]\n", - "[[0.17030757 0.16850299 0.24687602 0.45514832 0.45145637 0.56268179\n", - " 0.4723914 0.62266371 0.8026945 0.81119819 0.87005395 0.73125403\n", - " 0.9110609 0.83507433 0.90935654 0.90735586 0.92006095 0.88620215\n", - " 0.96581763 0.96554472]\n", - " [0.18431054 0.3834123 0.50873566 0.61052141 0.696016 0.79140483\n", - " 0.84466927 0.87844738 0.91858227 0.93545701 0.95087783 0.95794391\n", - " 0.96260089 0.96665922 0.98020554 0.98747975 0.99371878 0.99672513\n", - " 0.99769447 0.9985309 ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]] [0.03546181 0.05519153 0.07556117 0.10656697 0.11474724 0.13540866\n", - " 0.13170607 0.15011111 0.17212768 0.17466552 0.18209318 0.16891979\n", - " 0.18736618 0.18017336 0.18895621 0.18948356 0.19137797 0.18829273\n", - " 0.19635121 0.19640756]\n", - "\n", - "Now using 3 solutions, set number 3\n", - "Calculating energy landscape ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 7.582433\n", - " Iterations: 76\n", - " Function evaluations: 133\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 7.582433\n", - " Iterations: 18\n", - " Function evaluations: 35\n", - "P = [ 0.32081448 2.01979286 -0.32070449]\n", - "P_ = [ 0.32081448 2.01979286 -0.32070449 0.32081448 2.01979286 -0.32070449]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.243458\n", - " Iterations: 109\n", - " Function evaluations: 175\n", - "P = [ 0.1903835 1.79246955 -0.34115475 0.41965285 1.86446194 -0.27869995]\n", - "P_ = [ 0.1903835 1.79246955 -0.34115475 0.30501817 1.82846574 -0.30992735\n", - " 0.41965285 1.86446194 -0.27869995]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.640055\n", - " Iterations: 145\n", - " Function evaluations: 219\n", - "P = [ 0.16461571 1.98443818 -0.37072258 0.31353654 1.69631017 -0.32894311\n", - " 0.33873503 1.7333566 -0.2948949 ]\n", - "P_ = [ 0.16461571 1.98443818 -0.37072258 0.26389626 1.79235284 -0.3428696\n", - " 0.32193604 1.70865898 -0.31759371 0.33873503 1.7333566 -0.2948949 ]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.985613\n", - " Iterations: 250\n", - " Function evaluations: 368\n", - "P = [ 0.09870602 2.03797567 -0.35853087 0.21287591 1.99184538 -0.44389035\n", - " 0.31582436 1.69914379 -0.30621753 0.41935333 1.750912 -0.38400453]\n", - "P_ = [ 0.09870602 2.03797567 -0.35853087 0.18433344 2.00337796 -0.42255048\n", - " 0.26435014 1.84549458 -0.37505394 0.3417066 1.71208584 -0.32566428\n", - " 0.41935333 1.750912 -0.38400453]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.244063\n", - " Iterations: 897\n", - " Function evaluations: 1204\n", - "P = [ 0.09546701 2.16149461 -0.67125599 0.25982905 1.77637499 -0.07523623\n", - " 0.34087666 1.83392976 -0.67748191 0.46434086 1.61473823 -0.1949075\n", - " 0.71375053 1.74090867 -0.04941159]\n", - "P_ = [ 0.09546701 2.16149461 -0.67125599 0.22695664 1.85339891 -0.19444018\n", - " 0.30845762 1.81090785 -0.43658364 0.39026234 1.74625315 -0.48445214\n", - " 0.51422279 1.63997232 -0.16580832 0.71375053 1.74090867 -0.04941159]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.730792\n", - " Iterations: 355\n", - " Function evaluations: 497\n", - "P = [ 0.09370184 1.98885971 -0.68235497 0.24989254 1.90981722 -0.17993969\n", - " 0.34714667 1.70600831 -0.43267136 0.42275592 1.73891749 -0.52894917\n", - " 0.58140587 1.62863299 -0.15095641 0.52446715 1.72009826 -0.0514019 ]\n", - "P_ = [ 0.09370184 1.98885971 -0.68235497 0.22386076 1.92299097 -0.26367557\n", - " 0.31472863 1.77394461 -0.34842747 0.38495129 1.7224629 -0.48081027\n", - " 0.47563923 1.70215599 -0.40295158 0.57191608 1.6438772 -0.13436399\n", - " 0.52446715 1.72009826 -0.0514019 ]\n", - "Depth = 7, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.429493\n", - " Iterations: 833\n", - " Function evaluations: 1122\n", - "P = [ 0.08465426 2.04302947 -0.35522255 0.1969229 1.93441428 -0.29308491\n", - " 0.31555139 1.82988007 -0.33793937 0.3887191 1.6859591 -0.18404148\n", - " 0.47246787 1.7061529 -0.45057951 0.55785208 1.64801885 -0.17246939\n", - " 0.5497734 1.69522559 -0.06430227]\n", - "P_ = [ 0.08465426 2.04302947 -0.35522255 0.18088452 1.94993074 -0.30196172\n", - " 0.28165753 1.85974699 -0.32512381 0.35736151 1.74763952 -0.24999772\n", - " 0.42461143 1.69461359 -0.29827206 0.49686336 1.68954317 -0.37111947\n", - " 0.55669798 1.65476267 -0.15701695 0.5497734 1.69522559 -0.06430227]\n", - "Depth = 8, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.134069\n", - " Iterations: 913\n", - " Function evaluations: 1198\n", - "P = [ 0.08989168 1.91636503 -0.50120104 0.22460311 1.99519053 -0.22408707\n", - " 0.31587041 1.71255952 -0.49192131 0.40049058 1.80312702 -0.3227638\n", - " 0.46627639 1.60746718 -0.1443585 0.51481433 1.73721411 -0.17551317\n", - " 0.57529236 1.63692829 -0.17428971 0.64023931 1.67855631 -0.03998375]\n", - "P_ = [ 0.08989168 1.91636503 -0.50120104 0.20776418 1.98533735 -0.25872632\n", - " 0.29305359 1.78321727 -0.42496275 0.36875801 1.76916421 -0.38619786\n", - " 0.43338348 1.7052971 -0.23356115 0.48447812 1.65612228 -0.1560415\n", - " 0.52993383 1.71214265 -0.17520731 0.58341073 1.6421318 -0.15750146\n", - " 0.64023931 1.67855631 -0.03998375]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.000663\n", - " Iterations: 334\n", - " Function evaluations: 465\n", - "P = [ 0.08524977 1.98426368 -0.49742772 0.20771527 1.91868723 -0.26196983\n", - " 0.30110729 1.79365414 -0.45940595 0.38036662 1.74618822 -0.38691705\n", - " 0.44933418 1.69304074 -0.23870253 0.49926559 1.66567997 -0.15234196\n", - " 0.51662548 1.69560648 -0.17865441 0.56018275 1.62667859 -0.16028971\n", - " 0.52598932 1.65312646 -0.04389114]\n", - "P_ = [ 0.08524977 1.98426368 -0.49742772 0.19410799 1.92597351 -0.28813182\n", - " 0.28035351 1.82143927 -0.41553126 0.35394685 1.76201019 -0.41108002\n", - " 0.41868193 1.71666184 -0.30457565 0.47152591 1.6808804 -0.20032005\n", - " 0.50505222 1.67565548 -0.16111278 0.52630487 1.68028917 -0.17457337\n", - " 0.55638348 1.62961724 -0.14735653 0.52598932 1.65312646 -0.04389114]\n", - "Depth = 10, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.984991\n", - " Iterations: 351\n", - " Function evaluations: 494\n", - "P = [ 0.08283979 1.98990409 -0.48263004 0.1876815 1.93947832 -0.3113359\n", - " 0.27657171 1.82604048 -0.43456901 0.35502172 1.7651431 -0.40553091\n", - " 0.43610007 1.70057744 -0.3054732 0.48442991 1.68947804 -0.20302473\n", - " 0.52232948 1.66620219 -0.15331299 0.52434836 1.66988494 -0.17314247\n", - " 0.53317477 1.62932578 -0.14899027 0.53536205 1.61440392 -0.04422335]\n", - "P_ = [ 0.08283979 1.98990409 -0.48263004 0.17719733 1.94452089 -0.32846531\n", - " 0.25879367 1.84872804 -0.40992239 0.33148672 1.78341231 -0.41424234\n", - " 0.40366873 1.7264037 -0.34549628 0.46026499 1.69502774 -0.25424896\n", - " 0.49958974 1.6801677 -0.18314003 0.52293514 1.66730702 -0.15926183\n", - " 0.52611364 1.66177311 -0.16831203 0.5333935 1.6278336 -0.13851358\n", - " 0.53536205 1.61440392 -0.04422335]\n", - "Depth = 11, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.939192\n", - " Iterations: 712\n", - " Function evaluations: 923\n", - "P = [ 0.07195977 1.98828137 -0.29636077 0.1678825 1.97621044 -0.39463076\n", - " 0.26343734 1.84820111 -0.51419187 0.33890927 1.78795234 -0.42012811\n", - " 0.40908048 1.72258162 -0.37082146 0.47409992 1.68187522 -0.2687075\n", - " 0.50078621 1.68835524 -0.18481311 0.52691461 1.66104282 -0.17172741\n", - " 0.51641372 1.66203243 -0.1698504 0.54263839 1.60912926 -0.13658423\n", - " 0.53545808 1.59796108 -0.04229212]\n", - "P_ = [ 0.07195977 1.98828137 -0.29636077 0.15916225 1.9773078 -0.38569712\n", - " 0.24606373 1.87147553 -0.49245348 0.31832602 1.80438382 -0.44578187\n", - " 0.38356368 1.74635279 -0.38875115 0.44454563 1.70037813 -0.31512294\n", - " 0.48623005 1.68482068 -0.23057369 0.51028744 1.67842345 -0.18005467\n", - " 0.52405073 1.66131271 -0.1712155 0.52118184 1.65241367 -0.16380201\n", - " 0.54198564 1.60811397 -0.12801222 0.53545808 1.59796108 -0.04229212]\n", - "Depth = 12, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 0.08153891 1.99901638 0.19094891 0.17547289 2.00818733 -0.71771161\n", - " 0.28384335 1.84912651 -0.29865843 0.3370933 1.83541651 -1.34154186\n", - " 0.37240287 1.74169359 -0.85306826 0.41436591 1.72197309 -0.39633061\n", - " 0.49322221 1.71669332 -0.6949135 0.50925352 1.70209682 -0.52244678\n", - " 0.43142571 1.64386442 -0.29486606 0.55340621 1.67197132 -0.16910418\n", - " 0.67426445 1.64315986 0.09511029 0.65633562 1.62569895 0.19396201]\n", - "P_ = [ 0.08153891 1.99901638 0.19094891 0.16764506 2.00742308 -0.6419899\n", - " 0.26578161 1.87563664 -0.36850062 0.32378081 1.83884401 -1.080821\n", - " 0.36063301 1.77293456 -1.01589279 0.39688131 1.73018996 -0.58663796\n", - " 0.45379406 1.7193332 -0.54562206 0.49990192 1.71061144 -0.62305237\n", - " 0.48331091 1.68268602 -0.44658654 0.46192083 1.65089115 -0.26342559\n", - " 0.57354925 1.66716941 -0.12506844 0.67277039 1.64170478 0.10334794\n", - " 0.65633562 1.62569895 0.19396201]\n", - "Depth = 13, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 0.07464087 2.04623679 0.10210785 0.19508765 1.93120639 -0.89113435\n", - " 0.30137603 1.87283564 -0.34186382 0.3370354 1.83740901 -2.20026748\n", - " 0.34657022 1.75696334 -0.62953457 0.32790803 1.77022858 -1.55390508\n", - " 0.38154497 1.7890616 -1.46628098 0.4357355 1.75429041 -0.64412083\n", - " 0.44329641 1.70882185 -0.64975626 0.46914373 1.65352341 -0.64295977\n", - " 0.54466961 1.70978174 -0.16383734 0.6110678 1.6573369 -0.12289987\n", - " 0.60077656 1.64482487 0.11293546]\n", - "P_ = [ 0.07464087 2.04623679 0.10210785 0.18582251 1.94005488 -0.8147311\n", - " 0.28502397 1.88181576 -0.42636698 0.32880631 1.84558438 -1.7714051\n", - " 0.34363643 1.78171585 -1.11283701 0.33508579 1.76512656 -1.19837796\n", - " 0.35678946 1.78036944 -1.50672287 0.40655599 1.77301336 -1.08682245\n", - " 0.43864354 1.7368025 -0.6462883 0.45124943 1.69180694 -0.64766503\n", - " 0.48657278 1.6665061 -0.53239305 0.55488471 1.70171331 -0.15753927\n", - " 0.61027616 1.65637444 -0.10475869 0.60077656 1.64482487 0.11293546]\n", - "Depth = 14, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.559632\n", - " Iterations: 1531\n", - " Function evaluations: 1893\n", - "P = [ 0.06362302 2.02508845 0.11400758 0.16687964 1.96021473 -0.7321995\n", - " 0.27607866 1.85654529 -0.50178531 0.3267325 1.82125954 -1.84784653\n", - " 0.35946282 1.76618073 -1.11621117 0.35972056 1.76072227 -1.34867154\n", - " 0.36885965 1.76043574 -1.48011418 0.41104607 1.77025577 -1.12016244\n", - " 0.43846775 1.70779508 -0.63658235 0.46323789 1.69480055 -0.57906672\n", - " 0.4945663 1.66590283 -0.53400817 0.54604162 1.68956581 -0.17576396\n", - " 0.5898625 1.64422776 -0.11682443 0.62866424 1.62868467 0.09385608]\n", - "P_ = [ 0.06362302 2.02508845 0.11400758 0.15950417 1.96484857 -0.67175614\n", - " 0.2604788 1.87135521 -0.53470163 0.31587811 1.82882077 -1.55940484\n", - " 0.3501113 1.78191754 -1.32524984 0.35962851 1.76267172 -1.26564998\n", - " 0.3649429 1.76055854 -1.42378162 0.38995286 1.76534575 -1.30013831\n", - " 0.42279822 1.7434869 -0.91291383 0.44731423 1.70315418 -0.61604105\n", - " 0.47218886 1.68654406 -0.56619285 0.50559672 1.67097347 -0.45724156\n", - " 0.55230175 1.68308895 -0.16734402 0.59263405 1.64311754 -0.10177583\n", - " 0.62866424 1.62868467 0.09385608]\n", - "Depth = 15, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.535781\n", - " Iterations: 1479\n", - " Function evaluations: 1840\n", - "P = [ 0.06152386 1.99912723 0.12393824 0.14758523 1.96523065 -0.62121414\n", - " 0.24597088 1.85058665 -0.52228673 0.31663514 1.8133735 -1.60934115\n", - " 0.36894456 1.77042041 -1.27933482 0.37699626 1.75133479 -1.33191682\n", - " 0.37526429 1.74798528 -1.45461448 0.39383189 1.76220798 -1.27133318\n", - " 0.4198028 1.74299947 -0.9565692 0.44767364 1.69384471 -0.53743215\n", - " 0.486653 1.69028933 -0.555606 0.50630323 1.66963784 -0.38812998\n", - " 0.54496363 1.67565448 -0.17422147 0.59239348 1.63814221 -0.12251931\n", - " 0.64122975 1.61193774 0.10043124]\n", - "P_ = [ 0.06152386 1.99912723 0.12393824 0.14184781 1.96749042 -0.57153732\n", - " 0.23285279 1.86587251 -0.53547705 0.30250228 1.82081613 -1.39193027\n", - " 0.35499538 1.78187457 -1.36733651 0.37431236 1.75769666 -1.31438949\n", - " 0.37595708 1.74932508 -1.40553542 0.38516701 1.75557072 -1.35686446\n", - " 0.40595165 1.75324401 -1.12444332 0.43095114 1.72333757 -0.78891438\n", - " 0.46066676 1.69265959 -0.5434901 0.49189306 1.68478227 -0.51094573\n", - " 0.51403531 1.67084116 -0.34534828 0.55128761 1.67065284 -0.16732785\n", - " 0.59564923 1.63639524 -0.10765594 0.64122975 1.61193774 0.10043124]\n", - "Depth = 16, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.522982\n", - " Iterations: 1491\n", - " Function evaluations: 1877\n", - "P = [ 0.05403534 1.98027117 0.12489286 0.13446499 1.9703164 -0.58699667\n", - " 0.21973549 1.85975607 -0.53291396 0.2905488 1.81160273 -1.44441435\n", - " 0.360165 1.77754902 -1.34452423 0.38845635 1.75243189 -1.33723963\n", - " 0.38458549 1.74028096 -1.47138322 0.39210828 1.74682165 -1.26330672\n", - " 0.41318238 1.74711633 -1.14980704 0.43576198 1.72021959 -0.81276358\n", - " 0.46605241 1.68279887 -0.41931471 0.50207297 1.68727232 -0.50461583\n", - " 0.51450798 1.66718011 -0.36045895 0.54826724 1.66204881 -0.17369766\n", - " 0.59058216 1.62769144 -0.11240185 0.66080769 1.60057813 0.10414672]\n", - "P_ = [ 0.05403534 1.98027117 0.12489286 0.12943813 1.97093857 -0.54250358\n", - " 0.20907668 1.87357611 -0.5396743 0.2772713 1.82063148 -1.27350803\n", - " 0.34276095 1.78606245 -1.36949676 0.3796153 1.76028099 -1.33951607\n", - " 0.38603706 1.74483756 -1.42107937 0.38881706 1.7439601 -1.35434019\n", - " 0.40264533 1.74696899 -1.20655688 0.42306095 1.73534901 -1.00235053\n", - " 0.44712089 1.70618682 -0.66522025 0.47730883 1.68419682 -0.44597131\n", - " 0.50518172 1.68224927 -0.46857661 0.52083784 1.66621799 -0.32544121\n", - " 0.55355661 1.65775414 -0.16603568 0.59497126 1.62599686 -0.09886756\n", - " 0.66080769 1.60057813 0.10414672]\n", - "Depth = 17, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.512650\n", - " Iterations: 2387\n", - " Function evaluations: 2880\n", - "P = [ 0.0467971 1.98224194 0.12143971 0.12753231 1.95067365 -0.63622843\n", - " 0.20448663 1.85853927 -0.42541574 0.26396684 1.80815953 -1.36312081\n", - " 0.34366007 1.78114981 -1.27655428 0.39108047 1.75791416 -1.23918634\n", - " 0.38997824 1.74290109 -1.60693739 0.38784424 1.73317816 -1.2161191\n", - " 0.40994665 1.74447169 -1.14890371 0.43215991 1.7317972 -1.05400864\n", - " 0.44661274 1.70318037 -0.57803474 0.47525387 1.67580476 -0.47782643\n", - " 0.51732929 1.68966101 -0.41734578 0.5235396 1.65666245 -0.32899025\n", - " 0.53669182 1.6508883 -0.16537832 0.59784126 1.61244582 -0.10233718\n", - " 0.6527967 1.59532197 0.16440329]\n", - "P_ = [ 0.0467971 1.98224194 0.12143971 0.12278318 1.95253061 -0.59165972\n", - " 0.19543318 1.86937861 -0.45021723 0.25347033 1.81705007 -1.19764344\n", - " 0.32490872 1.78750504 -1.29692287 0.37713329 1.76474818 -1.25017691\n", - " 0.39036726 1.74819982 -1.47714291 0.38872295 1.73718172 -1.37704428\n", - " 0.39954552 1.73915709 -1.18053448 0.42039995 1.73850722 -1.10424721\n", - " 0.43811107 1.7200138 -0.85801939 0.45672137 1.69351839 -0.5426671\n", - " 0.487629 1.67988013 -0.460038 0.51879054 1.68189664 -0.39655624\n", - " 0.52586058 1.65564348 -0.30011755 0.54388588 1.64636566 -0.15796172\n", - " 0.60107393 1.61143853 -0.08664656 0.6527967 1.59532197 0.16440329]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.504387\n", - " Iterations: 1592\n", - " Function evaluations: 1989\n", - "P = [ 0.04443147 2.0081401 0.12216596 0.12329608 1.96875945 -0.61207032\n", - " 0.19415251 1.85199076 -0.47172127 0.24098936 1.80845899 -1.25211694\n", - " 0.32182572 1.78769282 -1.21904626 0.37981568 1.76291029 -1.21750202\n", - " 0.39223041 1.74431354 -1.50822151 0.3928496 1.73587328 -1.37068942\n", - " 0.40416355 1.73563529 -1.15913125 0.42023379 1.73839762 -1.1469886\n", - " 0.43885043 1.72556938 -0.84525072 0.44983727 1.68970582 -0.53387223\n", - " 0.49040108 1.68312985 -0.47146725 0.52963201 1.68377141 -0.39288229\n", - " 0.50757809 1.65304098 -0.3095064 0.51502126 1.64018705 -0.1654121\n", - " 0.59852351 1.60941805 -0.09618516 0.64303626 1.59447011 0.17037647]\n", - "P_ = [ 0.04443147 2.0081401 0.12216596 0.11891471 1.97094726 -0.57127942\n", - " 0.18627957 1.86496506 -0.48731561 0.23318322 1.81571429 -1.12205099\n", - " 0.30386208 1.79230752 -1.2263953 0.36370736 1.76979433 -1.21793098\n", - " 0.38809217 1.75051246 -1.41131501 0.3926088 1.7391556 -1.42417412\n", - " 0.39913513 1.73574106 -1.25315711 0.41219867 1.73701645 -1.15305993\n", - " 0.42850785 1.73269618 -1.01288287 0.44312309 1.71162244 -0.72415908\n", - " 0.46335854 1.68751383 -0.51307057 0.50129857 1.68330806 -0.44963809\n", - " 0.52473114 1.67694242 -0.37435431 0.50881862 1.65089866 -0.28549068\n", - " 0.52429929 1.63676827 -0.15772022 0.60099644 1.60858761 -0.08137618\n", - " 0.64303626 1.59447011 0.17037647]\n", - "Depth = 19, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.492172\n", - " Iterations: 3762\n", - " Function evaluations: 4461\n", - "P = [ 0.04287525 2.00981451 0.07581622 0.11923818 1.96261178 -0.57894081\n", - " 0.1960853 1.87216262 -0.61533191 0.22700611 1.80374307 -1.1739389\n", - " 0.27877884 1.76664127 -1.18047807 0.35612551 1.7686208 -0.9346371\n", - " 0.3924937 1.75395576 -1.571564 0.39323317 1.73545331 -1.42883708\n", - " 0.39029491 1.72776053 -1.16449134 0.40925032 1.72576766 -1.2399254\n", - " 0.4401255 1.74400209 -1.01737727 0.44032452 1.70332712 -0.77050683\n", - " 0.44283651 1.67905632 -0.57682187 0.51516849 1.68952905 -0.41216406\n", - " 0.55167839 1.67274178 -0.40424473 0.50153251 1.65124474 -0.49828287\n", - " 0.54743686 1.62518876 -0.16305941 0.62909335 1.60673417 -0.06513055\n", - " 0.79282808 1.58569614 0.08484026]\n", - "P_ = [ 0.04287525 2.00981451 0.07581622 0.11521907 1.96509614 -0.54447991\n", - " 0.18799613 1.88168359 -0.61150127 0.22212388 1.81454616 -1.0857378\n", - " 0.26787932 1.77445217 -1.1791014 0.33577113 1.76809987 -0.99933209\n", - " 0.38100901 1.75858682 -1.37042919 0.39296073 1.74227 -1.48142068\n", - " 0.39153207 1.73099959 -1.27579481 0.40027144 1.72671165 -1.20419347\n", - " 0.4238754 1.73440502 -1.13450786 0.4402093 1.72687579 -0.91343182\n", - " 0.44124999 1.69438524 -0.69914921 0.46567819 1.6823635 -0.52482466\n", - " 0.52477636 1.68511135 -0.41008002 0.54112136 1.66821609 -0.42404223\n", - " 0.50878057 1.64713064 -0.44535285 0.55603228 1.62324617 -0.15275111\n", - " 0.63771096 1.60562691 -0.05723735 0.79282808 1.58569614 0.08484026]\n", - "Depth = 20, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 1.484554\n", - " Iterations: 3114\n", - " Function evaluations: 3733\n", - "1.3571428571428572 [7.58243337 5.24345812 4.64005483 3.98561262 3.24406278 2.73079183\n", - " 2.42949298 2.13406874 2.00066273 1.98499101 1.93919192 1.85096231\n", - " 1.62002947 1.5596317 1.53578071 1.52298198 1.51265038 1.50438675\n", - " 1.49217229 1.48455378]\n", - "[[6.20528854 5.90276273 4.34974565 2.82648708 2.83216236 2.53390824\n", - " 2.48542936 2.39488186 1.78514917 1.78156864 1.63586622 1.93423131\n", - " 1.3466511 1.61587827 1.31723472 1.39380148 1.3212952 1.48519626\n", - " 1.19207192 1.19585198]\n", - " [7.30404471 4.53202785 3.46764965 2.88567087 2.50354724 2.12413704\n", - " 1.93259722 1.8208787 1.66881973 1.61137624 1.5777798 1.52441689\n", - " 1.50488971 1.32477289 1.14366376 1.10087346 1.06542039 1.04874467\n", - " 1.03100111 1.02313941]\n", - " [5.58705617 3.86360072 3.41898777 2.93676719 2.39036205 2.0121624\n", - " 1.79015272 1.5724717 1.47417254 1.46262495 1.42887826 1.36386696\n", - " 1.19370592 1.14920231 1.13162789 1.12219725 1.11458449 1.1084955\n", - " 1.09949537 1.09388173]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]] [1.90963894 1.42983913 1.12363831 0.86489251 0.77260717 0.66702077\n", - " 0.62081793 0.57882323 0.49281414 0.48555698 0.46425243 0.48225152\n", - " 0.40452467 0.40898535 0.35925264 0.36168722 0.35013001 0.36424364\n", - " 0.33225684 0.33128731]\n", - "[[0.17030757 0.16850299 0.24687602 0.45514832 0.45145637 0.56268179\n", - " 0.4723914 0.62266371 0.8026945 0.81119819 0.87005395 0.73125403\n", - " 0.9110609 0.83507433 0.90935654 0.90735586 0.92006095 0.88620215\n", - " 0.96581763 0.96554472]\n", - " [0.18431054 0.3834123 0.50873566 0.61052141 0.696016 0.79140483\n", - " 0.84466927 0.87844738 0.91858227 0.93545701 0.95087783 0.95794391\n", - " 0.96260089 0.96665922 0.98020554 0.98747975 0.99371878 0.99672513\n", - " 0.99769447 0.9985309 ]\n", - " [0.20432833 0.3184594 0.35443145 0.44587035 0.69188034 0.79613223\n", - " 0.85245109 0.94248088 0.96021228 0.960348 0.9695536 0.96022371\n", - " 0.98485672 0.99130491 0.99357222 0.99489111 0.99620155 0.99674134\n", - " 0.99723741 0.99702852]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]] [0.05589464 0.08703747 0.11100431 0.15115401 0.18393527 0.21502189\n", - " 0.21695118 0.2443592 0.26814891 0.27070032 0.27904854 0.26494216\n", - " 0.28585185 0.27930385 0.28831343 0.28897267 0.29099813 0.28796686\n", - " 0.29607495 0.29611041]\n", - "\n", - "Now using 3 solutions, set number 4\n", - "Calculating energy landscape ...\n", - "Optimization terminated successfully.\n", - " Current function value: 9.242271\n", - " Iterations: 62\n", - " Function evaluations: 115\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 9.242271\n", - " Iterations: 16\n", - " Function evaluations: 34\n", - "P = [6.02927747 1.17986704 0.32077922]\n", - "P_ = [6.02927747 1.17986704 0.32077922 6.02927747 1.17986704 0.32077922]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 6.633518\n", - " Iterations: 67\n", - " Function evaluations: 111\n", - "P = [6.10877249 1.31880689 0.33717655 5.8440234 1.319425 0.28207748]\n", - "P_ = [6.10877249 1.31880689 0.33717655 5.97639795 1.31911594 0.30962702\n", - " 5.8440234 1.319425 0.28207748]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.875879\n", - " Iterations: 110\n", - " Function evaluations: 178\n", - "P = [6.10701432 1.1897718 0.36565583 5.92979147 1.44333234 0.27307698\n", - " 5.81231615 1.33864253 0.28510898]\n", - "P_ = [6.10701432 1.1897718 0.36565583 5.98886575 1.35881216 0.3039366\n", - " 5.89063303 1.40843574 0.27708764 5.81231615 1.33864253 0.28510898]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.632974\n", - " Iterations: 370\n", - " Function evaluations: 544\n", - "P = [ 6.12672055 1.28496861 0.39850613 5.94787952 1.30854622 -0.23655022\n", - " 5.93306599 1.47110848 0.33210469 5.81733344 1.38991544 0.53437566]\n", - "P_ = [ 6.12672055 1.28496861 0.39850613 5.99258978 1.30265182 -0.07778614\n", - " 5.94047275 1.38982735 0.04777723 5.90413285 1.45081022 0.38267243\n", - " 5.81733344 1.38991544 0.53437566]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.299242\n", - " Iterations: 304\n", - " Function evaluations: 453\n", - "P = [ 6.15927024 1.27611124 0.22072745 6.00408635 1.33960482 -0.08547938\n", - " 5.96399013 1.42530942 0.05003062 5.92267561 1.44495086 0.44916375\n", - " 5.8005641 1.44770472 0.57380086]\n", - "P_ = [ 6.15927024e+00 1.27611124e+00 2.20727448e-01 6.03512313e+00\n", - " 1.32690610e+00 -2.42380118e-02 5.98002862e+00 1.39102758e+00\n", - " -4.17337797e-03 5.94746432e+00 1.43316599e+00 2.09683871e-01\n", - " 5.89825331e+00 1.44550163e+00 4.74091168e-01 5.80056410e+00\n", - " 1.44770472e+00 5.73800860e-01]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.115580\n", - " Iterations: 192\n", - " Function evaluations: 306\n", - "P = [ 6.17013100e+00 1.23751782e+00 2.20967141e-01 6.03043780e+00\n", - " 1.35152069e+00 -2.48200836e-02 5.97616181e+00 1.40659678e+00\n", - " -4.18388732e-03 5.93905895e+00 1.43098406e+00 2.21618559e-01\n", - " 5.87497711e+00 1.46133809e+00 4.32708681e-01 5.74237893e+00\n", - " 1.49072499e+00 5.75180534e-01]\n", - "P_ = [ 6.170131 1.23751782 0.22096714 6.05372 1.33252021 0.01614445\n", - " 5.9942538 1.38823808 -0.01106262 5.95761038 1.41879042 0.10871734\n", - " 5.91769833 1.44110207 0.29198193 5.85287741 1.46623591 0.45645399\n", - " 5.74237893 1.49072499 0.57518053]\n", - "Depth = 7, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 6.21198378e+00 1.14255281e+00 2.97516031e-02 6.08847059e+00\n", - " 1.19467544e+00 2.31180583e-02 6.01330395e+00 1.39924429e+00\n", - " -4.16116843e-03 5.94810599e+00 1.36242126e+00 3.58091329e-01\n", - " 5.95059464e+00 1.46463583e+00 2.12243635e-01 5.84390954e+00\n", - " 1.43989462e+00 3.94924840e-01 5.65032276e+00 1.48016688e+00\n", - " 2.72661691e-01]\n", - "P_ = [6.21198378e+00 1.14255281e+00 2.97516031e-02 6.10611533e+00\n", - " 1.18722935e+00 2.40657076e-02 6.03478013e+00 1.34079605e+00\n", - " 3.63289635e-03 5.97604797e+00 1.37820256e+00 2.02840259e-01\n", - " 5.94917256e+00 1.40622750e+00 2.95585175e-01 5.92011319e+00\n", - " 1.45756691e+00 2.64438265e-01 5.81625428e+00 1.44564780e+00\n", - " 3.77458676e-01 5.65032276e+00 1.48016688e+00 2.72661691e-01]\n", - "Depth = 8, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.726083\n", - " Iterations: 2607\n", - " Function evaluations: 3290\n", - "P = [ 6.18915144e+00 1.24314063e+00 7.29893236e-02 6.04798634e+00\n", - " 1.15164160e+00 5.23996824e-02 6.00283804e+00 1.47469772e+00\n", - " 4.95707488e-03 5.93698650e+00 1.29566761e+00 3.23267381e-01\n", - " 5.95748571e+00 1.51965922e+00 2.78415016e-02 5.82068415e+00\n", - " 1.38449779e+00 3.50826435e-01 5.58808654e+00 1.48624381e+00\n", - " -6.07394930e-01 5.56063562e+00 1.47390714e+00 2.22469554e-01]\n", - "P_ = [ 6.18915144 1.24314063 0.07298932 6.06563198 1.16307898 0.05497339\n", - " 6.01412511 1.39393369 0.01681773 5.96168082 1.3628039 0.20390102\n", - " 5.9472361 1.40766342 0.17555444 5.90618513 1.46897368 0.14896085\n", - " 5.76253475 1.4099343 0.11127109 5.58465518 1.48470173 -0.50366187\n", - " 5.56063562 1.47390714 0.22246955]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.585586\n", - " Iterations: 1968\n", - " Function evaluations: 2453\n", - "P = [ 6.21835102 1.14232905 0.08269483 6.08959656 1.31240255 0.06008418\n", - " 5.99888435 1.27967141 0.02252289 5.98609379 1.46476002 0.24575542\n", - " 5.91455011 1.34516616 0.15253231 5.94666471 1.51365654 0.13636435\n", - " 5.7883033 1.41517097 0.12511827 5.59892361 1.49419863 -0.31959866\n", - " 5.5868791 1.47601273 0.1064226 ]\n", - "P_ = [ 6.21835102 1.14232905 0.08269483 6.10390262 1.2935055 0.06259647\n", - " 6.01904262 1.28694499 0.03086984 5.99035731 1.40306382 0.17134458\n", - " 5.9463473 1.39831899 0.1939648 5.92882327 1.42005078 0.14534655\n", - " 5.89387757 1.48082801 0.13261565 5.74621892 1.43273267 0.02629228\n", - " 5.59758533 1.49217797 -0.27226296 5.5868791 1.47601273 0.1064226 ]\n", - "Depth = 10, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.506528\n", - " Iterations: 448\n", - " Function evaluations: 632\n", - "P = [ 6.22637131 1.07600786 0.08278479 6.1223304 1.23432963 0.06392346\n", - " 6.02214662 1.2991557 0.0313095 5.98691939 1.41071438 0.18404678\n", - " 5.94995548 1.4007939 0.18580176 5.91038664 1.437928 0.14638329\n", - " 5.91188971 1.48822073 0.14632894 5.67950894 1.45552805 0.02637678\n", - " 5.55288229 1.4928198 -0.26621657 5.56897181 1.49322961 0.10134079]\n", - "P_ = [ 6.22637131 1.07600786 0.08278479 6.13273449 1.21849745 0.06580959\n", - " 6.04218338 1.28619049 0.0378323 5.99748756 1.37724678 0.1382256\n", - " 5.96474104 1.4047621 0.18509977 5.93017106 1.41936095 0.16609253\n", - " 5.91098786 1.45804509 0.14636155 5.84217548 1.47841293 0.11034329\n", - " 5.65418361 1.4629864 -0.03214189 5.55449124 1.49286078 -0.22946083\n", - " 5.56897181 1.49322961 0.10134079]\n", - "Depth = 11, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.466375\n", - " Iterations: 513\n", - " Function evaluations: 723\n", - "P = [ 6.23289589 1.12897383 0.06025223 6.14179048 1.18565486 0.0662057\n", - " 6.04146072 1.29387442 0.03962647 5.99225747 1.37420024 0.1465765\n", - " 5.96413786 1.41093169 0.18374024 5.91559253 1.41873934 0.17524795\n", - " 5.91852989 1.46543259 0.15323227 5.80690876 1.48175208 0.11115032\n", - " 5.619002 1.46094343 -0.03511413 5.58025961 1.50219836 -0.22653488\n", - " 5.60484408 1.50444527 0.09551494]\n", - "P_ = [ 6.23289589 1.12897383 0.06025223 6.15007279 1.18050204 0.06566447\n", - " 6.05970249 1.27419814 0.04445905 6.00567654 1.3522932 0.11740831\n", - " 5.97436317 1.3975748 0.17022615 5.93765859 1.41519041 0.17910808\n", - " 5.91692769 1.43996355 0.16524082 5.87794039 1.47136695 0.13792974\n", - " 5.75566146 1.476077 0.07126001 5.61195793 1.46844433 -0.0699179\n", - " 5.58249457 1.50240263 -0.19725762 5.60484408 1.50444527 0.09551494]\n", - "Depth = 12, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.415282\n", - " Iterations: 934\n", - " Function evaluations: 1211\n", - "P = [ 6.23315256 1.13289706 0.03477695 6.15638275 1.18142182 0.07004891\n", - " 6.09474409 1.35042789 0.06091415 6.01617695 1.3419338 0.13236276\n", - " 5.96745226 1.39268702 0.20801014 5.9467709 1.42398978 0.13668403\n", - " 5.90801996 1.43193839 0.18416991 5.94040487 1.49453087 0.14838293\n", - " 5.80063583 1.48195036 0.07441904 5.61860227 1.47141291 -0.07074351\n", - " 5.57642193 1.50102427 -0.17900174 5.57536808 1.52190767 0.08388617]\n", - "P_ = [ 6.23315256 1.13289706 0.03477695 6.16278023 1.17737809 0.06710958\n", - " 6.1050172 1.32226021 0.06243661 6.03581874 1.34405732 0.11450061\n", - " 5.98369382 1.37576928 0.18279435 5.95538813 1.41094697 0.16640324\n", - " 5.92739543 1.42796409 0.16042697 5.92151367 1.45801859 0.16925867\n", - " 5.89381519 1.49033737 0.1237283 5.75512744 1.479316 0.0381284\n", - " 5.61157222 1.47634814 -0.08878655 5.5763341 1.50276456 -0.15709441\n", - " 5.57536808 1.52190767 0.08388617]\n", - "Depth = 13, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.384789\n", - " Iterations: 884\n", - " Function evaluations: 1160\n", - "P = [ 6.22936738 1.15552906 0.03740754 6.15446735 1.15944297 0.04217005\n", - " 6.09113909 1.31811664 0.07057621 6.05834858 1.38427315 0.12503432\n", - " 5.98803889 1.37526503 0.19034822 5.95558 1.41585243 0.15800875\n", - " 5.9470089 1.44273702 0.17418344 5.89518489 1.45203555 0.15385725\n", - " 5.92932573 1.50019457 0.12219996 5.76019335 1.48533704 0.04472266\n", - " 5.60513868 1.47696296 -0.08435641 5.5716255 1.51409325 -0.14164952\n", - " 5.52027552 1.53118793 0.08676225]\n", - "P_ = [ 6.22936738 1.15552906 0.03740754 6.16022889 1.1591419 0.0418037\n", - " 6.1008819 1.2937053 0.06620603 6.06591562 1.36900626 0.11246706\n", - " 6.00967264 1.37803676 0.17025163 5.96806419 1.40024189 0.17044701\n", - " 5.95096479 1.43032875 0.1667182 5.92309013 1.44702865 0.16480212\n", - " 5.90831598 1.47055825 0.14168137 5.87728499 1.49562303 0.09836079\n", - " 5.7244115 1.48340456 0.01493519 5.5999828 1.48267531 -0.09317073\n", - " 5.5676755 1.51540822 -0.12407938 5.52027552 1.53118793 0.08676225]\n", - "Depth = 14, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.275129\n", - " Iterations: 2868\n", - " Function evaluations: 3467\n", - "P = [ 6.21812598 1.19884938 0.05127736 6.15541614 1.24280583 -0.04271638\n", - " 6.14032478 1.33662009 0.09425126 6.07027633 1.32098305 0.33758288\n", - " 6.0247562 1.35786636 0.35529612 5.99937408 1.40028559 0.32797531\n", - " 5.96028675 1.39402984 0.17623823 5.94851712 1.45569868 0.18238868\n", - " 5.90774271 1.44049877 -0.04454973 5.98312423 1.51521891 0.08359866\n", - " 5.7809312 1.48392681 0.0180357 5.57911516 1.46615261 -0.12006967\n", - " 5.54746682 1.51653774 -0.12829774 5.55043685 1.50364197 0.03980025]\n", - "P_ = [ 6.21812598e+00 1.19884938e+00 5.12773619e-02 6.15989541e+00\n", - " 1.23966608e+00 -3.60025411e-02 6.14248069e+00 1.32321805e+00\n", - " 7.46844580e-02 6.08528672e+00 1.32433384e+00 2.85440387e-01\n", - " 6.03776195e+00 1.34732827e+00 3.50235191e-01 6.00843912e+00\n", - " 1.38513586e+00 3.37732739e-01 5.97703846e+00 1.39671088e+00\n", - " 2.41268407e-01 5.95440194e+00 1.42486426e+00 1.79313458e-01\n", - " 5.93104238e+00 1.44918443e+00 8.51293633e-02 5.93466468e+00\n", - " 1.46718454e+00 1.21754941e-03 5.92535479e+00 1.50627831e+00\n", - " 6.48663838e-02 5.73768490e+00 1.48011805e+00 -1.15583062e-02\n", - " 5.57459397e+00 1.47335049e+00 -1.21245108e-01 5.54767897e+00\n", - " 1.51561662e+00 -1.16290737e-01 5.55043685e+00 1.50364197e+00\n", - " 3.98002505e-02]\n", - "Depth = 15, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.139144\n", - " Iterations: 4293\n", - " Function evaluations: 5106\n", - "P = [ 6.20817048e+00 1.16133298e+00 -1.80158963e-02 6.11220954e+00\n", - " 1.25228365e+00 -1.05606254e-01 6.07343697e+00 1.32123751e+00\n", - " 1.07794922e-01 6.05078397e+00 1.32742638e+00 4.88456676e-01\n", - " 6.04443433e+00 1.35629715e+00 7.04120603e-01 6.03617309e+00\n", - " 1.36488904e+00 6.19978091e-01 6.07787385e+00 1.42735499e+00\n", - " 3.51758419e-01 6.00112725e+00 1.39793761e+00 3.42871451e-01\n", - " 5.99407195e+00 1.43409077e+00 1.09843644e-01 5.88915247e+00\n", - " 1.40383146e+00 -1.97505151e-03 5.97809672e+00 1.49663599e+00\n", - " 1.64467040e-01 5.72282239e+00 1.44969914e+00 7.77653016e-03\n", - " 5.53277047e+00 1.44665930e+00 -1.25674299e-01 5.51933325e+00\n", - " 1.49183757e+00 -3.20037427e-03 5.53377725e+00 1.48341659e+00\n", - " 9.16102302e-03]\n", - "P_ = [ 6.20817048e+00 1.16133298e+00 -1.80158963e-02 6.11860694e+00\n", - " 1.24622027e+00 -9.97668971e-02 6.07860664e+00 1.31204366e+00\n", - " 7.93414319e-02 6.05531457e+00 1.32618861e+00 4.12324325e-01\n", - " 6.04612757e+00 1.34859828e+00 6.46610223e-01 6.03892684e+00\n", - " 1.36202507e+00 6.48025595e-01 6.06119355e+00 1.40236861e+00\n", - " 4.59046288e-01 6.03694233e+00 1.41166572e+00 3.47018703e-01\n", - " 5.99783478e+00 1.41480909e+00 2.34125141e-01 5.95210416e+00\n", - " 1.42198705e+00 6.51161660e-02 5.91880055e+00 1.43476630e+00\n", - " 5.35056456e-02 5.91002357e+00 1.48411950e+00 1.22682904e-01\n", - " 5.68481201e+00 1.44909117e+00 -1.89136356e-02 5.53097884e+00\n", - " 1.45268307e+00 -1.09344442e-01 5.52029618e+00 1.49127617e+00\n", - " -2.37628112e-03 5.53377725e+00 1.48341659e+00 9.16102302e-03]\n", - "Depth = 16, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 6.19810559e+00 1.19299414e+00 -4.98494679e-02 6.09621330e+00\n", - " 1.15965101e+00 1.00110725e-01 6.07618799e+00 1.35377748e+00\n", - " 2.31476773e-04 6.04995841e+00 1.28760436e+00 1.43344020e+00\n", - " 6.02923643e+00 1.39695481e+00 2.72483366e-01 6.02030246e+00\n", - " 1.31101820e+00 1.47309500e+00 5.99230872e+00 1.40075775e+00\n", - " 1.32491585e+00 6.07895473e+00 1.43146274e+00 -3.81750453e-01\n", - " 6.06605788e+00 1.48154610e+00 1.37984221e+00 5.97876661e+00\n", - " 1.42255088e+00 -8.20315878e-02 5.88851699e+00 1.46018426e+00\n", - " 1.20827509e-01 5.95209841e+00 1.47853586e+00 8.90463175e-02\n", - " 5.77390407e+00 1.50162137e+00 4.53571343e-02 5.56836870e+00\n", - " 1.43524596e+00 1.70980815e-01 5.56335675e+00 1.53030031e+00\n", - " -2.72463989e-04 5.57050768e+00 1.47645322e+00 -7.35071898e-03]\n", - "P_ = [ 6.19810559e+00 1.19299414e+00 -4.98494679e-02 6.10258157e+00\n", - " 1.16173496e+00 9.07382129e-02 6.07869116e+00 1.32951167e+00\n", - " 1.27163828e-02 6.05487646e+00 1.30001182e+00 1.16471356e+00\n", - " 6.03441692e+00 1.36961719e+00 5.62722574e-01 6.02309433e+00\n", - " 1.33787339e+00 1.09790387e+00 6.00280637e+00 1.36710542e+00\n", - " 1.38048303e+00 6.04104710e+00 1.41802930e+00 3.64916053e-01\n", - " 6.07250631e+00 1.45650442e+00 4.99045880e-01 6.02786795e+00\n", - " 1.45573569e+00 7.40272426e-01 5.94492300e+00 1.43666340e+00\n", - " -5.95942663e-03 5.90838618e+00 1.46591914e+00 1.10895886e-01\n", - " 5.90754982e+00 1.48430724e+00 7.81240217e-02 5.73536619e+00\n", - " 1.48917598e+00 6.89115743e-02 5.56774220e+00 1.44712775e+00\n", - " 1.49574155e-01 5.56380368e+00 1.52693487e+00 -7.14854926e-04\n", - " 5.57050768e+00 1.47645322e+00 -7.35071898e-03]\n", - "Depth = 17, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 6.22273965e+00 1.19296279e+00 -2.53531393e-02 6.13201561e+00\n", - " 1.20658520e+00 1.76678370e-02 6.10249679e+00 1.28059925e+00\n", - " -4.99274271e-04 6.08912310e+00 1.29689494e+00 1.35856238e+00\n", - " 6.05076260e+00 1.39710047e+00 9.33597938e-01 6.04671863e+00\n", - " 1.33258820e+00 1.15558447e+00 6.01826050e+00 1.35199980e+00\n", - " 2.27858928e+00 5.98275447e+00 1.42573384e+00 3.13590175e-01\n", - " 5.97486412e+00 1.37773423e+00 1.53816464e+00 6.00652461e+00\n", - " 1.50364165e+00 9.30632064e-01 6.06180284e+00 1.47155112e+00\n", - " 3.28767714e-05 5.94478830e+00 1.50394530e+00 2.42864937e-01\n", - " 5.91834924e+00 1.48248285e+00 6.38351452e-02 5.70471321e+00\n", - " 1.50016951e+00 -1.12564266e-02 5.55810144e+00 1.48703847e+00\n", - " 1.30686098e-01 5.59986880e+00 1.51417385e+00 -8.87420808e-04\n", - " 5.66015776e+00 1.51875726e+00 -1.08826762e-02]\n", - "P_ = [ 6.22273965e+00 1.19296279e+00 -2.53531393e-02 6.13735232e+00\n", - " 1.20578388e+00 1.51371913e-02 6.10596960e+00 1.27189171e+00\n", - " 1.63803293e-03 6.09148317e+00 1.29401923e+00 1.11872797e+00\n", - " 6.05978860e+00 1.37352270e+00 1.03358957e+00 6.04790803e+00\n", - " 1.35156240e+00 1.09029432e+00 6.02830454e+00 1.34514865e+00\n", - " 1.88223464e+00 5.99737460e+00 1.39537276e+00 1.12270745e+00\n", - " 5.97857723e+00 1.40032228e+00 9.61894305e-01 5.98976317e+00\n", - " 1.43698478e+00 1.25226696e+00 6.02928623e+00 1.49042790e+00\n", - " 5.47444163e-01 6.02050359e+00 1.48298436e+00 8.57383098e-02\n", - " 5.93701211e+00 1.49763282e+00 1.90209116e-01 5.86808194e+00\n", - " 1.48664442e+00 4.61665401e-02 5.67884055e+00 1.49785227e+00\n", - " 1.37922542e-02 5.56301525e+00 1.49023087e+00 1.15206861e-01\n", - " 5.60341521e+00 1.51444346e+00 -1.47537701e-03 5.66015776e+00\n", - " 1.51875726e+00 -1.08826762e-02]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.848340\n", - " Iterations: 1595\n", - " Function evaluations: 2033\n", - "P = [ 6.23111870e+00 1.15693799e+00 -2.48510750e-02 6.14219554e+00\n", - " 1.18852485e+00 1.39049833e-02 6.09843320e+00 1.28829006e+00\n", - " 1.63317902e-03 6.08234676e+00 1.29274470e+00 1.10245903e+00\n", - " 6.05900742e+00 1.38664759e+00 1.00449433e+00 6.04641152e+00\n", - " 1.36212003e+00 1.07589184e+00 6.01116095e+00 1.34473949e+00\n", - " 1.83267911e+00 6.00770675e+00 1.40817922e+00 1.19252721e+00\n", - " 5.97553555e+00 1.41490096e+00 1.00727352e+00 5.97310713e+00\n", - " 1.43232135e+00 1.07740576e+00 6.00850596e+00 1.49655781e+00\n", - " 6.26990751e-01 6.04485978e+00 1.48569717e+00 8.83912915e-02\n", - " 5.92847463e+00 1.50139250e+00 2.12110538e-01 5.90460494e+00\n", - " 1.49590378e+00 4.45451584e-02 5.67858840e+00 1.49976139e+00\n", - " 1.31600002e-02 5.55646436e+00 1.49985953e+00 1.11571761e-01\n", - " 5.58416072e+00 1.50920298e+00 -1.50428522e-03 5.60084668e+00\n", - " 1.53215222e+00 -1.13637423e-02]\n", - "P_ = [ 6.23111870e+00 1.15693799e+00 -2.48510750e-02 6.14713572e+00\n", - " 1.18677002e+00 1.17518689e-02 6.10329568e+00 1.27720504e+00\n", - " 2.99671283e-03 6.08502783e+00 1.29200226e+00 9.18988056e-01\n", - " 6.06419394e+00 1.36578028e+00 1.02626426e+00 6.04991038e+00\n", - " 1.36893324e+00 1.05605920e+00 6.02291114e+00 1.35053300e+00\n", - " 1.58041669e+00 6.00905005e+00 1.38350822e+00 1.44147517e+00\n", - " 5.98983386e+00 1.41191352e+00 1.08960849e+00 5.97432134e+00\n", - " 1.42361115e+00 1.04233964e+00 5.98883995e+00 1.46087089e+00\n", - " 8.77221309e-01 6.02264356e+00 1.49233423e+00 4.17535405e-01\n", - " 6.00606473e+00 1.49092895e+00 1.29631040e-01 5.92184416e+00\n", - " 1.49986786e+00 1.65564599e-01 5.85437904e+00 1.49676103e+00\n", - " 3.75706788e-02 5.65823440e+00 1.49977775e+00 2.95619603e-02\n", - " 5.55954173e+00 1.50089769e+00 9.90077557e-02 5.58508771e+00\n", - " 1.51047794e+00 -2.05203284e-03 5.60084668e+00 1.53215222e+00\n", - " -1.13637423e-02]\n", - "Depth = 19, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.845047\n", - " Iterations: 1203\n", - " Function evaluations: 1602\n", - "P = [ 6.23647389e+00 1.15408902e+00 -2.51491253e-02 6.15253967e+00\n", - " 1.16758300e+00 1.20817769e-02 6.10006729e+00 1.28585694e+00\n", - " 2.71706213e-03 6.08342175e+00 1.29822540e+00 8.64499159e-01\n", - " 6.05788962e+00 1.36580858e+00 1.04033236e+00 6.05577240e+00\n", - " 1.37856349e+00 1.07429733e+00 6.02504518e+00 1.36401959e+00\n", - " 1.55420281e+00 6.00584408e+00 1.38411557e+00 1.43437497e+00\n", - " 5.98752664e+00 1.41477701e+00 1.15545547e+00 5.96987189e+00\n", - " 1.43182491e+00 1.08336149e+00 5.98592435e+00 1.45918656e+00\n", - " 8.51962813e-01 6.00291755e+00 1.49617193e+00 4.13401255e-01\n", - " 5.99567854e+00 1.49238968e+00 1.41723818e-01 5.92291627e+00\n", - " 1.50318721e+00 1.64728200e-01 5.86640614e+00 1.50867438e+00\n", - " 3.57992629e-02 5.65413201e+00 1.50637037e+00 2.81270401e-02\n", - " 5.55959209e+00 1.50996887e+00 9.77993808e-02 5.56491263e+00\n", - " 1.51540709e+00 -2.09461858e-03 5.58222096e+00 1.54330515e+00\n", - " -1.12278961e-02]\n", - "P_ = [ 6.23647389e+00 1.15408902e+00 -2.51491253e-02 6.15695726e+00\n", - " 1.16687279e+00 1.01222557e-02 6.10559070e+00 1.27340705e+00\n", - " 3.70282158e-03 6.08605000e+00 1.29627248e+00 7.28428302e-01\n", - " 6.06326480e+00 1.35158054e+00 1.00331484e+00 6.05632956e+00\n", - " 1.37520694e+00 1.06535918e+00 6.03474851e+00 1.36861240e+00\n", - " 1.40265371e+00 6.01291817e+00 1.37671179e+00 1.47852207e+00\n", - " 5.99523925e+00 1.40186693e+00 1.27289526e+00 5.97823467e+00\n", - " 1.42374959e+00 1.11751127e+00 5.97747569e+00 1.44478569e+00\n", - " 9.73751589e-01 5.99307938e+00 1.47475935e+00 6.67305315e-01\n", - " 6.00025054e+00 1.49477847e+00 3.13309568e-01 5.97270098e+00\n", - " 1.49579942e+00 1.48988360e-01 5.90804518e+00 1.50463120e+00\n", - " 1.30799532e-01 5.82171685e+00 1.50818932e+00 3.41840581e-02\n", - " 5.63920465e+00 1.50693856e+00 3.91279360e-02 5.56015215e+00\n", - " 1.51054131e+00 8.72842229e-02 5.56582360e+00 1.51687541e+00\n", - " -2.57531739e-03 5.58222096e+00 1.54330515e+00 -1.12278961e-02]\n", - "Depth = 20, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.831335\n", - " Iterations: 2355\n", - " Function evaluations: 2913\n", - "1.6 [9.24227102 6.63351797 4.87587877 3.63297407 3.29924219 3.11557963\n", - " 2.93133504 2.72608291 2.58558567 2.50652766 2.46637505 2.41528231\n", - " 2.38478884 2.27512941 2.13914427 1.97123176 1.87747446 1.8483403\n", - " 1.8450468 1.8313352 ]\n", - "[[6.20528854 5.90276273 4.34974565 2.82648708 2.83216236 2.53390824\n", - " 2.48542936 2.39488186 1.78514917 1.78156864 1.63586622 1.93423131\n", - " 1.3466511 1.61587827 1.31723472 1.39380148 1.3212952 1.48519626\n", - " 1.19207192 1.19585198]\n", - " [7.30404471 4.53202785 3.46764965 2.88567087 2.50354724 2.12413704\n", - " 1.93259722 1.8208787 1.66881973 1.61137624 1.5777798 1.52441689\n", - " 1.50488971 1.32477289 1.14366376 1.10087346 1.06542039 1.04874467\n", - " 1.03100111 1.02313941]\n", - " [5.58705617 3.86360072 3.41898777 2.93676719 2.39036205 2.0121624\n", - " 1.79015272 1.5724717 1.47417254 1.46262495 1.42887826 1.36386696\n", - " 1.19370592 1.14920231 1.13162789 1.12219725 1.11458449 1.1084955\n", - " 1.09949537 1.09388173]\n", - " [5.77641939 4.14594873 3.04742423 2.27060879 2.06202637 1.94723727\n", - " 1.8320844 1.70380182 1.61599104 1.56657979 1.54148441 1.50955144\n", - " 1.49049303 1.42195588 1.33696517 1.23201985 1.17342154 1.15521269\n", - " 1.15315425 1.1445845 ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]] [2.48728088 1.844434 1.42838073 1.09195339 0.9788098 0.86174449\n", - " 0.80402637 0.74920341 0.65441325 0.64221496 0.61840087 0.63320666\n", - " 0.55357398 0.55118093 0.49294915 0.4848892 0.46747216 0.47976491\n", - " 0.44757226 0.44574576]\n", - "[[0.17030757 0.16850299 0.24687602 0.45514832 0.45145637 0.56268179\n", - " 0.4723914 0.62266371 0.8026945 0.81119819 0.87005395 0.73125403\n", - " 0.9110609 0.83507433 0.90935654 0.90735586 0.92006095 0.88620215\n", - " 0.96581763 0.96554472]\n", - " [0.18431054 0.3834123 0.50873566 0.61052141 0.696016 0.79140483\n", - " 0.84466927 0.87844738 0.91858227 0.93545701 0.95087783 0.95794391\n", - " 0.96260089 0.96665922 0.98020554 0.98747975 0.99371878 0.99672513\n", - " 0.99769447 0.9985309 ]\n", - " [0.20432833 0.3184594 0.35443145 0.44587035 0.69188034 0.79613223\n", - " 0.85245109 0.94248088 0.96021228 0.960348 0.9695536 0.96022371\n", - " 0.98485672 0.99130491 0.99357222 0.99489111 0.99620155 0.99674134\n", - " 0.99723741 0.99702852]\n", - " [0.16226489 0.29705928 0.5086956 0.65943464 0.69698848 0.74147959\n", - " 0.75625945 0.9055608 0.93509535 0.96329039 0.97453832 0.97952655\n", - " 0.98353524 0.98310405 0.96598607 0.98112827 0.99426833 0.99638548\n", - " 0.99420366 0.9903845 ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]] [0.07212113 0.1167434 0.16187387 0.21709747 0.25363412 0.28916985\n", - " 0.29257712 0.33491528 0.36165844 0.36702936 0.37650237 0.36289482\n", - " 0.38420538 0.37761425 0.38491204 0.3870855 0.39042496 0.38760541\n", - " 0.39549532 0.39514886]\n", - "\n", - "Now using 3 solutions, set number 5\n", - "Calculating energy landscape ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 11.144350\n", - " Iterations: 62\n", - " Function evaluations: 113\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 11.144350\n", - " Iterations: 30\n", - " Function evaluations: 51\n", - "P = [1.97725339 2.50054176 6.56111627]\n", - "P_ = [1.97725339 2.50054176 6.56111627 1.97725339 2.50054176 6.56111627]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 7.520118\n", - " Iterations: 428\n", - " Function evaluations: 659\n", - "P = [ 1.97633312 2.49347932 6.71296349 1.65810579 2.89313612 14.09988284]\n", - "P_ = [ 1.97633312 2.49347932 6.71296349 1.81721945 2.69330772 10.40642316\n", - " 1.65810579 2.89313612 14.09988284]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.473465\n", - " Iterations: 587\n", - " Function evaluations: 854\n", - "P = [ 2.22608562 2.48309526 6.3751938 1.87401981 2.31147282 11.27360602\n", - " 1.91300231 2.55968188 13.31474094]\n", - "P_ = [ 2.22608562 2.48309526 6.3751938 1.99137508 2.3686803 9.64080195\n", - " 1.88701398 2.39420917 11.95398433 1.91300231 2.55968188 13.31474094]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.393583\n", - " Iterations: 513\n", - " Function evaluations: 724\n", - "P = [ 2.09283293 2.41171329 6.04723292 1.94046546 2.55981296 9.64623857\n", - " 1.90756988 2.34208087 11.91628755 1.97734394 2.76916612 14.03598746]\n", - "P_ = [ 2.09283293 2.41171329 6.04723292 1.97855733 2.52278804 8.74648716\n", - " 1.92401767 2.45094691 10.78126306 1.92501339 2.44885218 12.44621253\n", - " 1.97734394 2.76916612 14.03598746]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.618293\n", - " Iterations: 782\n", - " Function evaluations: 1079\n", - "P = [ 2.034341 2.46102894 5.89031265 2.01414158 2.76367098 8.95664416\n", - " 2.02048693 2.49504513 10.37469601 1.81379474 2.50504967 13.05287106\n", - " 2.13540295 2.84568226 10.18714638]\n", - "P_ = [ 2.034341 2.46102894 5.89031265 2.01818147 2.70314257 8.34337786\n", - " 2.01794879 2.60249547 9.80747527 1.93781005 2.49904695 11.44596603\n", - " 1.87811638 2.57317619 12.47972612 2.13540295 2.84568226 10.18714638]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.001348\n", - " Iterations: 1039\n", - " Function evaluations: 1385\n", - "P = [ 2.05352368 2.55139877 6.0910236 1.92588983 2.78273636 8.96945633\n", - " 1.97371442 2.64865576 9.70501881 1.91685082 2.54668898 11.3389672\n", - " 1.75449581 2.78137556 12.07442578 2.16530193 3.01518049 9.51855448]\n", - "P_ = [ 2.05352368 2.55139877 6.0910236 1.94716213 2.74418009 8.48971754\n", - " 1.95777289 2.69334929 9.45983132 1.94528262 2.59767237 10.52199301\n", - " 1.86273248 2.62491784 11.58412006 1.82296349 2.82034305 11.64844723\n", - " 2.16530193 3.01518049 9.51855448]\n", - "Depth = 7, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.649032\n", - " Iterations: 1863\n", - " Function evaluations: 2401\n", - "P = [ 2.0536265 2.55071862 6.44761279 1.97792652 2.84911259 8.62505982\n", - " 1.96547898 2.67546768 8.80615675 1.90389087 2.61641691 11.55632674\n", - " 1.71912913 2.76780058 11.83744017 1.87297365 2.87791986 9.90465809\n", - " 2.28005125 2.96205235 9.48306609]\n", - "P_ = [ 2.0536265 2.55071862 6.44761279 1.9887408 2.80648488 8.31399596\n", - " 1.96903542 2.72508051 8.75441477 1.93028577 2.64172438 10.37768246\n", - " 1.82470726 2.68129563 11.67680393 1.7630847 2.79926323 11.28521672\n", - " 1.93112759 2.88993879 9.84443066 2.28005125 2.96205235 9.48306609]\n", - "Depth = 8, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 2.02872363 2.52988038 6.25499073 1.99304369 2.8882925 8.69126246\n", - " 1.96745433 2.7554023 8.00353504 1.93084982 2.76694455 11.81419499\n", - " 1.71290267 2.82889238 11.17071117 1.77984819 2.86633733 11.63267205\n", - " 2.19260495 2.86201078 9.82406862 2.26918278 2.96507348 8.78420428]\n", - "P_ = [ 2.02872363 2.52988038 6.25499073 1.99750368 2.84349098 8.38672849\n", - " 1.97385167 2.78862485 8.17546689 1.94457651 2.76261621 10.38519751\n", - " 1.82187624 2.79791847 11.49245308 1.73800724 2.84293424 11.3439465\n", - " 1.88303738 2.86525569 11.18052119 2.20217718 2.87489361 9.69408558\n", - " 2.26918278 2.96507348 8.78420428]\n", - "Depth = 9, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 2.06605651 2.52525563 6.88045431 1.88722794 2.85830699 9.75020829\n", - " 2.0845198 2.74745085 7.84702502 1.88591807 2.71233217 9.73844766\n", - " 1.57516994 2.88104297 12.59478116 1.86238663 3.03108369 7.53761616\n", - " 1.89291853 2.84670293 15.34168557 2.14122994 2.82460924 9.01799095\n", - " 2.19821511 2.84602147 7.69838968]\n", - "P_ = [ 2.06605651 2.52525563 6.88045431 1.90709778 2.82130129 9.43134674\n", - " 2.04067717 2.77208555 8.26995463 1.95211865 2.7240384 9.10797345\n", - " 1.71328022 2.80606039 11.32529961 1.70282181 2.94772773 10.34715227\n", - " 1.87256393 2.96962344 10.13897263 1.94809884 2.84179322 13.9364201\n", - " 2.14756163 2.82698838 8.87136859 2.19821511 2.84602147 7.69838968]\n", - "Depth = 10, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 2.05857413 2.64742507 6.87476982 1.86256233 2.9539128 9.61159011\n", - " 2.13754081 2.78806087 7.83557287 1.92090937 2.70301724 9.5533525\n", - " 1.6841943 2.7930439 10.75157937 1.74838253 2.96515523 11.25052409\n", - " 1.75000268 3.10387037 4.46211918 2.02684758 2.9561279 16.78145267\n", - " 2.1632391 2.78862788 9.7572645 2.05502494 2.88902145 8.79462238]\n", - "P_ = [ 2.05857413 2.64742507 6.87476982 1.88216351 2.92326403 9.33790808\n", - " 2.08254512 2.82123126 8.19077632 1.9858988 2.72853033 9.03801861\n", - " 1.77888032 2.75703324 10.27228862 1.71628841 2.87909957 11.00105173\n", - " 1.74903059 3.02064129 8.53516212 1.83305615 3.05954763 8.15791922\n", - " 2.05412588 2.9226279 15.37661504 2.15241768 2.79866724 9.66100028\n", - " 2.05502494 2.88902145 8.79462238]\n", - "Depth = 11, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 2.0830222 2.56475163 6.23213594 1.9198323 2.85061268 9.48436954\n", - " 2.0753602 2.78895697 7.69487785 1.92301484 2.70479851 9.27145235\n", - " 1.71454958 2.75273368 11.87836142 1.72752865 2.91486184 10.9660732\n", - " 1.8598209 3.07267937 6.84668052 1.86182026 2.86774261 9.2250252\n", - " 1.85813272 2.89929768 14.05321576 2.14757666 2.83761608 8.99034541\n", - " 2.26958297 2.89970855 9.17729645]\n", - "P_ = [ 2.0830222 2.56475163 6.23213594 1.93466774 2.82462532 9.18871194\n", - " 2.0470824 2.8001671 8.02023997 1.96456358 2.72775082 8.84147748\n", - " 1.79035513 2.73530271 10.93039448 1.72162907 2.84116722 11.38074966\n", - " 1.78766149 2.98659708 9.09362198 1.86054794 2.99815692 7.71153313\n", - " 1.86081457 2.87634854 10.54180445 1.91075889 2.88808285 13.13269387\n", - " 2.15866814 2.84326085 9.00734096 2.26958297 2.89970855 9.17729645]\n", - "Depth = 12, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 2.10798587 2.4968624 5.64218147 2.02687491 2.82914193 10.37155819\n", - " 2.00982271 2.92729557 6.67739913 1.92605901 2.83606389 9.10643033\n", - " 1.69723802 2.76934797 10.60184038 1.76291581 2.75010239 11.95850698\n", - " 1.8462061 2.94090952 10.96917567 1.91657628 3.01508048 6.40445577\n", - " 1.7836334 2.94863925 10.38993993 1.94840281 2.83789905 13.16382654\n", - " 2.13585392 2.82351282 9.43994205 2.1338 2.95931647 8.13098979]\n", - "P_ = [ 2.10798587 2.4968624 5.64218147 2.03363416 2.80145197 9.97744347\n", - " 2.01266474 2.91093663 7.2930923 1.94699993 2.85887181 8.49917253\n", - " 1.77351168 2.79158661 10.10337036 1.73555007 2.75812138 11.39322923\n", - " 1.80456095 2.84550595 11.46384133 1.87552701 2.97181409 9.06720905\n", - " 1.87226199 2.99293341 7.73295049 1.82482575 2.9209542 11.08341158\n", - " 1.97964466 2.83550134 12.54317913 2.13568276 2.83482979 9.33086269\n", - " 2.1338 2.95931647 8.13098979]\n", - "Depth = 13, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 2.10812766 2.44661254 5.79811415 2.04713836 2.77194462 9.54042392\n", - " 1.98029309 2.8611085 7.33064862 1.93056355 2.88267367 9.20471968\n", - " 1.68744624 2.83211824 10.86503798 1.73501219 2.80708545 11.64582231\n", - " 1.91123914 2.88338123 12.35468332 1.92479867 3.10346127 7.74672789\n", - " 1.7775125 3.03706091 7.15082577 1.82772143 2.96524233 12.05910173\n", - " 2.08057517 2.87385328 12.54500883 2.14953232 2.8873698 7.95829488\n", - " 2.16045669 2.97630198 8.29258848]\n", - "P_ = [ 2.10812766 2.44661254 5.79811415 2.05182985 2.74691907 9.25255394\n", - " 1.99057698 2.84739098 7.67061405 1.9420396 2.8776971 8.77224174\n", - " 1.76225157 2.84767376 10.35417081 1.71671759 2.81671345 11.34552065\n", - " 1.82990362 2.84816779 12.0275167 1.91749738 2.98495663 10.22793466\n", - " 1.86815014 3.07792267 7.51753477 1.7929614 3.01496289 8.66106453\n", - " 1.8860723 2.94415255 12.17123414 2.09118396 2.87593275 11.83936053\n", - " 2.15037266 2.89421073 7.98400977 2.16045669 2.97630198 8.29258848]\n", - "Depth = 14, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 2.10431242 2.41829165 5.19551743 2.09495903 2.77062276 9.56823313\n", - " 1.90308989 2.97431965 8.0775026 2.04061924 2.95514489 8.43010783\n", - " 1.62696784 2.81928147 10.32722534 1.70827499 2.80973857 12.43914084\n", - " 1.82246376 2.86591105 12.11366701 1.88614565 2.93815435 9.79801862\n", - " 1.79991626 3.00224841 8.3608707 1.83693368 2.98199016 7.24878011\n", - " 1.9488327 2.95173778 10.88279709 2.09615283 3.00492809 12.18854954\n", - " 2.23335016 3.02967199 7.77699157 1.97220343 3.0542084 10.15729589]\n", - "P_ = [ 2.10431242 2.41829165 5.19551743 2.09562713 2.74545625 9.25589629\n", - " 1.93049977 2.94522009 8.29046411 2.01114866 2.95925377 8.35454956\n", - " 1.74515395 2.85809959 9.78519176 1.67923672 2.81314675 11.6848853\n", - " 1.77352572 2.84183713 12.25315579 1.85430471 2.9020327 10.95584281\n", - " 1.8491902 2.96562323 9.18209808 1.81313677 2.99501332 7.96369549\n", - " 1.86890483 2.97334662 8.28707068 1.9804013 2.9631357 11.16260119\n", - " 2.11575245 3.00846293 11.55832698 2.21469682 3.03142459 7.9470133\n", - " 1.97220343 3.0542084 10.15729589]\n", - "Depth = 15, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 2.10711167 2.45065645 4.88079307 2.12110993 2.75965085 8.5668873\n", - " 1.85360145 2.99245261 8.11639155 2.0296737 2.9376602 8.73217586\n", - " 1.69827684 2.85948278 10.95048872 1.68902851 2.81731386 11.28151264\n", - " 1.80129961 2.78357937 12.38597265 1.90502939 2.8379463 10.67753313\n", - " 1.76774545 2.89209696 8.75981498 1.94757879 2.91504605 7.55667459\n", - " 1.94001736 2.84855464 8.54891034 2.02107652 3.02332188 11.61807985\n", - " 2.01937866 3.16329059 12.27651661 2.2709017 3.01807119 7.92257094\n", - " 2.00581202 3.03383998 11.11086982]\n", - "P_ = [ 2.10711167 2.45065645 4.88079307 2.12017671 2.73905123 8.32114769\n", - " 1.88926925 2.96141237 8.17645765 1.99445925 2.94861868 8.609019\n", - " 1.78664934 2.88033009 10.35893862 1.69211128 2.83137017 11.17117134\n", - " 1.75639117 2.79707317 11.94418865 1.85662216 2.81257507 11.47480491\n", - " 1.84096355 2.86321661 9.782598 1.83967879 2.9012766 8.27855883\n", - " 1.94505832 2.89288225 7.88741984 1.96163314 2.89515924 9.36735554\n", - " 2.02073695 3.05131562 11.74976721 2.05291507 3.143928 11.69599052\n", - " 2.25322905 3.01912244 8.1351242 2.00581202 3.03383998 11.11086982]\n", - "Depth = 16, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 2.12377054 2.44990323 4.91853957 2.14174594 2.72144184 8.56964356\n", - " 1.83627452 2.92320288 9.40528026 2.06213456 2.93636486 7.68371529\n", - " 1.66199553 2.8193535 10.34427754 1.72638332 2.81785873 10.91550958\n", - " 1.76495564 2.76119805 12.19016445 1.90145197 2.8258039 11.13895716\n", - " 1.8805756 2.88683223 8.94505139 1.92322248 2.94970328 7.25542785\n", - " 1.8517702 2.88336106 8.21329317 1.94864911 2.98882844 10.44735433\n", - " 2.07549158 3.16175845 11.55299723 1.97232279 3.09163023 12.15410929\n", - " 2.3468272 2.96044739 8.77290651 1.88935101 3.06652517 10.69726381]\n", - "P_ = [ 2.12377054 2.44990323 4.91853957 2.14062248 2.70447067 8.34144956\n", - " 1.87445845 2.89798275 9.30082567 2.01978581 2.93389699 8.00650872\n", - " 1.76203029 2.84860634 9.67913698 1.70626214 2.81832585 10.73699957\n", - " 1.75049102 2.7824458 11.71216888 1.84173483 2.79753884 11.59886035\n", - " 1.89101378 2.85631807 10.04200428 1.89923361 2.91433832 8.20584109\n", - " 1.89642788 2.92482495 7.61462734 1.88204486 2.91631962 8.91143728\n", - " 1.98035973 3.03206094 10.72376505 2.05614743 3.14860941 11.66570574\n", - " 2.01913584 3.07523237 11.73145894 2.31823494 2.96707725 8.89317884\n", - " 1.88935101 3.06652517 10.69726381]\n", - "Depth = 17, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 2.1022441 2.46763181 5.18056488 2.17927577 2.73789296 7.68588551\n", - " 1.92520533 2.91994226 9.33992195 2.03954574 2.94610284 9.53287523\n", - " 1.58864297 2.67018994 9.53244062 1.71785457 2.78218728 9.90910081\n", - " 1.78070116 2.86283677 12.15524247 1.88250698 2.79703002 11.35471192\n", - " 1.89272559 2.85871809 9.99063327 1.87085875 2.96837291 7.22955712\n", - " 1.8979451 2.84137853 6.99549649 1.96469782 2.76631093 9.76594778\n", - " 1.91769655 2.90073743 10.99762273 2.06584059 3.30445726 12.80600607\n", - " 2.04070113 3.15736967 12.29069533 2.28554863 2.85619817 8.47614815\n", - " 1.90825871 3.02217492 9.63957378]\n", - "P_ = [ 2.1022441 2.46763181 5.18056488 2.1747445 2.72199525 7.53851371\n", - " 1.95509597 2.8985247 9.14532943 2.01936802 2.94148627 9.49882465\n", - " 1.69473774 2.73511063 9.53254288 1.67985116 2.74924689 9.7983184\n", - " 1.75852001 2.83437224 11.36248659 1.84058693 2.82412691 11.68434215\n", - " 1.88791683 2.82968841 10.63255263 1.88243531 2.91032036 8.69130332\n", - " 1.88201195 2.91608111 7.13317922 1.92150488 2.81488408 7.97330283\n", - " 1.95087392 2.80584813 10.12820512 1.95255397 2.99573033 11.4231247\n", - " 2.06140421 3.27850063 12.71506888 2.06950672 3.12193773 11.84192507\n", - " 2.2633551 2.8659615 8.54458496 1.90825871 3.02217492 9.63957378]\n", - "Depth = 18, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 2.10353072 2.48553735 5.14702869 2.12194503 2.83984673 8.09405416\n", - " 1.9728567 2.938136 7.95682531 2.0730789 2.95972715 8.94291233\n", - " 1.60704795 2.72905582 10.06961822 1.63880439 2.75414946 9.47044231\n", - " 1.75020751 2.82889646 12.31158435 1.75140157 2.86940649 11.61893339\n", - " 1.9083247 2.7947776 9.94820229 1.88963347 2.82354555 9.46249995\n", - " 1.82547826 2.93818538 6.77917865 1.86932923 2.81564847 7.97715771\n", - " 1.99489916 2.84813473 10.27106812 1.95000048 3.02848299 10.67313453\n", - " 2.0564616 3.32813464 13.39092585 2.07553804 3.12994784 10.33453922\n", - " 2.31667942 2.83572721 10.362792 1.91213965 3.02387865 9.80609576]\n", - "P_ = [ 2.10353072 2.48553735 5.14702869 2.12092201 2.82016288 7.93033052\n", - " 1.98942207 2.92721497 7.97207296 2.0563752 2.95612862 8.77856449\n", - " 1.71061038 2.78031612 9.81923913 1.62998316 2.74717901 9.63688006\n", - " 1.71307314 2.8039808 11.36453701 1.75093722 2.85365259 11.88829765\n", - " 1.83858109 2.82794599 10.69074945 1.89897908 2.80916158 9.70535112\n", - " 1.86112004 2.87449659 8.26991271 1.84253141 2.89053214 7.2450594\n", - " 1.91118587 2.82647722 8.74179451 1.9824273 2.89823146 10.38275323\n", - " 1.97365851 3.09507224 11.27708816 2.059641 3.2951035 12.88152808\n", - " 2.10233153 3.09725666 10.33767842 2.29420499 2.84618006 10.33186443\n", - " 1.91213965 3.02387865 9.80609576]\n", - "Depth = 19, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 2.0787802 2.43570168 4.67603001 2.13277398 2.8329755 8.46104943\n", - " 1.96846484 3.02101366 6.52341236 2.08127599 2.98295688 9.25252122\n", - " 1.67392441 2.75280912 11.10470368 1.60882057 2.76601571 9.11242968\n", - " 1.69408163 2.90985785 11.09608215 1.81152483 2.87787907 11.44712792\n", - " 1.73072861 2.85591747 11.99622846 1.87890733 2.7928376 10.15485062\n", - " 2.07546512 2.85962732 8.03520147 1.80743281 2.79904379 6.28069859\n", - " 1.7941585 2.78485799 9.29709805 1.91705039 2.84000678 11.20944882\n", - " 2.05118127 3.24306304 11.28375426 2.0438037 3.37622587 12.22531661\n", - " 2.067424 3.03239388 10.30725733 2.36163437 2.90372382 9.80277759\n", - " 2.02628889 3.04202398 8.60612981]\n", - "P_ = [ 2.0787802 2.43570168 4.67603001 2.1299322 2.81206635 8.26183788\n", - " 1.98576054 3.00122017 6.72737415 2.06346371 2.98896584 8.82160929\n", - " 1.75968264 2.80126128 10.71477053 1.62595316 2.7625403 9.63671231\n", - " 1.66715709 2.86443402 10.46966558 1.76825628 2.88966072 11.31779527\n", - " 1.76474807 2.86516446 11.76502823 1.80871741 2.82271754 11.02708223\n", - " 1.97201365 2.82447483 9.15080629 1.96260941 2.83411846 7.29646341\n", - " 1.80254227 2.79381744 7.39200365 1.83296646 2.8022734 9.90099829\n", - " 1.95234799 2.94607422 11.22900288 2.0496281 3.27109732 11.48197791\n", - " 2.04753322 3.32193661 11.92246514 2.09839352 3.01884967 10.2541542\n", - " 2.34398461 2.91100278 9.73979613 2.02628889 3.04202398 8.60612981]\n", - "Depth = 20, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "2.2857142857142856 [11.14435039 7.52011787 5.47346508 4.39358341 4.61829309 4.0013485\n", - " 3.64903166 3.5137233 3.40590865 3.26255546 3.16627128 3.01700447\n", - " 2.92920128 2.92284537 2.87453535 2.79026193 2.57354493 2.51534314\n", - " 2.44479359 2.37200446]\n", - "[[6.20528854 5.90276273 4.34974565 2.82648708 2.83216236 2.53390824\n", - " 2.48542936 2.39488186 1.78514917 1.78156864 1.63586622 1.93423131\n", - " 1.3466511 1.61587827 1.31723472 1.39380148 1.3212952 1.48519626\n", - " 1.19207192 1.19585198]\n", - " [7.30404471 4.53202785 3.46764965 2.88567087 2.50354724 2.12413704\n", - " 1.93259722 1.8208787 1.66881973 1.61137624 1.5777798 1.52441689\n", - " 1.50488971 1.32477289 1.14366376 1.10087346 1.06542039 1.04874467\n", - " 1.03100111 1.02313941]\n", - " [5.58705617 3.86360072 3.41898777 2.93676719 2.39036205 2.0121624\n", - " 1.79015272 1.5724717 1.47417254 1.46262495 1.42887826 1.36386696\n", - " 1.19370592 1.14920231 1.13162789 1.12219725 1.11458449 1.1084955\n", - " 1.09949537 1.09388173]\n", - " [5.77641939 4.14594873 3.04742423 2.27060879 2.06202637 1.94723727\n", - " 1.8320844 1.70380182 1.61599104 1.56657979 1.54148441 1.50955144\n", - " 1.49049303 1.42195588 1.33696517 1.23201985 1.17342154 1.15521269\n", - " 1.15315425 1.1445845 ]\n", - " [4.8756533 3.29005157 2.39464097 1.92219274 2.02050323 1.75058997\n", - " 1.59645135 1.53725395 1.49008503 1.42736801 1.38524369 1.31993946\n", - " 1.28152556 1.27874485 1.25760921 1.22073959 1.12592591 1.10046262\n", - " 1.0695972 1.03775195]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]] [2.97484621 2.17343916 1.66784483 1.28417267 1.18086012 1.03680349\n", - " 0.96367151 0.9029288 0.80342175 0.78495176 0.75692524 0.76520061\n", - " 0.68172653 0.67905542 0.61871008 0.60696316 0.58006475 0.58981117\n", - " 0.55453198 0.54952096]\n", - "[[0.17030757 0.16850299 0.24687602 0.45514832 0.45145637 0.56268179\n", - " 0.4723914 0.62266371 0.8026945 0.81119819 0.87005395 0.73125403\n", - " 0.9110609 0.83507433 0.90935654 0.90735586 0.92006095 0.88620215\n", - " 0.96581763 0.96554472]\n", - " [0.18431054 0.3834123 0.50873566 0.61052141 0.696016 0.79140483\n", - " 0.84466927 0.87844738 0.91858227 0.93545701 0.95087783 0.95794391\n", - " 0.96260089 0.96665922 0.98020554 0.98747975 0.99371878 0.99672513\n", - " 0.99769447 0.9985309 ]\n", - " [0.20432833 0.3184594 0.35443145 0.44587035 0.69188034 0.79613223\n", - " 0.85245109 0.94248088 0.96021228 0.960348 0.9695536 0.96022371\n", - " 0.98485672 0.99130491 0.99357222 0.99489111 0.99620155 0.99674134\n", - " 0.99723741 0.99702852]\n", - " [0.16226489 0.29705928 0.5086956 0.65943464 0.69698848 0.74147959\n", - " 0.75625945 0.9055608 0.93509535 0.96329039 0.97453832 0.97952655\n", - " 0.98353524 0.98310405 0.96598607 0.98112827 0.99426833 0.99638548\n", - " 0.99420366 0.9903845 ]\n", - " [0.12618061 0.21274452 0.44887434 0.55799579 0.47129411 0.67024636\n", - " 0.81569347 0.85178296 0.86009797 0.8940358 0.95873854 0.96613408\n", - " 0.97097553 0.95065719 0.97167497 0.98014358 0.98184616 0.97738053\n", - " 0.98501329 0.99168417]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]] [0.08473919 0.13801785 0.20676131 0.27289705 0.30076353 0.35619448\n", - " 0.37414647 0.42009357 0.44766824 0.45643294 0.47237622 0.45950823\n", - " 0.48130293 0.47267997 0.48207953 0.48509986 0.48860958 0.48534346\n", - " 0.49399664 0.49431728]\n", - "\n", - "Now using 3 solutions, set number 6\n", - "Calculating energy landscape ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 9.491659\n", - " Iterations: 70\n", - " Function evaluations: 128\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 9.491659\n", - " Iterations: 17\n", - " Function evaluations: 34\n", - "P = [0.22867351 1.96993302 0.32564453]\n", - "P_ = [0.22867351 1.96993302 0.32564453 0.22867351 1.96993302 0.32564453]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 6.048405\n", - " Iterations: 109\n", - " Function evaluations: 175\n", - "P = [0.2081537 1.73111324 0.32025028 0.42129876 1.84668442 0.13550886]\n", - "P_ = [0.2081537 1.73111324 0.32025028 0.31472623 1.78889883 0.22787957\n", - " 0.42129876 1.84668442 0.13550886]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.352686\n", - " Iterations: 251\n", - " Function evaluations: 374\n", - "P = [0.1657956 1.92305118 0.1810702 0.35776412 1.67413717 0.3587229\n", - " 0.41760512 1.77849811 0.13271793]\n", - "P_ = [0.1657956 1.92305118 0.1810702 0.29377461 1.7571085 0.29950534\n", - " 0.37771112 1.70892415 0.28338791 0.41760512 1.77849811 0.13271793]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.809655\n", - " Iterations: 82\n", - " Function evaluations: 137\n", - "P = [0.15506255 1.87833734 0.18291 0.29944751 1.75559238 0.31052103\n", - " 0.38989125 1.69557291 0.29004779 0.43109189 1.70384048 0.1360706 ]\n", - "P_ = [0.15506255 1.87833734 0.18291 0.26335127 1.78627862 0.27861828\n", - " 0.34466938 1.72558265 0.30028441 0.40019141 1.69763981 0.25155349\n", - " 0.43109189 1.70384048 0.1360706 ]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.646411\n", - " Iterations: 97\n", - " Function evaluations: 165\n", - "P = [0.13723349 1.91095384 0.18642417 0.26858495 1.73685915 0.28858403\n", - " 0.33977857 1.72023163 0.30440319 0.40979378 1.67918546 0.26191363\n", - " 0.44628722 1.64188437 0.14103189]\n", - "P_ = [0.13723349 1.91095384 0.18642417 0.24231466 1.77167809 0.26815205\n", - " 0.31130112 1.72688264 0.29807553 0.36778466 1.70381316 0.28740737\n", - " 0.41709247 1.67172524 0.23773728 0.44628722 1.64188437 0.14103189]\n", - "Depth = 6, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 0.12703998 1.99726675 -0.22650911 0.23828208 1.67069271 1.12504139\n", - " 0.28179723 1.77348066 -0.89319759 0.26747355 1.62723976 -0.38339961\n", - " 0.28809895 1.64699499 0.61392411 0.42679007 1.658738 -0.67271568]\n", - "P_ = [ 0.12703998 1.99726675 -0.22650911 0.21974173 1.72512171 0.89978298\n", - " 0.26729218 1.73921801 -0.22045126 0.27463539 1.70036021 -0.6382986\n", - " 0.27434869 1.63382484 -0.05095837 0.31121414 1.64895216 0.39948414\n", - " 0.42679007 1.658738 -0.67271568]\n", - "Depth = 7, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.120909\n", - " Iterations: 1847\n", - " Function evaluations: 2365\n", - "P = [ 0.12124804 1.96697008 -0.40857879 0.25263993 1.73676469 0.11684713\n", - " 0.26543497 1.78321698 -0.26670067 0.29129244 1.6616565 -0.59727836\n", - " 0.29151311 1.69315276 -0.04459176 0.42197791 1.63677848 0.47949098\n", - " 0.48788218 1.66965905 -0.19997711]\n", - "P_ = [ 0.12124804 1.96697008 -0.40857879 0.23386966 1.76965117 0.04178629\n", - " 0.26177925 1.76994489 -0.15711558 0.28021067 1.71375385 -0.45560221\n", - " 0.29138701 1.6751549 -0.36041267 0.32878877 1.67704582 0.10514616\n", - " 0.4313928 1.6414757 0.38242411 0.48788218 1.66965905 -0.19997711]\n", - "Depth = 8, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.004462\n", - " Iterations: 728\n", - " Function evaluations: 947\n", - "P = [ 0.11506528 1.88525004 -0.34541519 0.25158162 1.82709594 0.03779163\n", - " 0.27600126 1.71070769 -0.17704401 0.28557537 1.74730633 -0.51282201\n", - " 0.30712472 1.66022775 -0.15167929 0.33592933 1.6833405 0.11919985\n", - " 0.44101253 1.63164524 0.52610865 0.45906789 1.66108615 -0.17266856]\n", - "P_ = [ 0.11506528 1.88525004 -0.34541519 0.23451707 1.8343652 -0.01010922\n", - " 0.26989635 1.73980475 -0.1233351 0.28198508 1.73358184 -0.38690526\n", - " 0.29635005 1.70376704 -0.33225065 0.31792645 1.66889503 -0.05009961\n", - " 0.36220013 1.67041669 0.22092705 0.44326945 1.63532535 0.4387615\n", - " 0.45906789 1.66108615 -0.17266856]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.980407\n", - " Iterations: 417\n", - " Function evaluations: 581\n", - "P = [ 0.09843115 1.89278162 -0.2934979 0.22545243 1.80396586 -0.01047213\n", - " 0.27049137 1.73812747 -0.12810954 0.29119921 1.71867365 -0.40396081\n", - " 0.30096299 1.69547976 -0.32991882 0.32546049 1.65867792 -0.05106935\n", - " 0.39189359 1.65847334 0.23495789 0.43539712 1.63005656 0.47389318\n", - " 0.44715139 1.6186623 -0.17996861]\n", - "P_ = [ 0.09843115 1.89278162 -0.2934979 0.21133895 1.81383428 -0.04191944\n", - " 0.26048272 1.75275822 -0.10196789 0.2842966 1.72515826 -0.31201038\n", - " 0.29662354 1.70578816 -0.36282637 0.31185077 1.67912339 -0.20598572\n", - " 0.34760486 1.65860973 0.04427306 0.40156104 1.6521585 0.28805462\n", - " 0.43670315 1.62879053 0.40124187 0.44715139 1.6186623 -0.17996861]\n", - "Depth = 10, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.883905\n", - " Iterations: 1511\n", - " Function evaluations: 1877\n", - "P = [ 0.10344969 1.95756549 -0.25279562 0.18341913 1.72438815 -0.03884907\n", - " 0.18056148 1.714327 -0.12021632 0.2487435 1.72044813 -0.35399144\n", - " 0.29290594 1.69847003 -0.4649597 0.29991676 1.7081601 -0.04134809\n", - " 0.31845695 1.64216035 0.05469436 0.37484291 1.67948733 0.3441278\n", - " 0.44188826 1.61924942 0.69850749 0.46457812 1.63700531 -0.18272258]\n", - "P_ = [ 0.10344969 1.95756549 -0.25279562 0.17542218 1.74770589 -0.06024372\n", - " 0.18113301 1.71633923 -0.10394287 0.22828889 1.71861179 -0.2838589\n", - " 0.27524096 1.70726127 -0.4205724 0.29641135 1.70331506 -0.2531539\n", - " 0.30733283 1.6817602 -0.00293111 0.33537274 1.65335844 0.14152439\n", - " 0.38825198 1.66743975 0.41500374 0.44415725 1.62102501 0.61038449\n", - " 0.46457812 1.63700531 -0.18272258]\n", - "Depth = 11, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 1.31264581e-01 1.93612741e+00 -9.86502687e-01 2.63477083e-01\n", - " 1.72082790e+00 1.25816142e-01 2.53688619e-02 1.60490921e+00\n", - " -1.80431433e-01 2.67151161e-01 1.76974094e+00 -1.32947629e+00\n", - " 2.85484383e-01 1.75626332e+00 -9.26294590e-01 2.86027327e-01\n", - " 1.71224877e+00 -4.34619868e-01 3.00788558e-01 1.72007843e+00\n", - " -4.19706076e-04 3.34664211e-01 1.68684268e+00 -9.28310422e-02\n", - " 3.48389522e-01 1.70518171e+00 4.79495630e-02 4.19299413e-01\n", - " 1.64129622e+00 1.07095101e-01 4.73101734e-01 1.64824006e+00\n", - " 3.98516489e-01]\n", - "P_ = [ 0.13126458 1.93612741 -0.98650269 0.25145776 1.74040058 0.02469625\n", - " 0.06866127 1.62598533 -0.12475006 0.20121053 1.72478683 -1.01610042\n", - " 0.27881776 1.76116427 -1.07290612 0.28578053 1.73225538 -0.65810838\n", - " 0.29273698 1.71580771 -0.23725616 0.31310698 1.7079927 -0.03402383\n", - " 0.33840748 1.69184423 -0.05443633 0.36128223 1.69356617 0.0587033\n", - " 0.42419053 1.64192748 0.13358795 0.47310173 1.64824006 0.39851649]\n", - "Depth = 12, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.641487\n", - " Iterations: 2239\n", - " Function evaluations: 2746\n", - "P = [ 0.10416797 1.80584305 -0.85836901 0.23071368 1.85727434 0.02575133\n", - " 0.07969716 1.5519787 -0.1430176 0.22998211 1.75556591 -1.1143208\n", - " 0.27556761 1.73437787 -0.87558875 0.28904602 1.74825037 -0.71399031\n", - " 0.30710799 1.7000338 -0.20607416 0.31475792 1.71914481 -0.0311207\n", - " 0.33695143 1.68231182 -0.063203 0.34844499 1.68455344 0.06132344\n", - " 0.40753828 1.62506633 0.12289213 0.4563531 1.63748784 0.47172188]\n", - "P_ = [ 0.10416797 1.80584305 -0.85836901 0.22016821 1.8529884 -0.04792537\n", - " 0.10486658 1.6028613 -0.11488944 0.19241087 1.7046691 -0.871495\n", - " 0.26037244 1.74144055 -0.9551661 0.28343002 1.74247016 -0.78132299\n", - " 0.298077 1.72414209 -0.46003223 0.31029546 1.70799672 -0.13317688\n", - " 0.32215576 1.70686715 -0.0418148 0.33982482 1.68287223 -0.03207139\n", - " 0.35829387 1.67463892 0.07158489 0.41160618 1.62610146 0.15196128\n", - " 0.4563531 1.63748784 0.47172188]\n", - "Depth = 13, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.596498\n", - " Iterations: 887\n", - " Function evaluations: 1161\n", - "P = [ 0.09410201 1.80781033 -0.81605315 0.20575219 1.84585976 -0.04772781\n", - " 0.10246287 1.56886923 -0.1158574 0.19796195 1.72061646 -0.95205972\n", - " 0.27128326 1.73825819 -1.03853704 0.29093622 1.73589818 -0.74114385\n", - " 0.31312153 1.72348348 -0.46140512 0.31672414 1.70260608 -0.14013824\n", - " 0.31495794 1.70385046 -0.04287319 0.33610014 1.68105774 -0.03306623\n", - " 0.35944866 1.65983321 0.07150472 0.42446379 1.62838614 0.14914043\n", - " 0.44492428 1.62450318 0.47598328]\n", - "P_ = [ 0.09410201 1.80781033 -0.81605315 0.19716372 1.84293288 -0.10682976\n", - " 0.11835353 1.61148316 -0.10537592 0.1759237 1.68559787 -0.75908996\n", - " 0.24872286 1.73282997 -1.01192864 0.28337739 1.73680588 -0.85552585\n", - " 0.30288215 1.72921335 -0.5905153 0.31478427 1.71384776 -0.3131281\n", - " 0.31604483 1.70308469 -0.10272861 0.32146323 1.69683732 -0.03985567\n", - " 0.34148826 1.67615977 -0.00893447 0.36945099 1.6549952 0.08344867\n", - " 0.42603768 1.62808745 0.17428219 0.44492428 1.62450318 0.47598328]\n", - "Depth = 14, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.575144\n", - " Iterations: 678\n", - " Function evaluations: 901\n", - "P = [ 0.08709193 1.81944864 -0.81655697 0.18894622 1.82403597 -0.10881947\n", - " 0.11143555 1.58985889 -0.10640965 0.1697531 1.69325303 -0.80310227\n", - " 0.25266135 1.72771427 -1.04894018 0.2863944 1.73195383 -0.84690873\n", - " 0.30347512 1.72425275 -0.59865005 0.31656196 1.71109963 -0.32203362\n", - " 0.31740091 1.69654105 -0.10386318 0.32221652 1.70146403 -0.04073654\n", - " 0.34721322 1.6648378 -0.00904695 0.36864517 1.65061587 0.08098923\n", - " 0.41853494 1.61834622 0.18782113 0.45735469 1.61675355 0.48446436]\n", - "P_ = [ 0.08709193 1.81944864 -0.81655697 0.18167092 1.82370831 -0.15937215\n", - " 0.1225085 1.62331276 -0.10675391 0.15725648 1.67109715 -0.65381099\n", - " 0.22897328 1.7178682 -0.97870077 0.27434688 1.7304397 -0.91906282\n", - " 0.29615481 1.72755321 -0.70504663 0.31001854 1.71767619 -0.46034184\n", - " 0.31692151 1.70486024 -0.228532 0.31912077 1.69829926 -0.08131795\n", - " 0.32935844 1.69099939 -0.03168237 0.35180578 1.66179024 0.01024652\n", - " 0.37577228 1.64600592 0.09625093 0.42130778 1.61823245 0.20900993\n", - " 0.45735469 1.61675355 0.48446436]\n", - "Depth = 15, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.545574\n", - " Iterations: 3231\n", - " Function evaluations: 3817\n", - "P = [ 0.08294307 1.84540625 -0.78186342 0.16748461 1.80742518 -0.20544897\n", - " 0.08884299 1.58303576 -0.09497818 0.14685762 1.68518209 -0.71937181\n", - " 0.23758774 1.72115679 -0.9278364 0.27023395 1.72153224 -1.04302071\n", - " 0.28445076 1.72816806 -0.61123893 0.28863603 1.70612029 -0.49357175\n", - " 0.30996427 1.70846915 -0.30191915 0.32354124 1.70253212 -0.09650748\n", - " 0.32695932 1.68889446 -0.0390899 0.34625679 1.6629799 0.00963147\n", - " 0.3311483 1.63350704 0.07413858 0.38937393 1.6139325 0.1808627\n", - " 0.45162793 1.6161359 0.74449729]\n", - "P_ = [ 0.08294307 1.84540625 -0.78186342 0.16184851 1.80995725 -0.2438766\n", - " 0.09932854 1.61295435 -0.10970762 0.1352547 1.66475282 -0.59449308\n", - " 0.21339304 1.71156354 -0.87224584 0.25935188 1.72140709 -1.00462594\n", - " 0.27876404 1.72551373 -0.78395164 0.28668291 1.71640925 -0.5484831\n", - " 0.29858921 1.70721643 -0.40413387 0.31539506 1.70609434 -0.21975448\n", - " 0.3246806 1.69798623 -0.07736829 0.33210531 1.68198391 -0.02609753\n", - " 0.3432351 1.65708533 0.02253289 0.33891171 1.6308971 0.08836846\n", - " 0.39352419 1.6140794 0.21843834 0.45162793 1.6161359 0.74449729]\n", - "Depth = 16, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 0.08496654 1.86088629 -0.66124687 0.18574938 1.81747075 -0.29378596\n", - " 0.06671772 1.57387852 -0.09268758 0.18913692 1.71341354 -0.75528799\n", - " 0.21616617 1.69817318 -0.98150255 0.21814945 1.67904991 -0.86622281\n", - " 0.2455667 1.70415568 -0.58468494 0.27584714 1.69316296 -0.58351565\n", - " 0.30128946 1.7184458 -0.41485494 0.30655599 1.68561575 -0.36609378\n", - " 0.31778783 1.70272106 -0.10279174 0.32124355 1.67399893 -0.06679354\n", - " 0.34330945 1.65670384 -0.0236184 0.3544984 1.64016432 0.05877037\n", - " 0.34993711 1.59803706 0.21820813 0.42158967 1.61803891 0.6836247 ]\n", - "P_ = [ 0.08496654 1.86088629 -0.66124687 0.17945045 1.82018422 -0.31675227\n", - " 0.08159668 1.60432755 -0.11782487 0.16618332 1.68725072 -0.63105041\n", - " 0.20940886 1.70198327 -0.92494891 0.21752968 1.68502593 -0.90224773\n", - " 0.23528523 1.69474102 -0.69026164 0.26259945 1.69797227 -0.58402722\n", - " 0.2885683 1.70580438 -0.4991853 0.30359357 1.70408265 -0.39352193\n", - " 0.31076793 1.69203024 -0.26735551 0.31886774 1.69374539 -0.0915423\n", - " 0.32676003 1.66967516 -0.05599976 0.34540738 1.65360268 -0.0081705\n", - " 0.35392824 1.63489841 0.07870009 0.35441539 1.59928718 0.24729667\n", - " 0.42158967 1.61803891 0.6836247 ]\n", - "Depth = 17, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.493446\n", - " Iterations: 2250\n", - " Function evaluations: 2729\n", - "P = [ 0.07814554 1.86298664 -0.65298456 0.17558469 1.83249742 -0.30433207\n", - " 0.07450164 1.58958889 -0.11311214 0.17739227 1.70482622 -0.7720411\n", - " 0.23471629 1.72927256 -1.0340933 0.22544501 1.68045957 -0.81250987\n", - " 0.22577071 1.68551496 -0.69066283 0.26056195 1.69221439 -0.56774622\n", - " 0.28720614 1.70425191 -0.43998282 0.29913673 1.70426117 -0.46745588\n", - " 0.30836098 1.68594664 -0.38894973 0.32648979 1.69070997 -0.11371272\n", - " 0.33161519 1.66946927 -0.02613498 0.34328299 1.65391091 -0.00676748\n", - " 0.33153692 1.62126481 0.07716498 0.38765223 1.60801549 0.24252275\n", - " 0.45028484 1.60955304 0.71013401]\n", - "P_ = [ 0.07814554 1.86298664 -0.65298456 0.16985298 1.8342909 -0.32484104\n", - " 0.08639376 1.61816637 -0.13560861 0.1592351 1.68449022 -0.65575952\n", - " 0.22122828 1.72352048 -0.97243396 0.22817186 1.69481633 -0.87768147\n", - " 0.22565576 1.6837307 -0.73366767 0.24623615 1.6894558 -0.61835894\n", - " 0.2746677 1.69858719 -0.50010678 0.29282054 1.70425627 -0.45291132\n", - " 0.30293495 1.69671989 -0.43512982 0.31475939 1.68762782 -0.29180726\n", - " 0.32799726 1.68446271 -0.08795456 0.33436056 1.66580848 -0.02157792\n", - " 0.34121016 1.64814983 0.00804413 0.33813872 1.61970607 0.09661883\n", - " 0.3913365 1.60810593 0.2700293 0.45028484 1.60955304 0.71013401]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.478625\n", - " Iterations: 3013\n", - " Function evaluations: 3589\n", - "P = [ 0.07800182 1.855223 -0.61629977 0.164176 1.82326115 -0.31613211\n", - " 0.09371651 1.60073905 -0.1174746 0.16539991 1.71389529 -0.6347892\n", - " 0.22934169 1.7200045 -1.13407838 0.24637036 1.70453406 -0.82691992\n", - " 0.2338053 1.68235524 -0.62171092 0.24280651 1.67637884 -0.70330543\n", - " 0.27339617 1.69739182 -0.52565833 0.28295818 1.69335036 -0.43832336\n", - " 0.29263329 1.69345229 -0.53000712 0.31951562 1.68261646 -0.37855859\n", - " 0.32806639 1.68299049 -0.08368994 0.31903017 1.66574247 -0.02278029\n", - " 0.33721941 1.64433558 0.00705626 0.33493016 1.62602167 0.09146577\n", - " 0.39901444 1.60644604 0.34301087 0.45584623 1.61363307 0.5494713 ]\n", - "P_ = [ 0.07800182 1.855223 -0.61629977 0.15938855 1.82503681 -0.33280809\n", - " 0.10154534 1.62546372 -0.13954765 0.15345268 1.69503592 -0.5485701\n", - " 0.21513241 1.7186469 -1.02312523 0.24164017 1.7088314 -0.91224171\n", - " 0.23799365 1.68974818 -0.69011392 0.23930604 1.67870299 -0.67157423\n", - " 0.25980076 1.68805271 -0.6046126 0.27817718 1.69537109 -0.48199085\n", - " 0.28725823 1.69339566 -0.4790717 0.30308753 1.68923836 -0.47111047\n", - " 0.32236587 1.68274114 -0.28026904 0.32555633 1.67819937 -0.0667706\n", - " 0.32307223 1.66098538 -0.01614995 0.33683786 1.64128326 0.02112451\n", - " 0.34205063 1.6238466 0.11941523 0.40217176 1.60684532 0.35448089\n", - " 0.45584623 1.61363307 0.5494713 ]\n", - "Depth = 19, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.471168\n", - " Iterations: 1718\n", - " Function evaluations: 2140\n", - "P = [ 0.07277446 1.86492391 -0.5804565 0.15648188 1.81802768 -0.33668153\n", - " 0.10138213 1.61389663 -0.13748194 0.15265973 1.70081787 -0.56027233\n", - " 0.21812946 1.71948855 -0.99590913 0.24313706 1.70537837 -0.88458527\n", - " 0.23986332 1.6926119 -0.67045868 0.24127534 1.67532044 -0.66442632\n", - " 0.26332193 1.68557524 -0.59393396 0.27705053 1.69174153 -0.48147334\n", - " 0.28624014 1.68899178 -0.49212292 0.30633257 1.69015439 -0.50652622\n", - " 0.3240293 1.6777399 -0.29574068 0.3297599 1.67295175 -0.06528952\n", - " 0.3231557 1.65852174 -0.01618079 0.34600809 1.63799192 0.02024996\n", - " 0.35357784 1.62476646 0.12165531 0.40766448 1.60361407 0.36913102\n", - " 0.46003192 1.60875224 0.51390093]\n", - "P_ = [ 0.07277446 1.86492391 -0.5804565 0.15207623 1.8204959 -0.34951179\n", - " 0.10718211 1.63538411 -0.15845032 0.14456327 1.68709346 -0.49351596\n", - " 0.20434636 1.71555788 -0.90419612 0.23655611 1.70909158 -0.91388102\n", - " 0.24089713 1.69664342 -0.73807761 0.24075512 1.68169098 -0.66664877\n", - " 0.25403915 1.68125743 -0.62361495 0.27054751 1.68882066 -0.53474416\n", - " 0.2814035 1.69043902 -0.48651788 0.29470011 1.6894813 -0.49818747\n", - " 0.31285242 1.68558063 -0.42886839 0.32583897 1.67622786 -0.22296663\n", - " 0.32802195 1.66915438 -0.05236617 0.32796673 1.65419967 -0.00851116\n", - " 0.34720331 1.63590369 0.03626134 0.35927117 1.6225399 0.14770539\n", - " 0.41042066 1.6038845 0.37675049 0.46003192 1.60875224 0.51390093]\n", - "Depth = 20, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.468053\n", - " Iterations: 1102\n", - " Function evaluations: 1463\n", - "2.4285714285714284 [9.49165903 6.04840458 4.35268578 3.80965479 3.64641091 3.33322723\n", - " 3.12090875 3.00446248 2.98040658 2.88390517 2.71404212 2.64148713\n", - " 2.59649843 2.57514437 2.54557446 2.51290704 2.49344616 2.47862478\n", - " 2.4711684 2.46805344]\n", - "[[6.20528854 5.90276273 4.34974565 2.82648708 2.83216236 2.53390824\n", - " 2.48542936 2.39488186 1.78514917 1.78156864 1.63586622 1.93423131\n", - " 1.3466511 1.61587827 1.31723472 1.39380148 1.3212952 1.48519626\n", - " 1.19207192 1.19585198]\n", - " [7.30404471 4.53202785 3.46764965 2.88567087 2.50354724 2.12413704\n", - " 1.93259722 1.8208787 1.66881973 1.61137624 1.5777798 1.52441689\n", - " 1.50488971 1.32477289 1.14366376 1.10087346 1.06542039 1.04874467\n", - " 1.03100111 1.02313941]\n", - " [5.58705617 3.86360072 3.41898777 2.93676719 2.39036205 2.0121624\n", - " 1.79015272 1.5724717 1.47417254 1.46262495 1.42887826 1.36386696\n", - " 1.19370592 1.14920231 1.13162789 1.12219725 1.11458449 1.1084955\n", - " 1.09949537 1.09388173]\n", - " [5.77641939 4.14594873 3.04742423 2.27060879 2.06202637 1.94723727\n", - " 1.8320844 1.70380182 1.61599104 1.56657979 1.54148441 1.50955144\n", - " 1.49049303 1.42195588 1.33696517 1.23201985 1.17342154 1.15521269\n", - " 1.15315425 1.1445845 ]\n", - " [4.8756533 3.29005157 2.39464097 1.92219274 2.02050323 1.75058997\n", - " 1.59645135 1.53725395 1.49008503 1.42736801 1.38524369 1.31993946\n", - " 1.28152556 1.27874485 1.25760921 1.22073959 1.12592591 1.10046262\n", - " 1.0695972 1.03775195]\n", - " [3.90833019 2.49051953 1.79228238 1.56868139 1.50146331 1.37250533\n", - " 1.28508007 1.23713161 1.22722624 1.18749036 1.11754675 1.08767117\n", - " 1.06914641 1.06035356 1.04817772 1.03472643 1.02671312 1.0206102\n", - " 1.01753993 1.0162573 ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]] [3.36567923 2.42249111 1.84707306 1.44104081 1.33100646 1.17405402\n", - " 1.09217951 1.02664196 0.92614438 0.9037008 0.86867991 0.87396772\n", - " 0.78864117 0.78509078 0.72352785 0.71043581 0.68273607 0.69187219\n", - " 0.65628598 0.65114669]\n", - "[[0.17030757 0.16850299 0.24687602 0.45514832 0.45145637 0.56268179\n", - " 0.4723914 0.62266371 0.8026945 0.81119819 0.87005395 0.73125403\n", - " 0.9110609 0.83507433 0.90935654 0.90735586 0.92006095 0.88620215\n", - " 0.96581763 0.96554472]\n", - " [0.18431054 0.3834123 0.50873566 0.61052141 0.696016 0.79140483\n", - " 0.84466927 0.87844738 0.91858227 0.93545701 0.95087783 0.95794391\n", - " 0.96260089 0.96665922 0.98020554 0.98747975 0.99371878 0.99672513\n", - " 0.99769447 0.9985309 ]\n", - " [0.20432833 0.3184594 0.35443145 0.44587035 0.69188034 0.79613223\n", - " 0.85245109 0.94248088 0.96021228 0.960348 0.9695536 0.96022371\n", - " 0.98485672 0.99130491 0.99357222 0.99489111 0.99620155 0.99674134\n", - " 0.99723741 0.99702852]\n", - " [0.16226489 0.29705928 0.5086956 0.65943464 0.69698848 0.74147959\n", - " 0.75625945 0.9055608 0.93509535 0.96329039 0.97453832 0.97952655\n", - " 0.98353524 0.98310405 0.96598607 0.98112827 0.99426833 0.99638548\n", - " 0.99420366 0.9903845 ]\n", - " [0.12618061 0.21274452 0.44887434 0.55799579 0.47129411 0.67024636\n", - " 0.81569347 0.85178296 0.86009797 0.8940358 0.95873854 0.96613408\n", - " 0.97097553 0.95065719 0.97167497 0.98014358 0.98184616 0.97738053\n", - " 0.98501329 0.99168417]\n", - " [0.16591198 0.47710568 0.71119166 0.81217357 0.84357453 0.83394421\n", - " 0.8721109 0.91516457 0.91878387 0.95096964 0.96259298 0.97508223\n", - " 0.98345956 0.98682672 0.98877728 0.99066647 0.99277997 0.99525734\n", - " 0.99655034 0.99726773]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]] [0.10133039 0.18572842 0.27788047 0.35411441 0.38512098 0.4395889\n", - " 0.46135756 0.51161003 0.53954662 0.5515299 0.56863552 0.55701645\n", - " 0.57964888 0.57136264 0.58095726 0.5841665 0.58788757 0.5848692\n", - " 0.59365168 0.59404405]\n", - "\n", - "Now using 4 solutions, set number 1\n", - "Calculating energy landscape ...\n", - "Optimization terminated successfully.\n", - " Current function value: 7.225795\n", - " Iterations: 68\n", - " Function evaluations: 129\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 7.225795\n", - " Iterations: 17\n", - " Function evaluations: 34\n", - "P = [5.94789035 1.17997352 0.28581869]\n", - "P_ = [5.94789035 1.17997352 0.28581869 5.94789035 1.17997352 0.28581869]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.905247\n", - " Iterations: 101\n", - " Function evaluations: 168\n", - "P = [5.96903759 1.39860886 0.03841416 5.74014384 1.25303704 0.24512565]\n", - "P_ = [5.96903759 1.39860886 0.03841416 5.85459071 1.32582295 0.1417699\n", - " 5.74014384 1.25303704 0.24512565]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.172626\n", - " Iterations: 322\n", - " Function evaluations: 473\n", - "P = [5.97266013 1.22125327 0.04501097 5.73747507 1.34830605 0.12643645\n", - " 5.63343723 1.41337949 0.25053157]\n", - "P_ = [5.97266013 1.22125327 0.04501097 5.81587009 1.30595512 0.09929462\n", - " 5.70279579 1.3699972 0.16780149 5.63343723 1.41337949 0.25053157]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.749237\n", - " Iterations: 205\n", - " Function evaluations: 300\n", - "P = [5.94447168 1.26996725 0.04636016 5.69465055 1.23566042 0.09637654\n", - " 5.60152378 1.46854066 0.17121492 5.46833761 1.44881732 0.25208708]\n", - "P_ = [5.94447168 1.26996725 0.04636016 5.75710583 1.24423713 0.08387244\n", - " 5.64808716 1.35210054 0.13379573 5.56822723 1.46360982 0.19143296\n", - " 5.46833761 1.44881732 0.25208708]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.448177\n", - " Iterations: 175\n", - " Function evaluations: 272\n", - "P = [5.99321883 1.21376276 0.04538211 5.70774957 1.28369544 0.0849905\n", - " 5.62471515 1.36200331 0.13440596 5.5389902 1.48335559 0.19032834\n", - " 5.68178131 1.46739308 0.2539237 ]\n", - "P_ = [5.99321883 1.21376276 0.04538211 5.76484342 1.26970891 0.07706882\n", - " 5.65792892 1.33068016 0.11463977 5.59042517 1.41054422 0.15677491\n", - " 5.56754842 1.48016309 0.20304741 5.68178131 1.46739308 0.2539237 ]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.356122\n", - " Iterations: 163\n", - " Function evaluations: 273\n", - "P = [6.04472776 1.21593462 0.04573228 5.76214269 1.26811808 0.07772936\n", - " 5.66035891 1.33993058 0.11571956 5.58508993 1.41578131 0.15801892\n", - " 5.62827987 1.46997567 0.19975672 5.64230798 1.48655304 0.25494684]\n", - "P_ = [6.04472776 1.21593462 0.04573228 5.80924021 1.25942084 0.07239652\n", - " 5.69428684 1.31599308 0.10305616 5.62272442 1.37785595 0.13686924\n", - " 5.59948658 1.4338461 0.17193152 5.63061789 1.47273856 0.20895508\n", - " 5.64230798 1.48655304 0.25494684]\n", - "Depth = 7, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.324217\n", - " Iterations: 178\n", - " Function evaluations: 293\n", - "P = [6.06851459 1.21042498 0.04584365 5.80393575 1.24447884 0.07293344\n", - " 5.68823833 1.31410577 0.10484372 5.61324679 1.37925533 0.13948473\n", - " 5.60360969 1.42992526 0.17203967 5.62022132 1.48278162 0.20910824\n", - " 5.51749312 1.51627353 0.25834735]\n", - "P_ = [6.06851459 1.21042498 0.04584365 5.84173273 1.239614 0.06906347\n", - " 5.72129474 1.29421236 0.0957265 5.64538602 1.35133409 0.12463858\n", - " 5.6091166 1.40097101 0.15343685 5.60835587 1.44502708 0.18263069\n", - " 5.60554586 1.48756618 0.2161424 5.51749312 1.51627353 0.25834735]\n", - "Depth = 8, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.294351\n", - " Iterations: 327\n", - " Function evaluations: 492\n", - "P = [6.09187033 1.22064682 0.04561432 5.8365256 1.24473741 0.07005804\n", - " 5.7258587 1.29755363 0.09634462 5.63715359 1.35492249 0.12405028\n", - " 5.59420013 1.39311944 0.15451217 5.60597275 1.44619168 0.18288017\n", - " 5.54427862 1.49966199 0.21616201 5.55842298 1.52208488 0.25851257]\n", - "P_ = [6.09187033 1.22064682 0.04561432 5.86844369 1.24172609 0.06700257\n", - " 5.75352543 1.28434957 0.08977298 5.67041801 1.33340917 0.11366066\n", - " 5.61567686 1.37402097 0.13928122 5.59861486 1.41302153 0.16515017\n", - " 5.59054922 1.45955925 0.19120063 5.54604667 1.50246485 0.22145583\n", - " 5.55842298 1.52208488 0.25851257]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.267907\n", - " Iterations: 314\n", - " Function evaluations: 488\n", - "P = [6.10313275 1.20275372 0.04474845 5.8641031 1.25196073 0.06752431\n", - " 5.75162608 1.29248239 0.09082257 5.67242315 1.34603172 0.11331954\n", - " 5.61468978 1.37333342 0.14052999 5.59357889 1.42221036 0.16642146\n", - " 5.56317946 1.46178392 0.19152628 5.57198509 1.51114779 0.22158898\n", - " 5.59428545 1.52729393 0.25769564]\n", - "P_ = [6.10313275 1.20275372 0.04474845 5.89066195 1.24649328 0.06499366\n", - " 5.77662097 1.28347758 0.08564518 5.69882413 1.32818195 0.10582055\n", - " 5.64034905 1.36119933 0.12843645 5.60530716 1.3950565 0.15203731\n", - " 5.58344575 1.43540155 0.17478973 5.56513627 1.47275367 0.19820688\n", - " 5.57446291 1.51294181 0.22560083 5.59428545 1.52729393 0.25769564]\n", - "Depth = 10, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.242700\n", - " Iterations: 374\n", - " Function evaluations: 559\n", - "P = [6.10934415 1.21185533 0.04400559 5.88575481 1.23623973 0.06586731\n", - " 5.77907816 1.28501369 0.08746672 5.69323239 1.33365476 0.10706644\n", - " 5.63936743 1.36054934 0.12975393 5.59950223 1.41104312 0.15106397\n", - " 5.5660718 1.44787656 0.17566732 5.57908878 1.48072062 0.19401019\n", - " 5.57213837 1.52901171 0.22367606 5.54513377 1.53564736 0.25891864]\n", - "P_ = [6.10934415 1.21185533 0.04400559 5.90811375 1.23380129 0.06368113\n", - " 5.80041349 1.2752589 0.08314684 5.71898612 1.31906244 0.10118652\n", - " 5.66091341 1.34979151 0.12067893 5.61943483 1.38579623 0.14040895\n", - " 5.58613006 1.4257765 0.16090531 5.56997689 1.45772978 0.18117018\n", - " 5.5776987 1.49037884 0.19994336 5.56943791 1.52967528 0.22720032\n", - " 5.54513377 1.53564736 0.25891864]\n", - "Depth = 11, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.233368\n", - " Iterations: 432\n", - " Function evaluations: 654\n", - "P = [6.12912994 1.20984854 0.0439298 5.90090835 1.24548511 0.06431335\n", - " 5.8033351 1.26940203 0.08405269 5.72082592 1.32047139 0.10209799\n", - " 5.65709429 1.34455677 0.12172565 5.62538115 1.384786 0.13892136\n", - " 5.5716135 1.43311168 0.16126073 5.56796299 1.45760792 0.18161226\n", - " 5.58602564 1.49983259 0.1998295 5.54720175 1.53225418 0.22887874\n", - " 5.56993847 1.53797469 0.25943912]\n", - "P_ = [6.12912994 1.20984854 0.0439298 5.92165577 1.24224542 0.0624603\n", - " 5.82107569 1.2650535 0.08046372 5.74332843 1.30654338 0.09717655\n", - " 5.68026943 1.33579845 0.11458832 5.63979621 1.36649999 0.13110513\n", - " 5.60094131 1.40675222 0.14907562 5.57028604 1.4420194 0.16866128\n", - " 5.57288917 1.46912374 0.1865806 5.57896675 1.50572742 0.20511118\n", - " 5.54926873 1.53277422 0.23165696 5.56993847 1.53797469 0.25943912]\n", - "Depth = 12, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.226216\n", - " Iterations: 268\n", - " Function evaluations: 468\n", - "P = [6.13394086 1.20762851 0.04388936 5.92699222 1.24662483 0.06253905\n", - " 5.81363311 1.27317724 0.08093733 5.74851301 1.30592925 0.09776531\n", - " 5.68482659 1.33050435 0.11554566 5.63718356 1.36610018 0.13185198\n", - " 5.60589315 1.4103486 0.14899161 5.56701478 1.43974343 0.16743434\n", - " 5.56947846 1.47378905 0.18597544 5.56718506 1.50758622 0.20588086\n", - " 5.55305227 1.53409086 0.23296387 5.57801883 1.54035107 0.26131426]\n", - "P_ = [6.13394086 1.20762851 0.04388936 5.94423794 1.24337514 0.06098491\n", - " 5.83252629 1.26875184 0.07787095 5.76479303 1.29774125 0.09355831\n", - " 5.7060554 1.32231265 0.10961887 5.65703482 1.35126859 0.12505768\n", - " 5.62153835 1.38822439 0.1404218 5.58969383 1.42259644 0.15667608\n", - " 5.56783601 1.45109197 0.17361471 5.56890511 1.48223834 0.19095179\n", - " 5.56482959 1.51200366 0.21039469 5.55513281 1.53461254 0.23532641\n", - " 5.57801883 1.54035107 0.26131426]\n", - "Depth = 13, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.216715\n", - " Iterations: 633\n", - " Function evaluations: 908\n", - "P = [6.13872294 1.20237995 0.04275203 5.94137932 1.25648339 0.06139151\n", - " 5.83805689 1.28352797 0.08035296 5.75959136 1.30216414 0.0960372\n", - " 5.70900854 1.3238655 0.11320838 5.66328713 1.34500505 0.12674053\n", - " 5.62205406 1.38787366 0.14292839 5.59136024 1.4157902 0.15436198\n", - " 5.5695286 1.45313587 0.16424376 5.55995889 1.48070449 0.1867988\n", - " 5.55100092 1.51646407 0.20623402 5.57280504 1.53653982 0.23980954\n", - " 5.58495089 1.54627512 0.26343184]\n", - "P_ = [6.13872294 1.20237995 0.04275203 5.9565596 1.25232159 0.0599577\n", - " 5.85395265 1.27936727 0.07743581 5.77769879 1.29786348 0.09241776\n", - " 5.72457249 1.31718816 0.10792494 5.68087229 1.33687445 0.12153586\n", - " 5.64108471 1.36808815 0.13545707 5.60788768 1.40075822 0.14820543\n", - " 5.58296346 1.43015392 0.15816267 5.56658407 1.46161852 0.17118378\n", - " 5.55789167 1.4889567 0.19128385 5.5543554 1.51955265 0.21139948\n", - " 5.57373933 1.53728869 0.24162664 5.58495089 1.54627512 0.26343184]\n", - "Depth = 14, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.210074\n", - " Iterations: 370\n", - " Function evaluations: 618\n", - "P = [6.14476956 1.20407082 0.04267768 5.95381285 1.25332606 0.06021958\n", - " 5.85443443 1.28118302 0.07812006 5.77639157 1.30136582 0.09316664\n", - " 5.71996029 1.31788307 0.10864466 5.68573458 1.33658397 0.12269863\n", - " 5.64329558 1.36984256 0.13647708 5.60403844 1.39664188 0.1486059\n", - " 5.58371768 1.42966777 0.15769192 5.56090836 1.46379997 0.17123147\n", - " 5.55306687 1.49014287 0.19164885 5.55495932 1.5189783 0.21121546\n", - " 5.57304775 1.53920926 0.24012243 5.58301226 1.55139086 0.26326207]\n", - "P_ = [6.14476956 1.20407082 0.04267768 5.96745262 1.24980782 0.05896658\n", - " 5.86863135 1.27720345 0.07556285 5.79311504 1.29704094 0.08994237\n", - " 5.73608351 1.31316386 0.10422237 5.69795804 1.32990508 0.11767935\n", - " 5.66148372 1.35558888 0.13057203 5.62366701 1.38324222 0.14254149\n", - " 5.59532954 1.41079583 0.1524999 5.5755715 1.44185784 0.16252747\n", - " 5.55866794 1.47132651 0.17706501 5.5534724 1.49632189 0.1958417\n", - " 5.55754338 1.52186844 0.21534503 5.5737595 1.54007938 0.24177526\n", - " 5.58301226 1.55139086 0.26326207]\n", - "Depth = 15, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.112221\n", - " Iterations: 3509\n", - " Function evaluations: 4239\n", - "P = [6.08831062 1.20245455 0.01968091 5.90230899 1.33602139 0.042206\n", - " 5.84535169 1.34758283 0.06632891 5.75560597 1.43564647 0.1113683\n", - " 5.68245149 1.37685458 0.1355067 5.78380734 1.44093341 0.1700957\n", - " 5.77396714 1.3347183 0.21258284 5.71047557 1.26907317 0.16483107\n", - " 5.67593014 1.267622 0.16255784 5.63282328 1.32977818 0.0699212\n", - " 5.59580755 1.4465188 0.20166226 5.6462473 1.53909102 0.19535259\n", - " 5.48992804 1.49839507 0.11803675 5.79994642 1.58829822 0.20525025\n", - " 5.50402695 1.55997504 0.24729103]\n", - "P_ = [6.08831062 1.20245455 0.01968091 5.9147091 1.32711693 0.04070433\n", - " 5.85294599 1.3460413 0.06311252 5.77355512 1.41803375 0.10236042\n", - " 5.70195935 1.39253242 0.12906979 5.75002205 1.4195738 0.15856604\n", - " 5.77790322 1.37720434 0.19558798 5.74010497 1.29970756 0.18711523\n", - " 5.69435437 1.26839596 0.16377023 5.6586874 1.29248447 0.12550319\n", - " 5.6204847 1.36869172 0.11383489 5.60925815 1.47120473 0.19997968\n", - " 5.61498345 1.53095183 0.17988942 5.53126382 1.51038215 0.12966522\n", - " 5.78021846 1.58641001 0.20805297 5.50402695 1.55997504 0.24729103]\n", - "Depth = 16, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 6.13130616e+00 1.09300733e+00 2.56266890e-03 5.91066537e+00\n", - " 1.31968623e+00 -2.10666248e-02 5.80767777e+00 1.35128206e+00\n", - " 3.78000655e-02 5.72883089e+00 1.31777152e+00 1.09131594e-01\n", - " 5.67554847e+00 1.40868275e+00 1.72374414e-01 5.48141834e+00\n", - " 1.43388316e+00 2.30305658e-01 5.78682279e+00 1.48334018e+00\n", - " 5.24313992e-01 5.77517031e+00 1.41452098e+00 2.96622462e-01\n", - " 5.67216952e+00 1.27609709e+00 7.73210987e-01 5.76157649e+00\n", - " 1.21114064e+00 2.27827882e-01 5.63794282e+00 1.22062213e+00\n", - " 1.53908710e-01 5.68375083e+00 1.52637657e+00 5.88915913e-02\n", - " 6.04180790e+00 1.46788517e+00 -1.10918192e-01 4.95788782e+00\n", - " 1.57685903e+00 9.19961233e-02 7.17760401e+00 1.48598630e+00\n", - " -3.06779253e-02 3.91889256e+00 1.62473073e+00 4.95281579e-01]\n", - "P_ = [ 6.13130616e+00 1.09300733e+00 2.56266890e-03 5.92445542e+00\n", - " 1.30551880e+00 -1.95897940e-02 5.82055122e+00 1.34733258e+00\n", - " 3.04417292e-02 5.74361468e+00 1.32405475e+00 9.57569321e-02\n", - " 5.68886908e+00 1.38595495e+00 1.56563709e-01 5.54208401e+00\n", - " 1.42600803e+00 2.12202144e-01 5.67229612e+00 1.46479380e+00\n", - " 4.14060866e-01 5.78026827e+00 1.44462938e+00 3.96237506e-01\n", - " 5.72366991e+00 1.34530903e+00 5.34916724e-01 5.71128507e+00\n", - " 1.24767864e+00 5.34605878e-01 5.71521387e+00 1.21469620e+00\n", - " 2.00108192e-01 5.65225782e+00 1.31617039e+00 1.24215861e-01\n", - " 5.77326510e+00 1.51175372e+00 1.64391454e-02 5.83857289e+00\n", - " 1.48831777e+00 -7.28717581e-02 5.23535234e+00 1.56549994e+00\n", - " 7.66618672e-02 6.97393454e+00 1.49465782e+00 2.19454374e-03\n", - " 3.91889256e+00 1.62473073e+00 4.95281579e-01]\n", - "Depth = 17, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 1.594733\n", - " Iterations: 8701\n", - " Function evaluations: 10072\n", - "P = [ 6.19140977e+00 1.47243647e+00 -1.72115726e-04 5.87968673e+00\n", - " 1.30055173e+00 -1.52397761e-02 5.69154356e+00 1.20625127e+00\n", - " 3.96269823e-02 5.60655632e+00 1.31904135e+00 -1.52593167e-01\n", - " 5.65556668e+00 1.39431061e+00 5.42828913e-01 5.85909612e+00\n", - " 1.41816935e+00 2.46246913e-01 5.66450678e+00 1.42473788e+00\n", - " 8.29841689e-01 5.55182002e+00 1.45128328e+00 9.69049826e-01\n", - " 5.53456436e+00 1.46026714e+00 7.06653896e-01 5.63397817e+00\n", - " 1.33089777e+00 6.01387342e-01 5.80027315e+00 1.30581655e+00\n", - " -2.01739279e-01 5.88279708e+00 1.28216135e+00 1.44300566e-01\n", - " 5.78138483e+00 1.31709203e+00 1.39058444e-02 5.86046635e+00\n", - " 1.38057549e+00 -8.34547964e-03 5.24443207e+00 1.63462989e+00\n", - " 1.14352585e-01 7.00572604e+00 1.41395968e+00 2.70312109e-03\n", - " 3.66974584e+00 1.59733329e+00 5.66936524e-01]\n", - "P_ = [ 6.19140977e+00 1.47243647e+00 -1.72115726e-04 5.89802338e+00\n", - " 1.31066260e+00 -1.43534431e-02 5.71367805e+00 1.21734544e+00\n", - " 3.31720696e-02 5.62155407e+00 1.29913722e+00 -1.18671964e-01\n", - " 5.64403483e+00 1.37660019e+00 3.79200188e-01 5.79923452e+00\n", - " 1.41115207e+00 3.33476913e-01 5.73318537e+00 1.42241958e+00\n", - " 6.23867062e-01 5.59822045e+00 1.44035282e+00 9.11728828e-01\n", - " 5.54268467e+00 1.45603944e+00 8.30134334e-01 5.58134733e+00\n", - " 1.39938744e+00 6.57116694e-01 5.70245257e+00 1.32057021e+00\n", - " 2.70688145e-01 5.82939924e+00 1.29746766e+00 -7.96075692e-02\n", - " 5.85296995e+00 1.29243508e+00 1.05949177e-01 5.79999225e+00\n", - " 1.33202931e+00 8.67023873e-03 5.75175442e+00 1.42540862e+00\n", - " 1.33071199e-02 5.45164313e+00 1.60866869e+00 1.01217354e-01\n", - " 6.80949191e+00 1.42474636e+00 3.58933212e-02 3.66974584e+00\n", - " 1.59733329e+00 5.66936524e-01]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.564146\n", - " Iterations: 4482\n", - " Function evaluations: 5287\n", - "P = [ 6.18225781e+00 1.35521058e+00 -2.05781645e-04 5.84895399e+00\n", - " 1.26436672e+00 -1.37557061e-02 5.71140760e+00 1.20604505e+00\n", - " 2.23800831e-02 5.62535176e+00 1.30944228e+00 -1.61768368e-01\n", - " 5.66033737e+00 1.36069757e+00 3.81097732e-01 5.94883648e+00\n", - " 1.45357685e+00 2.33095606e-01 5.79685602e+00 1.46677331e+00\n", - " 7.02610935e-01 5.70293617e+00 1.46945770e+00 1.19123716e+00\n", - " 5.55308460e+00 1.48129612e+00 7.29752301e-01 5.63335446e+00\n", - " 1.41326663e+00 5.72962462e-01 5.73812716e+00 1.34215553e+00\n", - " 3.35916514e-01 5.87098185e+00 1.30784830e+00 -6.75830055e-02\n", - " 5.87277062e+00 1.30071039e+00 1.25894157e-01 5.78177809e+00\n", - " 1.36901266e+00 7.27537335e-03 5.84578893e+00 1.42720219e+00\n", - " 1.36620007e-02 5.50679029e+00 1.61434223e+00 7.34356754e-02\n", - " 6.81061727e+00 1.44701538e+00 4.12704829e-02 3.69443795e+00\n", - " 1.61768163e+00 4.55751992e-01]\n", - "P_ = [ 6.18225781e+00 1.35521058e+00 -2.05781645e-04 5.86747087e+00\n", - " 1.26941360e+00 -1.30029325e-02 5.72669053e+00 1.21252524e+00\n", - " 1.83649954e-02 5.63969440e+00 1.29220941e+00 -1.31076960e-01\n", - " 5.65256279e+00 1.34930751e+00 2.60460821e-01 5.86869784e+00\n", - " 1.42777705e+00 2.74207308e-01 5.84751617e+00 1.46237449e+00\n", - " 5.46105825e-01 5.73946055e+00 1.46841377e+00 1.00121585e+00\n", - " 5.61968530e+00 1.47603460e+00 9.34856684e-01 5.59321953e+00\n", - " 1.44728137e+00 6.51357381e-01 5.67992010e+00 1.38166170e+00\n", - " 4.67608707e-01 5.78979287e+00 1.32881383e+00 1.79000034e-01\n", - " 5.87157810e+00 1.30546900e+00 -3.09061800e-03 5.84749492e+00\n", - " 1.31968324e+00 9.29444949e-02 5.79600273e+00 1.38194367e+00\n", - " 8.69462387e-03 5.78928916e+00 1.45839220e+00 2.36242798e-02\n", - " 5.65165996e+00 1.59575036e+00 6.98617651e-02 6.63749620e+00\n", - " 1.45649684e+00 6.42972334e-02 3.69443795e+00 1.61768163e+00\n", - " 4.55751992e-01]\n", - "Depth = 19, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.574084\n", - " Iterations: 2482\n", - " Function evaluations: 3012\n", - "P = [ 6.18474234e+00 1.32610339e+00 -1.98228632e-04 5.86301698e+00\n", - " 1.30772239e+00 -1.35118503e-02 5.72455433e+00 1.21015652e+00\n", - " 1.79380920e-02 5.64117219e+00 1.31926685e+00 -1.26055129e-01\n", - " 5.66854125e+00 1.36456195e+00 3.31591177e-01 5.87970534e+00\n", - " 1.43333443e+00 2.59671158e-01 5.89866469e+00 1.47981744e+00\n", - " 4.80483833e-01 5.76624215e+00 1.48541117e+00 9.33569781e-01\n", - " 5.62993212e+00 1.47036685e+00 8.55511930e-01 5.64016879e+00\n", - " 1.48236912e+00 5.85891398e-01 5.71792869e+00 1.37308230e+00\n", - " 4.63339256e-01 5.81634460e+00 1.34977402e+00 1.76404060e-01\n", - " 5.91331155e+00 1.31046479e+00 -3.13302119e-03 5.84242050e+00\n", - " 1.32693836e+00 9.21782981e-02 5.82509810e+00 1.40490087e+00\n", - " 8.31134352e-03 5.80469582e+00 1.47661594e+00 2.58362869e-02\n", - " 5.73568139e+00 1.58890316e+00 7.12676748e-02 6.83211735e+00\n", - " 1.47132121e+00 6.64370328e-02 3.55499516e+00 1.61391884e+00\n", - " 4.46706387e-01]\n", - "P_ = [ 6.18474234e+00 1.32610339e+00 -1.98228632e-04 5.87994989e+00\n", - " 1.30868981e+00 -1.28111333e-02 5.73912935e+00 1.22042662e+00\n", - " 1.46275718e-02 5.65433779e+00 1.30203890e+00 -1.03319357e-01\n", - " 5.66277934e+00 1.35502614e+00 2.35244586e-01 5.82413584e+00\n", - " 1.41523641e+00 2.78597479e-01 5.89267753e+00 1.46513859e+00\n", - " 4.10753515e-01 5.81502940e+00 1.48335032e+00 7.66643379e-01\n", - " 5.68732581e+00 1.47670130e+00 8.88378394e-01 5.63531984e+00\n", - " 1.47668383e+00 7.13606387e-01 5.67700242e+00 1.43060168e+00\n", - " 5.27840383e-01 5.75936697e+00 1.36326829e+00 3.42524436e-01\n", - " 5.85206927e+00 1.33529167e+00 1.10258819e-01 5.89092490e+00\n", - " 1.31566697e+00 2.69652902e-02 5.83786198e+00 1.34745481e+00\n", - " 7.01080469e-02 5.82080288e+00 1.41999878e+00 1.20008053e-02\n", - " 5.79379880e+00 1.49434550e+00 3.30096640e-02 5.85109570e+00\n", - " 1.57652611e+00 7.07591861e-02 6.65963723e+00 1.47882635e+00\n", - " 8.64512094e-02 3.55499516e+00 1.61391884e+00 4.46706387e-01]\n", - "Depth = 20, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.594878\n", - " Iterations: 1753\n", - " Function evaluations: 2243\n", - "1.4285714285714286 [7.22579483 3.90524735 3.17262568 2.7492373 2.44817672 2.3561222\n", - " 2.32421652 2.29435143 2.26790717 2.24269994 2.23336799 2.2262163\n", - " 2.21671494 2.21007403 2.11222122 1.9213745 1.5947334 1.56414587\n", - " 1.57408394 1.59487843]\n", - "[[6.20528854 5.90276273 4.34974565 2.82648708 2.83216236 2.53390824\n", - " 2.48542936 2.39488186 1.78514917 1.78156864 1.63586622 1.93423131\n", - " 1.3466511 1.61587827 1.31723472 1.39380148 1.3212952 1.48519626\n", - " 1.19207192 1.19585198]\n", - " [7.30404471 4.53202785 3.46764965 2.88567087 2.50354724 2.12413704\n", - " 1.93259722 1.8208787 1.66881973 1.61137624 1.5777798 1.52441689\n", - " 1.50488971 1.32477289 1.14366376 1.10087346 1.06542039 1.04874467\n", - " 1.03100111 1.02313941]\n", - " [5.58705617 3.86360072 3.41898777 2.93676719 2.39036205 2.0121624\n", - " 1.79015272 1.5724717 1.47417254 1.46262495 1.42887826 1.36386696\n", - " 1.19370592 1.14920231 1.13162789 1.12219725 1.11458449 1.1084955\n", - " 1.09949537 1.09388173]\n", - " [5.77641939 4.14594873 3.04742423 2.27060879 2.06202637 1.94723727\n", - " 1.8320844 1.70380182 1.61599104 1.56657979 1.54148441 1.50955144\n", - " 1.49049303 1.42195588 1.33696517 1.23201985 1.17342154 1.15521269\n", - " 1.15315425 1.1445845 ]\n", - " [4.8756533 3.29005157 2.39464097 1.92219274 2.02050323 1.75058997\n", - " 1.59645135 1.53725395 1.49008503 1.42736801 1.38524369 1.31993946\n", - " 1.28152556 1.27874485 1.25760921 1.22073959 1.12592591 1.10046262\n", - " 1.0695972 1.03775195]\n", - " [3.90833019 2.49051953 1.79228238 1.56868139 1.50146331 1.37250533\n", - " 1.28508007 1.23713161 1.22722624 1.18749036 1.11754675 1.08767117\n", - " 1.06914641 1.06035356 1.04817772 1.03472643 1.02671312 1.0206102\n", - " 1.01753993 1.0162573 ]\n", - " [5.05805638 2.73367315 2.22083798 1.92446611 1.71372371 1.64928554\n", - " 1.62695157 1.606046 1.58753502 1.56988996 1.5633576 1.55835141\n", - " 1.55170046 1.54705182 1.47855486 1.34496215 1.11631338 1.09490211\n", - " 1.10185876 1.1164149 ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]] [3.87148487 2.69585843 2.06915686 1.63348742 1.50237883 1.33898258\n", - " 1.25487467 1.18724656 1.08489788 1.06068979 1.02501567 1.02980286\n", - " 0.94381122 0.93979596 0.87138333 0.84493202 0.7943674 0.80136241\n", - " 0.76647185 0.76278818]\n", - "[[0.17030757 0.16850299 0.24687602 0.45514832 0.45145637 0.56268179\n", - " 0.4723914 0.62266371 0.8026945 0.81119819 0.87005395 0.73125403\n", - " 0.9110609 0.83507433 0.90935654 0.90735586 0.92006095 0.88620215\n", - " 0.96581763 0.96554472]\n", - " [0.18431054 0.3834123 0.50873566 0.61052141 0.696016 0.79140483\n", - " 0.84466927 0.87844738 0.91858227 0.93545701 0.95087783 0.95794391\n", - " 0.96260089 0.96665922 0.98020554 0.98747975 0.99371878 0.99672513\n", - " 0.99769447 0.9985309 ]\n", - " [0.20432833 0.3184594 0.35443145 0.44587035 0.69188034 0.79613223\n", - " 0.85245109 0.94248088 0.96021228 0.960348 0.9695536 0.96022371\n", - " 0.98485672 0.99130491 0.99357222 0.99489111 0.99620155 0.99674134\n", - " 0.99723741 0.99702852]\n", - " [0.16226489 0.29705928 0.5086956 0.65943464 0.69698848 0.74147959\n", - " 0.75625945 0.9055608 0.93509535 0.96329039 0.97453832 0.97952655\n", - " 0.98353524 0.98310405 0.96598607 0.98112827 0.99426833 0.99638548\n", - " 0.99420366 0.9903845 ]\n", - " [0.12618061 0.21274452 0.44887434 0.55799579 0.47129411 0.67024636\n", - " 0.81569347 0.85178296 0.86009797 0.8940358 0.95873854 0.96613408\n", - " 0.97097553 0.95065719 0.97167497 0.98014358 0.98184616 0.97738053\n", - " 0.98501329 0.99168417]\n", - " [0.16591198 0.47710568 0.71119166 0.81217357 0.84357453 0.83394421\n", - " 0.8721109 0.91516457 0.91878387 0.95096964 0.96259298 0.97508223\n", - " 0.98345956 0.98682672 0.98877728 0.99066647 0.99277997 0.99525734\n", - " 0.99655034 0.99726773]\n", - " [0.22734335 0.60839544 0.7138562 0.8417705 0.91790046 0.94243412\n", - " 0.95221094 0.96613927 0.97815988 0.98960477 0.99420712 0.99604043\n", - " 0.99684518 0.99760603 0.99686578 0.95614355 0.99246989 0.99526167\n", - " 0.99274025 0.99074199]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]] [0.12406473 0.24656796 0.34926609 0.43829146 0.47691103 0.53383231\n", - " 0.55657865 0.60822396 0.63736261 0.65049038 0.66805623 0.65662049\n", - " 0.6793334 0.67112324 0.68064384 0.67978086 0.68713456 0.68439536\n", - " 0.6929257 0.69311825]\n", - "\n", - "Now using 4 solutions, set number 2\n", - "Calculating energy landscape ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 6.451504\n", - " Iterations: 101\n", - " Function evaluations: 181\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 6.451504\n", - " Iterations: 12\n", - " Function evaluations: 25\n", - "P = [ 0.31737312 0.3917661 -0.22473548]\n", - "P_ = [ 0.31737312 0.3917661 -0.22473548 0.31737312 0.3917661 -0.22473548]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.687726\n", - " Iterations: 59\n", - " Function evaluations: 99\n", - "P = [ 0.26103363 0.26265899 -0.25919057 0.49223753 0.22903985 -0.23204621]\n", - "P_ = [ 0.26103363 0.26265899 -0.25919057 0.37663558 0.24584942 -0.24561839\n", - " 0.49223753 0.22903985 -0.23204621]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.711834\n", - " Iterations: 197\n", - " Function evaluations: 280\n", - "P = [ 0.32763762 0.44317961 -0.2741866 0.53381769 0.05438249 -0.44364583\n", - " 0.53173043 0.21612798 -0.00658778]\n", - "P_ = [ 0.32763762 0.44317961 -0.2741866 0.465091 0.18398153 -0.38715942\n", - " 0.53312194 0.10829765 -0.29795981 0.53173043 0.21612798 -0.00658778]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.321943\n", - " Iterations: 170\n", - " Function evaluations: 247\n", - "P = [ 0.24174911 0.32579536 -0.28759297 0.5121532 0.23810427 -0.45670535\n", - " 0.54386146 0.10556477 -0.30108886 0.55952756 0.1372221 -0.00745342]\n", - "P_ = [ 0.24174911 0.32579536 -0.28759297 0.44455218 0.26002704 -0.41442725\n", - " 0.52800733 0.17183452 -0.3788971 0.54777798 0.1134791 -0.22768\n", - " 0.55952756 0.1372221 -0.00745342]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.014730\n", - " Iterations: 224\n", - " Function evaluations: 302\n", - "P = [ 0.18202223 0.38986113 -0.29011319 0.42009873 0.24567496 -0.51165175\n", - " 0.54550358 0.20197531 -0.37214621 0.56093677 0.09863566 -0.19432358\n", - " 0.57264603 0.11808009 -0.00826843]\n", - "P_ = [ 0.18202223 0.38986113 -0.29011319 0.37248343 0.27451219 -0.46734404\n", - " 0.49534164 0.21945517 -0.42794843 0.55167686 0.16063945 -0.30101716\n", - " 0.56327862 0.10252455 -0.15711255 0.57264603 0.11808009 -0.00826843]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.864456\n", - " Iterations: 310\n", - " Function evaluations: 425\n", - "P = [ 0.14970895 0.41912341 -0.32581183 0.37258225 0.33182172 -0.42949695\n", - " 0.52314224 0.2544152 -0.39173299 0.58062289 0.16126238 -0.30400188\n", - " 0.55052438 0.09593293 -0.15405171 0.72248517 0.09360193 -0.00588651]\n", - "P_ = [ 0.14970895 0.41912341 -0.32581183 0.3354367 0.34637201 -0.41221609\n", - " 0.47295558 0.28021737 -0.40432098 0.55188257 0.20783879 -0.34786743\n", - " 0.57059005 0.1394859 -0.25401849 0.57918451 0.09554443 -0.12935751\n", - " 0.72248517 0.09360193 -0.00588651]\n", - "Depth = 7, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 0.14141886 0.2735836 -0.54891144 0.2449557 0.46392523 -1.5680064\n", - " 0.26289767 0.35098551 -2.17949798 0.4323976 0.18194 -0.48709426\n", - " 0.55682493 0.21776778 -1.3055383 0.55306896 0.04676742 0.5643412\n", - " 0.62258034 0.10615645 0.02332893]\n", - "P_ = [ 0.14141886 0.2735836 -0.54891144 0.23016473 0.43673357 -1.4224214\n", - " 0.2577714 0.383254 -2.0047861 0.35975477 0.25438808 -1.21241014\n", - " 0.4857236 0.19729476 -0.83785599 0.5557518 0.16891053 -0.77128701\n", - " 0.56299916 0.05525157 0.48705373 0.62258034 0.10615645 0.02332893]\n", - "Depth = 8, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.203669\n", - " Iterations: 1900\n", - " Function evaluations: 2371\n", - "P = [ 0.09588699 0.29752324 -0.61588263 0.25501821 0.40324042 -1.40525608\n", - " 0.25101447 0.38656855 -2.97600006 0.3506814 0.25400134 -1.56493951\n", - " 0.50100582 0.19605634 -1.25729588 0.57793756 0.14441258 -0.71760797\n", - " 0.5423735 0.06837863 0.35352634 0.69755686 0.06699145 0.01077854]\n", - "P_ = [ 0.09588699 0.29752324 -0.61588263 0.23512681 0.39002577 -1.3065844\n", - " 0.2520154 0.39073652 -2.58331406 0.3133063 0.30371405 -2.09408721\n", - " 0.42584361 0.22502884 -1.41111769 0.52985522 0.17668993 -1.05491292\n", - " 0.56904654 0.12540409 -0.44982439 0.56177142 0.06820523 0.31068286\n", - " 0.69755686 0.06699145 0.01077854]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.172461\n", - " Iterations: 2285\n", - " Function evaluations: 2815\n", - "P = [ 0.08516754 0.38397483 -0.72421997 0.21305477 0.2818864 -0.97267644\n", - " 0.24484954 0.33527089 -2.2083933 0.27647688 0.30623326 -2.17016364\n", - " 0.38920262 0.24012013 -1.25657264 0.51876666 0.17744253 -1.09126327\n", - " 0.58576604 0.14353216 -0.3846528 0.55702424 0.06019318 0.34929543\n", - " 0.66857221 0.06970491 0.0150073 ]\n", - "P_ = [ 0.08516754 0.38397483 -0.72421997 0.19884507 0.29322956 -0.94507016\n", - " 0.23778403 0.32340767 -1.93378956 0.26593444 0.31591247 -2.18290686\n", - " 0.33910229 0.26950374 -1.66261308 0.44678664 0.21226342 -1.18310181\n", - " 0.54109979 0.16613907 -0.85572645 0.57937897 0.12501239 -0.22155319\n", - " 0.56941846 0.06125004 0.3121523 0.66857221 0.06970491 0.0150073 ]\n", - "Depth = 10, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.162127\n", - " Iterations: 1006\n", - " Function evaluations: 1263\n", - "P = [ 0.07518525 0.40797489 -0.71447512 0.17753165 0.31029016 -1.00052987\n", - " 0.23110459 0.30140922 -1.87607744 0.26787398 0.30537734 -2.09861993\n", - " 0.31802702 0.26893161 -1.75015631 0.45239486 0.22647261 -1.09330899\n", - " 0.56743167 0.18064807 -0.79764436 0.59217835 0.12170584 -0.24103334\n", - " 0.58968108 0.06463579 0.26966254 0.69880978 0.06195036 0.01834941]\n", - "P_ = [ 0.07518525 0.40797489 -0.71447512 0.16729701 0.32005863 -0.9719244\n", - " 0.22039 0.30318541 -1.70096793 0.25684316 0.3041869 -2.03185718\n", - " 0.29796581 0.2835099 -1.88954175 0.38521094 0.24770211 -1.42173265\n", - " 0.49840959 0.20814279 -0.97504314 0.57485567 0.1629654 -0.63066106\n", - " 0.5916789 0.11029183 -0.13889417 0.60059395 0.06436725 0.24453122\n", - " 0.69880978 0.06195036 0.01834941]\n", - "Depth = 11, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.151459\n", - " Iterations: 2611\n", - " Function evaluations: 3132\n", - "P = [ 0.05479618 0.41149544 -0.56813118 0.1687285 0.35697147 -0.97427525\n", - " 0.21656136 0.29047314 -1.65081549 0.27427668 0.27407928 -1.61280062\n", - " 0.33450452 0.30922941 -1.63463279 0.4005657 0.27844901 -1.56060714\n", - " 0.50856757 0.23090296 -0.58715278 0.58466737 0.16925248 -0.4610418\n", - " 0.60023908 0.13102317 -0.13748316 0.5965713 0.0633902 0.26617907\n", - " 0.68751363 0.06887863 0.01888345]\n", - "P_ = [ 0.05479618 0.41149544 -0.56813118 0.15837102 0.36192819 -0.93735306\n", - " 0.20786447 0.30256374 -1.52780818 0.25853614 0.27855033 -1.62316831\n", - " 0.31260349 0.29644754 -1.62669382 0.37053789 0.2924401 -1.59425516\n", - " 0.44965746 0.25683717 -1.11812789 0.53624023 0.2084846 -0.54129424\n", - " 0.5889142 0.1588263 -0.37279854 0.59957221 0.11872627 -0.06409003\n", - " 0.60483878 0.06388915 0.24369765 0.68751363 0.06887863 0.01888345]\n", - "Depth = 12, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.147294\n", - " Iterations: 1012\n", - " Function evaluations: 1287\n", - "P = [ 0.05841929 0.43270002 -0.57342612 0.13861125 0.37918634 -0.99034868\n", - " 0.20274308 0.31969524 -1.61817007 0.257992 0.27931412 -1.63235502\n", - " 0.31274364 0.27521277 -1.60578884 0.36998227 0.2816694 -1.45704667\n", - " 0.44534319 0.27160267 -1.15610178 0.53137165 0.20165842 -0.51821535\n", - " 0.59295804 0.16462553 -0.36793217 0.60758453 0.11541459 -0.0654931\n", - " 0.60193373 0.06160186 0.24045747 0.67461978 0.05761534 0.0194814 ]\n", - "P_ = [ 0.05841929 0.43270002 -0.57342612 0.13192859 0.38364581 -0.95560513\n", - " 0.19205444 0.32961042 -1.51353317 0.24417977 0.2894094 -1.62880878\n", - " 0.2944931 0.27657989 -1.61464424 0.34613284 0.27897914 -1.51902257\n", - " 0.40766273 0.27663604 -1.30657422 0.48118839 0.24245923 -0.89031577\n", - " 0.55190045 0.18931413 -0.46812096 0.59661467 0.1523228 -0.2923224\n", - " 0.60664273 0.1064458 -0.01450134 0.6079909 0.06126965 0.2220428\n", - " 0.67461978 0.05761534 0.0194814 ]\n", - "Depth = 13, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 1.142667\n", - " Iterations: 950\n", - " Function evaluations: 1205\n", - "P = [ 0.06032212 0.39610555 -0.54553297 0.13873957 0.3889279 -0.95478005\n", - " 0.18277864 0.32778035 -1.58176111 0.25253805 0.29681311 -1.66244138\n", - " 0.29393872 0.26559844 -1.58455497 0.35163271 0.26486394 -1.52363663\n", - " 0.40936072 0.27324986 -1.28858268 0.47642609 0.24526687 -0.9687769\n", - " 0.55468683 0.20169322 -0.46511286 0.60479568 0.15292603 -0.28141527\n", - " 0.60685074 0.11231372 -0.01547786 0.6078747 0.05947154 0.19416086\n", - " 0.69888473 0.05532586 0.01941206]\n", - "P_ = [ 0.06032212 0.39610555 -0.54553297 0.13270745 0.38948003 -0.9232995\n", - " 0.1760034 0.33718766 -1.48530248 0.23643973 0.3039594 -1.64382285\n", - " 0.28120005 0.27520295 -1.60852002 0.32944272 0.26514644 -1.54706677\n", - " 0.38271702 0.26937943 -1.39706912 0.44031397 0.26033463 -1.14098001\n", - " 0.50652637 0.22850777 -0.77505996 0.57010493 0.18668793 -0.40859052\n", - " 0.60526992 0.14355396 -0.2200451 0.60700827 0.10418415 0.01677425\n", - " 0.61487547 0.05915264 0.18071865 0.69888473 0.05532586 0.01941206]\n", - "Depth = 14, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.141047\n", - " Iterations: 857\n", - " Function evaluations: 1105\n", - "P = [ 0.054655 0.41093363 -0.53873613 0.13710357 0.37288934 -0.92176415\n", - " 0.17566797 0.33923898 -1.5323441 0.23633128 0.31117517 -1.65696963\n", - " 0.28841935 0.2737167 -1.60012782 0.33254642 0.26177285 -1.52639265\n", - " 0.39507491 0.25963646 -1.37789472 0.43810524 0.25041713 -1.15848176\n", - " 0.50280651 0.23695027 -0.80642087 0.56984824 0.186891 -0.40410315\n", - " 0.60625753 0.14838229 -0.22152309 0.6096294 0.10474623 0.01699949\n", - " 0.6241977 0.05942039 0.18428544 0.6829135 0.05179442 0.01975416]\n", - "P_ = [ 0.054655 0.41093363 -0.53873613 0.13121439 0.37560679 -0.894405\n", - " 0.17015877 0.34404617 -1.44511839 0.223332 0.31718884 -1.63026416\n", - " 0.27353704 0.28441912 -1.61636834 0.31678675 0.26603851 -1.55272664\n", - " 0.36827699 0.26055205 -1.44153669 0.41659007 0.25502679 -1.26818824\n", - " 0.46583435 0.24464562 -1.00759852 0.52674998 0.21907196 -0.66273597\n", - " 0.58025089 0.17588851 -0.35193742 0.60698007 0.13903171 -0.17041111\n", - " 0.61171059 0.09827111 0.04089748 0.62839168 0.05887568 0.17253321\n", - " 0.6829135 0.05179442 0.01975416]\n", - "Depth = 15, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.138944\n", - " Iterations: 689\n", - " Function evaluations: 929\n", - "P = [ 0.0538546 0.41514437 -0.53870402 0.12742414 0.37388029 -0.89410899\n", - " 0.17136914 0.33282226 -1.46848424 0.22703827 0.31944448 -1.63524153\n", - " 0.27086622 0.28577864 -1.59864052 0.31749205 0.26378817 -1.5741001\n", - " 0.37074895 0.26070686 -1.42908742 0.42272957 0.24600212 -1.31089574\n", - " 0.46520029 0.24460447 -1.06366776 0.52250034 0.22091004 -0.65614633\n", - " 0.58063095 0.18138584 -0.34825998 0.61318534 0.14265009 -0.16291858\n", - " 0.61420274 0.09945153 0.04077469 0.62623959 0.05956019 0.17419243\n", - " 0.70025789 0.04801651 0.0199281 ]\n", - "P_ = [ 0.0538546 0.41514437 -0.53870402 0.1225195 0.37663123 -0.87041533\n", - " 0.16550981 0.33829667 -1.39190088 0.21590444 0.32212004 -1.60189007\n", - " 0.25917877 0.2947562 -1.60840079 0.30195011 0.27111833 -1.58228024\n", - " 0.34944619 0.26193939 -1.48709249 0.39847195 0.25286433 -1.36605186\n", - " 0.44254924 0.24534989 -1.19552268 0.48812031 0.2351267 -0.90065919\n", - " 0.54187721 0.20773531 -0.55351755 0.58931212 0.17105631 -0.29883561\n", - " 0.61338882 0.13401038 -0.12217993 0.61580765 0.09413269 0.05856373\n", - " 0.63117414 0.05879062 0.16390814 0.70025789 0.04801651 0.0199281 ]\n", - "Depth = 16, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.138514\n", - " Iterations: 1022\n", - " Function evaluations: 1304\n", - "P = [ 0.05304928 0.40898658 -0.52951781 0.12112858 0.38296181 -0.8641156\n", - " 0.16169461 0.3352093 -1.43740654 0.22242737 0.3181542 -1.60641393\n", - " 0.26059505 0.29617145 -1.5993851 0.30042781 0.27551736 -1.61064597\n", - " 0.35443323 0.25961007 -1.48681272 0.39953427 0.25056856 -1.38497771\n", - " 0.45004901 0.24024841 -1.26861957 0.48690535 0.22987027 -0.90565724\n", - " 0.53901281 0.21370999 -0.56576781 0.58732174 0.17033122 -0.30244096\n", - " 0.61758597 0.13670835 -0.12505428 0.61625473 0.09699838 0.05838073\n", - " 0.6314551 0.05294745 0.1615338 0.68393899 0.04737241 0.02025891]\n", - "P_ = [ 0.05304928 0.40898658 -0.52951781 0.11687362 0.38458836 -0.84320324\n", - " 0.15662385 0.34117836 -1.36574518 0.21103997 0.32135203 -1.57472504\n", - " 0.25105313 0.30166714 -1.6011423 0.28798007 0.28197176 -1.60712695\n", - " 0.3341812 0.2655753 -1.53325019 0.37980256 0.25452422 -1.42953053\n", - " 0.42479164 0.24540849 -1.32679864 0.46617366 0.23570798 -1.10982355\n", - " 0.50644565 0.22381017 -0.7781987 0.55410935 0.20015412 -0.48347817\n", - " 0.59488779 0.1619255 -0.25809429 0.61733636 0.12926273 -0.09066021\n", - " 0.61815478 0.09149201 0.07127487 0.63473534 0.05259901 0.15270412\n", - " 0.68393899 0.04737241 0.02025891]\n", - "Depth = 17, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.136851\n", - " Iterations: 704\n", - " Function evaluations: 979\n", - "P = [ 0.05232243 0.40504871 -0.51801719 0.11814434 0.3814613 -0.85092415\n", - " 0.15278605 0.34334211 -1.39436395 0.21174234 0.32130828 -1.57323971\n", - " 0.25222682 0.29546125 -1.58443377 0.28501127 0.28413041 -1.61271433\n", - " 0.33378957 0.27082255 -1.51492002 0.38034377 0.25276116 -1.4649615\n", - " 0.42625009 0.24770463 -1.34221834 0.47218379 0.22892612 -1.10145866\n", - " 0.50406974 0.22406712 -0.80365096 0.55107118 0.2026017 -0.49906664\n", - " 0.59567633 0.16353531 -0.24880682 0.62050527 0.13154621 -0.09210292\n", - " 0.61916802 0.09149858 0.06686314 0.62829338 0.05309236 0.15059443\n", - " 0.70266259 0.04653484 0.0212771 ]\n", - "P_ = [ 0.05232243 0.40504871 -0.51801719 0.11427246 0.3828488 -0.83134139\n", - " 0.14871056 0.34782672 -1.33042986 0.20133829 0.32519661 -1.5416734\n", - " 0.24270106 0.30154291 -1.58179987 0.27536878 0.28746301 -1.60439652\n", - " 0.3165737 0.27551944 -1.54943566 0.36117439 0.2601982 -1.48553266\n", - " 0.40464712 0.25008417 -1.39997983 0.44786595 0.23886768 -1.22891966\n", - " 0.4853133 0.22692536 -0.97883196 0.52065848 0.21649109 -0.69615061\n", - " 0.56419034 0.19111159 -0.42546081 0.60151844 0.15600846 -0.21193532\n", - " 0.62026928 0.12447898 -0.06405009 0.62024159 0.0869802 0.07671388\n", - " 0.63266804 0.05270663 0.14298753 0.70266259 0.04653484 0.0212771 ]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.137065\n", - " Iterations: 1316\n", - " Function evaluations: 1678\n", - "P = [ 0.0504022 0.39635714 -0.47587007 0.11699637 0.38299721 -0.82088976\n", - " 0.14795966 0.35032149 -1.35819452 0.19940193 0.33037782 -1.54722502\n", - " 0.24499139 0.2988998 -1.56667401 0.27281165 0.28267267 -1.61331785\n", - " 0.31714659 0.28020805 -1.54672823 0.35971803 0.26513791 -1.4883548\n", - " 0.40519001 0.24972828 -1.46948981 0.45028362 0.23979786 -1.19398943\n", - " 0.48994817 0.22349861 -1.03126486 0.51757931 0.2122992 -0.73732743\n", - " 0.56447082 0.19599863 -0.42528626 0.60055738 0.15597625 -0.20995846\n", - " 0.6222295 0.12526155 -0.0647765 0.62166179 0.09112982 0.07701491\n", - " 0.63631875 0.05207217 0.13565578 0.69152529 0.04486149 0.02149533]\n", - "P_ = [ 0.0504022 0.39635714 -0.47587007 0.11329669 0.38373943 -0.801722\n", - " 0.1445193 0.35395212 -1.29849399 0.19082822 0.33370176 -1.51571994\n", - " 0.2348604 0.30589491 -1.56235201 0.2650838 0.28718021 -1.60036123\n", - " 0.30236828 0.28102959 -1.56892477 0.34316247 0.27099852 -1.51105558\n", - " 0.38498024 0.256577 -1.47787425 0.42773682 0.24476307 -1.33173962\n", - " 0.46791231 0.23255375 -1.1216674 0.50069361 0.21914328 -0.91695586\n", - " 0.53320981 0.20686568 -0.63331371 0.57449487 0.18488131 -0.36547298\n", - " 0.60537341 0.14915076 -0.17769581 0.62213488 0.11957293 -0.0411446\n", - " 0.62329034 0.08679008 0.08353056 0.63938578 0.05167158 0.12931353\n", - " 0.69152529 0.04486149 0.02149533]\n", - "Depth = 19, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.135915\n", - " Iterations: 779\n", - " Function evaluations: 1100\n", - "P = [ 0.04969993 0.39963404 -0.47387581 0.11305424 0.37943996 -0.79622505\n", - " 0.14439652 0.34638909 -1.31735043 0.19256477 0.33569482 -1.52815039\n", - " 0.23359015 0.30979862 -1.56089086 0.26335361 0.28748041 -1.60798661\n", - " 0.30212385 0.28149476 -1.56387552 0.34251468 0.27310886 -1.51644135\n", - " 0.38435894 0.26004622 -1.47837742 0.42901614 0.2459886 -1.3237465\n", - " 0.46785511 0.23457941 -1.11678973 0.50469582 0.21484449 -0.94520292\n", - " 0.53206962 0.20453036 -0.63146421 0.57107108 0.18693529 -0.35756678\n", - " 0.60658991 0.14868538 -0.17893013 0.62678912 0.1223586 -0.04237072\n", - " 0.62549983 0.08757299 0.08375986 0.63633205 0.05034281 0.12924014\n", - " 0.69403585 0.04401598 0.0216834 ]\n", - "P_ = [ 0.04969993 0.39963404 -0.47387581 0.1097198 0.3805028 -0.7792593\n", - " 0.14109733 0.34986813 -1.26249512 0.18495925 0.33738339 -1.49486619\n", - " 0.22495323 0.31525045 -1.55399813 0.25552112 0.29335362 -1.59559299\n", - " 0.28988062 0.28338497 -1.57780534 0.32763385 0.2761984 -1.53391709\n", - " 0.3667403 0.26554628 -1.49440434 0.40786273 0.25264748 -1.39699273\n", - " 0.44741355 0.24058425 -1.22571434 0.48336699 0.22626997 -1.04454265\n", - " 0.51478091 0.21104455 -0.82961497 0.54438587 0.19897402 -0.54497029\n", - " 0.58041814 0.17686952 -0.31055714 0.61084238 0.1431429 -0.15018078\n", - " 0.62658554 0.11686614 -0.02245537 0.62664006 0.08365402 0.08854726\n", - " 0.63936909 0.05000982 0.12357926 0.69403585 0.04401598 0.0216834 ]\n", - "Depth = 20, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 1.135676\n", - " Iterations: 978\n", - " Function evaluations: 1333\n", - "1.0666666666666667 [6.45150366 4.68772586 2.71183378 2.32194295 2.01472992 1.86445575\n", - " 1.42298426 1.20366917 1.17246137 1.16212741 1.15145871 1.1472943\n", - " 1.1426673 1.14104748 1.13894396 1.13851361 1.13685106 1.13706497\n", - " 1.13591528 1.13567623]\n", - "[[6.20528854 5.90276273 4.34974565 2.82648708 2.83216236 2.53390824\n", - " 2.48542936 2.39488186 1.78514917 1.78156864 1.63586622 1.93423131\n", - " 1.3466511 1.61587827 1.31723472 1.39380148 1.3212952 1.48519626\n", - " 1.19207192 1.19585198]\n", - " [7.30404471 4.53202785 3.46764965 2.88567087 2.50354724 2.12413704\n", - " 1.93259722 1.8208787 1.66881973 1.61137624 1.5777798 1.52441689\n", - " 1.50488971 1.32477289 1.14366376 1.10087346 1.06542039 1.04874467\n", - " 1.03100111 1.02313941]\n", - " [5.58705617 3.86360072 3.41898777 2.93676719 2.39036205 2.0121624\n", - " 1.79015272 1.5724717 1.47417254 1.46262495 1.42887826 1.36386696\n", - " 1.19370592 1.14920231 1.13162789 1.12219725 1.11458449 1.1084955\n", - " 1.09949537 1.09388173]\n", - " [5.77641939 4.14594873 3.04742423 2.27060879 2.06202637 1.94723727\n", - " 1.8320844 1.70380182 1.61599104 1.56657979 1.54148441 1.50955144\n", - " 1.49049303 1.42195588 1.33696517 1.23201985 1.17342154 1.15521269\n", - " 1.15315425 1.1445845 ]\n", - " [4.8756533 3.29005157 2.39464097 1.92219274 2.02050323 1.75058997\n", - " 1.59645135 1.53725395 1.49008503 1.42736801 1.38524369 1.31993946\n", - " 1.28152556 1.27874485 1.25760921 1.22073959 1.12592591 1.10046262\n", - " 1.0695972 1.03775195]\n", - " [3.90833019 2.49051953 1.79228238 1.56868139 1.50146331 1.37250533\n", - " 1.28508007 1.23713161 1.22722624 1.18749036 1.11754675 1.08767117\n", - " 1.06914641 1.06035356 1.04817772 1.03472643 1.02671312 1.0206102\n", - " 1.01753993 1.0162573 ]\n", - " [5.05805638 2.73367315 2.22083798 1.92446611 1.71372371 1.64928554\n", - " 1.62695157 1.606046 1.58753502 1.56988996 1.5633576 1.55835141\n", - " 1.55170046 1.54705182 1.47855486 1.34496215 1.11631338 1.09490211\n", - " 1.10185876 1.1164149 ]\n", - " [6.04828468 4.394743 2.54234416 2.17682152 1.8888093 1.74792727\n", - " 1.33404774 1.12843984 1.09918254 1.08949445 1.07949255 1.07558841\n", - " 1.07125059 1.06973202 1.06775996 1.06735651 1.06579787 1.06599841\n", - " 1.06492058 1.06469647]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]] [4.47631334 3.13533273 2.32339128 1.85116957 1.69125976 1.5137753\n", - " 1.38827944 1.30009055 1.19481613 1.16963924 1.13296493 1.13736171\n", - " 1.05093628 1.04676916 0.97815933 0.95166767 0.90094719 0.90796225\n", - " 0.87296391 0.86925782]\n", - "[[0.17030757 0.16850299 0.24687602 0.45514832 0.45145637 0.56268179\n", - " 0.4723914 0.62266371 0.8026945 0.81119819 0.87005395 0.73125403\n", - " 0.9110609 0.83507433 0.90935654 0.90735586 0.92006095 0.88620215\n", - " 0.96581763 0.96554472]\n", - " [0.18431054 0.3834123 0.50873566 0.61052141 0.696016 0.79140483\n", - " 0.84466927 0.87844738 0.91858227 0.93545701 0.95087783 0.95794391\n", - " 0.96260089 0.96665922 0.98020554 0.98747975 0.99371878 0.99672513\n", - " 0.99769447 0.9985309 ]\n", - " [0.20432833 0.3184594 0.35443145 0.44587035 0.69188034 0.79613223\n", - " 0.85245109 0.94248088 0.96021228 0.960348 0.9695536 0.96022371\n", - " 0.98485672 0.99130491 0.99357222 0.99489111 0.99620155 0.99674134\n", - " 0.99723741 0.99702852]\n", - " [0.16226489 0.29705928 0.5086956 0.65943464 0.69698848 0.74147959\n", - " 0.75625945 0.9055608 0.93509535 0.96329039 0.97453832 0.97952655\n", - " 0.98353524 0.98310405 0.96598607 0.98112827 0.99426833 0.99638548\n", - " 0.99420366 0.9903845 ]\n", - " [0.12618061 0.21274452 0.44887434 0.55799579 0.47129411 0.67024636\n", - " 0.81569347 0.85178296 0.86009797 0.8940358 0.95873854 0.96613408\n", - " 0.97097553 0.95065719 0.97167497 0.98014358 0.98184616 0.97738053\n", - " 0.98501329 0.99168417]\n", - " [0.16591198 0.47710568 0.71119166 0.81217357 0.84357453 0.83394421\n", - " 0.8721109 0.91516457 0.91878387 0.95096964 0.96259298 0.97508223\n", - " 0.98345956 0.98682672 0.98877728 0.99066647 0.99277997 0.99525734\n", - " 0.99655034 0.99726773]\n", - " [0.22734335 0.60839544 0.7138562 0.8417705 0.91790046 0.94243412\n", - " 0.95221094 0.96613927 0.97815988 0.98960477 0.99420712 0.99604043\n", - " 0.99684518 0.99760603 0.99686578 0.95614355 0.99246989 0.99526167\n", - " 0.99274025 0.99074199]\n", - " [0.20171815 0.41196483 0.83148116 0.90763496 0.95268836 0.97883882\n", - " 0.97019768 0.98987813 0.99334463 0.99508107 0.99722369 0.99778311\n", - " 0.99829285 0.99864429 0.99900392 0.99920338 0.99947974 0.99945438\n", - " 0.99960559 0.99965473]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]] [0.14423654 0.28776444 0.43241421 0.52905495 0.57217987 0.6317162\n", - " 0.65359842 0.70721177 0.73669708 0.74999849 0.7677786 0.75639881\n", - " 0.77916269 0.77098767 0.78054423 0.7797012 0.78708254 0.7843408\n", - " 0.79288626 0.79308373]\n", - "\n", - "Now using 4 solutions, set number 3\n", - "Calculating energy landscape ...\n", - "Optimization terminated successfully.\n", - " Current function value: 7.061941\n", - " Iterations: 105\n", - " Function evaluations: 181\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 7.061941\n", - " Iterations: 3\n", - " Function evaluations: 8\n", - "P = [ 0.36665897 0.39127126 -0.12749847]\n", - "P_ = [ 0.36665897 0.39127126 -0.12749847 0.36665897 0.39127126 -0.12749847]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.446637\n", - " Iterations: 97\n", - " Function evaluations: 157\n", - "P = [ 0.3910306 0.25736057 -0.14830691 0.67930353 0.30462576 -0.06057491]\n", - "P_ = [ 0.3910306 0.25736057 -0.14830691 0.53516707 0.28099316 -0.10444091\n", - " 0.67930353 0.30462576 -0.06057491]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.711375\n", - " Iterations: 98\n", - " Function evaluations: 148\n", - "P = [ 0.34158607 0.37248048 -0.17802627 0.6521917 0.18866494 -0.10277366\n", - " 0.65415265 0.23250513 -0.05185285]\n", - "P_ = [ 0.34158607 0.37248048 -0.17802627 0.54865649 0.24993679 -0.12785786\n", - " 0.65284535 0.20327834 -0.08580006 0.65415265 0.23250513 -0.05185285]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.475787\n", - " Iterations: 218\n", - " Function evaluations: 305\n", - "P = [ 0.28818497 0.37462111 -0.14941048 0.62961317 0.2896161 -0.1302463\n", - " 0.70214407 0.21860103 -0.07593941 0.70385553 0.14032254 -0.05285765]\n", - "P_ = [ 0.28818497 0.37462111 -0.14941048 0.54425612 0.31086735 -0.13503734\n", - " 0.66587862 0.25410857 -0.10309286 0.70257194 0.19903141 -0.07016897\n", - " 0.70385553 0.14032254 -0.05285765]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.471611\n", - " Iterations: 138\n", - " Function evaluations: 206\n", - "P = [ 0.1906002 0.40409658 -0.14541951 0.53379357 0.32685065 -0.12928928\n", - " 0.70200899 0.30189401 -0.1036675 0.73292064 0.18720318 -0.07498216\n", - " 0.76066087 0.13050545 -0.05245922]\n", - "P_ = [ 0.1906002 0.40409658 -0.14541951 0.4651549 0.34229984 -0.13251533\n", - " 0.63472282 0.31187667 -0.11391621 0.71437365 0.25601768 -0.09219336\n", - " 0.73846869 0.17586363 -0.07047758 0.76066087 0.13050545 -0.05245922]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.459703\n", - " Iterations: 132\n", - " Function evaluations: 191\n", - "P = [ 0.19439578 0.37449096 -0.13903532 0.44634323 0.37097348 -0.13433391\n", - " 0.62418955 0.3140826 -0.11920951 0.72426249 0.26467064 -0.0941766\n", - " 0.72126172 0.18268852 -0.0749046 0.75585905 0.11142673 -0.05414362]\n", - "P_ = [ 0.19439578 0.37449096 -0.13903532 0.40435198 0.37155973 -0.13511748\n", - " 0.56490744 0.33304623 -0.12425098 0.67422602 0.28937662 -0.10669305\n", - " 0.72326223 0.23734327 -0.0877526 0.72702794 0.17081156 -0.07144443\n", - " 0.75585905 0.11142673 -0.05414362]\n", - "Depth = 7, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.462205\n", - " Iterations: 152\n", - " Function evaluations: 226\n", - "P = [ 0.18559449 0.39617316 -0.1369624 0.4356239 0.35458799 -0.13697053\n", - " 0.54405624 0.33705636 -0.12634052 0.65805372 0.28890678 -0.10299706\n", - " 0.72061005 0.25269663 -0.08902165 0.73521613 0.17195892 -0.07284634\n", - " 0.76213598 0.108293 -0.05555203]\n", - "P_ = [ 0.18559449 0.39617316 -0.1369624 0.39990541 0.36052873 -0.13696936\n", - " 0.51307557 0.34206539 -0.12937767 0.60919766 0.30954231 -0.1130014\n", - " 0.68486357 0.27338814 -0.09700759 0.72478321 0.22962871 -0.08440013\n", - " 0.73906183 0.16286379 -0.07037572 0.76213598 0.108293 -0.05555203]\n", - "Depth = 8, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.444359\n", - " Iterations: 132\n", - " Function evaluations: 209\n", - "P = [ 0.18251059 0.39251803 -0.12987721 0.40610364 0.36581535 -0.13954004\n", - " 0.52776845 0.33599867 -0.13199664 0.59439525 0.3050962 -0.11598187\n", - " 0.67401643 0.28076722 -0.09933473 0.74307382 0.23831929 -0.08381209\n", - " 0.72846251 0.15802496 -0.07162979 0.75891169 0.10595273 -0.05617868]\n", - "P_ = [ 0.18251059 0.39251803 -0.12987721 0.37815451 0.36915318 -0.13833219\n", - " 0.49735224 0.34345284 -0.13388249 0.5694102 0.31668462 -0.12198741\n", - " 0.63420584 0.29293171 -0.1076583 0.69991295 0.26484924 -0.09351374\n", - " 0.73942099 0.21824571 -0.08076652 0.73226866 0.15151593 -0.0696984\n", - " 0.75891169 0.10595273 -0.05617868]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.431344\n", - " Iterations: 326\n", - " Function evaluations: 437\n", - "P = [ 0.14465672 0.40153427 -0.12310939 0.38601778 0.38617691 -0.13711952\n", - " 0.52235578 0.35493854 -0.14095635 0.58468531 0.3099169 -0.11817807\n", - " 0.61783729 0.29677441 -0.11313837 0.68969144 0.25633856 -0.09228204\n", - " 0.74186131 0.23600988 -0.08015004 0.74059246 0.15624535 -0.07050826\n", - " 0.74207687 0.10179847 -0.06184923]\n", - "P_ = [ 0.14465672 0.40153427 -0.12310939 0.35919988 0.38788328 -0.13556284\n", - " 0.49205845 0.3618804 -0.14010372 0.5639088 0.32492411 -0.12577083\n", - " 0.60310307 0.30261552 -0.11537824 0.64977247 0.27880292 -0.10386889\n", - " 0.7070814 0.24956234 -0.08823804 0.74157935 0.21828443 -0.07800742\n", - " 0.74075739 0.1501957 -0.06954615 0.74207687 0.10179847 -0.06184923]\n", - "Depth = 10, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.412933\n", - " Iterations: 236\n", - " Function evaluations: 330\n", - "P = [ 0.15331104 0.40016239 -0.12195102 0.35114561 0.39309844 -0.13771794\n", - " 0.4931735 0.36109687 -0.1525931 0.570869 0.32700437 -0.12285848\n", - " 0.60561016 0.29641853 -0.11596755 0.64208699 0.27794309 -0.10692954\n", - " 0.69940568 0.24397817 -0.09001623 0.74659478 0.22396587 -0.07619927\n", - " 0.73224163 0.1492242 -0.07087435 0.7764126 0.08640935 -0.0630028 ]\n", - "P_ = [ 0.15331104 0.40016239 -0.12195102 0.33136215 0.39380484 -0.13614124\n", - " 0.46476792 0.36749719 -0.14961807 0.54756035 0.33723212 -0.13177887\n", - " 0.5917137 0.30865287 -0.11872392 0.62384857 0.28718081 -0.11144855\n", - " 0.66501446 0.26435712 -0.10016422 0.71356241 0.23797448 -0.08587114\n", - " 0.74372415 0.20901754 -0.07513429 0.73665873 0.14294272 -0.0700872\n", - " 0.7764126 0.08640935 -0.0630028 ]\n", - "Depth = 11, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.409286\n", - " Iterations: 335\n", - " Function evaluations: 469\n", - "P = [ 0.15054304 0.40523093 -0.11899513 0.34666787 0.39750438 -0.13875283\n", - " 0.44704611 0.3826341 -0.15593948 0.5404096 0.34398851 -0.1294375\n", - " 0.60060898 0.3116733 -0.12123263 0.63138721 0.28005369 -0.11238468\n", - " 0.64750818 0.2638873 -0.10077311 0.71290399 0.22980731 -0.08550741\n", - " 0.74603916 0.21253395 -0.07609905 0.74661398 0.14330104 -0.07057167\n", - " 0.76737457 0.0785461 -0.0642421 ]\n", - "P_ = [ 0.15054304 0.40523093 -0.11899513 0.32883834 0.3982068 -0.13695668\n", - " 0.42879552 0.38533779 -0.15281463 0.51494683 0.35452822 -0.13666531\n", - " 0.5787183 0.32342429 -0.12421622 0.61739711 0.29442624 -0.11640648\n", - " 0.63871492 0.27270533 -0.10710669 0.67128847 0.25149457 -0.09522195\n", - " 0.72194085 0.22509639 -0.08294149 0.74614368 0.19994615 -0.07509407\n", - " 0.74850131 0.13741423 -0.06999625 0.76737457 0.0785461 -0.0642421 ]\n", - "Depth = 12, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.377259\n", - " Iterations: 692\n", - " Function evaluations: 891\n", - "P = [ 0.14807485 0.37458086 -0.11626142 0.33676435 0.33819731 -0.13003091\n", - " 0.44378324 0.32189581 -0.19346766 0.49941503 0.39848351 -0.14784242\n", - " 0.5971146 0.32276458 -0.11791235 0.64072646 0.30756761 -0.14095752\n", - " 0.62706152 0.28135788 -0.11108262 0.6624214 0.22279769 -0.08837635\n", - " 0.7201719 0.20356868 -0.09844288 0.7339901 0.20542673 -0.0740668\n", - " 0.72053923 0.12227614 -0.06853354 0.87599674 0.07166679 -0.06045737]\n", - "P_ = [ 0.14807485 0.37458086 -0.11626142 0.32104023 0.34122927 -0.12888346\n", - " 0.42594676 0.32461272 -0.18289487 0.48550708 0.37933658 -0.15924873\n", - " 0.56454808 0.34800422 -0.12788904 0.62255485 0.31389968 -0.13135537\n", - " 0.63389399 0.29446274 -0.12602007 0.64179481 0.2569578 -0.10162167\n", - " 0.68167157 0.21638802 -0.09173186 0.72362645 0.20403319 -0.09234886\n", - " 0.73174829 0.19156829 -0.07314459 0.73349402 0.1180587 -0.06786052\n", - " 0.87599674 0.07166679 -0.06045737]\n", - "Depth = 13, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.380297\n", - " Iterations: 406\n", - " Function evaluations: 556\n", - "P = [ 0.14166623 0.41587229 -0.11483159 0.3319283 0.33993534 -0.12937845\n", - " 0.42843336 0.33920641 -0.18557698 0.48780657 0.36992004 -0.15851267\n", - " 0.55732566 0.36205723 -0.12674139 0.62591569 0.32479513 -0.13083614\n", - " 0.63573868 0.29202287 -0.12961642 0.65479656 0.25271971 -0.10235356\n", - " 0.6645824 0.21840379 -0.0884236 0.70645242 0.20687882 -0.09216758\n", - " 0.73191889 0.18727429 -0.07288067 0.7531204 0.11887858 -0.07135057\n", - " 0.78356711 0.06996601 -0.06043235]\n", - "P_ = [ 0.14166623 0.41587229 -0.11483159 0.31729275 0.34577664 -0.12825946\n", - " 0.41358642 0.33931855 -0.17693105 0.47410506 0.36283228 -0.16475828\n", - " 0.53593517 0.36447656 -0.13651717 0.59953491 0.33912671 -0.12926124\n", - " 0.63120499 0.30714853 -0.13017937 0.64453462 0.27388295 -0.11703356\n", - " 0.65856034 0.23952128 -0.09699588 0.67746548 0.21485764 -0.08957559\n", - " 0.71232929 0.2023547 -0.08771675 0.73518066 0.17675187 -0.07264527\n", - " 0.75546245 0.11511607 -0.07051071 0.78356711 0.06996601 -0.06043235]\n", - "Depth = 14, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.379981\n", - " Iterations: 277\n", - " Function evaluations: 405\n", - "P = [ 0.14370695 0.40257072 -0.11439249 0.3125569 0.35324747 -0.12890765\n", - " 0.41395668 0.33789302 -0.18045776 0.48021494 0.35616438 -0.16366781\n", - " 0.54039631 0.3744527 -0.13729722 0.59301708 0.33580795 -0.13062421\n", - " 0.6241319 0.30895719 -0.12964424 0.65336615 0.27511444 -0.11766346\n", - " 0.65491975 0.23812859 -0.09734652 0.66362496 0.21745135 -0.08930122\n", - " 0.70713453 0.20070603 -0.08574968 0.75231924 0.17994744 -0.07330816\n", - " 0.74624027 0.11484402 -0.07126628 0.79628341 0.06949993 -0.06080272]\n", - "P_ = [ 0.14370695 0.40257072 -0.11439249 0.30049619 0.35677056 -0.12787085\n", - " 0.399471 0.34008651 -0.17309345 0.46601674 0.35224908 -0.16726566\n", - " 0.52320163 0.36922746 -0.14483168 0.57422395 0.34960965 -0.13300743\n", - " 0.61079698 0.32046466 -0.13006423 0.63874903 0.29203582 -0.12365385\n", - " 0.65403198 0.25926336 -0.1089562 0.65802876 0.23074386 -0.0944732\n", - " 0.67605627 0.21266697 -0.08828649 0.71681697 0.19625776 -0.08308364\n", - " 0.75145081 0.17064695 -0.07301646 0.74981478 0.11160516 -0.07051888\n", - " 0.79628341 0.06949993 -0.06080272]\n", - "Depth = 15, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.378586\n", - " Iterations: 294\n", - " Function evaluations: 429\n", - "P = [ 0.14163857 0.41343508 -0.11375079 0.30800345 0.35278921 -0.13357781\n", - " 0.38798869 0.34581804 -0.1770947 0.47487422 0.34909191 -0.16802641\n", - " 0.52406731 0.3727069 -0.14702683 0.57508252 0.34973333 -0.13443827\n", - " 0.6029525 0.3218306 -0.13009318 0.63979717 0.29377503 -0.12378076\n", - " 0.65809681 0.26018284 -0.10454234 0.65546958 0.23052174 -0.09426016\n", - " 0.66663018 0.21211526 -0.0878607 0.71927048 0.1976555 -0.08264806\n", - " 0.74918455 0.16991702 -0.07352121 0.74752146 0.11039733 -0.07122338\n", - " 0.78636428 0.06857776 -0.06124174]\n", - "P_ = [ 0.14163857 0.41343508 -0.11375079 0.29691246 0.35683226 -0.13225601\n", - " 0.37732399 0.34674753 -0.17129245 0.45749712 0.34843713 -0.16984007\n", - " 0.51094915 0.36640957 -0.15262672 0.55807745 0.35739119 -0.13863446\n", - " 0.59180451 0.33299169 -0.13183122 0.62260299 0.30686763 -0.12672656\n", - " 0.648337 0.27809867 -0.11480283 0.65704592 0.2483184 -0.10042947\n", - " 0.65918978 0.22438624 -0.09212701 0.68066759 0.20825932 -0.08647066\n", - " 0.72525329 0.1921078 -0.08082269 0.74896281 0.16198106 -0.07321484\n", - " 0.75011098 0.10760935 -0.07055794 0.78636428 0.06857776 -0.06124174]\n", - "Depth = 16, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.350999\n", - " Iterations: 928\n", - " Function evaluations: 1155\n", - "P = [ 0.14257586 0.36650947 -0.10326173 0.2982176 0.30755044 -0.1103425\n", - " 0.36774263 0.3453603 -0.18184979 0.44875801 0.35560058 -0.16857854\n", - " 0.532757 0.36570586 -0.18570373 0.55391226 0.36156854 -0.20240794\n", - " 0.57463217 0.35869422 -0.13339129 0.61254498 0.30447639 -0.1337445\n", - " 0.64354929 0.29065482 -0.10702713 0.6651811 0.26308964 -0.09706607\n", - " 0.66144104 0.20964688 -0.08910133 0.67596923 0.20083133 -0.09046651\n", - " 0.72620295 0.1894421 -0.09143695 0.74737398 0.16759222 -0.07218019\n", - " 0.7827553 0.09662268 -0.06843135 0.83198078 0.04320714 -0.06179649]\n", - "P_ = [ 0.14257586 0.36650947 -0.10326173 0.28848999 0.31123538 -0.10989995\n", - " 0.359052 0.34063407 -0.17291138 0.43356762 0.35368053 -0.1710669\n", - " 0.51175725 0.36317954 -0.18142244 0.54730124 0.36286145 -0.19718787\n", - " 0.56686221 0.35977209 -0.15927253 0.59595813 0.32819669 -0.13358997\n", - " 0.62804714 0.29756561 -0.12038582 0.65301321 0.27859506 -0.10266917\n", - " 0.66377858 0.2430486 -0.09407929 0.6659811 0.20689202 -0.08952795\n", - " 0.68852766 0.19798402 -0.09070912 0.73017252 0.18534525 -0.0878263\n", - " 0.75179665 0.15872103 -0.07171158 0.78583189 0.09328421 -0.06801667\n", - " 0.83198078 0.04320714 -0.06179649]\n", - "Depth = 17, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.348080\n", - " Iterations: 472\n", - " Function evaluations: 644\n", - "P = [ 0.13845564 0.37543668 -0.09402717 0.29474083 0.30378892 -0.11041245\n", - " 0.36034045 0.33053724 -0.17468879 0.4359395 0.35405145 -0.17298257\n", - " 0.50706994 0.36469663 -0.18271189 0.55281018 0.3536778 -0.19797705\n", - " 0.56901109 0.35775431 -0.16045521 0.588819 0.32760689 -0.13458857\n", - " 0.62245631 0.29824843 -0.12201115 0.65621939 0.27868533 -0.10330638\n", - " 0.67370461 0.24450108 -0.09493666 0.65717027 0.20867947 -0.09020617\n", - " 0.68066124 0.19717883 -0.09282304 0.73131268 0.1885092 -0.09031792\n", - " 0.7630268 0.15785533 -0.07265992 0.78277918 0.09334748 -0.06866036\n", - " 0.82839399 0.04306033 -0.06270119]\n", - "P_ = [ 0.13845564 0.37543668 -0.09402717 0.28554758 0.30800349 -0.10944861\n", - " 0.35262285 0.32739038 -0.16712687 0.42259849 0.34990188 -0.17328366\n", - " 0.49033337 0.36219188 -0.18042263 0.53935717 0.35691864 -0.1934873\n", - " 0.56329312 0.35631554 -0.17369821 0.5806628 0.34002053 -0.14523954\n", - " 0.60662698 0.31206418 -0.12792994 0.63834482 0.28904227 -0.1132089\n", - " 0.66341919 0.26460946 -0.09986002 0.66786896 0.23185816 -0.09326707\n", - " 0.66407938 0.20529693 -0.09097583 0.69257922 0.19513891 -0.0922336\n", - " 0.73690929 0.18309969 -0.0872018 0.76535061 0.15026617 -0.07218938\n", - " 0.7854624 0.09038941 -0.06830982 0.82839399 0.04306033 -0.06270119]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.073355\n", - " Iterations: 7552\n", - " Function evaluations: 8685\n", - "P = [ 0.08805289 0.10080748 -0.08908173 0.25879375 0.29928147 -0.02356131\n", - " 0.44211472 0.24211027 -1.09136173 0.48270293 0.28707037 -0.55712215\n", - " 0.49411525 0.21339079 -1.62436343 0.566521 0.30938451 -0.7471177\n", - " 0.48731531 0.22195384 -0.95403318 0.50937408 0.30420023 -0.28010945\n", - " 0.53871432 0.30321308 -0.10536951 0.56281667 0.32545295 0.01697261\n", - " 0.50724209 0.34319554 -0.15384258 0.61866263 0.37067267 0.08654324\n", - " 0.6922703 0.25904892 -0.11480043 0.6941132 0.2408248 -0.10570738\n", - " 0.63969846 0.14459562 0.01719394 0.79264242 0.04889469 -0.11298087\n", - " 0.88500137 0.04908203 -0.13982964 0.84692449 -0.00169993 -0.13859836]\n", - "P_ = [ 0.08805289 0.10080748 -0.08908173 0.24930815 0.28825514 -0.02720134\n", - " 0.42174573 0.24846262 -0.97271724 0.47593823 0.27957702 -0.64616208\n", - " 0.49157918 0.22976403 -1.3871987 0.54640829 0.28271959 -0.99079707\n", - " 0.51371721 0.2510974 -0.88506135 0.50079567 0.27221553 -0.5421909\n", - " 0.52567422 0.30365181 -0.1830317 0.5507655 0.31433302 -0.04419845\n", - " 0.53811686 0.33333855 -0.05894525 0.5505723 0.35388109 -0.06035921\n", - " 0.64319852 0.33346475 0.01942869 0.69278222 0.25398667 -0.11227458\n", - " 0.68202103 0.21944053 -0.07839598 0.66518912 0.12864546 -0.00450186\n", - " 0.80290453 0.0489155 -0.11596407 0.88288599 0.04626081 -0.13976124\n", - " 0.84692449 -0.00169993 -0.13859836]\n", - "Depth = 19, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.047202\n", - " Iterations: 2613\n", - " Function evaluations: 3050\n", - "P = [ 0.07837581 0.11654879 -0.08478989 0.23849962 0.28181263 -0.02606796\n", - " 0.44149534 0.2589633 -0.90194989 0.47153409 0.24688056 -0.75409259\n", - " 0.49525309 0.22443913 -1.3669202 0.54512185 0.27499274 -1.03919969\n", - " 0.52156192 0.25632638 -0.99293537 0.518222 0.25671625 -0.53743532\n", - " 0.55879409 0.3025481 -0.25674968 0.5742569 0.29944402 -0.04402241\n", - " 0.54754811 0.28921652 -0.03999928 0.563665 0.38526888 -0.04968078\n", - " 0.63457347 0.32209696 0.02143174 0.69367234 0.25288475 -0.10687942\n", - " 0.63723084 0.20537204 -0.08511668 0.72784284 0.11669857 -0.00500235\n", - " 0.78720848 0.0543562 -0.10638427 0.8663627 0.04017423 -0.1475615\n", - " 0.86827729 -0.00172359 -0.14134068]\n", - "P_ = [ 0.07837581 0.11654879 -0.08478989 0.23007205 0.27311453 -0.02915859\n", - " 0.42012737 0.26136849 -0.80975179 0.46679113 0.24878836 -0.77743848\n", - " 0.49025962 0.22916364 -1.23790386 0.53199849 0.26168916 -1.12544193\n", - " 0.5290019 0.26222102 -1.00754516 0.5194525 0.25657261 -0.70525113\n", - " 0.54171111 0.28325048 -0.37493311 0.56693241 0.30091438 -0.14478796\n", - " 0.56160537 0.29459941 -0.04211672 0.55433417 0.32965962 -0.0440757\n", - " 0.58978917 0.36199502 -0.02348143 0.65323627 0.30024047 -0.01908757\n", - " 0.67881931 0.2403814 -0.10115238 0.65630705 0.18670394 -0.06825051\n", - " 0.73721636 0.10685504 -0.02101002 0.79554051 0.05286336 -0.11071871\n", - " 0.86646347 0.03796908 -0.14723409 0.86827729 -0.00172359 -0.14134068]\n", - "Depth = 20, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.048957\n", - " Iterations: 1428\n", - " Function evaluations: 1764\n", - "2.0 [7.06194109 4.44663735 2.71137453 2.47578683 2.47161064 2.45970292\n", - " 2.46220453 2.44435861 2.43134423 2.41293288 2.40928577 2.37725864\n", - " 2.38029681 2.37998132 2.37858578 2.35099859 2.34808022 2.07335526\n", - " 2.04720175 2.04895682]\n", - "[[6.20528854 5.90276273 4.34974565 2.82648708 2.83216236 2.53390824\n", - " 2.48542936 2.39488186 1.78514917 1.78156864 1.63586622 1.93423131\n", - " 1.3466511 1.61587827 1.31723472 1.39380148 1.3212952 1.48519626\n", - " 1.19207192 1.19585198]\n", - " [7.30404471 4.53202785 3.46764965 2.88567087 2.50354724 2.12413704\n", - " 1.93259722 1.8208787 1.66881973 1.61137624 1.5777798 1.52441689\n", - " 1.50488971 1.32477289 1.14366376 1.10087346 1.06542039 1.04874467\n", - " 1.03100111 1.02313941]\n", - " [5.58705617 3.86360072 3.41898777 2.93676719 2.39036205 2.0121624\n", - " 1.79015272 1.5724717 1.47417254 1.46262495 1.42887826 1.36386696\n", - " 1.19370592 1.14920231 1.13162789 1.12219725 1.11458449 1.1084955\n", - " 1.09949537 1.09388173]\n", - " [5.77641939 4.14594873 3.04742423 2.27060879 2.06202637 1.94723727\n", - " 1.8320844 1.70380182 1.61599104 1.56657979 1.54148441 1.50955144\n", - " 1.49049303 1.42195588 1.33696517 1.23201985 1.17342154 1.15521269\n", - " 1.15315425 1.1445845 ]\n", - " [4.8756533 3.29005157 2.39464097 1.92219274 2.02050323 1.75058997\n", - " 1.59645135 1.53725395 1.49008503 1.42736801 1.38524369 1.31993946\n", - " 1.28152556 1.27874485 1.25760921 1.22073959 1.12592591 1.10046262\n", - " 1.0695972 1.03775195]\n", - " [3.90833019 2.49051953 1.79228238 1.56868139 1.50146331 1.37250533\n", - " 1.28508007 1.23713161 1.22722624 1.18749036 1.11754675 1.08767117\n", - " 1.06914641 1.06035356 1.04817772 1.03472643 1.02671312 1.0206102\n", - " 1.01753993 1.0162573 ]\n", - " [5.05805638 2.73367315 2.22083798 1.92446611 1.71372371 1.64928554\n", - " 1.62695157 1.606046 1.58753502 1.56988996 1.5633576 1.55835141\n", - " 1.55170046 1.54705182 1.47855486 1.34496215 1.11631338 1.09490211\n", - " 1.10185876 1.1164149 ]\n", - " [6.04828468 4.394743 2.54234416 2.17682152 1.8888093 1.74792727\n", - " 1.33404774 1.12843984 1.09918254 1.08949445 1.07949255 1.07558841\n", - " 1.07125059 1.06973202 1.06775996 1.06735651 1.06579787 1.06599841\n", - " 1.06492058 1.06469647]\n", - " [3.53097054 2.22331868 1.35568727 1.23789341 1.23580532 1.22985146\n", - " 1.23110227 1.22217931 1.21567212 1.20646644 1.20464288 1.18862932\n", - " 1.1901484 1.18999066 1.18929289 1.17549929 1.17404011 1.03667763\n", - " 1.02360088 1.02447841]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]] [4.82941039 3.35766459 2.45896 1.97495891 1.81484029 1.63676045\n", - " 1.51138967 1.42230848 1.31638334 1.29028588 1.25342922 1.25622464\n", - " 1.16995112 1.16576823 1.09708862 1.0692176 1.0183512 1.01163001\n", - " 0.975324 0.97170566]\n", - "[[0.17030757 0.16850299 0.24687602 0.45514832 0.45145637 0.56268179\n", - " 0.4723914 0.62266371 0.8026945 0.81119819 0.87005395 0.73125403\n", - " 0.9110609 0.83507433 0.90935654 0.90735586 0.92006095 0.88620215\n", - " 0.96581763 0.96554472]\n", - " [0.18431054 0.3834123 0.50873566 0.61052141 0.696016 0.79140483\n", - " 0.84466927 0.87844738 0.91858227 0.93545701 0.95087783 0.95794391\n", - " 0.96260089 0.96665922 0.98020554 0.98747975 0.99371878 0.99672513\n", - " 0.99769447 0.9985309 ]\n", - " [0.20432833 0.3184594 0.35443145 0.44587035 0.69188034 0.79613223\n", - " 0.85245109 0.94248088 0.96021228 0.960348 0.9695536 0.96022371\n", - " 0.98485672 0.99130491 0.99357222 0.99489111 0.99620155 0.99674134\n", - " 0.99723741 0.99702852]\n", - " [0.16226489 0.29705928 0.5086956 0.65943464 0.69698848 0.74147959\n", - " 0.75625945 0.9055608 0.93509535 0.96329039 0.97453832 0.97952655\n", - " 0.98353524 0.98310405 0.96598607 0.98112827 0.99426833 0.99638548\n", - " 0.99420366 0.9903845 ]\n", - " [0.12618061 0.21274452 0.44887434 0.55799579 0.47129411 0.67024636\n", - " 0.81569347 0.85178296 0.86009797 0.8940358 0.95873854 0.96613408\n", - " 0.97097553 0.95065719 0.97167497 0.98014358 0.98184616 0.97738053\n", - " 0.98501329 0.99168417]\n", - " [0.16591198 0.47710568 0.71119166 0.81217357 0.84357453 0.83394421\n", - " 0.8721109 0.91516457 0.91878387 0.95096964 0.96259298 0.97508223\n", - " 0.98345956 0.98682672 0.98877728 0.99066647 0.99277997 0.99525734\n", - " 0.99655034 0.99726773]\n", - " [0.22734335 0.60839544 0.7138562 0.8417705 0.91790046 0.94243412\n", - " 0.95221094 0.96613927 0.97815988 0.98960477 0.99420712 0.99604043\n", - " 0.99684518 0.99760603 0.99686578 0.95614355 0.99246989 0.99526167\n", - " 0.99274025 0.99074199]\n", - " [0.20171815 0.41196483 0.83148116 0.90763496 0.95268836 0.97883882\n", - " 0.97019768 0.98987813 0.99334463 0.99508107 0.99722369 0.99778311\n", - " 0.99829285 0.99864429 0.99900392 0.99920338 0.99947974 0.99945438\n", - " 0.99960559 0.99965473]\n", - " [0.27273331 0.67783024 0.94758816 0.98418751 0.98220597 0.98308976\n", - " 0.98294116 0.98399546 0.98812917 0.99150421 0.99259333 0.99753948\n", - " 0.99630335 0.99509594 0.99449959 0.99871455 0.99828233 0.99579829\n", - " 0.99865138 0.99786939]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. ]] [0.17150987 0.35554747 0.52717303 0.62747371 0.67040046 0.73002517\n", - " 0.75189254 0.80561132 0.83550999 0.84914891 0.86703794 0.85615275\n", - " 0.87879302 0.87049727 0.87999419 0.87957265 0.88691077 0.88392063\n", - " 0.8927514 0.89287067]\n", - "\n", - "Now using 4 solutions, set number 4\n", - "Calculating energy landscape ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 6.781526\n", - " Iterations: 103\n", - " Function evaluations: 180\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 6.781526\n", - " Iterations: 13\n", - " Function evaluations: 26\n", - "P = [ 0.33240471 0.39234587 -0.60216272]\n", - "P_ = [ 0.33240471 0.39234587 -0.60216272 0.33240471 0.39234587 -0.60216272]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.608862\n", - " Iterations: 268\n", - " Function evaluations: 396\n", - "P = [ 0.26534371 0.24040796 -0.09872448 0.48926034 0.24494531 -0.50119969]\n", - "P_ = [ 0.26534371 0.24040796 -0.09872448 0.37730202 0.24267664 -0.29996208\n", - " 0.48926034 0.24494531 -0.50119969]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.607445\n", - " Iterations: 206\n", - " Function evaluations: 309\n", - "P = [ 0.24343261 0.39655699 -0.11477548 0.46916478 0.16497325 -0.51224006\n", - " 0.51283783 0.16655293 -0.2376042 ]\n", - "P_ = [ 0.24343261 0.39655699 -0.11477548 0.39392072 0.24216783 -0.37975187\n", - " 0.48372246 0.16549981 -0.42069477 0.51283783 0.16655293 -0.2376042 ]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.017307\n", - " Iterations: 203\n", - " Function evaluations: 287\n", - "P = [ 0.20737724 0.27708209 -0.12368677 0.42099143 0.28654313 -0.46488851\n", - " 0.48324265 0.11467961 -0.56447167 0.51473312 0.12661036 -0.25525842]\n", - "P_ = [ 0.20737724 0.27708209 -0.12368677 0.36758788 0.28417787 -0.37958807\n", - " 0.45211704 0.20061137 -0.51468009 0.49111527 0.11766229 -0.48716835\n", - " 0.51473312 0.12661036 -0.25525842]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.627000\n", - " Iterations: 1206\n", - " Function evaluations: 1596\n", - "P = [ 0.20922832 0.42883644 -0.4825551 0.41285493 0.20267322 -0.47348811\n", - " 0.51109434 0.26586292 -0.92855357 0.51365867 0.05874629 -0.86317441\n", - " 0.64168628 0.11536454 0.48546332]\n", - "P_ = [ 0.20922832 0.42883644 -0.4825551 0.37212961 0.24790586 -0.47530151\n", - " 0.47179858 0.24058704 -0.74652738 0.51212007 0.18301626 -0.9024019\n", - " 0.53926419 0.07006994 -0.59344686 0.64168628 0.11536454 0.48546332]\n", - "Depth = 6, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 0.17730716 0.31595725 -1.06119704 0.36007231 0.34199148 -0.45180046\n", - " 0.40991222 0.26299477 -2.38436916 0.44271358 0.13272778 0.52241255\n", - " 0.50627347 0.16771016 -1.83227012 0.47093065 0.0840988 -2.00299173]\n", - "P_ = [ 0.17730716 0.31595725 -1.06119704 0.32961145 0.33765244 -0.55336656\n", - " 0.39329892 0.28932701 -1.74017959 0.4263129 0.19786128 -0.93097831\n", - " 0.46390021 0.14438857 -0.26248168 0.500383 0.15377493 -1.86072373\n", - " 0.47093065 0.0840988 -2.00299173]\n", - "Depth = 7, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 0.1842278 0.38836315 -0.75004293 0.36779873 0.35576123 -0.83147553\n", - " 0.43151129 0.36797707 -2.02642835 0.42221887 0.17811522 -1.13078654\n", - " 0.40421262 0.17036644 -1.15830407 0.51374733 0.15112018 -1.14308851\n", - " 0.62312204 0.101945 -2.16019523]\n", - "P_ = [ 0.1842278 0.38836315 -0.75004293 0.34157432 0.36041865 -0.8198423\n", - " 0.41330771 0.36448683 -1.68501326 0.42620134 0.25948458 -1.51463303\n", - " 0.41450191 0.17479431 -1.14257977 0.43550825 0.16486751 -1.15395677\n", - " 0.52937229 0.14409515 -1.28838947 0.62312204 0.101945 -2.16019523]\n", - "Depth = 8, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 0.17179561 0.36822584 -0.28791314 0.36405181 0.32252914 -0.45346069\n", - " 0.39725552 0.39049049 -1.2260236 0.41615024 0.29137549 -1.86434448\n", - " 0.3773546 0.22280218 -0.73118093 0.4022398 0.17252812 -2.06348316\n", - " 0.54742035 0.15909223 -0.15865587 0.5973754 0.13215436 -3.14455436]\n", - "P_ = [ 0.17179561 0.36822584 -0.28791314 0.34001978 0.32824123 -0.43276725\n", - " 0.38895459 0.37350015 -1.03288287 0.40906472 0.32854361 -1.62497415\n", - " 0.39675242 0.25708884 -1.29776271 0.38668655 0.20394941 -1.23079427\n", - " 0.43853493 0.16916915 -1.58727633 0.55366473 0.15572499 -0.53189318\n", - " 0.5973754 0.13215436 -3.14455436]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.575569\n", - " Iterations: 2485\n", - " Function evaluations: 3037\n", - "P = [ 0.18205696 0.37523682 -0.30101815 0.38063425 0.27985259 -0.47164556\n", - " 0.42780347 0.3002644 -0.41961691 0.43365377 0.34381952 -1.20322022\n", - " 0.43159964 0.28884611 -1.57123721 0.37422367 0.26518125 -1.26828879\n", - " 0.38149411 0.12226902 -1.92655971 0.55906668 0.19629406 -0.20626088\n", - " 0.60127585 0.16891453 -3.55532167]\n", - "P_ = [ 0.18205696 0.37523682 -0.30101815 0.35857011 0.29045084 -0.45268696\n", - " 0.41732142 0.29572845 -0.43117883 0.43170367 0.32930115 -0.94201912\n", - " 0.43251259 0.31327873 -1.4076741 0.40609921 0.27832839 -1.43659347\n", - " 0.37664715 0.21754384 -1.48771243 0.42095468 0.13871903 -1.54427108\n", - " 0.56375659 0.19325189 -0.57837874 0.60127585 0.16891453 -3.55532167]\n", - "Depth = 10, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 0.0578997 0.14008448 -0.87540343 0.3017999 0.4204401 -0.91245842\n", - " 0.35438362 0.2543934 -1.10118552 0.41442497 0.36636068 -2.44527694\n", - " 0.33445415 0.17394454 -2.07555838 0.25212516 0.27297234 -2.38056349\n", - " 0.24228442 0.21025533 -2.76957532 0.27082848 0.10742005 -2.3734533\n", - " 0.40506006 0.27285075 -0.33728674 0.53564536 0.25141209 -4.2331295 ]\n", - "P_ = [ 0.0578997 0.14008448 -0.87540343 0.27740988 0.39240454 -0.90875292\n", - " 0.34386688 0.28760274 -1.0634401 0.39641257 0.3327705 -2.04204951\n", - " 0.36644248 0.250911 -2.2234458 0.29328966 0.22345844 -2.22806094\n", - " 0.24818886 0.24788554 -2.53616822 0.25084764 0.17940475 -2.65073871\n", - " 0.2976748 0.14050619 -1.96621999 0.41811859 0.27070689 -0.72687102\n", - " 0.53564536 0.25141209 -4.2331295 ]\n", - "Depth = 11, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 0.04631931 0.06974513 -0.3839278 0.16633718 0.32976412 -1.55883597\n", - " 0.33663679 0.20725637 -1.48250701 0.34337441 0.33701028 -3.26481781\n", - " 0.42723653 0.27064059 -4.46720735 0.37413634 0.22350412 -3.22217831\n", - " 0.26523371 0.21870108 -3.12436717 0.30648012 0.28500629 -3.05606533\n", - " 0.18357933 0.10355111 -3.14223912 0.46196363 0.17060722 -0.23654481\n", - " 0.59131803 0.13390165 -3.46718331]\n", - "P_ = [ 0.04631931 0.06974513 -0.3839278 0.15542647 0.30612603 -1.45202614\n", - " 0.30567323 0.22953051 -1.49638501 0.34153688 0.30162285 -2.77873305\n", - " 0.39674121 0.29477502 -4.02997479 0.39827279 0.24492979 -3.7881006\n", - " 0.32463515 0.22132092 -3.1777187 0.28023241 0.24281207 -3.09953014\n", - " 0.27296172 0.23551852 -3.07956727 0.23419465 0.11574313 -2.61393106\n", - " 0.47372312 0.16727035 -0.53023922 0.59131803 0.13390165 -3.46718331]\n", - "Depth = 12, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.017322\n", - " Iterations: 5898\n", - " Function evaluations: 6970\n", - "P = [ 0.00947432 0.08678918 -0.45541992 0.13946054 0.38687086 -1.02359184\n", - " 0.33439255 0.24335659 -1.90502863 0.37932988 0.31174268 -2.92627999\n", - " 0.42770973 0.29508158 -4.38522192 0.35524027 0.2048257 -3.24439842\n", - " 0.3278279 0.28466351 -3.47974041 0.28003095 0.23464508 -4.08754704\n", - " 0.2206595 0.14280112 -2.80141052 0.26718329 0.09851218 -3.49063187\n", - " 0.47704646 0.07137495 -0.99806034 0.70971506 0.04023936 -4.41712431]\n", - "P_ = [ 0.00947432 0.08678918 -0.45541992 0.12862835 0.36186405 -0.97624418\n", - " 0.30190388 0.26727563 -1.7581225 0.36809555 0.29464615 -2.67096715\n", - " 0.41158311 0.30063528 -3.89890794 0.38543588 0.24243231 -3.71974154\n", - " 0.34153409 0.2447446 -3.36206941 0.30791251 0.26382249 -3.73299317\n", - " 0.26024047 0.20403043 -3.65883487 0.23229045 0.13172888 -2.97371586\n", - " 0.30216049 0.0939893 -3.07520328 0.49643551 0.06878032 -1.28298234\n", - " 0.70971506 0.04023936 -4.41712431]\n", - "Depth = 13, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 0.00842664 0.10466498 -0.42300068 0.1033075 0.42670829 -0.63613765\n", - " 0.26079328 0.36955121 -2.03498632 0.34253708 0.28590732 -2.99931913\n", - " 0.42533425 0.27306871 -3.51499429 0.38183495 0.24579585 -3.44055953\n", - " 0.38989377 0.30572955 -3.70810285 0.28554654 0.27723372 -4.03246059\n", - " 0.30085613 0.18921822 -3.84095322 0.15494856 0.10968866 -1.89648048\n", - " 0.33261571 0.12558964 -3.32285054 0.42649712 0.06692391 -1.98112661\n", - " 0.58003744 0.04850507 -2.91917009]\n", - "P_ = [ 0.00842664 0.10466498 -0.42300068 0.09600898 0.40193573 -0.6197425\n", - " 0.2365647 0.37834461 -1.81977883 0.32367313 0.30520976 -2.77678079\n", - " 0.3998582 0.27701905 -3.35632501 0.39856545 0.25628541 -3.46918829\n", - " 0.38617432 0.27806784 -3.58462132 0.34173351 0.29257763 -3.85780642\n", - " 0.29143484 0.2433816 -3.95880391 0.25596149 0.16474758 -3.24265392\n", - " 0.19594868 0.11335812 -2.2256428 0.34705901 0.11656414 -3.11643148\n", - " 0.43830791 0.06550708 -2.0532838 0.58003744 0.04850507 -2.91917009]\n", - "Depth = 14, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 1.003299\n", - " Iterations: 6328\n", - " Function evaluations: 7460\n", - "P = [ 0.00813477 0.11944068 -0.43926129 0.09277533 0.35734808 -0.36901783\n", - " 0.22299349 0.41041771 -1.80882363 0.31913375 0.3293801 -3.22569903\n", - " 0.39490146 0.25731453 -3.65940458 0.38263145 0.22257435 -3.20578081\n", - " 0.41460204 0.31306652 -3.88507608 0.33827254 0.31550811 -4.55411448\n", - " 0.32956206 0.26140973 -4.55438303 0.21174233 0.12343548 -3.37473807\n", - " 0.25688718 0.11852399 -2.69141462 0.32834413 0.0880752 -2.37281896\n", - " 0.37114732 0.07211994 -3.04205118 0.53246624 0.03744112 -3.76455093]\n", - "P_ = [ 0.00813477 0.11944068 -0.43926129 0.08672958 0.3403547 -0.37403522\n", - " 0.20439089 0.40283634 -1.60313709 0.29853227 0.3467453 -2.92208287\n", - " 0.37325355 0.2779047 -3.53548871 0.3870136 0.23498156 -3.3677893\n", - " 0.40090036 0.27428416 -3.59394954 0.37643729 0.31428731 -4.21959528\n", - " 0.33453948 0.29232309 -4.55422957 0.28748359 0.21213321 -4.13308126\n", - " 0.22464086 0.1220322 -3.1795028 0.27219938 0.11199925 -2.62314412\n", - " 0.33445887 0.08579588 -2.46842356 0.3826701 0.06964288 -3.0936583\n", - " 0.53246624 0.03744112 -3.76455093]\n", - "Depth = 15, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.001579\n", - " Iterations: 4152\n", - " Function evaluations: 4920\n", - "P = [ 0.0080522 0.12673346 -0.39168253 0.07843948 0.36868945 -0.3397419\n", - " 0.19345179 0.39004831 -1.56866573 0.30176568 0.36200994 -2.94071948\n", - " 0.36628043 0.27562615 -3.75748647 0.38476125 0.22698315 -3.35202128\n", - " 0.40105634 0.28229944 -3.6132197 0.37102556 0.31822777 -4.42523579\n", - " 0.33021123 0.28053398 -4.68390107 0.30270312 0.20228073 -4.40228202\n", - " 0.23799422 0.11250625 -3.32868108 0.29361952 0.10489933 -2.45670694\n", - " 0.35111435 0.09596484 -2.88820181 0.42798893 0.07144731 -3.44880036\n", - " 0.47219396 0.02801665 -4.11841116]\n", - "P_ = [ 0.0080522 0.12673346 -0.39168253 0.073747 0.35255905 -0.34320461\n", - " 0.17811682 0.38720046 -1.40480922 0.28010291 0.36761761 -2.66630873\n", - " 0.3490765 0.29866183 -3.53968194 0.37860098 0.24319749 -3.48717634\n", - " 0.3945383 0.26017293 -3.50874033 0.38503992 0.30146122 -4.04629495\n", - " 0.35197887 0.30063734 -4.54594625 0.31920798 0.24923268 -4.57125345\n", - " 0.28113348 0.1723559 -4.04441504 0.25282763 0.11047774 -3.09615464\n", - " 0.30511848 0.10311243 -2.54300591 0.36136429 0.09269584 -2.96294829\n", - " 0.43093593 0.06855193 -3.49344108 0.47219396 0.02801665 -4.11841116]\n", - "Depth = 16, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.001190\n", - " Iterations: 2900\n", - " Function evaluations: 3471\n", - "P = [ 0.00725777 0.14002943 -0.37131593 0.06584233 0.36602053 -0.35436833\n", - " 0.17043099 0.3869084 -1.34182629 0.25927869 0.37837399 -2.64960649\n", - " 0.34738232 0.30891972 -3.51882681 0.37220274 0.2435721 -3.51898404\n", - " 0.38997587 0.26682415 -3.53049363 0.38559237 0.30016908 -4.18629624\n", - " 0.35444069 0.2952181 -4.59041632 0.32834199 0.24040727 -4.68683806\n", - " 0.29641181 0.16833628 -4.27416621 0.25372456 0.10669041 -3.0536996\n", - " 0.3016963 0.1085924 -2.77127047 0.38749127 0.09931774 -3.14806885\n", - " 0.37637479 0.06390231 -3.57027485 0.44626645 0.02792139 -3.95653948]\n", - "P_ = [ 0.00725777 0.14002943 -0.37131593 0.0621808 0.35189609 -0.35542755\n", - " 0.15735741 0.38429742 -1.21839405 0.24261975 0.37997419 -2.4043977\n", - " 0.32535641 0.32628329 -3.30152173 0.36444636 0.26399323 -3.5189349\n", - " 0.38331095 0.25810463 -3.52617753 0.38751015 0.28558067 -3.8993826\n", - " 0.37001653 0.29769359 -4.38835628 0.34302251 0.27123836 -4.63260083\n", - " 0.31636817 0.21338065 -4.53208612 0.28307204 0.14907195 -3.89277039\n", - " 0.2657175 0.10716591 -2.98309231 0.31778285 0.1068534 -2.84192016\n", - " 0.38610171 0.09489081 -3.2008446 0.38074302 0.0616535 -3.59441639\n", - " 0.44626645 0.02792139 -3.95653948]\n", - "Depth = 17, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.001454\n", - " Iterations: 2481\n", - " Function evaluations: 3036\n", - "P = [ 0.00738598 0.14422313 -0.38941252 0.06147599 0.35347794 -0.3468392\n", - " 0.15192638 0.37830139 -1.207624 0.23336017 0.38675846 -2.43950434\n", - " 0.31567548 0.3326527 -3.31112735 0.35778254 0.26722041 -3.53866855\n", - " 0.38322595 0.25932684 -3.54799085 0.38308858 0.28758174 -4.01414807\n", - " 0.36943691 0.2954018 -4.47227038 0.35120114 0.26120132 -4.65224313\n", - " 0.32037773 0.20151536 -4.54862065 0.28038237 0.15283526 -4.00769792\n", - " 0.26704918 0.10554687 -3.12396249 0.32589139 0.11130014 -2.62835083\n", - " 0.37723764 0.09528564 -3.21709633 0.36492567 0.06081783 -3.27821095\n", - " 0.47753615 0.02798575 -3.9097687 ]\n", - "P_ = [ 0.00738598 0.14422313 -0.38941252 0.05829423 0.34116883 -0.34934352\n", - " 0.14128516 0.37538098 -1.1063552 0.2189895 0.38526604 -2.22211369\n", - " 0.29630717 0.34538347 -3.10603959 0.34539811 0.28646521 -3.47174467\n", - " 0.37424593 0.26211281 -3.54470063 0.38314515 0.27594737 -3.82220098\n", - " 0.37586123 0.29172177 -4.25668341 0.36085537 0.27930746 -4.55696344\n", - " 0.33850915 0.23662475 -4.60957505 0.30626172 0.18433415 -4.35770674\n", - " 0.27646084 0.13892691 -3.74777573 0.28089441 0.10690058 -3.00734798\n", - " 0.3349525 0.10847405 -2.73224709 0.37578917 0.0912306 -3.22428629\n", - " 0.37154981 0.05888653 -3.31536141 0.47753615 0.02798575 -3.9097687 ]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.000700\n", - " Iterations: 6126\n", - " Function evaluations: 7206\n", - "P = [ 0.00926414 0.16021059 -0.31211554 0.05526562 0.34574672 -0.30652282\n", - " 0.14152891 0.38403302 -1.32079078 0.20059561 0.37831809 -2.32500229\n", - " 0.29033796 0.35357246 -3.34928842 0.34304764 0.28825214 -3.65608613\n", - " 0.36657354 0.25589076 -3.42766775 0.38437191 0.28261566 -3.91030086\n", - " 0.36880548 0.28676687 -4.33398362 0.37111298 0.27046364 -4.52358998\n", - " 0.3212943 0.22193188 -4.63561508 0.29275693 0.17268346 -4.44279929\n", - " 0.29192621 0.1412357 -3.84859558 0.29467295 0.11110446 -3.20165411\n", - " 0.33149286 0.10989437 -2.68781938 0.35461542 0.0873313 -3.17010924\n", - " 0.43408803 0.05692584 -2.90503736 0.42633871 0.0252843 -3.61213288]\n", - "P_ = [ 0.00926414 0.16021059 -0.31211554 0.05270999 0.33543916 -0.30683352\n", - " 0.1319441 0.37977899 -1.20809434 0.19075116 0.37927058 -2.15763371\n", - " 0.27039522 0.35907149 -3.12166928 0.32840606 0.30639667 -3.57086455\n", - " 0.35873157 0.26667788 -3.50380721 0.37745032 0.27222264 -3.72261021\n", - " 0.3757239 0.28492189 -4.14568017 0.36995923 0.27861525 -4.4287868\n", - " 0.34897135 0.24889397 -4.57337892 0.31019644 0.20277972 -4.56063116\n", - " 0.29248003 0.16220088 -4.24473138 0.29268919 0.13286591 -3.66888961\n", - " 0.30285515 0.11083555 -3.08746861 0.33534662 0.10613386 -2.76820102\n", - " 0.36344571 0.08395291 -3.14065681 0.43365751 0.05516798 -2.94432045\n", - " 0.42633871 0.0252843 -3.61213288]\n", - "Depth = 19, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.000868\n", - " Iterations: 2151\n", - " Function evaluations: 2664\n", - "P = [ 0.0095159 0.1624712 -0.30953274 0.05154424 0.35476639 -0.30825128\n", - " 0.13064233 0.38022968 -1.19106843 0.18883141 0.37687706 -2.16606674\n", - " 0.26585569 0.36475602 -3.11902481 0.32271988 0.31108718 -3.63812535\n", - " 0.35499956 0.27204045 -3.55802656 0.38157194 0.27227156 -3.79576785\n", - " 0.37152342 0.28164204 -4.14105092 0.36909313 0.27735747 -4.42233695\n", - " 0.35081435 0.24188254 -4.57467681 0.30882378 0.19735618 -4.56238333\n", - " 0.29362137 0.16097011 -4.30628307 0.30031963 0.1317443 -3.65255623\n", - " 0.30490746 0.10991789 -2.98787022 0.33567282 0.10417546 -2.80989905\n", - " 0.37853266 0.08331457 -3.02588946 0.41890964 0.05507581 -2.96580601\n", - " 0.4481874 0.02449458 -3.76784391]\n", - "P_ = [ 0.0095159 0.1624712 -0.30953274 0.04933223 0.34464559 -0.30831872\n", - " 0.12231621 0.37754933 -1.09814031 0.17964366 0.37740642 -2.01211964\n", - " 0.24964006 0.36730782 -2.91840206 0.30775562 0.32521056 -3.50151995\n", - " 0.34480598 0.28437099 -3.58332091 0.37178211 0.27218642 -3.70817895\n", - " 0.37575437 0.27769658 -3.99566857 0.37024432 0.279387 -4.2890962\n", - " 0.36043476 0.26055356 -4.49449794 0.33313411 0.2231346 -4.56950061\n", - " 0.30322289 0.18395079 -4.4680306 0.29573661 0.15174091 -4.09984301\n", - " 0.30152695 0.12600051 -3.47763886 0.31138438 0.10870896 -2.9504026\n", - " 0.34244017 0.10088163 -2.8440028 0.38278287 0.08034207 -3.01956489\n", - " 0.42045057 0.05346627 -3.00801854 0.4481874 0.02449458 -3.76784391]\n", - "Depth = 20, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 1.000992\n", - " Iterations: 1502\n", - " Function evaluations: 1956\n", - "1.0 [6.78152592 4.60886198 3.60744455 3.01730702 2.62699999 2.18354325\n", - " 1.858517 1.66753139 1.57556942 1.34783355 1.07732346 1.01732235\n", - " 1.0127981 1.00329886 1.0015788 1.00119039 1.00145445 1.00070039\n", - " 1.00086837 1.00099187]\n", - "[[6.20528854 5.90276273 4.34974565 2.82648708 2.83216236 2.53390824\n", - " 2.48542936 2.39488186 1.78514917 1.78156864 1.63586622 1.93423131\n", - " 1.3466511 1.61587827 1.31723472 1.39380148 1.3212952 1.48519626\n", - " 1.19207192 1.19585198]\n", - " [7.30404471 4.53202785 3.46764965 2.88567087 2.50354724 2.12413704\n", - " 1.93259722 1.8208787 1.66881973 1.61137624 1.5777798 1.52441689\n", - " 1.50488971 1.32477289 1.14366376 1.10087346 1.06542039 1.04874467\n", - " 1.03100111 1.02313941]\n", - " [5.58705617 3.86360072 3.41898777 2.93676719 2.39036205 2.0121624\n", - " 1.79015272 1.5724717 1.47417254 1.46262495 1.42887826 1.36386696\n", - " 1.19370592 1.14920231 1.13162789 1.12219725 1.11458449 1.1084955\n", - " 1.09949537 1.09388173]\n", - " [5.77641939 4.14594873 3.04742423 2.27060879 2.06202637 1.94723727\n", - " 1.8320844 1.70380182 1.61599104 1.56657979 1.54148441 1.50955144\n", - " 1.49049303 1.42195588 1.33696517 1.23201985 1.17342154 1.15521269\n", - " 1.15315425 1.1445845 ]\n", - " [4.8756533 3.29005157 2.39464097 1.92219274 2.02050323 1.75058997\n", - " 1.59645135 1.53725395 1.49008503 1.42736801 1.38524369 1.31993946\n", - " 1.28152556 1.27874485 1.25760921 1.22073959 1.12592591 1.10046262\n", - " 1.0695972 1.03775195]\n", - " [3.90833019 2.49051953 1.79228238 1.56868139 1.50146331 1.37250533\n", - " 1.28508007 1.23713161 1.22722624 1.18749036 1.11754675 1.08767117\n", - " 1.06914641 1.06035356 1.04817772 1.03472643 1.02671312 1.0206102\n", - " 1.01753993 1.0162573 ]\n", - " [5.05805638 2.73367315 2.22083798 1.92446611 1.71372371 1.64928554\n", - " 1.62695157 1.606046 1.58753502 1.56988996 1.5633576 1.55835141\n", - " 1.55170046 1.54705182 1.47855486 1.34496215 1.11631338 1.09490211\n", - " 1.10185876 1.1164149 ]\n", - " [6.04828468 4.394743 2.54234416 2.17682152 1.8888093 1.74792727\n", - " 1.33404774 1.12843984 1.09918254 1.08949445 1.07949255 1.07558841\n", - " 1.07125059 1.06973202 1.06775996 1.06735651 1.06579787 1.06599841\n", - " 1.06492058 1.06469647]\n", - " [3.53097054 2.22331868 1.35568727 1.23789341 1.23580532 1.22985146\n", - " 1.23110227 1.22217931 1.21567212 1.20646644 1.20464288 1.18862932\n", - " 1.1901484 1.18999066 1.18929289 1.17549929 1.17404011 1.03667763\n", - " 1.02360088 1.02447841]\n", - " [6.78152592 4.60886198 3.60744455 3.01730702 2.62699999 2.18354325\n", - " 1.858517 1.66753139 1.57556942 1.34783355 1.07732346 1.01732235\n", - " 1.0127981 1.00329886 1.0015788 1.00119039 1.00145445 1.00070039\n", - " 1.00086837 1.00099187]] [5.50756298 3.81855079 2.81970446 2.27668961 2.07754029 1.85511478\n", - " 1.69724137 1.58906162 1.47394029 1.42506924 1.36116156 1.35795687\n", - " 1.27123093 1.26609811 1.1972465 1.16933664 1.11849665 1.11170005\n", - " 1.07541083 1.07180485]\n", - "[[0.17030757 0.16850299 0.24687602 0.45514832 0.45145637 0.56268179\n", - " 0.4723914 0.62266371 0.8026945 0.81119819 0.87005395 0.73125403\n", - " 0.9110609 0.83507433 0.90935654 0.90735586 0.92006095 0.88620215\n", - " 0.96581763 0.96554472]\n", - " [0.18431054 0.3834123 0.50873566 0.61052141 0.696016 0.79140483\n", - " 0.84466927 0.87844738 0.91858227 0.93545701 0.95087783 0.95794391\n", - " 0.96260089 0.96665922 0.98020554 0.98747975 0.99371878 0.99672513\n", - " 0.99769447 0.9985309 ]\n", - " [0.20432833 0.3184594 0.35443145 0.44587035 0.69188034 0.79613223\n", - " 0.85245109 0.94248088 0.96021228 0.960348 0.9695536 0.96022371\n", - " 0.98485672 0.99130491 0.99357222 0.99489111 0.99620155 0.99674134\n", - " 0.99723741 0.99702852]\n", - " [0.16226489 0.29705928 0.5086956 0.65943464 0.69698848 0.74147959\n", - " 0.75625945 0.9055608 0.93509535 0.96329039 0.97453832 0.97952655\n", - " 0.98353524 0.98310405 0.96598607 0.98112827 0.99426833 0.99638548\n", - " 0.99420366 0.9903845 ]\n", - " [0.12618061 0.21274452 0.44887434 0.55799579 0.47129411 0.67024636\n", - " 0.81569347 0.85178296 0.86009797 0.8940358 0.95873854 0.96613408\n", - " 0.97097553 0.95065719 0.97167497 0.98014358 0.98184616 0.97738053\n", - " 0.98501329 0.99168417]\n", - " [0.16591198 0.47710568 0.71119166 0.81217357 0.84357453 0.83394421\n", - " 0.8721109 0.91516457 0.91878387 0.95096964 0.96259298 0.97508223\n", - " 0.98345956 0.98682672 0.98877728 0.99066647 0.99277997 0.99525734\n", - " 0.99655034 0.99726773]\n", - " [0.22734335 0.60839544 0.7138562 0.8417705 0.91790046 0.94243412\n", - " 0.95221094 0.96613927 0.97815988 0.98960477 0.99420712 0.99604043\n", - " 0.99684518 0.99760603 0.99686578 0.95614355 0.99246989 0.99526167\n", - " 0.99274025 0.99074199]\n", - " [0.20171815 0.41196483 0.83148116 0.90763496 0.95268836 0.97883882\n", - " 0.97019768 0.98987813 0.99334463 0.99508107 0.99722369 0.99778311\n", - " 0.99829285 0.99864429 0.99900392 0.99920338 0.99947974 0.99945438\n", - " 0.99960559 0.99965473]\n", - " [0.27273331 0.67783024 0.94758816 0.98418751 0.98220597 0.98308976\n", - " 0.98294116 0.98399546 0.98812917 0.99150421 0.99259333 0.99753948\n", - " 0.99630335 0.99509594 0.99449959 0.99871455 0.99828233 0.99579829\n", - " 0.99865138 0.99786939]\n", - " [0.20992455 0.40344707 0.56854246 0.65866946 0.72710662 0.71050686\n", - " 0.78253162 0.8204782 0.84629338 0.93115307 0.98952245 0.9965675\n", - " 0.99788315 0.99958406 0.99972113 0.99980538 0.99983441 0.99991853\n", - " 0.99987969 0.99987333]] [0.19250233 0.39589217 0.58402727 0.69334065 0.74311112 0.80107586\n", - " 0.8301457 0.88765914 0.92013933 0.94226422 0.96599018 0.9558095\n", - " 0.97858134 0.97045567 0.9799663 0.97955319 0.98689421 0.98391248\n", - " 0.99273937 0.992858 ]\n" - ] - } - ], - "source": [ - "sol_arr = np.array([3,3,3,3,3,3,4,4,4,4])\n", - "num_arr = np.array([1,2,3,4,5,6,1,2,3,4])\n", - "\n", - "SP_avg, SP, C_avg, C, best_cost_overlap = averageQAOA(TailAssignmentInterlaced, options, simulation_args, num_routes, sol_arr, num_arr)" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "deeaff02", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[[0.12916193 0.1405906 0.20825739 0.3946113 0.33802979 0.35459621\n", - " 0.31621434 0.37980233 0.58538241 0.63536451 0.77815653 0.60759129\n", - " 0.72760674 0.63736704 0.82640758 0.72064467 0.76527415 0.78165875\n", - " 0.75232462 0.86160072]\n", - " [0.07339238 0.15544793 0.21481257 0.25442134 0.29076059 0.32998113\n", - " 0.34412803 0.35695075 0.36801542 0.38040556 0.38253663 0.38368893\n", - " 0.38517755 0.58597231 0.73470571 0.75354011 0.76371667 0.7812745\n", - " 0.84952851 0.87321511]\n", - " [0.06347722 0.10362987 0.12416638 0.16755845 0.24925607 0.31775773\n", - " 0.34156821 0.38418093 0.39254043 0.39441383 0.41040484 0.51042819\n", - " 0.61778584 0.64676662 0.66836731 0.68471078 0.7002794 0.71788741\n", - " 0.73247389 0.74812819]\n", - " [0.06714036 0.12041733 0.18018107 0.20956946 0.22311392 0.23533142\n", - " 0.26587805 0.28808192 0.30368657 0.30943559 0.31896882 0.33189597\n", - " 0.33983731 0.40695008 0.53995056 0.64957422 0.70449487 0.72366793\n", - " 0.73745082 0.75599367]\n", - " [0.10910998 0.19251708 0.35175904 0.54754993 0.32660484 0.45488914\n", - " 0.43285086 0.47029826 0.5476489 0.54131136 0.51622217 0.52629612\n", - " 0.5868988 0.62815578 0.64803626 0.68821062 0.87767876 0.92061854\n", - " 0.94663299 0.9737184 ]\n", - " [0.05089749 0.15217335 0.22047485 0.2354165 0.23986237 0.26335348\n", - " 0.31819856 0.33766338 0.33920048 0.36002508 0.52972824 0.54720631\n", - " 0.56663671 0.58068838 0.59472221 0.60420988 0.61429797 0.61993202\n", - " 0.62207972 0.62435015]\n", - " [0.0677032 0.1608066 0.18877981 0.22028839 0.23915787 0.24629382\n", - " 0.25007589 0.25519349 0.25921865 0.26198217 0.26466025 0.26761024\n", - " 0.27187485 0.27516276 0.34410547 0.52365115 0.80304006 0.81369584\n", - " 0.81174477 0.81617425]\n", - " [0.05694544 0.11686319 0.22164599 0.24134796 0.26198741 0.27757403\n", - " 0.40306418 0.42834795 0.43784858 0.4489348 0.46744814 0.47454883\n", - " 0.48088965 0.4860488 0.48889814 0.49064345 0.49113577 0.49098726\n", - " 0.49233241 0.49456254]\n", - " [0.07025609 0.17327541 0.24267992 0.25100506 0.25199102 0.25563613\n", - " 0.25809645 0.26041967 0.2630644 0.26607638 0.26846695 0.27636755\n", - " 0.27825889 0.28014004 0.28279283 0.29141732 0.29444545 0.43959611\n", - " 0.45280774 0.44888508]\n", - " [0.0923576 0.14185752 0.20528893 0.26158039 0.33277478 0.49727191\n", - " 0.60617526 0.67015182 0.73705519 0.89781435 0.97617708 0.99643614\n", - " 0.99702576 0.99943133 0.99968439 0.99979194 0.99982224 0.99991129\n", - " 0.99986741 0.99984037]]\n" - ] - } - ], - "source": [ - "print(best_cost_overlap)" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "id": "6727ad03", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[0.07804417 0.14575789 0.2158046 0.27833488 0.27535387 0.3232685\n", - " 0.35362498 0.38310905 0.4233661 0.44957636 0.49127696 0.49220696\n", - " 0.52519921 0.55266831 0.61276705 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\n", 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "print(np.sum(best_cost_overlap,axis=0)/10)\n", - "fig, ax = plt.subplots(figsize = (14,7))\n", - "fig.suptitle(f'Best cost overlap with interlaced on {num_routes} routes')\n", - "ax.plot(range(best_cost_overlap.shape[1]), np.sum(best_cost_overlap,axis=0)/10)\n", - "for i in range(10):\n", - " ax.scatter(range(best_cost_overlap.shape[1]), best_cost_overlap[i])\n", - "ax.hlines(1,1,max_depth,color = \"black\", ls = \"--\")\n", - "ax.grid(ls = \"--\")\n", - "ax.set_ylabel(r\"$|{\\langle x^* |\\gamma \\beta \\delta \\rangle}|^2$\", color = \"black\")\n", - "ax.set_xlabel(\"Depth, $d$\")\n", - "plt.savefig(f'./data/saved_histograms/Averages/Best cost overlap with interlaced on {num_routes} routes high sol.pdf')\n", - "plt.show()\n", - "plot_SP_C(SP_avg, C_avg, max_depth , title = f'Cost and success prob with interlaced on {num_routes} routes', savefig = f'./data/saved_histograms/Averages/Cost and success prob with interlaced high sol on {num_routes} routes maxdepth {max_depth}.pdf')" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "id": "fd3850ce", - "metadata": {}, - "outputs": [], - "source": [ - "np.save(f'./data/saved_probs_costs/Interlaced_average_cost_{num_routes}_routes_{max_depth}_depth_high_sol', C_avg)\n", - "np.save(f'./data/saved_probs_costs/Interlaced_average_success_prob_{num_routes}_routes_{max_depth}_depth_high_sol', SP_avg)\n", - "np.save(f'./data/saved_probs_costs/Interlaced_cost_{num_routes}_routes_{max_depth}_depth_high_sol', C)\n", - "np.save(f'./data/saved_probs_costs/Interlaced_success_prob_{num_routes}_routes_{max_depth}_depth_high_sol', SP)\n", - "np.save(f'./data/saved_probs_costs/Interlaced_best_cost_overlap_{num_routes}_routes_{max_depth}_depth_high_sol', best_cost_overlap)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d7d2631f", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/tailassignment_oop averages 7r high standard.ipynb b/tailassignment_oop averages 7r high standard.ipynb deleted file mode 100644 index 7364621..0000000 --- a/tailassignment_oop averages 7r high standard.ipynb +++ /dev/null @@ -1,6728 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "e429c1ea", - "metadata": {}, - "outputs": [], - "source": [ - "%load_ext autoreload\n", - "%autoreload 2" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "a25b06d2", - "metadata": {}, - "outputs": [], - "source": [ - "from qiskit import *\n", - "from qiskit.tools.monitor import job_monitor\n", - "\n", - "import numpy as np\n", - "from qaoa_OOP import *\n", - "from exactcover import *\n", - "from tailassignment_oop import * \n", - "from tailassignment_loader import * \n", - "from plots import *\n", - "\n", - "import os\n", - "\n", - "import sys\n", - "sys.path.append('../')\n", - "\n", - "from qiskit_utilities.utilities import *\n", - "\n", - "from qiskit.visualization import plot_histogram" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "d463d2d9", - "metadata": {}, - "outputs": [], - "source": [ - "from matplotlib import rc\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib as mpl\n", - "# from tqdm import tqdm\n", - "\n", - "fontsize = 24\n", - "newparams = {'axes.titlesize': fontsize,\n", - " 'axes.labelsize': fontsize,\n", - " 'ytick.labelsize': fontsize,\n", - " 'xtick.labelsize': fontsize, \n", - " 'legend.fontsize': fontsize,\n", - " 'figure.titlesize': fontsize,\n", - " 'legend.handlelength': 1.5, \n", - " 'lines.linewidth': 2,\n", - " 'lines.markersize': 7,\n", - " 'figure.figsize': (12, 7), \n", - " 'figure.dpi':200,\n", - " 'text.usetex' : False,\n", - " 'font.family' : \"sans-serif\"\n", - " }\n", - "\n", - "plt.rcParams.update(newparams)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "84bdda6a", - "metadata": {}, - "outputs": [], - "source": [ - "def averageQAOA(qaoa_type, options, simulation_args, num_route, num_sols, num_arr):\n", - " flights = 24\n", - " max_depth = simulation_args.get('max_depth',10)\n", - " SP_all = np.zeros((len(num_sols), max_depth))\n", - " C_all = np.zeros_like(SP_all)\n", - " SP_avg = np.zeros(max_depth)\n", - " C_avg = np.zeros_like(SP_avg)\n", - " per_cent_best_cost = np.zeros((len(num_sols), max_depth))\n", - " for i in range(len(num_sols)):\n", - " print()\n", - " print('Now using', num_sols[i], 'solutions, set number', num_arr[i])\n", - " FR,CR = load_giorgio(f'./data/tail_assignment/Our_routes/Giorgio_routes_cost/FRCR_{num_route}_{flights}_{num_sols[i]}_{num_arr[i]}.npy')\n", - " CR /= np.amax(CR)\n", - " mu = np.amax(CR)\n", - " options['FR'] = FR\n", - " options['CR'] = CR\n", - " options['mu'] = mu\n", - "\n", - " qaoa = qaoa_type(options)\n", - " Elandscape, gammabetas, E, best = qaoa.simulate(**simulation_args)\n", - " SP, C = qaoa.simulation_statistics(plot = False)\n", - " best_cost = np.max( qaoa.vector_cost(qaoa.state_strings) )\n", - " optimal_solution = qaoa.best_cost_string()\n", - " state_strings = qaoa.state_strings \n", - " for k in range(1,max_depth+1):\n", - " qaoa.depth = k\n", - " circuit = qaoa.createCircuit(qaoa.params['xL_d' +str(k)])\n", - " if qaoa.backend.configuration().local:\n", - " job = execute(circuit, backend = qaoa.backend, noise_model = qaoa.noise_model, shots = qaoa.shots)\n", - " else:\n", - " job = start_or_retrieve_job(name +\"_\"+str(g_it), qaoa.backend, circuit, options = {'shots' : qaoa.shots})\n", - " optimal_ind = np.where(state_strings==optimal_solution)\n", - " per_cent_best_cost[i, k-1] = (np.abs(job.result().get_statevector())**2)[optimal_ind]\n", - "\n", - "\n", - " SP_all[i] = SP\n", - " print(-best_cost, -C)\n", - " C_all[i] = C/best_cost\n", - " SP_avg += SP/len(num_sols)\n", - " C_avg += C/(len(num_sols)*best_cost)\n", - " print(C_all, C_avg)\n", - " print(SP_all, SP_avg)\n", - " return SP_avg, SP_all, C_avg, C_all, per_cent_best_cost\n" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "ba34f8b6", - "metadata": {}, - "outputs": [], - "source": [ - "num_routes = 7\n", - "\n", - "options={}\n", - "options['usebarrier'] = True\n", - "\n", - "\n", - "\n", - "beta_n = 60\n", - "gamma_n = 100\n", - "\n", - "beta_max = np.pi\n", - "gamma_max = 2 * np.pi\n", - "\n", - "optmethod = 'Nelder-Mead'\n", - "shots = 1024 # no need for more shots when using the statevector simulation\n", - "rerun = True\n", - "max_depth = 30" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "a4fcccfa", - "metadata": {}, - "outputs": [], - "source": [ - "Aer.backends()\n", - "backend = Aer.get_backend('statevector_simulator')" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "a60f7e98", - "metadata": {}, - "outputs": [], - "source": [ - "simulation_args = dict()\n", - "\n", - "simulation_args['backend'] = backend\n", - "simulation_args['optmethod'] = optmethod\n", - "simulation_args['max_depth'] = max_depth\n", - "simulation_args['repeats'] = 1\n", - "simulation_args['params_ll'] = np.array([0,0])\n", - "simulation_args['params_ul'] = np.array([gamma_max,beta_max])\n", - "simulation_args['params_n'] = np.array([gamma_n, beta_n])\n", - "simulation_args['shots'] = shots\n" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "c35f45c9", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'usebarrier': True}" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "options" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "28ce097d", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'backend': StatevectorSimulator('statevector_simulator'),\n", - " 'optmethod': 'Nelder-Mead',\n", - " 'max_depth': 30,\n", - " 'repeats': 1,\n", - " 'params_ll': array([0, 0]),\n", - " 'params_ul': array([6.28318531, 3.14159265]),\n", - " 'params_n': array([100, 60]),\n", - " 'shots': 1024}" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "simulation_args" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "a187660b", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Now using 3 solutions, set number 1\n", - "Calculating energy landscape ...\n", - "Optimization terminated successfully.\n", - " Current function value: 9.492244\n", - " Iterations: 25\n", - " Function evaluations: 49\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 9.492244\n", - " Iterations: 10\n", - " Function evaluations: 21\n", - "P = [3.06425867 0.85879717]\n", - "P_ = [3.06425867 0.85879717 3.06425867 0.85879717]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 8.591419\n", - " Iterations: 86\n", - " Function evaluations: 142\n", - "P = [3.2160068 1.28764719 3.11598436 0.54501049]\n", - "P_ = [3.2160068 1.28764719 3.16599558 0.91632884 3.11598436 0.54501049]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 6.515668\n", - " Iterations: 123\n", - " Function evaluations: 215\n", - "P = [3.19673597 1.03790096 3.08661874 0.9640635 3.01837595 0.52424973]\n", - "P_ = [3.19673597 1.03790096 3.12332448 0.98867599 3.06387114 0.81745891\n", - " 3.01837595 0.52424973]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 7.922434\n", - " Iterations: 78\n", - " Function evaluations: 135\n", - "P = [3.27284076 0.99052497 3.23247603 0.99403923 3.19853482 0.81664267\n", - " 3.07153197 0.53366627]\n", - "P_ = [3.27284076 0.99052497 3.24256721 0.99316067 3.21550543 0.90534095\n", - " 3.16678411 0.74589857 3.07153197 0.53366627]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 6.425289\n", - " Iterations: 360\n", - " Function evaluations: 528\n", - "P = [3.18807923 1.30430506 3.25867463 0.7905805 3.23867876 0.4273588\n", - " 3.29727434 0.69929161 3.17245077 0.81359087]\n", - "P_ = [3.18807923 1.30430506 3.24455555 0.89332541 3.2466771 0.57264748\n", - " 3.26211699 0.53613192 3.27230963 0.72215147 3.17245077 0.81359087]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.880136\n", - " Iterations: 459\n", - " Function evaluations: 657\n", - "P = [3.25263198 0.80579679 3.31841592 0.74536137 3.26600927 0.5607216\n", - " 3.27029348 0.43726145 3.35837694 1.02448873 3.14967733 1.01467097]\n", - "P_ = [3.25263198 0.80579679 3.30745193 0.75543394 3.28347815 0.62226819\n", - " 3.26815137 0.49899152 3.29965463 0.63300387 3.32359367 1.02285244\n", - " 3.14967733 1.01467097]\n", - "Depth = 7, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 6.442123\n", - " Iterations: 404\n", - " Function evaluations: 574\n", - "P = [3.22892589 0.83613915 3.22977853 0.85703441 3.28166311 0.72030355\n", - " 3.27300419 0.47949323 3.36557581 0.55678437 3.34590731 1.07393866\n", - " 3.21258925 0.71186606]\n", - "P_ = [3.22892589 0.83613915 3.22965673 0.85404937 3.26683895 0.75936951\n", - " 3.27671516 0.58269765 3.31267774 0.512618 3.35995624 0.70454274\n", - " 3.32686188 1.022214 3.21258925 0.71186606]\n", - "Depth = 8, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.437947\n", - " Iterations: 377\n", - " Function evaluations: 529\n", - "P = [3.29539604 0.89396508 3.28652832 0.86550484 3.26577069 0.77423072\n", - " 3.25945528 0.65394084 3.27241286 0.48203317 3.24564841 0.49630465\n", - " 3.30012444 1.11969593 3.15503151 0.83637339]\n", - "P_ = [3.29539604 0.89396508 3.28763678 0.86906237 3.2709601 0.79704925\n", - " 3.26182356 0.69904954 3.26593407 0.567987 3.26237619 0.48738498\n", - " 3.25926741 0.65215247 3.28198782 1.08428061 3.15503151 0.83637339]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.420211\n", - " Iterations: 516\n", - " Function evaluations: 711\n", - "P = [3.23971496 0.85945916 3.31679372 0.87229486 3.25528525 0.77543756\n", - " 3.25612821 0.50231703 3.21074039 0.58600302 3.22245814 0.60703829\n", - " 3.23891256 0.55360414 3.29514065 0.95117245 3.22365399 1.07201791]\n", - "P_ = [3.23971496 0.85945916 3.30822941 0.87086867 3.26895379 0.7969614\n", - " 3.25584722 0.5933572 3.23091275 0.54880924 3.21594828 0.59535203\n", - " 3.22794295 0.5892269 3.25140769 0.64195265 3.28719769 0.96459972\n", - " 3.22365399 1.07201791]\n", - "Depth = 10, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.349983\n", - " Iterations: 274\n", - " Function evaluations: 411\n", - "P = [3.21534499 0.83441862 3.30000982 0.86650684 3.22976575 0.75453046\n", - " 3.26609232 0.61976107 3.22066304 0.55732053 3.2253655 0.60264449\n", - " 3.21023108 0.60353057 3.25464337 0.69059697 3.31607688 0.92411058\n", - " 3.19986589 1.07893558]\n", - "P_ = [3.21534499 0.83441862 3.29154333 0.86329802 3.24381456 0.77692574\n", - " 3.25519435 0.66019188 3.23883475 0.58229674 3.22301427 0.57998251\n", - " 3.21931173 0.60299892 3.22355476 0.62965049 3.26693007 0.73729969\n", - " 3.30445578 0.93959308 3.19986589 1.07893558]\n", - "Depth = 11, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.675442\n", - " Iterations: 1888\n", - " Function evaluations: 2395\n", - "P = [3.24993135 0.82783128 3.31261453 0.8697421 3.24902097 0.68542217\n", - " 3.28833402 0.65399356 3.24846722 0.64635377 3.20070466 1.00835695\n", - " 3.20457954 0.78006536 3.24861612 0.75677724 3.18607564 0.19946347\n", - " 3.32878923 1.02545623 3.10852278 0.85440971]\n", - "P_ = [3.24993135 0.82783128 3.30691606 0.86593203 3.26058344 0.71893489\n", - " 3.27761228 0.662565 3.26296423 0.64913187 3.22241491 0.84381005\n", - " 3.20246597 0.90458805 3.22059284 0.77159695 3.23155963 0.60478257\n", - " 3.21202356 0.34964397 3.30876501 1.00990655 3.10852278 0.85440971]\n", - "Depth = 12, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.977074\n", - " Iterations: 1816\n", - " Function evaluations: 2275\n", - "P = [3.24450993 0.79256195 3.33868578 0.72212013 3.27984967 0.54683133\n", - " 3.33254199 0.58096932 3.30403114 0.65374221 3.14623111 1.03550449\n", - " 3.19786724 0.5982341 3.21436364 0.8866323 3.25006039 0.06539882\n", - " 3.2994934 0.22587424 3.3296763 0.79495203 3.16324123 0.91684269]\n", - "P_ = [3.24450993 0.79256195 3.33083779 0.72799028 3.28965569 0.57604613\n", - " 3.31936891 0.57243482 3.31353476 0.62948458 3.21198112 0.87643687\n", - " 3.17204918 0.81686929 3.20474074 0.71840002 3.22626255 0.6128878\n", - " 3.26241864 0.10551767 3.30452388 0.32072054 3.31580671 0.80510959\n", - " 3.16324123 0.91684269]\n", - "Depth = 13, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.378607\n", - " Iterations: 814\n", - " Function evaluations: 1073\n", - "P = [3.24920759 0.85352776 3.31848827 0.77367454 3.27095049 0.65793115\n", - " 3.30720441 0.60570283 3.30799419 0.4935709 3.21954385 0.79308193\n", - " 3.19647347 0.77019272 3.24410446 0.67427711 3.23084738 0.56209727\n", - " 3.28592515 0.11045804 3.2330733 0.344905 3.34044535 0.82450893\n", - " 3.17146988 0.96019288]\n", - "P_ = [3.24920759 0.85352776 3.31315899 0.7798171 3.278264 0.67573782\n", - " 3.29883812 0.61775552 3.30775118 0.52807303 3.25356321 0.67788538\n", - " 3.20712134 0.78075697 3.218457 0.72592397 3.23900558 0.63113101\n", - " 3.24779439 0.42313135 3.27372857 0.16456118 3.24959208 0.41869022\n", - " 3.32744724 0.83494616 3.17146988 0.96019288]\n", - "Depth = 14, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.826546\n", - " Iterations: 1603\n", - " Function evaluations: 2005\n", - "P = [3.25812942 0.6858814 3.27470778 0.87434899 3.23382832 0.87397463\n", - " 3.28254901 0.65916165 3.28966756 0.57386845 3.24557486 0.72884097\n", - " 3.22546354 0.8142508 3.25054944 0.73581088 3.21127752 0.50526834\n", - " 3.29907352 0.25253835 3.2258088 0.21134368 3.21299261 0.22774031\n", - " 3.37773164 0.76217095 3.15740215 1.00646895]\n", - "P_ = [3.25812942 0.6858814 3.27352361 0.86088702 3.23966824 0.87402811\n", - " 3.27210886 0.705193 3.28763369 0.59823794 3.26132225 0.67349364\n", - " 3.23408267 0.77764659 3.23800649 0.77503084 3.23371862 0.63700694\n", - " 3.24263324 0.41500763 3.27814075 0.24076844 3.22306248 0.21485724\n", - " 3.23652676 0.30408754 3.36199382 0.77962081 3.15740215 1.00646895]\n", - "Depth = 15, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.288875\n", - " Iterations: 412\n", - " Function evaluations: 581\n", - "P = [3.26077004 0.70704898 3.29603153 0.89083696 3.24187891 0.79841175\n", - " 3.26888095 0.68308236 3.29328154 0.61544195 3.30424898 0.68792866\n", - " 3.26323505 0.7801493 3.24738378 0.78777804 3.22529096 0.61563061\n", - " 3.23418235 0.41264763 3.26900732 0.24930463 3.20375957 0.21759161\n", - " 3.31027439 0.2985934 3.32696257 0.79643193 3.18035272 0.95948652]\n", - "P_ = [3.26077004 0.70704898 3.29368077 0.87858443 3.24909926 0.81073511\n", - " 3.26348054 0.70614823 3.28677471 0.63347939 3.30059316 0.66376643\n", - " 3.27964062 0.74326104 3.25478104 0.78421796 3.2370738 0.70744257\n", - " 3.22884752 0.53443742 3.24579068 0.35819996 3.25160792 0.24084782\n", - " 3.22506253 0.23379197 3.31249948 0.36497187 3.31718858 0.80730224\n", - " 3.18035272 0.95948652]\n", - "Depth = 16, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 4.930007\n", - " Iterations: 2218\n", - " Function evaluations: 2758\n", - "P = [3.27001925 0.71862724 3.33601498 1.02554782 3.27022476 0.76109618\n", - " 3.28439397 0.83422479 3.24802009 0.70479413 3.24786324 0.69074847\n", - " 3.28482815 0.89790234 3.23405586 0.58786182 3.22968963 0.63681006\n", - " 3.24239135 0.50739201 3.23422991 0.38296921 3.25848976 0.28556423\n", - " 3.2843526 0.1852213 3.18478072 0.28573455 3.32228407 0.81209163\n", - " 3.15023957 0.76554696]\n", - "P_ = [3.27001925 0.71862724 3.33189025 1.00636528 3.27844854 0.79415263\n", - " 3.28173725 0.82051318 3.25711356 0.73715179 3.24791225 0.69513774\n", - " 3.27096631 0.82021964 3.25626874 0.72350454 3.23187274 0.61233594\n", - " 3.23524663 0.58018966 3.23933081 0.46073346 3.24181111 0.35253015\n", - " 3.26495547 0.2604785 3.26568287 0.20406753 3.20196864 0.35152919\n", - " 3.31153129 0.80918259 3.15023957 0.76554696]\n", - "Depth = 17, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.143985\n", - " Iterations: 1423\n", - " Function evaluations: 1803\n", - "P = [3.24489611 0.87015429 3.29827833 1.13451215 3.23830503 0.82702659\n", - " 3.27345793 0.7985777 3.26577855 0.62799062 3.23724512 0.7371603\n", - " 3.26676473 0.87091602 3.25010699 0.67462866 3.22063307 0.63508491\n", - " 3.23127844 0.60354746 3.25341127 0.4972526 3.23148172 0.37678511\n", - " 3.28886817 0.26581127 3.26480667 0.22263117 3.21394617 0.1617687\n", - " 3.30022841 0.7280822 3.12636989 0.82028636]\n", - "P_ = [3.24489611 0.87015429 3.2951382 1.11896169 3.24536071 0.86320136\n", - " 3.26725448 0.80359809 3.26758546 0.66812875 3.2456373 0.70505157\n", - " 3.25634605 0.82370812 3.25696606 0.75545287 3.23450315 0.65369374\n", - " 3.22564266 0.62024376 3.24039196 0.55977899 3.24567143 0.45473466\n", - " 3.24836009 0.34414575 3.28320664 0.25565125 3.25583129 0.21189073\n", - " 3.22409702 0.22839381 3.29000144 0.73350597 3.12636989 0.82028636]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.154433\n", - " Iterations: 2149\n", - " Function evaluations: 2613\n", - "P = [3.22674601 0.85637936 3.27875453 1.31393482 3.24760291 0.77163534\n", - " 3.26165804 0.95767275 3.24991382 0.55494928 3.25938268 0.72157002\n", - " 3.25690332 0.81252388 3.27962871 0.65049825 3.22563734 0.55158106\n", - " 3.25026706 0.70319453 3.27371177 0.44435298 3.24963274 0.53181989\n", - " 3.29887091 0.27611795 3.24572549 0.22022535 3.28717504 0.24477937\n", - " 3.30811379 0.19249322 3.26939708 0.9374726 3.15693637 0.75607788]\n", - "P_ = [3.22674601 0.85637936 3.27586516 1.28851507 3.2510642 0.83189084\n", - " 3.25931552 0.92666651 3.25252365 0.64444339 3.25675244 0.67528649\n", - " 3.25772977 0.78220593 3.27079106 0.71350822 3.24963351 0.59554425\n", - " 3.2379522 0.62738779 3.26068693 0.58815384 3.2643477 0.47836789\n", - " 3.26604547 0.44658591 3.28410829 0.26059223 3.2549365 0.2256818\n", - " 3.29066483 0.23606501 3.30381193 0.27526871 3.26314926 0.92739512\n", - " 3.15693637 0.75607788]\n", - "Depth = 19, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.683046\n", - " Iterations: 2578\n", - " Function evaluations: 3137\n", - "P = [3.2301749 1.048724 3.2699288 1.42953637 3.22902962 0.82450731\n", - " 3.24821253 0.9264318 3.22851253 0.52066527 3.23867085 0.71135834\n", - " 3.23047112 0.85790544 3.25636421 0.58775045 3.1638215 0.52621985\n", - " 3.21952198 0.74620664 3.26767927 0.54635461 3.21398419 0.50682535\n", - " 3.29591183 0.3065432 3.26392266 0.30765623 3.26820556 0.21212779\n", - " 3.30219913 0.21566261 3.27293564 0.31264846 3.23554768 1.03293332\n", - " 3.1203457 0.63891494]\n", - "P_ = [3.2301749 1.048724 3.26783649 1.40949362 3.2333348 0.88819458\n", - " 3.24518365 0.91033846 3.2326599 0.6060898 3.23599761 0.66117595\n", - " 3.23306051 0.81162741 3.24682465 0.68728123 3.20278685 0.55212747\n", - " 3.19313754 0.64200237 3.24233333 0.65153989 3.24507082 0.52971071\n", - " 3.24416806 0.43303719 3.28580999 0.30689469 3.26504974 0.28251717\n", - " 3.2753621 0.21287197 3.29757858 0.23097616 3.26900007 0.38846792\n", - " 3.22948442 1.01219551 3.1203457 0.63891494]\n", - "Depth = 20, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.490669\n", - " Iterations: 2733\n", - " Function evaluations: 3287\n", - "P = [3.19058516 1.00639449 3.20891066 1.44209065 3.22506727 0.94462013\n", - " 3.2443062 0.97990386 3.20042463 0.58719795 3.2440531 0.68185176\n", - " 3.20581553 0.67878898 3.24791443 0.70370542 3.25391595 0.71784695\n", - " 3.19731071 0.69246431 3.23983745 0.56994113 3.21744669 0.65082568\n", - " 3.20564386 0.41518627 3.25656883 0.34411287 3.24685871 0.23408989\n", - " 3.2443433 0.27378404 3.21959706 0.21710509 3.35061107 0.26790038\n", - " 3.1723045 0.87846806 3.14366996 0.67694976]\n", - "P_ = [3.19058516 1.00639449 3.20799439 1.42030585 3.22345161 0.99436718\n", - " 3.24142036 0.9746113 3.20920095 0.66573913 3.23314598 0.65818831\n", - " 3.2172868 0.67970781 3.23317981 0.69498467 3.25151534 0.71219034\n", - " 3.22278307 0.7038865 3.21857408 0.63120272 3.22976161 0.60633918\n", - " 3.21272556 0.55656991 3.2234676 0.39031058 3.2536558 0.31110597\n", - " 3.24622986 0.24401343 3.23939405 0.26244825 3.23924916 0.22472439\n", - " 3.33278042 0.32895715 3.17087277 0.86839215 3.14366996 0.67694976]\n", - "Depth = 21, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.236594\n", - " Iterations: 1399\n", - " Function evaluations: 1760\n", - "P = [3.16682727 0.89842828 3.2244462 1.4231914 3.22471005 0.96315111\n", - " 3.24556634 1.07973694 3.21661032 0.68830464 3.24738684 0.64677088\n", - " 3.21949717 0.76009639 3.22702266 0.65830383 3.24283873 0.81075229\n", - " 3.19145937 0.71227355 3.23325408 0.57667925 3.19322185 0.68228903\n", - " 3.21559165 0.50175562 3.22890951 0.39474189 3.2219871 0.31168652\n", - " 3.22838858 0.25620253 3.25979161 0.25329269 3.25333432 0.23066961\n", - " 3.35425263 0.38593705 3.16028081 0.90221256 3.14770256 0.39924515]\n", - "P_ = [3.16682727 0.89842828 3.22170244 1.39820268 3.22468492 1.00696447\n", - " 3.24258687 1.06308182 3.22212575 0.76286318 3.2400591 0.65665987\n", - " 3.22746564 0.72771767 3.22451416 0.69223468 3.23681356 0.75267669\n", - " 3.2134791 0.75447872 3.21335184 0.64124796 3.21419111 0.62696962\n", - " 3.20280891 0.60491757 3.22066512 0.46098849 3.22660204 0.36705676\n", - " 3.22381609 0.29583395 3.23586549 0.25550971 3.25856165 0.24898353\n", - " 3.26775122 0.25285068 3.33577912 0.43510615 3.15968184 0.87826173\n", - " 3.14770256 0.39924515]\n", - "Depth = 22, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.651078\n", - " Iterations: 1532\n", - " Function evaluations: 1931\n", - "P = [3.15870416 0.91892239 3.20698141 1.52691031 3.22263058 0.91452165\n", - " 3.24907273 1.14830482 3.2038588 0.71630171 3.25384586 0.64791401\n", - " 3.2182115 0.72182305 3.23123624 0.68579303 3.21722694 0.69888224\n", - " 3.18980107 0.80739166 3.22359812 0.66056161 3.19249245 0.66289622\n", - " 3.20769956 0.62901626 3.20639237 0.4778469 3.2284388 0.35893342\n", - " 3.21577922 0.31198342 3.26146837 0.25958275 3.29256379 0.24342912\n", - " 3.19576444 0.25919948 3.35245553 0.44411906 3.12495614 0.68397486\n", - " 3.13720916 0.41528383]\n", - "P_ = [3.15870416 0.91892239 3.20478699 1.49927449 3.22120793 0.97019335\n", - " 3.24546698 1.1164253 3.21207952 0.79484773 3.24248516 0.66345667\n", - " 3.22792996 0.70166604 3.227092 0.69725713 3.22232123 0.69412253\n", - " 3.20102074 0.76300144 3.20823582 0.72730254 3.20804528 0.66172891\n", - " 3.19940477 0.64749624 3.2071648 0.56717425 3.21440925 0.43460563\n", - " 3.22441075 0.34399478 3.2282399 0.29769233 3.26853551 0.25591147\n", - " 3.27496391 0.24629646 3.21713141 0.28441578 3.33177377 0.46592413\n", - " 3.1255131 0.67176163 3.13720916 0.41528383]\n", - "Depth = 23, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.960582\n", - " Iterations: 1183\n", - " Function evaluations: 1529\n", - "P = [3.13658105 0.87333547 3.19675036 1.45991259 3.20467938 0.96911847\n", - " 3.260225 1.20290068 3.21463355 0.7704972 3.26899403 0.65309352\n", - " 3.2218469 0.66266549 3.2510706 0.64500211 3.22332637 0.77191408\n", - " 3.18965101 0.80783224 3.23397621 0.7113517 3.19350929 0.65460271\n", - " 3.22447244 0.63817504 3.21287144 0.55735543 3.22135771 0.43812484\n", - " 3.24441249 0.34235496 3.22967248 0.33854025 3.26842162 0.25287164\n", - " 3.23020178 0.25186842 3.25831621 0.29340852 3.25182464 0.45323567\n", - " 3.11009984 0.70901326 3.11770393 0.37307025]\n", - "P_ = [3.13658105 0.87333547 3.19413431 1.43440923 3.2039899 1.01179622\n", - " 3.25297992 1.17240735 3.22256249 0.8456978 3.25717653 0.67861606\n", - " 3.23414615 0.66016846 3.24217643 0.65037792 3.23297654 0.72777079\n", - " 3.20282833 0.79377731 3.21470438 0.75329976 3.21286304 0.68174353\n", - " 3.20831776 0.646746 3.21942853 0.60303608 3.21619216 0.51069998\n", - " 3.22937677 0.40481358 3.2399264 0.34119396 3.23978095 0.31619192\n", - " 3.26011296 0.25265355 3.23509124 0.25909279 3.25746948 0.31425554\n", - " 3.23950074 0.4754772 3.11043046 0.69440704 3.11770393 0.37307025]\n", - "Depth = 24, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.856653\n", - " Iterations: 3098\n", - " Function evaluations: 3692\n", - "P = [3.13466472 0.87969291 3.17691398 1.43833239 3.23477189 0.98366895\n", - " 3.27509868 1.20422808 3.20063043 0.70231888 3.25875592 0.7352557\n", - " 3.24026297 0.76922731 3.23489783 0.66505564 3.24708813 0.65655728\n", - " 3.22321035 0.84595123 3.20521109 0.52382892 3.2325367 0.68141418\n", - " 3.20412388 0.65203004 3.21434863 0.61985999 3.25020138 0.54470716\n", - " 3.21061944 0.44772244 3.25389565 0.32409372 3.20140371 0.29757744\n", - " 3.21832919 0.2594473 3.34041252 0.25477848 3.1396864 0.32074057\n", - " 3.20694383 0.49077628 3.12905944 0.69691271 3.13786138 0.4016483 ]\n", - "P_ = [3.13466472 0.87969291 3.17515359 1.41505574 3.2299504 1.02155757\n", - " 3.27005783 1.17665819 3.2130418 0.78597041 3.24664645 0.72839386\n", - " 3.2448862 0.76073441 3.23646266 0.69543904 3.24302469 0.65939007\n", - " 3.23216451 0.7749285 3.21271078 0.65804655 3.22001246 0.6091876\n", - " 3.21833029 0.66672211 3.20881022 0.63728544 3.22928728 0.58854631\n", - " 3.23535815 0.50833789 3.22504484 0.40651287 3.2385855 0.31635981\n", - " 3.20563508 0.28804491 3.24376322 0.25847463 3.30695817 0.26577216\n", - " 3.14809358 0.34199503 3.20045347 0.50795432 3.12942618 0.68461002\n", - " 3.13786138 0.4016483 ]\n", - "Depth = 25, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.262123\n", - " Iterations: 1732\n", - " Function evaluations: 2143\n", - "P = [3.12807749 0.87665573 3.16297538 1.48154347 3.22610687 0.96807568\n", - " 3.29180384 1.12682274 3.19370768 0.7796764 3.25912117 0.71230462\n", - " 3.24801139 0.74971365 3.24387551 0.66082816 3.23993916 0.66781025\n", - " 3.2075573 0.81452025 3.21760666 0.64540468 3.25020973 0.58925183\n", - " 3.21684768 0.67890808 3.23519775 0.61318052 3.24313564 0.61859678\n", - " 3.23206734 0.52841886 3.24157566 0.41164572 3.2433756 0.31066511\n", - " 3.2425574 0.29234641 3.22841314 0.25669362 3.2512441 0.26647143\n", - " 3.19564328 0.35046461 3.27685961 0.51788723 3.11678951 0.69135108\n", - " 3.12460057 0.4200925 ]\n", - "P_ = [3.12807749 0.87665573 3.16157946 1.45734796 3.22105635 1.0091531\n", - " 3.2839202 1.10777309 3.20940306 0.83521982 3.24603847 0.72577897\n", - " 3.25067773 0.74073548 3.24503356 0.6857161 3.2411988 0.66557598\n", - " 3.21921477 0.76170465 3.21358691 0.71305091 3.23586438 0.61395908\n", - " 3.23286147 0.63587308 3.22565572 0.64735885 3.23869043 0.61556367\n", - " 3.23870832 0.58252561 3.23549033 0.48638053 3.24215164 0.37933193\n", - " 3.24314651 0.30553588 3.23916278 0.28378974 3.23297933 0.25864918\n", - " 3.24234797 0.27991034 3.20538924 0.37055532 3.264054 0.53176434\n", - " 3.11710195 0.68050074 3.12460057 0.4200925 ]\n", - "Depth = 26, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.220780\n", - " Iterations: 1377\n", - " Function evaluations: 1765\n", - "P = [3.11959736 0.87382857 3.14995845 1.49349462 3.21658117 0.94002329\n", - " 3.29610522 1.15688075 3.21186612 0.8191869 3.27095284 0.66203034\n", - " 3.23834447 0.75267316 3.24676315 0.69053284 3.23464441 0.67465363\n", - " 3.20418452 0.77328849 3.21686247 0.71240452 3.241121 0.6570138\n", - " 3.23442632 0.64374837 3.23257017 0.64891608 3.24149423 0.6160522\n", - " 3.25320514 0.58217431 3.24023555 0.49456531 3.26269257 0.37080301\n", - " 3.254863 0.30194685 3.22038621 0.28600406 3.18949267 0.26164756\n", - " 3.24271432 0.28419249 3.28931092 0.3656233 3.23325808 0.54062029\n", - " 3.12278214 0.69962718 3.11991039 0.39526015]\n", - "P_ = [3.11959736 0.87382857 3.14879071 1.46966131 3.21145635 0.98259801\n", - " 3.28692937 1.13185874 3.22482598 0.8711398 3.25959001 0.69225276\n", - " 3.24586948 0.73175559 3.24449659 0.70726292 3.23837325 0.67953954\n", - " 3.21472833 0.73914565 3.21198634 0.73582143 3.23085778 0.68044834\n", - " 3.23751617 0.64987088 3.23349825 0.64633222 3.23668897 0.63374813\n", - " 3.24644885 0.60171925 3.24821684 0.54847855 3.24800914 0.45172452\n", - " 3.26028347 0.3496165 3.24558079 0.29765456 3.21325693 0.28038333\n", - " 3.1997276 0.26598312 3.24988303 0.2967203 3.28284329 0.38581526\n", - " 3.22475993 0.55285159 3.12267169 0.68792076 3.11991039 0.39526015]\n", - "Depth = 27, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.810934\n", - " Iterations: 2006\n", - " Function evaluations: 2476\n", - "P = [3.11876979 0.790694 3.15580401 1.64886481 3.23126235 0.96575884\n", - " 3.28253278 1.14989473 3.21488 0.87844701 3.27198799 0.65067572\n", - " 3.24037851 0.75257261 3.25220997 0.69262937 3.23376413 0.71537203\n", - " 3.19863271 0.84262944 3.21887539 0.73312901 3.22129661 0.71749703\n", - " 3.23867759 0.63127869 3.23009504 0.67877096 3.25139894 0.66220971\n", - " 3.24386941 0.57026548 3.23231401 0.47461694 3.27109792 0.42349025\n", - " 3.23687096 0.35692987 3.23628037 0.30046593 3.20650673 0.27906651\n", - " 3.20680158 0.27778539 3.31762656 0.30009972 3.25928554 0.38725434\n", - " 3.22347633 0.56245705 3.13105479 0.597831 3.10794242 0.40039565]\n", - "P_ = [3.11876979 0.790694 3.15443237 1.6170807 3.22567285 1.01635928\n", - " 3.27683607 1.12943519 3.22490263 0.91866149 3.26141244 0.69285559\n", - " 3.24740284 0.72992885 3.24914255 0.70817021 3.23922956 0.70863347\n", - " 3.21034318 0.8002103 3.2113781 0.77368472 3.22031019 0.72386561\n", - " 3.23095271 0.66959795 3.23422738 0.65590431 3.24035247 0.67079702\n", - " 3.24805248 0.6213456 3.23916166 0.53129755 3.24667842 0.45568113\n", - " 3.25968894 0.40130345 3.23669597 0.34019981 3.22856128 0.29491793\n", - " 3.20657225 0.27878182 3.22732472 0.28191767 3.30898345 0.31301152\n", - " 3.25530674 0.4067213 3.21663029 0.56507734 3.13019878 0.59051858\n", - " 3.10794242 0.40039565]\n", - "Depth = 28, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.964376\n", - " Iterations: 1640\n", - " Function evaluations: 2076\n", - "P = [3.1302402 0.78978414 3.16812789 1.59723077 3.21181511 0.9727002\n", - " 3.26011738 1.13679826 3.22764539 0.88364323 3.26802966 0.66488793\n", - " 3.23672709 0.69078355 3.24779101 0.7169304 3.24042675 0.72518579\n", - " 3.21728558 0.81256593 3.25694134 0.76203642 3.20762658 0.71759826\n", - " 3.24245719 0.65908098 3.23040964 0.71508694 3.26175329 0.67214661\n", - " 3.24434678 0.61645495 3.22228988 0.53160475 3.25943657 0.45486298\n", - " 3.23986667 0.41146497 3.23523619 0.35172787 3.22193007 0.29107017\n", - " 3.18209812 0.29690499 3.28348548 0.28363941 3.30962674 0.31724703\n", - " 3.24904446 0.41170356 3.19487112 0.54792617 3.11926641 0.59598399\n", - " 3.10589572 0.39762198]\n", - "P_ = [3.1302402 0.78978414 3.16677476 1.56839339 3.20869459 1.01730953\n", - " 3.25494214 1.11921633 3.23228425 0.91980824 3.26081819 0.70395138\n", - " 3.24343478 0.68523449 3.24502503 0.71039368 3.24253082 0.72282711\n", - " 3.22472381 0.78447946 3.24277857 0.78008267 3.22700023 0.73505611\n", - " 3.22752979 0.68415981 3.23600315 0.68908417 3.24608147 0.69361677\n", - " 3.25367169 0.64628977 3.23489382 0.58009058 3.23688322 0.5014562\n", - " 3.25244732 0.43936369 3.2383783 0.39226376 3.23143444 0.3343971\n", - " 3.21197208 0.29252887 3.20382398 0.29406236 3.28815356 0.28964077\n", - " 3.30097213 0.33074082 3.24324017 0.42629884 3.18947078 0.55135887\n", - " 3.11878888 0.58889963 3.10589572 0.39762198]\n", - "Depth = 29, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.892848\n", - " Iterations: 1641\n", - " Function evaluations: 2063\n", - "P = [3.14127601 0.77388862 3.1528727 1.585789 3.21852168 1.01496754\n", - " 3.25075098 1.14160929 3.22622138 0.86890171 3.276226 0.71982775\n", - " 3.28344877 0.68297106 3.25986931 0.7059698 3.25060882 0.73045756\n", - " 3.19716952 0.70979136 3.27667872 0.79579365 3.2346257 0.73568216\n", - " 3.20455908 0.68502705 3.24793716 0.69252749 3.27171845 0.70609345\n", - " 3.23517496 0.65051403 3.21776451 0.5696025 3.25609475 0.50615989\n", - " 3.25841166 0.43180162 3.26538862 0.39807407 3.18611552 0.3398083\n", - " 3.15855654 0.29374389 3.19735524 0.29295032 3.3104961 0.2939226\n", - " 3.34446554 0.35131061 3.25481741 0.43843592 3.16877286 0.5491537\n", - " 3.15552596 0.59770506 3.11849996 0.38471991]\n", - "P_ = [3.14127601 0.77388862 3.15247282 1.55779243 3.21399417 1.05433454\n", - " 3.24741692 1.12850842 3.22960477 0.90651655 3.26760451 0.74553015\n", - " 3.28195441 0.69059658 3.2655609 0.70041838 3.25316344 0.72370232\n", - " 3.21375413 0.71620501 3.24926176 0.76613769 3.25057685 0.75848307\n", - " 3.21700044 0.70598779 3.22849181 0.68916523 3.26023783 0.69954437\n", - " 3.25407677 0.67926201 3.22737028 0.61424335 3.2336253 0.54335039\n", - " 3.25697358 0.47795503 3.26081751 0.42017143 3.24078663 0.37999159\n", - " 3.17851304 0.32710088 3.16792174 0.29355234 3.2207637 0.29315148\n", - " 3.3163529 0.30381708 3.33210028 0.36332789 3.24591625 0.44988948\n", - " 3.16785928 0.55250207 3.1542492 0.59036074 3.11849996 0.38471991]\n", - "Depth = 30, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 4.733793\n", - " Iterations: 3079\n", - " Function evaluations: 3677\n", - "1.4444444444444444 [9.49224379 8.5914185 6.51566825 7.92243428 6.42528895 5.88013642\n", - " 6.44212283 5.43794686 5.42021124 5.34998253 3.67544153 3.97707443\n", - " 5.37860701 3.82654632 5.28887474 4.93000708 3.14398468 3.15443261\n", - " 3.68304584 2.49066897 3.23659373 2.65107815 2.96058249 2.85665338\n", - " 3.26212317 3.22077985 2.81093423 2.96437621 3.89284757 4.73379294]\n", - "[[6.57155339 5.94790512 4.51084725 5.48476219 4.44827696 4.07086367\n", - " 4.45993119 3.76473244 3.75245393 3.70383406 2.54453644 2.75335922\n", - " 3.72365101 2.64914745 3.66152866 3.41308183 2.17660478 2.18383796\n", - " 2.54980097 1.72430929 2.24071873 1.8353618 2.04963403 1.97768311\n", - " 2.25839296 2.22977067 1.94603139 2.05226045 2.69504832 3.27724127]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]] [0.65715534 0.59479051 0.45108472 0.54847622 0.4448277 0.40708637\n", - " 0.44599312 0.37647324 0.37524539 0.37038341 0.25445364 0.27533592\n", - " 0.3723651 0.26491475 0.36615287 0.34130818 0.21766048 0.2183838\n", - " 0.2549801 0.17243093 0.22407187 0.18353618 0.2049634 0.19776831\n", - " 0.2258393 0.22297707 0.19460314 0.20522605 0.26950483 0.32772413]\n", - "[[0.1749857 0.07463194 0.26530491 0.16394175 0.18892849 0.25701077\n", - " 0.24542951 0.40504394 0.18547862 0.24113788 0.62032714 0.68408453\n", - " 0.11521194 0.57930818 0.29653581 0.32221821 0.75779012 0.76858176\n", - " 0.59269399 0.8271978 0.69201592 0.87101232 0.79114835 0.72852071\n", - " 0.64433266 0.66377712 0.77675308 0.72982301 0.58648573 0.44154865]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]] [0.01749857 0.00746319 0.02653049 0.01639418 0.01889285 0.02570108\n", - " 0.02454295 0.04050439 0.01854786 0.02411379 0.06203271 0.06840845\n", - " 0.01152119 0.05793082 0.02965358 0.03222182 0.07577901 0.07685818\n", - " 0.0592694 0.08271978 0.06920159 0.08710123 0.07911484 0.07285207\n", - " 0.06443327 0.06637771 0.07767531 0.0729823 0.05864857 0.04415487]\n", - "\n", - "Now using 3 solutions, set number 2\n", - "Calculating energy landscape ...\n", - "Optimization terminated successfully.\n", - " Current function value: 7.039563\n", - " Iterations: 28\n", - " Function evaluations: 55\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 7.039563\n", - " Iterations: 6\n", - " Function evaluations: 13\n", - "P = [0.15171022 1.96832314]\n", - "P_ = [0.15171022 1.96832314 0.15171022 1.96832314]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 6.329221\n", - " Iterations: 47\n", - " Function evaluations: 78\n", - "P = [0.08201753 1.99042914 0.17316382 1.85954644]\n", - "P_ = [0.08201753 1.99042914 0.12759068 1.92498779 0.17316382 1.85954644]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.980918\n", - " Iterations: 59\n", - " Function evaluations: 100\n", - "P = [0.10459018 1.90606148 0.07725361 1.81615984 0.22893628 1.82981862]\n", - "P_ = [0.10459018 1.90606148 0.0863658 1.84612706 0.1278145 1.82071277\n", - " 0.22893628 1.82981862]\n", - "Depth = 4, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 3.780437\n", - " Iterations: 168\n", - " Function evaluations: 258\n", - "P = [0.05288565 2.11425996 0.13062444 1.87485044 0.12599333 1.82095433\n", - " 0.21031196 1.78829467]\n", - "P_ = [0.05288565 2.11425996 0.11118974 1.93470282 0.12830888 1.84790239\n", - " 0.14707299 1.81278942 0.21031196 1.78829467]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.036865\n", - " Iterations: 319\n", - " Function evaluations: 447\n", - "P = [0.09547631 1.89876613 0.03543993 1.85769985 0.20246084 1.78708054\n", - " 0.05424027 1.74892824 0.2533223 1.74949832]\n", - "P_ = [0.09547631 1.89876613 0.04744721 1.86591311 0.13565248 1.81532827\n", - " 0.14317261 1.77181962 0.09405667 1.74904225 0.2533223 1.74949832]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.008015\n", - " Iterations: 656\n", - " Function evaluations: 907\n", - "P = [-0.04344237 2.7200324 0.09311632 1.99630131 -0.01756695 1.55864537\n", - " 0.1921324 1.72484971 0.0687596 1.80716425 0.23704279 1.75021945]\n", - "P_ = [-0.04344237 2.7200324 0.07035654 2.11692316 0.01932747 1.70453068\n", - " 0.08728272 1.64174754 0.15100813 1.75228789 0.0968068 1.79767345\n", - " 0.23704279 1.75021945]\n", - "Depth = 7, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.431240\n", - " Iterations: 871\n", - " Function evaluations: 1175\n", - "P = [-0.05463572 2.76820282 0.04075092 1.41464023 0.01805277 1.86391686\n", - " 0.03931954 1.86533374 0.15938779 1.82903183 0.12392589 1.82057658\n", - " 0.25055045 1.766783 ]\n", - "P_ = [-0.05463572 2.76820282 0.02712425 1.60800631 0.02453796 1.73555211\n", - " 0.03020521 1.86472651 0.09077736 1.84977578 0.14925582 1.82661605\n", - " 0.14201512 1.81289178 0.25055045 1.766783 ]\n", - "Depth = 8, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.009626\n", - " Iterations: 903\n", - " Function evaluations: 1209\n", - "P = [-0.06112798 2.44925301 0.03873995 1.58577771 0.03015139 1.7445358\n", - " 0.03919327 1.3981336 -0.0414892 2.05717478 0.20900115 1.77082419\n", - " 0.03871572 1.73192579 0.23310849 1.75447384]\n", - "P_ = [-6.11279830e-02 2.44925301e+00 2.62564548e-02 1.69371212e+00\n", - " 3.22985284e-02 1.70484628e+00 3.58025632e-02 1.52803442e+00\n", - " -1.14796541e-03 1.72765419e+00 5.24446840e-02 1.94979331e+00\n", - " 1.66429796e-01 1.76109959e+00 6.30148158e-02 1.73474430e+00\n", - " 2.33108494e-01 1.75447384e+00]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.640466\n", - " Iterations: 2296\n", - " Function evaluations: 2945\n", - "P = [-1.31862517e-01 3.97945146e+00 1.00029464e-02 5.69407994e-01\n", - " 1.09286368e-01 1.87329123e+00 -4.17971180e-02 2.01975147e+00\n", - " 9.50771230e-04 9.81967711e-01 2.09270254e-01 1.98999505e+00\n", - " 2.03516182e-01 1.71606597e+00 3.38340385e-02 1.75092128e+00\n", - " 2.52575831e-01 1.75487722e+00]\n", - "P_ = [-0.13186252 3.97945146 -0.00575988 0.94830171 0.08722339 1.5835394\n", - " 0.00856404 1.97093139 -0.01804829 1.44320494 0.09353721 1.42997986\n", - " 0.20735223 1.89868536 0.16580904 1.7238116 0.05813868 1.75136083\n", - " 0.25257583 1.75487722]\n", - "Depth = 10, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.702510\n", - " Iterations: 1522\n", - " Function evaluations: 1957\n", - "P = [-0.11577223 2.61356959 -0.00315347 0.67148894 0.06734165 1.97024698\n", - " 0.01251602 2.3111795 -0.03366186 1.43410317 0.1293005 1.6926134\n", - " 0.05788893 1.80840498 0.18738168 1.72544405 0.04221089 1.74942243\n", - " 0.24969626 1.7370275 ]\n", - "P_ = [-0.11577223 2.61356959 -0.01441534 0.865697 0.05324262 1.71049537\n", - " 0.02896371 2.20889975 -0.01519071 1.7849337 0.04781932 1.56335829\n", - " 0.10073587 1.73893003 0.09673675 1.7835167 0.15834752 1.73023973\n", - " 0.06295943 1.74818293 0.24969626 1.7370275 ]\n", - "Depth = 11, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.341372\n", - " Iterations: 1372\n", - " Function evaluations: 1741\n", - "P = [-0.05413944 2.51615855 -0.02700031 0.89572681 0.08641243 0.41032332\n", - " 0.03344259 2.87854972 -0.0226581 1.9035141 0.03471319 1.85924552\n", - " 0.14972416 1.76259702 0.0388625 1.76468125 0.21681264 2.19470309\n", - " -0.01084652 1.22142921 0.28401769 1.72374907]\n", - "P_ = [-5.41394400e-02 2.51615855e+00 -2.94675037e-02 1.04303879e+00\n", - " 6.57919323e-02 4.98578501e-01 4.78889131e-02 2.20539706e+00\n", - " -2.25784771e-03 2.25807251e+00 8.63533045e-03 1.87936760e+00\n", - " 8.69909023e-02 1.81531439e+00 1.09410828e-01 1.76335492e+00\n", - " 8.73943569e-02 1.88195994e+00 1.75420064e-01 2.01774420e+00\n", - " 1.59593213e-02 1.26709465e+00 2.84017692e-01 1.72374907e+00]\n", - "Depth = 12, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [-0.09532737 1.97366518 0.02766034 0.91020855 -0.00671605 0.4443411\n", - " 0.03464019 0.72470237 -0.00587995 1.45775046 0.00890731 4.59623729\n", - " 0.02738322 2.10156289 0.20425893 1.85604422 0.06269081 1.69260613\n", - " 0.21086836 1.79073569 0.02171914 1.61687328 0.27384517 1.71783873]\n", - "P_ = [-9.53273696e-02 1.97366518e+00 1.74113684e-02 9.98829938e-01\n", - " -9.86651591e-04 5.21985678e-01 2.43011295e-02 6.54612053e-01\n", - " 7.62676620e-03 1.21340109e+00 2.74595504e-03 3.28853444e+00\n", - " 1.81452673e-02 3.34890009e+00 1.01081435e-01 1.99926344e+00\n", - " 1.57069560e-01 1.80156486e+00 9.97351992e-02 1.71713852e+00\n", - " 1.79343489e-01 1.76175862e+00 4.27296395e-02 1.62528707e+00\n", - " 2.73845166e-01 1.71783873e+00]\n", - "Depth = 13, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.525410\n", - " Iterations: 1550\n", - " Function evaluations: 1951\n", - "P = [-9.67372103e-02 1.38137272e+00 1.59503927e-02 1.11563456e+00\n", - " -1.79327526e-03 5.40911006e-01 -1.77117090e-04 6.32585161e-01\n", - " 1.33655567e-02 1.62511301e+00 1.27011338e-03 3.58257401e+00\n", - " 2.14062532e-02 3.47106302e+00 8.77838115e-02 1.73892328e+00\n", - " 1.23765311e-01 1.81379135e+00 8.67617024e-02 1.83469381e+00\n", - " 2.14044106e-01 1.78409523e+00 4.36727270e-02 1.65901035e+00\n", - " 2.44083793e-01 1.74411539e+00]\n", - "P_ = [-9.67372103e-02 1.38137272e+00 7.28211554e-03 1.13607595e+00\n", - " 9.36519807e-04 6.29330014e-01 -5.50076668e-04 6.11429587e-01\n", - " 9.19858015e-03 1.31971983e+00 5.92220697e-03 2.82970440e+00\n", - " 1.21126502e-02 3.52252963e+00 5.20420493e-02 2.67161391e+00\n", - " 1.01622850e-01 1.76771869e+00 1.12379586e-01 1.82022288e+00\n", - " 1.16134565e-01 1.82301721e+00 1.87833124e-01 1.76485140e+00\n", - " 5.90889628e-02 1.66555690e+00 2.44083793e-01 1.74411539e+00]\n", - "Depth = 14, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.382483\n", - " Iterations: 3651\n", - " Function evaluations: 4482\n", - "P = [ 7.68936652e-02 2.01639351e+00 9.78860532e-03 2.57908912e+00\n", - " 9.27347329e-04 1.27624822e+00 -7.52684224e-04 8.59609421e-01\n", - " 1.06413037e-02 -6.20230765e-01 4.14606821e-03 2.22141700e+00\n", - " 1.01370256e-02 2.96084611e+00 3.15729070e-02 3.06488822e+00\n", - " -6.13202276e-04 1.98852405e+00 1.65949969e-01 1.86320299e+00\n", - " 4.28242820e-02 1.68361127e+00 2.11787382e-01 1.80450861e+00\n", - " 4.01014748e-02 1.61673631e+00 2.52375368e-01 1.72397265e+00]\n", - "P_ = [ 7.68936652e-02 2.01639351e+00 1.45818239e-02 2.53889658e+00\n", - " 2.19324133e-03 1.46236834e+00 -3.92677463e-04 9.48889163e-01\n", - " 7.38587855e-03 -1.97419283e-01 6.46579516e-03 1.20654280e+00\n", - " 7.56947244e-03 2.64394792e+00 2.08549663e-02 3.01286717e+00\n", - " 1.77788601e-02 2.60358929e+00 5.88736447e-02 1.94376653e+00\n", - " 1.30771202e-01 1.81189107e+00 7.90306606e-02 1.70951784e+00\n", - " 1.87260824e-01 1.77768400e+00 5.52638958e-02 1.62439605e+00\n", - " 2.52375368e-01 1.72397265e+00]\n", - "Depth = 15, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.318224\n", - " Iterations: 3200\n", - " Function evaluations: 3918\n", - "P = [ 1.12528763e-02 1.97006540e+00 3.66382589e-02 3.33708467e+00\n", - " 2.42779294e-03 1.14168185e+00 -3.86797011e-04 3.70701237e-01\n", - " 8.12331403e-03 -2.41357167e-02 6.15922182e-03 1.54890939e+00\n", - " 3.16435439e-03 3.43121505e+00 2.57270413e-02 3.14485949e+00\n", - " 3.02865617e-02 1.58751608e+00 4.60944158e-02 1.94800798e+00\n", - " 1.66148493e-01 1.82238013e+00 7.95936811e-02 1.74407632e+00\n", - " 2.11103902e-01 1.80674967e+00 3.69710120e-02 1.59129966e+00\n", - " 2.45123573e-01 1.72143442e+00]\n", - "P_ = [1.12528763e-02 1.97006540e+00 3.49459001e-02 3.24595005e+00\n", - " 6.98918840e-03 1.43440222e+00 1.76120979e-04 5.24897360e-01\n", - " 5.85395108e-03 8.11541377e-02 6.81391922e-03 1.02456102e+00\n", - " 4.36230136e-03 2.67829278e+00 1.51977874e-02 3.27849209e+00\n", - " 2.78548175e-02 2.41809923e+00 3.66097034e-02 1.73171284e+00\n", - " 8.61124414e-02 1.90613203e+00 1.43067210e-01 1.80149911e+00\n", - " 1.05895725e-01 1.75661099e+00 1.87886183e-01 1.77802300e+00\n", - " 5.08478494e-02 1.59997531e+00 2.45123573e-01 1.72143442e+00]\n", - "Depth = 16, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 6.92362848e-03 1.14398868e+00 2.79501604e-02 3.80972187e+00\n", - " 1.70495385e-02 9.38572769e-01 -2.99438741e-04 7.12546996e-01\n", - " -3.35575485e-05 2.54151714e-02 -1.09777656e-03 -1.23539556e+00\n", - " 4.84888424e-03 3.41097469e+00 3.14473827e-02 3.67083790e+00\n", - " 8.72750147e-02 3.54396494e+00 1.33530188e-01 1.78845581e+00\n", - " 7.89981857e-02 1.77104295e+00 2.18872437e-01 1.41058830e+00\n", - " -3.30632321e-02 2.01121757e+00 2.19113713e-01 1.61201683e+00\n", - " 4.41955527e-02 1.75164757e+00 2.93563571e-01 1.68199777e+00]\n", - "P_ = [ 6.92362848e-03 1.14398868e+00 2.66360022e-02 3.64311354e+00\n", - " 1.84121163e-02 1.29746641e+00 2.95349449e-03 7.54926828e-01\n", - " -1.00027847e-04 1.97198127e-01 -7.65208117e-04 -8.41392208e-01\n", - " 2.61888644e-03 1.66858584e+00 1.98105396e-02 3.55714774e+00\n", - " 5.93611987e-02 3.60740142e+00 1.07511653e-01 2.77592970e+00\n", - " 1.13080687e-01 1.78192598e+00 1.22708889e-01 1.65840087e+00\n", - " 1.55888520e-01 1.56074562e+00 1.42199451e-02 1.93636743e+00\n", - " 1.97248943e-01 1.62947068e+00 5.97810538e-02 1.74729446e+00\n", - " 2.93563571e-01 1.68199777e+00]\n", - "Depth = 17, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 1.14297054e-02 1.12866723e+00 2.87698717e-02 2.62875121e+00\n", - " 1.78636119e-02 2.68101093e+00 1.50217936e-03 4.58839073e-01\n", - " 2.01746661e-05 2.09931989e-01 -7.63687078e-04 -6.03294299e-01\n", - " 4.11839383e-03 1.17972025e+00 1.86918947e-02 3.55518637e+00\n", - " 9.05108596e-02 3.53184693e+00 1.10174049e-01 3.45664798e+00\n", - " 1.55537780e-01 1.59700573e+00 2.37988697e-02 1.86874182e+00\n", - " 2.02246604e-01 1.55345985e+00 1.05645705e-02 1.86148934e+00\n", - " 2.46519948e-01 1.68883706e+00 6.15639197e-02 1.66880477e+00\n", - " 2.78879282e-01 1.67004550e+00]\n", - "P_ = [ 1.14297054e-02 1.12866723e+00 2.77498619e-02 2.54051097e+00\n", - " 1.91467013e-02 2.67486273e+00 4.38949098e-03 8.50987048e-01\n", - " 3.68881653e-04 2.68498362e-01 -5.33139506e-04 -3.64110097e-01\n", - " 2.39530645e-03 5.50420997e-01 1.26910414e-02 2.57705326e+00\n", - " 5.67136997e-02 3.54283019e+00 9.97641254e-02 3.49645919e+00\n", - " 1.28853233e-01 2.69091294e+00 1.09041694e-01 1.69291258e+00\n", - " 7.62834976e-02 1.77601183e+00 1.57144949e-01 1.62593738e+00\n", - " 5.22037547e-02 1.83102129e+00 2.24760415e-01 1.68648032e+00\n", - " 7.43471764e-02 1.66887775e+00 2.78879282e-01 1.67004550e+00]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.820105\n", - " Iterations: 5732\n", - " Function evaluations: 6846\n", - "P = [ 7.98749837e-03 6.78171047e-01 1.70245813e-02 4.38416911e+00\n", - " 2.01853699e-02 1.85973022e+00 5.62071487e-03 6.80149338e-01\n", - " 2.75806338e-04 2.17216690e-01 -5.31447610e-04 -3.18875760e-01\n", - " 2.25403417e-03 7.15638205e-01 1.39935168e-02 3.55065021e+00\n", - " 5.60206962e-02 3.54501895e+00 1.12697127e-01 4.74541545e+00\n", - " 5.04289479e-02 1.95469686e+00 1.78607828e-01 1.70756502e+00\n", - " 4.20020097e-02 1.76555182e+00 2.15288620e-01 1.77867540e+00\n", - " 6.14549715e-02 1.63734345e+00 2.40820432e-01 1.75171391e+00\n", - " 5.80542584e-02 1.57709983e+00 2.46728277e-01 1.66859138e+00]\n", - "P_ = [ 7.98749837e-03 6.78171047e-01 1.65225211e-02 4.17828033e+00\n", - " 1.98341712e-02 2.14022343e+00 8.04815737e-03 8.76746152e-01\n", - " 1.46356379e-03 3.20090612e-01 -3.07210402e-04 -1.69961191e-01\n", - " 1.32554024e-03 3.70800216e-01 9.42816244e-03 2.44814554e+00\n", - " 3.73419498e-02 3.54752173e+00 8.43589118e-02 4.14521720e+00\n", - " 8.50223810e-02 3.50509608e+00 1.00276290e-01 1.85859004e+00\n", - " 1.33072555e-01 1.72689395e+00 9.01371792e-02 1.76919726e+00\n", - " 1.81103365e-01 1.74726830e+00 9.13492148e-02 1.65640519e+00\n", - " 2.20513079e-01 1.73231234e+00 6.85361483e-02 1.58218270e+00\n", - " 2.46728277e-01 1.66859138e+00]\n", - "Depth = 19, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.855461\n", - " Iterations: 6128\n", - " Function evaluations: 7216\n", - "P = [-3.26074075e-03 9.37596745e-01 3.30546501e-02 3.32948432e+00\n", - " 2.49921125e-02 3.15708740e+00 -5.51329977e-03 8.33821696e-01\n", - " 3.18522378e-03 7.49838387e-01 -1.00797895e-05 -1.87992307e-01\n", - " 3.21506611e-03 3.29324751e-01 4.28824367e-03 1.75307947e+00\n", - " 7.41739503e-02 3.42506343e+00 6.73635249e-02 4.51929411e+00\n", - " 3.24746237e-02 3.45825674e+00 2.50464685e-02 1.76315331e+00\n", - " 1.74454968e-01 1.79585255e+00 4.28242985e-02 1.68860684e+00\n", - " 2.12965986e-01 1.85006114e+00 4.14757965e-02 1.55768291e+00\n", - " 2.40285131e-01 1.77650063e+00 3.46127082e-02 1.56059172e+00\n", - " 2.65441973e-01 1.67092537e+00]\n", - "P_ = [-3.26074075e-03 9.37596745e-01 3.11433137e-02 3.20359550e+00\n", - " 2.58408006e-02 3.17523445e+00 -6.96655738e-04 1.20065312e+00\n", - " 1.35395567e-03 7.67519083e-01 8.30789572e-04 5.88052439e-02\n", - " 2.19659898e-03 1.65961470e-01 3.89286246e-03 1.22853826e+00\n", - " 4.47483896e-02 2.72107018e+00 7.05895159e-02 4.00097432e+00\n", - " 5.08372033e-02 4.01669746e+00 2.93469794e-02 2.74452898e+00\n", - " 8.00917052e-02 1.77520040e+00 1.32887388e-01 1.76198548e+00\n", - " 8.75984267e-02 1.73109481e+00 1.76862788e-01 1.78850782e+00\n", - " 7.28667440e-02 1.59223307e+00 2.18635402e-01 1.75377338e+00\n", - " 4.67616169e-02 1.56639875e+00 2.65441973e-01 1.67092537e+00]\n", - "Depth = 20, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [-6.65251590e-03 1.47639267e+00 2.41238369e-02 3.34556011e+00\n", - " 2.36246033e-02 3.53406596e+00 -1.08355302e-03 1.42835870e+00\n", - " 1.11515932e-03 1.57747306e+00 6.88401739e-04 6.85338909e-02\n", - " 1.46483305e-03 2.12829008e-01 -5.89738825e-03 1.07087440e+00\n", - " 3.43341161e-02 2.02049837e+00 1.24192559e-01 4.98781350e+00\n", - " 4.82134851e-02 3.09812382e+00 -4.53071370e-03 3.09845732e+00\n", - " 3.09386568e-02 1.84676613e+00 1.70796889e-01 1.24835900e+00\n", - " -8.50767255e-03 2.19426913e+00 1.97463176e-01 1.68250080e+00\n", - " 6.91357717e-02 1.74371396e+00 2.38922460e-01 1.69333001e+00\n", - " 9.96720704e-02 1.65386670e+00 2.74822005e-01 1.65897405e+00]\n", - "P_ = [-6.65251590e-03 1.47639267e+00 2.25850192e-02 3.25210174e+00\n", - " 2.36745267e-02 3.51521537e+00 2.62267043e-03 1.74421479e+00\n", - " 6.75416848e-04 1.54765019e+00 7.95091133e-04 4.45768682e-01\n", - " 1.23190366e-03 1.69540473e-01 -3.32061079e-03 7.70558514e-01\n", - " 1.82415143e-02 1.64064878e+00 8.37562594e-02 3.65252169e+00\n", - " 8.62030218e-02 4.04296866e+00 2.44785957e-02 3.09827389e+00\n", - " 9.65703449e-03 2.59778085e+00 7.98890381e-02 1.63732364e+00\n", - " 1.17005521e-01 1.53213204e+00 4.29850397e-02 2.06632705e+00\n", - " 1.71797695e-01 1.69474344e+00 9.46037749e-02 1.73615637e+00\n", - " 2.24997421e-01 1.68938368e+00 1.08429567e-01 1.65412207e+00\n", - " 2.74822005e-01 1.65897405e+00]\n", - "Depth = 21, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [-6.18421932e-03 7.25548877e-01 1.80661631e-02 4.14509975e+00\n", - " 4.66769096e-02 2.68523803e+00 2.54164141e-03 2.15262669e+00\n", - " 6.40746692e-04 2.28209075e+00 5.50285705e-04 1.17760170e-01\n", - " 4.19329976e-04 1.05703530e-01 -1.92810528e-03 1.33563579e+00\n", - " 3.00324652e-02 1.34344878e+00 4.70518838e-02 3.62036091e+00\n", - " 6.92408625e-02 4.85341080e+00 4.82127645e-02 3.29098631e+00\n", - " 5.95439222e-03 1.64016856e+00 6.71788093e-02 1.82970285e+00\n", - " 1.43932988e-01 1.76741629e+00 7.21167727e-02 1.77022436e+00\n", - " 1.91795621e-01 1.75963581e+00 5.02083547e-02 1.69044294e+00\n", - " 2.28189900e-01 1.73100825e+00 9.47710824e-02 1.64826131e+00\n", - " 2.52351686e-01 1.68629363e+00]\n", - "P_ = [-6.18421932e-03 7.25548877e-01 1.69113830e-02 3.98226399e+00\n", - " 4.39520766e-02 2.82427248e+00 8.84667972e-03 2.22871403e+00\n", - " 1.00282188e-03 2.25743093e+00 5.71824035e-04 6.33076974e-01\n", - " 4.56745898e-04 1.09148284e-01 -1.14562686e-03 9.25658372e-01\n", - " 1.78570098e-02 1.34047240e+00 3.97578472e-02 2.64454142e+00\n", - " 5.86746822e-02 4.26624419e+00 5.92274825e-02 4.10939914e+00\n", - " 3.01020335e-02 2.58349299e+00 2.92779797e-02 1.71237210e+00\n", - " 9.27635355e-02 1.80894066e+00 1.23414069e-01 1.76821860e+00\n", - " 1.00611736e-01 1.76770328e+00 1.64826618e-01 1.74645622e+00\n", - " 7.56342898e-02 1.69623799e+00 2.15483346e-01 1.72312759e+00\n", - " 1.02274921e-01 1.65007238e+00 2.52351686e-01 1.68629363e+00]\n", - "Depth = 22, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [-1.45050257e-02 6.14913491e-01 1.21965985e-02 4.49598062e+00\n", - " 8.01728033e-03 3.34392421e+00 -1.98061244e-02 2.18586708e+00\n", - " 3.27343500e-03 2.30298941e+00 8.50261638e-04 8.62065499e-01\n", - " 1.26404528e-03 1.16485666e-01 -3.76572509e-04 1.50728233e+00\n", - " -6.37655339e-03 6.81278277e-01 3.78742798e-02 2.12683299e+00\n", - " 7.27809657e-02 5.05047581e+00 9.83260747e-02 3.35796222e+00\n", - " 4.26873774e-02 3.34723766e+00 8.50606631e-02 1.57496671e+00\n", - " 7.26289797e-02 1.90324274e+00 1.88164437e-01 1.75871278e+00\n", - " 6.46493245e-02 1.69278596e+00 2.04109598e-01 1.74413313e+00\n", - " -1.69861390e-02 1.63664661e+00 2.40256492e-01 1.61323667e+00\n", - " 7.30657416e-02 1.72779657e+00 2.92542835e-01 1.66858913e+00]\n", - "P_ = [-1.45050257e-02 6.14913491e-01 1.09828883e-02 4.31956848e+00\n", - " 8.39721835e-03 3.44865661e+00 -1.60120237e-02 2.34378396e+00\n", - " -9.22848522e-04 2.28169444e+00 1.40098286e-03 1.18954821e+00\n", - " 1.15119519e-03 3.19825620e-01 1.45442241e-04 1.06475612e+00\n", - " -4.19474216e-03 9.81643386e-01 1.97716662e-02 1.53546970e+00\n", - " 5.69142903e-02 3.72154726e+00 8.55535202e-02 4.20421901e+00\n", - " 7.30357578e-02 3.35308742e+00 6.00219034e-02 2.62221773e+00\n", - " 8.05400509e-02 1.69433981e+00 1.09390261e-01 1.85725594e+00\n", - " 1.54478497e-01 1.74073274e+00 9.63448413e-02 1.70445577e+00\n", - " 1.63910373e-01 1.72459013e+00 1.80924016e-02 1.63345435e+00\n", - " 2.25057333e-01 1.62365121e+00 8.30419731e-02 1.72510533e+00\n", - " 2.92542835e-01 1.66858913e+00]\n", - "Depth = 23, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 1.704664\n", - " Iterations: 7440\n", - " Function evaluations: 8646\n", - "P = [-1.27916037e-02 5.26733752e-01 1.20536740e-02 4.66079991e+00\n", - " 1.00050755e-02 3.81496699e+00 -2.82736499e-02 1.41691017e+00\n", - " -1.46618008e-03 2.41612401e+00 1.25971449e-03 9.93973175e-01\n", - " 5.04905968e-04 4.14294961e-01 3.72039585e-05 1.13154232e+00\n", - " -2.86693542e-03 9.53508773e-01 2.48761872e-02 2.04020555e+00\n", - " 1.08724216e-01 3.47061844e+00 4.47949652e-02 4.69088300e+00\n", - " 5.12804381e-02 2.76338567e+00 1.76303523e-02 2.25209538e+00\n", - " 1.31241732e-01 1.74454364e+00 8.42661905e-02 1.79796006e+00\n", - " 1.88766253e-01 1.80181688e+00 5.39874285e-02 1.62319386e+00\n", - " 2.08198816e-01 1.85521489e+00 1.65433677e-02 1.52573243e+00\n", - " 2.43218999e-01 1.69169254e+00 1.12982675e-01 1.65269843e+00\n", - " 2.64881907e-01 1.66044298e+00]\n", - "P_ = [-1.27916037e-02 5.26733752e-01 1.09734446e-02 4.48105790e+00\n", - " 1.01832145e-02 3.88851768e+00 -2.32807726e-02 1.72970019e+00\n", - " -6.12834873e-03 2.24234769e+00 6.67128715e-04 1.30313640e+00\n", - " 7.01812539e-04 5.65515365e-01 1.79548048e-04 9.13249644e-01\n", - " -1.85679998e-03 1.01543348e+00 1.40201827e-02 1.61497638e+00\n", - " 7.22685515e-02 2.84869979e+00 7.53698244e-02 4.10727821e+00\n", - " 4.78967131e-02 3.76903645e+00 3.66499660e-02 2.54108554e+00\n", - " 6.20869791e-02 2.05348818e+00 1.14902413e-01 1.76312326e+00\n", - " 1.16070557e-01 1.79913387e+00 1.53606560e-01 1.75521957e+00\n", - " 8.75116432e-02 1.67363322e+00 1.74867434e-01 1.79791359e+00\n", - " 4.61097543e-02 1.54737940e+00 2.31894101e-01 1.68830175e+00\n", - " 1.19586989e-01 1.65303515e+00 2.64881907e-01 1.66044298e+00]\n", - "Depth = 24, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [-1.46913662e-02 4.17720894e-01 9.14353102e-03 3.55677947e+00\n", - " 8.49812838e-03 3.98407361e+00 -3.83995610e-02 8.57960306e-01\n", - " -5.35271551e-03 2.37256193e+00 6.43771330e-04 1.32896314e+00\n", - " 4.05406299e-04 6.09174787e-01 3.12288782e-04 1.78447973e+00\n", - " -2.62190248e-03 1.17445132e+00 2.83474598e-02 1.61877282e+00\n", - " -2.89683409e-02 2.72131288e+00 4.29754696e-02 3.24797027e+00\n", - " 4.83975063e-02 3.71830435e+00 6.79792286e-02 3.15666657e+00\n", - " 4.29161990e-02 2.05259094e+00 1.32067787e-01 1.84529393e+00\n", - " 1.07827411e-01 1.87020519e+00 1.69509077e-01 1.71912867e+00\n", - " 5.72222267e-02 1.76883662e+00 1.98435500e-01 1.68721435e+00\n", - " 4.64214187e-02 1.73733866e+00 2.39422944e-01 1.69284921e+00\n", - " 6.96996788e-02 1.66400937e+00 2.60023369e-01 1.67601870e+00]\n", - "P_ = [-1.46913662e-02 4.17720894e-01 8.15041030e-03 3.42598537e+00\n", - " 8.55191194e-03 3.94846576e+00 -3.25373498e-02 1.24872447e+00\n", - " -1.08605231e-02 2.12012832e+00 -6.05496762e-04 1.54637955e+00\n", - " 4.64997557e-04 7.89121876e-01 3.39448058e-04 1.44168246e+00\n", - " -1.64383872e-03 1.37779412e+00 1.67339489e-02 1.45215226e+00\n", - " -5.08675730e-03 2.26192119e+00 1.00012231e-02 3.00658563e+00\n", - " 4.56864879e-02 3.48313731e+00 5.73724624e-02 3.46088703e+00\n", - " 5.75362996e-02 2.69663506e+00 7.63480445e-02 1.97485456e+00\n", - " 1.23987662e-01 1.85359769e+00 1.25817897e-01 1.82614121e+00\n", - " 1.41437365e-01 1.73155566e+00 8.66416585e-02 1.75183198e+00\n", - " 1.73099819e-01 1.69556840e+00 7.05466094e-02 1.73177748e+00\n", - " 2.25279339e-01 1.69044589e+00 7.76298326e-02 1.66450976e+00\n", - " 2.60023369e-01 1.67601870e+00]\n", - "Depth = 25, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [-1.72262575e-02 4.52777275e-01 5.14790816e-03 2.89048291e+00\n", - " 9.72095322e-03 3.19576959e+00 -3.65287179e-02 4.29488270e-01\n", - " -1.68066422e-02 2.14803354e+00 -5.21920224e-04 1.53381801e+00\n", - " 5.58204068e-04 9.20317942e-01 3.91835617e-04 1.48449018e+00\n", - " -2.69491919e-04 1.49585444e+00 2.23560778e-02 1.80876009e+00\n", - " -1.22558242e-02 2.30866837e+00 -3.95560823e-04 2.97246051e+00\n", - " 1.74213102e-02 3.57017416e+00 6.64115181e-02 3.52519373e+00\n", - " 3.69072261e-02 3.24865170e+00 8.28227994e-02 1.96158634e+00\n", - " 1.18026517e-01 1.79692147e+00 1.05450953e-01 1.85924434e+00\n", - " 1.69569433e-01 1.75820152e+00 8.14959367e-02 1.74267807e+00\n", - " 2.07286456e-01 1.79599398e+00 5.57571491e-02 1.62783262e+00\n", - " 2.22941368e-01 1.72888842e+00 1.03355485e-01 1.63777836e+00\n", - " 2.45784855e-01 1.67572958e+00]\n", - "P_ = [-1.72262575e-02 4.52777275e-01 4.25294154e-03 2.79297468e+00\n", - " 9.35510961e-03 3.17134666e+00 -3.09787574e-02 7.61442029e-01\n", - " -1.99621743e-02 1.87306629e+00 -3.77886462e-03 1.65666112e+00\n", - " 2.98974238e-04 1.06755796e+00 4.38418783e-04 1.32652196e+00\n", - " -5.78671074e-05 1.49221788e+00 1.42108727e-02 1.69611406e+00\n", - " 1.58893663e-03 2.10870506e+00 -5.61407670e-03 2.68039197e+00\n", - " 8.86921210e-03 3.28327161e+00 4.09366100e-02 3.54858355e+00\n", - " 5.34296296e-02 3.40351524e+00 5.52734554e-02 2.73382556e+00\n", - " 9.54961378e-02 1.90230698e+00 1.14002337e-01 1.81686479e+00\n", - " 1.23404128e-01 1.83095235e+00 1.48431794e-01 1.75447589e+00\n", - " 1.06654040e-01 1.75334125e+00 1.83041767e-01 1.76908816e+00\n", - " 7.58192553e-02 1.63995932e+00 2.13374497e-01 1.72159961e+00\n", - " 1.09052659e-01 1.63929641e+00 2.45784855e-01 1.67572958e+00]\n", - "Depth = 26, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [-3.64056707e-02 3.52139535e-01 7.42807990e-03 2.78730709e+00\n", - " 2.56682270e-03 2.25257295e+00 -3.81566935e-02 3.06780231e-01\n", - " -3.92688121e-02 1.97943625e+00 -3.25496845e-03 1.94988856e+00\n", - " 2.80370910e-04 7.87496098e-01 7.63932349e-04 1.42474062e+00\n", - " -7.00064036e-05 1.50034046e+00 1.46569866e-02 2.10430253e+00\n", - " 8.26478712e-04 1.85293419e+00 -7.35686522e-03 2.71914504e+00\n", - " 7.91950882e-03 3.49746943e+00 2.59377520e-02 3.76319959e+00\n", - " 5.77039032e-02 3.40350027e+00 4.17461828e-02 3.35952392e+00\n", - " 8.43235078e-02 1.93182363e+00 1.18400419e-01 1.78054681e+00\n", - " 9.92966119e-02 1.84705114e+00 1.71340971e-01 1.75305291e+00\n", - " 5.75071155e-02 1.71485146e+00 2.02423886e-01 1.78929680e+00\n", - " 4.74358654e-02 1.62693180e+00 2.33131417e-01 1.73068288e+00\n", - " 1.01320054e-01 1.61771492e+00 2.31314388e-01 1.66546926e+00]\n", - "P_ = [-3.64056707e-02 3.52139535e-01 5.74216642e-03 2.69364680e+00\n", - " 2.94076557e-03 2.29370635e+00 -3.34578262e-02 5.31294776e-01\n", - " -3.90977169e-02 1.72210455e+00 -1.01807076e-02 1.95557081e+00\n", - " -5.35476633e-04 1.05574051e+00 6.33742731e-04 1.25317478e+00\n", - " 1.86590136e-04 1.47707897e+00 9.55918134e-03 1.89523874e+00\n", - " 6.14590483e-03 1.94961433e+00 -3.89468125e-03 2.35267122e+00\n", - " 8.68874647e-04 3.13824278e+00 1.69286304e-02 3.63033451e+00\n", - " 4.05990525e-02 3.59718452e+00 5.09525599e-02 3.38489489e+00\n", - " 5.81220770e-02 2.81040842e+00 9.61193617e-02 1.87945857e+00\n", - " 1.12522325e-01 1.80100968e+00 1.18693170e-01 1.82174393e+00\n", - " 1.45071619e-01 1.74423719e+00 8.53757252e-02 1.72916787e+00\n", - " 1.78579575e-01 1.76431757e+00 6.88622752e-02 1.63890308e+00\n", - " 2.22992081e-01 1.72199304e+00 1.06319836e-01 1.61955162e+00\n", - " 2.31314388e-01 1.66546926e+00]\n", - "Depth = 27, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [-3.27092020e-02 8.24691036e-02 9.22208181e-03 3.22103189e+00\n", - " 2.90640832e-03 1.67594630e+00 -2.49181781e-02 5.76612633e-01\n", - " -6.26772090e-02 1.62843555e+00 -1.01261464e-02 1.36274806e+00\n", - " -4.85548331e-04 1.39304535e+00 3.56138507e-04 1.29729325e+00\n", - " 1.96756982e-04 1.69446486e+00 1.59542929e-02 3.14508601e+00\n", - " 9.76544902e-03 7.47559902e-01 -9.34510284e-04 1.64904566e+00\n", - " 7.69618663e-04 4.40217449e+00 2.39572783e-02 3.31367380e+00\n", - " 2.61610946e-02 3.98380666e+00 3.28778555e-02 3.46496941e+00\n", - " 5.94182502e-02 3.44645335e+00 7.58310409e-02 1.93121815e+00\n", - " 1.45524499e-01 1.79285745e+00 9.37703662e-02 1.81199661e+00\n", - " 1.90261045e-01 1.79544236e+00 7.03154378e-02 1.66320624e+00\n", - " 2.11247695e-01 1.83127684e+00 6.42272561e-02 1.55580609e+00\n", - " 2.24223492e-01 1.75165286e+00 6.68776392e-02 1.58195428e+00\n", - " 2.41934726e-01 1.66618292e+00]\n", - "P_ = [-3.27092020e-02 8.24691036e-02 7.66907130e-03 3.10478883e+00\n", - " 3.37423598e-03 1.79039709e+00 -2.18265574e-02 6.98760818e-01\n", - " -5.70832785e-02 1.47260993e+00 -1.98578247e-02 1.41194945e+00\n", - " -2.62790346e-03 1.38631262e+00 1.37923401e-04 1.32211787e+00\n", - " 2.43981138e-04 1.57678438e+00 1.07017809e-02 2.66154562e+00\n", - " 1.20576134e-02 1.63553253e+00 3.42473239e-03 1.28177369e+00\n", - " 1.22280201e-05 3.17856168e+00 1.27928496e-02 3.83776673e+00\n", - " 2.50183750e-02 3.63633036e+00 2.91463217e-02 3.75321233e+00\n", - " 4.36906089e-02 3.45742583e+00 6.54970616e-02 2.88525513e+00\n", - " 9.90621937e-02 1.88509792e+00 1.30189941e-01 1.79852831e+00\n", - " 1.18786468e-01 1.80770477e+00 1.63606466e-01 1.76605655e+00\n", - " 9.64140039e-02 1.69433042e+00 1.89466889e-01 1.79046635e+00\n", - " 8.20046156e-02 1.57756684e+00 2.12568243e-01 1.73908259e+00\n", - " 7.33612350e-02 1.58507386e+00 2.41934726e-01 1.66618292e+00]\n", - "Depth = 28, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [-4.05394788e-02 9.22854916e-02 3.48897494e-03 3.14446991e+00\n", - " 2.14410517e-03 1.75011104e+00 -1.92933898e-02 7.65677229e-01\n", - " -7.41810430e-02 1.30739735e+00 -2.11413476e-02 1.25360446e+00\n", - " -1.98924269e-03 1.76174466e+00 1.48472147e-04 1.29955384e+00\n", - " 2.46789038e-04 1.33634333e+00 9.14618643e-03 3.09642131e+00\n", - " 1.48393256e-02 1.88862637e+00 3.83337996e-03 1.04584608e+00\n", - " 1.16238422e-05 3.86787210e+00 1.34356739e-02 3.57326866e+00\n", - " 3.20883772e-02 3.06748933e+00 2.82893490e-02 4.22526417e+00\n", - " 5.37600855e-02 3.60174837e+00 6.30264348e-02 3.34672945e+00\n", - " 8.29294741e-02 1.86322938e+00 1.38453965e-01 1.76054026e+00\n", - " 8.98045426e-02 1.81509390e+00 1.78168298e-01 1.73620703e+00\n", - " 6.42231345e-02 1.72176420e+00 2.06307999e-01 1.72417298e+00\n", - " 3.22820725e-02 1.67416092e+00 2.40335673e-01 1.69531557e+00\n", - " 8.91888582e-02 1.66246445e+00 2.64733352e-01 1.66582757e+00]\n", - "P_ = [-4.05394788e-02 9.22854916e-02 1.91653016e-03 3.03546332e+00\n", - " 2.24016729e-03 1.84970811e+00 -1.69965153e-02 8.71152281e-01\n", - " -6.63399497e-02 1.23000876e+00 -3.06127218e-02 1.26321034e+00\n", - " -6.09326516e-03 1.65285747e+00 -3.85956562e-04 1.41510155e+00\n", - " 2.18698497e-04 1.32583205e+00 6.28566584e-03 2.53068196e+00\n", - " 1.28060616e-02 2.31998171e+00 8.15714431e-03 1.37693834e+00\n", - " 1.64951932e-03 2.65843238e+00 7.20307924e-03 3.71004883e+00\n", - " 2.27620255e-02 3.32037900e+00 3.03245427e-02 3.60502765e+00\n", - " 3.92053789e-02 3.95804311e+00 5.74004370e-02 3.50156236e+00\n", - " 7.01346631e-02 2.81690800e+00 1.00776632e-01 1.83022216e+00\n", - " 1.24554130e-01 1.77612701e+00 1.11895481e-01 1.79537218e+00\n", - " 1.53751477e-01 1.73311214e+00 8.95954317e-02 1.72219434e+00\n", - " 1.81447153e-01 1.71702840e+00 5.45735297e-02 1.67642749e+00\n", - " 2.29539472e-01 1.69296906e+00 9.54583044e-02 1.66258456e+00\n", - " 2.64733352e-01 1.66582757e+00]\n", - "Depth = 29, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [-5.41154150e-02 1.04847297e-01 2.33599694e-03 2.91577750e+00\n", - " 1.32103660e-03 1.96144245e+00 -9.85176114e-03 8.03970057e-01\n", - " -4.18227000e-02 1.48894130e+00 -3.17900274e-02 1.42092786e+00\n", - " -8.16923279e-03 1.09391653e+00 -5.51999028e-04 1.50024829e+00\n", - " 2.37279782e-04 1.46384068e+00 4.48595208e-03 2.94037941e+00\n", - " 1.47498406e-02 1.67989841e+00 1.15817355e-02 2.38820454e+00\n", - " 1.04864256e-03 2.37218281e+00 8.64638636e-03 3.63683234e+00\n", - " 2.54169672e-02 3.20876117e+00 3.02177433e-02 3.41754275e+00\n", - " 6.63676506e-02 4.55658162e+00 2.64422030e-02 3.43730535e+00\n", - " 3.89654037e-02 3.09697249e+00 3.73086191e-02 1.87706038e+00\n", - " 1.63837044e-01 1.74324044e+00 8.82073458e-02 1.77444058e+00\n", - " 2.01361687e-01 1.77055747e+00 4.47104594e-02 1.63291522e+00\n", - " 2.10225622e-01 1.70291000e+00 4.72861656e-02 1.65840682e+00\n", - " 2.48351463e-01 1.68171306e+00 1.11804311e-01 1.63912386e+00\n", - " 2.56395017e-01 1.64233781e+00]\n", - "P_ = [-5.41154150e-02 1.04847297e-01 3.89396529e-04 2.81884887e+00\n", - " 1.39103386e-03 2.02725866e+00 -8.69595447e-03 9.23708580e-01\n", - " -3.74129153e-02 1.39446251e+00 -3.35197986e-02 1.43265432e+00\n", - " -1.30562937e-02 1.16157404e+00 -2.39064166e-03 1.40216821e+00\n", - " 1.95476964e-05 1.47388416e+00 3.16739861e-03 2.48214326e+00\n", - " 1.12105687e-02 2.11454703e+00 1.27834305e-02 2.11953670e+00\n", - " 5.40716376e-03 2.37881249e+00 5.24050121e-03 3.06992048e+00\n", - " 1.73208247e-02 3.41541622e+00 2.77345832e-02 3.30955228e+00\n", - " 4.64228741e-02 3.92814638e+00 4.98467757e-02 4.09343282e+00\n", - " 3.11923826e-02 3.30821358e+00 3.83940987e-02 2.67631314e+00\n", - " 7.65760613e-02 1.83553006e+00 1.42973679e-01 1.75184738e+00\n", - " 1.15520463e-01 1.77350328e+00 1.68951088e-01 1.74207977e+00\n", - " 7.32475564e-02 1.64498329e+00 1.87751214e-01 1.69677163e+00\n", - " 6.80860240e-02 1.66081781e+00 2.38934418e-01 1.67877587e+00\n", - " 1.16790197e-01 1.63923469e+00 2.56395017e-01 1.64233781e+00]\n", - "Depth = 30, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "0.9285714285714285 [7.03956316 6.32922134 3.98091788 3.78043688 3.03686465 3.00801529\n", - " 3.4312401 3.00962554 2.6404663 2.70251012 2.3413721 2.51812869\n", - " 2.52541046 2.38248344 2.31822434 1.99630014 1.89217954 1.82010451\n", - " 1.85546104 1.85306333 1.95897305 1.73170995 1.70466389 1.8451085\n", - " 1.83981121 1.81356149 1.77291013 1.72257065 1.66720387 1.66805683]\n", - "[[6.57155339 5.94790512 4.51084725 5.48476219 4.44827696 4.07086367\n", - " 4.45993119 3.76473244 3.75245393 3.70383406 2.54453644 2.75335922\n", - " 3.72365101 2.64914745 3.66152866 3.41308183 2.17660478 2.18383796\n", - " 2.54980097 1.72430929 2.24071873 1.8353618 2.04963403 1.97768311\n", - " 2.25839296 2.22977067 1.94603139 2.05226045 2.69504832 3.27724127]\n", - " [7.58106801 6.81608452 4.28714233 4.07123972 3.27046962 3.23940109\n", - " 3.69518164 3.2411352 2.8435791 2.91039551 2.52147765 2.7118309\n", - " 2.7196728 2.5657514 2.49654928 2.14986169 2.03773181 1.96011255\n", - " 1.99818881 1.99560667 2.10966328 1.86491841 1.83579189 1.98703992\n", - " 1.98133515 1.95306622 1.90928783 1.85507609 1.79545032 1.7963689 ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]] [1.41526214 1.27639896 0.87979896 0.95560019 0.77187466 0.73102648\n", - " 0.81551128 0.70058676 0.6596033 0.66142296 0.50660141 0.54651901\n", - " 0.64433238 0.52148988 0.61580779 0.55629435 0.42143366 0.41439505\n", - " 0.45479898 0.3719916 0.4350382 0.37002802 0.38854259 0.3964723\n", - " 0.42397281 0.41828369 0.38553192 0.39073365 0.44904986 0.50736102]\n", - "[[0.1749857 0.07463194 0.26530491 0.16394175 0.18892849 0.25701077\n", - " 0.24542951 0.40504394 0.18547862 0.24113788 0.62032714 0.68408453\n", - " 0.11521194 0.57930818 0.29653581 0.32221821 0.75779012 0.76858176\n", - " 0.59269399 0.8271978 0.69201592 0.87101232 0.79114835 0.72852071\n", - " 0.64433266 0.66377712 0.77675308 0.72982301 0.58648573 0.44154865]\n", - " [0.17669094 0.20818569 0.40598211 0.40456531 0.54848127 0.5337594\n", - " 0.48446167 0.53759304 0.60295388 0.58451793 0.64895146 0.66165701\n", - " 0.62972457 0.66201878 0.67281148 0.75627098 0.78514972 0.80366385\n", - " 0.79430362 0.79961314 0.7524382 0.82370466 0.83214203 0.78138294\n", - " 0.78255631 0.78124579 0.80687807 0.80774629 0.84561002 0.84356134]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]] [0.03516766 0.02828176 0.0671287 0.05685071 0.07374098 0.07907702\n", - " 0.07298912 0.0942637 0.07884325 0.08256558 0.12692786 0.13457415\n", - " 0.07449365 0.1241327 0.09693473 0.10784892 0.15429398 0.15722456\n", - " 0.13869976 0.16268109 0.14444541 0.1694717 0.16232904 0.15099037\n", - " 0.1426889 0.14450229 0.15836311 0.15375693 0.14320957 0.128511 ]\n", - "\n", - "Now using 3 solutions, set number 3\n", - "Calculating energy landscape ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 7.704162\n", - " Iterations: 30\n", - " Function evaluations: 56\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 7.704162\n", - " Iterations: 6\n", - " Function evaluations: 13\n", - "P = [0.15260248 2.02589483]\n", - "P_ = [0.15260248 2.02589483 0.15260248 2.02589483]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 6.397471\n", - " Iterations: 98\n", - " Function evaluations: 160\n", - "P = [-0.11129321 2.10647611 0.07310716 2.13027992]\n", - "P_ = [-0.11129321 2.10647611 -0.01909303 2.11837801 0.07310716 2.13027992]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.452193\n", - " Iterations: 89\n", - " Function evaluations: 147\n", - "P = [ 0.13477173 3.0169489 -0.03127744 0.56944008 0.15647523 1.82257701]\n", - "P_ = [0.13477173 3.0169489 0.02407228 1.38527635 0.03130678 0.98715239\n", - " 0.15647523 1.82257701]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.573512\n", - " Iterations: 276\n", - " Function evaluations: 404\n", - "P = [-0.07213735 5.11159969 0.02945955 0.29990123 0.03303718 0.443112\n", - " 0.24455258 1.81892974]\n", - "P_ = [-7.21373519e-02 5.11159969e+00 4.06032549e-03 1.50282585e+00\n", - " 3.12483639e-02 3.71506617e-01 8.59160285e-02 7.87066436e-01\n", - " 2.44552584e-01 1.81892974e+00]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.109591\n", - " Iterations: 787\n", - " Function evaluations: 1130\n", - "P = [-0.02596614 2.04275549 -0.00317094 3.14577383 0.05720105 0.57647904\n", - " 0.15076635 0.31848173 0.18834702 1.75936522]\n", - "P_ = [-0.02596614 2.04275549 -0.00772998 2.92517016 0.03305225 1.60419695\n", - " 0.09462717 0.47328011 0.15828248 0.60665843 0.18834702 1.75936522]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.744367\n", - " Iterations: 1209\n", - " Function evaluations: 1648\n", - "P = [-0.03003726 3.02095173 -0.00524554 1.94011729 0.04618005 0.7446564\n", - " 0.11864224 0.34692317 0.15638739 0.2417508 0.20530215 1.70862322]\n", - "P_ = [-0.03003726 3.02095173 -0.0093775 2.12025637 0.02903818 1.14314336\n", - " 0.08241114 0.54578978 0.13122396 0.31186571 0.16453985 0.48622954\n", - " 0.20530215 1.70862322]\n", - "Depth = 7, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.822782\n", - " Iterations: 1584\n", - " Function evaluations: 2100\n", - "P = [-0.03080513 4.55926547 0.01226565 0.66708269 0.08149769 0.56319697\n", - " 0.17706292 0.30281955 0.20104467 0.25076918 0.29663933 0.19914516\n", - " 0.28073231 1.72191708]\n", - "P_ = [-0.03080513 4.55926547 0.00611268 1.22310881 0.06171711 0.5928786\n", - " 0.13610639 0.41440987 0.18734081 0.28051225 0.22835743 0.23601946\n", - " 0.2943669 0.416684 0.28073231 1.72191708]\n", - "Depth = 8, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.540037\n", - " Iterations: 928\n", - " Function evaluations: 1234\n", - "P = [-0.02945548 4.22478229 0.00546306 0.88397317 0.05684184 0.70218201\n", - " 0.15935463 0.37012721 0.19377956 0.2465379 0.22393307 0.19419209\n", - " 0.28001117 0.19819486 0.26146457 1.69673547]\n", - "P_ = [-2.94554766e-02 4.22478229e+00 1.09823882e-03 1.30157431e+00\n", - " 4.39971424e-02 7.47629798e-01 1.20912331e-01 4.94647760e-01\n", - " 1.76567095e-01 3.08332557e-01 2.05087129e-01 2.26908223e-01\n", - " 2.37952597e-01 1.95192780e-01 2.77692848e-01 3.85512435e-01\n", - " 2.61464567e-01 1.69673547e+00]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.398569\n", - " Iterations: 758\n", - " Function evaluations: 1009\n", - "P = [-3.07305504e-02 3.73566205e+00 1.23712678e-03 1.30478901e+00\n", - " 5.37110632e-02 7.51380844e-01 1.43887354e-01 4.28183670e-01\n", - " 1.88411021e-01 2.87710483e-01 2.15913882e-01 1.99931119e-01\n", - " 2.46590649e-01 2.20690468e-01 2.69426391e-01 1.88624864e-01\n", - " 2.85756867e-01 1.66613087e+00]\n", - "P_ = [-3.07305504e-02 3.73566205e+00 -2.31483735e-03 1.57488602e+00\n", - " 4.20501885e-02 8.74360438e-01 1.13828590e-01 5.35916061e-01\n", - " 1.68622724e-01 3.50143011e-01 2.00634515e-01 2.48697432e-01\n", - " 2.26139471e-01 2.06850902e-01 2.51665259e-01 2.13564778e-01\n", - " 2.71240888e-01 3.52792198e-01 2.85756867e-01 1.66613087e+00]\n", - "Depth = 10, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.176856\n", - " Iterations: 883\n", - " Function evaluations: 1128\n", - "P = [-3.24157700e-02 3.64670584e+00 -2.57628411e-03 1.53587668e+00\n", - " 5.30469944e-02 7.65240126e-01 1.61793293e-01 4.41291678e-01\n", - " 1.88303621e-01 2.99382725e-01 2.14502277e-01 2.45652357e-01\n", - " 2.73798914e-01 2.12635491e-01 2.27147949e-01 1.92863365e-01\n", - " 2.53497643e-01 1.25612734e-01 3.01085414e-01 1.67810373e+00]\n", - "P_ = [-0.03241577 3.64670584 -0.00556023 1.74695959 0.04192234 0.91936744\n", - " 0.1291694 0.53847621 0.17769949 0.35614631 0.20140295 0.27251754\n", - " 0.23822093 0.23244561 0.25980362 0.20670385 0.23241789 0.17941324\n", - " 0.25825642 0.28086183 0.30108541 1.67810373]\n", - "Depth = 11, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.055994\n", - " Iterations: 980\n", - " Function evaluations: 1269\n", - "P = [-0.03412043 3.5147581 -0.0058505 1.77016383 0.04491813 0.80142144\n", - " 0.14922136 0.54187017 0.17641657 0.3677548 0.19335341 0.2965668\n", - " 0.24533807 0.25723394 0.25682131 0.20792119 0.21920932 0.16566856\n", - " 0.26242894 0.13395594 0.28933259 1.66454087]\n", - "P_ = [-0.03412043 3.5147581 -0.00842049 1.92876331 0.03568747 0.97755642\n", - " 0.12077502 0.61265688 0.1665274 0.43106948 0.18565485 0.32892498\n", - " 0.2169828 0.27868823 0.24951379 0.23930203 0.2465635 0.19639775\n", - " 0.22706743 0.15990263 0.26487473 0.27310002 0.28933259 1.66454087]\n", - "Depth = 12, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.008825\n", - " Iterations: 1543\n", - " Function evaluations: 1969\n", - "P = [-0.03101667 2.75307166 -0.01107415 2.34374848 0.04199272 0.83010474\n", - " 0.13568503 0.55729001 0.16608768 0.42684475 0.187568 0.32100935\n", - " 0.23007402 0.2673138 0.2524898 0.23440318 0.22362756 0.16410831\n", - " 0.24725649 0.17358521 0.28293575 0.12788628 0.33413827 1.63348285]\n", - "P_ = [-0.03101667 2.75307166 -0.01273603 2.37785874 0.03314824 1.08237869\n", - " 0.11226195 0.62549369 0.15595346 0.4703265 0.17861787 0.36510743\n", - " 0.20882101 0.29416158 0.23941393 0.25360105 0.24286905 0.21097156\n", - " 0.22953479 0.16647754 0.25320303 0.16596872 0.28720263 0.25335266\n", - " 0.33413827 1.63348285]\n", - "Depth = 13, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.938693\n", - " Iterations: 2937\n", - " Function evaluations: 3590\n", - "P = [-0.03628484 2.14197448 -0.01293879 3.01882066 0.05974369 0.80552014\n", - " 0.14459399 0.53738522 0.17934604 0.39915984 0.19263178 0.32097381\n", - " 0.21847428 0.26767754 0.26312314 0.2678607 0.2405102 0.18811057\n", - " 0.21548899 0.13567944 0.26897424 0.17838948 0.32492817 0.09171462\n", - " 0.33582409 1.64899863]\n", - "P_ = [-0.03628484 2.14197448 -0.01473464 2.95137096 0.04856177 1.14602791\n", - " 0.12501315 0.59926251 0.1686531 0.44169073 0.18752188 0.35104536\n", - " 0.20654697 0.29227582 0.23908144 0.26776207 0.25442585 0.23718757\n", - " 0.23281136 0.17197791 0.22783174 0.1455356 0.27758254 0.16505488\n", - " 0.32576631 0.2115057 0.33582409 1.64899863]\n", - "Depth = 14, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.913664\n", - " Iterations: 1005\n", - " Function evaluations: 1262\n", - "P = [-0.03628779 2.32213479 -0.01703396 2.81526406 0.05943649 0.75112158\n", - " 0.14159427 0.54666643 0.17454806 0.43917076 0.19553418 0.36710651\n", - " 0.21115097 0.30584078 0.22387343 0.27543116 0.24623894 0.25900387\n", - " 0.24120844 0.18622032 0.23074999 0.16228924 0.27227467 0.16606169\n", - " 0.32891508 0.12084948 0.29750781 1.65199617]\n", - "P_ = [-0.03628779 2.32213479 -0.01840923 2.78004054 0.04851214 1.04599908\n", - " 0.12398903 0.59047825 0.1651327 0.46988381 0.18803914 0.39284374\n", - " 0.20445806 0.33209752 0.2175122 0.29063597 0.23345865 0.26839089\n", - " 0.24444233 0.23300974 0.23822031 0.17938286 0.23964814 0.16309762\n", - " 0.28036616 0.15960281 0.32667171 0.2302171 0.29750781 1.65199617]\n", - "Depth = 15, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 1.867141\n", - " Iterations: 1573\n", - " Function evaluations: 1916\n", - "P = [-0.03451412 2.42095 -0.01962205 2.59804403 0.05622697 0.77520268\n", - " 0.13598588 0.58319477 0.16841185 0.4838587 0.1836264 0.41711945\n", - " 0.21033713 0.36200808 0.21324797 0.31091108 0.22214115 0.27726866\n", - " 0.24780904 0.24759211 0.23090912 0.18489114 0.24217022 0.17084863\n", - " 0.29518183 0.16840128 0.3087237 0.11241434 0.31968711 1.63462866]\n", - "P_ = [-0.03451412 2.42095 -0.02061485 2.58623776 0.04611377 1.0182482\n", - " 0.1200341 0.62159636 0.15976492 0.51034832 0.17855488 0.43936587\n", - " 0.19965284 0.38405263 0.21188958 0.33475634 0.21739812 0.29521128\n", - " 0.2324083 0.26539804 0.24217574 0.22669178 0.23391208 0.18114647\n", - " 0.25277254 0.17035916 0.29698741 0.16093635 0.3094546 0.21389529\n", - " 0.31968711 1.63462866]\n", - "Depth = 16, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.753269\n", - " Iterations: 1476\n", - " Function evaluations: 1822\n", - "P = [-0.02688897 2.43339141 -0.01960695 2.51113099 0.05658702 0.74562572\n", - " 0.1364889 0.59715617 0.1697219 0.50645489 0.17770437 0.45288418\n", - " 0.19601078 0.42673243 0.20663552 0.37730201 0.21056545 0.31008847\n", - " 0.23081484 0.28971244 0.23752724 0.22010441 0.22826869 0.18494123\n", - " 0.25725615 0.2008124 0.32565062 0.16926247 0.31380237 0.10502611\n", - " 0.38108794 1.63957688]\n", - "P_ = [-0.02688897 2.43339141 -0.02006207 2.50627226 0.04706278 0.96631388\n", - " 0.1215073 0.62499421 0.16141365 0.52913021 0.17520985 0.46962503\n", - " 0.18914588 0.43653934 0.20198719 0.39892782 0.20860048 0.34369524\n", - " 0.21942456 0.30117396 0.23333199 0.26360943 0.23463394 0.20911592\n", - " 0.23551556 0.18890902 0.27008011 0.19489679 0.32416958 0.16123293\n", - " 0.31800771 0.20093553 0.38108794 1.63957688]\n", - "Depth = 17, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.696714\n", - " Iterations: 1310\n", - " Function evaluations: 1592\n", - "P = [-0.02697511 2.45374481 -0.01778969 2.57838906 0.05170715 0.75355306\n", - " 0.12667622 0.61778864 0.16507375 0.53225188 0.17998968 0.48189939\n", - " 0.19269045 0.44450227 0.19723773 0.43032986 0.19999118 0.36405078\n", - " 0.2213966 0.32509554 0.23144466 0.29643002 0.22628906 0.20053403\n", - " 0.23302776 0.21387518 0.27475244 0.20879646 0.3505959 0.17363456\n", - " 0.31829343 0.10278884 0.38916659 1.63600554]\n", - "P_ = [-0.02697511 2.45374481 -0.01833001 2.57105705 0.04353105 0.96823965\n", - " 0.11344639 0.64174707 0.15603904 0.55237818 0.17560265 0.49670894\n", - " 0.18820783 0.45770125 0.19536532 0.43616556 0.19869544 0.39524093\n", - " 0.21006432 0.3457189 0.22553403 0.31329209 0.22962503 0.26258438\n", - " 0.22827103 0.2044579 0.24284533 0.21268019 0.28813658 0.20259142\n", - " 0.34679561 0.16529977 0.32246244 0.19297806 0.38916659 1.63600554]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.700418\n", - " Iterations: 1446\n", - " Function evaluations: 1755\n", - "P = [-0.02433242 2.36406299 -0.01827932 2.65138385 0.04857301 0.74395832\n", - " 0.11130444 0.61434671 0.1557804 0.53936889 0.18270202 0.49255703\n", - " 0.19679122 0.45738371 0.19730224 0.44630103 0.19711504 0.40092455\n", - " 0.2061532 0.36045106 0.21925634 0.33203276 0.24190457 0.29625039\n", - " 0.22132148 0.20484816 0.21887016 0.21088034 0.30084471 0.22606179\n", - " 0.34795681 0.18479396 0.33547119 0.13128822 0.37019227 1.6449465 ]\n", - "P_ = [-0.02433242 2.36406299 -0.0186156 2.63542158 0.04114497 0.95589449\n", - " 0.1008492 0.63594865 0.14589685 0.55603063 0.17522379 0.50556033\n", - " 0.19209482 0.46910815 0.19710351 0.45061096 0.19719824 0.42109187\n", - " 0.20163412 0.3806878 0.21197682 0.3478207 0.22806398 0.31811739\n", - " 0.23504354 0.26578298 0.22064056 0.20652376 0.23708673 0.21425399\n", - " 0.30869673 0.21918382 0.34656952 0.17884887 0.33740014 0.21538035\n", - " 0.37019227 1.6449465 ]\n", - "Depth = 19, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.658465\n", - " Iterations: 2557\n", - " Function evaluations: 3033\n", - "P = [-0.02575746 2.21717687 -0.01838126 3.01816501 0.0521693 0.80411717\n", - " 0.11119885 0.64065354 0.13659665 0.54288216 0.16344298 0.50274132\n", - " 0.19568507 0.46986216 0.2021096 0.44291399 0.19917464 0.41257309\n", - " 0.20198533 0.39279055 0.20793268 0.35491662 0.22772703 0.31004509\n", - " 0.23395852 0.26747493 0.20894229 0.20313014 0.25884682 0.22886244\n", - " 0.30202818 0.21893635 0.37230714 0.16857407 0.3073555 0.10736286\n", - " 0.41809479 1.65542005]\n", - "P_ = [-0.02575746 2.21717687 -0.01876948 2.97600774 0.04474292 1.03717484\n", - " 0.10187839 0.66646359 0.13124975 0.56346561 0.15637816 0.5133047\n", - " 0.18550336 0.48024506 0.19974267 0.45284226 0.20041041 0.4253482\n", - " 0.20065395 0.40216123 0.2048025 0.37485027 0.21626714 0.33602335\n", - " 0.23002284 0.29436135 0.22605866 0.24715552 0.22207506 0.2099018\n", - " 0.26793764 0.22677273 0.31312486 0.21098441 0.36547012 0.16213078\n", - " 0.31318388 0.18883955 0.41809479 1.65542005]\n", - "Depth = 20, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.669512\n", - " Iterations: 1233\n", - " Function evaluations: 1520\n", - "P = [-0.02724772 1.99756509 -0.01539743 3.11702001 0.04899521 0.91630836\n", - " 0.10243101 0.67712639 0.13226229 0.59349858 0.15401808 0.52198998\n", - " 0.18450784 0.50136424 0.20457034 0.46550388 0.20725972 0.41512531\n", - " 0.20139821 0.39329343 0.20822445 0.37781408 0.21808064 0.35104574\n", - " 0.23303508 0.29872359 0.23423768 0.26513109 0.20812136 0.22076268\n", - " 0.26716072 0.23848596 0.29909733 0.22314302 0.37247009 0.19429107\n", - " 0.31127378 0.12178015 0.39470398 1.66682694]\n", - "P_ = [-0.02724772 1.99756509 -0.01598994 3.06104726 0.04255595 1.13637953\n", - " 0.09441564 0.71300369 0.12629603 0.61022414 0.14857913 0.53986713\n", - " 0.17536091 0.50755197 0.19754846 0.47805501 0.20618396 0.43527674\n", - " 0.20403589 0.40311778 0.20481133 0.38555376 0.21265974 0.36576833\n", - " 0.22406241 0.33011688 0.23345599 0.28696621 0.22640278 0.25182057\n", - " 0.2228812 0.2251935 0.27354804 0.23541737 0.31010325 0.21881522\n", - " 0.36635046 0.18703998 0.31544529 0.19903249 0.39470398 1.66682694]\n", - "Depth = 21, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.711953\n", - " Iterations: 1026\n", - " Function evaluations: 1262\n", - "P = [-0.02746379 2.00567843 -0.0152244 3.21187228 0.04221286 0.93326026\n", - " 0.09793756 0.73130393 0.12185045 0.63488894 0.15110873 0.55297972\n", - " 0.17884155 0.50646303 0.20095824 0.4907572 0.21777119 0.43112917\n", - " 0.20634334 0.39493859 0.20327966 0.39093143 0.21566533 0.38841622\n", - " 0.22464344 0.3491417 0.23355948 0.29763454 0.23226896 0.26864625\n", - " 0.21713988 0.23095884 0.27100211 0.24589792 0.29985696 0.23014108\n", - " 0.36148439 0.18754278 0.33303916 0.12619172 0.36396645 1.66811906]\n", - "P_ = [-0.02746379 2.00567843 -0.01580723 3.15443448 0.03674264 1.15027093\n", - " 0.08997689 0.76015483 0.11729562 0.6532537 0.14414247 0.57248192\n", - " 0.17091789 0.51975351 0.19358601 0.49599247 0.21136626 0.45384461\n", - " 0.21124099 0.41044884 0.20473856 0.3928396 0.2091776 0.38973371\n", - " 0.21951309 0.37158429 0.22804003 0.32951993 0.23312931 0.28797178\n", - " 0.22794637 0.25787841 0.22996422 0.23451576 0.27649827 0.24289662\n", - " 0.30866088 0.22405561 0.35877532 0.18169982 0.33451189 0.19961683\n", - " 0.36396645 1.66811906]\n", - "Depth = 22, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.634557\n", - " Iterations: 4882\n", - " Function evaluations: 5664\n", - "P = [-0.02049957 2.39514716 -0.01697495 3.41852149 0.04711733 0.80340725\n", - " 0.08302978 0.79122195 0.11287414 0.59372405 0.14969399 0.50602187\n", - " 0.18797809 0.46350217 0.20473096 0.41471257 0.22267763 0.40201489\n", - " 0.22843329 0.37701287 0.22010171 0.33792612 0.21113284 0.34746709\n", - " 0.22347579 0.35132149 0.2372241 0.30901422 0.23096484 0.25543285\n", - " 0.22839545 0.23263418 0.25004341 0.26128318 0.28622426 0.23259384\n", - " 0.33440773 0.20573792 0.35942411 0.14162933 0.32677218 0.10636337\n", - " 0.40416233 1.64374972]\n", - "P_ = [-0.02049957 2.39514716 -0.01713516 3.37200448 0.04129076 1.04114491\n", - " 0.07813263 0.79288359 0.1074479 0.62963276 0.14132584 0.52595418\n", - " 0.17753697 0.47509845 0.1994005 0.43023654 0.21615157 0.40663223\n", - " 0.2260787 0.38724097 0.22388879 0.35569283 0.21561727 0.34269661\n", - " 0.21674327 0.34921909 0.2291001 0.33401397 0.234948 0.28953009\n", - " 0.23014731 0.24817873 0.23429944 0.24044754 0.25826633 0.25476287\n", - " 0.29498489 0.22771094 0.33781905 0.19699584 0.35645575 0.13842333\n", - " 0.33028991 0.17624457 0.40416233 1.64374972]\n", - "Depth = 23, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 1.598394\n", - " Iterations: 1465\n", - " Function evaluations: 1784\n", - "P = [-0.02000621 2.44560874 -0.01784025 3.40429038 0.04034439 0.82029471\n", - " 0.07052689 0.82557495 0.10936863 0.63168034 0.14547781 0.51719456\n", - " 0.17739072 0.48024893 0.20260839 0.45044984 0.21350651 0.40565543\n", - " 0.22487785 0.39306146 0.22549623 0.34085839 0.21692672 0.34258676\n", - " 0.21817981 0.36260049 0.23270822 0.33571342 0.23382156 0.2993497\n", - " 0.23052597 0.27182952 0.23512792 0.23331897 0.24260702 0.27073483\n", - " 0.29124441 0.22340082 0.3555559 0.22539837 0.35923015 0.13343106\n", - " 0.3302897 0.12659439 0.44406317 1.64326214]\n", - "P_ = [-0.02000621 2.44560874 -0.01793442 3.36260857 0.03528486 1.04498998\n", - " 0.06659005 0.82488622 0.10261355 0.66540114 0.13762799 0.54208278\n", - " 0.16906561 0.48988692 0.19493345 0.45951913 0.20971586 0.4212361\n", - " 0.2204282 0.39798953 0.22522737 0.36355538 0.22102518 0.34176015\n", - " 0.21752602 0.35215854 0.22449651 0.35091046 0.23314388 0.32148414\n", - " 0.23267527 0.28977746 0.23192657 0.26010892 0.23707899 0.24307963\n", - " 0.25318036 0.26044483 0.30242902 0.22374822 0.35603515 0.21340263\n", - " 0.35671359 0.13283657 0.33523637 0.19253647 0.44406317 1.64326214]\n", - "Depth = 24, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.607283\n", - " Iterations: 1544\n", - " Function evaluations: 1858\n", - "P = [-0.02084561 2.43874576 -0.01835448 3.40920896 0.03546675 0.90836324\n", - " 0.0655526 0.87964144 0.10703554 0.68578757 0.14017615 0.53607742\n", - " 0.16338687 0.49307777 0.19248543 0.47399779 0.21262343 0.43097219\n", - " 0.21352896 0.38233588 0.23451879 0.35674195 0.2239305 0.32587753\n", - " 0.21734294 0.34396471 0.22930924 0.36701272 0.23284976 0.31343785\n", - " 0.23348864 0.28512493 0.23755924 0.28226763 0.22677397 0.23504116\n", - " 0.23854138 0.2807881 0.29671851 0.22673127 0.36623274 0.22358179\n", - " 0.36695145 0.13948788 0.33037755 0.14864504 0.45216262 1.64789481]\n", - "P_ = [-0.02084561 2.43874576 -0.01845828 3.368773 0.03098165 1.11676705\n", - " 0.06179187 0.88323167 0.10012172 0.71809655 0.13327185 0.56726704\n", - " 0.15758419 0.50382768 0.18399835 0.47956278 0.20591077 0.44531406\n", - " 0.21318939 0.4005745 0.22577303 0.36740609 0.22878347 0.34002372\n", - " 0.22063672 0.33492112 0.22282749 0.35452838 0.23078445 0.34468985\n", - " 0.23308934 0.3028205 0.23484551 0.2841725 0.23441354 0.26849324\n", - " 0.22971582 0.2464779 0.25066161 0.26952626 0.30830422 0.22620636\n", - " 0.36632258 0.21307005 0.36390363 0.14025098 0.33545193 0.21111378\n", - " 0.45216262 1.64789481]\n", - "Depth = 25, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.581795\n", - " Iterations: 2372\n", - " Function evaluations: 2819\n", - "P = [-0.02236661 2.35354548 -0.02684511 3.29209127 0.0378308 0.99211339\n", - " 0.05779907 0.94396444 0.09862728 0.73124698 0.13492528 0.56450082\n", - " 0.15875125 0.48108148 0.17992014 0.44849735 0.20768467 0.43777685\n", - " 0.21626184 0.41185427 0.22984173 0.38387146 0.23217654 0.35308279\n", - " 0.21278958 0.31580261 0.21990847 0.36139642 0.23264446 0.35282069\n", - " 0.23449629 0.29697665 0.23015648 0.28272121 0.23092942 0.2613633\n", - " 0.23285444 0.25032323 0.26320919 0.26748003 0.33110673 0.22271472\n", - " 0.34889385 0.20652037 0.37504619 0.14920041 0.33808295 0.10589318\n", - " 0.4288745 1.63601996]\n", - "P_ = [-0.02236661 2.35354548 -0.02666597 3.25454944 0.03265672 1.17611162\n", - " 0.05540288 0.94974232 0.09209476 0.76528177 0.12766568 0.59785005\n", - " 0.15303302 0.50110212 0.17399285 0.4576209 0.19880002 0.44120741\n", - " 0.21317406 0.4211864 0.22440977 0.39506459 0.23114922 0.36662981\n", - " 0.22209532 0.3336971 0.21620665 0.33768764 0.22551231 0.3576231\n", - " 0.23338519 0.33048308 0.23293396 0.29184469 0.23040382 0.27588668\n", - " 0.23146842 0.25827208 0.24013958 0.25444086 0.2767887 0.25852697\n", - " 0.33395267 0.22012362 0.35203213 0.19964198 0.37208913 0.14573583\n", - " 0.34171462 0.16709825 0.4288745 1.63601996]\n", - "Depth = 26, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.587271\n", - " Iterations: 1186\n", - " Function evaluations: 1477\n", - "P = [-0.02321478 2.04490615 -0.02710706 3.25048164 0.03379874 1.13376396\n", - " 0.05834127 0.99328434 0.08897425 0.74469425 0.12924972 0.5991745\n", - " 0.15471539 0.49191952 0.17526013 0.45358262 0.19549947 0.4309731\n", - " 0.21407721 0.43429084 0.22605326 0.39583341 0.23006357 0.36481878\n", - " 0.22491532 0.34183053 0.21636425 0.33747474 0.22651776 0.36546098\n", - " 0.23110602 0.33280761 0.23480582 0.29162047 0.22540002 0.26990847\n", - " 0.23216774 0.26147147 0.23824841 0.25726114 0.28471868 0.26513549\n", - " 0.32859875 0.23182145 0.36555035 0.21786037 0.36798384 0.1495139\n", - " 0.332202 0.13131401 0.42485012 1.64782433]\n", - "P_ = [-0.02321478 2.04490615 -0.02695736 3.20411335 0.02911368 1.29658839\n", - " 0.05550944 1.00949352 0.08426148 0.78293888 0.12150443 0.62715907\n", - " 0.14883869 0.51667067 0.16972885 0.46390409 0.18927198 0.43792987\n", - " 0.20764645 0.43314239 0.22144709 0.41062473 0.2283669 0.37794036\n", - " 0.22729144 0.35244049 0.22063978 0.33965263 0.22105048 0.35039147\n", - " 0.22845895 0.35164609 0.23252902 0.3169664 0.23154997 0.28410478\n", - " 0.2274824 0.26731247 0.23380484 0.26033792 0.24897232 0.2590783\n", - " 0.29315715 0.25872895 0.33428361 0.22967359 0.36583114 0.20997424\n", - " 0.36523139 0.14811391 0.33576539 0.18964133 0.42485012 1.64782433]\n", - "Depth = 27, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.582014\n", - " Iterations: 1431\n", - " Function evaluations: 1751\n", - "P = [-0.02316618 1.93569825 -0.02976941 3.24903905 0.03183005 1.24987934\n", - " 0.05707132 1.03864388 0.08075369 0.78762169 0.12661182 0.6216942\n", - " 0.1507326 0.52364065 0.16935143 0.45952614 0.18292384 0.44367315\n", - " 0.20337461 0.42742464 0.22099368 0.42609733 0.23137973 0.37700263\n", - " 0.22479455 0.35103305 0.22532569 0.340989 0.22512424 0.344381\n", - " 0.22899808 0.35275458 0.22741522 0.32654925 0.22724163 0.29997035\n", - " 0.2259396 0.26942463 0.23366679 0.25899036 0.2410652 0.26564907\n", - " 0.2915167 0.27333154 0.32433052 0.24024394 0.3652893 0.21758507\n", - " 0.36674424 0.15867741 0.33207149 0.13130632 0.41815479 1.65170725]\n", - "P_ = [-0.02316618 1.93569825 -0.02952485 3.2003968 0.02726713 1.39796525\n", - " 0.05426673 1.06211449 0.07724519 0.82481016 0.11811957 0.65242151\n", - " 0.14537242 0.54543033 0.16452432 0.47614842 0.17890239 0.44837033\n", - " 0.19655769 0.43284081 0.2144681 0.42658893 0.22714838 0.39700418\n", - " 0.22772129 0.36257509 0.22506996 0.34582503 0.2252287 0.34262219\n", - " 0.22684595 0.34810259 0.22835321 0.34207833 0.22735093 0.31670521\n", - " 0.22680762 0.28978844 0.22822914 0.26633299 0.2355849 0.26071669\n", - " 0.25227665 0.26735628 0.29759333 0.26720421 0.33039849 0.23688707\n", - " 0.36545096 0.21103978 0.36417589 0.15664992 0.33525976 0.18761747\n", - " 0.41815479 1.65170725]\n", - "Depth = 28, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.596813\n", - " Iterations: 1449\n", - " Function evaluations: 1749\n", - "P = [-0.02402328 1.8818008 -0.03011979 3.21210521 0.02836255 1.38924114\n", - " 0.05338244 1.05219267 0.0789796 0.82050131 0.12120769 0.64471737\n", - " 0.14739769 0.54287382 0.16596387 0.49056795 0.17800419 0.44396589\n", - " 0.19216013 0.43362782 0.21478978 0.42231406 0.22739956 0.40960118\n", - " 0.23006488 0.36992998 0.22278261 0.34343901 0.22878983 0.34068132\n", - " 0.22979723 0.34656274 0.22798467 0.34547452 0.22235084 0.32254385\n", - " 0.22672018 0.30843269 0.22856516 0.26424358 0.22870121 0.26232185\n", - " 0.2473817 0.26957114 0.29755342 0.28324006 0.32023897 0.24133007\n", - " 0.35949059 0.21496953 0.37023515 0.16454514 0.33578396 0.12959862\n", - " 0.38776487 1.6522515 ]\n", - "P_ = [-0.02402328 1.8818008 -0.02990206 3.16459434 0.02418524 1.51944571\n", - " 0.05070174 1.088305 0.07532286 0.85360008 0.11366696 0.67610736\n", - " 0.14178554 0.56469744 0.16132233 0.50364441 0.1745641 0.45728076\n", - " 0.18761001 0.43695077 0.20670776 0.42635469 0.22244572 0.41459553\n", - " 0.2289226 0.38693192 0.22616367 0.35573839 0.22578622 0.34206016\n", - " 0.22925755 0.34341198 0.22902042 0.34609636 0.22577138 0.33646604\n", - " 0.22391132 0.31750415 0.22731321 0.29422905 0.22860404 0.26369451\n", - " 0.23337134 0.26413417 0.25813279 0.27250019 0.30160441 0.27575613\n", - " 0.32584635 0.23756428 0.36064179 0.20956692 0.36777435 0.16204896\n", - " 0.33764042 0.18397908 0.38776487 1.6522515 ]\n", - "Depth = 29, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 1.587723\n", - " Iterations: 1419\n", - " Function evaluations: 1702\n", - "P = [-0.02885553 1.80817009 -0.03049418 3.2018107 0.02515452 1.51365906\n", - " 0.04614088 1.08643008 0.07605223 0.82137559 0.11502419 0.65738081\n", - " 0.14142941 0.56242516 0.16043238 0.52008539 0.17719521 0.4772555\n", - " 0.1896834 0.43680861 0.20061797 0.41770539 0.22309712 0.41138228\n", - " 0.22745693 0.39049764 0.22566858 0.35500765 0.22829773 0.34954733\n", - " 0.23408263 0.3343646 0.22968824 0.35147772 0.2251037 0.33338101\n", - " 0.22369287 0.32080797 0.2264321 0.29970441 0.22382903 0.25433176\n", - " 0.22341417 0.26534217 0.27028096 0.28240796 0.31458229 0.29396625\n", - " 0.3378527 0.23560899 0.3631095 0.20214883 0.37926158 0.17011469\n", - " 0.34178245 0.12358539 0.37783878 1.64532461]\n", - "P_ = [-0.02885553 1.80817009 -0.03043768 3.15375413 0.02131668 1.63008331\n", - " 0.04396988 1.13062618 0.07192653 0.85793483 0.10830489 0.68565577\n", - " 0.13596626 0.58207116 0.15584546 0.53030534 0.17257098 0.48907065\n", - " 0.18580775 0.4493611 0.19684743 0.42429271 0.21457055 0.4137807\n", - " 0.22565287 0.39913956 0.22647026 0.37091696 0.22702849 0.35218335\n", - " 0.23109044 0.34221774 0.23211273 0.342036 0.22779119 0.34398943\n", - " 0.22456856 0.32861193 0.22463743 0.31353088 0.22562425 0.28562324\n", - " 0.22371458 0.25736912 0.23472684 0.2694615 0.27944675 0.28479933\n", - " 0.31859443 0.28390465 0.3413364 0.23099379 0.3647804 0.19883495\n", - " 0.37667682 0.16690577 0.34302577 0.17605916 0.37783878 1.64532461]\n", - "Depth = 30, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.572005\n", - " Iterations: 1325\n", - " Function evaluations: 1612\n", - "1.3571428571428572 [7.7041625 6.39747079 5.45219263 4.57351163 4.10959139 3.74436665\n", - " 2.82278187 2.54003724 2.39856853 2.17685574 2.05599426 2.00882473\n", - " 1.93869315 1.91366429 1.86714097 1.75326851 1.69671438 1.70041763\n", - " 1.65846471 1.66951224 1.71195268 1.63455668 1.59839384 1.60728293\n", - " 1.5817952 1.58727145 1.58201417 1.59681334 1.58772315 1.57200466]\n", - "[[6.57155339 5.94790512 4.51084725 5.48476219 4.44827696 4.07086367\n", - " 4.45993119 3.76473244 3.75245393 3.70383406 2.54453644 2.75335922\n", - " 3.72365101 2.64914745 3.66152866 3.41308183 2.17660478 2.18383796\n", - " 2.54980097 1.72430929 2.24071873 1.8353618 2.04963403 1.97768311\n", - " 2.25839296 2.22977067 1.94603139 2.05226045 2.69504832 3.27724127]\n", - " [7.58106801 6.81608452 4.28714233 4.07123972 3.27046962 3.23940109\n", - " 3.69518164 3.2411352 2.8435791 2.91039551 2.52147765 2.7118309\n", - " 2.7196728 2.5657514 2.49654928 2.14986169 2.03773181 1.96011255\n", - " 1.99818881 1.99560667 2.10966328 1.86491841 1.83579189 1.98703992\n", - " 1.98133515 1.95306622 1.90928783 1.85507609 1.79545032 1.7963689 ]\n", - " [5.67675131 4.71392584 4.01740509 3.36995594 3.02811997 2.75900701\n", - " 2.07994453 1.87160639 1.76736629 1.60399896 1.51494314 1.48018664\n", - " 1.42851074 1.41006842 1.37578808 1.29188206 1.25021059 1.25293931\n", - " 1.22202663 1.23016691 1.26143882 1.20441019 1.17776388 1.18431374\n", - " 1.16553331 1.16956844 1.16569465 1.17659931 1.16990127 1.15831922]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]] [1.98293727 1.74779155 1.28153947 1.29259579 1.07468666 1.00692718\n", - " 1.02350574 0.8877474 0.83633993 0.82182285 0.65809572 0.69453768\n", - " 0.78718346 0.66249673 0.7533866 0.68548256 0.54645472 0.53968898\n", - " 0.57700164 0.49500829 0.56118208 0.49046904 0.50631898 0.51490368\n", - " 0.54052614 0.53524053 0.50210139 0.50839358 0.56603999 0.62319294]\n", - "[[0.1749857 0.07463194 0.26530491 0.16394175 0.18892849 0.25701077\n", - " 0.24542951 0.40504394 0.18547862 0.24113788 0.62032714 0.68408453\n", - " 0.11521194 0.57930818 0.29653581 0.32221821 0.75779012 0.76858176\n", - " 0.59269399 0.8271978 0.69201592 0.87101232 0.79114835 0.72852071\n", - " 0.64433266 0.66377712 0.77675308 0.72982301 0.58648573 0.44154865]\n", - " [0.17669094 0.20818569 0.40598211 0.40456531 0.54848127 0.5337594\n", - " 0.48446167 0.53759304 0.60295388 0.58451793 0.64895146 0.66165701\n", - " 0.62972457 0.66201878 0.67281148 0.75627098 0.78514972 0.80366385\n", - " 0.79430362 0.79961314 0.7524382 0.82370466 0.83214203 0.78138294\n", - " 0.78255631 0.78124579 0.80687807 0.80774629 0.84561002 0.84356134]\n", - " [0.1977358 0.23204622 0.30938238 0.39342279 0.41016143 0.46245125\n", - " 0.76102816 0.79966194 0.84980142 0.9167973 0.93013476 0.94105633\n", - " 0.96019643 0.9567664 0.95781341 0.97258171 0.97672161 0.97483651\n", - " 0.98345276 0.97827363 0.97171746 0.98525476 0.99020549 0.988242\n", - " 0.99105685 0.98789452 0.98718377 0.98332188 0.98342322 0.98330761]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]] [0.05494124 0.05148638 0.09806694 0.09619298 0.11475712 0.12532214\n", - " 0.14909193 0.17422989 0.16382339 0.17424531 0.21994134 0.22867979\n", - " 0.17051329 0.21980934 0.19271607 0.20510709 0.25196614 0.25470821\n", - " 0.23704504 0.26050846 0.24161716 0.26799717 0.26134959 0.24981456\n", - " 0.24179458 0.24329174 0.25708149 0.25208912 0.2415519 0.22684176]\n", - "\n", - "Now using 3 solutions, set number 5\n", - "Calculating energy landscape ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 11.451335\n", - " Iterations: 27\n", - " Function evaluations: 55\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 11.451335\n", - " Iterations: 11\n", - " Function evaluations: 25\n", - "P = [3.08521663 2.30087987]\n", - "P_ = [3.08521663 2.30087987 3.08521663 2.30087987]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 9.806289\n", - " Iterations: 45\n", - " Function evaluations: 86\n", - "P = [2.91190868 2.46597684 3.32287769 2.13831951]\n", - "P_ = [2.91190868 2.46597684 3.11739318 2.30214817 3.32287769 2.13831951]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 10.533044\n", - " Iterations: 136\n", - " Function evaluations: 225\n", - "P = [2.90001774 2.41624234 3.10724819 1.62572087 3.44990154 2.35699585]\n", - "P_ = [2.90001774 2.41624234 3.03817137 1.88922803 3.22146597 1.8694792\n", - " 3.44990154 2.35699585]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 8.763220\n", - " Iterations: 139\n", - " Function evaluations: 222\n", - "P = [2.86109423 2.54645386 3.16275491 2.03578163 3.25176739 1.8946006\n", - " 3.472158 2.0009374 ]\n", - "P_ = [2.86109423 2.54645386 3.08733974 2.16344969 3.20726115 1.96519111\n", - " 3.30686504 1.9211848 3.472158 2.0009374 ]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 8.910818\n", - " Iterations: 474\n", - " Function evaluations: 694\n", - "P = [2.95601681 2.08727242 3.27530825 1.79821511 3.35075119 1.93481944\n", - " 3.27336446 1.77300067 3.40424406 2.68637854]\n", - "P_ = [2.95601681 2.08727242 3.21144996 1.85602657 3.32057401 1.88017771\n", - " 3.3197965 1.87009193 3.29954038 1.95567624 3.40424406 2.68637854]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 12.185555\n", - " Iterations: 129\n", - " Function evaluations: 211\n", - "P = [2.93805202 2.04558542 3.13408923 1.8532145 3.36320059 1.8930127\n", - " 3.30468092 1.88355707 3.34957608 1.96735084 3.44658902 2.76096167]\n", - "P_ = [2.93805202 2.04558542 3.10141636 1.88527632 3.28683013 1.87974663\n", - " 3.33394075 1.88828489 3.31964597 1.91148833 3.3657449 2.09961932\n", - " 3.44658902 2.76096167]\n", - "Depth = 7, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 8.134716\n", - " Iterations: 806\n", - " Function evaluations: 1097\n", - "P = [2.98444318 2.14367178 3.13370335 2.07163579 3.18746612 1.76295608\n", - " 3.43773512 1.76046045 3.30927243 1.84644967 3.4004184 2.00468674\n", - " 3.47923019 2.96528566]\n", - "P_ = [2.98444318 2.14367178 3.11238046 2.08192664 3.17210533 1.85115028\n", - " 3.33047698 1.76153001 3.38267968 1.79731298 3.33531413 1.89166026\n", - " 3.41167723 2.14191516 3.47923019 2.96528566]\n", - "Depth = 8, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 7.775011\n", - " Iterations: 534\n", - " Function evaluations: 751\n", - "P = [2.91416364 2.32036053 3.09977383 2.07221835 3.14096364 1.95063983\n", - " 3.41259475 1.85366391 3.48844789 1.82762242 3.35697184 1.6045542\n", - " 3.36598 2.31315988 3.36728379 2.85009801]\n", - "P_ = [2.91416364 2.32036053 3.07657256 2.10323612 3.13066619 1.98103446\n", - " 3.31073309 1.89002988 3.45052132 1.84064317 3.43914437 1.74397184\n", - " 3.35922388 1.78170562 3.36614298 2.38027715 3.36728379 2.85009801]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 9.349738\n", - " Iterations: 472\n", - " Function evaluations: 653\n", - "P = [2.97452307 2.28307824 3.05463831 2.05110476 3.10403167 2.02315527\n", - " 3.28956364 1.86076572 3.44643186 1.9854092 3.49181655 1.78416548\n", - " 3.16629169 1.84788225 3.3636984 2.19315848 3.39499104 2.9419843 ]\n", - "P_ = [2.97452307 2.28307824 3.04573662 2.07687959 3.09305537 2.02936626\n", - " 3.22771965 1.91489557 3.37671265 1.9300121 3.46660283 1.89596755\n", - " 3.38330827 1.8054044 3.21015985 1.9246103 3.36717536 2.27636135\n", - " 3.39499104 2.9419843 ]\n", - "Depth = 10, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 9.520713\n", - " Iterations: 315\n", - " Function evaluations: 458\n", - "P = [2.98612165 2.31344952 3.1105312 2.08376775 3.10335693 2.03423957\n", - " 3.21390721 1.86260927 3.38475199 1.91117579 3.55463316 1.8576119\n", - " 3.4170855 1.84982423 3.23484256 1.88530794 3.43129138 2.28853063\n", - " 3.37765235 2.94062681]\n", - "P_ = [2.98612165 2.31344952 3.09809025 2.10673592 3.10479178 2.0441452\n", - " 3.18074213 1.91409836 3.31641408 1.89174918 3.46969258 1.88439385\n", - " 3.4996141 1.85449683 3.36241262 1.86046934 3.27413232 1.96595247\n", - " 3.42592748 2.35374025 3.37765235 2.94062681]\n", - "Depth = 11, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 8.842739\n", - " Iterations: 1543\n", - " Function evaluations: 1996\n", - "P = [2.79536749 2.71170747 3.16630131 2.06958187 3.13282183 1.98565641\n", - " 3.1777423 1.8763146 3.2978382 1.81355554 3.49074091 1.96339907\n", - " 3.51659964 1.73698581 3.38233797 1.87336464 3.29534024 2.00205033\n", - " 3.49044054 2.55482997 3.34813682 2.58235817]\n", - "P_ = [2.79536749 2.71170747 3.13258005 2.12795692 3.13890901 2.00091559\n", - " 3.16549126 1.90613509 3.25416696 1.83637702 3.40305786 1.89528837\n", - " 3.50249488 1.86048395 3.46777722 1.78657811 3.35861132 1.90846074\n", - " 3.33081302 2.10255572 3.47750384 2.55733253 3.34813682 2.58235817]\n", - "Depth = 12, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 6.263770\n", - " Iterations: 1531\n", - " Function evaluations: 1957\n", - "P = [2.7912182 2.68635951 3.08564823 1.93934487 3.08552182 1.74976578\n", - " 3.22708212 2.08433416 3.2375635 2.02354069 3.41644311 1.74882339\n", - " 3.49583235 1.92747205 3.48207766 1.74580411 3.3926451 1.94192349\n", - " 3.36003959 2.25588281 3.44116219 2.50995856 3.36082022 2.68464215]\n", - "P_ = [2.7912182 2.68635951 3.06111239 2.00159609 3.08554289 1.78136229\n", - " 3.19169204 2.00069206 3.23406971 2.04380518 3.34190994 1.86328893\n", - " 3.45613773 1.83814772 3.49010123 1.85177707 3.45226681 1.81117724\n", - " 3.38449372 2.02041332 3.37356003 2.29822877 3.43446703 2.52451552\n", - " 3.36082022 2.68464215]\n", - "Depth = 13, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.422921\n", - " Iterations: 1865\n", - " Function evaluations: 2403\n", - "P = [2.82195581 2.57800214 3.0207272 2.11537047 3.06687787 2.1290034\n", - " 3.23092286 2.15409133 3.04187049 2.09770281 3.36184631 1.68753009\n", - " 3.50197132 1.73449741 3.52086121 1.82654902 3.46820345 1.8970149\n", - " 3.35025612 2.1218193 3.35422872 2.22760719 3.41091586 2.5361529\n", - " 3.34053721 2.57912106]\n", - "P_ = [2.82195581 2.57800214 3.0054371 2.15095752 3.05977777 2.12690603\n", - " 3.19306632 2.14830181 3.10004045 2.11505313 3.23877869 1.84528883\n", - " 3.43729824 1.71282018 3.51068973 1.77698277 3.50060823 1.85365128\n", - " 3.43191197 1.96618548 3.35117287 2.14623189 3.36294982 2.27507576\n", - " 3.40550212 2.53945815 3.34053721 2.57912106]\n", - "Depth = 14, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.795204\n", - " Iterations: 1478\n", - " Function evaluations: 1879\n", - "P = [2.83328216 2.75155848 3.09697108 2.07606514 3.0882838 2.26820003\n", - " 3.23867304 2.16901332 3.10463601 2.1093688 3.25069502 1.73089048\n", - " 3.41562736 1.79762374 3.5360602 1.69359247 3.53892841 1.86632747\n", - " 3.33799554 1.9488483 3.34912199 2.31429637 3.33075549 2.2415262\n", - " 3.37155085 2.50211557 3.34837119 2.6640699 ]\n", - "P_ = [2.83328216 2.75155848 3.07813616 2.12431466 3.08952484 2.24075219\n", - " 3.20644677 2.19026762 3.14293231 2.12641009 3.19853109 1.86606131\n", - " 3.34494207 1.76902377 3.47584378 1.74560811 3.53728943 1.76762176\n", - " 3.46716667 1.8957992 3.34117452 2.05326204 3.34518631 2.29870276\n", - " 3.3365834 2.27875325 3.36989516 2.51368373 3.34837119 2.6640699 ]\n", - "Depth = 15, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.631584\n", - " Iterations: 1024\n", - " Function evaluations: 1356\n", - "P = [2.86208132 2.74319562 3.21081664 2.19787454 3.05719546 2.21141766\n", - " 3.22759994 2.18098637 3.13879829 2.07207837 3.20923241 2.00716935\n", - " 3.34844587 1.70929141 3.43790532 1.76954837 3.55046768 1.88310214\n", - " 3.47373161 1.84861556 3.29724079 1.97962834 3.29665105 2.32917617\n", - " 3.30298491 2.12267789 3.35777278 2.4313246 3.29728934 2.88955848]\n", - "P_ = [2.86208132 2.74319562 3.18756762 2.23422928 3.07767829 2.20961191\n", - " 3.19351904 2.18707263 3.16247873 2.1011205 3.18575437 2.02880569\n", - " 3.29276048 1.82844259 3.39615757 1.74142846 3.49043442 1.82254013\n", - " 3.51977325 1.86930751 3.41490133 1.89228649 3.29708353 2.07284109\n", - " 3.29791782 2.28787652 3.31028996 2.16383079 3.35374055 2.46187353\n", - " 3.29728934 2.88955848]\n", - "Depth = 16, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 7.391752\n", - " Iterations: 755\n", - " Function evaluations: 1035\n", - "P = [2.86315177 2.76698977 3.16494429 2.31049765 3.05251482 2.21901016\n", - " 3.2435565 2.14565012 3.16732396 2.12878332 3.20665824 2.01386429\n", - " 3.33499753 1.85882518 3.37669425 1.75146928 3.61871801 1.852192\n", - " 3.57701 1.88768308 3.3714069 1.75657008 3.34084947 2.13647229\n", - " 3.22046371 2.25210266 3.29054018 2.14345093 3.34944257 2.45543771\n", - " 3.28989072 2.80567541]\n", - "P_ = [2.86315177 2.76698977 3.14608226 2.33902841 3.0665685 2.2304461\n", - " 3.20773619 2.15940513 3.18638209 2.13300002 3.19436628 2.04977649\n", - " 3.2868703 1.91696485 3.35845193 1.79843749 3.49770613 1.80183064\n", - " 3.60047076 1.86771935 3.49990883 1.83851571 3.3618577 1.87528952\n", - " 3.31075303 2.16537988 3.23360305 2.23173046 3.29790298 2.18244928\n", - " 3.34572058 2.47732756 3.28989072 2.80567541]\n", - "Depth = 17, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 6.689906\n", - " Iterations: 1298\n", - " Function evaluations: 1677\n", - "P = [2.85988187 2.8742945 3.17971561 2.49092757 3.04205951 2.21824907\n", - " 3.26663474 2.10379433 3.20400607 2.14898625 3.13650748 1.89416232\n", - " 3.27754717 1.80083777 3.27462934 1.77007821 3.54690226 1.77986225\n", - " 3.68645027 1.7926078 3.52489138 1.83164933 3.3546824 1.90631925\n", - " 3.33401148 2.23771253 3.29205119 2.29327575 3.31451466 2.17920546\n", - " 3.34855455 2.46049688 3.28831492 2.96953671]\n", - "P_ = [2.85988187 2.8742945 3.16090186 2.51347857 3.05825435 2.25032889\n", - " 3.22700382 2.12399222 3.21874223 2.13835286 3.15636001 1.96911054\n", - " 3.22776846 1.83377585 3.2758308 1.78274391 3.41877383 1.775258\n", - " 3.61257191 1.78586016 3.61992602 1.80868372 3.46481762 1.85800342\n", - " 3.34860271 2.00378786 3.32413847 2.25078623 3.29601533 2.2731457\n", - " 3.31851935 2.21229857 3.34501104 2.4904404 3.28831492 2.96953671]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.171921\n", - " Iterations: 2039\n", - " Function evaluations: 2533\n", - "P = [2.90715935 2.89829194 3.17952887 2.42048525 3.05500074 2.3887938\n", - " 3.24581189 1.98936494 3.21701062 2.13310344 3.1953567 1.89979448\n", - " 3.2635553 1.77019499 3.28018457 1.84654115 3.41576331 1.78114825\n", - " 3.58521803 1.83664321 3.56431672 1.85550581 3.42361496 1.89189123\n", - " 3.41461094 2.05324457 3.34241937 2.27934912 3.33839563 2.44659623\n", - " 3.31446665 2.19228947 3.37297338 2.49427285 3.29160985 2.66024442]\n", - "P_ = [2.90715935 2.89829194 3.16439723 2.44703007 3.0688372 2.39231508\n", - " 3.21401003 2.05593642 3.2234109 2.10116155 3.20137168 1.96460252\n", - " 3.24082243 1.81339482 3.27371763 1.81685098 3.3555061 1.81021176\n", - " 3.50049067 1.80889573 3.57592856 1.84502659 3.50959937 1.86965569\n", - " 3.42061362 1.94567567 3.39455772 2.11605139 3.3415252 2.31651514\n", - " 3.33440746 2.40421177 3.3209674 2.22584318 3.36845319 2.5034935\n", - " 3.29160985 2.66024442]\n", - "Depth = 19, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.085717\n", - " Iterations: 1680\n", - " Function evaluations: 2117\n", - "P = [2.90822856 3.00157813 3.15658165 2.44348088 3.08908887 2.42485969\n", - " 3.21774618 2.06031888 3.26147283 2.01263786 3.19370622 1.95629994\n", - " 3.27876934 1.81919595 3.17081312 1.68913624 3.30988041 1.9397193\n", - " 3.48441105 1.85023305 3.57363387 1.99815289 3.47943911 1.88634998\n", - " 3.4449626 1.85746896 3.37608645 2.12124776 3.35815269 2.23294388\n", - " 3.36948785 2.3793463 3.30711697 2.37274746 3.39644755 2.49725524\n", - " 3.28522323 2.65531481]\n", - "P_ = [2.90822856 3.00157813 3.14351044 2.47285442 3.09619337 2.42681982\n", - " 3.19743187 2.11787795 3.25226722 2.02267597 3.21153954 1.97112571\n", - " 3.2519073 1.86249195 3.21058646 1.73705297 3.25132576 1.83421064\n", - " 3.40173865 1.89262127 3.52667449 1.92030034 3.53397292 1.95107798\n", - " 3.46673724 1.87570961 3.42321224 1.94076753 3.37136704 2.15064148\n", - " 3.36053904 2.26376544 3.35963982 2.37830437 3.31652019 2.38585354\n", - " 3.39059364 2.50557416 3.28522323 2.65531481]\n", - "Depth = 20, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.949543\n", - " Iterations: 2337\n", - " Function evaluations: 2862\n", - "P = [2.90058718 2.89628455 3.12835271 2.58739725 3.06076734 2.44036749\n", - " 3.22877323 2.0521967 3.26348481 2.05617373 3.19160917 1.88893923\n", - " 3.24675404 1.84966516 3.241836 1.82870737 3.27262236 1.86899202\n", - " 3.41222547 1.97788664 3.58580424 1.91310318 3.52493501 2.06116908\n", - " 3.4799392 1.91522256 3.40933037 1.95415894 3.21695305 1.90806292\n", - " 3.36006203 2.25818036 3.37002172 2.48237415 3.30112293 2.32031903\n", - " 3.40322828 2.40750951 3.30357688 2.71960626]\n", - "P_ = [2.90058718 2.89628455 3.11696443 2.60284161 3.06752588 2.45507047\n", - " 3.20357235 2.11042231 3.25654249 2.05537832 3.20957808 1.93074785\n", - " 3.23021058 1.86144738 3.24355731 1.8360426 3.26030782 1.85287816\n", - " 3.34940407 1.92888406 3.49901486 1.94549491 3.55841309 1.97973283\n", - " 3.50693669 2.00279047 3.45522611 1.92885029 3.35161717 1.94033014\n", - " 3.25273029 1.99559228 3.36205397 2.30301912 3.3596869 2.45806588\n", - " 3.31133347 2.32903808 3.39824571 2.42311434 3.30357688 2.71960626]\n", - "Depth = 21, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.556377\n", - " Iterations: 1818\n", - " Function evaluations: 2275\n", - "P = [2.8999047 2.73933738 3.15933224 2.49769719 3.02291128 2.46697886\n", - " 3.21929143 2.03668178 3.25486232 2.12544316 3.17693073 1.95997485\n", - " 3.27545532 1.86770887 3.25829177 1.76236736 3.2879187 1.90685224\n", - " 3.18324773 2.01051129 3.54277663 1.93916376 3.56005914 1.96680117\n", - " 3.45789043 2.10989745 3.48359686 1.91036746 3.32093579 1.95039418\n", - " 3.28117092 1.99388705 3.37503073 2.22700417 3.39161546 2.30990384\n", - " 3.31413816 2.51643356 3.40426391 2.46085697 3.34268933 2.81907339]\n", - "P_ = [2.8999047 2.73933738 3.14697855 2.50920387 3.03590375 2.46990442\n", - " 3.19123712 2.09815279 3.24808691 2.10853623 3.19548587 1.99937207\n", - " 3.24730544 1.89407058 3.26401295 1.7974812 3.27663225 1.85181038\n", - " 3.22810671 1.96608598 3.37157239 1.97313877 3.55100639 1.95232443\n", - " 3.51627255 2.02812815 3.46768335 2.03388603 3.4293765 1.9237097\n", - " 3.3095744 1.96282071 3.3035185 2.04939112 3.37818973 2.24279458\n", - " 3.38054727 2.33940808 3.32272156 2.51114056 3.40133179 2.4779149\n", - " 3.34268933 2.81907339]\n", - "Depth = 22, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.880399\n", - " Iterations: 1200\n", - " Function evaluations: 1575\n", - "P = [2.89179345 2.70982117 3.14957177 2.56432967 3.0453115 2.48048581\n", - " 3.19710541 2.10305548 3.27582511 2.14221588 3.22700323 1.98020621\n", - " 3.25606347 1.79670648 3.24845612 1.81182915 3.26373567 1.87737682\n", - " 3.16659577 1.88108703 3.37324427 1.96965467 3.58231451 2.00894318\n", - " 3.51556558 2.00319934 3.54426404 1.97136582 3.42960566 1.9285502\n", - " 3.34434338 2.01032131 3.32562289 1.91239209 3.38907319 2.2981225\n", - " 3.39764387 2.37899638 3.30190833 2.58190618 3.41581156 2.44188772\n", - " 3.33726391 2.95465438]\n", - "P_ = [2.89179345 2.70982117 3.13785458 2.57094292 3.05478971 2.48810798\n", - " 3.17640624 2.15452326 3.26151244 2.13509581 3.23809911 2.01702659\n", - " 3.24813795 1.84675186 3.25087664 1.80701739 3.25817947 1.85354131\n", - " 3.20633482 1.87956922 3.27931313 1.92939665 3.47777939 1.98929893\n", - " 3.55197409 2.00633234 3.52730586 1.99017653 3.50257008 1.9557965\n", - " 3.40247675 1.95456828 3.33923779 1.98361334 3.34004341 2.00005809\n", - " 3.39063149 2.31282684 3.38458902 2.4066659 3.31226317 2.56917723\n", - " 3.41224122 2.46519529 3.33726391 2.95465438]\n", - "Depth = 23, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.850281\n", - " Iterations: 2268\n", - " Function evaluations: 2802\n", - "P = [2.84958961 2.77289798 3.20226299 2.63082699 3.05631021 2.58362024\n", - " 3.22085904 2.13826571 3.27147583 2.09997102 3.26354029 2.05530141\n", - " 3.25377413 1.87266942 3.08147881 1.80585122 3.24952345 1.89269771\n", - " 3.19369539 1.87501193 3.25682182 1.81441606 3.4619851 1.96694811\n", - " 3.48714566 2.07755558 3.53482018 1.951815 3.47898676 1.98308679\n", - " 3.41950942 2.04043745 3.38633231 1.89744142 3.34370995 1.99051672\n", - " 3.36181303 2.37101291 3.36884251 2.39048524 3.3589565 2.61229608\n", - " 3.42022281 2.58822806 3.36202116 2.83508408]\n", - "P_ = [2.84958961 2.77289798 3.18692936 2.63700399 3.06900175 2.58772517\n", - " 3.19939615 2.19635543 3.26267291 2.10663097 3.26526541 2.06501219\n", - " 3.25632183 1.92031255 3.13391652 1.8261872 3.19107314 1.86249023\n", - " 3.21554115 1.88193245 3.22937554 1.84076209 3.36386353 1.893998\n", - " 3.47401841 2.01984734 3.50787372 2.02288576 3.51297232 1.96405178\n", - " 3.45829899 2.00303484 3.40941204 1.99691692 3.37521343 1.92172194\n", - " 3.3476454 2.07323329 3.36303555 2.3743994 3.36755303 2.41941709\n", - " 3.36428401 2.61020321 3.41769231 2.59896093 3.36202116 2.83508408]\n", - "Depth = 24, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 4.773331\n", - " Iterations: 1322\n", - " Function evaluations: 1712\n", - "P = [2.85930721 2.78233896 3.19686648 2.62878036 3.09425629 2.60425848\n", - " 3.18036822 2.21592138 3.27782728 2.1291664 3.28011116 2.05765475\n", - " 3.3041212 1.91145662 3.17047985 1.80356732 3.1962741 1.88555818\n", - " 3.20893563 1.86842739 3.23454514 1.84532243 3.4284466 1.85564686\n", - " 3.49778911 2.0177097 3.53674575 2.0156324 3.40825994 1.95604346\n", - " 3.46715356 2.01516087 3.44223838 1.97961324 3.35928668 1.91561898\n", - " 3.35208543 2.07081292 3.3443867 2.36439119 3.4322762 2.4286787\n", - " 3.39197137 2.61849402 3.32809799 2.57826187 3.3407432 2.86955188]\n", - "P_ = [2.85930721 2.78233896 3.18280151 2.63517863 3.10280714 2.60630197\n", - " 3.16960423 2.26446352 3.2615841 2.14362557 3.27963535 2.07255301\n", - " 3.29811869 1.94800616 3.20945857 1.83503503 3.18767601 1.85822789\n", - " 3.20418756 1.87485144 3.22387452 1.8549495 3.3395751 1.85091483\n", - " 3.46311785 1.93667828 3.51564424 2.0167576 3.48320999 1.99080367\n", - " 3.43034505 1.97821249 3.4588485 2.00331166 3.41804413 1.96094825\n", - " 3.35748637 1.95441747 3.35048153 2.13197506 3.35903495 2.37510578\n", - " 3.42723809 2.45240561 3.38664859 2.61514134 3.32862487 2.59039895\n", - " 3.3407432 2.86955188]\n", - "Depth = 25, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.266152\n", - " Iterations: 2024\n", - " Function evaluations: 2532\n", - "P = [2.85448426 2.82591669 3.16568653 2.67974411 3.06491246 2.548792\n", - " 3.21435 2.23182518 3.27738565 2.23071257 3.29369431 2.06354731\n", - " 3.22793646 1.86390082 3.21526445 1.7681256 3.20035313 1.93246432\n", - " 3.21625096 1.84270132 3.25768071 1.85838428 3.32620579 1.90119628\n", - " 3.49859441 1.89574041 3.50952348 2.2097548 3.33112294 1.92334853\n", - " 3.4509503 2.03720236 3.48146252 2.01686728 3.41830023 1.95536248\n", - " 3.3674692 2.05209402 3.35998749 2.06064188 3.38986538 2.40762662\n", - " 3.41992544 2.41557521 3.38722639 2.57347964 3.34417379 2.66767383\n", - " 3.39285638 2.81114856]\n", - "P_ = [2.85448426 2.82591669 3.15323844 2.68559101 3.07297439 2.55926817\n", - " 3.19641749 2.2698612 3.26729995 2.23089059 3.29043258 2.09698036\n", - " 3.24371834 1.91181598 3.21881261 1.79494266 3.20512475 1.87987593\n", - " 3.21052774 1.875016 3.24110881 1.8521111 3.29605476 1.882359\n", - " 3.41584787 1.89835923 3.50384036 2.04646732 3.43102724 2.08373604\n", - " 3.37905388 1.96889006 3.4619347 2.02988173 3.46125059 1.99718574\n", - " 3.40406754 1.98244731 3.36567359 2.05414551 3.36596307 2.13003883\n", - " 3.39467499 2.4088984 3.41600156 2.43452374 3.38378218 2.58101518\n", - " 3.34612109 2.67341282 3.39285638 2.81114856]\n", - "Depth = 26, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.651534\n", - " Iterations: 1273\n", - " Function evaluations: 1651\n", - "P = [2.85823723 2.83236809 3.13784779 2.66706002 3.07715432 2.60446462\n", - " 3.17623251 2.28663091 3.28515493 2.24238969 3.28672364 2.09288497\n", - " 3.26049235 1.93426623 3.2166296 1.78464425 3.19061084 1.89303862\n", - " 3.20423754 1.88395396 3.23978571 1.871853 3.30509058 1.90401397\n", - " 3.28246306 1.90554682 3.48805993 2.07344194 3.43588078 2.11133474\n", - " 3.40310951 1.96158038 3.4699824 2.03294756 3.48338939 1.95775156\n", - " 3.39235062 2.02211507 3.34281174 2.07070054 3.36416994 2.153203\n", - " 3.41605965 2.41569048 3.39585748 2.43468513 3.37633659 2.56291755\n", - " 3.36535046 2.65149423 3.36167705 2.7632069 ]\n", - "P_ = [2.85823723 2.83236809 3.12709354 2.67341802 3.08182305 2.60927965\n", - " 3.16480042 2.32330403 3.26839764 2.24919603 3.28642197 2.12163588\n", - " 3.26654573 1.97087056 3.2284388 1.82492709 3.19861661 1.85968651\n", - " 3.19952061 1.88709865 3.22611334 1.87650722 3.2774616 1.89040741\n", - " 3.29290653 1.90483935 3.3852615 1.98949438 3.46397725 2.09093093\n", - " 3.42201602 2.04797713 3.42882985 1.98902929 3.47462328 2.00691817\n", - " 3.45537746 1.97755572 3.37901323 2.03519577 3.34774056 2.08973957\n", - " 3.37414873 2.20368136 3.41295162 2.41861273 3.39360507 2.44948118\n", - " 3.3754915 2.56973114 3.36520917 2.65579087 3.36167705 2.7632069 ]\n", - "Depth = 27, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.787013\n", - " Iterations: 2858\n", - " Function evaluations: 3457\n", - "P = [2.85285549 2.88204905 3.12830587 2.65749279 3.10925869 2.60488577\n", - " 3.1720339 2.17218733 3.27830003 2.28817981 3.29401215 2.09861718\n", - " 3.26927191 1.96912039 3.24608626 1.87921835 3.19304944 1.86181117\n", - " 3.26309446 1.85624624 3.23035953 1.86986473 3.37488759 1.81698664\n", - " 3.2893706 1.76950854 3.38348553 2.08934308 3.45357533 2.1290486\n", - " 3.43056629 2.0556419 3.44223541 1.916491 3.53050559 1.97614571\n", - " 3.45931804 2.05797153 3.32177719 1.99935388 3.33781217 2.22809485\n", - " 3.36202332 2.26335032 3.45394999 2.35461087 3.40883996 2.46885935\n", - " 3.3739711 2.57764385 3.32257773 2.52227074 3.42074712 2.76265704]\n", - "P_ = [2.85285549 2.88204905 3.11810401 2.66580969 3.11066959 2.60878259\n", - " 3.16505888 2.22026494 3.2625569 2.27099574 3.2911025 2.13372137\n", - " 3.27476974 1.99789745 3.25209736 1.90252628 3.20876405 1.86696885\n", - " 3.23974612 1.85810122 3.24248358 1.86482085 3.31600578 1.83852957\n", - " 3.32737815 1.79060992 3.33817093 1.93534867 3.41723247 2.10846055\n", - " 3.44334909 2.0964234 3.43532037 1.99895079 3.47492807 1.93858534\n", - " 3.5067764 2.00342098 3.41856519 2.04060333 3.32593441 2.05865709\n", - " 3.34319242 2.2359294 3.37904678 2.28025042 3.44726702 2.37153657\n", - " 3.40496564 2.48094651 3.37016418 2.57354214 3.32621363 2.53117393\n", - " 3.42074712 2.76265704]\n", - "Depth = 28, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.596240\n", - " Iterations: 2482\n", - " Function evaluations: 3027\n", - "P = [2.88659804 2.74718912 3.10800061 2.65451052 3.08136428 2.58198841\n", - " 3.24075309 2.21046918 3.2630327 2.42153925 3.315429 2.04334082\n", - " 3.29403132 2.05584559 3.23860178 1.85928109 3.23139752 1.92237515\n", - " 3.25756931 1.89166942 3.25406094 1.90831108 3.28358624 1.85007415\n", - " 3.32983155 1.8311716 3.35841703 2.00068379 3.45129497 2.01401187\n", - " 3.4422263 2.10424703 3.42772988 1.92672075 3.46763309 1.96108565\n", - " 3.51136065 2.0019719 3.41589309 2.01960043 3.34935914 1.99725651\n", - " 3.40438378 2.21489809 3.38154972 2.18975374 3.45706195 2.31777554\n", - " 3.40340042 2.52027722 3.35891461 2.51638549 3.42172698 2.53523861\n", - " 3.4334494 2.83005222]\n", - "P_ = [2.88659804 2.74718912 3.10009337 2.65782047 3.08326688 2.58716856\n", - " 3.22367572 2.25027482 3.2598499 2.39138638 3.30607252 2.11087625\n", - " 3.29861654 2.053166 3.25245917 1.90842222 3.23345588 1.90434828\n", - " 3.24915695 1.90153912 3.25531393 1.90236763 3.27198702 1.87295294\n", - " 3.31001214 1.8392727 3.3451452 1.92198171 3.404856 2.00734783\n", - " 3.44708452 2.05590677 3.43601355 2.02816434 3.44340614 1.94022125\n", - " 3.48325008 1.97568788 3.48067465 2.00763821 3.39688339 2.01321645\n", - " 3.3631153 2.05166691 3.39949077 2.20951002 3.39503405 2.21261478\n", - " 3.44939602 2.34670435 3.39863408 2.51986025 3.3634012 2.51773214\n", - " 3.42214564 2.54576766 3.4334494 2.83005222]\n", - "Depth = 29, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.153323\n", - " Iterations: 2327\n", - " Function evaluations: 2865\n", - "P = [2.87341191 2.68931461 3.11864425 2.63105846 3.09048396 2.62260861\n", - " 3.18726165 2.23713633 3.2676171 2.48458587 3.29903282 2.06570157\n", - " 3.2851752 1.96742107 3.25573914 1.93237423 3.22147863 1.88136621\n", - " 3.26826935 1.90538519 3.26127582 1.87789625 3.28907625 1.88754579\n", - " 3.30326902 1.78828712 3.34527063 1.95765023 3.36951488 1.94201229\n", - " 3.43509418 2.15121468 3.43041189 2.09099513 3.42985061 1.90942421\n", - " 3.45721194 2.0314167 3.44785941 2.02965951 3.42478816 2.00140875\n", - " 3.36902057 2.08075813 3.41617726 2.23740494 3.39076824 2.19999704\n", - " 3.45289965 2.31308854 3.40087842 2.54559043 3.38934261 2.53700357\n", - " 3.38322247 2.6943777 3.44294978 2.74965286]\n", - "P_ = [2.87341191 2.68931461 3.11018797 2.6330673 3.09242605 2.62319136\n", - " 3.17725017 2.27701277 3.25653359 2.4504549 3.29361632 2.137923\n", - " 3.2880423 1.98775497 3.2628444 1.94083381 3.23092981 1.89543739\n", - " 3.25374809 1.89793103 3.26368738 1.88737519 3.27853126 1.88388562\n", - " 3.29739615 1.82935967 3.32644232 1.88172883 3.35781076 1.94956164\n", - " 3.40117385 2.04300655 3.43299522 2.12421971 3.43017963 2.01586234\n", - " 3.44022905 1.95569723 3.45398693 2.03081077 3.44069937 2.02089203\n", - " 3.409404 2.02329824 3.38040322 2.11856943 3.41092022 2.22966538\n", - " 3.40148055 2.21949557 3.44572431 2.34515776 3.39968506 2.54470214\n", - " 3.38892053 2.54785696 3.38528203 2.69628374 3.44294978 2.74965286]\n", - "Depth = 30, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 3.568228\n", - " Iterations: 3032\n", - " Function evaluations: 3690\n", - "2.2857142857142856 [11.45133476 9.80628903 10.53304391 8.76321997 8.91081807 12.18555498\n", - " 8.13471592 7.77501089 9.34973755 9.52071308 8.84273883 6.26376956\n", - " 5.42292081 4.79520442 5.63158373 7.3917518 6.68990559 5.17192061\n", - " 5.08571674 3.94954343 4.55637716 4.88039903 5.85028149 4.77333057\n", - " 5.26615174 5.65153396 4.78701302 4.59624046 5.15332304 3.56822798]\n", - "[[6.57155339 5.94790512 4.51084725 5.48476219 4.44827696 4.07086367\n", - " 4.45993119 3.76473244 3.75245393 3.70383406 2.54453644 2.75335922\n", - " 3.72365101 2.64914745 3.66152866 3.41308183 2.17660478 2.18383796\n", - " 2.54980097 1.72430929 2.24071873 1.8353618 2.04963403 1.97768311\n", - " 2.25839296 2.22977067 1.94603139 2.05226045 2.69504832 3.27724127]\n", - " [7.58106801 6.81608452 4.28714233 4.07123972 3.27046962 3.23940109\n", - " 3.69518164 3.2411352 2.8435791 2.91039551 2.52147765 2.7118309\n", - " 2.7196728 2.5657514 2.49654928 2.14986169 2.03773181 1.96011255\n", - " 1.99818881 1.99560667 2.10966328 1.86491841 1.83579189 1.98703992\n", - " 1.98133515 1.95306622 1.90928783 1.85507609 1.79545032 1.7963689 ]\n", - " [5.67675131 4.71392584 4.01740509 3.36995594 3.02811997 2.75900701\n", - " 2.07994453 1.87160639 1.76736629 1.60399896 1.51494314 1.48018664\n", - " 1.42851074 1.41006842 1.37578808 1.29188206 1.25021059 1.25293931\n", - " 1.22202663 1.23016691 1.26143882 1.20441019 1.17776388 1.18431374\n", - " 1.16553331 1.16956844 1.16569465 1.17659931 1.16990127 1.15831922]\n", - " [5.00995896 4.29025145 4.60820671 3.83390873 3.89848291 5.33118031\n", - " 3.55893822 3.40156727 4.09051018 4.16531197 3.86869824 2.74039918\n", - " 2.37252786 2.09790193 2.46381788 3.23389141 2.92683369 2.26271526\n", - " 2.22500107 1.72792525 1.99341501 2.13517458 2.55949815 2.08833212\n", - " 2.30394139 2.47254611 2.09431819 2.0108552 2.25457883 1.56109974]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]] [2.48393317 2.17681669 1.74236014 1.67598666 1.46453495 1.54004521\n", - " 1.37939956 1.22790413 1.24539095 1.23835405 1.04496555 0.9685776\n", - " 1.02443624 0.87228692 0.99976839 1.0088717 0.83913809 0.76596051\n", - " 0.79950175 0.66780081 0.76052358 0.7039865 0.7622688 0.72373689\n", - " 0.77092028 0.78249514 0.71153321 0.7094791 0.79149787 0.77930291]\n", - "[[0.1749857 0.07463194 0.26530491 0.16394175 0.18892849 0.25701077\n", - " 0.24542951 0.40504394 0.18547862 0.24113788 0.62032714 0.68408453\n", - " 0.11521194 0.57930818 0.29653581 0.32221821 0.75779012 0.76858176\n", - " 0.59269399 0.8271978 0.69201592 0.87101232 0.79114835 0.72852071\n", - " 0.64433266 0.66377712 0.77675308 0.72982301 0.58648573 0.44154865]\n", - " [0.17669094 0.20818569 0.40598211 0.40456531 0.54848127 0.5337594\n", - " 0.48446167 0.53759304 0.60295388 0.58451793 0.64895146 0.66165701\n", - " 0.62972457 0.66201878 0.67281148 0.75627098 0.78514972 0.80366385\n", - " 0.79430362 0.79961314 0.7524382 0.82370466 0.83214203 0.78138294\n", - " 0.78255631 0.78124579 0.80687807 0.80774629 0.84561002 0.84356134]\n", - " [0.1977358 0.23204622 0.30938238 0.39342279 0.41016143 0.46245125\n", - " 0.76102816 0.79966194 0.84980142 0.9167973 0.93013476 0.94105633\n", - " 0.96019643 0.9567664 0.95781341 0.97258171 0.97672161 0.97483651\n", - " 0.98345276 0.97827363 0.97171746 0.98525476 0.99020549 0.988242\n", - " 0.99105685 0.98789452 0.98718377 0.98332188 0.98342322 0.98330761]\n", - " [0.05772911 0.21353746 0.01841155 0.31450455 0.21424321 0.05404723\n", - " 0.43161435 0.34272799 0.28819124 0.28689022 0.1868918 0.50636735\n", - " 0.71458126 0.77159991 0.58971876 0.39292553 0.46431953 0.6325678\n", - " 0.69978407 0.80479284 0.72769493 0.74105124 0.53269212 0.73999712\n", - " 0.61502723 0.52602161 0.71815241 0.71745393 0.53403795 0.82706806]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]] [0.06071416 0.07284013 0.0999081 0.12764344 0.13618144 0.13072686\n", - " 0.19225337 0.20850269 0.19264252 0.20293433 0.23863052 0.27931652\n", - " 0.24197142 0.29696933 0.25168795 0.24439964 0.2983981 0.31796499\n", - " 0.30702344 0.34098774 0.31438665 0.3421023 0.3146188 0.32381428\n", - " 0.30329731 0.2958939 0.32889673 0.32383451 0.29495569 0.30954857]\n", - "\n", - "Now using 3 solutions, set number 6\n", - "Calculating energy landscape ...\n", - "Optimization terminated successfully.\n", - " Current function value: 9.716628\n", - " Iterations: 23\n", - " Function evaluations: 45\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 9.716628\n", - " Iterations: 6\n", - " Function evaluations: 13\n", - "P = [0.11407941 1.95640691]\n", - "P_ = [0.11407941 1.95640691 0.11407941 1.95640691]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 9.095520\n", - " Iterations: 32\n", - " Function evaluations: 56\n", - "P = [0.0752484 1.91621899 0.1357591 1.87956749]\n", - "P_ = [0.0752484 1.91621899 0.10550375 1.89789324 0.1357591 1.87956749]\n", - "Depth = 3, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 6.296254\n", - " Iterations: 135\n", - " Function evaluations: 200\n", - "P = [0.0912175 1.88244575 0.05611754 1.74218153 0.1903651 1.81563093]\n", - "P_ = [0.0912175 1.88244575 0.06781753 1.78893627 0.10086673 1.76666467\n", - " 0.1903651 1.81563093]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 6.226025\n", - " Iterations: 158\n", - " Function evaluations: 241\n", - "P = [0.03185976 2.10869391 0.10465552 1.86913619 0.08555688 1.75484448\n", - " 0.17507612 1.78711209]\n", - "P_ = [0.03185976 2.10869391 0.08645658 1.92902562 0.0951062 1.81199033\n", - " 0.10793669 1.76291138 0.17507612 1.78711209]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.659312\n", - " Iterations: 581\n", - " Function evaluations: 826\n", - "P = [ 0.07343328 0.91292824 -0.02334356 2.75546042 0.19783753 1.61856624\n", - " 0.01950003 1.8182347 0.20716979 1.77268648]\n", - "P_ = [ 0.07343328 0.91292824 -0.00398819 2.38695398 0.10936509 2.07332391\n", - " 0.12650253 1.69843363 0.05703398 1.80912506 0.20716979 1.77268648]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.559582\n", - " Iterations: 918\n", - " Function evaluations: 1248\n", - "P = [ 0.02654763 0.61775965 -0.00929733 2.89285929 0.08432839 3.47910598\n", - " 0.1627231 1.63220063 0.03012729 1.81328997 0.21321109 1.76392748]\n", - "P_ = [ 0.02654763 0.61775965 -0.00332317 2.51367602 0.05311982 3.28369042\n", - " 0.12352574 2.5556533 0.11852449 1.69256374 0.06064125 1.80506288\n", - " 0.21321109 1.76392748]\n", - "Depth = 7, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.231183\n", - " Iterations: 1041\n", - " Function evaluations: 1382\n", - "P = [6.78675216e-02 1.41319111e-01 2.80033295e-03 3.48825727e+00\n", - " 1.37319666e-01 3.41166471e+00 8.99384556e-02 3.02735433e+00\n", - " 3.22036159e-02 1.48878236e+00 1.00149803e-02 1.96560417e+00\n", - " 1.93379093e-01 1.75879799e+00]\n", - "P_ = [0.06786752 0.14131911 0.01209565 3.01012325 0.09888557 3.4335483\n", - " 0.11024469 3.19205878 0.06519495 2.36796635 0.02586401 1.62501716\n", - " 0.03620985 1.93606043 0.19337909 1.75879799]\n", - "Depth = 8, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.954214\n", - " Iterations: 1039\n", - " Function evaluations: 1375\n", - "P = [0.04323703 0.21362469 0.00862483 3.33755888 0.0706904 3.42850016\n", - " 0.13671783 3.37048185 0.09531508 3.0595854 0.02749174 1.57889082\n", - " 0.01257597 1.84542753 0.20020028 1.74655943]\n", - "P_ = [0.04323703 0.21362469 0.01295135 2.94706711 0.05517401 3.40576484\n", - " 0.11195754 3.39223872 0.11601646 3.21503362 0.06988133 2.50432493\n", - " 0.0237628 1.64552499 0.03602901 1.83306901 0.20020028 1.74655943]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.551782\n", - " Iterations: 1035\n", - " Function evaluations: 1359\n", - "P = [ 3.24577019e-02 5.44761310e-01 5.82190385e-03 3.20934951e+00\n", - " 8.84093296e-02 3.53345505e+00 1.28251368e-01 3.39571409e+00\n", - " 1.33252221e-01 3.32240769e+00 1.46927469e-01 2.80950344e+00\n", - " -5.78068481e-03 2.21570754e+00 1.51818655e-04 1.43508470e+00\n", - " 1.60518640e-01 1.70108146e+00]\n", - "P_ = [ 0.0324577 0.54476131 0.00878144 2.91328415 0.07005657 3.4614316\n", - " 0.11497069 3.44162774 0.13102962 3.35498831 0.13933011 3.09445025\n", - " 0.09602475 2.61157147 -0.00446235 2.0422358 0.01797035 1.46463989\n", - " 0.16051864 1.70108146]\n", - "Depth = 10, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.333946\n", - " Iterations: 621\n", - " Function evaluations: 858\n", - "P = [ 2.90213435e-02 4.83243393e-01 8.64667868e-03 3.27100891e+00\n", - " 7.38612617e-02 3.55527504e+00 1.15783498e-01 3.43398729e+00\n", - " 1.33502076e-01 3.38000326e+00 1.55274277e-01 3.32575600e+00\n", - " 1.49606374e-01 2.79032370e+00 -1.17276897e-03 2.03329494e+00\n", - " 1.90785559e-02 1.60728245e+00 1.61283085e-01 1.66427693e+00]\n", - "P_ = [2.90213435e-02 4.83243393e-01 1.06841452e-02 2.99223236e+00\n", - " 6.08183451e-02 3.49842182e+00 1.03206827e-01 3.47037362e+00\n", - " 1.26414645e-01 3.40159687e+00 1.44388176e-01 3.35287963e+00\n", - " 1.53007116e-01 3.11158308e+00 1.04372631e-01 2.56321507e+00\n", - " 2.87749600e-03 1.94809244e+00 3.32990089e-02 1.61298190e+00\n", - " 1.61283085e-01 1.66427693e+00]\n", - "Depth = 11, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.301509\n", - " Iterations: 293\n", - " Function evaluations: 429\n", - "P = [2.92880051e-02 4.96984799e-01 9.06751751e-03 3.18800049e+00\n", - " 5.97887070e-02 3.52340689e+00 1.03777063e-01 3.44896351e+00\n", - " 1.25741302e-01 3.37889960e+00 1.38344002e-01 3.34834617e+00\n", - " 1.54707538e-01 3.28401514e+00 1.06233352e-01 2.75210377e+00\n", - " 2.84872167e-03 2.04468323e+00 3.31495969e-02 1.59402116e+00\n", - " 1.60430892e-01 1.64985190e+00]\n", - "P_ = [0.02928801 0.4969848 0.01090574 2.9433627 0.05056667 3.46242391\n", - " 0.09178024 3.46926625 0.11775431 3.40437738 0.1326155 3.36223409\n", - " 0.14578197 3.31910479 0.13708056 3.09059282 0.07803754 2.5591709\n", - " 0.00835797 1.96274467 0.04472062 1.59909669 0.16043089 1.6498519 ]\n", - "Depth = 12, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.295170\n", - " Iterations: 472\n", - " Function evaluations: 646\n", - "P = [0.02961441 0.4964643 0.01058279 3.1896158 0.04965628 3.48633436\n", - " 0.09008732 3.45115604 0.11755386 3.39720175 0.13336164 3.34718226\n", - " 0.1361037 3.30212854 0.13356416 3.26436172 0.07884175 2.71084617\n", - " 0.00807926 2.03806228 0.04405517 1.60762708 0.1613791 1.62568211]\n", - "P_ = [0.02961441 0.4964643 0.01216876 2.9651865 0.04314403 3.43688127\n", - " 0.07997956 3.45995062 0.10839834 3.41518652 0.12677506 3.36802371\n", - " 0.13473267 3.3246554 0.13504556 3.28639236 0.11532336 3.07985653\n", - " 0.06115113 2.5426502 0.01407525 1.96632308 0.05383216 1.60913167\n", - " 0.1613791 1.62568211]\n", - "Depth = 13, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.232292\n", - " Iterations: 1165\n", - " Function evaluations: 1505\n", - "P = [0.02660866 0.50781921 0.01257197 3.21496421 0.0431145 3.49544108\n", - " 0.0799965 3.47069532 0.11244078 3.40956527 0.12229318 3.35528029\n", - " 0.13662303 3.32447027 0.13027379 3.26921538 0.11058898 3.20194468\n", - " 0.0583527 3.08034298 0.01422417 1.6965686 0.05237504 1.58988086\n", - " 0.16829494 1.61662073]\n", - "P_ = [0.02660866 0.50781921 0.01365171 3.00672229 0.03841565 3.45229079\n", - " 0.07148527 3.47640588 0.10245793 3.42837452 0.1185038 3.37615913\n", - " 0.13000925 3.33869028 0.13369261 3.29896801 0.12270271 3.24334203\n", - " 0.09451628 3.16452877 0.04816919 2.76101043 0.02009354 1.6801551\n", - " 0.06129196 1.59193778 0.16829494 1.61662073]\n", - "Depth = 14, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.202767\n", - " Iterations: 980\n", - " Function evaluations: 1279\n", - "P = [0.02398145 0.49852182 0.01381896 3.22253767 0.03757115 3.48361443\n", - " 0.07164205 3.45909752 0.09976874 3.41161787 0.11691471 3.37133272\n", - " 0.13219209 3.33883206 0.13593748 3.29106239 0.12441227 3.24051237\n", - " 0.09359484 3.19472123 0.04840746 3.02483309 0.01919908 1.73319243\n", - " 0.06254844 1.58223807 0.16483324 1.60907897]\n", - "P_ = [0.02398145 0.49852182 0.01454486 3.0279651 0.03417798 3.44631775\n", - " 0.06434115 3.46435115 0.09173255 3.42518349 0.11079115 3.38572027\n", - " 0.12564464 3.35276091 0.13406479 3.31494722 0.1309981 3.26939809\n", - " 0.11340604 3.22415839 0.08068416 3.14618176 0.04214852 2.74805295\n", - " 0.02539185 1.71162752 0.0698545 1.58415527 0.16483324 1.60907897]\n", - "Depth = 15, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.209599\n", - " Iterations: 473\n", - " Function evaluations: 664\n", - "P = [0.0239188 0.49994438 0.01451467 3.14184845 0.03414154 3.47989059\n", - " 0.06383337 3.41439108 0.09026694 3.39432575 0.10962209 3.36480416\n", - " 0.12607199 3.33516792 0.13563997 3.30496938 0.12934794 3.24954935\n", - " 0.11217839 3.19110085 0.07963906 3.28018614 0.04203771 2.8768908\n", - " 0.02545102 1.78311403 0.06925482 1.57861228 0.1635842 1.59793906]\n", - "P_ = [0.0239188 0.49994438 0.01514161 2.96572152 0.03152462 3.4348183\n", - " 0.057895 3.42749098 0.08321799 3.39967651 0.10317037 3.37464469\n", - " 0.11949203 3.34702242 0.13117491 3.31906203 0.13270369 3.2791067\n", - " 0.12248012 3.22616995 0.10133195 3.22079594 0.06961204 3.17264071\n", - " 0.03872037 2.65813545 0.03129153 1.75584713 0.07554345 1.57990073\n", - " 0.1635842 1.59793906]\n", - "Depth = 16, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 3.163860\n", - " Iterations: 1116\n", - " Function evaluations: 1444\n", - "P = [0.02031851 0.50923353 0.01446723 3.22185389 0.03242274 3.52256504\n", - " 0.06728002 3.44400061 0.07891395 3.39487365 0.10363333 3.37560305\n", - " 0.11779757 3.34678994 0.12580998 3.31816973 0.13642641 3.27723492\n", - " 0.12283926 3.25201562 0.10018242 3.12162139 0.06567412 3.2941579\n", - " 0.03661449 3.01764675 0.02884298 1.64429256 0.07779053 1.59133703\n", - " 0.17292826 1.60787038]\n", - "P_ = [0.02031851 0.50923353 0.01483294 3.05231512 0.0301783 3.48497615\n", - " 0.06074428 3.45873144 0.07600547 3.40715539 0.09590852 3.38162511\n", - " 0.11248598 3.35759486 0.12230455 3.33069107 0.13111819 3.29770233\n", - " 0.13048203 3.26620148 0.11434294 3.20311779 0.08939858 3.17553905\n", - " 0.05840921 3.22503011 0.03515733 2.76014284 0.03496142 1.63767312\n", - " 0.08373664 1.59237036 0.17292826 1.60787038]\n", - "Depth = 17, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.046467\n", - " Iterations: 2220\n", - " Function evaluations: 2688\n", - "P = [0.01654442 0.53041891 0.01591019 3.5653786 0.03149117 3.60328997\n", - " 0.05188931 3.57705159 0.08409751 3.47281156 0.09329385 3.42315844\n", - " 0.110905 3.379848 0.1151816 3.34844115 0.11971439 3.31153584\n", - " 0.13774565 3.30238595 0.149406 3.26396979 0.08777824 3.10312528\n", - " 0.0546758 3.27152533 0.0413793 3.10314427 0.03672266 1.62217152\n", - " 0.02002402 1.57939007 0.16462937 1.62978849]\n", - "P_ = [0.01654442 0.53041891 0.0159475 3.38685156 0.02965811 3.59882981\n", - " 0.04828964 3.58168189 0.07651911 3.49733862 0.09058905 3.4377623\n", - " 0.1046893 3.39513404 0.11342065 3.36137338 0.11758132 3.32890304\n", - " 0.12819969 3.30723001 0.14254697 3.28656753 0.12765503 3.20720113\n", - " 0.07804223 3.1526547 0.05154721 3.23190625 0.04055754 2.84179613\n", - " 0.03475812 1.61713841 0.02853022 1.58235468 0.16462937 1.62978849]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.044138\n", - " Iterations: 510\n", - " Function evaluations: 725\n", - "P = [0.01641293 0.52767943 0.01589016 3.4662132 0.02944341 3.60646888\n", - " 0.04837398 3.56405905 0.07508848 3.49705393 0.09170099 3.42576136\n", - " 0.10439987 3.39512668 0.11205356 3.35247419 0.11635026 3.33459229\n", - " 0.12846295 3.29611963 0.14190482 3.28164064 0.12795169 3.20109542\n", - " 0.07702588 3.1563573 0.05120632 3.31254109 0.04097665 2.92906164\n", - " 0.0347341 1.69900857 0.02820066 1.6101692 0.16483964 1.6175537 ]\n", - "P_ = [0.01641293 0.52767943 0.01591921 3.30296132 0.0279375 3.59088491\n", - " 0.04521889 3.57112736 0.06915192 3.51194395 0.0870864 3.44556485\n", - " 0.10016691 3.40533824 0.10907713 3.36906127 0.11444062 3.3425398\n", - " 0.12240661 3.31535596 0.13443712 3.28968452 0.1364786 3.2503175\n", - " 0.11097642 3.18618272 0.06985378 3.19974169 0.04893306 3.22732343\n", - " 0.03993622 2.72405279 0.03400816 1.68913753 0.03579172 1.61057945\n", - " 0.16483964 1.6175537 ]\n", - "Depth = 19, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.010682\n", - " Iterations: 1336\n", - " Function evaluations: 1686\n", - "P = [0.0161541 0.52613424 0.01530157 3.51915361 0.02837695 3.45251447\n", - " 0.04445855 3.54875208 0.0706489 3.44472562 0.08928526 3.4506433\n", - " 0.10736794 3.40352557 0.11094433 3.35411572 0.11600584 3.34526279\n", - " 0.12318648 3.3112448 0.13478489 3.28680199 0.139298 3.26326075\n", - " 0.11229399 3.17422621 0.07051735 3.188051 0.05118473 3.29360221\n", - " 0.03632968 2.88102984 0.03175272 1.76291806 0.0341754 1.57986848\n", - " 0.16700498 1.62081777]\n", - "P_ = [0.0161541 0.52613424 0.01534644 3.36162628 0.0270006 3.45952911\n", - " 0.04191935 3.53355667 0.06513514 3.46662593 0.08438096 3.44908602\n", - " 0.10165762 3.41840485 0.10962671 3.37231935 0.11387468 3.34899034\n", - " 0.11978512 3.32735858 0.12868046 3.29966663 0.13668514 3.27688989\n", - " 0.12934915 3.23045855 0.09910137 3.17859194 0.06542982 3.21582763\n", - " 0.04805735 3.20674487 0.035607 2.70448588 0.03200774 1.74364968\n", - " 0.04116643 1.58202371 0.16700498 1.62081777]\n", - "Depth = 20, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.993902\n", - " Iterations: 794\n", - " Function evaluations: 1071\n", - "P = [0.01590049 0.52102916 0.01510348 3.50532954 0.02693446 3.46425815\n", - " 0.04168075 3.50147007 0.06505714 3.44332947 0.08382189 3.41742517\n", - " 0.10008621 3.41210694 0.11285057 3.35757559 0.11410041 3.32857316\n", - " 0.12118818 3.32257522 0.13029374 3.28753156 0.13789977 3.27050903\n", - " 0.13037896 3.2370367 0.10028057 3.14729574 0.06507062 3.21689489\n", - " 0.04909603 3.28386558 0.0349179 2.81791062 0.03174376 1.80646295\n", - " 0.0404559 1.57437647 0.165694 1.61979181]\n", - "P_ = [0.01590049 0.52102916 0.01514333 3.35611452 0.02575136 3.46836529\n", - " 0.03946881 3.49588828 0.06038186 3.45495759 0.0791307 3.42390124\n", - " 0.09520691 3.41370241 0.10838304 3.37666156 0.11360047 3.34017413\n", - " 0.11799868 3.32527429 0.12574096 3.30505339 0.13371645 3.27987142\n", - " 0.13489144 3.2571201 0.11984452 3.20562736 0.08971758 3.16817549\n", - " 0.06107697 3.23363756 0.0462604 3.19067458 0.03444178 2.66619347\n", - " 0.03261497 1.78325431 0.04671781 1.57664724 0.165694 1.61979181]\n", - "Depth = 21, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.979093\n", - " Iterations: 1068\n", - " Function evaluations: 1373\n", - "P = [0.01578299 0.56683127 0.01485745 3.46713531 0.02538596 3.4640273\n", - " 0.03939128 3.48792317 0.05994514 3.42443057 0.07914513 3.41995481\n", - " 0.09873181 3.40914707 0.10440778 3.37564371 0.11906363 3.34233122\n", - " 0.11640858 3.31607674 0.12510527 3.30924536 0.13298593 3.27396063\n", - " 0.1343849 3.26202128 0.11711188 3.22035173 0.08988534 3.13306651\n", - " 0.06085944 3.24188551 0.046184 3.27684822 0.03305695 2.79627047\n", - " 0.03240913 1.80091894 0.04609169 1.5914334 0.16271597 1.61757021]\n", - "P_ = [0.01578299 0.56683127 0.01490152 3.3290256 0.02438324 3.4643233\n", - " 0.03739052 3.48450947 0.05603012 3.4365244 0.07457371 3.42102047\n", - " 0.09313561 3.412235 0.10251579 3.3868115 0.11348045 3.35502169\n", - " 0.11754646 3.32732866 0.12096399 3.3124984 0.12885796 3.29244311\n", - " 0.13358549 3.26884377 0.1278047 3.24614717 0.10803637 3.19125666\n", - " 0.08159223 3.16415765 0.05736529 3.25020996 0.04368361 3.1853096\n", - " 0.03296441 2.65407739 0.03371223 1.78096794 0.05164523 1.59267801\n", - " 0.16271597 1.61757021]\n", - "Depth = 22, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.967518\n", - " Iterations: 1060\n", - " Function evaluations: 1367\n", - "P = [0.01568941 0.56404135 0.01468816 3.42639521 0.02433986 3.52664176\n", - " 0.03724073 3.44155807 0.05648449 3.44311843 0.07404164 3.39540715\n", - " 0.09285231 3.40001478 0.1040272 3.38302812 0.10904707 3.33506926\n", - " 0.11811435 3.32321559 0.12171976 3.29094223 0.12828294 3.29542579\n", - " 0.13450488 3.24088334 0.12738924 3.25577932 0.10850142 3.19005604\n", - " 0.08217715 3.11375841 0.05666706 3.26389018 0.04470026 3.28854575\n", - " 0.03211429 2.76990687 0.03530384 1.79772203 0.05101004 1.58411538\n", - " 0.16391529 1.61151092]\n", - "P_ = [0.01568941 0.56404135 0.01473367 3.29628821 0.02346243 3.51752844\n", - " 0.03548152 3.45316039 0.05298562 3.44283472 0.07005138 3.40625062\n", - " 0.08772213 3.39875815 0.10047155 3.38843297 0.10722166 3.35250884\n", - " 0.11440501 3.32806482 0.12008094 3.30561194 0.12500135 3.29318401\n", - " 0.13111109 3.27063377 0.13159394 3.24697715 0.12052094 3.23187995\n", - " 0.10012552 3.16577952 0.07521985 3.15470344 0.05394734 3.26949372\n", - " 0.0424119 3.19424777 0.03254923 2.63733621 0.03673167 1.77830324\n", - " 0.0561421 1.58536063 0.16391529 1.61151092]\n", - "Depth = 23, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.931361\n", - " Iterations: 2155\n", - " Function evaluations: 2665\n", - "P = [0.0158852 0.57823753 0.01451309 3.52053202 0.0230031 3.4840758\n", - " 0.03389829 3.52505822 0.0536229 3.40819282 0.07039255 3.42599369\n", - " 0.0879159 3.38069686 0.09959503 3.3722241 0.11113734 3.34885788\n", - " 0.11589922 3.30517883 0.11976306 3.30139565 0.12717955 3.27189206\n", - " 0.12589429 3.26994122 0.12987681 3.21104533 0.1204654 3.23839956\n", - " 0.09184751 3.14826724 0.08345476 3.15907928 0.05455213 3.16608839\n", - " 0.0421758 3.31269553 0.03215069 2.8805627 0.03557165 1.70664363\n", - " 0.05441129 1.59213142 0.16641457 1.60903061]\n", - "P_ = [0.0158852 0.57823753 0.01457275 3.39260617 0.02226484 3.48724591\n", - " 0.03247718 3.51971268 0.05019253 3.42851724 0.06674697 3.42212393\n", - " 0.08334459 3.39251342 0.09604052 3.37480277 0.10712262 3.35698527\n", - " 0.11403587 3.32227063 0.11808313 3.30304051 0.12363254 3.28600247\n", - " 0.12656486 3.27095905 0.12762582 3.24433432 0.12619408 3.22174916\n", - " 0.11051135 3.20704919 0.08929319 3.15155786 0.07591495 3.16090775\n", - " 0.05186163 3.19795951 0.0404323 3.23754199 0.0325969 2.72744282\n", - " 0.03720988 1.69668605 0.059281 1.59286616 0.16641457 1.60903061]\n", - "Depth = 24, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.936130\n", - " Iterations: 708\n", - " Function evaluations: 979\n", - "P = [0.01591366 0.5779946 0.0144981 3.43427423 0.02199642 3.47322502\n", - " 0.03247703 3.50932877 0.05018317 3.41646336 0.06701577 3.42480253\n", - " 0.08303467 3.378972 0.09635573 3.3746724 0.10674342 3.35386755\n", - " 0.11433448 3.32346593 0.11875256 3.29868394 0.12396727 3.27549491\n", - " 0.126072 3.27442211 0.1281345 3.23587139 0.12603891 3.2211364\n", - " 0.11087847 3.21256503 0.08982615 3.14646883 0.07587293 3.15173672\n", - " 0.05175009 3.19822642 0.04042319 3.31390701 0.03233081 2.81828938\n", - " 0.03699585 1.72820038 0.05892064 1.60744331 0.16657364 1.60570292]\n", - "P_ = [0.01591366 0.5779946 0.01455708 3.31526258 0.02137156 3.46997912\n", - " 0.03116695 3.5048158 0.04723215 3.43194093 0.06350898 3.42306521\n", - " 0.07902994 3.39042963 0.09247042 3.37592645 0.10328085 3.3608025\n", - " 0.11148783 3.33486654 0.11691169 3.30900977 0.12157719 3.28612321\n", - " 0.12501964 3.27495851 0.12701731 3.25675303 0.12726134 3.22973181\n", - " 0.12035375 3.21792214 0.10386103 3.19053296 0.08575646 3.1480053\n", - " 0.06984222 3.16335914 0.04939032 3.22232654 0.03907446 3.23130407\n", - " 0.03291394 2.68202826 0.03882292 1.71813729 0.06340618 1.60737079\n", - " 0.16657364 1.60570292]\n", - "Depth = 25, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.919615\n", - " Iterations: 1269\n", - " Function evaluations: 1660\n", - "P = [0.01592708 0.58856682 0.0141809 3.41726063 0.02094684 3.55343926\n", - " 0.03087051 3.49266507 0.04737523 3.4554299 0.06335642 3.40467904\n", - " 0.07932216 3.39471365 0.09191588 3.35688244 0.10538711 3.35761489\n", - " 0.11271698 3.33161046 0.11381599 3.29935961 0.12134016 3.28236578\n", - " 0.12407572 3.25760998 0.12690003 3.25954976 0.1249973 3.21838621\n", - " 0.11860422 3.20831879 0.1046811 3.20780032 0.0858527 3.13718215\n", - " 0.06926012 3.1507785 0.04902173 3.20478801 0.03931784 3.28852016\n", - " 0.03233242 2.83537947 0.03946237 1.75022039 0.06411168 1.58336387\n", - " 0.1688489 1.60621251]\n", - "P_ = [0.01592708 0.58856682 0.01425074 3.30411288 0.02040557 3.54254497\n", - " 0.02967967 3.49995797 0.04473447 3.46138753 0.06016018 3.41482921\n", - " 0.07549038 3.39710534 0.08838964 3.36747518 0.10107632 3.3573805\n", - " 0.11007823 3.34097205 0.11337639 3.31225995 0.11802953 3.28984307\n", - " 0.12276265 3.26949276 0.12543139 3.25854107 0.12606283 3.24143779\n", - " 0.12244007 3.21435924 0.1135919 3.20813214 0.09865601 3.1852025\n", - " 0.08120678 3.14098913 0.06440291 3.16374078 0.04708095 3.22153444\n", - " 0.03820017 3.21601765 0.03318801 2.70516038 0.04143432 1.73687187\n", - " 0.06830117 1.58427782 0.1688489 1.60621251]\n", - "Depth = 26, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.916369\n", - " Iterations: 1165\n", - " Function evaluations: 1537\n", - "P = [0.01590826 0.59034815 0.01406404 3.42409539 0.02039346 3.56588352\n", - " 0.02943694 3.50501548 0.04455808 3.47316278 0.0603689 3.42579577\n", - " 0.07560722 3.39741555 0.0883176 3.38291798 0.10079249 3.34019833\n", - " 0.11002997 3.34796607 0.11318154 3.31227947 0.11666846 3.29036809\n", - " 0.12218091 3.26806936 0.12667143 3.25859632 0.12596326 3.24836903\n", - " 0.12221622 3.20155704 0.11272468 3.21029633 0.09874289 3.19881896\n", - " 0.08107657 3.12890618 0.06488612 3.15366337 0.04686052 3.22536536\n", - " 0.03791537 3.28287478 0.03270957 2.81943099 0.04105096 1.75078244\n", - " 0.06767112 1.5925646 0.17037394 1.60813677]\n", - "P_ = [0.01590826 0.59034815 0.01413498 3.31510511 0.01990659 3.55497674\n", - " 0.02839346 3.51203871 0.04223175 3.47806319 0.05732836 3.43490481\n", - " 0.07209068 3.40396483 0.08489558 3.38682117 0.09695406 3.35334284\n", - " 0.10683238 3.34527724 0.1119694 3.32600509 0.11519323 3.29963829\n", - " 0.1196367 3.27836108 0.12442617 3.26333284 0.12634458 3.25387603\n", - " 0.12437797 3.22856396 0.11856562 3.20491831 0.10788483 3.20632339\n", - " 0.0933071 3.17730733 0.07671761 3.13557157 0.06072637 3.17020998\n", - " 0.0451403 3.23642486 0.03711448 3.21157573 0.03367204 2.69612539\n", - " 0.04309867 1.73861184 0.07162123 1.59316353 0.17037394 1.60813677]\n", - "Depth = 27, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.914513\n", - " Iterations: 1047\n", - " Function evaluations: 1388\n", - "P = [0.01600777 0.59441035 0.01405422 3.33891777 0.01979295 3.56156066\n", - " 0.02829462 3.49760951 0.04215104 3.47745948 0.05702065 3.44251439\n", - " 0.07210975 3.40230507 0.08455687 3.38989953 0.09675473 3.35770048\n", - " 0.10701156 3.33426116 0.11114707 3.33141276 0.11557739 3.29784735\n", - " 0.11811592 3.27580325 0.12338971 3.25682396 0.12565894 3.25302269\n", - " 0.12599619 3.23151734 0.12061265 3.19682548 0.10826721 3.20878563\n", - " 0.09314607 3.18192382 0.07661225 3.12296923 0.06048939 3.16593366\n", - " 0.04490189 3.22598292 0.03713216 3.26401763 0.03370435 2.81892455\n", - " 0.04332611 1.75929744 0.07128946 1.59559438 0.16964128 1.60349817]\n", - "P_ = [0.01600777 0.59441035 0.01412657 3.23726934 0.01936786 3.54506859\n", - " 0.02734999 3.5047152 0.04009824 3.48044467 0.05426702 3.4489857\n", - " 0.06875662 3.41124048 0.08132984 3.39311578 0.09314055 3.36724094\n", - " 0.10359262 3.34207427 0.1096154 3.33246772 0.11377244 3.31152215\n", - " 0.11698768 3.28560063 0.12085047 3.26596214 0.1244823 3.25499372\n", - " 0.12580883 3.24346476 0.12380289 3.21738362 0.11604026 3.20125517\n", - " 0.10322683 3.1998317 0.08824716 3.1644558 0.07243225 3.13410816\n", - " 0.0570255 3.17927794 0.04346305 3.23302638 0.03662434 3.19807791\n", - " 0.03477344 2.7011882 0.04539747 1.74717128 0.07493212 1.59588711\n", - " 0.16964128 1.60349817]\n", - "Depth = 28, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.910077\n", - " Iterations: 1064\n", - " Function evaluations: 1412\n", - "P = [0.01604876 0.59917317 0.01418592 3.29026085 0.01912754 3.56056517\n", - " 0.02720008 3.45269787 0.0396991 3.47981254 0.05442114 3.44456624\n", - " 0.06894596 3.41204104 0.08153736 3.39403042 0.09332452 3.37649946\n", - " 0.10295985 3.33557487 0.10931751 3.32716639 0.11370101 3.3127554\n", - " 0.11693971 3.28798582 0.12218574 3.25757439 0.12522601 3.25446058\n", - " 0.12604089 3.23918222 0.12336663 3.2154606 0.11648746 3.18990837\n", - " 0.10308171 3.20373462 0.08869912 3.16482409 0.07300445 3.12962168\n", - " 0.05759541 3.16663329 0.0432945 3.23243396 0.03652172 3.23465653\n", - " 0.03423085 2.83347968 0.04516579 1.76452914 0.07424692 1.59132831\n", - " 0.16938934 1.60122255]\n", - "P_ = [0.01604876 0.59917317 0.01425245 3.19415057 0.01877457 3.54125772\n", - " 0.02633516 3.46425508 0.03791353 3.47593902 0.05179221 3.45086022\n", - " 0.0658335 3.41901073 0.07838951 3.39853308 0.08995676 3.3815083\n", - " 0.09986278 3.3487292 0.10704692 3.33016942 0.11197892 3.31841686\n", - " 0.11555169 3.29860135 0.11975008 3.27169398 0.12370588 3.25601748\n", - " 0.12560435 3.24736706 0.12489478 3.22901581 0.1206641 3.20542222\n", - " 0.11169969 3.19484631 0.09845873 3.19122766 0.08421493 3.15476626\n", - " 0.06915219 3.13887458 0.05453093 3.18073343 0.04208508 3.23283085\n", - " 0.03619445 3.17734555 0.03540245 2.71894926 0.04724302 1.75215765\n", - " 0.07764486 1.59168167 0.16938934 1.60122255]\n", - "Depth = 29, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.893831\n", - " Iterations: 1450\n", - " Function evaluations: 1868\n", - "P = [0.01619052 0.59630725 0.01416911 3.22581289 0.01886948 3.60070094\n", - " 0.02624472 3.46866502 0.03806034 3.48639501 0.05104098 3.45926236\n", - " 0.06585272 3.41870177 0.07796344 3.40339247 0.09028553 3.37441692\n", - " 0.10210288 3.35814962 0.10674819 3.31647218 0.11390689 3.31972778\n", - " 0.1142882 3.29784373 0.12084572 3.28307081 0.12422392 3.25448078\n", - " 0.12671791 3.24235293 0.12744983 3.23162774 0.11971708 3.19406324\n", - " 0.11249982 3.19617529 0.09868937 3.19879257 0.08374447 3.15518477\n", - " 0.06866077 3.12748379 0.0546199 3.18037916 0.0417498 3.2161261\n", - " 0.03619391 3.21934461 0.03536893 2.8684144 0.04453944 1.75086731\n", - " 0.07628882 1.58186305 0.16926525 1.59137145]\n", - "P_ = [0.01619052 0.59630725 0.01423881 3.13514028 0.01854532 3.57484659\n", - " 0.02548176 3.4823239 0.0364306 3.48394949 0.04880294 3.4639404\n", - " 0.06278822 3.42709362 0.07504016 3.40708782 0.08688633 3.38241017\n", - " 0.09843543 3.36319809 0.10514636 3.33084371 0.11119152 3.3184929\n", - " 0.11413042 3.3068992 0.11790614 3.28969315 0.12259307 3.26828286\n", - " 0.12542792 3.24862596 0.12704601 3.23754509 0.12425007 3.21608381\n", - " 0.1169795 3.19486437 0.1077376 3.1970778 0.09405129 3.18525911\n", - " 0.07958345 3.14754312 0.06527159 3.14025164 0.05195712 3.18777508\n", - " 0.04079188 3.21668102 0.03608012 3.17094044 0.03631761 2.75280608\n", - " 0.04672905 1.73921184 0.0794949 1.58219092 0.16926525 1.59137145]\n", - "Depth = 30, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.891599\n", - " Iterations: 832\n", - " Function evaluations: 1181\n", - "2.4285714285714284 [9.71662794 9.09551952 6.29625365 6.22602508 4.65931241 4.55958218\n", - " 4.2311833 3.95421445 3.5517817 3.33394625 3.30150882 3.29516958\n", - " 3.23229165 3.20276678 3.20959895 3.16385971 3.04646704 3.0441384\n", - " 3.01068239 2.99390176 2.97909311 2.96751779 2.93136117 2.93613007\n", - " 2.91961466 2.91636898 2.91451262 2.91007683 2.89383082 2.89159868]\n", - "[[6.57155339 5.94790512 4.51084725 5.48476219 4.44827696 4.07086367\n", - " 4.45993119 3.76473244 3.75245393 3.70383406 2.54453644 2.75335922\n", - " 3.72365101 2.64914745 3.66152866 3.41308183 2.17660478 2.18383796\n", - " 2.54980097 1.72430929 2.24071873 1.8353618 2.04963403 1.97768311\n", - " 2.25839296 2.22977067 1.94603139 2.05226045 2.69504832 3.27724127]\n", - " [7.58106801 6.81608452 4.28714233 4.07123972 3.27046962 3.23940109\n", - " 3.69518164 3.2411352 2.8435791 2.91039551 2.52147765 2.7118309\n", - " 2.7196728 2.5657514 2.49654928 2.14986169 2.03773181 1.96011255\n", - " 1.99818881 1.99560667 2.10966328 1.86491841 1.83579189 1.98703992\n", - " 1.98133515 1.95306622 1.90928783 1.85507609 1.79545032 1.7963689 ]\n", - " [5.67675131 4.71392584 4.01740509 3.36995594 3.02811997 2.75900701\n", - " 2.07994453 1.87160639 1.76736629 1.60399896 1.51494314 1.48018664\n", - " 1.42851074 1.41006842 1.37578808 1.29188206 1.25021059 1.25293931\n", - " 1.22202663 1.23016691 1.26143882 1.20441019 1.17776388 1.18431374\n", - " 1.16553331 1.16956844 1.16569465 1.17659931 1.16990127 1.15831922]\n", - " [5.00995896 4.29025145 4.60820671 3.83390873 3.89848291 5.33118031\n", - " 3.55893822 3.40156727 4.09051018 4.16531197 3.86869824 2.74039918\n", - " 2.37252786 2.09790193 2.46381788 3.23389141 2.92683369 2.26271526\n", - " 2.22500107 1.72792525 1.99341501 2.13517458 2.55949815 2.08833212\n", - " 2.30394139 2.47254611 2.09431819 2.0108552 2.25457883 1.56109974]\n", - " [4.00096445 3.74521392 2.59257503 2.56365739 1.9185404 1.87747501\n", - " 1.74225195 1.62820595 1.46249835 1.3728014 1.35944481 1.35683453\n", - " 1.33094362 1.31878632 1.32159957 1.30276576 1.25442761 1.25346875\n", - " 1.23969275 1.23278308 1.2266854 1.22191909 1.20703107 1.20899474\n", - " 1.20219427 1.20085781 1.20009343 1.19826693 1.1915774 1.19065828]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]] [2.88402961 2.55133809 2.00161764 1.9323524 1.65638899 1.72779271\n", - " 1.55362475 1.39072472 1.39164078 1.37563419 1.18091003 1.10426105\n", - " 1.1575306 1.00416555 1.13192835 1.13914828 0.96458085 0.89130738\n", - " 0.92347102 0.79107912 0.88319212 0.82617841 0.8829719 0.84463636\n", - " 0.89113971 0.90258092 0.83154255 0.8293058 0.91065561 0.89836874]\n", - "[[0.1749857 0.07463194 0.26530491 0.16394175 0.18892849 0.25701077\n", - " 0.24542951 0.40504394 0.18547862 0.24113788 0.62032714 0.68408453\n", - " 0.11521194 0.57930818 0.29653581 0.32221821 0.75779012 0.76858176\n", - " 0.59269399 0.8271978 0.69201592 0.87101232 0.79114835 0.72852071\n", - " 0.64433266 0.66377712 0.77675308 0.72982301 0.58648573 0.44154865]\n", - " [0.17669094 0.20818569 0.40598211 0.40456531 0.54848127 0.5337594\n", - " 0.48446167 0.53759304 0.60295388 0.58451793 0.64895146 0.66165701\n", - " 0.62972457 0.66201878 0.67281148 0.75627098 0.78514972 0.80366385\n", - " 0.79430362 0.79961314 0.7524382 0.82370466 0.83214203 0.78138294\n", - " 0.78255631 0.78124579 0.80687807 0.80774629 0.84561002 0.84356134]\n", - " [0.1977358 0.23204622 0.30938238 0.39342279 0.41016143 0.46245125\n", - " 0.76102816 0.79966194 0.84980142 0.9167973 0.93013476 0.94105633\n", - " 0.96019643 0.9567664 0.95781341 0.97258171 0.97672161 0.97483651\n", - " 0.98345276 0.97827363 0.97171746 0.98525476 0.99020549 0.988242\n", - " 0.99105685 0.98789452 0.98718377 0.98332188 0.98342322 0.98330761]\n", - " [0.05772911 0.21353746 0.01841155 0.31450455 0.21424321 0.05404723\n", - " 0.43161435 0.34272799 0.28819124 0.28689022 0.1868918 0.50636735\n", - " 0.71458126 0.77159991 0.58971876 0.39292553 0.46431953 0.6325678\n", - " 0.69978407 0.80479284 0.72769493 0.74105124 0.53269212 0.73999712\n", - " 0.61502723 0.52602161 0.71815241 0.71745393 0.53403795 0.82706806]\n", - " [0.12450898 0.13546046 0.33397169 0.30579603 0.53279986 0.54005574\n", - " 0.5789386 0.62157361 0.67239022 0.70608977 0.71741324 0.71989795\n", - " 0.72816408 0.73770709 0.7462425 0.75395046 0.77610427 0.778063\n", - " 0.78739546 0.80304068 0.8044153 0.81655327 0.83574318 0.83983299\n", - " 0.85295023 0.85822598 0.86248183 0.86742561 0.8687046 0.87578262]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]] [0.07316505 0.08638618 0.13330526 0.15822304 0.18946143 0.18473244\n", - " 0.25014723 0.27066005 0.25988154 0.27354331 0.31037184 0.35130632\n", - " 0.31478783 0.37074004 0.3263122 0.31979469 0.37600852 0.39577129\n", - " 0.38576299 0.42129181 0.39482818 0.42375762 0.39819312 0.40779758\n", - " 0.38859233 0.3817165 0.41514492 0.41057707 0.38182615 0.39712683]\n", - "\n", - "Now using 3 solutions, set number 4\n", - "Calculating energy landscape ...\n", - "Optimization terminated successfully.\n", - " Current function value: 9.454284\n", - " Iterations: 25\n", - " Function evaluations: 47\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 9.454284\n", - " Iterations: 6\n", - " Function evaluations: 13\n", - "P = [0.11689081 1.96852709]\n", - "P_ = [0.11689081 1.96852709 0.11689081 1.96852709]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 7.732047\n", - " Iterations: 115\n", - " Function evaluations: 191\n", - "P = [-0.12018172 2.14320614 0.06157656 2.128436 ]\n", - "P_ = [-0.12018172 2.14320614 -0.02930258 2.13582107 0.06157656 2.128436 ]\n", - "Depth = 3, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 5.943679\n", - " Iterations: 480\n", - " Function evaluations: 716\n", - "P = [-0.08735662 2.60185821 -0.13204786 2.7836504 0.13470159 1.79277905]\n", - "P_ = [-0.08735662 2.60185821 -0.11715078 2.72305301 -0.04313138 2.45335995\n", - " 0.13470159 1.79277905]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.377762\n", - " Iterations: 438\n", - " Function evaluations: 635\n", - "P = [-0.08401732 2.61152392 -0.17229979 2.88088377 -0.08120406 2.65233542\n", - " 0.04101447 1.93901704]\n", - "P_ = [-0.08401732 2.61152392 -0.15022917 2.81354381 -0.12675193 2.7666096\n", - " -0.05064943 2.47400583 0.04101447 1.93901704]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.706772\n", - " Iterations: 172\n", - " Function evaluations: 255\n", - "P = [-0.07666095 2.62917004 -0.15042997 2.80977187 -0.13554052 3.06441513\n", - " -0.05555215 2.68259129 0.0399375 1.86584067]\n", - "P_ = [-0.07666095 2.62917004 -0.13567616 2.7736515 -0.1414963 2.96255782\n", - " -0.10354517 2.91168559 -0.03645422 2.51924116 0.0399375 1.86584067]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.596591\n", - " Iterations: 931\n", - " Function evaluations: 1288\n", - "P = [-0.0604275 2.55978384 -0.13423924 2.75246689 -0.16713957 2.82308014\n", - " -0.20917708 2.96916183 -0.04460611 2.48218776 0.02210934 2.16682027]\n", - "P_ = [-0.0604275 2.55978384 -0.12193728 2.72035305 -0.15617279 2.79954239\n", - " -0.18815832 2.89612098 -0.15432009 2.80683714 -0.03348687 2.42962651\n", - " 0.02210934 2.16682027]\n", - "Depth = 7, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.399031\n", - " Iterations: 262\n", - " Function evaluations: 377\n", - "P = [-0.06041856 2.56351758 -0.13013041 2.74531319 -0.15701277 2.84540181\n", - " -0.16089615 2.92475812 -0.16388341 3.0509978 -0.03290207 2.57777745\n", - " 0.02172198 2.06175928]\n", - "P_ = [-0.06041856 2.56351758 -0.12017157 2.71934239 -0.14933209 2.81680506\n", - " -0.15923184 2.89074827 -0.1621764 2.97886084 -0.12646017 2.91579199\n", - " -0.02509863 2.50406057 0.02172198 2.06175928]\n", - "Depth = 8, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.245156\n", - " Iterations: 216\n", - " Function evaluations: 332\n", - "P = [-0.05894689 2.53329365 -0.11895221 2.73681169 -0.14496625 2.82360812\n", - " -0.16187085 2.89700455 -0.15860324 2.97844459 -0.13318334 3.09310383\n", - " -0.02472753 2.60510077 0.02182975 2.05053713]\n", - "P_ = [-0.05894689 2.53329365 -0.11145154 2.71137193 -0.13846274 2.80190901\n", - " -0.15553162 2.86948089 -0.16023705 2.93772457 -0.14907078 3.0214418\n", - " -0.10606939 2.97110307 -0.01890787 2.53578031 0.02182975 2.05053713]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.191328\n", - " Iterations: 215\n", - " Function evaluations: 323\n", - "P = [-0.05627967 2.56882503 -0.11192992 2.74209114 -0.13598992 2.82478516\n", - " -0.15282146 2.89059246 -0.16005298 2.94693001 -0.14536441 3.03640058\n", - " -0.10787825 3.11667178 -0.01901951 2.62299398 0.02181028 2.03943187]\n", - "P_ = [-0.05627967 2.56882503 -0.10574656 2.72283935 -0.13064325 2.80640871\n", - " -0.14721095 2.86865669 -0.15683897 2.9218911 -0.15352473 2.98669471\n", - " -0.13286903 3.06315765 -0.08813186 3.0069656 -0.01448287 2.55815375\n", - " 0.02181028 2.03943187]\n", - "Depth = 10, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.870481\n", - " Iterations: 1814\n", - " Function evaluations: 2315\n", - "P = [-0.0306985 2.23579018 -0.07473286 2.47348749 -0.13221114 2.72591894\n", - " -0.15158949 2.81916082 -0.16561741 2.91966935 -0.15956114 2.93972592\n", - " -0.20929111 2.96103952 -0.08155651 3.61328684 -0.01556111 2.44145233\n", - " 0.02213518 1.82275055]\n", - "P_ = [-0.0306985 2.23579018 -0.07032942 2.44971776 -0.12071548 2.67543265\n", - " -0.14577598 2.79118825 -0.16000624 2.87946594 -0.16258927 2.92969764\n", - " -0.17945313 2.94825136 -0.17097073 3.15671371 -0.06835743 3.37891994\n", - " -0.01179148 2.37958215 0.02213518 1.82275055]\n", - "Depth = 11, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.743143\n", - " Iterations: 1718\n", - " Function evaluations: 2186\n", - "P = [-0.03181703 2.303299 -0.06722905 2.48387366 -0.10658628 2.7059763\n", - " -0.12691232 2.81372322 -0.14995734 2.856383 -0.16567508 2.91553804\n", - " -0.19096178 2.95652187 -0.22679973 3.02656619 -0.11783328 3.59044126\n", - " -0.00952401 2.50623663 0.01161819 1.73527444]\n", - "P_ = [-0.03181703 2.303299 -0.06400978 2.46745778 -0.09943042 2.665594\n", - " -0.12136885 2.78433769 -0.14157733 2.84087035 -0.15853065 2.88864938\n", - " -0.17716904 2.93416705 -0.20399376 2.98199253 -0.19708161 3.1803503\n", - " -0.09814069 3.39331315 -0.00760199 2.43614916 0.01161819 1.73527444]\n", - "Depth = 12, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.694979\n", - " Iterations: 463\n", - " Function evaluations: 626\n", - "P = [-0.0304279 2.29460814 -0.0661234 2.48061794 -0.09912705 2.69626058\n", - " -0.12809128 2.77521111 -0.14184104 2.85823386 -0.16161937 2.8925095\n", - " -0.15770942 2.97027335 -0.20409732 2.97756686 -0.19608124 3.07590253\n", - " -0.09739658 3.54705 -0.00739589 2.51244859 0.01165817 1.76211887]\n", - "P_ = [-0.0304279 2.29460814 -0.06314878 2.46511712 -0.09362644 2.66032014\n", - " -0.12085022 2.75547348 -0.13725779 2.83055961 -0.1533784 2.87822798\n", - " -0.15966439 2.93139142 -0.17703771 2.97331231 -0.2014253 3.01034541\n", - " -0.17141008 3.1936894 -0.08239647 3.37461644 -0.00580805 2.44992111\n", - " 0.01165817 1.76211887]\n", - "Depth = 13, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.637311\n", - " Iterations: 257\n", - " Function evaluations: 400\n", - "P = [-0.03013229 2.32413328 -0.06343267 2.47986998 -0.0951616 2.66426005\n", - " -0.12042471 2.76222673 -0.13888149 2.82484601 -0.15208371 2.88852132\n", - " -0.15917341 2.92324228 -0.17758792 2.98708375 -0.20049983 2.9973469\n", - " -0.17058652 3.11899456 -0.08187575 3.47669705 -0.0057598 2.5212015\n", - " 0.01155553 1.7989489 ]\n", - "P_ = [-0.03013229 2.32413328 -0.0608711 2.46789024 -0.09028023 2.63589235\n", - " -0.11459476 2.73961903 -0.13320248 2.80557854 -0.14700594 2.86403081\n", - " -0.15590124 2.90721722 -0.16767242 2.95270757 -0.18640019 2.99103111\n", - " -0.19129574 3.03477695 -0.1501148 3.20154129 -0.0701656 3.32969774\n", - " -0.00442785 2.46564361 0.01155553 1.7989489 ]\n", - "Depth = 14, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.570329\n", - " Iterations: 594\n", - " Function evaluations: 808\n", - "P = [-0.02627937 2.37910184 -0.06080925 2.52834294 -0.09217352 2.6713137\n", - " -0.11496737 2.75455364 -0.13309526 2.81852711 -0.14595447 2.86249222\n", - " -0.15711599 2.91833361 -0.16696965 2.94468183 -0.18904548 3.00244033\n", - " -0.19255248 3.0177971 -0.15371955 3.15120005 -0.06903224 3.4267585\n", - " -0.00440051 2.54431341 0.01159382 1.80541786]\n", - "P_ = [-2.62793674e-02 2.37910184e+00 -5.83428263e-02 2.51768286e+00\n", - " -8.76929057e-02 2.65088930e+00 -1.10082975e-01 2.73671651e+00\n", - " -1.27915861e-01 2.80024897e+00 -1.41361894e-01 2.84679039e+00\n", - " -1.52332481e-01 2.89440158e+00 -1.62042818e-01 2.93150772e+00\n", - " -1.76430718e-01 2.96943547e+00 -1.90297980e-01 3.00792489e+00\n", - " -1.81457357e-01 3.05591223e+00 -1.35572269e-01 3.21024829e+00\n", - " -5.97991391e-02 3.30069491e+00 -3.25805523e-03 2.49153515e+00\n", - " 1.15938194e-02 1.80541786e+00]\n", - "Depth = 15, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.526041\n", - " Iterations: 395\n", - " Function evaluations: 556\n", - "P = [-2.56203985e-02 2.36388824e+00 -5.83303087e-02 2.51345909e+00\n", - " -8.84011445e-02 2.68131390e+00 -1.11351981e-01 2.75507681e+00\n", - " -1.27135239e-01 2.80756825e+00 -1.43120112e-01 2.85445440e+00\n", - " -1.51540131e-01 2.89534457e+00 -1.64757300e-01 2.94330012e+00\n", - " -1.75552182e-01 2.96441855e+00 -1.92984854e-01 3.02017611e+00\n", - " -1.80482309e-01 3.03584357e+00 -1.34787077e-01 3.15579816e+00\n", - " -5.92169842e-02 3.38596283e+00 -3.06520204e-03 2.57941805e+00\n", - " 1.14884005e-02 1.81981406e+00]\n", - "P_ = [-2.56203985e-02 2.36388824e+00 -5.61496480e-02 2.50348770e+00\n", - " -8.43916998e-02 2.65893325e+00 -1.06761813e-01 2.74032423e+00\n", - " -1.22926370e-01 2.79357054e+00 -1.37791821e-01 2.83882569e+00\n", - " -1.48172123e-01 2.87898850e+00 -1.58589288e-01 2.92092087e+00\n", - " -1.69794912e-01 2.95315539e+00 -1.82525251e-01 2.98672158e+00\n", - " -1.88817339e-01 3.02539860e+00 -1.68296914e-01 3.06783146e+00\n", - " -1.19673059e-01 3.20183109e+00 -5.17300799e-02 3.27842352e+00\n", - " -2.09496187e-03 2.52877778e+00 1.14884005e-02 1.81981406e+00]\n", - "Depth = 16, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.495150\n", - " Iterations: 328\n", - " Function evaluations: 494\n", - "P = [-2.53740025e-02 2.35357629e+00 -5.65193733e-02 2.50936892e+00\n", - " -8.40092933e-02 2.65518279e+00 -1.07852897e-01 2.74296404e+00\n", - " -1.22880875e-01 2.78412345e+00 -1.38064007e-01 2.83534249e+00\n", - " -1.49488618e-01 2.87273675e+00 -1.59163463e-01 2.92260442e+00\n", - " -1.70421884e-01 2.94221000e+00 -1.81947159e-01 2.99011592e+00\n", - " -1.90181118e-01 3.03266822e+00 -1.68481563e-01 3.04497531e+00\n", - " -1.21248584e-01 3.18874566e+00 -5.15172772e-02 3.32979582e+00\n", - " -2.07817045e-03 2.59992463e+00 1.14699015e-02 1.83702616e+00]\n", - "P_ = [-2.53740025e-02 2.35357629e+00 -5.45727876e-02 2.49963188e+00\n", - " -8.05730533e-02 2.63695605e+00 -1.03382221e-01 2.72650505e+00\n", - " -1.19123880e-01 2.77383360e+00 -1.33319278e-01 2.81933654e+00\n", - " -1.45204389e-01 2.85871391e+00 -1.54930719e-01 2.90078731e+00\n", - " -1.64792674e-01 2.93240721e+00 -1.75464192e-01 2.96316884e+00\n", - " -1.85034893e-01 3.00607303e+00 -1.83400007e-01 3.03651418e+00\n", - " -1.56673318e-01 3.08091790e+00 -1.08173964e-01 3.21519257e+00\n", - " -4.53373889e-02 3.23856192e+00 -1.23141595e-03 2.55224348e+00\n", - " 1.14699015e-02 1.83702616e+00]\n", - "Depth = 17, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.410349\n", - " Iterations: 2304\n", - " Function evaluations: 2822\n", - "P = [-2.03275321e-02 2.27195518e+00 -5.23236632e-02 2.47621092e+00\n", - " -7.66185067e-02 2.66728304e+00 -1.02358496e-01 2.72621082e+00\n", - " -1.22685073e-01 2.78787518e+00 -1.38251806e-01 2.82926838e+00\n", - " -1.47577634e-01 2.85392047e+00 -1.68059599e-01 2.89761431e+00\n", - " -1.66658960e-01 2.92742410e+00 -1.95373540e-01 2.97606618e+00\n", - " -1.85936989e-01 2.98819350e+00 -2.41381221e-01 3.02762981e+00\n", - " -1.87289882e-01 3.04368163e+00 -1.12342613e-01 3.21349260e+00\n", - " -8.17803211e-02 2.99243954e+00 -1.07534210e-03 2.75530165e+00\n", - " 1.24338350e-03 2.00084591e+00]\n", - "P_ = [-2.03275321e-02 2.27195518e+00 -5.04415378e-02 2.46419588e+00\n", - " -7.37602898e-02 2.64480396e+00 -9.78161447e-02 2.71581180e+00\n", - " -1.17902349e-01 2.77336592e+00 -1.33673355e-01 2.81709391e+00\n", - " -1.44286165e-01 2.84521973e+00 -1.59625849e-01 2.87962273e+00\n", - " -1.67318084e-01 2.91339597e+00 -1.80171703e-01 2.95031449e+00\n", - " -1.91487901e-01 2.98105978e+00 -2.05505541e-01 3.00211220e+00\n", - " -2.25472004e-01 3.03235094e+00 -1.69655230e-01 3.08363716e+00\n", - " -1.06949267e-01 3.17448323e+00 -7.22856177e-02 2.96454096e+00\n", - " -9.38946479e-04 2.71092190e+00 1.24338350e-03 2.00084591e+00]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.375849\n", - " Iterations: 492\n", - " Function evaluations: 717\n", - "P = [-2.03968702e-02 2.29148836e+00 -5.01244605e-02 2.47439861e+00\n", - " -7.41307829e-02 2.65496083e+00 -9.67828467e-02 2.71265985e+00\n", - " -1.18378740e-01 2.76464997e+00 -1.31391161e-01 2.81524078e+00\n", - " -1.44790983e-01 2.83853878e+00 -1.59236879e-01 2.87657355e+00\n", - " -1.66500930e-01 2.90532803e+00 -1.81629607e-01 2.94911606e+00\n", - " -1.90535646e-01 2.97929908e+00 -2.03382226e-01 3.00895263e+00\n", - " -2.27904715e-01 3.04223374e+00 -1.69444401e-01 3.07452931e+00\n", - " -1.07699546e-01 3.19121857e+00 -7.36164302e-02 2.99770435e+00\n", - " -9.40008836e-04 2.74271231e+00 1.24741168e-03 2.02652036e+00]\n", - "P_ = [-2.03968702e-02 2.29148836e+00 -4.84729277e-02 2.46423693e+00\n", - " -7.14634138e-02 2.63489836e+00 -9.30075027e-02 2.70304334e+00\n", - " -1.13579653e-01 2.75309661e+00 -1.27776600e-01 2.80118778e+00\n", - " -1.40324376e-01 2.83077278e+00 -1.53619031e-01 2.86178225e+00\n", - " -1.63272463e-01 2.89254826e+00 -1.74065268e-01 2.92722204e+00\n", - " -1.85587846e-01 2.96253073e+00 -1.95531538e-01 2.99083101e+00\n", - " -2.11556389e-01 3.02004633e+00 -2.11665739e-01 3.05120473e+00\n", - " -1.55723322e-01 3.10046026e+00 -1.02019027e-01 3.15896620e+00\n", - " -6.55412723e-02 2.96937190e+00 -8.18485474e-04 2.70292387e+00\n", - " 1.24741168e-03 2.02652036e+00]\n", - "Depth = 19, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.351109\n", - " Iterations: 414\n", - " Function evaluations: 636\n", - "P = [-2.00815099e-02 2.30048567e+00 -4.84837649e-02 2.46752589e+00\n", - " -7.29295436e-02 2.64069568e+00 -9.34135200e-02 2.69906354e+00\n", - " -1.12726188e-01 2.75109388e+00 -1.27387353e-01 2.79287213e+00\n", - " -1.40867638e-01 2.83023963e+00 -1.53985569e-01 2.85316571e+00\n", - " -1.62150817e-01 2.88918101e+00 -1.74211785e-01 2.91985478e+00\n", - " -1.86513465e-01 2.96184106e+00 -1.94767101e-01 2.98910395e+00\n", - " -2.12615083e-01 3.02045389e+00 -2.12514906e-01 3.05806041e+00\n", - " -1.55712269e-01 3.09501477e+00 -1.02617084e-01 3.15955377e+00\n", - " -6.59073746e-02 2.99634657e+00 -8.13948825e-04 2.72799610e+00\n", - " 1.24697017e-03 2.07145570e+00]\n", - "P_ = [-2.00815099e-02 2.30048567e+00 -4.69889094e-02 2.45873430e+00\n", - " -7.03563037e-02 2.62246728e+00 -9.01792079e-02 2.68984756e+00\n", - " -1.08660363e-01 2.74014013e+00 -1.23529151e-01 2.78187785e+00\n", - " -1.36610706e-01 2.81843937e+00 -1.49152647e-01 2.84471926e+00\n", - " -1.58712818e-01 2.87401668e+00 -1.68498695e-01 2.90532510e+00\n", - " -1.80038896e-01 2.93974302e+00 -1.89988680e-01 2.97332017e+00\n", - " -2.01342673e-01 3.00065393e+00 -2.12583448e-01 3.03232964e+00\n", - " -1.97566843e-01 3.06778524e+00 -1.44534335e-01 3.10860193e+00\n", - " -9.68208139e-02 3.13378421e+00 -5.90554350e-02 2.96809915e+00\n", - " -7.05479404e-04 2.69344134e+00 1.24697017e-03 2.07145570e+00]\n", - "Depth = 20, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.326780\n", - " Iterations: 427\n", - " Function evaluations: 656\n", - "P = [-1.98639425e-02 2.29115594e+00 -4.74990723e-02 2.45984359e+00\n", - " -7.08643723e-02 2.63631526e+00 -9.17839432e-02 2.69176402e+00\n", - " -1.09005689e-01 2.73833930e+00 -1.23310963e-01 2.77531090e+00\n", - " -1.35490598e-01 2.81384538e+00 -1.49741562e-01 2.83759797e+00\n", - " -1.57378353e-01 2.86810778e+00 -1.67810504e-01 2.89803984e+00\n", - " -1.78998548e-01 2.93553384e+00 -1.90206114e-01 2.97268217e+00\n", - " -1.99671031e-01 2.99514917e+00 -2.13623938e-01 3.03320941e+00\n", - " -1.97848263e-01 3.06576270e+00 -1.45176504e-01 3.11015742e+00\n", - " -9.72412957e-02 3.15138427e+00 -5.92840064e-02 2.99472224e+00\n", - " -7.05912996e-04 2.70572017e+00 1.25402349e-03 2.10825304e+00]\n", - "P_ = [-1.98639425e-02 2.29115594e+00 -4.61173158e-02 2.45140921e+00\n", - " -6.85278423e-02 2.61866809e+00 -8.86460076e-02 2.68344671e+00\n", - " -1.05561340e-01 2.72902424e+00 -1.19734644e-01 2.76606800e+00\n", - " -1.31836708e-01 2.80228504e+00 -1.44753724e-01 2.82928456e+00\n", - " -1.54323637e-01 2.85590385e+00 -1.63116036e-01 2.88457041e+00\n", - " -1.73404526e-01 2.91678684e+00 -1.84041953e-01 2.95225059e+00\n", - " -1.93992081e-01 2.98166897e+00 -2.04554548e-01 3.00847025e+00\n", - " -2.08891235e-01 3.04297539e+00 -1.84680323e-01 3.07686138e+00\n", - " -1.35589462e-01 3.11840279e+00 -9.15477023e-02 3.12788496e+00\n", - " -5.34261971e-02 2.96582203e+00 -6.07916172e-04 2.67584681e+00\n", - " 1.25402349e-03 2.10825304e+00]\n", - "Depth = 21, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.293160\n", - " Iterations: 649\n", - " Function evaluations: 916\n", - "P = [-1.89155967e-02 2.26479569e+00 -4.70026658e-02 2.47402006e+00\n", - " -7.21883236e-02 2.63285395e+00 -9.18905638e-02 2.68984156e+00\n", - " -1.07564606e-01 2.72609902e+00 -1.19880866e-01 2.75958469e+00\n", - " -1.32084664e-01 2.79488087e+00 -1.41419097e-01 2.81763308e+00\n", - " -1.53900034e-01 2.84568071e+00 -1.62920859e-01 2.88265056e+00\n", - " -1.72280687e-01 2.91031706e+00 -1.81695320e-01 2.95109167e+00\n", - " -1.92126464e-01 2.98120794e+00 -1.97118091e-01 3.01168030e+00\n", - " -2.08933701e-01 3.05461958e+00 -1.87156962e-01 3.06838515e+00\n", - " -1.35734257e-01 3.12223817e+00 -9.20115116e-02 3.16796458e+00\n", - " -5.33675370e-02 2.97907783e+00 -6.12564284e-04 2.69483224e+00\n", - " 1.26116504e-03 2.11372280e+00]\n", - "P_ = [-1.89155967e-02 2.26479569e+00 -4.56651864e-02 2.46405700e+00\n", - " -6.97896896e-02 2.61772691e+00 -8.90759580e-02 2.68170047e+00\n", - " -1.04579074e-01 2.71919284e+00 -1.16948423e-01 2.75161191e+00\n", - " -1.28597865e-01 2.78479625e+00 -1.38307620e-01 2.81004901e+00\n", - " -1.49145392e-01 2.83499590e+00 -1.59054791e-01 2.86680634e+00\n", - " -1.67823626e-01 2.89714254e+00 -1.76763846e-01 2.92973354e+00\n", - " -1.86165810e-01 2.96399864e+00 -1.94028036e-01 2.99281646e+00\n", - " -2.01056628e-01 3.02599339e+00 -2.02711775e-01 3.05855260e+00\n", - " -1.74913461e-01 3.08120730e+00 -1.27406115e-01 3.13094796e+00\n", - " -8.64909438e-02 3.14098076e+00 -4.83432539e-02 2.95200682e+00\n", - " -5.23339078e-04 2.66716036e+00 1.26116504e-03 2.11372280e+00]\n", - "Depth = 22, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.267454\n", - " Iterations: 326\n", - " Function evaluations: 539\n", - "P = [-1.90186214e-02 2.28946997e+00 -4.53732059e-02 2.46057187e+00\n", - " -7.02824416e-02 2.62067800e+00 -8.90509370e-02 2.67832716e+00\n", - " -1.05050132e-01 2.72149388e+00 -1.17445889e-01 2.74746880e+00\n", - " -1.28975186e-01 2.78353071e+00 -1.38096450e-01 2.80560016e+00\n", - " -1.48213648e-01 2.83298892e+00 -1.59600283e-01 2.86402835e+00\n", - " -1.67535404e-01 2.89415675e+00 -1.76551093e-01 2.92488711e+00\n", - " -1.85900002e-01 2.96109299e+00 -1.94292767e-01 2.99178830e+00\n", - " -1.99555694e-01 3.02366281e+00 -2.02989775e-01 3.06018697e+00\n", - " -1.75485240e-01 3.07645431e+00 -1.27930385e-01 3.13424090e+00\n", - " -8.69087619e-02 3.15090704e+00 -4.85735157e-02 2.97102014e+00\n", - " -5.16057201e-04 2.68771782e+00 1.26944948e-03 2.14317380e+00]\n", - "P_ = [-1.90186214e-02 2.28946997e+00 -4.41752702e-02 2.45279451e+00\n", - " -6.80179656e-02 2.60612289e+00 -8.64915967e-02 2.67046591e+00\n", - " -1.02141187e-01 2.71364539e+00 -1.14628671e-01 2.74156541e+00\n", - " -1.25830832e-01 2.77369565e+00 -1.35194230e-01 2.79857806e+00\n", - " -1.44534667e-01 2.82302937e+00 -1.54942114e-01 2.85133040e+00\n", - " -1.63928531e-01 2.88046202e+00 -1.72043248e-01 2.90952193e+00\n", - " -1.80800597e-01 2.94134433e+00 -1.89333406e-01 2.97365016e+00\n", - " -1.96206558e-01 3.00337903e+00 -2.00648356e-01 3.03528414e+00\n", - " -1.95488538e-01 3.06462352e+00 -1.64677319e-01 3.08958762e+00\n", - " -1.20471908e-01 3.13727110e+00 -8.16812283e-02 3.12637701e+00\n", - " -4.42046558e-02 2.94526538e+00 -4.34897806e-04 2.66296582e+00\n", - " 1.26944948e-03 2.14317380e+00]\n", - "Depth = 23, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.238389\n", - " Iterations: 470\n", - " Function evaluations: 724\n", - "P = [-1.83947664e-02 2.29199858e+00 -4.48818197e-02 2.45447726e+00\n", - " -6.84808644e-02 2.61910211e+00 -8.72034824e-02 2.67508224e+00\n", - " -1.01796686e-01 2.71317555e+00 -1.15336933e-01 2.74394994e+00\n", - " -1.25782328e-01 2.77024077e+00 -1.35798538e-01 2.79340926e+00\n", - " -1.43354607e-01 2.81803692e+00 -1.54453397e-01 2.84785674e+00\n", - " -1.64509068e-01 2.87542581e+00 -1.71924692e-01 2.91067363e+00\n", - " -1.80037020e-01 2.93504251e+00 -1.89899725e-01 2.97625013e+00\n", - " -1.97808881e-01 3.00139141e+00 -1.97793245e-01 3.03835154e+00\n", - " -1.96141133e-01 3.06882447e+00 -1.67068540e-01 3.08200900e+00\n", - " -1.20614017e-01 3.14147372e+00 -8.16311409e-02 3.14179672e+00\n", - " -4.41663638e-02 2.96499432e+00 -4.36383554e-04 2.67567276e+00\n", - " 1.28102634e-03 2.16108468e+00]\n", - "P_ = [-1.83947664e-02 2.29199858e+00 -4.37302087e-02 2.44741297e+00\n", - " -6.64287735e-02 2.60478690e+00 -8.47614018e-02 2.66778048e+00\n", - " -9.92587373e-02 2.70655063e+00 -1.12393401e-01 2.73725985e+00\n", - " -1.23057443e-01 2.76338229e+00 -1.32750126e-01 2.78635798e+00\n", - " -1.40726409e-01 2.80947077e+00 -1.50110392e-01 2.83618811e+00\n", - " -1.60137037e-01 2.86343926e+00 -1.68378089e-01 2.89381598e+00\n", - " -1.75804501e-01 2.92232831e+00 -1.84325153e-01 2.95295886e+00\n", - " -1.92994612e-01 2.98608802e+00 -1.97803442e-01 3.01424711e+00\n", - " -1.97290428e-01 3.04762591e+00 -1.88556979e-01 3.07226391e+00\n", - " -1.56969731e-01 3.09493611e+00 -1.13834386e-01 3.14152989e+00\n", - " -7.67444309e-02 3.11873554e+00 -4.03637569e-02 2.93983593e+00\n", - " -3.61713558e-04 2.65329937e+00 1.28102634e-03 2.16108468e+00]\n", - "Depth = 24, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.177568\n", - " Iterations: 1572\n", - " Function evaluations: 1987\n", - "P = [-1.50862049e-02 2.19498175e+00 -4.43412502e-02 2.44354939e+00\n", - " -7.34196139e-02 2.66857437e+00 -8.66416252e-02 2.70654924e+00\n", - " -1.07213911e-01 2.72882496e+00 -1.15773905e-01 2.74675468e+00\n", - " -1.19925447e-01 2.77170795e+00 -1.30842063e-01 2.76406982e+00\n", - " -1.36098720e-01 2.80112460e+00 -1.47350431e-01 2.80630850e+00\n", - " -1.59509837e-01 2.83882650e+00 -1.69130764e-01 2.86458155e+00\n", - " -1.78951484e-01 2.90837356e+00 -1.84676051e-01 2.94176076e+00\n", - " -1.95713846e-01 2.98665709e+00 -2.10997851e-01 3.00613545e+00\n", - " -1.98636296e-01 3.04596080e+00 -1.91979457e-01 3.07337114e+00\n", - " -1.69522294e-01 3.06123222e+00 -1.13038091e-01 3.14674855e+00\n", - " -7.66269735e-02 3.20067340e+00 -4.05356135e-02 2.93645390e+00\n", - " -3.61252919e-04 2.64983922e+00 1.24386324e-03 2.15646104e+00]\n", - "P_ = [-1.50862049e-02 2.19498175e+00 -4.31222900e-02 2.43319240e+00\n", - " -7.09964169e-02 2.64982229e+00 -8.49888738e-02 2.70180238e+00\n", - " -1.03785197e-01 2.72511234e+00 -1.13990573e-01 2.74301932e+00\n", - " -1.18887561e-01 2.76546963e+00 -1.27658050e-01 2.76629761e+00\n", - " -1.34346501e-01 2.78877301e+00 -1.43131040e-01 2.80436454e+00\n", - " -1.54443418e-01 2.82527734e+00 -1.64721172e-01 2.85277716e+00\n", - " -1.74041124e-01 2.88647756e+00 -1.81575244e-01 2.92367603e+00\n", - " -1.89275132e-01 2.96046756e+00 -2.01445348e-01 2.99396147e+00\n", - " -2.06877333e-01 3.01941056e+00 -1.96694718e-01 3.05395548e+00\n", - " -1.86365166e-01 3.07033641e+00 -1.57754751e-01 3.07904812e+00\n", - " -1.06969571e-01 3.15573602e+00 -7.21155535e-02 3.16764597e+00\n", - " -3.71877502e-02 2.91256934e+00 -2.94373079e-04 2.62928179e+00\n", - " 1.24386324e-03 2.15646104e+00]\n", - "Depth = 25, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.142962\n", - " Iterations: 643\n", - " Function evaluations: 947\n", - "P = [-1.51179809e-02 2.24399404e+00 -4.12015515e-02 2.42756689e+00\n", - " -7.13650504e-02 2.64448504e+00 -8.56433007e-02 2.70315714e+00\n", - " -1.04427939e-01 2.72744156e+00 -1.14858665e-01 2.75016351e+00\n", - " -1.18871727e-01 2.76971694e+00 -1.27376678e-01 2.77486105e+00\n", - " -1.34562145e-01 2.78523285e+00 -1.43239668e-01 2.80188777e+00\n", - " -1.54119479e-01 2.82060066e+00 -1.64350957e-01 2.84907626e+00\n", - " -1.74340210e-01 2.88026345e+00 -1.81017728e-01 2.92258775e+00\n", - " -1.87671629e-01 2.95513981e+00 -2.01498722e-01 2.99462215e+00\n", - " -2.07851867e-01 3.01395373e+00 -1.97017026e-01 3.05467056e+00\n", - " -1.87513684e-01 3.07484773e+00 -1.60560521e-01 3.07193500e+00\n", - " -1.07297845e-01 3.15847480e+00 -7.18809203e-02 3.17024105e+00\n", - " -3.70922111e-02 2.93406804e+00 -2.94879936e-04 2.64783690e+00\n", - " 1.24471268e-03 2.18682204e+00]\n", - "P_ = [-1.51179809e-02 2.24399404e+00 -4.01582087e-02 2.42022398e+00\n", - " -6.89519705e-02 2.62713159e+00 -8.39299106e-02 2.69611649e+00\n", - " -1.01422397e-01 2.72355606e+00 -1.12772520e-01 2.74561912e+00\n", - " -1.17908592e-01 2.76502412e+00 -1.24995292e-01 2.77342070e+00\n", - " -1.32262796e-01 2.78191388e+00 -1.40115760e-01 2.79589200e+00\n", - " -1.49767554e-01 2.81311551e+00 -1.59849106e-01 2.83654700e+00\n", - " -1.69545368e-01 2.86529360e+00 -1.77545419e-01 2.90057911e+00\n", - " -1.83945445e-01 2.93691065e+00 -1.93202467e-01 2.97093274e+00\n", - " -2.03785854e-01 3.00158152e+00 -2.04384718e-01 3.02698312e+00\n", - " -1.94356090e-01 3.06032017e+00 -1.81044925e-01 3.07414867e+00\n", - " -1.49907986e-01 3.08924296e+00 -1.01631137e-01 3.16035740e+00\n", - " -6.77062752e-02 3.14190029e+00 -3.41484246e-02 2.91116955e+00\n", - " -2.33296232e-04 2.62939631e+00 1.24471268e-03 2.18682204e+00]\n", - "Depth = 26, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.114607\n", - " Iterations: 498\n", - " Function evaluations: 773\n", - "P = [-1.51563957e-02 2.25557435e+00 -3.97082574e-02 2.40669007e+00\n", - " -6.83772997e-02 2.62287022e+00 -8.43798037e-02 2.70222269e+00\n", - " -1.01990160e-01 2.72300453e+00 -1.13302305e-01 2.75037866e+00\n", - " -1.19459753e-01 2.76875231e+00 -1.24730062e-01 2.77610306e+00\n", - " -1.33361217e-01 2.78497227e+00 -1.39434777e-01 2.79203877e+00\n", - " -1.49472303e-01 2.81067669e+00 -1.59676707e-01 2.83229172e+00\n", - " -1.69238763e-01 2.86244390e+00 -1.77160026e-01 2.89575774e+00\n", - " -1.83622377e-01 2.93423620e+00 -1.92199075e-01 2.96357749e+00\n", - " -2.02797520e-01 3.00121193e+00 -2.05123030e-01 3.02187596e+00\n", - " -1.94917472e-01 3.06174288e+00 -1.83411029e-01 3.07553851e+00\n", - " -1.50470644e-01 3.08282876e+00 -1.01443912e-01 3.16206052e+00\n", - " -6.76532023e-02 3.15366880e+00 -3.43440835e-02 2.93007489e+00\n", - " -2.34473779e-04 2.64602680e+00 1.24652277e-03 2.20979509e+00]\n", - "P_ = [-1.51563957e-02 2.25557435e+00 -3.87639550e-02 2.40087792e+00\n", - " -6.61719888e-02 2.60624097e+00 -8.25333609e-02 2.69306664e+00\n", - " -9.92808746e-02 2.71980732e+00 -1.11126893e-01 2.74511440e+00\n", - " -1.18038803e-01 2.76451223e+00 -1.23311132e-01 2.77412401e+00\n", - " -1.30705477e-01 2.78224328e+00 -1.37332391e-01 2.78959267e+00\n", - " -1.45611716e-01 2.80350826e+00 -1.55359459e-01 2.82314690e+00\n", - " -1.64825506e-01 2.84852751e+00 -1.73199395e-01 2.87910082e+00\n", - " -1.80142650e-01 2.91351703e+00 -1.87250980e-01 2.94664983e+00\n", - " -1.96275400e-01 2.97805228e+00 -2.03602504e-01 3.00836486e+00\n", - " -2.01982858e-01 3.03414270e+00 -1.91819583e-01 3.06545709e+00\n", - " -1.75809401e-01 3.07722088e+00 -1.41042426e-01 3.09806564e+00\n", - " -9.62453413e-02 3.16076949e+00 -6.38098424e-02 3.12786950e+00\n", - " -3.17202673e-02 2.90822503e+00 -1.77512374e-04 2.62924866e+00\n", - " 1.24652277e-03 2.20979509e+00]\n", - "Depth = 27, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.091745\n", - " Iterations: 559\n", - " Function evaluations: 840\n", - "P = [-1.46077287e-02 2.27040411e+00 -3.88730083e-02 2.38842706e+00\n", - " -6.65089885e-02 2.60139200e+00 -8.30007265e-02 2.70108353e+00\n", - " -1.00704208e-01 2.73009766e+00 -1.11273897e-01 2.75275798e+00\n", - " -1.18597965e-01 2.76666166e+00 -1.23926742e-01 2.77830441e+00\n", - " -1.30506982e-01 2.78531150e+00 -1.38545743e-01 2.78845503e+00\n", - " -1.45303384e-01 2.79924609e+00 -1.54582259e-01 2.82066183e+00\n", - " -1.64868037e-01 2.84404409e+00 -1.73954900e-01 2.87674288e+00\n", - " -1.79574180e-01 2.91007546e+00 -1.85941271e-01 2.94372286e+00\n", - " -1.95855417e-01 2.97441427e+00 -2.01093115e-01 3.00720611e+00\n", - " -2.01349736e-01 3.02974095e+00 -1.92456485e-01 3.06414162e+00\n", - " -1.80343106e-01 3.08152132e+00 -1.41402146e-01 3.09213256e+00\n", - " -9.63912326e-02 3.16151213e+00 -6.40630560e-02 3.14282872e+00\n", - " -3.17339976e-02 2.93324509e+00 -1.77324346e-04 2.64079746e+00\n", - " 1.24718232e-03 2.23111963e+00]\n", - "P_ = [-1.46077287e-02 2.27040411e+00 -3.79742942e-02 2.38405584e+00\n", - " -6.44618788e-02 2.58561682e+00 -8.11683112e-02 2.69000669e+00\n", - " -9.80814699e-02 2.72579927e+00 -1.09316547e-01 2.74856162e+00\n", - " -1.16970394e-01 2.76357195e+00 -1.22545207e-01 2.77528592e+00\n", - " -1.28557281e-01 2.78323533e+00 -1.35866156e-01 2.78740719e+00\n", - " -1.42800554e-01 2.79524940e+00 -1.50801977e-01 2.81193690e+00\n", - " -1.60296580e-01 2.83365197e+00 -1.69579743e-01 2.86099902e+00\n", - " -1.76660479e-01 2.89279190e+00 -1.82403998e-01 2.92502986e+00\n", - " -1.89980368e-01 2.95622677e+00 -1.97795305e-01 2.98655940e+00\n", - " -2.01178655e-01 3.01471772e+00 -1.98714698e-01 3.03993374e+00\n", - " -1.89315980e-01 3.06864747e+00 -1.71689560e-01 3.08387938e+00\n", - " -1.33066792e-01 3.10498063e+00 -9.16018731e-02 3.15874422e+00\n", - " -6.04709384e-02 3.11954165e+00 -2.93964663e-02 2.91158231e+00\n", - " -1.24564840e-04 2.62562421e+00 1.24718232e-03 2.23111963e+00]\n", - "Depth = 28, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.071563\n", - " Iterations: 606\n", - " Function evaluations: 909\n", - "P = [-1.44031851e-02 2.26319995e+00 -3.81173098e-02 2.38939107e+00\n", - " -6.37888150e-02 2.58391923e+00 -8.28337252e-02 2.68658602e+00\n", - " -9.85682151e-02 2.73512369e+00 -1.10185704e-01 2.75848141e+00\n", - " -1.16805119e-01 2.77182989e+00 -1.23234325e-01 2.77709180e+00\n", - " -1.28997098e-01 2.78557779e+00 -1.35903573e-01 2.78898721e+00\n", - " -1.43452290e-01 2.79371898e+00 -1.50319637e-01 2.80805512e+00\n", - " -1.59396141e-01 2.83008745e+00 -1.68820290e-01 2.85869954e+00\n", - " -1.76107048e-01 2.89179734e+00 -1.81456691e-01 2.91940933e+00\n", - " -1.89311716e-01 2.95242058e+00 -1.94399596e-01 2.98324409e+00\n", - " -2.00059699e-01 3.01340654e+00 -2.00229013e-01 3.03523070e+00\n", - " -1.90127203e-01 3.07059467e+00 -1.76258324e-01 3.08280171e+00\n", - " -1.33280128e-01 3.10135865e+00 -9.19333480e-02 3.16228788e+00\n", - " -6.06817658e-02 3.13601063e+00 -2.94500403e-02 2.92619047e+00\n", - " -1.24319459e-04 2.63961521e+00 1.25232437e-03 2.24364671e+00]\n", - "P_ = [-1.44031851e-02 2.26319995e+00 -3.72703768e-02 2.38488424e+00\n", - " -6.19551361e-02 2.57002436e+00 -8.07931991e-02 2.67558601e+00\n", - " -9.63204308e-02 2.72818974e+00 -1.08111152e-01 2.75431039e+00\n", - " -1.15386673e-01 2.76896950e+00 -1.21627024e-01 2.77577632e+00\n", - " -1.27350592e-01 2.78315322e+00 -1.33683635e-01 2.78789132e+00\n", - " -1.40756320e-01 2.79202906e+00 -1.47621751e-01 2.80242306e+00\n", - " -1.55506211e-01 2.82064502e+00 -1.64444793e-01 2.84541536e+00\n", - " -1.72463669e-01 2.87524844e+00 -1.78590811e-01 2.90461719e+00\n", - " -1.84823130e-01 2.93355701e+00 -1.91310526e-01 2.96452982e+00\n", - " -1.96421061e-01 2.99401639e+00 -2.00114121e-01 3.02042145e+00\n", - " -1.97342781e-01 3.04533469e+00 -1.86659983e-01 3.07364643e+00\n", - " -1.67048710e-01 3.08677819e+00 -1.25896774e-01 3.11223887e+00\n", - " -8.74688363e-02 3.15853399e+00 -5.73355095e-02 3.11352990e+00\n", - " -2.73553459e-02 2.90572080e+00 -7.51536086e-05 2.62547348e+00\n", - " 1.25232437e-03 2.24364671e+00]\n", - "Depth = 29, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.044297\n", - " Iterations: 1241\n", - " Function evaluations: 1615\n", - "P = [-1.37831656e-02 2.27046545e+00 -3.49354779e-02 2.41421577e+00\n", - " -6.27353800e-02 2.57555636e+00 -8.20198980e-02 2.66114473e+00\n", - " -9.80313413e-02 2.73633155e+00 -1.09708740e-01 2.76872467e+00\n", - " -1.19454424e-01 2.78496340e+00 -1.24983225e-01 2.78823484e+00\n", - " -1.27355639e-01 2.80003950e+00 -1.33848338e-01 2.79806667e+00\n", - " -1.44744421e-01 2.80993879e+00 -1.46694648e-01 2.80282080e+00\n", - " -1.53413133e-01 2.81194841e+00 -1.61263240e-01 2.83520540e+00\n", - " -1.70663734e-01 2.87268141e+00 -1.78271391e-01 2.90458266e+00\n", - " -1.80533452e-01 2.93099977e+00 -1.91746135e-01 2.95295998e+00\n", - " -1.94825522e-01 2.99089055e+00 -2.00058500e-01 3.01792449e+00\n", - " -2.01659285e-01 3.04816004e+00 -1.84570975e-01 3.08189526e+00\n", - " -1.72390271e-01 3.08650431e+00 -1.22259604e-01 3.10772107e+00\n", - " -8.82236092e-02 3.16385012e+00 -5.76244357e-02 3.14931471e+00\n", - " -2.73658933e-02 2.94471028e+00 -7.44570753e-05 2.62213176e+00\n", - " 1.26259785e-03 2.22958727e+00]\n", - "P_ = [-1.37831656e-02 2.27046545e+00 -3.42060878e-02 2.40925886e+00\n", - " -6.08181454e-02 2.56442942e+00 -8.00249479e-02 2.65229076e+00\n", - " -9.58228664e-02 2.72596095e+00 -1.07695395e-01 2.76313965e+00\n", - " -1.17438075e-01 2.78160367e+00 -1.23648687e-01 2.78744518e+00\n", - " -1.26701180e-01 2.79678304e+00 -1.31833363e-01 2.79867892e+00\n", - " -1.40987151e-01 2.80584496e+00 -1.45954907e-01 2.80552073e+00\n", - " -1.50633070e-01 2.80817147e+00 -1.57744227e-01 2.82477985e+00\n", - " -1.66125565e-01 2.85458954e+00 -1.74336396e-01 2.88808201e+00\n", - " -1.79285418e-01 2.91642481e+00 -1.85173183e-01 2.94008675e+00\n", - " -1.92914178e-01 2.96734744e+00 -1.96629997e-01 3.00021260e+00\n", - " -2.00555295e-01 3.02730793e+00 -1.96945268e-01 3.05746630e+00\n", - " -1.81630805e-01 3.08300779e+00 -1.62018409e-01 3.09089399e+00\n", - " -1.16391329e-01 3.11739849e+00 -8.40030336e-02 3.16184524e+00\n", - " -5.44942416e-02 3.12814874e+00 -2.54837253e-02 2.92246348e+00\n", - " -2.83517329e-05 2.60859574e+00 1.26259785e-03 2.22958727e+00]\n", - "Depth = 30, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.028169\n", - " Iterations: 712\n", - " Function evaluations: 1061\n", - "1.6 [9.45428431 7.73204653 5.9436793 5.37776193 4.70677244 3.59659132\n", - " 3.39903125 3.24515611 3.19132803 2.87048125 2.74314322 2.69497931\n", - " 2.63731118 2.57032937 2.52604078 2.49514988 2.41034932 2.37584949\n", - " 2.35110895 2.32677959 2.29315992 2.267454 2.23838903 2.17756777\n", - " 2.14296241 2.11460658 2.09174483 2.07156304 2.04429703 2.02816922]\n", - "[[6.57155339 5.94790512 4.51084725 5.48476219 4.44827696 4.07086367\n", - " 4.45993119 3.76473244 3.75245393 3.70383406 2.54453644 2.75335922\n", - " 3.72365101 2.64914745 3.66152866 3.41308183 2.17660478 2.18383796\n", - " 2.54980097 1.72430929 2.24071873 1.8353618 2.04963403 1.97768311\n", - " 2.25839296 2.22977067 1.94603139 2.05226045 2.69504832 3.27724127]\n", - " [7.58106801 6.81608452 4.28714233 4.07123972 3.27046962 3.23940109\n", - " 3.69518164 3.2411352 2.8435791 2.91039551 2.52147765 2.7118309\n", - " 2.7196728 2.5657514 2.49654928 2.14986169 2.03773181 1.96011255\n", - " 1.99818881 1.99560667 2.10966328 1.86491841 1.83579189 1.98703992\n", - " 1.98133515 1.95306622 1.90928783 1.85507609 1.79545032 1.7963689 ]\n", - " [5.67675131 4.71392584 4.01740509 3.36995594 3.02811997 2.75900701\n", - " 2.07994453 1.87160639 1.76736629 1.60399896 1.51494314 1.48018664\n", - " 1.42851074 1.41006842 1.37578808 1.29188206 1.25021059 1.25293931\n", - " 1.22202663 1.23016691 1.26143882 1.20441019 1.17776388 1.18431374\n", - " 1.16553331 1.16956844 1.16569465 1.17659931 1.16990127 1.15831922]\n", - " [5.00995896 4.29025145 4.60820671 3.83390873 3.89848291 5.33118031\n", - " 3.55893822 3.40156727 4.09051018 4.16531197 3.86869824 2.74039918\n", - " 2.37252786 2.09790193 2.46381788 3.23389141 2.92683369 2.26271526\n", - " 2.22500107 1.72792525 1.99341501 2.13517458 2.55949815 2.08833212\n", - " 2.30394139 2.47254611 2.09431819 2.0108552 2.25457883 1.56109974]\n", - " [4.00096445 3.74521392 2.59257503 2.56365739 1.9185404 1.87747501\n", - " 1.74225195 1.62820595 1.46249835 1.3728014 1.35944481 1.35683453\n", - " 1.33094362 1.31878632 1.32159957 1.30276576 1.25442761 1.25346875\n", - " 1.23969275 1.23278308 1.2266854 1.22191909 1.20703107 1.20899474\n", - " 1.20219427 1.20085781 1.20009343 1.19826693 1.1915774 1.19065828]\n", - " [5.90892769 4.83252908 3.71479956 3.36110121 2.94173277 2.24786958\n", - " 2.12439453 2.02822257 1.99458002 1.79405078 1.71446451 1.68436207\n", - " 1.64831949 1.60645585 1.57877549 1.55946868 1.50646832 1.48490593\n", - " 1.46944309 1.45423724 1.43322495 1.41715875 1.39899314 1.36097986\n", - " 1.33935151 1.32162911 1.30734052 1.2947269 1.27768564 1.26760576]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]] [3.47492238 3.03459099 2.3730976 2.26846252 1.95056226 1.95257967\n", - " 1.76606421 1.59354698 1.59109879 1.55503927 1.35235648 1.27269726\n", - " 1.32236255 1.16481114 1.2898059 1.29509514 1.11522768 1.03979798\n", - " 1.07041533 0.93650284 1.02651462 0.96789428 1.02287122 0.98073435\n", - " 1.02507486 1.03474384 0.9622766 0.95877849 1.03842418 1.02512932]\n", - "[[0.1749857 0.07463194 0.26530491 0.16394175 0.18892849 0.25701077\n", - " 0.24542951 0.40504394 0.18547862 0.24113788 0.62032714 0.68408453\n", - " 0.11521194 0.57930818 0.29653581 0.32221821 0.75779012 0.76858176\n", - " 0.59269399 0.8271978 0.69201592 0.87101232 0.79114835 0.72852071\n", - " 0.64433266 0.66377712 0.77675308 0.72982301 0.58648573 0.44154865]\n", - " [0.17669094 0.20818569 0.40598211 0.40456531 0.54848127 0.5337594\n", - " 0.48446167 0.53759304 0.60295388 0.58451793 0.64895146 0.66165701\n", - " 0.62972457 0.66201878 0.67281148 0.75627098 0.78514972 0.80366385\n", - " 0.79430362 0.79961314 0.7524382 0.82370466 0.83214203 0.78138294\n", - " 0.78255631 0.78124579 0.80687807 0.80774629 0.84561002 0.84356134]\n", - " [0.1977358 0.23204622 0.30938238 0.39342279 0.41016143 0.46245125\n", - " 0.76102816 0.79966194 0.84980142 0.9167973 0.93013476 0.94105633\n", - " 0.96019643 0.9567664 0.95781341 0.97258171 0.97672161 0.97483651\n", - " 0.98345276 0.97827363 0.97171746 0.98525476 0.99020549 0.988242\n", - " 0.99105685 0.98789452 0.98718377 0.98332188 0.98342322 0.98330761]\n", - " [0.05772911 0.21353746 0.01841155 0.31450455 0.21424321 0.05404723\n", - " 0.43161435 0.34272799 0.28819124 0.28689022 0.1868918 0.50636735\n", - " 0.71458126 0.77159991 0.58971876 0.39292553 0.46431953 0.6325678\n", - " 0.69978407 0.80479284 0.72769493 0.74105124 0.53269212 0.73999712\n", - " 0.61502723 0.52602161 0.71815241 0.71745393 0.53403795 0.82706806]\n", - " [0.12450898 0.13546046 0.33397169 0.30579603 0.53279986 0.54005574\n", - " 0.5789386 0.62157361 0.67239022 0.70608977 0.71741324 0.71989795\n", - " 0.72816408 0.73770709 0.7462425 0.75395046 0.77610427 0.778063\n", - " 0.78739546 0.80304068 0.8044153 0.81655327 0.83574318 0.83983299\n", - " 0.85295023 0.85822598 0.86248183 0.86742561 0.8687046 0.87578262]\n", - " [0.15384579 0.23299282 0.34316369 0.40381029 0.48323069 0.60966505\n", - " 0.65090211 0.6781041 0.69468559 0.73757271 0.76352272 0.78064924\n", - " 0.80250928 0.8256876 0.84161068 0.85173433 0.88960447 0.89427145\n", - " 0.89713168 0.89784489 0.90396968 0.90972365 0.91944211 0.93551855\n", - " 0.93997379 0.94289646 0.9440385 0.94476954 0.94821036 0.94920811]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]] [0.08854963 0.10968546 0.16762163 0.19860407 0.23778449 0.24569894\n", - " 0.31523744 0.33847046 0.3293501 0.34730058 0.38672411 0.42937124\n", - " 0.39503876 0.4533088 0.41047326 0.40496812 0.46496897 0.48519844\n", - " 0.47547616 0.5110763 0.48522515 0.51472999 0.49013733 0.50134943\n", - " 0.48258971 0.47600615 0.50954877 0.50505403 0.47664719 0.49204764]\n", - "\n", - "Now using 4 solutions, set number 1\n", - "Calculating energy landscape ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 7.253294\n", - " Iterations: 27\n", - " Function evaluations: 53\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 7.253294\n", - " Iterations: 6\n", - " Function evaluations: 13\n", - "P = [0.16618058 1.96400103]\n", - "P_ = [0.16618058 1.96400103 0.16618058 1.96400103]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.562815\n", - " Iterations: 46\n", - " Function evaluations: 82\n", - "P = [0.12625088 2.03310653 0.22890462 1.84889789]\n", - "P_ = [0.12625088 2.03310653 0.17757775 1.94100221 0.22890462 1.84889789]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.670307\n", - " Iterations: 57\n", - " Function evaluations: 96\n", - "P = [0.09834632 2.0748473 0.21783049 1.9098336 0.23497436 1.7663227 ]\n", - "P_ = [0.09834632 2.0748473 0.17800243 1.96483817 0.22354511 1.86199663\n", - " 0.23497436 1.7663227 ]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.170993\n", - " Iterations: 71\n", - " Function evaluations: 119\n", - "P = [0.09736598 2.08683431 0.18071437 1.91252354 0.21791385 1.82005028\n", - " 0.26434961 1.69255596]\n", - "P_ = [0.09736598 2.08683431 0.15987727 1.95610123 0.19931411 1.86628691\n", - " 0.22952279 1.7881767 0.26434961 1.69255596]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.684926\n", - " Iterations: 308\n", - " Function evaluations: 431\n", - "P = [0.13134849 2.06098637 0.15090955 1.87390065 0.2262351 1.88972906\n", - " 0.32195049 1.78165728 0.38359012 1.70612871]\n", - "P_ = [0.13134849 2.06098637 0.14699734 1.91131779 0.19610488 1.8833977\n", - " 0.26452126 1.84650035 0.33427842 1.76655157 0.38359012 1.70612871]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.545421\n", - " Iterations: 220\n", - " Function evaluations: 321\n", - "P = [0.11993401 2.14426306 0.17304424 1.82356629 0.16896733 1.91020814\n", - " 0.30168452 1.82913187 0.36119893 1.74608584 0.32441941 1.66514002]\n", - "P_ = [0.11993401 2.14426306 0.16419253 1.87701575 0.1703263 1.88132752\n", - " 0.23532592 1.86967001 0.32152266 1.80144986 0.35506901 1.73259487\n", - " 0.32441941 1.66514002]\n", - "Depth = 7, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.566772\n", - " Iterations: 164\n", - " Function evaluations: 239\n", - "P = [0.11817735 2.12607939 0.17634556 1.89451999 0.17345182 1.87535056\n", - " 0.26243252 1.85278294 0.30884593 1.77533856 0.2908882 1.72402289\n", - " 0.33889277 1.63757126]\n", - "P_ = [0.11817735 2.12607939 0.16803582 1.9275999 0.1742786 1.88082754\n", - " 0.22429793 1.86245477 0.28232398 1.81959249 0.30371515 1.76067694\n", - " 0.297746 1.71167265 0.33889277 1.63757126]\n", - "Depth = 8, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.491338\n", - " Iterations: 193\n", - " Function evaluations: 281\n", - "P = [0.09181818 2.11622126 0.17254683 1.96049421 0.2000407 1.88822439\n", - " 0.25092851 1.83148842 0.29951288 1.75856421 0.30212084 1.71415572\n", - " 0.33164167 1.62872971 0.33065391 1.57382747]\n", - "P_ = [0.09181818 2.11622126 0.16245575 1.97996009 0.19316723 1.90629185\n", - " 0.23184558 1.85276441 0.27522069 1.79502632 0.30049086 1.74191103\n", - " 0.30950105 1.69279921 0.3315182 1.62186693 0.33065391 1.57382747]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.464166\n", - " Iterations: 133\n", - " Function evaluations: 211\n", - "P = [0.08762545 2.11194835 0.16490925 1.96355944 0.19466205 1.90268941\n", - " 0.23882691 1.85125113 0.28235719 1.78734013 0.30017538 1.76420169\n", - " 0.31464514 1.68366233 0.32744854 1.61349262 0.32693047 1.60852589]\n", - "P_ = [0.08762545 2.11194835 0.15632216 1.9800471 0.18805031 1.91621608\n", - " 0.22410529 1.86839722 0.2630104 1.81574502 0.29027639 1.77705638\n", - " 0.30499864 1.73735523 0.31749034 1.66806906 0.32739098 1.61294076\n", - " 0.32693047 1.60852589]\n", - "Depth = 10, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.435400\n", - " Iterations: 257\n", - " Function evaluations: 359\n", - "P = [0.08232607 2.09664044 0.14656278 1.96581392 0.20808878 1.92978993\n", - " 0.24027539 1.85459128 0.28737648 1.79270345 0.29191098 1.76783289\n", - " 0.31203372 1.69788809 0.29615091 1.62235857 0.31428607 1.62164662\n", - " 0.33706541 1.60927934]\n", - "P_ = [0.08232607 2.09664044 0.14013911 1.97889657 0.19578358 1.93699473\n", - " 0.23061941 1.87715088 0.26853605 1.81745859 0.28964373 1.78026817\n", - " 0.29996007 1.73985497 0.30726888 1.67522923 0.29977794 1.62221618\n", - " 0.316564 1.62040989 0.33706541 1.60927934]\n", - "Depth = 11, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.433891\n", - " Iterations: 157\n", - " Function evaluations: 248\n", - "P = [0.08194763 2.11394009 0.14106071 1.96627065 0.19867741 1.95642716\n", - " 0.23673545 1.86973709 0.2664463 1.82167914 0.29191393 1.79407324\n", - " 0.30606518 1.72684959 0.29755744 1.65739752 0.29759555 1.64443984\n", - " 0.32093897 1.62088959 0.34212837 1.57457394]\n", - "P_ = [0.08194763 2.11394009 0.1356868 1.97969514 0.18820165 1.95821688\n", - " 0.22635599 1.89337984 0.25564235 1.83915476 0.28033773 1.80662138\n", - " 0.29834632 1.76351704 0.30297146 1.70159429 0.29756783 1.65386361\n", - " 0.30183981 1.64015798 0.32286528 1.61667907 0.34212837 1.57457394]\n", - "Depth = 12, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.448624\n", - " Iterations: 218\n", - " Function evaluations: 328\n", - "P = [0.07951773 2.10654746 0.13546842 1.9784905 0.19069159 1.9795462\n", - " 0.23429149 1.89339894 0.25803613 1.83856965 0.28194517 1.81437279\n", - " 0.3001872 1.75118722 0.28412612 1.68561281 0.29961957 1.66428509\n", - " 0.30084606 1.63720242 0.32942162 1.60423043 0.35443378 1.59068593]\n", - "P_ = [0.07951773 2.10654746 0.13080587 1.98916191 0.18148773 1.97937025\n", - " 0.22339152 1.91493576 0.25012125 1.85684608 0.27198307 1.82445482\n", - " 0.29106619 1.78278 0.29349508 1.72386455 0.2892906 1.67850357\n", - " 0.29992619 1.65751442 0.30560865 1.63170709 0.33150597 1.60310172\n", - " 0.35443378 1.59068593]\n", - "Depth = 13, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.456639\n", - " Iterations: 129\n", - " Function evaluations: 219\n", - "P = [0.08192455 2.11605336 0.13085921 1.9839502 0.18269045 1.98788765\n", - " 0.22724875 1.91090896 0.24945116 1.85832767 0.27487183 1.83419184\n", - " 0.28900381 1.77024766 0.2872291 1.71348241 0.29276316 1.69100129\n", - " 0.2969905 1.65192352 0.30479133 1.62311309 0.33645632 1.60676742\n", - " 0.35740037 1.57866243]\n", - "P_ = [0.08192455 2.11605336 0.12709501 1.99411198 0.17471641 1.98728188\n", - " 0.21696607 1.92867327 0.24261965 1.87450653 0.26509465 1.84347485\n", - " 0.28248136 1.79976036 0.28818471 1.74404831 0.28935758 1.70483582\n", - " 0.29406388 1.67897736 0.29879069 1.64527496 0.30966287 1.62059837\n", - " 0.3380674 1.6046055 0.35740037 1.57866243]\n", - "Depth = 14, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.452884\n", - " Iterations: 287\n", - " Function evaluations: 416\n", - "P = [0.0822508 2.12931708 0.12852434 1.99232167 0.17883511 2.02492838\n", - " 0.22368919 1.93371788 0.24829894 1.89614503 0.26973569 1.85071987\n", - " 0.282443 1.78189418 0.27186768 1.72595796 0.29217108 1.71707583\n", - " 0.28425105 1.66542542 0.30682025 1.61846651 0.30970696 1.61347256\n", - " 0.34999558 1.57213922 0.35183185 1.5622746 ]\n", - "P_ = [0.0822508 2.12931708 0.12521908 2.00210705 0.17164786 2.02027028\n", - " 0.2140776 1.95326299 0.24126758 1.90688013 0.26207971 1.86694314\n", - " 0.27699701 1.8113909 0.27715534 1.75392607 0.28056914 1.72215133\n", - " 0.2893425 1.69862925 0.29069939 1.65200859 0.30743883 1.61739638\n", - " 0.31546248 1.60756779 0.35012674 1.57143461 0.35183185 1.5622746 ]\n", - "Depth = 15, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.363248\n", - " Iterations: 651\n", - " Function evaluations: 851\n", - "P = [0.08540651 2.10105022 0.13340918 2.05744139 0.18494288 2.12805145\n", - " 0.22338719 2.00155245 0.23259399 1.96360962 0.26551985 1.90177766\n", - " 0.28049844 1.78692738 0.27960765 1.73321538 0.28818306 1.72681238\n", - " 0.24912502 1.63382437 0.30433264 1.59159008 0.32728758 1.59374547\n", - " 0.25637587 1.55748651 0.35038968 1.51483818 0.36666745 1.53732905]\n", - "P_ = [0.08540651 2.10105022 0.130209 2.06034865 0.17807172 2.11863678\n", - " 0.21569833 2.02685225 0.23013884 1.97372771 0.25454456 1.92238831\n", - " 0.274507 1.83286749 0.28002335 1.75828098 0.2836095 1.73022731\n", - " 0.27255984 1.68961717 0.26752756 1.61974627 0.31045396 1.59216485\n", - " 0.31310523 1.58649368 0.26891104 1.55180006 0.35147486 1.51633757\n", - " 0.36666745 1.53732905]\n", - "Depth = 16, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.376496\n", - " Iterations: 223\n", - " Function evaluations: 359\n", - "P = [0.08177879 2.09985592 0.13178494 2.03830204 0.17843588 2.10803093\n", - " 0.21715499 2.03720993 0.2286208 1.98284717 0.25142647 1.94170673\n", - " 0.27859011 1.81798747 0.28488693 1.75504419 0.28535778 1.74428612\n", - " 0.27596747 1.66123066 0.26705338 1.62290018 0.31467959 1.60445716\n", - " 0.31297645 1.58740962 0.2720023 1.55013688 0.35084225 1.53112814\n", - " 0.36778052 1.54120364]\n", - "P_ = [0.08177879 2.09985592 0.12865955 2.04214916 0.17260451 2.09931482\n", - " 0.20989516 2.05048887 0.22575435 1.99643786 0.2442997 1.95456312\n", - " 0.26840375 1.8643822 0.28213207 1.78258188 0.28512235 1.74966516\n", - " 0.28124952 1.70794935 0.27262469 1.64685673 0.28193657 1.61713674\n", - " 0.31425381 1.60019527 0.3052938 1.58042098 0.28185729 1.54776079\n", - " 0.35190089 1.53175786 0.36778052 1.54120364]\n", - "Depth = 17, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.363516\n", - " Iterations: 396\n", - " Function evaluations: 556\n", - "P = [0.0817837 2.11609025 0.13310163 2.043217 0.17685477 2.10049616\n", - " 0.20937363 2.04856003 0.22170268 2.02302067 0.23829628 1.96177599\n", - " 0.26401385 1.85920664 0.27955801 1.78823606 0.28695882 1.74966776\n", - " 0.28010754 1.69110818 0.2709383 1.63199059 0.28738263 1.61699143\n", - " 0.31627245 1.58456492 0.31106184 1.57466819 0.2935599 1.54934818\n", - " 0.34808532 1.52070987 0.37333377 1.55880243]\n", - "P_ = [0.0817837 2.11609025 0.13008293 2.04750366 0.17170735 2.09375744\n", - " 0.20363501 2.05772523 0.21880173 2.02902993 0.23341581 1.97978913\n", - " 0.25493706 1.89540759 0.27315747 1.81745924 0.28347609 1.76781755\n", - " 0.28373469 1.72211031 0.27633197 1.66676564 0.27674218 1.62669677\n", - " 0.29587964 1.60745422 0.31504642 1.58223628 0.30797326 1.57019996\n", - " 0.29997465 1.54597897 0.34957052 1.52295061 0.37333377 1.55880243]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.353300\n", - " Iterations: 345\n", - " Function evaluations: 514\n", - "P = [0.08057673 2.12969524 0.13368683 2.03722648 0.17360286 2.10919953\n", - " 0.20864923 2.05701893 0.21182403 2.03419698 0.23356177 1.98930613\n", - " 0.25478579 1.89170154 0.27398629 1.82202699 0.2862836 1.77004657\n", - " 0.2806083 1.71203275 0.27623768 1.6532665 0.27561289 1.62640064\n", - " 0.29545455 1.60407828 0.32131233 1.58523479 0.31267455 1.56294291\n", - " 0.30199809 1.52937686 0.35347033 1.5441138 0.36910682 1.54834209]\n", - "P_ = [0.08057673 2.12969524 0.13073627 2.04236364 0.16916775 2.10120253\n", - " 0.20280817 2.0657157 0.21111852 2.03926853 0.22752351 2.00177581\n", - " 0.24771112 1.9242364 0.26651943 1.84912265 0.28081813 1.79314898\n", - " 0.28344595 1.74103966 0.2786658 1.68591442 0.2759947 1.64281867\n", - " 0.28222677 1.61895986 0.30263726 1.59884398 0.31939282 1.58028104\n", - " 0.31089514 1.55734857 0.30771723 1.5310143 0.35433903 1.5443487\n", - " 0.36910682 1.54834209]\n", - "Depth = 19, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.351183\n", - " Iterations: 401\n", - " Function evaluations: 566\n", - "P = [0.07792567 2.12508572 0.13343313 2.03769467 0.17487823 2.10872523\n", - " 0.2065944 2.07822836 0.21206005 2.04997364 0.22226339 2.00827437\n", - " 0.2508392 1.9216482 0.26223595 1.85845204 0.28315362 1.79696392\n", - " 0.27624276 1.73581813 0.27537346 1.67466942 0.27987634 1.64124407\n", - " 0.27675967 1.6142503 0.30707155 1.60312002 0.32273959 1.57766891\n", - " 0.3140862 1.53677446 0.31020762 1.56096353 0.35585993 1.52985176\n", - " 0.36998634 1.54580178]\n", - "P_ = [0.07792567 2.12508572 0.13051169 2.0422942 0.17051558 2.10124833\n", - " 0.20158658 2.08304365 0.21090939 2.055922 0.2195783 2.01924787\n", - " 0.24181526 1.94900384 0.25803715 1.88173483 0.27434618 1.82285366\n", - " 0.27951632 1.76478193 0.27583098 1.70685295 0.27726941 1.66059559\n", - " 0.27872809 1.631299 0.28633184 1.61073548 0.31119472 1.59642236\n", - " 0.32091783 1.56905955 0.31347379 1.54059379 0.31501312 1.55768861\n", - " 0.35660342 1.53069123 0.36998634 1.54580178]\n", - "Depth = 20, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.341548\n", - " Iterations: 254\n", - " Function evaluations: 406\n", - "P = [0.07723118 2.13844867 0.13181881 2.03874827 0.17295229 2.10470436\n", - " 0.20429909 2.08343483 0.21197929 2.05946659 0.22148398 2.02246466\n", - " 0.23794885 1.94371808 0.2596138 1.88147308 0.27409854 1.82638989\n", - " 0.27648614 1.7691253 0.27824296 1.70023763 0.27467217 1.65969201\n", - " 0.27678862 1.62954657 0.28697777 1.61139658 0.31165859 1.59537596\n", - " 0.32199878 1.55920862 0.31600647 1.55261155 0.31709004 1.53572773\n", - " 0.35960771 1.5330084 0.37323181 1.5526311 ]\n", - "P_ = [0.07723118 2.13844867 0.12908943 2.04373329 0.16883894 2.09810875\n", - " 0.19959707 2.08662526 0.21044325 2.06426024 0.21910781 2.03171514\n", - " 0.23300939 1.96734205 0.25203107 1.90325883 0.26830464 1.84842316\n", - " 0.27541172 1.79489436 0.27736455 1.73468146 0.27663611 1.6819921\n", - " 0.27551875 1.64763383 0.28035482 1.62319407 0.29438201 1.60659039\n", - " 0.31424364 1.58633413 0.32080032 1.55788921 0.316169 1.55007898\n", - " 0.32134181 1.5354558 0.36028891 1.53398954 0.37323181 1.5526311 ]\n", - "Depth = 21, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.294380\n", - " Iterations: 1202\n", - " Function evaluations: 1496\n", - "P = [0.07529152 2.09772642 0.131824 2.08632367 0.1929481 2.11070262\n", - " 0.20766774 2.11584474 0.2254692 2.09636296 0.21507549 2.04853179\n", - " 0.22664328 1.98779345 0.24127347 1.9235778 0.26999559 1.83162699\n", - " 0.21968622 1.80107475 0.29072437 1.73579264 0.18827489 1.65432788\n", - " 0.25394774 1.65998542 0.27547847 1.63087128 0.3276104 1.5989803\n", - " 0.34758489 1.55735567 0.33340728 1.54013178 0.30864019 1.49422528\n", - " 0.32262961 1.51989904 0.36086636 1.51315389 0.40494638 1.52481859]\n", - "P_ = [0.07529152 2.09772642 0.12913198 2.08686666 0.18712676 2.10838081\n", - " 0.20556494 2.11511015 0.22207844 2.10007377 0.21755019 2.05992016\n", - " 0.2233382 2.00514726 0.23639674 1.94498302 0.25905383 1.86665587\n", - " 0.24124738 1.81416856 0.25689668 1.76687936 0.2419389 1.69699989\n", - " 0.21642039 1.65675254 0.26214992 1.64889432 0.29285578 1.62024095\n", - " 0.3333174 1.58708755 0.34420927 1.55325475 0.32868974 1.53138769\n", - " 0.31063868 1.49789296 0.32627121 1.51925665 0.36296541 1.51370935\n", - " 0.40494638 1.52481859]\n", - "Depth = 22, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.305827\n", - " Iterations: 426\n", - " Function evaluations: 638\n", - "P = [0.07414615 2.10792732 0.12980068 2.06699914 0.1851379 2.10267048\n", - " 0.2068955 2.11038934 0.221394 2.11135454 0.21897232 2.05774033\n", - " 0.22279346 2.00256886 0.23708805 1.93614728 0.2559945 1.86575941\n", - " 0.24087438 1.80804338 0.25978294 1.76100826 0.24547558 1.69821456\n", - " 0.21979038 1.67154347 0.26181385 1.64033413 0.29687977 1.62105408\n", - " 0.33154252 1.57652045 0.34654725 1.56459429 0.33018418 1.51882249\n", - " 0.31317298 1.51247559 0.32862374 1.51982184 0.36073416 1.51799792\n", - " 0.40628936 1.5283034 ]\n", - "P_ = [0.07414615 2.10792732 0.12727093 2.06885951 0.18010724 2.09942763\n", - " 0.20392855 2.10933676 0.21875791 2.11117905 0.2195227 2.06992538\n", - " 0.22175133 2.01761563 0.23253977 1.95728142 0.24911943 1.891355\n", - " 0.24705988 1.83165449 0.25118814 1.78238786 0.25262926 1.72961141\n", - " 0.23380049 1.68609134 0.2369818 1.65877601 0.2745651 1.6333232\n", - " 0.30790883 1.60688429 0.33563472 1.57326786 0.34282837 1.55419161\n", - " 0.32709123 1.51766851 0.3152799 1.51347735 0.33154287 1.51965603\n", - " 0.36280485 1.51846635 0.40628936 1.5283034 ]\n", - "Depth = 23, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.310709\n", - " Iterations: 414\n", - " Function evaluations: 634\n", - "P = [0.07222509 2.12831468 0.1264571 2.04024282 0.17977874 2.09522462\n", - " 0.20484771 2.0921634 0.21797253 2.11206924 0.22105213 2.07742235\n", - " 0.22039929 2.00902586 0.23488068 1.95844281 0.24837878 1.89565073\n", - " 0.24551792 1.83450702 0.25352456 1.78277999 0.25062845 1.73011153\n", - " 0.23929549 1.68609205 0.24059032 1.66221528 0.27596522 1.63695563\n", - " 0.31036888 1.59774248 0.33775826 1.56942093 0.34816559 1.5474969\n", - " 0.32639752 1.52098348 0.32456886 1.51196452 0.33054911 1.5158127\n", - " 0.36722146 1.52444124 0.40116285 1.54636501]\n", - "P_ = [0.07222509 2.12831468 0.12409918 2.04407203 0.17514207 2.0904436\n", - " 0.20157785 2.09256269 0.21568995 2.10860736 0.22038265 2.08495428\n", - " 0.2205696 2.02686843 0.2304733 1.97383765 0.24368379 1.91749145\n", - " 0.24663739 1.85843282 0.25004342 1.80527 0.25201355 1.75530079\n", - " 0.24520834 1.70905873 0.23985846 1.67571084 0.25443267 1.65233107\n", - " 0.28793171 1.62331627 0.31870478 1.58912288 0.34047322 1.56370162\n", - " 0.3434334 1.54173311 0.3260795 1.51941496 0.32534889 1.51246645\n", - " 0.33373801 1.51656301 0.36869717 1.52539445 0.40116285 1.54636501]\n", - "Depth = 24, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.268901\n", - " Iterations: 1467\n", - " Function evaluations: 1832\n", - "P = [0.07207725 2.15746274 0.12335445 2.01731326 0.17853093 2.10313818\n", - " 0.20692038 2.06541936 0.2026972 2.08398687 0.22339496 2.09854048\n", - " 0.2075951 2.03282685 0.22888765 1.96471706 0.23412737 1.88467013\n", - " 0.2296225 1.86832384 0.25586415 1.8120425 0.24638348 1.74956895\n", - " 0.24260905 1.74090317 0.26546912 1.67815733 0.25386087 1.63474031\n", - " 0.30027532 1.62235384 0.26950501 1.58504 0.38384954 1.54278268\n", - " 0.3182293 1.54107468 0.34691345 1.5249464 0.3289571 1.5109243\n", - " 0.3612503 1.49853651 0.37042732 1.52126917 0.43135608 1.56440749]\n", - "P_ = [0.07207725 2.15746274 0.1212179 2.02315283 0.17393289 2.0959861\n", - " 0.2033717 2.07013421 0.20340106 2.08089228 0.21908293 2.09550848\n", - " 0.21154506 2.04925526 0.22267732 1.98458242 0.2323808 1.91135244\n", - " 0.23131183 1.8744537 0.24493013 1.83549306 0.25072879 1.77820266\n", - " 0.24449626 1.74523606 0.25308658 1.71214466 0.26063235 1.6600669\n", - " 0.27126629 1.63009538 0.29001855 1.6099159 0.3028555 1.57271495\n", - " 0.36744448 1.54235568 0.32420517 1.53771463 0.34392073 1.52260939\n", - " 0.33299375 1.50937583 0.36201505 1.5004309 0.37296601 1.5230666\n", - " 0.43135608 1.56440749]\n", - "Depth = 25, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.293493\n", - " Iterations: 582\n", - " Function evaluations: 859\n", - "P = [0.07107771 2.12549945 0.12339156 2.03464643 0.1737758 2.07877912\n", - " 0.20418603 2.07289074 0.20620517 2.07621607 0.21606191 2.09861443\n", - " 0.2142729 2.05173435 0.22105795 1.98893803 0.23466281 1.91637084\n", - " 0.22207625 1.87677493 0.24693299 1.83544859 0.25133421 1.77415304\n", - " 0.24295123 1.76666295 0.25546436 1.70771144 0.26186621 1.66220769\n", - " 0.27337964 1.63045539 0.28895826 1.6076046 0.30770346 1.56955245\n", - " 0.36911323 1.55250244 0.32526011 1.53402609 0.34726409 1.51348085\n", - " 0.33334465 1.51327103 0.36307995 1.49268083 0.37190322 1.53613043\n", - " 0.43541354 1.56177503]\n", - "P_ = [0.07107771 2.12549945 0.12129901 2.03828055 0.16974506 2.0752485\n", - " 0.2005368 2.07359735 0.2058821 2.07568402 0.21409056 2.09413476\n", - " 0.21470226 2.06298557 0.21915813 2.006521 0.23030925 1.93959234\n", - " 0.22660741 1.89102946 0.2369903 1.85197913 0.24939767 1.80112308\n", - " 0.24697506 1.77025819 0.24895753 1.73836622 0.25828117 1.68768979\n", - " 0.26647158 1.64950677 0.27898794 1.6222291 0.29495672 1.59542791\n", - " 0.32489819 1.56477845 0.35858849 1.54806812 0.32966091 1.52991704\n", - " 0.34503698 1.51344728 0.33691289 1.51080021 0.36378582 1.4961568\n", - " 0.37444363 1.53715621 0.43541354 1.56177503]\n", - "Depth = 26, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.284885\n", - " Iterations: 364\n", - " Function evaluations: 591\n", - "P = [0.07081179 2.14664377 0.12273952 2.03663397 0.1715473 2.08241137\n", - " 0.19901264 2.06279038 0.20621179 2.06878707 0.21224961 2.08766798\n", - " 0.21448692 2.07098341 0.22040272 2.00643722 0.23074483 1.94372587\n", - " 0.226999 1.89049773 0.23860806 1.84313637 0.25117692 1.8038592\n", - " 0.24562823 1.75992473 0.25149867 1.74211819 0.25839782 1.6925408\n", - " 0.2669504 1.64913169 0.27932248 1.62085767 0.29567421 1.5912176\n", - " 0.32598714 1.56120766 0.35957528 1.55076609 0.33146741 1.52547628\n", - " 0.34652179 1.51417773 0.33847525 1.50580143 0.3603736 1.50307351\n", - " 0.37474061 1.53359816 0.43459353 1.56740298]\n", - "P_ = [0.07081179 2.14664377 0.1207423 2.04086511 0.16779286 2.07889003\n", - " 0.19584357 2.06505434 0.20510423 2.0678645 0.21108849 2.08403703\n", - " 0.21397062 2.07483369 0.21881001 2.02381504 0.22756265 1.96302167\n", - " 0.22829563 1.90892285 0.23414304 1.86135228 0.24585933 1.82047647\n", - " 0.24818916 1.78020218 0.24856345 1.75102146 0.25468289 1.71923632\n", - " 0.26201622 1.67417541 0.27170889 1.63825707 0.28498269 1.61059765\n", - " 0.30500127 1.58198377 0.3350301 1.55839647 0.35308885 1.54492998\n", - " 0.33436248 1.52330348 0.34528386 1.51288907 0.34100198 1.50548667\n", - " 0.36147875 1.50542156 0.37704265 1.53489834 0.43459353 1.56740298]\n", - "Depth = 27, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.303498\n", - " Iterations: 400\n", - " Function evaluations: 633\n", - "P = [0.07027779 2.13923767 0.12148003 2.04164988 0.16785534 2.08577038\n", - " 0.1971163 2.06070238 0.20258136 2.06385208 0.2117458 2.07834483\n", - " 0.21266198 2.06905268 0.2195248 2.03572306 0.22834969 1.95822017\n", - " 0.22874338 1.91518748 0.23485044 1.85260694 0.24430554 1.82187335\n", - " 0.24838394 1.7812589 0.25020551 1.75221021 0.2565636 1.72048942\n", - " 0.2648587 1.66856372 0.27370477 1.64351185 0.28599173 1.60749566\n", - " 0.30814956 1.57275923 0.33750017 1.55927602 0.35499756 1.54913969\n", - " 0.33608944 1.52051237 0.34569063 1.50696228 0.34150544 1.51167931\n", - " 0.35745899 1.5092037 0.37579316 1.53873046 0.43580883 1.57298842]\n", - "P_ = [0.07027779 2.13923767 0.11958365 2.04526425 0.16442013 2.08250219\n", - " 0.19386509 2.06348771 0.20177172 2.06338546 0.21004868 2.07566099\n", - " 0.21245839 2.0711176 0.21774555 2.04436407 0.22573491 1.98118399\n", - " 0.22861215 1.92953171 0.23258857 1.87578492 0.24045346 1.83439444\n", - " 0.24657132 1.79930976 0.24932846 1.76619662 0.25326681 1.73693724\n", - " 0.26025031 1.69741133 0.26846265 1.6583574 0.27825549 1.63017252\n", - " 0.29337767 1.59591685 0.31684604 1.56876421 0.34203653 1.55664809\n", - " 0.35079576 1.54277806 0.33786744 1.51800309 0.34507061 1.5076611\n", - " 0.34327806 1.51140424 0.35881707 1.51139087 0.37801597 1.53999927\n", - " 0.43580883 1.57298842]\n", - "Depth = 28, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.296411\n", - " Iterations: 474\n", - " Function evaluations: 718\n", - "P = [0.06980995 2.13902773 0.12024341 2.04181344 0.16804889 2.08641015\n", - " 0.19486242 2.06511043 0.2009583 2.06168834 0.20818573 2.07362737\n", - " 0.21004443 2.0642258 0.21823197 2.04594362 0.22650088 1.9851959\n", - " 0.22636923 1.93418996 0.23542219 1.86731946 0.23631612 1.83363741\n", - " 0.24524007 1.80000988 0.25367152 1.76681216 0.25314316 1.73685949\n", - " 0.26246232 1.69179323 0.26855233 1.66123221 0.28088124 1.64000256\n", - " 0.29428277 1.59262376 0.31885921 1.56927412 0.34367104 1.55717492\n", - " 0.35084287 1.5419548 0.34232556 1.51205353 0.34639895 1.51100805\n", - " 0.34356942 1.50867206 0.35336714 1.51866669 0.37535084 1.54672813\n", - " 0.43899681 1.5705303 ]\n", - "P_ = [0.06980995 2.13902773 0.11844222 2.04528538 0.16463421 2.08322467\n", - " 0.19198955 2.06739255 0.20008746 2.06217721 0.20689512 2.0714954\n", - " 0.20964614 2.06624042 0.21618508 2.05051416 0.22413833 2.00255239\n", - " 0.22641154 1.95058473 0.23218899 1.89120178 0.23596493 1.84686964\n", - " 0.24141552 1.81442168 0.24975692 1.78222539 0.25340734 1.75183582\n", - " 0.25746991 1.71593586 0.26507232 1.67869565 0.27339583 1.65289199\n", - " 0.2856675 1.62308156 0.30218234 1.58511852 0.32594831 1.56581721\n", - " 0.345464 1.55336989 0.34901773 1.53554739 0.34305295 1.51186684\n", - " 0.34599473 1.51067434 0.34461918 1.50974291 0.3549374 1.52067108\n", - " 0.37762391 1.54757821 0.43899681 1.5705303 ]\n", - "Depth = 29, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.308194\n", - " Iterations: 429\n", - " Function evaluations: 678\n", - "P = [0.06906777 2.13696007 0.11909569 2.04848797 0.16310029 2.08480984\n", - " 0.19386054 2.0656873 0.20020687 2.06205056 0.20563707 2.06886242\n", - " 0.20924328 2.06106312 0.21318324 2.05002731 0.22425641 2.00473347\n", - " 0.22456874 1.95680074 0.2328147 1.88847403 0.2354999 1.84299988\n", - " 0.23955028 1.80947221 0.25114415 1.78641149 0.25366845 1.75156177\n", - " 0.26005979 1.71350192 0.26682018 1.6815909 0.27224369 1.65527677\n", - " 0.28446154 1.6199951 0.30567381 1.58131737 0.32987988 1.56162542\n", - " 0.34808513 1.55059749 0.35297899 1.534412 0.34419783 1.51600007\n", - " 0.34644938 1.50760737 0.34731605 1.50807076 0.35660641 1.52869469\n", - " 0.37940976 1.55534605 0.44074982 1.57584859]\n", - "P_ = [0.06906777 2.13696007 0.11737059 2.05153873 0.16006549 2.08230488\n", - " 0.19067844 2.06766549 0.19933151 2.06255218 0.20470083 2.06768797\n", - " 0.20849717 2.06267677 0.21223221 2.05269112 0.22120174 2.01722832\n", - " 0.22447181 1.97167642 0.22997127 1.91203496 0.23448138 1.86024869\n", - " 0.23787426 1.82334573 0.2459469 1.79674905 0.25244983 1.76838577\n", - " 0.25675392 1.73318805 0.26309031 1.69919698 0.2690644 1.6707023\n", - " 0.27687805 1.64189407 0.29177611 1.60665795 0.31318604 1.57520607\n", - " 0.33490202 1.55858323 0.34926641 1.54669065 0.35116219 1.53060264\n", - " 0.34458603 1.51455306 0.34656892 1.50767128 0.34827713 1.51020427\n", - " 0.35817905 1.53053272 0.38152493 1.55605304 0.44074982 1.57584859]\n", - "Depth = 30, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.304654\n", - " Iterations: 351\n", - " Function evaluations: 581\n", - "1.4285714285714286 [7.25329418 4.56281458 3.67030721 3.17099314 2.6849261 2.54542057\n", - " 2.56677162 2.49133841 2.4641662 2.43540025 2.43389127 2.44862413\n", - " 2.45663888 2.45288449 2.36324836 2.37649645 2.36351613 2.35330001\n", - " 2.35118344 2.34154786 2.29438033 2.30582703 2.31070861 2.26890101\n", - " 2.29349309 2.28488493 2.30349773 2.29641104 2.30819364 2.30465394]\n", - "[[6.57155339 5.94790512 4.51084725 5.48476219 4.44827696 4.07086367\n", - " 4.45993119 3.76473244 3.75245393 3.70383406 2.54453644 2.75335922\n", - " 3.72365101 2.64914745 3.66152866 3.41308183 2.17660478 2.18383796\n", - " 2.54980097 1.72430929 2.24071873 1.8353618 2.04963403 1.97768311\n", - " 2.25839296 2.22977067 1.94603139 2.05226045 2.69504832 3.27724127]\n", - " [7.58106801 6.81608452 4.28714233 4.07123972 3.27046962 3.23940109\n", - " 3.69518164 3.2411352 2.8435791 2.91039551 2.52147765 2.7118309\n", - " 2.7196728 2.5657514 2.49654928 2.14986169 2.03773181 1.96011255\n", - " 1.99818881 1.99560667 2.10966328 1.86491841 1.83579189 1.98703992\n", - " 1.98133515 1.95306622 1.90928783 1.85507609 1.79545032 1.7963689 ]\n", - " [5.67675131 4.71392584 4.01740509 3.36995594 3.02811997 2.75900701\n", - " 2.07994453 1.87160639 1.76736629 1.60399896 1.51494314 1.48018664\n", - " 1.42851074 1.41006842 1.37578808 1.29188206 1.25021059 1.25293931\n", - " 1.22202663 1.23016691 1.26143882 1.20441019 1.17776388 1.18431374\n", - " 1.16553331 1.16956844 1.16569465 1.17659931 1.16990127 1.15831922]\n", - " [5.00995896 4.29025145 4.60820671 3.83390873 3.89848291 5.33118031\n", - " 3.55893822 3.40156727 4.09051018 4.16531197 3.86869824 2.74039918\n", - " 2.37252786 2.09790193 2.46381788 3.23389141 2.92683369 2.26271526\n", - " 2.22500107 1.72792525 1.99341501 2.13517458 2.55949815 2.08833212\n", - " 2.30394139 2.47254611 2.09431819 2.0108552 2.25457883 1.56109974]\n", - " [4.00096445 3.74521392 2.59257503 2.56365739 1.9185404 1.87747501\n", - " 1.74225195 1.62820595 1.46249835 1.3728014 1.35944481 1.35683453\n", - " 1.33094362 1.31878632 1.32159957 1.30276576 1.25442761 1.25346875\n", - " 1.23969275 1.23278308 1.2266854 1.22191909 1.20703107 1.20899474\n", - " 1.20219427 1.20085781 1.20009343 1.19826693 1.1915774 1.19065828]\n", - " [5.90892769 4.83252908 3.71479956 3.36110121 2.94173277 2.24786958\n", - " 2.12439453 2.02822257 1.99458002 1.79405078 1.71446451 1.68436207\n", - " 1.64831949 1.60645585 1.57877549 1.55946868 1.50646832 1.48490593\n", - " 1.46944309 1.45423724 1.43322495 1.41715875 1.39899314 1.36097986\n", - " 1.33935151 1.32162911 1.30734052 1.2947269 1.27768564 1.26760576]\n", - " [5.07730592 3.19397021 2.56921505 2.2196952 1.87944827 1.7817944\n", - " 1.79674014 1.74393688 1.72491634 1.70478017 1.70372389 1.71403689\n", - " 1.71964722 1.71701915 1.65427385 1.66354751 1.65446129 1.64731001\n", - " 1.64582841 1.63908351 1.60606623 1.61407892 1.61749603 1.58823071\n", - " 1.60544517 1.59941945 1.61244841 1.60748773 1.61573555 1.61325776]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]] [3.98265297 3.35398801 2.6300191 2.49043204 2.13850709 2.13075911\n", - " 1.94573822 1.76794067 1.76359042 1.72551729 1.52272887 1.44410094\n", - " 1.49432727 1.33651305 1.45523328 1.46144989 1.28067381 1.20452898\n", - " 1.23499817 1.10041119 1.18712124 1.12930217 1.18462082 1.13955742\n", - " 1.18561938 1.19468578 1.12352144 1.11952726 1.19999773 1.18645509]\n", - "[[0.1749857 0.07463194 0.26530491 0.16394175 0.18892849 0.25701077\n", - " 0.24542951 0.40504394 0.18547862 0.24113788 0.62032714 0.68408453\n", - " 0.11521194 0.57930818 0.29653581 0.32221821 0.75779012 0.76858176\n", - " 0.59269399 0.8271978 0.69201592 0.87101232 0.79114835 0.72852071\n", - " 0.64433266 0.66377712 0.77675308 0.72982301 0.58648573 0.44154865]\n", - " [0.17669094 0.20818569 0.40598211 0.40456531 0.54848127 0.5337594\n", - " 0.48446167 0.53759304 0.60295388 0.58451793 0.64895146 0.66165701\n", - " 0.62972457 0.66201878 0.67281148 0.75627098 0.78514972 0.80366385\n", - " 0.79430362 0.79961314 0.7524382 0.82370466 0.83214203 0.78138294\n", - " 0.78255631 0.78124579 0.80687807 0.80774629 0.84561002 0.84356134]\n", - " [0.1977358 0.23204622 0.30938238 0.39342279 0.41016143 0.46245125\n", - " 0.76102816 0.79966194 0.84980142 0.9167973 0.93013476 0.94105633\n", - " 0.96019643 0.9567664 0.95781341 0.97258171 0.97672161 0.97483651\n", - " 0.98345276 0.97827363 0.97171746 0.98525476 0.99020549 0.988242\n", - " 0.99105685 0.98789452 0.98718377 0.98332188 0.98342322 0.98330761]\n", - " [0.05772911 0.21353746 0.01841155 0.31450455 0.21424321 0.05404723\n", - " 0.43161435 0.34272799 0.28819124 0.28689022 0.1868918 0.50636735\n", - " 0.71458126 0.77159991 0.58971876 0.39292553 0.46431953 0.6325678\n", - " 0.69978407 0.80479284 0.72769493 0.74105124 0.53269212 0.73999712\n", - " 0.61502723 0.52602161 0.71815241 0.71745393 0.53403795 0.82706806]\n", - " [0.12450898 0.13546046 0.33397169 0.30579603 0.53279986 0.54005574\n", - " 0.5789386 0.62157361 0.67239022 0.70608977 0.71741324 0.71989795\n", - " 0.72816408 0.73770709 0.7462425 0.75395046 0.77610427 0.778063\n", - " 0.78739546 0.80304068 0.8044153 0.81655327 0.83574318 0.83983299\n", - " 0.85295023 0.85822598 0.86248183 0.86742561 0.8687046 0.87578262]\n", - " [0.15384579 0.23299282 0.34316369 0.40381029 0.48323069 0.60966505\n", - " 0.65090211 0.6781041 0.69468559 0.73757271 0.76352272 0.78064924\n", - " 0.80250928 0.8256876 0.84161068 0.85173433 0.88960447 0.89427145\n", - " 0.89713168 0.89784489 0.90396968 0.90972365 0.91944211 0.93551855\n", - " 0.93997379 0.94289646 0.9440385 0.94476954 0.94821036 0.94920811]\n", - " [0.22662278 0.49591192 0.64928992 0.72253971 0.88505646 0.91736256\n", - " 0.93108311 0.94041937 0.96629845 0.97837675 0.97999527 0.98011569\n", - " 0.97939879 0.97927928 0.98252313 0.98523181 0.98698179 0.98795262\n", - " 0.98839303 0.98858465 0.9918529 0.99290353 0.99289167 0.99426743\n", - " 0.9945867 0.99461399 0.99442154 0.99355126 0.99301575 0.99210625]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]] [0.11121191 0.15927665 0.23255062 0.27085804 0.32629014 0.3374352\n", - " 0.40834575 0.4325124 0.42597994 0.44513825 0.48472364 0.52738281\n", - " 0.49297863 0.55123673 0.50872558 0.5034913 0.56366715 0.5839937\n", - " 0.57431546 0.60993476 0.58441044 0.61402034 0.5894265 0.60077617\n", - " 0.58204838 0.57546755 0.60899092 0.60440915 0.57594876 0.59125826]\n", - "\n", - "Now using 4 solutions, set number 2\n", - "Calculating energy landscape ...\n", - "Optimization terminated successfully.\n", - " Current function value: 6.499947\n", - " Iterations: 26\n", - " Function evaluations: 53\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 6.499947\n", - " Iterations: 6\n", - " Function evaluations: 13\n", - "P = [0.15706929 1.96338189]\n", - "P_ = [0.15706929 1.96338189 0.15706929 1.96338189]\n", - "Depth = 2, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 4.888827\n", - " Iterations: 54\n", - " Function evaluations: 92\n", - "P = [0.12298934 2.0474592 0.23418704 1.79796742]\n", - "P_ = [0.12298934 2.0474592 0.17858819 1.92271331 0.23418704 1.79796742]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.955272\n", - " Iterations: 101\n", - " Function evaluations: 158\n", - "P = [0.16373996 2.04702152 0.26734738 1.81865798 0.26971103 1.7939582 ]\n", - "P_ = [0.16373996 2.04702152 0.23281157 1.89477916 0.26813526 1.81042472\n", - " 0.26971103 1.7939582 ]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.561037\n", - " Iterations: 148\n", - " Function evaluations: 230\n", - "P = [0.10595433 2.11466627 0.2390295 1.91465565 0.27351626 1.80357261\n", - " 0.26950291 1.72233405]\n", - "P_ = [0.10595433 2.11466627 0.20576071 1.96465831 0.25627288 1.85911413\n", - " 0.27251292 1.78326297 0.26950291 1.72233405]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.308965\n", - " Iterations: 103\n", - " Function evaluations: 164\n", - "P = [0.10757123 2.07809045 0.20092504 1.90163185 0.2603246 1.83544419\n", - " 0.25678884 1.73228277 0.2982155 1.6579102 ]\n", - "P_ = [0.10757123 2.07809045 0.18225428 1.93692357 0.23656478 1.86191925\n", - " 0.2589103 1.79417962 0.26507417 1.71740826 0.2982155 1.6579102 ]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.029317\n", - " Iterations: 195\n", - " Function evaluations: 281\n", - "P = [0.10940592 2.092238 0.19344878 1.88181565 0.16319433 1.77457412\n", - " 0.21978419 1.80236107 0.25517728 1.70414201 0.31834169 1.67543869]\n", - "P_ = [0.10940592 2.092238 0.17944164 1.91688604 0.17327915 1.8103213\n", - " 0.19148926 1.7884676 0.23158189 1.76962138 0.26570468 1.69935812\n", - " 0.31834169 1.67543869]\n", - "Depth = 7, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.982022\n", - " Iterations: 141\n", - " Function evaluations: 218\n", - "P = [0.08761668 2.13729174 0.17628558 1.9220364 0.17494488 1.79446\n", - " 0.21668311 1.79839811 0.25737696 1.73444276 0.27994201 1.67152739\n", - " 0.32960699 1.58907917]\n", - "P_ = [0.08761668 2.13729174 0.16361859 1.95278716 0.17532793 1.8309104\n", - " 0.1987953 1.79671034 0.23412333 1.77098867 0.26382412 1.71646694\n", - " 0.28703701 1.65974908 0.32960699 1.58907917]\n", - "Depth = 8, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.986168\n", - " Iterations: 104\n", - " Function evaluations: 164\n", - "P = [0.08415292 2.15198541 0.1671557 1.95616963 0.17821729 1.83707626\n", - " 0.19947789 1.80196304 0.24056445 1.7649085 0.27273772 1.70788235\n", - " 0.27578018 1.6338185 0.33153877 1.59968681]\n", - "P_ = [0.08415292 2.15198541 0.15678036 1.9806466 0.17545189 1.8668496\n", - " 0.19150517 1.8151305 0.22002117 1.78343577 0.25262943 1.74352369\n", - " 0.27349833 1.68936638 0.28275 1.62955203 0.33153877 1.59968681]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.949438\n", - " Iterations: 96\n", - " Function evaluations: 161\n", - "P = [0.08026488 2.17623303 0.15806302 1.98726562 0.17390769 1.87704877\n", - " 0.20061081 1.82762415 0.218823 1.77358342 0.25900962 1.74859449\n", - " 0.2719121 1.66976025 0.28816715 1.64005865 0.32931844 1.59254547]\n", - "P_ = [0.08026488 2.17623303 0.14941878 2.008262 0.17038665 1.9015414\n", - " 0.19170977 1.84409903 0.2107287 1.79760152 0.23668372 1.76247723\n", - " 0.26331045 1.72231641 0.27552433 1.66315989 0.29273951 1.63477941\n", - " 0.32931844 1.59254547]\n", - "Depth = 10, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.967916\n", - " Iterations: 149\n", - " Function evaluations: 233\n", - "P = [0.07561096 2.1721082 0.1498244 2.00538381 0.17067133 1.92869947\n", - " 0.20230401 1.86208928 0.21505534 1.79291601 0.24245068 1.76395423\n", - " 0.25981542 1.70936299 0.2841661 1.6600627 0.29008254 1.61672477\n", - " 0.33513047 1.57269818]\n", - "P_ = [0.07561096 2.1721082 0.14240306 2.02205625 0.16650195 1.94403634\n", - " 0.19281421 1.88207234 0.20995481 1.82058532 0.22875301 1.77843512\n", - " 0.24939657 1.74211774 0.26712062 1.6945729 0.28534939 1.65139511\n", - " 0.29458734 1.61232211 0.33513047 1.57269818]\n", - "Depth = 11, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.953029\n", - " Iterations: 146\n", - " Function evaluations: 231\n", - "P = [0.07420902 2.17986344 0.1417001 2.0192255 0.16685836 1.95811282\n", - " 0.20264194 1.901031 0.21383123 1.81978056 0.23666666 1.78324288\n", - " 0.24707479 1.72790632 0.27673085 1.69583959 0.2762581 1.63661455\n", - " 0.2911362 1.59539327 0.33175729 1.58448102]\n", - "P_ = [0.07420902 2.17986344 0.13556455 2.03382895 0.16228413 1.96922421\n", - " 0.19288279 1.91659877 0.2097624 1.84932618 0.22628692 1.79985091\n", - " 0.24139763 1.7580899 0.25785881 1.71624569 0.27660192 1.6796873\n", - " 0.27896321 1.62911977 0.29482903 1.59440125 0.33175729 1.58448102]\n", - "Depth = 12, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.971053\n", - " Iterations: 156\n", - " Function evaluations: 248\n", - "P = [0.07156244 2.17736035 0.13723749 2.03090072 0.16104735 1.98910922\n", - " 0.19820506 1.92647929 0.21147835 1.85142256 0.23028875 1.80543828\n", - " 0.2373607 1.75392507 0.26117107 1.71688897 0.27174175 1.66448503\n", - " 0.28358153 1.61650887 0.29876717 1.59873585 0.33559352 1.57189738]\n", - "P_ = [0.07156244 2.17736035 0.13176457 2.04310569 0.15707904 1.99607447\n", - " 0.18891564 1.94213677 0.20705392 1.87644147 0.22245108 1.8245984\n", - " 0.23382472 1.77968167 0.24728169 1.73849336 0.26469463 1.69942099\n", - " 0.27470169 1.65249099 0.28611247 1.6135467 0.30183603 1.59649931\n", - " 0.33559352 1.57189738]\n", - "Depth = 13, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.971208\n", - " Iterations: 152\n", - " Function evaluations: 244\n", - "P = [0.07094182 2.18117282 0.13101915 2.03803157 0.15837814 2.00537834\n", - " 0.19202446 1.94959254 0.20800529 1.8795165 0.22676929 1.82750962\n", - " 0.23121453 1.77276778 0.2545053 1.73560448 0.25340917 1.6901\n", - " 0.27772868 1.64558715 0.29037148 1.61500679 0.30311929 1.58812267\n", - " 0.33770966 1.57982924]\n", - "P_ = [0.07094182 2.18117282 0.12639782 2.04904244 0.15416906 2.01040191\n", - " 0.18425992 1.96246619 0.20308811 1.90107836 0.21955237 1.84751227\n", - " 0.22916288 1.79803324 0.24196412 1.75561548 0.25408371 1.71810275\n", - " 0.2608921 1.67640374 0.28064625 1.63853014 0.29233268 1.61087077\n", - " 0.30578008 1.58748472 0.33770966 1.57982924]\n", - "Depth = 14, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.965505\n", - " Iterations: 452\n", - " Function evaluations: 617\n", - "P = [0.06433336 2.19453734 0.12212393 2.03353684 0.15380153 2.02184347\n", - " 0.18989409 1.97164598 0.20441586 1.90041466 0.23375225 1.85097691\n", - " 0.23313358 1.77325434 0.23011851 1.74543203 0.23161864 1.6881628\n", - " 0.26090376 1.66513013 0.28515293 1.63565275 0.27536805 1.59708942\n", - " 0.32240985 1.58307228 0.37167556 1.58937598]\n", - "P_ = [0.06433336 2.19453734 0.11799604 2.04503688 0.14927616 2.02351395\n", - " 0.18215997 1.98240258 0.20026678 1.92076647 0.22327496 1.86863325\n", - " 0.23339872 1.80656401 0.23162605 1.75934318 0.23076142 1.72088807\n", - " 0.24207761 1.67993685 0.26783209 1.65670802 0.28305617 1.62738918\n", - " 0.2820883 1.59508697 0.32592883 1.58352254 0.37167556 1.58937598]\n", - "Depth = 15, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.968167\n", - " Iterations: 174\n", - " Function evaluations: 298\n", - "P = [0.06411609 2.1867073 0.11924298 2.04081332 0.14891653 2.0280927\n", - " 0.18434336 1.97988086 0.19753877 1.9236232 0.22329412 1.87127045\n", - " 0.23128644 1.8006883 0.23318027 1.76106499 0.23030733 1.71843157\n", - " 0.24678046 1.67512304 0.26769425 1.65473313 0.28332383 1.62672598\n", - " 0.28480656 1.5990514 0.32802971 1.59046375 0.37334551 1.58978028]\n", - "P_ = [0.06411609 2.1867073 0.11556786 2.05053959 0.14496006 2.02978878\n", - " 0.17725799 1.98952323 0.19401999 1.93862524 0.214709 1.88872137\n", - " 0.22808951 1.82892116 0.23229649 1.77955587 0.23183957 1.74116939\n", - " 0.23689658 1.70110816 0.25375172 1.6683264 0.27186214 1.64726455\n", - " 0.28362038 1.62119107 0.29056965 1.59790638 0.33105076 1.59041819\n", - " 0.37334551 1.58978028]\n", - "Depth = 16, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.975130\n", - " Iterations: 230\n", - " Function evaluations: 368\n", - "P = [0.06321803 2.19552257 0.11846696 2.04161295 0.14167827 2.0286526\n", - " 0.17828012 1.99382919 0.19119432 1.93264973 0.21364372 1.89437964\n", - " 0.22437439 1.82779056 0.23517761 1.77734237 0.22963595 1.73886521\n", - " 0.24452474 1.69996944 0.25366086 1.6684009 0.27215067 1.64067639\n", - " 0.28965886 1.62037877 0.29527137 1.60126386 0.33432564 1.59048448\n", - " 0.37451641 1.58891698]\n", - "P_ = [0.06321803 2.19552257 0.1150139 2.0512323 0.13877685 2.03027264\n", - " 0.17141727 2.00035858 0.18796577 1.94794459 0.20662829 1.90633905\n", - " 0.22035039 1.85276147 0.2304512 1.79941346 0.23240678 1.75810379\n", - " 0.2361498 1.72184831 0.24795079 1.68813124 0.25943893 1.659737\n", - " 0.27652772 1.63560199 0.29071121 1.61679472 0.30015315 1.59991643\n", - " 0.33683756 1.59038651 0.37451641 1.58891698]\n", - "Depth = 17, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 1.984139\n", - " Iterations: 212\n", - " Function evaluations: 356\n", - "P = [0.06295195 2.19706894 0.11444204 2.04915369 0.13937509 2.03455539\n", - " 0.17231074 1.99652897 0.18559372 1.9481673 0.20586716 1.90324758\n", - " 0.21675714 1.85329342 0.23441683 1.80191096 0.22928551 1.75189904\n", - " 0.242602 1.71856007 0.25265426 1.69084404 0.25922495 1.65031415\n", - " 0.28187207 1.63285668 0.29365075 1.61627918 0.30227724 1.59896481\n", - " 0.33614795 1.594722 0.37501892 1.58674906]\n", - "P_ = [0.06295195 2.19706894 0.11141321 2.05785458 0.13644179 2.03627283\n", - " 0.16649856 2.00323951 0.18246831 1.95954652 0.19990439 1.91645926\n", - " 0.21291362 1.8709243 0.2271452 1.82306844 0.23170025 1.77543406\n", - " 0.2355521 1.73621011 0.24674117 1.70714759 0.25497332 1.67653937\n", - " 0.26588587 1.6451796 0.28464352 1.62895609 0.29517308 1.6132237\n", - " 0.30626203 1.59846566 0.33843448 1.594253 0.37501892 1.58674906]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.983082\n", - " Iterations: 204\n", - " Function evaluations: 333\n", - "P = [0.06079548 2.2045252 0.11300465 2.05873743 0.13628417 2.04255719\n", - " 0.1678854 2.00149986 0.17884703 1.95660976 0.20030549 1.91961075\n", - " 0.20963433 1.86662048 0.23009541 1.82746468 0.23266445 1.77073821\n", - " 0.23847032 1.72964237 0.25063196 1.71352776 0.25773287 1.67142333\n", - " 0.2670486 1.6452613 0.2867957 1.63122083 0.29895866 1.61197584\n", - " 0.30640887 1.59845734 0.33879924 1.59473381 0.37768018 1.58210124]\n", - "P_ = [0.06079548 2.2045252 0.11010414 2.06683675 0.13369756 2.044355\n", - " 0.16261853 2.00834275 0.17641111 1.96658534 0.1943448 1.92988825\n", - " 0.20652472 1.88428391 0.22213832 1.84269194 0.23152265 1.79594998\n", - " 0.23556738 1.75019029 0.24387549 1.72248032 0.25339343 1.69715381\n", - " 0.26083812 1.66270265 0.27253391 1.64136117 0.28949858 1.62694417\n", - " 0.30020036 1.60972276 0.3100078 1.59804361 0.34095929 1.594032\n", - " 0.37768018 1.58210124]\n", - "Depth = 19, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.919298\n", - " Iterations: 1297\n", - " Function evaluations: 1628\n", - "P = [0.07376491 2.14364889 0.08190907 2.0695512 0.16072306 2.07570895\n", - " 0.12170724 1.93187686 0.1529947 2.02388809 0.1812431 1.8798608\n", - " 0.17940391 1.88791252 0.19559045 1.76526768 0.22539763 1.80849575\n", - " 0.34630763 1.72075667 0.25311758 1.72877482 0.29472153 1.62432913\n", - " 0.20933485 1.60250562 0.3159205 1.66360685 0.25824877 1.65200776\n", - " 0.31730789 1.65146498 0.34621458 1.64318676 0.18754389 1.64338712\n", - " 0.36596112 1.599337 ]\n", - "P_ = [0.07376491 2.14364889 0.08148043 2.07345107 0.15242685 2.07506076\n", - " 0.12786763 1.95458719 0.14640787 2.0045173 0.17380931 1.91776272\n", - " 0.17998471 1.88536987 0.18962699 1.81045262 0.21284723 1.79029446\n", - " 0.28903447 1.76231729 0.30216498 1.72455474 0.27063504 1.68479769\n", - " 0.26326328 1.61628889 0.24299347 1.62180075 0.30074373 1.66055446\n", - " 0.27068227 1.65189349 0.3218721 1.65015789 0.32951241 1.64320785\n", - " 0.19693427 1.64106869 0.36596112 1.599337 ]\n", - "Depth = 20, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.010003\n", - " Iterations: 380\n", - " Function evaluations: 555\n", - "P = [0.07282448 2.12637381 0.08337129 2.04599016 0.1471489 2.10258421\n", - " 0.12956577 1.91857985 0.14477568 2.03851725 0.17606956 1.92617652\n", - " 0.18116057 1.89222586 0.19463746 1.80838423 0.21516155 1.83894724\n", - " 0.28720984 1.72876897 0.30055133 1.72487139 0.27980001 1.68424735\n", - " 0.25413347 1.60503362 0.24541854 1.63556717 0.30391207 1.65909732\n", - " 0.27134092 1.64738611 0.32364652 1.63405475 0.32839104 1.63944383\n", - " 0.19925629 1.62464899 0.36864891 1.58790924]\n", - "P_ = [0.07282448 2.12637381 0.08284395 2.05000935 0.14077113 2.09692481\n", - " 0.13220324 1.94618051 0.1417337 2.01452977 0.16824609 1.9542617\n", - " 0.17963327 1.90241106 0.18992055 1.8377288 0.20695191 1.82672204\n", - " 0.2547881 1.77834919 0.29388058 1.72682018 0.29121324 1.70659057\n", - " 0.2695334 1.65256186 0.25108324 1.61572036 0.2629666 1.64262621\n", - " 0.29576928 1.65616952 0.28180204 1.64471984 0.3243582 1.63486311\n", - " 0.31547756 1.63796434 0.20772592 1.622812 0.36864891 1.58790924]\n", - "Depth = 21, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.949847\n", - " Iterations: 544\n", - " Function evaluations: 769\n", - "P = [0.07221812 2.11446082 0.08358594 2.04434863 0.14449872 2.1013003\n", - " 0.13330743 1.95444549 0.14217747 2.01050855 0.16936316 1.95017002\n", - " 0.18015411 1.92412707 0.19527895 1.82462708 0.21086856 1.85516019\n", - " 0.2597393 1.76784654 0.28906557 1.71816512 0.28891514 1.69332933\n", - " 0.26919137 1.6464076 0.24429638 1.62688009 0.25725277 1.63053462\n", - " 0.29162932 1.66431755 0.27858828 1.63302694 0.31511693 1.63406264\n", - " 0.31209157 1.64629097 0.21282072 1.6202537 0.38216047 1.57907592]\n", - "P_ = [0.07221812 2.11446082 0.08304461 2.04768731 0.1386975 2.09587633\n", - " 0.13490619 1.97542475 0.14048794 1.99982987 0.16289038 1.96453634\n", - " 0.17707098 1.93156792 0.19023734 1.85779374 0.20492966 1.84352853\n", - " 0.23879469 1.80526668 0.27510068 1.74182294 0.28899394 1.70633855\n", - " 0.28046209 1.67322002 0.25970756 1.63896855 0.24861517 1.62809826\n", - " 0.26707464 1.64018689 0.28852431 1.6568674 0.28554612 1.63322422\n", - " 0.31468473 1.63580954 0.30263721 1.64381123 0.22088452 1.61829286\n", - " 0.38216047 1.57907592]\n", - "Depth = 22, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.986389\n", - " Iterations: 348\n", - " Function evaluations: 531\n", - "P = [0.06852947 2.12465731 0.08429433 2.03455331 0.13782545 2.10782044\n", - " 0.13731157 1.97192202 0.13974418 2.00692155 0.16565127 1.94884723\n", - " 0.17585928 1.94260916 0.19320361 1.8474135 0.20715735 1.85393436\n", - " 0.24439239 1.79960409 0.27363686 1.75403479 0.28924192 1.68922496\n", - " 0.2831581 1.66693184 0.25846498 1.64181144 0.24876417 1.62364874\n", - " 0.26756361 1.64711971 0.2879415 1.65457874 0.2855759 1.62965192\n", - " 0.31456774 1.64357348 0.30129864 1.64106362 0.22382507 1.60082017\n", - " 0.38665752 1.57959856]\n", - "P_ = [0.06852947 2.12465731 0.08357774 2.03864895 0.13295899 2.10115979\n", - " 0.13738165 1.99045363 0.13930189 2.000558 0.15976329 1.96204594\n", - " 0.17307528 1.94431045 0.18768496 1.87770303 0.20208327 1.85156314\n", - " 0.22915988 1.82183011 0.26034392 1.77474811 0.28143939 1.72162987\n", - " 0.28647655 1.67909172 0.27305637 1.65665531 0.25493741 1.63520682\n", - " 0.25474581 1.63111678 0.27312121 1.64915399 0.28740386 1.64891356\n", - " 0.29084714 1.63218311 0.31275832 1.64323122 0.29425559 1.63740513\n", - " 0.23122655 1.59985555 0.38665752 1.57959856]\n", - "Depth = 23, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.957480\n", - " Iterations: 360\n", - " Function evaluations: 555\n", - "P = [0.06805512 2.12805296 0.08391013 2.0349739 0.13432357 2.10612944\n", - " 0.13764269 1.98787336 0.13879706 1.99945504 0.16089299 1.95444312\n", - " 0.17284563 1.94723177 0.18845699 1.86673461 0.2024127 1.86319031\n", - " 0.23355564 1.80907845 0.25730541 1.78787652 0.28016167 1.71239242\n", - " 0.28872044 1.67072627 0.27103344 1.66397908 0.25539968 1.62694765\n", - " 0.25716178 1.63909414 0.27138582 1.64752771 0.2865412 1.64662257\n", - " 0.29255303 1.63819379 0.31044968 1.65290276 0.29781086 1.62400724\n", - " 0.23389951 1.5935477 0.3889098 1.58275954]\n", - "P_ = [0.06805512 2.12805296 0.08322079 2.03902081 0.1299398 2.099942\n", - " 0.13720976 2.00329806 0.1385963 1.99744084 0.15608953 1.96422832\n", - " 0.16972755 1.94911299 0.18370571 1.89123374 0.19755854 1.86442311\n", - " 0.22136928 1.83025265 0.24697943 1.79709475 0.26923041 1.74849351\n", - " 0.28425499 1.69246513 0.28103044 1.66779271 0.26491588 1.64948852\n", - " 0.25601258 1.63117251 0.26149083 1.64166088 0.2753394 1.64729158\n", - " 0.28784812 1.64479022 0.29566549 1.64075187 0.30880114 1.64913378\n", - " 0.29225335 1.62135858 0.24063909 1.59307865 0.3889098 1.58275954]\n", - "Depth = 24, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.971140\n", - " Iterations: 405\n", - " Function evaluations: 624\n", - "P = [0.06689718 2.1385342 0.08427989 2.0205662 0.12904611 2.10858769\n", - " 0.13823959 2.00418083 0.13696987 2.00491956 0.15789403 1.96104795\n", - " 0.16903557 1.9554995 0.18231528 1.88650166 0.19727409 1.87224011\n", - " 0.22215128 1.82089937 0.24857915 1.80285004 0.26616493 1.7472375\n", - " 0.28454679 1.68668618 0.2844928 1.66810799 0.26378199 1.64196793\n", - " 0.25881133 1.63779048 0.26308319 1.64162496 0.27615626 1.65118807\n", - " 0.28917075 1.65035081 0.29465331 1.64926888 0.30878673 1.64408659\n", - " 0.29239003 1.61461599 0.2431959 1.59668157 0.39534115 1.5824426 ]\n", - "P_ = [0.06689718 2.1385342 0.08355561 2.02548153 0.12531559 2.10125257\n", - " 0.13709041 2.01723168 0.13718149 2.00479644 0.15353483 1.97018786\n", - " 0.16625018 1.95688661 0.17844203 1.90662603 0.19228782 1.87699396\n", - " 0.21282233 1.84015215 0.23756754 1.8103706 0.25810478 1.77272658\n", - " 0.27535586 1.71696184 0.28452205 1.67817118 0.2758633 1.6572163\n", - " 0.26191799 1.64040139 0.26023528 1.63906864 0.26689617 1.6444142\n", - " 0.27940988 1.65097875 0.29031295 1.65012541 0.29700888 1.64840517\n", - " 0.30673714 1.64040277 0.28829052 1.61312145 0.24953529 1.59608828\n", - " 0.39534115 1.5824426 ]\n", - "Depth = 25, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 1.965344\n", - " Iterations: 419\n", - " Function evaluations: 645\n", - "P = [0.0664789 2.13071993 0.08392494 2.01202679 0.12765991 2.10379696\n", - " 0.13516311 2.0114732 0.13689902 2.00892511 0.15255579 1.96350939\n", - " 0.16613791 1.96422142 0.17561094 1.89473844 0.19248245 1.88422495\n", - " 0.21276094 1.82976422 0.23863236 1.816351 0.25779194 1.767292\n", - " 0.27660372 1.71853224 0.28697337 1.67910569 0.27869746 1.64790656\n", - " 0.26348539 1.64911501 0.26298942 1.63643133 0.26776399 1.64555681\n", - " 0.28170744 1.65978125 0.28950637 1.65974425 0.2969573 1.64849854\n", - " 0.30521345 1.63768305 0.28968478 1.61732549 0.25034435 1.58937622\n", - " 0.3990776 1.58947499]\n", - "P_ = [0.0664789 2.13071993 0.0832271 2.01677451 0.12416112 2.09645534\n", - " 0.13426273 2.02255205 0.13662127 2.0093328 0.14942443 1.97259253\n", - " 0.1628782 1.96405053 0.17295849 1.91419368 0.18708356 1.88758927\n", - " 0.20546068 1.84937008 0.2282838 1.82171629 0.24936172 1.78887796\n", - " 0.26757407 1.74193692 0.28158116 1.6996075 0.28333197 1.66537807\n", - " 0.27261263 1.64838994 0.26330684 1.64454889 0.26451728 1.63935148\n", - " 0.27166816 1.64953965 0.28357918 1.65977237 0.29099655 1.6574951\n", - " 0.29827828 1.64676806 0.30335001 1.63524015 0.28653754 1.61508955\n", - " 0.25629368 1.58938017 0.3990776 1.58947499]\n", - "Depth = 26, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.975662\n", - " Iterations: 387\n", - " Function evaluations: 611\n", - "P = [0.06525064 2.13564014 0.08398487 2.00799003 0.12391271 2.10053221\n", - " 0.13550565 2.01974092 0.1346108 2.01243284 0.14993639 1.97086309\n", - " 0.16250983 1.96994718 0.17355878 1.90509811 0.18669761 1.89243026\n", - " 0.20489097 1.84311126 0.22934557 1.8213694 0.25006358 1.79098351\n", - " 0.27059022 1.73845641 0.28392796 1.70341418 0.28271764 1.65716523\n", - " 0.27562691 1.65238494 0.26555213 1.64916045 0.26341757 1.63761857\n", - " 0.27139797 1.65911216 0.28398449 1.66591052 0.29165237 1.653003\n", - " 0.2978948 1.64357453 0.30174895 1.63976959 0.28886192 1.61099387\n", - " 0.25802876 1.59062319 0.40064934 1.58681866]\n", - "P_ = [0.06525064 2.13564014 0.08326432 2.01289965 0.12084134 2.09341358\n", - " 0.134168 2.02906299 0.13474847 2.01355716 0.14698917 1.97885727\n", - " 0.15960827 1.97015854 0.17058406 1.92255747 0.18265489 1.89632806\n", - " 0.19859327 1.86018322 0.21993996 1.82973165 0.24129827 1.80383908\n", - " 0.26111639 1.76269969 0.27725909 1.72093529 0.28336935 1.68206851\n", - " 0.27971772 1.6551428 0.27175199 1.65114475 0.26481324 1.64516518\n", - " 0.26587308 1.64423198 0.27478665 1.66094249 0.285754 1.66293186\n", - " 0.29285284 1.65118983 0.29848774 1.64298915 0.30026198 1.63644932\n", - " 0.28649014 1.60942689 0.26351416 1.59047686 0.40064934 1.58681866]\n", - "Depth = 27, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.975645\n", - " Iterations: 380\n", - " Function evaluations: 580\n", - "P = [0.06477204 2.13813072 0.08356349 2.00555542 0.12296788 2.09485952\n", - " 0.13361427 2.02522874 0.13445581 2.01720453 0.14595531 1.97488523\n", - " 0.15977873 1.97517202 0.16926502 1.91411237 0.1829637 1.89967577\n", - " 0.19768695 1.85331924 0.22091918 1.82883241 0.23869379 1.8001551\n", - " 0.26349703 1.76215624 0.28007366 1.72162448 0.28511851 1.68119798\n", - " 0.28330643 1.65426526 0.27384064 1.65194177 0.26585494 1.64722608\n", - " 0.26567314 1.65019717 0.27681941 1.66685324 0.28488277 1.66137529\n", - " 0.29140076 1.65014158 0.29789369 1.6471924 0.30265266 1.62943795\n", - " 0.28859338 1.60760437 0.26341605 1.58861726 0.40313111 1.5910862 ]\n", - "P_ = [0.06477204 2.13813072 0.08286751 2.01046562 0.12004903 2.0882444\n", - " 0.13243134 2.03296549 0.13433113 2.01839331 0.14382577 1.98272214\n", - " 0.15670686 1.97510829 0.16680561 1.92994265 0.17890484 1.90395328\n", - " 0.1927792 1.86877142 0.21231465 1.83790161 0.23145228 1.81183845\n", - " 0.25247337 1.77904462 0.27209232 1.74113977 0.28250266 1.70215987\n", - " 0.28431314 1.66922788 0.27945 1.65331865 0.27088298 1.65019522\n", - " 0.26579434 1.64821645 0.26897574 1.6551323 0.27890991 1.66543303\n", - " 0.28633121 1.65887891 0.29260315 1.64959543 0.29859872 1.64456211\n", - " 0.30109052 1.627012 0.28672839 1.60619792 0.26859068 1.5887087\n", - " 0.40313111 1.5910862 ]\n", - "Depth = 28, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.975538\n", - " Iterations: 388\n", - " Function evaluations: 612\n", - "P = [0.06384747 2.14268594 0.08377974 2.00018233 0.11979638 2.09177433\n", - " 0.13429126 2.03004985 0.13181343 2.02012607 0.14470129 1.9808686\n", - " 0.15585325 1.97985361 0.16635575 1.92220214 0.17918837 1.90689322\n", - " 0.19164189 1.86546191 0.21222191 1.83987946 0.22988524 1.81293341\n", - " 0.25488088 1.77262773 0.27438288 1.7453824 0.28180326 1.70011787\n", - " 0.28691229 1.67201694 0.28010538 1.65504691 0.27231721 1.64548805\n", - " 0.2660027 1.65791089 0.26900684 1.65592397 0.27777777 1.66300563\n", - " 0.28601045 1.66004388 0.2933278 1.65257744 0.29843201 1.63909273\n", - " 0.30987514 1.63195718 0.286496 1.6036846 0.26945055 1.59192089\n", - " 0.40425539 1.58986493]\n", - "P_ = [0.06384747 2.14268594 0.08306788 2.00527174 0.11722376 2.08523204\n", - " 0.13273823 2.03666319 0.13216741 2.02154376 0.14239988 1.98787887\n", - " 0.15346354 1.98007111 0.16373012 1.93661501 0.17552191 1.9112672\n", - " 0.18763897 1.87877912 0.2048719 1.84901605 0.22294608 1.82351936\n", - " 0.24416846 1.78990159 0.26532838 1.75803202 0.27809307 1.72275014\n", - " 0.28417531 1.68707101 0.28399504 1.66474407 0.27704574 1.65129164\n", - " 0.27006203 1.64992478 0.26696832 1.65727224 0.27151282 1.6579473\n", - " 0.27983594 1.66226519 0.28757845 1.65844393 0.29423926 1.65016946\n", - " 0.30006674 1.63807337 0.30737023 1.62892797 0.28527846 1.60284434\n", - " 0.274265 1.59184746 0.40425539 1.58986493]\n", - "Depth = 29, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.979082\n", - " Iterations: 524\n", - " Function evaluations: 776\n", - "P = [0.06371532 2.14321294 0.08299379 1.99640501 0.12083547 2.08382756\n", - " 0.13240833 2.03118564 0.13223601 2.02197044 0.14122299 1.98532711\n", - " 0.15466018 1.98054911 0.16153854 1.92731334 0.17511425 1.91499912\n", - " 0.18525607 1.87124366 0.20352353 1.84955395 0.21952916 1.82574098\n", - " 0.24791078 1.78457126 0.26799023 1.75554406 0.27981067 1.72645817\n", - " 0.28829778 1.68748965 0.28821411 1.6671798 0.27965487 1.64821013\n", - " 0.27327754 1.65538825 0.26745771 1.66247248 0.26622752 1.65372711\n", - " 0.27575738 1.66628179 0.2868581 1.66297448 0.29376228 1.64321439\n", - " 0.30068404 1.63585113 0.3105821 1.62554972 0.28966569 1.60421297\n", - " 0.27514873 1.59429725 0.4073548 1.58787156]\n", - "P_ = [0.06371532 2.14321294 0.08232901 2.00146735 0.1182257 2.07779842\n", - " 0.13121113 2.03663136 0.13225977 2.0232415 0.13967351 1.99164492\n", - " 0.15188007 1.98153766 0.15987825 1.94016336 0.17136923 1.91839614\n", - " 0.18210861 1.88482294 0.1972244 1.85703316 0.21345806 1.83477349\n", - " 0.23616666 1.80160701 0.25898909 1.76855625 0.27410425 1.74049964\n", - " 0.2839079 1.70764578 0.28826027 1.67838523 0.28467236 1.65933028\n", - " 0.27723588 1.65093286 0.2712707 1.65783109 0.26707592 1.6597584\n", - " 0.26885645 1.65719047 0.27843687 1.66548348 0.28828655 1.65888619\n", - " 0.29495569 1.64194486 0.30204929 1.63443024 0.30841833 1.62334247\n", - " 0.28866452 1.60352912 0.27970756 1.59407568 0.4073548 1.58787156]\n", - "Depth = 30, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.971173\n", - " Iterations: 394\n", - " Function evaluations: 624\n", - "1.0666666666666667 [6.49994672 4.88882719 2.95527185 2.56103691 2.30896497 2.02931692\n", - " 1.98202209 1.98616825 1.94943845 1.96791642 1.95302927 1.97105298\n", - " 1.97120794 1.9655048 1.9681674 1.9751298 1.98413897 1.98308202\n", - " 1.91929808 2.01000255 1.94984691 1.98638931 1.95748009 1.97114047\n", - " 1.96534448 1.97566161 1.97564463 1.97553754 1.97908207 1.97117283]\n", - "[[6.57155339 5.94790512 4.51084725 5.48476219 4.44827696 4.07086367\n", - " 4.45993119 3.76473244 3.75245393 3.70383406 2.54453644 2.75335922\n", - " 3.72365101 2.64914745 3.66152866 3.41308183 2.17660478 2.18383796\n", - " 2.54980097 1.72430929 2.24071873 1.8353618 2.04963403 1.97768311\n", - " 2.25839296 2.22977067 1.94603139 2.05226045 2.69504832 3.27724127]\n", - " [7.58106801 6.81608452 4.28714233 4.07123972 3.27046962 3.23940109\n", - " 3.69518164 3.2411352 2.8435791 2.91039551 2.52147765 2.7118309\n", - " 2.7196728 2.5657514 2.49654928 2.14986169 2.03773181 1.96011255\n", - " 1.99818881 1.99560667 2.10966328 1.86491841 1.83579189 1.98703992\n", - " 1.98133515 1.95306622 1.90928783 1.85507609 1.79545032 1.7963689 ]\n", - " [5.67675131 4.71392584 4.01740509 3.36995594 3.02811997 2.75900701\n", - " 2.07994453 1.87160639 1.76736629 1.60399896 1.51494314 1.48018664\n", - " 1.42851074 1.41006842 1.37578808 1.29188206 1.25021059 1.25293931\n", - " 1.22202663 1.23016691 1.26143882 1.20441019 1.17776388 1.18431374\n", - " 1.16553331 1.16956844 1.16569465 1.17659931 1.16990127 1.15831922]\n", - " [5.00995896 4.29025145 4.60820671 3.83390873 3.89848291 5.33118031\n", - " 3.55893822 3.40156727 4.09051018 4.16531197 3.86869824 2.74039918\n", - " 2.37252786 2.09790193 2.46381788 3.23389141 2.92683369 2.26271526\n", - " 2.22500107 1.72792525 1.99341501 2.13517458 2.55949815 2.08833212\n", - " 2.30394139 2.47254611 2.09431819 2.0108552 2.25457883 1.56109974]\n", - " [4.00096445 3.74521392 2.59257503 2.56365739 1.9185404 1.87747501\n", - " 1.74225195 1.62820595 1.46249835 1.3728014 1.35944481 1.35683453\n", - " 1.33094362 1.31878632 1.32159957 1.30276576 1.25442761 1.25346875\n", - " 1.23969275 1.23278308 1.2266854 1.22191909 1.20703107 1.20899474\n", - " 1.20219427 1.20085781 1.20009343 1.19826693 1.1915774 1.19065828]\n", - " [5.90892769 4.83252908 3.71479956 3.36110121 2.94173277 2.24786958\n", - " 2.12439453 2.02822257 1.99458002 1.79405078 1.71446451 1.68436207\n", - " 1.64831949 1.60645585 1.57877549 1.55946868 1.50646832 1.48490593\n", - " 1.46944309 1.45423724 1.43322495 1.41715875 1.39899314 1.36097986\n", - " 1.33935151 1.32162911 1.30734052 1.2947269 1.27768564 1.26760576]\n", - " [5.07730592 3.19397021 2.56921505 2.2196952 1.87944827 1.7817944\n", - " 1.79674014 1.74393688 1.72491634 1.70478017 1.70372389 1.71403689\n", - " 1.71964722 1.71701915 1.65427385 1.66354751 1.65446129 1.64731001\n", - " 1.64582841 1.63908351 1.60606623 1.61407892 1.61749603 1.58823071\n", - " 1.60544517 1.59941945 1.61244841 1.60748773 1.61573555 1.61325776]\n", - " [6.09370005 4.58327549 2.77056736 2.4009721 2.16465466 1.90248461\n", - " 1.85814571 1.86203274 1.82759854 1.84492164 1.83096494 1.84786217\n", - " 1.84800744 1.84266075 1.84515694 1.85168419 1.86013029 1.8591394\n", - " 1.79934195 1.88437739 1.82798148 1.86223998 1.83513759 1.84794419\n", - " 1.84251045 1.85218276 1.85216684 1.85206644 1.85538944 1.84797453]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]] [4.59202298 3.81231556 2.90707584 2.73052925 2.35497256 2.32100757\n", - " 2.13155279 1.95414394 1.94635027 1.91000945 1.70582536 1.62888716\n", - " 1.67912802 1.52077913 1.63974898 1.64661831 1.46668684 1.39044292\n", - " 1.41493237 1.28884893 1.36991939 1.31552617 1.36813458 1.32435184\n", - " 1.36987042 1.37990406 1.30873813 1.3047339 1.38553668 1.37125255]\n", - "[[0.1749857 0.07463194 0.26530491 0.16394175 0.18892849 0.25701077\n", - " 0.24542951 0.40504394 0.18547862 0.24113788 0.62032714 0.68408453\n", - " 0.11521194 0.57930818 0.29653581 0.32221821 0.75779012 0.76858176\n", - " 0.59269399 0.8271978 0.69201592 0.87101232 0.79114835 0.72852071\n", - " 0.64433266 0.66377712 0.77675308 0.72982301 0.58648573 0.44154865]\n", - " [0.17669094 0.20818569 0.40598211 0.40456531 0.54848127 0.5337594\n", - " 0.48446167 0.53759304 0.60295388 0.58451793 0.64895146 0.66165701\n", - " 0.62972457 0.66201878 0.67281148 0.75627098 0.78514972 0.80366385\n", - " 0.79430362 0.79961314 0.7524382 0.82370466 0.83214203 0.78138294\n", - " 0.78255631 0.78124579 0.80687807 0.80774629 0.84561002 0.84356134]\n", - " [0.1977358 0.23204622 0.30938238 0.39342279 0.41016143 0.46245125\n", - " 0.76102816 0.79966194 0.84980142 0.9167973 0.93013476 0.94105633\n", - " 0.96019643 0.9567664 0.95781341 0.97258171 0.97672161 0.97483651\n", - " 0.98345276 0.97827363 0.97171746 0.98525476 0.99020549 0.988242\n", - " 0.99105685 0.98789452 0.98718377 0.98332188 0.98342322 0.98330761]\n", - " [0.05772911 0.21353746 0.01841155 0.31450455 0.21424321 0.05404723\n", - " 0.43161435 0.34272799 0.28819124 0.28689022 0.1868918 0.50636735\n", - " 0.71458126 0.77159991 0.58971876 0.39292553 0.46431953 0.6325678\n", - " 0.69978407 0.80479284 0.72769493 0.74105124 0.53269212 0.73999712\n", - " 0.61502723 0.52602161 0.71815241 0.71745393 0.53403795 0.82706806]\n", - " [0.12450898 0.13546046 0.33397169 0.30579603 0.53279986 0.54005574\n", - " 0.5789386 0.62157361 0.67239022 0.70608977 0.71741324 0.71989795\n", - " 0.72816408 0.73770709 0.7462425 0.75395046 0.77610427 0.778063\n", - " 0.78739546 0.80304068 0.8044153 0.81655327 0.83574318 0.83983299\n", - " 0.85295023 0.85822598 0.86248183 0.86742561 0.8687046 0.87578262]\n", - " [0.15384579 0.23299282 0.34316369 0.40381029 0.48323069 0.60966505\n", - " 0.65090211 0.6781041 0.69468559 0.73757271 0.76352272 0.78064924\n", - " 0.80250928 0.8256876 0.84161068 0.85173433 0.88960447 0.89427145\n", - " 0.89713168 0.89784489 0.90396968 0.90972365 0.91944211 0.93551855\n", - " 0.93997379 0.94289646 0.9440385 0.94476954 0.94821036 0.94920811]\n", - " [0.22662278 0.49591192 0.64928992 0.72253971 0.88505646 0.91736256\n", - " 0.93108311 0.94041937 0.96629845 0.97837675 0.97999527 0.98011569\n", - " 0.97939879 0.97927928 0.98252313 0.98523181 0.98698179 0.98795262\n", - " 0.98839303 0.98858465 0.9918529 0.99290353 0.99289167 0.99426743\n", - " 0.9945867 0.99461399 0.99442154 0.99355126 0.99301575 0.99210625]\n", - " [0.1997449 0.39406338 0.8125561 0.89215215 0.93988072 0.97583839\n", - " 0.98050285 0.98626726 0.98996115 0.99116577 0.99318232 0.99328416\n", - " 0.99223222 0.99419442 0.9931634 0.99226818 0.99206014 0.99172956\n", - " 0.99264689 0.98944046 0.9912926 0.99247498 0.99365946 0.99432346\n", - " 0.99379021 0.99295831 0.9931038 0.99245639 0.99277207 0.99313253]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]] [0.1311864 0.19868299 0.31380624 0.36007326 0.42027821 0.43501904\n", - " 0.50639604 0.53113912 0.52497606 0.54425483 0.58404187 0.62671123\n", - " 0.59220186 0.65065617 0.60804192 0.60271812 0.66287317 0.68316666\n", - " 0.67358015 0.70887881 0.6835397 0.71326784 0.68879244 0.70020852\n", - " 0.6814274 0.67476338 0.7083013 0.70365479 0.67522597 0.69057152]\n", - "\n", - "Now using 4 solutions, set number 3\n", - "Calculating energy landscape ...\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 7.139535\n", - " Iterations: 23\n", - " Function evaluations: 44\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 7.139535\n", - " Iterations: 6\n", - " Function evaluations: 13\n", - "P = [0.17961272 1.96243231]\n", - "P_ = [0.17961272 1.96243231 0.17961272 1.96243231]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 5.049507\n", - " Iterations: 71\n", - " Function evaluations: 120\n", - "P = [0.18303272 2.1169084 0.32130532 1.85502987]\n", - "P_ = [0.18303272 2.1169084 0.25216902 1.98596913 0.32130532 1.85502987]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.613761\n", - " Iterations: 50\n", - " Function evaluations: 87\n", - "P = [0.15718867 2.0973104 0.3002773 1.94788852 0.30737335 1.81106403]\n", - "P_ = [0.15718867 2.0973104 0.25258109 1.99769582 0.30264265 1.90228036\n", - " 0.30737335 1.81106403]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.928660\n", - " Iterations: 243\n", - " Function evaluations: 356\n", - "P = [0.1443243 2.09615077 0.24432009 1.86101891 0.17813547 1.79599216\n", - " 0.25545675 1.77531699]\n", - "P_ = [0.1443243 2.09615077 0.21932114 1.91980188 0.21122778 1.82850554\n", - " 0.19746579 1.79082337 0.25545675 1.77531699]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.669350\n", - " Iterations: 226\n", - " Function evaluations: 331\n", - "P = [0.09963524 2.09355701 0.17351557 1.88023402 0.21262608 1.89610063\n", - " 0.2753192 1.83275498 0.276892 1.67300447]\n", - "P_ = [0.09963524 2.09355701 0.1587395 1.92289862 0.19698188 1.88975399\n", - " 0.23770333 1.87076237 0.27563376 1.80080488 0.276892 1.67300447]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.555121\n", - " Iterations: 140\n", - " Function evaluations: 212\n", - "P = [0.10566526 2.08747413 0.16010064 1.88577291 0.21430545 1.91018815\n", - " 0.23898452 1.7989697 0.21888865 1.72967649 0.30595338 1.64666695]\n", - "P_ = [0.10566526 2.08747413 0.15102808 1.91938978 0.19623718 1.90204974\n", - " 0.22664499 1.85457893 0.2322859 1.77587196 0.23339944 1.71584157\n", - " 0.30595338 1.64666695]\n", - "Depth = 7, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.530674\n", - " Iterations: 291\n", - " Function evaluations: 425\n", - "P = [0.0850034 2.12581487 0.1534327 1.88506142 0.19151417 1.91651395\n", - " 0.24799277 1.81405731 0.17701817 1.73670978 0.25922608 1.69035874\n", - " 0.38999756 1.59767742]\n", - "P_ = [0.0850034 2.12581487 0.14365709 1.91945477 0.18063375 1.90752751\n", - " 0.22378766 1.8579673 0.21757509 1.78090837 0.20050614 1.72346663\n", - " 0.27790772 1.67711855 0.38999756 1.59767742]\n", - "Depth = 8, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.540076\n", - " Iterations: 75\n", - " Function evaluations: 132\n", - "P = [0.0826958 2.12989969 0.14265266 1.93325134 0.18327343 1.9076983\n", - " 0.22382807 1.85875488 0.21848331 1.76193965 0.20691291 1.72044413\n", - " 0.27802714 1.66162032 0.40223535 1.60866626]\n", - "P_ = [0.0826958 2.12989969 0.13515805 1.95783239 0.17311824 1.91408656\n", - " 0.20862008 1.87710866 0.22115569 1.81034727 0.21414441 1.74637883\n", - " 0.22469147 1.70573818 0.29355317 1.65500107 0.40223535 1.60866626]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.549686\n", - " Iterations: 134\n", - " Function evaluations: 213\n", - "P = [0.07991339 2.10833345 0.1362025 1.93733428 0.17535662 1.94032617\n", - " 0.21539483 1.85623004 0.21528096 1.80978312 0.22063529 1.72269699\n", - " 0.2275382 1.71701956 0.30256139 1.64436562 0.39751573 1.61403004]\n", - "P_ = [0.07991339 2.10833345 0.12994815 1.95633419 0.1666557 1.93966131\n", - " 0.20204876 1.88426208 0.21533157 1.83042619 0.21766067 1.77107817\n", - " 0.22293626 1.72080451 0.24421002 1.70087424 0.31311187 1.640995\n", - " 0.39751573 1.61403004]\n", - "Depth = 10, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.550575\n", - " Iterations: 122\n", - " Function evaluations: 206\n", - "P = [0.07947492 2.13925926 0.12840558 1.94507826 0.16853021 1.93594853\n", - " 0.20320016 1.88504419 0.21583252 1.82343627 0.21676781 1.77594805\n", - " 0.22393394 1.71990942 0.24559179 1.68132655 0.31475554 1.65181182\n", - " 0.40534078 1.60719515]\n", - "P_ = [0.07947492 2.13925926 0.12351252 1.96449636 0.16050528 1.93777448\n", - " 0.19279918 1.90031549 0.21077958 1.84807944 0.21630017 1.79969216\n", - " 0.21963427 1.7535326 0.2304313 1.70833456 0.25942454 1.67542361\n", - " 0.32381406 1.64735016 0.40534078 1.60719515]\n", - "Depth = 11, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.440619\n", - " Iterations: 577\n", - " Function evaluations: 782\n", - "P = [0.09164092 2.14845492 0.13360384 1.91144351 0.15461381 1.94570429\n", - " 0.17324902 1.79115998 0.19637203 1.88090421 0.17545799 1.69825594\n", - " 0.20248886 1.78348359 0.17614573 1.67288117 0.27617563 1.70649069\n", - " 0.37750648 1.66970957 0.50511691 1.62471358]\n", - "P_ = [0.09164092 2.14845492 0.12978903 1.93299001 0.15079381 1.93947506\n", - " 0.16816669 1.83330843 0.18796366 1.84826994 0.18496437 1.78127788\n", - " 0.18774475 1.73699578 0.19290954 1.74326453 0.20342661 1.6820474\n", - " 0.29459942 1.69980321 0.38910743 1.66561902 0.50511691 1.62471358]\n", - "Depth = 12, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.468357\n", - " Iterations: 284\n", - " Function evaluations: 398\n", - "P = [0.08707542 2.15761993 0.1407801 1.95363453 0.15753639 1.94821166\n", - " 0.17182969 1.85662159 0.15713969 1.81401584 0.19499817 1.79442512\n", - " 0.19092769 1.76144423 0.20179985 1.72598424 0.20790002 1.72001057\n", - " 0.29676332 1.66828367 0.40979017 1.62295882 0.48214103 1.58967652]\n", - "P_ = [0.08707542 2.15761993 0.13630471 1.97063331 0.15474367 1.94911547\n", - " 0.16825636 1.87951911 0.16203636 1.82821776 0.17922381 1.80258792\n", - " 0.19296293 1.77793467 0.19545776 1.74666923 0.20383324 1.72399302\n", - " 0.23011585 1.70707884 0.31560113 1.66072953 0.41581941 1.6201853\n", - " 0.48214103 1.58967652]\n", - "Depth = 13, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.436269\n", - " Iterations: 406\n", - " Function evaluations: 569\n", - "P = [0.07657993 2.10679461 0.12765587 1.99732118 0.16853924 1.98940194\n", - " 0.17779863 1.8679652 0.15480939 1.82561533 0.18007962 1.81233862\n", - " 0.18812602 1.77507499 0.20338578 1.7767893 0.21246767 1.70647184\n", - " 0.24209409 1.70226838 0.31054238 1.63177179 0.41943029 1.603524\n", - " 0.51846506 1.56918847]\n", - "P_ = [0.07657993 2.10679461 0.12372695 2.00574222 0.16224949 1.99062028\n", - " 0.17566185 1.89598907 0.161883 1.83864606 0.1703603 1.81744505\n", - " 0.18441229 1.79227359 0.19516898 1.77586621 0.20687882 1.74974413\n", - " 0.22158349 1.70517847 0.25788985 1.68599994 0.32729436 1.62742598\n", - " 0.42704835 1.6008828 0.51846506 1.56918847]\n", - "Depth = 14, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.449968\n", - " Iterations: 124\n", - " Function evaluations: 224\n", - "P = [0.0755455 2.1186432 0.12413481 1.99194238 0.16374672 1.98946587\n", - " 0.1786238 1.9031882 0.16120997 1.83562962 0.17180735 1.81199592\n", - " 0.18529787 1.79827593 0.19612044 1.7768869 0.20829098 1.74687168\n", - " 0.22080705 1.71207618 0.25857188 1.67223858 0.32886728 1.63460794\n", - " 0.42254721 1.59856378 0.52046495 1.58045879]\n", - "P_ = [0.0755455 2.1186432 0.12066415 2.00099244 0.15808788 1.98981966\n", - " 0.17543585 1.92167627 0.16618535 1.85493207 0.16802257 1.82043653\n", - " 0.17951622 1.80415593 0.19070915 1.78758142 0.20133639 1.76402323\n", - " 0.21276101 1.73444471 0.231597 1.70069401 0.27363518 1.66417487\n", - " 0.34225013 1.62945877 0.42954134 1.59727057 0.52046495 1.58045879]\n", - "Depth = 15, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.418132\n", - " Iterations: 403\n", - " Function evaluations: 573\n", - "P = [0.07567789 2.12765958 0.11634724 1.95724533 0.16108612 2.01272246\n", - " 0.18335824 1.91679153 0.16709675 1.86135019 0.16187371 1.82145577\n", - " 0.17598118 1.79573131 0.19226548 1.80808332 0.21062604 1.76836618\n", - " 0.21273392 1.73798358 0.22503736 1.69355245 0.27103025 1.65769887\n", - " 0.33651141 1.62997779 0.45685167 1.58788521 0.51573731 1.55870434]\n", - "P_ = [0.07567789 2.12765958 0.11363595 1.96860628 0.15512093 2.00532551\n", - " 0.17890381 1.93597772 0.17143315 1.87613455 0.16361472 1.83475391\n", - " 0.17033819 1.80602109 0.18466614 1.80231905 0.20083374 1.78954865\n", - " 0.21146919 1.75621314 0.21683507 1.7231732 0.23730213 1.68399149\n", - " 0.28412648 1.65215466 0.35255678 1.62436544 0.46077738 1.58593982\n", - " 0.51573731 1.55870434]\n", - "Depth = 16, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.425034\n", - " Iterations: 241\n", - " Function evaluations: 376\n", - "P = [0.0744911 2.12641864 0.11558181 1.95645336 0.15579562 1.9972039\n", - " 0.18152464 1.93773971 0.1726045 1.86982437 0.16726099 1.82618266\n", - " 0.16968572 1.81334749 0.18310551 1.80104537 0.20241173 1.79240735\n", - " 0.21113458 1.7539459 0.21657205 1.7117284 0.23441574 1.68838456\n", - " 0.28878589 1.64706052 0.34949431 1.6151897 0.45771614 1.59127891\n", - " 0.52474619 1.57318815]\n", - "P_ = [0.0744911 2.12641864 0.11301364 1.96707619 0.15076889 1.99211008\n", - " 0.17670045 1.94888925 0.17483453 1.8868032 0.16893084 1.83982069\n", - " 0.16877644 1.81816068 0.17723435 1.80642755 0.19275862 1.79672636\n", - " 0.20622798 1.77558047 0.21317363 1.73811434 0.22214821 1.70443345\n", - " 0.24800828 1.67805355 0.30016872 1.64108474 0.36302204 1.61220085\n", - " 0.46190552 1.59014824 0.52474619 1.57318815]\n", - "Depth = 17, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.410083\n", - " Iterations: 424\n", - " Function evaluations: 602\n", - "P = [0.06860254 2.15064417 0.11446287 1.984811 0.15651162 1.99943576\n", - " 0.17391473 1.92874212 0.17583896 1.90719006 0.1747912 1.8465023\n", - " 0.17156324 1.81026613 0.17386175 1.80913696 0.19411493 1.7894891\n", - " 0.20549175 1.77023877 0.21305616 1.73481096 0.2231712 1.70380505\n", - " 0.2558119 1.67255953 0.30083802 1.63406345 0.36181848 1.61582837\n", - " 0.4611174 1.5715884 0.53291287 1.55609836]\n", - "P_ = [0.06860254 2.15064417 0.1117652 1.9945659 0.15156471 1.9977152\n", - " 0.17084359 1.94121747 0.1753862 1.91226113 0.17509936 1.86435164\n", - " 0.17270252 1.82305537 0.1729153 1.80960191 0.18458402 1.79873515\n", - " 0.19946873 1.78043012 0.20860651 1.75565085 0.21662618 1.7238677\n", - " 0.23277141 1.69461519 0.26640628 1.66350163 0.31159928 1.6308455\n", - " 0.37350071 1.61062366 0.46534066 1.57067722 0.53291287 1.55609836]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.421623\n", - " Iterations: 191\n", - " Function evaluations: 325\n", - "P = [0.06773319 2.14345704 0.11320782 1.99471579 0.15248818 2.00548653\n", - " 0.17169076 1.93554931 0.17426553 1.90525877 0.1776416 1.86160591\n", - " 0.17323822 1.8344662 0.172194 1.80288402 0.18390806 1.79538451\n", - " 0.1998523 1.78758475 0.21041842 1.74673527 0.21763548 1.73261238\n", - " 0.23411533 1.69071952 0.26845292 1.66346355 0.31289956 1.62927603\n", - " 0.36909953 1.6033083 0.46737736 1.57917666 0.53537962 1.56380818]\n", - "P_ = [0.06773319 2.14345704 0.11068145 2.00297919 0.1481237 2.00428978\n", - " 0.16849033 1.94720551 0.17369336 1.91199 0.17670381 1.87373171\n", - " 0.17470601 1.84351277 0.17260008 1.81516598 0.17870181 1.79871762\n", - " 0.19188018 1.79148463 0.20454835 1.76942942 0.21322506 1.74124303\n", - " 0.22312877 1.71864809 0.24365355 1.68314842 0.27832995 1.65586633\n", - " 0.32226622 1.62494808 0.38001929 1.60062701 0.47115527 1.57832285\n", - " 0.53537962 1.56380818]\n", - "Depth = 19, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.396860\n", - " Iterations: 1257\n", - " Function evaluations: 1592\n", - "P = [0.06450197 2.1267366 0.10486605 2.00275021 0.1636396 2.02550526\n", - " 0.16531554 1.93966786 0.18149422 1.93067263 0.17037443 1.89633166\n", - " 0.20090173 1.85772838 0.16783433 1.81563535 0.18345627 1.78201576\n", - " 0.17854143 1.78583507 0.20623848 1.75434217 0.19439997 1.72897825\n", - " 0.25016309 1.70101999 0.23298284 1.66879113 0.29306048 1.64699644\n", - " 0.29534854 1.62829271 0.43589966 1.59613402 0.3103042 1.55543414\n", - " 0.52910104 1.56095692]\n", - "P_ = [0.06450197 2.1267366 0.10274162 2.00927581 0.15745291 2.02310999\n", - " 0.16505092 1.95322113 0.17808818 1.93256636 0.17330069 1.90536876\n", - " 0.19126153 1.86991889 0.18001706 1.83114331 0.17687861 1.79617138\n", - " 0.18086952 1.78402592 0.19166109 1.77091738 0.20125384 1.74366263\n", - " 0.21494428 1.71867784 0.24473775 1.69084246 0.24879275 1.66305568\n", - " 0.29354218 1.64305881 0.31754082 1.62321502 0.42267909 1.59184983\n", - " 0.32181982 1.55572482 0.52910104 1.56095692]\n", - "Depth = 20, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.411078\n", - " Iterations: 353\n", - " Function evaluations: 557\n", - "P = [0.06211786 2.10957669 0.10433153 2.00691785 0.15650213 2.02137398\n", - " 0.16644356 1.94974141 0.17751412 1.92961249 0.17537105 1.90047808\n", - " 0.19097451 1.88144462 0.18231323 1.82695478 0.17857293 1.80154872\n", - " 0.18095038 1.78911013 0.19447364 1.76123081 0.20337537 1.7533056\n", - " 0.21861755 1.71123854 0.24389611 1.70244518 0.25066929 1.65637394\n", - " 0.29496776 1.64975369 0.32093424 1.61330359 0.4208166 1.58289132\n", - " 0.32045717 1.55476515 0.52864798 1.56841822]\n", - "P_ = [0.06211786 2.10957669 0.10222085 2.01205079 0.15128507 2.01992837\n", - " 0.16495234 1.9604863 0.17530001 1.93363827 0.17590682 1.90776168\n", - " 0.18629347 1.88715466 0.18534468 1.84602622 0.18006905 1.81171114\n", - " 0.17988053 1.7947075 0.18771201 1.77517047 0.19847942 1.75766447\n", - " 0.20947224 1.73647878 0.22746505 1.70816087 0.24592806 1.68862381\n", - " 0.26174391 1.65471888 0.30016105 1.64246367 0.3359166 1.60874175\n", - " 0.41078065 1.58007871 0.33086671 1.5554478 0.52864798 1.56841822]\n", - "Depth = 21, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.409050\n", - " Iterations: 257\n", - " Function evaluations: 429\n", - "P = [0.06172436 2.11534039 0.10183164 2.00778222 0.15232103 2.02268604\n", - " 0.16508795 1.9659686 0.17583921 1.93218571 0.17651331 1.90539073\n", - " 0.18682229 1.89220609 0.18593737 1.84983111 0.18302223 1.81309113\n", - " 0.18102885 1.79217668 0.18835377 1.77511219 0.19838211 1.76032728\n", - " 0.21302911 1.73370265 0.22781745 1.71314766 0.24428456 1.68603366\n", - " 0.26286573 1.65681128 0.29778878 1.6350286 0.33482145 1.6050132\n", - " 0.4068598 1.5720928 0.33163552 1.56230087 0.53222391 1.5629755 ]\n", - "P_ = [0.06172436 2.11534039 0.09992177 2.01290404 0.14751251 2.02126663\n", - " 0.1632641 1.97407109 0.17379135 1.93862055 0.17635281 1.91177049\n", - " 0.18387687 1.89597313 0.18623234 1.8639561 0.18413276 1.82708731\n", - " 0.18188316 1.80114002 0.18486571 1.78323814 0.19312917 1.76807176\n", - " 0.2046594 1.74891673 0.21866276 1.72587218 0.23330649 1.70410966\n", - " 0.24959347 1.67768441 0.27118074 1.65162493 0.30484262 1.62931138\n", - " 0.34511265 1.60031029 0.39969559 1.57116024 0.34118735 1.562333\n", - " 0.53222391 1.5629755 ]\n", - "Depth = 22, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.409961\n", - " Iterations: 412\n", - " Function evaluations: 617\n", - "P = [0.05964525 2.11812166 0.09976953 2.00340691 0.1478399 2.03042918\n", - " 0.16411549 1.97285291 0.17323997 1.94483111 0.17762334 1.90731832\n", - " 0.18128999 1.89862744 0.18684114 1.87172904 0.18716432 1.82899082\n", - " 0.18569793 1.80482508 0.18437079 1.77819908 0.19580857 1.77309544\n", - " 0.20925645 1.74914862 0.22228314 1.72547246 0.23314822 1.70228576\n", - " 0.25061556 1.67167901 0.26909876 1.6502887 0.30542833 1.62729319\n", - " 0.34016651 1.58800215 0.40190306 1.57384417 0.34252567 1.57092458\n", - " 0.53057486 1.57136379]\n", - "P_ = [0.05964525 2.11812166 0.0979457 2.00862122 0.14346987 2.02797261\n", - " 0.16189609 1.98070422 0.17158098 1.94992598 0.17662712 1.91584395\n", - " 0.18029 1.90099768 0.18507487 1.88028762 0.1870468 1.84453199\n", - " 0.18629782 1.81471107 0.18497404 1.79030181 0.19008968 1.77564726\n", - " 0.20192124 1.76221053 0.21458555 1.73946292 0.22623408 1.71704093\n", - " 0.23870601 1.69254725 0.25565643 1.66584529 0.27735548 1.64506245\n", - " 0.31174436 1.62014937 0.34858513 1.58607152 0.39650512 1.57357876\n", - " 0.35107336 1.57094454 0.53057486 1.57136379]\n", - "Depth = 23, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.407856\n", - " Iterations: 343\n", - " Function evaluations: 541\n", - "P = [0.0591731 2.1174483 0.09737152 2.00450785 0.1436816 2.0338643\n", - " 0.16067625 1.97741156 0.1720807 1.95238781 0.17634001 1.91631411\n", - " 0.1806909 1.9043035 0.18392216 1.880249 0.18902625 1.84658389\n", - " 0.18792776 1.81739915 0.18711328 1.78908131 0.19042736 1.77803552\n", - " 0.20376645 1.76145942 0.21681797 1.74181009 0.22637138 1.71618484\n", - " 0.23989094 1.69029912 0.25705223 1.6647807 0.27509356 1.64342041\n", - " 0.30771467 1.61562599 0.3495186 1.58830864 0.4023536 1.5775539\n", - " 0.35193504 1.56787172 0.53210941 1.5692542 ]\n", - "P_ = [0.0591731 2.1174483 0.09571072 2.0094183 0.13965464 2.03131156\n", - " 0.15845955 1.98477496 0.17009732 1.95673976 0.17541407 1.92415622\n", - " 0.17955589 1.9074367 0.18293873 1.88756994 0.18725091 1.8582935\n", - " 0.1883576 1.82881927 0.1874674 1.80139342 0.18884237 1.78331829\n", - " 0.19680692 1.77010782 0.20944102 1.75291623 0.22055626 1.73178282\n", - " 0.23107383 1.70718111 0.24511394 1.68253265 0.26175866 1.65920845\n", - " 0.28218511 1.63737815 0.31498492 1.61087515 0.35641013 1.58690585\n", - " 0.39796938 1.57671197 0.35976871 1.56793182 0.53210941 1.5692542 ]\n", - "Depth = 24, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.408410\n", - " Iterations: 390\n", - " Function evaluations: 622\n", - "P = [0.05810291 2.12128314 0.09619649 2.00236577 0.13958296 2.03669165\n", - " 0.15785738 1.98255459 0.16930261 1.96167336 0.17613882 1.92665774\n", - " 0.17894024 1.91011778 0.18254214 1.88702157 0.18704339 1.85881567\n", - " 0.19068607 1.83095964 0.18951193 1.80087354 0.18930969 1.78717001\n", - " 0.19885898 1.76845045 0.21079378 1.75603555 0.21936021 1.73146757\n", - " 0.23358626 1.70432235 0.24654608 1.68371613 0.26221214 1.65663618\n", - " 0.28201914 1.63468072 0.31645629 1.60760969 0.35871735 1.59162405\n", - " 0.39788017 1.5740002 0.36114434 1.57437068 0.53149173 1.57167896]\n", - "P_ = [0.05810291 2.12128314 0.09460926 2.00732066 0.13596742 2.03383116\n", - " 0.15557307 1.98932172 0.16739507 1.96515357 0.17471461 1.93395266\n", - " 0.17823988 1.91425277 0.18149158 1.89375796 0.18554297 1.86821763\n", - " 0.18932007 1.84140565 0.19000116 1.81340942 0.18940238 1.7934508\n", - " 0.19408434 1.77781023 0.2043291 1.76276028 0.21436313 1.74579889\n", - " 0.22469498 1.72128812 0.2379062 1.69745361 0.25111535 1.67581781\n", - " 0.26716389 1.65114732 0.28919355 1.62904092 0.3234998 1.60494542\n", - " 0.3636127 1.58942107 0.39481885 1.57403107 0.36824215 1.57425853\n", - " 0.53149173 1.57167896]\n", - "Depth = 25, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.409134\n", - " Iterations: 279\n", - " Function evaluations: 487\n", - "P = [0.05748032 2.12255181 0.0948721 2.00797039 0.13631763 2.03574082\n", - " 0.1539989 1.98884927 0.16775233 1.96780049 0.1753486 1.93660788\n", - " 0.1787915 1.9171505 0.18153964 1.89251336 0.18636594 1.86879791\n", - " 0.19010512 1.84260818 0.19140547 1.81519032 0.19027063 1.79576961\n", - " 0.19563956 1.77673895 0.2045387 1.76637448 0.21318909 1.74410831\n", - " 0.22763731 1.71959074 0.23894216 1.69921508 0.25153324 1.67059491\n", - " 0.26672791 1.65086788 0.29149976 1.62587579 0.32390058 1.60829509\n", - " 0.36252188 1.58785598 0.39640954 1.57737059 0.36820033 1.57115367\n", - " 0.52888255 1.57292211]\n", - "P_ = [0.05748032 2.12255181 0.09337642 2.01255365 0.13300199 2.03351918\n", - " 0.15187715 1.99447626 0.16555178 1.9711683 0.17382934 1.9428464\n", - " 0.1779652 1.92182027 0.18077016 1.89941176 0.18482153 1.87638685\n", - " 0.18875902 1.85203648 0.19088533 1.82615747 0.19076996 1.80431472\n", - " 0.19306248 1.78587366 0.19991115 1.771764 0.20834487 1.75657736\n", - " 0.21896837 1.73430128 0.23170705 1.7122555 0.2429713 1.69005663\n", - " 0.25578775 1.66507134 0.27267316 1.64486978 0.29797993 1.62235965\n", - " 0.33007999 1.60502484 0.3665884 1.58659773 0.3941528 1.57687324\n", - " 0.37462762 1.57122441 0.52888255 1.57292211]\n", - "Depth = 26, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.406555\n", - " Iterations: 553\n", - " Function evaluations: 813\n", - "P = [0.05639983 2.13292779 0.0944144 2.01288083 0.13367109 2.0426977\n", - " 0.1498131 1.99315819 0.16207952 1.9742589 0.17471761 1.94943719\n", - " 0.17815477 1.92920365 0.18161153 1.90190634 0.18278601 1.87488092\n", - " 0.19007918 1.85472364 0.1925708 1.82934608 0.1944873 1.80989572\n", - " 0.19664565 1.78822158 0.20083451 1.77661697 0.20665981 1.75265696\n", - " 0.22411998 1.73243657 0.2366719 1.71720885 0.24497013 1.68788483\n", - " 0.25577556 1.66598278 0.26922934 1.64082576 0.29881508 1.62381756\n", - " 0.33059015 1.59847844 0.36707554 1.58538826 0.39031738 1.57148813\n", - " 0.37126942 1.57377059 0.52753071 1.57504995]\n", - "P_ = [0.05639983 2.13292779 0.0929523 2.01749802 0.13065134 2.04040409\n", - " 0.14795056 1.99887429 0.16019238 1.97716648 0.17228721 1.95421059\n", - " 0.17736158 1.93387293 0.18068087 1.90925561 0.18242463 1.88319643\n", - " 0.18755462 1.86170116 0.19161248 1.83910668 0.19367647 1.81812472\n", - " 0.19564949 1.79822503 0.19874008 1.78241928 0.20352311 1.7655585\n", - " 0.2140468 1.74410218 0.22894764 1.72657975 0.23954436 1.70705823\n", - " 0.24829488 1.68114574 0.25939773 1.65920974 0.27605682 1.63690079\n", - " 0.30492567 1.61894465 0.33620329 1.59646456 0.36975729 1.5837844\n", - " 0.38885215 1.57166371 0.37727947 1.57381979 0.52753071 1.57504995]\n", - "Depth = 27, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.411445\n", - " Iterations: 356\n", - " Function evaluations: 591\n", - "P = [0.05606591 2.12830711 0.09319642 2.01892665 0.13134888 2.04628101\n", - " 0.14699036 1.99599392 0.15970722 1.98009019 0.1717439 1.9557829\n", - " 0.17814336 1.93791779 0.18066044 1.90790496 0.18597498 1.88387754\n", - " 0.18731933 1.86297764 0.19252099 1.83981843 0.1942746 1.82095747\n", - " 0.19706587 1.79906532 0.19894629 1.78372922 0.20324966 1.76263515\n", - " 0.2153285 1.74326645 0.22967476 1.72899859 0.24022029 1.70400603\n", - " 0.24998165 1.68121328 0.26120906 1.65801189 0.27475562 1.63744002\n", - " 0.30478204 1.61525051 0.33658866 1.5964944 0.36785448 1.58290903\n", - " 0.38894843 1.57420192 0.37616356 1.57340819 0.5291195 1.57615203]\n", - "P_ = [0.05606591 2.12830711 0.09182121 2.02297777 0.12852277 2.04425476\n", - " 0.14525242 2.00158137 0.15782324 1.9824463 0.16951489 1.96028425\n", - " 0.17672126 1.94188781 0.18000786 1.91568607 0.1844003 1.89099678\n", - " 0.18687121 1.86994427 0.19059445 1.84839592 0.19356017 1.82864156\n", - " 0.19582531 1.80879516 0.1980409 1.79111327 0.20101828 1.77357282\n", - " 0.20861803 1.75402684 0.22117327 1.73745362 0.23358051 1.71974208\n", - " 0.24347408 1.69640845 0.25330829 1.67433879 0.26472113 1.65267844\n", - " 0.28142816 1.63250902 0.31067216 1.61177716 0.34122063 1.59448175\n", - " 0.37019825 1.58194157 0.3880014 1.57414312 0.38182859 1.57350982\n", - " 0.5291195 1.57615203]\n", - "Depth = 28, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.407403\n", - " Iterations: 558\n", - " Function evaluations: 826\n", - "P = [0.05471624 2.12821895 0.09168325 2.02555305 0.12937579 2.05325192\n", - " 0.14572372 1.99805139 0.15610087 1.98336568 0.16879328 1.965433\n", - " 0.17687685 1.9478009 0.18192681 1.91864049 0.18596361 1.89148721\n", - " 0.1883279 1.87206483 0.18974934 1.85321233 0.19647548 1.83356065\n", - " 0.19910742 1.81449377 0.19977416 1.78894637 0.19932037 1.76681096\n", - " 0.21050787 1.75294552 0.22146623 1.74287491 0.23712213 1.71815936\n", - " 0.24574813 1.69701976 0.25558039 1.6727781 0.26313098 1.65396285\n", - " 0.27780523 1.629424 0.30961251 1.60636972 0.34019076 1.59488119\n", - " 0.36936618 1.58269032 0.38703287 1.5739688 0.38339413 1.57100432\n", - " 0.52863672 1.57534621]\n", - "P_ = [0.05471624 2.12821895 0.090363 2.02921969 0.12668346 2.05127343\n", - " 0.14397215 2.00396573 0.15461842 1.98546363 0.16652678 1.96863526\n", - " 0.17514465 1.95157921 0.18066432 1.92593059 0.18481024 1.89924529\n", - " 0.18756795 1.87830774 0.18924169 1.85994537 0.19383307 1.84128095\n", - " 0.19797945 1.82266529 0.1994646 1.80080766 0.19954726 1.77787866\n", - " 0.20451456 1.76037344 0.21520431 1.74862955 0.22761676 1.73316523\n", - " 0.24020285 1.7106095 0.2489085 1.6892278 0.2577377 1.66740232\n", - " 0.26679954 1.64782814 0.28462107 1.62448379 0.31507291 1.6043182\n", - " 0.34435868 1.59313964 0.37125904 1.58175587 0.38677296 1.57375705\n", - " 0.38858136 1.57115939 0.52863672 1.57534621]\n", - "Depth = 29, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.411102\n", - " Iterations: 381\n", - " Function evaluations: 632\n", - "P = [0.05418239 2.12740048 0.0898696 2.02739659 0.12734085 2.05673228\n", - " 0.14360854 2.006788 0.15453927 1.98730086 0.16562921 1.96821122\n", - " 0.17546422 1.95384947 0.18059811 1.92653771 0.1875736 1.90096422\n", - " 0.18774952 1.87908504 0.18953648 1.86006037 0.19361414 1.84493584\n", - " 0.1998491 1.82463614 0.20044786 1.80314351 0.20016417 1.7756763\n", - " 0.20444502 1.75970826 0.21449984 1.75175079 0.22797495 1.73109849\n", - " 0.24150177 1.7108103 0.25092283 1.68814605 0.25669388 1.66986794\n", - " 0.26679764 1.64411776 0.28445405 1.62225429 0.31495167 1.60776902\n", - " 0.34514242 1.59043227 0.37211205 1.58413428 0.38839578 1.57161964\n", - " 0.39111933 1.57095888 0.53098114 1.57326441]\n", - "P_ = [0.05418239 2.12740048 0.08863901 2.030845 0.12475663 2.05470913\n", - " 0.14192567 2.01195465 0.15303158 1.98998874 0.16371715 1.97150253\n", - " 0.17342939 1.95682087 0.17935889 1.9331302 0.18564933 1.90801898\n", - " 0.18769492 1.88587513 0.18892029 1.8666206 0.19206744 1.85067273\n", - " 0.19726912 1.83303602 0.20017945 1.81277814 0.20030112 1.78893634\n", - " 0.20223078 1.76796759 0.20895235 1.75614112 0.22007575 1.74320501\n", - " 0.23310581 1.72340297 0.24475041 1.70299504 0.25271384 1.68247354\n", - " 0.25948112 1.66276444 0.27105953 1.63884037 0.2907639 1.61925734\n", - " 0.32015697 1.60477993 0.34886237 1.58956358 0.37379658 1.58283967\n", - " 0.38858361 1.57157407 0.39594215 1.57103838 0.53098114 1.57326441]\n", - "Depth = 30, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.407778\n", - " Iterations: 422\n", - " Function evaluations: 685\n", - "2.0 [7.13953473 5.04950729 3.61376134 2.92865995 2.66935007 2.55512103\n", - " 2.53067433 2.54007585 2.54968636 2.55057487 2.44061882 2.46835678\n", - " 2.436269 2.44996818 2.4181315 2.42503395 2.41008275 2.4216235\n", - " 2.39686031 2.41107789 2.4090499 2.40996057 2.40785622 2.40840954\n", - " 2.40913425 2.40655473 2.41144462 2.40740341 2.41110229 2.40777813]\n", - "[[6.57155339 5.94790512 4.51084725 5.48476219 4.44827696 4.07086367\n", - " 4.45993119 3.76473244 3.75245393 3.70383406 2.54453644 2.75335922\n", - " 3.72365101 2.64914745 3.66152866 3.41308183 2.17660478 2.18383796\n", - " 2.54980097 1.72430929 2.24071873 1.8353618 2.04963403 1.97768311\n", - " 2.25839296 2.22977067 1.94603139 2.05226045 2.69504832 3.27724127]\n", - " [7.58106801 6.81608452 4.28714233 4.07123972 3.27046962 3.23940109\n", - " 3.69518164 3.2411352 2.8435791 2.91039551 2.52147765 2.7118309\n", - " 2.7196728 2.5657514 2.49654928 2.14986169 2.03773181 1.96011255\n", - " 1.99818881 1.99560667 2.10966328 1.86491841 1.83579189 1.98703992\n", - " 1.98133515 1.95306622 1.90928783 1.85507609 1.79545032 1.7963689 ]\n", - " [5.67675131 4.71392584 4.01740509 3.36995594 3.02811997 2.75900701\n", - " 2.07994453 1.87160639 1.76736629 1.60399896 1.51494314 1.48018664\n", - " 1.42851074 1.41006842 1.37578808 1.29188206 1.25021059 1.25293931\n", - " 1.22202663 1.23016691 1.26143882 1.20441019 1.17776388 1.18431374\n", - " 1.16553331 1.16956844 1.16569465 1.17659931 1.16990127 1.15831922]\n", - " [5.00995896 4.29025145 4.60820671 3.83390873 3.89848291 5.33118031\n", - " 3.55893822 3.40156727 4.09051018 4.16531197 3.86869824 2.74039918\n", - " 2.37252786 2.09790193 2.46381788 3.23389141 2.92683369 2.26271526\n", - " 2.22500107 1.72792525 1.99341501 2.13517458 2.55949815 2.08833212\n", - " 2.30394139 2.47254611 2.09431819 2.0108552 2.25457883 1.56109974]\n", - " [4.00096445 3.74521392 2.59257503 2.56365739 1.9185404 1.87747501\n", - " 1.74225195 1.62820595 1.46249835 1.3728014 1.35944481 1.35683453\n", - " 1.33094362 1.31878632 1.32159957 1.30276576 1.25442761 1.25346875\n", - " 1.23969275 1.23278308 1.2266854 1.22191909 1.20703107 1.20899474\n", - " 1.20219427 1.20085781 1.20009343 1.19826693 1.1915774 1.19065828]\n", - " [5.90892769 4.83252908 3.71479956 3.36110121 2.94173277 2.24786958\n", - " 2.12439453 2.02822257 1.99458002 1.79405078 1.71446451 1.68436207\n", - " 1.64831949 1.60645585 1.57877549 1.55946868 1.50646832 1.48490593\n", - " 1.46944309 1.45423724 1.43322495 1.41715875 1.39899314 1.36097986\n", - " 1.33935151 1.32162911 1.30734052 1.2947269 1.27768564 1.26760576]\n", - " [5.07730592 3.19397021 2.56921505 2.2196952 1.87944827 1.7817944\n", - " 1.79674014 1.74393688 1.72491634 1.70478017 1.70372389 1.71403689\n", - " 1.71964722 1.71701915 1.65427385 1.66354751 1.65446129 1.64731001\n", - " 1.64582841 1.63908351 1.60606623 1.61407892 1.61749603 1.58823071\n", - " 1.60544517 1.59941945 1.61244841 1.60748773 1.61573555 1.61325776]\n", - " [6.09370005 4.58327549 2.77056736 2.4009721 2.16465466 1.90248461\n", - " 1.85814571 1.86203274 1.82759854 1.84492164 1.83096494 1.84786217\n", - " 1.84800744 1.84266075 1.84515694 1.85168419 1.86013029 1.8591394\n", - " 1.79934195 1.88437739 1.82798148 1.86223998 1.83513759 1.84794419\n", - " 1.84251045 1.85218276 1.85216684 1.85206644 1.85538944 1.84797453]\n", - " [3.56976737 2.52475365 1.80688067 1.46432998 1.33467503 1.27756052\n", - " 1.26533716 1.27003792 1.27484318 1.27528744 1.22030941 1.23417839\n", - " 1.2181345 1.22498409 1.20906575 1.21251697 1.20504138 1.21081175\n", - " 1.19843016 1.20553894 1.20452495 1.20498028 1.20392811 1.20420477\n", - " 1.20456712 1.20327737 1.20572231 1.20370171 1.20555114 1.20388906]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]] [4.94899972 4.06479093 3.08776391 2.87696225 2.48844006 2.44876362\n", - " 2.25808651 2.08114774 2.07383459 2.03753819 1.8278563 1.752305\n", - " 1.80094147 1.64327754 1.76065555 1.76787001 1.58719098 1.51152409\n", - " 1.53477538 1.40940283 1.49037188 1.4360242 1.48852739 1.44477232\n", - " 1.49032713 1.50023179 1.42931036 1.42510408 1.50609179 1.49164145]\n", - "[[0.1749857 0.07463194 0.26530491 0.16394175 0.18892849 0.25701077\n", - " 0.24542951 0.40504394 0.18547862 0.24113788 0.62032714 0.68408453\n", - " 0.11521194 0.57930818 0.29653581 0.32221821 0.75779012 0.76858176\n", - " 0.59269399 0.8271978 0.69201592 0.87101232 0.79114835 0.72852071\n", - " 0.64433266 0.66377712 0.77675308 0.72982301 0.58648573 0.44154865]\n", - " [0.17669094 0.20818569 0.40598211 0.40456531 0.54848127 0.5337594\n", - " 0.48446167 0.53759304 0.60295388 0.58451793 0.64895146 0.66165701\n", - " 0.62972457 0.66201878 0.67281148 0.75627098 0.78514972 0.80366385\n", - " 0.79430362 0.79961314 0.7524382 0.82370466 0.83214203 0.78138294\n", - " 0.78255631 0.78124579 0.80687807 0.80774629 0.84561002 0.84356134]\n", - " [0.1977358 0.23204622 0.30938238 0.39342279 0.41016143 0.46245125\n", - " 0.76102816 0.79966194 0.84980142 0.9167973 0.93013476 0.94105633\n", - " 0.96019643 0.9567664 0.95781341 0.97258171 0.97672161 0.97483651\n", - " 0.98345276 0.97827363 0.97171746 0.98525476 0.99020549 0.988242\n", - " 0.99105685 0.98789452 0.98718377 0.98332188 0.98342322 0.98330761]\n", - " [0.05772911 0.21353746 0.01841155 0.31450455 0.21424321 0.05404723\n", - " 0.43161435 0.34272799 0.28819124 0.28689022 0.1868918 0.50636735\n", - " 0.71458126 0.77159991 0.58971876 0.39292553 0.46431953 0.6325678\n", - " 0.69978407 0.80479284 0.72769493 0.74105124 0.53269212 0.73999712\n", - " 0.61502723 0.52602161 0.71815241 0.71745393 0.53403795 0.82706806]\n", - " [0.12450898 0.13546046 0.33397169 0.30579603 0.53279986 0.54005574\n", - " 0.5789386 0.62157361 0.67239022 0.70608977 0.71741324 0.71989795\n", - " 0.72816408 0.73770709 0.7462425 0.75395046 0.77610427 0.778063\n", - " 0.78739546 0.80304068 0.8044153 0.81655327 0.83574318 0.83983299\n", - " 0.85295023 0.85822598 0.86248183 0.86742561 0.8687046 0.87578262]\n", - " [0.15384579 0.23299282 0.34316369 0.40381029 0.48323069 0.60966505\n", - " 0.65090211 0.6781041 0.69468559 0.73757271 0.76352272 0.78064924\n", - " 0.80250928 0.8256876 0.84161068 0.85173433 0.88960447 0.89427145\n", - " 0.89713168 0.89784489 0.90396968 0.90972365 0.91944211 0.93551855\n", - " 0.93997379 0.94289646 0.9440385 0.94476954 0.94821036 0.94920811]\n", - " [0.22662278 0.49591192 0.64928992 0.72253971 0.88505646 0.91736256\n", - " 0.93108311 0.94041937 0.96629845 0.97837675 0.97999527 0.98011569\n", - " 0.97939879 0.97927928 0.98252313 0.98523181 0.98698179 0.98795262\n", - " 0.98839303 0.98858465 0.9918529 0.99290353 0.99289167 0.99426743\n", - " 0.9945867 0.99461399 0.99442154 0.99355126 0.99301575 0.99210625]\n", - " [0.1997449 0.39406338 0.8125561 0.89215215 0.93988072 0.97583839\n", - " 0.98050285 0.98626726 0.98996115 0.99116577 0.99318232 0.99328416\n", - " 0.99223222 0.99419442 0.9931634 0.99226818 0.99206014 0.99172956\n", - " 0.99264689 0.98944046 0.9912926 0.99247498 0.99365946 0.99432346\n", - " 0.99379021 0.99295831 0.9931038 0.99245639 0.99277207 0.99313253]\n", - " [0.26415019 0.58986982 0.84151077 0.92289843 0.95683247 0.97222603\n", - " 0.97482575 0.9763395 0.97674997 0.97931421 0.99098921 0.98701103\n", - " 0.99265455 0.99212748 0.997278 0.99588027 0.99858407 0.9965231\n", - " 0.99929919 0.99908139 0.99837773 0.99891483 0.99899648 0.99913097\n", - " 0.99908424 0.99921098 0.99889051 0.9990329 0.9989961 0.9989517 ]\n", - " [0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0.\n", - " 0. 0. 0. 0. 0. 0. ]] [0.15760142 0.25766997 0.39795731 0.4523631 0.51596146 0.53224164\n", - " 0.60387861 0.62877308 0.62265105 0.64218625 0.68314079 0.72541233\n", - " 0.69146731 0.74986892 0.70776972 0.70230615 0.76273157 0.78281897\n", - " 0.77351007 0.80878695 0.78337747 0.81315932 0.78869209 0.80012162\n", - " 0.78133582 0.77468448 0.80819035 0.80355808 0.77512558 0.79046669]\n", - "\n", - "Now using 4 solutions, set number 4\n", - "Calculating energy landscape ...\n", - "Optimization terminated successfully.\n", - " Current function value: 6.896662\n", - " Iterations: 27\n", - " Function evaluations: 53\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 6.896662\n", - " Iterations: 6\n", - " Function evaluations: 13\n", - "P = [0.16448156 1.96498578]\n", - "P_ = [0.16448156 1.96498578 0.16448156 1.96498578]\n", - "Depth = 2, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 4.948376\n", - " Iterations: 45\n", - " Function evaluations: 78\n", - "P = [0.12244468 2.03955118 0.23410048 1.81957601]\n", - "P_ = [0.12244468 2.03955118 0.17827258 1.92956359 0.23410048 1.81957601]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 4.083124\n", - " Iterations: 58\n", - " Function evaluations: 97\n", - "P = [0.10359111 2.09411402 0.20805619 1.87218864 0.23714403 1.74176503]\n", - "P_ = [0.10359111 2.09411402 0.1732345 1.94616377 0.21775213 1.8287141\n", - " 0.23714403 1.74176503]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.521546\n", - " Iterations: 45\n", - " Function evaluations: 78\n", - "P = [0.0936458 2.08516868 0.18080823 1.93503096 0.22402082 1.79800055\n", - " 0.25891739 1.70972759]\n", - "P_ = [0.0936458 2.08516868 0.15901763 1.97256539 0.20241453 1.86651575\n", - " 0.23274496 1.77593231 0.25891739 1.70972759]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.286317\n", - " Iterations: 86\n", - " Function evaluations: 137\n", - "P = [0.08118684 2.09895904 0.16452419 1.94015778 0.20990142 1.87369581\n", - " 0.25105804 1.75486062 0.26597277 1.67256165]\n", - "P_ = [0.08118684 2.09895904 0.14785672 1.97191803 0.19175053 1.9002806\n", - " 0.22636407 1.82616173 0.25404099 1.73840082 0.26597277 1.67256165]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 3.045796\n", - " Iterations: 83\n", - " Function evaluations: 136\n", - "P = [0.08023159 2.13146771 0.15377694 1.94301911 0.17627148 1.86716756\n", - " 0.23912835 1.81958709 0.26172224 1.71483423 0.28025643 1.66265833]\n", - "P_ = [0.08023159 2.13146771 0.14151938 1.97442721 0.1687733 1.89245141\n", - " 0.20769991 1.84337732 0.24665964 1.78466947 0.26481127 1.70613825\n", - " 0.28025643 1.66265833]\n", - "Depth = 7, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.827403\n", - " Iterations: 204\n", - " Function evaluations: 293\n", - "P = [0.07001698 2.05664984 0.1269588 1.87088495 0.17308742 1.87828622\n", - " 0.23007406 1.81227008 0.29830244 1.76603661 0.28726359 1.68207969\n", - " 0.30152453 1.67932701]\n", - "P_ = [0.07001698 2.05664984 0.11882425 1.89742279 0.15990781 1.87617157\n", - " 0.20565121 1.84056271 0.25931479 1.79245573 0.29514848 1.74204891\n", - " 0.28930087 1.68168645 0.30152453 1.67932701]\n", - "Depth = 8, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.694743\n", - " Iterations: 133\n", - " Function evaluations: 209\n", - "P = [0.06805659 2.09395245 0.12387722 1.91338551 0.15811402 1.86948192\n", - " 0.21012501 1.82573255 0.2539984 1.77886532 0.31158122 1.72987731\n", - " 0.28350132 1.68533653 0.30481508 1.65823257]\n", - "P_ = [0.06805659 2.09395245 0.11689964 1.93595638 0.14955482 1.88045782\n", - " 0.19062089 1.84213857 0.2320617 1.80229893 0.27559195 1.76049481\n", - " 0.30456124 1.71874211 0.28616554 1.68194853 0.30481508 1.65823257]\n", - "Depth = 9, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.605462\n", - " Iterations: 109\n", - " Function evaluations: 178\n", - "P = [0.06697602 2.09815002 0.11629932 1.91772829 0.151881 1.90198696\n", - " 0.19266506 1.82070974 0.23357737 1.79058775 0.27768718 1.74612308\n", - " 0.31059506 1.72436416 0.29165023 1.68307233 0.30531574 1.64952275]\n", - "P_ = [0.06697602 2.09815002 0.11081895 1.93777515 0.14397396 1.90548503\n", - " 0.17907037 1.84780215 0.21539412 1.8039753 0.25318173 1.77082568\n", - " 0.28865647 1.73887011 0.3063851 1.7151882 0.29316862 1.6793446\n", - " 0.30531574 1.64952275]\n", - "Depth = 10, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.633537\n", - " Iterations: 180\n", - " Function evaluations: 277\n", - "P = [0.06228553 2.13302734 0.11284727 1.93956367 0.14173502 1.92344037\n", - " 0.18801894 1.84908425 0.208796 1.80732118 0.26120851 1.76133141\n", - " 0.29070825 1.73763898 0.31149576 1.70285049 0.29447415 1.66517113\n", - " 0.31459009 1.61184738]\n", - "P_ = [0.06228553 2.13302734 0.1077911 1.95891004 0.13595747 1.92666503\n", - " 0.17413376 1.87139108 0.20048518 1.82402641 0.23500226 1.7843263\n", - " 0.27300841 1.75185444 0.2969445 1.72720243 0.30809144 1.69531462\n", - " 0.29648574 1.65983876 0.31459009 1.61184738]\n", - "Depth = 11, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.631327\n", - " Iterations: 110\n", - " Function evaluations: 191\n", - "P = [0.06288223 2.12388443 0.1057018 1.95468895 0.13913623 1.93578468\n", - " 0.17613078 1.87222074 0.20075566 1.83511747 0.2344485 1.77944402\n", - " 0.26888141 1.75341844 0.29863491 1.7199063 0.30253096 1.69481042\n", - " 0.29346283 1.64575975 0.32929319 1.62048867]\n", - "P_ = [0.06288223 2.12388443 0.10180911 1.97007036 0.13305724 1.93922182\n", - " 0.16604136 1.88955636 0.19180116 1.84860957 0.21913358 1.80475013\n", - " 0.25009982 1.76761421 0.27970086 1.7412322 0.29969747 1.71306197\n", - " 0.3008822 1.68589211 0.29672013 1.64346238 0.32929319 1.62048867]\n", - "Depth = 12, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.643222\n", - " Iterations: 134\n", - " Function evaluations: 224\n", - "P = [0.06062287 2.12476446 0.10407531 1.95415803 0.13291921 1.94687513\n", - " 0.16928245 1.88908844 0.1910799 1.85860042 0.2188725 1.80062579\n", - " 0.24847284 1.77379051 0.27943386 1.73479123 0.30053289 1.71607533\n", - " 0.30720187 1.67369223 0.30146483 1.64876094 0.33264282 1.61068061]\n", - "P_ = [0.06062287 2.12476446 0.10045427 1.96837523 0.1281119 1.94808895\n", - " 0.16019164 1.90353511 0.18381408 1.86876309 0.20729225 1.82478188\n", - " 0.23367267 1.78720815 0.26137327 1.75754081 0.28646687 1.7285526\n", - " 0.30220013 1.70547956 0.30624569 1.66953702 0.30406299 1.64558758\n", - " 0.33264282 1.61068061]\n", - "Depth = 13, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.445946\n", - " Iterations: 797\n", - " Function evaluations: 1051\n", - "P = [0.1150929 2.08308651 0.03683792 1.7464884 0.15864284 1.89097992\n", - " 0.080634 1.82214545 0.21191785 1.85269663 0.1678335 1.80062852\n", - " 0.25026778 1.77409195 0.28080692 1.75186886 0.32537398 1.70407798\n", - " 0.32481002 1.67821466 0.40757818 1.61961383 0.18384823 1.60949651\n", - " 0.37881619 1.52858853]\n", - "P_ = [0.1150929 2.08308651 0.04285753 1.77238057 0.13990362 1.86875045\n", - " 0.09863604 1.83803032 0.17152282 1.84329626 0.18478902 1.82065472\n", - " 0.21222119 1.7863396 0.26436277 1.76383514 0.2979481 1.73348776\n", - " 0.32520046 1.69612004 0.34391036 1.66469139 0.37315819 1.61805732\n", - " 0.19884577 1.60327282 0.37881619 1.52858853]\n", - "Depth = 14, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.793790\n", - " Iterations: 363\n", - " Function evaluations: 499\n", - "P = [0.11133165 2.06392681 0.0434983 1.69899594 0.13867966 1.87935577\n", - " 0.0967242 1.78487129 0.17950826 1.83163678 0.18722425 1.82399312\n", - " 0.21609183 1.77369018 0.27442826 1.80474315 0.31842276 1.71868638\n", - " 0.29173145 1.65817341 0.33963921 1.63033427 0.36258522 1.66150402\n", - " 0.19567172 1.59402962 0.4221959 1.58026059]\n", - "P_ = [0.11133165 2.06392681 0.04834354 1.72506244 0.12508233 1.85359008\n", - " 0.10571465 1.80511796 0.15585567 1.81827521 0.18446854 1.82672299\n", - " 0.20372001 1.79524858 0.24526004 1.78921666 0.29328305 1.76786167\n", - " 0.30889015 1.6970746 0.30541938 1.65021937 0.34455622 1.6370135\n", - " 0.33874044 1.65186482 0.21185202 1.59304612 0.4221959 1.58026059]\n", - "Depth = 15, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.509341\n", - " Iterations: 496\n", - " Function evaluations: 656\n", - "P = [0.10745533 2.04219263 0.0424948 1.75094232 0.13170192 1.85838233\n", - " 0.09917242 1.82908932 0.16692367 1.82706955 0.18785749 1.86219242\n", - " 0.23279819 1.77123249 0.25161299 1.7857541 0.30922538 1.72670702\n", - " 0.29860843 1.70062263 0.29432738 1.65707748 0.33949868 1.66952555\n", - " 0.31640041 1.58504657 0.20674052 1.55473541 0.41423551 1.56377653]\n", - "P_ = [0.10745533 2.04219263 0.0468255 1.77035901 0.11980764 1.84405699\n", - " 0.10567832 1.83494792 0.14885667 1.82760815 0.18087955 1.8504848\n", - " 0.21482191 1.80761646 0.24283275 1.77897735 0.27849877 1.7581988\n", - " 0.3049786 1.71627326 0.29718141 1.68610758 0.30637306 1.66039696\n", - " 0.33487903 1.65262975 0.30177909 1.58100508 0.22057352 1.55533815\n", - " 0.41423551 1.56377653]\n", - "Depth = 16, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.729320\n", - " Iterations: 354\n", - " Function evaluations: 497\n", - "P = [0.09251061 2.03430449 0.0469084 1.76772347 0.12021126 1.86464431\n", - " 0.10574491 1.84543185 0.15247177 1.80917218 0.18473948 1.86766175\n", - " 0.22106792 1.77772614 0.2468897 1.78690356 0.28640522 1.73427544\n", - " 0.30086079 1.72009242 0.30539618 1.65813373 0.30847935 1.6630051\n", - " 0.33767417 1.62351817 0.3079047 1.55545463 0.22012329 1.60953251\n", - " 0.42009625 1.59299665]\n", - "P_ = [0.09251061 2.03430449 0.04975854 1.78438478 0.1110484 1.8525292\n", - " 0.10845735 1.84903419 0.14079006 1.8182371 0.17465582 1.84938376\n", - " 0.20744476 1.81145199 0.23559267 1.78288844 0.26664746 1.7605895\n", - " 0.29272953 1.72807037 0.30256156 1.69685791 0.30635967 1.65965604\n", - " 0.31577805 1.65313337 0.33209239 1.61075625 0.29693202 1.56221436\n", - " 0.2326216 1.60849902 0.42009625 1.59299665]\n", - "Depth = 17, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.544776\n", - " Iterations: 549\n", - " Function evaluations: 737\n", - "P = [0.08025792 2.00750138 0.05021549 1.79543247 0.12208228 1.88224679\n", - " 0.10505223 1.8290652 0.14690646 1.81590638 0.17634965 1.84595526\n", - " 0.21575306 1.79249296 0.23986594 1.77120252 0.26614962 1.73585602\n", - " 0.29862035 1.72931719 0.31442903 1.69809009 0.30525722 1.66285921\n", - " 0.30900035 1.64662828 0.34466028 1.57993276 0.30779847 1.57871952\n", - " 0.23385726 1.59019371 0.38054371 1.60086569]\n", - "P_ = [0.08025792 2.00750138 0.05198269 1.80790711 0.11362736 1.87203334\n", - " 0.10805754 1.83845019 0.13705841 1.81900257 0.16768989 1.83711736\n", - " 0.20184597 1.81136201 0.2299371 1.77996917 0.25378083 1.75248967\n", - " 0.28142997 1.73277893 0.30512981 1.71645897 0.31119192 1.68565566\n", - " 0.30635814 1.65808541 0.31739092 1.63093521 0.33815525 1.57971866\n", - " 0.29909951 1.58006942 0.24248588 1.59082148 0.38054371 1.60086569]\n", - "Depth = 18, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.520949\n", - " Iterations: 1613\n", - " Function evaluations: 1981\n", - "P = [0.02383476 2.18613007 0.08884026 2.02696623 0.11673424 1.82809574\n", - " 0.12186587 1.76841693 0.0896825 1.75357953 0.16623584 1.77498815\n", - " 0.21954052 1.72142773 0.27310841 1.76313357 0.27792506 1.67418442\n", - " 0.24538462 1.76140726 0.24963371 1.65635329 0.31420032 1.69680752\n", - " 0.27660746 1.54794755 0.37683305 1.63646173 0.37159794 1.5745189\n", - " 0.13339703 1.6414655 0.28677277 1.61457472 0.35723159 1.64086 ]\n", - "P_ = [0.02383476 2.18613007 0.08522884 2.03580867 0.11363491 1.85019246\n", - " 0.1210106 1.7783634 0.09683436 1.75687673 0.14497102 1.76904131\n", - " 0.20177229 1.7392812 0.25227645 1.74691463 0.27578433 1.71371737\n", - " 0.26165484 1.71779584 0.24727311 1.71471661 0.27474295 1.67208549\n", - " 0.30166937 1.64718753 0.3044479 1.57253482 0.37566969 1.62269666\n", - " 0.33189779 1.58567667 0.15043878 1.63847763 0.29068715 1.61603501\n", - " 0.35723159 1.64086 ]\n", - "Depth = 19, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.560034\n", - " Iterations: 513\n", - " Function evaluations: 701\n", - "P = [0.02533317 2.17831047 0.08319517 2.03090783 0.11481421 1.89214723\n", - " 0.11862351 1.80138756 0.09757438 1.73195478 0.14415841 1.78959888\n", - " 0.20024003 1.75935596 0.24087203 1.72397318 0.27940894 1.7237565\n", - " 0.26977105 1.68424661 0.23432329 1.70229831 0.27765426 1.67441406\n", - " 0.31095934 1.61728475 0.30676075 1.58523379 0.38322087 1.60839146\n", - " 0.33418147 1.59187227 0.15266858 1.6163199 0.29801393 1.62662923\n", - " 0.34496797 1.6097549 ]\n", - "P_ = [0.02533317 2.17831047 0.08014981 2.03866587 0.11148589 1.90675361\n", - " 0.11802204 1.81571803 0.10200578 1.74657221 0.13189946 1.77442938\n", - " 0.18253005 1.76890636 0.22590235 1.73700894 0.26318287 1.72384773\n", - " 0.27433637 1.70296182 0.25298001 1.69279742 0.25256791 1.69055757\n", - " 0.28992455 1.65336642 0.30963347 1.60716339 0.32688184 1.59132791\n", - " 0.37289679 1.60491373 0.30552154 1.59573242 0.16796809 1.61740509\n", - " 0.3004852 1.62574111 0.34496797 1.6097549 ]\n", - "Depth = 20, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.330850\n", - " Iterations: 3526\n", - " Function evaluations: 4225\n", - "P = [0.03010726 2.89384754 0.11149035 2.2224592 0.02022304 1.70575893\n", - " 0.1679019 1.7534193 0.01375491 1.98666522 0.21530249 1.83277769\n", - " 0.15290575 1.86426131 0.22194855 1.75158986 0.26384301 1.7184503\n", - " 0.31280908 1.71637157 0.25772085 1.58749423 0.17201884 1.77319342\n", - " 0.26266377 1.57249697 0.2951899 1.69661159 0.32276243 1.45147509\n", - " 0.24544816 1.55239549 0.33835402 1.55514372 0.22489564 1.63631047\n", - " 0.43782797 1.60152443 0.38672197 1.62822503]\n", - "P_ = [0.03010726 2.89384754 0.1074212 2.25602862 0.02934978 1.75742896\n", - " 0.14575007 1.74627025 0.04458431 1.94001604 0.1649156 1.87124957\n", - " 0.17162477 1.85481622 0.19778357 1.79102487 0.24708523 1.73170612\n", - " 0.29077435 1.717307 0.28526497 1.6519329 0.21915495 1.67105887\n", - " 0.20827681 1.69291484 0.27404792 1.61593708 0.30346166 1.62307064\n", - " 0.30343387 1.47670519 0.26402934 1.55294514 0.32133526 1.56731874\n", - " 0.24618887 1.63283187 0.43527267 1.60285946 0.38672197 1.62822503]\n", - "Depth = 21, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.512860\n", - " Iterations: 4571\n", - " Function evaluations: 5412\n", - "P = [ 0.02225252 2.32281977 -0.01227846 2.16843575 0.03278802 2.37548619\n", - " 0.01460117 1.77939817 0.10965016 2.12009375 0.09712081 1.78289024\n", - " 0.15181607 1.92952765 0.27018554 1.71215981 0.17106321 1.62751104\n", - " 0.18971698 1.61834118 0.36491125 1.55760161 0.23165271 1.67642833\n", - " 0.27088695 1.57127281 0.24699719 1.57113915 0.25793771 1.34252105\n", - " 0.27826441 1.45926263 0.31031703 1.47035163 0.20458963 1.5511667\n", - " 0.28021737 1.52730482 0.45045251 1.57055656 0.66397836 1.591013 ]\n", - "P_ = [ 0.02225252 2.32281977 -0.01063413 2.17578737 0.02849598 2.3557671\n", - " 0.01719929 1.8645536 0.09154559 2.05519935 0.10010399 1.86317679\n", - " 0.13618886 1.88763125 0.23072905 1.78461575 0.2088241 1.65975819\n", - " 0.1817225 1.62227112 0.28148541 1.58652521 0.3014548 1.61418576\n", - " 0.24846738 1.63136168 0.26178609 1.57122189 0.25064403 1.49493312\n", - " 0.26374534 1.37587579 0.28589599 1.46190287 0.29017848 1.48574498\n", - " 0.21539359 1.54775786 0.29643024 1.53142404 0.4606204 1.57153068\n", - " 0.66397836 1.591013 ]\n", - "Depth = 22, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.491365\n", - " Iterations: 2659\n", - " Function evaluations: 3214\n", - "P = [ 0.02472556 2.04730074 -0.01228316 1.95681381 0.03024948 2.65110162\n", - " 0.01846168 2.08259495 0.05369504 2.05799063 0.1065143 1.78653705\n", - " 0.10702088 1.8492563 0.21757644 1.78237478 0.22770573 1.66277392\n", - " 0.22498567 1.64176745 0.27622273 1.57731431 0.26048032 1.63656848\n", - " 0.27388059 1.58164577 0.23466253 1.54266612 0.27010954 1.42573966\n", - " 0.30891509 1.42635045 0.26989489 1.48873588 0.28484769 1.49858372\n", - " 0.20061635 1.5292008 0.31759546 1.51987908 0.52289282 1.59027828\n", - " 0.67046837 1.54748556]\n", - "P_ = [ 0.02472556 2.04730074 -0.01060095 1.96092686 0.02638288 2.58798455\n", - " 0.02006911 2.16011859 0.04728897 2.06246414 0.09450992 1.84823104\n", - " 0.10688272 1.83215105 0.18239967 1.80365526 0.22402235 1.70626514\n", - " 0.22609842 1.650361 0.25293316 1.60661119 0.26835152 1.60694139\n", - " 0.26657135 1.61160361 0.25783684 1.56569955 0.24755235 1.5001474\n", - " 0.28245676 1.425934 0.29827322 1.44336465 0.27329325 1.49097402\n", - " 0.2695329 1.50415047 0.21656805 1.52792966 0.33625885 1.52627901\n", - " 0.5296008 1.58833315 0.67046837 1.54748556]\n", - "Depth = 23, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.404610\n", - " Iterations: 5043\n", - " Function evaluations: 5911\n", - "P = [ 0.0345044 2.05826197 -0.01055278 1.89917442 0.03650919 2.80731687\n", - " 0.04776519 3.55373233 0.06487553 1.85791863 0.05078939 1.82517965\n", - " 0.15108832 1.86810805 0.12004837 1.74149994 0.1703751 1.68328575\n", - " 0.25760011 1.65273114 0.27552961 1.59957367 0.23750421 1.587918\n", - " 0.32519134 1.69022791 0.20121679 1.63417688 0.21892556 1.53699013\n", - " 0.35063122 1.34057832 0.25521769 1.46701331 0.31017411 1.47075229\n", - " 0.30330353 1.54292912 0.16395429 1.58506339 0.29766571 1.58502592\n", - " 0.48954743 1.51616782 0.51595187 1.60585803]\n", - "P_ = [ 0.0345044 2.05826197 -0.00859377 1.90609127 0.03241684 2.72834796\n", - " 0.04629701 3.45637379 0.06189982 2.15284275 0.05385159 1.83229682\n", - " 0.12492338 1.85690934 0.12949531 1.78003285 0.15287015 1.70353417\n", - " 0.22346859 1.66468729 0.26773417 1.62268562 0.25569027 1.59349245\n", - " 0.27944153 1.63684883 0.27128936 1.6658579 0.20814631 1.59614728\n", - " 0.26473623 1.46867298 0.32159232 1.37905854 0.26955415 1.4679887\n", - " 0.3086805 1.48644291 0.27906888 1.55025682 0.18139491 1.58505851\n", - " 0.31435108 1.57903826 0.49069545 1.52006739 0.51595187 1.60585803]\n", - "Depth = 24, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.429285\n", - " Iterations: 5259\n", - " Function evaluations: 6176\n", - "P = [ 0.0342763 2.1201762 -0.00855308 1.77649149 0.03715021 3.24221572\n", - " 0.04735155 4.10168924 0.05212498 2.28395686 0.07347248 1.93018631\n", - " 0.11190047 1.88641144 0.10463886 1.76091072 0.19611124 1.76611474\n", - " 0.23320053 1.62652952 0.25426706 1.57865385 0.21965096 1.58527509\n", - " 0.27259014 1.59061356 0.27718933 1.66024894 0.17218527 1.67639614\n", - " 0.27207573 1.43763988 0.29458246 1.40914642 0.25423432 1.4186911\n", - " 0.38012371 1.50509388 0.26800866 1.52948757 0.14382785 1.61823697\n", - " 0.25572111 1.61986287 0.66802506 1.53919446 0.36564443 1.6270857 ]\n", - "P_ = [ 0.0342763 2.1201762 -0.00676853 1.79081169 0.0333416 3.12007203\n", - " 0.04607639 3.99425505 0.05132941 2.58691226 0.06902509 2.00388851\n", - " 0.10229348 1.89735516 0.10675683 1.79751509 0.16562045 1.76438007\n", - " 0.21929204 1.67887398 0.24548933 1.59860205 0.23551667 1.58224036\n", - " 0.24612055 1.58794433 0.2746981 1.62252978 0.23343763 1.66697694\n", - " 0.20964419 1.58686254 0.27957798 1.42814206 0.28281426 1.41193028\n", - " 0.28570667 1.4402918 0.35676641 1.5101759 0.24731186 1.54427913\n", - " 0.15781451 1.6184402 0.29007978 1.61314051 0.65542587 1.5428566\n", - " 0.36564443 1.6270857 ]\n", - "Depth = 25, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.485122\n", - " Iterations: 3196\n", - " Function evaluations: 3785\n", - "P = [ 3.86987206e-02 2.03040312e+00 -7.23224706e-03 2.02883063e+00\n", - " 1.41735442e-03 3.56195585e+00 1.47741913e-02 4.22233534e+00\n", - " 7.13975924e-02 2.27873099e+00 4.84696246e-02 2.00488548e+00\n", - " 1.28849429e-01 2.01224719e+00 1.10029314e-01 1.72257633e+00\n", - " 1.41569542e-01 1.85106640e+00 1.82286648e-01 1.71046257e+00\n", - " 2.78568069e-01 1.66704005e+00 2.20693308e-01 1.55113096e+00\n", - " 2.29558184e-01 1.59844582e+00 3.17457728e-01 1.59903926e+00\n", - " 1.94814089e-01 1.60697606e+00 2.93474982e-01 1.56873835e+00\n", - " 3.10253493e-01 1.41302855e+00 3.01575839e-01 1.43871135e+00\n", - " 2.40511955e-01 1.47473251e+00 3.97513395e-01 1.51880665e+00\n", - " 3.11789404e-01 1.55848581e+00 1.84914363e-01 1.60634350e+00\n", - " 3.14982411e-01 1.58800427e+00 4.87950729e-01 1.57210524e+00\n", - " 3.51079582e-01 1.62873267e+00]\n", - "P_ = [ 3.86987206e-02 2.03040312e+00 -5.39500835e-03 2.02889353e+00\n", - " 7.25386304e-04 3.43930584e+00 1.31713708e-02 4.14308981e+00\n", - " 6.23378482e-02 2.58970769e+00 5.30552182e-02 2.05965458e+00\n", - " 1.09558276e-01 2.01048038e+00 1.15298946e-01 1.80368417e+00\n", - " 1.31476669e-01 1.80994958e+00 1.67628490e-01 1.76107995e+00\n", - " 2.40055500e-01 1.68440906e+00 2.46158203e-01 1.60213096e+00\n", - " 2.25303044e-01 1.57573469e+00 2.71749965e-01 1.59873067e+00\n", - " 2.63494527e-01 1.60253145e+00 2.34278446e-01 1.59168097e+00\n", - " 2.99515246e-01 1.51268282e+00 3.07476644e-01 1.42124704e+00\n", - " 2.84477951e-01 1.44879727e+00 2.78192300e-01 1.48531030e+00\n", - " 3.80368596e-01 1.52674248e+00 2.91489397e-01 1.56614304e+00\n", - " 2.00522528e-01 1.60414280e+00 3.28819876e-01 1.58673234e+00\n", - " 4.82475883e-01 1.57437034e+00 3.51079582e-01 1.62873267e+00]\n", - "Depth = 26, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [-3.14285817e-02 1.64962745e+00 -9.43970618e-04 1.52954689e+00\n", - " 6.79663115e-04 4.48460534e+00 4.14671358e-02 3.82055393e+00\n", - " 9.26051066e-02 2.71687880e+00 9.87039235e-02 1.87065173e+00\n", - " 9.21112324e-03 2.10183694e+00 1.87051550e-01 1.95916008e+00\n", - " 2.72957160e-02 1.69190799e+00 1.00853974e-01 1.75130165e+00\n", - " 2.93617108e-01 1.72522179e+00 2.55034842e-01 1.63325955e+00\n", - " 1.79774662e-01 1.61046252e+00 3.71819900e-01 1.61200033e+00\n", - " 2.82487197e-01 1.71608030e+00 2.67454875e-01 1.70425343e+00\n", - " 2.42993250e-01 1.42979246e+00 1.98133411e-01 1.45292725e+00\n", - " 3.26217223e-01 1.57802039e+00 2.67501216e-01 1.49898858e+00\n", - " 2.51998729e-01 1.57562829e+00 4.18176894e-01 1.62533460e+00\n", - " 5.71996241e-02 1.58038884e+00 3.42567703e-01 1.52468891e+00\n", - " 5.72221443e-01 1.70814895e+00 4.01027702e-01 1.56779186e+00]\n", - "P_ = [-3.14285817e-02 1.64962745e+00 -2.11645566e-03 1.53416537e+00\n", - " 5.54768213e-04 4.25729315e+00 3.67608889e-02 3.89717525e+00\n", - " 8.47377264e-02 2.88667498e+00 9.75310741e-02 2.03338770e+00\n", - " 2.98633079e-02 2.04848651e+00 1.39171435e-01 1.99757308e+00\n", - " 7.64513571e-02 1.77413940e+00 7.53915001e-02 1.73074231e+00\n", - " 2.19477441e-01 1.73525251e+00 2.71358109e-01 1.67216666e+00\n", - " 2.14510130e-01 1.62098423e+00 2.75797281e-01 1.61123142e+00\n", - " 3.30589422e-01 1.66003724e+00 2.76127368e-01 1.71107663e+00\n", - " 2.58046557e-01 1.59869152e+00 2.27464844e-01 1.43780066e+00\n", - " 2.37543814e-01 1.49141745e+00 3.10409067e-01 1.55674259e+00\n", - " 2.63923719e-01 1.51667467e+00 2.83956068e-01 1.58518720e+00\n", - " 3.62641930e-01 1.61841987e+00 9.01267102e-02 1.57396192e+00\n", - " 3.60233376e-01 1.53880122e+00 5.65637069e-01 1.70275060e+00\n", - " 4.01027702e-01 1.56779186e+00]\n", - "Depth = 27, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.580740\n", - " Iterations: 3672\n", - " Function evaluations: 4340\n", - "P = [-3.18072145e-02 1.96305386e+00 -1.97126780e-03 1.72115723e+00\n", - " 6.10383833e-04 4.42874158e+00 4.34194021e-02 4.38244884e+00\n", - " 7.29698238e-02 2.50105373e+00 8.55522296e-02 2.19422914e+00\n", - " 3.09939697e-02 2.22815268e+00 1.24447949e-01 2.06835558e+00\n", - " 7.57302334e-02 1.62150149e+00 8.10095474e-02 1.71442608e+00\n", - " 1.66736383e-01 1.79931366e+00 2.42786820e-01 1.69143855e+00\n", - " 2.27467812e-01 1.69485067e+00 2.78889012e-01 1.68420850e+00\n", - " 2.67393700e-01 1.77227218e+00 2.23151134e-01 1.62848420e+00\n", - " 2.47638066e-01 1.57759943e+00 2.23686292e-01 1.45779854e+00\n", - " 2.38858667e-01 1.48323165e+00 3.10409352e-01 1.51484035e+00\n", - " 2.87163657e-01 1.58915085e+00 2.95661590e-01 1.60081748e+00\n", - " 4.69573774e-01 1.52957170e+00 8.66135290e-02 1.54184122e+00\n", - " 3.79904651e-01 1.54297601e+00 5.45996003e-01 1.49716242e+00\n", - " 4.02425311e-01 1.57221462e+00]\n", - "P_ = [-3.18072145e-02 1.96305386e+00 -3.07630286e-03 1.73011637e+00\n", - " 4.19150379e-04 4.22817977e+00 3.86628446e-02 4.38759247e+00\n", - " 6.85919835e-02 2.77977893e+00 8.32221545e-02 2.25104851e+00\n", - " 4.31180275e-02 2.22061411e+00 1.00219140e-01 2.10978446e+00\n", - " 9.01651122e-02 1.75390270e+00 7.92497760e-02 1.68345122e+00\n", - " 1.34985703e-01 1.76787381e+00 2.11803309e-01 1.73538767e+00\n", - " 2.34276260e-01 1.69333417e+00 2.54130656e-01 1.68933251e+00\n", - " 2.73354232e-01 1.72660953e+00 2.47730338e-01 1.70836641e+00\n", - " 2.33127292e-01 1.60775337e+00 2.38767039e-01 1.53322873e+00\n", - " 2.28743750e-01 1.46627624e+00 2.60058870e-01 1.49259719e+00\n", - " 3.04382690e-01 1.53410603e+00 2.89052087e-01 1.59174343e+00\n", - " 3.27867550e-01 1.58762382e+00 4.12838923e-01 1.53138941e+00\n", - " 1.19201431e-01 1.54196731e+00 3.92207714e-01 1.53958241e+00\n", - " 5.40678570e-01 1.49994214e+00 4.02425311e-01 1.57221462e+00]\n", - "Depth = 28, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [-2.69594914e-02 2.17336399e+00 -3.27491362e-03 1.25968366e+00\n", - " 4.35492489e-04 5.47583016e+00 4.54464216e-02 4.16780608e+00\n", - " 4.31146474e-02 2.59904185e+00 1.80580097e-01 2.05633237e+00\n", - " 3.04993660e-02 1.72313192e+00 1.50527577e-01 2.20673476e+00\n", - " 5.50321568e-02 1.48967521e+00 1.28131280e-01 1.83840666e+00\n", - " 8.60527757e-02 1.74001319e+00 2.37902619e-01 1.72174119e+00\n", - " 1.80754514e-01 1.60660411e+00 2.99591363e-01 1.68230520e+00\n", - " 4.14392430e-01 1.57764160e+00 2.16321136e-01 1.93751885e+00\n", - " 2.89303420e-01 1.61611252e+00 2.53268957e-01 1.64039823e+00\n", - " 2.06056089e-01 1.38593142e+00 2.28915362e-01 1.56767903e+00\n", - " 2.17458921e-01 1.41319306e+00 1.74834854e-01 1.53799340e+00\n", - " 2.85883248e-01 1.51784561e+00 4.03478003e-01 1.63607207e+00\n", - " 1.02963524e-01 1.51355905e+00 5.15759217e-01 1.62740724e+00\n", - " 6.75721745e-01 1.39477693e+00 2.70190098e-01 1.47973587e+00]\n", - "P_ = [-2.69594914e-02 2.17336399e+00 -4.12079139e-03 1.29231510e+00\n", - " 1.70463482e-04 5.17467684e+00 4.06238221e-02 4.30795151e+00\n", - " 4.34477580e-02 2.82315102e+00 1.56032696e-01 2.15324478e+00\n", - " 6.26595227e-02 1.79453202e+00 1.20520525e-01 2.08583405e+00\n", - " 8.23165627e-02 1.69454936e+00 1.04635133e-01 1.72631441e+00\n", - " 1.01080813e-01 1.77515371e+00 1.78247323e-01 1.72891947e+00\n", - " 2.05246559e-01 1.65594858e+00 2.44417112e-01 1.64715827e+00\n", - " 3.56991897e-01 1.62997340e+00 3.22430758e-01 1.74472746e+00\n", - " 2.47599258e-01 1.79977328e+00 2.75147024e-01 1.62565334e+00\n", - " 2.36407218e-01 1.54951723e+00 2.13403712e-01 1.44435030e+00\n", - " 2.25642093e-01 1.52354018e+00 2.06802904e-01 1.44439315e+00\n", - " 1.98630938e-01 1.53367602e+00 3.06882311e-01 1.53895747e+00\n", - " 3.60547363e-01 1.61857021e+00 1.47191634e-01 1.52575707e+00\n", - " 5.27185112e-01 1.61079079e+00 6.61238472e-01 1.39781118e+00\n", - " 2.70190098e-01 1.47973587e+00]\n", - "Depth = 29, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 2.558837\n", - " Iterations: 2791\n", - " Function evaluations: 3308\n", - "P = [-3.24050174e-02 2.18211535e+00 -4.33665740e-03 1.18586514e+00\n", - " 1.69302759e-04 4.91203467e+00 4.02272483e-02 4.33506958e+00\n", - " 3.64607196e-02 2.73679517e+00 1.26620876e-01 2.24526033e+00\n", - " 7.06331463e-02 1.86011291e+00 1.17576808e-01 2.14345054e+00\n", - " 9.00084329e-02 1.72767455e+00 9.63164950e-02 1.86510463e+00\n", - " 1.10824698e-01 1.82033641e+00 1.35653411e-01 1.71961916e+00\n", - " 2.07235843e-01 1.62071289e+00 2.30032039e-01 1.60559155e+00\n", - " 3.30037839e-01 1.61473310e+00 3.63889348e-01 1.70080367e+00\n", - " 2.40745539e-01 1.70310617e+00 3.02643558e-01 1.64132552e+00\n", - " 1.65988695e-01 1.54766261e+00 1.95038702e-01 1.40579168e+00\n", - " 3.19555362e-01 1.60687543e+00 2.39265950e-01 1.48660703e+00\n", - " 2.10446514e-01 1.61770018e+00 2.83954822e-01 1.51432593e+00\n", - " 3.37412689e-01 1.66560407e+00 1.69518423e-01 1.57119999e+00\n", - " 5.13672778e-01 1.64629924e+00 5.91530295e-01 1.48519090e+00\n", - " 2.33264632e-01 1.45817811e+00]\n", - "P_ = [-3.24050174e-02 2.18211535e+00 -5.30453188e-03 1.22021860e+00\n", - " -1.41453114e-04 4.65505746e+00 3.60833229e-02 4.39475563e+00\n", - " 3.69802408e-02 2.95724682e+00 1.11076021e-01 2.33000772e+00\n", - " 8.22168145e-02 1.93979858e+00 1.06245579e-01 2.07505870e+00\n", - " 9.76135019e-02 1.84237138e+00 9.43588206e-02 1.82245392e+00\n", - " 1.05821870e-01 1.83577373e+00 1.26235624e-01 1.75782226e+00\n", - " 1.77615526e-01 1.66163962e+00 2.19813054e-01 1.61237008e+00\n", - " 2.81759177e-01 1.61031994e+00 3.46379947e-01 1.65628441e+00\n", - " 3.08686951e-01 1.70183583e+00 2.66358513e-01 1.67754176e+00\n", - " 2.50808955e-01 1.60579821e+00 1.76005939e-01 1.49874160e+00\n", - " 2.33681803e-01 1.46819698e+00 2.97406559e-01 1.57369794e+00\n", - " 2.32309535e-01 1.51825021e+00 2.25655129e-01 1.59631240e+00\n", - " 2.93171696e-01 1.54040837e+00 3.14254859e-01 1.65258282e+00\n", - " 2.05120598e-01 1.57896887e+00 5.19042262e-01 1.63518832e+00\n", - " 5.79176307e-01 1.48425942e+00 2.33264632e-01 1.45817811e+00]\n", - "Depth = 30, Rep = 1\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization terminated successfully.\n", - " Current function value: 2.449098\n", - " Iterations: 3370\n", - " Function evaluations: 3983\n", - "1.0 [6.89666207 4.94837648 4.08312367 3.52154552 3.286317 3.04579633\n", - " 2.82740345 2.69474296 2.60546241 2.6335368 2.63132655 2.64322155\n", - " 2.44594644 2.79378958 2.50934107 2.72932005 2.54477617 2.52094902\n", - " 2.5600339 2.33084953 2.51286024 2.49136476 2.40461021 2.42928495\n", - " 2.48512222 2.35257258 2.58074003 2.2669885 2.55883697 2.4490982 ]\n", - "[[6.57155339 5.94790512 4.51084725 5.48476219 4.44827696 4.07086367\n", - " 4.45993119 3.76473244 3.75245393 3.70383406 2.54453644 2.75335922\n", - " 3.72365101 2.64914745 3.66152866 3.41308183 2.17660478 2.18383796\n", - " 2.54980097 1.72430929 2.24071873 1.8353618 2.04963403 1.97768311\n", - " 2.25839296 2.22977067 1.94603139 2.05226045 2.69504832 3.27724127]\n", - " [7.58106801 6.81608452 4.28714233 4.07123972 3.27046962 3.23940109\n", - " 3.69518164 3.2411352 2.8435791 2.91039551 2.52147765 2.7118309\n", - " 2.7196728 2.5657514 2.49654928 2.14986169 2.03773181 1.96011255\n", - " 1.99818881 1.99560667 2.10966328 1.86491841 1.83579189 1.98703992\n", - " 1.98133515 1.95306622 1.90928783 1.85507609 1.79545032 1.7963689 ]\n", - " [5.67675131 4.71392584 4.01740509 3.36995594 3.02811997 2.75900701\n", - " 2.07994453 1.87160639 1.76736629 1.60399896 1.51494314 1.48018664\n", - " 1.42851074 1.41006842 1.37578808 1.29188206 1.25021059 1.25293931\n", - " 1.22202663 1.23016691 1.26143882 1.20441019 1.17776388 1.18431374\n", - " 1.16553331 1.16956844 1.16569465 1.17659931 1.16990127 1.15831922]\n", - " [5.00995896 4.29025145 4.60820671 3.83390873 3.89848291 5.33118031\n", - " 3.55893822 3.40156727 4.09051018 4.16531197 3.86869824 2.74039918\n", - " 2.37252786 2.09790193 2.46381788 3.23389141 2.92683369 2.26271526\n", - " 2.22500107 1.72792525 1.99341501 2.13517458 2.55949815 2.08833212\n", - " 2.30394139 2.47254611 2.09431819 2.0108552 2.25457883 1.56109974]\n", - " [4.00096445 3.74521392 2.59257503 2.56365739 1.9185404 1.87747501\n", - " 1.74225195 1.62820595 1.46249835 1.3728014 1.35944481 1.35683453\n", - " 1.33094362 1.31878632 1.32159957 1.30276576 1.25442761 1.25346875\n", - " 1.23969275 1.23278308 1.2266854 1.22191909 1.20703107 1.20899474\n", - " 1.20219427 1.20085781 1.20009343 1.19826693 1.1915774 1.19065828]\n", - " [5.90892769 4.83252908 3.71479956 3.36110121 2.94173277 2.24786958\n", - " 2.12439453 2.02822257 1.99458002 1.79405078 1.71446451 1.68436207\n", - " 1.64831949 1.60645585 1.57877549 1.55946868 1.50646832 1.48490593\n", - " 1.46944309 1.45423724 1.43322495 1.41715875 1.39899314 1.36097986\n", - " 1.33935151 1.32162911 1.30734052 1.2947269 1.27768564 1.26760576]\n", - " [5.07730592 3.19397021 2.56921505 2.2196952 1.87944827 1.7817944\n", - " 1.79674014 1.74393688 1.72491634 1.70478017 1.70372389 1.71403689\n", - " 1.71964722 1.71701915 1.65427385 1.66354751 1.65446129 1.64731001\n", - " 1.64582841 1.63908351 1.60606623 1.61407892 1.61749603 1.58823071\n", - " 1.60544517 1.59941945 1.61244841 1.60748773 1.61573555 1.61325776]\n", - " [6.09370005 4.58327549 2.77056736 2.4009721 2.16465466 1.90248461\n", - " 1.85814571 1.86203274 1.82759854 1.84492164 1.83096494 1.84786217\n", - " 1.84800744 1.84266075 1.84515694 1.85168419 1.86013029 1.8591394\n", - " 1.79934195 1.88437739 1.82798148 1.86223998 1.83513759 1.84794419\n", - " 1.84251045 1.85218276 1.85216684 1.85206644 1.85538944 1.84797453]\n", - " [3.56976737 2.52475365 1.80688067 1.46432998 1.33467503 1.27756052\n", - " 1.26533716 1.27003792 1.27484318 1.27528744 1.22030941 1.23417839\n", - " 1.2181345 1.22498409 1.20906575 1.21251697 1.20504138 1.21081175\n", - " 1.19843016 1.20553894 1.20452495 1.20498028 1.20392811 1.20420477\n", - " 1.20456712 1.20327737 1.20572231 1.20370171 1.20555114 1.20388906]\n", - " [6.89666207 4.94837648 4.08312367 3.52154552 3.286317 3.04579633\n", - " 2.82740345 2.69474296 2.60546241 2.6335368 2.63132655 2.64322155\n", - " 2.44594644 2.79378958 2.50934107 2.72932005 2.54477617 2.52094902\n", - " 2.5600339 2.33084953 2.51286024 2.49136476 2.40461021 2.42928495\n", - " 2.48512222 2.35257258 2.58074003 2.2669885 2.55883697 2.4490982 ]] [5.63866592 4.55962858 3.49607627 3.2291168 2.81707176 2.75334325\n", - " 2.54082685 2.35062203 2.33438083 2.30089187 2.09098896 2.01662715\n", - " 2.04553611 1.92265649 2.01158966 2.04080202 1.84166859 1.76361899\n", - " 1.79077877 1.64248778 1.74165791 1.68516068 1.72898841 1.68770081\n", - " 1.73883936 1.73548905 1.68738436 1.65180292 1.76197549 1.73655127]\n", - "[[0.1749857 0.07463194 0.26530491 0.16394175 0.18892849 0.25701077\n", - " 0.24542951 0.40504394 0.18547862 0.24113788 0.62032714 0.68408453\n", - " 0.11521194 0.57930818 0.29653581 0.32221821 0.75779012 0.76858176\n", - " 0.59269399 0.8271978 0.69201592 0.87101232 0.79114835 0.72852071\n", - " 0.64433266 0.66377712 0.77675308 0.72982301 0.58648573 0.44154865]\n", - " [0.17669094 0.20818569 0.40598211 0.40456531 0.54848127 0.5337594\n", - " 0.48446167 0.53759304 0.60295388 0.58451793 0.64895146 0.66165701\n", - " 0.62972457 0.66201878 0.67281148 0.75627098 0.78514972 0.80366385\n", - " 0.79430362 0.79961314 0.7524382 0.82370466 0.83214203 0.78138294\n", - " 0.78255631 0.78124579 0.80687807 0.80774629 0.84561002 0.84356134]\n", - " [0.1977358 0.23204622 0.30938238 0.39342279 0.41016143 0.46245125\n", - " 0.76102816 0.79966194 0.84980142 0.9167973 0.93013476 0.94105633\n", - " 0.96019643 0.9567664 0.95781341 0.97258171 0.97672161 0.97483651\n", - " 0.98345276 0.97827363 0.97171746 0.98525476 0.99020549 0.988242\n", - " 0.99105685 0.98789452 0.98718377 0.98332188 0.98342322 0.98330761]\n", - " [0.05772911 0.21353746 0.01841155 0.31450455 0.21424321 0.05404723\n", - " 0.43161435 0.34272799 0.28819124 0.28689022 0.1868918 0.50636735\n", - " 0.71458126 0.77159991 0.58971876 0.39292553 0.46431953 0.6325678\n", - " 0.69978407 0.80479284 0.72769493 0.74105124 0.53269212 0.73999712\n", - " 0.61502723 0.52602161 0.71815241 0.71745393 0.53403795 0.82706806]\n", - " [0.12450898 0.13546046 0.33397169 0.30579603 0.53279986 0.54005574\n", - " 0.5789386 0.62157361 0.67239022 0.70608977 0.71741324 0.71989795\n", - " 0.72816408 0.73770709 0.7462425 0.75395046 0.77610427 0.778063\n", - " 0.78739546 0.80304068 0.8044153 0.81655327 0.83574318 0.83983299\n", - " 0.85295023 0.85822598 0.86248183 0.86742561 0.8687046 0.87578262]\n", - " [0.15384579 0.23299282 0.34316369 0.40381029 0.48323069 0.60966505\n", - " 0.65090211 0.6781041 0.69468559 0.73757271 0.76352272 0.78064924\n", - " 0.80250928 0.8256876 0.84161068 0.85173433 0.88960447 0.89427145\n", - " 0.89713168 0.89784489 0.90396968 0.90972365 0.91944211 0.93551855\n", - " 0.93997379 0.94289646 0.9440385 0.94476954 0.94821036 0.94920811]\n", - " [0.22662278 0.49591192 0.64928992 0.72253971 0.88505646 0.91736256\n", - " 0.93108311 0.94041937 0.96629845 0.97837675 0.97999527 0.98011569\n", - " 0.97939879 0.97927928 0.98252313 0.98523181 0.98698179 0.98795262\n", - " 0.98839303 0.98858465 0.9918529 0.99290353 0.99289167 0.99426743\n", - " 0.9945867 0.99461399 0.99442154 0.99355126 0.99301575 0.99210625]\n", - " [0.1997449 0.39406338 0.8125561 0.89215215 0.93988072 0.97583839\n", - " 0.98050285 0.98626726 0.98996115 0.99116577 0.99318232 0.99328416\n", - " 0.99223222 0.99419442 0.9931634 0.99226818 0.99206014 0.99172956\n", - " 0.99264689 0.98944046 0.9912926 0.99247498 0.99365946 0.99432346\n", - " 0.99379021 0.99295831 0.9931038 0.99245639 0.99277207 0.99313253]\n", - " [0.26415019 0.58986982 0.84151077 0.92289843 0.95683247 0.97222603\n", - " 0.97482575 0.9763395 0.97674997 0.97931421 0.99098921 0.98701103\n", - " 0.99265455 0.99212748 0.997278 0.99588027 0.99858407 0.9965231\n", - " 0.99929919 0.99908139 0.99837773 0.99891483 0.99899648 0.99913097\n", - " 0.99908424 0.99921098 0.99889051 0.9990329 0.9989961 0.9989517 ]\n", - " [0.2078407 0.39185815 0.52883442 0.6602746 0.74124914 0.80761426\n", - " 0.92747099 0.96869989 0.98667715 0.98687849 0.98657826 0.98622107\n", - " 0.98386718 0.97357819 0.98336615 0.98153527 0.98441083 0.9913277\n", - " 0.99528599 0.97942874 0.99282883 0.99624753 0.98917797 0.99182223\n", - " 0.98353342 0.95672302 0.99361887 0.97221749 0.9841256 0.99414314]] [0.17838549 0.29685579 0.45084075 0.51839056 0.59008637 0.61300307\n", - " 0.69662571 0.72564306 0.72131877 0.7408741 0.78179862 0.82403444\n", - " 0.78985403 0.84722673 0.80610633 0.80045968 0.86117266 0.88195174\n", - " 0.87303867 0.90672982 0.88266035 0.91278408 0.88760989 0.89930384\n", - " 0.87968917 0.87035678 0.90755224 0.90077983 0.87353814 0.889881 ]\n" - ] - } - ], - "source": [ - "sol_arr = np.array([3,3,3,3,3,3,4,4,4,4])\n", - "num_arr = np.array([1,2,3,5,6,4,1,2,3,4])\n", - "\n", - "SP_avg, SP, C_avg, C, best_cost_overlap= averageQAOA(QAOATailAssignment,options, simulation_args, num_routes, sol_arr, num_arr)" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "6727ad03", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[0.06987256 0.08108344 0.14658584 0.15198281 0.17974263 0.17559157\n", - " 0.24238732 0.19650296 0.23081171 0.23049123 0.22520827 0.24035581\n", - " 0.26729888 0.23596674 0.26950808 0.24815165 0.27490349 0.28523951\n", - " 0.27860074 0.32617423 0.31068805 0.31170007 0.28575556 0.33336599\n", - " 0.31549966 0.33683292 0.30396993 0.33238454 0.33721702 0.37751695]\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "print(np.sum(best_cost_overlap,axis=0)/10)\n", - "fig, ax = plt.subplots(figsize = (14,7))\n", - "fig.suptitle(f'Best cost overlap with standard x mixer on {num_routes} routes')\n", - "ax.plot(range(best_cost_overlap.shape[1]), np.sum(best_cost_overlap,axis=0)/10)\n", - "for i in range(10):\n", - " ax.scatter(range(best_cost_overlap.shape[1]), best_cost_overlap[i])\n", - "ax.hlines(1,1,max_depth,color = \"black\", ls = \"--\")\n", - "ax.grid(ls = \"--\")\n", - "ax.set_ylabel(r\"$|{\\langle x^* |\\gamma \\beta \\delta \\rangle}|^2$\", color = \"black\")\n", - "ax.set_xlabel(\"Depth, $d$\")\n", - "plt.savefig(f'./data/saved_histograms/Averages/Best cost overlap with standard x mixer on {num_routes} routes high sol.pdf')\n", - "plt.show()\n", - "plot_SP_C(SP_avg, C_avg, max_depth, title = f'Cost and success prob with standard x mixer on {num_routes} routes', savefig = f'./data/saved_histograms/Averages/Cost and success prob with standard x mixer on {num_routes} routes maxdepth {max_depth}.pdf')" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "e58dae0d", - "metadata": {}, - "outputs": [], - "source": [ - "np.save(f'./data/saved_probs_costs/Standard_average_cost_{num_routes}_routes_{max_depth}_depth_high_sol', C_avg)\n", - "np.save(f'./data/saved_probs_costs/Standard_average_success_prob_{num_routes}_routes_{max_depth}_depth_high_sol', SP_avg)\n", - "np.save(f'./data/saved_probs_costs/Standard_cost_{num_routes}_routes_{max_depth}_depth_high_sol', C)\n", - "np.save(f'./data/saved_probs_costs/Standard_success_prob_{num_routes}_routes_{max_depth}_depth_high_sol', SP)\n", - "np.save(f'./data/saved_probs_costs/Standard_best_cost_overlap_{num_routes}_routes_{max_depth}_depth_high_sol', best_cost_overlap)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/tailassignment_oop.ipynb b/tailassignment_oop.ipynb deleted file mode 100644 index 6a075dc..0000000 --- a/tailassignment_oop.ipynb +++ /dev/null @@ -1,631 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "e429c1ea", - "metadata": {}, - "outputs": [], - "source": [ - "%load_ext autoreload\n", - "%autoreload 2" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "a25b06d2", - "metadata": {}, - "outputs": [], - "source": [ - "from qiskit import *\n", - "from qiskit.tools.monitor import job_monitor\n", - "\n", - "import numpy as np\n", - "from qaoa import *\n", - "from exactcover import *\n", - "\n", - "#from classical_exactcover_solver import *\n", - "import os\n", - "\n", - "import sys\n", - "sys.path.append('../')\n", - "\n", - "from qiskit_utilities.utilities import *\n", - "from data.tailassignment_loader import * \n", - "from tqdm import tqdm # progress bar\n", - "\n", - "from qiskit.visualization import plot_histogram" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "53a5e2ea", - "metadata": {}, - "outputs": [], - "source": [ - "from tailassignment_oop import *" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "d463d2d9", - "metadata": {}, - "outputs": [], - "source": [ - "from matplotlib import rc\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib as mpl\n", - "from tqdm import tqdm\n", - "\n", - "fontsize = 24\n", - "newparams = {'axes.titlesize': fontsize,\n", - " 'axes.labelsize': fontsize,\n", - " 'ytick.labelsize': fontsize,\n", - " 'xtick.labelsize': fontsize, \n", - " 'legend.fontsize': fontsize,\n", - " 'figure.titlesize': fontsize,\n", - " 'legend.handlelength': 1.5, \n", - " 'lines.linewidth': 2,\n", - " 'lines.markersize': 7,\n", - " 'figure.figsize': (12, 7), \n", - " 'figure.dpi':200,\n", - " 'text.usetex' : True,\n", - " 'font.family' : \"sans-serif\"\n", - " }\n", - "\n", - "plt.rcParams.update(newparams)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "5a113cdc", - "metadata": {}, - "outputs": [], - "source": [ - "instances = 4\n", - "flights = 3\n", - "solutions = 2\n", - "\n", - "path_to_examples = \"../data/tailassignment_samples/\"\n", - "\n", - "FR, CR, best_sol = load_FR_CR(path_to_examples + f'FRCR_{instances}_{flights}_{solutions}.txt')\n", - "\n", - "# Using big weights does not work for some reason\n", - "\n", - "CR /= np.max(CR)\n", - "mu = np.max(CR**2)\n", - "\n", - "# Best solution \n", - "best_key = \"\".join([str(i) for i in best_sol])[::-1]\n", - "best_cost = CR @ best_sol" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "ba34f8b6", - "metadata": {}, - "outputs": [], - "source": [ - "options={}\n", - "options['FR'] = FR\n", - "options['CR'] = CR\n", - "options['mu'] = 1 \n", - "options['usebarrier'] = True\n", - "\n", - "beta_n = 20\n", - "gamma_n = 40\n", - "\n", - "beta_max = np.pi\n", - "gamma_max = 2 * np.pi\n", - "\n", - "optmethod = 'Nelder-Mead' \n", - "# shots = 1024 # no need for shots when using statevector simulator\n", - "rerun = True\n", - "max_depth = 6" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "a4fcccfa", - "metadata": {}, - "outputs": [], - "source": [ - "Aer.backends()\n", - "backend = Aer.get_backend('statevector_simulator')" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "a60f7e98", - "metadata": {}, - "outputs": [], - "source": [ - "simulation_args = dict()\n", - "\n", - "simulation_args['backend'] = backend\n", - "simulation_args['optmethod'] = optmethod\n", - "simulation_args['max_depth'] = max_depth\n", - "simulation_args['repeats'] = 1\n", - "simulation_args['params_ll'] = np.array([0,0])\n", - "simulation_args['params_ul'] = np.array([gamma_max,beta_max])\n", - "simulation_args['params_n'] = np.array([gamma_n, beta_n])\n", - "#simulation_args['shots'] = shots" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "c35f45c9", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'FR': array([[1., 0., 1., 0.],\n", - " [1., 0., 0., 1.],\n", - " [0., 1., 0., 0.]]),\n", - " 'CR': array([1. , 0.2, 0.2, 0.2]),\n", - " 'mu': 1,\n", - " 'usebarrier': True}" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "options" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "28ce097d", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'backend': StatevectorSimulator('statevector_simulator'),\n", - " 'optmethod': 'Nelder-Mead',\n", - " 'max_depth': 6,\n", - " 'repeats': 1,\n", - " 'params_ll': array([0, 0]),\n", - " 'params_ul': array([6.28318531, 3.14159265]),\n", - " 'params_n': array([40, 20])}" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "simulation_args" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "45109054", - "metadata": {}, - "outputs": [], - "source": [ - "qaoa = QAOATailAssignment(options)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "a187660b", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Calculating energy landscape ...\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.274616\n", - " Iterations: 12\n", - " Function evaluations: 25\n", - "P = [4.63693086 2.08222408]\n", - "P_ = [4.63693086 2.08222408 4.63693086 2.08222408]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 0.825644\n", - " Iterations: 103\n", - " Function evaluations: 178\n", - "P = [5.21564194 0.68800555 4.65967747 1.13229415]\n", - "P_ = [5.21564194 0.68800555 4.9376597 0.91014985 4.65967747 1.13229415]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 0.634388\n", - " Iterations: 758\n", - " Function evaluations: 1157\n", - "P = [ 0.88308603 1.66436249 11.05318715 0.53304712 1.83559113 0.36774109]\n", - "P_ = [0.88308603 1.66436249 7.66315344 0.91015224 7.98065514 0.47794511\n", - " 1.83559113 0.36774109]\n", - "Depth = 4, Rep = 1\n", - "Warning: Maximum number of function evaluations has been exceeded.\n", - "P = [ 1.5385118 1.7689693 11.62115802 2.32698721 6.53211416 1.40958954\n", - " -2.02950038 0.35174176]\n", - "P_ = [ 1.5385118 1.7689693 9.10049647 2.18748273 9.07663609 1.86828838\n", - " 4.39171052 1.14512759 -2.02950038 0.35174176]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 0.606343\n", - " Iterations: 605\n", - " Function evaluations: 857\n", - "P = [ 0.73316308 1.82246342 6.07258527 2.54955159 10.65684692 1.71849418\n", - " 1.32197278 1.22743467 -3.65505396 0.37776341]\n", - "P_ = [ 0.73316308 1.82246342 5.00470084 2.40413396 8.82314226 2.05091715\n", - " 6.92289727 1.52207038 0.32656743 1.05750042 -3.65505396 0.37776341]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 0.663175\n", - " Iterations: 1549\n", - " Function evaluations: 2142\n" - ] - } - ], - "source": [ - "Elandscape, gammabetas, E, best = qaoa.simulate(**simulation_args)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "85b7867b", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", - "\n", - "shiftg=gamma_max/(2*gamma_n)\n", - "shiftb=beta_max/(2*beta_n)\n", - "\n", - "fig = plt.figure(figsize=(20,10));\n", - "plt.clf()\n", - "plt.imshow(Elandscape,\n", - " interpolation='spline36',\n", - " origin='lower',\n", - " extent=[-shiftg,gamma_max+shiftg,-shiftb,beta_max+shiftb], \n", - " aspect=1)\n", - "\n", - "plt.xticks([0,gamma_max], ['0', r'$2\\pi$'])\n", - "plt.yticks([0,beta_max], ['0', r'$\\pi$'])\n", - "plt.xlabel('$\\gamma$',loc='center')\n", - "plt.ylabel(r'$\\beta$',loc='center')\n", - "\n", - "plt.colorbar(shrink=0.25, pad=0.075, orientation=\"horizontal\")\n", - "plt.plot(gammabetas['xL_d1'][0], gammabetas['xL_d1'][1],'ob')\n", - "\n", - "# plot all gamma-and beta values for each layer in the same plot\n", - "# Note that the energy landscape is high dimensional and thus this may not necessarily \n", - "# be linked to the landscape \n", - "\n", - "cmap = plt.get_cmap('bwr')\n", - "\n", - "#for d in range(maxdepth):\n", - "# plt.plot(gammabetas[f'xL_d{d+1}'][0], gammabetas[f'xL_d{d+1}'][1],marker = \"o\", color = cmap(d/maxdepth))\n", - " \n", - "plt.tight_layout()" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "9ab4e654", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "(array([0.58914725, 0.81347256, 0.97374979, 0.93436368, 0.99655575,\n", - " 0.9694273 ]),\n", - " array([-1.27461561, -0.82564369, -0.63438787, -0.66783713, -0.60634294,\n", - " -0.66317525]))" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "qaoa.simulation_statistics(plot = True)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "eb6283f7", - "metadata": {}, - "outputs": [], - "source": [ - "options={}\n", - "options['FR'] = FR\n", - "options['CR'] = CR\n", - "options['mu'] = 1 \n", - "options['usebarrier'] = True\n", - "\n", - "beta_n = 10\n", - "gamma_n = 10\n", - "delta_n = 10\n", - "\n", - "beta_max = np.pi\n", - "gamma_max = 2 * np.pi\n", - "delta_max = 2 * np.pi\n", - "\n", - "optmethod = 'Nelder-Mead' \n", - "#shots = 1024 # no need for shots when using the statevector simulation\n", - "rerun = True\n", - "max_depth = 6" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "2b3192ac", - "metadata": {}, - "outputs": [], - "source": [ - "simulation_args = dict()\n", - "\n", - "simulation_args['backend'] = backend\n", - "simulation_args['optmethod'] = optmethod\n", - "simulation_args['max_depth'] = max_depth\n", - "simulation_args['repeats'] = 1\n", - "simulation_args['params_ll'] = np.array([0,0,0])\n", - "simulation_args['params_ul'] = np.array([gamma_max,beta_max,delta_max])\n", - "simulation_args['params_n'] = np.array([gamma_n, beta_n, delta_n])\n", - "#simulation_args['shots'] = shots" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "fb541b03", - "metadata": {}, - "outputs": [], - "source": [ - "qaoa3param = TailAssignmentInterlaced(options)" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "6ad97020", - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Calculating energy landscape ...\n", - "Calculating energy landscape done.\n", - "Depth = 1, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 1.365817\n", - " Iterations: 18\n", - " Function evaluations: 34\n", - "P = [ 2.27744219 1.98994452 -0.77012173]\n", - "P_ = [ 2.27744219 1.98994452 -0.77012173 2.27744219 1.98994452 -0.77012173]\n", - "Depth = 2, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 0.938149\n", - " Iterations: 228\n", - " Function evaluations: 361\n", - "P = [ 1.90731182 1.78017818 -0.13736 3.24354404 1.88790795 -1.10840756]\n", - "P_ = [ 1.90731182 1.78017818 -0.13736 2.57542793 1.83404306 -0.62288378\n", - " 3.24354404 1.88790795 -1.10840756]\n", - "Depth = 3, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 0.895595\n", - " Iterations: 321\n", - " Function evaluations: 475\n", - "P = [ 0.96754207 1.99046486 -0.12208485 2.57817891 1.80842723 -0.73584181\n", - " 3.18275465 1.78573012 -1.5817201 ]\n", - "P_ = [ 0.96754207 1.99046486 -0.12208485 2.04129996 1.86910644 -0.53125615\n", - " 2.77970416 1.80086153 -1.01780124 3.18275465 1.78573012 -1.5817201 ]\n", - "Depth = 4, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 0.629867\n", - " Iterations: 1231\n", - " Function evaluations: 1690\n", - "P = [-1.22358544 1.77046283 0.42689747 1.14093634 1.75756487 -2.7543179\n", - " 2.44572533 1.8361149 -0.6130251 3.00106931 2.08586357 -7.15588436]\n", - "P_ = [-1.22358544 1.77046283 0.42689747 0.54980589 1.76078936 -1.95901406\n", - " 1.79333083 1.79683989 -1.6836715 2.58456133 1.89855207 -2.24873991\n", - " 3.00106931 2.08586357 -7.15588436]\n", - "Depth = 5, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 0.602613\n", - " Iterations: 2112\n", - " Function evaluations: 2777\n", - "P = [-1.39657264 1.27106912 0.53543616 0.53057898 1.64463705 -1.45319903\n", - " 2.08641364 1.88296995 -1.79873363 2.33509589 1.86237938 -2.5258287\n", - " 2.93706488 1.85772591 -4.46476926]\n", - "P_ = [-1.39657264 1.27106912 0.53543616 0.14514865 1.56992347 -1.05547199\n", - " 1.46407977 1.78763679 -1.66051979 2.18588654 1.87473372 -2.08957166\n", - " 2.45548969 1.86144869 -2.91361681 2.93706488 1.85772591 -4.46476926]\n", - "Depth = 6, Rep = 1\n", - "Optimization terminated successfully.\n", - " Current function value: 0.601151\n", - " Iterations: 1321\n", - " Function evaluations: 1736\n" - ] - } - ], - "source": [ - "qaoa3param.simulate(**simulation_args);" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "03e3350b", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(figsize = (15,8))\n", - "\n", - "for i in range(max_depth - 1):\n", - "\n", - " ax.plot(gammabetadeltas[f'xL_d{i+1}'][::3]/np.pi, \n", - " ls = \"--\",alpha =0.5, marker = \"o\",\n", - " color = \"blue\")\n", - " ax.plot(gammabetadeltas[f'xL_d{i+1}'][1::3]/np.pi,\n", - " ls = \"--\",alpha =0.5, marker = \"o\", \n", - " color = \"red\")\n", - " ax.plot(gammabetadeltas[f'xL_d{i+1}'][2::3]/np.pi,\n", - " ls = \"--\",alpha =0.5, marker = \"o\",\n", - " color = \"green\")\n", - "\n", - "ax.plot(gammabetadeltas[f'xL_d{max_depth}'][::3]/np.pi, \n", - " ls = \"--\",alpha =0.5, marker = \"o\",\n", - " color = \"blue\",label=r\"$\\gamma$\")\n", - "ax.plot(gammabetadeltas[f'xL_d{max_depth}'][1::3]/np.pi,\n", - " ls = \"--\",alpha =0.5, marker = \"o\", \n", - " color = \"red\", label = r\"$\\beta$\")\n", - "ax.plot(gammabetadeltas[f'xL_d{max_depth}'][2::3]/np.pi,\n", - " ls = \"--\",alpha =0.5, marker = \"o\",\n", - " color = \"green\", label = r\"$\\delta$\")\n", - "\n", - "ax.set_xlabel(r\"$i$\")\n", - "ax.set_ylabel(r\"$\\gamma/\\pi, \\beta /\\pi, \\delta/\\pi$\")\n", - "\n", - "plt.suptitle(r\"\\textbf{Parameter values as a function of depth, $d$}\")\n", - "\n", - "box = ax.get_position()\n", - "ax.set_position([box.x0, box.y0, box.width * 1, box.height])\n", - "ax.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n", - "\n", - "ax.grid(ls = \"--\")\n", - "\n", - "plt.tight_layout()\n", - "#fig.savefig(f\"../../imgs/params_{instances}_{flights}_{solutions}.pdf\")" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/tailassignment_oop.py b/tailassignment_oop.py deleted file mode 100644 index 26643d3..0000000 --- a/tailassignment_oop.py +++ /dev/null @@ -1,659 +0,0 @@ -from qaoa_OOP import * - -class QAOATailAssignment(QAOAStandard): - - def __init__(self,options): - number_of_qubits = options['CR'].size - super().__init__(number_of_qubits, options) - - # Vectorized functions for the cost and is_solution: - # Very useful for simulation with the statevector, as it - # allows for avoiding multiple nested loops in the measurementStatistics function - - self.vector_cost = np.vectorize(self.cost) - self.vector_is_solution = np.vectorize(self.is_solution) - - # Save matrices as variables of object: - - self.FR = self.options.get('FR', None) - self.CR = self.options.get('CR', None) - self.mu = self.options.get('mu', 1) - - self.F, self.R = np.shape(self.FR) - - def cost(self,binstring): - - # Reverse string since qiskit uses ordering MSB ... LSB - x = np.array(list(map(int,binstring[::-1]))) - return - ( (self.CR @ x) + self.mu * np.sum((1 - (self.FR @ x))**2) ) - - def mix_states(self,beta): - """ - Applies unitary evolution of mixer hamiltonian with - time parameter beta - - Parameters - ---------- - beta : float - Time/angle for applying hamiltonian. - - """ - self.qc.rx( - 2 * beta, self.q_register ) - - def apply_exco(self,gamma): - """ - Applies unitary evolution of exact cover hamiltonian with - time-parameter gamma - - Parameters - ---------- - gamma : float - Time/angle for applying hamiltonian. - - """ - - for r in range(self.R): - hr = 0.5 * self.mu * self.FR[:,r] @ (np.sum(self.FR,axis = 1) - 2) - - # Apply only if hr differs sufficiently from 0 - if not np.isclose(hr, 0): - self.qc.rz( gamma * hr, self.q_register[r]) - - for r_ in range(r+1,self.R): - Jrr_ = 0.5 * self.FR[:,r] @ self.FR[:,r_] - - # Apply U(gamma), coupling part - # Only if the coupling constant differs sufficiently from 0 - - if not np.isclose(Jrr_, 0): - self.qc.cx(self.q_register[r], self.q_register[r_]) - self.qc.rz(gamma * Jrr_, self.q_register[r_]) - self.qc.cx(self.q_register[r], self.q_register[r_]) - - - def apply_cost(self,gamma): - """ - Applies unitary evolution of cost hamiltonian with - time-parameter gamma - - Parameters - ---------- - gamma : float - Time/angle for applying hamiltonian. - - """ - - for r in range(self.R): - hr = 0.5 * self.CR[r] - - # Apply only if hr differs sufficiently from 0 - if not np.isclose(hr, 0): - self.qc.rz( gamma * hr, self.q_register[r]) - - def apply_hamiltonian(self,gamma): - """ - Applies unitary evolution of the full hamiltonian representing the - problem, with time parameter gamma - - Parameters - ---------- - gamma : float - Time/angle for applying hamiltonian. - - """ - - for r in range(self.R): - hr = 0.5 * self.CR[r] + 0.5 * self.mu * self.FR[:,r] @ (np.sum(self.FR,axis = 1) - 2) - - # Apply only if hr differs sufficiently from 0 - if not np.isclose(hr, 0): - self.qc.rz( gamma * hr, self.q_register[r]) - - for r_ in range(r+1,self.R): - Jrr_ = 0.5 * self.FR[:,r] @ self.FR[:,r_] - - # Apply U(gamma), coupling part - - # Apply U(gamma), coupling part - # Only if the coupling constant differs sufficiently from 0 - - if not np.isclose(Jrr_, 0): - self.qc.cx(self.q_register[r], self.q_register[r_]) - self.qc.rz(gamma * Jrr_, self.q_register[r_]) - self.qc.cx(self.q_register[r], self.q_register[r_]) - - - def createCircuit(self, params): - - """ - Implements the ciruit for the tail assignment problem - Parameters - ---------- - params : array - variational parameters gamma_1 beta_1, ... , gamma_p beta_p - - Returns - ------- - qc : QuantumCircuit - - """ - - self.initial_state(self.R) - - gammas = params[::2] - betas = params[1::2] - - D = np.size(gammas) - - for d in range(D): - - gamma = gammas[d] - beta = betas[d] - - # Hamiltonian - cost + constraint - self.apply_hamiltonian(gamma) - # This is an equivalent implementation, but requires more gates. - # as the h-terms are not collected together - #self.apply_cost(gamma) - #self.apply_exco(gamma) - - if self.options['usebarrier']: - self.qc.barrier() - - # Apply mixer U(beta): - self.mix_states(beta) - - if self.options['usebarrier']: - self.qc.barrier() - - if "statevector" not in self.backend.name().split('_'): - # Do not measure at the end of the circuit if using a - # statevector simulation - self.qc.measure(self.q_register,self.c_register) - - return self.qc - - def simulation_statistics(self, best_sol = None , plot = True, savefig = None): - """ - Do simulation again with optimal found parameters and - return the success probability together with the average hamiltonian. - - Parameters - ---------- - plot : bool - If True, plot the results - savefig : string or None - If not None, save the figure with the filename/path given by savefig - - Returns - ------- - SP : array - Success probability as a function of depth - C : array - Total cost as a function of depth. - P : array - Probability of best state as a function of depth - """ - - SP = np.zeros(self.max_depth) - C = np.zeros(self.max_depth) - P = np.zeros(self.max_depth) - - # Provide the optimal solution if not running a statevector simulation - # The simulation statistics depends on either using the statevector simulator - # or explicitly providing the best solution as an argument to this function. - - assert("statevector" in self.backend.name().split('_') or best_sol != None) - - if best_sol == None: - best_index = np.argmax( self.vector_cost(self.state_strings) ) - best_sol = self.state_strings[best_index] - - self.depth = 1 - while self.continue_simulation(): - - qc = self.createCircuit(self.params[f'xL_d{self.depth}']) - job = execute(qc, - backend = self.backend, - noise_model = self.noise_model, - shots = self.shots) - - SP[self.depth - 1] = self.successProbability(job) - - if "statevector" in self.backend.name().split('_'): - - statevector = job.result().get_statevector() - probs = (np.abs(statevector))**2 - - C[self.depth - 1 ] = self.vector_cost(self.state_strings) @ probs - P[self.depth - 1 ] = probs[best_index] - else: - - counts = job.result().get_counts() - binstrings = np.array(list(counts.keys())) - counts_per_string = np.array(list(counts.values())) - - C[self.depth - 1] = self.vector_cost(binstrings) @ counts_per_string / self.shots - - if best_sol not in binstrings: - P[self.depth - 1] = 0 - else: - P[self.depth - 1] = counts_per_string[ binstrings == best_sol ][0] / self.shots - - self.depth += 1 - if plot: - plot_H_prob(self,SP,C, savefig) - - return SP, C, P - - def is_solution(self,binstring): - a = np.array(list(map(int,binstring[::-1]))) - return np.all(np.sum(self.FR * a,1)-1 == 0) - - def successProbability(self,job): - """ - Calculation of the success probability for a given job - Separating the calculation for a simulation done with the - statevector is a bit hackey. - - Parameters - ---------- - job : Qiskit job - - Returns - ------- - s_prob : float - Success probability - """ - - - if "statevector" in self.backend.name().split('_'): - - experiment_results = job.result().results - statevector = job.result().get_statevector() - probs = (np.abs(statevector))**2 - - s_prob = self.vector_is_solution(self.state_strings) @ probs - - else: - - experiment_results = job.result().results - s_prob = 0 - # assumes experiment results is a one-dimensional array - - for result in experiment_results: - n_shots = result.shots - counts = result.data.counts - for hexkey in list(counts.keys()): - count = counts[hexkey] - binstring = "{0:b}".format(int(hexkey,0)).zfill(self.R) - if self.is_solution(binstring): - s_prob += count/n_shots - - return s_prob - - def measurementStatistics(self,job): - """ - Measurement statistics for the tail assignment problem. - Calculating only the expectations and the best cost - - Parameters - ---------- - job : Qiskit job - ... - - Returns - ------- - expectation_values : array - variances : array - cost_best : float - - """ - - cost_best = - np.inf - experiment_results = job.result().results - expectations = np.zeros(len(experiment_results)) - - ## Simulation done with statevector - ## Much faster than doing it with other simulators in this implementation, - ## as many operations are vectorized here and don't depend on iterating through - ## dictionaries - - if "statevector" in self.backend.name().split('_'): - - statevector = job.result().get_statevector() - probs = np.abs(statevector)**2 - - costs = self.vector_cost(self.state_strings) - E = costs @ probs - - best_sampled_state = np.max( costs @ np.ceil(probs)) - cost_best = max(cost_best,best_sampled_state) - - expectations[0] = E - - ## Simulation done with other simulators - - else: - - for i, result in enumerate(experiment_results): - n_shots = result.shots - counts = result.data.counts - - E = 0 - - for hexkey in list(counts.keys()): - count = counts[hexkey] - binstring = "{0:b}".format(int(hexkey,0)).zfill(self.R) - cost = self.cost(binstring) - cost_best = max(cost_best, cost) - E += cost*count/n_shots - - expectations[i] = E - - - return expectations, None , cost_best - -class QAOAExactCover(QAOATailAssignment): - - def __init__(self, options = None): - - # Exactly the same as the tail assignment class, except we - # force the weights to be 0, even if non-zero weights are provided - - CR = np.zeros_like(options['FR'][0,:]) - options['CR'] = CR - - self.tol = options.get('tol', 0.9) - - super().__init__(options) - - def cost(self, binstring): - # Reverse string since qiskit uses ordering MSB ... LSB - x = np.array(list(map(int,binstring[::-1]))) - return - ( self.mu * np.sum((1 - (self.FR @ x))**2) ) - - def apply_hamiltonian(self,gamma): - # The hamiltonian in this case is only the exact cover part - super().apply_exco(gamma) - - def continue_simulation(self): - """ - Terminate the optimisation loop if the success probability of - the previous iteration is higher than the tolerance provided. - If the depth exceeds max_depth, then terminate anyways. - - """ - if self.depth <= self.max_depth: - job = execute(self.qc, - backend = self.backend, - noise_model = self.noise_model, - shots = self.shots) - - sp = self.successProbability(job) - - return sp < self.tol - else: - return False - - -class TailAssignmentInterlaced(QAOATailAssignment): - - def createCircuit(self, params): - - """ - Implements the ciruit for the tail assignment problem, with three parameters - Parameters - ---------- - params : array - variational parameters gamma_1 beta_1 delta_1 , ... , gamma_p beta_p delta_p - - Returns - ------- - qc : QuantumCircuit - - """ - - self.initial_state(self.R) - - gammas = params[::3] - betas = params[1::3] - deltas = params[2::3] - - D = np.size(gammas) - - for d in range(D): - - gamma = gammas[d] - beta = betas[d] - delta = deltas[d] - - # Hamiltonian - weights - self.apply_cost(delta) - - if self.options['usebarrier']: - self.qc.barrier() - - # Apply mixer U(beta) inbetween hamiltonians - self.mix_states(beta) - - if self.options['usebarrier']: - self.qc.barrier() - - self.apply_exco(gamma) - - # Apply mixer U(beta) at the end - self.mix_states(beta) - - if self.options['usebarrier']: - self.qc.barrier() - - if "statevector" not in self.backend.name().split('_'): - # Do not measure at the end of the circuit if using a - # statevector simulation - self.qc.measure(self.q_register,self.c_register) - - return self.qc - - - - -class TailAssignmentNFam(QAOATailAssignment): - """ - This class implements the freedom for the QAOA to rotate each qubit around a different axis in the xy-plane when mixing. - The axis is decided by one variational parameter per qubit which is optimized along with the other variational parameters. - For all layers at a given depth the qubit rotates around the same axis. - This is the NFam from https://arxiv.org/abs/2107.13129. - """ - - def __init__(self,options): - super().__init__(options) - - #Need an initial axis for the mixer to rotate around - #This can be chosen in options, or defaults to the (1,1) axis - self.init_thetas = options.get('init_thetas', np.zeros(self.FR.shape[1])+np.pi/4) - def mix_states(self,beta, thetas): - """ - Applies unitary evolution of mixer hamiltonian with - time parameter beta - - Parameters - ---------- - beta : float - Time/angle for applying hamiltonian. - thetas : array of floats - Angles deciding which axis to rotate around - - """ - for i in range(self.FR.shape[1]): - if np.abs(2 * beta * np.cos(thetas[i]))>1e-6: - self.qc.rx( - 2 * beta * np.cos(thetas[i]), self.q_register[i] ) - if np.abs(2 * beta * np.sin(thetas[i]))>1e-6: - self.qc.ry( - 2 * beta * np.sin(thetas[i]), self.q_register[i] ) - - - def createCircuit(self, params): - - """ - Implements the ciruit for the tail assignment problem, with two parameters - and an extra number of params equvalent to the number of qubits - Parameters - ---------- - params : array - variational parameters theta_1, ...theta_n, gamma_1 beta_1 , ... , gamma_p beta_p - except for in the first layer when it only contains gamma_1 beta_1 to allow for a grid search - - Returns - ------- - qc : QuantumCircuit - - """ - - self.initial_state(self.R) - rN = self.FR.shape[1] - if self.depth==1: - #Sets the correct params, and the initial theta values - gammas = params[::2] - betas = params[1::2] - thetas = self.init_thetas - else: - #Picks out the rotation angles first and the sets the rest of the params as usual - thetas = params[:rN] - gammas = params[rN::2] - betas = params[rN + 1::2] - - for d in range(self.depth): - - gamma = gammas[d] - beta = betas[d] - - # Hamiltonian - cost + constraint - self.apply_hamiltonian(gamma) - - if self.options['usebarrier']: - self.qc.barrier() - - # Apply mixer U(beta, thetas) at the end - self.mix_states(beta, thetas) - - if self.options['usebarrier']: - self.qc.barrier() - - if "statevector" not in self.backend.name().split('_'): - # Do not measure at the end of the circuit if using a - # statevector simulation - self.qc.measure(self.q_register,self.c_register) - - return self.qc - - def interp_init(self): - x_prev_0 = self.params[f'xL_d{self.depth - 1}'] - print(f"P = {x_prev_0}") - rN = self.FR.shape[1] - - # Minimize needs one-dimensional input, but the interpolation of the - # parameters can be done with a multidimensional input - # - # gamma_1 gamma_2 gamma_3 ... - # beta_1 beta_2 beta_3 ... - # ... - # The resulting flattened vector will be - # theta_1, .. theta_n, gamma_1 beta_1 gamma-2 beta_2 ... - # Which is what we want for the createCircuit method called in get-val - - p = self.depth - 1 - if self.depth > 2: - #Updates all params according to heuristic, except the theta values as they are not part of the heuristic. - #The theta values are the first rN values - x_prev = x_prev_0[rN:].reshape((p,self.q)) - else: - #For the first update the theta values need to be added seperately - x_prev_0 = self.init_thetas - x_prev = self.params[f'xL_d{self.depth - 1}'] - x = np.zeros((p+1,self.q)) - x_prev = x_prev.reshape((p,self.q)) - x[0,:] = x_prev[0,:] - - for i in range(2,p+1): - x[i - 1,:] = (i - 1)/p * x_prev[i-2,:] + (p - i + 1)/p * x_prev[i-1,:] - - x[p,:] = x_prev[p-1,:] - print(f"P_ = {x.flatten()}") - self.params[f'x0_d{self.depth}'] = x.flatten() - - return np.append(x_prev_0[:rN], x.flatten()) - - -class TailAssignmentInterlacedNFam(TailAssignmentXYPlane): - """ - This class extends the NFam from https://arxiv.org/abs/2107.13129 to also include our interlaced method. - """ - - - def createCircuit(self, params): - - """ - Implements the ciruit for the tail assignment problem, with three parameters - and an extra number of params equvalent to the number of qubits - Parameters - ---------- - params : array - variational parameters theta_1, ..., theta_n gamma_1 beta_1 delta_1 , ... , gamma_p beta_p delta_p - - Returns - ------- - qc : QuantumCircuit - - """ - - self.initial_state(self.R) - rN = self.FR.shape[1] - if self.depth==1: - #Sets the correct params, and the initial theta values - gammas = params[::3] - betas = params[1::3] - deltas = params[2::3] - thetas = self.init_thetas - else: - #Picks out the rotation angles first and the sets the rest of the params as usual - thetas = params[:rN] - gammas = params[rN::3] - betas = params[rN + 1::3] - deltas = params[rN + 2::3] - - - for d in range(self.depth): - - gamma = gammas[d] - beta = betas[d] - delta = deltas[d] - - # Hamiltonian - weights - self.apply_cost(delta) - - if self.options['usebarrier']: - self.qc.barrier() - - # Apply mixer U(beta, thetas) inbetween hamiltonians - self.mix_states(beta, thetas) - - if self.options['usebarrier']: - self.qc.barrier() - - # Hamiltonian - constraints - self.apply_exco(gamma) - - if self.options['usebarrier']: - self.qc.barrier() - # Apply mixer U(beta, thetas) at the end - self.mix_states(beta, thetas) - - if self.options['usebarrier']: - self.qc.barrier() - - if "statevector" not in self.backend.name().split('_'): - # Do not measure at the end of the circuit if using a - # statevector simulation - self.qc.measure(self.q_register,self.c_register) - - return self.qc \ No newline at end of file