python_guide.py

#!/usr/bin/python

import collections
from collections import Counter
import matplotlib.gridspec as gridspec
import numpy as np
import glob
import os
import pdb
plt.legend(frameon=False)

# debugging
pdb.set_trace()

python - m pdb myscript.py

# Numpy array, how to select indices satisfying multiple conditions?
x = array([5, 2, 3, 1, 4, 5])
y = array(['f', 'o', 'o', 'b', 'a', 'r'])
out = y[(1 < x) & (x < 5)]


# Concatenate item in list to strings
sentence = ['this', 'is', 'a', 'sentence']
>> > '-'.join(sentence)
'this-is-a-sentence'

# Map two lists into a dictionary
keys = ['a', 'b', 'c']
values = [1, 2, 3]
dictionary = dict(zip(keys, values))
print dictionary
#{'a': 1, 'b': 2, 'c': 3}

# concatenate two dictionaries to create a new one
python - mtimeit - s'd1={1:2,3:4}; d2={5:6,7:9}; d3={10:8,13:22}' \
    'd4 = dict(d1, **d2); d4.update(d3)'

1000000 loops, best of 3: 1.88 usec per loop


# Find all files in directory with extension .txt in Python
os.chdir("/mydir")
for file in glob.glob("*.txt"):
    print(file)

# or

for file in os.listdir("/mydir"):
    if file.endswith(".txt"):
        print(file)
# or

for root, dirs, files in os.walk("/mydir"):
    for file in files:
        if file.endswith(".txt"):
            print(os.path.join(root, file))
# or

glob.glob('./*.txt')


# fixed seed
np.random.seed(123)
print np.random.rand(2)

# normal random distrbution
mu = 0
sigma = .1
np.random.normal(mu, sigma, 1000)

a0 = np.array([1, 2, 3])
np.matlib.repmat(a0, 2, 3)
# size of figure
plt.figure(figsize=(10, 10))

# trace and sum of matrix or 2D array
np.trace(A)
np.sum(A)
np.transpose(A)

# get the current time
>> > from time import gmtime, strftime
>> > strftime("%Y-%m-%d %H:%M:%S", gmtime())
'2009-01-05 22:14:39'

# imshow
fig = plt.figure()

ax1 = fig.add_subplot(2, 1, 1)
ax1.set_aspect('equal')
plt.imshow(Conn, interpolation='nearest', cmap='afmhot')  # , cmap=plt.cm.ocean
plt.colorbar()
ax2 = fig.add_subplot(2, 1, 2)
ax2.set_aspect('equal')
plt.imshow(Corr, interpolation='nearest', cmap='afmhot')  # , cmap=plt.cm.ocean
plt.colorbar()

# append
list.append(obj)


fig = plt.figure(figsize=(10, 6))
gs = gridspec.GridSpec(4, 1)
ax1 = plt.subplot(gs[0:3, 0])
plt.plot(t, sol[:, 0])
plt.ylabel('V')
plt.tick_params(
    axis='x',          # changes apply to the x-axis
    which='both',      # both major and minor ticks are affected
    bottom='off',      # ticks along the bottom edge are off
    top='off',         # ticks along the top edge are off
    labelbottom='off')  # labels along the bottom edge are off
ax2 = plt.subplot(gs[3, 0])
plt.plot(t, y)

# hide axis labels:
ax.get_xaxis().set_ticks([])
ax.get_yaxis().set_ticks([])


# add row of time to the first row of matrix A
np.insert(A, 0, t[:], axis=0)


# extend and append:
x = [1, 2, 3]
x.append([4, 5])
# out: [1, 2, 3, [4, 5]]
x = [1, 2, 3]
x.extend([4, 5])
# out:[1, 2, 3, 4, 5]


# To delete the first row, do this:
x = numpy.delete(x, (0), axis=0)
# To delete the third column, do this:
x = numpy.delete(x, (2), axis=1)

# delete zero rows of ndarray
Conn[np.all(Conn == 0, axis=1)]
Conn = Conn[~np.all(Conn == 0, axis=1)]
# print with out new line
sys.stdout.write('%d ' % item)


# numpy.ndarray.tolist
a = np.array([1, 2])
a.tolist()


# There's a simple way to check if matrix is symmetric using numpy:
(arr.transpose() == arr).all()

# How to count the occurrence of certain item in an ndarray in Python?
y = np.array([1, 2, 2, 2, 2, 0, 2, 3, 3, 3, 0, 0, 2, 2, 0])
np.count_nonzero(y == 1)

# How can I count the occurrences of a list item in Python?
[1, 2, 3, 4, 1, 4, 1].count(1)

>>z = ['blue', 'red', 'blue', 'yellow', 'blue', 'red']
>>Counter(z)
Counter({'blue': 3, 'red': 2, 'yellow': 1})

alist = ['a1', 'a2', 'a3']
for i, a in enumerate(alist):
    print i, a

0 a1
1 a2
2 a3

alist = ['a1', 'a2', 'a3']
blist = ['b1', 'b2', 'b3']

for a, b in zip(alist, blist):
    print a, b
a1 b1
a2 b2
a3 b3

alist = ['a1', 'a2', 'a3']
blist = ['b1', 'b2', 'b3']

for i, (a, b) in enumerate(zip(alist, blist)):
    print i, a, b

0 a1 b1
1 a2 b2
2 a3 b3


# run.py

os.system("make clean")
os.system("make")
for i, j in zip(g_n, tau_n):
    command = "./prog   " + str(i) + " " + str(j)
    os.system(command)

# Using a string variable as a variable name
foo = 'bar'
exec(foo+" = 'somthing else'")
print bar
somthing else

foo = 'bar'
exec(foo+" = 1")
print bar

foo = 'bar'
exec(foo+" = np.random.rand()")

x = 'buffalo'
exec("%s = %d" % (x, 2))

# print with leading zero:
print "%02d" % 5  # prints   05
print "%06.2f" % 5  # prints   005.00


# box annotation
bbox_props = dict(boxstyle="round,pad=0.1", fc="linen", ec="linen", lw=2)
t = ax1.text(0.8, 0.8, " A ", ha="center", va="center", rotation=0,
             size=20,
             bbox=bbox_props)


def check_symmetric(a, tol=1e-8):
    return np.allclose(a, a.T, atol=tol)


# How to count the frequency of the elements in a list?
a = [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 4, 5, 5]
counter = collections.Counter(a)
print(counter)
# Counter({1: 4, 2: 4, 3: 2, 5: 2, 4: 1})
print(counter.values())
# [4, 4, 2, 1, 2]
print(counter.keys())
# [1, 2, 3, 4, 5]
print(counter.most_common(3))
# [(1, 4), (2, 4), (3, 2)]



# colab save file in drive
from google.colab import files
files.download("data.csv")


#3D array
a = np.tile(np.arange(1,7, dtype=float), 2)
b = a.reshape((2,2,3))
x = np.nanmean(b, axis=0)