~

density.py

@@ -21,4 +21,3 @@ def get_density(s, T):
         def rho(T):
             return A / B ** (1 + (1 - T / C) ** D)
     return rho(T) if s != 'Hexane' else rho
-

mccabethiele.py

@@ -3,13 +3,13 @@
 from matplotlib import pyplot, style
 from scipy.optimize import fsolve
 
-
 np.seterr(divide='ignore', invalid='ignore')
 
 
 def main():
     st.title('McCabe-Thiele Plot Generator')
-    st.write('The McCabe-Thiele method is used to determine the number of equilibrium stages for a distillation column.')
+    st.write(
+        'The McCabe-Thiele method is used to determine the number of equilibrium stages for a distillation column.')
 
     style.use('classic')
 
@@ -22,11 +22,9 @@ def main():
         q = st.number_input('Thermal Quality', value=1.000)
         a = st.number_input('Relative Volatility', value=2.500)
 
-
         def dbf(f):
             return [xd * f[0] + xb * f[1] - zf * F, f[0] + f[1] - F]
 
-
         [D, B] = fsolve(dbf, [30, 20])
 
         st.write('Distillate: ', round(D, 4), 'Bottoms: ', round(B, 4))
@@ -36,34 +34,27 @@ def dbf(f):
         Vr = Lr + D
         Vs = Vr + (q - 1) * F
 
-
         def x_eq(x):
             # x on the equlibrium curve
             return x / (a * (1 - x) + x)
 
-
         def rec_opline(x):
             # rectifying section operating line: y = (Lr/Vr)*x + (D*xd/Vr)
             return (Lr / Vr) * x + (D * xd / Vr)
 
-
         def strip_opline(x):
             # stripping section operating line: y = (Ls/Vs)*x - (B*xb/Vs)
             return (Ls / Vs) * x - (B * xb / Vs)
 
-
         # intersection point of rectifying opline and stripping opline
         def inter_pt(p):
             return [(Lr / Vr) * p[0] + (D * xd / Vr) - p[1], (Ls / Vs) * p[0] - (B * xb / Vs) - p[1]]
 
-
         [xq, yq] = fsolve(inter_pt, [0.5, 0.5])
 
-
         def min_reflux(x):
             return [q * x[0] - zf - x[1] * (q - 1), x[1] - a * x[0] / (1 + x[0] * (a - 1))]
 
-
         [xrmin, yrmin] = fsolve(min_reflux, [0.5, 0.6])
 
         slope = (xd - yrmin) / (xd - xrmin)
@@ -121,12 +112,10 @@ def min_reflux(x):
         xb_tr = st.number_input('Bottom concentration', value=0.100)
         a_tr = st.number_input('Relative Volatility (average)', value=2.500)
 
-
         def x_eq(x):
             # x on the equlibrium curve
             return x / (a_tr * (1 - x) + x)
 
-
         # y-x equilibrium curve
         x = np.linspace(0, 1, 10000)
         y = a_tr * x / (1 + x * (a_tr - 1))

volume.py

@@ -1,11 +1,9 @@
 import pandas as pd
 from density import get_density
 
-
 molecular_weights = pd.read_csv("molecularWeights.txt", sep='!', names=['Compounds', 'MW'])
-molecular_weights = dict(zip(molecular_weights['Compounds'], molecular_weights['MW'] ))
+molecular_weights = dict(zip(molecular_weights['Compounds'], molecular_weights['MW']))
 
 
 def get_volume(s, T):
-    return 0.001*molecular_weights[s]/get_density(s, T)
-
+    return 0.001 * molecular_weights[s] / get_density(s, T)