In [61]:

    

import numpy as np
import pandas as pd
import math
import cmath
import pickle
from scipy.optimize import root
import matplotlib.pyplot as plt
%matplotlib inline


    

In [62]:

    

a = ("Table1.txt")
a


    

    
Out[62]:





'Table1.txt'

In [381]:

    

class InterfazPolimero:
    def __init__ (self,a):
        self.a=a

    def Lire(self):
        tab = pd.read_csv(self.a,sep=" ")
        coef =tab.values
        self.Experiment = coef[:,0]
        self.Thickness = coef[:,1]
        self.FoodSimulant = coef[:,2]
        self.Cpo = coef[:,3]
        self.K = coef [:,4]
        self.Dp = coef[:,5]
        self.RMSE = coef[:,6]
        self.k = coef[:,7]
        self.c4 = coef[:,8]
#         self.c1 =coef[:,9]
        self.c2 = np.zeros(10)
        
        return tab
    
    def inicializarC2(self):
        self.c2 = np.zeros(10)
        self.dimension = np.shape(self.c2)
        print(self.dimension)
        return self.c2
    
    
    def calcul(self):
        self.j1 = (self.Dp / (self.Thickness / 2)) * (self.Cpo - self.c2)
        print(self.j1)
        self.c3 = self.c2 / self.K
        self.j2 = self.k * (self.c3 - self.c4)
        return (self.j1 - self.j2) / self.j1
            
    def calcul2(self): 
        i = 0
        for self.Thickness, self.Dp, self.K, self.k, self.c in enumerate(tab):
            self.sol = root(calcul,15,args=(float(self.Dp),float(self.k),float(self.K),float(self.c4),float(self.Cpo),float(self.Thickness)))
            c2[i]= self.sol.x
            i = i + 1
        print(self.c2)
        return self.c2
    
    def Garder(self):
        raw_data ={"résultat" : [1.115510936772821, 1.0542169426645587, 1.041340418781726, 1.0219,1.4353658536585368, 1.0542169426645587, 1.058921125781793,1.0217682926829268, 1.05340368852459, 1.058921125781793]}
        df = pd.DataFrame(raw_data,index=["1","2","3","4","5","6","7","8","9","10"])
        df.to_csv("c2rep")
        return df

    
    def Graphique(self):
        plt.plot(self.Dp,self.Cpo,"^")
        plt.title("Cpo=f(Dp)")
        
    def Graphique2(self):
        plt.plot(self.Dp,[1.115510936772821, 1.0542169426645587, 1.041340418781726, 1.0219,1.4353658536585368, 1.0542169426645587, 1.058921125781793,1.0217682926829268, 1.05340368852459, 1.058921125781793],"^")
        
    def Graphique3(self):
        plt.plot(self.Cpo,[1.115510936772821, 1.0542169426645587, 1.041340418781726, 1.0219,1.4353658536585368, 1.0542169426645587, 1.058921125781793,1.0217682926829268, 1.05340368852459, 1.058921125781793],"^")


    

In [382]:

    

p = InterfazPolimero("Table1.txt")
p


    

    
Out[382]:





<__main__.InterfazPolimero at 0x1e944c70a58>

In [383]:

    

p.Lire()


    

    
Out[383]:







  

    

      

      
Experiment
      
Thickness
      
FoodSimulant
      
Cpo
      
K
      
Dp
      
RMSE
      
k
      
c4
      
c1
    
  
  

    

      
0
      
1
      
0.000146
      
EtOH95%
      
1157
      
52.0
      
1.950000e-13
      
1.5
      
0.000007
      
0.05
      
1045
    
    

      
1
      
2
      
0.000146
      
NaN
      
2440
      
35.0
      
1.970000e-13
      
3.0
      
0.000007
      
0.05
      
1069
    
    

      
2
      
3
      
0.000146
      
NaN
      
3152
      
24.0
      
2.000000e-13
      
2.6
      
0.000007
      
0.05
      
1094
    
    

      
3
      
4
      
0.000146
      
NaN
      
5950
      
0.5
      
2.000000e-13
      
2.3
      
0.000007
      
0.05
      
1119
    
    

      
4
      
5
      
0.000050
      
EtOH95%
      
2050
      
334.0
      
1.000000e-14
      
3.1
      
0.000007
      
0.05
      
1144
    
    

      
5
      
6
      
0.000146
      
NaN
      
2440
      
35.0
      
1.970000e-13
      
3.0
      
0.000007
      
0.05
      
1169
    
    

      
6
      
7
      
0.000190
      
NaN
      
2878
      
34.0
      
2.000000e-13
      
4.6
      
0.000007
      
0.05
      
1194
    
    

      
7
      
8
      
0.000050
      
EtOH10%
      
2050
      
1.0
      
2.000000e-13
      
1.0
      
0.000007
      
0.05
      
1219
    
    

      
8
      
9
      
0.000146
      
NaN
      
2440
      
1.0
      
2.000000e-13
      
1.0
      
0.000007
      
0.05
      
1244
    
    

      
9
      
10
      
0.000190
      
NaN
      
2878
      
1.0
      
2.000000e-13
      
1.0
      
0.000007
      
0.05
      
1269
    
  

In [384]:

    

p.calcul()


    

    




[3.0906164383561645e-06 6.584657534246575e-06 8.635616438356165e-06
 1.63013698630137e-05 8.199999999999999e-07 6.584657534246575e-06
 6.058947368421054e-06 1.6400000000000002e-05 6.684931506849316e-06
 6.058947368421054e-06]






    
Out[384]:





array([1.115510936772821, 1.0542169426645587, 1.041340418781726, 1.0219,
       1.4353658536585368, 1.0542169426645587, 1.058921125781793,
       1.0217682926829268, 1.05340368852459, 1.058921125781793],
      dtype=object)

In [385]:

    

p.Graphique()


    

In [386]:

    

table = p.Garder()
table


    

    
Out[386]:







  

    

      

      
résultat
    
  
  

    

      
1
      
1.115511
    
    

      
2
      
1.054217
    
    

      
3
      
1.041340
    
    

      
4
      
1.021900
    
    

      
5
      
1.435366
    
    

      
6
      
1.054217
    
    

      
7
      
1.058921
    
    

      
8
      
1.021768
    
    

      
9
      
1.053404
    
    

      
10
      
1.058921
    
  

In [387]:

    

p.Graphique2()


    

In [388]:

    

p.Graphique3()


    

In [ ]:

    




    

In [ ]: