In [1]:

    

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


    

In [2]:

    

table = ("Tablea1.txt")
table


    

    
Out[2]:





'Tablea1.txt'

In [3]:

    

class Polynome:
    def __init__(self,table):
        self.table=table
        
    def Lire(self):
        self.abc = pd.read_csv(self.table,sep=" ")
        coef = self.abc.values
        self.a = coef[:,0]
        self.b = coef[:,1]
        self.c = coef[:,2]
        
        print(self.a,self.b,self.c)
        return self.abc 
    
    def calcul(self):
        i = 0
        self.x1 = np.zeros(1)
        self.x2 = np.zeros(1)
        self.x0 = np.zeros(1)
        self.x11 =np.zeros(1)
        self.x12 =np.zeros(1)
                
        print("a : {0},b : {1} et c : {2}".format(self.a,self.b,self.c))
        
        for self.a2, self.b2, self.c2 in zip(self.a,self.b, self.c):
            self.Delta = (self.b**2)-(4 * self.a * self.c)
            print ("Delta = {}".format(self.Delta))
            if self.Delta < 0:
                self.x11 = (-self.b2-cmath.sqrt(self.Delta))/(2*self.a2)
                self.x12 = (-self.b2-cmath.sqrt(self.Delta))/(2*self.a2)
                print ("L'equation a deux solutions : x1 = {0} et x2 ={1}".format(self.x11,self.x12))
            elif self.Delta == 0:
                self.x0 = (-self.b2/(2*self.a2))
                print ("L'equation a une solution: x = {}".format(self.x0))
            else:
                self.x1 = (-self.b2+math.sqrt(self.Delta))/(2*self.a2)
                self.x2 = (-self.b2-math.sqrt(self.Delta))/(2*self.a2)
                print ("L'equation a deux solutions : x1 = {0} et x2 ={1}".format(self.x1,self.x2))
                


    def graphique2(self):
        
        fig,axes=plt.subplots(4,2)
        x = np.linspace(-5,5,100)
        g = (self.a2*x**2)+self.b2*x+self.c2 
    

        for self.a2,self.b2,self.c2 in zip(self.a,self.b,self.c):

            axes[0,0].plot(x,g)
            axes[1,1].plot(x,g)
            axes[0,1].plot(x,g)
            axes[1,0].plot(x,g)


    

In [7]:

    

p = Polynome("Table1.txt")
p


    

    
Out[7]:





<__main__.Polynome at 0x7fe54fc64828>

In [8]:

    

p.Lire()


    

    




[1 2 3 4 5 6 7 8 9 10] [146 146 146 146 50 146 190 50 146 190] ['EtOH95%' nan nan nan 'EtOH95%' nan nan 'EtOH10%' nan nan]






    
Out[8]:






  

    

      

      
Experiment
      
Thickness
      
FoodSimulant
      
Cpo
      
K
      
Dp
      
RMSE
      
k
      
c4
    
  
  

    

      
0
      
1
      
146
      
EtOH95%
      
1157(+/-112)
      
52.0
      
1.950000e-13
      
1.5
      
0.000007
      
0.05
    
    

      
1
      
2
      
146
      
NaN
      
2440(+/-62)
      
35.0
      
1.970000e-13
      
3.0
      
0.000007
      
0.05
    
    

      
2
      
3
      
146
      
NaN
      
3152(+/-40)
      
24.0
      
2.000000e-13
      
2.6
      
0.000007
      
0.05
    
    

      
3
      
4
      
146
      
NaN
      
5950(+/-35)
      
0.5
      
2.000000e-13
      
2.3
      
0.000007
      
0.05
    
    

      
4
      
5
      
50
      
EtOH95%
      
2050(+/-110)
      
334.0
      
1.000000e-14
      
3.1
      
0.000007
      
0.05
    
    

      
5
      
6
      
146
      
NaN
      
2440(+/-62)
      
35.0
      
1.970000e-13
      
3.0
      
0.000007
      
0.05
    
    

      
6
      
7
      
190
      
NaN
      
2878(+/-115)
      
34.0
      
2.000000e-13
      
4.6
      
0.000007
      
0.05
    
    

      
7
      
8
      
50
      
EtOH10%
      
2050(+/-110)
      
0.0
      
0.000000e+00
      
0.0
      
0.000007
      
0.05
    
    

      
8
      
9
      
146
      
NaN
      
2440(+/-62)
      
0.0
      
0.000000e+00
      
0.0
      
0.000007
      
0.05
    
    

      
9
      
10
      
190
      
NaN
      
2878(+/-115)
      
0.0
      
0.000000e+00
      
0.0
      
0.000007
      
0.05
    
  

In [9]:

    

p.calcul()


    

    




a : [1 2 3 4 5 6 7 8 9 10],b : [146 146 146 146 50 146 190 50 146 190] et c : ['EtOH95%' nan nan nan 'EtOH95%' nan nan 'EtOH10%' nan nan]






    




---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-9-f83de2fb7f7c> in <module>()
----> 1 p.calcul()

<ipython-input-3-c8c05230e69d> in calcul(self)
     24 
     25         for self.a2, self.b2, self.c2 in zip(self.a,self.b, self.c):
---> 26             self.Delta = (self.b**2)-(4 * self.a * self.c)
     27             print ("Delta = {}".format(self.Delta))
     28             if self.Delta < 0:

TypeError: unsupported operand type(s) for -: 'int' and 'str'

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