In [43]:

    

import pandas as pd
import numpy as np
import math as mt


    

In [80]:

    

a7=results_comparison_7=pd.read_csv('results_comparison_7.csv')
t_7 = 34.06065011024475
error_7=sum((a7.iloc[:,4]-a17.iloc[:,4])/a17.iloc[:,4])/93
t=[34.06,38.70,79.41,122.06,179.87,257.69]


    

In [17]:

    

a9=results_comparison_9=pd.read_csv('results_comparison_9.csv')
t_9 = 38.70302104949951
error_9=sum((a9.iloc[:,4]-a17.iloc[:,4])/a17.iloc[:,4])/93


    

In [18]:

    

a11=results_comparison_11=pd.read_csv('results_comparison_11.csv')
t_11 = 79.40560698509216
error_11=sum((a11.iloc[:,4]-a17.iloc[:,4])/a17.iloc[:,4])/93


    

In [19]:

    

a13=results_comparison_13=pd.read_csv('results_comparison_13.csv')
t_13 = 122.063303232193
error_13=sum((a13.iloc[:,4]-a17.iloc[:,4])/a17.iloc[:,4])/93


    

In [20]:

    

a15=results_comparison_15=pd.read_csv('results_comparison_15.csv')
t_15 = 179.87312602996826
error_15=sum((a15.iloc[:,4]-a17.iloc[:,4])/a17.iloc[:,4])/93


    

In [21]:

    

a17=results_comparison_17=pd.read_csv('results_comparison_17.csv')
t_17 = 257.692342042923
error_17 = 0


    

In [165]:

    

plot = [[1e-7,error_9*100],[1e-9,error_9*100],[1e-11,error_11*100],[1e-13,error_13*100],[1e-15,error_15*100],[1e-17,0]]


    

In [166]:

    

import matplotlib.pyplot as plt
x=[mt.log10(1e-7),mt.log10(1e-9),mt.log10(1e-11),mt.log10(1e-13),mt.log10(1e-15),mt.log10(1e-17)]
y=[-error_7*100,-error_9*100,-error_11*100,-error_13*100,-error_15*100,0]
t


    

    
Out[166]:





[34.06, 38.7, 79.41, 122.06, 179.87, 257.69]

In [184]:

    

fig = plt.figure(figsize=(10, 8))
ax1 = fig.add_subplot(111)
lns1 = ax1.plot(x, y,'.g-' , label='atol_err')
ax2 = ax1.twinx()
lns2 = ax2.plot(x, t, '.b-', label='running_time')

lns = lns1+lns2
labs = [l.get_label() for l in lns]
ax1.legend(lns, labs, loc=9)

ax1.set_xlabel('abtol')
ax1.set_ylabel('error(%)')
ax2.set_ylabel('t(s)')

ax1.grid(linestyle = '--')

plt.show()


    

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