[FIXED] Try to get a multiple plot with different X-axes

Issue

I need to get something like this:

but I understand that I know I have to give a separate time for each time of the plot but I don't know how. There is also something wrong with my plot I think it plot more than one tiem and they are over each other.

Update:

With help of @Zephyr Now it look like this:

But it should be like this:

Here is the code:

import mpmath as mp
import numpy as np
import sympy
beta = 0.25;
L=[0.04980905361573844, 0.0208207352451072, 0.012368753716465475, 0.009117292529338674, 0.007461219338976698, 0.006510364609693688, 0.005899506135250773, 0.005485130537183343, 0.0051898472561455, 0.004961157595209418, 0.004778617403698715, 0.00463084459959999, 0.004510113095117956, 0.004410195593051274, 0.004330450690278247]
Lc=[1.7509008762765992, 0.14986486457338544, 0.03453912303580302, 0.014622269851256788, 0.00831141421008418, 0.005660123321843252, 0.004287823173522503, 0.0034922189865254395, 0.0029879534061896186, 0.0026315863522143363, 0.002367747989524076, 0.0021671535838986545, 0.0020116727106455415, 0.0018885896058416002, 0.0017939246597491803]
for k0 in [0.052,0.12,0.252,0.464,0.792,1.264,1.928,2.824,4,5.600,7.795,10.806,14.928,20.599,28.000]:
    t=np.linspace(k0,30,50)
    for i in range(len(L)):
        j0 = L[i];
        j1 = Lc[i];
        G = []
        def f(s):
            return s**(beta - 1)/(j0*s**beta + j1*sympy.gamma(beta + 1))

        for j in range(len(t)):
            G.append(mp.invertlaplace(f, t[j], method = 'dehoog', dps = 10, degree = 50))

        plt.plot(t,G)

The answer should be like that but I get this erorr

import numpy as np
import sympy
beta = 0.25;
L=[0.04980905361573844, 0.0208207352451072, 0.012368753716465475, 0.009117292529338674, 0.007461219338976698, 0.006510364609693688, 0.005899506135250773, 0.005485130537183343, 0.0051898472561455, 0.004961157595209418, 0.004778617403698715, 0.00463084459959999, 0.004510113095117956, 0.004410195593051274, 0.004330450690278247]
Lc=[1.7509008762765992, 0.14986486457338544, 0.03453912303580302, 0.014622269851256788, 0.00831141421008418, 0.005660123321843252, 0.004287823173522503, 0.0034922189865254395, 0.0029879534061896186, 0.0026315863522143363, 0.002367747989524076, 0.0021671535838986545, 0.0020116727106455415, 0.0018885896058416002, 0.0017939246597491803]
for k0 in [0.052,0.12,0.252,0.464,0.792,1.264,1.928,2.824,4,5.600,7.795,10.806,14.928,20.599,28.000]:
    t[k0]=np.linspace(k0,30,50)
    for i in range(len(L)):
        j0 = L[i];
        j1 = Lc[i];
        G = []
        def f(s):
            return s**(beta - 1)/(j0*s**beta + j1*sympy.gamma(beta + 1))

        for j in range(len(t[k0])):
            G.append(mp.invertlaplace(f, t[k0][j], method = 'dehoog', dps = 10, degree = 50))

        plt.plot(t[k0],G)

The function of dashed line is:

31.9279939766313*exp(-0.18*sympy.sqrt(7)/sympy.sqrt(t))

]

For each step should be done something like this.

Solution

You are looping one time too many, this is the reason why you are plotting more than one line overlapped.
You should re-structured your code in this way:

import mpmath as mp
import numpy as np
import sympy
import matplotlib.pyplot as plt


beta = 0.25
L = [0.04980905361573844, 0.0208207352451072, 0.012368753716465475, 0.009117292529338674, 0.007461219338976698, 0.006510364609693688, 0.005899506135250773, 0.005485130537183343, 0.0051898472561455, 0.004961157595209418, 0.004778617403698715, 0.00463084459959999, 0.004510113095117956, 0.004410195593051274, 0.004330450690278247]
Lc = [1.7509008762765992, 0.14986486457338544, 0.03453912303580302, 0.014622269851256788, 0.00831141421008418, 0.005660123321843252, 0.004287823173522503, 0.0034922189865254395, 0.0029879534061896186, 0.0026315863522143363, 0.002367747989524076, 0.0021671535838986545, 0.0020116727106455415, 0.0018885896058416002, 0.0017939246597491803]
K = [0.052, 0.12, 0.252, 0.464, 0.792, 1.264, 1.928, 2.824, 4, 5.600, 7.795, 10.806, 14.928, 20.599, 28.000]


def f(s):
    return s**(beta - 1)/(j0*s**beta + j1*sympy.gamma(beta + 1))


for k0, j0, j1 in zip(K, L, Lc):
    t = np.linspace(k0, 30, 50)
    G = []
    for j in range(len(t)):
        G.append(mp.invertlaplace(f, t[j], method = 'dehoog', dps = 10, degree = 50))

    plt.plot(t, G)

plt.show()

Thanks to zip you can iterate over K, L and Lc lists, picking one element from each lists at the same time; no need of i and j counters.

Answered By - Zephyr