Matplotlib subplots function: plot each row in a matrix in a subplot using for loop

Question

I have a function that returns a matrix with varying rows but constant columns (10) e.g (5, 10), (7, 10) , (20,10) etc.

Plotting the matrix using a constant x-axis matrix yields the following plot 1

Now, trying to use code to add each plot into a separate subplot

#the constant x-axis is
myx = [  6.89668072, 6.79190465,  6.48075998e+00 ,  5.97270071, 5.28316394 , 4.43310092,   3.44834036,  2.35880373,  1.19759604e+00 ,  4.22299899e-16]
#the y axis for this example is 
finalyy =[np.array([ 0.        ,  0.19801812,  0.32703622,  0.39731833,  0.43205176,
0.44652588,  0.44920819,  0.44348252,  0.430474  ,  0.40601885]), np.array([ 0.        ,  0.18017484,  0.30180713,  0.37321907,  0.41381173,
0.43625179,  0.44750785,  0.44986628,  0.44364735,  0.42256948]), np.array([ 0.        ,  0.16233156,  0.27657803,  0.3491198 ,  0.3955717 ,
0.4259777 ,  0.44580751,  0.45625005,  0.4568207 ,  0.43912011]), np.array([ 0.        ,  0.14448829,  0.25134894,  0.32502053,  0.37733167,
0.41570361,  0.44410717,  0.46263381,  0.46999405,  0.45567074]), np.array([ 0.        ,  0.12664501,  0.22611984,  0.30092126,  0.35909164,
0.40542952,  0.44240682,  0.46901757,  0.4831674 ,  0.47222137])]

#getting the value of rows in finalyy matrix
last = np.array(finalyy).shape
finalval = last[0]
m = 3 #used below to define number of subplots

#creating subplot numbers eg 331 332 333 334 335 etc
empty = []
for x in range (1,finalval+1):
    mat = (str(m)+ str(m)+str(x))
    empty.append(mat)
finalempty = np.asarray(empty)

#trying to plot each row in finalyy matrix whilst using each of the subplot index above
fig = plt.figure()
for row in finalyy:
    for j in finalempty:
      ax1 = fig.add_subplot(j)

    ax1.plot(myx,row,  'r-')

plt.tight_layout()
plt.show()

the code also generates this Plot 2

I want to plot each curve in a subplot using a function.

ImportanceOfBeingErnest · Accepted Answer · 2017-07-23 12:43:38Z

ax1.plot(myx,row, 'r-') plots all rows to ax1, which is the last of the axes.

Your problem can be simplified by using plt.subplots to create the subplots.

import numpy as np
import matplotlib.pyplot as plt
myx = [  6.89668072, 6.79190465,  6.48075998e+00 ,  5.97270071, 5.28316394 , 4.43310092,  
         3.44834036,  2.35880373,  1.19759604e+00 ,  4.22299899e-16]
#the y axis for this example is 
finalyy =[np.array([ 0.        ,  0.19801812,  0.32703622,  0.39731833,  0.43205176,
                    0.44652588,  0.44920819,  0.44348252,  0.430474  ,  0.40601885]), 
            np.array([ 0.        ,  0.18017484,  0.30180713,  0.37321907,  0.41381173,
                      0.43625179,  0.44750785,  0.44986628,  0.44364735,  0.42256948]), 
            np.array([ 0.        ,  0.16233156,  0.27657803,  0.3491198 ,  0.3955717 ,
                      0.4259777 ,  0.44580751,  0.45625005,  0.4568207 ,  0.43912011]), 
            np.array([ 0.        ,  0.14448829,  0.25134894,  0.32502053,  0.37733167,
                      0.41570361,  0.44410717,  0.46263381,  0.46999405,  0.45567074]),
            np.array([ 0.        ,  0.12664501,  0.22611984,  0.30092126,  0.35909164,
                      0.40542952,  0.44240682,  0.46901757,  0.4831674 ,  0.47222137])]

m = 3 #used below to define number of subplots

fig, axes = plt.subplots(nrows=m, ncols=m)
for ax, row in zip(axes.flatten(), finalyy):
    ax.plot(myx,row,  'r-')

# turn remaining axes off
for i in range(len(finalyy),m**2):
    axes.flatten()[i].axis("off")

plt.tight_layout()
plt.show()

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