CODEWITHSUNDEEP
pythonmatplotlib
Lior
Lior

Reputation: 2019

Why does matplotlib.pyploy.imshow change it axes?

I try to plot images in different subplots, but for some reason the images' axes changes while plotting. To demonstrate this, in the following example I plot the images in a 4-by-2 grid of subplots, and I keep checking whether the axes of the first image stays the same:

import matplotlib.pyplot as plt
import numpy as np
_,ax = plt.subplots(4,2)
ims = [[None]*2]*4
for i in range(4):
     for j in range(2):
         plt.sca(ax[i][j])
         ims[i][j] = plt.imshow(np.random.rand(10,10))
         print(ims[0][0].axes is ax[0][0])

The output indicates that after the third image was plotted, the axes of the first image was changed:

True
True
False
False
False
False
False
False

Also, this turns out to be true:

ims[0][0].axes is ax[3][0]

output:

True

The reason this bothers me is that I want to update the images in future steps using ims[0][0].set_data(), but when I try to do that they only update in the axes ax[3][0]

How is behavior explained, and how can I work around it?

Upvotes: 2

Views: 152

Answers (1)

ImportanceOfBeingErnest
ImportanceOfBeingErnest

Reputation: 339220

Here is a workaround. You can create a single list and append your AxesImage objects to that list. This works as expected.

import matplotlib.pyplot as plt
import numpy as np
_,ax = plt.subplots(4,2)
ims2=[]

for i in range(4):
     for j in range(2):
         im = ax[i][j].imshow(np.zeros(shape=(10,10)), vmin=0, vmax = 1)
         ims2.append(im)
         print(ims2[0].axes is ax[0][0])

for i in range(4):
     for j in range(2):   
         ims2[i*2+j].set_data(np.random.rand(10,10))

plt.show()

I cannot well explain the problem, but is has to do with python lists.
Here, you are using

ims = [[None]*2]*4

which is not the same as

ims = [ [ None for j in range(2)] for i in range(4)]

although both commands print the same list. Using the second approach will work for you as well.

Upvotes: 2

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