Turn off axes in subplots

I have the following code:

import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import matplotlib.cm as cm

img = mpimg.imread("lena.jpg")

fig, axs = plt.subplots(2, 2)
axs[0,0].imshow(img, cmap = cm.Greys_r)
axs[0,0].set_title("Rank = 512")

rank = 128
new_img = prune_matrix(rank, img)
axs[0,1].imshow(new_img, cmap = cm.Greys_r)
axs[0,1].set_title("Rank = %s" %rank)

rank = 32
new_img = prune_matrix(rank, img)
axs[1,0].imshow(new_img, cmap = cm.Greys_r)
axs[1,0].set_title("Rank = %s" %rank)

rank = 16
new_img = prune_matrix(rank, img)
axs[1,1].imshow(new_img, cmap = cm.Greys_r)
axs[1,1].set_title("Rank = %s" %rank)

plt.show()

However, the result is pretty ugly because of the values on the axes:

How can I turn off axes values for all subplots simultaneously?

How to remove axis, legends, and white padding doesn't work because I don't know how to make it work with subplots.

• You can turn the Axes off by following the advice in Veedrac's comment (linking to here) with one small modification.
• Rather than using plt.axis('off'), use ax.axis('off') where ax is a matplotlib.axes object.
  • To do this, index each Axes, axs[0, 0].axis('off'), and so on for each subplot.
  • See Native Matplotlib interfaces for the difference between pyplot and Axes.
• The code below shows the result without the prune_matrix, which is not available.

import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import matplotlib.cm as cm
import matplotlib.cbook as cbook  # used for matplotlib sample image

# load readily available sample image
with cbook.get_sample_data('grace_hopper.jpg') as image_file:
    img = plt.imread(image_file)

# read a local file
# img = mpimg.imread("file.jpg")

fig, axs = plt.subplots(nrows=2, ncols=2, figsize=(8, 8), tight_layout=True)
axs[0, 0].imshow(img, cmap=cm.Greys_r)
axs[0, 0].set_title("Rank = 512")
axs[0, 0].axis("off")

axs[0, 1].imshow(img, cmap=cm.Greys_r)
axs[0, 1].set_title("Rank = %s" % 128)
axs[0, 1].axis("off")

axs[1, 0].imshow(img, cmap=cm.Greys_r)
axs[1, 0].set_title("Rank = %s" % 32)
axs[1, 0].axis("off")

axs[1, 1].imshow(img, cmap=cm.Greys_r)
axs[1, 1].set_title("Rank = %s" % 16)
axs[1, 1].axis("off")

plt.show()

Note: To turn off only the x or y axis you can use set_visible() e.g.:

axs[0, 0].xaxis.set_visible(False) # Hide only x axis

• Iterative approach

fig, axs = plt.subplots(nrows=2, ncols=2, figsize=(8, 8), tight_layout=True)

# convert the 2d array to 1d, which removes the need to iterate through i and j
axs = axs.flat
ranks = [512, 128, 32, 16]

# iterate through each Axes with the associate rank
for ax, rank in zip(axs, ranks):

    ax.imshow(img, cmap=cm.Greys_r)
    ax.set_title(f'Rank = {rank}')
    ax.axis('off')

plt.show()