Matplotlib：如何取消设置默认颜色图？

Question

I am showing images with matplotlib and applying some colormaps to the images. I've figured you can set a default colormap by something like

plt.set_cmap('jet')

and then that colormap will be applied every time when using plt.imshow()

But how about undoing that? If I want to show the original images again without any colormap? I haven't found in the docs anything about that, neither by quick googling so any help would be appreciated.

Thanks!

Answer 1

You can set the colormap using set_cmap as you are aware. This changes the colormap for all subsequent figures plotted. If you want to undo the changes you have made, simply go back to the matplotlib default colormap, which in matplotlib 2 is viridis .

However, there is also a cmap argument for imshow() which lets you change the colormap applied for an individual plot. This means you don't keep having to change the global colormap, however you would have to write this in every call to imshow()

import numpy as np
import matplotlib.pyplot as plt

data = np.random.randn(25).reshape(5,5)

fig, (ax1, ax2) = plt.subplots(1,2)

ax1.imshow(data)
ax1.set_title("Matplotlib default cmap")

ax2.imshow(data, cmap='jet')
ax2.set_title("jet cmap")

plt.show()

Which gives:

Answer 2

The command plt.set_cmap("jet") sets the colormap in the rcParams to be the "jet" colormap.

In order to get back the default colormap, you can set the cmap to the default colormap from the rcParamsDefault dictionary.

import matplotlib.pyplot as plt
print(plt.rcParams["image.cmap"]) # prints viridis

plt.set_cmap("jet")
print(plt.rcParams["image.cmap"]) # prints jet

plt.set_cmap(plt.rcParamsDefault["image.cmap"])
print(plt.rcParams["image.cmap"]) # prints viridis