How can I plot NaN values as a special color with imshow?

colormap, imshow, matplotlib, nan, python

Solution

With newer versions of Matplotlib, it is not necessary to use a masked array anymore.

For example, let’s generate an array where every 7th value is a NaN:

arr = np.arange(100, dtype=float).reshape(10, 10)
arr[~(arr % 7).astype(bool)] = np.nan

`.cm.get_cmap()` is replaced by `.colormaps.get_cmap('viridis')` in `matplotlib v3.7.0`

Set the color with `.set_bad`.

import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np

arr = np.arange(100, dtype=float).reshape(10, 10)
arr[~(arr % 7).astype(bool)] = np.nan

cmap = mpl.colormaps.get_cmap('viridis')  # viridis is the default colormap for imshow
cmap.set_bad(color='red')

plt.imshow(arr, cmap=cmap)

`.cm.get_cmap()` is deprecated

We can modify the current colormap and plot the array with the following lines:

current_cmap = mpl.cm.get_cmap()
current_cmap.set_bad(color='red')
plt.imshow(arr)

Problem

I am trying to use imshow in matplotlib to plot data as a heatmap, but some of the values are NaNs. I'd like the NaNs to be rendered as a special color not found in the colormap. example: ``` import numpy as np import matplotlib.pyplot as plt f = plt.figure() ax = f.add_subplot(111) a = np.arange(25).reshape((5,5)).astype(float) a[3,:] = np.nan ax.imshow(a, interpolation='nearest') f.canvas.draw() ``` The resultant image is unexpectedly all blue (the lowest color in the jet colormap). However, if I do the plotting like this: ``` ax.imshow(a, interpolation='nearest', vmin=0, vmax=24) ``` --then I get something better, but the NaN values are drawn the same color as vmin... Is there a graceful way that I can set NaNs to be drawn with a special color (eg: gray or transparent)?

Original source