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.


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')

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)?

Hrm, it appears I can use a masked array to do this:

masked_array = np.ma.array (a, mask=np.isnan(a))
cmap = matplotlib.cm.jet
ax.imshow(masked_array, interpolation='nearest', cmap=cmap)

This should suffice, though I’m still open to suggestions. :]

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

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

current_cmap = matplotlib.cm.get_cmap()

plot result