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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') 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)?
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 cmap.set_bad('white',1.) 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() current_cmap.set_bad(color="red") plt.imshow(arr)