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)?

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, letâ€™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)
```

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