On 12 October 2010 14:57, Stefan Mauerberger
<stefan.mauerber...@mnet-online.de> wrote:
> I am having trouble with colormaps unsing pcolormesh. I would like to
> plot and colorise a seismic wave field above a map. Plotting works fine
> but I do not know how to bring transparency into colormaps. For negative
> values I want the coloration being blue then it should become
> transparent and the greatest value should be drawn red. I have tried a
> lot but without any success. As far as I can see, the keyarg alpha does
> not fit my needs at all.
>
> Do you have any suggestions for me?
You can't make the actual colormap contain transparent color entries,
but you can easily plot a masked array using a custom colormap. The
attached script based on
http://matplotlib.sourceforge.net/examples/pylab_examples/custom_cmap.html
should help you get what you want.
The important part of the script is to create a Numpy masked array to
exclude the regions you'd like to appear transparent:
cond = (-0.1 < Z) & (Z < 0.1)
Z_masked = np.ma.masked_where(cond, Z)
Cheers,
Scott
#!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap
cdict = {'red': ((0.0, 0.0, 0.0),
(0.25,0.0, 0.0),
(0.5, 0.8, 1.0),
(0.75,1.0, 1.0),
(1.0, 0.4, 1.0)),
'green': ((0.0, 0.0, 0.0),
(0.25,0.0, 0.0),
(0.5, 0.9, 0.9),
(0.75,0.0, 0.0),
(1.0, 0.0, 0.0)),
'blue': ((0.0, 0.0, 0.4),
(0.25,1.0, 1.0),
(0.5, 1.0, 0.8),
(0.75,0.0, 0.0),
(1.0, 0.0, 0.0))
}
blue_red = LinearSegmentedColormap('BlueRed', cdict)
x = np.arange(0, np.pi, 0.1)
y = np.arange(0, 2*np.pi, 0.1)
X, Y = np.meshgrid(x,y)
Z = np.cos(X) * np.sin(Y)
cond = (-0.1 < Z) & (Z < 0.1)
Z_masked = np.ma.masked_where(cond, Z)
plt.subplot(111)
## plt.imshow(Z_masked, cmap=blue_red, interpolation='nearest')
plt.pcolormesh(X, Y, Z_masked, cmap=blue_red)
plt.colorbar()
plt.show()
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