On Mon, Jan 2, 2012 at 3:33 PM, Eric Firing <efir...@hawaii.edu> wrote:
> On 12/30/2011 01:57 PM, Paul Ivanov wrote:
>
>> Eric Firing, on 2011-12-27 15:31, wrote:
>>
>>> It looks like this is something I can fix by modifying ListedColormap.
>>> It is discarding the alpha values, and I don't think there is any reason
>>> it needs to do so.
>>>
>>
>> One of my first attempts at a contribution to matplotlib three
>> years ago was related to this. It was in reply to a similar
>> question on list, and I wrote a patch, but never saw it through
>> to inclusion because it wasn't something I needed.
>>
>> http://www.mail-archive.com/**matplotlib-users@lists.**
>> sourceforge.net/msg09216.html<http://www.mail-archive.com/matplotlib-users@lists.sourceforge.net/msg09216.html>
>>
>> I think it's a helpful starting point, as I include a discussion
>> on the limitation of mpl colormaps there.
>>
>
> I'm switching this to the devel list.
>
> Please try
> https://github.com/efiring/**matplotlib/tree/colormap_alpha<https://github.com/efiring/matplotlib/tree/colormap_alpha>
> which has changes similar to yours so that alpha is fully changeable in
> colormaps.
>
> I think this is going to be OK as far as the colormap end of things is
> concerned, but it turns up a new problem related to alpha in images, and
> reminds us of an old problem with alpha in agg, at least. The problems are
> illustrated in the attached modification of the custom_cmap.py example. I
> added a fourth panel for testing alpha. Look at the comments on the code
> for that panel, and try switching between pcolormesh and imshow.
> Pcolormesh basically works as expected, except for the prominent artifacts
> on patch boundaries (visible also in the colorbar for that panel). These
> boundary artifacts are the old problem. The new problem is that imshow with
> alpha in the colormap is completely wonky with a white background, but
> looks more normal with a black background--which is not so good if what you
> really want is a white background showing through the transparency.
>
> Eric
>
This is great! I had hacked together a custom colormap class and overrode
its __call__ method to get a similar effect. This solution is much more
elegant and general.
As for the imshow issue, it seems to be an issue with the "nearest"
interpolation method. The example copied below shows the result for three
different interpolation methods. The weird behavior only occurs when
interpolation is set to 'nearest' (I checked all other interpolation
methods, not just the 3 below). What's really strange is that
`interpolation='none'` gives the expected result, but in theory, 'none'
maps to the same interpolation function as 'nearest'. A quick scan of
matplotlib.image suggests that 'none' and 'nearest' share the same code
path, but I'm obviously missing something.
-Tony
#~~~~
import matplotlib.pyplot as plt
cdict = {'red': ((0.0, 0.0, 0.0),
(0.5, 0.8, 1.0),
(1.0, 0.4, 1.0)),
'green': ((0.0, 0.0, 0.0),
(0.5, 0.9, 0.9),
(1.0, 0.0, 0.0)),
'blue': ((0.0, 0.0, 0.4),
(0.5, 1.0, 0.8),
(1.0, 0.0, 0.0)),
'alpha': ((0.0, 1.0, 1.0),
(0.5, 0.3, 0.3),
(1.0, 1.0, 1.0))}
plt.register_cmap(name='BlueRedAlpha', data=cdict)
if __name__ == '__main__':
import numpy as np
w = 10
y = np.linspace(0, 2*np.pi, w+1)
Z = np.tile(y, (w+1, 1))
plt.rcParams['image.cmap'] = 'BlueRedAlpha'
f, axes = plt.subplots(ncols=3)
interp_method = ['none', 'bilinear', 'nearest']
for interp, ax in zip(interp_method, axes):
# Draw a line with low zorder so it will be behind the image.
ax.plot([0, w], [0, w], color='c', lw=20, zorder=-1)
ax.imshow(Z, interpolation=interp)
ax.set_title(interp)
plt.show()
#~~~~
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