Colormap alpha #660
Colormap alpha #660
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Colormap alpha
| @@ -200,6 +200,8 @@ def _get_unsampled_image(self, A, image_extents, viewlim): | |||
| else: | |||
| if self._rgbacache is None: | |||
| x = self.to_rgba(self._A, bytes=True) | |||
| # premultiply the colors | |||
| x[...,0:3] *= x[...,3:4] / 255.0 | |||
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This line gave me an error, actually:
TypeError: Cannot cast ufunc multiply output from dtype('float64') to dtype('uint8') with casting rule 'same_kind'
I had to change it to
x[...,0:3] = np.uint8(x[...,0:3] * (x[...,3:4] / 255.0))But I'm not sure if x is guaranteed to be uint8.
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With "bytes=True" in the line above, it is guaranteed to be uint8.
It looks like what we might want to do here, though, is leave "bytes=False", premultiply, and then convert to uint8. Or that could all be done inside to_rgba, controlled by another kwarg. (to_rgba is already a little bit hard to follow, though.)
What numpy version are you using? Mike's version worked on mine (1.6.2.dev-396dbb9).
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I'm running github master ('2.0.0.dev-b817938').
I'm not quite sure what you have in mind. The following wouldn't work
x = self.to_rgba(self._A)
x[...,0:3] *= x[...,3:4] / 255.0
x = np.uint8(x)because x is not guaranteed to be float (right?). So would the alternative be something like
x = self.to_rgba(self._A)
rgb = x[...,0:3] * (x[...,3:4] / 255.0)
x = np.uint8(np.hstack(rgb, x[...,3]))There was a problem hiding this comment.
I see in your latest commits, you make sure that to_rgba returns normalized float values. Just confirm, this now works perfectly on my system.
Previously, it was possible for the bytes kwarg to be False, but the returned value to still be in bytes form (if the input x was in bytes). Now bytes=False guarantees the output will be floating point.
The earlier version of the premultiplication step did not work with numpy 2, and required additional dtype conversion steps in the common case of a colormapped image.
Expands LinearSegmentedColormap and ListedColormap to support full RGBA. This was prompted by a mailing list thread: http://www.mail-archive.com/matplotlib-users@lists.sourceforge.net/msg22983.html, continued with: http://www.mail-archive.com/matplotlib-devel@lists.sourceforge.net/msg08808.html. It is close to a patch proposed by @ivanov a couple years ago. A changeset by @mdboom is included to fix a bug in images with alpha less than 1.