Eric Firing schrieb:
John Hunter wrote:On Mon, Jul 21, 2008 at 3:12 AM, Klaus Zimmermann <[EMAIL PROTECTED]> wrote:Hello *,right now the NonUniformImage class in image.py uses numpy's asarray method. All similar classes instead use numpy.ma.asarray, thus allowing for masked images.
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Masked arrays are handled automatically as needed by the ScalarMappable.to_rgba() method.I just checked and I think your changes solve my problem well, obviously without introducing the potential problems you mentioned above. Thanks!What we really wanted, and the change I made throughout image.py, is to keep masked input as masked, and to ensure that anything else is a plain ndarray. This is now committed.
I was just confused by the different semantics: AxesImage : does masks, NxM array expects N, M dimensions. NonUniformImage : didn't do masks, NxM array expects N, M dimensions. PcolorImage: does masks, NxM array expects N+1, M+1 dimensions.Though I think the mask thingie in the NonUniformImage was simply a bug and I understand why PcolorImage is the way it is, it still stumped me at first sight. Also I find it difficult to understand the difference Pcolor and NonUniform since NonUniform does pseudo colors just as well? However if you feel this is just a lack of RTFM on my part please feel free to ignore.
I considered using np.asanyarray(A) but rejected it because it could fail for matrix input if any code is expecting iteration or single-indexing to return a 1-D array.Makes sense. But perhaps we should refactor that check into a (module) function of its own, as to avoid recundancy? I can do that if you want, or if you prefer a classmethod in AxesImage?
We lack examples to test masking of various types of input in the various types of image, though. Maybe I will add that later. Klaus, if you have any nice, small examples you would like to add to the mpl examples directory, that illustrate features or use cases that are not exercised in any present examples, please submit them.
Will do. Cheers, Klaus
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