New colormap normalizations: sqrt, arcsinh #1780
Conversation
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A question to the other developers: In the interest of preventing a combinatorial explosion by creating a class for each elementary mathematical function, would it be a better idea to have a class that will take a callable in its constructor, and have it normalise the data with respect to the underlying callable? For example, the user could call something like |
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That would be my preference too |
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@keflavich I am in agreement with you. The general 'take a callable' approach is more robust to changing requirements. |
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+1 for this (this being the callable method). |
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While preferable, It is not simple: the normalization classes also include the inverse function, else features like colorbar won't work right. |
| self.nthroot = nthroot | ||
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| def __call__(self, value, clip=None, midpoint=None): | ||
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PEP8 compliance: there should only be one blank line here.
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In principle, I think I'm in favour of this change. It definitely needs some tests though (they don't need to be pictorial). @keflavich - do you fancy trying to get this into v1.3? |
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Yes, sounds like a good idea. I'll work on it. I guess I should start with autopep8 and then work on tests. When's the 1.3 deadline |
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@keflavich autopep8 really doesn't work well: you might have to recheck everything by hand. |
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Closing as the PR seems to have stalled. I love the idea of a callable in a Norm constructor though - if somebody wants to take that forwards I'd be more than happy to review. Cheers, |
(this may be best to regard as a feature request with sample code included; I doubt my code conforms to mpl standards)
Related to #1355, #1204, and #632, I think there should be more default normalizations available in matplotlib. This pull request includes two that I've made use of: a sqrt/n'th root normalization and an arcsinh normalization. The former is good for emphasizing values near 1 (e.g., ratios of like values) and the latter is useful for high dynamic range images where the low scales are to be emphasized (e.g., images of stars with nebulosity around them); it largely serves the same purposes as SymLogNorm but with a different shape.
In part, I often want to reproduce figures made by ds9, which includes a wider range of default normalizations.
If there's an easier way to accomplish what I'm doing - e.g. just wrapping a function in some
Normalizesubclass - please let me know; I'm not up to date on new features of matplotlib unless they're thoroughly exampled in the gallery.