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  • Colormap Normalisation Giving Unexpected/Incorrect Output · 4 ✖

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630280798 https://github.com/pydata/xarray/issues/4061#issuecomment-630280798 https://api.github.com/repos/pydata/xarray/issues/4061 MDEyOklzc3VlQ29tbWVudDYzMDI4MDc5OA== dcherian 2448579 2020-05-18T16:03:40Z 2020-05-18T16:03:40Z MEMBER

Seems like we should do whatever mpl does when given a norm and a colormap

 
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   Colormap Normalisation Giving Unexpected/Incorrect Output 618141254
629695308 https://github.com/pydata/xarray/issues/4061#issuecomment-629695308 https://api.github.com/repos/pydata/xarray/issues/4061 MDEyOklzc3VlQ29tbWVudDYyOTY5NTMwOA== mathause 10194086 2020-05-16T19:30:14Z 2020-05-16T19:30:14Z MEMBER

That's probably gonna need a extend="both"

 
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   Colormap Normalisation Giving Unexpected/Incorrect Output 618141254
629387430 https://github.com/pydata/xarray/issues/4061#issuecomment-629387430 https://api.github.com/repos/pydata/xarray/issues/4061 MDEyOklzc3VlQ29tbWVudDYyOTM4NzQzMA== mathause 10194086 2020-05-15T17:33:33Z 2020-05-15T17:33:33Z MEMBER

If you use python norm = colors.BoundaryNorm(boundaries=bounds, ncolors=9) it works. A new norm with ncolors=9 is built in _build_discrete_cmap - however, it is not used as norm is already defined:

https://github.com/pydata/xarray/blob/2542a63f6ebed1a464af7fc74b9f3bf302925803/xarray/plot/utils.py#L290-L292

The fix might be to use:

python if levels is not None or isinstance(norm, mpl.colors.BoundaryNorm): cmap, norm = _build_discrete_cmap(cmap, levels, extend, filled) this breaks one test which is probably fixable (it tests that the norm is not changed when it is given).

Note that mpl seems to use a LinearSegmentedColormap while xarray creates a ListedColormap.

 
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   Colormap Normalisation Giving Unexpected/Incorrect Output 618141254
629197481 https://github.com/pydata/xarray/issues/4061#issuecomment-629197481 https://api.github.com/repos/pydata/xarray/issues/4061 MDEyOklzc3VlQ29tbWVudDYyOTE5NzQ4MQ== mathause 10194086 2020-05-15T12:05:39Z 2020-05-15T12:05:39Z MEMBER

What should also work is img = ds['var'].plot(ax=ax, cmap=cmap, levels=levels)

 
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   Colormap Normalisation Giving Unexpected/Incorrect Output 618141254

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