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  • rjp23 · 3 ✖

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  • Colormap Normalisation Giving Unexpected/Incorrect Output · 3 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1456441488 https://github.com/pydata/xarray/issues/4061#issuecomment-1456441488 https://api.github.com/repos/pydata/xarray/issues/4061 IC_kwDOAMm_X85Wz4iQ rjp23 31730876 2023-03-06T16:20:20Z 2023-03-06T16:20:20Z NONE

I’m not sure that’s a solution if we argue that xarray should do what matplotlib does with the same keywords.

I can test if this “works” and will report back but it’s still not a fix.

 
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   Colormap Normalisation Giving Unexpected/Incorrect Output 618141254
629689922 https://github.com/pydata/xarray/issues/4061#issuecomment-629689922 https://api.github.com/repos/pydata/xarray/issues/4061 MDEyOklzc3VlQ29tbWVudDYyOTY4OTkyMg== rjp23 31730876 2020-05-16T18:44:55Z 2020-05-16T18:44:55Z NONE

Neither of those solutions seem to work for diverging colormaps where the data extends outside the range, i.e. the < and > data ends up with no colour.

 
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   Colormap Normalisation Giving Unexpected/Incorrect Output 618141254
628619788 https://github.com/pydata/xarray/issues/4061#issuecomment-628619788 https://api.github.com/repos/pydata/xarray/issues/4061 MDEyOklzc3VlQ29tbWVudDYyODYxOTc4OA== rjp23 31730876 2020-05-14T13:03:12Z 2020-05-14T13:03:12Z NONE

It might be useful to note here that my solution for now was just to pass the arrays directly to pcolormesh rather than going through the xarray plot interface.

i.e. I changed from

img = ds['var'].plot(ax=ax, cmap=cmap, norm=norm) to img = ax.pcolormesh(ds.x.values, ds.y.values, ds.tas.values, cmap=cmap, norm=norm)

 
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   Colormap Normalisation Giving Unexpected/Incorrect Output 618141254

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