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  • xarray imshow and pcolormesh behave badly when the array does not contain values larger the BoundaryNorm vmax · 6 ✖

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  • CONTRIBUTOR · 6 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1464031031 https://github.com/pydata/xarray/issues/7014#issuecomment-1464031031 https://api.github.com/repos/pydata/xarray/issues/7014 IC_kwDOAMm_X85XQ1c3 veenstrajelmer 60435591 2023-03-10T16:07:26Z 2023-03-10T16:07:43Z CONTRIBUTOR

Thanks to @jklymak, there was an update in PR I created (https://github.com/pydata/xarray/pull/7553). @ghiggi with the code from this PR, your code shows identical plots (except for the first one, but that should be the case). Hopefully the PR can be merged somewhere soon.

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  xarray imshow and pcolormesh behave badly when the array does not contain values larger the BoundaryNorm vmax 1368027148
1448311848 https://github.com/pydata/xarray/issues/7014#issuecomment-1448311848 https://api.github.com/repos/pydata/xarray/issues/7014 IC_kwDOAMm_X85WU3wo veenstrajelmer 60435591 2023-02-28T14:46:32Z 2023-02-28T14:46:32Z CONTRIBUTOR

@ghiggi: If I understand it correctly, your issue/examplecode covers multiple issues. Since one subissue might be using norm instead levels, I would recommend trimming down your example code do only show the remaining vmax issue.

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  xarray imshow and pcolormesh behave badly when the array does not contain values larger the BoundaryNorm vmax 1368027148
1446128457 https://github.com/pydata/xarray/issues/7014#issuecomment-1446128457 https://api.github.com/repos/pydata/xarray/issues/7014 IC_kwDOAMm_X85WMitJ veenstrajelmer 60435591 2023-02-27T11:06:40Z 2023-02-27T11:18:17Z CONTRIBUTOR

The related issues https://github.com/pydata/xarray/issues/4061 and https://github.com/Deltares/xugrid/issues/49 are fixed by supplying levels=levels instead of norm=norm to ds.plot(), as suggested by https://github.com/pydata/xarray/pull/7553#discussion_r1117264787. However, I cannot judge if this also fixes the example from this issue, since the plots still all look different. However, commenting #da1.data[da1.data>=norm.vmax] = norm.vmax - 1 solves most of the differences. @ghiggi: could you check if this suggestion solves your issue indeed?

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  xarray imshow and pcolormesh behave badly when the array does not contain values larger the BoundaryNorm vmax 1368027148
1441530710 https://github.com/pydata/xarray/issues/7014#issuecomment-1441530710 https://api.github.com/repos/pydata/xarray/issues/7014 IC_kwDOAMm_X85V7ANW veenstrajelmer 60435591 2023-02-23T10:36:36Z 2023-02-23T15:55:21Z CONTRIBUTOR

I just combined @Huite's suggestion with splitting the if-statement. This works for both solving the issue and keeping the testcases in test_plot.py green. if levels is not None: cmap, newnorm = _build_discrete_cmap(cmap, levels, extend, filled) norm = newnorm if norm is None else norm if isinstance(norm, mpl.colors.BoundaryNorm): cmap, norm = _build_discrete_cmap(cmap, levels, extend, filled) This could replace this code: https://github.com/pydata/xarray/blob/1de881e5f5d4d7697403f9ab7686849ab02953bd/xarray/plot/utils.py#L307

However, a bit up in the code there is a if isinstance(norm, mpl.colors.BoundaryNorm) statement, which I guess could be combined. https://github.com/pydata/xarray/blob/1de881e5f5d4d7697403f9ab7686849ab02953bd/xarray/plot/utils.py#L277 if isinstance(norm, mpl.colors.BoundaryNorm): levels = norm.boundaries

I think it is a potential solution nevertheless, but some help is appreciated with the last steps. Also since the case of @ghiggi seems not to be solved with this fix. It does solve https://github.com/pydata/xarray/issues/4061 though.

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  xarray imshow and pcolormesh behave badly when the array does not contain values larger the BoundaryNorm vmax 1368027148
1412027546 https://github.com/pydata/xarray/issues/7014#issuecomment-1412027546 https://api.github.com/repos/pydata/xarray/issues/7014 IC_kwDOAMm_X85UKdSa Huite 13662783 2023-02-01T13:06:09Z 2023-02-01T13:06:45Z CONTRIBUTOR

Debugging this, @headtr1ck points correctly to _determine_cmap_params:

python if levels is not None or isinstance(norm, mpl.colors.BoundaryNorm): cmap, newnorm = _build_discrete_cmap(cmap, levels, extend, filled) norm = newnorm if norm is None else norm

The problem lies in the second line. In _build_discrete_cmap, a new cmap is returned with a different number of levels. However, if the original norm is not None, you end up with a mismatch, as the old norm expects the old cmap.

What then happens, is that the norm calls into the cmap. Calling into cmap doesn't do any checks whether the value is larger than N, it just takes the highest available value. The examples in #4061 show this quite clearly, but to illustrate:

```python import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np

data = np.arange(100).reshape((10, 10)) cmap = mpl.cm.get_cmap("viridis") print(cmap.N) # 256 boundaries = [0, 25, 50, 75, 100] norm = mpl.colors.BoundaryNorm(boundaries, cmap.N) fig, ax = plt.subplots() ax.imshow(data, norm=norm, cmap=cmap)

%%

colors = [cmap(i/255) for i in np.linspace(0, cmap.N, len(boundaries) - 1)] new_cmap, new_norm = mpl.colors.from_levels_and_colors(boundaries, colors) print(new_cmap.N) # 4 fig, ax = plt.subplots() ax.imshow(data, norm=new_norm, cmap=new_cmap)

%%

Mismatched

fig, ax = plt.subplots() ax.imshow(data, norm=norm, cmap=new_cmap)

%%

```

This is avoided here by removing the conditional in the second line, or just making sure both cmap and norm are replaced by their new values:

python if levels is not None or isinstance(norm, mpl.colors.BoundaryNorm): cmap, norm = _build_discrete_cmap(cmap, levels, extend, filled)

Then, the cmap and norm remain in sync.

However, when running the tests in test_plot.py, this gives a single questionable(?) failure:

```python def test_norm_sets_vmin_vmax(self) -> None: vmin = self.data.min() vmax = self.data.max()

    for norm, extend, levels in zip(
        [
            mpl.colors.Normalize(),
            mpl.colors.Normalize(),
            mpl.colors.Normalize(vmin + 0.1, vmax - 0.1),
            mpl.colors.Normalize(None, vmax - 0.1),
            mpl.colors.Normalize(vmin + 0.1, None),
        ],
        ["neither", "neither", "both", "max", "min"],
        [7, None, None, None, None],
    ):

        test_min = vmin if norm.vmin is None else norm.vmin
        test_max = vmax if norm.vmax is None else norm.vmax

        cmap_params = _determine_cmap_params(self.data, norm=norm, levels=levels)
        assert cmap_params["vmin"] is None
        assert cmap_params["vmax"] is None
        assert cmap_params["norm"].vmin == test_min
        assert cmap_params["norm"].vmax == test_max
        assert cmap_params["extend"] == extend
      assert cmap_params["norm"] == norm

E assert <matplotlib.colors.BoundaryNorm object at 0x000001C7A4CB07C0> == <matplotlib.colors.Normalize object at 0x000001C7A50C4760> ```

I don't understand why the conditional is there. At first sight, it doesn't make a lot of sense to create a new norm and cmap, but then take the original norm?

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  xarray imshow and pcolormesh behave badly when the array does not contain values larger the BoundaryNorm vmax 1368027148
1410362988 https://github.com/pydata/xarray/issues/7014#issuecomment-1410362988 https://api.github.com/repos/pydata/xarray/issues/7014 IC_kwDOAMm_X85UEG5s veenstrajelmer 60435591 2023-01-31T13:32:44Z 2023-01-31T13:32:44Z CONTRIBUTOR

Is there any update on this issue? I have been running into the same problem recently and am happy to see that this issue was already recognized by others.

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  xarray imshow and pcolormesh behave badly when the array does not contain values larger the BoundaryNorm vmax 1368027148

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