Apr 6, 2025 · Apr 10, 2025 · Apr 17, 2025 · May 4, 2025 · May 7, 2025 · Apr 6, 2025
diff --git a/lib/matplotlib/cbook.py b/lib/matplotlib/cbook.py
    try:
        xm = np.ma.masked_where(~(np.isfinite(x)), x, copy=False)
    except TypeError:
        return x
        if len(x.dtype.descr) == 1:
            return x
        else:
            # in case of a dtype with multiple fields:
            try:
                mask = np.empty(x.shape, dtype=np.dtype('bool, '*len(x.dtype.descr)))
                for dd, dm in zip(x.dtype.descr, mask.dtype.descr):
                    mask[dm[0]] = ~(np.isfinite(x[dd[0]]))
                xm = np.ma.array(x, mask=mask, copy=False)
            except TypeError:
                return x
    return xm


diff --git a/lib/matplotlib/cm.py b/lib/matplotlib/cm.py
        return _colormaps[name]
    else:
        return _colormaps[name].resampled(lut)


 def _ensure_cmap(cmap):
    """
    Ensure that we have a `.Colormap` object.

    For internal use to preserve type stability of errors.

    Parameters
    ----------
    cmap : None, str, Colormap

        - if a `Colormap`, return it
        - if a string, look it up in mpl.colormaps
        - if None, look up the default color map in mpl.colormaps

    Returns
    -------
    Colormap

    """
    if isinstance(cmap, colors.Colormap):
        return cmap
    cmap_name = mpl._val_or_rc(cmap, "image.cmap")
    # use check_in_list to ensure type stability of the exception raised by
    # the internal usage of this (ValueError vs KeyError)
    if cmap_name not in _colormaps:
        _api.check_in_list(sorted(_colormaps), cmap=cmap_name)
    return mpl.colormaps[cmap_name]
Original file line number	Diff line number	Diff line change
Expand Up		@@ -690,7 +690,17 @@
		try:
		xm = np.ma.masked_where(~(np.isfinite(x)), x, copy=False)
		except TypeError:
		return x
		if len(x.dtype.descr) == 1:
		return x
		else:
		# in case of a dtype with multiple fields:
		try:
Copy link Member oscargusApr 6, 2025 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. Would be good to get at least partial coverage for this branch. Copy link Member oscargusApr 6, 2025 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. I haven't really been involved in this work nor understand how it works, but there is quite a bit of introduced code to deal with multiple datatypes? If this will be covered by tests/functionality in later PRs, that is fine, if not, please add tests for (most of) it. Copy link ContributorAuthor trygvradApr 6, 2025 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. I was asked to split#29221 into multiple PRs, and this PR is one of them. There is tests for this functionality in#29221 using the top-level plotting functions (axes.imshow() etc.) In my mind it is better to test using the top-level API, but if you wish I could add dedicated testing to this PR.
		mask = np.empty(x.shape, dtype=np.dtype('bool, '*len(x.dtype.descr)))
Check warning on line 698 in lib/matplotlib/cbook.py View check run for this annotation Codecov/ codecov/patch lib/matplotlib/cbook.py#L697-L698 `Added lines #L697 - L698 were not covered by tests`
Copy link Contributor anntzerApr 10, 2025 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. Could the dtype be e.g.`[("mask", bool, len(x.dtype.descr))]` (with a slightly different API)? Copy link ContributorAuthor trygvradApr 10, 2025 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. This is an interesting idea. I'll make a prototype and see if this would add unnecessary complexity somewhere else.
		for dd, dm in zip(x.dtype.descr, mask.dtype.descr):
		mask[dm[0]] = ~(np.isfinite(x[dd[0]]))
		xm = np.ma.array(x, mask=mask, copy=False)
Copy link Contributor anntzerApr 10, 2025 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. Do numpy masked arrays actually support struct arrays as mask, with possibly different masking of the fields? Copy link ContributorAuthor trygvradApr 10, 2025 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. I have found that this is the only way numpy supports masking dtypes with multiple fields, but I will see if`[("mask", bool, len(x.dtype.descr))]` as you suggest bellow is a reasonable approach to using a single mask.
		except TypeError:
		return x
Check warning on line 703 in lib/matplotlib/cbook.py View check run for this annotation Codecov/ codecov/patch lib/matplotlib/cbook.py#L700-L703 `Added lines #L700 - L703 were not covered by tests`
		return xm


Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -278,32 +278,3 @@ def get_cmap(name=None, lut=None):
		return _colormaps[name]
		else:
		return _colormaps[name].resampled(lut)


		def _ensure_cmap(cmap):
		"""
		Ensure that we have a `.Colormap` object.

		For internal use to preserve type stability of errors.

		Parameters
		----------
		cmap : None, str, Colormap

		- if a `Colormap`, return it
		- if a string, look it up in mpl.colormaps
		- if None, look up the default color map in mpl.colormaps

		Returns
		-------
		Colormap

		"""
		if isinstance(cmap, colors.Colormap):
		return cmap
		cmap_name = mpl._val_or_rc(cmap, "image.cmap")
		# use check_in_list to ensure type stability of the exception raised by
		# the internal usage of this (ValueError vs KeyError)
		if cmap_name not in _colormaps:
		_api.check_in_list(sorted(_colormaps), cmap=cmap_name)
		return mpl.colormaps[cmap_name]