Jan 24, 2024 · Jan 24, 2024 · Jan 25, 2024 · Jan 30, 2024 · Jan 30, 2024 · Jan 30, 2024
diff --git a/doc/api/next_api_changes/behavior/27721-DS.rst b/doc/api/next_api_changes/behavior/27721-DS.rst
 Unit converters can now support units in images
 -----------------------------------------------

 `~.cm.ScalarMappable` can now contain data with units. This adds support for
 unit-ful data to be plotted using - `~.axes.Axes.imshow`, `~.axes.Axes.pcolor`,
 and `~.axes.Axes.pcolormesh`

 For this to be supported by third-party `~.units.ConversionInterface`,
 the `~.units.ConversionInterface.default_units` and
 `~.units.ConversionInterface.convert` methods must allow for the *axis*
 argument to be ``None``, and `~.units.ConversionInterface.convert` must be able to
 convert data of more than one dimension (e.g. when plotting images the data is 2D).

 If a conversion interface raises an error when given ``None`` or 2D data as described
 above, this error will be re-raised when a user tries to use one of the newly supported
 plotting methods with unit-ful data.

 If you have a custom conversion interface you want to forbid using with image data, the
 `~.units.ConversionInterface` methods that accept a ``units`` parameter should raise
 a `matplotlib.units.ConversionError` when given ``units=None``.
diff --git a/doc/users/next_whats_new/image_units.rst b/doc/users/next_whats_new/image_units.rst
 Unit support for images
 -----------------------
 This adds support for image data with units has been added to the following plotting
 methods:

 - `~.axes.Axes.imshow`
 - `~.axes.Axes.pcolor`
 - `~.axes.Axes.pcolormesh`

 If the data has units, the ``vmin`` and ``vmax`` units to these methods can also have
 units, and if you add a colorbar the ``levels`` argument to ``colorbar`` can also
 have units.
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
 from numpy import ma

 import matplotlib as mpl
 import matplotlib.cm as cm
 import matplotlib.category  # Register category unit converter as side effect.
 import matplotlib.cbook as cbook
 import matplotlib.collections as mcoll
        self.add_image(im)
        return im

    @staticmethod
    def _convert_C_units(C):
        """
        Remove any units attached to C, and return the units and converter used to do
        the conversion.
        """
        sm = cm.ScalarMappable()
        C = sm._strip_units(C)
        converter = sm._converter
        units = sm._units

        C = np.asanyarray(C)
        C = cbook.safe_masked_invalid(C, copy=True)
        return C, units, converter

    def _pcolorargs(self, funcname, *args, shading='auto', **kwargs):
        # - create X and Y if not present;
        # - reshape X and Y as needed if they are 1-D;
        # - check for proper sizes based on `shading` kwarg;
        # - reset shading if shading='auto' to flat or nearest
        #   depending on size;
        # - if C has units, get the converter

        _valid_shading = ['gouraud', 'nearest', 'flat', 'auto']
        try:
            shading = 'auto'

        if len(args) == 1:
            C = np.asanyarray(args[0])
            C, units, converter = self._convert_C_units(args[0])
            nrows, ncols = C.shape[:2]
            if shading in ['gouraud', 'nearest']:
                X, Y = np.meshgrid(np.arange(ncols), np.arange(nrows))
            else:
                X, Y = np.meshgrid(np.arange(ncols + 1), np.arange(nrows + 1))
                shading = 'flat'
            C = cbook.safe_masked_invalid(C, copy=True)
            return X, Y, C, shading
            return X, Y, C, shading, units, converter

        if len(args) == 3:
            # Check x and y for bad data...
            C = np.asanyarray(args[2])
            C, units, converter = self._convert_C_units(args[2])
            # unit conversion allows e.g. datetime objects as axis values
            X, Y = args[:2]
            X, Y = self._process_unit_info([("x", X), ("y", Y)], kwargs)
                shading = 'flat'

        C = cbook.safe_masked_invalid(C, copy=True)
        return X, Y, C, shading
        return X, Y, C, shading, units, converter

    @_preprocess_data()
    @_docstring.dedent_interpd
        if shading is None:
            shading = mpl.rcParams['pcolor.shading']
        shading = shading.lower()
        X, Y, C, shading = self._pcolorargs('pcolor', *args, shading=shading,
                                            kwargs=kwargs)
        X, Y, C, shading, units, converter = self._pcolorargs(
            'pcolor', *args, shading=shading, kwargs=kwargs
        )
        linewidths = (0.25,)
        if 'linewidth' in kwargs:
            kwargs['linewidths'] = kwargs.pop('linewidth')

        collection = mcoll.PolyQuadMesh(
            coords, array=C, cmap=cmap, norm=norm, alpha=alpha, **kwargs)
        collection._units = units
        collection._converter = converter
        collection._scale_norm(norm, vmin, vmax)

        # Transform from native to data coordinates?
        shading = shading.lower()
        kwargs.setdefault('edgecolors', 'none')

        X, Y, C, shading = self._pcolorargs('pcolormesh', *args,
                                            shading=shading, kwargs=kwargs)
        X, Y, C, shading, units, converter = self._pcolorargs(
            'pcolormesh', *args, shading=shading, kwargs=kwargs
        )
        coords = np.stack([X, Y], axis=-1)

        kwargs.setdefault('snap', mpl.rcParams['pcolormesh.snap'])

        collection = mcoll.QuadMesh(
            coords, antialiased=antialiased, shading=shading,
            array=C, cmap=cmap, norm=norm, alpha=alpha, **kwargs)
        collection._units = units
        collection._converter = converter
        collection._scale_norm(norm, vmin, vmax)

        coords = coords.reshape(-1, 2)  # flatten the grid structure; keep x, y
diff --git a/lib/matplotlib/category.py b/lib/matplotlib/category.py
            object storing string to integer mapping
        """
        # the conversion call stack is default_units -> axis_info -> convert
        if axis is None:
            return UnitData(data)
        if axis.units is None:
            axis.set_units(UnitData(data))
        else:
        TypeError
            If elements in *data* are neither str nor bytes.
        """
        data = np.atleast_1d(np.array(data, dtype=object))
        data = np.atleast_1d(np.array(data, dtype=object).ravel())
        # check if convertible to number:
        convertible = True
        for val in OrderedDict.fromkeys(data):
diff --git a/lib/matplotlib/cm.py b/lib/matplotlib/cm.py
 from matplotlib import _api, colors, cbook, scale
 from matplotlib._cm import datad
 from matplotlib._cm_listed import cmaps as cmaps_listed
 import matplotlib.units as munits


 _LUTSIZE = mpl.rcParams['image.lut']
            The colormap used to map normalized data values to RGBA colors.
        """
        self._A = None
        self._units = None
        self._converter = None
        self._norm = None  # So that the setter knows we're initializing.
        self.set_norm(norm)  # The Normalize instance of this ScalarMappable.
        self.cmap = None  # So that the setter knows we're initializing.
        rgba = self.cmap(x, alpha=alpha, bytes=bytes)
        return rgba

    def _strip_units(self, A):
        """
        Remove units from A, and save the units and converter used to do the conversion.
        """
        self._converter = munits.registry.get_converter(A)
        if self._converter is None:
            self._units = None
            return A

        try:
            self._units = self._converter.default_units(A, None)
        except Exception as e:
            if isinstance(e, munits.ConversionError):
                raise e

            raise RuntimeError(
                f'{self._converter} failed when trying to return the default units for '
                'this image. This may be because support has not been '
                'implemented for `axis=None` in the default_units() method.'
            ) from e

        try:
            A = self._converter.convert(A, self._units, None)
        except Exception as e:
            if isinstance(e, munits.ConversionError):
                raise e

            raise munits.ConversionError(
                f'{self._converter} failed when trying to convert the units for this '
                'image. This may be because support has not been implemented '
                'for `axis=None` in the convert() method.'
            ) from e

        return A

    def set_array(self, A):
        """
        Set the value array from array-like *A*.
        if A is None:
            self._A = None
            return

        A = self._strip_units(A)
        A = cbook.safe_masked_invalid(A, copy=True)
        if not np.can_cast(A.dtype, float, "same_kind"):
            raise TypeError(f"Image data of dtype {A.dtype} cannot be "
                vmin, vmax = vmin
            except (TypeError, ValueError):
                pass
        if vmin is not None:
            self.norm.vmin = colors._sanitize_extrema(vmin)
        if vmax is not None:
            self.norm.vmax = colors._sanitize_extrema(vmax)

        def _process_lim(lim):
            if self._converter is not None:
                lim = self._converter.convert(lim, self._units, axis=None)
            return colors._sanitize_extrema(lim)

        self.norm.vmin = _process_lim(vmin)
        self.norm.vmax = _process_lim(vmax)

    def get_alpha(self):
        """
diff --git a/lib/matplotlib/collections.py b/lib/matplotlib/collections.py
        self._widths = 0.5 * np.asarray(widths).ravel()
        self._heights = 0.5 * np.asarray(heights).ravel()
        self._angles = np.deg2rad(angles).ravel()
        self._units = units
        self._length_units = units
        self.set_transform(transforms.IdentityTransform())
        self._transforms = np.empty((0, 3, 3))
        self._paths = [mpath.Path.unit_circle()]
        ax = self.axes
        fig = self.figure

        if self._units == 'xy':
        if self._length_units == 'xy':
            sc = 1
        elif self._units == 'x':
        elif self._length_units == 'x':
            sc = ax.bbox.width / ax.viewLim.width
        elif self._units == 'y':
        elif self._length_units == 'y':
            sc = ax.bbox.height / ax.viewLim.height
        elif self._units == 'inches':
        elif self._length_units == 'inches':
            sc = fig.dpi
        elif self._units == 'points':
        elif self._length_units == 'points':
            sc = fig.dpi / 72.0
        elif self._units == 'width':
        elif self._length_units == 'width':
            sc = ax.bbox.width
        elif self._units == 'height':
        elif self._length_units == 'height':
            sc = ax.bbox.height
        elif self._units == 'dots':
        elif self._length_units == 'dots':
            sc = 1.0
        else:
            raise ValueError(f'Unrecognized units: {self._units!r}')
            raise ValueError(f'Unrecognized units: {self._length_units!r}')

        self._transforms = np.zeros((len(self._widths), 3, 3))
        widths = self._widths * sc
        self._transforms[:, 2, 2] = 1.0

        _affine = transforms.Affine2D
        if self._units == 'xy':
        if self._length_units == 'xy':
            m = ax.transData.get_affine().get_matrix().copy()
            m[:2, 2:] = 0
            self.set_transform(_affine(m))
diff --git a/lib/matplotlib/colorbar.py b/lib/matplotlib/colorbar.py
                 drawedges=False,
                 extendfrac=None,
                 extendrect=False,
                 label='',
                 label=None,
                 location=None,
                 ):

                orientation) if location is None else location
        self.ticklocation = ticklocation

        self.set_label(label)
        if label is not None:
            self.set_label(label)
        self._reset_locator_formatter_scale()
        self._set_units_from_mappable()

        if ticks is not None and self._converter is not None:
            ticks = self._converter.convert(ticks, self._units, self._long_axis())

        if np.iterable(ticks):
            self._locator = ticker.FixedLocator(ticks, nbins=len(ticks))
 else:
 elif isinstance(ticks, ticker.Locator):
            self._locator = ticks

        if isinstance(format, str):
            elif self.orientation == 'vertical':
                self.norm.vmin, self.norm.vmax = points[:, 1]

    def _set_units_from_mappable(self):
        """
        Set the colorbar locator and formatter if the mappable has units.
        """
        self._units = self.mappable._units
        self._converter = self.mappable._converter
        if self._converter is not None:

            axis = self._long_axis()
            info = self._converter.axisinfo(self._units, axis)

            if info is not None:
                if info.majloc is not None:
                    self.locator = info.majloc
                if info.minloc is not None:
                    self.minorlocator = info.minloc
                if info.majfmt is not None:
                    self.formatter = info.majfmt
                if info.minfmt is not None:
                    self.minorformatter = info.minfmt


 ColorbarBase = Colorbar  # Backcompat API

diff --git a/lib/matplotlib/colorbar.pyi b/lib/matplotlib/colorbar.pyi
        drawedges: bool = ...,
        extendfrac: Literal["auto"] | float | Sequence[float] | None = ...,
        extendrect: bool = ...,
        label: str = ...,
        label: str| None= ...,
        location: Literal["left", "right", "top", "bottom"] | None = ...
    ) -> None: ...
    @property
diff --git a/lib/matplotlib/image.py b/lib/matplotlib/image.py
        """
        if isinstance(A, PIL.Image.Image):
            A = pil_to_array(A)  # Needed e.g. to apply png palette.

        A = self._strip_units(A)
        self._A = self._normalize_image_array(A)
        self._imcache = None
        self.stale = True
            (M, N) `~numpy.ndarray` or masked array of values to be
            colormapped, or (M, N, 3) RGB array, or (M, N, 4) RGBA array.
        """
        A = self._strip_units(A)
        A = self._normalize_image_array(A)
        x = np.array(x, np.float32)
        y = np.array(y, np.float32)
            - (M, N, 3): RGB array
            - (M, N, 4): RGBA array
        """
        A = self._strip_units(A)
        A = self._normalize_image_array(A)
        x = np.arange(0., A.shape[1] + 1) if x is None else np.array(x, float).ravel()
        y = np.arange(0., A.shape[0] + 1) if y is None else np.array(y, float).ravel()
diff --git a/lib/matplotlib/tests/baseline_images/test_units/mappable_units.png b/lib/matplotlib/tests/baseline_images/test_units/mappable_units.png
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1,20 @@
		Unit converters can now support units in images
		-----------------------------------------------

		`~.cm.ScalarMappable` can now contain data with units. This adds support for
		unit-ful data to be plotted using - `~.axes.Axes.imshow`, `~.axes.Axes.pcolor`,
		and `~.axes.Axes.pcolormesh`

		For this to be supported by third-party `~.units.ConversionInterface`,
		the `~.units.ConversionInterface.default_units` and
		`~.units.ConversionInterface.convert` methods must allow for the axis
		argument to be ``None``, and `~.units.ConversionInterface.convert` must be able to
		convert data of more than one dimension (e.g. when plotting images the data is 2D).

		If a conversion interface raises an error when given ``None`` or 2D data as described
		above, this error will be re-raised when a user tries to use one of the newly supported
		plotting methods with unit-ful data.

		If you have a custom conversion interface you want to forbid using with image data, the
		`~.units.ConversionInterface` methods that accept a ``units`` parameter should raise
		a `matplotlib.units.ConversionError` when given ``units=None``.
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1,12 @@
		Unit support for images
		-----------------------
		This adds support for image data with units has been added to the following plotting
		methods:

		- `~.axes.Axes.imshow`
		- `~.axes.Axes.pcolor`
		- `~.axes.Axes.pcolormesh`

		If the data has units, the ``vmin`` and ``vmax`` units to these methods can also have
		units, and if you add a colorbar the ``levels`` argument to ``colorbar`` can also
		have units.
Original file line number	Diff line number	Diff line change
Expand Up		@@ -8,6 +8,7 @@
		from numpy import ma

		import matplotlib as mpl
		import matplotlib.cm as cm
		import matplotlib.category # Register category unit converter as side effect.
		import matplotlib.cbook as cbook
		import matplotlib.collections as mcoll
Expand DownExpand Up		@@ -5838,12 +5839,28 @@ def imshow(self, X, cmap=None, norm=None, *, aspect=None,
		self.add_image(im)
		return im

		@staticmethod
		def _convert_C_units(C):
		"""
		Remove any units attached to C, and return the units and converter used to do
		the conversion.
		"""
		sm = cm.ScalarMappable()
		C = sm._strip_units(C)
		converter = sm._converter
		units = sm._units

		C = np.asanyarray(C)
		C = cbook.safe_masked_invalid(C, copy=True)
		return C, units, converter

		def _pcolorargs(self, funcname, args, shading='auto', *kwargs):
		# - create X and Y if not present;
		# - reshape X and Y as needed if they are 1-D;
		# - check for proper sizes based on `shading` kwarg;
		# - reset shading if shading='auto' to flat or nearest
		# depending on size;
		# - if C has units, get the converter

		_valid_shading = ['gouraud', 'nearest', 'flat', 'auto']
		try:
Expand All		@@ -5855,19 +5872,19 @@ def _pcolorargs(self, funcname, args, shading='auto', *kwargs):
		shading = 'auto'

		if len(args) == 1:
		C = np.asanyarray(args[0])
		C, units, converter = self._convert_C_units(args[0])
		nrows, ncols = C.shape[:2]
		if shading in ['gouraud', 'nearest']:
		X, Y = np.meshgrid(np.arange(ncols), np.arange(nrows))
		else:
		X, Y = np.meshgrid(np.arange(ncols + 1), np.arange(nrows + 1))
		shading = 'flat'
		C = cbook.safe_masked_invalid(C, copy=True)
		return X, Y, C, shading
		return X, Y, C, shading, units, converter

		if len(args) == 3:
		# Check x and y for bad data...
		C = np.asanyarray(args[2])
		C, units, converter = self._convert_C_units(args[2])
		# unit conversion allows e.g. datetime objects as axis values
		X, Y = args[:2]
		X, Y = self._process_unit_info([("x", X), ("y", Y)], kwargs)
Expand DownExpand Up		@@ -5948,7 +5965,7 @@ def _interp_grid(X):
		shading = 'flat'

		C = cbook.safe_masked_invalid(C, copy=True)
		return X, Y, C, shading
		return X, Y, C, shading, units, converter

		@_preprocess_data()
		@_docstring.dedent_interpd
Expand DownExpand Up		@@ -6100,8 +6117,9 @@ def pcolor(self, *args, shading=None, alpha=None, norm=None, cmap=None,
		if shading is None:
		shading = mpl.rcParams['pcolor.shading']
		shading = shading.lower()
		X, Y, C, shading = self._pcolorargs('pcolor', *args, shading=shading,
		kwargs=kwargs)
		X, Y, C, shading, units, converter = self._pcolorargs(
		'pcolor', *args, shading=shading, kwargs=kwargs
		)
		linewidths = (0.25,)
		if 'linewidth' in kwargs:
		kwargs['linewidths'] = kwargs.pop('linewidth')
Expand DownExpand Up		@@ -6137,6 +6155,8 @@ def pcolor(self, *args, shading=None, alpha=None, norm=None, cmap=None,

		collection = mcoll.PolyQuadMesh(
		coords, array=C, cmap=cmap, norm=norm, alpha=alpha, **kwargs)
		collection._units = units
		collection._converter = converter
		collection._scale_norm(norm, vmin, vmax)

		# Transform from native to data coordinates?
Expand DownExpand Up		@@ -6356,15 +6376,18 @@ def pcolormesh(self, *args, alpha=None, norm=None, cmap=None, vmin=None,
		shading = shading.lower()
		kwargs.setdefault('edgecolors', 'none')

		X, Y, C, shading = self._pcolorargs('pcolormesh', *args,
		shading=shading, kwargs=kwargs)
		X, Y, C, shading, units, converter = self._pcolorargs(
		'pcolormesh', *args, shading=shading, kwargs=kwargs
		)
		coords = np.stack([X, Y], axis=-1)

		kwargs.setdefault('snap', mpl.rcParams['pcolormesh.snap'])

		collection = mcoll.QuadMesh(
		coords, antialiased=antialiased, shading=shading,
		array=C, cmap=cmap, norm=norm, alpha=alpha, **kwargs)
		collection._units = units
		collection._converter = converter
		collection._scale_norm(norm, vmin, vmax)

		coords = coords.reshape(-1, 2) # flatten the grid structure; keep x, y
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -101,6 +101,8 @@ def default_units(data, axis):
		object storing string to integer mapping
		"""
		# the conversion call stack is default_units -> axis_info -> convert
		if axis is None:
		return UnitData(data)
		if axis.units is None:
		axis.set_units(UnitData(data))
		else:
Expand DownExpand Up		@@ -208,7 +210,7 @@ def update(self, data):
		TypeError
		If elements in data are neither str nor bytes.
		"""
		data = np.atleast_1d(np.array(data, dtype=object))
		data = np.atleast_1d(np.array(data, dtype=object).ravel())
		# check if convertible to number:
		convertible = True
		for val in OrderedDict.fromkeys(data):
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -24,6 +24,7 @@
		from matplotlib import _api, colors, cbook, scale
		from matplotlib._cm import datad
		from matplotlib._cm_listed import cmaps as cmaps_listed
		import matplotlib.units as munits


		_LUTSIZE = mpl.rcParams['image.lut']
Expand DownExpand Up		@@ -283,6 +284,8 @@ def __init__(self, norm=None, cmap=None):
		The colormap used to map normalized data values to RGBA colors.
		"""
		self._A = None
		self._units = None
		self._converter = None
		self._norm = None # So that the setter knows we're initializing.
		self.set_norm(norm) # The Normalize instance of this ScalarMappable.
		self.cmap = None # So that the setter knows we're initializing.
Expand DownExpand Up		@@ -393,6 +396,41 @@ def to_rgba(self, x, alpha=None, bytes=False, norm=True):
		rgba = self.cmap(x, alpha=alpha, bytes=bytes)
		return rgba

		def _strip_units(self, A):
		"""
		Remove units from A, and save the units and converter used to do the conversion.
		"""
		self._converter = munits.registry.get_converter(A)
		if self._converter is None:
		self._units = None
		return A

		try:
		self._units = self._converter.default_units(A, None)
		except Exception as e:
		if isinstance(e, munits.ConversionError):
		raise e

		raise RuntimeError(
		f'{self._converter} failed when trying to return the default units for '
		'this image. This may be because support has not been '
		'implemented for `axis=None` in the default_units() method.'
		) from e

		try:
		A = self._converter.convert(A, self._units, None)
		except Exception as e:
		if isinstance(e, munits.ConversionError):
		raise e

		raise munits.ConversionError(
		f'{self._converter} failed when trying to convert the units for this '
		'image. This may be because support has not been implemented '
		'for `axis=None` in the convert() method.'
		) from e

		return A

		def set_array(self, A):
		"""
		Set the value array from array-like A.
Expand All		@@ -408,7 +446,7 @@ def set_array(self, A):
		if A is None:
		self._A = None
		return

		A = self._strip_units(A)
		A = cbook.safe_masked_invalid(A, copy=True)
		if not np.can_cast(A.dtype, float, "same_kind"):
		raise TypeError(f"Image data of dtype {A.dtype} cannot be "
Expand DownExpand Up		@@ -458,10 +496,14 @@ def set_clim(self, vmin=None, vmax=None):
		vmin, vmax = vmin
		except (TypeError, ValueError):
		pass
		if vmin is not None:
		self.norm.vmin = colors._sanitize_extrema(vmin)
		if vmax is not None:
		self.norm.vmax = colors._sanitize_extrema(vmax)

		def _process_lim(lim):
		if self._converter is not None:
		lim = self._converter.convert(lim, self._units, axis=None)
		return colors._sanitize_extrema(lim)

		self.norm.vmin = _process_lim(vmin)
		self.norm.vmax = _process_lim(vmax)

		def get_alpha(self):
		"""
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -1751,7 +1751,7 @@ def __init__(self, widths, heights, angles, , units='points', *kwargs):
		self._widths = 0.5 * np.asarray(widths).ravel()
		self._heights = 0.5 * np.asarray(heights).ravel()
		self._angles = np.deg2rad(angles).ravel()
		self._units = units
		self._length_units = units
		self.set_transform(transforms.IdentityTransform())
		self._transforms = np.empty((0, 3, 3))
		self._paths = [mpath.Path.unit_circle()]
Expand All		@@ -1762,24 +1762,24 @@ def _set_transforms(self):
		ax = self.axes
		fig = self.figure

		if self._units == 'xy':
		if self._length_units == 'xy':
		sc = 1
		elif self._units == 'x':
		elif self._length_units == 'x':
		sc = ax.bbox.width / ax.viewLim.width
		elif self._units == 'y':
		elif self._length_units == 'y':
		sc = ax.bbox.height / ax.viewLim.height
		elif self._units == 'inches':
		elif self._length_units == 'inches':
		sc = fig.dpi
		elif self._units == 'points':
		elif self._length_units == 'points':
		sc = fig.dpi / 72.0
		elif self._units == 'width':
		elif self._length_units == 'width':
		sc = ax.bbox.width
		elif self._units == 'height':
		elif self._length_units == 'height':
		sc = ax.bbox.height
		elif self._units == 'dots':
		elif self._length_units == 'dots':
		sc = 1.0
		else:
		raise ValueError(f'Unrecognized units: {self._units!r}')
		raise ValueError(f'Unrecognized units: {self._length_units!r}')

		self._transforms = np.zeros((len(self._widths), 3, 3))
		widths = self._widths * sc
Expand All		@@ -1793,7 +1793,7 @@ def _set_transforms(self):
		self._transforms[:, 2, 2] = 1.0

		_affine = transforms.Affine2D
		if self._units == 'xy':
		if self._length_units == 'xy':
		m = ax.transData.get_affine().get_matrix().copy()
		m[:2, 2:] = 0
		self.set_transform(_affine(m))
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -291,7 +291,7 @@ def __init__(self, ax, mappable=None, *, cmap=None,
		drawedges=False,
		extendfrac=None,
		extendrect=False,
		label='',
		label=None,
		location=None,
		):

Expand DownExpand Up		@@ -391,12 +391,17 @@ def __init__(self, ax, mappable=None, *, cmap=None,
		orientation) if location is None else location
		self.ticklocation = ticklocation

		self.set_label(label)
		if label is not None:
		self.set_label(label)
		self._reset_locator_formatter_scale()
		self._set_units_from_mappable()

		if ticks is not None and self._converter is not None:
		ticks = self._converter.convert(ticks, self._units, self._long_axis())

		if np.iterable(ticks):
		self._locator = ticker.FixedLocator(ticks, nbins=len(ticks))
		else:
		elif isinstance(ticks, ticker.Locator):
		self._locator = ticks

		if isinstance(format, str):
Expand DownExpand Up		@@ -1331,6 +1336,27 @@ def drag_pan(self, button, key, x, y):
		elif self.orientation == 'vertical':
		self.norm.vmin, self.norm.vmax = points[:, 1]

		def _set_units_from_mappable(self):
		"""
		Set the colorbar locator and formatter if the mappable has units.
		"""
		self._units = self.mappable._units
		self._converter = self.mappable._converter
		if self._converter is not None:

		axis = self._long_axis()
		info = self._converter.axisinfo(self._units, axis)

		if info is not None:
		if info.majloc is not None:
		self.locator = info.majloc
		if info.minloc is not None:
		self.minorlocator = info.minloc
		if info.majfmt is not None:
		self.formatter = info.majfmt
		if info.minfmt is not None:
		self.minorformatter = info.minfmt


		ColorbarBase = Colorbar # Backcompat API

Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -59,7 +59,7 @@ class Colorbar:
		drawedges: bool = ...,
		extendfrac: Literal["auto"] \| float \| Sequence[float] \| None = ...,
		extendrect: bool = ...,
		label: str = ...,
		label: str\| None= ...,
		location: Literal["left", "right", "top", "bottom"] \| None = ...
		) -> None: ...
		@property
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -726,6 +726,8 @@ def set_data(self, A):
		"""
		if isinstance(A, PIL.Image.Image):
		A = pil_to_array(A) # Needed e.g. to apply png palette.

		A = self._strip_units(A)
		self._A = self._normalize_image_array(A)
		self._imcache = None
		self.stale = True
Expand DownExpand Up		@@ -1140,6 +1142,7 @@ def set_data(self, x, y, A):
		(M, N) `~numpy.ndarray` or masked array of values to be
		colormapped, or (M, N, 3) RGB array, or (M, N, 4) RGBA array.
		"""
		A = self._strip_units(A)
		A = self._normalize_image_array(A)
		x = np.array(x, np.float32)
		y = np.array(y, np.float32)
Expand DownExpand Up		@@ -1300,6 +1303,7 @@ def set_data(self, x, y, A):
		- (M, N, 3): RGB array
		- (M, N, 4): RGBA array
		"""
		A = self._strip_units(A)
		A = self._normalize_image_array(A)
		x = np.arange(0., A.shape[1] + 1) if x is None else np.array(x, float).ravel()
		y = np.arange(0., A.shape[0] + 1) if y is None else np.array(y, float).ravel()
Expand Down