up follow livre

venv/lib/python3.13/site-packages/mpl_toolkits/axes_grid1/__init__.py

@@ -0,0 +1,10 @@
+from . import axes_size as Size
+from .axes_divider import Divider, SubplotDivider, make_axes_locatable
+from .axes_grid import AxesGrid, Grid, ImageGrid
+
+from .parasite_axes import host_subplot, host_axes
+
+__all__ = ["Size",
+           "Divider", "SubplotDivider", "make_axes_locatable",
+           "AxesGrid", "Grid", "ImageGrid",
+           "host_subplot", "host_axes"]

venv/lib/python3.13/site-packages/mpl_toolkits/axes_grid1/anchored_artists.py

@@ -0,0 +1,414 @@
+from matplotlib import transforms
+from matplotlib.offsetbox import (AnchoredOffsetbox, AuxTransformBox,
+                                  DrawingArea, TextArea, VPacker)
+from matplotlib.patches import (Rectangle, ArrowStyle,
+                                FancyArrowPatch, PathPatch)
+from matplotlib.text import TextPath
+
+__all__ = ['AnchoredDrawingArea', 'AnchoredAuxTransformBox',
+           'AnchoredSizeBar', 'AnchoredDirectionArrows']
+
+
+class AnchoredDrawingArea(AnchoredOffsetbox):
+    def __init__(self, width, height, xdescent, ydescent,
+                 loc, pad=0.4, borderpad=0.5, prop=None, frameon=True,
+                 **kwargs):
+        """
+        An anchored container with a fixed size and fillable `.DrawingArea`.
+
+        Artists added to the *drawing_area* will have their coordinates
+        interpreted as pixels. Any transformations set on the artists will be
+        overridden.
+
+        Parameters
+        ----------
+        width, height : float
+            Width and height of the container, in pixels.
+        xdescent, ydescent : float
+            Descent of the container in the x- and y- direction, in pixels.
+        loc : str
+            Location of this artist.  Valid locations are
+            'upper left', 'upper center', 'upper right',
+            'center left', 'center', 'center right',
+            'lower left', 'lower center', 'lower right'.
+            For backward compatibility, numeric values are accepted as well.
+            See the parameter *loc* of `.Legend` for details.
+        pad : float, default: 0.4
+            Padding around the child objects, in fraction of the font size.
+        borderpad : float, default: 0.5
+            Border padding, in fraction of the font size.
+        prop : `~matplotlib.font_manager.FontProperties`, optional
+            Font property used as a reference for paddings.
+        frameon : bool, default: True
+            If True, draw a box around this artist.
+        **kwargs
+            Keyword arguments forwarded to `.AnchoredOffsetbox`.
+
+        Attributes
+        ----------
+        drawing_area : `~matplotlib.offsetbox.DrawingArea`
+            A container for artists to display.
+
+        Examples
+        --------
+        To display blue and red circles of different sizes in the upper right
+        of an Axes *ax*:
+
+        >>> ada = AnchoredDrawingArea(20, 20, 0, 0,
+        ...                           loc='upper right', frameon=False)
+        >>> ada.drawing_area.add_artist(Circle((10, 10), 10, fc="b"))
+        >>> ada.drawing_area.add_artist(Circle((30, 10), 5, fc="r"))
+        >>> ax.add_artist(ada)
+        """
+        self.da = DrawingArea(width, height, xdescent, ydescent)
+        self.drawing_area = self.da
+
+        super().__init__(
+            loc, pad=pad, borderpad=borderpad, child=self.da, prop=None,
+            frameon=frameon, **kwargs
+        )
+
+
+class AnchoredAuxTransformBox(AnchoredOffsetbox):
+    def __init__(self, transform, loc,
+                 pad=0.4, borderpad=0.5, prop=None, frameon=True, **kwargs):
+        """
+        An anchored container with transformed coordinates.
+
+        Artists added to the *drawing_area* are scaled according to the
+        coordinates of the transformation used. The dimensions of this artist
+        will scale to contain the artists added.
+
+        Parameters
+        ----------
+        transform : `~matplotlib.transforms.Transform`
+            The transformation object for the coordinate system in use, i.e.,
+            :attr:`matplotlib.axes.Axes.transData`.
+        loc : str
+            Location of this artist.  Valid locations are
+            'upper left', 'upper center', 'upper right',
+            'center left', 'center', 'center right',
+            'lower left', 'lower center', 'lower right'.
+            For backward compatibility, numeric values are accepted as well.
+            See the parameter *loc* of `.Legend` for details.
+        pad : float, default: 0.4
+            Padding around the child objects, in fraction of the font size.
+        borderpad : float, default: 0.5
+            Border padding, in fraction of the font size.
+        prop : `~matplotlib.font_manager.FontProperties`, optional
+            Font property used as a reference for paddings.
+        frameon : bool, default: True
+            If True, draw a box around this artist.
+        **kwargs
+            Keyword arguments forwarded to `.AnchoredOffsetbox`.
+
+        Attributes
+        ----------
+        drawing_area : `~matplotlib.offsetbox.AuxTransformBox`
+            A container for artists to display.
+
+        Examples
+        --------
+        To display an ellipse in the upper left, with a width of 0.1 and
+        height of 0.4 in data coordinates:
+
+        >>> box = AnchoredAuxTransformBox(ax.transData, loc='upper left')
+        >>> el = Ellipse((0, 0), width=0.1, height=0.4, angle=30)
+        >>> box.drawing_area.add_artist(el)
+        >>> ax.add_artist(box)
+        """
+        self.drawing_area = AuxTransformBox(transform)
+
+        super().__init__(loc, pad=pad, borderpad=borderpad,
+                         child=self.drawing_area, prop=prop, frameon=frameon,
+                         **kwargs)
+
+
+class AnchoredSizeBar(AnchoredOffsetbox):
+    def __init__(self, transform, size, label, loc,
+                 pad=0.1, borderpad=0.1, sep=2,
+                 frameon=True, size_vertical=0, color='black',
+                 label_top=False, fontproperties=None, fill_bar=None,
+                 **kwargs):
+        """
+        Draw a horizontal scale bar with a center-aligned label underneath.
+
+        Parameters
+        ----------
+        transform : `~matplotlib.transforms.Transform`
+            The transformation object for the coordinate system in use, i.e.,
+            :attr:`matplotlib.axes.Axes.transData`.
+        size : float
+            Horizontal length of the size bar, given in coordinates of
+            *transform*.
+        label : str
+            Label to display.
+        loc : str
+            Location of the size bar.  Valid locations are
+            'upper left', 'upper center', 'upper right',
+            'center left', 'center', 'center right',
+            'lower left', 'lower center', 'lower right'.
+            For backward compatibility, numeric values are accepted as well.
+            See the parameter *loc* of `.Legend` for details.
+        pad : float, default: 0.1
+            Padding around the label and size bar, in fraction of the font
+            size.
+        borderpad : float, default: 0.1
+            Border padding, in fraction of the font size.
+        sep : float, default: 2
+            Separation between the label and the size bar, in points.
+        frameon : bool, default: True
+            If True, draw a box around the horizontal bar and label.
+        size_vertical : float, default: 0
+            Vertical length of the size bar, given in coordinates of
+            *transform*.
+        color : str, default: 'black'
+            Color for the size bar and label.
+        label_top : bool, default: False
+            If True, the label will be over the size bar.
+        fontproperties : `~matplotlib.font_manager.FontProperties`, optional
+            Font properties for the label text.
+        fill_bar : bool, optional
+            If True and if *size_vertical* is nonzero, the size bar will
+            be filled in with the color specified by the size bar.
+            Defaults to True if *size_vertical* is greater than
+            zero and False otherwise.
+        **kwargs
+            Keyword arguments forwarded to `.AnchoredOffsetbox`.
+
+        Attributes
+        ----------
+        size_bar : `~matplotlib.offsetbox.AuxTransformBox`
+            Container for the size bar.
+        txt_label : `~matplotlib.offsetbox.TextArea`
+            Container for the label of the size bar.
+
+        Notes
+        -----
+        If *prop* is passed as a keyword argument, but *fontproperties* is
+        not, then *prop* is assumed to be the intended *fontproperties*.
+        Using both *prop* and *fontproperties* is not supported.
+
+        Examples
+        --------
+        >>> import matplotlib.pyplot as plt
+        >>> import numpy as np
+        >>> from mpl_toolkits.axes_grid1.anchored_artists import (
+        ...     AnchoredSizeBar)
+        >>> fig, ax = plt.subplots()
+        >>> ax.imshow(np.random.random((10, 10)))
+        >>> bar = AnchoredSizeBar(ax.transData, 3, '3 data units', 4)
+        >>> ax.add_artist(bar)
+        >>> fig.show()
+
+        Using all the optional parameters
+
+        >>> import matplotlib.font_manager as fm
+        >>> fontprops = fm.FontProperties(size=14, family='monospace')
+        >>> bar = AnchoredSizeBar(ax.transData, 3, '3 units', 4, pad=0.5,
+        ...                       sep=5, borderpad=0.5, frameon=False,
+        ...                       size_vertical=0.5, color='white',
+        ...                       fontproperties=fontprops)
+        """
+        if fill_bar is None:
+            fill_bar = size_vertical > 0
+
+        self.size_bar = AuxTransformBox(transform)
+        self.size_bar.add_artist(Rectangle((0, 0), size, size_vertical,
+                                           fill=fill_bar, facecolor=color,
+                                           edgecolor=color))
+
+        if fontproperties is None and 'prop' in kwargs:
+            fontproperties = kwargs.pop('prop')
+
+        if fontproperties is None:
+            textprops = {'color': color}
+        else:
+            textprops = {'color': color, 'fontproperties': fontproperties}
+
+        self.txt_label = TextArea(label, textprops=textprops)
+
+        if label_top:
+            _box_children = [self.txt_label, self.size_bar]
+        else:
+            _box_children = [self.size_bar, self.txt_label]
+
+        self._box = VPacker(children=_box_children,
+                            align="center",
+                            pad=0, sep=sep)
+
+        super().__init__(loc, pad=pad, borderpad=borderpad, child=self._box,
+                         prop=fontproperties, frameon=frameon, **kwargs)
+
+
+class AnchoredDirectionArrows(AnchoredOffsetbox):
+    def __init__(self, transform, label_x, label_y, length=0.15,
+                 fontsize=0.08, loc='upper left', angle=0, aspect_ratio=1,
+                 pad=0.4, borderpad=0.4, frameon=False, color='w', alpha=1,
+                 sep_x=0.01, sep_y=0, fontproperties=None, back_length=0.15,
+                 head_width=10, head_length=15, tail_width=2,
+                 text_props=None, arrow_props=None,
+                 **kwargs):
+        """
+        Draw two perpendicular arrows to indicate directions.
+
+        Parameters
+        ----------
+        transform : `~matplotlib.transforms.Transform`
+            The transformation object for the coordinate system in use, i.e.,
+            :attr:`matplotlib.axes.Axes.transAxes`.
+        label_x, label_y : str
+            Label text for the x and y arrows
+        length : float, default: 0.15
+            Length of the arrow, given in coordinates of *transform*.
+        fontsize : float, default: 0.08
+            Size of label strings, given in coordinates of *transform*.
+        loc : str, default: 'upper left'
+            Location of the arrow.  Valid locations are
+            'upper left', 'upper center', 'upper right',
+            'center left', 'center', 'center right',
+            'lower left', 'lower center', 'lower right'.
+            For backward compatibility, numeric values are accepted as well.
+            See the parameter *loc* of `.Legend` for details.
+        angle : float, default: 0
+            The angle of the arrows in degrees.
+        aspect_ratio : float, default: 1
+            The ratio of the length of arrow_x and arrow_y.
+            Negative numbers can be used to change the direction.
+        pad : float, default: 0.4
+            Padding around the labels and arrows, in fraction of the font size.
+        borderpad : float, default: 0.4
+            Border padding, in fraction of the font size.
+        frameon : bool, default: False
+            If True, draw a box around the arrows and labels.
+        color : str, default: 'white'
+            Color for the arrows and labels.
+        alpha : float, default: 1
+            Alpha values of the arrows and labels
+        sep_x, sep_y : float, default: 0.01 and 0 respectively
+            Separation between the arrows and labels in coordinates of
+            *transform*.
+        fontproperties : `~matplotlib.font_manager.FontProperties`, optional
+            Font properties for the label text.
+        back_length : float, default: 0.15
+            Fraction of the arrow behind the arrow crossing.
+        head_width : float, default: 10
+            Width of arrow head, sent to `.ArrowStyle`.
+        head_length : float, default: 15
+            Length of arrow head, sent to `.ArrowStyle`.
+        tail_width : float, default: 2
+            Width of arrow tail, sent to `.ArrowStyle`.
+        text_props, arrow_props : dict
+            Properties of the text and arrows, passed to `.TextPath` and
+            `.FancyArrowPatch`.
+        **kwargs
+            Keyword arguments forwarded to `.AnchoredOffsetbox`.
+
+        Attributes
+        ----------
+        arrow_x, arrow_y : `~matplotlib.patches.FancyArrowPatch`
+            Arrow x and y
+        text_path_x, text_path_y : `~matplotlib.text.TextPath`
+            Path for arrow labels
+        p_x, p_y : `~matplotlib.patches.PathPatch`
+            Patch for arrow labels
+        box : `~matplotlib.offsetbox.AuxTransformBox`
+            Container for the arrows and labels.
+
+        Notes
+        -----
+        If *prop* is passed as a keyword argument, but *fontproperties* is
+        not, then *prop* is assumed to be the intended *fontproperties*.
+        Using both *prop* and *fontproperties* is not supported.
+
+        Examples
+        --------
+        >>> import matplotlib.pyplot as plt
+        >>> import numpy as np
+        >>> from mpl_toolkits.axes_grid1.anchored_artists import (
+        ...     AnchoredDirectionArrows)
+        >>> fig, ax = plt.subplots()
+        >>> ax.imshow(np.random.random((10, 10)))
+        >>> arrows = AnchoredDirectionArrows(ax.transAxes, '111', '110')
+        >>> ax.add_artist(arrows)
+        >>> fig.show()
+
+        Using several of the optional parameters, creating downward pointing
+        arrow and high contrast text labels.
+
+        >>> import matplotlib.font_manager as fm
+        >>> fontprops = fm.FontProperties(family='monospace')
+        >>> arrows = AnchoredDirectionArrows(ax.transAxes, 'East', 'South',
+        ...                                  loc='lower left', color='k',
+        ...                                  aspect_ratio=-1, sep_x=0.02,
+        ...                                  sep_y=-0.01,
+        ...                                  text_props={'ec':'w', 'fc':'k'},
+        ...                                  fontproperties=fontprops)
+        """
+        if arrow_props is None:
+            arrow_props = {}
+
+        if text_props is None:
+            text_props = {}
+
+        arrowstyle = ArrowStyle("Simple",
+                                head_width=head_width,
+                                head_length=head_length,
+                                tail_width=tail_width)
+
+        if fontproperties is None and 'prop' in kwargs:
+            fontproperties = kwargs.pop('prop')
+
+        if 'color' not in arrow_props:
+            arrow_props['color'] = color
+
+        if 'alpha' not in arrow_props:
+            arrow_props['alpha'] = alpha
+
+        if 'color' not in text_props:
+            text_props['color'] = color
+
+        if 'alpha' not in text_props:
+            text_props['alpha'] = alpha
+
+        t_start = transform
+        t_end = t_start + transforms.Affine2D().rotate_deg(angle)
+
+        self.box = AuxTransformBox(t_end)
+
+        length_x = length
+        length_y = length*aspect_ratio
+
+        self.arrow_x = FancyArrowPatch(
+                (0, back_length*length_y),
+                (length_x, back_length*length_y),
+                arrowstyle=arrowstyle,
+                shrinkA=0.0,
+                shrinkB=0.0,
+                **arrow_props)
+
+        self.arrow_y = FancyArrowPatch(
+                (back_length*length_x, 0),
+                (back_length*length_x, length_y),
+                arrowstyle=arrowstyle,
+                shrinkA=0.0,
+                shrinkB=0.0,
+                **arrow_props)
+
+        self.box.add_artist(self.arrow_x)
+        self.box.add_artist(self.arrow_y)
+
+        text_path_x = TextPath((
+            length_x+sep_x, back_length*length_y+sep_y), label_x,
+            size=fontsize, prop=fontproperties)
+        self.p_x = PathPatch(text_path_x, transform=t_start, **text_props)
+        self.box.add_artist(self.p_x)
+
+        text_path_y = TextPath((
+            length_x*back_length+sep_x, length_y*(1-back_length)+sep_y),
+            label_y, size=fontsize, prop=fontproperties)
+        self.p_y = PathPatch(text_path_y, **text_props)
+        self.box.add_artist(self.p_y)
+
+        super().__init__(loc, pad=pad, borderpad=borderpad, child=self.box,
+                         frameon=frameon, **kwargs)

venv/lib/python3.13/site-packages/mpl_toolkits/axes_grid1/axes_divider.py

@@ -0,0 +1,618 @@
+"""
+Helper classes to adjust the positions of multiple axes at drawing time.
+"""
+
+import functools
+
+import numpy as np
+
+import matplotlib as mpl
+from matplotlib import _api
+from matplotlib.gridspec import SubplotSpec
+import matplotlib.transforms as mtransforms
+from . import axes_size as Size
+
+
+class Divider:
+    """
+    An Axes positioning class.
+
+    The divider is initialized with lists of horizontal and vertical sizes
+    (:mod:`mpl_toolkits.axes_grid1.axes_size`) based on which a given
+    rectangular area will be divided.
+
+    The `new_locator` method then creates a callable object
+    that can be used as the *axes_locator* of the axes.
+    """
+
+    def __init__(self, fig, pos, horizontal, vertical,
+                 aspect=None, anchor="C"):
+        """
+        Parameters
+        ----------
+        fig : Figure
+        pos : tuple of 4 floats
+            Position of the rectangle that will be divided.
+        horizontal : list of :mod:`~mpl_toolkits.axes_grid1.axes_size`
+            Sizes for horizontal division.
+        vertical : list of :mod:`~mpl_toolkits.axes_grid1.axes_size`
+            Sizes for vertical division.
+        aspect : bool, optional
+            Whether overall rectangular area is reduced so that the relative
+            part of the horizontal and vertical scales have the same scale.
+        anchor : (float, float) or {'C', 'SW', 'S', 'SE', 'E', 'NE', 'N', \
+'NW', 'W'}, default: 'C'
+            Placement of the reduced rectangle, when *aspect* is True.
+        """
+
+        self._fig = fig
+        self._pos = pos
+        self._horizontal = horizontal
+        self._vertical = vertical
+        self._anchor = anchor
+        self.set_anchor(anchor)
+        self._aspect = aspect
+        self._xrefindex = 0
+        self._yrefindex = 0
+        self._locator = None
+
+    def get_horizontal_sizes(self, renderer):
+        return np.array([s.get_size(renderer) for s in self.get_horizontal()])
+
+    def get_vertical_sizes(self, renderer):
+        return np.array([s.get_size(renderer) for s in self.get_vertical()])
+
+    def set_position(self, pos):
+        """
+        Set the position of the rectangle.
+
+        Parameters
+        ----------
+        pos : tuple of 4 floats
+            position of the rectangle that will be divided
+        """
+        self._pos = pos
+
+    def get_position(self):
+        """Return the position of the rectangle."""
+        return self._pos
+
+    def set_anchor(self, anchor):
+        """
+        Parameters
+        ----------
+        anchor : (float, float) or {'C', 'SW', 'S', 'SE', 'E', 'NE', 'N', \
+'NW', 'W'}
+            Either an (*x*, *y*) pair of relative coordinates (0 is left or
+            bottom, 1 is right or top), 'C' (center), or a cardinal direction
+            ('SW', southwest, is bottom left, etc.).
+
+        See Also
+        --------
+        .Axes.set_anchor
+        """
+        if isinstance(anchor, str):
+            _api.check_in_list(mtransforms.Bbox.coefs, anchor=anchor)
+        elif not isinstance(anchor, (tuple, list)) or len(anchor) != 2:
+            raise TypeError("anchor must be str or 2-tuple")
+        self._anchor = anchor
+
+    def get_anchor(self):
+        """Return the anchor."""
+        return self._anchor
+
+    def get_subplotspec(self):
+        return None
+
+    def set_horizontal(self, h):
+        """
+        Parameters
+        ----------
+        h : list of :mod:`~mpl_toolkits.axes_grid1.axes_size`
+            sizes for horizontal division
+        """
+        self._horizontal = h
+
+    def get_horizontal(self):
+        """Return horizontal sizes."""
+        return self._horizontal
+
+    def set_vertical(self, v):
+        """
+        Parameters
+        ----------
+        v : list of :mod:`~mpl_toolkits.axes_grid1.axes_size`
+            sizes for vertical division
+        """
+        self._vertical = v
+
+    def get_vertical(self):
+        """Return vertical sizes."""
+        return self._vertical
+
+    def set_aspect(self, aspect=False):
+        """
+        Parameters
+        ----------
+        aspect : bool
+        """
+        self._aspect = aspect
+
+    def get_aspect(self):
+        """Return aspect."""
+        return self._aspect
+
+    def set_locator(self, _locator):
+        self._locator = _locator
+
+    def get_locator(self):
+        return self._locator
+
+    def get_position_runtime(self, ax, renderer):
+        if self._locator is None:
+            return self.get_position()
+        else:
+            return self._locator(ax, renderer).bounds
+
+    @staticmethod
+    def _calc_k(sizes, total):
+        # sizes is a (n, 2) array of (rel_size, abs_size); this method finds
+        # the k factor such that sum(rel_size * k + abs_size) == total.
+        rel_sum, abs_sum = sizes.sum(0)
+        return (total - abs_sum) / rel_sum if rel_sum else 0
+
+    @staticmethod
+    def _calc_offsets(sizes, k):
+        # Apply k factors to (n, 2) sizes array of (rel_size, abs_size); return
+        # the resulting cumulative offset positions.
+        return np.cumsum([0, *(sizes @ [k, 1])])
+
+    def new_locator(self, nx, ny, nx1=None, ny1=None):
+        """
+        Return an axes locator callable for the specified cell.
+
+        Parameters
+        ----------
+        nx, nx1 : int
+            Integers specifying the column-position of the
+            cell. When *nx1* is None, a single *nx*-th column is
+            specified. Otherwise, location of columns spanning between *nx*
+            to *nx1* (but excluding *nx1*-th column) is specified.
+        ny, ny1 : int
+            Same as *nx* and *nx1*, but for row positions.
+        """
+        if nx1 is None:
+            nx1 = nx + 1
+        if ny1 is None:
+            ny1 = ny + 1
+        # append_size("left") adds a new size at the beginning of the
+        # horizontal size lists; this shift transforms e.g.
+        # new_locator(nx=2, ...) into effectively new_locator(nx=3, ...).  To
+        # take that into account, instead of recording nx, we record
+        # nx-self._xrefindex, where _xrefindex is shifted by 1 by each
+        # append_size("left"), and re-add self._xrefindex back to nx in
+        # _locate, when the actual axes position is computed.  Ditto for y.
+        xref = self._xrefindex
+        yref = self._yrefindex
+        locator = functools.partial(
+            self._locate, nx - xref, ny - yref, nx1 - xref, ny1 - yref)
+        locator.get_subplotspec = self.get_subplotspec
+        return locator
+
+    def _locate(self, nx, ny, nx1, ny1, axes, renderer):
+        """
+        Implementation of ``divider.new_locator().__call__``.
+
+        The axes locator callable returned by ``new_locator()`` is created as
+        a `functools.partial` of this method with *nx*, *ny*, *nx1*, and *ny1*
+        specifying the requested cell.
+        """
+        nx += self._xrefindex
+        nx1 += self._xrefindex
+        ny += self._yrefindex
+        ny1 += self._yrefindex
+
+        fig_w, fig_h = self._fig.bbox.size / self._fig.dpi
+        x, y, w, h = self.get_position_runtime(axes, renderer)
+
+        hsizes = self.get_horizontal_sizes(renderer)
+        vsizes = self.get_vertical_sizes(renderer)
+        k_h = self._calc_k(hsizes, fig_w * w)
+        k_v = self._calc_k(vsizes, fig_h * h)
+
+        if self.get_aspect():
+            k = min(k_h, k_v)
+            ox = self._calc_offsets(hsizes, k)
+            oy = self._calc_offsets(vsizes, k)
+
+            ww = (ox[-1] - ox[0]) / fig_w
+            hh = (oy[-1] - oy[0]) / fig_h
+            pb = mtransforms.Bbox.from_bounds(x, y, w, h)
+            pb1 = mtransforms.Bbox.from_bounds(x, y, ww, hh)
+            x0, y0 = pb1.anchored(self.get_anchor(), pb).p0
+
+        else:
+            ox = self._calc_offsets(hsizes, k_h)
+            oy = self._calc_offsets(vsizes, k_v)
+            x0, y0 = x, y
+
+        if nx1 is None:
+            nx1 = -1
+        if ny1 is None:
+            ny1 = -1
+
+        x1, w1 = x0 + ox[nx] / fig_w, (ox[nx1] - ox[nx]) / fig_w
+        y1, h1 = y0 + oy[ny] / fig_h, (oy[ny1] - oy[ny]) / fig_h
+
+        return mtransforms.Bbox.from_bounds(x1, y1, w1, h1)
+
+    def append_size(self, position, size):
+        _api.check_in_list(["left", "right", "bottom", "top"],
+                           position=position)
+        if position == "left":
+            self._horizontal.insert(0, size)
+            self._xrefindex += 1
+        elif position == "right":
+            self._horizontal.append(size)
+        elif position == "bottom":
+            self._vertical.insert(0, size)
+            self._yrefindex += 1
+        else:  # 'top'
+            self._vertical.append(size)
+
+    def add_auto_adjustable_area(self, use_axes, pad=0.1, adjust_dirs=None):
+        """
+        Add auto-adjustable padding around *use_axes* to take their decorations
+        (title, labels, ticks, ticklabels) into account during layout.
+
+        Parameters
+        ----------
+        use_axes : `~matplotlib.axes.Axes` or list of `~matplotlib.axes.Axes`
+            The Axes whose decorations are taken into account.
+        pad : float, default: 0.1
+            Additional padding in inches.
+        adjust_dirs : list of {"left", "right", "bottom", "top"}, optional
+            The sides where padding is added; defaults to all four sides.
+        """
+        if adjust_dirs is None:
+            adjust_dirs = ["left", "right", "bottom", "top"]
+        for d in adjust_dirs:
+            self.append_size(d, Size._AxesDecorationsSize(use_axes, d) + pad)
+
+
+class SubplotDivider(Divider):
+    """
+    The Divider class whose rectangle area is specified as a subplot geometry.
+    """
+
+    def __init__(self, fig, *args, horizontal=None, vertical=None,
+                 aspect=None, anchor='C'):
+        """
+        Parameters
+        ----------
+        fig : `~matplotlib.figure.Figure`
+
+        *args : tuple (*nrows*, *ncols*, *index*) or int
+            The array of subplots in the figure has dimensions ``(nrows,
+            ncols)``, and *index* is the index of the subplot being created.
+            *index* starts at 1 in the upper left corner and increases to the
+            right.
+
+            If *nrows*, *ncols*, and *index* are all single digit numbers, then
+            *args* can be passed as a single 3-digit number (e.g. 234 for
+            (2, 3, 4)).
+        horizontal : list of :mod:`~mpl_toolkits.axes_grid1.axes_size`, optional
+            Sizes for horizontal division.
+        vertical : list of :mod:`~mpl_toolkits.axes_grid1.axes_size`, optional
+            Sizes for vertical division.
+        aspect : bool, optional
+            Whether overall rectangular area is reduced so that the relative
+            part of the horizontal and vertical scales have the same scale.
+        anchor : (float, float) or {'C', 'SW', 'S', 'SE', 'E', 'NE', 'N', \
+'NW', 'W'}, default: 'C'
+            Placement of the reduced rectangle, when *aspect* is True.
+        """
+        self.figure = fig
+        super().__init__(fig, [0, 0, 1, 1],
+                         horizontal=horizontal or [], vertical=vertical or [],
+                         aspect=aspect, anchor=anchor)
+        self.set_subplotspec(SubplotSpec._from_subplot_args(fig, args))
+
+    def get_position(self):
+        """Return the bounds of the subplot box."""
+        return self.get_subplotspec().get_position(self.figure).bounds
+
+    def get_subplotspec(self):
+        """Get the SubplotSpec instance."""
+        return self._subplotspec
+
+    def set_subplotspec(self, subplotspec):
+        """Set the SubplotSpec instance."""
+        self._subplotspec = subplotspec
+        self.set_position(subplotspec.get_position(self.figure))
+
+
+class AxesDivider(Divider):
+    """
+    Divider based on the preexisting axes.
+    """
+
+    def __init__(self, axes, xref=None, yref=None):
+        """
+        Parameters
+        ----------
+        axes : :class:`~matplotlib.axes.Axes`
+        xref
+        yref
+        """
+        self._axes = axes
+        if xref is None:
+            self._xref = Size.AxesX(axes)
+        else:
+            self._xref = xref
+        if yref is None:
+            self._yref = Size.AxesY(axes)
+        else:
+            self._yref = yref
+
+        super().__init__(fig=axes.get_figure(), pos=None,
+                         horizontal=[self._xref], vertical=[self._yref],
+                         aspect=None, anchor="C")
+
+    def _get_new_axes(self, *, axes_class=None, **kwargs):
+        axes = self._axes
+        if axes_class is None:
+            axes_class = type(axes)
+        return axes_class(axes.get_figure(), axes.get_position(original=True),
+                          **kwargs)
+
+    def new_horizontal(self, size, pad=None, pack_start=False, **kwargs):
+        """
+        Helper method for ``append_axes("left")`` and ``append_axes("right")``.
+
+        See the documentation of `append_axes` for more details.
+
+        :meta private:
+        """
+        if pad is None:
+            pad = mpl.rcParams["figure.subplot.wspace"] * self._xref
+        pos = "left" if pack_start else "right"
+        if pad:
+            if not isinstance(pad, Size._Base):
+                pad = Size.from_any(pad, fraction_ref=self._xref)
+            self.append_size(pos, pad)
+        if not isinstance(size, Size._Base):
+            size = Size.from_any(size, fraction_ref=self._xref)
+        self.append_size(pos, size)
+        locator = self.new_locator(
+            nx=0 if pack_start else len(self._horizontal) - 1,
+            ny=self._yrefindex)
+        ax = self._get_new_axes(**kwargs)
+        ax.set_axes_locator(locator)
+        return ax
+
+    def new_vertical(self, size, pad=None, pack_start=False, **kwargs):
+        """
+        Helper method for ``append_axes("top")`` and ``append_axes("bottom")``.
+
+        See the documentation of `append_axes` for more details.
+
+        :meta private:
+        """
+        if pad is None:
+            pad = mpl.rcParams["figure.subplot.hspace"] * self._yref
+        pos = "bottom" if pack_start else "top"
+        if pad:
+            if not isinstance(pad, Size._Base):
+                pad = Size.from_any(pad, fraction_ref=self._yref)
+            self.append_size(pos, pad)
+        if not isinstance(size, Size._Base):
+            size = Size.from_any(size, fraction_ref=self._yref)
+        self.append_size(pos, size)
+        locator = self.new_locator(
+            nx=self._xrefindex,
+            ny=0 if pack_start else len(self._vertical) - 1)
+        ax = self._get_new_axes(**kwargs)
+        ax.set_axes_locator(locator)
+        return ax
+
+    def append_axes(self, position, size, pad=None, *, axes_class=None,
+                    **kwargs):
+        """
+        Add a new axes on a given side of the main axes.
+
+        Parameters
+        ----------
+        position : {"left", "right", "bottom", "top"}
+            Where the new axes is positioned relative to the main axes.
+        size : :mod:`~mpl_toolkits.axes_grid1.axes_size` or float or str
+            The axes width or height.  float or str arguments are interpreted
+            as ``axes_size.from_any(size, AxesX(<main_axes>))`` for left or
+            right axes, and likewise with ``AxesY`` for bottom or top axes.
+        pad : :mod:`~mpl_toolkits.axes_grid1.axes_size` or float or str
+            Padding between the axes.  float or str arguments are interpreted
+            as for *size*.  Defaults to :rc:`figure.subplot.wspace` times the
+            main Axes width (left or right axes) or :rc:`figure.subplot.hspace`
+            times the main Axes height (bottom or top axes).
+        axes_class : subclass type of `~.axes.Axes`, optional
+            The type of the new axes.  Defaults to the type of the main axes.
+        **kwargs
+            All extra keywords arguments are passed to the created axes.
+        """
+        create_axes, pack_start = _api.check_getitem({
+            "left": (self.new_horizontal, True),
+            "right": (self.new_horizontal, False),
+            "bottom": (self.new_vertical, True),
+            "top": (self.new_vertical, False),
+        }, position=position)
+        ax = create_axes(
+            size, pad, pack_start=pack_start, axes_class=axes_class, **kwargs)
+        self._fig.add_axes(ax)
+        return ax
+
+    def get_aspect(self):
+        if self._aspect is None:
+            aspect = self._axes.get_aspect()
+            if aspect == "auto":
+                return False
+            else:
+                return True
+        else:
+            return self._aspect
+
+    def get_position(self):
+        if self._pos is None:
+            bbox = self._axes.get_position(original=True)
+            return bbox.bounds
+        else:
+            return self._pos
+
+    def get_anchor(self):
+        if self._anchor is None:
+            return self._axes.get_anchor()
+        else:
+            return self._anchor
+
+    def get_subplotspec(self):
+        return self._axes.get_subplotspec()
+
+
+# Helper for HBoxDivider/VBoxDivider.
+# The variable names are written for a horizontal layout, but the calculations
+# work identically for vertical layouts.
+def _locate(x, y, w, h, summed_widths, equal_heights, fig_w, fig_h, anchor):
+
+    total_width = fig_w * w
+    max_height = fig_h * h
+
+    # Determine the k factors.
+    n = len(equal_heights)
+    eq_rels, eq_abss = equal_heights.T
+    sm_rels, sm_abss = summed_widths.T
+    A = np.diag([*eq_rels, 0])
+    A[:n, -1] = -1
+    A[-1, :-1] = sm_rels
+    B = [*(-eq_abss), total_width - sm_abss.sum()]
+    # A @ K = B: This finds factors {k_0, ..., k_{N-1}, H} so that
+    #   eq_rel_i * k_i + eq_abs_i = H for all i: all axes have the same height
+    #   sum(sm_rel_i * k_i + sm_abs_i) = total_width: fixed total width
+    # (foo_rel_i * k_i + foo_abs_i will end up being the size of foo.)
+    *karray, height = np.linalg.solve(A, B)
+    if height > max_height:  # Additionally, upper-bound the height.
+        karray = (max_height - eq_abss) / eq_rels
+
+    # Compute the offsets corresponding to these factors.
+    ox = np.cumsum([0, *(sm_rels * karray + sm_abss)])
+    ww = (ox[-1] - ox[0]) / fig_w
+    h0_rel, h0_abs = equal_heights[0]
+    hh = (karray[0]*h0_rel + h0_abs) / fig_h
+    pb = mtransforms.Bbox.from_bounds(x, y, w, h)
+    pb1 = mtransforms.Bbox.from_bounds(x, y, ww, hh)
+    x0, y0 = pb1.anchored(anchor, pb).p0
+
+    return x0, y0, ox, hh
+
+
+class HBoxDivider(SubplotDivider):
+    """
+    A `.SubplotDivider` for laying out axes horizontally, while ensuring that
+    they have equal heights.
+
+    Examples
+    --------
+    .. plot:: gallery/axes_grid1/demo_axes_hbox_divider.py
+    """
+
+    def new_locator(self, nx, nx1=None):
+        """
+        Create an axes locator callable for the specified cell.
+
+        Parameters
+        ----------
+        nx, nx1 : int
+            Integers specifying the column-position of the
+            cell. When *nx1* is None, a single *nx*-th column is
+            specified. Otherwise, location of columns spanning between *nx*
+            to *nx1* (but excluding *nx1*-th column) is specified.
+        """
+        return super().new_locator(nx, 0, nx1, 0)
+
+    def _locate(self, nx, ny, nx1, ny1, axes, renderer):
+        # docstring inherited
+        nx += self._xrefindex
+        nx1 += self._xrefindex
+        fig_w, fig_h = self._fig.bbox.size / self._fig.dpi
+        x, y, w, h = self.get_position_runtime(axes, renderer)
+        summed_ws = self.get_horizontal_sizes(renderer)
+        equal_hs = self.get_vertical_sizes(renderer)
+        x0, y0, ox, hh = _locate(
+            x, y, w, h, summed_ws, equal_hs, fig_w, fig_h, self.get_anchor())
+        if nx1 is None:
+            nx1 = -1
+        x1, w1 = x0 + ox[nx] / fig_w, (ox[nx1] - ox[nx]) / fig_w
+        y1, h1 = y0, hh
+        return mtransforms.Bbox.from_bounds(x1, y1, w1, h1)
+
+
+class VBoxDivider(SubplotDivider):
+    """
+    A `.SubplotDivider` for laying out axes vertically, while ensuring that
+    they have equal widths.
+    """
+
+    def new_locator(self, ny, ny1=None):
+        """
+        Create an axes locator callable for the specified cell.
+
+        Parameters
+        ----------
+        ny, ny1 : int
+            Integers specifying the row-position of the
+            cell. When *ny1* is None, a single *ny*-th row is
+            specified. Otherwise, location of rows spanning between *ny*
+            to *ny1* (but excluding *ny1*-th row) is specified.
+        """
+        return super().new_locator(0, ny, 0, ny1)
+
+    def _locate(self, nx, ny, nx1, ny1, axes, renderer):
+        # docstring inherited
+        ny += self._yrefindex
+        ny1 += self._yrefindex
+        fig_w, fig_h = self._fig.bbox.size / self._fig.dpi
+        x, y, w, h = self.get_position_runtime(axes, renderer)
+        summed_hs = self.get_vertical_sizes(renderer)
+        equal_ws = self.get_horizontal_sizes(renderer)
+        y0, x0, oy, ww = _locate(
+            y, x, h, w, summed_hs, equal_ws, fig_h, fig_w, self.get_anchor())
+        if ny1 is None:
+            ny1 = -1
+        x1, w1 = x0, ww
+        y1, h1 = y0 + oy[ny] / fig_h, (oy[ny1] - oy[ny]) / fig_h
+        return mtransforms.Bbox.from_bounds(x1, y1, w1, h1)
+
+
+def make_axes_locatable(axes):
+    divider = AxesDivider(axes)
+    locator = divider.new_locator(nx=0, ny=0)
+    axes.set_axes_locator(locator)
+
+    return divider
+
+
+def make_axes_area_auto_adjustable(
+        ax, use_axes=None, pad=0.1, adjust_dirs=None):
+    """
+    Add auto-adjustable padding around *ax* to take its decorations (title,
+    labels, ticks, ticklabels) into account during layout, using
+    `.Divider.add_auto_adjustable_area`.
+
+    By default, padding is determined from the decorations of *ax*.
+    Pass *use_axes* to consider the decorations of other Axes instead.
+    """
+    if adjust_dirs is None:
+        adjust_dirs = ["left", "right", "bottom", "top"]
+    divider = make_axes_locatable(ax)
+    if use_axes is None:
+        use_axes = ax
+    divider.add_auto_adjustable_area(use_axes=use_axes, pad=pad,
+                                     adjust_dirs=adjust_dirs)

venv/lib/python3.13/site-packages/mpl_toolkits/axes_grid1/axes_grid.py

@@ -0,0 +1,563 @@
+from numbers import Number
+import functools
+from types import MethodType
+
+import numpy as np
+
+from matplotlib import _api, cbook
+from matplotlib.gridspec import SubplotSpec
+
+from .axes_divider import Size, SubplotDivider, Divider
+from .mpl_axes import Axes, SimpleAxisArtist
+
+
+class CbarAxesBase:
+    def __init__(self, *args, orientation, **kwargs):
+        self.orientation = orientation
+        super().__init__(*args, **kwargs)
+
+    def colorbar(self, mappable, **kwargs):
+        return self.get_figure(root=False).colorbar(
+            mappable, cax=self, location=self.orientation, **kwargs)
+
+
+_cbaraxes_class_factory = cbook._make_class_factory(CbarAxesBase, "Cbar{}")
+
+
+class Grid:
+    """
+    A grid of Axes.
+
+    In Matplotlib, the Axes location (and size) is specified in normalized
+    figure coordinates. This may not be ideal for images that needs to be
+    displayed with a given aspect ratio; for example, it is difficult to
+    display multiple images of a same size with some fixed padding between
+    them.  AxesGrid can be used in such case.
+
+    Attributes
+    ----------
+    axes_all : list of Axes
+        A flat list of Axes. Note that you can also access this directly
+        from the grid. The following is equivalent ::
+
+            grid[i] == grid.axes_all[i]
+            len(grid) == len(grid.axes_all)
+
+    axes_column : list of list of Axes
+        A 2D list of Axes where the first index is the column. This results
+        in the usage pattern ``grid.axes_column[col][row]``.
+    axes_row : list of list of Axes
+        A 2D list of Axes where the first index is the row. This results
+        in the usage pattern ``grid.axes_row[row][col]``.
+    axes_llc : Axes
+        The Axes in the lower left corner.
+    ngrids : int
+        Number of Axes in the grid.
+    """
+
+    _defaultAxesClass = Axes
+
+    def __init__(self, fig,
+                 rect,
+                 nrows_ncols,
+                 ngrids=None,
+                 direction="row",
+                 axes_pad=0.02,
+                 *,
+                 share_all=False,
+                 share_x=True,
+                 share_y=True,
+                 label_mode="L",
+                 axes_class=None,
+                 aspect=False,
+                 ):
+        """
+        Parameters
+        ----------
+        fig : `.Figure`
+            The parent figure.
+        rect : (float, float, float, float), (int, int, int), int, or \
+    `~.SubplotSpec`
+            The axes position, as a ``(left, bottom, width, height)`` tuple,
+            as a three-digit subplot position code (e.g., ``(1, 2, 1)`` or
+            ``121``), or as a `~.SubplotSpec`.
+        nrows_ncols : (int, int)
+            Number of rows and columns in the grid.
+        ngrids : int or None, default: None
+            If not None, only the first *ngrids* axes in the grid are created.
+        direction : {"row", "column"}, default: "row"
+            Whether axes are created in row-major ("row by row") or
+            column-major order ("column by column").  This also affects the
+            order in which axes are accessed using indexing (``grid[index]``).
+        axes_pad : float or (float, float), default: 0.02
+            Padding or (horizontal padding, vertical padding) between axes, in
+            inches.
+        share_all : bool, default: False
+            Whether all axes share their x- and y-axis.  Overrides *share_x*
+            and *share_y*.
+        share_x : bool, default: True
+            Whether all axes of a column share their x-axis.
+        share_y : bool, default: True
+            Whether all axes of a row share their y-axis.
+        label_mode : {"L", "1", "all", "keep"}, default: "L"
+            Determines which axes will get tick labels:
+
+            - "L": All axes on the left column get vertical tick labels;
+              all axes on the bottom row get horizontal tick labels.
+            - "1": Only the bottom left axes is labelled.
+            - "all": All axes are labelled.
+            - "keep": Do not do anything.
+
+        axes_class : subclass of `matplotlib.axes.Axes`, default: `.mpl_axes.Axes`
+            The type of Axes to create.
+        aspect : bool, default: False
+            Whether the axes aspect ratio follows the aspect ratio of the data
+            limits.
+        """
+        self._nrows, self._ncols = nrows_ncols
+
+        if ngrids is None:
+            ngrids = self._nrows * self._ncols
+        else:
+            if not 0 < ngrids <= self._nrows * self._ncols:
+                raise ValueError(
+                    "ngrids must be positive and not larger than nrows*ncols")
+
+        self.ngrids = ngrids
+
+        self._horiz_pad_size, self._vert_pad_size = map(
+            Size.Fixed, np.broadcast_to(axes_pad, 2))
+
+        _api.check_in_list(["column", "row"], direction=direction)
+        self._direction = direction
+
+        if axes_class is None:
+            axes_class = self._defaultAxesClass
+        elif isinstance(axes_class, (list, tuple)):
+            cls, kwargs = axes_class
+            axes_class = functools.partial(cls, **kwargs)
+
+        kw = dict(horizontal=[], vertical=[], aspect=aspect)
+        if isinstance(rect, (Number, SubplotSpec)):
+            self._divider = SubplotDivider(fig, rect, **kw)
+        elif len(rect) == 3:
+            self._divider = SubplotDivider(fig, *rect, **kw)
+        elif len(rect) == 4:
+            self._divider = Divider(fig, rect, **kw)
+        else:
+            raise TypeError("Incorrect rect format")
+
+        rect = self._divider.get_position()
+
+        axes_array = np.full((self._nrows, self._ncols), None, dtype=object)
+        for i in range(self.ngrids):
+            col, row = self._get_col_row(i)
+            if share_all:
+                sharex = sharey = axes_array[0, 0]
+            else:
+                sharex = axes_array[0, col] if share_x else None
+                sharey = axes_array[row, 0] if share_y else None
+            axes_array[row, col] = axes_class(
+                fig, rect, sharex=sharex, sharey=sharey)
+        self.axes_all = axes_array.ravel(
+            order="C" if self._direction == "row" else "F").tolist()
+        self.axes_column = axes_array.T.tolist()
+        self.axes_row = axes_array.tolist()
+        self.axes_llc = self.axes_column[0][-1]
+
+        self._init_locators()
+
+        for ax in self.axes_all:
+            fig.add_axes(ax)
+
+        self.set_label_mode(label_mode)
+
+    def _init_locators(self):
+        self._divider.set_horizontal(
+            [Size.Scaled(1), self._horiz_pad_size] * (self._ncols-1) + [Size.Scaled(1)])
+        self._divider.set_vertical(
+            [Size.Scaled(1), self._vert_pad_size] * (self._nrows-1) + [Size.Scaled(1)])
+        for i in range(self.ngrids):
+            col, row = self._get_col_row(i)
+            self.axes_all[i].set_axes_locator(
+                self._divider.new_locator(nx=2 * col, ny=2 * (self._nrows - 1 - row)))
+
+    def _get_col_row(self, n):
+        if self._direction == "column":
+            col, row = divmod(n, self._nrows)
+        else:
+            row, col = divmod(n, self._ncols)
+
+        return col, row
+
+    # Good to propagate __len__ if we have __getitem__
+    def __len__(self):
+        return len(self.axes_all)
+
+    def __getitem__(self, i):
+        return self.axes_all[i]
+
+    def get_geometry(self):
+        """
+        Return the number of rows and columns of the grid as (nrows, ncols).
+        """
+        return self._nrows, self._ncols
+
+    def set_axes_pad(self, axes_pad):
+        """
+        Set the padding between the axes.
+
+        Parameters
+        ----------
+        axes_pad : (float, float)
+            The padding (horizontal pad, vertical pad) in inches.
+        """
+        self._horiz_pad_size.fixed_size = axes_pad[0]
+        self._vert_pad_size.fixed_size = axes_pad[1]
+
+    def get_axes_pad(self):
+        """
+        Return the axes padding.
+
+        Returns
+        -------
+        hpad, vpad
+            Padding (horizontal pad, vertical pad) in inches.
+        """
+        return (self._horiz_pad_size.fixed_size,
+                self._vert_pad_size.fixed_size)
+
+    def set_aspect(self, aspect):
+        """Set the aspect of the SubplotDivider."""
+        self._divider.set_aspect(aspect)
+
+    def get_aspect(self):
+        """Return the aspect of the SubplotDivider."""
+        return self._divider.get_aspect()
+
+    def set_label_mode(self, mode):
+        """
+        Define which axes have tick labels.
+
+        Parameters
+        ----------
+        mode : {"L", "1", "all", "keep"}
+            The label mode:
+
+            - "L": All axes on the left column get vertical tick labels;
+              all axes on the bottom row get horizontal tick labels.
+            - "1": Only the bottom left axes is labelled.
+            - "all": All axes are labelled.
+            - "keep": Do not do anything.
+        """
+        _api.check_in_list(["all", "L", "1", "keep"], mode=mode)
+        is_last_row, is_first_col = (
+            np.mgrid[:self._nrows, :self._ncols] == [[[self._nrows - 1]], [[0]]])
+        if mode == "all":
+            bottom = left = np.full((self._nrows, self._ncols), True)
+        elif mode == "L":
+            bottom = is_last_row
+            left = is_first_col
+        elif mode == "1":
+            bottom = left = is_last_row & is_first_col
+        else:
+            return
+        for i in range(self._nrows):
+            for j in range(self._ncols):
+                ax = self.axes_row[i][j]
+                if isinstance(ax.axis, MethodType):
+                    bottom_axis = SimpleAxisArtist(ax.xaxis, 1, ax.spines["bottom"])
+                    left_axis = SimpleAxisArtist(ax.yaxis, 1, ax.spines["left"])
+                else:
+                    bottom_axis = ax.axis["bottom"]
+                    left_axis = ax.axis["left"]
+                bottom_axis.toggle(ticklabels=bottom[i, j], label=bottom[i, j])
+                left_axis.toggle(ticklabels=left[i, j], label=left[i, j])
+
+    def get_divider(self):
+        return self._divider
+
+    def set_axes_locator(self, locator):
+        self._divider.set_locator(locator)
+
+    def get_axes_locator(self):
+        return self._divider.get_locator()
+
+
+class ImageGrid(Grid):
+    """
+    A grid of Axes for Image display.
+
+    This class is a specialization of `~.axes_grid1.axes_grid.Grid` for displaying a
+    grid of images.  In particular, it forces all axes in a column to share their x-axis
+    and all axes in a row to share their y-axis.  It further provides helpers to add
+    colorbars to some or all axes.
+    """
+
+    def __init__(self, fig,
+                 rect,
+                 nrows_ncols,
+                 ngrids=None,
+                 direction="row",
+                 axes_pad=0.02,
+                 *,
+                 share_all=False,
+                 aspect=True,
+                 label_mode="L",
+                 cbar_mode=None,
+                 cbar_location="right",
+                 cbar_pad=None,
+                 cbar_size="5%",
+                 cbar_set_cax=True,
+                 axes_class=None,
+                 ):
+        """
+        Parameters
+        ----------
+        fig : `.Figure`
+            The parent figure.
+        rect : (float, float, float, float) or int
+            The axes position, as a ``(left, bottom, width, height)`` tuple or
+            as a three-digit subplot position code (e.g., "121").
+        nrows_ncols : (int, int)
+            Number of rows and columns in the grid.
+        ngrids : int or None, default: None
+            If not None, only the first *ngrids* axes in the grid are created.
+        direction : {"row", "column"}, default: "row"
+            Whether axes are created in row-major ("row by row") or
+            column-major order ("column by column").  This also affects the
+            order in which axes are accessed using indexing (``grid[index]``).
+        axes_pad : float or (float, float), default: 0.02in
+            Padding or (horizontal padding, vertical padding) between axes, in
+            inches.
+        share_all : bool, default: False
+            Whether all axes share their x- and y-axis.  Note that in any case,
+            all axes in a column share their x-axis and all axes in a row share
+            their y-axis.
+        aspect : bool, default: True
+            Whether the axes aspect ratio follows the aspect ratio of the data
+            limits.
+        label_mode : {"L", "1", "all"}, default: "L"
+            Determines which axes will get tick labels:
+
+            - "L": All axes on the left column get vertical tick labels;
+              all axes on the bottom row get horizontal tick labels.
+            - "1": Only the bottom left axes is labelled.
+            - "all": all axes are labelled.
+
+        cbar_mode : {"each", "single", "edge", None}, default: None
+            Whether to create a colorbar for "each" axes, a "single" colorbar
+            for the entire grid, colorbars only for axes on the "edge"
+            determined by *cbar_location*, or no colorbars.  The colorbars are
+            stored in the :attr:`cbar_axes` attribute.
+        cbar_location : {"left", "right", "bottom", "top"}, default: "right"
+        cbar_pad : float, default: None
+            Padding between the image axes and the colorbar axes.
+
+            .. versionchanged:: 3.10
+                ``cbar_mode="single"`` no longer adds *axes_pad* between the axes
+                and the colorbar if the *cbar_location* is "left" or "bottom".
+
+        cbar_size : size specification (see `.Size.from_any`), default: "5%"
+            Colorbar size.
+        cbar_set_cax : bool, default: True
+            If True, each axes in the grid has a *cax* attribute that is bound
+            to associated *cbar_axes*.
+        axes_class : subclass of `matplotlib.axes.Axes`, default: None
+        """
+        _api.check_in_list(["each", "single", "edge", None],
+                           cbar_mode=cbar_mode)
+        _api.check_in_list(["left", "right", "bottom", "top"],
+                           cbar_location=cbar_location)
+        self._colorbar_mode = cbar_mode
+        self._colorbar_location = cbar_location
+        self._colorbar_pad = cbar_pad
+        self._colorbar_size = cbar_size
+        # The colorbar axes are created in _init_locators().
+
+        super().__init__(
+            fig, rect, nrows_ncols, ngrids,
+            direction=direction, axes_pad=axes_pad,
+            share_all=share_all, share_x=True, share_y=True, aspect=aspect,
+            label_mode=label_mode, axes_class=axes_class)
+
+        for ax in self.cbar_axes:
+            fig.add_axes(ax)
+
+        if cbar_set_cax:
+            if self._colorbar_mode == "single":
+                for ax in self.axes_all:
+                    ax.cax = self.cbar_axes[0]
+            elif self._colorbar_mode == "edge":
+                for index, ax in enumerate(self.axes_all):
+                    col, row = self._get_col_row(index)
+                    if self._colorbar_location in ("left", "right"):
+                        ax.cax = self.cbar_axes[row]
+                    else:
+                        ax.cax = self.cbar_axes[col]
+            else:
+                for ax, cax in zip(self.axes_all, self.cbar_axes):
+                    ax.cax = cax
+
+    def _init_locators(self):
+        # Slightly abusing this method to inject colorbar creation into init.
+
+        if self._colorbar_pad is None:
+            # horizontal or vertical arrangement?
+            if self._colorbar_location in ("left", "right"):
+                self._colorbar_pad = self._horiz_pad_size.fixed_size
+            else:
+                self._colorbar_pad = self._vert_pad_size.fixed_size
+        self.cbar_axes = [
+            _cbaraxes_class_factory(self._defaultAxesClass)(
+                self.axes_all[0].get_figure(root=False), self._divider.get_position(),
+                orientation=self._colorbar_location)
+            for _ in range(self.ngrids)]
+
+        cb_mode = self._colorbar_mode
+        cb_location = self._colorbar_location
+
+        h = []
+        v = []
+
+        h_ax_pos = []
+        h_cb_pos = []
+        if cb_mode == "single" and cb_location in ("left", "bottom"):
+            if cb_location == "left":
+                sz = self._nrows * Size.AxesX(self.axes_llc)
+                h.append(Size.from_any(self._colorbar_size, sz))
+                h.append(Size.from_any(self._colorbar_pad, sz))
+                locator = self._divider.new_locator(nx=0, ny=0, ny1=-1)
+            elif cb_location == "bottom":
+                sz = self._ncols * Size.AxesY(self.axes_llc)
+                v.append(Size.from_any(self._colorbar_size, sz))
+                v.append(Size.from_any(self._colorbar_pad, sz))
+                locator = self._divider.new_locator(nx=0, nx1=-1, ny=0)
+            for i in range(self.ngrids):
+                self.cbar_axes[i].set_visible(False)
+            self.cbar_axes[0].set_axes_locator(locator)
+            self.cbar_axes[0].set_visible(True)
+
+        for col, ax in enumerate(self.axes_row[0]):
+            if col != 0:
+                h.append(self._horiz_pad_size)
+
+            if ax:
+                sz = Size.AxesX(ax, aspect="axes", ref_ax=self.axes_all[0])
+            else:
+                sz = Size.AxesX(self.axes_all[0],
+                                aspect="axes", ref_ax=self.axes_all[0])
+
+            if (cb_location == "left"
+                    and (cb_mode == "each"
+                         or (cb_mode == "edge" and col == 0))):
+                h_cb_pos.append(len(h))
+                h.append(Size.from_any(self._colorbar_size, sz))
+                h.append(Size.from_any(self._colorbar_pad, sz))
+
+            h_ax_pos.append(len(h))
+            h.append(sz)
+
+            if (cb_location == "right"
+                    and (cb_mode == "each"
+                         or (cb_mode == "edge" and col == self._ncols - 1))):
+                h.append(Size.from_any(self._colorbar_pad, sz))
+                h_cb_pos.append(len(h))
+                h.append(Size.from_any(self._colorbar_size, sz))
+
+        v_ax_pos = []
+        v_cb_pos = []
+        for row, ax in enumerate(self.axes_column[0][::-1]):
+            if row != 0:
+                v.append(self._vert_pad_size)
+
+            if ax:
+                sz = Size.AxesY(ax, aspect="axes", ref_ax=self.axes_all[0])
+            else:
+                sz = Size.AxesY(self.axes_all[0],
+                                aspect="axes", ref_ax=self.axes_all[0])
+
+            if (cb_location == "bottom"
+                    and (cb_mode == "each"
+                         or (cb_mode == "edge" and row == 0))):
+                v_cb_pos.append(len(v))
+                v.append(Size.from_any(self._colorbar_size, sz))
+                v.append(Size.from_any(self._colorbar_pad, sz))
+
+            v_ax_pos.append(len(v))
+            v.append(sz)
+
+            if (cb_location == "top"
+                    and (cb_mode == "each"
+                         or (cb_mode == "edge" and row == self._nrows - 1))):
+                v.append(Size.from_any(self._colorbar_pad, sz))
+                v_cb_pos.append(len(v))
+                v.append(Size.from_any(self._colorbar_size, sz))
+
+        for i in range(self.ngrids):
+            col, row = self._get_col_row(i)
+            locator = self._divider.new_locator(nx=h_ax_pos[col],
+                                                ny=v_ax_pos[self._nrows-1-row])
+            self.axes_all[i].set_axes_locator(locator)
+
+            if cb_mode == "each":
+                if cb_location in ("right", "left"):
+                    locator = self._divider.new_locator(
+                        nx=h_cb_pos[col], ny=v_ax_pos[self._nrows - 1 - row])
+
+                elif cb_location in ("top", "bottom"):
+                    locator = self._divider.new_locator(
+                        nx=h_ax_pos[col], ny=v_cb_pos[self._nrows - 1 - row])
+
+                self.cbar_axes[i].set_axes_locator(locator)
+            elif cb_mode == "edge":
+                if (cb_location == "left" and col == 0
+                        or cb_location == "right" and col == self._ncols - 1):
+                    locator = self._divider.new_locator(
+                        nx=h_cb_pos[0], ny=v_ax_pos[self._nrows - 1 - row])
+                    self.cbar_axes[row].set_axes_locator(locator)
+                elif (cb_location == "bottom" and row == self._nrows - 1
+                      or cb_location == "top" and row == 0):
+                    locator = self._divider.new_locator(nx=h_ax_pos[col],
+                                                        ny=v_cb_pos[0])
+                    self.cbar_axes[col].set_axes_locator(locator)
+
+        if cb_mode == "single":
+            if cb_location == "right":
+                sz = self._nrows * Size.AxesX(self.axes_llc)
+                h.append(Size.from_any(self._colorbar_pad, sz))
+                h.append(Size.from_any(self._colorbar_size, sz))
+                locator = self._divider.new_locator(nx=-2, ny=0, ny1=-1)
+            elif cb_location == "top":
+                sz = self._ncols * Size.AxesY(self.axes_llc)
+                v.append(Size.from_any(self._colorbar_pad, sz))
+                v.append(Size.from_any(self._colorbar_size, sz))
+                locator = self._divider.new_locator(nx=0, nx1=-1, ny=-2)
+            if cb_location in ("right", "top"):
+                for i in range(self.ngrids):
+                    self.cbar_axes[i].set_visible(False)
+                self.cbar_axes[0].set_axes_locator(locator)
+                self.cbar_axes[0].set_visible(True)
+        elif cb_mode == "each":
+            for i in range(self.ngrids):
+                self.cbar_axes[i].set_visible(True)
+        elif cb_mode == "edge":
+            if cb_location in ("right", "left"):
+                count = self._nrows
+            else:
+                count = self._ncols
+            for i in range(count):
+                self.cbar_axes[i].set_visible(True)
+            for j in range(i + 1, self.ngrids):
+                self.cbar_axes[j].set_visible(False)
+        else:
+            for i in range(self.ngrids):
+                self.cbar_axes[i].set_visible(False)
+                self.cbar_axes[i].set_position([1., 1., 0.001, 0.001],
+                                               which="active")
+
+        self._divider.set_horizontal(h)
+        self._divider.set_vertical(v)
+
+
+AxesGrid = ImageGrid

venv/lib/python3.13/site-packages/mpl_toolkits/axes_grid1/axes_rgb.py

@@ -0,0 +1,157 @@
+from types import MethodType
+
+import numpy as np
+
+from .axes_divider import make_axes_locatable, Size
+from .mpl_axes import Axes, SimpleAxisArtist
+
+
+def make_rgb_axes(ax, pad=0.01, axes_class=None, **kwargs):
+    """
+    Parameters
+    ----------
+    ax : `~matplotlib.axes.Axes`
+        Axes instance to create the RGB Axes in.
+    pad : float, optional
+        Fraction of the Axes height to pad.
+    axes_class : `matplotlib.axes.Axes` or None, optional
+        Axes class to use for the R, G, and B Axes. If None, use
+        the same class as *ax*.
+    **kwargs
+        Forwarded to *axes_class* init for the R, G, and B Axes.
+    """
+
+    divider = make_axes_locatable(ax)
+
+    pad_size = pad * Size.AxesY(ax)
+
+    xsize = ((1-2*pad)/3) * Size.AxesX(ax)
+    ysize = ((1-2*pad)/3) * Size.AxesY(ax)
+
+    divider.set_horizontal([Size.AxesX(ax), pad_size, xsize])
+    divider.set_vertical([ysize, pad_size, ysize, pad_size, ysize])
+
+    ax.set_axes_locator(divider.new_locator(0, 0, ny1=-1))
+
+    ax_rgb = []
+    if axes_class is None:
+        axes_class = type(ax)
+
+    for ny in [4, 2, 0]:
+        ax1 = axes_class(ax.get_figure(), ax.get_position(original=True),
+                         sharex=ax, sharey=ax, **kwargs)
+        locator = divider.new_locator(nx=2, ny=ny)
+        ax1.set_axes_locator(locator)
+        for t in ax1.yaxis.get_ticklabels() + ax1.xaxis.get_ticklabels():
+            t.set_visible(False)
+        try:
+            for axis in ax1.axis.values():
+                axis.major_ticklabels.set_visible(False)
+        except AttributeError:
+            pass
+
+        ax_rgb.append(ax1)
+
+    fig = ax.get_figure()
+    for ax1 in ax_rgb:
+        fig.add_axes(ax1)
+
+    return ax_rgb
+
+
+class RGBAxes:
+    """
+    4-panel `~.Axes.imshow` (RGB, R, G, B).
+
+    Layout::
+
+        ┌───────────────┬─────┐
+        │               │  R  │
+        │               ├─────┤
+        │      RGB      │  G  │
+        │               ├─────┤
+        │               │  B  │
+        └───────────────┴─────┘
+
+    Subclasses can override the ``_defaultAxesClass`` attribute.
+    By default RGBAxes uses `.mpl_axes.Axes`.
+
+    Attributes
+    ----------
+    RGB : ``_defaultAxesClass``
+        The Axes object for the three-channel `~.Axes.imshow`.
+    R : ``_defaultAxesClass``
+        The Axes object for the red channel `~.Axes.imshow`.
+    G : ``_defaultAxesClass``
+        The Axes object for the green channel `~.Axes.imshow`.
+    B : ``_defaultAxesClass``
+        The Axes object for the blue channel `~.Axes.imshow`.
+    """
+
+    _defaultAxesClass = Axes
+
+    def __init__(self, *args, pad=0, **kwargs):
+        """
+        Parameters
+        ----------
+        pad : float, default: 0
+            Fraction of the Axes height to put as padding.
+        axes_class : `~matplotlib.axes.Axes`
+            Axes class to use. If not provided, ``_defaultAxesClass`` is used.
+        *args
+            Forwarded to *axes_class* init for the RGB Axes
+        **kwargs
+            Forwarded to *axes_class* init for the RGB, R, G, and B Axes
+        """
+        axes_class = kwargs.pop("axes_class", self._defaultAxesClass)
+        self.RGB = ax = axes_class(*args, **kwargs)
+        ax.get_figure().add_axes(ax)
+        self.R, self.G, self.B = make_rgb_axes(
+            ax, pad=pad, axes_class=axes_class, **kwargs)
+        # Set the line color and ticks for the axes.
+        for ax1 in [self.RGB, self.R, self.G, self.B]:
+            if isinstance(ax1.axis, MethodType):
+                ad = Axes.AxisDict(self)
+                ad.update(
+                    bottom=SimpleAxisArtist(ax1.xaxis, 1, ax1.spines["bottom"]),
+                    top=SimpleAxisArtist(ax1.xaxis, 2, ax1.spines["top"]),
+                    left=SimpleAxisArtist(ax1.yaxis, 1, ax1.spines["left"]),
+                    right=SimpleAxisArtist(ax1.yaxis, 2, ax1.spines["right"]))
+            else:
+                ad = ax1.axis
+            ad[:].line.set_color("w")
+            ad[:].major_ticks.set_markeredgecolor("w")
+
+    def imshow_rgb(self, r, g, b, **kwargs):
+        """
+        Create the four images {rgb, r, g, b}.
+
+        Parameters
+        ----------
+        r, g, b : array-like
+            The red, green, and blue arrays.
+        **kwargs
+            Forwarded to `~.Axes.imshow` calls for the four images.
+
+        Returns
+        -------
+        rgb : `~matplotlib.image.AxesImage`
+        r : `~matplotlib.image.AxesImage`
+        g : `~matplotlib.image.AxesImage`
+        b : `~matplotlib.image.AxesImage`
+        """
+        if not (r.shape == g.shape == b.shape):
+            raise ValueError(
+                f'Input shapes ({r.shape}, {g.shape}, {b.shape}) do not match')
+        RGB = np.dstack([r, g, b])
+        R = np.zeros_like(RGB)
+        R[:, :, 0] = r
+        G = np.zeros_like(RGB)
+        G[:, :, 1] = g
+        B = np.zeros_like(RGB)
+        B[:, :, 2] = b
+        im_rgb = self.RGB.imshow(RGB, **kwargs)
+        im_r = self.R.imshow(R, **kwargs)
+        im_g = self.G.imshow(G, **kwargs)
+        im_b = self.B.imshow(B, **kwargs)
+        return im_rgb, im_r, im_g, im_b

venv/lib/python3.13/site-packages/mpl_toolkits/axes_grid1/axes_size.py

@@ -0,0 +1,271 @@
+"""
+Provides classes of simple units that will be used with `.AxesDivider`
+class (or others) to determine the size of each Axes. The unit
+classes define `get_size` method that returns a tuple of two floats,
+meaning relative and absolute sizes, respectively.
+
+Note that this class is nothing more than a simple tuple of two
+floats. Take a look at the Divider class to see how these two
+values are used.
+
+Once created, the unit classes can be modified by simple arithmetic
+operations: addition /subtraction with another unit type or a real number and scaling
+(multiplication or division) by a real number.
+"""
+
+from numbers import Real
+
+from matplotlib import _api
+from matplotlib.axes import Axes
+
+
+class _Base:
+    def __rmul__(self, other):
+        return self * other
+
+    def __mul__(self, other):
+        if not isinstance(other, Real):
+            return NotImplemented
+        return Fraction(other, self)
+
+    def __div__(self, other):
+        return (1 / other) * self
+
+    def __add__(self, other):
+        if isinstance(other, _Base):
+            return Add(self, other)
+        else:
+            return Add(self, Fixed(other))
+
+    def __neg__(self):
+        return -1 * self
+
+    def __radd__(self, other):
+        # other cannot be a _Base instance, because A + B would trigger
+        # A.__add__(B) first.
+        return Add(self, Fixed(other))
+
+    def __sub__(self, other):
+        return self + (-other)
+
+    def get_size(self, renderer):
+        """
+        Return two-float tuple with relative and absolute sizes.
+        """
+        raise NotImplementedError("Subclasses must implement")
+
+
+class Add(_Base):
+    """
+    Sum of two sizes.
+    """
+
+    def __init__(self, a, b):
+        self._a = a
+        self._b = b
+
+    def get_size(self, renderer):
+        a_rel_size, a_abs_size = self._a.get_size(renderer)
+        b_rel_size, b_abs_size = self._b.get_size(renderer)
+        return a_rel_size + b_rel_size, a_abs_size + b_abs_size
+
+
+class Fixed(_Base):
+    """
+    Simple fixed size with absolute part = *fixed_size* and relative part = 0.
+    """
+
+    def __init__(self, fixed_size):
+        _api.check_isinstance(Real, fixed_size=fixed_size)
+        self.fixed_size = fixed_size
+
+    def get_size(self, renderer):
+        rel_size = 0.
+        abs_size = self.fixed_size
+        return rel_size, abs_size
+
+
+class Scaled(_Base):
+    """
+    Simple scaled(?) size with absolute part = 0 and
+    relative part = *scalable_size*.
+    """
+
+    def __init__(self, scalable_size):
+        self._scalable_size = scalable_size
+
+    def get_size(self, renderer):
+        rel_size = self._scalable_size
+        abs_size = 0.
+        return rel_size, abs_size
+
+Scalable = Scaled
+
+
+def _get_axes_aspect(ax):
+    aspect = ax.get_aspect()
+    if aspect == "auto":
+        aspect = 1.
+    return aspect
+
+
+class AxesX(_Base):
+    """
+    Scaled size whose relative part corresponds to the data width
+    of the *axes* multiplied by the *aspect*.
+    """
+
+    def __init__(self, axes, aspect=1., ref_ax=None):
+        self._axes = axes
+        self._aspect = aspect
+        if aspect == "axes" and ref_ax is None:
+            raise ValueError("ref_ax must be set when aspect='axes'")
+        self._ref_ax = ref_ax
+
+    def get_size(self, renderer):
+        l1, l2 = self._axes.get_xlim()
+        if self._aspect == "axes":
+            ref_aspect = _get_axes_aspect(self._ref_ax)
+            aspect = ref_aspect / _get_axes_aspect(self._axes)
+        else:
+            aspect = self._aspect
+
+        rel_size = abs(l2-l1)*aspect
+        abs_size = 0.
+        return rel_size, abs_size
+
+
+class AxesY(_Base):
+    """
+    Scaled size whose relative part corresponds to the data height
+    of the *axes* multiplied by the *aspect*.
+    """
+
+    def __init__(self, axes, aspect=1., ref_ax=None):
+        self._axes = axes
+        self._aspect = aspect
+        if aspect == "axes" and ref_ax is None:
+            raise ValueError("ref_ax must be set when aspect='axes'")
+        self._ref_ax = ref_ax
+
+    def get_size(self, renderer):
+        l1, l2 = self._axes.get_ylim()
+
+        if self._aspect == "axes":
+            ref_aspect = _get_axes_aspect(self._ref_ax)
+            aspect = _get_axes_aspect(self._axes)
+        else:
+            aspect = self._aspect
+
+        rel_size = abs(l2-l1)*aspect
+        abs_size = 0.
+        return rel_size, abs_size
+
+
+class MaxExtent(_Base):
+    """
+    Size whose absolute part is either the largest width or the largest height
+    of the given *artist_list*.
+    """
+
+    def __init__(self, artist_list, w_or_h):
+        self._artist_list = artist_list
+        _api.check_in_list(["width", "height"], w_or_h=w_or_h)
+        self._w_or_h = w_or_h
+
+    def add_artist(self, a):
+        self._artist_list.append(a)
+
+    def get_size(self, renderer):
+        rel_size = 0.
+        extent_list = [
+            getattr(a.get_window_extent(renderer), self._w_or_h) / a.figure.dpi
+            for a in self._artist_list]
+        abs_size = max(extent_list, default=0)
+        return rel_size, abs_size
+
+
+class MaxWidth(MaxExtent):
+    """
+    Size whose absolute part is the largest width of the given *artist_list*.
+    """
+
+    def __init__(self, artist_list):
+        super().__init__(artist_list, "width")
+
+
+class MaxHeight(MaxExtent):
+    """
+    Size whose absolute part is the largest height of the given *artist_list*.
+    """
+
+    def __init__(self, artist_list):
+        super().__init__(artist_list, "height")
+
+
+class Fraction(_Base):
+    """
+    An instance whose size is a *fraction* of the *ref_size*.
+
+    >>> s = Fraction(0.3, AxesX(ax))
+    """
+
+    def __init__(self, fraction, ref_size):
+        _api.check_isinstance(Real, fraction=fraction)
+        self._fraction_ref = ref_size
+        self._fraction = fraction
+
+    def get_size(self, renderer):
+        if self._fraction_ref is None:
+            return self._fraction, 0.
+        else:
+            r, a = self._fraction_ref.get_size(renderer)
+            rel_size = r*self._fraction
+            abs_size = a*self._fraction
+            return rel_size, abs_size
+
+
+def from_any(size, fraction_ref=None):
+    """
+    Create a Fixed unit when the first argument is a float, or a
+    Fraction unit if that is a string that ends with %. The second
+    argument is only meaningful when Fraction unit is created.
+
+    >>> from mpl_toolkits.axes_grid1.axes_size import from_any
+    >>> a = from_any(1.2) # => Fixed(1.2)
+    >>> from_any("50%", a) # => Fraction(0.5, a)
+    """
+    if isinstance(size, Real):
+        return Fixed(size)
+    elif isinstance(size, str):
+        if size[-1] == "%":
+            return Fraction(float(size[:-1]) / 100, fraction_ref)
+    raise ValueError("Unknown format")
+
+
+class _AxesDecorationsSize(_Base):
+    """
+    Fixed size, corresponding to the size of decorations on a given Axes side.
+    """
+
+    _get_size_map = {
+        "left":   lambda tight_bb, axes_bb: axes_bb.xmin - tight_bb.xmin,
+        "right":  lambda tight_bb, axes_bb: tight_bb.xmax - axes_bb.xmax,
+        "bottom": lambda tight_bb, axes_bb: axes_bb.ymin - tight_bb.ymin,
+        "top":    lambda tight_bb, axes_bb: tight_bb.ymax - axes_bb.ymax,
+    }
+
+    def __init__(self, ax, direction):
+        _api.check_in_list(self._get_size_map, direction=direction)
+        self._direction = direction
+        self._ax_list = [ax] if isinstance(ax, Axes) else ax
+
+    def get_size(self, renderer):
+        sz = max([
+            self._get_size_map[self._direction](
+                ax.get_tightbbox(renderer, call_axes_locator=False), ax.bbox)
+            for ax in self._ax_list])
+        dpi = renderer.points_to_pixels(72)
+        abs_size = sz / dpi
+        rel_size = 0
+        return rel_size, abs_size

venv/lib/python3.13/site-packages/mpl_toolkits/axes_grid1/inset_locator.py

@@ -0,0 +1,519 @@
+"""
+A collection of functions and objects for creating or placing inset axes.
+"""
+
+from matplotlib import _api, _docstring
+from matplotlib.offsetbox import AnchoredOffsetbox
+from matplotlib.patches import Patch, Rectangle
+from matplotlib.path import Path
+from matplotlib.transforms import Bbox
+from matplotlib.transforms import IdentityTransform, TransformedBbox
+
+from . import axes_size as Size
+from .parasite_axes import HostAxes
+
+
+class AnchoredLocatorBase(AnchoredOffsetbox):
+    def __init__(self, bbox_to_anchor, offsetbox, loc,
+                 borderpad=0.5, bbox_transform=None):
+        super().__init__(
+            loc, pad=0., child=None, borderpad=borderpad,
+            bbox_to_anchor=bbox_to_anchor, bbox_transform=bbox_transform
+        )
+
+    def draw(self, renderer):
+        raise RuntimeError("No draw method should be called")
+
+    def __call__(self, ax, renderer):
+        fig = ax.get_figure(root=False)
+        if renderer is None:
+            renderer = fig._get_renderer()
+        self.axes = ax
+        bbox = self.get_window_extent(renderer)
+        px, py = self.get_offset(bbox.width, bbox.height, 0, 0, renderer)
+        bbox_canvas = Bbox.from_bounds(px, py, bbox.width, bbox.height)
+        tr = fig.transSubfigure.inverted()
+        return TransformedBbox(bbox_canvas, tr)
+
+
+class AnchoredSizeLocator(AnchoredLocatorBase):
+    def __init__(self, bbox_to_anchor, x_size, y_size, loc,
+                 borderpad=0.5, bbox_transform=None):
+        super().__init__(
+            bbox_to_anchor, None, loc,
+            borderpad=borderpad, bbox_transform=bbox_transform
+        )
+
+        self.x_size = Size.from_any(x_size)
+        self.y_size = Size.from_any(y_size)
+
+    def get_bbox(self, renderer):
+        bbox = self.get_bbox_to_anchor()
+        dpi = renderer.points_to_pixels(72.)
+
+        r, a = self.x_size.get_size(renderer)
+        width = bbox.width * r + a * dpi
+        r, a = self.y_size.get_size(renderer)
+        height = bbox.height * r + a * dpi
+
+        fontsize = renderer.points_to_pixels(self.prop.get_size_in_points())
+        pad = self.pad * fontsize
+
+        return Bbox.from_bounds(0, 0, width, height).padded(pad)
+
+
+class AnchoredZoomLocator(AnchoredLocatorBase):
+    def __init__(self, parent_axes, zoom, loc,
+                 borderpad=0.5,
+                 bbox_to_anchor=None,
+                 bbox_transform=None):
+        self.parent_axes = parent_axes
+        self.zoom = zoom
+        if bbox_to_anchor is None:
+            bbox_to_anchor = parent_axes.bbox
+        super().__init__(
+            bbox_to_anchor, None, loc, borderpad=borderpad,
+            bbox_transform=bbox_transform)
+
+    def get_bbox(self, renderer):
+        bb = self.parent_axes.transData.transform_bbox(self.axes.viewLim)
+        fontsize = renderer.points_to_pixels(self.prop.get_size_in_points())
+        pad = self.pad * fontsize
+        return (
+            Bbox.from_bounds(
+                0, 0, abs(bb.width * self.zoom), abs(bb.height * self.zoom))
+            .padded(pad))
+
+
+class BboxPatch(Patch):
+    @_docstring.interpd
+    def __init__(self, bbox, **kwargs):
+        """
+        Patch showing the shape bounded by a Bbox.
+
+        Parameters
+        ----------
+        bbox : `~matplotlib.transforms.Bbox`
+            Bbox to use for the extents of this patch.
+
+        **kwargs
+            Patch properties. Valid arguments include:
+
+            %(Patch:kwdoc)s
+        """
+        if "transform" in kwargs:
+            raise ValueError("transform should not be set")
+
+        kwargs["transform"] = IdentityTransform()
+        super().__init__(**kwargs)
+        self.bbox = bbox
+
+    def get_path(self):
+        # docstring inherited
+        x0, y0, x1, y1 = self.bbox.extents
+        return Path._create_closed([(x0, y0), (x1, y0), (x1, y1), (x0, y1)])
+
+
+class BboxConnector(Patch):
+    @staticmethod
+    def get_bbox_edge_pos(bbox, loc):
+        """
+        Return the ``(x, y)`` coordinates of corner *loc* of *bbox*; parameters
+        behave as documented for the `.BboxConnector` constructor.
+        """
+        x0, y0, x1, y1 = bbox.extents
+        if loc == 1:
+            return x1, y1
+        elif loc == 2:
+            return x0, y1
+        elif loc == 3:
+            return x0, y0
+        elif loc == 4:
+            return x1, y0
+
+    @staticmethod
+    def connect_bbox(bbox1, bbox2, loc1, loc2=None):
+        """
+        Construct a `.Path` connecting corner *loc1* of *bbox1* to corner
+        *loc2* of *bbox2*, where parameters behave as documented as for the
+        `.BboxConnector` constructor.
+        """
+        if isinstance(bbox1, Rectangle):
+            bbox1 = TransformedBbox(Bbox.unit(), bbox1.get_transform())
+        if isinstance(bbox2, Rectangle):
+            bbox2 = TransformedBbox(Bbox.unit(), bbox2.get_transform())
+        if loc2 is None:
+            loc2 = loc1
+        x1, y1 = BboxConnector.get_bbox_edge_pos(bbox1, loc1)
+        x2, y2 = BboxConnector.get_bbox_edge_pos(bbox2, loc2)
+        return Path([[x1, y1], [x2, y2]])
+
+    @_docstring.interpd
+    def __init__(self, bbox1, bbox2, loc1, loc2=None, **kwargs):
+        """
+        Connect two bboxes with a straight line.
+
+        Parameters
+        ----------
+        bbox1, bbox2 : `~matplotlib.transforms.Bbox`
+            Bounding boxes to connect.
+
+        loc1, loc2 : {1, 2, 3, 4}
+            Corner of *bbox1* and *bbox2* to draw the line. Valid values are::
+
+                'upper right'  : 1,
+                'upper left'   : 2,
+                'lower left'   : 3,
+                'lower right'  : 4
+
+            *loc2* is optional and defaults to *loc1*.
+
+        **kwargs
+            Patch properties for the line drawn. Valid arguments include:
+
+            %(Patch:kwdoc)s
+        """
+        if "transform" in kwargs:
+            raise ValueError("transform should not be set")
+
+        kwargs["transform"] = IdentityTransform()
+        kwargs.setdefault(
+            "fill", bool({'fc', 'facecolor', 'color'}.intersection(kwargs)))
+        super().__init__(**kwargs)
+        self.bbox1 = bbox1
+        self.bbox2 = bbox2
+        self.loc1 = loc1
+        self.loc2 = loc2
+
+    def get_path(self):
+        # docstring inherited
+        return self.connect_bbox(self.bbox1, self.bbox2,
+                                 self.loc1, self.loc2)
+
+
+class BboxConnectorPatch(BboxConnector):
+    @_docstring.interpd
+    def __init__(self, bbox1, bbox2, loc1a, loc2a, loc1b, loc2b, **kwargs):
+        """
+        Connect two bboxes with a quadrilateral.
+
+        The quadrilateral is specified by two lines that start and end at
+        corners of the bboxes. The four sides of the quadrilateral are defined
+        by the two lines given, the line between the two corners specified in
+        *bbox1* and the line between the two corners specified in *bbox2*.
+
+        Parameters
+        ----------
+        bbox1, bbox2 : `~matplotlib.transforms.Bbox`
+            Bounding boxes to connect.
+
+        loc1a, loc2a, loc1b, loc2b : {1, 2, 3, 4}
+            The first line connects corners *loc1a* of *bbox1* and *loc2a* of
+            *bbox2*; the second line connects corners *loc1b* of *bbox1* and
+            *loc2b* of *bbox2*.  Valid values are::
+
+                'upper right'  : 1,
+                'upper left'   : 2,
+                'lower left'   : 3,
+                'lower right'  : 4
+
+        **kwargs
+            Patch properties for the line drawn:
+
+            %(Patch:kwdoc)s
+        """
+        if "transform" in kwargs:
+            raise ValueError("transform should not be set")
+        super().__init__(bbox1, bbox2, loc1a, loc2a, **kwargs)
+        self.loc1b = loc1b
+        self.loc2b = loc2b
+
+    def get_path(self):
+        # docstring inherited
+        path1 = self.connect_bbox(self.bbox1, self.bbox2, self.loc1, self.loc2)
+        path2 = self.connect_bbox(self.bbox2, self.bbox1,
+                                  self.loc2b, self.loc1b)
+        path_merged = [*path1.vertices, *path2.vertices, path1.vertices[0]]
+        return Path(path_merged)
+
+
+def _add_inset_axes(parent_axes, axes_class, axes_kwargs, axes_locator):
+    """Helper function to add an inset axes and disable navigation in it."""
+    if axes_class is None:
+        axes_class = HostAxes
+    if axes_kwargs is None:
+        axes_kwargs = {}
+    fig = parent_axes.get_figure(root=False)
+    inset_axes = axes_class(
+        fig, parent_axes.get_position(),
+        **{"navigate": False, **axes_kwargs, "axes_locator": axes_locator})
+    return fig.add_axes(inset_axes)
+
+
+@_docstring.interpd
+def inset_axes(parent_axes, width, height, loc='upper right',
+               bbox_to_anchor=None, bbox_transform=None,
+               axes_class=None, axes_kwargs=None,
+               borderpad=0.5):
+    """
+    Create an inset axes with a given width and height.
+
+    Both sizes used can be specified either in inches or percentage.
+    For example,::
+
+        inset_axes(parent_axes, width='40%%', height='30%%', loc='lower left')
+
+    creates in inset axes in the lower left corner of *parent_axes* which spans
+    over 30%% in height and 40%% in width of the *parent_axes*. Since the usage
+    of `.inset_axes` may become slightly tricky when exceeding such standard
+    cases, it is recommended to read :doc:`the examples
+    </gallery/axes_grid1/inset_locator_demo>`.
+
+    Notes
+    -----
+    The meaning of *bbox_to_anchor* and *bbox_to_transform* is interpreted
+    differently from that of legend. The value of bbox_to_anchor
+    (or the return value of its get_points method; the default is
+    *parent_axes.bbox*) is transformed by the bbox_transform (the default
+    is Identity transform) and then interpreted as points in the pixel
+    coordinate (which is dpi dependent).
+
+    Thus, following three calls are identical and creates an inset axes
+    with respect to the *parent_axes*::
+
+       axins = inset_axes(parent_axes, "30%%", "40%%")
+       axins = inset_axes(parent_axes, "30%%", "40%%",
+                          bbox_to_anchor=parent_axes.bbox)
+       axins = inset_axes(parent_axes, "30%%", "40%%",
+                          bbox_to_anchor=(0, 0, 1, 1),
+                          bbox_transform=parent_axes.transAxes)
+
+    Parameters
+    ----------
+    parent_axes : `matplotlib.axes.Axes`
+        Axes to place the inset axes.
+
+    width, height : float or str
+        Size of the inset axes to create. If a float is provided, it is
+        the size in inches, e.g. *width=1.3*. If a string is provided, it is
+        the size in relative units, e.g. *width='40%%'*. By default, i.e. if
+        neither *bbox_to_anchor* nor *bbox_transform* are specified, those
+        are relative to the parent_axes. Otherwise, they are to be understood
+        relative to the bounding box provided via *bbox_to_anchor*.
+
+    loc : str, default: 'upper right'
+        Location to place the inset axes.  Valid locations are
+        'upper left', 'upper center', 'upper right',
+        'center left', 'center', 'center right',
+        'lower left', 'lower center', 'lower right'.
+        For backward compatibility, numeric values are accepted as well.
+        See the parameter *loc* of `.Legend` for details.
+
+    bbox_to_anchor : tuple or `~matplotlib.transforms.BboxBase`, optional
+        Bbox that the inset axes will be anchored to. If None,
+        a tuple of (0, 0, 1, 1) is used if *bbox_transform* is set
+        to *parent_axes.transAxes* or *parent_axes.figure.transFigure*.
+        Otherwise, *parent_axes.bbox* is used. If a tuple, can be either
+        [left, bottom, width, height], or [left, bottom].
+        If the kwargs *width* and/or *height* are specified in relative units,
+        the 2-tuple [left, bottom] cannot be used. Note that,
+        unless *bbox_transform* is set, the units of the bounding box
+        are interpreted in the pixel coordinate. When using *bbox_to_anchor*
+        with tuple, it almost always makes sense to also specify
+        a *bbox_transform*. This might often be the axes transform
+        *parent_axes.transAxes*.
+
+    bbox_transform : `~matplotlib.transforms.Transform`, optional
+        Transformation for the bbox that contains the inset axes.
+        If None, a `.transforms.IdentityTransform` is used. The value
+        of *bbox_to_anchor* (or the return value of its get_points method)
+        is transformed by the *bbox_transform* and then interpreted
+        as points in the pixel coordinate (which is dpi dependent).
+        You may provide *bbox_to_anchor* in some normalized coordinate,
+        and give an appropriate transform (e.g., *parent_axes.transAxes*).
+
+    axes_class : `~matplotlib.axes.Axes` type, default: `.HostAxes`
+        The type of the newly created inset axes.
+
+    axes_kwargs : dict, optional
+        Keyword arguments to pass to the constructor of the inset axes.
+        Valid arguments include:
+
+        %(Axes:kwdoc)s
+
+    borderpad : float, default: 0.5
+        Padding between inset axes and the bbox_to_anchor.
+        The units are axes font size, i.e. for a default font size of 10 points
+        *borderpad = 0.5* is equivalent to a padding of 5 points.
+
+    Returns
+    -------
+    inset_axes : *axes_class*
+        Inset axes object created.
+    """
+
+    if (bbox_transform in [parent_axes.transAxes,
+                           parent_axes.get_figure(root=False).transFigure]
+            and bbox_to_anchor is None):
+        _api.warn_external("Using the axes or figure transform requires a "
+                           "bounding box in the respective coordinates. "
+                           "Using bbox_to_anchor=(0, 0, 1, 1) now.")
+        bbox_to_anchor = (0, 0, 1, 1)
+    if bbox_to_anchor is None:
+        bbox_to_anchor = parent_axes.bbox
+    if (isinstance(bbox_to_anchor, tuple) and
+            (isinstance(width, str) or isinstance(height, str))):
+        if len(bbox_to_anchor) != 4:
+            raise ValueError("Using relative units for width or height "
+                             "requires to provide a 4-tuple or a "
+                             "`Bbox` instance to `bbox_to_anchor.")
+    return _add_inset_axes(
+        parent_axes, axes_class, axes_kwargs,
+        AnchoredSizeLocator(
+            bbox_to_anchor, width, height, loc=loc,
+            bbox_transform=bbox_transform, borderpad=borderpad))
+
+
+@_docstring.interpd
+def zoomed_inset_axes(parent_axes, zoom, loc='upper right',
+                      bbox_to_anchor=None, bbox_transform=None,
+                      axes_class=None, axes_kwargs=None,
+                      borderpad=0.5):
+    """
+    Create an anchored inset axes by scaling a parent axes. For usage, also see
+    :doc:`the examples </gallery/axes_grid1/inset_locator_demo2>`.
+
+    Parameters
+    ----------
+    parent_axes : `~matplotlib.axes.Axes`
+        Axes to place the inset axes.
+
+    zoom : float
+        Scaling factor of the data axes. *zoom* > 1 will enlarge the
+        coordinates (i.e., "zoomed in"), while *zoom* < 1 will shrink the
+        coordinates (i.e., "zoomed out").
+
+    loc : str, default: 'upper right'
+        Location to place the inset axes.  Valid locations are
+        'upper left', 'upper center', 'upper right',
+        'center left', 'center', 'center right',
+        'lower left', 'lower center', 'lower right'.
+        For backward compatibility, numeric values are accepted as well.
+        See the parameter *loc* of `.Legend` for details.
+
+    bbox_to_anchor : tuple or `~matplotlib.transforms.BboxBase`, optional
+        Bbox that the inset axes will be anchored to. If None,
+        *parent_axes.bbox* is used. If a tuple, can be either
+        [left, bottom, width, height], or [left, bottom].
+        If the kwargs *width* and/or *height* are specified in relative units,
+        the 2-tuple [left, bottom] cannot be used. Note that
+        the units of the bounding box are determined through the transform
+        in use. When using *bbox_to_anchor* it almost always makes sense to
+        also specify a *bbox_transform*. This might often be the axes transform
+        *parent_axes.transAxes*.
+
+    bbox_transform : `~matplotlib.transforms.Transform`, optional
+        Transformation for the bbox that contains the inset axes.
+        If None, a `.transforms.IdentityTransform` is used (i.e. pixel
+        coordinates). This is useful when not providing any argument to
+        *bbox_to_anchor*. When using *bbox_to_anchor* it almost always makes
+        sense to also specify a *bbox_transform*. This might often be the
+        axes transform *parent_axes.transAxes*. Inversely, when specifying
+        the axes- or figure-transform here, be aware that not specifying
+        *bbox_to_anchor* will use *parent_axes.bbox*, the units of which are
+        in display (pixel) coordinates.
+
+    axes_class : `~matplotlib.axes.Axes` type, default: `.HostAxes`
+        The type of the newly created inset axes.
+
+    axes_kwargs : dict, optional
+        Keyword arguments to pass to the constructor of the inset axes.
+        Valid arguments include:
+
+        %(Axes:kwdoc)s
+
+    borderpad : float, default: 0.5
+        Padding between inset axes and the bbox_to_anchor.
+        The units are axes font size, i.e. for a default font size of 10 points
+        *borderpad = 0.5* is equivalent to a padding of 5 points.
+
+    Returns
+    -------
+    inset_axes : *axes_class*
+        Inset axes object created.
+    """
+
+    return _add_inset_axes(
+        parent_axes, axes_class, axes_kwargs,
+        AnchoredZoomLocator(
+            parent_axes, zoom=zoom, loc=loc,
+            bbox_to_anchor=bbox_to_anchor, bbox_transform=bbox_transform,
+            borderpad=borderpad))
+
+
+class _TransformedBboxWithCallback(TransformedBbox):
+    """
+    Variant of `.TransformBbox` which calls *callback* before returning points.
+
+    Used by `.mark_inset` to unstale the parent axes' viewlim as needed.
+    """
+
+    def __init__(self, *args, callback, **kwargs):
+        super().__init__(*args, **kwargs)
+        self._callback = callback
+
+    def get_points(self):
+        self._callback()
+        return super().get_points()
+
+
+@_docstring.interpd
+def mark_inset(parent_axes, inset_axes, loc1, loc2, **kwargs):
+    """
+    Draw a box to mark the location of an area represented by an inset axes.
+
+    This function draws a box in *parent_axes* at the bounding box of
+    *inset_axes*, and shows a connection with the inset axes by drawing lines
+    at the corners, giving a "zoomed in" effect.
+
+    Parameters
+    ----------
+    parent_axes : `~matplotlib.axes.Axes`
+        Axes which contains the area of the inset axes.
+
+    inset_axes : `~matplotlib.axes.Axes`
+        The inset axes.
+
+    loc1, loc2 : {1, 2, 3, 4}
+        Corners to use for connecting the inset axes and the area in the
+        parent axes.
+
+    **kwargs
+        Patch properties for the lines and box drawn:
+
+        %(Patch:kwdoc)s
+
+    Returns
+    -------
+    pp : `~matplotlib.patches.Patch`
+        The patch drawn to represent the area of the inset axes.
+
+    p1, p2 : `~matplotlib.patches.Patch`
+        The patches connecting two corners of the inset axes and its area.
+    """
+    rect = _TransformedBboxWithCallback(
+        inset_axes.viewLim, parent_axes.transData,
+        callback=parent_axes._unstale_viewLim)
+
+    kwargs.setdefault("fill", bool({'fc', 'facecolor', 'color'}.intersection(kwargs)))
+    pp = BboxPatch(rect, **kwargs)
+    parent_axes.add_patch(pp)
+
+    p1 = BboxConnector(inset_axes.bbox, rect, loc1=loc1, **kwargs)
+    inset_axes.add_patch(p1)
+    p1.set_clip_on(False)
+    p2 = BboxConnector(inset_axes.bbox, rect, loc1=loc2, **kwargs)
+    inset_axes.add_patch(p2)
+    p2.set_clip_on(False)
+
+    return pp, p1, p2

venv/lib/python3.13/site-packages/mpl_toolkits/axes_grid1/mpl_axes.py

@@ -0,0 +1,128 @@
+import matplotlib.axes as maxes
+from matplotlib.artist import Artist
+from matplotlib.axis import XAxis, YAxis
+
+
+class SimpleChainedObjects:
+    def __init__(self, objects):
+        self._objects = objects
+
+    def __getattr__(self, k):
+        _a = SimpleChainedObjects([getattr(a, k) for a in self._objects])
+        return _a
+
+    def __call__(self, *args, **kwargs):
+        for m in self._objects:
+            m(*args, **kwargs)
+
+
+class Axes(maxes.Axes):
+
+    class AxisDict(dict):
+        def __init__(self, axes):
+            self.axes = axes
+            super().__init__()
+
+        def __getitem__(self, k):
+            if isinstance(k, tuple):
+                r = SimpleChainedObjects(
+                    # super() within a list comprehension needs explicit args.
+                    [super(Axes.AxisDict, self).__getitem__(k1) for k1 in k])
+                return r
+            elif isinstance(k, slice):
+                if k.start is None and k.stop is None and k.step is None:
+                    return SimpleChainedObjects(list(self.values()))
+                else:
+                    raise ValueError("Unsupported slice")
+            else:
+                return dict.__getitem__(self, k)
+
+        def __call__(self, *v, **kwargs):
+            return maxes.Axes.axis(self.axes, *v, **kwargs)
+
+    @property
+    def axis(self):
+        return self._axislines
+
+    def clear(self):
+        # docstring inherited
+        super().clear()
+        # Init axis artists.
+        self._axislines = self.AxisDict(self)
+        self._axislines.update(
+            bottom=SimpleAxisArtist(self.xaxis, 1, self.spines["bottom"]),
+            top=SimpleAxisArtist(self.xaxis, 2, self.spines["top"]),
+            left=SimpleAxisArtist(self.yaxis, 1, self.spines["left"]),
+            right=SimpleAxisArtist(self.yaxis, 2, self.spines["right"]))
+
+
+class SimpleAxisArtist(Artist):
+    def __init__(self, axis, axisnum, spine):
+        self._axis = axis
+        self._axisnum = axisnum
+        self.line = spine
+
+        if isinstance(axis, XAxis):
+            self._axis_direction = ["bottom", "top"][axisnum-1]
+        elif isinstance(axis, YAxis):
+            self._axis_direction = ["left", "right"][axisnum-1]
+        else:
+            raise ValueError(
+                f"axis must be instance of XAxis or YAxis, but got {axis}")
+        super().__init__()
+
+    @property
+    def major_ticks(self):
+        tickline = "tick%dline" % self._axisnum
+        return SimpleChainedObjects([getattr(tick, tickline)
+                                     for tick in self._axis.get_major_ticks()])
+
+    @property
+    def major_ticklabels(self):
+        label = "label%d" % self._axisnum
+        return SimpleChainedObjects([getattr(tick, label)
+                                     for tick in self._axis.get_major_ticks()])
+
+    @property
+    def label(self):
+        return self._axis.label
+
+    def set_visible(self, b):
+        self.toggle(all=b)
+        self.line.set_visible(b)
+        self._axis.set_visible(True)
+        super().set_visible(b)
+
+    def set_label(self, txt):
+        self._axis.set_label_text(txt)
+
+    def toggle(self, all=None, ticks=None, ticklabels=None, label=None):
+
+        if all:
+            _ticks, _ticklabels, _label = True, True, True
+        elif all is not None:
+            _ticks, _ticklabels, _label = False, False, False
+        else:
+            _ticks, _ticklabels, _label = None, None, None
+
+        if ticks is not None:
+            _ticks = ticks
+        if ticklabels is not None:
+            _ticklabels = ticklabels
+        if label is not None:
+            _label = label
+
+        if _ticks is not None:
+            tickparam = {f"tick{self._axisnum}On": _ticks}
+            self._axis.set_tick_params(**tickparam)
+        if _ticklabels is not None:
+            tickparam = {f"label{self._axisnum}On": _ticklabels}
+            self._axis.set_tick_params(**tickparam)
+
+        if _label is not None:
+            pos = self._axis.get_label_position()
+            if (pos == self._axis_direction) and not _label:
+                self._axis.label.set_visible(False)
+            elif _label:
+                self._axis.label.set_visible(True)
+                self._axis.set_label_position(self._axis_direction)

venv/lib/python3.13/site-packages/mpl_toolkits/axes_grid1/parasite_axes.py

@@ -0,0 +1,257 @@
+from matplotlib import _api, cbook
+import matplotlib.artist as martist
+import matplotlib.transforms as mtransforms
+from matplotlib.transforms import Bbox
+from .mpl_axes import Axes
+
+
+class ParasiteAxesBase:
+
+    def __init__(self, parent_axes, aux_transform=None,
+                 *, viewlim_mode=None, **kwargs):
+        self._parent_axes = parent_axes
+        self.transAux = aux_transform
+        self.set_viewlim_mode(viewlim_mode)
+        kwargs["frameon"] = False
+        super().__init__(parent_axes.get_figure(root=False),
+                         parent_axes._position, **kwargs)
+
+    def clear(self):
+        super().clear()
+        martist.setp(self.get_children(), visible=False)
+        self._get_lines = self._parent_axes._get_lines
+        self._parent_axes.callbacks._connect_picklable(
+            "xlim_changed", self._sync_lims)
+        self._parent_axes.callbacks._connect_picklable(
+            "ylim_changed", self._sync_lims)
+
+    def pick(self, mouseevent):
+        # This most likely goes to Artist.pick (depending on axes_class given
+        # to the factory), which only handles pick events registered on the
+        # axes associated with each child:
+        super().pick(mouseevent)
+        # But parasite axes are additionally given pick events from their host
+        # axes (cf. HostAxesBase.pick), which we handle here:
+        for a in self.get_children():
+            if (hasattr(mouseevent.inaxes, "parasites")
+                    and self in mouseevent.inaxes.parasites):
+                a.pick(mouseevent)
+
+    # aux_transform support
+
+    def _set_lim_and_transforms(self):
+        if self.transAux is not None:
+            self.transAxes = self._parent_axes.transAxes
+            self.transData = self.transAux + self._parent_axes.transData
+            self._xaxis_transform = mtransforms.blended_transform_factory(
+                self.transData, self.transAxes)
+            self._yaxis_transform = mtransforms.blended_transform_factory(
+                self.transAxes, self.transData)
+        else:
+            super()._set_lim_and_transforms()
+
+    def set_viewlim_mode(self, mode):
+        _api.check_in_list([None, "equal", "transform"], mode=mode)
+        self._viewlim_mode = mode
+
+    def get_viewlim_mode(self):
+        return self._viewlim_mode
+
+    def _sync_lims(self, parent):
+        viewlim = parent.viewLim.frozen()
+        mode = self.get_viewlim_mode()
+        if mode is None:
+            pass
+        elif mode == "equal":
+            self.viewLim.set(viewlim)
+        elif mode == "transform":
+            self.viewLim.set(viewlim.transformed(self.transAux.inverted()))
+        else:
+            _api.check_in_list([None, "equal", "transform"], mode=mode)
+
+    # end of aux_transform support
+
+
+parasite_axes_class_factory = cbook._make_class_factory(
+    ParasiteAxesBase, "{}Parasite")
+ParasiteAxes = parasite_axes_class_factory(Axes)
+
+
+class HostAxesBase:
+    def __init__(self, *args, **kwargs):
+        self.parasites = []
+        super().__init__(*args, **kwargs)
+
+    def get_aux_axes(
+            self, tr=None, viewlim_mode="equal", axes_class=None, **kwargs):
+        """
+        Add a parasite axes to this host.
+
+        Despite this method's name, this should actually be thought of as an
+        ``add_parasite_axes`` method.
+
+        .. versionchanged:: 3.7
+           Defaults to same base axes class as host axes.
+
+        Parameters
+        ----------
+        tr : `~matplotlib.transforms.Transform` or None, default: None
+            If a `.Transform`, the following relation will hold:
+            ``parasite.transData = tr + host.transData``.
+            If None, the parasite's and the host's ``transData`` are unrelated.
+        viewlim_mode : {"equal", "transform", None}, default: "equal"
+            How the parasite's view limits are set: directly equal to the
+            parent axes ("equal"), equal after application of *tr*
+            ("transform"), or independently (None).
+        axes_class : subclass type of `~matplotlib.axes.Axes`, optional
+            The `~.axes.Axes` subclass that is instantiated.  If None, the base
+            class of the host axes is used.
+        **kwargs
+            Other parameters are forwarded to the parasite axes constructor.
+        """
+        if axes_class is None:
+            axes_class = self._base_axes_class
+        parasite_axes_class = parasite_axes_class_factory(axes_class)
+        ax2 = parasite_axes_class(
+            self, tr, viewlim_mode=viewlim_mode, **kwargs)
+        # note that ax2.transData == tr + ax1.transData
+        # Anything you draw in ax2 will match the ticks and grids of ax1.
+        self.parasites.append(ax2)
+        ax2._remove_method = self.parasites.remove
+        return ax2
+
+    def draw(self, renderer):
+        orig_children_len = len(self._children)
+
+        locator = self.get_axes_locator()
+        if locator:
+            pos = locator(self, renderer)
+            self.set_position(pos, which="active")
+            self.apply_aspect(pos)
+        else:
+            self.apply_aspect()
+
+        rect = self.get_position()
+        for ax in self.parasites:
+            ax.apply_aspect(rect)
+            self._children.extend(ax.get_children())
+
+        super().draw(renderer)
+        del self._children[orig_children_len:]
+
+    def clear(self):
+        super().clear()
+        for ax in self.parasites:
+            ax.clear()
+
+    def pick(self, mouseevent):
+        super().pick(mouseevent)
+        # Also pass pick events on to parasite axes and, in turn, their
+        # children (cf. ParasiteAxesBase.pick)
+        for a in self.parasites:
+            a.pick(mouseevent)
+
+    def twinx(self, axes_class=None):
+        """
+        Create a twin of Axes with a shared x-axis but independent y-axis.
+
+        The y-axis of self will have ticks on the left and the returned axes
+        will have ticks on the right.
+        """
+        ax = self._add_twin_axes(axes_class, sharex=self)
+        self.axis["right"].set_visible(False)
+        ax.axis["right"].set_visible(True)
+        ax.axis["left", "top", "bottom"].set_visible(False)
+        return ax
+
+    def twiny(self, axes_class=None):
+        """
+        Create a twin of Axes with a shared y-axis but independent x-axis.
+
+        The x-axis of self will have ticks on the bottom and the returned axes
+        will have ticks on the top.
+        """
+        ax = self._add_twin_axes(axes_class, sharey=self)
+        self.axis["top"].set_visible(False)
+        ax.axis["top"].set_visible(True)
+        ax.axis["left", "right", "bottom"].set_visible(False)
+        return ax
+
+    def twin(self, aux_trans=None, axes_class=None):
+        """
+        Create a twin of Axes with no shared axis.
+
+        While self will have ticks on the left and bottom axis, the returned
+        axes will have ticks on the top and right axis.
+        """
+        if aux_trans is None:
+            aux_trans = mtransforms.IdentityTransform()
+        ax = self._add_twin_axes(
+            axes_class, aux_transform=aux_trans, viewlim_mode="transform")
+        self.axis["top", "right"].set_visible(False)
+        ax.axis["top", "right"].set_visible(True)
+        ax.axis["left", "bottom"].set_visible(False)
+        return ax
+
+    def _add_twin_axes(self, axes_class, **kwargs):
+        """
+        Helper for `.twinx`/`.twiny`/`.twin`.
+
+        *kwargs* are forwarded to the parasite axes constructor.
+        """
+        if axes_class is None:
+            axes_class = self._base_axes_class
+        ax = parasite_axes_class_factory(axes_class)(self, **kwargs)
+        self.parasites.append(ax)
+        ax._remove_method = self._remove_any_twin
+        return ax
+
+    def _remove_any_twin(self, ax):
+        self.parasites.remove(ax)
+        restore = ["top", "right"]
+        if ax._sharex:
+            restore.remove("top")
+        if ax._sharey:
+            restore.remove("right")
+        self.axis[tuple(restore)].set_visible(True)
+        self.axis[tuple(restore)].toggle(ticklabels=False, label=False)
+
+    def get_tightbbox(self, renderer=None, *, call_axes_locator=True,
+                      bbox_extra_artists=None):
+        bbs = [
+            *[ax.get_tightbbox(renderer, call_axes_locator=call_axes_locator)
+              for ax in self.parasites],
+            super().get_tightbbox(renderer,
+                                  call_axes_locator=call_axes_locator,
+                                  bbox_extra_artists=bbox_extra_artists)]
+        return Bbox.union([b for b in bbs if b.width != 0 or b.height != 0])
+
+
+host_axes_class_factory = host_subplot_class_factory = \
+    cbook._make_class_factory(HostAxesBase, "{}HostAxes", "_base_axes_class")
+HostAxes = SubplotHost = host_axes_class_factory(Axes)
+
+
+def host_axes(*args, axes_class=Axes, figure=None, **kwargs):
+    """
+    Create axes that can act as a hosts to parasitic axes.
+
+    Parameters
+    ----------
+    figure : `~matplotlib.figure.Figure`
+        Figure to which the axes will be added. Defaults to the current figure
+        `.pyplot.gcf()`.
+
+    *args, **kwargs
+        Will be passed on to the underlying `~.axes.Axes` object creation.
+    """
+    import matplotlib.pyplot as plt
+    host_axes_class = host_axes_class_factory(axes_class)
+    if figure is None:
+        figure = plt.gcf()
+    ax = host_axes_class(figure, *args, **kwargs)
+    figure.add_axes(ax)
+    return ax
+
+
+host_subplot = host_axes

venv/lib/python3.13/site-packages/mpl_toolkits/axes_grid1/tests/__init__.py

@@ -0,0 +1,10 @@
+from pathlib import Path
+
+
+# Check that the test directories exist
+if not (Path(__file__).parent / "baseline_images").exists():
+    raise OSError(
+        'The baseline image directory does not exist. '
+        'This is most likely because the test data is not installed. '
+        'You may need to install matplotlib from source to get the '
+        'test data.')

venv/lib/python3.13/site-packages/mpl_toolkits/axes_grid1/tests/conftest.py

@@ -0,0 +1,2 @@
+from matplotlib.testing.conftest import (mpl_test_settings,  # noqa
+                                         pytest_configure, pytest_unconfigure)

venv/lib/python3.13/site-packages/mpl_toolkits/axes_grid1/tests/test_axes_grid1.py

@@ -0,0 +1,782 @@
+from itertools import product
+import io
+import platform
+
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+import matplotlib.ticker as mticker
+from matplotlib import cbook
+from matplotlib.backend_bases import MouseEvent
+from matplotlib.colors import LogNorm
+from matplotlib.patches import Circle, Ellipse
+from matplotlib.transforms import Bbox, TransformedBbox
+from matplotlib.testing.decorators import (
+    check_figures_equal, image_comparison, remove_ticks_and_titles)
+
+from mpl_toolkits.axes_grid1 import (
+    axes_size as Size,
+    host_subplot, make_axes_locatable,
+    Grid, AxesGrid, ImageGrid)
+from mpl_toolkits.axes_grid1.anchored_artists import (
+    AnchoredAuxTransformBox, AnchoredDrawingArea,
+    AnchoredDirectionArrows, AnchoredSizeBar)
+from mpl_toolkits.axes_grid1.axes_divider import (
+    Divider, HBoxDivider, make_axes_area_auto_adjustable, SubplotDivider,
+    VBoxDivider)
+from mpl_toolkits.axes_grid1.axes_rgb import RGBAxes
+from mpl_toolkits.axes_grid1.inset_locator import (
+    zoomed_inset_axes, mark_inset, inset_axes, BboxConnectorPatch)
+import mpl_toolkits.axes_grid1.mpl_axes
+import pytest
+
+import numpy as np
+from numpy.testing import assert_array_equal, assert_array_almost_equal
+
+
+def test_divider_append_axes():
+    fig, ax = plt.subplots()
+    divider = make_axes_locatable(ax)
+    axs = {
+        "main": ax,
+        "top": divider.append_axes("top", 1.2, pad=0.1, sharex=ax),
+        "bottom": divider.append_axes("bottom", 1.2, pad=0.1, sharex=ax),
+        "left": divider.append_axes("left", 1.2, pad=0.1, sharey=ax),
+        "right": divider.append_axes("right", 1.2, pad=0.1, sharey=ax),
+    }
+    fig.canvas.draw()
+    bboxes = {k: axs[k].get_window_extent() for k in axs}
+    dpi = fig.dpi
+    assert bboxes["top"].height == pytest.approx(1.2 * dpi)
+    assert bboxes["bottom"].height == pytest.approx(1.2 * dpi)
+    assert bboxes["left"].width == pytest.approx(1.2 * dpi)
+    assert bboxes["right"].width == pytest.approx(1.2 * dpi)
+    assert bboxes["top"].y0 - bboxes["main"].y1 == pytest.approx(0.1 * dpi)
+    assert bboxes["main"].y0 - bboxes["bottom"].y1 == pytest.approx(0.1 * dpi)
+    assert bboxes["main"].x0 - bboxes["left"].x1 == pytest.approx(0.1 * dpi)
+    assert bboxes["right"].x0 - bboxes["main"].x1 == pytest.approx(0.1 * dpi)
+    assert bboxes["left"].y0 == bboxes["main"].y0 == bboxes["right"].y0
+    assert bboxes["left"].y1 == bboxes["main"].y1 == bboxes["right"].y1
+    assert bboxes["top"].x0 == bboxes["main"].x0 == bboxes["bottom"].x0
+    assert bboxes["top"].x1 == bboxes["main"].x1 == bboxes["bottom"].x1
+
+
+# Update style when regenerating the test image
+@image_comparison(['twin_axes_empty_and_removed'], extensions=["png"], tol=1,
+                  style=('classic', '_classic_test_patch'))
+def test_twin_axes_empty_and_removed():
+    # Purely cosmetic font changes (avoid overlap)
+    mpl.rcParams.update(
+        {"font.size": 8, "xtick.labelsize": 8, "ytick.labelsize": 8})
+    generators = ["twinx", "twiny", "twin"]
+    modifiers = ["", "host invisible", "twin removed", "twin invisible",
+                 "twin removed\nhost invisible"]
+    # Unmodified host subplot at the beginning for reference
+    h = host_subplot(len(modifiers)+1, len(generators), 2)
+    h.text(0.5, 0.5, "host_subplot",
+           horizontalalignment="center", verticalalignment="center")
+    # Host subplots with various modifications (twin*, visibility) applied
+    for i, (mod, gen) in enumerate(product(modifiers, generators),
+                                   len(generators) + 1):
+        h = host_subplot(len(modifiers)+1, len(generators), i)
+        t = getattr(h, gen)()
+        if "twin invisible" in mod:
+            t.axis[:].set_visible(False)
+        if "twin removed" in mod:
+            t.remove()
+        if "host invisible" in mod:
+            h.axis[:].set_visible(False)
+        h.text(0.5, 0.5, gen + ("\n" + mod if mod else ""),
+               horizontalalignment="center", verticalalignment="center")
+    plt.subplots_adjust(wspace=0.5, hspace=1)
+
+
+def test_twin_axes_both_with_units():
+    host = host_subplot(111)
+    with pytest.warns(mpl.MatplotlibDeprecationWarning):
+        host.plot_date([0, 1, 2], [0, 1, 2], xdate=False, ydate=True)
+    twin = host.twinx()
+    twin.plot(["a", "b", "c"])
+    assert host.get_yticklabels()[0].get_text() == "00:00:00"
+    assert twin.get_yticklabels()[0].get_text() == "a"
+
+
+def test_axesgrid_colorbar_log_smoketest():
+    fig = plt.figure()
+    grid = AxesGrid(fig, 111,  # modified to be only subplot
+                    nrows_ncols=(1, 1),
+                    ngrids=1,
+                    label_mode="L",
+                    cbar_location="top",
+                    cbar_mode="single",
+                    )
+
+    Z = 10000 * np.random.rand(10, 10)
+    im = grid[0].imshow(Z, interpolation="nearest", norm=LogNorm())
+
+    grid.cbar_axes[0].colorbar(im)
+
+
+def test_inset_colorbar_tight_layout_smoketest():
+    fig, ax = plt.subplots(1, 1)
+    pts = ax.scatter([0, 1], [0, 1], c=[1, 5])
+
+    cax = inset_axes(ax, width="3%", height="70%")
+    plt.colorbar(pts, cax=cax)
+
+    with pytest.warns(UserWarning, match="This figure includes Axes"):
+        # Will warn, but not raise an error
+        plt.tight_layout()
+
+
+@image_comparison(['inset_locator.png'], style='default', remove_text=True)
+def test_inset_locator():
+    fig, ax = plt.subplots(figsize=[5, 4])
+
+    # prepare the demo image
+    # Z is a 15x15 array
+    Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy")
+    extent = (-3, 4, -4, 3)
+    Z2 = np.zeros((150, 150))
+    ny, nx = Z.shape
+    Z2[30:30+ny, 30:30+nx] = Z
+
+    ax.imshow(Z2, extent=extent, interpolation="nearest",
+              origin="lower")
+
+    axins = zoomed_inset_axes(ax, zoom=6, loc='upper right')
+    axins.imshow(Z2, extent=extent, interpolation="nearest",
+                 origin="lower")
+    axins.yaxis.get_major_locator().set_params(nbins=7)
+    axins.xaxis.get_major_locator().set_params(nbins=7)
+    # sub region of the original image
+    x1, x2, y1, y2 = -1.5, -0.9, -2.5, -1.9
+    axins.set_xlim(x1, x2)
+    axins.set_ylim(y1, y2)
+
+    plt.xticks(visible=False)
+    plt.yticks(visible=False)
+
+    # draw a bbox of the region of the inset axes in the parent axes and
+    # connecting lines between the bbox and the inset axes area
+    mark_inset(ax, axins, loc1=2, loc2=4, fc="none", ec="0.5")
+
+    asb = AnchoredSizeBar(ax.transData,
+                          0.5,
+                          '0.5',
+                          loc='lower center',
+                          pad=0.1, borderpad=0.5, sep=5,
+                          frameon=False)
+    ax.add_artist(asb)
+
+
+@image_comparison(['inset_axes.png'], style='default', remove_text=True)
+def test_inset_axes():
+    fig, ax = plt.subplots(figsize=[5, 4])
+
+    # prepare the demo image
+    # Z is a 15x15 array
+    Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy")
+    extent = (-3, 4, -4, 3)
+    Z2 = np.zeros((150, 150))
+    ny, nx = Z.shape
+    Z2[30:30+ny, 30:30+nx] = Z
+
+    ax.imshow(Z2, extent=extent, interpolation="nearest",
+              origin="lower")
+
+    # creating our inset axes with a bbox_transform parameter
+    axins = inset_axes(ax, width=1., height=1., bbox_to_anchor=(1, 1),
+                       bbox_transform=ax.transAxes)
+
+    axins.imshow(Z2, extent=extent, interpolation="nearest",
+                 origin="lower")
+    axins.yaxis.get_major_locator().set_params(nbins=7)
+    axins.xaxis.get_major_locator().set_params(nbins=7)
+    # sub region of the original image
+    x1, x2, y1, y2 = -1.5, -0.9, -2.5, -1.9
+    axins.set_xlim(x1, x2)
+    axins.set_ylim(y1, y2)
+
+    plt.xticks(visible=False)
+    plt.yticks(visible=False)
+
+    # draw a bbox of the region of the inset axes in the parent axes and
+    # connecting lines between the bbox and the inset axes area
+    mark_inset(ax, axins, loc1=2, loc2=4, fc="none", ec="0.5")
+
+    asb = AnchoredSizeBar(ax.transData,
+                          0.5,
+                          '0.5',
+                          loc='lower center',
+                          pad=0.1, borderpad=0.5, sep=5,
+                          frameon=False)
+    ax.add_artist(asb)
+
+
+def test_inset_axes_complete():
+    dpi = 100
+    figsize = (6, 5)
+    fig, ax = plt.subplots(figsize=figsize, dpi=dpi)
+    fig.subplots_adjust(.1, .1, .9, .9)
+
+    ins = inset_axes(ax, width=2., height=2., borderpad=0)
+    fig.canvas.draw()
+    assert_array_almost_equal(
+        ins.get_position().extents,
+        [(0.9*figsize[0]-2.)/figsize[0], (0.9*figsize[1]-2.)/figsize[1],
+         0.9, 0.9])
+
+    ins = inset_axes(ax, width="40%", height="30%", borderpad=0)
+    fig.canvas.draw()
+    assert_array_almost_equal(
+        ins.get_position().extents, [.9-.8*.4, .9-.8*.3, 0.9, 0.9])
+
+    ins = inset_axes(ax, width=1., height=1.2, bbox_to_anchor=(200, 100),
+                     loc=3, borderpad=0)
+    fig.canvas.draw()
+    assert_array_almost_equal(
+        ins.get_position().extents,
+        [200/dpi/figsize[0], 100/dpi/figsize[1],
+         (200/dpi+1)/figsize[0], (100/dpi+1.2)/figsize[1]])
+
+    ins1 = inset_axes(ax, width="35%", height="60%", loc=3, borderpad=1)
+    ins2 = inset_axes(ax, width="100%", height="100%",
+                      bbox_to_anchor=(0, 0, .35, .60),
+                      bbox_transform=ax.transAxes, loc=3, borderpad=1)
+    fig.canvas.draw()
+    assert_array_equal(ins1.get_position().extents,
+                       ins2.get_position().extents)
+
+    with pytest.raises(ValueError):
+        ins = inset_axes(ax, width="40%", height="30%",
+                         bbox_to_anchor=(0.4, 0.5))
+
+    with pytest.warns(UserWarning):
+        ins = inset_axes(ax, width="40%", height="30%",
+                         bbox_transform=ax.transAxes)
+
+
+def test_inset_axes_tight():
+    # gh-26287 found that inset_axes raised with bbox_inches=tight
+    fig, ax = plt.subplots()
+    inset_axes(ax, width=1.3, height=0.9)
+
+    f = io.BytesIO()
+    fig.savefig(f, bbox_inches="tight")
+
+
+@image_comparison(['fill_facecolor.png'], remove_text=True, style='mpl20')
+def test_fill_facecolor():
+    fig, ax = plt.subplots(1, 5)
+    fig.set_size_inches(5, 5)
+    for i in range(1, 4):
+        ax[i].yaxis.set_visible(False)
+    ax[4].yaxis.tick_right()
+    bbox = Bbox.from_extents(0, 0.4, 1, 0.6)
+
+    # fill with blue by setting 'fc' field
+    bbox1 = TransformedBbox(bbox, ax[0].transData)
+    bbox2 = TransformedBbox(bbox, ax[1].transData)
+    # set color to BboxConnectorPatch
+    p = BboxConnectorPatch(
+        bbox1, bbox2, loc1a=1, loc2a=2, loc1b=4, loc2b=3,
+        ec="r", fc="b")
+    p.set_clip_on(False)
+    ax[0].add_patch(p)
+    # set color to marked area
+    axins = zoomed_inset_axes(ax[0], 1, loc='upper right')
+    axins.set_xlim(0, 0.2)
+    axins.set_ylim(0, 0.2)
+    plt.gca().axes.xaxis.set_ticks([])
+    plt.gca().axes.yaxis.set_ticks([])
+    mark_inset(ax[0], axins, loc1=2, loc2=4, fc="b", ec="0.5")
+
+    # fill with yellow by setting 'facecolor' field
+    bbox3 = TransformedBbox(bbox, ax[1].transData)
+    bbox4 = TransformedBbox(bbox, ax[2].transData)
+    # set color to BboxConnectorPatch
+    p = BboxConnectorPatch(
+        bbox3, bbox4, loc1a=1, loc2a=2, loc1b=4, loc2b=3,
+        ec="r", facecolor="y")
+    p.set_clip_on(False)
+    ax[1].add_patch(p)
+    # set color to marked area
+    axins = zoomed_inset_axes(ax[1], 1, loc='upper right')
+    axins.set_xlim(0, 0.2)
+    axins.set_ylim(0, 0.2)
+    plt.gca().axes.xaxis.set_ticks([])
+    plt.gca().axes.yaxis.set_ticks([])
+    mark_inset(ax[1], axins, loc1=2, loc2=4, facecolor="y", ec="0.5")
+
+    # fill with green by setting 'color' field
+    bbox5 = TransformedBbox(bbox, ax[2].transData)
+    bbox6 = TransformedBbox(bbox, ax[3].transData)
+    # set color to BboxConnectorPatch
+    p = BboxConnectorPatch(
+        bbox5, bbox6, loc1a=1, loc2a=2, loc1b=4, loc2b=3,
+        ec="r", color="g")
+    p.set_clip_on(False)
+    ax[2].add_patch(p)
+    # set color to marked area
+    axins = zoomed_inset_axes(ax[2], 1, loc='upper right')
+    axins.set_xlim(0, 0.2)
+    axins.set_ylim(0, 0.2)
+    plt.gca().axes.xaxis.set_ticks([])
+    plt.gca().axes.yaxis.set_ticks([])
+    mark_inset(ax[2], axins, loc1=2, loc2=4, color="g", ec="0.5")
+
+    # fill with green but color won't show if set fill to False
+    bbox7 = TransformedBbox(bbox, ax[3].transData)
+    bbox8 = TransformedBbox(bbox, ax[4].transData)
+    # BboxConnectorPatch won't show green
+    p = BboxConnectorPatch(
+        bbox7, bbox8, loc1a=1, loc2a=2, loc1b=4, loc2b=3,
+        ec="r", fc="g", fill=False)
+    p.set_clip_on(False)
+    ax[3].add_patch(p)
+    # marked area won't show green
+    axins = zoomed_inset_axes(ax[3], 1, loc='upper right')
+    axins.set_xlim(0, 0.2)
+    axins.set_ylim(0, 0.2)
+    axins.xaxis.set_ticks([])
+    axins.yaxis.set_ticks([])
+    mark_inset(ax[3], axins, loc1=2, loc2=4, fc="g", ec="0.5", fill=False)
+
+
+# Update style when regenerating the test image
+@image_comparison(['zoomed_axes.png', 'inverted_zoomed_axes.png'],
+                  style=('classic', '_classic_test_patch'),
+                  tol=0 if platform.machine() == 'x86_64' else 0.02)
+def test_zooming_with_inverted_axes():
+    fig, ax = plt.subplots()
+    ax.plot([1, 2, 3], [1, 2, 3])
+    ax.axis([1, 3, 1, 3])
+    inset_ax = zoomed_inset_axes(ax, zoom=2.5, loc='lower right')
+    inset_ax.axis([1.1, 1.4, 1.1, 1.4])
+
+    fig, ax = plt.subplots()
+    ax.plot([1, 2, 3], [1, 2, 3])
+    ax.axis([3, 1, 3, 1])
+    inset_ax = zoomed_inset_axes(ax, zoom=2.5, loc='lower right')
+    inset_ax.axis([1.4, 1.1, 1.4, 1.1])
+
+
+# Update style when regenerating the test image
+@image_comparison(['anchored_direction_arrows.png'],
+                  tol=0 if platform.machine() == 'x86_64' else 0.01,
+                  style=('classic', '_classic_test_patch'))
+def test_anchored_direction_arrows():
+    fig, ax = plt.subplots()
+    ax.imshow(np.zeros((10, 10)), interpolation='nearest')
+
+    simple_arrow = AnchoredDirectionArrows(ax.transAxes, 'X', 'Y')
+    ax.add_artist(simple_arrow)
+
+
+# Update style when regenerating the test image
+@image_comparison(['anchored_direction_arrows_many_args.png'],
+                  style=('classic', '_classic_test_patch'))
+def test_anchored_direction_arrows_many_args():
+    fig, ax = plt.subplots()
+    ax.imshow(np.ones((10, 10)))
+
+    direction_arrows = AnchoredDirectionArrows(
+            ax.transAxes, 'A', 'B', loc='upper right', color='red',
+            aspect_ratio=-0.5, pad=0.6, borderpad=2, frameon=True, alpha=0.7,
+            sep_x=-0.06, sep_y=-0.08, back_length=0.1, head_width=9,
+            head_length=10, tail_width=5)
+    ax.add_artist(direction_arrows)
+
+
+def test_axes_locatable_position():
+    fig, ax = plt.subplots()
+    divider = make_axes_locatable(ax)
+    with mpl.rc_context({"figure.subplot.wspace": 0.02}):
+        cax = divider.append_axes('right', size='5%')
+    fig.canvas.draw()
+    assert np.isclose(cax.get_position(original=False).width,
+                      0.03621495327102808)
+
+
+@image_comparison(['image_grid_each_left_label_mode_all.png'], style='mpl20',
+                  savefig_kwarg={'bbox_inches': 'tight'})
+def test_image_grid_each_left_label_mode_all():
+    imdata = np.arange(100).reshape((10, 10))
+
+    fig = plt.figure(1, (3, 3))
+    grid = ImageGrid(fig, (1, 1, 1), nrows_ncols=(3, 2), axes_pad=(0.5, 0.3),
+                     cbar_mode="each", cbar_location="left", cbar_size="15%",
+                     label_mode="all")
+    # 3-tuple rect => SubplotDivider
+    assert isinstance(grid.get_divider(), SubplotDivider)
+    assert grid.get_axes_pad() == (0.5, 0.3)
+    assert grid.get_aspect()  # True by default for ImageGrid
+    for ax, cax in zip(grid, grid.cbar_axes):
+        im = ax.imshow(imdata, interpolation='none')
+        cax.colorbar(im)
+
+
+@image_comparison(['image_grid_single_bottom_label_mode_1.png'], style='mpl20',
+                  savefig_kwarg={'bbox_inches': 'tight'})
+def test_image_grid_single_bottom():
+    imdata = np.arange(100).reshape((10, 10))
+
+    fig = plt.figure(1, (2.5, 1.5))
+    grid = ImageGrid(fig, (0, 0, 1, 1), nrows_ncols=(1, 3),
+                     axes_pad=(0.2, 0.15), cbar_mode="single", cbar_pad=0.3,
+                     cbar_location="bottom", cbar_size="10%", label_mode="1")
+    # 4-tuple rect => Divider, isinstance will give True for SubplotDivider
+    assert type(grid.get_divider()) is Divider
+    for i in range(3):
+        im = grid[i].imshow(imdata, interpolation='none')
+    grid.cbar_axes[0].colorbar(im)
+
+
+def test_image_grid_label_mode_invalid():
+    fig = plt.figure()
+    with pytest.raises(ValueError, match="'foo' is not a valid value for mode"):
+        ImageGrid(fig, (0, 0, 1, 1), (2, 1), label_mode="foo")
+
+
+@image_comparison(['image_grid.png'],
+                  remove_text=True, style='mpl20',
+                  savefig_kwarg={'bbox_inches': 'tight'})
+def test_image_grid():
+    # test that image grid works with bbox_inches=tight.
+    im = np.arange(100).reshape((10, 10))
+
+    fig = plt.figure(1, (4, 4))
+    grid = ImageGrid(fig, 111, nrows_ncols=(2, 2), axes_pad=0.1)
+    assert grid.get_axes_pad() == (0.1, 0.1)
+    for i in range(4):
+        grid[i].imshow(im, interpolation='nearest')
+
+
+def test_gettightbbox():
+    fig, ax = plt.subplots(figsize=(8, 6))
+
+    l, = ax.plot([1, 2, 3], [0, 1, 0])
+
+    ax_zoom = zoomed_inset_axes(ax, 4)
+    ax_zoom.plot([1, 2, 3], [0, 1, 0])
+
+    mark_inset(ax, ax_zoom, loc1=1, loc2=3, fc="none", ec='0.3')
+
+    remove_ticks_and_titles(fig)
+    bbox = fig.get_tightbbox(fig.canvas.get_renderer())
+    np.testing.assert_array_almost_equal(bbox.extents,
+                                         [-17.7, -13.9, 7.2, 5.4])
+
+
+@pytest.mark.parametrize("click_on", ["big", "small"])
+@pytest.mark.parametrize("big_on_axes,small_on_axes", [
+    ("gca", "gca"),
+    ("host", "host"),
+    ("host", "parasite"),
+    ("parasite", "host"),
+    ("parasite", "parasite")
+])
+def test_picking_callbacks_overlap(big_on_axes, small_on_axes, click_on):
+    """Test pick events on normal, host or parasite axes."""
+    # Two rectangles are drawn and "clicked on", a small one and a big one
+    # enclosing the small one. The axis on which they are drawn as well as the
+    # rectangle that is clicked on are varied.
+    # In each case we expect that both rectangles are picked if we click on the
+    # small one and only the big one is picked if we click on the big one.
+    # Also tests picking on normal axes ("gca") as a control.
+    big = plt.Rectangle((0.25, 0.25), 0.5, 0.5, picker=5)
+    small = plt.Rectangle((0.4, 0.4), 0.2, 0.2, facecolor="r", picker=5)
+    # Machinery for "receiving" events
+    received_events = []
+    def on_pick(event):
+        received_events.append(event)
+    plt.gcf().canvas.mpl_connect('pick_event', on_pick)
+    # Shortcut
+    rectangles_on_axes = (big_on_axes, small_on_axes)
+    # Axes setup
+    axes = {"gca": None, "host": None, "parasite": None}
+    if "gca" in rectangles_on_axes:
+        axes["gca"] = plt.gca()
+    if "host" in rectangles_on_axes or "parasite" in rectangles_on_axes:
+        axes["host"] = host_subplot(111)
+        axes["parasite"] = axes["host"].twin()
+    # Add rectangles to axes
+    axes[big_on_axes].add_patch(big)
+    axes[small_on_axes].add_patch(small)
+    # Simulate picking with click mouse event
+    if click_on == "big":
+        click_axes = axes[big_on_axes]
+        axes_coords = (0.3, 0.3)
+    else:
+        click_axes = axes[small_on_axes]
+        axes_coords = (0.5, 0.5)
+    # In reality mouse events never happen on parasite axes, only host axes
+    if click_axes is axes["parasite"]:
+        click_axes = axes["host"]
+    (x, y) = click_axes.transAxes.transform(axes_coords)
+    m = MouseEvent("button_press_event", click_axes.get_figure(root=True).canvas, x, y,
+                   button=1)
+    click_axes.pick(m)
+    # Checks
+    expected_n_events = 2 if click_on == "small" else 1
+    assert len(received_events) == expected_n_events
+    event_rects = [event.artist for event in received_events]
+    assert big in event_rects
+    if click_on == "small":
+        assert small in event_rects
+
+
+@image_comparison(['anchored_artists.png'], remove_text=True, style='mpl20')
+def test_anchored_artists():
+    fig, ax = plt.subplots(figsize=(3, 3))
+    ada = AnchoredDrawingArea(40, 20, 0, 0, loc='upper right', pad=0.,
+                              frameon=False)
+    p1 = Circle((10, 10), 10)
+    ada.drawing_area.add_artist(p1)
+    p2 = Circle((30, 10), 5, fc="r")
+    ada.drawing_area.add_artist(p2)
+    ax.add_artist(ada)
+
+    box = AnchoredAuxTransformBox(ax.transData, loc='upper left')
+    el = Ellipse((0, 0), width=0.1, height=0.4, angle=30, color='cyan')
+    box.drawing_area.add_artist(el)
+    ax.add_artist(box)
+
+    # This block used to test the AnchoredEllipse class, but that was removed. The block
+    # remains, though it duplicates the above ellipse, so that the test image doesn't
+    # need to be regenerated.
+    box = AnchoredAuxTransformBox(ax.transData, loc='lower left', frameon=True,
+                                  pad=0.5, borderpad=0.4)
+    el = Ellipse((0, 0), width=0.1, height=0.25, angle=-60)
+    box.drawing_area.add_artist(el)
+    ax.add_artist(box)
+
+    asb = AnchoredSizeBar(ax.transData, 0.2, r"0.2 units", loc='lower right',
+                          pad=0.3, borderpad=0.4, sep=4, fill_bar=True,
+                          frameon=False, label_top=True, prop={'size': 20},
+                          size_vertical=0.05, color='green')
+    ax.add_artist(asb)
+
+
+def test_hbox_divider():
+    arr1 = np.arange(20).reshape((4, 5))
+    arr2 = np.arange(20).reshape((5, 4))
+
+    fig, (ax1, ax2) = plt.subplots(1, 2)
+    ax1.imshow(arr1)
+    ax2.imshow(arr2)
+
+    pad = 0.5  # inches.
+    divider = HBoxDivider(
+        fig, 111,  # Position of combined axes.
+        horizontal=[Size.AxesX(ax1), Size.Fixed(pad), Size.AxesX(ax2)],
+        vertical=[Size.AxesY(ax1), Size.Scaled(1), Size.AxesY(ax2)])
+    ax1.set_axes_locator(divider.new_locator(0))
+    ax2.set_axes_locator(divider.new_locator(2))
+
+    fig.canvas.draw()
+    p1 = ax1.get_position()
+    p2 = ax2.get_position()
+    assert p1.height == p2.height
+    assert p2.width / p1.width == pytest.approx((4 / 5) ** 2)
+
+
+def test_vbox_divider():
+    arr1 = np.arange(20).reshape((4, 5))
+    arr2 = np.arange(20).reshape((5, 4))
+
+    fig, (ax1, ax2) = plt.subplots(1, 2)
+    ax1.imshow(arr1)
+    ax2.imshow(arr2)
+
+    pad = 0.5  # inches.
+    divider = VBoxDivider(
+        fig, 111,  # Position of combined axes.
+        horizontal=[Size.AxesX(ax1), Size.Scaled(1), Size.AxesX(ax2)],
+        vertical=[Size.AxesY(ax1), Size.Fixed(pad), Size.AxesY(ax2)])
+    ax1.set_axes_locator(divider.new_locator(0))
+    ax2.set_axes_locator(divider.new_locator(2))
+
+    fig.canvas.draw()
+    p1 = ax1.get_position()
+    p2 = ax2.get_position()
+    assert p1.width == p2.width
+    assert p1.height / p2.height == pytest.approx((4 / 5) ** 2)
+
+
+def test_axes_class_tuple():
+    fig = plt.figure()
+    axes_class = (mpl_toolkits.axes_grid1.mpl_axes.Axes, {})
+    gr = AxesGrid(fig, 111, nrows_ncols=(1, 1), axes_class=axes_class)
+
+
+def test_grid_axes_lists():
+    """Test Grid axes_all, axes_row and axes_column relationship."""
+    fig = plt.figure()
+    grid = Grid(fig, 111, (2, 3), direction="row")
+    assert_array_equal(grid, grid.axes_all)
+    assert_array_equal(grid.axes_row, np.transpose(grid.axes_column))
+    assert_array_equal(grid, np.ravel(grid.axes_row), "row")
+    assert grid.get_geometry() == (2, 3)
+    grid = Grid(fig, 111, (2, 3), direction="column")
+    assert_array_equal(grid, np.ravel(grid.axes_column), "column")
+
+
+@pytest.mark.parametrize('direction', ('row', 'column'))
+def test_grid_axes_position(direction):
+    """Test positioning of the axes in Grid."""
+    fig = plt.figure()
+    grid = Grid(fig, 111, (2, 2), direction=direction)
+    loc = [ax.get_axes_locator() for ax in np.ravel(grid.axes_row)]
+    # Test nx.
+    assert loc[1].args[0] > loc[0].args[0]
+    assert loc[0].args[0] == loc[2].args[0]
+    assert loc[3].args[0] == loc[1].args[0]
+    # Test ny.
+    assert loc[2].args[1] < loc[0].args[1]
+    assert loc[0].args[1] == loc[1].args[1]
+    assert loc[3].args[1] == loc[2].args[1]
+
+
+@pytest.mark.parametrize('rect, ngrids, error, message', (
+    ((1, 1), None, TypeError, "Incorrect rect format"),
+    (111, -1, ValueError, "ngrids must be positive"),
+    (111, 7, ValueError, "ngrids must be positive"),
+))
+def test_grid_errors(rect, ngrids, error, message):
+    fig = plt.figure()
+    with pytest.raises(error, match=message):
+        Grid(fig, rect, (2, 3), ngrids=ngrids)
+
+
+@pytest.mark.parametrize('anchor, error, message', (
+    (None, TypeError, "anchor must be str"),
+    ("CC", ValueError, "'CC' is not a valid value for anchor"),
+    ((1, 1, 1), TypeError, "anchor must be str"),
+))
+def test_divider_errors(anchor, error, message):
+    fig = plt.figure()
+    with pytest.raises(error, match=message):
+        Divider(fig, [0, 0, 1, 1], [Size.Fixed(1)], [Size.Fixed(1)],
+                anchor=anchor)
+
+
+@check_figures_equal(extensions=["png"])
+def test_mark_inset_unstales_viewlim(fig_test, fig_ref):
+    inset, full = fig_test.subplots(1, 2)
+    full.plot([0, 5], [0, 5])
+    inset.set(xlim=(1, 2), ylim=(1, 2))
+    # Check that mark_inset unstales full's viewLim before drawing the marks.
+    mark_inset(full, inset, 1, 4)
+
+    inset, full = fig_ref.subplots(1, 2)
+    full.plot([0, 5], [0, 5])
+    inset.set(xlim=(1, 2), ylim=(1, 2))
+    mark_inset(full, inset, 1, 4)
+    # Manually unstale the full's viewLim.
+    fig_ref.canvas.draw()
+
+
+def test_auto_adjustable():
+    fig = plt.figure()
+    ax = fig.add_axes([0, 0, 1, 1])
+    pad = 0.1
+    make_axes_area_auto_adjustable(ax, pad=pad)
+    fig.canvas.draw()
+    tbb = ax.get_tightbbox()
+    assert tbb.x0 == pytest.approx(pad * fig.dpi)
+    assert tbb.x1 == pytest.approx(fig.bbox.width - pad * fig.dpi)
+    assert tbb.y0 == pytest.approx(pad * fig.dpi)
+    assert tbb.y1 == pytest.approx(fig.bbox.height - pad * fig.dpi)
+
+
+# Update style when regenerating the test image
+@image_comparison(['rgb_axes.png'], remove_text=True,
+                  style=('classic', '_classic_test_patch'))
+def test_rgb_axes():
+    fig = plt.figure()
+    ax = RGBAxes(fig, (0.1, 0.1, 0.8, 0.8), pad=0.1)
+    rng = np.random.default_rng(19680801)
+    r = rng.random((5, 5))
+    g = rng.random((5, 5))
+    b = rng.random((5, 5))
+    ax.imshow_rgb(r, g, b, interpolation='none')
+
+
+# The original version of this test relied on mpl_toolkits's slightly different
+# colorbar implementation; moving to matplotlib's own colorbar implementation
+# caused the small image comparison error.
+@image_comparison(['imagegrid_cbar_mode.png'],
+                  remove_text=True, style='mpl20', tol=0.3)
+def test_imagegrid_cbar_mode_edge():
+    arr = np.arange(16).reshape((4, 4))
+
+    fig = plt.figure(figsize=(18, 9))
+
+    positions = (241, 242, 243, 244, 245, 246, 247, 248)
+    directions = ['row']*4 + ['column']*4
+    cbar_locations = ['left', 'right', 'top', 'bottom']*2
+
+    for position, direction, location in zip(
+            positions, directions, cbar_locations):
+        grid = ImageGrid(fig, position,
+                         nrows_ncols=(2, 2),
+                         direction=direction,
+                         cbar_location=location,
+                         cbar_size='20%',
+                         cbar_mode='edge')
+        ax1, ax2, ax3, ax4 = grid
+
+        ax1.imshow(arr, cmap='nipy_spectral')
+        ax2.imshow(arr.T, cmap='hot')
+        ax3.imshow(np.hypot(arr, arr.T), cmap='jet')
+        ax4.imshow(np.arctan2(arr, arr.T), cmap='hsv')
+
+        # In each row/column, the "first" colorbars must be overwritten by the
+        # "second" ones.  To achieve this, clear out the axes first.
+        for ax in grid:
+            ax.cax.cla()
+            cb = ax.cax.colorbar(ax.images[0])
+
+
+def test_imagegrid():
+    fig = plt.figure()
+    grid = ImageGrid(fig, 111, nrows_ncols=(1, 1))
+    ax = grid[0]
+    im = ax.imshow([[1, 2]], norm=mpl.colors.LogNorm())
+    cb = ax.cax.colorbar(im)
+    assert isinstance(cb.locator, mticker.LogLocator)
+
+
+def test_removal():
+    import matplotlib.pyplot as plt
+    import mpl_toolkits.axisartist as AA
+    fig = plt.figure()
+    ax = host_subplot(111, axes_class=AA.Axes, figure=fig)
+    col = ax.fill_between(range(5), 0, range(5))
+    fig.canvas.draw()
+    col.remove()
+    fig.canvas.draw()
+
+
+@image_comparison(['anchored_locator_base_call.png'], style="mpl20")
+def test_anchored_locator_base_call():
+    fig = plt.figure(figsize=(3, 3))
+    fig1, fig2 = fig.subfigures(nrows=2, ncols=1)
+
+    ax = fig1.subplots()
+    ax.set(aspect=1, xlim=(-15, 15), ylim=(-20, 5))
+    ax.set(xticks=[], yticks=[])
+
+    Z = cbook.get_sample_data("axes_grid/bivariate_normal.npy")
+    extent = (-3, 4, -4, 3)
+
+    axins = zoomed_inset_axes(ax, zoom=2, loc="upper left")
+    axins.set(xticks=[], yticks=[])
+
+    axins.imshow(Z, extent=extent, origin="lower")
+
+
+def test_grid_with_axes_class_not_overriding_axis():
+    Grid(plt.figure(), 111, (2, 2), axes_class=mpl.axes.Axes)
+    RGBAxes(plt.figure(), 111, axes_class=mpl.axes.Axes)

venv/lib/python3.13/site-packages/mpl_toolkits/axisartist/__init__.py

@@ -0,0 +1,14 @@
+from .axislines import Axes
+from .axislines import (  # noqa: F401
+    AxesZero, AxisArtistHelper, AxisArtistHelperRectlinear,
+    GridHelperBase, GridHelperRectlinear, Subplot, SubplotZero)
+from .axis_artist import AxisArtist, GridlinesCollection  # noqa: F401
+from .grid_helper_curvelinear import GridHelperCurveLinear  # noqa: F401
+from .floating_axes import FloatingAxes, FloatingSubplot  # noqa: F401
+from mpl_toolkits.axes_grid1.parasite_axes import (
+    host_axes_class_factory, parasite_axes_class_factory)
+
+
+ParasiteAxes = parasite_axes_class_factory(Axes)
+HostAxes = host_axes_class_factory(Axes)
+SubplotHost = HostAxes

venv/lib/python3.13/site-packages/mpl_toolkits/axisartist/angle_helper.py

@@ -0,0 +1,394 @@
+import numpy as np
+import math
+
+from mpl_toolkits.axisartist.grid_finder import ExtremeFinderSimple
+
+
+def select_step_degree(dv):
+
+    degree_limits_ = [1.5, 3, 7, 13, 20, 40, 70, 120, 270, 520]
+    degree_steps_  = [1,   2, 5, 10, 15, 30, 45,  90, 180, 360]
+    degree_factors = [1.] * len(degree_steps_)
+
+    minsec_limits_ = [1.5, 2.5, 3.5, 8, 11, 18, 25, 45]
+    minsec_steps_  = [1,   2,   3,   5, 10, 15, 20, 30]
+
+    minute_limits_ = np.array(minsec_limits_) / 60
+    minute_factors = [60.] * len(minute_limits_)
+
+    second_limits_ = np.array(minsec_limits_) / 3600
+    second_factors = [3600.] * len(second_limits_)
+
+    degree_limits = [*second_limits_, *minute_limits_, *degree_limits_]
+    degree_steps = [*minsec_steps_, *minsec_steps_, *degree_steps_]
+    degree_factors = [*second_factors, *minute_factors, *degree_factors]
+
+    n = np.searchsorted(degree_limits, dv)
+    step = degree_steps[n]
+    factor = degree_factors[n]
+
+    return step, factor
+
+
+def select_step_hour(dv):
+
+    hour_limits_ = [1.5, 2.5, 3.5, 5, 7, 10, 15, 21, 36]
+    hour_steps_  = [1,   2,   3,   4, 6,  8, 12, 18, 24]
+    hour_factors = [1.] * len(hour_steps_)
+
+    minsec_limits_ = [1.5, 2.5, 3.5, 4.5, 5.5, 8, 11, 14, 18, 25, 45]
+    minsec_steps_  = [1,   2,   3,   4,   5,   6, 10, 12, 15, 20, 30]
+
+    minute_limits_ = np.array(minsec_limits_) / 60
+    minute_factors = [60.] * len(minute_limits_)
+
+    second_limits_ = np.array(minsec_limits_) / 3600
+    second_factors = [3600.] * len(second_limits_)
+
+    hour_limits = [*second_limits_, *minute_limits_, *hour_limits_]
+    hour_steps = [*minsec_steps_, *minsec_steps_, *hour_steps_]
+    hour_factors = [*second_factors, *minute_factors, *hour_factors]
+
+    n = np.searchsorted(hour_limits, dv)
+    step = hour_steps[n]
+    factor = hour_factors[n]
+
+    return step, factor
+
+
+def select_step_sub(dv):
+
+    # subarcsec or degree
+    tmp = 10.**(int(math.log10(dv))-1.)
+
+    factor = 1./tmp
+
+    if 1.5*tmp >= dv:
+        step = 1
+    elif 3.*tmp >= dv:
+        step = 2
+    elif 7.*tmp >= dv:
+        step = 5
+    else:
+        step = 1
+        factor = 0.1*factor
+
+    return step, factor
+
+
+def select_step(v1, v2, nv, hour=False, include_last=True,
+                threshold_factor=3600.):
+
+    if v1 > v2:
+        v1, v2 = v2, v1
+
+    dv = (v2 - v1) / nv
+
+    if hour:
+        _select_step = select_step_hour
+        cycle = 24.
+    else:
+        _select_step = select_step_degree
+        cycle = 360.
+
+    # for degree
+    if dv > 1 / threshold_factor:
+        step, factor = _select_step(dv)
+    else:
+        step, factor = select_step_sub(dv*threshold_factor)
+
+        factor = factor * threshold_factor
+
+    levs = np.arange(np.floor(v1 * factor / step),
+                     np.ceil(v2 * factor / step) + 0.5,
+                     dtype=int) * step
+
+    # n : number of valid levels. If there is a cycle, e.g., [0, 90, 180,
+    # 270, 360], the grid line needs to be extended from 0 to 360, so
+    # we need to return the whole array. However, the last level (360)
+    # needs to be ignored often. In this case, so we return n=4.
+
+    n = len(levs)
+
+    # we need to check the range of values
+    # for example, -90 to 90, 0 to 360,
+
+    if factor == 1. and levs[-1] >= levs[0] + cycle:  # check for cycle
+        nv = int(cycle / step)
+        if include_last:
+            levs = levs[0] + np.arange(0, nv+1, 1) * step
+        else:
+            levs = levs[0] + np.arange(0, nv, 1) * step
+
+        n = len(levs)
+
+    return np.array(levs), n, factor
+
+
+def select_step24(v1, v2, nv, include_last=True, threshold_factor=3600):
+    v1, v2 = v1 / 15, v2 / 15
+    levs, n, factor = select_step(v1, v2, nv, hour=True,
+                                  include_last=include_last,
+                                  threshold_factor=threshold_factor)
+    return levs * 15, n, factor
+
+
+def select_step360(v1, v2, nv, include_last=True, threshold_factor=3600):
+    return select_step(v1, v2, nv, hour=False,
+                       include_last=include_last,
+                       threshold_factor=threshold_factor)
+
+
+class LocatorBase:
+    def __init__(self, nbins, include_last=True):
+        self.nbins = nbins
+        self._include_last = include_last
+
+    def set_params(self, nbins=None):
+        if nbins is not None:
+            self.nbins = int(nbins)
+
+
+class LocatorHMS(LocatorBase):
+    def __call__(self, v1, v2):
+        return select_step24(v1, v2, self.nbins, self._include_last)
+
+
+class LocatorHM(LocatorBase):
+    def __call__(self, v1, v2):
+        return select_step24(v1, v2, self.nbins, self._include_last,
+                             threshold_factor=60)
+
+
+class LocatorH(LocatorBase):
+    def __call__(self, v1, v2):
+        return select_step24(v1, v2, self.nbins, self._include_last,
+                             threshold_factor=1)
+
+
+class LocatorDMS(LocatorBase):
+    def __call__(self, v1, v2):
+        return select_step360(v1, v2, self.nbins, self._include_last)
+
+
+class LocatorDM(LocatorBase):
+    def __call__(self, v1, v2):
+        return select_step360(v1, v2, self.nbins, self._include_last,
+                              threshold_factor=60)
+
+
+class LocatorD(LocatorBase):
+    def __call__(self, v1, v2):
+        return select_step360(v1, v2, self.nbins, self._include_last,
+                              threshold_factor=1)
+
+
+class FormatterDMS:
+    deg_mark = r"^{\circ}"
+    min_mark = r"^{\prime}"
+    sec_mark = r"^{\prime\prime}"
+
+    fmt_d = "$%d" + deg_mark + "$"
+    fmt_ds = r"$%d.%s" + deg_mark + "$"
+
+    # %s for sign
+    fmt_d_m = r"$%s%d" + deg_mark + r"\,%02d" + min_mark + "$"
+    fmt_d_ms = r"$%s%d" + deg_mark + r"\,%02d.%s" + min_mark + "$"
+
+    fmt_d_m_partial = "$%s%d" + deg_mark + r"\,%02d" + min_mark + r"\,"
+    fmt_s_partial = "%02d" + sec_mark + "$"
+    fmt_ss_partial = "%02d.%s" + sec_mark + "$"
+
+    def _get_number_fraction(self, factor):
+        ## check for fractional numbers
+        number_fraction = None
+        # check for 60
+
+        for threshold in [1, 60, 3600]:
+            if factor <= threshold:
+                break
+
+            d = factor // threshold
+            int_log_d = int(np.floor(np.log10(d)))
+            if 10**int_log_d == d and d != 1:
+                number_fraction = int_log_d
+                factor = factor // 10**int_log_d
+                return factor, number_fraction
+
+        return factor, number_fraction
+
+    def __call__(self, direction, factor, values):
+        if len(values) == 0:
+            return []
+
+        ss = np.sign(values)
+        signs = ["-" if v < 0 else "" for v in values]
+
+        factor, number_fraction = self._get_number_fraction(factor)
+
+        values = np.abs(values)
+
+        if number_fraction is not None:
+            values, frac_part = divmod(values, 10 ** number_fraction)
+            frac_fmt = "%%0%dd" % (number_fraction,)
+            frac_str = [frac_fmt % (f1,) for f1 in frac_part]
+
+        if factor == 1:
+            if number_fraction is None:
+                return [self.fmt_d % (s * int(v),) for s, v in zip(ss, values)]
+            else:
+                return [self.fmt_ds % (s * int(v), f1)
+                        for s, v, f1 in zip(ss, values, frac_str)]
+        elif factor == 60:
+            deg_part, min_part = divmod(values, 60)
+            if number_fraction is None:
+                return [self.fmt_d_m % (s1, d1, m1)
+                        for s1, d1, m1 in zip(signs, deg_part, min_part)]
+            else:
+                return [self.fmt_d_ms % (s, d1, m1, f1)
+                        for s, d1, m1, f1
+                        in zip(signs, deg_part, min_part, frac_str)]
+
+        elif factor == 3600:
+            if ss[-1] == -1:
+                inverse_order = True
+                values = values[::-1]
+                signs = signs[::-1]
+            else:
+                inverse_order = False
+
+            l_hm_old = ""
+            r = []
+
+            deg_part, min_part_ = divmod(values, 3600)
+            min_part, sec_part = divmod(min_part_, 60)
+
+            if number_fraction is None:
+                sec_str = [self.fmt_s_partial % (s1,) for s1 in sec_part]
+            else:
+                sec_str = [self.fmt_ss_partial % (s1, f1)
+                           for s1, f1 in zip(sec_part, frac_str)]
+
+            for s, d1, m1, s1 in zip(signs, deg_part, min_part, sec_str):
+                l_hm = self.fmt_d_m_partial % (s, d1, m1)
+                if l_hm != l_hm_old:
+                    l_hm_old = l_hm
+                    l = l_hm + s1
+                else:
+                    l = "$" + s + s1
+                r.append(l)
+
+            if inverse_order:
+                return r[::-1]
+            else:
+                return r
+
+        else:  # factor > 3600.
+            return [r"$%s^{\circ}$" % v for v in ss*values]
+
+
+class FormatterHMS(FormatterDMS):
+    deg_mark = r"^\mathrm{h}"
+    min_mark = r"^\mathrm{m}"
+    sec_mark = r"^\mathrm{s}"
+
+    fmt_d = "$%d" + deg_mark + "$"
+    fmt_ds = r"$%d.%s" + deg_mark + "$"
+
+    # %s for sign
+    fmt_d_m = r"$%s%d" + deg_mark + r"\,%02d" + min_mark+"$"
+    fmt_d_ms = r"$%s%d" + deg_mark + r"\,%02d.%s" + min_mark+"$"
+
+    fmt_d_m_partial = "$%s%d" + deg_mark + r"\,%02d" + min_mark + r"\,"
+    fmt_s_partial = "%02d" + sec_mark + "$"
+    fmt_ss_partial = "%02d.%s" + sec_mark + "$"
+
+    def __call__(self, direction, factor, values):  # hour
+        return super().__call__(direction, factor, np.asarray(values) / 15)
+
+
+class ExtremeFinderCycle(ExtremeFinderSimple):
+    # docstring inherited
+
+    def __init__(self, nx, ny,
+                 lon_cycle=360., lat_cycle=None,
+                 lon_minmax=None, lat_minmax=(-90, 90)):
+        """
+        This subclass handles the case where one or both coordinates should be
+        taken modulo 360, or be restricted to not exceed a specific range.
+
+        Parameters
+        ----------
+        nx, ny : int
+            The number of samples in each direction.
+
+        lon_cycle, lat_cycle : 360 or None
+            If not None, values in the corresponding direction are taken modulo
+            *lon_cycle* or *lat_cycle*; in theory this can be any number but
+            the implementation actually assumes that it is 360 (if not None);
+            other values give nonsensical results.
+
+            This is done by "unwrapping" the transformed grid coordinates so
+            that jumps are less than a half-cycle; then normalizing the span to
+            no more than a full cycle.
+
+            For example, if values are in the union of the [0, 2] and
+            [358, 360] intervals (typically, angles measured modulo 360), the
+            values in the second interval are normalized to [-2, 0] instead so
+            that the values now cover [-2, 2].  If values are in a range of
+            [5, 1000], this gets normalized to [5, 365].
+
+        lon_minmax, lat_minmax : (float, float) or None
+            If not None, the computed bounding box is clipped to the given
+            range in the corresponding direction.
+        """
+        self.nx, self.ny = nx, ny
+        self.lon_cycle, self.lat_cycle = lon_cycle, lat_cycle
+        self.lon_minmax = lon_minmax
+        self.lat_minmax = lat_minmax
+
+    def __call__(self, transform_xy, x1, y1, x2, y2):
+        # docstring inherited
+        x, y = np.meshgrid(
+            np.linspace(x1, x2, self.nx), np.linspace(y1, y2, self.ny))
+        lon, lat = transform_xy(np.ravel(x), np.ravel(y))
+
+        # iron out jumps, but algorithm should be improved.
+        # This is just naive way of doing and my fail for some cases.
+        # Consider replacing this with numpy.unwrap
+        # We are ignoring invalid warnings. They are triggered when
+        # comparing arrays with NaNs using > We are already handling
+        # that correctly using np.nanmin and np.nanmax
+        with np.errstate(invalid='ignore'):
+            if self.lon_cycle is not None:
+                lon0 = np.nanmin(lon)
+                lon -= 360. * ((lon - lon0) > 180.)
+            if self.lat_cycle is not None:
+                lat0 = np.nanmin(lat)
+                lat -= 360. * ((lat - lat0) > 180.)
+
+        lon_min, lon_max = np.nanmin(lon), np.nanmax(lon)
+        lat_min, lat_max = np.nanmin(lat), np.nanmax(lat)
+
+        lon_min, lon_max, lat_min, lat_max = \
+            self._add_pad(lon_min, lon_max, lat_min, lat_max)
+
+        # check cycle
+        if self.lon_cycle:
+            lon_max = min(lon_max, lon_min + self.lon_cycle)
+        if self.lat_cycle:
+            lat_max = min(lat_max, lat_min + self.lat_cycle)
+
+        if self.lon_minmax is not None:
+            min0 = self.lon_minmax[0]
+            lon_min = max(min0, lon_min)
+            max0 = self.lon_minmax[1]
+            lon_max = min(max0, lon_max)
+
+        if self.lat_minmax is not None:
+            min0 = self.lat_minmax[0]
+            lat_min = max(min0, lat_min)
+            max0 = self.lat_minmax[1]
+            lat_max = min(max0, lat_max)
+
+        return lon_min, lon_max, lat_min, lat_max

venv/lib/python3.13/site-packages/mpl_toolkits/axisartist/axes_divider.py

@@ -0,0 +1,2 @@
+from mpl_toolkits.axes_grid1.axes_divider import (  # noqa
+    Divider, SubplotDivider, AxesDivider, make_axes_locatable)

venv/lib/python3.13/site-packages/mpl_toolkits/axisartist/axisline_style.py

@@ -0,0 +1,193 @@
+"""
+Provides classes to style the axis lines.
+"""
+import math
+
+import numpy as np
+
+import matplotlib as mpl
+from matplotlib.patches import _Style, FancyArrowPatch
+from matplotlib.path import Path
+from matplotlib.transforms import IdentityTransform
+
+
+class _FancyAxislineStyle:
+    class SimpleArrow(FancyArrowPatch):
+        """The artist class that will be returned for SimpleArrow style."""
+        _ARROW_STYLE = "->"
+
+        def __init__(self, axis_artist, line_path, transform,
+                     line_mutation_scale):
+            self._axis_artist = axis_artist
+            self._line_transform = transform
+            self._line_path = line_path
+            self._line_mutation_scale = line_mutation_scale
+
+            FancyArrowPatch.__init__(self,
+                                     path=self._line_path,
+                                     arrowstyle=self._ARROW_STYLE,
+                                     patchA=None,
+                                     patchB=None,
+                                     shrinkA=0.,
+                                     shrinkB=0.,
+                                     mutation_scale=line_mutation_scale,
+                                     mutation_aspect=None,
+                                     transform=IdentityTransform(),
+                                     )
+
+        def set_line_mutation_scale(self, scale):
+            self.set_mutation_scale(scale*self._line_mutation_scale)
+
+        def _extend_path(self, path, mutation_size=10):
+            """
+            Extend the path to make a room for drawing arrow.
+            """
+            (x0, y0), (x1, y1) = path.vertices[-2:]
+            theta = math.atan2(y1 - y0, x1 - x0)
+            x2 = x1 + math.cos(theta) * mutation_size
+            y2 = y1 + math.sin(theta) * mutation_size
+            if path.codes is None:
+                return Path(np.concatenate([path.vertices, [[x2, y2]]]))
+            else:
+                return Path(np.concatenate([path.vertices, [[x2, y2]]]),
+                            np.concatenate([path.codes, [Path.LINETO]]))
+
+        def set_path(self, path):
+            self._line_path = path
+
+        def draw(self, renderer):
+            """
+            Draw the axis line.
+             1) Transform the path to the display coordinate.
+             2) Extend the path to make a room for arrow.
+             3) Update the path of the FancyArrowPatch.
+             4) Draw.
+            """
+            path_in_disp = self._line_transform.transform_path(self._line_path)
+            mutation_size = self.get_mutation_scale()  # line_mutation_scale()
+            extended_path = self._extend_path(path_in_disp,
+                                              mutation_size=mutation_size)
+            self._path_original = extended_path
+            FancyArrowPatch.draw(self, renderer)
+
+        def get_window_extent(self, renderer=None):
+
+            path_in_disp = self._line_transform.transform_path(self._line_path)
+            mutation_size = self.get_mutation_scale()  # line_mutation_scale()
+            extended_path = self._extend_path(path_in_disp,
+                                              mutation_size=mutation_size)
+            self._path_original = extended_path
+            return FancyArrowPatch.get_window_extent(self, renderer)
+
+    class FilledArrow(SimpleArrow):
+        """The artist class that will be returned for FilledArrow style."""
+        _ARROW_STYLE = "-|>"
+
+        def __init__(self, axis_artist, line_path, transform,
+                     line_mutation_scale, facecolor):
+            super().__init__(axis_artist, line_path, transform,
+                             line_mutation_scale)
+            self.set_facecolor(facecolor)
+
+
+class AxislineStyle(_Style):
+    """
+    A container class which defines style classes for AxisArtists.
+
+    An instance of any axisline style class is a callable object,
+    whose call signature is ::
+
+       __call__(self, axis_artist, path, transform)
+
+    When called, this should return an `.Artist` with the following methods::
+
+      def set_path(self, path):
+          # set the path for axisline.
+
+      def set_line_mutation_scale(self, scale):
+          # set the scale
+
+      def draw(self, renderer):
+          # draw
+    """
+
+    _style_list = {}
+
+    class _Base:
+        # The derived classes are required to be able to be initialized
+        # w/o arguments, i.e., all its argument (except self) must have
+        # the default values.
+
+        def __init__(self):
+            """
+            initialization.
+            """
+            super().__init__()
+
+        def __call__(self, axis_artist, transform):
+            """
+            Given the AxisArtist instance, and transform for the path (set_path
+            method), return the Matplotlib artist for drawing the axis line.
+            """
+            return self.new_line(axis_artist, transform)
+
+    class SimpleArrow(_Base):
+        """
+        A simple arrow.
+        """
+
+        ArrowAxisClass = _FancyAxislineStyle.SimpleArrow
+
+        def __init__(self, size=1):
+            """
+            Parameters
+            ----------
+            size : float
+                Size of the arrow as a fraction of the ticklabel size.
+            """
+
+            self.size = size
+            super().__init__()
+
+        def new_line(self, axis_artist, transform):
+
+            linepath = Path([(0, 0), (0, 1)])
+            axisline = self.ArrowAxisClass(axis_artist, linepath, transform,
+                                           line_mutation_scale=self.size)
+            return axisline
+
+    _style_list["->"] = SimpleArrow
+
+    class FilledArrow(SimpleArrow):
+        """
+        An arrow with a filled head.
+        """
+
+        ArrowAxisClass = _FancyAxislineStyle.FilledArrow
+
+        def __init__(self, size=1, facecolor=None):
+            """
+            Parameters
+            ----------
+            size : float
+                Size of the arrow as a fraction of the ticklabel size.
+            facecolor : :mpltype:`color`, default: :rc:`axes.edgecolor`
+                Fill color.
+
+                .. versionadded:: 3.7
+            """
+
+            if facecolor is None:
+                facecolor = mpl.rcParams['axes.edgecolor']
+            self.size = size
+            self._facecolor = facecolor
+            super().__init__(size=size)
+
+        def new_line(self, axis_artist, transform):
+            linepath = Path([(0, 0), (0, 1)])
+            axisline = self.ArrowAxisClass(axis_artist, linepath, transform,
+                                           line_mutation_scale=self.size,
+                                           facecolor=self._facecolor)
+            return axisline
+
+    _style_list["-|>"] = FilledArrow

venv/lib/python3.13/site-packages/mpl_toolkits/axisartist/axislines.py

@@ -0,0 +1,479 @@
+"""
+Axislines includes modified implementation of the Axes class. The
+biggest difference is that the artists responsible for drawing the axis spine,
+ticks, ticklabels and axis labels are separated out from Matplotlib's Axis
+class. Originally, this change was motivated to support curvilinear
+grid. Here are a few reasons that I came up with a new axes class:
+
+* "top" and "bottom" x-axis (or "left" and "right" y-axis) can have
+  different ticks (tick locations and labels). This is not possible
+  with the current Matplotlib, although some twin axes trick can help.
+
+* Curvilinear grid.
+
+* angled ticks.
+
+In the new axes class, xaxis and yaxis is set to not visible by
+default, and new set of artist (AxisArtist) are defined to draw axis
+line, ticks, ticklabels and axis label. Axes.axis attribute serves as
+a dictionary of these artists, i.e., ax.axis["left"] is a AxisArtist
+instance responsible to draw left y-axis. The default Axes.axis contains
+"bottom", "left", "top" and "right".
+
+AxisArtist can be considered as a container artist and has the following
+children artists which will draw ticks, labels, etc.
+
+* line
+* major_ticks, major_ticklabels
+* minor_ticks, minor_ticklabels
+* offsetText
+* label
+
+Note that these are separate artists from `matplotlib.axis.Axis`, thus most
+tick-related functions in Matplotlib won't work. For example, color and
+markerwidth of the ``ax.axis["bottom"].major_ticks`` will follow those of
+Axes.xaxis unless explicitly specified.
+
+In addition to AxisArtist, the Axes will have *gridlines* attribute,
+which obviously draws grid lines. The gridlines needs to be separated
+from the axis as some gridlines can never pass any axis.
+"""
+
+import numpy as np
+
+import matplotlib as mpl
+from matplotlib import _api
+import matplotlib.axes as maxes
+from matplotlib.path import Path
+from mpl_toolkits.axes_grid1 import mpl_axes
+from .axisline_style import AxislineStyle  # noqa
+from .axis_artist import AxisArtist, GridlinesCollection
+
+
+class _AxisArtistHelperBase:
+    """
+    Base class for axis helper.
+
+    Subclasses should define the methods listed below.  The *axes*
+    argument will be the ``.axes`` attribute of the caller artist. ::
+
+        # Construct the spine.
+
+        def get_line_transform(self, axes):
+            return transform
+
+        def get_line(self, axes):
+            return path
+
+        # Construct the label.
+
+        def get_axislabel_transform(self, axes):
+            return transform
+
+        def get_axislabel_pos_angle(self, axes):
+            return (x, y), angle
+
+        # Construct the ticks.
+
+        def get_tick_transform(self, axes):
+            return transform
+
+        def get_tick_iterators(self, axes):
+            # A pair of iterables (one for major ticks, one for minor ticks)
+            # that yield (tick_position, tick_angle, tick_label).
+            return iter_major, iter_minor
+    """
+
+    def __init__(self, nth_coord):
+        self.nth_coord = nth_coord
+
+    def update_lim(self, axes):
+        pass
+
+    def get_nth_coord(self):
+        return self.nth_coord
+
+    def _to_xy(self, values, const):
+        """
+        Create a (*values.shape, 2)-shape array representing (x, y) pairs.
+
+        The other coordinate is filled with the constant *const*.
+
+        Example::
+
+            >>> self.nth_coord = 0
+            >>> self._to_xy([1, 2, 3], const=0)
+            array([[1, 0],
+                   [2, 0],
+                   [3, 0]])
+        """
+        if self.nth_coord == 0:
+            return np.stack(np.broadcast_arrays(values, const), axis=-1)
+        elif self.nth_coord == 1:
+            return np.stack(np.broadcast_arrays(const, values), axis=-1)
+        else:
+            raise ValueError("Unexpected nth_coord")
+
+
+class _FixedAxisArtistHelperBase(_AxisArtistHelperBase):
+    """Helper class for a fixed (in the axes coordinate) axis."""
+
+    @_api.delete_parameter("3.9", "nth_coord")
+    def __init__(self, loc, nth_coord=None):
+        """``nth_coord = 0``: x-axis; ``nth_coord = 1``: y-axis."""
+        super().__init__(_api.check_getitem(
+            {"bottom": 0, "top": 0, "left": 1, "right": 1}, loc=loc))
+        self._loc = loc
+        self._pos = {"bottom": 0, "top": 1, "left": 0, "right": 1}[loc]
+        # axis line in transAxes
+        self._path = Path(self._to_xy((0, 1), const=self._pos))
+
+    # LINE
+
+    def get_line(self, axes):
+        return self._path
+
+    def get_line_transform(self, axes):
+        return axes.transAxes
+
+    # LABEL
+
+    def get_axislabel_transform(self, axes):
+        return axes.transAxes
+
+    def get_axislabel_pos_angle(self, axes):
+        """
+        Return the label reference position in transAxes.
+
+        get_label_transform() returns a transform of (transAxes+offset)
+        """
+        return dict(left=((0., 0.5), 90),  # (position, angle_tangent)
+                    right=((1., 0.5), 90),
+                    bottom=((0.5, 0.), 0),
+                    top=((0.5, 1.), 0))[self._loc]
+
+    # TICK
+
+    def get_tick_transform(self, axes):
+        return [axes.get_xaxis_transform(), axes.get_yaxis_transform()][self.nth_coord]
+
+
+class _FloatingAxisArtistHelperBase(_AxisArtistHelperBase):
+    def __init__(self, nth_coord, value):
+        self._value = value
+        super().__init__(nth_coord)
+
+    def get_line(self, axes):
+        raise RuntimeError("get_line method should be defined by the derived class")
+
+
+class FixedAxisArtistHelperRectilinear(_FixedAxisArtistHelperBase):
+
+    @_api.delete_parameter("3.9", "nth_coord")
+    def __init__(self, axes, loc, nth_coord=None):
+        """
+        nth_coord = along which coordinate value varies
+        in 2D, nth_coord = 0 ->  x axis, nth_coord = 1 -> y axis
+        """
+        super().__init__(loc)
+        self.axis = [axes.xaxis, axes.yaxis][self.nth_coord]
+
+    # TICK
+
+    def get_tick_iterators(self, axes):
+        """tick_loc, tick_angle, tick_label"""
+        angle_normal, angle_tangent = {0: (90, 0), 1: (0, 90)}[self.nth_coord]
+
+        major = self.axis.major
+        major_locs = major.locator()
+        major_labels = major.formatter.format_ticks(major_locs)
+
+        minor = self.axis.minor
+        minor_locs = minor.locator()
+        minor_labels = minor.formatter.format_ticks(minor_locs)
+
+        tick_to_axes = self.get_tick_transform(axes) - axes.transAxes
+
+        def _f(locs, labels):
+            for loc, label in zip(locs, labels):
+                c = self._to_xy(loc, const=self._pos)
+                # check if the tick point is inside axes
+                c2 = tick_to_axes.transform(c)
+                if mpl.transforms._interval_contains_close((0, 1), c2[self.nth_coord]):
+                    yield c, angle_normal, angle_tangent, label
+
+        return _f(major_locs, major_labels), _f(minor_locs, minor_labels)
+
+
+class FloatingAxisArtistHelperRectilinear(_FloatingAxisArtistHelperBase):
+
+    def __init__(self, axes, nth_coord,
+                 passingthrough_point, axis_direction="bottom"):
+        super().__init__(nth_coord, passingthrough_point)
+        self._axis_direction = axis_direction
+        self.axis = [axes.xaxis, axes.yaxis][self.nth_coord]
+
+    def get_line(self, axes):
+        fixed_coord = 1 - self.nth_coord
+        data_to_axes = axes.transData - axes.transAxes
+        p = data_to_axes.transform([self._value, self._value])
+        return Path(self._to_xy((0, 1), const=p[fixed_coord]))
+
+    def get_line_transform(self, axes):
+        return axes.transAxes
+
+    def get_axislabel_transform(self, axes):
+        return axes.transAxes
+
+    def get_axislabel_pos_angle(self, axes):
+        """
+        Return the label reference position in transAxes.
+
+        get_label_transform() returns a transform of (transAxes+offset)
+        """
+        angle = [0, 90][self.nth_coord]
+        fixed_coord = 1 - self.nth_coord
+        data_to_axes = axes.transData - axes.transAxes
+        p = data_to_axes.transform([self._value, self._value])
+        verts = self._to_xy(0.5, const=p[fixed_coord])
+        return (verts, angle) if 0 <= verts[fixed_coord] <= 1 else (None, None)
+
+    def get_tick_transform(self, axes):
+        return axes.transData
+
+    def get_tick_iterators(self, axes):
+        """tick_loc, tick_angle, tick_label"""
+        angle_normal, angle_tangent = {0: (90, 0), 1: (0, 90)}[self.nth_coord]
+
+        major = self.axis.major
+        major_locs = major.locator()
+        major_labels = major.formatter.format_ticks(major_locs)
+
+        minor = self.axis.minor
+        minor_locs = minor.locator()
+        minor_labels = minor.formatter.format_ticks(minor_locs)
+
+        data_to_axes = axes.transData - axes.transAxes
+
+        def _f(locs, labels):
+            for loc, label in zip(locs, labels):
+                c = self._to_xy(loc, const=self._value)
+                c1, c2 = data_to_axes.transform(c)
+                if 0 <= c1 <= 1 and 0 <= c2 <= 1:
+                    yield c, angle_normal, angle_tangent, label
+
+        return _f(major_locs, major_labels), _f(minor_locs, minor_labels)
+
+
+class AxisArtistHelper:  # Backcompat.
+    Fixed = _FixedAxisArtistHelperBase
+    Floating = _FloatingAxisArtistHelperBase
+
+
+class AxisArtistHelperRectlinear:  # Backcompat.
+    Fixed = FixedAxisArtistHelperRectilinear
+    Floating = FloatingAxisArtistHelperRectilinear
+
+
+class GridHelperBase:
+
+    def __init__(self):
+        self._old_limits = None
+        super().__init__()
+
+    def update_lim(self, axes):
+        x1, x2 = axes.get_xlim()
+        y1, y2 = axes.get_ylim()
+        if self._old_limits != (x1, x2, y1, y2):
+            self._update_grid(x1, y1, x2, y2)
+            self._old_limits = (x1, x2, y1, y2)
+
+    def _update_grid(self, x1, y1, x2, y2):
+        """Cache relevant computations when the axes limits have changed."""
+
+    def get_gridlines(self, which, axis):
+        """
+        Return list of grid lines as a list of paths (list of points).
+
+        Parameters
+        ----------
+        which : {"both", "major", "minor"}
+        axis : {"both", "x", "y"}
+        """
+        return []
+
+
+class GridHelperRectlinear(GridHelperBase):
+
+    def __init__(self, axes):
+        super().__init__()
+        self.axes = axes
+
+    @_api.delete_parameter(
+        "3.9", "nth_coord", addendum="'nth_coord' is now inferred from 'loc'.")
+    def new_fixed_axis(
+            self, loc, nth_coord=None, axis_direction=None, offset=None, axes=None):
+        if axes is None:
+            _api.warn_external(
+                "'new_fixed_axis' explicitly requires the axes keyword.")
+            axes = self.axes
+        if axis_direction is None:
+            axis_direction = loc
+        return AxisArtist(axes, FixedAxisArtistHelperRectilinear(axes, loc),
+                          offset=offset, axis_direction=axis_direction)
+
+    def new_floating_axis(self, nth_coord, value, axis_direction="bottom", axes=None):
+        if axes is None:
+            _api.warn_external(
+                "'new_floating_axis' explicitly requires the axes keyword.")
+            axes = self.axes
+        helper = FloatingAxisArtistHelperRectilinear(
+            axes, nth_coord, value, axis_direction)
+        axisline = AxisArtist(axes, helper, axis_direction=axis_direction)
+        axisline.line.set_clip_on(True)
+        axisline.line.set_clip_box(axisline.axes.bbox)
+        return axisline
+
+    def get_gridlines(self, which="major", axis="both"):
+        """
+        Return list of gridline coordinates in data coordinates.
+
+        Parameters
+        ----------
+        which : {"both", "major", "minor"}
+        axis : {"both", "x", "y"}
+        """
+        _api.check_in_list(["both", "major", "minor"], which=which)
+        _api.check_in_list(["both", "x", "y"], axis=axis)
+        gridlines = []
+
+        if axis in ("both", "x"):
+            locs = []
+            y1, y2 = self.axes.get_ylim()
+            if which in ("both", "major"):
+                locs.extend(self.axes.xaxis.major.locator())
+            if which in ("both", "minor"):
+                locs.extend(self.axes.xaxis.minor.locator())
+            gridlines.extend([[x, x], [y1, y2]] for x in locs)
+
+        if axis in ("both", "y"):
+            x1, x2 = self.axes.get_xlim()
+            locs = []
+            if self.axes.yaxis._major_tick_kw["gridOn"]:
+                locs.extend(self.axes.yaxis.major.locator())
+            if self.axes.yaxis._minor_tick_kw["gridOn"]:
+                locs.extend(self.axes.yaxis.minor.locator())
+            gridlines.extend([[x1, x2], [y, y]] for y in locs)
+
+        return gridlines
+
+
+class Axes(maxes.Axes):
+
+    def __init__(self, *args, grid_helper=None, **kwargs):
+        self._axisline_on = True
+        self._grid_helper = grid_helper if grid_helper else GridHelperRectlinear(self)
+        super().__init__(*args, **kwargs)
+        self.toggle_axisline(True)
+
+    def toggle_axisline(self, b=None):
+        if b is None:
+            b = not self._axisline_on
+        if b:
+            self._axisline_on = True
+            self.spines[:].set_visible(False)
+            self.xaxis.set_visible(False)
+            self.yaxis.set_visible(False)
+        else:
+            self._axisline_on = False
+            self.spines[:].set_visible(True)
+            self.xaxis.set_visible(True)
+            self.yaxis.set_visible(True)
+
+    @property
+    def axis(self):
+        return self._axislines
+
+    def clear(self):
+        # docstring inherited
+
+        # Init gridlines before clear() as clear() calls grid().
+        self.gridlines = gridlines = GridlinesCollection(
+            [],
+            colors=mpl.rcParams['grid.color'],
+            linestyles=mpl.rcParams['grid.linestyle'],
+            linewidths=mpl.rcParams['grid.linewidth'])
+        self._set_artist_props(gridlines)
+        gridlines.set_grid_helper(self.get_grid_helper())
+
+        super().clear()
+
+        # clip_path is set after Axes.clear(): that's when a patch is created.
+        gridlines.set_clip_path(self.axes.patch)
+
+        # Init axis artists.
+        self._axislines = mpl_axes.Axes.AxisDict(self)
+        new_fixed_axis = self.get_grid_helper().new_fixed_axis
+        self._axislines.update({
+            loc: new_fixed_axis(loc=loc, axes=self, axis_direction=loc)
+            for loc in ["bottom", "top", "left", "right"]})
+        for axisline in [self._axislines["top"], self._axislines["right"]]:
+            axisline.label.set_visible(False)
+            axisline.major_ticklabels.set_visible(False)
+            axisline.minor_ticklabels.set_visible(False)
+
+    def get_grid_helper(self):
+        return self._grid_helper
+
+    def grid(self, visible=None, which='major', axis="both", **kwargs):
+        """
+        Toggle the gridlines, and optionally set the properties of the lines.
+        """
+        # There are some discrepancies in the behavior of grid() between
+        # axes_grid and Matplotlib, because axes_grid explicitly sets the
+        # visibility of the gridlines.
+        super().grid(visible, which=which, axis=axis, **kwargs)
+        if not self._axisline_on:
+            return
+        if visible is None:
+            visible = (self.axes.xaxis._minor_tick_kw["gridOn"]
+                       or self.axes.xaxis._major_tick_kw["gridOn"]
+                       or self.axes.yaxis._minor_tick_kw["gridOn"]
+                       or self.axes.yaxis._major_tick_kw["gridOn"])
+        self.gridlines.set(which=which, axis=axis, visible=visible)
+        self.gridlines.set(**kwargs)
+
+    def get_children(self):
+        if self._axisline_on:
+            children = [*self._axislines.values(), self.gridlines]
+        else:
+            children = []
+        children.extend(super().get_children())
+        return children
+
+    def new_fixed_axis(self, loc, offset=None):
+        return self.get_grid_helper().new_fixed_axis(loc, offset=offset, axes=self)
+
+    def new_floating_axis(self, nth_coord, value, axis_direction="bottom"):
+        return self.get_grid_helper().new_floating_axis(
+            nth_coord, value, axis_direction=axis_direction, axes=self)
+
+
+class AxesZero(Axes):
+
+    def clear(self):
+        super().clear()
+        new_floating_axis = self.get_grid_helper().new_floating_axis
+        self._axislines.update(
+            xzero=new_floating_axis(
+                nth_coord=0, value=0., axis_direction="bottom", axes=self),
+            yzero=new_floating_axis(
+                nth_coord=1, value=0., axis_direction="left", axes=self),
+        )
+        for k in ["xzero", "yzero"]:
+            self._axislines[k].line.set_clip_path(self.patch)
+            self._axislines[k].set_visible(False)
+
+
+Subplot = Axes
+SubplotZero = AxesZero

venv/lib/python3.13/site-packages/mpl_toolkits/axisartist/floating_axes.py

@@ -0,0 +1,275 @@
+"""
+An experimental support for curvilinear grid.
+"""
+
+# TODO :
+# see if tick_iterator method can be simplified by reusing the parent method.
+
+import functools
+
+import numpy as np
+
+import matplotlib as mpl
+from matplotlib import _api, cbook
+import matplotlib.patches as mpatches
+from matplotlib.path import Path
+
+from mpl_toolkits.axes_grid1.parasite_axes import host_axes_class_factory
+
+from . import axislines, grid_helper_curvelinear
+from .axis_artist import AxisArtist
+from .grid_finder import ExtremeFinderSimple
+
+
+class FloatingAxisArtistHelper(
+        grid_helper_curvelinear.FloatingAxisArtistHelper):
+    pass
+
+
+class FixedAxisArtistHelper(grid_helper_curvelinear.FloatingAxisArtistHelper):
+
+    def __init__(self, grid_helper, side, nth_coord_ticks=None):
+        """
+        nth_coord = along which coordinate value varies.
+         nth_coord = 0 ->  x axis, nth_coord = 1 -> y axis
+        """
+        lon1, lon2, lat1, lat2 = grid_helper.grid_finder.extreme_finder(*[None] * 5)
+        value, nth_coord = _api.check_getitem(
+            dict(left=(lon1, 0), right=(lon2, 0), bottom=(lat1, 1), top=(lat2, 1)),
+            side=side)
+        super().__init__(grid_helper, nth_coord, value, axis_direction=side)
+        if nth_coord_ticks is None:
+            nth_coord_ticks = nth_coord
+        self.nth_coord_ticks = nth_coord_ticks
+
+        self.value = value
+        self.grid_helper = grid_helper
+        self._side = side
+
+    def update_lim(self, axes):
+        self.grid_helper.update_lim(axes)
+        self._grid_info = self.grid_helper._grid_info
+
+    def get_tick_iterators(self, axes):
+        """tick_loc, tick_angle, tick_label, (optionally) tick_label"""
+
+        grid_finder = self.grid_helper.grid_finder
+
+        lat_levs, lat_n, lat_factor = self._grid_info["lat_info"]
+        yy0 = lat_levs / lat_factor
+
+        lon_levs, lon_n, lon_factor = self._grid_info["lon_info"]
+        xx0 = lon_levs / lon_factor
+
+        extremes = self.grid_helper.grid_finder.extreme_finder(*[None] * 5)
+        xmin, xmax = sorted(extremes[:2])
+        ymin, ymax = sorted(extremes[2:])
+
+        def trf_xy(x, y):
+            trf = grid_finder.get_transform() + axes.transData
+            return trf.transform(np.column_stack(np.broadcast_arrays(x, y))).T
+
+        if self.nth_coord == 0:
+            mask = (ymin <= yy0) & (yy0 <= ymax)
+            (xx1, yy1), (dxx1, dyy1), (dxx2, dyy2) = \
+                grid_helper_curvelinear._value_and_jacobian(
+                    trf_xy, self.value, yy0[mask], (xmin, xmax), (ymin, ymax))
+            labels = self._grid_info["lat_labels"]
+
+        elif self.nth_coord == 1:
+            mask = (xmin <= xx0) & (xx0 <= xmax)
+            (xx1, yy1), (dxx2, dyy2), (dxx1, dyy1) = \
+                grid_helper_curvelinear._value_and_jacobian(
+                    trf_xy, xx0[mask], self.value, (xmin, xmax), (ymin, ymax))
+            labels = self._grid_info["lon_labels"]
+
+        labels = [l for l, m in zip(labels, mask) if m]
+
+        angle_normal = np.arctan2(dyy1, dxx1)
+        angle_tangent = np.arctan2(dyy2, dxx2)
+        mm = (dyy1 == 0) & (dxx1 == 0)  # points with degenerate normal
+        angle_normal[mm] = angle_tangent[mm] + np.pi / 2
+
+        tick_to_axes = self.get_tick_transform(axes) - axes.transAxes
+        in_01 = functools.partial(
+            mpl.transforms._interval_contains_close, (0, 1))
+
+        def f1():
+            for x, y, normal, tangent, lab \
+                    in zip(xx1, yy1, angle_normal, angle_tangent, labels):
+                c2 = tick_to_axes.transform((x, y))
+                if in_01(c2[0]) and in_01(c2[1]):
+                    yield [x, y], *np.rad2deg([normal, tangent]), lab
+
+        return f1(), iter([])
+
+    def get_line(self, axes):
+        self.update_lim(axes)
+        k, v = dict(left=("lon_lines0", 0),
+                    right=("lon_lines0", 1),
+                    bottom=("lat_lines0", 0),
+                    top=("lat_lines0", 1))[self._side]
+        xx, yy = self._grid_info[k][v]
+        return Path(np.column_stack([xx, yy]))
+
+
+class ExtremeFinderFixed(ExtremeFinderSimple):
+    # docstring inherited
+
+    def __init__(self, extremes):
+        """
+        This subclass always returns the same bounding box.
+
+        Parameters
+        ----------
+        extremes : (float, float, float, float)
+            The bounding box that this helper always returns.
+        """
+        self._extremes = extremes
+
+    def __call__(self, transform_xy, x1, y1, x2, y2):
+        # docstring inherited
+        return self._extremes
+
+
+class GridHelperCurveLinear(grid_helper_curvelinear.GridHelperCurveLinear):
+
+    def __init__(self, aux_trans, extremes,
+                 grid_locator1=None,
+                 grid_locator2=None,
+                 tick_formatter1=None,
+                 tick_formatter2=None):
+        # docstring inherited
+        super().__init__(aux_trans,
+                         extreme_finder=ExtremeFinderFixed(extremes),
+                         grid_locator1=grid_locator1,
+                         grid_locator2=grid_locator2,
+                         tick_formatter1=tick_formatter1,
+                         tick_formatter2=tick_formatter2)
+
+    def new_fixed_axis(
+            self, loc, nth_coord=None, axis_direction=None, offset=None, axes=None):
+        if axes is None:
+            axes = self.axes
+        if axis_direction is None:
+            axis_direction = loc
+        # This is not the same as the FixedAxisArtistHelper class used by
+        # grid_helper_curvelinear.GridHelperCurveLinear.new_fixed_axis!
+        helper = FixedAxisArtistHelper(
+            self, loc, nth_coord_ticks=nth_coord)
+        axisline = AxisArtist(axes, helper, axis_direction=axis_direction)
+        # Perhaps should be moved to the base class?
+        axisline.line.set_clip_on(True)
+        axisline.line.set_clip_box(axisline.axes.bbox)
+        return axisline
+
+    # new_floating_axis will inherit the grid_helper's extremes.
+
+    # def new_floating_axis(self, nth_coord, value, axes=None, axis_direction="bottom"):
+    #     axis = super(GridHelperCurveLinear,
+    #                  self).new_floating_axis(nth_coord,
+    #                                          value, axes=axes,
+    #                                          axis_direction=axis_direction)
+    #     # set extreme values of the axis helper
+    #     if nth_coord == 1:
+    #         axis.get_helper().set_extremes(*self._extremes[:2])
+    #     elif nth_coord == 0:
+    #         axis.get_helper().set_extremes(*self._extremes[2:])
+    #     return axis
+
+    def _update_grid(self, x1, y1, x2, y2):
+        if self._grid_info is None:
+            self._grid_info = dict()
+
+        grid_info = self._grid_info
+
+        grid_finder = self.grid_finder
+        extremes = grid_finder.extreme_finder(grid_finder.inv_transform_xy,
+                                              x1, y1, x2, y2)
+
+        lon_min, lon_max = sorted(extremes[:2])
+        lat_min, lat_max = sorted(extremes[2:])
+        grid_info["extremes"] = lon_min, lon_max, lat_min, lat_max  # extremes
+
+        lon_levs, lon_n, lon_factor = \
+            grid_finder.grid_locator1(lon_min, lon_max)
+        lon_levs = np.asarray(lon_levs)
+        lat_levs, lat_n, lat_factor = \
+            grid_finder.grid_locator2(lat_min, lat_max)
+        lat_levs = np.asarray(lat_levs)
+
+        grid_info["lon_info"] = lon_levs, lon_n, lon_factor
+        grid_info["lat_info"] = lat_levs, lat_n, lat_factor
+
+        grid_info["lon_labels"] = grid_finder._format_ticks(
+            1, "bottom", lon_factor, lon_levs)
+        grid_info["lat_labels"] = grid_finder._format_ticks(
+            2, "bottom", lat_factor, lat_levs)
+
+        lon_values = lon_levs[:lon_n] / lon_factor
+        lat_values = lat_levs[:lat_n] / lat_factor
+
+        lon_lines, lat_lines = grid_finder._get_raw_grid_lines(
+            lon_values[(lon_min < lon_values) & (lon_values < lon_max)],
+            lat_values[(lat_min < lat_values) & (lat_values < lat_max)],
+            lon_min, lon_max, lat_min, lat_max)
+
+        grid_info["lon_lines"] = lon_lines
+        grid_info["lat_lines"] = lat_lines
+
+        lon_lines, lat_lines = grid_finder._get_raw_grid_lines(
+            # lon_min, lon_max, lat_min, lat_max)
+            extremes[:2], extremes[2:], *extremes)
+
+        grid_info["lon_lines0"] = lon_lines
+        grid_info["lat_lines0"] = lat_lines
+
+    def get_gridlines(self, which="major", axis="both"):
+        grid_lines = []
+        if axis in ["both", "x"]:
+            grid_lines.extend(self._grid_info["lon_lines"])
+        if axis in ["both", "y"]:
+            grid_lines.extend(self._grid_info["lat_lines"])
+        return grid_lines
+
+
+class FloatingAxesBase:
+
+    def __init__(self, *args, grid_helper, **kwargs):
+        _api.check_isinstance(GridHelperCurveLinear, grid_helper=grid_helper)
+        super().__init__(*args, grid_helper=grid_helper, **kwargs)
+        self.set_aspect(1.)
+
+    def _gen_axes_patch(self):
+        # docstring inherited
+        x0, x1, y0, y1 = self.get_grid_helper().grid_finder.extreme_finder(*[None] * 5)
+        patch = mpatches.Polygon([(x0, y0), (x1, y0), (x1, y1), (x0, y1)])
+        patch.get_path()._interpolation_steps = 100
+        return patch
+
+    def clear(self):
+        super().clear()
+        self.patch.set_transform(
+            self.get_grid_helper().grid_finder.get_transform()
+            + self.transData)
+        # The original patch is not in the draw tree; it is only used for
+        # clipping purposes.
+        orig_patch = super()._gen_axes_patch()
+        orig_patch.set_figure(self.get_figure(root=False))
+        orig_patch.set_transform(self.transAxes)
+        self.patch.set_clip_path(orig_patch)
+        self.gridlines.set_clip_path(orig_patch)
+        self.adjust_axes_lim()
+
+    def adjust_axes_lim(self):
+        bbox = self.patch.get_path().get_extents(
+            # First transform to pixel coords, then to parent data coords.
+            self.patch.get_transform() - self.transData)
+        bbox = bbox.expanded(1.02, 1.02)
+        self.set_xlim(bbox.xmin, bbox.xmax)
+        self.set_ylim(bbox.ymin, bbox.ymax)
+
+
+floatingaxes_class_factory = cbook._make_class_factory(FloatingAxesBase, "Floating{}")
+FloatingAxes = floatingaxes_class_factory(host_axes_class_factory(axislines.Axes))
+FloatingSubplot = FloatingAxes

venv/lib/python3.13/site-packages/mpl_toolkits/axisartist/grid_finder.py

@@ -0,0 +1,326 @@
+import numpy as np
+
+from matplotlib import ticker as mticker, _api
+from matplotlib.transforms import Bbox, Transform
+
+
+def _find_line_box_crossings(xys, bbox):
+    """
+    Find the points where a polyline crosses a bbox, and the crossing angles.
+
+    Parameters
+    ----------
+    xys : (N, 2) array
+        The polyline coordinates.
+    bbox : `.Bbox`
+        The bounding box.
+
+    Returns
+    -------
+    list of ((float, float), float)
+        Four separate lists of crossings, for the left, right, bottom, and top
+        sides of the bbox, respectively.  For each list, the entries are the
+        ``((x, y), ccw_angle_in_degrees)`` of the crossing, where an angle of 0
+        means that the polyline is moving to the right at the crossing point.
+
+        The entries are computed by linearly interpolating at each crossing
+        between the nearest points on either side of the bbox edges.
+    """
+    crossings = []
+    dxys = xys[1:] - xys[:-1]
+    for sl in [slice(None), slice(None, None, -1)]:
+        us, vs = xys.T[sl]  # "this" coord, "other" coord
+        dus, dvs = dxys.T[sl]
+        umin, vmin = bbox.min[sl]
+        umax, vmax = bbox.max[sl]
+        for u0, inside in [(umin, us > umin), (umax, us < umax)]:
+            cross = []
+            idxs, = (inside[:-1] ^ inside[1:]).nonzero()
+            for idx in idxs:
+                v = vs[idx] + (u0 - us[idx]) * dvs[idx] / dus[idx]
+                if not vmin <= v <= vmax:
+                    continue
+                crossing = (u0, v)[sl]
+                theta = np.degrees(np.arctan2(*dxys[idx][::-1]))
+                cross.append((crossing, theta))
+            crossings.append(cross)
+    return crossings
+
+
+class ExtremeFinderSimple:
+    """
+    A helper class to figure out the range of grid lines that need to be drawn.
+    """
+
+    def __init__(self, nx, ny):
+        """
+        Parameters
+        ----------
+        nx, ny : int
+            The number of samples in each direction.
+        """
+        self.nx = nx
+        self.ny = ny
+
+    def __call__(self, transform_xy, x1, y1, x2, y2):
+        """
+        Compute an approximation of the bounding box obtained by applying
+        *transform_xy* to the box delimited by ``(x1, y1, x2, y2)``.
+
+        The intended use is to have ``(x1, y1, x2, y2)`` in axes coordinates,
+        and have *transform_xy* be the transform from axes coordinates to data
+        coordinates; this method then returns the range of data coordinates
+        that span the actual axes.
+
+        The computation is done by sampling ``nx * ny`` equispaced points in
+        the ``(x1, y1, x2, y2)`` box and finding the resulting points with
+        extremal coordinates; then adding some padding to take into account the
+        finite sampling.
+
+        As each sampling step covers a relative range of *1/nx* or *1/ny*,
+        the padding is computed by expanding the span covered by the extremal
+        coordinates by these fractions.
+        """
+        x, y = np.meshgrid(
+            np.linspace(x1, x2, self.nx), np.linspace(y1, y2, self.ny))
+        xt, yt = transform_xy(np.ravel(x), np.ravel(y))
+        return self._add_pad(xt.min(), xt.max(), yt.min(), yt.max())
+
+    def _add_pad(self, x_min, x_max, y_min, y_max):
+        """Perform the padding mentioned in `__call__`."""
+        dx = (x_max - x_min) / self.nx
+        dy = (y_max - y_min) / self.ny
+        return x_min - dx, x_max + dx, y_min - dy, y_max + dy
+
+
+class _User2DTransform(Transform):
+    """A transform defined by two user-set functions."""
+
+    input_dims = output_dims = 2
+
+    def __init__(self, forward, backward):
+        """
+        Parameters
+        ----------
+        forward, backward : callable
+            The forward and backward transforms, taking ``x`` and ``y`` as
+            separate arguments and returning ``(tr_x, tr_y)``.
+        """
+        # The normal Matplotlib convention would be to take and return an
+        # (N, 2) array but axisartist uses the transposed version.
+        super().__init__()
+        self._forward = forward
+        self._backward = backward
+
+    def transform_non_affine(self, values):
+        # docstring inherited
+        return np.transpose(self._forward(*np.transpose(values)))
+
+    def inverted(self):
+        # docstring inherited
+        return type(self)(self._backward, self._forward)
+
+
+class GridFinder:
+    """
+    Internal helper for `~.grid_helper_curvelinear.GridHelperCurveLinear`, with
+    the same constructor parameters; should not be directly instantiated.
+    """
+
+    def __init__(self,
+                 transform,
+                 extreme_finder=None,
+                 grid_locator1=None,
+                 grid_locator2=None,
+                 tick_formatter1=None,
+                 tick_formatter2=None):
+        if extreme_finder is None:
+            extreme_finder = ExtremeFinderSimple(20, 20)
+        if grid_locator1 is None:
+            grid_locator1 = MaxNLocator()
+        if grid_locator2 is None:
+            grid_locator2 = MaxNLocator()
+        if tick_formatter1 is None:
+            tick_formatter1 = FormatterPrettyPrint()
+        if tick_formatter2 is None:
+            tick_formatter2 = FormatterPrettyPrint()
+        self.extreme_finder = extreme_finder
+        self.grid_locator1 = grid_locator1
+        self.grid_locator2 = grid_locator2
+        self.tick_formatter1 = tick_formatter1
+        self.tick_formatter2 = tick_formatter2
+        self.set_transform(transform)
+
+    def _format_ticks(self, idx, direction, factor, levels):
+        """
+        Helper to support both standard formatters (inheriting from
+        `.mticker.Formatter`) and axisartist-specific ones; should be called instead of
+        directly calling ``self.tick_formatter1`` and ``self.tick_formatter2``.  This
+        method should be considered as a temporary workaround which will be removed in
+        the future at the same time as axisartist-specific formatters.
+        """
+        fmt = _api.check_getitem(
+            {1: self.tick_formatter1, 2: self.tick_formatter2}, idx=idx)
+        return (fmt.format_ticks(levels) if isinstance(fmt, mticker.Formatter)
+                else fmt(direction, factor, levels))
+
+    def get_grid_info(self, x1, y1, x2, y2):
+        """
+        lon_values, lat_values : list of grid values. if integer is given,
+                           rough number of grids in each direction.
+        """
+
+        extremes = self.extreme_finder(self.inv_transform_xy, x1, y1, x2, y2)
+
+        # min & max rage of lat (or lon) for each grid line will be drawn.
+        # i.e., gridline of lon=0 will be drawn from lat_min to lat_max.
+
+        lon_min, lon_max, lat_min, lat_max = extremes
+        lon_levs, lon_n, lon_factor = self.grid_locator1(lon_min, lon_max)
+        lon_levs = np.asarray(lon_levs)
+        lat_levs, lat_n, lat_factor = self.grid_locator2(lat_min, lat_max)
+        lat_levs = np.asarray(lat_levs)
+
+        lon_values = lon_levs[:lon_n] / lon_factor
+        lat_values = lat_levs[:lat_n] / lat_factor
+
+        lon_lines, lat_lines = self._get_raw_grid_lines(lon_values,
+                                                        lat_values,
+                                                        lon_min, lon_max,
+                                                        lat_min, lat_max)
+
+        bb = Bbox.from_extents(x1, y1, x2, y2).expanded(1 + 2e-10, 1 + 2e-10)
+
+        grid_info = {
+            "extremes": extremes,
+            # "lon", "lat", filled below.
+        }
+
+        for idx, lon_or_lat, levs, factor, values, lines in [
+                (1, "lon", lon_levs, lon_factor, lon_values, lon_lines),
+                (2, "lat", lat_levs, lat_factor, lat_values, lat_lines),
+        ]:
+            grid_info[lon_or_lat] = gi = {
+                "lines": [[l] for l in lines],
+                "ticks": {"left": [], "right": [], "bottom": [], "top": []},
+            }
+            for (lx, ly), v, level in zip(lines, values, levs):
+                all_crossings = _find_line_box_crossings(np.column_stack([lx, ly]), bb)
+                for side, crossings in zip(
+                        ["left", "right", "bottom", "top"], all_crossings):
+                    for crossing in crossings:
+                        gi["ticks"][side].append({"level": level, "loc": crossing})
+            for side in gi["ticks"]:
+                levs = [tick["level"] for tick in gi["ticks"][side]]
+                labels = self._format_ticks(idx, side, factor, levs)
+                for tick, label in zip(gi["ticks"][side], labels):
+                    tick["label"] = label
+
+        return grid_info
+
+    def _get_raw_grid_lines(self,
+                            lon_values, lat_values,
+                            lon_min, lon_max, lat_min, lat_max):
+
+        lons_i = np.linspace(lon_min, lon_max, 100)  # for interpolation
+        lats_i = np.linspace(lat_min, lat_max, 100)
+
+        lon_lines = [self.transform_xy(np.full_like(lats_i, lon), lats_i)
+                     for lon in lon_values]
+        lat_lines = [self.transform_xy(lons_i, np.full_like(lons_i, lat))
+                     for lat in lat_values]
+
+        return lon_lines, lat_lines
+
+    def set_transform(self, aux_trans):
+        if isinstance(aux_trans, Transform):
+            self._aux_transform = aux_trans
+        elif len(aux_trans) == 2 and all(map(callable, aux_trans)):
+            self._aux_transform = _User2DTransform(*aux_trans)
+        else:
+            raise TypeError("'aux_trans' must be either a Transform "
+                            "instance or a pair of callables")
+
+    def get_transform(self):
+        return self._aux_transform
+
+    update_transform = set_transform  # backcompat alias.
+
+    def transform_xy(self, x, y):
+        return self._aux_transform.transform(np.column_stack([x, y])).T
+
+    def inv_transform_xy(self, x, y):
+        return self._aux_transform.inverted().transform(
+            np.column_stack([x, y])).T
+
+    def update(self, **kwargs):
+        for k, v in kwargs.items():
+            if k in ["extreme_finder",
+                     "grid_locator1",
+                     "grid_locator2",
+                     "tick_formatter1",
+                     "tick_formatter2"]:
+                setattr(self, k, v)
+            else:
+                raise ValueError(f"Unknown update property {k!r}")
+
+
+class MaxNLocator(mticker.MaxNLocator):
+    def __init__(self, nbins=10, steps=None,
+                 trim=True,
+                 integer=False,
+                 symmetric=False,
+                 prune=None):
+        # trim argument has no effect. It has been left for API compatibility
+        super().__init__(nbins, steps=steps, integer=integer,
+                         symmetric=symmetric, prune=prune)
+        self.create_dummy_axis()
+
+    def __call__(self, v1, v2):
+        locs = super().tick_values(v1, v2)
+        return np.array(locs), len(locs), 1  # 1: factor (see angle_helper)
+
+
+class FixedLocator:
+    def __init__(self, locs):
+        self._locs = locs
+
+    def __call__(self, v1, v2):
+        v1, v2 = sorted([v1, v2])
+        locs = np.array([l for l in self._locs if v1 <= l <= v2])
+        return locs, len(locs), 1  # 1: factor (see angle_helper)
+
+
+# Tick Formatter
+
+class FormatterPrettyPrint:
+    def __init__(self, useMathText=True):
+        self._fmt = mticker.ScalarFormatter(
+            useMathText=useMathText, useOffset=False)
+        self._fmt.create_dummy_axis()
+
+    def __call__(self, direction, factor, values):
+        return self._fmt.format_ticks(values)
+
+
+class DictFormatter:
+    def __init__(self, format_dict, formatter=None):
+        """
+        format_dict : dictionary for format strings to be used.
+        formatter : fall-back formatter
+        """
+        super().__init__()
+        self._format_dict = format_dict
+        self._fallback_formatter = formatter
+
+    def __call__(self, direction, factor, values):
+        """
+        factor is ignored if value is found in the dictionary
+        """
+        if self._fallback_formatter:
+            fallback_strings = self._fallback_formatter(
+                direction, factor, values)
+        else:
+            fallback_strings = [""] * len(values)
+        return [self._format_dict.get(k, v)
+                for k, v in zip(values, fallback_strings)]

venv/lib/python3.13/site-packages/mpl_toolkits/axisartist/grid_helper_curvelinear.py

@@ -0,0 +1,328 @@
+"""
+An experimental support for curvilinear grid.
+"""
+
+import functools
+
+import numpy as np
+
+import matplotlib as mpl
+from matplotlib import _api
+from matplotlib.path import Path
+from matplotlib.transforms import Affine2D, IdentityTransform
+from .axislines import (
+    _FixedAxisArtistHelperBase, _FloatingAxisArtistHelperBase, GridHelperBase)
+from .axis_artist import AxisArtist
+from .grid_finder import GridFinder
+
+
+def _value_and_jacobian(func, xs, ys, xlims, ylims):
+    """
+    Compute *func* and its derivatives along x and y at positions *xs*, *ys*,
+    while ensuring that finite difference calculations don't try to evaluate
+    values outside of *xlims*, *ylims*.
+    """
+    eps = np.finfo(float).eps ** (1/2)  # see e.g. scipy.optimize.approx_fprime
+    val = func(xs, ys)
+    # Take the finite difference step in the direction where the bound is the
+    # furthest; the step size is min of epsilon and distance to that bound.
+    xlo, xhi = sorted(xlims)
+    dxlo = xs - xlo
+    dxhi = xhi - xs
+    xeps = (np.take([-1, 1], dxhi >= dxlo)
+            * np.minimum(eps, np.maximum(dxlo, dxhi)))
+    val_dx = func(xs + xeps, ys)
+    ylo, yhi = sorted(ylims)
+    dylo = ys - ylo
+    dyhi = yhi - ys
+    yeps = (np.take([-1, 1], dyhi >= dylo)
+            * np.minimum(eps, np.maximum(dylo, dyhi)))
+    val_dy = func(xs, ys + yeps)
+    return (val, (val_dx - val) / xeps, (val_dy - val) / yeps)
+
+
+class FixedAxisArtistHelper(_FixedAxisArtistHelperBase):
+    """
+    Helper class for a fixed axis.
+    """
+
+    def __init__(self, grid_helper, side, nth_coord_ticks=None):
+        """
+        nth_coord = along which coordinate value varies.
+         nth_coord = 0 ->  x axis, nth_coord = 1 -> y axis
+        """
+
+        super().__init__(loc=side)
+
+        self.grid_helper = grid_helper
+        if nth_coord_ticks is None:
+            nth_coord_ticks = self.nth_coord
+        self.nth_coord_ticks = nth_coord_ticks
+
+        self.side = side
+
+    def update_lim(self, axes):
+        self.grid_helper.update_lim(axes)
+
+    def get_tick_transform(self, axes):
+        return axes.transData
+
+    def get_tick_iterators(self, axes):
+        """tick_loc, tick_angle, tick_label"""
+        v1, v2 = axes.get_ylim() if self.nth_coord == 0 else axes.get_xlim()
+        if v1 > v2:  # Inverted limits.
+            side = {"left": "right", "right": "left",
+                    "top": "bottom", "bottom": "top"}[self.side]
+        else:
+            side = self.side
+
+        angle_tangent = dict(left=90, right=90, bottom=0, top=0)[side]
+
+        def iter_major():
+            for nth_coord, show_labels in [
+                    (self.nth_coord_ticks, True), (1 - self.nth_coord_ticks, False)]:
+                gi = self.grid_helper._grid_info[["lon", "lat"][nth_coord]]
+                for tick in gi["ticks"][side]:
+                    yield (*tick["loc"], angle_tangent,
+                           (tick["label"] if show_labels else ""))
+
+        return iter_major(), iter([])
+
+
+class FloatingAxisArtistHelper(_FloatingAxisArtistHelperBase):
+
+    def __init__(self, grid_helper, nth_coord, value, axis_direction=None):
+        """
+        nth_coord = along which coordinate value varies.
+         nth_coord = 0 ->  x axis, nth_coord = 1 -> y axis
+        """
+        super().__init__(nth_coord, value)
+        self.value = value
+        self.grid_helper = grid_helper
+        self._extremes = -np.inf, np.inf
+        self._line_num_points = 100  # number of points to create a line
+
+    def set_extremes(self, e1, e2):
+        if e1 is None:
+            e1 = -np.inf
+        if e2 is None:
+            e2 = np.inf
+        self._extremes = e1, e2
+
+    def update_lim(self, axes):
+        self.grid_helper.update_lim(axes)
+
+        x1, x2 = axes.get_xlim()
+        y1, y2 = axes.get_ylim()
+        grid_finder = self.grid_helper.grid_finder
+        extremes = grid_finder.extreme_finder(grid_finder.inv_transform_xy,
+                                              x1, y1, x2, y2)
+
+        lon_min, lon_max, lat_min, lat_max = extremes
+        e_min, e_max = self._extremes  # ranges of other coordinates
+        if self.nth_coord == 0:
+            lat_min = max(e_min, lat_min)
+            lat_max = min(e_max, lat_max)
+        elif self.nth_coord == 1:
+            lon_min = max(e_min, lon_min)
+            lon_max = min(e_max, lon_max)
+
+        lon_levs, lon_n, lon_factor = \
+            grid_finder.grid_locator1(lon_min, lon_max)
+        lat_levs, lat_n, lat_factor = \
+            grid_finder.grid_locator2(lat_min, lat_max)
+
+        if self.nth_coord == 0:
+            xx0 = np.full(self._line_num_points, self.value)
+            yy0 = np.linspace(lat_min, lat_max, self._line_num_points)
+            xx, yy = grid_finder.transform_xy(xx0, yy0)
+        elif self.nth_coord == 1:
+            xx0 = np.linspace(lon_min, lon_max, self._line_num_points)
+            yy0 = np.full(self._line_num_points, self.value)
+            xx, yy = grid_finder.transform_xy(xx0, yy0)
+
+        self._grid_info = {
+            "extremes": (lon_min, lon_max, lat_min, lat_max),
+            "lon_info": (lon_levs, lon_n, np.asarray(lon_factor)),
+            "lat_info": (lat_levs, lat_n, np.asarray(lat_factor)),
+            "lon_labels": grid_finder._format_ticks(
+                1, "bottom", lon_factor, lon_levs),
+            "lat_labels": grid_finder._format_ticks(
+                2, "bottom", lat_factor, lat_levs),
+            "line_xy": (xx, yy),
+        }
+
+    def get_axislabel_transform(self, axes):
+        return Affine2D()  # axes.transData
+
+    def get_axislabel_pos_angle(self, axes):
+        def trf_xy(x, y):
+            trf = self.grid_helper.grid_finder.get_transform() + axes.transData
+            return trf.transform([x, y]).T
+
+        xmin, xmax, ymin, ymax = self._grid_info["extremes"]
+        if self.nth_coord == 0:
+            xx0 = self.value
+            yy0 = (ymin + ymax) / 2
+        elif self.nth_coord == 1:
+            xx0 = (xmin + xmax) / 2
+            yy0 = self.value
+        xy1, dxy1_dx, dxy1_dy = _value_and_jacobian(
+            trf_xy, xx0, yy0, (xmin, xmax), (ymin, ymax))
+        p = axes.transAxes.inverted().transform(xy1)
+        if 0 <= p[0] <= 1 and 0 <= p[1] <= 1:
+            d = [dxy1_dy, dxy1_dx][self.nth_coord]
+            return xy1, np.rad2deg(np.arctan2(*d[::-1]))
+        else:
+            return None, None
+
+    def get_tick_transform(self, axes):
+        return IdentityTransform()  # axes.transData
+
+    def get_tick_iterators(self, axes):
+        """tick_loc, tick_angle, tick_label, (optionally) tick_label"""
+
+        lat_levs, lat_n, lat_factor = self._grid_info["lat_info"]
+        yy0 = lat_levs / lat_factor
+
+        lon_levs, lon_n, lon_factor = self._grid_info["lon_info"]
+        xx0 = lon_levs / lon_factor
+
+        e0, e1 = self._extremes
+
+        def trf_xy(x, y):
+            trf = self.grid_helper.grid_finder.get_transform() + axes.transData
+            return trf.transform(np.column_stack(np.broadcast_arrays(x, y))).T
+
+        # find angles
+        if self.nth_coord == 0:
+            mask = (e0 <= yy0) & (yy0 <= e1)
+            (xx1, yy1), (dxx1, dyy1), (dxx2, dyy2) = _value_and_jacobian(
+                trf_xy, self.value, yy0[mask], (-np.inf, np.inf), (e0, e1))
+            labels = self._grid_info["lat_labels"]
+
+        elif self.nth_coord == 1:
+            mask = (e0 <= xx0) & (xx0 <= e1)
+            (xx1, yy1), (dxx2, dyy2), (dxx1, dyy1) = _value_and_jacobian(
+                trf_xy, xx0[mask], self.value, (-np.inf, np.inf), (e0, e1))
+            labels = self._grid_info["lon_labels"]
+
+        labels = [l for l, m in zip(labels, mask) if m]
+
+        angle_normal = np.arctan2(dyy1, dxx1)
+        angle_tangent = np.arctan2(dyy2, dxx2)
+        mm = (dyy1 == 0) & (dxx1 == 0)  # points with degenerate normal
+        angle_normal[mm] = angle_tangent[mm] + np.pi / 2
+
+        tick_to_axes = self.get_tick_transform(axes) - axes.transAxes
+        in_01 = functools.partial(
+            mpl.transforms._interval_contains_close, (0, 1))
+
+        def iter_major():
+            for x, y, normal, tangent, lab \
+                    in zip(xx1, yy1, angle_normal, angle_tangent, labels):
+                c2 = tick_to_axes.transform((x, y))
+                if in_01(c2[0]) and in_01(c2[1]):
+                    yield [x, y], *np.rad2deg([normal, tangent]), lab
+
+        return iter_major(), iter([])
+
+    def get_line_transform(self, axes):
+        return axes.transData
+
+    def get_line(self, axes):
+        self.update_lim(axes)
+        x, y = self._grid_info["line_xy"]
+        return Path(np.column_stack([x, y]))
+
+
+class GridHelperCurveLinear(GridHelperBase):
+    def __init__(self, aux_trans,
+                 extreme_finder=None,
+                 grid_locator1=None,
+                 grid_locator2=None,
+                 tick_formatter1=None,
+                 tick_formatter2=None):
+        """
+        Parameters
+        ----------
+        aux_trans : `.Transform` or tuple[Callable, Callable]
+            The transform from curved coordinates to rectilinear coordinate:
+            either a `.Transform` instance (which provides also its inverse),
+            or a pair of callables ``(trans, inv_trans)`` that define the
+            transform and its inverse.  The callables should have signature::
+
+                x_rect, y_rect = trans(x_curved, y_curved)
+                x_curved, y_curved = inv_trans(x_rect, y_rect)
+
+        extreme_finder
+
+        grid_locator1, grid_locator2
+            Grid locators for each axis.
+
+        tick_formatter1, tick_formatter2
+            Tick formatters for each axis.
+        """
+        super().__init__()
+        self._grid_info = None
+        self.grid_finder = GridFinder(aux_trans,
+                                      extreme_finder,
+                                      grid_locator1,
+                                      grid_locator2,
+                                      tick_formatter1,
+                                      tick_formatter2)
+
+    def update_grid_finder(self, aux_trans=None, **kwargs):
+        if aux_trans is not None:
+            self.grid_finder.update_transform(aux_trans)
+        self.grid_finder.update(**kwargs)
+        self._old_limits = None  # Force revalidation.
+
+    @_api.make_keyword_only("3.9", "nth_coord")
+    def new_fixed_axis(
+            self, loc, nth_coord=None, axis_direction=None, offset=None, axes=None):
+        if axes is None:
+            axes = self.axes
+        if axis_direction is None:
+            axis_direction = loc
+        helper = FixedAxisArtistHelper(self, loc, nth_coord_ticks=nth_coord)
+        axisline = AxisArtist(axes, helper, axis_direction=axis_direction)
+        # Why is clip not set on axisline, unlike in new_floating_axis or in
+        # the floating_axig.GridHelperCurveLinear subclass?
+        return axisline
+
+    def new_floating_axis(self, nth_coord, value, axes=None, axis_direction="bottom"):
+        if axes is None:
+            axes = self.axes
+        helper = FloatingAxisArtistHelper(
+            self, nth_coord, value, axis_direction)
+        axisline = AxisArtist(axes, helper)
+        axisline.line.set_clip_on(True)
+        axisline.line.set_clip_box(axisline.axes.bbox)
+        # axisline.major_ticklabels.set_visible(True)
+        # axisline.minor_ticklabels.set_visible(False)
+        return axisline
+
+    def _update_grid(self, x1, y1, x2, y2):
+        self._grid_info = self.grid_finder.get_grid_info(x1, y1, x2, y2)
+
+    def get_gridlines(self, which="major", axis="both"):
+        grid_lines = []
+        if axis in ["both", "x"]:
+            for gl in self._grid_info["lon"]["lines"]:
+                grid_lines.extend(gl)
+        if axis in ["both", "y"]:
+            for gl in self._grid_info["lat"]["lines"]:
+                grid_lines.extend(gl)
+        return grid_lines
+
+    @_api.deprecated("3.9")
+    def get_tick_iterator(self, nth_coord, axis_side, minor=False):
+        angle_tangent = dict(left=90, right=90, bottom=0, top=0)[axis_side]
+        lon_or_lat = ["lon", "lat"][nth_coord]
+        if not minor:  # major ticks
+            for tick in self._grid_info[lon_or_lat]["ticks"][axis_side]:
+                yield *tick["loc"], angle_tangent, tick["label"]
+        else:
+            for tick in self._grid_info[lon_or_lat]["ticks"][axis_side]:
+                yield *tick["loc"], angle_tangent, ""

venv/lib/python3.13/site-packages/mpl_toolkits/axisartist/parasite_axes.py

@@ -0,0 +1,7 @@
+from mpl_toolkits.axes_grid1.parasite_axes import (
+    host_axes_class_factory, parasite_axes_class_factory)
+from .axislines import Axes
+
+
+ParasiteAxes = parasite_axes_class_factory(Axes)
+HostAxes = SubplotHost = host_axes_class_factory(Axes)

venv/lib/python3.13/site-packages/mpl_toolkits/axisartist/tests/__init__.py

@@ -0,0 +1,10 @@
+from pathlib import Path
+
+
+# Check that the test directories exist
+if not (Path(__file__).parent / "baseline_images").exists():
+    raise OSError(
+        'The baseline image directory does not exist. '
+        'This is most likely because the test data is not installed. '
+        'You may need to install matplotlib from source to get the '
+        'test data.')

venv/lib/python3.13/site-packages/mpl_toolkits/axisartist/tests/conftest.py

@@ -0,0 +1,2 @@
+from matplotlib.testing.conftest import (mpl_test_settings,  # noqa
+                                         pytest_configure, pytest_unconfigure)

venv/lib/python3.13/site-packages/mpl_toolkits/axisartist/tests/test_angle_helper.py

@@ -0,0 +1,141 @@
+import re
+
+import numpy as np
+import pytest
+
+from mpl_toolkits.axisartist.angle_helper import (
+    FormatterDMS, FormatterHMS, select_step, select_step24, select_step360)
+
+
+_MS_RE = (
+    r'''\$  # Mathtext
+        (
+            # The sign sometimes appears on a 0 when a fraction is shown.
+            # Check later that there's only one.
+            (?P<degree_sign>-)?
+            (?P<degree>[0-9.]+)  # Degrees value
+            {degree}  # Degree symbol (to be replaced by format.)
+        )?
+        (
+            (?(degree)\\,)  # Separator if degrees are also visible.
+            (?P<minute_sign>-)?
+            (?P<minute>[0-9.]+)  # Minutes value
+            {minute}  # Minute symbol (to be replaced by format.)
+        )?
+        (
+            (?(minute)\\,)  # Separator if minutes are also visible.
+            (?P<second_sign>-)?
+            (?P<second>[0-9.]+)  # Seconds value
+            {second}  # Second symbol (to be replaced by format.)
+        )?
+        \$  # Mathtext
+    '''
+)
+DMS_RE = re.compile(_MS_RE.format(degree=re.escape(FormatterDMS.deg_mark),
+                                  minute=re.escape(FormatterDMS.min_mark),
+                                  second=re.escape(FormatterDMS.sec_mark)),
+                    re.VERBOSE)
+HMS_RE = re.compile(_MS_RE.format(degree=re.escape(FormatterHMS.deg_mark),
+                                  minute=re.escape(FormatterHMS.min_mark),
+                                  second=re.escape(FormatterHMS.sec_mark)),
+                    re.VERBOSE)
+
+
+def dms2float(degrees, minutes=0, seconds=0):
+    return degrees + minutes / 60.0 + seconds / 3600.0
+
+
+@pytest.mark.parametrize('args, kwargs, expected_levels, expected_factor', [
+    ((-180, 180, 10), {'hour': False}, np.arange(-180, 181, 30), 1.0),
+    ((-12, 12, 10), {'hour': True}, np.arange(-12, 13, 2), 1.0)
+])
+def test_select_step(args, kwargs, expected_levels, expected_factor):
+    levels, n, factor = select_step(*args, **kwargs)
+
+    assert n == len(levels)
+    np.testing.assert_array_equal(levels, expected_levels)
+    assert factor == expected_factor
+
+
+@pytest.mark.parametrize('args, kwargs, expected_levels, expected_factor', [
+    ((-180, 180, 10), {}, np.arange(-180, 181, 30), 1.0),
+    ((-12, 12, 10), {}, np.arange(-750, 751, 150), 60.0)
+])
+def test_select_step24(args, kwargs, expected_levels, expected_factor):
+    levels, n, factor = select_step24(*args, **kwargs)
+
+    assert n == len(levels)
+    np.testing.assert_array_equal(levels, expected_levels)
+    assert factor == expected_factor
+
+
+@pytest.mark.parametrize('args, kwargs, expected_levels, expected_factor', [
+    ((dms2float(20, 21.2), dms2float(21, 33.3), 5), {},
+     np.arange(1215, 1306, 15), 60.0),
+    ((dms2float(20.5, seconds=21.2), dms2float(20.5, seconds=33.3), 5), {},
+     np.arange(73820, 73835, 2), 3600.0),
+    ((dms2float(20, 21.2), dms2float(20, 53.3), 5), {},
+     np.arange(1220, 1256, 5), 60.0),
+    ((21.2, 33.3, 5), {},
+     np.arange(20, 35, 2), 1.0),
+    ((dms2float(20, 21.2), dms2float(21, 33.3), 5), {},
+     np.arange(1215, 1306, 15), 60.0),
+    ((dms2float(20.5, seconds=21.2), dms2float(20.5, seconds=33.3), 5), {},
+     np.arange(73820, 73835, 2), 3600.0),
+    ((dms2float(20.5, seconds=21.2), dms2float(20.5, seconds=21.4), 5), {},
+     np.arange(7382120, 7382141, 5), 360000.0),
+    # test threshold factor
+    ((dms2float(20.5, seconds=11.2), dms2float(20.5, seconds=53.3), 5),
+     {'threshold_factor': 60}, np.arange(12301, 12310), 600.0),
+    ((dms2float(20.5, seconds=11.2), dms2float(20.5, seconds=53.3), 5),
+     {'threshold_factor': 1}, np.arange(20502, 20517, 2), 1000.0),
+])
+def test_select_step360(args, kwargs, expected_levels, expected_factor):
+    levels, n, factor = select_step360(*args, **kwargs)
+
+    assert n == len(levels)
+    np.testing.assert_array_equal(levels, expected_levels)
+    assert factor == expected_factor
+
+
+@pytest.mark.parametrize('Formatter, regex',
+                         [(FormatterDMS, DMS_RE),
+                          (FormatterHMS, HMS_RE)],
+                         ids=['Degree/Minute/Second', 'Hour/Minute/Second'])
+@pytest.mark.parametrize('direction, factor, values', [
+    ("left", 60, [0, -30, -60]),
+    ("left", 600, [12301, 12302, 12303]),
+    ("left", 3600, [0, -30, -60]),
+    ("left", 36000, [738210, 738215, 738220]),
+    ("left", 360000, [7382120, 7382125, 7382130]),
+    ("left", 1., [45, 46, 47]),
+    ("left", 10., [452, 453, 454]),
+])
+def test_formatters(Formatter, regex, direction, factor, values):
+    fmt = Formatter()
+    result = fmt(direction, factor, values)
+
+    prev_degree = prev_minute = prev_second = None
+    for tick, value in zip(result, values):
+        m = regex.match(tick)
+        assert m is not None, f'{tick!r} is not an expected tick format.'
+
+        sign = sum(m.group(sign + '_sign') is not None
+                   for sign in ('degree', 'minute', 'second'))
+        assert sign <= 1, f'Only one element of tick {tick!r} may have a sign.'
+        sign = 1 if sign == 0 else -1
+
+        degree = float(m.group('degree') or prev_degree or 0)
+        minute = float(m.group('minute') or prev_minute or 0)
+        second = float(m.group('second') or prev_second or 0)
+        if Formatter == FormatterHMS:
+            # 360 degrees as plot range -> 24 hours as labelled range
+            expected_value = pytest.approx((value // 15) / factor)
+        else:
+            expected_value = pytest.approx(value / factor)
+        assert sign * dms2float(degree, minute, second) == expected_value, \
+            f'{tick!r} does not match expected tick value.'
+
+        prev_degree = degree
+        prev_minute = minute
+        prev_second = second

venv/lib/python3.13/site-packages/mpl_toolkits/axisartist/tests/test_axis_artist.py

@@ -0,0 +1,99 @@
+import matplotlib.pyplot as plt
+from matplotlib.testing.decorators import image_comparison
+
+from mpl_toolkits.axisartist import AxisArtistHelperRectlinear
+from mpl_toolkits.axisartist.axis_artist import (AxisArtist, AxisLabel,
+                                                 LabelBase, Ticks, TickLabels)
+
+
+@image_comparison(['axis_artist_ticks.png'], style='default')
+def test_ticks():
+    fig, ax = plt.subplots()
+
+    ax.xaxis.set_visible(False)
+    ax.yaxis.set_visible(False)
+
+    locs_angles = [((i / 10, 0.0), i * 30) for i in range(-1, 12)]
+
+    ticks_in = Ticks(ticksize=10, axis=ax.xaxis)
+    ticks_in.set_locs_angles(locs_angles)
+    ax.add_artist(ticks_in)
+
+    ticks_out = Ticks(ticksize=10, tick_out=True, color='C3', axis=ax.xaxis)
+    ticks_out.set_locs_angles(locs_angles)
+    ax.add_artist(ticks_out)
+
+
+@image_comparison(['axis_artist_labelbase.png'], style='default')
+def test_labelbase():
+    # Remove this line when this test image is regenerated.
+    plt.rcParams['text.kerning_factor'] = 6
+
+    fig, ax = plt.subplots()
+
+    ax.plot([0.5], [0.5], "o")
+
+    label = LabelBase(0.5, 0.5, "Test")
+    label._ref_angle = -90
+    label._offset_radius = 50
+    label.set_rotation(-90)
+    label.set(ha="center", va="top")
+    ax.add_artist(label)
+
+
+@image_comparison(['axis_artist_ticklabels.png'], style='default')
+def test_ticklabels():
+    # Remove this line when this test image is regenerated.
+    plt.rcParams['text.kerning_factor'] = 6
+
+    fig, ax = plt.subplots()
+
+    ax.xaxis.set_visible(False)
+    ax.yaxis.set_visible(False)
+
+    ax.plot([0.2, 0.4], [0.5, 0.5], "o")
+
+    ticks = Ticks(ticksize=10, axis=ax.xaxis)
+    ax.add_artist(ticks)
+    locs_angles_labels = [((0.2, 0.5), -90, "0.2"),
+                          ((0.4, 0.5), -120, "0.4")]
+    tick_locs_angles = [(xy, a + 180) for xy, a, l in locs_angles_labels]
+    ticks.set_locs_angles(tick_locs_angles)
+
+    ticklabels = TickLabels(axis_direction="left")
+    ticklabels._locs_angles_labels = locs_angles_labels
+    ticklabels.set_pad(10)
+    ax.add_artist(ticklabels)
+
+    ax.plot([0.5], [0.5], "s")
+    axislabel = AxisLabel(0.5, 0.5, "Test")
+    axislabel._offset_radius = 20
+    axislabel._ref_angle = 0
+    axislabel.set_axis_direction("bottom")
+    ax.add_artist(axislabel)
+
+    ax.set_xlim(0, 1)
+    ax.set_ylim(0, 1)
+
+
+@image_comparison(['axis_artist.png'], style='default')
+def test_axis_artist():
+    # Remove this line when this test image is regenerated.
+    plt.rcParams['text.kerning_factor'] = 6
+
+    fig, ax = plt.subplots()
+
+    ax.xaxis.set_visible(False)
+    ax.yaxis.set_visible(False)
+
+    for loc in ('left', 'right', 'bottom'):
+        helper = AxisArtistHelperRectlinear.Fixed(ax, loc=loc)
+        axisline = AxisArtist(ax, helper, offset=None, axis_direction=loc)
+        ax.add_artist(axisline)
+
+    # Settings for bottom AxisArtist.
+    axisline.set_label("TTT")
+    axisline.major_ticks.set_tick_out(False)
+    axisline.label.set_pad(5)
+
+    ax.set_ylabel("Test")

venv/lib/python3.13/site-packages/mpl_toolkits/axisartist/tests/test_axislines.py

@@ -0,0 +1,145 @@
+import numpy as np
+import matplotlib.pyplot as plt
+from matplotlib.testing.decorators import image_comparison
+from matplotlib.transforms import IdentityTransform
+
+from mpl_toolkits.axisartist.axislines import AxesZero, SubplotZero, Subplot
+from mpl_toolkits.axisartist import Axes, SubplotHost
+
+
+@image_comparison(['SubplotZero.png'], style='default')
+def test_SubplotZero():
+    # Remove this line when this test image is regenerated.
+    plt.rcParams['text.kerning_factor'] = 6
+
+    fig = plt.figure()
+
+    ax = SubplotZero(fig, 1, 1, 1)
+    fig.add_subplot(ax)
+
+    ax.axis["xzero"].set_visible(True)
+    ax.axis["xzero"].label.set_text("Axis Zero")
+
+    for n in ["top", "right"]:
+        ax.axis[n].set_visible(False)
+
+    xx = np.arange(0, 2 * np.pi, 0.01)
+    ax.plot(xx, np.sin(xx))
+    ax.set_ylabel("Test")
+
+
+@image_comparison(['Subplot.png'], style='default')
+def test_Subplot():
+    # Remove this line when this test image is regenerated.
+    plt.rcParams['text.kerning_factor'] = 6
+
+    fig = plt.figure()
+
+    ax = Subplot(fig, 1, 1, 1)
+    fig.add_subplot(ax)
+
+    xx = np.arange(0, 2 * np.pi, 0.01)
+    ax.plot(xx, np.sin(xx))
+    ax.set_ylabel("Test")
+
+    ax.axis["top"].major_ticks.set_tick_out(True)
+    ax.axis["bottom"].major_ticks.set_tick_out(True)
+
+    ax.axis["bottom"].set_label("Tk0")
+
+
+def test_Axes():
+    fig = plt.figure()
+    ax = Axes(fig, [0.15, 0.1, 0.65, 0.8])
+    fig.add_axes(ax)
+    ax.plot([1, 2, 3], [0, 1, 2])
+    ax.set_xscale('log')
+    fig.canvas.draw()
+
+
+@image_comparison(['ParasiteAxesAuxTrans_meshplot.png'],
+                  remove_text=True, style='default', tol=0.075)
+def test_ParasiteAxesAuxTrans():
+    data = np.ones((6, 6))
+    data[2, 2] = 2
+    data[0, :] = 0
+    data[-2, :] = 0
+    data[:, 0] = 0
+    data[:, -2] = 0
+    x = np.arange(6)
+    y = np.arange(6)
+    xx, yy = np.meshgrid(x, y)
+
+    funcnames = ['pcolor', 'pcolormesh', 'contourf']
+
+    fig = plt.figure()
+    for i, name in enumerate(funcnames):
+
+        ax1 = SubplotHost(fig, 1, 3, i+1)
+        fig.add_subplot(ax1)
+
+        ax2 = ax1.get_aux_axes(IdentityTransform(), viewlim_mode=None)
+        if name.startswith('pcolor'):
+            getattr(ax2, name)(xx, yy, data[:-1, :-1])
+        else:
+            getattr(ax2, name)(xx, yy, data)
+        ax1.set_xlim((0, 5))
+        ax1.set_ylim((0, 5))
+
+    ax2.contour(xx, yy, data, colors='k')
+
+
+@image_comparison(['axisline_style.png'], remove_text=True, style='mpl20')
+def test_axisline_style():
+    fig = plt.figure(figsize=(2, 2))
+    ax = fig.add_subplot(axes_class=AxesZero)
+    ax.axis["xzero"].set_axisline_style("-|>")
+    ax.axis["xzero"].set_visible(True)
+    ax.axis["yzero"].set_axisline_style("->")
+    ax.axis["yzero"].set_visible(True)
+
+    for direction in ("left", "right", "bottom", "top"):
+        ax.axis[direction].set_visible(False)
+
+
+@image_comparison(['axisline_style_size_color.png'], remove_text=True,
+                  style='mpl20')
+def test_axisline_style_size_color():
+    fig = plt.figure(figsize=(2, 2))
+    ax = fig.add_subplot(axes_class=AxesZero)
+    ax.axis["xzero"].set_axisline_style("-|>", size=2.0, facecolor='r')
+    ax.axis["xzero"].set_visible(True)
+    ax.axis["yzero"].set_axisline_style("->, size=1.5")
+    ax.axis["yzero"].set_visible(True)
+
+    for direction in ("left", "right", "bottom", "top"):
+        ax.axis[direction].set_visible(False)
+
+
+@image_comparison(['axisline_style_tight.png'], remove_text=True,
+                  style='mpl20')
+def test_axisline_style_tight():
+    fig = plt.figure(figsize=(2, 2), layout='tight')
+    ax = fig.add_subplot(axes_class=AxesZero)
+    ax.axis["xzero"].set_axisline_style("-|>", size=5, facecolor='g')
+    ax.axis["xzero"].set_visible(True)
+    ax.axis["yzero"].set_axisline_style("->, size=8")
+    ax.axis["yzero"].set_visible(True)
+
+    for direction in ("left", "right", "bottom", "top"):
+        ax.axis[direction].set_visible(False)
+
+
+@image_comparison(['subplotzero_ylabel.png'], style='mpl20')
+def test_subplotzero_ylabel():
+    fig = plt.figure()
+    ax = fig.add_subplot(111, axes_class=SubplotZero)
+
+    ax.set(xlim=(-3, 7), ylim=(-3, 7), xlabel="x", ylabel="y")
+
+    zero_axis = ax.axis["xzero", "yzero"]
+    zero_axis.set_visible(True)  # they are hidden by default
+
+    ax.axis["left", "right", "bottom", "top"].set_visible(False)
+
+    zero_axis.set_axisline_style("->")

venv/lib/python3.13/site-packages/mpl_toolkits/axisartist/tests/test_floating_axes.py

@@ -0,0 +1,115 @@
+import numpy as np
+
+import matplotlib.pyplot as plt
+import matplotlib.projections as mprojections
+import matplotlib.transforms as mtransforms
+from matplotlib.testing.decorators import image_comparison
+from mpl_toolkits.axisartist.axislines import Subplot
+from mpl_toolkits.axisartist.floating_axes import (
+    FloatingAxes, GridHelperCurveLinear)
+from mpl_toolkits.axisartist.grid_finder import FixedLocator
+from mpl_toolkits.axisartist import angle_helper
+
+
+def test_subplot():
+    fig = plt.figure(figsize=(5, 5))
+    ax = Subplot(fig, 111)
+    fig.add_subplot(ax)
+
+
+# Rather high tolerance to allow ongoing work with floating axes internals;
+# remove when image is regenerated.
+@image_comparison(['curvelinear3.png'], style='default', tol=5)
+def test_curvelinear3():
+    fig = plt.figure(figsize=(5, 5))
+
+    tr = (mtransforms.Affine2D().scale(np.pi / 180, 1) +
+          mprojections.PolarAxes.PolarTransform(apply_theta_transforms=False))
+    grid_helper = GridHelperCurveLinear(
+        tr,
+        extremes=(0, 360, 10, 3),
+        grid_locator1=angle_helper.LocatorDMS(15),
+        grid_locator2=FixedLocator([2, 4, 6, 8, 10]),
+        tick_formatter1=angle_helper.FormatterDMS(),
+        tick_formatter2=None)
+    ax1 = fig.add_subplot(axes_class=FloatingAxes, grid_helper=grid_helper)
+
+    r_scale = 10
+    tr2 = mtransforms.Affine2D().scale(1, 1 / r_scale) + tr
+    grid_helper2 = GridHelperCurveLinear(
+        tr2,
+        extremes=(0, 360, 10 * r_scale, 3 * r_scale),
+        grid_locator2=FixedLocator([30, 60, 90]))
+
+    ax1.axis["right"] = axis = grid_helper2.new_fixed_axis("right", axes=ax1)
+
+    ax1.axis["left"].label.set_text("Test 1")
+    ax1.axis["right"].label.set_text("Test 2")
+    ax1.axis["left", "right"].set_visible(False)
+
+    axis = grid_helper.new_floating_axis(1, 7, axes=ax1,
+                                         axis_direction="bottom")
+    ax1.axis["z"] = axis
+    axis.toggle(all=True, label=True)
+    axis.label.set_text("z = ?")
+    axis.label.set_visible(True)
+    axis.line.set_color("0.5")
+
+    ax2 = ax1.get_aux_axes(tr)
+
+    xx, yy = [67, 90, 75, 30], [2, 5, 8, 4]
+    ax2.scatter(xx, yy)
+    l, = ax2.plot(xx, yy, "k-")
+    l.set_clip_path(ax1.patch)
+
+
+# Rather high tolerance to allow ongoing work with floating axes internals;
+# remove when image is regenerated.
+@image_comparison(['curvelinear4.png'], style='default', tol=0.9)
+def test_curvelinear4():
+    # Remove this line when this test image is regenerated.
+    plt.rcParams['text.kerning_factor'] = 6
+
+    fig = plt.figure(figsize=(5, 5))
+
+    tr = (mtransforms.Affine2D().scale(np.pi / 180, 1) +
+          mprojections.PolarAxes.PolarTransform(apply_theta_transforms=False))
+    grid_helper = GridHelperCurveLinear(
+        tr,
+        extremes=(120, 30, 10, 0),
+        grid_locator1=angle_helper.LocatorDMS(5),
+        grid_locator2=FixedLocator([2, 4, 6, 8, 10]),
+        tick_formatter1=angle_helper.FormatterDMS(),
+        tick_formatter2=None)
+    ax1 = fig.add_subplot(axes_class=FloatingAxes, grid_helper=grid_helper)
+    ax1.clear()  # Check that clear() also restores the correct limits on ax1.
+
+    ax1.axis["left"].label.set_text("Test 1")
+    ax1.axis["right"].label.set_text("Test 2")
+    ax1.axis["top"].set_visible(False)
+
+    axis = grid_helper.new_floating_axis(1, 70, axes=ax1,
+                                         axis_direction="bottom")
+    ax1.axis["z"] = axis
+    axis.toggle(all=True, label=True)
+    axis.label.set_axis_direction("top")
+    axis.label.set_text("z = ?")
+    axis.label.set_visible(True)
+    axis.line.set_color("0.5")
+
+    ax2 = ax1.get_aux_axes(tr)
+
+    xx, yy = [67, 90, 75, 30], [2, 5, 8, 4]
+    ax2.scatter(xx, yy)
+    l, = ax2.plot(xx, yy, "k-")
+    l.set_clip_path(ax1.patch)
+
+
+def test_axis_direction():
+    # Check that axis direction is propagated on a floating axis
+    fig = plt.figure()
+    ax = Subplot(fig, 111)
+    fig.add_subplot(ax)
+    ax.axis['y'] = ax.new_floating_axis(nth_coord=1, value=0,
+                                        axis_direction='left')
+    assert ax.axis['y']._axis_direction == 'left'

venv/lib/python3.13/site-packages/mpl_toolkits/axisartist/tests/test_grid_finder.py

@@ -0,0 +1,34 @@
+import numpy as np
+import pytest
+
+from matplotlib.transforms import Bbox
+from mpl_toolkits.axisartist.grid_finder import (
+    _find_line_box_crossings, FormatterPrettyPrint, MaxNLocator)
+
+
+def test_find_line_box_crossings():
+    x = np.array([-3, -2, -1, 0., 1, 2, 3, 2, 1, 0, -1, -2, -3, 5])
+    y = np.arange(len(x))
+    bbox = Bbox.from_extents(-2, 3, 2, 12.5)
+    left, right, bottom, top = _find_line_box_crossings(
+        np.column_stack([x, y]), bbox)
+    ((lx0, ly0), la0), ((lx1, ly1), la1), = left
+    ((rx0, ry0), ra0), ((rx1, ry1), ra1), = right
+    ((bx0, by0), ba0), = bottom
+    ((tx0, ty0), ta0), = top
+    assert (lx0, ly0, la0) == (-2, 11, 135)
+    assert (lx1, ly1, la1) == pytest.approx((-2., 12.125, 7.125016))
+    assert (rx0, ry0, ra0) == (2, 5, 45)
+    assert (rx1, ry1, ra1) == (2, 7, 135)
+    assert (bx0, by0, ba0) == (0, 3, 45)
+    assert (tx0, ty0, ta0) == pytest.approx((1., 12.5, 7.125016))
+
+
+def test_pretty_print_format():
+    locator = MaxNLocator()
+    locs, nloc, factor = locator(0, 100)
+
+    fmt = FormatterPrettyPrint()
+
+    assert fmt("left", None, locs) == \
+        [r'$\mathdefault{%d}$' % (l, ) for l in locs]

venv/lib/python3.13/site-packages/mpl_toolkits/axisartist/tests/test_grid_helper_curvelinear.py

@@ -0,0 +1,207 @@
+import numpy as np
+
+import matplotlib.pyplot as plt
+from matplotlib.path import Path
+from matplotlib.projections import PolarAxes
+from matplotlib.ticker import FuncFormatter
+from matplotlib.transforms import Affine2D, Transform
+from matplotlib.testing.decorators import image_comparison
+
+from mpl_toolkits.axisartist import SubplotHost
+from mpl_toolkits.axes_grid1.parasite_axes import host_axes_class_factory
+from mpl_toolkits.axisartist import angle_helper
+from mpl_toolkits.axisartist.axislines import Axes
+from mpl_toolkits.axisartist.grid_helper_curvelinear import \
+    GridHelperCurveLinear
+
+
+@image_comparison(['custom_transform.png'], style='default', tol=0.2)
+def test_custom_transform():
+    class MyTransform(Transform):
+        input_dims = output_dims = 2
+
+        def __init__(self, resolution):
+            """
+            Resolution is the number of steps to interpolate between each input
+            line segment to approximate its path in transformed space.
+            """
+            Transform.__init__(self)
+            self._resolution = resolution
+
+        def transform(self, ll):
+            x, y = ll.T
+            return np.column_stack([x, y - x])
+
+        transform_non_affine = transform
+
+        def transform_path(self, path):
+            ipath = path.interpolated(self._resolution)
+            return Path(self.transform(ipath.vertices), ipath.codes)
+
+        transform_path_non_affine = transform_path
+
+        def inverted(self):
+            return MyTransformInv(self._resolution)
+
+    class MyTransformInv(Transform):
+        input_dims = output_dims = 2
+
+        def __init__(self, resolution):
+            Transform.__init__(self)
+            self._resolution = resolution
+
+        def transform(self, ll):
+            x, y = ll.T
+            return np.column_stack([x, y + x])
+
+        def inverted(self):
+            return MyTransform(self._resolution)
+
+    fig = plt.figure()
+
+    SubplotHost = host_axes_class_factory(Axes)
+
+    tr = MyTransform(1)
+    grid_helper = GridHelperCurveLinear(tr)
+    ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)
+    fig.add_subplot(ax1)
+
+    ax2 = ax1.get_aux_axes(tr, viewlim_mode="equal")
+    ax2.plot([3, 6], [5.0, 10.])
+
+    ax1.set_aspect(1.)
+    ax1.set_xlim(0, 10)
+    ax1.set_ylim(0, 10)
+
+    ax1.grid(True)
+
+
+@image_comparison(['polar_box.png'], style='default', tol=0.04)
+def test_polar_box():
+    fig = plt.figure(figsize=(5, 5))
+
+    # PolarAxes.PolarTransform takes radian. However, we want our coordinate
+    # system in degree
+    tr = (Affine2D().scale(np.pi / 180., 1.) +
+          PolarAxes.PolarTransform(apply_theta_transforms=False))
+
+    # polar projection, which involves cycle, and also has limits in
+    # its coordinates, needs a special method to find the extremes
+    # (min, max of the coordinate within the view).
+    extreme_finder = angle_helper.ExtremeFinderCycle(20, 20,
+                                                     lon_cycle=360,
+                                                     lat_cycle=None,
+                                                     lon_minmax=None,
+                                                     lat_minmax=(0, np.inf))
+
+    grid_helper = GridHelperCurveLinear(
+        tr,
+        extreme_finder=extreme_finder,
+        grid_locator1=angle_helper.LocatorDMS(12),
+        tick_formatter1=angle_helper.FormatterDMS(),
+        tick_formatter2=FuncFormatter(lambda x, p: "eight" if x == 8 else f"{int(x)}"),
+    )
+
+    ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)
+
+    ax1.axis["right"].major_ticklabels.set_visible(True)
+    ax1.axis["top"].major_ticklabels.set_visible(True)
+
+    # let right axis shows ticklabels for 1st coordinate (angle)
+    ax1.axis["right"].get_helper().nth_coord_ticks = 0
+    # let bottom axis shows ticklabels for 2nd coordinate (radius)
+    ax1.axis["bottom"].get_helper().nth_coord_ticks = 1
+
+    fig.add_subplot(ax1)
+
+    ax1.axis["lat"] = axis = grid_helper.new_floating_axis(0, 45, axes=ax1)
+    axis.label.set_text("Test")
+    axis.label.set_visible(True)
+    axis.get_helper().set_extremes(2, 12)
+
+    ax1.axis["lon"] = axis = grid_helper.new_floating_axis(1, 6, axes=ax1)
+    axis.label.set_text("Test 2")
+    axis.get_helper().set_extremes(-180, 90)
+
+    # A parasite axes with given transform
+    ax2 = ax1.get_aux_axes(tr, viewlim_mode="equal")
+    assert ax2.transData == tr + ax1.transData
+    # Anything you draw in ax2 will match the ticks and grids of ax1.
+    ax2.plot(np.linspace(0, 30, 50), np.linspace(10, 10, 50))
+
+    ax1.set_aspect(1.)
+    ax1.set_xlim(-5, 12)
+    ax1.set_ylim(-5, 10)
+
+    ax1.grid(True)
+
+
+# Remove tol & kerning_factor when this test image is regenerated.
+@image_comparison(['axis_direction.png'], style='default', tol=0.13)
+def test_axis_direction():
+    plt.rcParams['text.kerning_factor'] = 6
+
+    fig = plt.figure(figsize=(5, 5))
+
+    # PolarAxes.PolarTransform takes radian. However, we want our coordinate
+    # system in degree
+    tr = (Affine2D().scale(np.pi / 180., 1.) +
+          PolarAxes.PolarTransform(apply_theta_transforms=False))
+
+    # polar projection, which involves cycle, and also has limits in
+    # its coordinates, needs a special method to find the extremes
+    # (min, max of the coordinate within the view).
+
+    # 20, 20 : number of sampling points along x, y direction
+    extreme_finder = angle_helper.ExtremeFinderCycle(20, 20,
+                                                     lon_cycle=360,
+                                                     lat_cycle=None,
+                                                     lon_minmax=None,
+                                                     lat_minmax=(0, np.inf),
+                                                     )
+
+    grid_locator1 = angle_helper.LocatorDMS(12)
+    tick_formatter1 = angle_helper.FormatterDMS()
+
+    grid_helper = GridHelperCurveLinear(tr,
+                                        extreme_finder=extreme_finder,
+                                        grid_locator1=grid_locator1,
+                                        tick_formatter1=tick_formatter1)
+
+    ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)
+
+    for axis in ax1.axis.values():
+        axis.set_visible(False)
+
+    fig.add_subplot(ax1)
+
+    ax1.axis["lat1"] = axis = grid_helper.new_floating_axis(
+        0, 130,
+        axes=ax1, axis_direction="left")
+    axis.label.set_text("Test")
+    axis.label.set_visible(True)
+    axis.get_helper().set_extremes(0.001, 10)
+
+    ax1.axis["lat2"] = axis = grid_helper.new_floating_axis(
+        0, 50,
+        axes=ax1, axis_direction="right")
+    axis.label.set_text("Test")
+    axis.label.set_visible(True)
+    axis.get_helper().set_extremes(0.001, 10)
+
+    ax1.axis["lon"] = axis = grid_helper.new_floating_axis(
+        1, 10,
+        axes=ax1, axis_direction="bottom")
+    axis.label.set_text("Test 2")
+    axis.get_helper().set_extremes(50, 130)
+    axis.major_ticklabels.set_axis_direction("top")
+    axis.label.set_axis_direction("top")
+
+    grid_helper.grid_finder.grid_locator1.set_params(nbins=5)
+    grid_helper.grid_finder.grid_locator2.set_params(nbins=5)
+
+    ax1.set_aspect(1.)
+    ax1.set_xlim(-8, 8)
+    ax1.set_ylim(-4, 12)
+
+    ax1.grid(True)

venv/lib/python3.13/site-packages/mpl_toolkits/mplot3d/__init__.py

@@ -0,0 +1,3 @@
+from .axes3d import Axes3D
+
+__all__ = ['Axes3D']

venv/lib/python3.13/site-packages/mpl_toolkits/mplot3d/axis3d.py

@@ -0,0 +1,750 @@
+# axis3d.py, original mplot3d version by John Porter
+# Created: 23 Sep 2005
+# Parts rewritten by Reinier Heeres <reinier@heeres.eu>
+
+import inspect
+
+import numpy as np
+
+import matplotlib as mpl
+from matplotlib import (
+    _api, artist, lines as mlines, axis as maxis, patches as mpatches,
+    transforms as mtransforms, colors as mcolors)
+from . import art3d, proj3d
+
+
+def _move_from_center(coord, centers, deltas, axmask=(True, True, True)):
+    """
+    For each coordinate where *axmask* is True, move *coord* away from
+    *centers* by *deltas*.
+    """
+    coord = np.asarray(coord)
+    return coord + axmask * np.copysign(1, coord - centers) * deltas
+
+
+def _tick_update_position(tick, tickxs, tickys, labelpos):
+    """Update tick line and label position and style."""
+
+    tick.label1.set_position(labelpos)
+    tick.label2.set_position(labelpos)
+    tick.tick1line.set_visible(True)
+    tick.tick2line.set_visible(False)
+    tick.tick1line.set_linestyle('-')
+    tick.tick1line.set_marker('')
+    tick.tick1line.set_data(tickxs, tickys)
+    tick.gridline.set_data([0], [0])
+
+
+class Axis(maxis.XAxis):
+    """An Axis class for the 3D plots."""
+    # These points from the unit cube make up the x, y and z-planes
+    _PLANES = (
+        (0, 3, 7, 4), (1, 2, 6, 5),  # yz planes
+        (0, 1, 5, 4), (3, 2, 6, 7),  # xz planes
+        (0, 1, 2, 3), (4, 5, 6, 7),  # xy planes
+    )
+
+    # Some properties for the axes
+    _AXINFO = {
+        'x': {'i': 0, 'tickdir': 1, 'juggled': (1, 0, 2)},
+        'y': {'i': 1, 'tickdir': 0, 'juggled': (0, 1, 2)},
+        'z': {'i': 2, 'tickdir': 0, 'juggled': (0, 2, 1)},
+    }
+
+    def _old_init(self, adir, v_intervalx, d_intervalx, axes, *args,
+                  rotate_label=None, **kwargs):
+        return locals()
+
+    def _new_init(self, axes, *, rotate_label=None, **kwargs):
+        return locals()
+
+    def __init__(self, *args, **kwargs):
+        params = _api.select_matching_signature(
+            [self._old_init, self._new_init], *args, **kwargs)
+        if "adir" in params:
+            _api.warn_deprecated(
+                "3.6", message=f"The signature of 3D Axis constructors has "
+                f"changed in %(since)s; the new signature is "
+                f"{inspect.signature(type(self).__init__)}", pending=True)
+            if params["adir"] != self.axis_name:
+                raise ValueError(f"Cannot instantiate {type(self).__name__} "
+                                 f"with adir={params['adir']!r}")
+        axes = params["axes"]
+        rotate_label = params["rotate_label"]
+        args = params.get("args", ())
+        kwargs = params["kwargs"]
+
+        name = self.axis_name
+
+        self._label_position = 'default'
+        self._tick_position = 'default'
+
+        # This is a temporary member variable.
+        # Do not depend on this existing in future releases!
+        self._axinfo = self._AXINFO[name].copy()
+        # Common parts
+        self._axinfo.update({
+            'label': {'va': 'center', 'ha': 'center',
+                      'rotation_mode': 'anchor'},
+            'color': mpl.rcParams[f'axes3d.{name}axis.panecolor'],
+            'tick': {
+                'inward_factor': 0.2,
+                'outward_factor': 0.1,
+            },
+        })
+
+        if mpl.rcParams['_internal.classic_mode']:
+            self._axinfo.update({
+                'axisline': {'linewidth': 0.75, 'color': (0, 0, 0, 1)},
+                'grid': {
+                    'color': (0.9, 0.9, 0.9, 1),
+                    'linewidth': 1.0,
+                    'linestyle': '-',
+                },
+            })
+            self._axinfo['tick'].update({
+                'linewidth': {
+                    True: mpl.rcParams['lines.linewidth'],  # major
+                    False: mpl.rcParams['lines.linewidth'],  # minor
+                }
+            })
+        else:
+            self._axinfo.update({
+                'axisline': {
+                    'linewidth': mpl.rcParams['axes.linewidth'],
+                    'color': mpl.rcParams['axes.edgecolor'],
+                },
+                'grid': {
+                    'color': mpl.rcParams['grid.color'],
+                    'linewidth': mpl.rcParams['grid.linewidth'],
+                    'linestyle': mpl.rcParams['grid.linestyle'],
+                },
+            })
+            self._axinfo['tick'].update({
+                'linewidth': {
+                    True: (  # major
+                        mpl.rcParams['xtick.major.width'] if name in 'xz'
+                        else mpl.rcParams['ytick.major.width']),
+                    False: (  # minor
+                        mpl.rcParams['xtick.minor.width'] if name in 'xz'
+                        else mpl.rcParams['ytick.minor.width']),
+                }
+            })
+
+        super().__init__(axes, *args, **kwargs)
+
+        # data and viewing intervals for this direction
+        if "d_intervalx" in params:
+            self.set_data_interval(*params["d_intervalx"])
+        if "v_intervalx" in params:
+            self.set_view_interval(*params["v_intervalx"])
+        self.set_rotate_label(rotate_label)
+        self._init3d()  # Inline after init3d deprecation elapses.
+
+    __init__.__signature__ = inspect.signature(_new_init)
+    adir = _api.deprecated("3.6", pending=True)(
+        property(lambda self: self.axis_name))
+
+    def _init3d(self):
+        self.line = mlines.Line2D(
+            xdata=(0, 0), ydata=(0, 0),
+            linewidth=self._axinfo['axisline']['linewidth'],
+            color=self._axinfo['axisline']['color'],
+            antialiased=True)
+
+        # Store dummy data in Polygon object
+        self.pane = mpatches.Polygon([[0, 0], [0, 1]], closed=False)
+        self.set_pane_color(self._axinfo['color'])
+
+        self.axes._set_artist_props(self.line)
+        self.axes._set_artist_props(self.pane)
+        self.gridlines = art3d.Line3DCollection([])
+        self.axes._set_artist_props(self.gridlines)
+        self.axes._set_artist_props(self.label)
+        self.axes._set_artist_props(self.offsetText)
+        # Need to be able to place the label at the correct location
+        self.label._transform = self.axes.transData
+        self.offsetText._transform = self.axes.transData
+
+    @_api.deprecated("3.6", pending=True)
+    def init3d(self):  # After deprecation elapses, inline _init3d to __init__.
+        self._init3d()
+
+    def get_major_ticks(self, numticks=None):
+        ticks = super().get_major_ticks(numticks)
+        for t in ticks:
+            for obj in [
+                    t.tick1line, t.tick2line, t.gridline, t.label1, t.label2]:
+                obj.set_transform(self.axes.transData)
+        return ticks
+
+    def get_minor_ticks(self, numticks=None):
+        ticks = super().get_minor_ticks(numticks)
+        for t in ticks:
+            for obj in [
+                    t.tick1line, t.tick2line, t.gridline, t.label1, t.label2]:
+                obj.set_transform(self.axes.transData)
+        return ticks
+
+    def set_ticks_position(self, position):
+        """
+        Set the ticks position.
+
+        Parameters
+        ----------
+        position : {'lower', 'upper', 'both', 'default', 'none'}
+            The position of the bolded axis lines, ticks, and tick labels.
+        """
+        _api.check_in_list(['lower', 'upper', 'both', 'default', 'none'],
+                           position=position)
+        self._tick_position = position
+
+    def get_ticks_position(self):
+        """
+        Get the ticks position.
+
+        Returns
+        -------
+        str : {'lower', 'upper', 'both', 'default', 'none'}
+            The position of the bolded axis lines, ticks, and tick labels.
+        """
+        return self._tick_position
+
+    def set_label_position(self, position):
+        """
+        Set the label position.
+
+        Parameters
+        ----------
+        position : {'lower', 'upper', 'both', 'default', 'none'}
+            The position of the axis label.
+        """
+        _api.check_in_list(['lower', 'upper', 'both', 'default', 'none'],
+                           position=position)
+        self._label_position = position
+
+    def get_label_position(self):
+        """
+        Get the label position.
+
+        Returns
+        -------
+        str : {'lower', 'upper', 'both', 'default', 'none'}
+            The position of the axis label.
+        """
+        return self._label_position
+
+    def set_pane_color(self, color, alpha=None):
+        """
+        Set pane color.
+
+        Parameters
+        ----------
+        color : :mpltype:`color`
+            Color for axis pane.
+        alpha : float, optional
+            Alpha value for axis pane. If None, base it on *color*.
+        """
+        color = mcolors.to_rgba(color, alpha)
+        self._axinfo['color'] = color
+        self.pane.set_edgecolor(color)
+        self.pane.set_facecolor(color)
+        self.pane.set_alpha(color[-1])
+        self.stale = True
+
+    def set_rotate_label(self, val):
+        """
+        Whether to rotate the axis label: True, False or None.
+        If set to None the label will be rotated if longer than 4 chars.
+        """
+        self._rotate_label = val
+        self.stale = True
+
+    def get_rotate_label(self, text):
+        if self._rotate_label is not None:
+            return self._rotate_label
+        else:
+            return len(text) > 4
+
+    def _get_coord_info(self):
+        mins, maxs = np.array([
+            self.axes.get_xbound(),
+            self.axes.get_ybound(),
+            self.axes.get_zbound(),
+        ]).T
+
+        # Project the bounds along the current position of the cube:
+        bounds = mins[0], maxs[0], mins[1], maxs[1], mins[2], maxs[2]
+        bounds_proj = self.axes._transformed_cube(bounds)
+
+        # Determine which one of the parallel planes are higher up:
+        means_z0 = np.zeros(3)
+        means_z1 = np.zeros(3)
+        for i in range(3):
+            means_z0[i] = np.mean(bounds_proj[self._PLANES[2 * i], 2])
+            means_z1[i] = np.mean(bounds_proj[self._PLANES[2 * i + 1], 2])
+        highs = means_z0 < means_z1
+
+        # Special handling for edge-on views
+        equals = np.abs(means_z0 - means_z1) <= np.finfo(float).eps
+        if np.sum(equals) == 2:
+            vertical = np.where(~equals)[0][0]
+            if vertical == 2:  # looking at XY plane
+                highs = np.array([True, True, highs[2]])
+            elif vertical == 1:  # looking at XZ plane
+                highs = np.array([True, highs[1], False])
+            elif vertical == 0:  # looking at YZ plane
+                highs = np.array([highs[0], False, False])
+
+        return mins, maxs, bounds_proj, highs
+
+    def _calc_centers_deltas(self, maxs, mins):
+        centers = 0.5 * (maxs + mins)
+        # In mpl3.8, the scale factor was 1/12. mpl3.9 changes this to
+        # 1/12 * 24/25 = 0.08 to compensate for the change in automargin
+        # behavior and keep appearance the same. The 24/25 factor is from the
+        # 1/48 padding added to each side of the axis in mpl3.8.
+        scale = 0.08
+        deltas = (maxs - mins) * scale
+        return centers, deltas
+
+    def _get_axis_line_edge_points(self, minmax, maxmin, position=None):
+        """Get the edge points for the black bolded axis line."""
+        # When changing vertical axis some of the axes has to be
+        # moved to the other plane so it looks the same as if the z-axis
+        # was the vertical axis.
+        mb = [minmax, maxmin]  # line from origin to nearest corner to camera
+        mb_rev = mb[::-1]
+        mm = [[mb, mb_rev, mb_rev], [mb_rev, mb_rev, mb], [mb, mb, mb]]
+        mm = mm[self.axes._vertical_axis][self._axinfo["i"]]
+
+        juggled = self._axinfo["juggled"]
+        edge_point_0 = mm[0].copy()  # origin point
+
+        if ((position == 'lower' and mm[1][juggled[-1]] < mm[0][juggled[-1]]) or
+                (position == 'upper' and mm[1][juggled[-1]] > mm[0][juggled[-1]])):
+            edge_point_0[juggled[-1]] = mm[1][juggled[-1]]
+        else:
+            edge_point_0[juggled[0]] = mm[1][juggled[0]]
+
+        edge_point_1 = edge_point_0.copy()
+        edge_point_1[juggled[1]] = mm[1][juggled[1]]
+
+        return edge_point_0, edge_point_1
+
+    def _get_all_axis_line_edge_points(self, minmax, maxmin, axis_position=None):
+        # Determine edge points for the axis lines
+        edgep1s = []
+        edgep2s = []
+        position = []
+        if axis_position in (None, 'default'):
+            edgep1, edgep2 = self._get_axis_line_edge_points(minmax, maxmin)
+            edgep1s = [edgep1]
+            edgep2s = [edgep2]
+            position = ['default']
+        else:
+            edgep1_l, edgep2_l = self._get_axis_line_edge_points(minmax, maxmin,
+                                                                 position='lower')
+            edgep1_u, edgep2_u = self._get_axis_line_edge_points(minmax, maxmin,
+                                                                 position='upper')
+            if axis_position in ('lower', 'both'):
+                edgep1s.append(edgep1_l)
+                edgep2s.append(edgep2_l)
+                position.append('lower')
+            if axis_position in ('upper', 'both'):
+                edgep1s.append(edgep1_u)
+                edgep2s.append(edgep2_u)
+                position.append('upper')
+        return edgep1s, edgep2s, position
+
+    def _get_tickdir(self, position):
+        """
+        Get the direction of the tick.
+
+        Parameters
+        ----------
+        position : str, optional : {'upper', 'lower', 'default'}
+            The position of the axis.
+
+        Returns
+        -------
+        tickdir : int
+            Index which indicates which coordinate the tick line will
+            align with.
+        """
+        _api.check_in_list(('upper', 'lower', 'default'), position=position)
+
+        # TODO: Move somewhere else where it's triggered less:
+        tickdirs_base = [v["tickdir"] for v in self._AXINFO.values()]  # default
+        elev_mod = np.mod(self.axes.elev + 180, 360) - 180
+        azim_mod = np.mod(self.axes.azim, 360)
+        if position == 'upper':
+            if elev_mod >= 0:
+                tickdirs_base = [2, 2, 0]
+            else:
+                tickdirs_base = [1, 0, 0]
+            if 0 <= azim_mod < 180:
+                tickdirs_base[2] = 1
+        elif position == 'lower':
+            if elev_mod >= 0:
+                tickdirs_base = [1, 0, 1]
+            else:
+                tickdirs_base = [2, 2, 1]
+            if 0 <= azim_mod < 180:
+                tickdirs_base[2] = 0
+        info_i = [v["i"] for v in self._AXINFO.values()]
+
+        i = self._axinfo["i"]
+        vert_ax = self.axes._vertical_axis
+        j = vert_ax - 2
+        # default: tickdir = [[1, 2, 1], [2, 2, 0], [1, 0, 0]][vert_ax][i]
+        tickdir = np.roll(info_i, -j)[np.roll(tickdirs_base, j)][i]
+        return tickdir
+
+    def active_pane(self):
+        mins, maxs, tc, highs = self._get_coord_info()
+        info = self._axinfo
+        index = info['i']
+        if not highs[index]:
+            loc = mins[index]
+            plane = self._PLANES[2 * index]
+        else:
+            loc = maxs[index]
+            plane = self._PLANES[2 * index + 1]
+        xys = np.array([tc[p] for p in plane])
+        return xys, loc
+
+    def draw_pane(self, renderer):
+        """
+        Draw pane.
+
+        Parameters
+        ----------
+        renderer : `~matplotlib.backend_bases.RendererBase` subclass
+        """
+        renderer.open_group('pane3d', gid=self.get_gid())
+        xys, loc = self.active_pane()
+        self.pane.xy = xys[:, :2]
+        self.pane.draw(renderer)
+        renderer.close_group('pane3d')
+
+    def _axmask(self):
+        axmask = [True, True, True]
+        axmask[self._axinfo["i"]] = False
+        return axmask
+
+    def _draw_ticks(self, renderer, edgep1, centers, deltas, highs,
+                    deltas_per_point, pos):
+        ticks = self._update_ticks()
+        info = self._axinfo
+        index = info["i"]
+        juggled = info["juggled"]
+
+        mins, maxs, tc, highs = self._get_coord_info()
+        centers, deltas = self._calc_centers_deltas(maxs, mins)
+
+        # Draw ticks:
+        tickdir = self._get_tickdir(pos)
+        tickdelta = deltas[tickdir] if highs[tickdir] else -deltas[tickdir]
+
+        tick_info = info['tick']
+        tick_out = tick_info['outward_factor'] * tickdelta
+        tick_in = tick_info['inward_factor'] * tickdelta
+        tick_lw = tick_info['linewidth']
+        edgep1_tickdir = edgep1[tickdir]
+        out_tickdir = edgep1_tickdir + tick_out
+        in_tickdir = edgep1_tickdir - tick_in
+
+        default_label_offset = 8.  # A rough estimate
+        points = deltas_per_point * deltas
+        for tick in ticks:
+            # Get tick line positions
+            pos = edgep1.copy()
+            pos[index] = tick.get_loc()
+            pos[tickdir] = out_tickdir
+            x1, y1, z1 = proj3d.proj_transform(*pos, self.axes.M)
+            pos[tickdir] = in_tickdir
+            x2, y2, z2 = proj3d.proj_transform(*pos, self.axes.M)
+
+            # Get position of label
+            labeldeltas = (tick.get_pad() + default_label_offset) * points
+
+            pos[tickdir] = edgep1_tickdir
+            pos = _move_from_center(pos, centers, labeldeltas, self._axmask())
+            lx, ly, lz = proj3d.proj_transform(*pos, self.axes.M)
+
+            _tick_update_position(tick, (x1, x2), (y1, y2), (lx, ly))
+            tick.tick1line.set_linewidth(tick_lw[tick._major])
+            tick.draw(renderer)
+
+    def _draw_offset_text(self, renderer, edgep1, edgep2, labeldeltas, centers,
+                          highs, pep, dx, dy):
+        # Get general axis information:
+        info = self._axinfo
+        index = info["i"]
+        juggled = info["juggled"]
+        tickdir = info["tickdir"]
+
+        # Which of the two edge points do we want to
+        # use for locating the offset text?
+        if juggled[2] == 2:
+            outeredgep = edgep1
+            outerindex = 0
+        else:
+            outeredgep = edgep2
+            outerindex = 1
+
+        pos = _move_from_center(outeredgep, centers, labeldeltas,
+                                self._axmask())
+        olx, oly, olz = proj3d.proj_transform(*pos, self.axes.M)
+        self.offsetText.set_text(self.major.formatter.get_offset())
+        self.offsetText.set_position((olx, oly))
+        angle = art3d._norm_text_angle(np.rad2deg(np.arctan2(dy, dx)))
+        self.offsetText.set_rotation(angle)
+        # Must set rotation mode to "anchor" so that
+        # the alignment point is used as the "fulcrum" for rotation.
+        self.offsetText.set_rotation_mode('anchor')
+
+        # ----------------------------------------------------------------------
+        # Note: the following statement for determining the proper alignment of
+        # the offset text. This was determined entirely by trial-and-error
+        # and should not be in any way considered as "the way".  There are
+        # still some edge cases where alignment is not quite right, but this
+        # seems to be more of a geometry issue (in other words, I might be
+        # using the wrong reference points).
+        #
+        # (TT, FF, TF, FT) are the shorthand for the tuple of
+        #   (centpt[tickdir] <= pep[tickdir, outerindex],
+        #    centpt[index] <= pep[index, outerindex])
+        #
+        # Three-letters (e.g., TFT, FTT) are short-hand for the array of bools
+        # from the variable 'highs'.
+        # ---------------------------------------------------------------------
+        centpt = proj3d.proj_transform(*centers, self.axes.M)
+        if centpt[tickdir] > pep[tickdir, outerindex]:
+            # if FT and if highs has an even number of Trues
+            if (centpt[index] <= pep[index, outerindex]
+                    and np.count_nonzero(highs) % 2 == 0):
+                # Usually, this means align right, except for the FTT case,
+                # in which offset for axis 1 and 2 are aligned left.
+                if highs.tolist() == [False, True, True] and index in (1, 2):
+                    align = 'left'
+                else:
+                    align = 'right'
+            else:
+                # The FF case
+                align = 'left'
+        else:
+            # if TF and if highs has an even number of Trues
+            if (centpt[index] > pep[index, outerindex]
+                    and np.count_nonzero(highs) % 2 == 0):
+                # Usually mean align left, except if it is axis 2
+                align = 'right' if index == 2 else 'left'
+            else:
+                # The TT case
+                align = 'right'
+
+        self.offsetText.set_va('center')
+        self.offsetText.set_ha(align)
+        self.offsetText.draw(renderer)
+
+    def _draw_labels(self, renderer, edgep1, edgep2, labeldeltas, centers, dx, dy):
+        label = self._axinfo["label"]
+
+        # Draw labels
+        lxyz = 0.5 * (edgep1 + edgep2)
+        lxyz = _move_from_center(lxyz, centers, labeldeltas, self._axmask())
+        tlx, tly, tlz = proj3d.proj_transform(*lxyz, self.axes.M)
+        self.label.set_position((tlx, tly))
+        if self.get_rotate_label(self.label.get_text()):
+            angle = art3d._norm_text_angle(np.rad2deg(np.arctan2(dy, dx)))
+            self.label.set_rotation(angle)
+        self.label.set_va(label['va'])
+        self.label.set_ha(label['ha'])
+        self.label.set_rotation_mode(label['rotation_mode'])
+        self.label.draw(renderer)
+
+    @artist.allow_rasterization
+    def draw(self, renderer):
+        self.label._transform = self.axes.transData
+        self.offsetText._transform = self.axes.transData
+        renderer.open_group("axis3d", gid=self.get_gid())
+
+        # Get general axis information:
+        mins, maxs, tc, highs = self._get_coord_info()
+        centers, deltas = self._calc_centers_deltas(maxs, mins)
+
+        # Calculate offset distances
+        # A rough estimate; points are ambiguous since 3D plots rotate
+        reltoinches = self.get_figure(root=False).dpi_scale_trans.inverted()
+        ax_inches = reltoinches.transform(self.axes.bbox.size)
+        ax_points_estimate = sum(72. * ax_inches)
+        deltas_per_point = 48 / ax_points_estimate
+        default_offset = 21.
+        labeldeltas = (self.labelpad + default_offset) * deltas_per_point * deltas
+
+        # Determine edge points for the axis lines
+        minmax = np.where(highs, maxs, mins)  # "origin" point
+        maxmin = np.where(~highs, maxs, mins)  # "opposite" corner near camera
+
+        for edgep1, edgep2, pos in zip(*self._get_all_axis_line_edge_points(
+                                           minmax, maxmin, self._tick_position)):
+            # Project the edge points along the current position
+            pep = proj3d._proj_trans_points([edgep1, edgep2], self.axes.M)
+            pep = np.asarray(pep)
+
+            # The transAxes transform is used because the Text object
+            # rotates the text relative to the display coordinate system.
+            # Therefore, if we want the labels to remain parallel to the
+            # axis regardless of the aspect ratio, we need to convert the
+            # edge points of the plane to display coordinates and calculate
+            # an angle from that.
+            # TODO: Maybe Text objects should handle this themselves?
+            dx, dy = (self.axes.transAxes.transform([pep[0:2, 1]]) -
+                      self.axes.transAxes.transform([pep[0:2, 0]]))[0]
+
+            # Draw the lines
+            self.line.set_data(pep[0], pep[1])
+            self.line.draw(renderer)
+
+            # Draw ticks
+            self._draw_ticks(renderer, edgep1, centers, deltas, highs,
+                             deltas_per_point, pos)
+
+            # Draw Offset text
+            self._draw_offset_text(renderer, edgep1, edgep2, labeldeltas,
+                                   centers, highs, pep, dx, dy)
+
+        for edgep1, edgep2, pos in zip(*self._get_all_axis_line_edge_points(
+                                           minmax, maxmin, self._label_position)):
+            # See comments above
+            pep = proj3d._proj_trans_points([edgep1, edgep2], self.axes.M)
+            pep = np.asarray(pep)
+            dx, dy = (self.axes.transAxes.transform([pep[0:2, 1]]) -
+                      self.axes.transAxes.transform([pep[0:2, 0]]))[0]
+
+            # Draw labels
+            self._draw_labels(renderer, edgep1, edgep2, labeldeltas, centers, dx, dy)
+
+        renderer.close_group('axis3d')
+        self.stale = False
+
+    @artist.allow_rasterization
+    def draw_grid(self, renderer):
+        if not self.axes._draw_grid:
+            return
+
+        renderer.open_group("grid3d", gid=self.get_gid())
+
+        ticks = self._update_ticks()
+        if len(ticks):
+            # Get general axis information:
+            info = self._axinfo
+            index = info["i"]
+
+            mins, maxs, tc, highs = self._get_coord_info()
+
+            minmax = np.where(highs, maxs, mins)
+            maxmin = np.where(~highs, maxs, mins)
+
+            # Grid points where the planes meet
+            xyz0 = np.tile(minmax, (len(ticks), 1))
+            xyz0[:, index] = [tick.get_loc() for tick in ticks]
+
+            # Grid lines go from the end of one plane through the plane
+            # intersection (at xyz0) to the end of the other plane.  The first
+            # point (0) differs along dimension index-2 and the last (2) along
+            # dimension index-1.
+            lines = np.stack([xyz0, xyz0, xyz0], axis=1)
+            lines[:, 0, index - 2] = maxmin[index - 2]
+            lines[:, 2, index - 1] = maxmin[index - 1]
+            self.gridlines.set_segments(lines)
+            gridinfo = info['grid']
+            self.gridlines.set_color(gridinfo['color'])
+            self.gridlines.set_linewidth(gridinfo['linewidth'])
+            self.gridlines.set_linestyle(gridinfo['linestyle'])
+            self.gridlines.do_3d_projection()
+            self.gridlines.draw(renderer)
+
+        renderer.close_group('grid3d')
+
+    # TODO: Get this to work (more) properly when mplot3d supports the
+    #       transforms framework.
+    def get_tightbbox(self, renderer=None, *, for_layout_only=False):
+        # docstring inherited
+        if not self.get_visible():
+            return
+        # We have to directly access the internal data structures
+        # (and hope they are up to date) because at draw time we
+        # shift the ticks and their labels around in (x, y) space
+        # based on the projection, the current view port, and their
+        # position in 3D space. If we extend the transforms framework
+        # into 3D we would not need to do this different book keeping
+        # than we do in the normal axis
+        major_locs = self.get_majorticklocs()
+        minor_locs = self.get_minorticklocs()
+
+        ticks = [*self.get_minor_ticks(len(minor_locs)),
+                 *self.get_major_ticks(len(major_locs))]
+        view_low, view_high = self.get_view_interval()
+        if view_low > view_high:
+            view_low, view_high = view_high, view_low
+        interval_t = self.get_transform().transform([view_low, view_high])
+
+        ticks_to_draw = []
+        for tick in ticks:
+            try:
+                loc_t = self.get_transform().transform(tick.get_loc())
+            except AssertionError:
+                # Transform.transform doesn't allow masked values but
+                # some scales might make them, so we need this try/except.
+                pass
+            else:
+                if mtransforms._interval_contains_close(interval_t, loc_t):
+                    ticks_to_draw.append(tick)
+
+        ticks = ticks_to_draw
+
+        bb_1, bb_2 = self._get_ticklabel_bboxes(ticks, renderer)
+        other = []
+
+        if self.line.get_visible():
+            other.append(self.line.get_window_extent(renderer))
+        if (self.label.get_visible() and not for_layout_only and
+                self.label.get_text()):
+            other.append(self.label.get_window_extent(renderer))
+
+        return mtransforms.Bbox.union([*bb_1, *bb_2, *other])
+
+    d_interval = _api.deprecated(
+        "3.6", alternative="get_data_interval", pending=True)(
+            property(lambda self: self.get_data_interval(),
+                     lambda self, minmax: self.set_data_interval(*minmax)))
+    v_interval = _api.deprecated(
+        "3.6", alternative="get_view_interval", pending=True)(
+            property(lambda self: self.get_view_interval(),
+                     lambda self, minmax: self.set_view_interval(*minmax)))
+
+
+class XAxis(Axis):
+    axis_name = "x"
+    get_view_interval, set_view_interval = maxis._make_getset_interval(
+        "view", "xy_viewLim", "intervalx")
+    get_data_interval, set_data_interval = maxis._make_getset_interval(
+        "data", "xy_dataLim", "intervalx")
+
+
+class YAxis(Axis):
+    axis_name = "y"
+    get_view_interval, set_view_interval = maxis._make_getset_interval(
+        "view", "xy_viewLim", "intervaly")
+    get_data_interval, set_data_interval = maxis._make_getset_interval(
+        "data", "xy_dataLim", "intervaly")
+
+
+class ZAxis(Axis):
+    axis_name = "z"
+    get_view_interval, set_view_interval = maxis._make_getset_interval(
+        "view", "zz_viewLim", "intervalx")
+    get_data_interval, set_data_interval = maxis._make_getset_interval(
+        "data", "zz_dataLim", "intervalx")

venv/lib/python3.13/site-packages/mpl_toolkits/mplot3d/proj3d.py

@@ -0,0 +1,219 @@
+"""
+Various transforms used for by the 3D code
+"""
+
+import numpy as np
+
+from matplotlib import _api
+
+
+def world_transformation(xmin, xmax,
+                         ymin, ymax,
+                         zmin, zmax, pb_aspect=None):
+    """
+    Produce a matrix that scales homogeneous coords in the specified ranges
+    to [0, 1], or [0, pb_aspect[i]] if the plotbox aspect ratio is specified.
+    """
+    dx = xmax - xmin
+    dy = ymax - ymin
+    dz = zmax - zmin
+    if pb_aspect is not None:
+        ax, ay, az = pb_aspect
+        dx /= ax
+        dy /= ay
+        dz /= az
+
+    return np.array([[1/dx,    0,    0, -xmin/dx],
+                     [   0, 1/dy,    0, -ymin/dy],
+                     [   0,    0, 1/dz, -zmin/dz],
+                     [   0,    0,    0,        1]])
+
+
+def _rotation_about_vector(v, angle):
+    """
+    Produce a rotation matrix for an angle in radians about a vector.
+    """
+    vx, vy, vz = v / np.linalg.norm(v)
+    s = np.sin(angle)
+    c = np.cos(angle)
+    t = 2*np.sin(angle/2)**2  # more numerically stable than t = 1-c
+
+    R = np.array([
+        [t*vx*vx + c,    t*vx*vy - vz*s, t*vx*vz + vy*s],
+        [t*vy*vx + vz*s, t*vy*vy + c,    t*vy*vz - vx*s],
+        [t*vz*vx - vy*s, t*vz*vy + vx*s, t*vz*vz + c]])
+
+    return R
+
+
+def _view_axes(E, R, V, roll):
+    """
+    Get the unit viewing axes in data coordinates.
+
+    Parameters
+    ----------
+    E : 3-element numpy array
+        The coordinates of the eye/camera.
+    R : 3-element numpy array
+        The coordinates of the center of the view box.
+    V : 3-element numpy array
+        Unit vector in the direction of the vertical axis.
+    roll : float
+        The roll angle in radians.
+
+    Returns
+    -------
+    u : 3-element numpy array
+        Unit vector pointing towards the right of the screen.
+    v : 3-element numpy array
+        Unit vector pointing towards the top of the screen.
+    w : 3-element numpy array
+        Unit vector pointing out of the screen.
+    """
+    w = (E - R)
+    w = w/np.linalg.norm(w)
+    u = np.cross(V, w)
+    u = u/np.linalg.norm(u)
+    v = np.cross(w, u)  # Will be a unit vector
+
+    # Save some computation for the default roll=0
+    if roll != 0:
+        # A positive rotation of the camera is a negative rotation of the world
+        Rroll = _rotation_about_vector(w, -roll)
+        u = np.dot(Rroll, u)
+        v = np.dot(Rroll, v)
+    return u, v, w
+
+
+def _view_transformation_uvw(u, v, w, E):
+    """
+    Return the view transformation matrix.
+
+    Parameters
+    ----------
+    u : 3-element numpy array
+        Unit vector pointing towards the right of the screen.
+    v : 3-element numpy array
+        Unit vector pointing towards the top of the screen.
+    w : 3-element numpy array
+        Unit vector pointing out of the screen.
+    E : 3-element numpy array
+        The coordinates of the eye/camera.
+    """
+    Mr = np.eye(4)
+    Mt = np.eye(4)
+    Mr[:3, :3] = [u, v, w]
+    Mt[:3, -1] = -E
+    M = np.dot(Mr, Mt)
+    return M
+
+
+def _persp_transformation(zfront, zback, focal_length):
+    e = focal_length
+    a = 1  # aspect ratio
+    b = (zfront+zback)/(zfront-zback)
+    c = -2*(zfront*zback)/(zfront-zback)
+    proj_matrix = np.array([[e,   0,  0, 0],
+                            [0, e/a,  0, 0],
+                            [0,   0,  b, c],
+                            [0,   0, -1, 0]])
+    return proj_matrix
+
+
+def _ortho_transformation(zfront, zback):
+    # note: w component in the resulting vector will be (zback-zfront), not 1
+    a = -(zfront + zback)
+    b = -(zfront - zback)
+    proj_matrix = np.array([[2, 0,  0, 0],
+                            [0, 2,  0, 0],
+                            [0, 0, -2, 0],
+                            [0, 0,  a, b]])
+    return proj_matrix
+
+
+def _proj_transform_vec(vec, M):
+    vecw = np.dot(M, vec.data)
+    w = vecw[3]
+    txs, tys, tzs = vecw[0]/w, vecw[1]/w, vecw[2]/w
+    if np.ma.isMA(vec[0]):  # we check each to protect for scalars
+        txs = np.ma.array(txs, mask=vec[0].mask)
+    if np.ma.isMA(vec[1]):
+        tys = np.ma.array(tys, mask=vec[1].mask)
+    if np.ma.isMA(vec[2]):
+        tzs = np.ma.array(tzs, mask=vec[2].mask)
+    return txs, tys, tzs
+
+
+def _proj_transform_vec_clip(vec, M, focal_length):
+    vecw = np.dot(M, vec.data)
+    w = vecw[3]
+    txs, tys, tzs = vecw[0] / w, vecw[1] / w, vecw[2] / w
+    if np.isinf(focal_length):  # don't clip orthographic projection
+        tis = np.ones(txs.shape, dtype=bool)
+    else:
+        tis = (-1 <= txs) & (txs <= 1) & (-1 <= tys) & (tys <= 1) & (tzs <= 0)
+    if np.ma.isMA(vec[0]):
+        tis = tis & ~vec[0].mask
+    if np.ma.isMA(vec[1]):
+        tis = tis & ~vec[1].mask
+    if np.ma.isMA(vec[2]):
+        tis = tis & ~vec[2].mask
+
+    txs = np.ma.masked_array(txs, ~tis)
+    tys = np.ma.masked_array(tys, ~tis)
+    tzs = np.ma.masked_array(tzs, ~tis)
+    return txs, tys, tzs, tis
+
+
+def inv_transform(xs, ys, zs, invM):
+    """
+    Transform the points by the inverse of the projection matrix, *invM*.
+    """
+    vec = _vec_pad_ones(xs, ys, zs)
+    vecr = np.dot(invM, vec)
+    if vecr.shape == (4,):
+        vecr = vecr.reshape((4, 1))
+    for i in range(vecr.shape[1]):
+        if vecr[3][i] != 0:
+            vecr[:, i] = vecr[:, i] / vecr[3][i]
+    return vecr[0], vecr[1], vecr[2]
+
+
+def _vec_pad_ones(xs, ys, zs):
+    if np.ma.isMA(xs) or np.ma.isMA(ys) or np.ma.isMA(zs):
+        return np.ma.array([xs, ys, zs, np.ones_like(xs)])
+    else:
+        return np.array([xs, ys, zs, np.ones_like(xs)])
+
+
+def proj_transform(xs, ys, zs, M):
+    """
+    Transform the points by the projection matrix *M*.
+    """
+    vec = _vec_pad_ones(xs, ys, zs)
+    return _proj_transform_vec(vec, M)
+
+
+@_api.deprecated("3.10")
+def proj_transform_clip(xs, ys, zs, M):
+    return _proj_transform_clip(xs, ys, zs, M, focal_length=np.inf)
+
+
+def _proj_transform_clip(xs, ys, zs, M, focal_length):
+    """
+    Transform the points by the projection matrix
+    and return the clipping result
+    returns txs, tys, tzs, tis
+    """
+    vec = _vec_pad_ones(xs, ys, zs)
+    return _proj_transform_vec_clip(vec, M, focal_length)
+
+
+def _proj_points(points, M):
+    return np.column_stack(_proj_trans_points(points, M))
+
+
+def _proj_trans_points(points, M):
+    points = np.asanyarray(points)
+    xs, ys, zs = points[:, 0], points[:, 1], points[:, 2]
+    return proj_transform(xs, ys, zs, M)

venv/lib/python3.13/site-packages/mpl_toolkits/mplot3d/tests/__init__.py

@@ -0,0 +1,10 @@
+from pathlib import Path
+
+
+# Check that the test directories exist
+if not (Path(__file__).parent / "baseline_images").exists():
+    raise OSError(
+        'The baseline image directory does not exist. '
+        'This is most likely because the test data is not installed. '
+        'You may need to install matplotlib from source to get the '
+        'test data.')

venv/lib/python3.13/site-packages/mpl_toolkits/mplot3d/tests/conftest.py

@@ -0,0 +1,2 @@
+from matplotlib.testing.conftest import (mpl_test_settings,  # noqa
+                                         pytest_configure, pytest_unconfigure)

venv/lib/python3.13/site-packages/mpl_toolkits/mplot3d/tests/test_art3d.py

@@ -0,0 +1,102 @@
+import numpy as np
+
+import matplotlib.pyplot as plt
+
+from matplotlib.backend_bases import MouseEvent
+from mpl_toolkits.mplot3d.art3d import (
+    Line3DCollection,
+    Poly3DCollection,
+    _all_points_on_plane,
+)
+
+
+def test_scatter_3d_projection_conservation():
+    fig = plt.figure()
+    ax = fig.add_subplot(projection='3d')
+    # fix axes3d projection
+    ax.roll = 0
+    ax.elev = 0
+    ax.azim = -45
+    ax.stale = True
+
+    x = [0, 1, 2, 3, 4]
+    scatter_collection = ax.scatter(x, x, x)
+    fig.canvas.draw_idle()
+
+    # Get scatter location on canvas and freeze the data
+    scatter_offset = scatter_collection.get_offsets()
+    scatter_location = ax.transData.transform(scatter_offset)
+
+    # Yaw -44 and -46 are enough to produce two set of scatter
+    # with opposite z-order without moving points too far
+    for azim in (-44, -46):
+        ax.azim = azim
+        ax.stale = True
+        fig.canvas.draw_idle()
+
+        for i in range(5):
+            # Create a mouse event used to locate and to get index
+            # from each dots
+            event = MouseEvent("button_press_event", fig.canvas,
+                               *scatter_location[i, :])
+            contains, ind = scatter_collection.contains(event)
+            assert contains is True
+            assert len(ind["ind"]) == 1
+            assert ind["ind"][0] == i
+
+
+def test_zordered_error():
+    # Smoke test for https://github.com/matplotlib/matplotlib/issues/26497
+    lc = [(np.fromiter([0.0, 0.0, 0.0], dtype="float"),
+           np.fromiter([1.0, 1.0, 1.0], dtype="float"))]
+    pc = [np.fromiter([0.0, 0.0], dtype="float"),
+          np.fromiter([0.0, 1.0], dtype="float"),
+          np.fromiter([1.0, 1.0], dtype="float")]
+
+    fig = plt.figure()
+    ax = fig.add_subplot(projection="3d")
+    ax.add_collection(Line3DCollection(lc))
+    ax.scatter(*pc, visible=False)
+    plt.draw()
+
+
+def test_all_points_on_plane():
+    # Non-coplanar points
+    points = np.array([[0, 0, 0], [1, 0, 0], [0, 1, 0], [0, 0, 1]])
+    assert not _all_points_on_plane(*points.T)
+
+    # Duplicate points
+    points = np.array([[0, 0, 0], [1, 0, 0], [0, 1, 0], [0, 0, 0]])
+    assert _all_points_on_plane(*points.T)
+
+    # NaN values
+    points = np.array([[0, 0, 0], [1, 0, 0], [0, 1, 0], [0, 0, np.nan]])
+    assert _all_points_on_plane(*points.T)
+
+    # Less than 3 unique points
+    points = np.array([[0, 0, 0], [0, 0, 0], [0, 0, 0]])
+    assert _all_points_on_plane(*points.T)
+
+    # All points lie on a line
+    points = np.array([[0, 0, 0], [0, 1, 0], [0, 2, 0], [0, 3, 0]])
+    assert _all_points_on_plane(*points.T)
+
+    # All points lie on two lines, with antiparallel vectors
+    points = np.array([[-2, 2, 0], [-1, 1, 0], [1, -1, 0],
+                       [0, 0, 0], [2, 0, 0], [1, 0, 0]])
+    assert _all_points_on_plane(*points.T)
+
+    # All points lie on a plane
+    points = np.array([[0, 0, 0], [0, 1, 0], [1, 0, 0], [1, 1, 0], [1, 2, 0]])
+    assert _all_points_on_plane(*points.T)
+
+
+def test_generate_normals():
+    # Smoke test for https://github.com/matplotlib/matplotlib/issues/29156
+    vertices = ((0, 0, 0), (0, 5, 0), (5, 5, 0), (5, 0, 0))
+    shape = Poly3DCollection([vertices], edgecolors='r', shade=True)
+
+    fig = plt.figure()
+    ax = fig.add_subplot(projection='3d')
+    ax.add_collection3d(shape)
+    plt.draw()

venv/lib/python3.13/site-packages/mpl_toolkits/mplot3d/tests/test_legend3d.py

@@ -0,0 +1,117 @@
+import platform
+
+import numpy as np
+
+import matplotlib as mpl
+from matplotlib.colors import same_color
+from matplotlib.testing.decorators import image_comparison
+import matplotlib.pyplot as plt
+from mpl_toolkits.mplot3d import art3d
+
+
+@image_comparison(['legend_plot.png'], remove_text=True, style='mpl20')
+def test_legend_plot():
+    fig, ax = plt.subplots(subplot_kw=dict(projection='3d'))
+    x = np.arange(10)
+    ax.plot(x, 5 - x, 'o', zdir='y', label='z=1')
+    ax.plot(x, x - 5, 'o', zdir='y', label='z=-1')
+    ax.legend()
+
+
+@image_comparison(['legend_bar.png'], remove_text=True, style='mpl20')
+def test_legend_bar():
+    fig, ax = plt.subplots(subplot_kw=dict(projection='3d'))
+    x = np.arange(10)
+    b1 = ax.bar(x, x, zdir='y', align='edge', color='m')
+    b2 = ax.bar(x, x[::-1], zdir='x', align='edge', color='g')
+    ax.legend([b1[0], b2[0]], ['up', 'down'])
+
+
+@image_comparison(['fancy.png'], remove_text=True, style='mpl20',
+                  tol=0 if platform.machine() == 'x86_64' else 0.011)
+def test_fancy():
+    fig, ax = plt.subplots(subplot_kw=dict(projection='3d'))
+    ax.plot(np.arange(10), np.full(10, 5), np.full(10, 5), 'o--', label='line')
+    ax.scatter(np.arange(10), np.arange(10, 0, -1), label='scatter')
+    ax.errorbar(np.full(10, 5), np.arange(10), np.full(10, 10),
+                xerr=0.5, zerr=0.5, label='errorbar')
+    ax.legend(loc='lower left', ncols=2, title='My legend', numpoints=1)
+
+
+def test_linecollection_scaled_dashes():
+    lines1 = [[(0, .5), (.5, 1)], [(.3, .6), (.2, .2)]]
+    lines2 = [[[0.7, .2], [.8, .4]], [[.5, .7], [.6, .1]]]
+    lines3 = [[[0.6, .2], [.8, .4]], [[.5, .7], [.1, .1]]]
+    lc1 = art3d.Line3DCollection(lines1, linestyles="--", lw=3)
+    lc2 = art3d.Line3DCollection(lines2, linestyles="-.")
+    lc3 = art3d.Line3DCollection(lines3, linestyles=":", lw=.5)
+
+    fig, ax = plt.subplots(subplot_kw=dict(projection='3d'))
+    ax.add_collection(lc1)
+    ax.add_collection(lc2)
+    ax.add_collection(lc3)
+
+    leg = ax.legend([lc1, lc2, lc3], ['line1', 'line2', 'line 3'])
+    h1, h2, h3 = leg.legend_handles
+
+    for oh, lh in zip((lc1, lc2, lc3), (h1, h2, h3)):
+        assert oh.get_linestyles()[0] == lh._dash_pattern
+
+
+def test_handlerline3d():
+    # Test marker consistency for monolithic Line3D legend handler.
+    fig, ax = plt.subplots(subplot_kw=dict(projection='3d'))
+    ax.scatter([0, 1], [0, 1], marker="v")
+    handles = [art3d.Line3D([0], [0], [0], marker="v")]
+    leg = ax.legend(handles, ["Aardvark"], numpoints=1)
+    assert handles[0].get_marker() == leg.legend_handles[0].get_marker()
+
+
+def test_contour_legend_elements():
+    x, y = np.mgrid[1:10, 1:10]
+    h = x * y
+    colors = ['blue', '#00FF00', 'red']
+
+    fig, ax = plt.subplots(subplot_kw=dict(projection='3d'))
+    cs = ax.contour(x, y, h, levels=[10, 30, 50], colors=colors, extend='both')
+
+    artists, labels = cs.legend_elements()
+    assert labels == ['$x = 10.0$', '$x = 30.0$', '$x = 50.0$']
+    assert all(isinstance(a, mpl.lines.Line2D) for a in artists)
+    assert all(same_color(a.get_color(), c)
+               for a, c in zip(artists, colors))
+
+
+def test_contourf_legend_elements():
+    x, y = np.mgrid[1:10, 1:10]
+    h = x * y
+
+    fig, ax = plt.subplots(subplot_kw=dict(projection='3d'))
+    cs = ax.contourf(x, y, h, levels=[10, 30, 50],
+                     colors=['#FFFF00', '#FF00FF', '#00FFFF'],
+                     extend='both')
+    cs.cmap.set_over('red')
+    cs.cmap.set_under('blue')
+    cs.changed()
+    artists, labels = cs.legend_elements()
+    assert labels == ['$x \\leq -1e+250s$',
+                      '$10.0 < x \\leq 30.0$',
+                      '$30.0 < x \\leq 50.0$',
+                      '$x > 1e+250s$']
+    expected_colors = ('blue', '#FFFF00', '#FF00FF', 'red')
+    assert all(isinstance(a, mpl.patches.Rectangle) for a in artists)
+    assert all(same_color(a.get_facecolor(), c)
+               for a, c in zip(artists, expected_colors))
+
+
+def test_legend_Poly3dCollection():
+
+    verts = np.asarray([[0, 0, 0], [0, 1, 1], [1, 0, 1]])
+    mesh = art3d.Poly3DCollection([verts], label="surface")
+
+    fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
+    mesh.set_edgecolor('k')
+    handle = ax.add_collection3d(mesh)
+    leg = ax.legend()
+    assert (leg.legend_handles[0].get_facecolor()
+            == handle.get_facecolor()).all()