I am done

rl/Lib/site-packages/matplotlib/axes/__init__.py

@@ -0,0 +1,18 @@
+from . import _base
+from ._axes import Axes  # noqa: F401
+
+# Backcompat.
+Subplot = Axes
+
+
+class _SubplotBaseMeta(type):
+    def __instancecheck__(self, obj):
+        return (isinstance(obj, _base._AxesBase)
+                and obj.get_subplotspec() is not None)
+
+
+class SubplotBase(metaclass=_SubplotBaseMeta):
+    pass
+
+
+def subplot_class_factory(cls): return cls

rl/Lib/site-packages/matplotlib/axes/__init__.pyi

@@ -0,0 +1,16 @@
+from typing import TypeVar
+
+from ._axes import Axes as Axes
+
+
+_T = TypeVar("_T")
+
+# Backcompat.
+Subplot = Axes
+
+class _SubplotBaseMeta(type):
+    def __instancecheck__(self, obj) -> bool: ...
+
+class SubplotBase(metaclass=_SubplotBaseMeta): ...
+
+def subplot_class_factory(cls: type[_T]) -> type[_T]: ...

rl/Lib/site-packages/matplotlib/axes/_axes.pyi

@@ -0,0 +1,772 @@
+from matplotlib.axes._base import _AxesBase
+from matplotlib.axes._secondary_axes import SecondaryAxis
+
+from matplotlib.artist import Artist
+from matplotlib.backend_bases import RendererBase
+from matplotlib.collections import (
+    Collection,
+    LineCollection,
+    PathCollection,
+    PolyCollection,
+    EventCollection,
+    QuadMesh,
+)
+from matplotlib.colors import Colormap, Normalize
+from matplotlib.container import BarContainer, ErrorbarContainer, StemContainer
+from matplotlib.contour import ContourSet, QuadContourSet
+from matplotlib.image import AxesImage, PcolorImage
+from matplotlib.legend import Legend
+from matplotlib.legend_handler import HandlerBase
+from matplotlib.lines import Line2D, AxLine
+from matplotlib.mlab import GaussianKDE
+from matplotlib.patches import Rectangle, FancyArrow, Polygon, StepPatch, Wedge
+from matplotlib.quiver import Quiver, QuiverKey, Barbs
+from matplotlib.text import Annotation, Text
+from matplotlib.transforms import Transform, Bbox
+import matplotlib.tri as mtri
+import matplotlib.table as mtable
+import matplotlib.stackplot as mstack
+import matplotlib.streamplot as mstream
+
+import datetime
+import PIL.Image
+from collections.abc import Callable, Iterable, Sequence
+from typing import Any, Literal, overload
+import numpy as np
+from numpy.typing import ArrayLike
+from matplotlib.typing import ColorType, MarkerType, LineStyleType
+
+class Axes(_AxesBase):
+    def get_title(self, loc: Literal["left", "center", "right"] = ...) -> str: ...
+    def set_title(
+        self,
+        label: str,
+        fontdict: dict[str, Any] | None = ...,
+        loc: Literal["left", "center", "right"] | None = ...,
+        pad: float | None = ...,
+        *,
+        y: float | None = ...,
+        **kwargs
+    ) -> Text: ...
+    def get_legend_handles_labels(
+        self, legend_handler_map: dict[type, HandlerBase] | None = ...
+    ) -> tuple[list[Artist], list[Any]]: ...
+    legend_: Legend | None
+
+    @overload
+    def legend(self) -> Legend: ...
+    @overload
+    def legend(self, handles: Iterable[Artist | tuple[Artist, ...]], labels: Iterable[str], **kwargs) -> Legend: ...
+    @overload
+    def legend(self, *, handles: Iterable[Artist | tuple[Artist, ...]], **kwargs) -> Legend: ...
+    @overload
+    def legend(self, labels: Iterable[str], **kwargs) -> Legend: ...
+    @overload
+    def legend(self, **kwargs) -> Legend: ...
+
+    def inset_axes(
+        self,
+        bounds: tuple[float, float, float, float],
+        *,
+        transform: Transform | None = ...,
+        zorder: float = ...,
+        **kwargs
+    ) -> Axes: ...
+    def indicate_inset(
+        self,
+        bounds: tuple[float, float, float, float],
+        inset_ax: Axes | None = ...,
+        *,
+        transform: Transform | None = ...,
+        facecolor: ColorType = ...,
+        edgecolor: ColorType = ...,
+        alpha: float = ...,
+        zorder: float = ...,
+        **kwargs
+    ) -> Rectangle: ...
+    def indicate_inset_zoom(self, inset_ax: Axes, **kwargs) -> Rectangle: ...
+    def secondary_xaxis(
+        self,
+        location: Literal["top", "bottom"] | float,
+        *,
+        functions: tuple[
+            Callable[[ArrayLike], ArrayLike], Callable[[ArrayLike], ArrayLike]
+        ]
+        | Transform
+        | None = ...,
+        transform: Transform | None = ...,
+        **kwargs
+    ) -> SecondaryAxis: ...
+    def secondary_yaxis(
+        self,
+        location: Literal["left", "right"] | float,
+        *,
+        functions: tuple[
+            Callable[[ArrayLike], ArrayLike], Callable[[ArrayLike], ArrayLike]
+        ]
+        | Transform
+        | None = ...,
+        transform: Transform | None = ...,
+        **kwargs
+    ) -> SecondaryAxis: ...
+    def text(
+        self,
+        x: float,
+        y: float,
+        s: str,
+        fontdict: dict[str, Any] | None = ...,
+        **kwargs
+    ) -> Text: ...
+    def annotate(
+        self,
+        text: str,
+        xy: tuple[float, float],
+        xytext: tuple[float, float] | None = ...,
+        xycoords: str
+        | Artist
+        | Transform
+        | Callable[[RendererBase], Bbox | Transform]
+        | tuple[float, float] = ...,
+        textcoords: str
+        | Artist
+        | Transform
+        | Callable[[RendererBase], Bbox | Transform]
+        | tuple[float, float]
+        | None = ...,
+        arrowprops: dict[str, Any] | None = ...,
+        annotation_clip: bool | None = ...,
+        **kwargs
+    ) -> Annotation: ...
+    def axhline(
+        self, y: float = ..., xmin: float = ..., xmax: float = ..., **kwargs
+    ) -> Line2D: ...
+    def axvline(
+        self, x: float = ..., ymin: float = ..., ymax: float = ..., **kwargs
+    ) -> Line2D: ...
+
+    # TODO: Could separate the xy2 and slope signatures
+    def axline(
+        self,
+        xy1: tuple[float, float],
+        xy2: tuple[float, float] | None = ...,
+        *,
+        slope: float | None = ...,
+        **kwargs
+    ) -> AxLine: ...
+    def axhspan(
+        self, ymin: float, ymax: float, xmin: float = ..., xmax: float = ..., **kwargs
+    ) -> Rectangle: ...
+    def axvspan(
+        self, xmin: float, xmax: float, ymin: float = ..., ymax: float = ..., **kwargs
+    ) -> Rectangle: ...
+    def hlines(
+        self,
+        y: float | ArrayLike,
+        xmin: float | ArrayLike,
+        xmax: float | ArrayLike,
+        colors: ColorType | Sequence[ColorType] | None = ...,
+        linestyles: LineStyleType = ...,
+        label: str = ...,
+        *,
+        data=...,
+        **kwargs
+    ) -> LineCollection: ...
+    def vlines(
+        self,
+        x: float | ArrayLike,
+        ymin: float | ArrayLike,
+        ymax: float | ArrayLike,
+        colors: ColorType | Sequence[ColorType] | None = ...,
+        linestyles: LineStyleType = ...,
+        label: str = ...,
+        *,
+        data=...,
+        **kwargs
+    ) -> LineCollection: ...
+    def eventplot(
+        self,
+        positions: ArrayLike | Sequence[ArrayLike],
+        orientation: Literal["horizontal", "vertical"] = ...,
+        lineoffsets: float | Sequence[float] = ...,
+        linelengths: float | Sequence[float] = ...,
+        linewidths: float | Sequence[float] | None = ...,
+        colors: ColorType | Sequence[ColorType] | None = ...,
+        alpha: float | Sequence[float] | None = ...,
+        linestyles: LineStyleType | Sequence[LineStyleType] = ...,
+        *,
+        data=...,
+        **kwargs
+    ) -> EventCollection: ...
+    def plot(
+        self,
+        *args: float | ArrayLike | str,
+        scalex: bool = ...,
+        scaley: bool = ...,
+        data = ...,
+        **kwargs
+    ) -> list[Line2D]: ...
+    def plot_date(
+        self,
+        x: ArrayLike,
+        y: ArrayLike,
+        fmt: str = ...,
+        tz: str | datetime.tzinfo | None = ...,
+        xdate: bool = ...,
+        ydate: bool = ...,
+        *,
+        data=...,
+        **kwargs
+    ) -> list[Line2D]: ...
+    def loglog(self, *args, **kwargs) -> list[Line2D]: ...
+    def semilogx(self, *args, **kwargs) -> list[Line2D]: ...
+    def semilogy(self, *args, **kwargs) -> list[Line2D]: ...
+    def acorr(
+        self, x: ArrayLike, *, data=..., **kwargs
+    ) -> tuple[np.ndarray, np.ndarray, LineCollection | Line2D, Line2D | None]: ...
+    def xcorr(
+        self,
+        x: ArrayLike,
+        y: ArrayLike,
+        normed: bool = ...,
+        detrend: Callable[[ArrayLike], ArrayLike] = ...,
+        usevlines: bool = ...,
+        maxlags: int = ...,
+        *,
+        data = ...,
+        **kwargs
+    ) -> tuple[np.ndarray, np.ndarray, LineCollection | Line2D, Line2D | None]: ...
+    def step(
+        self,
+        x: ArrayLike,
+        y: ArrayLike,
+        *args,
+        where: Literal["pre", "post", "mid"] = ...,
+        data = ...,
+        **kwargs
+    ) -> list[Line2D]: ...
+    def bar(
+        self,
+        x: float | ArrayLike,
+        height: float | ArrayLike,
+        width: float | ArrayLike = ...,
+        bottom: float | ArrayLike | None = ...,
+        *,
+        align: Literal["center", "edge"] = ...,
+        data = ...,
+        **kwargs
+    ) -> BarContainer: ...
+    def barh(
+        self,
+        y: float | ArrayLike,
+        width: float | ArrayLike,
+        height: float | ArrayLike = ...,
+        left: float | ArrayLike | None = ...,
+        *,
+        align: Literal["center", "edge"] = ...,
+        data = ...,
+        **kwargs
+    ) -> BarContainer: ...
+    def bar_label(
+        self,
+        container: BarContainer,
+        labels: ArrayLike | None = ...,
+        *,
+        fmt: str | Callable[[float], str] = ...,
+        label_type: Literal["center", "edge"] = ...,
+        padding: float = ...,
+        **kwargs
+    ) -> list[Annotation]: ...
+    def broken_barh(
+        self,
+        xranges: Sequence[tuple[float, float]],
+        yrange: tuple[float, float],
+        *,
+        data=...,
+        **kwargs
+    ) -> PolyCollection: ...
+    def stem(
+        self,
+        *args: ArrayLike | str,
+        linefmt: str | None = ...,
+        markerfmt: str | None = ...,
+        basefmt: str | None = ...,
+        bottom: float = ...,
+        label: str | None = ...,
+        orientation: Literal["vertical", "horizontal"] = ...,
+        data=...,
+    ) -> StemContainer: ...
+
+    # TODO: data kwarg preprocessor?
+    def pie(
+        self,
+        x: ArrayLike,
+        explode: ArrayLike | None = ...,
+        labels: Sequence[str] | None = ...,
+        colors: ColorType | Sequence[ColorType] | None = ...,
+        autopct: str | Callable[[float], str] | None = ...,
+        pctdistance: float = ...,
+        shadow: bool = ...,
+        labeldistance: float | None = ...,
+        startangle: float = ...,
+        radius: float = ...,
+        counterclock: bool = ...,
+        wedgeprops: dict[str, Any] | None = ...,
+        textprops: dict[str, Any] | None = ...,
+        center: tuple[float, float] = ...,
+        frame: bool = ...,
+        rotatelabels: bool = ...,
+        *,
+        normalize: bool = ...,
+        hatch: str | Sequence[str] | None = ...,
+        data=...,
+    ) -> tuple[list[Wedge], list[Text]] | tuple[
+        list[Wedge], list[Text], list[Text]
+    ]: ...
+    def errorbar(
+        self,
+        x: float | ArrayLike,
+        y: float | ArrayLike,
+        yerr: float | ArrayLike | None = ...,
+        xerr: float | ArrayLike | None = ...,
+        fmt: str = ...,
+        ecolor: ColorType | None = ...,
+        elinewidth: float | None = ...,
+        capsize: float | None = ...,
+        barsabove: bool = ...,
+        lolims: bool | ArrayLike = ...,
+        uplims: bool | ArrayLike = ...,
+        xlolims: bool | ArrayLike = ...,
+        xuplims: bool | ArrayLike = ...,
+        errorevery: int | tuple[int, int] = ...,
+        capthick: float | None = ...,
+        *,
+        data=...,
+        **kwargs
+    ) -> ErrorbarContainer: ...
+    def boxplot(
+        self,
+        x: ArrayLike | Sequence[ArrayLike],
+        notch: bool | None = ...,
+        sym: str | None = ...,
+        vert: bool | None = ...,
+        whis: float | tuple[float, float] | None = ...,
+        positions: ArrayLike | None = ...,
+        widths: float | ArrayLike | None = ...,
+        patch_artist: bool | None = ...,
+        bootstrap: int | None = ...,
+        usermedians: ArrayLike | None = ...,
+        conf_intervals: ArrayLike | None = ...,
+        meanline: bool | None = ...,
+        showmeans: bool | None = ...,
+        showcaps: bool | None = ...,
+        showbox: bool | None = ...,
+        showfliers: bool | None = ...,
+        boxprops: dict[str, Any] | None = ...,
+        tick_labels: Sequence[str] | None = ...,
+        flierprops: dict[str, Any] | None = ...,
+        medianprops: dict[str, Any] | None = ...,
+        meanprops: dict[str, Any] | None = ...,
+        capprops: dict[str, Any] | None = ...,
+        whiskerprops: dict[str, Any] | None = ...,
+        manage_ticks: bool = ...,
+        autorange: bool = ...,
+        zorder: float | None = ...,
+        capwidths: float | ArrayLike | None = ...,
+        label: Sequence[str] | None = ...,
+        *,
+        data=...,
+    ) -> dict[str, Any]: ...
+    def bxp(
+        self,
+        bxpstats: Sequence[dict[str, Any]],
+        positions: ArrayLike | None = ...,
+        widths: float | ArrayLike | None = ...,
+        vert: bool = ...,
+        patch_artist: bool = ...,
+        shownotches: bool = ...,
+        showmeans: bool = ...,
+        showcaps: bool = ...,
+        showbox: bool = ...,
+        showfliers: bool = ...,
+        boxprops: dict[str, Any] | None = ...,
+        whiskerprops: dict[str, Any] | None = ...,
+        flierprops: dict[str, Any] | None = ...,
+        medianprops: dict[str, Any] | None = ...,
+        capprops: dict[str, Any] | None = ...,
+        meanprops: dict[str, Any] | None = ...,
+        meanline: bool = ...,
+        manage_ticks: bool = ...,
+        zorder: float | None = ...,
+        capwidths: float | ArrayLike | None = ...,
+        label: Sequence[str] | None = ...,
+    ) -> dict[str, Any]: ...
+    def scatter(
+        self,
+        x: float | ArrayLike,
+        y: float | ArrayLike,
+        s: float | ArrayLike | None = ...,
+        c: ArrayLike | Sequence[ColorType] | ColorType | None = ...,
+        marker: MarkerType | None = ...,
+        cmap: str | Colormap | None = ...,
+        norm: str | Normalize | None = ...,
+        vmin: float | None = ...,
+        vmax: float | None = ...,
+        alpha: float | None = ...,
+        linewidths: float | Sequence[float] | None = ...,
+        *,
+        edgecolors: Literal["face", "none"] | ColorType | Sequence[ColorType] | None = ...,
+        plotnonfinite: bool = ...,
+        data=...,
+        **kwargs
+    ) -> PathCollection: ...
+    def hexbin(
+        self,
+        x: ArrayLike,
+        y: ArrayLike,
+        C: ArrayLike | None = ...,
+        gridsize: int | tuple[int, int] = ...,
+        bins: Literal["log"] | int | Sequence[float] | None = ...,
+        xscale: Literal["linear", "log"] = ...,
+        yscale: Literal["linear", "log"] = ...,
+        extent: tuple[float, float, float, float] | None = ...,
+        cmap: str | Colormap | None = ...,
+        norm: str | Normalize | None = ...,
+        vmin: float | None = ...,
+        vmax: float | None = ...,
+        alpha: float | None = ...,
+        linewidths: float | None = ...,
+        edgecolors: Literal["face", "none"] | ColorType = ...,
+        reduce_C_function: Callable[[np.ndarray | list[float]], float] = ...,
+        mincnt: int | None = ...,
+        marginals: bool = ...,
+        *,
+        data=...,
+        **kwargs
+    ) -> PolyCollection: ...
+    def arrow(
+        self, x: float, y: float, dx: float, dy: float, **kwargs
+    ) -> FancyArrow: ...
+    def quiverkey(
+        self, Q: Quiver, X: float, Y: float, U: float, label: str, **kwargs
+    ) -> QuiverKey: ...
+    def quiver(self, *args, data=..., **kwargs) -> Quiver: ...
+    def barbs(self, *args, data=..., **kwargs) -> Barbs: ...
+    def fill(self, *args, data=..., **kwargs) -> list[Polygon]: ...
+    def fill_between(
+        self,
+        x: ArrayLike,
+        y1: ArrayLike | float,
+        y2: ArrayLike | float = ...,
+        where: Sequence[bool] | None = ...,
+        interpolate: bool = ...,
+        step: Literal["pre", "post", "mid"] | None = ...,
+        *,
+        data=...,
+        **kwargs
+    ) -> PolyCollection: ...
+    def fill_betweenx(
+        self,
+        y: ArrayLike,
+        x1: ArrayLike | float,
+        x2: ArrayLike | float = ...,
+        where: Sequence[bool] | None = ...,
+        step: Literal["pre", "post", "mid"] | None = ...,
+        interpolate: bool = ...,
+        *,
+        data=...,
+        **kwargs
+    ) -> PolyCollection: ...
+    def imshow(
+        self,
+        X: ArrayLike | PIL.Image.Image,
+        cmap: str | Colormap | None = ...,
+        norm: str | Normalize | None = ...,
+        *,
+        aspect: Literal["equal", "auto"] | float | None = ...,
+        interpolation: str | None = ...,
+        alpha: float | ArrayLike | None = ...,
+        vmin: float | None = ...,
+        vmax: float | None = ...,
+        origin: Literal["upper", "lower"] | None = ...,
+        extent: tuple[float, float, float, float] | None = ...,
+        interpolation_stage: Literal["data", "rgba"] | None = ...,
+        filternorm: bool = ...,
+        filterrad: float = ...,
+        resample: bool | None = ...,
+        url: str | None = ...,
+        data=...,
+        **kwargs
+    ) -> AxesImage: ...
+    def pcolor(
+        self,
+        *args: ArrayLike,
+        shading: Literal["flat", "nearest", "auto"] | None = ...,
+        alpha: float | None = ...,
+        norm: str | Normalize | None = ...,
+        cmap: str | Colormap | None = ...,
+        vmin: float | None = ...,
+        vmax: float | None = ...,
+        data=...,
+        **kwargs
+    ) -> Collection: ...
+    def pcolormesh(
+        self,
+        *args: ArrayLike,
+        alpha: float | None = ...,
+        norm: str | Normalize | None = ...,
+        cmap: str | Colormap | None = ...,
+        vmin: float | None = ...,
+        vmax: float | None = ...,
+        shading: Literal["flat", "nearest", "gouraud", "auto"] | None = ...,
+        antialiased: bool = ...,
+        data=...,
+        **kwargs
+    ) -> QuadMesh: ...
+    def pcolorfast(
+        self,
+        *args: ArrayLike | tuple[float, float],
+        alpha: float | None = ...,
+        norm: str | Normalize | None = ...,
+        cmap: str | Colormap | None = ...,
+        vmin: float | None = ...,
+        vmax: float | None = ...,
+        data=...,
+        **kwargs
+    ) -> AxesImage | PcolorImage | QuadMesh: ...
+    def contour(self, *args, data=..., **kwargs) -> QuadContourSet: ...
+    def contourf(self, *args, data=..., **kwargs) -> QuadContourSet: ...
+    def clabel(
+        self, CS: ContourSet, levels: ArrayLike | None = ..., **kwargs
+    ) -> list[Text]: ...
+    def hist(
+        self,
+        x: ArrayLike | Sequence[ArrayLike],
+        bins: int | Sequence[float] | str | None = ...,
+        range: tuple[float, float] | None = ...,
+        density: bool = ...,
+        weights: ArrayLike | None = ...,
+        cumulative: bool | float = ...,
+        bottom: ArrayLike | float | None = ...,
+        histtype: Literal["bar", "barstacked", "step", "stepfilled"] = ...,
+        align: Literal["left", "mid", "right"] = ...,
+        orientation: Literal["vertical", "horizontal"] = ...,
+        rwidth: float | None = ...,
+        log: bool = ...,
+        color: ColorType | Sequence[ColorType] | None = ...,
+        label: str | Sequence[str] | None = ...,
+        stacked: bool = ...,
+        *,
+        data=...,
+        **kwargs
+    ) -> tuple[
+        np.ndarray | list[np.ndarray],
+        np.ndarray,
+        BarContainer | Polygon | list[BarContainer | Polygon],
+    ]: ...
+    def stairs(
+        self,
+        values: ArrayLike,
+        edges: ArrayLike | None = ...,
+        *,
+        orientation: Literal["vertical", "horizontal"] = ...,
+        baseline: float | ArrayLike | None = ...,
+        fill: bool = ...,
+        data=...,
+        **kwargs
+    ) -> StepPatch: ...
+    def hist2d(
+        self,
+        x: ArrayLike,
+        y: ArrayLike,
+        bins: None
+        | int
+        | tuple[int, int]
+        | ArrayLike
+        | tuple[ArrayLike, ArrayLike] = ...,
+        range: ArrayLike | None = ...,
+        density: bool = ...,
+        weights: ArrayLike | None = ...,
+        cmin: float | None = ...,
+        cmax: float | None = ...,
+        *,
+        data=...,
+        **kwargs
+    ) -> tuple[np.ndarray, np.ndarray, np.ndarray, QuadMesh]: ...
+    def ecdf(
+        self,
+        x: ArrayLike,
+        weights: ArrayLike | None = ...,
+        *,
+        complementary: bool=...,
+        orientation: Literal["vertical", "horizonatal"]=...,
+        compress: bool=...,
+        data=...,
+        **kwargs
+    ) -> Line2D: ...
+    def psd(
+        self,
+        x: ArrayLike,
+        NFFT: int | None = ...,
+        Fs: float | None = ...,
+        Fc: int | None = ...,
+        detrend: Literal["none", "mean", "linear"]
+        | Callable[[ArrayLike], ArrayLike]
+        | None = ...,
+        window: Callable[[ArrayLike], ArrayLike] | ArrayLike | None = ...,
+        noverlap: int | None = ...,
+        pad_to: int | None = ...,
+        sides: Literal["default", "onesided", "twosided"] | None = ...,
+        scale_by_freq: bool | None = ...,
+        return_line: bool | None = ...,
+        *,
+        data=...,
+        **kwargs
+    ) -> tuple[np.ndarray, np.ndarray] | tuple[np.ndarray, np.ndarray, Line2D]: ...
+    def csd(
+        self,
+        x: ArrayLike,
+        y: ArrayLike,
+        NFFT: int | None = ...,
+        Fs: float | None = ...,
+        Fc: int | None = ...,
+        detrend: Literal["none", "mean", "linear"]
+        | Callable[[ArrayLike], ArrayLike]
+        | None = ...,
+        window: Callable[[ArrayLike], ArrayLike] | ArrayLike | None = ...,
+        noverlap: int | None = ...,
+        pad_to: int | None = ...,
+        sides: Literal["default", "onesided", "twosided"] | None = ...,
+        scale_by_freq: bool | None = ...,
+        return_line: bool | None = ...,
+        *,
+        data=...,
+        **kwargs
+    ) -> tuple[np.ndarray, np.ndarray] | tuple[np.ndarray, np.ndarray, Line2D]: ...
+    def magnitude_spectrum(
+        self,
+        x: ArrayLike,
+        Fs: float | None = ...,
+        Fc: int | None = ...,
+        window: Callable[[ArrayLike], ArrayLike] | ArrayLike | None = ...,
+        pad_to: int | None = ...,
+        sides: Literal["default", "onesided", "twosided"] | None = ...,
+        scale: Literal["default", "linear", "dB"] | None = ...,
+        *,
+        data=...,
+        **kwargs
+    ) -> tuple[np.ndarray, np.ndarray, Line2D]: ...
+    def angle_spectrum(
+        self,
+        x: ArrayLike,
+        Fs: float | None = ...,
+        Fc: int | None = ...,
+        window: Callable[[ArrayLike], ArrayLike] | ArrayLike | None = ...,
+        pad_to: int | None = ...,
+        sides: Literal["default", "onesided", "twosided"] | None = ...,
+        *,
+        data=...,
+        **kwargs
+    ) -> tuple[np.ndarray, np.ndarray, Line2D]: ...
+    def phase_spectrum(
+        self,
+        x: ArrayLike,
+        Fs: float | None = ...,
+        Fc: int | None = ...,
+        window: Callable[[ArrayLike], ArrayLike] | ArrayLike | None = ...,
+        pad_to: int | None = ...,
+        sides: Literal["default", "onesided", "twosided"] | None = ...,
+        *,
+        data=...,
+        **kwargs
+    ) -> tuple[np.ndarray, np.ndarray, Line2D]: ...
+    def cohere(
+        self,
+        x: ArrayLike,
+        y: ArrayLike,
+        NFFT: int = ...,
+        Fs: float = ...,
+        Fc: int = ...,
+        detrend: Literal["none", "mean", "linear"]
+        | Callable[[ArrayLike], ArrayLike] = ...,
+        window: Callable[[ArrayLike], ArrayLike] | ArrayLike = ...,
+        noverlap: int = ...,
+        pad_to: int | None = ...,
+        sides: Literal["default", "onesided", "twosided"] = ...,
+        scale_by_freq: bool | None = ...,
+        *,
+        data=...,
+        **kwargs
+    ) -> tuple[np.ndarray, np.ndarray]: ...
+    def specgram(
+        self,
+        x: ArrayLike,
+        NFFT: int | None = ...,
+        Fs: float | None = ...,
+        Fc: int | None = ...,
+        detrend: Literal["none", "mean", "linear"]
+        | Callable[[ArrayLike], ArrayLike]
+        | None = ...,
+        window: Callable[[ArrayLike], ArrayLike] | ArrayLike | None = ...,
+        noverlap: int | None = ...,
+        cmap: str | Colormap | None = ...,
+        xextent: tuple[float, float] | None = ...,
+        pad_to: int | None = ...,
+        sides: Literal["default", "onesided", "twosided"] | None = ...,
+        scale_by_freq: bool | None = ...,
+        mode: Literal["default", "psd", "magnitude", "angle", "phase"] | None = ...,
+        scale: Literal["default", "linear", "dB"] | None = ...,
+        vmin: float | None = ...,
+        vmax: float | None = ...,
+        *,
+        data=...,
+        **kwargs
+    ) -> tuple[np.ndarray, np.ndarray, np.ndarray, AxesImage]: ...
+    def spy(
+        self,
+        Z: ArrayLike,
+        precision: float | Literal["present"] = ...,
+        marker: str | None = ...,
+        markersize: float | None = ...,
+        aspect: Literal["equal", "auto"] | float | None = ...,
+        origin: Literal["upper", "lower"] = ...,
+        **kwargs
+    ) -> AxesImage: ...
+    def matshow(self, Z: ArrayLike, **kwargs) -> AxesImage: ...
+    def violinplot(
+        self,
+        dataset: ArrayLike | Sequence[ArrayLike],
+        positions: ArrayLike | None = ...,
+        vert: bool = ...,
+        widths: float | ArrayLike = ...,
+        showmeans: bool = ...,
+        showextrema: bool = ...,
+        showmedians: bool = ...,
+        quantiles: Sequence[float | Sequence[float]] | None = ...,
+        points: int = ...,
+        bw_method: Literal["scott", "silverman"]
+        | float
+        | Callable[[GaussianKDE], float]
+        | None = ...,
+        side: Literal["both", "low", "high"] = ...,
+        *,
+        data=...,
+    ) -> dict[str, Collection]: ...
+    def violin(
+        self,
+        vpstats: Sequence[dict[str, Any]],
+        positions: ArrayLike | None = ...,
+        vert: bool = ...,
+        widths: float | ArrayLike = ...,
+        showmeans: bool = ...,
+        showextrema: bool = ...,
+        showmedians: bool = ...,
+        side: Literal["both", "low", "high"] = ...,
+    ) -> dict[str, Collection]: ...
+
+    table = mtable.table
+    stackplot = mstack.stackplot
+    streamplot = mstream.streamplot
+    tricontour = mtri.tricontour
+    tricontourf = mtri.tricontourf
+    tripcolor = mtri.tripcolor
+    triplot = mtri.triplot

rl/Lib/site-packages/matplotlib/axes/_base.pyi

@@ -0,0 +1,459 @@
+import matplotlib.artist as martist
+
+import datetime
+from collections.abc import Callable, Iterable, Iterator, Sequence
+from matplotlib import cbook
+from matplotlib.artist import Artist
+from matplotlib.axes import Axes
+from matplotlib.axis import XAxis, YAxis, Tick
+from matplotlib.backend_bases import RendererBase, MouseButton, MouseEvent
+from matplotlib.cbook import CallbackRegistry
+from matplotlib.container import Container
+from matplotlib.collections import Collection
+from matplotlib.cm import ScalarMappable
+from matplotlib.legend import Legend
+from matplotlib.lines import Line2D
+from matplotlib.gridspec import SubplotSpec, GridSpec
+from matplotlib.figure import Figure
+from matplotlib.image import AxesImage
+from matplotlib.patches import Patch
+from matplotlib.scale import ScaleBase
+from matplotlib.spines import Spines
+from matplotlib.table import Table
+from matplotlib.text import Text
+from matplotlib.transforms import Transform, Bbox
+
+from cycler import Cycler
+
+import numpy as np
+from numpy.typing import ArrayLike
+from typing import Any, Literal, TypeVar, overload
+from matplotlib.typing import ColorType
+
+_T = TypeVar("_T", bound=Artist)
+
+class _axis_method_wrapper:
+    attr_name: str
+    method_name: str
+    __doc__: str
+    def __init__(
+        self, attr_name: str, method_name: str, *, doc_sub: dict[str, str] | None = ...
+    ) -> None: ...
+    def __set_name__(self, owner: Any, name: str) -> None: ...
+
+class _AxesBase(martist.Artist):
+    name: str
+    patch: Patch
+    spines: Spines
+    fmt_xdata: Callable[[float], str] | None
+    fmt_ydata: Callable[[float], str] | None
+    xaxis: XAxis
+    yaxis: YAxis
+    bbox: Bbox
+    dataLim: Bbox
+    transAxes: Transform
+    transScale: Transform
+    transLimits: Transform
+    transData: Transform
+    ignore_existing_data_limits: bool
+    axison: bool
+    containers: list[Container]
+    callbacks: CallbackRegistry
+    child_axes: list[_AxesBase]
+    legend_: Legend | None
+    title: Text
+    _projection_init: Any
+
+    def __init__(
+        self,
+        fig: Figure,
+        *args: tuple[float, float, float, float] | Bbox | int,
+        facecolor: ColorType | None = ...,
+        frameon: bool = ...,
+        sharex: _AxesBase | None = ...,
+        sharey: _AxesBase | None = ...,
+        label: Any = ...,
+        xscale: str | ScaleBase | None = ...,
+        yscale: str | ScaleBase | None = ...,
+        box_aspect: float | None = ...,
+        forward_navigation_events: bool | Literal["auto"] = ...,
+        **kwargs
+    ) -> None: ...
+    def get_subplotspec(self) -> SubplotSpec | None: ...
+    def set_subplotspec(self, subplotspec: SubplotSpec) -> None: ...
+    def get_gridspec(self) -> GridSpec | None: ...
+    def set_figure(self, fig: Figure) -> None: ...
+    @property
+    def viewLim(self) -> Bbox: ...
+    def get_xaxis_transform(
+        self, which: Literal["grid", "tick1", "tick2"] = ...
+    ) -> Transform: ...
+    def get_xaxis_text1_transform(
+        self, pad_points: float
+    ) -> tuple[
+        Transform,
+        Literal["center", "top", "bottom", "baseline", "center_baseline"],
+        Literal["center", "left", "right"],
+    ]: ...
+    def get_xaxis_text2_transform(
+        self, pad_points
+    ) -> tuple[
+        Transform,
+        Literal["center", "top", "bottom", "baseline", "center_baseline"],
+        Literal["center", "left", "right"],
+    ]: ...
+    def get_yaxis_transform(
+        self, which: Literal["grid", "tick1", "tick2"] = ...
+    ) -> Transform: ...
+    def get_yaxis_text1_transform(
+        self, pad_points
+    ) -> tuple[
+        Transform,
+        Literal["center", "top", "bottom", "baseline", "center_baseline"],
+        Literal["center", "left", "right"],
+    ]: ...
+    def get_yaxis_text2_transform(
+        self, pad_points
+    ) -> tuple[
+        Transform,
+        Literal["center", "top", "bottom", "baseline", "center_baseline"],
+        Literal["center", "left", "right"],
+    ]: ...
+    def get_position(self, original: bool = ...) -> Bbox: ...
+    def set_position(
+        self,
+        pos: Bbox | tuple[float, float, float, float],
+        which: Literal["both", "active", "original"] = ...,
+    ) -> None: ...
+    def reset_position(self) -> None: ...
+    def set_axes_locator(
+        self, locator: Callable[[_AxesBase, RendererBase], Bbox]
+    ) -> None: ...
+    def get_axes_locator(self) -> Callable[[_AxesBase, RendererBase], Bbox]: ...
+    def sharex(self, other: _AxesBase) -> None: ...
+    def sharey(self, other: _AxesBase) -> None: ...
+    def clear(self) -> None: ...
+    def cla(self) -> None: ...
+
+    class ArtistList(Sequence[_T]):
+        def __init__(
+            self,
+            axes: _AxesBase,
+            prop_name: str,
+            valid_types: type | Iterable[type] | None = ...,
+            invalid_types: type | Iterable[type] | None = ...,
+        ) -> None: ...
+        def __len__(self) -> int: ...
+        def __iter__(self) -> Iterator[_T]: ...
+        @overload
+        def __getitem__(self, key: int) -> _T: ...
+        @overload
+        def __getitem__(self, key: slice) -> list[_T]: ...
+
+        @overload
+        def __add__(self, other: _AxesBase.ArtistList[_T]) -> list[_T]: ...
+        @overload
+        def __add__(self, other: list[Any]) -> list[Any]: ...
+        @overload
+        def __add__(self, other: tuple[Any]) -> tuple[Any]: ...
+
+        @overload
+        def __radd__(self, other: _AxesBase.ArtistList[_T]) -> list[_T]: ...
+        @overload
+        def __radd__(self, other: list[Any]) -> list[Any]: ...
+        @overload
+        def __radd__(self, other: tuple[Any]) -> tuple[Any]: ...
+
+    @property
+    def artists(self) -> _AxesBase.ArtistList[Artist]: ...
+    @property
+    def collections(self) -> _AxesBase.ArtistList[Collection]: ...
+    @property
+    def images(self) -> _AxesBase.ArtistList[AxesImage]: ...
+    @property
+    def lines(self) -> _AxesBase.ArtistList[Line2D]: ...
+    @property
+    def patches(self) -> _AxesBase.ArtistList[Patch]: ...
+    @property
+    def tables(self) -> _AxesBase.ArtistList[Table]: ...
+    @property
+    def texts(self) -> _AxesBase.ArtistList[Text]: ...
+    def get_facecolor(self) -> ColorType: ...
+    def set_facecolor(self, color: ColorType | None) -> None: ...
+    @overload
+    def set_prop_cycle(self, cycler: Cycler) -> None: ...
+    @overload
+    def set_prop_cycle(self, label: str, values: Iterable[Any]) -> None: ...
+    @overload
+    def set_prop_cycle(self, **kwargs: Iterable[Any]) -> None: ...
+    def get_aspect(self) -> float | Literal["auto"]: ...
+    def set_aspect(
+        self,
+        aspect: float | Literal["auto", "equal"],
+        adjustable: Literal["box", "datalim"] | None = ...,
+        anchor: str | tuple[float, float] | None = ...,
+        share: bool = ...,
+    ) -> None: ...
+    def get_adjustable(self) -> Literal["box", "datalim"]: ...
+    def set_adjustable(
+        self, adjustable: Literal["box", "datalim"], share: bool = ...
+    ) -> None: ...
+    def get_box_aspect(self) -> float | None: ...
+    def set_box_aspect(self, aspect: float | None = ...) -> None: ...
+    def get_anchor(self) -> str | tuple[float, float]: ...
+    def set_anchor(
+        self, anchor: str | tuple[float, float], share: bool = ...
+    ) -> None: ...
+    def get_data_ratio(self) -> float: ...
+    def apply_aspect(self, position: Bbox | None = ...) -> None: ...
+    @overload
+    def axis(
+        self,
+        arg: tuple[float, float, float, float] | bool | str | None = ...,
+        /,
+        *,
+        emit: bool = ...
+    ) -> tuple[float, float, float, float]: ...
+    @overload
+    def axis(
+        self,
+        *,
+        emit: bool = ...,
+        xmin: float | None = ...,
+        xmax: float | None = ...,
+        ymin: float | None = ...,
+        ymax: float | None = ...
+    ) -> tuple[float, float, float, float]: ...
+    def get_legend(self) -> Legend: ...
+    def get_images(self) -> list[AxesImage]: ...
+    def get_lines(self) -> list[Line2D]: ...
+    def get_xaxis(self) -> XAxis: ...
+    def get_yaxis(self) -> YAxis: ...
+    def has_data(self) -> bool: ...
+    def add_artist(self, a: Artist) -> Artist: ...
+    def add_child_axes(self, ax: _AxesBase) -> _AxesBase: ...
+    def add_collection(
+        self, collection: Collection, autolim: bool = ...
+    ) -> Collection: ...
+    def add_image(self, image: AxesImage) -> AxesImage: ...
+    def add_line(self, line: Line2D) -> Line2D: ...
+    def add_patch(self, p: Patch) -> Patch: ...
+    def add_table(self, tab: Table) -> Table: ...
+    def add_container(self, container: Container) -> Container: ...
+    def relim(self, visible_only: bool = ...) -> None: ...
+    def update_datalim(
+        self, xys: ArrayLike, updatex: bool = ..., updatey: bool = ...
+    ) -> None: ...
+    def in_axes(self, mouseevent: MouseEvent) -> bool: ...
+    def get_autoscale_on(self) -> bool: ...
+    def set_autoscale_on(self, b: bool) -> None: ...
+    @property
+    def use_sticky_edges(self) -> bool: ...
+    @use_sticky_edges.setter
+    def use_sticky_edges(self, b: bool) -> None: ...
+    def get_xmargin(self) -> float: ...
+    def get_ymargin(self) -> float: ...
+    def set_xmargin(self, m: float) -> None: ...
+    def set_ymargin(self, m: float) -> None: ...
+
+    # Probably could be made better with overloads
+    def margins(
+        self,
+        *margins: float,
+        x: float | None = ...,
+        y: float | None = ...,
+        tight: bool | None = ...
+    ) -> tuple[float, float] | None: ...
+    def set_rasterization_zorder(self, z: float | None) -> None: ...
+    def get_rasterization_zorder(self) -> float | None: ...
+    def autoscale(
+        self,
+        enable: bool = ...,
+        axis: Literal["both", "x", "y"] = ...,
+        tight: bool | None = ...,
+    ) -> None: ...
+    def autoscale_view(
+        self, tight: bool | None = ..., scalex: bool = ..., scaley: bool = ...
+    ) -> None: ...
+    def draw_artist(self, a: Artist) -> None: ...
+    def redraw_in_frame(self) -> None: ...
+    def get_frame_on(self) -> bool: ...
+    def set_frame_on(self, b: bool) -> None: ...
+    def get_axisbelow(self) -> bool | Literal["line"]: ...
+    def set_axisbelow(self, b: bool | Literal["line"]) -> None: ...
+    def grid(
+        self,
+        visible: bool | None = ...,
+        which: Literal["major", "minor", "both"] = ...,
+        axis: Literal["both", "x", "y"] = ...,
+        **kwargs
+    ) -> None: ...
+    def ticklabel_format(
+        self,
+        *,
+        axis: Literal["both", "x", "y"] = ...,
+        style: Literal["", "sci", "scientific", "plain"] | None = ...,
+        scilimits: tuple[int, int] | None = ...,
+        useOffset: bool | float | None = ...,
+        useLocale: bool | None = ...,
+        useMathText: bool | None = ...
+    ) -> None: ...
+    def locator_params(
+        self, axis: Literal["both", "x", "y"] = ..., tight: bool | None = ..., **kwargs
+    ) -> None: ...
+    def tick_params(self, axis: Literal["both", "x", "y"] = ..., **kwargs) -> None: ...
+    def set_axis_off(self) -> None: ...
+    def set_axis_on(self) -> None: ...
+    def get_xlabel(self) -> str: ...
+    def set_xlabel(
+        self,
+        xlabel: str,
+        fontdict: dict[str, Any] | None = ...,
+        labelpad: float | None = ...,
+        *,
+        loc: Literal["left", "center", "right"] | None = ...,
+        **kwargs
+    ) -> Text: ...
+    def invert_xaxis(self) -> None: ...
+    def get_xbound(self) -> tuple[float, float]: ...
+    def set_xbound(
+        self, lower: float | None = ..., upper: float | None = ...
+    ) -> None: ...
+    def get_xlim(self) -> tuple[float, float]: ...
+    def set_xlim(
+        self,
+        left: float | tuple[float, float] | None = ...,
+        right: float | None = ...,
+        *,
+        emit: bool = ...,
+        auto: bool | None = ...,
+        xmin: float | None = ...,
+        xmax: float | None = ...
+    ) -> tuple[float, float]: ...
+    def get_ylabel(self) -> str: ...
+    def set_ylabel(
+        self,
+        ylabel: str,
+        fontdict: dict[str, Any] | None = ...,
+        labelpad: float | None = ...,
+        *,
+        loc: Literal["bottom", "center", "top"] | None = ...,
+        **kwargs
+    ) -> Text: ...
+    def invert_yaxis(self) -> None: ...
+    def get_ybound(self) -> tuple[float, float]: ...
+    def set_ybound(
+        self, lower: float | None = ..., upper: float | None = ...
+    ) -> None: ...
+    def get_ylim(self) -> tuple[float, float]: ...
+    def set_ylim(
+        self,
+        bottom: float | tuple[float, float] | None = ...,
+        top: float | None = ...,
+        *,
+        emit: bool = ...,
+        auto: bool | None = ...,
+        ymin: float | None = ...,
+        ymax: float | None = ...
+    ) -> tuple[float, float]: ...
+    def format_xdata(self, x: float) -> str: ...
+    def format_ydata(self, y: float) -> str: ...
+    def format_coord(self, x: float, y: float) -> str: ...
+    def minorticks_on(self) -> None: ...
+    def minorticks_off(self) -> None: ...
+    def can_zoom(self) -> bool: ...
+    def can_pan(self) -> bool: ...
+    def get_navigate(self) -> bool: ...
+    def set_navigate(self, b: bool) -> None: ...
+    def get_forward_navigation_events(self) -> bool | Literal["auto"]: ...
+    def set_forward_navigation_events(self, forward: bool | Literal["auto"]) -> None: ...
+    def get_navigate_mode(self) -> Literal["PAN", "ZOOM"] | None: ...
+    def set_navigate_mode(self, b: Literal["PAN", "ZOOM"] | None) -> None: ...
+    def start_pan(self, x: float, y: float, button: MouseButton) -> None: ...
+    def end_pan(self) -> None: ...
+    def drag_pan(
+        self, button: MouseButton, key: str | None, x: float, y: float
+    ) -> None: ...
+    def get_children(self) -> list[Artist]: ...
+    def contains_point(self, point: tuple[int, int]) -> bool: ...
+    def get_default_bbox_extra_artists(self) -> list[Artist]: ...
+    def get_tightbbox(
+        self,
+        renderer: RendererBase | None = ...,
+        *,
+        call_axes_locator: bool = ...,
+        bbox_extra_artists: Sequence[Artist] | None = ...,
+        for_layout_only: bool = ...
+    ) -> Bbox | None: ...
+    def twinx(self) -> Axes: ...
+    def twiny(self) -> Axes: ...
+    def get_shared_x_axes(self) -> cbook.GrouperView: ...
+    def get_shared_y_axes(self) -> cbook.GrouperView: ...
+    def label_outer(self, remove_inner_ticks: bool = ...) -> None: ...
+
+    # The methods underneath this line are added via the `_axis_method_wrapper` class
+    # Initially they are set to an object, but that object uses `__set_name__` to override
+    # itself with a method modified from the Axis methods for the x or y Axis.
+    # As such, they are typed according to the resultant method rather than as that object.
+
+    def get_xgridlines(self) -> list[Line2D]: ...
+    def get_xticklines(self, minor: bool = ...) -> list[Line2D]: ...
+    def get_ygridlines(self) -> list[Line2D]: ...
+    def get_yticklines(self, minor: bool = ...) -> list[Line2D]: ...
+    def _sci(self, im: ScalarMappable) -> None: ...
+    def get_autoscalex_on(self) -> bool: ...
+    def get_autoscaley_on(self) -> bool: ...
+    def set_autoscalex_on(self, b: bool) -> None: ...
+    def set_autoscaley_on(self, b: bool) -> None: ...
+    def xaxis_inverted(self) -> bool: ...
+    def get_xscale(self) -> str: ...
+    def set_xscale(self, value: str | ScaleBase, **kwargs) -> None: ...
+    def get_xticks(self, *, minor: bool = ...) -> np.ndarray: ...
+    def set_xticks(
+        self,
+        ticks: ArrayLike,
+        labels: Iterable[str] | None = ...,
+        *,
+        minor: bool = ...,
+        **kwargs
+    ) -> list[Tick]: ...
+    def get_xmajorticklabels(self) -> list[Text]: ...
+    def get_xminorticklabels(self) -> list[Text]: ...
+    def get_xticklabels(
+        self, minor: bool = ..., which: Literal["major", "minor", "both"] | None = ...
+    ) -> list[Text]: ...
+    def set_xticklabels(
+        self,
+        labels: Iterable[str | Text],
+        *,
+        minor: bool = ...,
+        fontdict: dict[str, Any] | None = ...,
+        **kwargs
+    ) -> list[Text]: ...
+    def yaxis_inverted(self) -> bool: ...
+    def get_yscale(self) -> str: ...
+    def set_yscale(self, value: str | ScaleBase, **kwargs) -> None: ...
+    def get_yticks(self, *, minor: bool = ...) -> np.ndarray: ...
+    def set_yticks(
+        self,
+        ticks: ArrayLike,
+        labels: Iterable[str] | None = ...,
+        *,
+        minor: bool = ...,
+        **kwargs
+    ) -> list[Tick]: ...
+    def get_ymajorticklabels(self) -> list[Text]: ...
+    def get_yminorticklabels(self) -> list[Text]: ...
+    def get_yticklabels(
+        self, minor: bool = ..., which: Literal["major", "minor", "both"] | None = ...
+    ) -> list[Text]: ...
+    def set_yticklabels(
+        self,
+        labels: Iterable[str | Text],
+        *,
+        minor: bool = ...,
+        fontdict: dict[str, Any] | None = ...,
+        **kwargs
+    ) -> list[Text]: ...
+    def xaxis_date(self, tz: str | datetime.tzinfo | None = ...) -> None: ...
+    def yaxis_date(self, tz: str | datetime.tzinfo | None = ...) -> None: ...

rl/Lib/site-packages/matplotlib/axes/_secondary_axes.py

@@ -0,0 +1,321 @@
+import numbers
+
+import numpy as np
+
+from matplotlib import _api, _docstring, transforms
+import matplotlib.ticker as mticker
+from matplotlib.axes._base import _AxesBase, _TransformedBoundsLocator
+from matplotlib.axis import Axis
+from matplotlib.transforms import Transform
+
+
+class SecondaryAxis(_AxesBase):
+    """
+    General class to hold a Secondary_X/Yaxis.
+    """
+
+    def __init__(self, parent, orientation, location, functions, transform=None,
+                 **kwargs):
+        """
+        See `.secondary_xaxis` and `.secondary_yaxis` for the doc string.
+        While there is no need for this to be private, it should really be
+        called by those higher level functions.
+        """
+        _api.check_in_list(["x", "y"], orientation=orientation)
+        self._functions = functions
+        self._parent = parent
+        self._orientation = orientation
+        self._ticks_set = False
+
+        if self._orientation == 'x':
+            super().__init__(self._parent.figure, [0, 1., 1, 0.0001], **kwargs)
+            self._axis = self.xaxis
+            self._locstrings = ['top', 'bottom']
+            self._otherstrings = ['left', 'right']
+        else:  # 'y'
+            super().__init__(self._parent.figure, [0, 1., 0.0001, 1], **kwargs)
+            self._axis = self.yaxis
+            self._locstrings = ['right', 'left']
+            self._otherstrings = ['top', 'bottom']
+        self._parentscale = None
+        # this gets positioned w/o constrained_layout so exclude:
+
+        self.set_location(location, transform)
+        self.set_functions(functions)
+
+        # styling:
+        otheraxis = self.yaxis if self._orientation == 'x' else self.xaxis
+        otheraxis.set_major_locator(mticker.NullLocator())
+        otheraxis.set_ticks_position('none')
+
+        self.spines[self._otherstrings].set_visible(False)
+        self.spines[self._locstrings].set_visible(True)
+
+        if self._pos < 0.5:
+            # flip the location strings...
+            self._locstrings = self._locstrings[::-1]
+        self.set_alignment(self._locstrings[0])
+
+    def set_alignment(self, align):
+        """
+        Set if axes spine and labels are drawn at top or bottom (or left/right)
+        of the Axes.
+
+        Parameters
+        ----------
+        align : {'top', 'bottom', 'left', 'right'}
+            Either 'top' or 'bottom' for orientation='x' or
+            'left' or 'right' for orientation='y' axis.
+        """
+        _api.check_in_list(self._locstrings, align=align)
+        if align == self._locstrings[1]:  # Need to change the orientation.
+            self._locstrings = self._locstrings[::-1]
+        self.spines[self._locstrings[0]].set_visible(True)
+        self.spines[self._locstrings[1]].set_visible(False)
+        self._axis.set_ticks_position(align)
+        self._axis.set_label_position(align)
+
+    def set_location(self, location, transform=None):
+        """
+        Set the vertical or horizontal location of the axes in
+        parent-normalized coordinates.
+
+        Parameters
+        ----------
+        location : {'top', 'bottom', 'left', 'right'} or float
+            The position to put the secondary axis.  Strings can be 'top' or
+            'bottom' for orientation='x' and 'right' or 'left' for
+            orientation='y'. A float indicates the relative position on the
+            parent Axes to put the new Axes, 0.0 being the bottom (or left)
+            and 1.0 being the top (or right).
+
+        transform : `.Transform`, optional
+            Transform for the location to use. Defaults to
+            the parent's ``transAxes``, so locations are normally relative to
+            the parent axes.
+
+            .. versionadded:: 3.9
+        """
+
+        _api.check_isinstance((transforms.Transform, None), transform=transform)
+
+        # This puts the rectangle into figure-relative coordinates.
+        if isinstance(location, str):
+            _api.check_in_list(self._locstrings, location=location)
+            self._pos = 1. if location in ('top', 'right') else 0.
+        elif isinstance(location, numbers.Real):
+            self._pos = location
+        else:
+            raise ValueError(
+                f"location must be {self._locstrings[0]!r}, "
+                f"{self._locstrings[1]!r}, or a float, not {location!r}")
+
+        self._loc = location
+
+        if self._orientation == 'x':
+            # An x-secondary axes is like an inset axes from x = 0 to x = 1 and
+            # from y = pos to y = pos + eps, in the parent's transAxes coords.
+            bounds = [0, self._pos, 1., 1e-10]
+
+            # If a transformation is provided, use its y component rather than
+            # the parent's transAxes. This can be used to place axes in the data
+            # coords, for instance.
+            if transform is not None:
+                transform = transforms.blended_transform_factory(
+                    self._parent.transAxes, transform)
+        else:  # 'y'
+            bounds = [self._pos, 0, 1e-10, 1]
+            if transform is not None:
+                transform = transforms.blended_transform_factory(
+                    transform, self._parent.transAxes)  # Use provided x axis
+
+        # If no transform is provided, use the parent's transAxes
+        if transform is None:
+            transform = self._parent.transAxes
+
+        # this locator lets the axes move in the parent axes coordinates.
+        # so it never needs to know where the parent is explicitly in
+        # figure coordinates.
+        # it gets called in ax.apply_aspect() (of all places)
+        self.set_axes_locator(_TransformedBoundsLocator(bounds, transform))
+
+    def apply_aspect(self, position=None):
+        # docstring inherited.
+        self._set_lims()
+        super().apply_aspect(position)
+
+    @_docstring.copy(Axis.set_ticks)
+    def set_ticks(self, ticks, labels=None, *, minor=False, **kwargs):
+        ret = self._axis.set_ticks(ticks, labels, minor=minor, **kwargs)
+        self.stale = True
+        self._ticks_set = True
+        return ret
+
+    def set_functions(self, functions):
+        """
+        Set how the secondary axis converts limits from the parent Axes.
+
+        Parameters
+        ----------
+        functions : 2-tuple of func, or `Transform` with an inverse.
+            Transform between the parent axis values and the secondary axis
+            values.
+
+            If supplied as a 2-tuple of functions, the first function is
+            the forward transform function and the second is the inverse
+            transform.
+
+            If a transform is supplied, then the transform must have an
+            inverse.
+        """
+
+        if (isinstance(functions, tuple) and len(functions) == 2 and
+                callable(functions[0]) and callable(functions[1])):
+            # make an arbitrary convert from a two-tuple of functions
+            # forward and inverse.
+            self._functions = functions
+        elif isinstance(functions, Transform):
+            self._functions = (
+                 functions.transform,
+                 lambda x: functions.inverted().transform(x)
+            )
+        elif functions is None:
+            self._functions = (lambda x: x, lambda x: x)
+        else:
+            raise ValueError('functions argument of secondary Axes '
+                             'must be a two-tuple of callable functions '
+                             'with the first function being the transform '
+                             'and the second being the inverse')
+        self._set_scale()
+
+    def draw(self, renderer):
+        """
+        Draw the secondary Axes.
+
+        Consults the parent Axes for its limits and converts them
+        using the converter specified by
+        `~.axes._secondary_axes.set_functions` (or *functions*
+        parameter when Axes initialized.)
+        """
+        self._set_lims()
+        # this sets the scale in case the parent has set its scale.
+        self._set_scale()
+        super().draw(renderer)
+
+    def _set_scale(self):
+        """
+        Check if parent has set its scale
+        """
+
+        if self._orientation == 'x':
+            pscale = self._parent.xaxis.get_scale()
+            set_scale = self.set_xscale
+        else:  # 'y'
+            pscale = self._parent.yaxis.get_scale()
+            set_scale = self.set_yscale
+        if pscale == self._parentscale:
+            return
+
+        if self._ticks_set:
+            ticks = self._axis.get_ticklocs()
+
+        # need to invert the roles here for the ticks to line up.
+        set_scale('functionlog' if pscale == 'log' else 'function',
+                  functions=self._functions[::-1])
+
+        # OK, set_scale sets the locators, but if we've called
+        # axsecond.set_ticks, we want to keep those.
+        if self._ticks_set:
+            self._axis.set_major_locator(mticker.FixedLocator(ticks))
+
+        # If the parent scale doesn't change, we can skip this next time.
+        self._parentscale = pscale
+
+    def _set_lims(self):
+        """
+        Set the limits based on parent limits and the convert method
+        between the parent and this secondary Axes.
+        """
+        if self._orientation == 'x':
+            lims = self._parent.get_xlim()
+            set_lim = self.set_xlim
+        else:  # 'y'
+            lims = self._parent.get_ylim()
+            set_lim = self.set_ylim
+        order = lims[0] < lims[1]
+        lims = self._functions[0](np.array(lims))
+        neworder = lims[0] < lims[1]
+        if neworder != order:
+            # Flip because the transform will take care of the flipping.
+            lims = lims[::-1]
+        set_lim(lims)
+
+    def set_aspect(self, *args, **kwargs):
+        """
+        Secondary Axes cannot set the aspect ratio, so calling this just
+        sets a warning.
+        """
+        _api.warn_external("Secondary Axes can't set the aspect ratio")
+
+    def set_color(self, color):
+        """
+        Change the color of the secondary Axes and all decorators.
+
+        Parameters
+        ----------
+        color : :mpltype:`color`
+        """
+        axis = self._axis_map[self._orientation]
+        axis.set_tick_params(colors=color)
+        for spine in self.spines.values():
+            if spine.axis is axis:
+                spine.set_color(color)
+        axis.label.set_color(color)
+
+
+_secax_docstring = '''
+Warnings
+--------
+This method is experimental as of 3.1, and the API may change.
+
+Parameters
+----------
+location : {'top', 'bottom', 'left', 'right'} or float
+    The position to put the secondary axis.  Strings can be 'top' or
+    'bottom' for orientation='x' and 'right' or 'left' for
+    orientation='y'. A float indicates the relative position on the
+    parent Axes to put the new Axes, 0.0 being the bottom (or left)
+    and 1.0 being the top (or right).
+
+functions : 2-tuple of func, or Transform with an inverse
+
+    If a 2-tuple of functions, the user specifies the transform
+    function and its inverse.  i.e.
+    ``functions=(lambda x: 2 / x, lambda x: 2 / x)`` would be an
+    reciprocal transform with a factor of 2. Both functions must accept
+    numpy arrays as input.
+
+    The user can also directly supply a subclass of
+    `.transforms.Transform` so long as it has an inverse.
+
+    See :doc:`/gallery/subplots_axes_and_figures/secondary_axis`
+    for examples of making these conversions.
+
+transform : `.Transform`, optional
+    If specified, *location* will be
+    placed relative to this transform (in the direction of the axis)
+    rather than the parent's axis. i.e. a secondary x-axis will
+    use the provided y transform and the x transform of the parent.
+
+    .. versionadded:: 3.9
+
+Returns
+-------
+ax : axes._secondary_axes.SecondaryAxis
+
+Other Parameters
+----------------
+**kwargs : `~matplotlib.axes.Axes` properties.
+    Other miscellaneous Axes parameters.
+'''
+_docstring.interpd.update(_secax_docstring=_secax_docstring)

rl/Lib/site-packages/matplotlib/axes/_secondary_axes.pyi

@@ -0,0 +1,45 @@
+from matplotlib.axes._base import _AxesBase
+from matplotlib.axis import Tick
+
+from matplotlib.transforms import Transform
+
+from collections.abc import Callable, Iterable
+from typing import Literal
+from numpy.typing import ArrayLike
+from matplotlib.typing import ColorType
+
+class SecondaryAxis(_AxesBase):
+    def __init__(
+        self,
+        parent: _AxesBase,
+        orientation: Literal["x", "y"],
+        location: Literal["top", "bottom", "right", "left"] | float,
+        functions: tuple[
+            Callable[[ArrayLike], ArrayLike], Callable[[ArrayLike], ArrayLike]
+        ]
+        | Transform,
+        transform: Transform | None = ...,
+        **kwargs
+    ) -> None: ...
+    def set_alignment(
+        self, align: Literal["top", "bottom", "right", "left"]
+    ) -> None: ...
+    def set_location(
+        self,
+        location: Literal["top", "bottom", "right", "left"] | float,
+        transform: Transform | None = ...
+    ) -> None: ...
+    def set_ticks(
+        self,
+        ticks: ArrayLike,
+        labels: Iterable[str] | None = ...,
+        *,
+        minor: bool = ...,
+        **kwargs
+    ) -> list[Tick]: ...
+    def set_functions(
+        self,
+        functions: tuple[Callable[[ArrayLike], ArrayLike], Callable[[ArrayLike], ArrayLike]] | Transform,
+    ) -> None: ...
+    def set_aspect(self, *args, **kwargs) -> None: ...
+    def set_color(self, color: ColorType) -> None: ...