"""
This type stub file was generated by pyright.
"""

import datetime
import PIL.Image
import numpy as np
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 BrokenBarHCollection, Collection, EventCollection, LineCollection, PathCollection, PolyCollection, 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
from matplotlib.mlab import GaussianKDE
from matplotlib.patches import FancyArrow, Polygon, Rectangle, StepPatch, Wedge
from matplotlib.quiver import Barbs, Quiver, QuiverKey
from matplotlib.text import Annotation, Text
from matplotlib.transforms import Bbox, Transform
from collections.abc import Callable, Sequence
from typing import Any, Literal, overload
from numpy.typing import ArrayLike
from matplotlib.typing import ColorType, LineStyleType, MarkerType

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: Sequence[Artist | tuple[Artist, ...]], labels: Sequence[str], **kwargs) -> Legend:
        ...
    
    @overload
    def legend(self, *, handles: Sequence[Artist | tuple[Artist, ...]], **kwargs) -> Legend:
        ...
    
    @overload
    def legend(self, labels: Sequence[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 = ..., **kwargs) -> SecondaryAxis:
        ...
    
    def secondary_yaxis(self, location: Literal["left", "right"] | float, *, functions: tuple[Callable[[ArrayLike], ArrayLike], Callable[[ArrayLike], ArrayLike]] | 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:
        ...
    
    def axline(self, xy1: tuple[float, float], xy2: tuple[float, float] | None = ..., *, slope: float | None = ..., **kwargs) -> Line2D:
        ...
    
    def axhspan(self, ymin: float, ymax: float, xmin: float = ..., xmax: float = ..., **kwargs) -> Polygon:
        ...
    
    def axvspan(self, xmin: float, xmax: float, ymin: float = ..., ymax: float = ..., **kwargs) -> Polygon:
        ...
    
    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) -> BrokenBarHCollection:
        ...
    
    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:
        ...
    
    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 = ..., 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 = ..., *, 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 = ...) -> dict[str, Any]:
        ...
    
    def scatter(self, x: float | ArrayLike, y: float | ArrayLike, s: float | ArrayLike | None = ..., c: 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 = ..., *, 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 = ...) -> dict[str, Collection]:
        ...
    
    table = ...
    stackplot = ...
    streamplot = ...
    tricontour = ...
    tricontourf = ...
    tripcolor = ...
    triplot = ...