diff --git "a/llava_next/lib/python3.10/site-packages/matplotlib/pyplot.py" "b/llava_next/lib/python3.10/site-packages/matplotlib/pyplot.py" new file mode 100644--- /dev/null +++ "b/llava_next/lib/python3.10/site-packages/matplotlib/pyplot.py" @@ -0,0 +1,4597 @@ +# Note: The first part of this file can be modified in place, but the latter +# part is autogenerated by the boilerplate.py script. + +""" +`matplotlib.pyplot` is a state-based interface to matplotlib. It provides +an implicit, MATLAB-like, way of plotting. It also opens figures on your +screen, and acts as the figure GUI manager. + +pyplot is mainly intended for interactive plots and simple cases of +programmatic plot generation:: + + import numpy as np + import matplotlib.pyplot as plt + + x = np.arange(0, 5, 0.1) + y = np.sin(x) + plt.plot(x, y) + +The explicit object-oriented API is recommended for complex plots, though +pyplot is still usually used to create the figure and often the Axes in the +figure. See `.pyplot.figure`, `.pyplot.subplots`, and +`.pyplot.subplot_mosaic` to create figures, and +:doc:`Axes API ` for the plotting methods on an Axes:: + + import numpy as np + import matplotlib.pyplot as plt + + x = np.arange(0, 5, 0.1) + y = np.sin(x) + fig, ax = plt.subplots() + ax.plot(x, y) + + +See :ref:`api_interfaces` for an explanation of the tradeoffs between the +implicit and explicit interfaces. +""" + +# fmt: off + +from __future__ import annotations + +from contextlib import AbstractContextManager, ExitStack +from enum import Enum +import functools +import importlib +import inspect +import logging +import sys +import threading +import time +from typing import TYPE_CHECKING, cast, overload + +from cycler import cycler # noqa: F401 +import matplotlib +import matplotlib.colorbar +import matplotlib.image +from matplotlib import _api +from matplotlib import ( # noqa: F401 Re-exported for typing. + cm as cm, get_backend as get_backend, rcParams as rcParams, style as style) +from matplotlib import _pylab_helpers +from matplotlib import interactive # noqa: F401 +from matplotlib import cbook +from matplotlib import _docstring +from matplotlib.backend_bases import ( + FigureCanvasBase, FigureManagerBase, MouseButton) +from matplotlib.figure import Figure, FigureBase, figaspect +from matplotlib.gridspec import GridSpec, SubplotSpec +from matplotlib import rcsetup, rcParamsDefault, rcParamsOrig +from matplotlib.artist import Artist +from matplotlib.axes import Axes +from matplotlib.axes import Subplot # noqa: F401 +from matplotlib.backends import BackendFilter, backend_registry +from matplotlib.projections import PolarAxes +from matplotlib import mlab # for detrend_none, window_hanning +from matplotlib.scale import get_scale_names # noqa: F401 + +from matplotlib.cm import _colormaps +from matplotlib.colors import _color_sequences, Colormap + +import numpy as np + +if TYPE_CHECKING: + from collections.abc import Callable, Hashable, Iterable, Sequence + import datetime + import pathlib + import os + from typing import Any, BinaryIO, Literal, TypeVar + from typing_extensions import ParamSpec + + import PIL.Image + from numpy.typing import ArrayLike + + import matplotlib.axes + import matplotlib.artist + import matplotlib.backend_bases + from matplotlib.axis import Tick + from matplotlib.axes._base import _AxesBase + from matplotlib.backend_bases import RendererBase, Event + from matplotlib.cm import ScalarMappable + from matplotlib.contour import ContourSet, QuadContourSet + from matplotlib.collections import ( + Collection, + LineCollection, + PolyCollection, + PathCollection, + EventCollection, + QuadMesh, + ) + from matplotlib.colorbar import Colorbar + from matplotlib.container import ( + BarContainer, + ErrorbarContainer, + StemContainer, + ) + from matplotlib.figure import SubFigure + from matplotlib.legend import Legend + from matplotlib.mlab import GaussianKDE + from matplotlib.image import AxesImage, FigureImage + from matplotlib.patches import FancyArrow, StepPatch, Wedge + from matplotlib.quiver import Barbs, Quiver, QuiverKey + from matplotlib.scale import ScaleBase + from matplotlib.transforms import Transform, Bbox + from matplotlib.typing import ColorType, LineStyleType, MarkerType, HashableList + from matplotlib.widgets import SubplotTool + + _P = ParamSpec('_P') + _R = TypeVar('_R') + _T = TypeVar('_T') + + +# We may not need the following imports here: +from matplotlib.colors import Normalize +from matplotlib.lines import Line2D, AxLine +from matplotlib.text import Text, Annotation +from matplotlib.patches import Arrow, Circle, Rectangle # noqa: F401 +from matplotlib.patches import Polygon +from matplotlib.widgets import Button, Slider, Widget # noqa: F401 + +from .ticker import ( # noqa: F401 + TickHelper, Formatter, FixedFormatter, NullFormatter, FuncFormatter, + FormatStrFormatter, ScalarFormatter, LogFormatter, LogFormatterExponent, + LogFormatterMathtext, Locator, IndexLocator, FixedLocator, NullLocator, + LinearLocator, LogLocator, AutoLocator, MultipleLocator, MaxNLocator) + +_log = logging.getLogger(__name__) + + +# Explicit rename instead of import-as for typing's sake. +colormaps = _colormaps +color_sequences = _color_sequences + + +@overload +def _copy_docstring_and_deprecators( + method: Any, + func: Literal[None] = None +) -> Callable[[Callable[_P, _R]], Callable[_P, _R]]: ... + + +@overload +def _copy_docstring_and_deprecators( + method: Any, func: Callable[_P, _R]) -> Callable[_P, _R]: ... + + +def _copy_docstring_and_deprecators( + method: Any, + func: Callable[_P, _R] | None = None +) -> Callable[[Callable[_P, _R]], Callable[_P, _R]] | Callable[_P, _R]: + if func is None: + return cast('Callable[[Callable[_P, _R]], Callable[_P, _R]]', + functools.partial(_copy_docstring_and_deprecators, method)) + decorators: list[Callable[[Callable[_P, _R]], Callable[_P, _R]]] = [ + _docstring.copy(method) + ] + # Check whether the definition of *method* includes @_api.rename_parameter + # or @_api.make_keyword_only decorators; if so, propagate them to the + # pyplot wrapper as well. + while hasattr(method, "__wrapped__"): + potential_decorator = _api.deprecation.DECORATORS.get(method) + if potential_decorator: + decorators.append(potential_decorator) + method = method.__wrapped__ + for decorator in decorators[::-1]: + func = decorator(func) + _add_pyplot_note(func, method) + return func + + +_NO_PYPLOT_NOTE = [ + 'FigureBase._gci', # wrapped_func is private + '_AxesBase._sci', # wrapped_func is private + 'Artist.findobj', # not a standard pyplot wrapper because it does not operate + # on the current Figure / Axes. Explanation of relation would + # be more complex and is not too important. +] + + +def _add_pyplot_note(func, wrapped_func): + """ + Add a note to the docstring of *func* that it is a pyplot wrapper. + + The note is added to the "Notes" section of the docstring. If that does + not exist, a "Notes" section is created. In numpydoc, the "Notes" + section is the third last possible section, only potentially followed by + "References" and "Examples". + """ + if not func.__doc__: + return # nothing to do + + qualname = wrapped_func.__qualname__ + if qualname in _NO_PYPLOT_NOTE: + return + + wrapped_func_is_method = True + if "." not in qualname: + # method qualnames are prefixed by the class and ".", e.g. "Axes.plot" + wrapped_func_is_method = False + link = f"{wrapped_func.__module__}.{qualname}" + elif qualname.startswith("Axes."): # e.g. "Axes.plot" + link = ".axes." + qualname + elif qualname.startswith("_AxesBase."): # e.g. "_AxesBase.set_xlabel" + link = ".axes.Axes" + qualname[9:] + elif qualname.startswith("Figure."): # e.g. "Figure.figimage" + link = "." + qualname + elif qualname.startswith("FigureBase."): # e.g. "FigureBase.gca" + link = ".Figure" + qualname[10:] + elif qualname.startswith("FigureCanvasBase."): # "FigureBaseCanvas.mpl_connect" + link = "." + qualname + else: + raise RuntimeError(f"Wrapped method from unexpected class: {qualname}") + + if wrapped_func_is_method: + message = f"This is the :ref:`pyplot wrapper ` for `{link}`." + else: + message = f"This is equivalent to `{link}`." + + # Find the correct insert position: + # - either we already have a "Notes" section into which we can insert + # - or we create one before the next present section. Note that in numpydoc, the + # "Notes" section is the third last possible section, only potentially followed + # by "References" and "Examples". + # - or we append a new "Notes" section at the end. + doc = inspect.cleandoc(func.__doc__) + if "\nNotes\n-----" in doc: + before, after = doc.split("\nNotes\n-----", 1) + elif (index := doc.find("\nReferences\n----------")) != -1: + before, after = doc[:index], doc[index:] + elif (index := doc.find("\nExamples\n--------")) != -1: + before, after = doc[:index], doc[index:] + else: + # No "Notes", "References", or "Examples" --> append to the end. + before = doc + "\n" + after = "" + + func.__doc__ = f"{before}\nNotes\n-----\n\n.. note::\n\n {message}\n{after}" + + +## Global ## + + +# The state controlled by {,un}install_repl_displayhook(). +_ReplDisplayHook = Enum("_ReplDisplayHook", ["NONE", "PLAIN", "IPYTHON"]) +_REPL_DISPLAYHOOK = _ReplDisplayHook.NONE + + +def _draw_all_if_interactive() -> None: + if matplotlib.is_interactive(): + draw_all() + + +def install_repl_displayhook() -> None: + """ + Connect to the display hook of the current shell. + + The display hook gets called when the read-evaluate-print-loop (REPL) of + the shell has finished the execution of a command. We use this callback + to be able to automatically update a figure in interactive mode. + + This works both with IPython and with vanilla python shells. + """ + global _REPL_DISPLAYHOOK + + if _REPL_DISPLAYHOOK is _ReplDisplayHook.IPYTHON: + return + + # See if we have IPython hooks around, if so use them. + # Use ``sys.modules.get(name)`` rather than ``name in sys.modules`` as + # entries can also have been explicitly set to None. + mod_ipython = sys.modules.get("IPython") + if not mod_ipython: + _REPL_DISPLAYHOOK = _ReplDisplayHook.PLAIN + return + ip = mod_ipython.get_ipython() + if not ip: + _REPL_DISPLAYHOOK = _ReplDisplayHook.PLAIN + return + + ip.events.register("post_execute", _draw_all_if_interactive) + _REPL_DISPLAYHOOK = _ReplDisplayHook.IPYTHON + + if mod_ipython.version_info[:2] < (8, 24): + # Use of backend2gui is not needed for IPython >= 8.24 as that functionality + # has been moved to Matplotlib. + # This code can be removed when Python 3.12, the latest version supported by + # IPython < 8.24, reaches end-of-life in late 2028. + from IPython.core.pylabtools import backend2gui + ipython_gui_name = backend2gui.get(get_backend()) + else: + _, ipython_gui_name = backend_registry.resolve_backend(get_backend()) + # trigger IPython's eventloop integration, if available + if ipython_gui_name: + ip.enable_gui(ipython_gui_name) + + +def uninstall_repl_displayhook() -> None: + """Disconnect from the display hook of the current shell.""" + global _REPL_DISPLAYHOOK + if _REPL_DISPLAYHOOK is _ReplDisplayHook.IPYTHON: + from IPython import get_ipython + ip = get_ipython() + ip.events.unregister("post_execute", _draw_all_if_interactive) + _REPL_DISPLAYHOOK = _ReplDisplayHook.NONE + + +draw_all = _pylab_helpers.Gcf.draw_all + + +# Ensure this appears in the pyplot docs. +@_copy_docstring_and_deprecators(matplotlib.set_loglevel) +def set_loglevel(*args, **kwargs) -> None: + return matplotlib.set_loglevel(*args, **kwargs) + + +@_copy_docstring_and_deprecators(Artist.findobj) +def findobj( + o: Artist | None = None, + match: Callable[[Artist], bool] | type[Artist] | None = None, + include_self: bool = True +) -> list[Artist]: + if o is None: + o = gcf() + return o.findobj(match, include_self=include_self) + + +_backend_mod: type[matplotlib.backend_bases._Backend] | None = None + + +def _get_backend_mod() -> type[matplotlib.backend_bases._Backend]: + """ + Ensure that a backend is selected and return it. + + This is currently private, but may be made public in the future. + """ + if _backend_mod is None: + # Use rcParams._get("backend") to avoid going through the fallback + # logic (which will (re)import pyplot and then call switch_backend if + # we need to resolve the auto sentinel) + switch_backend(rcParams._get("backend")) + return cast(type[matplotlib.backend_bases._Backend], _backend_mod) + + +def switch_backend(newbackend: str) -> None: + """ + Set the pyplot backend. + + Switching to an interactive backend is possible only if no event loop for + another interactive backend has started. Switching to and from + non-interactive backends is always possible. + + If the new backend is different than the current backend then all open + Figures will be closed via ``plt.close('all')``. + + Parameters + ---------- + newbackend : str + The case-insensitive name of the backend to use. + + """ + global _backend_mod + # make sure the init is pulled up so we can assign to it later + import matplotlib.backends + + if newbackend is rcsetup._auto_backend_sentinel: + current_framework = cbook._get_running_interactive_framework() + + if (current_framework and + (backend := backend_registry.backend_for_gui_framework( + current_framework))): + candidates = [backend] + else: + candidates = [] + candidates += [ + "macosx", "qtagg", "gtk4agg", "gtk3agg", "tkagg", "wxagg"] + + # Don't try to fallback on the cairo-based backends as they each have + # an additional dependency (pycairo) over the agg-based backend, and + # are of worse quality. + for candidate in candidates: + try: + switch_backend(candidate) + except ImportError: + continue + else: + rcParamsOrig['backend'] = candidate + return + else: + # Switching to Agg should always succeed; if it doesn't, let the + # exception propagate out. + switch_backend("agg") + rcParamsOrig["backend"] = "agg" + return + # have to escape the switch on access logic + old_backend = dict.__getitem__(rcParams, 'backend') + + module = backend_registry.load_backend_module(newbackend) + canvas_class = module.FigureCanvas + + required_framework = canvas_class.required_interactive_framework + if required_framework is not None: + current_framework = cbook._get_running_interactive_framework() + if (current_framework and required_framework + and current_framework != required_framework): + raise ImportError( + "Cannot load backend {!r} which requires the {!r} interactive " + "framework, as {!r} is currently running".format( + newbackend, required_framework, current_framework)) + + # Load the new_figure_manager() and show() functions from the backend. + + # Classically, backends can directly export these functions. This should + # keep working for backcompat. + new_figure_manager = getattr(module, "new_figure_manager", None) + show = getattr(module, "show", None) + + # In that classical approach, backends are implemented as modules, but + # "inherit" default method implementations from backend_bases._Backend. + # This is achieved by creating a "class" that inherits from + # backend_bases._Backend and whose body is filled with the module globals. + class backend_mod(matplotlib.backend_bases._Backend): + locals().update(vars(module)) + + # However, the newer approach for defining new_figure_manager and + # show is to derive them from canvas methods. In that case, also + # update backend_mod accordingly; also, per-backend customization of + # draw_if_interactive is disabled. + if new_figure_manager is None: + + def new_figure_manager_given_figure(num, figure): + return canvas_class.new_manager(figure, num) + + def new_figure_manager(num, *args, FigureClass=Figure, **kwargs): + fig = FigureClass(*args, **kwargs) + return new_figure_manager_given_figure(num, fig) + + def draw_if_interactive() -> None: + if matplotlib.is_interactive(): + manager = _pylab_helpers.Gcf.get_active() + if manager: + manager.canvas.draw_idle() + + backend_mod.new_figure_manager_given_figure = ( # type: ignore[method-assign] + new_figure_manager_given_figure) + backend_mod.new_figure_manager = ( # type: ignore[method-assign] + new_figure_manager) + backend_mod.draw_if_interactive = ( # type: ignore[method-assign] + draw_if_interactive) + + # If the manager explicitly overrides pyplot_show, use it even if a global + # show is already present, as the latter may be here for backcompat. + manager_class = getattr(canvas_class, "manager_class", None) + # We can't compare directly manager_class.pyplot_show and FMB.pyplot_show because + # pyplot_show is a classmethod so the above constructs are bound classmethods, and + # thus always different (being bound to different classes). We also have to use + # getattr_static instead of vars as manager_class could have no __dict__. + manager_pyplot_show = inspect.getattr_static(manager_class, "pyplot_show", None) + base_pyplot_show = inspect.getattr_static(FigureManagerBase, "pyplot_show", None) + if (show is None + or (manager_pyplot_show is not None + and manager_pyplot_show != base_pyplot_show)): + if not manager_pyplot_show: + raise ValueError( + f"Backend {newbackend} defines neither FigureCanvas.manager_class nor " + f"a toplevel show function") + _pyplot_show = cast('Any', manager_class).pyplot_show + backend_mod.show = _pyplot_show # type: ignore[method-assign] + + _log.debug("Loaded backend %s version %s.", + newbackend, backend_mod.backend_version) + + if newbackend in ("ipympl", "widget"): + # ipympl < 0.9.4 expects rcParams["backend"] to be the fully-qualified backend + # name "module://ipympl.backend_nbagg" not short names "ipympl" or "widget". + import importlib.metadata as im + from matplotlib import _parse_to_version_info # type: ignore[attr-defined] + try: + module_version = im.version("ipympl") + if _parse_to_version_info(module_version) < (0, 9, 4): + newbackend = "module://ipympl.backend_nbagg" + except im.PackageNotFoundError: + pass + + rcParams['backend'] = rcParamsDefault['backend'] = newbackend + _backend_mod = backend_mod + for func_name in ["new_figure_manager", "draw_if_interactive", "show"]: + globals()[func_name].__signature__ = inspect.signature( + getattr(backend_mod, func_name)) + + # Need to keep a global reference to the backend for compatibility reasons. + # See https://github.com/matplotlib/matplotlib/issues/6092 + matplotlib.backends.backend = newbackend # type: ignore[attr-defined] + + if not cbook._str_equal(old_backend, newbackend): + if get_fignums(): + _api.warn_deprecated("3.8", message=( + "Auto-close()ing of figures upon backend switching is deprecated since " + "%(since)s and will be removed %(removal)s. To suppress this warning, " + "explicitly call plt.close('all') first.")) + close("all") + + # Make sure the repl display hook is installed in case we become interactive. + install_repl_displayhook() + + +def _warn_if_gui_out_of_main_thread() -> None: + warn = False + canvas_class = cast(type[FigureCanvasBase], _get_backend_mod().FigureCanvas) + if canvas_class.required_interactive_framework: + if hasattr(threading, 'get_native_id'): + # This compares native thread ids because even if Python-level + # Thread objects match, the underlying OS thread (which is what + # really matters) may be different on Python implementations with + # green threads. + if threading.get_native_id() != threading.main_thread().native_id: + warn = True + else: + # Fall back to Python-level Thread if native IDs are unavailable, + # mainly for PyPy. + if threading.current_thread() is not threading.main_thread(): + warn = True + if warn: + _api.warn_external( + "Starting a Matplotlib GUI outside of the main thread will likely " + "fail.") + + +# This function's signature is rewritten upon backend-load by switch_backend. +def new_figure_manager(*args, **kwargs): + """Create a new figure manager instance.""" + _warn_if_gui_out_of_main_thread() + return _get_backend_mod().new_figure_manager(*args, **kwargs) + + +# This function's signature is rewritten upon backend-load by switch_backend. +def draw_if_interactive(*args, **kwargs): + """ + Redraw the current figure if in interactive mode. + + .. warning:: + + End users will typically not have to call this function because the + the interactive mode takes care of this. + """ + return _get_backend_mod().draw_if_interactive(*args, **kwargs) + + +# This function's signature is rewritten upon backend-load by switch_backend. +def show(*args, **kwargs) -> None: + """ + Display all open figures. + + Parameters + ---------- + block : bool, optional + Whether to wait for all figures to be closed before returning. + + If `True` block and run the GUI main loop until all figure windows + are closed. + + If `False` ensure that all figure windows are displayed and return + immediately. In this case, you are responsible for ensuring + that the event loop is running to have responsive figures. + + Defaults to True in non-interactive mode and to False in interactive + mode (see `.pyplot.isinteractive`). + + See Also + -------- + ion : Enable interactive mode, which shows / updates the figure after + every plotting command, so that calling ``show()`` is not necessary. + ioff : Disable interactive mode. + savefig : Save the figure to an image file instead of showing it on screen. + + Notes + ----- + **Saving figures to file and showing a window at the same time** + + If you want an image file as well as a user interface window, use + `.pyplot.savefig` before `.pyplot.show`. At the end of (a blocking) + ``show()`` the figure is closed and thus unregistered from pyplot. Calling + `.pyplot.savefig` afterwards would save a new and thus empty figure. This + limitation of command order does not apply if the show is non-blocking or + if you keep a reference to the figure and use `.Figure.savefig`. + + **Auto-show in jupyter notebooks** + + The jupyter backends (activated via ``%matplotlib inline``, + ``%matplotlib notebook``, or ``%matplotlib widget``), call ``show()`` at + the end of every cell by default. Thus, you usually don't have to call it + explicitly there. + """ + _warn_if_gui_out_of_main_thread() + return _get_backend_mod().show(*args, **kwargs) + + +def isinteractive() -> bool: + """ + Return whether plots are updated after every plotting command. + + The interactive mode is mainly useful if you build plots from the command + line and want to see the effect of each command while you are building the + figure. + + In interactive mode: + + - newly created figures will be shown immediately; + - figures will automatically redraw on change; + - `.pyplot.show` will not block by default. + + In non-interactive mode: + + - newly created figures and changes to figures will not be reflected until + explicitly asked to be; + - `.pyplot.show` will block by default. + + See Also + -------- + ion : Enable interactive mode. + ioff : Disable interactive mode. + show : Show all figures (and maybe block). + pause : Show all figures, and block for a time. + """ + return matplotlib.is_interactive() + + +# Note: The return type of ioff being AbstractContextManager +# instead of ExitStack is deliberate. +# See https://github.com/matplotlib/matplotlib/issues/27659 +# and https://github.com/matplotlib/matplotlib/pull/27667 for more info. +def ioff() -> AbstractContextManager: + """ + Disable interactive mode. + + See `.pyplot.isinteractive` for more details. + + See Also + -------- + ion : Enable interactive mode. + isinteractive : Whether interactive mode is enabled. + show : Show all figures (and maybe block). + pause : Show all figures, and block for a time. + + Notes + ----- + For a temporary change, this can be used as a context manager:: + + # if interactive mode is on + # then figures will be shown on creation + plt.ion() + # This figure will be shown immediately + fig = plt.figure() + + with plt.ioff(): + # interactive mode will be off + # figures will not automatically be shown + fig2 = plt.figure() + # ... + + To enable optional usage as a context manager, this function returns a + context manager object, which is not intended to be stored or + accessed by the user. + """ + stack = ExitStack() + stack.callback(ion if isinteractive() else ioff) + matplotlib.interactive(False) + uninstall_repl_displayhook() + return stack + + +# Note: The return type of ion being AbstractContextManager +# instead of ExitStack is deliberate. +# See https://github.com/matplotlib/matplotlib/issues/27659 +# and https://github.com/matplotlib/matplotlib/pull/27667 for more info. +def ion() -> AbstractContextManager: + """ + Enable interactive mode. + + See `.pyplot.isinteractive` for more details. + + See Also + -------- + ioff : Disable interactive mode. + isinteractive : Whether interactive mode is enabled. + show : Show all figures (and maybe block). + pause : Show all figures, and block for a time. + + Notes + ----- + For a temporary change, this can be used as a context manager:: + + # if interactive mode is off + # then figures will not be shown on creation + plt.ioff() + # This figure will not be shown immediately + fig = plt.figure() + + with plt.ion(): + # interactive mode will be on + # figures will automatically be shown + fig2 = plt.figure() + # ... + + To enable optional usage as a context manager, this function returns a + context manager object, which is not intended to be stored or + accessed by the user. + """ + stack = ExitStack() + stack.callback(ion if isinteractive() else ioff) + matplotlib.interactive(True) + install_repl_displayhook() + return stack + + +def pause(interval: float) -> None: + """ + Run the GUI event loop for *interval* seconds. + + If there is an active figure, it will be updated and displayed before the + pause, and the GUI event loop (if any) will run during the pause. + + This can be used for crude animation. For more complex animation use + :mod:`matplotlib.animation`. + + If there is no active figure, sleep for *interval* seconds instead. + + See Also + -------- + matplotlib.animation : Proper animations + show : Show all figures and optional block until all figures are closed. + """ + manager = _pylab_helpers.Gcf.get_active() + if manager is not None: + canvas = manager.canvas + if canvas.figure.stale: + canvas.draw_idle() + show(block=False) + canvas.start_event_loop(interval) + else: + time.sleep(interval) + + +@_copy_docstring_and_deprecators(matplotlib.rc) +def rc(group: str, **kwargs) -> None: + matplotlib.rc(group, **kwargs) + + +@_copy_docstring_and_deprecators(matplotlib.rc_context) +def rc_context( + rc: dict[str, Any] | None = None, + fname: str | pathlib.Path | os.PathLike | None = None, +) -> AbstractContextManager[None]: + return matplotlib.rc_context(rc, fname) + + +@_copy_docstring_and_deprecators(matplotlib.rcdefaults) +def rcdefaults() -> None: + matplotlib.rcdefaults() + if matplotlib.is_interactive(): + draw_all() + + +# getp/get/setp are explicitly reexported so that they show up in pyplot docs. + + +@_copy_docstring_and_deprecators(matplotlib.artist.getp) +def getp(obj, *args, **kwargs): + return matplotlib.artist.getp(obj, *args, **kwargs) + + +@_copy_docstring_and_deprecators(matplotlib.artist.get) +def get(obj, *args, **kwargs): + return matplotlib.artist.get(obj, *args, **kwargs) + + +@_copy_docstring_and_deprecators(matplotlib.artist.setp) +def setp(obj, *args, **kwargs): + return matplotlib.artist.setp(obj, *args, **kwargs) + + +def xkcd( + scale: float = 1, length: float = 100, randomness: float = 2 +) -> ExitStack: + """ + Turn on `xkcd `_ sketch-style drawing mode. + + This will only have an effect on things drawn after this function is called. + + For best results, install the `xkcd script `_ + font; xkcd fonts are not packaged with Matplotlib. + + Parameters + ---------- + scale : float, optional + The amplitude of the wiggle perpendicular to the source line. + length : float, optional + The length of the wiggle along the line. + randomness : float, optional + The scale factor by which the length is shrunken or expanded. + + Notes + ----- + This function works by a number of rcParams, so it will probably + override others you have set before. + + If you want the effects of this function to be temporary, it can + be used as a context manager, for example:: + + with plt.xkcd(): + # This figure will be in XKCD-style + fig1 = plt.figure() + # ... + + # This figure will be in regular style + fig2 = plt.figure() + """ + # This cannot be implemented in terms of contextmanager() or rc_context() + # because this needs to work as a non-contextmanager too. + + if rcParams['text.usetex']: + raise RuntimeError( + "xkcd mode is not compatible with text.usetex = True") + + stack = ExitStack() + stack.callback(dict.update, rcParams, rcParams.copy()) # type: ignore[arg-type] + + from matplotlib import patheffects + rcParams.update({ + 'font.family': ['xkcd', 'xkcd Script', 'Comic Neue', 'Comic Sans MS'], + 'font.size': 14.0, + 'path.sketch': (scale, length, randomness), + 'path.effects': [ + patheffects.withStroke(linewidth=4, foreground="w")], + 'axes.linewidth': 1.5, + 'lines.linewidth': 2.0, + 'figure.facecolor': 'white', + 'grid.linewidth': 0.0, + 'axes.grid': False, + 'axes.unicode_minus': False, + 'axes.edgecolor': 'black', + 'xtick.major.size': 8, + 'xtick.major.width': 3, + 'ytick.major.size': 8, + 'ytick.major.width': 3, + }) + + return stack + + +## Figures ## + +def figure( + # autoincrement if None, else integer from 1-N + num: int | str | Figure | SubFigure | None = None, + # defaults to rc figure.figsize + figsize: tuple[float, float] | None = None, + # defaults to rc figure.dpi + dpi: float | None = None, + *, + # defaults to rc figure.facecolor + facecolor: ColorType | None = None, + # defaults to rc figure.edgecolor + edgecolor: ColorType | None = None, + frameon: bool = True, + FigureClass: type[Figure] = Figure, + clear: bool = False, + **kwargs +) -> Figure: + """ + Create a new figure, or activate an existing figure. + + Parameters + ---------- + num : int or str or `.Figure` or `.SubFigure`, optional + A unique identifier for the figure. + + If a figure with that identifier already exists, this figure is made + active and returned. An integer refers to the ``Figure.number`` + attribute, a string refers to the figure label. + + If there is no figure with the identifier or *num* is not given, a new + figure is created, made active and returned. If *num* is an int, it + will be used for the ``Figure.number`` attribute, otherwise, an + auto-generated integer value is used (starting at 1 and incremented + for each new figure). If *num* is a string, the figure label and the + window title is set to this value. If num is a ``SubFigure``, its + parent ``Figure`` is activated. + + figsize : (float, float), default: :rc:`figure.figsize` + Width, height in inches. + + dpi : float, default: :rc:`figure.dpi` + The resolution of the figure in dots-per-inch. + + facecolor : :mpltype:`color`, default: :rc:`figure.facecolor` + The background color. + + edgecolor : :mpltype:`color`, default: :rc:`figure.edgecolor` + The border color. + + frameon : bool, default: True + If False, suppress drawing the figure frame. + + FigureClass : subclass of `~matplotlib.figure.Figure` + If set, an instance of this subclass will be created, rather than a + plain `.Figure`. + + clear : bool, default: False + If True and the figure already exists, then it is cleared. + + layout : {'constrained', 'compressed', 'tight', 'none', `.LayoutEngine`, None}, \ +default: None + The layout mechanism for positioning of plot elements to avoid + overlapping Axes decorations (labels, ticks, etc). Note that layout + managers can measurably slow down figure display. + + - 'constrained': The constrained layout solver adjusts Axes sizes + to avoid overlapping Axes decorations. Can handle complex plot + layouts and colorbars, and is thus recommended. + + See :ref:`constrainedlayout_guide` + for examples. + + - 'compressed': uses the same algorithm as 'constrained', but + removes extra space between fixed-aspect-ratio Axes. Best for + simple grids of Axes. + + - 'tight': Use the tight layout mechanism. This is a relatively + simple algorithm that adjusts the subplot parameters so that + decorations do not overlap. See `.Figure.set_tight_layout` for + further details. + + - 'none': Do not use a layout engine. + + - A `.LayoutEngine` instance. Builtin layout classes are + `.ConstrainedLayoutEngine` and `.TightLayoutEngine`, more easily + accessible by 'constrained' and 'tight'. Passing an instance + allows third parties to provide their own layout engine. + + If not given, fall back to using the parameters *tight_layout* and + *constrained_layout*, including their config defaults + :rc:`figure.autolayout` and :rc:`figure.constrained_layout.use`. + + **kwargs + Additional keyword arguments are passed to the `.Figure` constructor. + + Returns + ------- + `~matplotlib.figure.Figure` + + Notes + ----- + A newly created figure is passed to the `~.FigureCanvasBase.new_manager` + method or the `new_figure_manager` function provided by the current + backend, which install a canvas and a manager on the figure. + + Once this is done, :rc:`figure.hooks` are called, one at a time, on the + figure; these hooks allow arbitrary customization of the figure (e.g., + attaching callbacks) or of associated elements (e.g., modifying the + toolbar). See :doc:`/gallery/user_interfaces/mplcvd` for an example of + toolbar customization. + + If you are creating many figures, make sure you explicitly call + `.pyplot.close` on the figures you are not using, because this will + enable pyplot to properly clean up the memory. + + `~matplotlib.rcParams` defines the default values, which can be modified + in the matplotlibrc file. + """ + if isinstance(num, FigureBase): + # type narrowed to `Figure | SubFigure` by combination of input and isinstance + if num.canvas.manager is None: + raise ValueError("The passed figure is not managed by pyplot") + _pylab_helpers.Gcf.set_active(num.canvas.manager) + return num.figure + + allnums = get_fignums() + next_num = max(allnums) + 1 if allnums else 1 + fig_label = '' + if num is None: + num = next_num + elif isinstance(num, str): + fig_label = num + all_labels = get_figlabels() + if fig_label not in all_labels: + if fig_label == 'all': + _api.warn_external("close('all') closes all existing figures.") + num = next_num + else: + inum = all_labels.index(fig_label) + num = allnums[inum] + else: + num = int(num) # crude validation of num argument + + # Type of "num" has narrowed to int, but mypy can't quite see it + manager = _pylab_helpers.Gcf.get_fig_manager(num) # type: ignore[arg-type] + if manager is None: + max_open_warning = rcParams['figure.max_open_warning'] + if len(allnums) == max_open_warning >= 1: + _api.warn_external( + f"More than {max_open_warning} figures have been opened. " + f"Figures created through the pyplot interface " + f"(`matplotlib.pyplot.figure`) are retained until explicitly " + f"closed and may consume too much memory. (To control this " + f"warning, see the rcParam `figure.max_open_warning`). " + f"Consider using `matplotlib.pyplot.close()`.", + RuntimeWarning) + + manager = new_figure_manager( + num, figsize=figsize, dpi=dpi, + facecolor=facecolor, edgecolor=edgecolor, frameon=frameon, + FigureClass=FigureClass, **kwargs) + fig = manager.canvas.figure + if fig_label: + fig.set_label(fig_label) + + for hookspecs in rcParams["figure.hooks"]: + module_name, dotted_name = hookspecs.split(":") + obj: Any = importlib.import_module(module_name) + for part in dotted_name.split("."): + obj = getattr(obj, part) + obj(fig) + + _pylab_helpers.Gcf._set_new_active_manager(manager) + + # make sure backends (inline) that we don't ship that expect this + # to be called in plotting commands to make the figure call show + # still work. There is probably a better way to do this in the + # FigureManager base class. + draw_if_interactive() + + if _REPL_DISPLAYHOOK is _ReplDisplayHook.PLAIN: + fig.stale_callback = _auto_draw_if_interactive + + if clear: + manager.canvas.figure.clear() + + return manager.canvas.figure + + +def _auto_draw_if_interactive(fig, val): + """ + An internal helper function for making sure that auto-redrawing + works as intended in the plain python repl. + + Parameters + ---------- + fig : Figure + A figure object which is assumed to be associated with a canvas + """ + if (val and matplotlib.is_interactive() + and not fig.canvas.is_saving() + and not fig.canvas._is_idle_drawing): + # Some artists can mark themselves as stale in the middle of drawing + # (e.g. axes position & tick labels being computed at draw time), but + # this shouldn't trigger a redraw because the current redraw will + # already take them into account. + with fig.canvas._idle_draw_cntx(): + fig.canvas.draw_idle() + + +def gcf() -> Figure: + """ + Get the current figure. + + If there is currently no figure on the pyplot figure stack, a new one is + created using `~.pyplot.figure()`. (To test whether there is currently a + figure on the pyplot figure stack, check whether `~.pyplot.get_fignums()` + is empty.) + """ + manager = _pylab_helpers.Gcf.get_active() + if manager is not None: + return manager.canvas.figure + else: + return figure() + + +def fignum_exists(num: int | str) -> bool: + """ + Return whether the figure with the given id exists. + + Parameters + ---------- + num : int or str + A figure identifier. + + Returns + ------- + bool + Whether or not a figure with id *num* exists. + """ + return ( + _pylab_helpers.Gcf.has_fignum(num) + if isinstance(num, int) + else num in get_figlabels() + ) + + +def get_fignums() -> list[int]: + """Return a list of existing figure numbers.""" + return sorted(_pylab_helpers.Gcf.figs) + + +def get_figlabels() -> list[Any]: + """Return a list of existing figure labels.""" + managers = _pylab_helpers.Gcf.get_all_fig_managers() + managers.sort(key=lambda m: m.num) + return [m.canvas.figure.get_label() for m in managers] + + +def get_current_fig_manager() -> FigureManagerBase | None: + """ + Return the figure manager of the current figure. + + The figure manager is a container for the actual backend-depended window + that displays the figure on screen. + + If no current figure exists, a new one is created, and its figure + manager is returned. + + Returns + ------- + `.FigureManagerBase` or backend-dependent subclass thereof + """ + return gcf().canvas.manager + + +@_copy_docstring_and_deprecators(FigureCanvasBase.mpl_connect) +def connect(s: str, func: Callable[[Event], Any]) -> int: + return gcf().canvas.mpl_connect(s, func) + + +@_copy_docstring_and_deprecators(FigureCanvasBase.mpl_disconnect) +def disconnect(cid: int) -> None: + gcf().canvas.mpl_disconnect(cid) + + +def close(fig: None | int | str | Figure | Literal["all"] = None) -> None: + """ + Close a figure window. + + Parameters + ---------- + fig : None or int or str or `.Figure` + The figure to close. There are a number of ways to specify this: + + - *None*: the current figure + - `.Figure`: the given `.Figure` instance + - ``int``: a figure number + - ``str``: a figure name + - 'all': all figures + + """ + if fig is None: + manager = _pylab_helpers.Gcf.get_active() + if manager is None: + return + else: + _pylab_helpers.Gcf.destroy(manager) + elif fig == 'all': + _pylab_helpers.Gcf.destroy_all() + elif isinstance(fig, int): + _pylab_helpers.Gcf.destroy(fig) + elif hasattr(fig, 'int'): + # if we are dealing with a type UUID, we + # can use its integer representation + _pylab_helpers.Gcf.destroy(fig.int) + elif isinstance(fig, str): + all_labels = get_figlabels() + if fig in all_labels: + num = get_fignums()[all_labels.index(fig)] + _pylab_helpers.Gcf.destroy(num) + elif isinstance(fig, Figure): + _pylab_helpers.Gcf.destroy_fig(fig) + else: + raise TypeError("close() argument must be a Figure, an int, a string, " + "or None, not %s" % type(fig)) + + +def clf() -> None: + """Clear the current figure.""" + gcf().clear() + + +def draw() -> None: + """ + Redraw the current figure. + + This is used to update a figure that has been altered, but not + automatically re-drawn. If interactive mode is on (via `.ion()`), this + should be only rarely needed, but there may be ways to modify the state of + a figure without marking it as "stale". Please report these cases as bugs. + + This is equivalent to calling ``fig.canvas.draw_idle()``, where ``fig`` is + the current figure. + + See Also + -------- + .FigureCanvasBase.draw_idle + .FigureCanvasBase.draw + """ + gcf().canvas.draw_idle() + + +@_copy_docstring_and_deprecators(Figure.savefig) +def savefig(*args, **kwargs) -> None: + fig = gcf() + # savefig default implementation has no return, so mypy is unhappy + # presumably this is here because subclasses can return? + res = fig.savefig(*args, **kwargs) # type: ignore[func-returns-value] + fig.canvas.draw_idle() # Need this if 'transparent=True', to reset colors. + return res + + +## Putting things in figures ## + + +def figlegend(*args, **kwargs) -> Legend: + return gcf().legend(*args, **kwargs) +if Figure.legend.__doc__: + figlegend.__doc__ = Figure.legend.__doc__ \ + .replace(" legend(", " figlegend(") \ + .replace("fig.legend(", "plt.figlegend(") \ + .replace("ax.plot(", "plt.plot(") + + +## Axes ## + +@_docstring.dedent_interpd +def axes( + arg: None | tuple[float, float, float, float] = None, + **kwargs +) -> matplotlib.axes.Axes: + """ + Add an Axes to the current figure and make it the current Axes. + + Call signatures:: + + plt.axes() + plt.axes(rect, projection=None, polar=False, **kwargs) + plt.axes(ax) + + Parameters + ---------- + arg : None or 4-tuple + The exact behavior of this function depends on the type: + + - *None*: A new full window Axes is added using + ``subplot(**kwargs)``. + - 4-tuple of floats *rect* = ``(left, bottom, width, height)``. + A new Axes is added with dimensions *rect* in normalized + (0, 1) units using `~.Figure.add_axes` on the current figure. + + projection : {None, 'aitoff', 'hammer', 'lambert', 'mollweide', \ +'polar', 'rectilinear', str}, optional + The projection type of the `~.axes.Axes`. *str* is the name of + a custom projection, see `~matplotlib.projections`. The default + None results in a 'rectilinear' projection. + + polar : bool, default: False + If True, equivalent to projection='polar'. + + sharex, sharey : `~matplotlib.axes.Axes`, optional + Share the x or y `~matplotlib.axis` with sharex and/or sharey. + The axis will have the same limits, ticks, and scale as the axis + of the shared Axes. + + label : str + A label for the returned Axes. + + Returns + ------- + `~.axes.Axes`, or a subclass of `~.axes.Axes` + The returned Axes class depends on the projection used. It is + `~.axes.Axes` if rectilinear projection is used and + `.projections.polar.PolarAxes` if polar projection is used. + + Other Parameters + ---------------- + **kwargs + This method also takes the keyword arguments for + the returned Axes class. The keyword arguments for the + rectilinear Axes class `~.axes.Axes` can be found in + the following table but there might also be other keyword + arguments if another projection is used, see the actual Axes + class. + + %(Axes:kwdoc)s + + See Also + -------- + .Figure.add_axes + .pyplot.subplot + .Figure.add_subplot + .Figure.subplots + .pyplot.subplots + + Examples + -------- + :: + + # Creating a new full window Axes + plt.axes() + + # Creating a new Axes with specified dimensions and a grey background + plt.axes((left, bottom, width, height), facecolor='grey') + """ + fig = gcf() + pos = kwargs.pop('position', None) + if arg is None: + if pos is None: + return fig.add_subplot(**kwargs) + else: + return fig.add_axes(pos, **kwargs) + else: + return fig.add_axes(arg, **kwargs) + + +def delaxes(ax: matplotlib.axes.Axes | None = None) -> None: + """ + Remove an `~.axes.Axes` (defaulting to the current Axes) from its figure. + """ + if ax is None: + ax = gca() + ax.remove() + + +def sca(ax: Axes) -> None: + """ + Set the current Axes to *ax* and the current Figure to the parent of *ax*. + """ + # Mypy sees ax.figure as potentially None, + # but if you are calling this, it won't be None + # Additionally the slight difference between `Figure` and `FigureBase` mypy catches + figure(ax.figure) # type: ignore[arg-type] + ax.figure.sca(ax) # type: ignore[union-attr] + + +def cla() -> None: + """Clear the current Axes.""" + # Not generated via boilerplate.py to allow a different docstring. + return gca().cla() + + +## More ways of creating Axes ## + +@_docstring.dedent_interpd +def subplot(*args, **kwargs) -> Axes: + """ + Add an Axes to the current figure or retrieve an existing Axes. + + This is a wrapper of `.Figure.add_subplot` which provides additional + behavior when working with the implicit API (see the notes section). + + Call signatures:: + + subplot(nrows, ncols, index, **kwargs) + subplot(pos, **kwargs) + subplot(**kwargs) + subplot(ax) + + Parameters + ---------- + *args : int, (int, int, *index*), or `.SubplotSpec`, default: (1, 1, 1) + The position of the subplot described by one of + + - Three integers (*nrows*, *ncols*, *index*). The subplot will take the + *index* position on a grid with *nrows* rows and *ncols* columns. + *index* starts at 1 in the upper left corner and increases to the + right. *index* can also be a two-tuple specifying the (*first*, + *last*) indices (1-based, and including *last*) of the subplot, e.g., + ``fig.add_subplot(3, 1, (1, 2))`` makes a subplot that spans the + upper 2/3 of the figure. + - A 3-digit integer. The digits are interpreted as if given separately + as three single-digit integers, i.e. ``fig.add_subplot(235)`` is the + same as ``fig.add_subplot(2, 3, 5)``. Note that this can only be used + if there are no more than 9 subplots. + - A `.SubplotSpec`. + + projection : {None, 'aitoff', 'hammer', 'lambert', 'mollweide', \ +'polar', 'rectilinear', str}, optional + The projection type of the subplot (`~.axes.Axes`). *str* is the name + of a custom projection, see `~matplotlib.projections`. The default + None results in a 'rectilinear' projection. + + polar : bool, default: False + If True, equivalent to projection='polar'. + + sharex, sharey : `~matplotlib.axes.Axes`, optional + Share the x or y `~matplotlib.axis` with sharex and/or sharey. The + axis will have the same limits, ticks, and scale as the axis of the + shared Axes. + + label : str + A label for the returned Axes. + + Returns + ------- + `~.axes.Axes` + + The Axes of the subplot. The returned Axes can actually be an instance + of a subclass, such as `.projections.polar.PolarAxes` for polar + projections. + + Other Parameters + ---------------- + **kwargs + This method also takes the keyword arguments for the returned Axes + base class; except for the *figure* argument. The keyword arguments + for the rectilinear base class `~.axes.Axes` can be found in + the following table but there might also be other keyword + arguments if another projection is used. + + %(Axes:kwdoc)s + + Notes + ----- + Creating a new Axes will delete any preexisting Axes that + overlaps with it beyond sharing a boundary:: + + import matplotlib.pyplot as plt + # plot a line, implicitly creating a subplot(111) + plt.plot([1, 2, 3]) + # now create a subplot which represents the top plot of a grid + # with 2 rows and 1 column. Since this subplot will overlap the + # first, the plot (and its Axes) previously created, will be removed + plt.subplot(211) + + If you do not want this behavior, use the `.Figure.add_subplot` method + or the `.pyplot.axes` function instead. + + If no *kwargs* are passed and there exists an Axes in the location + specified by *args* then that Axes will be returned rather than a new + Axes being created. + + If *kwargs* are passed and there exists an Axes in the location + specified by *args*, the projection type is the same, and the + *kwargs* match with the existing Axes, then the existing Axes is + returned. Otherwise a new Axes is created with the specified + parameters. We save a reference to the *kwargs* which we use + for this comparison. If any of the values in *kwargs* are + mutable we will not detect the case where they are mutated. + In these cases we suggest using `.Figure.add_subplot` and the + explicit Axes API rather than the implicit pyplot API. + + See Also + -------- + .Figure.add_subplot + .pyplot.subplots + .pyplot.axes + .Figure.subplots + + Examples + -------- + :: + + plt.subplot(221) + + # equivalent but more general + ax1 = plt.subplot(2, 2, 1) + + # add a subplot with no frame + ax2 = plt.subplot(222, frameon=False) + + # add a polar subplot + plt.subplot(223, projection='polar') + + # add a red subplot that shares the x-axis with ax1 + plt.subplot(224, sharex=ax1, facecolor='red') + + # delete ax2 from the figure + plt.delaxes(ax2) + + # add ax2 to the figure again + plt.subplot(ax2) + + # make the first Axes "current" again + plt.subplot(221) + + """ + # Here we will only normalize `polar=True` vs `projection='polar'` and let + # downstream code deal with the rest. + unset = object() + projection = kwargs.get('projection', unset) + polar = kwargs.pop('polar', unset) + if polar is not unset and polar: + # if we got mixed messages from the user, raise + if projection is not unset and projection != 'polar': + raise ValueError( + f"polar={polar}, yet projection={projection!r}. " + "Only one of these arguments should be supplied." + ) + kwargs['projection'] = projection = 'polar' + + # if subplot called without arguments, create subplot(1, 1, 1) + if len(args) == 0: + args = (1, 1, 1) + + # This check was added because it is very easy to type subplot(1, 2, False) + # when subplots(1, 2, False) was intended (sharex=False, that is). In most + # cases, no error will ever occur, but mysterious behavior can result + # because what was intended to be the sharex argument is instead treated as + # a subplot index for subplot() + if len(args) >= 3 and isinstance(args[2], bool): + _api.warn_external("The subplot index argument to subplot() appears " + "to be a boolean. Did you intend to use " + "subplots()?") + # Check for nrows and ncols, which are not valid subplot args: + if 'nrows' in kwargs or 'ncols' in kwargs: + raise TypeError("subplot() got an unexpected keyword argument 'ncols' " + "and/or 'nrows'. Did you intend to call subplots()?") + + fig = gcf() + + # First, search for an existing subplot with a matching spec. + key = SubplotSpec._from_subplot_args(fig, args) + + for ax in fig.axes: + # If we found an Axes at the position, we can reuse it if the user passed no + # kwargs or if the Axes class and kwargs are identical. + if (ax.get_subplotspec() == key + and (kwargs == {} + or (ax._projection_init + == fig._process_projection_requirements(**kwargs)))): + break + else: + # we have exhausted the known Axes and none match, make a new one! + ax = fig.add_subplot(*args, **kwargs) + + fig.sca(ax) + + return ax + + +@overload +def subplots( + nrows: Literal[1] = ..., + ncols: Literal[1] = ..., + *, + sharex: bool | Literal["none", "all", "row", "col"] = ..., + sharey: bool | Literal["none", "all", "row", "col"] = ..., + squeeze: Literal[True] = ..., + width_ratios: Sequence[float] | None = ..., + height_ratios: Sequence[float] | None = ..., + subplot_kw: dict[str, Any] | None = ..., + gridspec_kw: dict[str, Any] | None = ..., + **fig_kw +) -> tuple[Figure, Axes]: + ... + + +@overload +def subplots( + nrows: int = ..., + ncols: int = ..., + *, + sharex: bool | Literal["none", "all", "row", "col"] = ..., + sharey: bool | Literal["none", "all", "row", "col"] = ..., + squeeze: Literal[False], + width_ratios: Sequence[float] | None = ..., + height_ratios: Sequence[float] | None = ..., + subplot_kw: dict[str, Any] | None = ..., + gridspec_kw: dict[str, Any] | None = ..., + **fig_kw +) -> tuple[Figure, np.ndarray]: # TODO numpy/numpy#24738 + ... + + +@overload +def subplots( + nrows: int = ..., + ncols: int = ..., + *, + sharex: bool | Literal["none", "all", "row", "col"] = ..., + sharey: bool | Literal["none", "all", "row", "col"] = ..., + squeeze: bool = ..., + width_ratios: Sequence[float] | None = ..., + height_ratios: Sequence[float] | None = ..., + subplot_kw: dict[str, Any] | None = ..., + gridspec_kw: dict[str, Any] | None = ..., + **fig_kw +) -> tuple[Figure, Any]: + ... + + +def subplots( + nrows: int = 1, ncols: int = 1, *, + sharex: bool | Literal["none", "all", "row", "col"] = False, + sharey: bool | Literal["none", "all", "row", "col"] = False, + squeeze: bool = True, + width_ratios: Sequence[float] | None = None, + height_ratios: Sequence[float] | None = None, + subplot_kw: dict[str, Any] | None = None, + gridspec_kw: dict[str, Any] | None = None, + **fig_kw +) -> tuple[Figure, Any]: + """ + Create a figure and a set of subplots. + + This utility wrapper makes it convenient to create common layouts of + subplots, including the enclosing figure object, in a single call. + + Parameters + ---------- + nrows, ncols : int, default: 1 + Number of rows/columns of the subplot grid. + + sharex, sharey : bool or {'none', 'all', 'row', 'col'}, default: False + Controls sharing of properties among x (*sharex*) or y (*sharey*) + axes: + + - True or 'all': x- or y-axis will be shared among all subplots. + - False or 'none': each subplot x- or y-axis will be independent. + - 'row': each subplot row will share an x- or y-axis. + - 'col': each subplot column will share an x- or y-axis. + + When subplots have a shared x-axis along a column, only the x tick + labels of the bottom subplot are created. Similarly, when subplots + have a shared y-axis along a row, only the y tick labels of the first + column subplot are created. To later turn other subplots' ticklabels + on, use `~matplotlib.axes.Axes.tick_params`. + + When subplots have a shared axis that has units, calling + `.Axis.set_units` will update each axis with the new units. + + Note that it is not possible to unshare axes. + + squeeze : bool, default: True + - If True, extra dimensions are squeezed out from the returned + array of `~matplotlib.axes.Axes`: + + - if only one subplot is constructed (nrows=ncols=1), the + resulting single Axes object is returned as a scalar. + - for Nx1 or 1xM subplots, the returned object is a 1D numpy + object array of Axes objects. + - for NxM, subplots with N>1 and M>1 are returned as a 2D array. + + - If False, no squeezing at all is done: the returned Axes object is + always a 2D array containing Axes instances, even if it ends up + being 1x1. + + width_ratios : array-like of length *ncols*, optional + Defines the relative widths of the columns. Each column gets a + relative width of ``width_ratios[i] / sum(width_ratios)``. + If not given, all columns will have the same width. Equivalent + to ``gridspec_kw={'width_ratios': [...]}``. + + height_ratios : array-like of length *nrows*, optional + Defines the relative heights of the rows. Each row gets a + relative height of ``height_ratios[i] / sum(height_ratios)``. + If not given, all rows will have the same height. Convenience + for ``gridspec_kw={'height_ratios': [...]}``. + + subplot_kw : dict, optional + Dict with keywords passed to the + `~matplotlib.figure.Figure.add_subplot` call used to create each + subplot. + + gridspec_kw : dict, optional + Dict with keywords passed to the `~matplotlib.gridspec.GridSpec` + constructor used to create the grid the subplots are placed on. + + **fig_kw + All additional keyword arguments are passed to the + `.pyplot.figure` call. + + Returns + ------- + fig : `.Figure` + + ax : `~matplotlib.axes.Axes` or array of Axes + *ax* can be either a single `~.axes.Axes` object, or an array of Axes + objects if more than one subplot was created. The dimensions of the + resulting array can be controlled with the squeeze keyword, see above. + + Typical idioms for handling the return value are:: + + # using the variable ax for single a Axes + fig, ax = plt.subplots() + + # using the variable axs for multiple Axes + fig, axs = plt.subplots(2, 2) + + # using tuple unpacking for multiple Axes + fig, (ax1, ax2) = plt.subplots(1, 2) + fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2) + + The names ``ax`` and pluralized ``axs`` are preferred over ``axes`` + because for the latter it's not clear if it refers to a single + `~.axes.Axes` instance or a collection of these. + + See Also + -------- + .pyplot.figure + .pyplot.subplot + .pyplot.axes + .Figure.subplots + .Figure.add_subplot + + Examples + -------- + :: + + # First create some toy data: + x = np.linspace(0, 2*np.pi, 400) + y = np.sin(x**2) + + # Create just a figure and only one subplot + fig, ax = plt.subplots() + ax.plot(x, y) + ax.set_title('Simple plot') + + # Create two subplots and unpack the output array immediately + f, (ax1, ax2) = plt.subplots(1, 2, sharey=True) + ax1.plot(x, y) + ax1.set_title('Sharing Y axis') + ax2.scatter(x, y) + + # Create four polar Axes and access them through the returned array + fig, axs = plt.subplots(2, 2, subplot_kw=dict(projection="polar")) + axs[0, 0].plot(x, y) + axs[1, 1].scatter(x, y) + + # Share a X axis with each column of subplots + plt.subplots(2, 2, sharex='col') + + # Share a Y axis with each row of subplots + plt.subplots(2, 2, sharey='row') + + # Share both X and Y axes with all subplots + plt.subplots(2, 2, sharex='all', sharey='all') + + # Note that this is the same as + plt.subplots(2, 2, sharex=True, sharey=True) + + # Create figure number 10 with a single subplot + # and clears it if it already exists. + fig, ax = plt.subplots(num=10, clear=True) + + """ + fig = figure(**fig_kw) + axs = fig.subplots(nrows=nrows, ncols=ncols, sharex=sharex, sharey=sharey, + squeeze=squeeze, subplot_kw=subplot_kw, + gridspec_kw=gridspec_kw, height_ratios=height_ratios, + width_ratios=width_ratios) + return fig, axs + + +@overload +def subplot_mosaic( + mosaic: str, + *, + sharex: bool = ..., + sharey: bool = ..., + width_ratios: ArrayLike | None = ..., + height_ratios: ArrayLike | None = ..., + empty_sentinel: str = ..., + subplot_kw: dict[str, Any] | None = ..., + gridspec_kw: dict[str, Any] | None = ..., + per_subplot_kw: dict[str | tuple[str, ...], dict[str, Any]] | None = ..., + **fig_kw: Any +) -> tuple[Figure, dict[str, matplotlib.axes.Axes]]: ... + + +@overload +def subplot_mosaic( + mosaic: list[HashableList[_T]], + *, + sharex: bool = ..., + sharey: bool = ..., + width_ratios: ArrayLike | None = ..., + height_ratios: ArrayLike | None = ..., + empty_sentinel: _T = ..., + subplot_kw: dict[str, Any] | None = ..., + gridspec_kw: dict[str, Any] | None = ..., + per_subplot_kw: dict[_T | tuple[_T, ...], dict[str, Any]] | None = ..., + **fig_kw: Any +) -> tuple[Figure, dict[_T, matplotlib.axes.Axes]]: ... + + +@overload +def subplot_mosaic( + mosaic: list[HashableList[Hashable]], + *, + sharex: bool = ..., + sharey: bool = ..., + width_ratios: ArrayLike | None = ..., + height_ratios: ArrayLike | None = ..., + empty_sentinel: Any = ..., + subplot_kw: dict[str, Any] | None = ..., + gridspec_kw: dict[str, Any] | None = ..., + per_subplot_kw: dict[Hashable | tuple[Hashable, ...], dict[str, Any]] | None = ..., + **fig_kw: Any +) -> tuple[Figure, dict[Hashable, matplotlib.axes.Axes]]: ... + + +def subplot_mosaic( + mosaic: str | list[HashableList[_T]] | list[HashableList[Hashable]], + *, + sharex: bool = False, + sharey: bool = False, + width_ratios: ArrayLike | None = None, + height_ratios: ArrayLike | None = None, + empty_sentinel: Any = '.', + subplot_kw: dict[str, Any] | None = None, + gridspec_kw: dict[str, Any] | None = None, + per_subplot_kw: dict[str | tuple[str, ...], dict[str, Any]] | + dict[_T | tuple[_T, ...], dict[str, Any]] | + dict[Hashable | tuple[Hashable, ...], dict[str, Any]] | None = None, + **fig_kw: Any +) -> tuple[Figure, dict[str, matplotlib.axes.Axes]] | \ + tuple[Figure, dict[_T, matplotlib.axes.Axes]] | \ + tuple[Figure, dict[Hashable, matplotlib.axes.Axes]]: + """ + Build a layout of Axes based on ASCII art or nested lists. + + This is a helper function to build complex GridSpec layouts visually. + + See :ref:`mosaic` + for an example and full API documentation + + Parameters + ---------- + mosaic : list of list of {hashable or nested} or str + + A visual layout of how you want your Axes to be arranged + labeled as strings. For example :: + + x = [['A panel', 'A panel', 'edge'], + ['C panel', '.', 'edge']] + + produces 4 Axes: + + - 'A panel' which is 1 row high and spans the first two columns + - 'edge' which is 2 rows high and is on the right edge + - 'C panel' which in 1 row and 1 column wide in the bottom left + - a blank space 1 row and 1 column wide in the bottom center + + Any of the entries in the layout can be a list of lists + of the same form to create nested layouts. + + If input is a str, then it must be of the form :: + + ''' + AAE + C.E + ''' + + where each character is a column and each line is a row. + This only allows only single character Axes labels and does + not allow nesting but is very terse. + + sharex, sharey : bool, default: False + If True, the x-axis (*sharex*) or y-axis (*sharey*) will be shared + among all subplots. In that case, tick label visibility and axis units + behave as for `subplots`. If False, each subplot's x- or y-axis will + be independent. + + width_ratios : array-like of length *ncols*, optional + Defines the relative widths of the columns. Each column gets a + relative width of ``width_ratios[i] / sum(width_ratios)``. + If not given, all columns will have the same width. Convenience + for ``gridspec_kw={'width_ratios': [...]}``. + + height_ratios : array-like of length *nrows*, optional + Defines the relative heights of the rows. Each row gets a + relative height of ``height_ratios[i] / sum(height_ratios)``. + If not given, all rows will have the same height. Convenience + for ``gridspec_kw={'height_ratios': [...]}``. + + empty_sentinel : object, optional + Entry in the layout to mean "leave this space empty". Defaults + to ``'.'``. Note, if *layout* is a string, it is processed via + `inspect.cleandoc` to remove leading white space, which may + interfere with using white-space as the empty sentinel. + + subplot_kw : dict, optional + Dictionary with keywords passed to the `.Figure.add_subplot` call + used to create each subplot. These values may be overridden by + values in *per_subplot_kw*. + + per_subplot_kw : dict, optional + A dictionary mapping the Axes identifiers or tuples of identifiers + to a dictionary of keyword arguments to be passed to the + `.Figure.add_subplot` call used to create each subplot. The values + in these dictionaries have precedence over the values in + *subplot_kw*. + + If *mosaic* is a string, and thus all keys are single characters, + it is possible to use a single string instead of a tuple as keys; + i.e. ``"AB"`` is equivalent to ``("A", "B")``. + + .. versionadded:: 3.7 + + gridspec_kw : dict, optional + Dictionary with keywords passed to the `.GridSpec` constructor used + to create the grid the subplots are placed on. + + **fig_kw + All additional keyword arguments are passed to the + `.pyplot.figure` call. + + Returns + ------- + fig : `.Figure` + The new figure + + dict[label, Axes] + A dictionary mapping the labels to the Axes objects. The order of + the Axes is left-to-right and top-to-bottom of their position in the + total layout. + + """ + fig = figure(**fig_kw) + ax_dict = fig.subplot_mosaic( # type: ignore[misc] + mosaic, # type: ignore[arg-type] + sharex=sharex, sharey=sharey, + height_ratios=height_ratios, width_ratios=width_ratios, + subplot_kw=subplot_kw, gridspec_kw=gridspec_kw, + empty_sentinel=empty_sentinel, + per_subplot_kw=per_subplot_kw, # type: ignore[arg-type] + ) + return fig, ax_dict + + +def subplot2grid( + shape: tuple[int, int], loc: tuple[int, int], + rowspan: int = 1, colspan: int = 1, + fig: Figure | None = None, + **kwargs +) -> matplotlib.axes.Axes: + """ + Create a subplot at a specific location inside a regular grid. + + Parameters + ---------- + shape : (int, int) + Number of rows and of columns of the grid in which to place axis. + loc : (int, int) + Row number and column number of the axis location within the grid. + rowspan : int, default: 1 + Number of rows for the axis to span downwards. + colspan : int, default: 1 + Number of columns for the axis to span to the right. + fig : `.Figure`, optional + Figure to place the subplot in. Defaults to the current figure. + **kwargs + Additional keyword arguments are handed to `~.Figure.add_subplot`. + + Returns + ------- + `~.axes.Axes` + + The Axes of the subplot. The returned Axes can actually be an instance + of a subclass, such as `.projections.polar.PolarAxes` for polar + projections. + + Notes + ----- + The following call :: + + ax = subplot2grid((nrows, ncols), (row, col), rowspan, colspan) + + is identical to :: + + fig = gcf() + gs = fig.add_gridspec(nrows, ncols) + ax = fig.add_subplot(gs[row:row+rowspan, col:col+colspan]) + """ + if fig is None: + fig = gcf() + rows, cols = shape + gs = GridSpec._check_gridspec_exists(fig, rows, cols) + subplotspec = gs.new_subplotspec(loc, rowspan=rowspan, colspan=colspan) + return fig.add_subplot(subplotspec, **kwargs) + + +def twinx(ax: matplotlib.axes.Axes | None = None) -> _AxesBase: + """ + Make and return a second Axes that shares the *x*-axis. The new Axes will + overlay *ax* (or the current Axes if *ax* is *None*), and its ticks will be + on the right. + + Examples + -------- + :doc:`/gallery/subplots_axes_and_figures/two_scales` + """ + if ax is None: + ax = gca() + ax1 = ax.twinx() + return ax1 + + +def twiny(ax: matplotlib.axes.Axes | None = None) -> _AxesBase: + """ + Make and return a second Axes that shares the *y*-axis. The new Axes will + overlay *ax* (or the current Axes if *ax* is *None*), and its ticks will be + on the top. + + Examples + -------- + :doc:`/gallery/subplots_axes_and_figures/two_scales` + """ + if ax is None: + ax = gca() + ax1 = ax.twiny() + return ax1 + + +def subplot_tool(targetfig: Figure | None = None) -> SubplotTool | None: + """ + Launch a subplot tool window for a figure. + + Returns + ------- + `matplotlib.widgets.SubplotTool` + """ + if targetfig is None: + targetfig = gcf() + tb = targetfig.canvas.manager.toolbar # type: ignore[union-attr] + if hasattr(tb, "configure_subplots"): # toolbar2 + from matplotlib.backend_bases import NavigationToolbar2 + return cast(NavigationToolbar2, tb).configure_subplots() + elif hasattr(tb, "trigger_tool"): # toolmanager + from matplotlib.backend_bases import ToolContainerBase + cast(ToolContainerBase, tb).trigger_tool("subplots") + return None + else: + raise ValueError("subplot_tool can only be launched for figures with " + "an associated toolbar") + + +def box(on: bool | None = None) -> None: + """ + Turn the Axes box on or off on the current Axes. + + Parameters + ---------- + on : bool or None + The new `~matplotlib.axes.Axes` box state. If ``None``, toggle + the state. + + See Also + -------- + :meth:`matplotlib.axes.Axes.set_frame_on` + :meth:`matplotlib.axes.Axes.get_frame_on` + """ + ax = gca() + if on is None: + on = not ax.get_frame_on() + ax.set_frame_on(on) + +## Axis ## + + +def xlim(*args, **kwargs) -> tuple[float, float]: + """ + Get or set the x limits of the current Axes. + + Call signatures:: + + left, right = xlim() # return the current xlim + xlim((left, right)) # set the xlim to left, right + xlim(left, right) # set the xlim to left, right + + If you do not specify args, you can pass *left* or *right* as kwargs, + i.e.:: + + xlim(right=3) # adjust the right leaving left unchanged + xlim(left=1) # adjust the left leaving right unchanged + + Setting limits turns autoscaling off for the x-axis. + + Returns + ------- + left, right + A tuple of the new x-axis limits. + + Notes + ----- + Calling this function with no arguments (e.g. ``xlim()``) is the pyplot + equivalent of calling `~.Axes.get_xlim` on the current Axes. + Calling this function with arguments is the pyplot equivalent of calling + `~.Axes.set_xlim` on the current Axes. All arguments are passed though. + """ + ax = gca() + if not args and not kwargs: + return ax.get_xlim() + ret = ax.set_xlim(*args, **kwargs) + return ret + + +def ylim(*args, **kwargs) -> tuple[float, float]: + """ + Get or set the y-limits of the current Axes. + + Call signatures:: + + bottom, top = ylim() # return the current ylim + ylim((bottom, top)) # set the ylim to bottom, top + ylim(bottom, top) # set the ylim to bottom, top + + If you do not specify args, you can alternatively pass *bottom* or + *top* as kwargs, i.e.:: + + ylim(top=3) # adjust the top leaving bottom unchanged + ylim(bottom=1) # adjust the bottom leaving top unchanged + + Setting limits turns autoscaling off for the y-axis. + + Returns + ------- + bottom, top + A tuple of the new y-axis limits. + + Notes + ----- + Calling this function with no arguments (e.g. ``ylim()``) is the pyplot + equivalent of calling `~.Axes.get_ylim` on the current Axes. + Calling this function with arguments is the pyplot equivalent of calling + `~.Axes.set_ylim` on the current Axes. All arguments are passed though. + """ + ax = gca() + if not args and not kwargs: + return ax.get_ylim() + ret = ax.set_ylim(*args, **kwargs) + return ret + + +def xticks( + ticks: ArrayLike | None = None, + labels: Sequence[str] | None = None, + *, + minor: bool = False, + **kwargs +) -> tuple[list[Tick] | np.ndarray, list[Text]]: + """ + Get or set the current tick locations and labels of the x-axis. + + Pass no arguments to return the current values without modifying them. + + Parameters + ---------- + ticks : array-like, optional + The list of xtick locations. Passing an empty list removes all xticks. + labels : array-like, optional + The labels to place at the given *ticks* locations. This argument can + only be passed if *ticks* is passed as well. + minor : bool, default: False + If ``False``, get/set the major ticks/labels; if ``True``, the minor + ticks/labels. + **kwargs + `.Text` properties can be used to control the appearance of the labels. + + .. warning:: + + This only sets the properties of the current ticks, which is + only sufficient if you either pass *ticks*, resulting in a + fixed list of ticks, or if the plot is static. + + Ticks are not guaranteed to be persistent. Various operations + can create, delete and modify the Tick instances. There is an + imminent risk that these settings can get lost if you work on + the figure further (including also panning/zooming on a + displayed figure). + + Use `~.pyplot.tick_params` instead if possible. + + + Returns + ------- + locs + The list of xtick locations. + labels + The list of xlabel `.Text` objects. + + Notes + ----- + Calling this function with no arguments (e.g. ``xticks()``) is the pyplot + equivalent of calling `~.Axes.get_xticks` and `~.Axes.get_xticklabels` on + the current Axes. + Calling this function with arguments is the pyplot equivalent of calling + `~.Axes.set_xticks` and `~.Axes.set_xticklabels` on the current Axes. + + Examples + -------- + >>> locs, labels = xticks() # Get the current locations and labels. + >>> xticks(np.arange(0, 1, step=0.2)) # Set label locations. + >>> xticks(np.arange(3), ['Tom', 'Dick', 'Sue']) # Set text labels. + >>> xticks([0, 1, 2], ['January', 'February', 'March'], + ... rotation=20) # Set text labels and properties. + >>> xticks([]) # Disable xticks. + """ + ax = gca() + + locs: list[Tick] | np.ndarray + if ticks is None: + locs = ax.get_xticks(minor=minor) + if labels is not None: + raise TypeError("xticks(): Parameter 'labels' can't be set " + "without setting 'ticks'") + else: + locs = ax.set_xticks(ticks, minor=minor) + + labels_out: list[Text] = [] + if labels is None: + labels_out = ax.get_xticklabels(minor=minor) + for l in labels_out: + l._internal_update(kwargs) + else: + labels_out = ax.set_xticklabels(labels, minor=minor, **kwargs) + + return locs, labels_out + + +def yticks( + ticks: ArrayLike | None = None, + labels: Sequence[str] | None = None, + *, + minor: bool = False, + **kwargs +) -> tuple[list[Tick] | np.ndarray, list[Text]]: + """ + Get or set the current tick locations and labels of the y-axis. + + Pass no arguments to return the current values without modifying them. + + Parameters + ---------- + ticks : array-like, optional + The list of ytick locations. Passing an empty list removes all yticks. + labels : array-like, optional + The labels to place at the given *ticks* locations. This argument can + only be passed if *ticks* is passed as well. + minor : bool, default: False + If ``False``, get/set the major ticks/labels; if ``True``, the minor + ticks/labels. + **kwargs + `.Text` properties can be used to control the appearance of the labels. + + .. warning:: + + This only sets the properties of the current ticks, which is + only sufficient if you either pass *ticks*, resulting in a + fixed list of ticks, or if the plot is static. + + Ticks are not guaranteed to be persistent. Various operations + can create, delete and modify the Tick instances. There is an + imminent risk that these settings can get lost if you work on + the figure further (including also panning/zooming on a + displayed figure). + + Use `~.pyplot.tick_params` instead if possible. + + Returns + ------- + locs + The list of ytick locations. + labels + The list of ylabel `.Text` objects. + + Notes + ----- + Calling this function with no arguments (e.g. ``yticks()``) is the pyplot + equivalent of calling `~.Axes.get_yticks` and `~.Axes.get_yticklabels` on + the current Axes. + Calling this function with arguments is the pyplot equivalent of calling + `~.Axes.set_yticks` and `~.Axes.set_yticklabels` on the current Axes. + + Examples + -------- + >>> locs, labels = yticks() # Get the current locations and labels. + >>> yticks(np.arange(0, 1, step=0.2)) # Set label locations. + >>> yticks(np.arange(3), ['Tom', 'Dick', 'Sue']) # Set text labels. + >>> yticks([0, 1, 2], ['January', 'February', 'March'], + ... rotation=45) # Set text labels and properties. + >>> yticks([]) # Disable yticks. + """ + ax = gca() + + locs: list[Tick] | np.ndarray + if ticks is None: + locs = ax.get_yticks(minor=minor) + if labels is not None: + raise TypeError("yticks(): Parameter 'labels' can't be set " + "without setting 'ticks'") + else: + locs = ax.set_yticks(ticks, minor=minor) + + labels_out: list[Text] = [] + if labels is None: + labels_out = ax.get_yticklabels(minor=minor) + for l in labels_out: + l._internal_update(kwargs) + else: + labels_out = ax.set_yticklabels(labels, minor=minor, **kwargs) + + return locs, labels_out + + +def rgrids( + radii: ArrayLike | None = None, + labels: Sequence[str | Text] | None = None, + angle: float | None = None, + fmt: str | None = None, + **kwargs +) -> tuple[list[Line2D], list[Text]]: + """ + Get or set the radial gridlines on the current polar plot. + + Call signatures:: + + lines, labels = rgrids() + lines, labels = rgrids(radii, labels=None, angle=22.5, fmt=None, **kwargs) + + When called with no arguments, `.rgrids` simply returns the tuple + (*lines*, *labels*). When called with arguments, the labels will + appear at the specified radial distances and angle. + + Parameters + ---------- + radii : tuple with floats + The radii for the radial gridlines + + labels : tuple with strings or None + The labels to use at each radial gridline. The + `matplotlib.ticker.ScalarFormatter` will be used if None. + + angle : float + The angular position of the radius labels in degrees. + + fmt : str or None + Format string used in `matplotlib.ticker.FormatStrFormatter`. + For example '%f'. + + Returns + ------- + lines : list of `.lines.Line2D` + The radial gridlines. + + labels : list of `.text.Text` + The tick labels. + + Other Parameters + ---------------- + **kwargs + *kwargs* are optional `.Text` properties for the labels. + + See Also + -------- + .pyplot.thetagrids + .projections.polar.PolarAxes.set_rgrids + .Axis.get_gridlines + .Axis.get_ticklabels + + Examples + -------- + :: + + # set the locations of the radial gridlines + lines, labels = rgrids( (0.25, 0.5, 1.0) ) + + # set the locations and labels of the radial gridlines + lines, labels = rgrids( (0.25, 0.5, 1.0), ('Tom', 'Dick', 'Harry' )) + """ + ax = gca() + if not isinstance(ax, PolarAxes): + raise RuntimeError('rgrids only defined for polar Axes') + if all(p is None for p in [radii, labels, angle, fmt]) and not kwargs: + lines_out: list[Line2D] = ax.yaxis.get_gridlines() + labels_out: list[Text] = ax.yaxis.get_ticklabels() + elif radii is None: + raise TypeError("'radii' cannot be None when other parameters are passed") + else: + lines_out, labels_out = ax.set_rgrids( + radii, labels=labels, angle=angle, fmt=fmt, **kwargs) + return lines_out, labels_out + + +def thetagrids( + angles: ArrayLike | None = None, + labels: Sequence[str | Text] | None = None, + fmt: str | None = None, + **kwargs +) -> tuple[list[Line2D], list[Text]]: + """ + Get or set the theta gridlines on the current polar plot. + + Call signatures:: + + lines, labels = thetagrids() + lines, labels = thetagrids(angles, labels=None, fmt=None, **kwargs) + + When called with no arguments, `.thetagrids` simply returns the tuple + (*lines*, *labels*). When called with arguments, the labels will + appear at the specified angles. + + Parameters + ---------- + angles : tuple with floats, degrees + The angles of the theta gridlines. + + labels : tuple with strings or None + The labels to use at each radial gridline. The + `.projections.polar.ThetaFormatter` will be used if None. + + fmt : str or None + Format string used in `matplotlib.ticker.FormatStrFormatter`. + For example '%f'. Note that the angle in radians will be used. + + Returns + ------- + lines : list of `.lines.Line2D` + The theta gridlines. + + labels : list of `.text.Text` + The tick labels. + + Other Parameters + ---------------- + **kwargs + *kwargs* are optional `.Text` properties for the labels. + + See Also + -------- + .pyplot.rgrids + .projections.polar.PolarAxes.set_thetagrids + .Axis.get_gridlines + .Axis.get_ticklabels + + Examples + -------- + :: + + # set the locations of the angular gridlines + lines, labels = thetagrids(range(45, 360, 90)) + + # set the locations and labels of the angular gridlines + lines, labels = thetagrids(range(45, 360, 90), ('NE', 'NW', 'SW', 'SE')) + """ + ax = gca() + if not isinstance(ax, PolarAxes): + raise RuntimeError('thetagrids only defined for polar Axes') + if all(param is None for param in [angles, labels, fmt]) and not kwargs: + lines_out: list[Line2D] = ax.xaxis.get_ticklines() + labels_out: list[Text] = ax.xaxis.get_ticklabels() + elif angles is None: + raise TypeError("'angles' cannot be None when other parameters are passed") + else: + lines_out, labels_out = ax.set_thetagrids(angles, + labels=labels, fmt=fmt, + **kwargs) + return lines_out, labels_out + + +@_api.deprecated("3.7", pending=True) +def get_plot_commands() -> list[str]: + """ + Get a sorted list of all of the plotting commands. + """ + NON_PLOT_COMMANDS = { + 'connect', 'disconnect', 'get_current_fig_manager', 'ginput', + 'new_figure_manager', 'waitforbuttonpress'} + return [name for name in _get_pyplot_commands() + if name not in NON_PLOT_COMMANDS] + + +def _get_pyplot_commands() -> list[str]: + # This works by searching for all functions in this module and removing + # a few hard-coded exclusions, as well as all of the colormap-setting + # functions, and anything marked as private with a preceding underscore. + exclude = {'colormaps', 'colors', 'get_plot_commands', *colormaps} + this_module = inspect.getmodule(get_plot_commands) + return sorted( + name for name, obj in globals().items() + if not name.startswith('_') and name not in exclude + and inspect.isfunction(obj) + and inspect.getmodule(obj) is this_module) + + +## Plotting part 1: manually generated functions and wrappers ## + + +@_copy_docstring_and_deprecators(Figure.colorbar) +def colorbar( + mappable: ScalarMappable | None = None, + cax: matplotlib.axes.Axes | None = None, + ax: matplotlib.axes.Axes | Iterable[matplotlib.axes.Axes] | None = None, + **kwargs +) -> Colorbar: + if mappable is None: + mappable = gci() + if mappable is None: + raise RuntimeError('No mappable was found to use for colorbar ' + 'creation. First define a mappable such as ' + 'an image (with imshow) or a contour set (' + 'with contourf).') + ret = gcf().colorbar(mappable, cax=cax, ax=ax, **kwargs) + return ret + + +def clim(vmin: float | None = None, vmax: float | None = None) -> None: + """ + Set the color limits of the current image. + + If either *vmin* or *vmax* is None, the image min/max respectively + will be used for color scaling. + + If you want to set the clim of multiple images, use + `~.ScalarMappable.set_clim` on every image, for example:: + + for im in gca().get_images(): + im.set_clim(0, 0.5) + + """ + im = gci() + if im is None: + raise RuntimeError('You must first define an image, e.g., with imshow') + + im.set_clim(vmin, vmax) + + +def get_cmap(name: Colormap | str | None = None, lut: int | None = None) -> Colormap: + """ + Get a colormap instance, defaulting to rc values if *name* is None. + + Parameters + ---------- + name : `~matplotlib.colors.Colormap` or str or None, default: None + If a `.Colormap` instance, it will be returned. Otherwise, the name of + a colormap known to Matplotlib, which will be resampled by *lut*. The + default, None, means :rc:`image.cmap`. + lut : int or None, default: None + If *name* is not already a Colormap instance and *lut* is not None, the + colormap will be resampled to have *lut* entries in the lookup table. + + Returns + ------- + Colormap + """ + if name is None: + name = rcParams['image.cmap'] + if isinstance(name, Colormap): + return name + _api.check_in_list(sorted(_colormaps), name=name) + if lut is None: + return _colormaps[name] + else: + return _colormaps[name].resampled(lut) + + +def set_cmap(cmap: Colormap | str) -> None: + """ + Set the default colormap, and applies it to the current image if any. + + Parameters + ---------- + cmap : `~matplotlib.colors.Colormap` or str + A colormap instance or the name of a registered colormap. + + See Also + -------- + colormaps + get_cmap + """ + cmap = get_cmap(cmap) + + rc('image', cmap=cmap.name) + im = gci() + + if im is not None: + im.set_cmap(cmap) + + +@_copy_docstring_and_deprecators(matplotlib.image.imread) +def imread( + fname: str | pathlib.Path | BinaryIO, format: str | None = None +) -> np.ndarray: + return matplotlib.image.imread(fname, format) + + +@_copy_docstring_and_deprecators(matplotlib.image.imsave) +def imsave( + fname: str | os.PathLike | BinaryIO, arr: ArrayLike, **kwargs +) -> None: + matplotlib.image.imsave(fname, arr, **kwargs) + + +def matshow(A: ArrayLike, fignum: None | int = None, **kwargs) -> AxesImage: + """ + Display a 2D array as a matrix in a new figure window. + + The origin is set at the upper left hand corner. + The indexing is ``(row, column)`` so that the first index runs vertically + and the second index runs horizontally in the figure: + + .. code-block:: none + + A[0, 0] ⋯ A[0, M-1] + ⋮ ⋮ + A[N-1, 0] ⋯ A[N-1, M-1] + + The aspect ratio of the figure window is that of the array, + unless this would make an excessively short or narrow figure. + + Tick labels for the xaxis are placed on top. + + Parameters + ---------- + A : 2D array-like + The matrix to be displayed. + + fignum : None or int + If *None*, create a new, appropriately sized figure window. + + If 0, use the current Axes (creating one if there is none, without ever + adjusting the figure size). + + Otherwise, create a new Axes on the figure with the given number + (creating it at the appropriate size if it does not exist, but not + adjusting the figure size otherwise). Note that this will be drawn on + top of any preexisting Axes on the figure. + + Returns + ------- + `~matplotlib.image.AxesImage` + + Other Parameters + ---------------- + **kwargs : `~matplotlib.axes.Axes.imshow` arguments + + """ + A = np.asanyarray(A) + if fignum == 0: + ax = gca() + else: + # Extract actual aspect ratio of array and make appropriately sized + # figure. + fig = figure(fignum, figsize=figaspect(A)) + ax = fig.add_axes((0.15, 0.09, 0.775, 0.775)) + im = ax.matshow(A, **kwargs) + sci(im) + return im + + +def polar(*args, **kwargs) -> list[Line2D]: + """ + Make a polar plot. + + call signature:: + + polar(theta, r, **kwargs) + + Multiple *theta*, *r* arguments are supported, with format strings, as in + `plot`. + """ + # If an axis already exists, check if it has a polar projection + if gcf().get_axes(): + ax = gca() + if not isinstance(ax, PolarAxes): + _api.warn_external('Trying to create polar plot on an Axes ' + 'that does not have a polar projection.') + else: + ax = axes(projection="polar") + return ax.plot(*args, **kwargs) + + +# If rcParams['backend_fallback'] is true, and an interactive backend is +# requested, ignore rcParams['backend'] and force selection of a backend that +# is compatible with the current running interactive framework. +if (rcParams["backend_fallback"] + and rcParams._get_backend_or_none() in ( # type: ignore[attr-defined] + set(backend_registry.list_builtin(BackendFilter.INTERACTIVE)) - + {'webagg', 'nbagg'}) + and cbook._get_running_interactive_framework()): + rcParams._set("backend", rcsetup._auto_backend_sentinel) + +# fmt: on + +################# REMAINING CONTENT GENERATED BY boilerplate.py ############## + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Figure.figimage) +def figimage( + X: ArrayLike, + xo: int = 0, + yo: int = 0, + alpha: float | None = None, + norm: str | Normalize | None = None, + cmap: str | Colormap | None = None, + vmin: float | None = None, + vmax: float | None = None, + origin: Literal["upper", "lower"] | None = None, + resize: bool = False, + **kwargs, +) -> FigureImage: + return gcf().figimage( + X, + xo=xo, + yo=yo, + alpha=alpha, + norm=norm, + cmap=cmap, + vmin=vmin, + vmax=vmax, + origin=origin, + resize=resize, + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Figure.text) +def figtext( + x: float, y: float, s: str, fontdict: dict[str, Any] | None = None, **kwargs +) -> Text: + return gcf().text(x, y, s, fontdict=fontdict, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Figure.gca) +def gca() -> Axes: + return gcf().gca() + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Figure._gci) +def gci() -> ScalarMappable | None: + return gcf()._gci() + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Figure.ginput) +def ginput( + n: int = 1, + timeout: float = 30, + show_clicks: bool = True, + mouse_add: MouseButton = MouseButton.LEFT, + mouse_pop: MouseButton = MouseButton.RIGHT, + mouse_stop: MouseButton = MouseButton.MIDDLE, +) -> list[tuple[int, int]]: + return gcf().ginput( + n=n, + timeout=timeout, + show_clicks=show_clicks, + mouse_add=mouse_add, + mouse_pop=mouse_pop, + mouse_stop=mouse_stop, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Figure.subplots_adjust) +def subplots_adjust( + left: float | None = None, + bottom: float | None = None, + right: float | None = None, + top: float | None = None, + wspace: float | None = None, + hspace: float | None = None, +) -> None: + gcf().subplots_adjust( + left=left, bottom=bottom, right=right, top=top, wspace=wspace, hspace=hspace + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Figure.suptitle) +def suptitle(t: str, **kwargs) -> Text: + return gcf().suptitle(t, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Figure.tight_layout) +def tight_layout( + *, + pad: float = 1.08, + h_pad: float | None = None, + w_pad: float | None = None, + rect: tuple[float, float, float, float] | None = None, +) -> None: + gcf().tight_layout(pad=pad, h_pad=h_pad, w_pad=w_pad, rect=rect) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Figure.waitforbuttonpress) +def waitforbuttonpress(timeout: float = -1) -> None | bool: + return gcf().waitforbuttonpress(timeout=timeout) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.acorr) +def acorr( + x: ArrayLike, *, data=None, **kwargs +) -> tuple[np.ndarray, np.ndarray, LineCollection | Line2D, Line2D | None]: + return gca().acorr(x, **({"data": data} if data is not None else {}), **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.angle_spectrum) +def angle_spectrum( + x: ArrayLike, + Fs: float | None = None, + Fc: int | None = None, + window: Callable[[ArrayLike], ArrayLike] | ArrayLike | None = None, + pad_to: int | None = None, + sides: Literal["default", "onesided", "twosided"] | None = None, + *, + data=None, + **kwargs, +) -> tuple[np.ndarray, np.ndarray, Line2D]: + return gca().angle_spectrum( + x, + Fs=Fs, + Fc=Fc, + window=window, + pad_to=pad_to, + sides=sides, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.annotate) +def annotate( + text: str, + xy: tuple[float, float], + xytext: tuple[float, float] | None = None, + xycoords: str + | Artist + | Transform + | Callable[[RendererBase], Bbox | Transform] + | tuple[float, float] = "data", + textcoords: str + | Artist + | Transform + | Callable[[RendererBase], Bbox | Transform] + | tuple[float, float] + | None = None, + arrowprops: dict[str, Any] | None = None, + annotation_clip: bool | None = None, + **kwargs, +) -> Annotation: + return gca().annotate( + text, + xy, + xytext=xytext, + xycoords=xycoords, + textcoords=textcoords, + arrowprops=arrowprops, + annotation_clip=annotation_clip, + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.arrow) +def arrow(x: float, y: float, dx: float, dy: float, **kwargs) -> FancyArrow: + return gca().arrow(x, y, dx, dy, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.autoscale) +def autoscale( + enable: bool = True, + axis: Literal["both", "x", "y"] = "both", + tight: bool | None = None, +) -> None: + gca().autoscale(enable=enable, axis=axis, tight=tight) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.axhline) +def axhline(y: float = 0, xmin: float = 0, xmax: float = 1, **kwargs) -> Line2D: + return gca().axhline(y=y, xmin=xmin, xmax=xmax, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.axhspan) +def axhspan( + ymin: float, ymax: float, xmin: float = 0, xmax: float = 1, **kwargs +) -> Rectangle: + return gca().axhspan(ymin, ymax, xmin=xmin, xmax=xmax, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.axis) +def axis( + arg: tuple[float, float, float, float] | bool | str | None = None, + /, + *, + emit: bool = True, + **kwargs, +) -> tuple[float, float, float, float]: + return gca().axis(arg, emit=emit, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.axline) +def axline( + xy1: tuple[float, float], + xy2: tuple[float, float] | None = None, + *, + slope: float | None = None, + **kwargs, +) -> AxLine: + return gca().axline(xy1, xy2=xy2, slope=slope, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.axvline) +def axvline(x: float = 0, ymin: float = 0, ymax: float = 1, **kwargs) -> Line2D: + return gca().axvline(x=x, ymin=ymin, ymax=ymax, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.axvspan) +def axvspan( + xmin: float, xmax: float, ymin: float = 0, ymax: float = 1, **kwargs +) -> Rectangle: + return gca().axvspan(xmin, xmax, ymin=ymin, ymax=ymax, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.bar) +def bar( + x: float | ArrayLike, + height: float | ArrayLike, + width: float | ArrayLike = 0.8, + bottom: float | ArrayLike | None = None, + *, + align: Literal["center", "edge"] = "center", + data=None, + **kwargs, +) -> BarContainer: + return gca().bar( + x, + height, + width=width, + bottom=bottom, + align=align, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.barbs) +def barbs(*args, data=None, **kwargs) -> Barbs: + return gca().barbs(*args, **({"data": data} if data is not None else {}), **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.barh) +def barh( + y: float | ArrayLike, + width: float | ArrayLike, + height: float | ArrayLike = 0.8, + left: float | ArrayLike | None = None, + *, + align: Literal["center", "edge"] = "center", + data=None, + **kwargs, +) -> BarContainer: + return gca().barh( + y, + width, + height=height, + left=left, + align=align, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.bar_label) +def bar_label( + container: BarContainer, + labels: ArrayLike | None = None, + *, + fmt: str | Callable[[float], str] = "%g", + label_type: Literal["center", "edge"] = "edge", + padding: float = 0, + **kwargs, +) -> list[Annotation]: + return gca().bar_label( + container, + labels=labels, + fmt=fmt, + label_type=label_type, + padding=padding, + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.boxplot) +def boxplot( + x: ArrayLike | Sequence[ArrayLike], + notch: bool | None = None, + sym: str | None = None, + vert: bool | None = None, + whis: float | tuple[float, float] | None = None, + positions: ArrayLike | None = None, + widths: float | ArrayLike | None = None, + patch_artist: bool | None = None, + bootstrap: int | None = None, + usermedians: ArrayLike | None = None, + conf_intervals: ArrayLike | None = None, + meanline: bool | None = None, + showmeans: bool | None = None, + showcaps: bool | None = None, + showbox: bool | None = None, + showfliers: bool | None = None, + boxprops: dict[str, Any] | None = None, + tick_labels: Sequence[str] | None = None, + flierprops: dict[str, Any] | None = None, + medianprops: dict[str, Any] | None = None, + meanprops: dict[str, Any] | None = None, + capprops: dict[str, Any] | None = None, + whiskerprops: dict[str, Any] | None = None, + manage_ticks: bool = True, + autorange: bool = False, + zorder: float | None = None, + capwidths: float | ArrayLike | None = None, + label: Sequence[str] | None = None, + *, + data=None, +) -> dict[str, Any]: + return gca().boxplot( + x, + notch=notch, + sym=sym, + vert=vert, + whis=whis, + positions=positions, + widths=widths, + patch_artist=patch_artist, + bootstrap=bootstrap, + usermedians=usermedians, + conf_intervals=conf_intervals, + meanline=meanline, + showmeans=showmeans, + showcaps=showcaps, + showbox=showbox, + showfliers=showfliers, + boxprops=boxprops, + tick_labels=tick_labels, + flierprops=flierprops, + medianprops=medianprops, + meanprops=meanprops, + capprops=capprops, + whiskerprops=whiskerprops, + manage_ticks=manage_ticks, + autorange=autorange, + zorder=zorder, + capwidths=capwidths, + label=label, + **({"data": data} if data is not None else {}), + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.broken_barh) +def broken_barh( + xranges: Sequence[tuple[float, float]], + yrange: tuple[float, float], + *, + data=None, + **kwargs, +) -> PolyCollection: + return gca().broken_barh( + xranges, yrange, **({"data": data} if data is not None else {}), **kwargs + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.clabel) +def clabel(CS: ContourSet, levels: ArrayLike | None = None, **kwargs) -> list[Text]: + return gca().clabel(CS, levels=levels, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.cohere) +def cohere( + x: ArrayLike, + y: ArrayLike, + NFFT: int = 256, + Fs: float = 2, + Fc: int = 0, + detrend: Literal["none", "mean", "linear"] + | Callable[[ArrayLike], ArrayLike] = mlab.detrend_none, + window: Callable[[ArrayLike], ArrayLike] | ArrayLike = mlab.window_hanning, + noverlap: int = 0, + pad_to: int | None = None, + sides: Literal["default", "onesided", "twosided"] = "default", + scale_by_freq: bool | None = None, + *, + data=None, + **kwargs, +) -> tuple[np.ndarray, np.ndarray]: + return gca().cohere( + x, + y, + NFFT=NFFT, + Fs=Fs, + Fc=Fc, + detrend=detrend, + window=window, + noverlap=noverlap, + pad_to=pad_to, + sides=sides, + scale_by_freq=scale_by_freq, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.contour) +def contour(*args, data=None, **kwargs) -> QuadContourSet: + __ret = gca().contour( + *args, **({"data": data} if data is not None else {}), **kwargs + ) + if __ret._A is not None: # type: ignore[attr-defined] + sci(__ret) + return __ret + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.contourf) +def contourf(*args, data=None, **kwargs) -> QuadContourSet: + __ret = gca().contourf( + *args, **({"data": data} if data is not None else {}), **kwargs + ) + if __ret._A is not None: # type: ignore[attr-defined] + sci(__ret) + return __ret + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.csd) +def csd( + x: ArrayLike, + y: ArrayLike, + NFFT: int | None = None, + Fs: float | None = None, + Fc: int | None = None, + detrend: Literal["none", "mean", "linear"] + | Callable[[ArrayLike], ArrayLike] + | None = None, + window: Callable[[ArrayLike], ArrayLike] | ArrayLike | None = None, + noverlap: int | None = None, + pad_to: int | None = None, + sides: Literal["default", "onesided", "twosided"] | None = None, + scale_by_freq: bool | None = None, + return_line: bool | None = None, + *, + data=None, + **kwargs, +) -> tuple[np.ndarray, np.ndarray] | tuple[np.ndarray, np.ndarray, Line2D]: + return gca().csd( + x, + y, + NFFT=NFFT, + Fs=Fs, + Fc=Fc, + detrend=detrend, + window=window, + noverlap=noverlap, + pad_to=pad_to, + sides=sides, + scale_by_freq=scale_by_freq, + return_line=return_line, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.ecdf) +def ecdf( + x: ArrayLike, + weights: ArrayLike | None = None, + *, + complementary: bool = False, + orientation: Literal["vertical", "horizonatal"] = "vertical", + compress: bool = False, + data=None, + **kwargs, +) -> Line2D: + return gca().ecdf( + x, + weights=weights, + complementary=complementary, + orientation=orientation, + compress=compress, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.errorbar) +def errorbar( + x: float | ArrayLike, + y: float | ArrayLike, + yerr: float | ArrayLike | None = None, + xerr: float | ArrayLike | None = None, + fmt: str = "", + ecolor: ColorType | None = None, + elinewidth: float | None = None, + capsize: float | None = None, + barsabove: bool = False, + lolims: bool | ArrayLike = False, + uplims: bool | ArrayLike = False, + xlolims: bool | ArrayLike = False, + xuplims: bool | ArrayLike = False, + errorevery: int | tuple[int, int] = 1, + capthick: float | None = None, + *, + data=None, + **kwargs, +) -> ErrorbarContainer: + return gca().errorbar( + x, + y, + yerr=yerr, + xerr=xerr, + fmt=fmt, + ecolor=ecolor, + elinewidth=elinewidth, + capsize=capsize, + barsabove=barsabove, + lolims=lolims, + uplims=uplims, + xlolims=xlolims, + xuplims=xuplims, + errorevery=errorevery, + capthick=capthick, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.eventplot) +def eventplot( + positions: ArrayLike | Sequence[ArrayLike], + orientation: Literal["horizontal", "vertical"] = "horizontal", + lineoffsets: float | Sequence[float] = 1, + linelengths: float | Sequence[float] = 1, + linewidths: float | Sequence[float] | None = None, + colors: ColorType | Sequence[ColorType] | None = None, + alpha: float | Sequence[float] | None = None, + linestyles: LineStyleType | Sequence[LineStyleType] = "solid", + *, + data=None, + **kwargs, +) -> EventCollection: + return gca().eventplot( + positions, + orientation=orientation, + lineoffsets=lineoffsets, + linelengths=linelengths, + linewidths=linewidths, + colors=colors, + alpha=alpha, + linestyles=linestyles, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.fill) +def fill(*args, data=None, **kwargs) -> list[Polygon]: + return gca().fill(*args, **({"data": data} if data is not None else {}), **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.fill_between) +def fill_between( + x: ArrayLike, + y1: ArrayLike | float, + y2: ArrayLike | float = 0, + where: Sequence[bool] | None = None, + interpolate: bool = False, + step: Literal["pre", "post", "mid"] | None = None, + *, + data=None, + **kwargs, +) -> PolyCollection: + return gca().fill_between( + x, + y1, + y2=y2, + where=where, + interpolate=interpolate, + step=step, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.fill_betweenx) +def fill_betweenx( + y: ArrayLike, + x1: ArrayLike | float, + x2: ArrayLike | float = 0, + where: Sequence[bool] | None = None, + step: Literal["pre", "post", "mid"] | None = None, + interpolate: bool = False, + *, + data=None, + **kwargs, +) -> PolyCollection: + return gca().fill_betweenx( + y, + x1, + x2=x2, + where=where, + step=step, + interpolate=interpolate, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.grid) +def grid( + visible: bool | None = None, + which: Literal["major", "minor", "both"] = "major", + axis: Literal["both", "x", "y"] = "both", + **kwargs, +) -> None: + gca().grid(visible=visible, which=which, axis=axis, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.hexbin) +def hexbin( + x: ArrayLike, + y: ArrayLike, + C: ArrayLike | None = None, + gridsize: int | tuple[int, int] = 100, + bins: Literal["log"] | int | Sequence[float] | None = None, + xscale: Literal["linear", "log"] = "linear", + yscale: Literal["linear", "log"] = "linear", + extent: tuple[float, float, float, float] | None = None, + cmap: str | Colormap | None = None, + norm: str | Normalize | None = None, + vmin: float | None = None, + vmax: float | None = None, + alpha: float | None = None, + linewidths: float | None = None, + edgecolors: Literal["face", "none"] | ColorType = "face", + reduce_C_function: Callable[[np.ndarray | list[float]], float] = np.mean, + mincnt: int | None = None, + marginals: bool = False, + *, + data=None, + **kwargs, +) -> PolyCollection: + __ret = gca().hexbin( + x, + y, + C=C, + gridsize=gridsize, + bins=bins, + xscale=xscale, + yscale=yscale, + extent=extent, + cmap=cmap, + norm=norm, + vmin=vmin, + vmax=vmax, + alpha=alpha, + linewidths=linewidths, + edgecolors=edgecolors, + reduce_C_function=reduce_C_function, + mincnt=mincnt, + marginals=marginals, + **({"data": data} if data is not None else {}), + **kwargs, + ) + sci(__ret) + return __ret + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.hist) +def hist( + x: ArrayLike | Sequence[ArrayLike], + bins: int | Sequence[float] | str | None = None, + range: tuple[float, float] | None = None, + density: bool = False, + weights: ArrayLike | None = None, + cumulative: bool | float = False, + bottom: ArrayLike | float | None = None, + histtype: Literal["bar", "barstacked", "step", "stepfilled"] = "bar", + align: Literal["left", "mid", "right"] = "mid", + orientation: Literal["vertical", "horizontal"] = "vertical", + rwidth: float | None = None, + log: bool = False, + color: ColorType | Sequence[ColorType] | None = None, + label: str | Sequence[str] | None = None, + stacked: bool = False, + *, + data=None, + **kwargs, +) -> tuple[ + np.ndarray | list[np.ndarray], + np.ndarray, + BarContainer | Polygon | list[BarContainer | Polygon], +]: + return gca().hist( + x, + bins=bins, + range=range, + density=density, + weights=weights, + cumulative=cumulative, + bottom=bottom, + histtype=histtype, + align=align, + orientation=orientation, + rwidth=rwidth, + log=log, + color=color, + label=label, + stacked=stacked, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.stairs) +def stairs( + values: ArrayLike, + edges: ArrayLike | None = None, + *, + orientation: Literal["vertical", "horizontal"] = "vertical", + baseline: float | ArrayLike | None = 0, + fill: bool = False, + data=None, + **kwargs, +) -> StepPatch: + return gca().stairs( + values, + edges=edges, + orientation=orientation, + baseline=baseline, + fill=fill, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.hist2d) +def hist2d( + x: ArrayLike, + y: ArrayLike, + bins: None | int | tuple[int, int] | ArrayLike | tuple[ArrayLike, ArrayLike] = 10, + range: ArrayLike | None = None, + density: bool = False, + weights: ArrayLike | None = None, + cmin: float | None = None, + cmax: float | None = None, + *, + data=None, + **kwargs, +) -> tuple[np.ndarray, np.ndarray, np.ndarray, QuadMesh]: + __ret = gca().hist2d( + x, + y, + bins=bins, + range=range, + density=density, + weights=weights, + cmin=cmin, + cmax=cmax, + **({"data": data} if data is not None else {}), + **kwargs, + ) + sci(__ret[-1]) + return __ret + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.hlines) +def hlines( + y: float | ArrayLike, + xmin: float | ArrayLike, + xmax: float | ArrayLike, + colors: ColorType | Sequence[ColorType] | None = None, + linestyles: LineStyleType = "solid", + label: str = "", + *, + data=None, + **kwargs, +) -> LineCollection: + return gca().hlines( + y, + xmin, + xmax, + colors=colors, + linestyles=linestyles, + label=label, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.imshow) +def imshow( + X: ArrayLike | PIL.Image.Image, + cmap: str | Colormap | None = None, + norm: str | Normalize | None = None, + *, + aspect: Literal["equal", "auto"] | float | None = None, + interpolation: str | None = None, + alpha: float | ArrayLike | None = None, + vmin: float | None = None, + vmax: float | None = None, + origin: Literal["upper", "lower"] | None = None, + extent: tuple[float, float, float, float] | None = None, + interpolation_stage: Literal["data", "rgba"] | None = None, + filternorm: bool = True, + filterrad: float = 4.0, + resample: bool | None = None, + url: str | None = None, + data=None, + **kwargs, +) -> AxesImage: + __ret = gca().imshow( + X, + cmap=cmap, + norm=norm, + aspect=aspect, + interpolation=interpolation, + alpha=alpha, + vmin=vmin, + vmax=vmax, + origin=origin, + extent=extent, + interpolation_stage=interpolation_stage, + filternorm=filternorm, + filterrad=filterrad, + resample=resample, + url=url, + **({"data": data} if data is not None else {}), + **kwargs, + ) + sci(__ret) + return __ret + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.legend) +def legend(*args, **kwargs) -> Legend: + return gca().legend(*args, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.locator_params) +def locator_params( + axis: Literal["both", "x", "y"] = "both", tight: bool | None = None, **kwargs +) -> None: + gca().locator_params(axis=axis, tight=tight, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.loglog) +def loglog(*args, **kwargs) -> list[Line2D]: + return gca().loglog(*args, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.magnitude_spectrum) +def magnitude_spectrum( + x: ArrayLike, + Fs: float | None = None, + Fc: int | None = None, + window: Callable[[ArrayLike], ArrayLike] | ArrayLike | None = None, + pad_to: int | None = None, + sides: Literal["default", "onesided", "twosided"] | None = None, + scale: Literal["default", "linear", "dB"] | None = None, + *, + data=None, + **kwargs, +) -> tuple[np.ndarray, np.ndarray, Line2D]: + return gca().magnitude_spectrum( + x, + Fs=Fs, + Fc=Fc, + window=window, + pad_to=pad_to, + sides=sides, + scale=scale, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.margins) +def margins( + *margins: float, + x: float | None = None, + y: float | None = None, + tight: bool | None = True, +) -> tuple[float, float] | None: + return gca().margins(*margins, x=x, y=y, tight=tight) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.minorticks_off) +def minorticks_off() -> None: + gca().minorticks_off() + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.minorticks_on) +def minorticks_on() -> None: + gca().minorticks_on() + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.pcolor) +def pcolor( + *args: ArrayLike, + shading: Literal["flat", "nearest", "auto"] | None = None, + alpha: float | None = None, + norm: str | Normalize | None = None, + cmap: str | Colormap | None = None, + vmin: float | None = None, + vmax: float | None = None, + data=None, + **kwargs, +) -> Collection: + __ret = gca().pcolor( + *args, + shading=shading, + alpha=alpha, + norm=norm, + cmap=cmap, + vmin=vmin, + vmax=vmax, + **({"data": data} if data is not None else {}), + **kwargs, + ) + sci(__ret) + return __ret + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.pcolormesh) +def pcolormesh( + *args: ArrayLike, + alpha: float | None = None, + norm: str | Normalize | None = None, + cmap: str | Colormap | None = None, + vmin: float | None = None, + vmax: float | None = None, + shading: Literal["flat", "nearest", "gouraud", "auto"] | None = None, + antialiased: bool = False, + data=None, + **kwargs, +) -> QuadMesh: + __ret = gca().pcolormesh( + *args, + alpha=alpha, + norm=norm, + cmap=cmap, + vmin=vmin, + vmax=vmax, + shading=shading, + antialiased=antialiased, + **({"data": data} if data is not None else {}), + **kwargs, + ) + sci(__ret) + return __ret + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.phase_spectrum) +def phase_spectrum( + x: ArrayLike, + Fs: float | None = None, + Fc: int | None = None, + window: Callable[[ArrayLike], ArrayLike] | ArrayLike | None = None, + pad_to: int | None = None, + sides: Literal["default", "onesided", "twosided"] | None = None, + *, + data=None, + **kwargs, +) -> tuple[np.ndarray, np.ndarray, Line2D]: + return gca().phase_spectrum( + x, + Fs=Fs, + Fc=Fc, + window=window, + pad_to=pad_to, + sides=sides, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.pie) +def pie( + x: ArrayLike, + explode: ArrayLike | None = None, + labels: Sequence[str] | None = None, + colors: ColorType | Sequence[ColorType] | None = None, + autopct: str | Callable[[float], str] | None = None, + pctdistance: float = 0.6, + shadow: bool = False, + labeldistance: float | None = 1.1, + startangle: float = 0, + radius: float = 1, + counterclock: bool = True, + wedgeprops: dict[str, Any] | None = None, + textprops: dict[str, Any] | None = None, + center: tuple[float, float] = (0, 0), + frame: bool = False, + rotatelabels: bool = False, + *, + normalize: bool = True, + hatch: str | Sequence[str] | None = None, + data=None, +) -> tuple[list[Wedge], list[Text]] | tuple[list[Wedge], list[Text], list[Text]]: + return gca().pie( + x, + explode=explode, + labels=labels, + colors=colors, + autopct=autopct, + pctdistance=pctdistance, + shadow=shadow, + labeldistance=labeldistance, + startangle=startangle, + radius=radius, + counterclock=counterclock, + wedgeprops=wedgeprops, + textprops=textprops, + center=center, + frame=frame, + rotatelabels=rotatelabels, + normalize=normalize, + hatch=hatch, + **({"data": data} if data is not None else {}), + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.plot) +def plot( + *args: float | ArrayLike | str, + scalex: bool = True, + scaley: bool = True, + data=None, + **kwargs, +) -> list[Line2D]: + return gca().plot( + *args, + scalex=scalex, + scaley=scaley, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.plot_date) +def plot_date( + x: ArrayLike, + y: ArrayLike, + fmt: str = "o", + tz: str | datetime.tzinfo | None = None, + xdate: bool = True, + ydate: bool = False, + *, + data=None, + **kwargs, +) -> list[Line2D]: + return gca().plot_date( + x, + y, + fmt=fmt, + tz=tz, + xdate=xdate, + ydate=ydate, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.psd) +def psd( + x: ArrayLike, + NFFT: int | None = None, + Fs: float | None = None, + Fc: int | None = None, + detrend: Literal["none", "mean", "linear"] + | Callable[[ArrayLike], ArrayLike] + | None = None, + window: Callable[[ArrayLike], ArrayLike] | ArrayLike | None = None, + noverlap: int | None = None, + pad_to: int | None = None, + sides: Literal["default", "onesided", "twosided"] | None = None, + scale_by_freq: bool | None = None, + return_line: bool | None = None, + *, + data=None, + **kwargs, +) -> tuple[np.ndarray, np.ndarray] | tuple[np.ndarray, np.ndarray, Line2D]: + return gca().psd( + x, + NFFT=NFFT, + Fs=Fs, + Fc=Fc, + detrend=detrend, + window=window, + noverlap=noverlap, + pad_to=pad_to, + sides=sides, + scale_by_freq=scale_by_freq, + return_line=return_line, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.quiver) +def quiver(*args, data=None, **kwargs) -> Quiver: + __ret = gca().quiver( + *args, **({"data": data} if data is not None else {}), **kwargs + ) + sci(__ret) + return __ret + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.quiverkey) +def quiverkey( + Q: Quiver, X: float, Y: float, U: float, label: str, **kwargs +) -> QuiverKey: + return gca().quiverkey(Q, X, Y, U, label, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.scatter) +def scatter( + x: float | ArrayLike, + y: float | ArrayLike, + s: float | ArrayLike | None = None, + c: ArrayLike | Sequence[ColorType] | ColorType | None = None, + marker: MarkerType | None = None, + cmap: str | Colormap | None = None, + norm: str | Normalize | None = None, + vmin: float | None = None, + vmax: float | None = None, + alpha: float | None = None, + linewidths: float | Sequence[float] | None = None, + *, + edgecolors: Literal["face", "none"] | ColorType | Sequence[ColorType] | None = None, + plotnonfinite: bool = False, + data=None, + **kwargs, +) -> PathCollection: + __ret = gca().scatter( + x, + y, + s=s, + c=c, + marker=marker, + cmap=cmap, + norm=norm, + vmin=vmin, + vmax=vmax, + alpha=alpha, + linewidths=linewidths, + edgecolors=edgecolors, + plotnonfinite=plotnonfinite, + **({"data": data} if data is not None else {}), + **kwargs, + ) + sci(__ret) + return __ret + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.semilogx) +def semilogx(*args, **kwargs) -> list[Line2D]: + return gca().semilogx(*args, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.semilogy) +def semilogy(*args, **kwargs) -> list[Line2D]: + return gca().semilogy(*args, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.specgram) +def specgram( + x: ArrayLike, + NFFT: int | None = None, + Fs: float | None = None, + Fc: int | None = None, + detrend: Literal["none", "mean", "linear"] + | Callable[[ArrayLike], ArrayLike] + | None = None, + window: Callable[[ArrayLike], ArrayLike] | ArrayLike | None = None, + noverlap: int | None = None, + cmap: str | Colormap | None = None, + xextent: tuple[float, float] | None = None, + pad_to: int | None = None, + sides: Literal["default", "onesided", "twosided"] | None = None, + scale_by_freq: bool | None = None, + mode: Literal["default", "psd", "magnitude", "angle", "phase"] | None = None, + scale: Literal["default", "linear", "dB"] | None = None, + vmin: float | None = None, + vmax: float | None = None, + *, + data=None, + **kwargs, +) -> tuple[np.ndarray, np.ndarray, np.ndarray, AxesImage]: + __ret = gca().specgram( + x, + NFFT=NFFT, + Fs=Fs, + Fc=Fc, + detrend=detrend, + window=window, + noverlap=noverlap, + cmap=cmap, + xextent=xextent, + pad_to=pad_to, + sides=sides, + scale_by_freq=scale_by_freq, + mode=mode, + scale=scale, + vmin=vmin, + vmax=vmax, + **({"data": data} if data is not None else {}), + **kwargs, + ) + sci(__ret[-1]) + return __ret + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.spy) +def spy( + Z: ArrayLike, + precision: float | Literal["present"] = 0, + marker: str | None = None, + markersize: float | None = None, + aspect: Literal["equal", "auto"] | float | None = "equal", + origin: Literal["upper", "lower"] = "upper", + **kwargs, +) -> AxesImage: + __ret = gca().spy( + Z, + precision=precision, + marker=marker, + markersize=markersize, + aspect=aspect, + origin=origin, + **kwargs, + ) + if isinstance(__ret, cm.ScalarMappable): + sci(__ret) # noqa + return __ret + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.stackplot) +def stackplot( + x, *args, labels=(), colors=None, hatch=None, baseline="zero", data=None, **kwargs +): + return gca().stackplot( + x, + *args, + labels=labels, + colors=colors, + hatch=hatch, + baseline=baseline, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.stem) +def stem( + *args: ArrayLike | str, + linefmt: str | None = None, + markerfmt: str | None = None, + basefmt: str | None = None, + bottom: float = 0, + label: str | None = None, + orientation: Literal["vertical", "horizontal"] = "vertical", + data=None, +) -> StemContainer: + return gca().stem( + *args, + linefmt=linefmt, + markerfmt=markerfmt, + basefmt=basefmt, + bottom=bottom, + label=label, + orientation=orientation, + **({"data": data} if data is not None else {}), + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.step) +def step( + x: ArrayLike, + y: ArrayLike, + *args, + where: Literal["pre", "post", "mid"] = "pre", + data=None, + **kwargs, +) -> list[Line2D]: + return gca().step( + x, + y, + *args, + where=where, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.streamplot) +def streamplot( + x, + y, + u, + v, + density=1, + linewidth=None, + color=None, + cmap=None, + norm=None, + arrowsize=1, + arrowstyle="-|>", + minlength=0.1, + transform=None, + zorder=None, + start_points=None, + maxlength=4.0, + integration_direction="both", + broken_streamlines=True, + *, + data=None, +): + __ret = gca().streamplot( + x, + y, + u, + v, + density=density, + linewidth=linewidth, + color=color, + cmap=cmap, + norm=norm, + arrowsize=arrowsize, + arrowstyle=arrowstyle, + minlength=minlength, + transform=transform, + zorder=zorder, + start_points=start_points, + maxlength=maxlength, + integration_direction=integration_direction, + broken_streamlines=broken_streamlines, + **({"data": data} if data is not None else {}), + ) + sci(__ret.lines) + return __ret + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.table) +def table( + cellText=None, + cellColours=None, + cellLoc="right", + colWidths=None, + rowLabels=None, + rowColours=None, + rowLoc="left", + colLabels=None, + colColours=None, + colLoc="center", + loc="bottom", + bbox=None, + edges="closed", + **kwargs, +): + return gca().table( + cellText=cellText, + cellColours=cellColours, + cellLoc=cellLoc, + colWidths=colWidths, + rowLabels=rowLabels, + rowColours=rowColours, + rowLoc=rowLoc, + colLabels=colLabels, + colColours=colColours, + colLoc=colLoc, + loc=loc, + bbox=bbox, + edges=edges, + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.text) +def text( + x: float, y: float, s: str, fontdict: dict[str, Any] | None = None, **kwargs +) -> Text: + return gca().text(x, y, s, fontdict=fontdict, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.tick_params) +def tick_params(axis: Literal["both", "x", "y"] = "both", **kwargs) -> None: + gca().tick_params(axis=axis, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.ticklabel_format) +def ticklabel_format( + *, + axis: Literal["both", "x", "y"] = "both", + style: Literal["", "sci", "scientific", "plain"] | None = None, + scilimits: tuple[int, int] | None = None, + useOffset: bool | float | None = None, + useLocale: bool | None = None, + useMathText: bool | None = None, +) -> None: + gca().ticklabel_format( + axis=axis, + style=style, + scilimits=scilimits, + useOffset=useOffset, + useLocale=useLocale, + useMathText=useMathText, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.tricontour) +def tricontour(*args, **kwargs): + __ret = gca().tricontour(*args, **kwargs) + if __ret._A is not None: # type: ignore[attr-defined] + sci(__ret) + return __ret + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.tricontourf) +def tricontourf(*args, **kwargs): + __ret = gca().tricontourf(*args, **kwargs) + if __ret._A is not None: # type: ignore[attr-defined] + sci(__ret) + return __ret + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.tripcolor) +def tripcolor( + *args, + alpha=1.0, + norm=None, + cmap=None, + vmin=None, + vmax=None, + shading="flat", + facecolors=None, + **kwargs, +): + __ret = gca().tripcolor( + *args, + alpha=alpha, + norm=norm, + cmap=cmap, + vmin=vmin, + vmax=vmax, + shading=shading, + facecolors=facecolors, + **kwargs, + ) + sci(__ret) + return __ret + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.triplot) +def triplot(*args, **kwargs): + return gca().triplot(*args, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.violinplot) +def violinplot( + dataset: ArrayLike | Sequence[ArrayLike], + positions: ArrayLike | None = None, + vert: bool = True, + widths: float | ArrayLike = 0.5, + showmeans: bool = False, + showextrema: bool = True, + showmedians: bool = False, + quantiles: Sequence[float | Sequence[float]] | None = None, + points: int = 100, + bw_method: Literal["scott", "silverman"] + | float + | Callable[[GaussianKDE], float] + | None = None, + side: Literal["both", "low", "high"] = "both", + *, + data=None, +) -> dict[str, Collection]: + return gca().violinplot( + dataset, + positions=positions, + vert=vert, + widths=widths, + showmeans=showmeans, + showextrema=showextrema, + showmedians=showmedians, + quantiles=quantiles, + points=points, + bw_method=bw_method, + side=side, + **({"data": data} if data is not None else {}), + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.vlines) +def vlines( + x: float | ArrayLike, + ymin: float | ArrayLike, + ymax: float | ArrayLike, + colors: ColorType | Sequence[ColorType] | None = None, + linestyles: LineStyleType = "solid", + label: str = "", + *, + data=None, + **kwargs, +) -> LineCollection: + return gca().vlines( + x, + ymin, + ymax, + colors=colors, + linestyles=linestyles, + label=label, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.xcorr) +def xcorr( + x: ArrayLike, + y: ArrayLike, + normed: bool = True, + detrend: Callable[[ArrayLike], ArrayLike] = mlab.detrend_none, + usevlines: bool = True, + maxlags: int = 10, + *, + data=None, + **kwargs, +) -> tuple[np.ndarray, np.ndarray, LineCollection | Line2D, Line2D | None]: + return gca().xcorr( + x, + y, + normed=normed, + detrend=detrend, + usevlines=usevlines, + maxlags=maxlags, + **({"data": data} if data is not None else {}), + **kwargs, + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes._sci) +def sci(im: ScalarMappable) -> None: + gca()._sci(im) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.set_title) +def title( + label: str, + fontdict: dict[str, Any] | None = None, + loc: Literal["left", "center", "right"] | None = None, + pad: float | None = None, + *, + y: float | None = None, + **kwargs, +) -> Text: + return gca().set_title(label, fontdict=fontdict, loc=loc, pad=pad, y=y, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.set_xlabel) +def xlabel( + xlabel: str, + fontdict: dict[str, Any] | None = None, + labelpad: float | None = None, + *, + loc: Literal["left", "center", "right"] | None = None, + **kwargs, +) -> Text: + return gca().set_xlabel( + xlabel, fontdict=fontdict, labelpad=labelpad, loc=loc, **kwargs + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.set_ylabel) +def ylabel( + ylabel: str, + fontdict: dict[str, Any] | None = None, + labelpad: float | None = None, + *, + loc: Literal["bottom", "center", "top"] | None = None, + **kwargs, +) -> Text: + return gca().set_ylabel( + ylabel, fontdict=fontdict, labelpad=labelpad, loc=loc, **kwargs + ) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.set_xscale) +def xscale(value: str | ScaleBase, **kwargs) -> None: + gca().set_xscale(value, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +@_copy_docstring_and_deprecators(Axes.set_yscale) +def yscale(value: str | ScaleBase, **kwargs) -> None: + gca().set_yscale(value, **kwargs) + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def autumn() -> None: + """ + Set the colormap to 'autumn'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("autumn") + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def bone() -> None: + """ + Set the colormap to 'bone'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("bone") + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def cool() -> None: + """ + Set the colormap to 'cool'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("cool") + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def copper() -> None: + """ + Set the colormap to 'copper'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("copper") + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def flag() -> None: + """ + Set the colormap to 'flag'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("flag") + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def gray() -> None: + """ + Set the colormap to 'gray'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("gray") + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def hot() -> None: + """ + Set the colormap to 'hot'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("hot") + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def hsv() -> None: + """ + Set the colormap to 'hsv'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("hsv") + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def jet() -> None: + """ + Set the colormap to 'jet'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("jet") + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def pink() -> None: + """ + Set the colormap to 'pink'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("pink") + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def prism() -> None: + """ + Set the colormap to 'prism'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("prism") + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def spring() -> None: + """ + Set the colormap to 'spring'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("spring") + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def summer() -> None: + """ + Set the colormap to 'summer'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("summer") + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def winter() -> None: + """ + Set the colormap to 'winter'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("winter") + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def magma() -> None: + """ + Set the colormap to 'magma'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("magma") + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def inferno() -> None: + """ + Set the colormap to 'inferno'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("inferno") + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def plasma() -> None: + """ + Set the colormap to 'plasma'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("plasma") + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def viridis() -> None: + """ + Set the colormap to 'viridis'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("viridis") + + +# Autogenerated by boilerplate.py. Do not edit as changes will be lost. +def nipy_spectral() -> None: + """ + Set the colormap to 'nipy_spectral'. + + This changes the default colormap as well as the colormap of the current + image if there is one. See ``help(colormaps)`` for more information. + """ + set_cmap("nipy_spectral")