""" This type stub file was generated by pyright. """ import matplotlib as mpl from distutils.version import LooseVersion """Control plot style and scaling using the matplotlib rcParams interface.""" __all__ = ["set_theme", "set", "reset_defaults", "reset_orig", "axes_style", "set_style", "plotting_context", "set_context", "set_palette"] _style_keys = ... _context_keys = ... if LooseVersion(mpl.__version__) >= "3.0": ... def set_theme(context=..., style=..., palette=..., font=..., font_scale=..., color_codes=..., rc=...): # -> None: """Set multiple theme parameters in one step. Each set of parameters can be set directly or temporarily, see the referenced functions below for more information. Parameters ---------- context : string or dict Plotting context parameters, see :func:`plotting_context`. style : string or dict Axes style parameters, see :func:`axes_style`. palette : string or sequence Color palette, see :func:`color_palette`. font : string Font family, see matplotlib font manager. font_scale : float, optional Separate scaling factor to independently scale the size of the font elements. color_codes : bool If ``True`` and ``palette`` is a seaborn palette, remap the shorthand color codes (e.g. "b", "g", "r", etc.) to the colors from this palette. rc : dict or None Dictionary of rc parameter mappings to override the above. """ ... def set(*args, **kwargs): # -> None: """Alias for :func:`set_theme`, which is the preferred interface.""" ... def reset_defaults(): # -> None: """Restore all RC params to default settings.""" ... def reset_orig(): # -> None: """Restore all RC params to original settings (respects custom rc).""" ... def axes_style(style=..., rc=...): # -> _AxesStyle: """Return a parameter dict for the aesthetic style of the plots. This affects things like the color of the axes, whether a grid is enabled by default, and other aesthetic elements. This function returns an object that can be used in a ``with`` statement to temporarily change the style parameters. Parameters ---------- style : dict, None, or one of {darkgrid, whitegrid, dark, white, ticks} A dictionary of parameters or the name of a preconfigured set. rc : dict, optional Parameter mappings to override the values in the preset seaborn style dictionaries. This only updates parameters that are considered part of the style definition. Examples -------- >>> st = axes_style("whitegrid") >>> set_style("ticks", {"xtick.major.size": 8, "ytick.major.size": 8}) >>> import matplotlib.pyplot as plt >>> with axes_style("white"): ... f, ax = plt.subplots() ... ax.plot(x, y) # doctest: +SKIP See Also -------- set_style : set the matplotlib parameters for a seaborn theme plotting_context : return a parameter dict to to scale plot elements color_palette : define the color palette for a plot """ ... def set_style(style=..., rc=...): # -> None: """Set the aesthetic style of the plots. This affects things like the color of the axes, whether a grid is enabled by default, and other aesthetic elements. Parameters ---------- style : dict, None, or one of {darkgrid, whitegrid, dark, white, ticks} A dictionary of parameters or the name of a preconfigured set. rc : dict, optional Parameter mappings to override the values in the preset seaborn style dictionaries. This only updates parameters that are considered part of the style definition. Examples -------- >>> set_style("whitegrid") >>> set_style("ticks", {"xtick.major.size": 8, "ytick.major.size": 8}) See Also -------- axes_style : return a dict of parameters or use in a ``with`` statement to temporarily set the style. set_context : set parameters to scale plot elements set_palette : set the default color palette for figures """ ... def plotting_context(context=..., font_scale=..., rc=...): # -> _PlottingContext: """Return a parameter dict to scale elements of the figure. This affects things like the size of the labels, lines, and other elements of the plot, but not the overall style. The base context is "notebook", and the other contexts are "paper", "talk", and "poster", which are version of the notebook parameters scaled by .8, 1.3, and 1.6, respectively. This function returns an object that can be used in a ``with`` statement to temporarily change the context parameters. Parameters ---------- context : dict, None, or one of {paper, notebook, talk, poster} A dictionary of parameters or the name of a preconfigured set. font_scale : float, optional Separate scaling factor to independently scale the size of the font elements. rc : dict, optional Parameter mappings to override the values in the preset seaborn context dictionaries. This only updates parameters that are considered part of the context definition. Examples -------- >>> c = plotting_context("poster") >>> c = plotting_context("notebook", font_scale=1.5) >>> c = plotting_context("talk", rc={"lines.linewidth": 2}) >>> import matplotlib.pyplot as plt >>> with plotting_context("paper"): ... f, ax = plt.subplots() ... ax.plot(x, y) # doctest: +SKIP See Also -------- set_context : set the matplotlib parameters to scale plot elements axes_style : return a dict of parameters defining a figure style color_palette : define the color palette for a plot """ ... def set_context(context=..., font_scale=..., rc=...): # -> None: """Set the plotting context parameters. This affects things like the size of the labels, lines, and other elements of the plot, but not the overall style. The base context is "notebook", and the other contexts are "paper", "talk", and "poster", which are version of the notebook parameters scaled by .8, 1.3, and 1.6, respectively. Parameters ---------- context : dict, None, or one of {paper, notebook, talk, poster} A dictionary of parameters or the name of a preconfigured set. font_scale : float, optional Separate scaling factor to independently scale the size of the font elements. rc : dict, optional Parameter mappings to override the values in the preset seaborn context dictionaries. This only updates parameters that are considered part of the context definition. Examples -------- >>> set_context("paper") >>> set_context("talk", font_scale=1.4) >>> set_context("talk", rc={"lines.linewidth": 2}) See Also -------- plotting_context : return a dictionary of rc parameters, or use in a ``with`` statement to temporarily set the context. set_style : set the default parameters for figure style set_palette : set the default color palette for figures """ ... class _RCAesthetics(dict): def __enter__(self): # -> None: ... def __exit__(self, exc_type, exc_value, exc_tb): # -> None: ... def __call__(self, func): # -> _Wrapped[..., Unknown, (*args: Unknown, **kwargs: Unknown), Unknown]: ... class _AxesStyle(_RCAesthetics): """Light wrapper on a dict to set style temporarily.""" _keys = ... _set = ... class _PlottingContext(_RCAesthetics): """Light wrapper on a dict to set context temporarily.""" _keys = ... _set = ... def set_palette(palette, n_colors=..., desat=..., color_codes=...): # -> None: """Set the matplotlib color cycle using a seaborn palette. Parameters ---------- palette : seaborn color paltte | matplotlib colormap | hls | husl Palette definition. Should be something that :func:`color_palette` can process. n_colors : int Number of colors in the cycle. The default number of colors will depend on the format of ``palette``, see the :func:`color_palette` documentation for more information. desat : float Proportion to desaturate each color by. color_codes : bool If ``True`` and ``palette`` is a seaborn palette, remap the shorthand color codes (e.g. "b", "g", "r", etc.) to the colors from this palette. Examples -------- >>> set_palette("Reds") >>> set_palette("Set1", 8, .75) See Also -------- color_palette : build a color palette or set the color cycle temporarily in a ``with`` statement. set_context : set parameters to scale plot elements set_style : set the default parameters for figure style """ ...