Initial configuration commit
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typings/seaborn/palettes.pyi
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typings/seaborn/palettes.pyi
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"""
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This type stub file was generated by pyright.
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"""
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__all__ = ["color_palette", "hls_palette", "husl_palette", "mpl_palette", "dark_palette", "light_palette", "diverging_palette", "blend_palette", "xkcd_palette", "crayon_palette", "cubehelix_palette", "set_color_codes"]
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SEABORN_PALETTES = ...
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MPL_QUAL_PALS = ...
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QUAL_PALETTE_SIZES = ...
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QUAL_PALETTES = ...
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class _ColorPalette(list):
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"""Set the color palette in a with statement, otherwise be a list."""
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def __enter__(self): # -> Self@_ColorPalette:
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"""Open the context."""
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...
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def __exit__(self, *args): # -> None:
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"""Close the context."""
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...
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def as_hex(self): # -> _ColorPalette:
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"""Return a color palette with hex codes instead of RGB values."""
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...
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def color_palette(palette=..., n_colors=..., desat=..., as_cmap=...): # -> _ColorPalette | list[tuple[float, float, float]] | Any | list[str]:
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"""Return a list of colors or continuous colormap defining a palette.
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Possible ``palette`` values include:
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- Name of a seaborn palette (deep, muted, bright, pastel, dark, colorblind)
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- Name of matplotlib colormap
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- 'husl' or 'hls'
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- 'ch:<cubehelix arguments>'
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- 'light:<color>', 'dark:<color>', 'blend:<color>,<color>',
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- A sequence of colors in any format matplotlib accepts
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Calling this function with ``palette=None`` will return the current
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matplotlib color cycle.
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This function can also be used in a ``with`` statement to temporarily
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set the color cycle for a plot or set of plots.
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See the :ref:`tutorial <palette_tutorial>` for more information.
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Parameters
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----------
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palette: None, string, or sequence, optional
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Name of palette or None to return current palette. If a sequence, input
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colors are used but possibly cycled and desaturated.
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n_colors : int, optional
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Number of colors in the palette. If ``None``, the default will depend
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on how ``palette`` is specified. Named palettes default to 6 colors,
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but grabbing the current palette or passing in a list of colors will
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not change the number of colors unless this is specified. Asking for
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more colors than exist in the palette will cause it to cycle. Ignored
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when ``as_cmap`` is True.
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desat : float, optional
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Proportion to desaturate each color by.
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as_cmap : bool
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If True, return a :class:`matplotlib.colors.Colormap`.
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Returns
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-------
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list of RGB tuples or :class:`matplotlib.colors.Colormap`
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See Also
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--------
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set_palette : Set the default color cycle for all plots.
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set_color_codes : Reassign color codes like ``"b"``, ``"g"``, etc. to
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colors from one of the seaborn palettes.
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Examples
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--------
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.. include:: ../docstrings/color_palette.rst
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"""
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...
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def hls_palette(n_colors=..., h=..., l=..., s=..., as_cmap=...): # -> _ColorPalette:
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"""Get a set of evenly spaced colors in HLS hue space.
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h, l, and s should be between 0 and 1
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Parameters
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----------
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n_colors : int
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number of colors in the palette
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h : float
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first hue
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l : float
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lightness
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s : float
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saturation
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Returns
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-------
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list of RGB tuples or :class:`matplotlib.colors.Colormap`
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See Also
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--------
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husl_palette : Make a palette using evenly spaced hues in the HUSL system.
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Examples
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--------
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Create a palette of 10 colors with the default parameters:
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.. plot::
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:context: close-figs
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>>> import seaborn as sns; sns.set_theme()
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>>> sns.palplot(sns.hls_palette(10))
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Create a palette of 10 colors that begins at a different hue value:
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.. plot::
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:context: close-figs
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>>> sns.palplot(sns.hls_palette(10, h=.5))
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Create a palette of 10 colors that are darker than the default:
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.. plot::
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:context: close-figs
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>>> sns.palplot(sns.hls_palette(10, l=.4))
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Create a palette of 10 colors that are less saturated than the default:
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.. plot::
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:context: close-figs
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>>> sns.palplot(sns.hls_palette(10, s=.4))
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"""
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...
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def husl_palette(n_colors=..., h=..., s=..., l=..., as_cmap=...): # -> _ColorPalette:
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"""Get a set of evenly spaced colors in HUSL hue space.
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h, s, and l should be between 0 and 1
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Parameters
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----------
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n_colors : int
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number of colors in the palette
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h : float
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first hue
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s : float
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saturation
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l : float
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lightness
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Returns
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-------
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list of RGB tuples or :class:`matplotlib.colors.Colormap`
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See Also
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--------
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hls_palette : Make a palette using evently spaced circular hues in the
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HSL system.
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Examples
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--------
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Create a palette of 10 colors with the default parameters:
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.. plot::
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:context: close-figs
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>>> import seaborn as sns; sns.set_theme()
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>>> sns.palplot(sns.husl_palette(10))
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Create a palette of 10 colors that begins at a different hue value:
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.. plot::
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:context: close-figs
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>>> sns.palplot(sns.husl_palette(10, h=.5))
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Create a palette of 10 colors that are darker than the default:
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.. plot::
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:context: close-figs
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>>> sns.palplot(sns.husl_palette(10, l=.4))
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Create a palette of 10 colors that are less saturated than the default:
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.. plot::
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:context: close-figs
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>>> sns.palplot(sns.husl_palette(10, s=.4))
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"""
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...
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def mpl_palette(name, n_colors=..., as_cmap=...): # -> _ColorPalette:
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"""Return discrete colors from a matplotlib palette.
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Note that this handles the qualitative colorbrewer palettes
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properly, although if you ask for more colors than a particular
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qualitative palette can provide you will get fewer than you are
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expecting. In contrast, asking for qualitative color brewer palettes
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using :func:`color_palette` will return the expected number of colors,
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but they will cycle.
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If you are using the IPython notebook, you can also use the function
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:func:`choose_colorbrewer_palette` to interactively select palettes.
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Parameters
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----------
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name : string
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Name of the palette. This should be a named matplotlib colormap.
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n_colors : int
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Number of discrete colors in the palette.
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Returns
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-------
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list of RGB tuples or :class:`matplotlib.colors.Colormap`
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Examples
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--------
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Create a qualitative colorbrewer palette with 8 colors:
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.. plot::
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:context: close-figs
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>>> import seaborn as sns; sns.set_theme()
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>>> sns.palplot(sns.mpl_palette("Set2", 8))
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Create a sequential colorbrewer palette:
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.. plot::
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:context: close-figs
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>>> sns.palplot(sns.mpl_palette("Blues"))
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Create a diverging palette:
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.. plot::
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:context: close-figs
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>>> sns.palplot(sns.mpl_palette("seismic", 8))
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Create a "dark" sequential palette:
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.. plot::
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:context: close-figs
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>>> sns.palplot(sns.mpl_palette("GnBu_d"))
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"""
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...
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def dark_palette(color, n_colors=..., reverse=..., as_cmap=..., input=...): # -> _ColorPalette:
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"""Make a sequential palette that blends from dark to ``color``.
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This kind of palette is good for data that range between relatively
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uninteresting low values and interesting high values.
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The ``color`` parameter can be specified in a number of ways, including
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all options for defining a color in matplotlib and several additional
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color spaces that are handled by seaborn. You can also use the database
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of named colors from the XKCD color survey.
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If you are using the IPython notebook, you can also choose this palette
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interactively with the :func:`choose_dark_palette` function.
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Parameters
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----------
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color : base color for high values
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hex, rgb-tuple, or html color name
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n_colors : int, optional
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number of colors in the palette
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reverse : bool, optional
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if True, reverse the direction of the blend
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as_cmap : bool, optional
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If True, return a :class:`matplotlib.colors.Colormap`.
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input : {'rgb', 'hls', 'husl', xkcd'}
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Color space to interpret the input color. The first three options
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apply to tuple inputs and the latter applies to string inputs.
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Returns
|
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-------
|
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list of RGB tuples or :class:`matplotlib.colors.Colormap`
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See Also
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--------
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light_palette : Create a sequential palette with bright low values.
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diverging_palette : Create a diverging palette with two colors.
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Examples
|
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--------
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Generate a palette from an HTML color:
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.. plot::
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:context: close-figs
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>>> import seaborn as sns; sns.set_theme()
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>>> sns.palplot(sns.dark_palette("purple"))
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Generate a palette that decreases in lightness:
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.. plot::
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:context: close-figs
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>>> sns.palplot(sns.dark_palette("seagreen", reverse=True))
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Generate a palette from an HUSL-space seed:
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.. plot::
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:context: close-figs
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>>> sns.palplot(sns.dark_palette((260, 75, 60), input="husl"))
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Generate a colormap object:
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.. plot::
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:context: close-figs
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>>> from numpy import arange
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>>> x = arange(25).reshape(5, 5)
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>>> cmap = sns.dark_palette("#2ecc71", as_cmap=True)
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>>> ax = sns.heatmap(x, cmap=cmap)
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"""
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...
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def light_palette(color, n_colors=..., reverse=..., as_cmap=..., input=...): # -> _ColorPalette:
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"""Make a sequential palette that blends from light to ``color``.
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|
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This kind of palette is good for data that range between relatively
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uninteresting low values and interesting high values.
|
||||
|
||||
The ``color`` parameter can be specified in a number of ways, including
|
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all options for defining a color in matplotlib and several additional
|
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color spaces that are handled by seaborn. You can also use the database
|
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of named colors from the XKCD color survey.
|
||||
|
||||
If you are using the IPython notebook, you can also choose this palette
|
||||
interactively with the :func:`choose_light_palette` function.
|
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|
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Parameters
|
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----------
|
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color : base color for high values
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hex code, html color name, or tuple in ``input`` space.
|
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n_colors : int, optional
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number of colors in the palette
|
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reverse : bool, optional
|
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if True, reverse the direction of the blend
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as_cmap : bool, optional
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If True, return a :class:`matplotlib.colors.Colormap`.
|
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input : {'rgb', 'hls', 'husl', xkcd'}
|
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Color space to interpret the input color. The first three options
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apply to tuple inputs and the latter applies to string inputs.
|
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|
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Returns
|
||||
-------
|
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list of RGB tuples or :class:`matplotlib.colors.Colormap`
|
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|
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See Also
|
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--------
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dark_palette : Create a sequential palette with dark low values.
|
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diverging_palette : Create a diverging palette with two colors.
|
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|
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Examples
|
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--------
|
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|
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Generate a palette from an HTML color:
|
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|
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.. plot::
|
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:context: close-figs
|
||||
|
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>>> import seaborn as sns; sns.set_theme()
|
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>>> sns.palplot(sns.light_palette("purple"))
|
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|
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Generate a palette that increases in lightness:
|
||||
|
||||
.. plot::
|
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:context: close-figs
|
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|
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>>> sns.palplot(sns.light_palette("seagreen", reverse=True))
|
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|
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Generate a palette from an HUSL-space seed:
|
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|
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.. plot::
|
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:context: close-figs
|
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|
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>>> sns.palplot(sns.light_palette((260, 75, 60), input="husl"))
|
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|
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Generate a colormap object:
|
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|
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.. plot::
|
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:context: close-figs
|
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|
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>>> from numpy import arange
|
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>>> x = arange(25).reshape(5, 5)
|
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>>> cmap = sns.light_palette("#2ecc71", as_cmap=True)
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>>> ax = sns.heatmap(x, cmap=cmap)
|
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|
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"""
|
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...
|
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def diverging_palette(h_neg, h_pos, s=..., l=..., sep=..., n=..., center=..., as_cmap=...): # -> _ColorPalette:
|
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"""Make a diverging palette between two HUSL colors.
|
||||
|
||||
If you are using the IPython notebook, you can also choose this palette
|
||||
interactively with the :func:`choose_diverging_palette` function.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
h_neg, h_pos : float in [0, 359]
|
||||
Anchor hues for negative and positive extents of the map.
|
||||
s : float in [0, 100], optional
|
||||
Anchor saturation for both extents of the map.
|
||||
l : float in [0, 100], optional
|
||||
Anchor lightness for both extents of the map.
|
||||
sep : int, optional
|
||||
Size of the intermediate region.
|
||||
n : int, optional
|
||||
Number of colors in the palette (if not returning a cmap)
|
||||
center : {"light", "dark"}, optional
|
||||
Whether the center of the palette is light or dark
|
||||
as_cmap : bool, optional
|
||||
If True, return a :class:`matplotlib.colors.Colormap`.
|
||||
|
||||
Returns
|
||||
-------
|
||||
list of RGB tuples or :class:`matplotlib.colors.Colormap`
|
||||
|
||||
See Also
|
||||
--------
|
||||
dark_palette : Create a sequential palette with dark values.
|
||||
light_palette : Create a sequential palette with light values.
|
||||
|
||||
Examples
|
||||
--------
|
||||
|
||||
Generate a blue-white-red palette:
|
||||
|
||||
.. plot::
|
||||
:context: close-figs
|
||||
|
||||
>>> import seaborn as sns; sns.set_theme()
|
||||
>>> sns.palplot(sns.diverging_palette(240, 10, n=9))
|
||||
|
||||
Generate a brighter green-white-purple palette:
|
||||
|
||||
.. plot::
|
||||
:context: close-figs
|
||||
|
||||
>>> sns.palplot(sns.diverging_palette(150, 275, s=80, l=55, n=9))
|
||||
|
||||
Generate a blue-black-red palette:
|
||||
|
||||
.. plot::
|
||||
:context: close-figs
|
||||
|
||||
>>> sns.palplot(sns.diverging_palette(250, 15, s=75, l=40,
|
||||
... n=9, center="dark"))
|
||||
|
||||
Generate a colormap object:
|
||||
|
||||
.. plot::
|
||||
:context: close-figs
|
||||
|
||||
>>> from numpy import arange
|
||||
>>> x = arange(25).reshape(5, 5)
|
||||
>>> cmap = sns.diverging_palette(220, 20, as_cmap=True)
|
||||
>>> ax = sns.heatmap(x, cmap=cmap)
|
||||
|
||||
"""
|
||||
...
|
||||
|
||||
def blend_palette(colors, n_colors=..., as_cmap=..., input=...): # -> _ColorPalette:
|
||||
"""Make a palette that blends between a list of colors.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
colors : sequence of colors in various formats interpreted by ``input``
|
||||
hex code, html color name, or tuple in ``input`` space.
|
||||
n_colors : int, optional
|
||||
Number of colors in the palette.
|
||||
as_cmap : bool, optional
|
||||
If True, return a :class:`matplotlib.colors.Colormap`.
|
||||
|
||||
Returns
|
||||
-------
|
||||
list of RGB tuples or :class:`matplotlib.colors.Colormap`
|
||||
|
||||
"""
|
||||
...
|
||||
|
||||
def xkcd_palette(colors): # -> _ColorPalette | list[tuple[float, float, float]] | Any | list[str]:
|
||||
"""Make a palette with color names from the xkcd color survey.
|
||||
|
||||
See xkcd for the full list of colors: https://xkcd.com/color/rgb/
|
||||
|
||||
This is just a simple wrapper around the ``seaborn.xkcd_rgb`` dictionary.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
colors : list of strings
|
||||
List of keys in the ``seaborn.xkcd_rgb`` dictionary.
|
||||
|
||||
Returns
|
||||
-------
|
||||
palette : seaborn color palette
|
||||
Returns the list of colors as RGB tuples in an object that behaves like
|
||||
other seaborn color palettes.
|
||||
|
||||
See Also
|
||||
--------
|
||||
crayon_palette : Make a palette with Crayola crayon colors.
|
||||
|
||||
"""
|
||||
...
|
||||
|
||||
def crayon_palette(colors): # -> _ColorPalette | list[tuple[float, float, float]] | Any | list[str]:
|
||||
"""Make a palette with color names from Crayola crayons.
|
||||
|
||||
Colors are taken from here:
|
||||
https://en.wikipedia.org/wiki/List_of_Crayola_crayon_colors
|
||||
|
||||
This is just a simple wrapper around the ``seaborn.crayons`` dictionary.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
colors : list of strings
|
||||
List of keys in the ``seaborn.crayons`` dictionary.
|
||||
|
||||
Returns
|
||||
-------
|
||||
palette : seaborn color palette
|
||||
Returns the list of colors as rgb tuples in an object that behaves like
|
||||
other seaborn color palettes.
|
||||
|
||||
See Also
|
||||
--------
|
||||
xkcd_palette : Make a palette with named colors from the XKCD color survey.
|
||||
|
||||
"""
|
||||
...
|
||||
|
||||
def cubehelix_palette(n_colors=..., start=..., rot=..., gamma=..., hue=..., light=..., dark=..., reverse=..., as_cmap=...): # -> _ColorPalette:
|
||||
"""Make a sequential palette from the cubehelix system.
|
||||
|
||||
This produces a colormap with linearly-decreasing (or increasing)
|
||||
brightness. That means that information will be preserved if printed to
|
||||
black and white or viewed by someone who is colorblind. "cubehelix" is
|
||||
also available as a matplotlib-based palette, but this function gives the
|
||||
user more control over the look of the palette and has a different set of
|
||||
defaults.
|
||||
|
||||
In addition to using this function, it is also possible to generate a
|
||||
cubehelix palette generally in seaborn using a string-shorthand; see the
|
||||
example below.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
n_colors : int
|
||||
Number of colors in the palette.
|
||||
start : float, 0 <= start <= 3
|
||||
The hue at the start of the helix.
|
||||
rot : float
|
||||
Rotations around the hue wheel over the range of the palette.
|
||||
gamma : float 0 <= gamma
|
||||
Gamma factor to emphasize darker (gamma < 1) or lighter (gamma > 1)
|
||||
colors.
|
||||
hue : float, 0 <= hue <= 1
|
||||
Saturation of the colors.
|
||||
dark : float 0 <= dark <= 1
|
||||
Intensity of the darkest color in the palette.
|
||||
light : float 0 <= light <= 1
|
||||
Intensity of the lightest color in the palette.
|
||||
reverse : bool
|
||||
If True, the palette will go from dark to light.
|
||||
as_cmap : bool
|
||||
If True, return a :class:`matplotlib.colors.Colormap`.
|
||||
|
||||
Returns
|
||||
-------
|
||||
list of RGB tuples or :class:`matplotlib.colors.Colormap`
|
||||
|
||||
See Also
|
||||
--------
|
||||
choose_cubehelix_palette : Launch an interactive widget to select cubehelix
|
||||
palette parameters.
|
||||
dark_palette : Create a sequential palette with dark low values.
|
||||
light_palette : Create a sequential palette with bright low values.
|
||||
|
||||
References
|
||||
----------
|
||||
Green, D. A. (2011). "A colour scheme for the display of astronomical
|
||||
intensity images". Bulletin of the Astromical Society of India, Vol. 39,
|
||||
p. 289-295.
|
||||
|
||||
Examples
|
||||
--------
|
||||
|
||||
Generate the default palette:
|
||||
|
||||
.. plot::
|
||||
:context: close-figs
|
||||
|
||||
>>> import seaborn as sns; sns.set_theme()
|
||||
>>> sns.palplot(sns.cubehelix_palette())
|
||||
|
||||
Rotate backwards from the same starting location:
|
||||
|
||||
.. plot::
|
||||
:context: close-figs
|
||||
|
||||
>>> sns.palplot(sns.cubehelix_palette(rot=-.4))
|
||||
|
||||
Use a different starting point and shorter rotation:
|
||||
|
||||
.. plot::
|
||||
:context: close-figs
|
||||
|
||||
>>> sns.palplot(sns.cubehelix_palette(start=2.8, rot=.1))
|
||||
|
||||
Reverse the direction of the lightness ramp:
|
||||
|
||||
.. plot::
|
||||
:context: close-figs
|
||||
|
||||
>>> sns.palplot(sns.cubehelix_palette(reverse=True))
|
||||
|
||||
Generate a colormap object:
|
||||
|
||||
.. plot::
|
||||
:context: close-figs
|
||||
|
||||
>>> from numpy import arange
|
||||
>>> x = arange(25).reshape(5, 5)
|
||||
>>> cmap = sns.cubehelix_palette(as_cmap=True)
|
||||
>>> ax = sns.heatmap(x, cmap=cmap)
|
||||
|
||||
Use the full lightness range:
|
||||
|
||||
.. plot::
|
||||
:context: close-figs
|
||||
|
||||
>>> cmap = sns.cubehelix_palette(dark=0, light=1, as_cmap=True)
|
||||
>>> ax = sns.heatmap(x, cmap=cmap)
|
||||
|
||||
Use through the :func:`color_palette` interface:
|
||||
|
||||
.. plot::
|
||||
:context: close-figs
|
||||
|
||||
>>> sns.palplot(sns.color_palette("ch:2,r=.2,l=.6"))
|
||||
|
||||
"""
|
||||
...
|
||||
|
||||
def set_color_codes(palette=...): # -> None:
|
||||
"""Change how matplotlib color shorthands are interpreted.
|
||||
|
||||
Calling this will change how shorthand codes like "b" or "g"
|
||||
are interpreted by matplotlib in subsequent plots.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
palette : {deep, muted, pastel, dark, bright, colorblind}
|
||||
Named seaborn palette to use as the source of colors.
|
||||
|
||||
See Also
|
||||
--------
|
||||
set : Color codes can be set through the high-level seaborn style
|
||||
manager.
|
||||
set_palette : Color codes can also be set through the function that
|
||||
sets the matplotlib color cycle.
|
||||
|
||||
Examples
|
||||
--------
|
||||
|
||||
Map matplotlib color codes to the default seaborn palette.
|
||||
|
||||
.. plot::
|
||||
:context: close-figs
|
||||
|
||||
>>> import matplotlib.pyplot as plt
|
||||
>>> import seaborn as sns; sns.set_theme()
|
||||
>>> sns.set_color_codes()
|
||||
>>> _ = plt.plot([0, 1], color="r")
|
||||
|
||||
Use a different seaborn palette.
|
||||
|
||||
.. plot::
|
||||
:context: close-figs
|
||||
|
||||
>>> sns.set_color_codes("dark")
|
||||
>>> _ = plt.plot([0, 1], color="g")
|
||||
>>> _ = plt.plot([0, 2], color="m")
|
||||
|
||||
"""
|
||||
...
|
||||
|
||||
Loading…
Add table
Add a link
Reference in a new issue