matplotlib 3.5.1

BackRef

RGB and RGBA are sequences of, respectively, 3 or 4 floats in the range 0-1.

This module includes functions and classes for color specification conversions, and for mapping numbers to colors in a 1-D array of colors called a colormap.

Mapping data onto colors using a colormap typically involves two steps: a data array is first mapped onto the range 0-1 using a subclass of Normalize , then this number is mapped to a color using a subclass of Colormap . Two subclasses of Colormap provided here: LinearSegmentedColormap , which uses piecewise-linear interpolation to define colormaps, and ListedColormap , which makes a colormap from a list of colors.

.. seealso:: 
    :doc:`/tutorials/colors/colormap-manipulation` for examples of how to
    make colormaps and

    :doc:`/tutorials/colors/colormaps` for a list of built-in colormaps.

    :doc:`/tutorials/colors/colormapnorms` for more details about data
    normalization

    More colormaps are available at palettable_.

The module also provides functions for checking whether an object can be interpreted as a color (is_color_like ), for converting such an object to an RGBA tuple (:None:None:`to_rgba`) or to an HTML-like hex string in the "#rrggbb" format (to_hex ), and a sequence of colors to an (n, 4) RGBA array (to_rgba_array ). Caching is used for efficiency.

Colors that Matplotlib recognizes are listed at /tutorials/colors/colors .

            <Unimplemented 'target' '.. _palettable: https://jiffyclub.github.io/palettable/'>
           
            <Unimplemented 'target' '.. _xkcd color survey: https://xkcd.com/color/rgb/'>
           

A module for converting numbers or color arguments to RGB or RGBA.

A module for converting numbers or color arguments to RGB or RGBA.

RGB and RGBA are sequences of, respectively, 3 or 4 floats in the range 0-1.

This module includes functions and classes for color specification conversions, and for mapping numbers to colors in a 1-D array of colors called a colormap.

Mapping data onto colors using a colormap typically involves two steps: a data array is first mapped onto the range 0-1 using a subclass of Normalize , then this number is mapped to a color using a subclass of Colormap . Two subclasses of Colormap provided here: LinearSegmentedColormap , which uses piecewise-linear interpolation to define colormaps, and ListedColormap , which makes a colormap from a list of colors.

.. seealso:: 
    :doc:`/tutorials/colors/colormap-manipulation` for examples of how to
    make colormaps and

    :doc:`/tutorials/colors/colormaps` for a list of built-in colormaps.

    :doc:`/tutorials/colors/colormapnorms` for more details about data
    normalization

    More colormaps are available at palettable_.

The module also provides functions for checking whether an object can be interpreted as a color (is_color_like ), for converting such an object to an RGBA tuple (:None:None:`to_rgba`) or to an HTML-like hex string in the "#rrggbb" format (to_hex ), and a sequence of colors to an (n, 4) RGBA array (to_rgba_array ). Caching is used for efficiency.

Colors that Matplotlib recognizes are listed at /tutorials/colors/colors .

            <Unimplemented 'target' '.. _palettable: https://jiffyclub.github.io/palettable/'>
           
            <Unimplemented 'target' '.. _xkcd color survey: https://xkcd.com/color/rgb/'>
           

Examples

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

matplotlib.pyplot.plot matplotlib.axes._axes.Axes.plot papyri

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


File: /matplotlib/colors.py#0
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