matplotlib.colors.Colormap

class matplotlib.colors.Colormap(name, N=256)[source]

Bases: object

Baseclass for all scalar to RGBA mappings.

Typically, Colormap instances are used to convert data values (floats) from the interval [0, 1] to the RGBA color that the respective Colormap represents. For scaling of data into the [0, 1] interval see matplotlib.colors.Normalize. Subclasses of matplotlib.cm.ScalarMappable make heavy use of this data -> normalize -> map-to-color processing chain.

Parameters:
namestr

The name of the colormap.

Nint

The number of rgb quantization levels.

__call__(X, alpha=None, bytes=False)[source]
Parameters:
Xfloat or int, ndarray or scalar

The data value(s) to convert to RGBA. For floats, X should be in the interval [0.0, 1.0] to return the RGBA values X*100 percent along the Colormap line. For integers, X should be in the interval [0, Colormap.N) to return RGBA values indexed from the Colormap with index X.

alphafloat, array-like, None

Alpha must be a scalar between 0 and 1, a sequence of such floats with shape matching X, or None.

bytesbool

If False (default), the returned RGBA values will be floats in the interval [0, 1] otherwise they will be uint8s in the interval [0, 255].

Returns:
Tuple of RGBA values if X is scalar, otherwise an array of
RGBA values with a shape of X.shape + (4, ).
__copy__()[source]
__dict__ = mappingproxy({'__module__': 'matplotlib.colors', '__doc__': '\n Baseclass for all scalar to RGBA mappings.\n\n Typically, Colormap instances are used to convert data values (floats)\n from the interval ``[0, 1]`` to the RGBA color that the respective\n Colormap represents. For scaling of data into the ``[0, 1]`` interval see\n `matplotlib.colors.Normalize`. Subclasses of `matplotlib.cm.ScalarMappable`\n make heavy use of this ``data -> normalize -> map-to-color`` processing\n chain.\n ', '__init__': <function Colormap.__init__>, '__call__': <function Colormap.__call__>, '__copy__': <function Colormap.__copy__>, 'get_bad': <function Colormap.get_bad>, 'set_bad': <function Colormap.set_bad>, 'get_under': <function Colormap.get_under>, 'set_under': <function Colormap.set_under>, 'get_over': <function Colormap.get_over>, 'set_over': <function Colormap.set_over>, '_set_extremes': <function Colormap._set_extremes>, '_init': <function Colormap._init>, 'is_gray': <function Colormap.is_gray>, '_resample': <function Colormap._resample>, 'reversed': <function Colormap.reversed>, '_repr_png_': <function Colormap._repr_png_>, '_repr_html_': <function Colormap._repr_html_>, '__dict__': <attribute '__dict__' of 'Colormap' objects>, '__weakref__': <attribute '__weakref__' of 'Colormap' objects>})
__init__(name, N=256)[source]
Parameters:
namestr

The name of the colormap.

Nint

The number of rgb quantization levels.

__module__ = 'matplotlib.colors'
__weakref__

list of weak references to the object (if defined)

colorbar_extend

When this colormap exists on a scalar mappable and colorbar_extend is not False, colorbar creation will pick up colorbar_extend as the default value for the extend keyword in the matplotlib.colorbar.Colorbar constructor.

get_bad()[source]

Get the color for masked values.

get_over()[source]

Get the color for high out-of-range values.

get_under()[source]

Get the color for low out-of-range values.

is_gray()[source]

Return whether the colormap is grayscale.

reversed(name=None)[source]

Return a reversed instance of the Colormap.

Note

This function is not implemented for base class.

Parameters:
namestr, optional

The name for the reversed colormap. If it's None the name will be the name of the parent colormap + "_r".

set_bad(color='k', alpha=None)[source]

Set the color for masked values.

set_over(color='k', alpha=None)[source]

Set the color for high out-of-range values.

set_under(color='k', alpha=None)[source]

Set the color for low out-of-range values.