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matplotlib cm

matplotlib.cm

This module provides a large set of colormaps, functions for registering new colormaps and for getting a colormap by name, and a mixin class for adding color mapping functionality.

class matplotlib.cm.ScalarMappable(norm=None, cmap=None)

This is a mixin class to support scalar -> RGBA mapping. Handles normalization and colormapping

norm is an instance of colors.Normalize or one of its subclasses, used to map luminance to 0-1. cmap is a cm colormap instance, for example cm.jet

add_checker(checker)

Add an entry to a dictionary of boolean flags that are set to True when the mappable is changed.

autoscale()

Autoscale the scalar limits on the norm instance using the current array

autoscale_None()

Autoscale the scalar limits on the norm instance using the current array, changing only limits that are None

changed()

Call this whenever the mappable is changed to notify all the callbackSM listeners to the ‘changed’ signal

check_update(checker)

If mappable has changed since the last check, return True; else return False

get_array()

Return the array

get_clim()

return the min, max of the color limits for image scaling

get_cmap()

return the colormap

set_array(A)

Set the image array from numpy array A

set_clim(vmin=None, vmax=None)

set the norm limits for image scaling; if vmin is a length2 sequence, interpret it as (vmin, vmax) which is used to support setp

ACCEPTS: a length 2 sequence of floats

set_cmap(cmap)

set the colormap for luminance data

ACCEPTS: a colormap or registered colormap name

set_colorbar(im, ax)

set the colorbar image and axes associated with mappable

set_norm(norm)

set the normalization instance

to_rgba(x, alpha=None, bytes=False)

Return a normalized rgba array corresponding to x. If x is already an rgb array, insert alpha; if it is already rgba, return it unchanged. If bytes is True, return rgba as 4 uint8s instead of 4 floats.

matplotlib.cm.get_cmap(name=None, lut=None)

Get a colormap instance, defaulting to rc values if name is None.

Colormaps added with register_cmap() take precedence over builtin colormaps.

If name is a colors.Colormap instance, it will be returned.

If lut is not None it must be an integer giving the number of entries desired in the lookup table, and name must be a standard mpl colormap name with a corresponding data dictionary in datad.

matplotlib.cm.register_cmap(name=None, cmap=None, data=None, lut=None)

Add a colormap to the set recognized by get_cmap().

It can be used in two ways:

register_cmap(name='swirly', cmap=swirly_cmap)

register_cmap(name='choppy', data=choppydata, lut=128)

In the first case, cmap must be a colors.Colormap instance. The name is optional; if absent, the name will be the name attribute of the cmap.

In the second case, the three arguments are passed to the colors.LinearSegmentedColormap initializer, and the resulting colormap is registered.

matplotlib.cm.revcmap(data)