@header@

matplotlib.cm

index
/usr/local/lib/python2.3/site-packages/matplotlib/cm.py

This module contains the instantiations of color mapping classes

Classes

ScalarMappable

class ScalarMappable

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

Methods defined here:

__init__(self, norm=None, cmap=None)
norm is a colors.Norm instance to map luminance to 0-1 cmap is a cm colormap instance

add_observer(self, mappable)
whenever the norm, clim or cmap is set, call the notify instance of the mappable observer with self. This is designed to allow one image to follow changes in the cmap of another image

autoscale(self)
Autoscale the scalar limits on the norm instance using the current array

changed(self)
Call this whenever the mappable is changed so observers can update state

notify(self, mappable)
If this is called then we are pegged to another mappable. Update the cmap, norm accordingly

set_array(self, A)
Set the image array from numeric/numarray A

set_clim(self, vmin=None, vmax=None)
set the norm limits for image scaling

set_cmap(self, cmap)
set the colormap for luminance data

set_norm(self, norm)
set the colormap for luminance data

to_rgba(self, x, alpha=1.0)

Functions

ColormapJet(N=256)

Grayscale(N=256)

get_cmap(name=None, lut=None)
Get a colormap instance, defaulting to rc values if name is None

Data

LUTSIZE = 256
datad = {'gray': {'blue': ((0.0, 0, 0), (1.0, 1, 1)), 'green': ((0.0, 0, 0), (1.0, 1, 1)), 'red': ((0.0, 0, 0), (1.0, 1, 1))}, 'jet': {'blue': ((0.0, 0.5, 0.5), (0.11, 1, 1), (0.34000000000000002, 1, 1), (0.65000000000000002, 0, 0), (1, 0, 0)), 'green': ((0.0, 0, 0), (0.125, 0, 0), (0.375, 1, 1), (0.64000000000000001, 1, 1), (0.91000000000000003, 0, 0), (1, 0, 0)), 'red': ((0.0, 0, 0), (0.34999999999999998, 0, 0), (0.66000000000000003, 1, 1), (0.89000000000000001, 1, 1), (1, 0.5, 0.5))}}
gray = <matplotlib.colors.LinearSegmentedColormap instance>
jet = <matplotlib.colors.LinearSegmentedColormap instance>
nx = <matplotlib.nc_imports._TypeNamespace instance>
rcParams = {'axes.edgecolor': 'k', 'axes.facecolor': 'w', 'axes.grid': False, 'axes.hold': True, 'axes.labelcolor': 'k', 'axes.labelsize': 12.0, 'axes.linewidth': 1.0, 'axes.titlesize': 14.0, 'backend': 'GTKAgg', 'datapath': '/usr/local/share/matplotlib', ...}
verbose = <matplotlib.Verbose instance>
@footer@

Data
		LUTSIZE = 256 datad = {'gray': {'blue': ((0.0, 0, 0), (1.0, 1, 1)), 'green': ((0.0, 0, 0), (1.0, 1, 1)), 'red': ((0.0, 0, 0), (1.0, 1, 1))}, 'jet': {'blue': ((0.0, 0.5, 0.5), (0.11, 1, 1), (0.34000000000000002, 1, 1), (0.65000000000000002, 0, 0), (1, 0, 0)), 'green': ((0.0, 0, 0), (0.125, 0, 0), (0.375, 1, 1), (0.64000000000000001, 1, 1), (0.91000000000000003, 0, 0), (1, 0, 0)), 'red': ((0.0, 0, 0), (0.34999999999999998, 0, 0), (0.66000000000000003, 1, 1), (0.89000000000000001, 1, 1), (1, 0.5, 0.5))}} gray = <matplotlib.colors.LinearSegmentedColormap instance> jet = <matplotlib.colors.LinearSegmentedColormap instance> nx = <matplotlib.nc_imports._TypeNamespace instance> rcParams = {'axes.edgecolor': 'k', 'axes.facecolor': 'w', 'axes.grid': False, 'axes.hold': True, 'axes.labelcolor': 'k', 'axes.labelsize': 12.0, 'axes.linewidth': 1.0, 'axes.titlesize': 14.0, 'backend': 'GTKAgg', 'datapath': '/usr/local/share/matplotlib', ...} verbose = <matplotlib.Verbose instance>