matplotlib.colors  Note The Color tutorials and examples demonstrate how to set colors and colormaps. You may want to read those instead.  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.  See also Creating Colormaps in Matplotlib for examples of how to make colormaps and Choosing Colormaps in Matplotlib for a list of built-in colormaps. Colormap Normalization 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 (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 Specifying Colors.  Classes  
BoundaryNorm(boundaries, ncolors[, clip, extend]) Generate a colormap index based on discrete intervals.  
Colormap(name[, N]) Baseclass for all scalar to RGBA mappings.  
CenteredNorm([vcenter, halfrange, clip]) Normalize symmetrical data around a center (0 by default).  
LightSource([azdeg, altdeg, hsv_min_val, ...]) Create a light source coming from the specified azimuth and elevation.  
LinearSegmentedColormap(name, segmentdata[, ...]) Colormap objects based on lookup tables using linear segments.  
ListedColormap(colors[, name, N]) Colormap object generated from a list of colors.  
LogNorm([vmin, vmax, clip]) Normalize a given value to the 0-1 range on a log scale.  
NoNorm([vmin, vmax, clip]) Dummy replacement for Normalize, for the case where we want to use indices directly in a ScalarMappable.  
Normalize([vmin, vmax, clip]) A class which, when called, linearly normalizes data into the [0.0, 1.0] interval.  
PowerNorm(gamma[, vmin, vmax, clip]) Linearly map a given value to the 0-1 range and then apply a power-law normalization over that range.  
SymLogNorm(linthresh[, linscale, vmin, ...]) The symmetrical logarithmic scale is logarithmic in both the positive and negative directions from the origin.  
TwoSlopeNorm(vcenter[, vmin, vmax]) Normalize data with a set center.  
FuncNorm(functions[, vmin, vmax, clip]) Arbitrary normalization using functions for the forward and inverse.     Functions  
from_levels_and_colors(levels, colors[, extend]) A helper routine to generate a cmap and a norm instance which behave similar to contourf's levels and colors arguments.  
hsv_to_rgb(hsv) Convert hsv values to rgb.  
rgb_to_hsv(arr) Convert float rgb values (in the range [0, 1]), in a numpy array to hsv values.  
to_hex(c[, keep_alpha]) Convert c to a hex color.  
to_rgb(c) Convert c to an RGB color, silently dropping the alpha channel.  
to_rgba(c[, alpha]) Convert c to an RGBA color.  
to_rgba_array(c[, alpha]) Convert c to a (n, 4) array of RGBA colors.  
is_color_like(c) Return whether c can be interpreted as an RGB(A) color.  
same_color(c1, c2) Return whether the colors c1 and c2 are the same.  
get_named_colors_mapping() Return the global mapping of names to named colors.  
make_norm_from_scale(scale_cls[, ...]) Decorator for building a Normalize subclass from a ScaleBase subclass.