matplotlib.colors

For a visual representation of the Matplotlib colormaps, see:

• The Color examples for examples of controlling color with Matplotlib.
• The Colors tutorial for an in-depth guide on controlling color.

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 are provided here: LinearSegmentedColormap, which uses piecewise-linear interpolation to define colormaps, and ListedColormap, which makes a colormap from a list of colors.

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.

Matplotlib recognizes the following formats to specify a color:

• an RGB or RGBA tuple of float values in [0, 1] (e.g., (0.1, 0.2, 0.5) or (0.1, 0.2, 0.5, 0.3));
• a hex RGB or RGBA string (e.g., '#0f0f0f' or '#0f0f0f80'; case-insensitive);
• a string representation of a float value in [0, 1] inclusive for gray level (e.g., '0.5');
• one of {'b', 'g', 'r', 'c', 'm', 'y', 'k', 'w'};
• a X11/CSS4 color name (case-insensitive);
• a name from the xkcd color survey, prefixed with 'xkcd:' (e.g., 'xkcd:sky blue'; case insensitive);
• one of the Tableau Colors from the 'T10' categorical palette (the default color cycle): {'tab:blue', 'tab:orange', 'tab:green', 'tab:red', 'tab:purple', 'tab:brown', 'tab:pink', 'tab:gray', 'tab:olive', 'tab:cyan'} (case-insensitive);
• a "CN" color spec, i.e. 'C' followed by a number, which is an index into the default property cycle (matplotlib.rcParams['axes.prop_cycle']); the indexing is intended to occur at rendering time, and defaults to black if the cycle does not include color.

Classes

BoundaryNorm(boundaries, ncolors[, clip])	Generate a colormap index based on discrete intervals.
Colormap(name[, N])	Baseclass for all scalar to RGBA mappings.
DivergingNorm(vcenter[, vmin, vmax])	Normalize data with a set center.
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, can normalize 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.

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.
makeMappingArray(N, data[, gamma])	Create an N -element 1-d lookup table.
get_named_colors_mapping()	Return the global mapping of names to named colors.