color example code: colormaps_reference.py

""" ================== Colormap reference ================== Reference for colormaps included with Matplotlib. This reference example shows all colormaps included with Matplotlib. Note that any colormap listed here can be reversed by appending "_r" (e.g., "pink_r"). These colormaps are divided into the following categories: Sequential: These colormaps are approximately monochromatic colormaps varying smoothly between two color tones---usually from low saturation (e.g. white) to high saturation (e.g. a bright blue). Sequential colormaps are ideal for representing most scientific data since they show a clear progression from low-to-high values. Diverging: These colormaps have a median value (usually light in color) and vary smoothly to two different color tones at high and low values. Diverging colormaps are ideal when your data has a median value that is significant (e.g. 0, such that positive and negative values are represented by different colors of the colormap). Qualitative: These colormaps vary rapidly in color. Qualitative colormaps are useful for choosing a set of discrete colors. For example:: color_list = plt.cm.Set3(np.linspace(0, 1, 12)) gives a list of RGB colors that are good for plotting a series of lines on a dark background. Miscellaneous: Colormaps that don't fit into the categories above. """
import numpy as np
import matplotlib.pyplot as plt


# Have colormaps separated into categories:
# http://matplotlib.org/examples/color/colormaps_reference.html
cmaps = [('Perceptually Uniform Sequential', [
            'viridis', 'plasma', 'inferno', 'magma']),
         ('Sequential', [
            'Greys', 'Purples', 'Blues', 'Greens', 'Oranges', 'Reds',
            'YlOrBr', 'YlOrRd', 'OrRd', 'PuRd', 'RdPu', 'BuPu',
            'GnBu', 'PuBu', 'YlGnBu', 'PuBuGn', 'BuGn', 'YlGn']),
         ('Sequential (2)', [
            'binary', 'gist_yarg', 'gist_gray', 'gray', 'bone', 'pink',
            'spring', 'summer', 'autumn', 'winter', 'cool', 'Wistia',
            'hot', 'afmhot', 'gist_heat', 'copper']),
         ('Diverging', [
            'PiYG', 'PRGn', 'BrBG', 'PuOr', 'RdGy', 'RdBu',
            'RdYlBu', 'RdYlGn', 'Spectral', 'coolwarm', 'bwr', 'seismic']),
         ('Qualitative', [
            'Pastel1', 'Pastel2', 'Paired', 'Accent',
            'Dark2', 'Set1', 'Set2', 'Set3',
            'tab10', 'tab20', 'tab20b', 'tab20c']),
         ('Miscellaneous', [
            'flag', 'prism', 'ocean', 'gist_earth', 'terrain', 'gist_stern',
            'gnuplot', 'gnuplot2', 'CMRmap', 'cubehelix', 'brg', 'hsv',
            'gist_rainbow', 'rainbow', 'jet', 'nipy_spectral', 'gist_ncar'])]


nrows = max(len(cmap_list) for cmap_category, cmap_list in cmaps)
gradient = np.linspace(0, 1, 256)
gradient = np.vstack((gradient, gradient))


def plot_color_gradients(cmap_category, cmap_list, nrows):
    fig, axes = plt.subplots(nrows=nrows)
    fig.subplots_adjust(top=0.95, bottom=0.01, left=0.2, right=0.99)
    axes[0].set_title(cmap_category + ' colormaps', fontsize=14)

    for ax, name in zip(axes, cmap_list):
        ax.imshow(gradient, aspect='auto', cmap=plt.get_cmap(name))
        pos = list(ax.get_position().bounds)
        x_text = pos[0] - 0.01
        y_text = pos[1] + pos[3]/2.
        fig.text(x_text, y_text, name, va='center', ha='right', fontsize=10)

    # Turn off *all* ticks & spines, not just the ones with colormaps.
    for ax in axes:
        ax.set_axis_off()


for cmap_category, cmap_list in cmaps:
    plot_color_gradients(cmap_category, cmap_list, nrows)

plt.show()

example

inferno

viridis

plasma

magma

Blues

BuGn

BuPu

GnBu

Greens

Greys

Oranges

OrRd

PuBu

PuBu

PuBuGn

PuRd

Purples

RuPu

Reds

YlGn

YlGnBu

YlOrBr

YlOrRd

binary

spring

summer

autumn

winter

cool

Wistia

afmhot

gist_heat

copper

PiYG

PRGn

BrBG

coolwarm

bwr

seimic

Pastel1

Paired

Accent

Dark2

Set1

Set2

tab10

tab20

tab20b

flag

prism

ocean

gist_earth

terrain

gist_stern

hsv

gist_rainbow

rainbow

jet

nipy_spectral

gist_ncar

cubehelix

brg

gnuplot2

CMPmap

bone

pink

gnuplot