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matplotlib example matplotlib 3d bghot (snippet)

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Python matplotlib example 'matplotlib 3d bghot'

Functions in program:

  • def plot_color_gradients(cmap_category, cmap_list):

Modules used in program:

  • import matplotlib.pyplot as plt
  • import numpy as np

python matplotlib 3d bghot

Python matplotlib example: matplotlib 3d bghot

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', 'inferno', 'plasma', 'magma']),
         ('Sequential',     ['Blues', 'BuGn', 'BuPu',
                             'GnBu', 'Greens', 'Greys', 'Oranges', 'OrRd',
                             'PuBu', 'PuBuGn', 'PuRd', 'Purples', 'RdPu',
                             'Reds', 'YlGn', 'YlGnBu', 'YlOrBr', 'YlOrRd']),
         ('Sequential (2)', ['afmhot', 'autumn', 'bone', 'cool',
                             'copper', 'gist_heat', 'gray', 'hot',
                             'pink', 'spring', 'summer', 'winter']),
         ('Diverging',      ['BrBG', 'bwr', 'coolwarm', 'PiYG', 'PRGn', 'PuOr',
                             'RdBu', 'RdGy', 'RdYlBu', 'RdYlGn', 'Spectral',
                             'seismic']),
         ('Qualitative',    ['Accent', 'Dark2', 'Paired', 'Pastel1',
                             'Pastel2', 'Set1', 'Set2', 'Set3']),
         ('Miscellaneous',  ['gist_earth', 'terrain', 'ocean', 'gist_stern',
                             'brg', 'CMRmap', 'cubehelix',
                             'gnuplot', 'gnuplot2', 'gist_ncar',
                             'nipy_spectral', 'jet', 'rainbow',
                             'gist_rainbow', 'hsv', 'flag', 'prism'])]


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):
    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)

plt.show()