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import numpy as npimport matplotlib.pyplot as pltcmaps = [('Perceptually Uniform Sequential', [            'viridis', 'plasma', 'inferno', 'magma', 'cividis']),         ('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']),         ('Cyclic', ['twilight', 'twilight_shifted', 'hsv']),         ('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',            'gist_rainbow', 'rainbow', 'jet', 'turbo', 'nipy_spectral',            'gist_ncar'])]gradient = np.linspace(0, 1, 256)gradient = np.vstack((gradient, gradient))def plot_color_gradients(cmap_category, cmap_list):    # Create figure and adjust figure height to number of colormaps    nrows = len(cmap_list)    figh = 0.35 + 0.15 + (nrows + (nrows-1)*0.1)*0.22    fig, axs = plt.subplots(nrows=nrows, figsize=(6.4, figh))    fig.subplots_adjust(top=1-.35/figh, bottom=.15/figh, left=0.2, right=0.99)    axs[0].set_title(cmap_category + ' colormaps', fontsize=14)    for ax, name in zip(axs, cmap_list):        ax.imshow(gradient, aspect='auto', cmap=plt.get_cmap(name))        ax.text(-.01, .5, name, va='center', ha='right', fontsize=10,                transform=ax.transAxes)    # Turn off *all* ticks & spines, not just the ones with colormaps.    for ax in axs:        ax.set_axis_off()for cmap_category, cmap_list in cmaps:    plot_color_gradients(cmap_category, cmap_list)plt.show()

plt.cm下可用的色彩图

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