Shading example

Example showing how to make shaded relief plots like Mathematica or Generic Mapping Tools.

import numpy as np
from matplotlib import cbook
import matplotlib.pyplot as plt
from matplotlib.colors import LightSource


def main():
    # Test data
    x, y = np.mgrid[-5:5:0.05, -5:5:0.05]
    z = 5 * (np.sqrt(x**2 + y**2) + np.sin(x**2 + y**2))

    dem = cbook.get_sample_data('jacksboro_fault_dem.npz', np_load=True)
    elev = dem['elevation']

    fig = compare(z, plt.cm.copper)
    fig.suptitle('HSV Blending Looks Best with Smooth Surfaces', y=0.95)

    fig = compare(elev, plt.cm.gist_earth, ve=0.05)
    fig.suptitle('Overlay Blending Looks Best with Rough Surfaces', y=0.95)

    plt.show()


def compare(z, cmap, ve=1):
    # Create subplots and hide ticks
    fig, axs = plt.subplots(ncols=2, nrows=2)
    for ax in axs.flat:
        ax.set(xticks=[], yticks=[])

    # Illuminate the scene from the northwest
    ls = LightSource(azdeg=315, altdeg=45)

    axs[0, 0].imshow(z, cmap=cmap)
    axs[0, 0].set(xlabel='Colormapped Data')

    axs[0, 1].imshow(ls.hillshade(z, vert_exag=ve), cmap='gray')
    axs[0, 1].set(xlabel='Illumination Intensity')

    rgb = ls.shade(z, cmap=cmap, vert_exag=ve, blend_mode='hsv')
    axs[1, 0].imshow(rgb)
    axs[1, 0].set(xlabel='Blend Mode: "hsv" (default)')

    rgb = ls.shade(z, cmap=cmap, vert_exag=ve, blend_mode='overlay')
    axs[1, 1].imshow(rgb)
    axs[1, 1].set(xlabel='Blend Mode: "overlay"')

    return fig


if __name__ == '__main__':
    main()

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References

The use of the following functions, methods and classes is shown in this example:

import matplotlib
matplotlib.colors.LightSource
matplotlib.axes.Axes.imshow
matplotlib.pyplot.imshow

Out:

<function imshow at 0x7f73be827820>