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Version 3.0.0rc1.post31+g9f74ea72a
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Shading Example

Example showing how to make shaded relief plots like Mathematica (http://reference.wolfram.com/mathematica/ref/ReliefPlot.html) or Generic Mapping Tools (https://gmt.soest.hawaii.edu/)

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


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))

    filename = get_sample_data('jacksboro_fault_dem.npz', asfileobj=False)
    with np.load(filename) as dem:
        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()
  • ../../_images/sphx_glr_shading_example_001.png
  • ../../_images/sphx_glr_shading_example_002.png

References

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

Keywords: matplotlib code example, codex, python plot, pyplot Gallery generated by Sphinx-Gallery