### Related Topics

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)
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].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()

## 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