.. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_gallery_specialty_plots_topographic_hillshading.py: ======================= Topographic hillshading ======================= Demonstrates the visual effect of varying blend mode and vertical exaggeration on "hillshaded" plots. Note that the "overlay" and "soft" blend modes work well for complex surfaces such as this example, while the default "hsv" blend mode works best for smooth surfaces such as many mathematical functions. In most cases, hillshading is used purely for visual purposes, and *dx*/*dy* can be safely ignored. In that case, you can tweak *vert_exag* (vertical exaggeration) by trial and error to give the desired visual effect. However, this example demonstrates how to use the *dx* and *dy* kwargs to ensure that the *vert_exag* parameter is the true vertical exaggeration. .. image:: /gallery/specialty_plots/images/sphx_glr_topographic_hillshading_001.png :class: sphx-glr-single-img .. code-block:: default import numpy as np import matplotlib.pyplot as plt from matplotlib.cbook import get_sample_data from matplotlib.colors import LightSource with np.load(get_sample_data('jacksboro_fault_dem.npz')) as dem: z = dem['elevation'] #-- Optional dx and dy for accurate vertical exaggeration ---------------- # If you need topographically accurate vertical exaggeration, or you don't # want to guess at what *vert_exag* should be, you'll need to specify the # cellsize of the grid (i.e. the *dx* and *dy* parameters). Otherwise, any # *vert_exag* value you specify will be relative to the grid spacing of # your input data (in other words, *dx* and *dy* default to 1.0, and # *vert_exag* is calculated relative to those parameters). Similarly, *dx* # and *dy* are assumed to be in the same units as your input z-values. # Therefore, we'll need to convert the given dx and dy from decimal degrees # to meters. dx, dy = dem['dx'], dem['dy'] dy = 111200 * dy dx = 111200 * dx * np.cos(np.radians(dem['ymin'])) #------------------------------------------------------------------------- # Shade from the northwest, with the sun 45 degrees from horizontal ls = LightSource(azdeg=315, altdeg=45) cmap = plt.cm.gist_earth fig, axes = plt.subplots(nrows=4, ncols=3, figsize=(8, 9)) plt.setp(axes.flat, xticks=[], yticks=[]) # Vary vertical exaggeration and blend mode and plot all combinations for col, ve in zip(axes.T, [0.1, 1, 10]): # Show the hillshade intensity image in the first row col[0].imshow(ls.hillshade(z, vert_exag=ve, dx=dx, dy=dy), cmap='gray') # Place hillshaded plots with different blend modes in the rest of the rows for ax, mode in zip(col[1:], ['hsv', 'overlay', 'soft']): rgb = ls.shade(z, cmap=cmap, blend_mode=mode, vert_exag=ve, dx=dx, dy=dy) ax.imshow(rgb) # Label rows and columns for ax, ve in zip(axes[0], [0.1, 1, 10]): ax.set_title('{0}'.format(ve), size=18) for ax, mode in zip(axes[:, 0], ['Hillshade', 'hsv', 'overlay', 'soft']): ax.set_ylabel(mode, size=18) # Group labels... axes[0, 1].annotate('Vertical Exaggeration', (0.5, 1), xytext=(0, 30), textcoords='offset points', xycoords='axes fraction', ha='center', va='bottom', size=20) axes[2, 0].annotate('Blend Mode', (0, 0.5), xytext=(-30, 0), textcoords='offset points', xycoords='axes fraction', ha='right', va='center', size=20, rotation=90) fig.subplots_adjust(bottom=0.05, right=0.95) plt.show() .. _sphx_glr_download_gallery_specialty_plots_topographic_hillshading.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download :download:`Download Python source code: topographic_hillshading.py ` .. container:: sphx-glr-download :download:`Download Jupyter notebook: topographic_hillshading.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature Keywords: matplotlib code example, codex, python plot, pyplot `Gallery generated by Sphinx-Gallery `_