The 2019 SciPy John Hunter Excellence in Plotting Contest is accepting submissions!
Apply by June 8th

Version 3.1.0
matplotlib
Fork me on GitHub

Related Topics

DivergingNorm colormap normalizationΒΆ

Sometimes we want to have a different colormap on either side of a conceptual center point, and we want those two colormaps to have different linear scales. An example is a topographic map where the land and ocean have a center at zero, but land typically has a greater elevation range than the water has depth range, and they are often represented by a different colormap.

../../_images/sphx_glr_colormap_normalizations_diverging_001.png
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cbook as cbook
import matplotlib.colors as colors

filename = cbook.get_sample_data('topobathy.npz', asfileobj=False)
with np.load(filename) as dem:
    topo = dem['topo']
    longitude = dem['longitude']
    latitude = dem['latitude']

fig, ax = plt.subplots(constrained_layout=True)
# make a colormap that has land and ocean clearly delineated and of the
# same length (256 + 256)
colors_undersea = plt.cm.terrain(np.linspace(0, 0.17, 256))
colors_land = plt.cm.terrain(np.linspace(0.25, 1, 256))
all_colors = np.vstack((colors_undersea, colors_land))
terrain_map = colors.LinearSegmentedColormap.from_list('terrain_map',
    all_colors)

# make the norm:  Note the center is offset so that the land has more
# dynamic range:
divnorm = colors.DivergingNorm(vmin=-500, vcenter=0, vmax=4000)

pcm = ax.pcolormesh(longitude, latitude, topo, rasterized=True, norm=divnorm,
    cmap=terrain_map,)
ax.set_xlabel('Lon $[^o E]$')
ax.set_ylabel('Lat $[^o N]$')
ax.set_aspect(1 / np.cos(np.deg2rad(49)))
fig.colorbar(pcm, shrink=0.6, extend='both', label='Elevation [m]')
plt.show()

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