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Contour labels#
An example of adding contour labels to matplotlib contours.
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
def sample_data(shape=(73, 145)):
"""Return ``lons``, ``lats`` and ``data`` of some fake data."""
import numpy as np
nlats, nlons = shape
lats = np.linspace(-np.pi / 2, np.pi / 2, nlats)
lons = np.linspace(0, 2 * np.pi, nlons)
lons, lats = np.meshgrid(lons, lats)
wave = 0.75 * (np.sin(2 * lats) ** 8) * np.cos(4 * lons)
mean = 0.5 * np.cos(2 * lats) * ((np.sin(2 * lats)) ** 2 + 2)
lats = np.rad2deg(lats)
lons = np.rad2deg(lons)
data = wave + mean
return lons, lats, data
def main():
fig = plt.figure()
# Setup a global EckertIII map with faint coastlines.
ax = fig.add_subplot(1, 1, 1, projection=ccrs.EckertIII())
ax.set_global()
ax.coastlines('110m', alpha=0.1)
# Use the same sample data as the waves example, but make it
# more dependent on y for more interesting contours.
x, y, z = sample_data((20, 40))
z = z * -1.5 * y
# Add colourful filled contours.
filled_c = ax.contourf(x, y, z, transform=ccrs.PlateCarree())
# And black line contours (or set colors='none' for invisible lines).
line_c = ax.contour(x, y, z, levels=filled_c.levels,
colors='black',
transform=ccrs.PlateCarree())
# Add a colorbar for the filled contour.
fig.colorbar(filled_c, orientation='horizontal')
# Use the line contours to place contour labels.
ax.clabel(
line_c, # Typically best results when labelling line contours.
colors=['black'],
manual=False, # Automatic placement vs manual placement.
inline=True, # Cut the line where the label will be placed.
fmt=' {:.0f} '.format, # Labes as integers, with some extra space.
)
plt.show()
if __name__ == '__main__':
main()
Total running time of the script: (0 minutes 0.507 seconds)