Regridding vectors with quiverΒΆ

This example demonstrates the regridding functionality in quiver (there exists equivalent functionality in cartopy.mpl.geoaxes.GeoAxes.barbs()).

Regridding can be an effective way of visualising a vector field, particularly if the data is dense or warped.

import matplotlib.pyplot as plt
import numpy as np

import as ccrs

def sample_data(shape=(20, 30)):
    Return ``(x, y, u, v, crs)`` of some vector data
    computed mathematically. The returned CRS will be a North Polar
    Stereographic projection, meaning that the vectors will be unevenly
    spaced in a PlateCarree projection.

    crs = ccrs.NorthPolarStereo()
    scale = 1e7
    x = np.linspace(-scale, scale, shape[1])
    y = np.linspace(-scale, scale, shape[0])

    x2d, y2d = np.meshgrid(x, y)
    u = 10 * np.cos(2 * x2d / scale + 3 * y2d / scale)
    v = 20 * np.cos(6 * x2d / scale)

    return x, y, u, v, crs

def main():
    fig = plt.figure(figsize=(8, 10))

    x, y, u, v, vector_crs = sample_data(shape=(50, 50))
    ax1 = fig.add_subplot(2, 1, 1, projection=ccrs.PlateCarree())
    ax1.set_extent([-45, 55, 20, 80], ccrs.PlateCarree())
    ax1.quiver(x, y, u, v, transform=vector_crs)

    ax2 = fig.add_subplot(2, 1, 2, projection=ccrs.PlateCarree())
    ax2.set_title('The same vector field regridded')
    ax2.set_extent([-45, 55, 20, 80], ccrs.PlateCarree())
    ax2.quiver(x, y, u, v, transform=vector_crs, regrid_shape=20)

if __name__ == '__main__':

Total running time of the script: ( 0 minutes 0.438 seconds)

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