Using Cartopy and AxesGrid toolkit

This example demonstrates how to use cartopy GeoAxes with AxesGrid from the mpl_toolkits.axes_grid1. The script constructs an axes_class kwarg with Plate Carree projection and passes it to the AxesGrid instance. The AxesGrid built-in labelling is switched off, and instead a standard procedure of creating grid lines is used. Then some fake data is plotted.

Out:

/root/project/examples/miscellanea/axes_grid_basic.py:71: MatplotlibDeprecationWarning: Since 3.2, mpl_toolkits's own colorbar implementation is deprecated; it will be removed two minor releases later.  Set the 'mpl_toolkits.legacy_colorbar' rcParam to False to use Matplotlib's default colorbar implementation and suppress this deprecation warning.
  axgr.cbar_axes[0].colorbar(p)
/opt/conda/envs/test-environment/lib/python3.7/site-packages/mpl_toolkits/axes_grid1/axes_grid.py:46: MatplotlibDeprecationWarning:
The mpl_toolkits.axes_grid1.colorbar module was deprecated in Matplotlib 3.2 and will be removed two minor releases later. Use matplotlib.colorbar instead.
  from .colorbar import Colorbar

import cartopy.crs as ccrs
from cartopy.mpl.geoaxes import GeoAxes
from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import AxesGrid
import numpy as np


def sample_data_3d(shape):
    """Return `lons`, `lats`, `times` and fake `data`"""
    ntimes, 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

    times = np.linspace(-1, 1, ntimes)
    new_shape = data.shape + (ntimes, )
    data = np.rollaxis(data.repeat(ntimes).reshape(new_shape), -1)
    data *= times[:, np.newaxis, np.newaxis]

    return lons, lats, times, data


def main():
    projection = ccrs.PlateCarree()
    axes_class = (GeoAxes,
                  dict(map_projection=projection))

    lons, lats, times, data = sample_data_3d((6, 73, 145))

    fig = plt.figure()
    axgr = AxesGrid(fig, 111, axes_class=axes_class,
                    nrows_ncols=(3, 2),
                    axes_pad=0.6,
                    cbar_location='right',
                    cbar_mode='single',
                    cbar_pad=0.2,
                    cbar_size='3%',
                    label_mode='')  # note the empty label_mode

    for i, ax in enumerate(axgr):
        ax.coastlines()
        ax.set_xticks(np.linspace(-180, 180, 5), crs=projection)
        ax.set_yticks(np.linspace(-90, 90, 5), crs=projection)
        lon_formatter = LongitudeFormatter(zero_direction_label=True)
        lat_formatter = LatitudeFormatter()
        ax.xaxis.set_major_formatter(lon_formatter)
        ax.yaxis.set_major_formatter(lat_formatter)

        p = ax.contourf(lons, lats, data[i, ...],
                        transform=projection,
                        cmap='RdBu')

    axgr.cbar_axes[0].colorbar(p)

    plt.show()


if __name__ == '__main__':
    main()