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"""
Using Cartopy and AxesGrid toolkit
----------------------------------
This example demonstrates how to use cartopy `~cartopy.mpl.geoaxes.GeoAxes`
with `~mpl_toolkits.axes_grid1.axes_grid.AxesGrid` from the
:mod:`mpl_toolkits.axes_grid1`. The script constructs an ``axes_class`` kwarg
with Plate Carree projection and passes it to the
`~mpl_toolkits.axes_grid1.axes_grid.AxesGrid` instance. The
`~mpl_toolkits.axes_grid1.axes_grid.AxesGrid` built-in tick labelling
is not used, and instead a standard procedure of creating grid lines is used.
Then some fake data is plotted.
"""
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import AxesGrid
import numpy as np
import cartopy.crs as ccrs
from cartopy.mpl.geoaxes import GeoAxes
from cartopy.mpl.ticker import LatitudeFormatter, LongitudeFormatter
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(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='keep')
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()
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