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"""
Aligning Cartopy and Matplotlib axes
====================================
Sometimes it is useful to line up a standard Matplotlib axes with a Cartopy map, for
example when plotting zonal mean data next to a global contour plot. This example
demonstrates one way to do that for projections where latitude lines are horizontal.
"""
# sphinx_gallery_multi_image = "single"
import matplotlib.pyplot as plt
import numpy as np
import cartopy.crs as ccrs
PC_PROJ = ccrs.PlateCarree()
def map_and_latitudes(map_proj):
"""
Create a map with the given projection, together with a rectangular axes
whose y-axis matches the map.
"""
fig = plt.figure(figsize=(12, 5), layout='compressed')
# Create the map.
map_ax = fig.add_subplot(projection=map_proj)
map_ax.set_global()
gl = map_ax.gridlines(draw_labels=True)
map_ax.coastlines()
# Add the rectangular axes to the right of the map.
rect_ax = map_ax.inset_axes([1.1, 0, 0.3, 1])
# Set up scaling for the rectangular axes latitudes. This part is
# necessary for projections with uneven latitude spacing, such as Mercator,
# but can be skipped for PlateCarree for example.
# Create functions to map between latitude and the projection's y values.
# Assume these are not x-dependent so we can just set x/longitude to zero.
def to_map(lat):
"""Transform latitudes to projection's y-values."""
dummy_lon = np.zeros_like(lat)
projected = map_proj.transform_points(PC_PROJ, dummy_lon, lat)
return np.take(projected, 1, axis=-1)
def from_map(y):
"""Transform projection's y-values to latitude."""
dummy_x = np.zeros_like(y)
projected = PC_PROJ.transform_points(map_proj, dummy_x, y)
return np.take(projected, 1, axis=-1)
# Use these function to define the y-scale on the rectangular axes.
rect_ax.set_yscale('function', functions=(to_map, from_map))
# Convert the map's y-limits to latitudes and set the y-limits.
rect_ax.set_ylim(from_map(np.array(map_ax.get_ylim())))
# y-axis visual choices.
rect_ax.grid(axis='y')
rect_ax.yaxis.tick_right()
rect_ax.yaxis.set_major_locator(gl.ylocator)
rect_ax.yaxis.set_major_formatter(gl.yformatter)
# Plot some dummy data.
y = np.linspace(-90, 90, 21)
y_rad = np.deg2rad(y)
rect_ax.plot(np.sin(y_rad), y, label='sine')
rect_ax.plot(np.cos(y_rad), y, label='cosine')
rect_ax.legend()
# Add the projection name as the title.
fig.suptitle(type(map_proj).__name__)
if __name__ == '__main__':
for map_proj in [ccrs.PlateCarree(), ccrs.Mercator(), ccrs.Robinson()]:
map_and_latitudes(map_proj)
plt.show()
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