Beautifully simple maps

Cartopy has exposed an interface to enable easy map creation using matplotlib. Creating a basic map is as simple as telling matplotlib to use a specific map projection, and then adding some coastlines to the axes:



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%matplotlib inline
import cartopy.crs as ccrs
import matplotlib.pyplot as plt

plt.figure(figsize=(12, 12))
ax = plt.axes(projection=ccrs.PlateCarree())
ax.coastlines();

A list of the available projections to be used with matplotlib can be found on the Cartopy projection list notebook.

The line plt.axes(projection=ccrs.PlateCarree()) sets up a GeoAxes instance which exposes a variety of other map related methods, in the case of the previous example, we used the coastlines() method to add coastlines to the map.

Lets create another map in a different projection, and make use of the stock_img() method to add an underlay image to the map:



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import cartopy.crs as ccrs
import matplotlib.pyplot as plt


plt.figure(figsize=(12, 12))
ax = plt.axes(projection=ccrs.Mollweide())
ax.stock_img();

Adding data to the map

Once you have the map just the way you want it, data can be added to it in exactly the same way as with normal matplotlib axes. By default, the coordinate system of any data added to a GeoAxes is the same as the coordinate system of the GeoAxes itself, to control which coordinate system that the given data is in, you can add the transform keyword with an appropriate cartopy.crs.CRS instance:



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%matplotlib inline
import cartopy.crs as ccrs
import matplotlib.pyplot as plt

plt.figure(figsize=(12, 12))
ax = plt.axes(projection=ccrs.PlateCarree())
ax.stock_img()

ny_lon, ny_lat = -75, 43
delhi_lon, delhi_lat = 77.23, 28.61

plt.plot([ny_lon, delhi_lon], [ny_lat, delhi_lat],
         color='blue', linewidth=2, marker='o',
         transform=ccrs.Geodetic(),
         )

plt.plot([ny_lon, delhi_lon], [ny_lat, delhi_lat],
         color='gray', linestyle='--',
         transform=ccrs.PlateCarree(),
         )

plt.text(ny_lon - 3, ny_lat - 12, 'New York',
         horizontalalignment='right',
         transform=ccrs.Geodetic())

plt.text(delhi_lon + 3, delhi_lat - 12, 'Delhi',
         horizontalalignment='left',
         transform=ccrs.Geodetic());

Notice how the line in blue between New York and Delhi is not straight on a flat PlateCarree map, this is because the Geodetic coordinate system is a truly spherical coordinate system, where a line between two points is defined as the shortest path between those points on the globe rather than 2d Cartesian space.



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