Merge pull request #1753 from mcuntz/add_cyclic_point_2d

Added support for 2-dimensional coord in add_cyclic_point.

docs/source/contributors.rst

@@ -42,6 +42,7 @@ the package wouldn't be as rich or diverse as it is today:
  * Kacper Makuch
  * Stephane Raynaud
  * John Krasting
+ * Matthias Cuntz
 
 Thank you!
 

examples/scalar_data/wrapping_global.py

@@ -0,0 +1,91 @@
+"""
+Adding a cyclic point to help with wrapping of global data
+==========================================================
+
+Cartopy represents data in Cartesian projected coordinates, meaning that 350
+degrees longitude, is not just 10 degrees away from 0 degrees as it is when
+represented in spherical coordinates. This means that the plotting methods will
+not plot data between the last and the first longitude.
+
+To help with this, the data and longitude/latitude coordinate arrays can be
+expanded with a cyclic point to close this gap. The routine `add_cyclic`
+repeats the last data column. It can also add the first longitude plus the
+cyclic keyword (defaults to 360) to the end of the longitude array so that the
+data values at the ending longitudes will be closed to the wrap point.
+
+"""
+import numpy as np
+import matplotlib.pyplot as plt
+import cartopy.crs as ccrs
+import cartopy.util as cutil
+
+
+def main():
+
+    # data with longitude centers from 0 to 360
+    nlon = 24
+    nlat = 12
+    # 7.5, 22.5, ..., 337.5, 352.5
+    dlon = 360//nlon
+    lon = np.linspace(dlon/2., 360.-dlon/2., nlon)
+# -82.5, -67.5, ..., 67.5, 82.5
+    dlat = 180//nlat
+    lat = np.linspace(-90.+dlat/2., 90.-dlat/2., nlat)
+    # 0, 1, ..., 10, 11, 11, 10, ..., 1, 0
+    data = np.concatenate((np.arange(nlon // 2),
+                           np.arange(nlon // 2)[::-1]))
+    data = np.tile(data, nlat).reshape((nlat, nlon))
+
+    fig = plt.figure()
+
+    # plot with central longitude 180
+    ax1 = fig.add_subplot(2, 2, 1,
+                          projection=ccrs.Robinson(central_longitude=180))
+    ax1.set_title("1d longitudes, central longitude=180",
+                  fontsize='small')
+    ax1.set_global()
+    ax1.contourf(lon, lat, data,
+                 transform=ccrs.PlateCarree(), cmap='RdBu')
+    ax1.coastlines()
+
+    # plot with central longitude 0
+    ax2 = fig.add_subplot(2, 2, 2,
+                          projection=ccrs.Robinson(central_longitude=0))
+    ax2.set_title("1d longitudes, central longitude=0",
+                  fontsize='small')
+    ax2.set_global()
+    ax2.contourf(lon, lat, data,
+                 transform=ccrs.PlateCarree(), cmap='RdBu')
+    ax2.coastlines()
+
+    # add cyclic points to data and longitudes
+    # latitudes are unchanged in 1-dimension
+    cdata, clon, clat = cutil.add_cyclic(data, lon, lat)
+    ax3 = fig.add_subplot(2, 2, 3,
+                          projection=ccrs.Robinson(central_longitude=180))
+    ax3.set_title("Cyclic 1d longitudes, central longitude=180",
+                  fontsize='small')
+    ax3.set_global()
+    ax3.contourf(clon, clat, cdata,
+                 transform=ccrs.PlateCarree(), cmap='RdBu')
+    ax3.coastlines()
+
+    # add_cyclic also works with 2-dimensional data
+    # Cyclic points are added to data, longitudes, and latitudes to
+    # ensure the dimensions of the returned arrays are all the same shape.
+    lon2d, lat2d = np.meshgrid(lon, lat)
+    cdata, clon2d, clat2d = cutil.add_cyclic(data, lon2d, lat2d)
+    ax4 = fig.add_subplot(2, 2, 4,
+                          projection=ccrs.Robinson(central_longitude=0))
+    ax4.set_title("Cyclic 2d longitudes, central longitude=0",
+                  fontsize='small')
+    ax4.set_global()
+    ax4.contourf(clon2d, clat2d, cdata,
+                 transform=ccrs.PlateCarree(), cmap='RdBu')
+    ax4.coastlines()
+
+    plt.show()
+
+
+if __name__ == '__main__':
+    main()