In [ ]:
%matplotlib inline
%config InlineBackend.figure_format = "retina"
from matplotlib import rcParams
rcParams["savefig.dpi"] = 200
rcParams["font.size"] = 8
import warnings
warnings.filterwarnings("ignore")
% comment: leave next cell as RawNBConvert -> else the warning mesage is not correctly displayed
Creating own regions is straightforward. Import regionmask and check the version:
In [ ]:
import regionmask
regionmask.__version__
Import numpy
In [ ]:
import numpy as np
Assume you have two custom regions in the US, you can easily use these to create Regions
:
In [ ]:
US1 = np.array([[-100.0, 30], [-100, 40], [-120, 35]])
US2 = np.array([[-100.0, 30], [-80, 30], [-80, 40], [-100, 40]])
regionmask.Regions([US1, US2])
If you want to set the names
and abbrevs
yourself you can still do that:
In [ ]:
names = ["US_west", "US_east"]
abbrevs = ["USw", "USe"]
USregions = regionmask.Regions([US1, US2], names=names, abbrevs=abbrevs, name="US")
USregions
Again we can plot the outline of the defined regions
In [ ]:
ax = USregions.plot(label="abbrev")
# load cartopy
import cartopy.crs as ccrs
# fine tune the extent
ax.set_extent([225, 300, 25, 45], crs=ccrs.PlateCarree())
and obtain a mask:
In [ ]:
import numpy as np
# define lat/ lon grid
lon = np.arange(200.5, 330, 1)
lat = np.arange(74.5, 15, -1)
# for the plotting
lon_edges = np.arange(200, 331, 1)
lat_edges = np.arange(75, 14, -1)
mask = USregions.mask(lon, lat)
In [ ]:
import matplotlib.pyplot as plt
ax = plt.subplot(111, projection=ccrs.PlateCarree())
# pcolormesh does not handle NaNs, requires masked array
mask_ma = np.ma.masked_invalid(mask)
h = ax.pcolormesh(
lon_edges, lat_edges, mask_ma, transform=ccrs.PlateCarree(), cmap="viridis",
)
ax.coastlines()
# add the outlines of the regions
USregions.plot_regions(ax=ax, add_label=False)
ax.set_extent([225, 300, 25, 45], crs=ccrs.PlateCarree())
In [ ]:
from shapely.geometry import Polygon, MultiPolygon
US1_poly = Polygon(US1)
US2_poly = Polygon(US2)
US1_poly, US2_poly
In [ ]:
USregions_poly = regionmask.Regions([US1_poly, US2_poly])
USregions_poly
In [ ]:
US1_shifted = US1 - (5, 0)
US2_hole = np.array([[-98.0, 33], [-92, 33], [-92, 37], [-98, 37], [-98.0, 33]])
Create Polygons
, a MultiPolygon
, and finally Regions
In [ ]:
US1_poly = Polygon(US1_shifted)
US2_poly = Polygon(US2, holes=[US2_hole])
US_multipoly = MultiPolygon([US1_poly, US2_poly])
USregions_poly = regionmask.Regions([US_multipoly])
In [ ]:
USregions_poly.plot();
Create a mask:
In [ ]:
mask = USregions_poly.mask(lon, lat)
and plot it:
In [ ]:
ax = plt.subplot(111, projection=ccrs.PlateCarree())
mask.plot(transform=ccrs.PlateCarree(), add_colorbar=False)
ax.coastlines();