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%matplotlib inline

import matplotlib as mpl

mpl.rcParams["figure.dpi"] = 200
mpl.rcParams["font.size"] = 8

import warnings

warnings.filterwarnings("ignore")

Create your own region

Creating own regions is straightforward. Import regionmask and check the version:

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

import regionmask

regionmask.__version__

'0.13.0.post1.dev28+g9a07e5799'

Assume you have two custom regions in the US, you can easily use these to create Regions:

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])

<regionmask.Regions 'unnamed'>
overlap:  None

Regions:
0 r0 Region0
1 r1 Region1

[2 regions]

Note

Set overlap=True if some of the regions overlap. See the tutorial on overlapping regions for details.

If you want to set the names and abbrevs yourself you can still do that:

names = ["US_west", "US_east"]
abbrevs = ["USw", "USe"]

USregions = regionmask.Regions([US1, US2], names=names, abbrevs=abbrevs, name="US")
USregions

<regionmask.Regions 'US'>
overlap:  None

Regions:
0 USw US_west
1 USe US_east

[2 regions]

Again we can plot the outline of the defined regions

ax = USregions.plot(label="abbrev")

# fine tune the extent
ax.set_extent([225, 300, 25, 45], crs=ccrs.PlateCarree())

and obtain a mask:

import numpy as np

# define lat/ lon grid
lon = np.arange(200.5, 330, 1)
lat = np.arange(74.5, 15, -1)

mask = USregions.mask(lon, lat)

ax = plt.subplot(111, projection=ccrs.PlateCarree())

h = mask.plot(
    transform=ccrs.PlateCarree(),
    cmap="Paired",
    add_colorbar=False,
    vmax=12,
)

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())

Use shapely Polygon

You can also define the region with shapely polygons (see geopandas tutorial how to work with shapefiles).

from shapely.geometry import MultiPolygon, Polygon

US1_poly = Polygon(US1)
US2_poly = Polygon(US2)

USregions_poly = regionmask.Regions([US1_poly, US2_poly])

USregions_poly

<regionmask.Regions 'unnamed'>
overlap:  None

Regions:
0 r0 Region0
1 r1 Region1

[2 regions]

Create Regions with MultiPolygon and interiors

Create two discontiguous regions and combine them to one. Add a hole to one of the regions

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

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])

USregions_poly.plot();

Create a mask:

mask = USregions_poly.mask(lon, lat)

and plot it:

ax = plt.subplot(111, projection=ccrs.PlateCarree())

mask.plot(transform=ccrs.PlateCarree(), add_colorbar=False)

ax.coastlines()

# fine tune the extent
ax.set_extent([225, 300, 25, 45], crs=ccrs.PlateCarree())