None

Note

This tutorial was generated from an IPython notebook that can be accessed from github.

Overlapping regions

Two or more on regions can share the same area - they overlap. One example are region 3 and 4 of the PRUDENCE regions. This notebook illustrates how overlapping regions can be treated in regionmask.

In short

Important

Starting with v0.11.0 regionmask checks if gridpoints belong to more than one region (unless overlap=False). Thus, it creates the correct mask (or raises an error) per default.

In detail

When creating your own Regions you can tell regionmask if they are overlapping:

region = regionmask.Regions(..., overlap=overlap)
region = regionmask.from_geopandas(..., overlap=overlap)

where overlap must be one of None (default), True or False.

• For overlap=None regionmask checks if any grid point belongs to more than one region. If so, 2D masks raise and error (because overlapping regions cannot be represented by a 2D mask). mask_3D(...) returns the correct mask.

• For overlap=True 2D masks raise an error and mask_3D(...) returns the correct mask.

• If you have two overlapping regions and overlap=False regionmask will silently assign the gridpoints of the overlapping regions to the one with the higher number.

• Setting overlap to True or False is (slightly) faster than the default of None.

• overlap is correctly set for regions in regionmask.defined_regions.

Example

To illustrate the problem we construct two regions in North America that partially overlap. One is horizontal, the other vertical.

Preparation

Import regionmask and check the version:

import regionmask

regionmask.__version__

'0.12.1.post1.dev10+g9fd2ed6'

Other imports

import cartopy.crs as ccrs
import matplotlib.patheffects as pe
import numpy as np
from matplotlib import colors as mplc
from shapely.geometry import box

Define grid:

ds_US = regionmask.core.utils.create_lon_lat_dataarray_from_bounds(
    *(-160, -29, 2), *(76, 13, -2)
)

Define some colors:

cmap = mplc.ListedColormap(["none", "#9ecae1"])

Define helper function:

def plot_region_vh(mask, region):

    fg = mask.plot(
        subplot_kws=dict(projection=ccrs.PlateCarree()),
        col="region",
        cmap=cmap,
        add_colorbar=False,
        transform=ccrs.PlateCarree(),
        ec="0.5",
        lw=0.25,
    )

    for ax in fg.axs.flatten():
        region[[0]].plot(ax=ax, add_label=False, line_kws=dict(color="#6a3d9a"))
        region[[1]].plot(ax=ax, add_label=False, line_kws=dict(color="#ff7f00"))

        ax.set_extent([-105, -75, 25, 55], ccrs.PlateCarree())
        ax.plot(
            ds_US.LON, ds_US.lat, "*", color="0.5", ms=0.5, transform=ccrs.PlateCarree()
        )

Define overlapping polygons:

coords_v = box(-100, 28, -90, 50)
coords_h = box(-100, 40, -80, 50)

Default behavior (overlap=None)

First test what happens if we keep the default value of overlap=None:

region_vh = regionmask.Regions([coords_v, coords_h])

Create a mask

mask_vh = region_vh.mask_3D(ds_US)

Plot the masked regions:

plot_region_vh(mask_vh, region_vh)

The small gray points show the gridpoint center and the vertical and horizontal lines are the gridpoint boundaries. The colored rectangles are the two regions. Here regionmask detects that certain gridpoints belong to two regions and correctly assigns them.

Setting overlap=False

We test what happens for overlap=False:

region_vh_overlap_false = regionmask.Regions([coords_v, coords_h], overlap=False)

Create a mask

mask_vh_overlap_false = region_vh_overlap_false.mask_3D(ds_US)

Plot the masked regions:

plot_region_vh(mask_vh_overlap_false, region_vh_overlap_false)

We can see that only the gridpoints in the lower part of the vertical (magenta) region were assigned to it. All gridpoints of the overlapping part are now assigned to the horizontal (orange) region - the gridpoints are assigned to the region with the higher number. By switching the order of the regions you could have the common gridpoints assigned to the vertical region.

Setting overlap=True

Passing overlap=True has the same effect as the default:

region_overlap = regionmask.Regions([coords_v, coords_h], overlap=True)

region_overlap

<regionmask.Regions 'unnamed'>
overlap:  True

Regions:
0 r0 Region0
1 r1 Region1

[2 regions]

Now it says overlap:  True - and we can again create a mask:

mask_overlap = region_overlap.mask_3D(ds_US)

and plot it

plot_region_vh(mask_overlap, region_vh)

And the gridpoints in the overlapping part are assigned to both regions.

PRUDENCE regions

The PRUDENCE regions are a real-world example of overlapping areas. The prudence regions already set overlap=True.

prudence = regionmask.defined_regions.prudence
prudence

<regionmask.Regions 'PRUDENCE'>
Source:   Christensen and Christensen, 2007, Climatic Change 81:7-30 (https:/...
overlap:  True

Regions:
1 BI     British Isles
2 IP Iberian Peninsula
3 FR            France
4 ME        Mid-Europe
5 SC       Scandinavia
6 AL              Alps
7 MD     Mediterranean
8 EA    Eastern Europe

[8 regions]

Regions 3 and 4 overlap in Western France:

proj = ccrs.LambertConformal(central_longitude=10)

text_kws = dict(
    bbox=dict(color="none"),
    path_effects=[pe.withStroke(linewidth=3, foreground="w")],
    color="#67000d",
)

ax = prudence.plot(
    projection=proj, text_kws=text_kws, resolution="50m", line_kws=dict(lw=0.75)
)


ax.set_extent([-10.0, 30.0, 40.0, 55.0], ccrs.PlateCarree())

Create mask of PRUDENCE regions

lon = np.arange(-12, 33, 0.25)
lat = np.arange(72, 33, -0.25)

mask_prudence = prudence.mask_3D(lon, lat)

proj = ccrs.LambertConformal(central_longitude=10)

fg = mask_prudence.sel(region=[3, 4]).plot(
    subplot_kws=dict(projection=proj),
    col="region",
    cmap=cmap,
    add_colorbar=False,
    transform=ccrs.PlateCarree(),
)


for ax in fg.axs.flatten():
    regionmask.defined_regions.prudence.plot(
        ax=ax, add_label=False, resolution="50m", line_kws=dict(lw=0.75)
    )

As above the gridpoints below the overlapping part is now assigned to both regions.