Intersection joiner

In [1]:

import geopandas as gpd
from shapely import geometry
import matplotlib.pyplot as plt
from srai.constants import WGS84_CRS, REGIONS_INDEX, FEATURES_INDEX
from srai.plotting.folium_wrapper import plot_regions

import geopandas as gpd from shapely import geometry import matplotlib.pyplot as plt from srai.constants import WGS84_CRS, REGIONS_INDEX, FEATURES_INDEX from srai.plotting.folium_wrapper import plot_regions

Define example regions and features¶

In [2]:

regions = gpd.GeoDataFrame(
    geometry=[
        geometry.Polygon([(-1, 0), (-1, -1), (0, -1), (0, 0)]),
        geometry.Polygon([(1, 0), (1, 1), (0, 1), (0, 0)]),
        geometry.Polygon([(-2, -1), (-2, -2), (-1, -2), (-1, -1)]),
        geometry.Polygon([(-2, 0.5), (-2, -0.5), (-1, -0.5), (-1, 0.5)]),
    ],
    crs=WGS84_CRS,
    index=gpd.pd.Index(name=REGIONS_INDEX, data=[1, 2, 3, 4]),
)

features = gpd.GeoDataFrame(
    geometry=[
        geometry.Polygon([(-1.5, 0.5), (-1.5, 0), (-0.5, 0), (-0.5, 0.5)]),
        geometry.Polygon([(-1.5, -1.5), (-1.5, -2.5), (-0.5, -2.5), (-0.5, -1.5)]),
        geometry.Point((0, 0)),
        geometry.Point((-0.5, -0.5)),
    ],
    crs=WGS84_CRS,
    index=gpd.pd.Index(name=FEATURES_INDEX, data=[1, 2, 3, 4]),
)

regions = gpd.GeoDataFrame( geometry=[ geometry.Polygon([(-1, 0), (-1, -1), (0, -1), (0, 0)]), geometry.Polygon([(1, 0), (1, 1), (0, 1), (0, 0)]), geometry.Polygon([(-2, -1), (-2, -2), (-1, -2), (-1, -1)]), geometry.Polygon([(-2, 0.5), (-2, -0.5), (-1, -0.5), (-1, 0.5)]), ], crs=WGS84_CRS, index=gpd.pd.Index(name=REGIONS_INDEX, data=[1, 2, 3, 4]), ) features = gpd.GeoDataFrame( geometry=[ geometry.Polygon([(-1.5, 0.5), (-1.5, 0), (-0.5, 0), (-0.5, 0.5)]), geometry.Polygon([(-1.5, -1.5), (-1.5, -2.5), (-0.5, -2.5), (-0.5, -1.5)]), geometry.Point((0, 0)), geometry.Point((-0.5, -0.5)), ], crs=WGS84_CRS, index=gpd.pd.Index(name=FEATURES_INDEX, data=[1, 2, 3, 4]), )

In [3]:

regions

regions

Out[3]:

	geometry
region_id
1	POLYGON ((-1.00000 0.00000, -1.00000 -1.00000,...
2	POLYGON ((1.00000 0.00000, 1.00000 1.00000, 0....
3	POLYGON ((-2.00000 -1.00000, -2.00000 -2.00000...
4	POLYGON ((-2.00000 0.50000, -2.00000 -0.50000,...

In [4]:

features

features

Out[4]:

	geometry
feature_id
1	POLYGON ((-1.50000 0.50000, -1.50000 0.00000, ...
2	POLYGON ((-1.50000 -1.50000, -1.50000 -2.50000...
3	POINT (0.00000 0.00000)
4	POINT (-0.50000 -0.50000)

In [5]:

folium_map = plot_regions(regions, colormap=["royalblue"])
features.explore(
    m=folium_map,
    style_kwds=dict(color="red", opacity=0.8, fillColor="red", fillOpacity=0.5),
    marker_kwds=dict(radius=3),
)

folium_map = plot_regions(regions, colormap=["royalblue"]) features.explore( m=folium_map, style_kwds=dict(color="red", opacity=0.8, fillColor="red", fillOpacity=0.5), marker_kwds=dict(radius=3), )

Out[5]:

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Join regions with features using intersection joiner¶

In [6]:

from srai.joiners import IntersectionJoiner

joiner = IntersectionJoiner()
joint = joiner.transform(regions, features, return_geom=True)

joint

from srai.joiners import IntersectionJoiner joiner = IntersectionJoiner() joint = joiner.transform(regions, features, return_geom=True) joint

Out[6]:

		geometry
region_id	feature_id
1	3	POINT (0.00000 0.00000)
	4	POINT (-0.50000 -0.50000)
2	3	POINT (0.00000 0.00000)
1	1	LINESTRING (-1.00000 0.00000, -0.50000 0.00000)
4	1	POLYGON ((-1.50000 0.00000, -1.50000 0.50000, ...
3	2	POLYGON ((-1.50000 -1.50000, -1.00000 -1.50000...

In [7]:

folium_map = plot_regions(regions, colormap=["royalblue"])
features.explore(
    m=folium_map,
    style_kwds=dict(color="red", opacity=0.5, fillColor="red", fillOpacity=0.5),
    marker_kwds=dict(radius=3),
)
joint.explore(
    m=folium_map,
    style_kwds=dict(color="yellow", opacity=1.0, fillColor="yellow", fillOpacity=1.0),
    marker_kwds=dict(radius=3),
)

folium_map = plot_regions(regions, colormap=["royalblue"]) features.explore( m=folium_map, style_kwds=dict(color="red", opacity=0.5, fillColor="red", fillOpacity=0.5), marker_kwds=dict(radius=3), ) joint.explore( m=folium_map, style_kwds=dict(color="yellow", opacity=1.0, fillColor="yellow", fillOpacity=1.0), marker_kwds=dict(radius=3), )

Out[7]:

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