geopandas.GeoSeries.relate

GeoSeries.relate(other, align=None)

Returns the DE-9IM intersection matrices for the geometries

The operation works on a 1-to-1 row-wise manner:

Parameters:

otherBaseGeometry or GeoSeries

The other geometry to computed the DE-9IM intersection matrices from.

alignbool | None (default None)

If True, automatically aligns GeoSeries based on their indices. If False, the order of elements is preserved. None defaults to True.

Returns:

spatial_relations: Series of strings

The DE-9IM intersection matrices which describe the spatial relations of the other geometry.

Examples

>>> from shapely.geometry import Polygon, LineString, Point
>>> s = geopandas.GeoSeries(
...     [
...         Polygon([(0, 0), (2, 2), (0, 2)]),
...         Polygon([(0, 0), (2, 2), (0, 2)]),
...         LineString([(0, 0), (2, 2)]),
...         LineString([(2, 0), (0, 2)]),
...         Point(0, 1),
...     ],
... )
>>> s2 = geopandas.GeoSeries(
...     [
...         Polygon([(0, 0), (1, 1), (0, 1)]),
...         LineString([(1, 0), (1, 3)]),
...         LineString([(2, 0), (0, 2)]),
...         Point(1, 1),
...         Point(0, 1),
...     ],
...     index=range(1, 6),
... )

>>> s
0    POLYGON ((0 0, 2 2, 0 2, 0 0))
1    POLYGON ((0 0, 2 2, 0 2, 0 0))
2             LINESTRING (0 0, 2 2)
3             LINESTRING (2 0, 0 2)
4                       POINT (0 1)
dtype: geometry

>>> s2
1    POLYGON ((0 0, 1 1, 0 1, 0 0))
2             LINESTRING (1 0, 1 3)
3             LINESTRING (2 0, 0 2)
4                       POINT (1 1)
5                       POINT (0 1)
dtype: geometry

We can relate each geometry and a single shapely geometry:

>>> s.relate(Polygon([(0, 0), (1, 1), (0, 1)]))
0    212F11FF2
1    212F11FF2
2    F11F00212
3    F01FF0212
4    F0FFFF212
dtype: object

We can also check two GeoSeries against each other, row by row. The GeoSeries above have different indices. We can either align both GeoSeries based on index values and compare elements with the same index using align=True or ignore index and compare elements based on their matching order using align=False:

>>> s.relate(s2, align=True)
0         None
1    212F11FF2
2    0F1FF0102
3    1FFF0FFF2
4    FF0FFF0F2
5         None
dtype: object

>>> s.relate(s2, align=False)
0    212F11FF2
1    1F20F1102
2    0F1FF0102
3    0F1FF0FF2
4    0FFFFFFF2
dtype: object