GeoDataFrame.is_valid_coverage

Return whether the geometry column forms a valid polygonal coverage. A coverage is valid when polygon interiors do not overlap and shared boundaries are edge-matched. Geometries without polygonal components and missing geometries are ignored. A positive gap_width additionally detects narrow gaps up to that width.

Signature

is_valid_coverage(*, gap_width=0.0)

Parameters

float

default:"0.0"

Finite, non-negative maximum width of gaps to report as coverage invalidities.

Returns

bool

True when no invalid coverage edges are found.

This method discovers and validates neighbouring polygons on Spark executors, then reduces the invalid-edge results to one Python bool.

See also

GeoSeries.invalid_coverage_edges: return invalid edges for each input
geometry

Examples

>>> from shapely.geometry import box
>>> from sedona.spark.geopandas import GeoSeries
>>> coverage = GeoSeries([box(0, 0, 1, 1), box(1, 0, 2, 1)])
>>> coverage.is_valid_coverage()
True

Overlapping polygon interiors make a coverage invalid:

>>> overlapping = GeoSeries(
...     [box(0, 0, 1, 1), box(0.5, 0, 1.5, 1)]
... )
>>> overlapping.is_valid_coverage()
False

A positive gap width can also detect narrow gaps:

>>> separated = GeoSeries(
...     [box(0, 0, 1, 1), box(1.1, 0, 2.1, 1)]
... )
>>> separated.is_valid_coverage(gap_width=0.2)
False

​Signature

​Parameters

​Returns

​Examples

Signature

Parameters

Returns

Examples