cartagen.partition_quadtree

partition_quadtree(objects, max_points=1, max_depth=None)

Partition objects using a quadtree.

This algorithm inserts the centroids (or surface points) of the provided objects into a quadtree built over the extent of the dataset, then collects the leaf cells and assigns each object to the leaf it was placed in.

Parameters:

• objects (GeoDataFrame) – The objects to partition. Supports Point, LineString, and Polygon geometries.

• max_points (int, optional) – Maximum number of points a quadtree node can hold before it subdivides. Lower values produce finer partitions. Defaults to 1.

• max_depth (int, optional) – Maximum depth the quadtree is allowed to reach. Nodes at this depth will not subdivide further, even if they exceed max_points. If set to None, depth is unlimited. Defaults to None.

Returns:

partition (tuple) – A tuple containing two elements:

1. A list of lists of index ordered by the quadtree leaf cells

2. A list of the geometry of the quadtree leaf cells

See also

partition_grid

Partition objects using a grid of a given shape.

partition_networks

Partition objects using one or multiple networks.

Examples

>>> points = gpd.GeoDataFrame(geometry=[Point(1, 1), Point(3, 3)])
>>> partition_quadtree(points, max_points=1)
([[0], [1]], [<POLYGON (...)>, <POLYGON (...)>])

(Source code)