cartagen.quadtree_simplification

quadtree_simplification(points, depth, quadtree=False)

Reduce a set of points by simplification using a quadtree.

For each quadtree cell, the point closest to the cluster’s centroid is selected.

This algorithm was proposed by Bereuter & Weibel. [1] The quadtree algorithm iteratively divide the point set into four chunks, creating clusters, until the depth parameter is reach or only one point remain per cluster.

Parameters:

• points (GeoDataFrame of Point) – The points to reduce.

• depth (int) – The maximum depth of the quadtree. This acts as a selector for the wanted degree of generalisation. The lower the value, the more generalised the point set will be.

• quadtree (bool, optional) – If set to True, returns a tuple with the reduced points and the quadtree.

Returns:

• points (GeoDataFrame of Point) – The provided set of points with two new attributes:

  • ’selected_kmeans’: Set to True if the point has been selected.

• quadtree (QuadTree, optional)

See also

quadtree_selection

Reduce a set of points by selection using a quadtree.

quadtree_aggregation

Reduce a set of points by aggregation using a quadtree.

References

[1]

Pia Bereuter and Robert Weibel. Quadtree-based algorithms for point data generalisation. In Computer Science. 2012. URL: https://api.semanticscholar.org/CorpusID:268066143.

(Source code)