cartagen.quadtree_selection

cartagen.quadtree_selection#

quadtree_selection(points, depth, column, quadtree=False)#

Reduce a set of points by selection using a quadtree.

For each quadtree cell, the point with the largest value 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.

  • column (str) – Name of the column to use.

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

    • ’cell_count’: The number of points in the quadtree cell represented by this point.

  • quadtree (QuadTree, optional)

See also

quadtree_simplification

Reduce a set of points by simplification using a quadtree.

quadtree_aggregation

Reduce a set of points by aggregation using a quadtree.

References

(Source code)

../_images/quadtree_selection.png