pointpats.k

pointpats.k(coordinates, support=None, distances=None, metric='euclidean', edge_correction=None)[source]

Ripley’s K function

This function counts the number of pairs of points that are closer than a given distance. As d increases, K approaches the number of point pairs.

coordinatesgeopandas object | numpy.ndarray, (n,2)

input coordinates to function

supporttuple of length 1, 2, or 3, int, or numpy.ndarray

tuple, encoding (stop,), (start, stop), or (start, stop, num) int, encoding number of equally-spaced intervals numpy.ndarray, used directly within numpy.histogram

distances: numpy.ndarray, (n, p) or (p,)

distances from every point in a random point set of size p to some point in coordinates

metric: str or callable

distance metric to use when building search tree

hull: bounding box, scipy.spatial.ConvexHull, shapely.geometry.Polygon

the hull used to construct a random sample pattern, if distances is None

edge_correction: bool or str

whether or not to conduct edge correction. Not yet implemented.

Returns:
a tuple containing the support values used to evalute the function
and the values of the function at each distance value in the support.