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.

coordinatesnumpy.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.

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