# pointpats.k

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

  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.

  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.