# API reference¶

## Point Pattern¶

 PointPattern(points[, window, names, …]) Planar Point Pattern Class 2-D.

## Point Processes¶

 PointProcess(window, n, samples[, asPP]) Point Process base class. PoissonPointProcess(window, n, samples[, …]) Poisson point process including $$N$$-conditioned CSR process and $$\lambda$$-conditioned CSR process. PoissonClusterPointProcess(window, n, …[, …]) Poisson cluster point process (Neyman Scott).

## Centrography¶

 mbr(points) Find minimum bounding rectangle of a point array. hull(points) Find convex hull of a point array. mean_center(points) Find mean center of a point array. weighted_mean_center(points, weights) Find weighted mean center of a marked point pattern. manhattan_median(points) Find manhattan median of a point array. std_distance(points) Calculate standard distance of a point array. euclidean_median(points) Calculate the Euclidean median for a point pattern. ellipse(points) Calculate parameters of standard deviational ellipse for a point pattern. skyum(points[, not_hull]) Implements Skyum (1990)’s algorithm for the minimum bounding circle in R^2. dtot(coord, points) Sum of Euclidean distances between event points and a selected point. _circle(p, q, r[, dmetric]) Returns (radius, (center_x, center_y)) of the circumscribed circle by the triangle pqr.

 RectangleM(pp[, count_column, count_row, …]) Rectangle grid structure for quadrat-based method. HexagonM(pp, lh) Hexagon grid structure for quadrat-based method. QStatistic(pp[, shape, nx, ny, lh, realizations]) Quadrat analysis of point pattern.

## Distance Based Statistics¶

 DStatistic(name) Abstract Base Class for distance statistics. G(pp[, intervals, dmin, dmax, d]) Estimates the nearest neighbor distance distribution function G for a point pattern. F(pp[, n, intervals, dmin, dmax, d]) Estimates the empty space distribution function for a point pattern: F(d). J(pp[, n, intervals, dmin, dmax, d]) Estimates the J function for a point pattern [LB96] K(pp[, intervals, dmin, dmax, d]) Estimates the K function for a point pattern. L(pp[, intervals, dmin, dmax, d]) Estimates the $$L$$ function for a point pattern [OSullivanU10]. Envelopes(*args, **kwargs) Abstract base class for simulation envelopes. Genv(pp[, intervals, dmin, dmax, d, pct, …]) Simulation envelope for G function. Fenv(pp[, n, intervals, dmin, dmax, d, pct, …]) Simulation envelope for F function. Jenv(pp[, n, intervals, dmin, dmax, d, pct, …]) Simulation envelope for J function. Kenv(pp[, intervals, dmin, dmax, d, pct, …]) Simulation envelope for K function. Lenv(pp[, intervals, dmin, dmax, d, pct, …]) Simulation envelope for L function.

## Window functions¶

 Window(parts[, holes]) Geometric container for point patterns. as_window(pysal_polygon) Convert a libpysal polygon to a Window. poly_from_bbox(bbox) to_ccf(poly)

## Space-Time Interaction Tests¶

 SpaceTimeEvents(path, time_col[, …]) Method for reformatting event data stored in a shapefile for use in calculating metrics of spatio-temporal interaction. knox(s_coords, t_coords, delta, tau[, …]) Knox test for spatio-temporal interaction. mantel(s_coords, t_coords[, permutations, …]) Standardized Mantel test for spatio-temporal interaction. jacquez(s_coords, t_coords, k[, permutations]) Jacquez k nearest neighbors test for spatio-temporal interaction. modified_knox(s_coords, t_coords, delta, tau) Baker’s modified Knox test for spatio-temporal interaction.