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).



Find minimum bounding rectangle of a point array.


Find convex hull of a point array.


Find mean center of a point array.

weighted_mean_center(points, weights)

Find weighted mean center of a marked point pattern.


Find manhattan median of a point array.


Calculate standard distance of a point array.


Calculate the Euclidean median for a point pattern.


Calculate parameters of standard deviational ellipse for a point pattern.


WARNING: This function is deprecated in favor of minimum_bounding_circle

dtot(coord, points)

Sum of Euclidean distances between event points and a selected point.


plot_density(data, bandwidth[, kernel, ...])

Plot kernel density of a given point pattern

Quadrat Based Statistics

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, ...])

Quadrat analysis of point pattern.

Distance Based Statistics

f(coordinates[, support, distances, metric, ...])

Ripley's F function

g(coordinates[, support, distances, metric, ...])

Ripley's G function

k(coordinates[, support, distances, metric, ...])

Ripley's K function

j(coordinates[, support, distances, metric, ...])

Ripely's J function

l(coordinates[, support, permutations, ...])

Ripley's L function

f_test(coordinates[, support, distances, ...])

Ripley's F function

g_test(coordinates[, support, distances, ...])

Ripley's G function

k_test(coordinates[, support, distances, ...])

Ripley's K function

j_test(coordinates[, support, distances, ...])

Ripley's J function

l_test(coordinates[, support, distances, ...])

Ripley's L function

Window functions

Window(parts[, holes])

Geometric container for point patterns.


Convert a libpysal polygon to a Window.



Random distributions

random.poisson(hull[, intensity, size])

Simulate a poisson random point process with a specified intensity.

random.normal(hull[, center, cov, size])

Simulate a multivariate random normal point cluster

random.cluster_poisson(hull[, intensity, ...])

Simulate a cluster poisson random point process with a specified intensity & number of seeds.

random.cluster_normal(hull[, cov, size, n_seeds])

Simulate a cluster poisson random point process with a specified intensity & number of seeds.

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[, ...])

Global Knox statistic for space-time interactions

KnoxLocal(s_coords, t_coords, delta, tau[, ...])

Local Knox statistics for space-time interactions

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.