# pointpats.G¶

class pointpats.G(pp, intervals=10, dmin=0.0, dmax=None, d=None)[source]

Estimates the nearest neighbor distance distribution function G for a point pattern.

Parameters
ppPointPattern

Point Pattern instance.

intervalsint

The length of distance domain sequence.

dminfloat

The minimum of the distance domain.

dmaxfloat

The maximum of the distance domain.

dsequence

The distance domain sequence. If d is specified, intervals, dmin and dmax are ignored.

Notes

In the analysis of planar point processes, the estimate of $$G$$ is typically compared to the value expected from a completely spatial random (CSR) process given as:

$G(d) = 1 - e^{-\lambda \pi d^2}$

where $$\lambda$$ is the intensity (points per unit area) of the point process and $$d$$ is distance.

For a clustered pattern, the empirical function will be above the expectation, while for a uniform pattern the empirical function falls below the expectation.

Attributes
namestring

Name of the function. (“G”, “F”, “J”, “K” or “L”)

darray

The distance domain sequence.

Garray

The cumulative nearest neighbor distance distribution over d.

Methods

 plot(self[, qq]) Plot the distance function
__init__(self, pp, intervals=10, dmin=0.0, dmax=None, d=None)[source]

Initialize self. See help(type(self)) for accurate signature.