pointpats.J

class pointpats.J(pp, n=100, intervals=10, dmin=0.0, dmax=None, d=None)

Estimates the J function for a point pattern [LB96]

Parameters

ppPointPattern

Point Pattern instance.

nint

Number of empty space points (random points).

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

The \(J\) function is a ratio of the hazard functions defined for \(G\) and \(F\):

\[J(d) = \frac{1-G(d) }{1-F(d)}\]

where \(G(d)\) is the nearest neighbor distance distribution function (see G) and \(F(d)\) is the empty space function (see F).

For a CSR process the J function equals 1. Empirical values larger than 1 are indicative of uniformity, while values below 1 suggest clustering.

Attributes

darray

The distance domain sequence.

jarray

F function over d.

__init__(self, pp, n=100, intervals=10, dmin=0.0, dmax=None, d=None)

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

Methods

__init__(self, pp[, n, intervals, dmin, dmax, d])	Initialize self.
plot(self[, qq])	Plot the distance function

plot(self, qq=False)

Plot the distance function

Parameters

qq: Boolean

If False the statistic is plotted against distance. If Frue, the quantile-quantile plot is generated, observed vs. CSR.