pointpats.L¶
-
class
pointpats.L(pp, intervals=10, dmin=0.0, dmax=None, d=None)[source]¶ Estimates the \(L\) function for a point pattern [OSullivanU10].
- Parameters
- pp
PointPattern 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.
- pp
Notes
In the analysis of planar point processes, the \(L\) function is a scaled version of \(K\) function. Its estimate is also typically compared to the value expected from a process that displays complete spatial randomness (CSR):
\[L(d) = \sqrt{\frac{K(d)}{\pi}}-d\]where \(K(d)\) is the estimator for the \(K\) function and \(d\) is distance.
The expectation under the null of CSR is 0 (a horizonal line at 0). For a clustered pattern, the empirical \(L\) function will be above the expectation, while for a uniform pattern the empirical function falls below the expectation.
- Attributes
- darray
The distance domain sequence.
- larray
L function over d.
-
__init__(self, pp, intervals=10, dmin=0.0, dmax=None, d=None)[source]¶ Initialize self. See help(type(self)) for accurate signature.
Methods
__init__(self, pp[, intervals, dmin, dmax, d])Initialize self.
plot(self)Plot the distance function