Latin Hypercubic sampling¶

class
stats_arrays.
LatinHypercubeRNG
(params, seed=None, samples=10, **kwargs)¶ A random number generator that precalculates a sample space to draw from.
Inputs
 params : A Parameter array which gives parameters for distributions (one distribution per row).
 seed : An integer (or array of integers) to seed the NumPy random number generator.
 samples : An integer number of samples to construct for each distribution.

__init__
(params, seed=None, samples=10, **kwargs)¶

build_hypercube
()¶ Build an array, of shape self.length rows by self.samples columns, which contains the sample space to be drawn from when doing Latin Hypercubic sampling.
Each row represents a different data point and distribution. The final sample space is self.hypercube. All distributions from uncertainty_choices are usable, and bounded distributions are also fine.
Builds
self.hypercube : Numpy array with dimensions self.length by self.samples.

next
()¶ Draw directly from precomputed sample space.