# scipy.stats.qmc.LatinHypercube.random#

LatinHypercube.random(n=1, *, workers=1)[source]#

Draw n in the half-open interval [0, 1).

Parameters:
nint, optional

Number of samples to generate in the parameter space. Default is 1.

workersint, optional

Only supported with Halton. Number of workers to use for parallel processing. If -1 is given all CPU threads are used. Default is 1. It becomes faster than one worker for n greater than $$10^3$$.

Returns:
samplearray_like (n, d)

QMC sample.