Sampler APIs
Sample
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Samplers
QuasiMonteCarlo.GridSample
— TypeGridSample{T}
The grid is given by lb:dx[i]:ub
in the ith direction.
QuasiMonteCarlo.UniformSample
— Typestruct UniformSample <: SamplingAlgorithm end
Uniformly distributed random numbers.
QuasiMonteCarlo.SobolSample
— Typestruct SobolSample <: SamplingAlgorithm end
Samples using the Sobol sequence.
QuasiMonteCarlo.LatinHypercubeSample
— Typestruct LatinHypercubeSample <: SamplingAlgorithm end
Samples using a Latin Hypercube.
LatinHypercubeSample(threading=false)
Keyword arguments:
threading
: whether to use threading. Default is false, i.e. serial.
QuasiMonteCarlo.LatticeRuleSample
— Typestruct LatticeRuleSample <: SamplingAlgorithm end
Samples using a randomly-shifted rank-1 lattice rule.
QuasiMonteCarlo.LowDiscrepancySample
— Typestruct LowDiscrepancySample{T} <: SamplingAlgorithm
base[i]
is the base in the ith direction.
QuasiMonteCarlo.GoldenSample
— Typestruct GoldenSample <: SamplingAlgorithm end
QuasiMonteCarlo.KroneckerSample
— Typestruct KroneckerSample{A,B} <: SamplingAlgorithm
KroneckerSample(alpha, s0)
for a Kronecker sequence, where alpha is an length-d vector of irrational numbers (often sqrt(d)) and s0 is a length-d seed vector (often 0).
QuasiMonteCarlo.SectionSample
— Typestruct SectionSample{T} <: SamplingAlgorithm
SectionSample(x0, sampler)
where sampler
is any sampler above and x0
is a vector of either NaN
for a free dimension or some scalar for a constrained dimension.