API

filldist(d::Distribution, ns...)

Create a product distribution from a single distribution and a list of dimension sizes. If size(d) is (d1, d2, ...) and ns is (n1, n2, ...), then the resulting distribution will have size (d1, d2, ..., n1, n2, ...).

The default behaviour is to use Distributions.product_distribution, with FillArrays.Fill supplied as the array argument. However, this behaviour is specialised in some instances, such as the one shown below.

When sampling from the resulting distribution, the output will be an array where each element is sampled from the original distribution d.

Examples

julia> d = filldist(Normal(0, 1), 4, 5)  # size(Normal(0, 1)) == ()
DistributionsAD.MatrixOfUnivariate{Continuous, Normal{Float64}, FillArrays.Fill{Normal{Float64}, 2, Tuple{Base.OneTo{Int64}, Base.OneTo{Int64}}}}(
dists: Fill(Normal{Float64}(μ=0.0, σ=1.0), 4, 5)
)

julia> size(d)
(4, 5)

julia> Random.seed!(42); rand(d)
4×5 Matrix{Float64}:
 -0.363357   0.816307  -2.11433     0.433886  -0.206613
  0.251737   0.476738   0.0437817  -0.39544   -0.310744
 -0.314988  -0.859555  -0.825335    0.517131  -0.0404734
 -0.311252  -1.46929    0.840289    1.44722    0.104771

arraydist(dists::AbstractArray{<:Distribution})

Create a product distribution from an array of sub-distributions. Each element of dists should have the same size. If the size of each element is (d1, d2, ...), and size(dists) is (n1, n2, ...), then the resulting distribution will have size (d1, d2, ..., n1, n2, ...).

The default behaviour is to directly use Distributions.product_distribution, although this can sometimes be specialised.

Examples

julia> d1 = arraydist([Normal(0, 1), Normal(10, 1)])
Product{Continuous, Normal{Float64}, Vector{Normal{Float64}}}(v=Normal{Float64}[Normal{Float64}(μ=0.0, σ=1.0), Normal{Float64}(μ=10.0, σ=1.0)])

julia> size(d1)
(2,)

julia> Random.seed!(42); rand(d1)
2-element Vector{Float64}:
 0.7883556016042917
 9.1201414040456

julia> d2 = arraydist([Normal(0, 1) Normal(5, 1); Normal(10, 1) Normal(15, 1)])
DistributionsAD.MatrixOfUnivariate{Continuous, Normal{Float64}, Matrix{Normal{Float64}}}(
dists: Normal{Float64}[Normal{Float64}(μ=0.0, σ=1.0) Normal{Float64}(μ=5.0, σ=1.0); Normal{Float64}(μ=10.0, σ=1.0) Normal{Float64}(μ=15.0, σ=1.0)]
)

julia> size(d2)
(2, 2)

julia> Random.seed!(42); rand(d2)
2×2 Matrix{Float64}:
 0.788356   4.12621
 9.12014   14.2667