Remove constraint on AbstractPDMat #1552
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| Original file line number | Diff line number | Diff line change | ||||
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@@ -19,7 +19,7 @@ which is also a subtype of `AbstractMvNormal` to represent a multivariate normal | |||||
| canonical parameters. Particularly, `MvNormalCanon` is defined as: | ||||||
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| ```julia | ||||||
| struct MvNormalCanon{T<:Real,P<:AbstractMatrix,V<:AbstractVector} <: AbstractMvNormal | ||||||
| μ::V # the mean vector | ||||||
| h::V # potential vector, i.e. inv(Σ) * μ | ||||||
| J::P # precision matrix, i.e. inv(Σ) | ||||||
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@@ -40,10 +40,19 @@ const ZeroMeanIsoNormalCanon{Axes} = MvNormalCanon{Float64, ScalMat{Float64}, | |||||
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| **Note:** `MvNormalCanon` share the same set of methods as `MvNormal`. | ||||||
| """ | ||||||
| struct MvNormalCanon{T<:Real,P<:AbstractMatrix,V<:AbstractVector} <: AbstractMvNormal | ||||||
| μ::V # the mean vector | ||||||
| h::V # potential vector, i.e. inv(Σ) * μ | ||||||
| J::P # precision matrix, i.e. inv(Σ) | ||||||
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| function MvNormalCanon{T,P,V}(μ::V, h::AbstractVector, J::P) where {T<:Real, V<:AbstractVector{T}, P} | ||||||
| length(μ) == length(h) == dim(J) || throw(DimensionMismatch("Inconsistent argument dimensions")) | ||||||
| if typeof(μ) === typeof(h) | ||||||
| return new{T,typeof(J),typeof(μ)}(μ, h, J) | ||||||
| else | ||||||
| return new{T,typeof(J),Vector{T}}(collect(μ), collect(h), J) | ||||||
| end | ||||||
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There was a problem hiding this comment. This should be handled by an outer constructor shouldn't it? It seems a bit weird to lie about the type of the constructed distribution and get something else than There was a problem hiding this comment. that does seem odd. |
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| end | ||||||
| end | ||||||
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| const FullNormalCanon = MvNormalCanon{Float64,PDMat{Float64,Matrix{Float64}},Vector{Float64}} | ||||||
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@@ -56,26 +65,17 @@ const ZeroMeanIsoNormalCanon{Axes} = MvNormalCanon{Float64,ScalMat{Float64},Zer | |||||
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| ### Constructors | ||||||
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There was a problem hiding this comment. I guess we want to keep this function but change |
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| function MvNormalCanon(μ::AbstractVector{T}, h::AbstractVector{T}, J::P) where {T<:Real, P} | ||||||
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| R = promote_type(T, eltype(J)) | ||||||
| MvNormalCanon{T,P,typeof(μ)}(convert(AbstractArray{R}, μ), convert(AbstractArray{R}, h), convert(AbstractArray{R}, J)) | ||||||
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There was a problem hiding this comment. For the old function here (relaxed to
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| end | ||||||
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| function MvNormalCanon(μ::AbstractVector{<:Real}, h::AbstractVector{<:Real}, J::AbstractMatrix{<:Real}) | ||||||
| R = Base.promote_eltype(μ, h, J) | ||||||
| MvNormalCanon(convert(AbstractArray{R}, μ), convert(AbstractArray{R}, h), convert(AbstractArray{R}, J)) | ||||||
| end | ||||||
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| function MvNormalCanon(h::AbstractVector{<:Real}, J::AbstractMatrix{<:Real}) | ||||||
| length(h) == dim(J) || throw(DimensionMismatch("Inconsistent argument dimensions")) | ||||||
| R = Base.promote_eltype(h, J) | ||||||
| hh = convert(AbstractArray{R}, h) | ||||||
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@@ -89,7 +89,7 @@ end | |||||
| Construct a multivariate normal distribution with potential vector `h` and precision matrix | ||||||
| `J`. | ||||||
| """ | ||||||
| MvNormalCanon(h::AbstractVector{<:Real}, J::Matrix{<:Real}) = MvNormalCanon(h, PDMat(J)) | ||||||
| MvNormalCanon(h::AbstractVector{<:Real}, J::Diagonal{<:Real}) = MvNormalCanon(h, PDiagMat(J.diag)) | ||||||
| MvNormalCanon(μ::AbstractVector{<:Real}, J::Union{Symmetric{<:Real,<:Diagonal{<:Real}},Hermitian{<:Real,<:Diagonal{<:Real}}}) = MvNormalCanon(μ, PDiagMat(J.data.diag)) | ||||||
| function MvNormalCanon(h::AbstractVector{<:Real}, J::UniformScaling{<:Real}) | ||||||
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@@ -170,7 +170,7 @@ sqmahal!(r::AbstractVector, d::MvNormalCanon, x::AbstractMatrix) = quad!(r, d.J, | |||||
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| # Sampling (for GenericMvNormal) | ||||||
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| unwhiten_winv!(J::AbstractMatrix, x::AbstractVecOrMat) = unwhiten!(inv(J), x) | ||||||
| unwhiten_winv!(J::PDiagMat, x::AbstractVecOrMat) = whiten!(J, x) | ||||||
| unwhiten_winv!(J::ScalMat, x::AbstractVecOrMat) = whiten!(J, x) | ||||||
| if isdefined(PDMats, :PDSparseMat) | ||||||
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| Original file line number | Diff line number | Diff line change |
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@@ -9,6 +9,7 @@ using Distributions | |
| using LinearAlgebra, Random, Test | ||
| using SparseArrays | ||
| using FillArrays | ||
| using BlockDiagonals | ||
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| ###### General Testing | ||
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@@ -51,7 +52,11 @@ using FillArrays | |
| (MvNormal(mu, Diagonal(dv)), mu, Matrix(Diagonal(dv))), | ||
| (MvNormal(mu, Symmetric(Diagonal(dv))), mu, Matrix(Diagonal(dv))), | ||
| (MvNormal(mu, Hermitian(Diagonal(dv))), mu, Matrix(Diagonal(dv))), | ||
| (MvNormal(mu_r, Diagonal(dv)), mu_r, Matrix(Diagonal(dv))), | ||
| (MvNormal([mu_r; mu_r], BlockDiagonal([C, C])), [mu_r; mu_r], Matrix(BlockDiagonal([C, C]))), | ||
| (MvNormal([mu_r; mu_r], BlockDiagonal([PDMat(C), PDMat(C)])), [mu_r; mu_r], Matrix(BlockDiagonal([C, C]))), | ||
| (MvNormalCanon([mu_r; mu_r], BlockDiagonal([C, C])), BlockDiagonal([C, C]) \ [mu_r; mu_r], inv(BlockDiagonal([C, C]))), | ||
| ] | ||
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| @test mean(g) ≈ μ | ||
| @test cov(g) ≈ Σ | ||
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I guess here we might want to change it to
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The tests pass, right now.
It took some effort to make sure the constructors cover the right cases and don't stackoverflow, or ambiguity error.
I could go and give them another pass over now that it is working, but I wouldn't want to just go and relax the ones there right now whily-nilly
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I think without this relaxation you can provoke a test error when you use something like
MvNormal(::Vector{Float32}, ::BlockDiagonal{Float64}).