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Do not promote mean and covariance of MvNormal to common element type #1965

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Do not promote mean and covariance of MvNormal to common element type #1965

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00d80b4
Do not promote mean and covariance of `MvNormal` to common element type
devmotion Apr 11, 2025
5a69e1d
Fix failing test
devmotion Apr 11, 2025
7637c4d
More test fixes
devmotion Apr 11, 2025
12241fe
Merge branch 'master' into dw/mvnormal_promote
devmotion Apr 13, 2025
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16 changes: 7 additions & 9 deletions src/multivariate/mvnormal.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -178,14 +178,9 @@ const ZeroMeanDiagNormal{Axes} = MvNormal{Float64,PDiagMat{Float64,Vector{Float6
const ZeroMeanFullNormal{Axes} = MvNormal{Float64,PDMat{Float64,Matrix{Float64}},Zeros{Float64,1,Axes}}

### Construction
function MvNormal(μ::AbstractVector{T}, Σ::AbstractPDMat{T}) where {T<:Real}
size(Σ, 1) == length(μ) || throw(DimensionMismatch("The dimensions of mu and Sigma are inconsistent."))
MvNormal{T,typeof(Σ), typeof(μ)}(μ, Σ)
end

function MvNormal(μ::AbstractVector{<:Real}, Σ::AbstractPDMat{<:Real})
R = Base.promote_eltype(μ, Σ)
MvNormal(convert(AbstractArray{R}, μ), convert(AbstractArray{R}, Σ))
size(Σ, 1) == length(μ) || throw(DimensionMismatch("The dimensions of mu and Sigma are inconsistent."))
return MvNormal{Base.promote_eltype(μ, Σ),typeof(Σ),typeof(μ)}(μ, Σ)
end

# constructor with general covariance matrix
Expand All @@ -197,8 +192,11 @@ Construct a multivariate normal distribution with mean `μ` and covariance matri
MvNormal(μ::AbstractVector{<:Real}, Σ::AbstractMatrix{<:Real}) = MvNormal(μ, PDMat(Σ))
MvNormal(μ::AbstractVector{<:Real}, Σ::Diagonal{<:Real}) = MvNormal(μ, PDiagMat(Σ.diag))
MvNormal(μ::AbstractVector{<:Real}, Σ::Union{Symmetric{<:Real,<:Diagonal{<:Real}},Hermitian{<:Real,<:Diagonal{<:Real}}}) = MvNormal(μ, PDiagMat(Σ.data.diag))
MvNormal(μ::AbstractVector{<:Real}, Σ::UniformScaling{<:Real}) =
MvNormal(μ, ScalMat(length(μ), Σ.λ))
function MvNormal(μ::AbstractVector{<:Real}, Σ::UniformScaling{<:Real})
# Promote `Bool` (`I`) to avoid surprising covariance element types
λ = Σ isa UniformScaling{Bool} ? promote_type(eltype(μ), Bool)(Σ.λ) : Σ.λ
return MvNormal(μ, ScalMat(length(μ), λ))
end
function MvNormal(
μ::AbstractVector{<:Real}, Σ::Diagonal{<:Real,<:FillArrays.AbstractFill{<:Real,1}}
)
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10 changes: 5 additions & 5 deletions test/multivariate/mvnormal.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -82,9 +82,9 @@ end
C = [4. -2. -1.; -2. 5. -1.; -1. -1. 6.]
J = inv(C)
h = J \ mu
@test typeof(MvNormal(mu, PDMat(Array{Float32}(C)))) == typeof(MvNormal(mu, PDMat(C)))
@test typeof(MvNormal(mu, Array{Float32}(C))) == typeof(MvNormal(mu, PDMat(C)))
@test typeof(@test_deprecated(MvNormal(mu, 2.0f0))) == typeof(@test_deprecated(MvNormal(mu, 2.0)))
@test MvNormal(mu, PDMat(Array{Float32}(C))) isa MvNormal{Float64, PDMat{Float32, Matrix{Float32}}, Vector{Float64}}
@test MvNormal(mu, Array{Float32}(C)) isa MvNormal{Float64, PDMat{Float32, Matrix{Float32}}, Vector{Float64}}
@test @test_deprecated(MvNormal(mu, 2.0f0)) isa MvNormal{Float64, ScalMat{Float32}, Vector{Float64}}

@test typeof(MvNormalCanon(h, PDMat(Array{Float32}(J)))) == typeof(MvNormalCanon(h, PDMat(J)))
@test typeof(MvNormalCanon(h, Array{Float32}(J))) == typeof(MvNormalCanon(h, PDMat(J)))
Expand All @@ -102,9 +102,9 @@ end
@test typeof(convert(MvNormalCanon{Float64}, d)) == typeof(MvNormalCanon(mu, h, PDMat(J)))
@test typeof(convert(MvNormalCanon{Float64}, d.μ, d.h, d.J)) == typeof(MvNormalCanon(mu, h, PDMat(J)))

@test MvNormal(mu, I) === @test_deprecated(MvNormal(mu, 1))
@test MvNormal(mu, I) === @test_deprecated(MvNormal(mu, 1.0))
@test MvNormal(mu, 9 * I) === @test_deprecated(MvNormal(mu, 3))
@test MvNormal(mu, 0.25f0 * I) === @test_deprecated(MvNormal(mu, 0.5))
@test MvNormal(mu, 0.25f0 * I) === @test_deprecated(MvNormal(mu, 0.5f0))

@test MvNormal(mu, I) === MvNormal(mu, Diagonal(Ones(length(mu))))
@test MvNormal(mu, 9 * I) === MvNormal(mu, Diagonal(Fill(9, length(mu))))
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