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**BREAKING** Fix loss of structure in cov() and invcov() of AbstractMvNormal subtypes #1373

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**BREAKING** Fix loss of structure in cov() and invcov() of AbstractMvNormal subtypes #1373

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8830b3f
do not convert covariance/precision matrices of AbstractMvNormal subt…
st-- Jul 28, 2021
8b5261c
Merge branch 'master' into st/cov_pdmat
st-- Jan 7, 2022
f919388
Merge branch 'master' into st/cov_pdmat
st-- Nov 23, 2023
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13 changes: 4 additions & 9 deletions src/multivariate/mvnormal.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -106,14 +106,10 @@ function kldivergence(p::AbstractMvNormal, q::AbstractMvNormal)
# This is the generic implementation for AbstractMvNormal, you might need to specialize for your type
length(p) == length(q) ||
throw(DimensionMismatch("Distributions p and q have different dimensions $(length(p)) and $(length(q))"))
# logdetcov is used separately from _cov for any potential optimization done there
return (tr(_cov(q) \ _cov(p)) + sqmahal(q, mean(p)) - length(p) + logdetcov(q) - logdetcov(p)) / 2
# logdetcov is used for any potential optimization done there
return (tr(cov(q) \ cov(p)) + sqmahal(q, mean(p)) - length(p) + logdetcov(q) - logdetcov(p)) / 2
end

# This is a workaround to take advantage of the PDMats objects for MvNormal and avoid copies as Matrix
# TODO: Remove this once `cov(::MvNormal)` returns the PDMats object
_cov(d::AbstractMvNormal) = cov(d)

"""
invcov(d::AbstractMvNormal)

Expand Down Expand Up @@ -256,10 +252,9 @@ params(d::MvNormal) = (d.μ, d.Σ)
@inline partype(d::MvNormal{T}) where {T<:Real} = T

var(d::MvNormal) = diag(d.Σ)
cov(d::MvNormal) = Matrix(d.Σ)
_cov(d::MvNormal) = d.Σ
cov(d::MvNormal) = d.Σ

invcov(d::MvNormal) = Matrix(inv(d.Σ))
invcov(d::MvNormal) = inv(d.Σ)
logdetcov(d::MvNormal) = logdet(d.Σ)

### Evaluation
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4 changes: 2 additions & 2 deletions src/multivariate/mvnormalcanon.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -157,8 +157,8 @@ params(d::MvNormalCanon) = (d.μ, d.h, d.J)
Base.eltype(::Type{<:MvNormalCanon{T}}) where {T} = T

var(d::MvNormalCanon) = diag(inv(d.J))
cov(d::MvNormalCanon) = Matrix(inv(d.J))
invcov(d::MvNormalCanon) = Matrix(d.J)
cov(d::MvNormalCanon) = inv(d.J)
invcov(d::MvNormalCanon) = d.J
logdetcov(d::MvNormalCanon) = -logdet(d.J)


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