ReactiveBayes · bvdmitri · Oct 9, 2023 · Oct 9, 2023 · Oct 9, 2023
diff --git a/Project.toml b/Project.toml
@@ -8,6 +8,7 @@ DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 DomainIntegrals = "cc6bae93-f070-4015-88fd-838f9505a86c"
 DomainSets = "5b8099bc-c8ec-5219-889f-1d9e522a28bf"
+FastCholesky = "2d5283b6-8564-42b6-bb00-83ed8e915756"
 FastGaussQuadrature = "442a2c76-b920-505d-bb47-c5924d526838"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 HCubature = "19dc6840-f33b-545b-b366-655c7e3ffd49"
@@ -44,6 +45,7 @@ DataStructures = "0.17, 0.18"
 Distributions = "0.24, 0.25"
 DomainIntegrals = "0.3.2, 0.4"
 DomainSets = "0.5.2, 0.6"
+FastCholesky = "1.3.0"
 FastGaussQuadrature = "0.4, 0.5"
 ForwardDiff = "0.10"
 HCubature = "1.0.0"

diff --git a/src/ReactiveMP.jl b/src/ReactiveMP.jl
@@ -2,7 +2,7 @@
 module ReactiveMP
 
 # List global dependencies here
-using TinyHugeNumbers, MatrixCorrectionTools
+using TinyHugeNumbers, MatrixCorrectionTools, FastCholesky, LinearAlgebra
 
 import MatrixCorrectionTools: AbstractCorrectionStrategy, correction!
 
@@ -16,7 +16,6 @@ include("helpers/helpers.jl")
 # This should be included before `distributions/*.jl`
 include("score/counting.jl")
 
-include("helpers/algebra/cholesky.jl")
 include("helpers/algebra/companion_matrix.jl")
 include("helpers/algebra/common.jl")
 include("helpers/algebra/permutation_matrix.jl")

diff --git a/src/distributions/wishart_inverse.jl b/src/distributions/wishart_inverse.jl
@@ -79,7 +79,7 @@ end
 function Distributions.rand!(rng::AbstractRNG, sampleable::InverseWishartMessage, x::AbstractVector{<:AbstractMatrix})
     (df, S⁻¹) = Distributions.params(sampleable)
     S = cholinv(S⁻¹)
-    L = Distributions.PDMats.chol_lower(ReactiveMP.fastcholesky(S))
+    L = Distributions.PDMats.chol_lower(fastcholesky(S))
 
     # check 
     p = size(S, 1)
@@ -124,7 +124,7 @@ function Distributions.pdf!(out::AbstractArray{<:Real}, distribution::ReactiveMP
     R = similar(T)
     l = length(T)
 
-    M = ReactiveMP.fastcholesky!(T)
+    M = fastcholesky!(T)
 
     # logc0 evaluation
     h_df = df / 2
@@ -134,7 +134,7 @@ function Distributions.pdf!(out::AbstractArray{<:Real}, distribution::ReactiveMP
     # logkernel evaluation 
     @inbounds for i in 1:length(out)
         copyto!(T, 1, samples[i], 1, l)
-        C = ReactiveMP.fastcholesky!(T)
+        C = fastcholesky!(T)
         ld = logdet(C)
         LinearAlgebra.inv!(C)
         mul!(R, Ψ, C.factors)

diff --git a/src/helpers/algebra/cholesky.jl b/src/helpers/algebra/cholesky.jl
diff --git a/test/algebra/test_cholesky.jl b/test/algebra/test_cholesky.jl
diff --git a/test/distributions/test_mv_normal_mean_covariance.jl b/test/distributions/test_mv_normal_mean_covariance.jl
@@ -4,6 +4,7 @@ using Test
 using ReactiveMP
 using LinearAlgebra
 using Distributions
+using FastCholesky
 
 @testset "MvNormalMeanCovariance" begin
     @testset "Constructor" begin

diff --git a/test/distributions/test_mv_normal_mean_precision.jl b/test/distributions/test_mv_normal_mean_precision.jl
@@ -4,6 +4,7 @@ using Test
 using ReactiveMP
 using LinearAlgebra
 using Distributions
+using FastCholesky
 
 @testset "MvNormalMeanPrecision" begin
     @testset "Constructor" begin

diff --git a/test/distributions/test_mv_normal_weighted_mean_precision.jl b/test/distributions/test_mv_normal_weighted_mean_precision.jl
@@ -4,6 +4,7 @@ using Test
 using ReactiveMP
 using LinearAlgebra
 using Distributions
+using FastCholesky
 
 @testset "MvNormalWeightedMeanPrecision" begin
     @testset "Constructor" begin

diff --git a/test/distributions/test_pointmass.jl b/test/distributions/test_pointmass.jl
@@ -6,6 +6,7 @@ using Distributions
 using Random
 using SpecialFunctions
 using LinearAlgebra: UniformScaling, I
+using FastCholesky
 
 import ReactiveMP: CountingReal, tiny, huge
 import ReactiveMP.MacroHelpers: @test_inferred

diff --git a/test/distributions/test_sample_list.jl b/test/distributions/test_sample_list.jl
@@ -7,6 +7,7 @@ using Distributions
 using LinearAlgebra
 using StaticArrays
 using StableRNGs
+using FastCholesky
 
 import ReactiveMP: deep_eltype, get_samples, get_weights, sample_list_zero_element
 import ReactiveMP: get_meta, is_meta_present, get_unnormalised_weights, get_entropy, get_logproposal, get_logintegrand

diff --git a/test/distributions/test_wishart.jl b/test/distributions/test_wishart.jl
@@ -5,6 +5,7 @@ using ReactiveMP
 using Distributions
 using Random
 using LinearAlgebra
+using FastCholesky
 
 import ReactiveMP: WishartMessage
 

diff --git a/test/distributions/test_wishart_inverse.jl b/test/distributions/test_wishart_inverse.jl
@@ -6,6 +6,7 @@ using Distributions
 using Random
 using LinearAlgebra
 using StableRNGs
+using FastCholesky
 
 import ReactiveMP: InverseWishartMessage
 import Distributions: pdf!

diff --git a/test/rules/mv_normal_mean_precision/test_precision.jl b/test/rules/mv_normal_mean_precision/test_precision.jl
@@ -3,6 +3,7 @@ module RulesMvNormalMeanPrecisionPrecisionTest
 using Test
 using ReactiveMP
 using Random
+using FastCholesky
 
 import ReactiveMP: WishartMessage, @test_rules
 

diff --git a/test/rules/wishart/test_marginals.jl b/test/rules/wishart/test_marginals.jl
@@ -4,6 +4,7 @@ using Test
 using ReactiveMP
 using Random
 using Distributions
+using FastCholesky
 
 import ReactiveMP: WishartMessage, @test_marginalrules
 

diff --git a/test/rules/wishart/test_out.jl b/test/rules/wishart/test_out.jl
@@ -4,6 +4,7 @@ using Test
 using ReactiveMP
 using Random
 using Distributions
+using FastCholesky
 
 import ReactiveMP: WishartMessage, @test_rules