Dispatch on invunwhiten! from PDMats (#250)

* Dispatch on invunwhiten! from PDMats

* Typo

* Fix tests

* Increment patch number

* Remove outdated comment

---------

Co-authored-by: Seth Axen <[email protected]>

Author: ErikQQY

Project.toml

@@ -1,7 +1,7 @@
 name = "Pathfinder"
 uuid = "b1d3bc72-d0e7-4279-b92f-7fa5d6d2d454"
 authors = ["Seth Axen <[email protected]> and contributors"]
-version = "0.9.16"
+version = "0.9.17"
 
 [deps]
 ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
@@ -50,7 +50,7 @@ Optim = "1.7.2"
 Optimization = "3.21, 4"
 OptimizationNLopt = "0.2, 0.3"
 OptimizationOptimJL = "0.2.1, 0.3, 0.4"
-PDMats = "0.11.26"
+PDMats = "0.11.35"
 PSIS = "0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9"
 ProgressLogging = "0.1.4"
 Random = "1"

src/integration/advancedhmc.jl

@@ -70,7 +70,7 @@ function Base.rand(
 ) where {T}
     M⁻¹ = metric.M⁻¹
     r = randn(rng, T, size(metric)...)
-    invunwhiten!(r, M⁻¹, r)
+    PDMats.invunwhiten!(r, M⁻¹, r)
     return r
 end
 

src/woodbury.jl

@@ -414,8 +414,7 @@ function PDMats.whiten!(
     return ldiv!(pdfactorize(W).L, r)
 end
 
-# similar to unwhiten!(r, inv(W), x) but without the inversion
-function invunwhiten!(
+function PDMats.invunwhiten!(
     r::AbstractVecOrMat{T}, W::WoodburyPDMat, x::AbstractVecOrMat{T}
 ) where {T}
     copyto!(r, x)

test/woodbury.jl

@@ -358,18 +358,18 @@ end
             _, R = factorize(W)
 
             x = randn(T, n)
-            @test @inferred(Pathfinder.invunwhiten!(similar(x), W, x)) ≈ R \ x
+            @test @inferred(invunwhiten!(similar(x), W, x)) ≈ R \ x
 
             X = randn(T, n, 100)
-            @test @inferred(Pathfinder.invunwhiten!(similar(X), W, X)) ≈ R \ X
+            @test @inferred(invunwhiten!(similar(X), W, X)) ≈ R \ X
         end
 
         @testset "quad/quad!" begin
             x = randn(T, n)
             @test @inferred(quad(W, x)) ≈ dot(x, Wmat, x)
 
             u = randn(T, n)
-            @test quad(W, Pathfinder.invunwhiten!(similar(u), W, u)) ≈ dot(u, u)
+            @test quad(W, invunwhiten!(similar(u), W, u)) ≈ dot(u, u)
 
             X = randn(T, n, 10)
             quad_W_X = @inferred quad(W, X)
@@ -379,7 +379,7 @@ end
             @test quad_W_X2 ≈ quad_W_X
 
             U = randn(T, n, 10)
-            @test quad(W, Pathfinder.invunwhiten!(similar(U), W, U)) ≈
+            @test quad(W, invunwhiten!(similar(U), W, U)) ≈
                 vec(sum(abs2, U; dims=1))
         end