Merge pull request #77 from JuliaStats/db/LinAlgnames

Update to cholesky name and accessors

Author: andreasnoack

REQUIRE

@@ -1,2 +1,2 @@
-julia 0.7.0-DEV.3449
+julia 0.7.0-DEV.5190 # for cholesky function
 Compat 0.61.0

src/chol.jl

@@ -1,5 +1,5 @@
 CholType{T,S<:AbstractMatrix} = Cholesky{T,S}
-chol_lower(a::Matrix) = chol(a)'
+chol_lower(a::Matrix) = cholesky(a).L
 
 if HAVE_CHOLMOD
     CholTypeSparse{T} = SuiteSparse.CHOLMOD.Factor{T}

src/pdmat.jl

@@ -13,7 +13,7 @@ function PDMat(mat::AbstractMatrix,chol::CholType)
     PDMat{eltype(mat),typeof(mat)}(d, mat, chol)
 end
 
-PDMat(mat::Matrix) = PDMat(mat, cholfact(mat))
+PDMat(mat::Matrix) = PDMat(mat, cholesky(mat))
 PDMat(mat::Symmetric) = PDMat(Matrix(mat))
 PDMat(fac::CholType) = PDMat(Matrix(fac), fac)
 

src/pdsparsemat.jl

@@ -13,7 +13,7 @@ function PDSparseMat(mat::AbstractSparseMatrix,chol::CholTypeSparse)
     PDSparseMat{eltype(mat),typeof(mat)}(d, mat, chol)
 end
 
-PDSparseMat(mat::SparseMatrixCSC) = PDSparseMat(mat, cholfact(mat))
+PDSparseMat(mat::SparseMatrixCSC) = PDSparseMat(mat, cholesky(mat))
 PDSparseMat(fac::CholTypeSparse) = PDSparseMat(sparse(fac) |> x -> x*x', fac)
 
 ### Conversion

src/testutils.jl

@@ -222,7 +222,7 @@ end
 
 function pdtest_whiten(C::AbstractPDMat, Cmat::Matrix, verbose::Int)
     Y = chol_lower(Cmat)
-    Q = qr(convert(Array{eltype(C),2},randn(size(Cmat))))[1]
+    Q = qr(convert(Array{eltype(C),2},randn(size(Cmat)))).Q
     Y = Y * Q'                    # generate a matrix Y such that Y * Y' = C
     @test Y * Y' ≈ Cmat
     d = dim(C)

test/pdmtypes.jl

@@ -7,13 +7,13 @@ call_test_pdmat(p::AbstractPDMat,m::Matrix) = test_pdmat(p,m,cmat_eq=true,verbos
 for T in [Float64, Float32]
     #test that all external constructors are accessible
     m = Matrix{T}(I, 2, 2)
-    @test PDMat(m, cholfact(m)).mat == PDMat(Symmetric(m)).mat == PDMat(m).mat == PDMat(cholfact(m)).mat
+    @test PDMat(m, cholesky(m)).mat == PDMat(Symmetric(m)).mat == PDMat(m).mat == PDMat(cholesky(m)).mat
     d = ones(T,2)
     @test PDiagMat(d,d).inv_diag == PDiagMat(d).inv_diag
     x = one(T)
     @test ScalMat(2,x,x).inv_value == ScalMat(2,x).inv_value
     s = SparseMatrixCSC{T}(I, 2, 2)
-    @test PDSparseMat(s, cholfact(s)).mat == PDSparseMat(s).mat == PDSparseMat(cholfact(s)).mat
+    @test PDSparseMat(s, cholesky(s)).mat == PDSparseMat(s).mat == PDSparseMat(cholesky(s)).mat
 
     #test the functionality
     M = convert(Array{T,2}, [4. -2. -1.; -2. 5. -1.; -1. -1. 6.])