fix tests

Author: dlfivefifty

src/infqr.jl

@@ -158,9 +158,10 @@ end
 qr_layout(::BandedLayouts, ::NTuple{2,OneToInf{Int}}, A) = adaptiveqr(A)
 qr_layout(::AbstractBandedLayout, ::NTuple{2,OneToInf{Int}}, A) = adaptiveqr(A)
 qr_layout(::AbstractAlmostBandedLayout, ::NTuple{2,OneToInf{Int}}, A) = adaptiveqr(A)
-__qr_layout(_, ::NTuple{2,InfiniteCardinal{0}}, A) = adaptiveqr(A)
+_qr_layout(_, ::NTuple{2,InfiniteCardinal{0}}, A) = adaptiveqr(A)
 qr_layout(::AbstractBlockBandedLayout, ::NTuple{2,InfiniteCardinal{0}}, A) = adaptiveqr(A)
 factorize_layout(::BandedLayouts, ::NTuple{2,OneToInf{Int}}, A) = qr(A)
+factorize_layout(::AbstractBandedLayout, ::NTuple{2,OneToInf{Int}}, A) = qr(A)
 
 
 cache_layout(::TriangularLayout{UPLO, UNIT, <:AdaptiveLayout}, A::AbstractMatrix) where {UPLO, UNIT} = A # already cached

test/test_bidiagonalconjugation.jl

@@ -120,19 +120,19 @@ end
              (_BandedMatrix(Vcat(
              (-(0:∞) ./ (2:2:∞))',
              ((2:∞) ./ (2:2:∞))'), ℵ₀, 0,1),
-             LazyBandedMatrices.Tridiagonal((2:∞) ./ (3:2:∞), -1 ./ ((1:2:∞) .* (3:2:∞)), (1:∞) ./ (3:2:∞)))
+             LazyBandedMatrices.Tridiagonal((2:∞) ./ (3:2:∞), -1 ./ ((1:2:∞) .* (3:2:∞)), (1:∞) ./ (3:2:∞))),
             # P -> C^(5/2)
             (_BandedMatrix(Vcat((-3 ./ (3:2:∞))', Zeros(1,∞), (3 ./ (3:2:∞))'), ℵ₀, 0,2) *
             _BandedMatrix(Vcat((-1 ./ (1:2:∞))', Zeros(1,∞), (1 ./ (1:2:∞))'), ℵ₀, 0,2),
             LazyBandedMatrices.Tridiagonal((1:∞) ./ (1:2:∞), Zeros(∞), (1:∞) ./ (3:2:∞)))
             )
         n = 1000
-        @time U = V = R[1:n,1:n]
-        @time X = Tridiagonal(Vector(X_T.dl[1:n-1]), Vector(X_T.d[1:n]), Vector(X_T.du[1:n-1]))
-        @time UX = InfiniteLinearAlgebra.upper_mul_tri_triview(U, X)
+        U = V = R[1:n,1:n]
+        X = Tridiagonal(Vector(X_T.dl[1:n-1]), Vector(X_T.d[1:n]), Vector(X_T.du[1:n-1]))
+        UX = InfiniteLinearAlgebra.upper_mul_tri_triview(U, X)
         @test Tridiagonal(U*X) ≈  UX
         # U*X*inv(U) only depends on Tridiagonal(U*X)
-        @time Y = InfiniteLinearAlgebra.tri_mul_invupper_triview(UX, U)
+        Y = InfiniteLinearAlgebra.tri_mul_invupper_triview(UX, U)
         @test Tridiagonal(U*X / U) ≈ Tridiagonal(UX / U) ≈ Y
 
         data = TridiagonalConjugationData(R, X_T)
@@ -162,8 +162,8 @@ end
         X_T = LazyBandedMatrices.Tridiagonal(Vcat(1/sqrt(2), Fill(1/2,∞)), Zeros(∞), Vcat(1/sqrt(2), Fill(1/2,∞)))
         data = TridiagonalConjugationData(R, X_T);
         n = 1000
-        @time U = V = R[1:n,1:n];
-        @time X = Tridiagonal(Vector(X_T.dl[1:n-1]), Vector(X_T.d[1:n]), Vector(X_T.du[1:n-1]));
+        U = V = R[1:n,1:n];
+        X = Tridiagonal(Vector(X_T.dl[1:n-1]), Vector(X_T.d[1:n]), Vector(X_T.du[1:n-1]));
         UX = Tridiagonal(U*X)
         Y = Tridiagonal(UX / U)
         @test data.UX[1,:] ≈ UX[1,1:100]