updates

Author: dlfivefifty

src/InfiniteLinearAlgebra.jl

@@ -11,7 +11,7 @@ import FillArrays: AbstractFill
 import BandedMatrices: BandedMatrix, _BandedMatrix, bandeddata, bandwidths
 import LinearAlgebra: lmul!,  ldiv!, matprod, qr, AbstractTriangular, AbstractQ, adjoint, transpose
 import LazyArrays: CachedArray, DenseColumnMajor, FillLayout, ApplyMatrix, check_mul_axes, ApplyStyle, LazyArrayApplyStyle, LazyArrayStyle,
-                    CachedMatrix, CachedArray, resizedata!, MemoryLayout
+                    CachedMatrix, CachedArray, resizedata!, MemoryLayout, mulapplystyle
 import MatrixFactorizations: ql, ql!, QLPackedQ, getL, getR, reflector!, reflectorApply!, QL, QR, QRPackedQ
 
 import BlockArrays: BlockSizes, cumulsizes, _find_block, AbstractBlockVecOrMat, sizes_from_blocks
@@ -22,9 +22,7 @@ import BlockBandedMatrices: _BlockSkylineMatrix, _BandedMatrix, AbstractBlockSiz
         BlockSkylineSizes, BlockSkylineMatrix, BlockBandedMatrix, _BlockBandedMatrix, BlockTridiagonal
 
 
-# Fix ∞ BandedMatrix
-# ApplyStyle(::typeof(*), ::Type{<:BandedMatrix{<:Any,<:Any,<:OneToInf}}, _::Type{<:AbstractArray}...) =
-#     LazyArrayApplyStyle()
+
 
 # BroadcastStyle(::Type{<:BandedMatrix{<:Any,<:Any,<:OneToInf}}) = LazyArrayStyle{2}()
 
@@ -57,4 +55,13 @@ include("banded/infqltoeplitz.jl")
 include("infql.jl")
 include("infqr.jl")
 
+###
+# temporary work arounds
+###
+
+# Fix ∞ BandedMatrix
+ApplyStyle(::typeof(*), ::Type{<:BandedMatrix{<:Any,<:AbstractFill,<:OneToInf}}...) =
+    LazyArrayApplyStyle()
+
+
 end # module

src/banded/hessenbergq.jl

@@ -130,6 +130,8 @@ getindex(Q::LowerHessenbergQ, i::Integer, j::Integer) = (Q')[j,i]'
 # QLPackedQ, QRPackedQ <-> Lower/UpperHessenbergQ
 ###
 
+UpperHessenbergQ(Q::LinearAlgebra.QRPackedQ) = UpperHessenbergQ(QRPackedQ(Q))
+
 function UpperHessenbergQ(Q::QRPackedQ{T}) where T
     @assert bandwidth(Q.factors,1) == 1
     q = Vector{Matrix{T}}()

test/runtests.jl

@@ -6,55 +6,62 @@ import BlockArrays: _BlockArray
 import BlockBandedMatrices: isblockbanded, _BlockBandedMatrix
 import MatrixFactorizations: QLPackedQ
 import BandedMatrices: bandeddata, _BandedMatrix
+import LazyArrays: colsupport
 
 @testset "Algebra" begin 
-    A = BlockTridiagonal(Vcat([fill(1.0,2,1),Matrix(1.0I,2,2),Matrix(1.0I,2,2),Matrix(1.0I,2,2)],Fill(Matrix(1.0I,2,2), ∞)), 
-                        Vcat([zeros(1,1)], Fill(zeros(2,2), ∞)), 
-                        Vcat([fill(1.0,1,2),Matrix(1.0I,2,2)], Fill(Matrix(1.0I,2,2), ∞)))
-                        
-    @test A isa InfiniteLinearAlgebra.BlockTriPertToeplitz                       
-    @test isblockbanded(A)
+    @testset "BlockTridiagonal" begin
+        A = BlockTridiagonal(Vcat([fill(1.0,2,1),Matrix(1.0I,2,2),Matrix(1.0I,2,2),Matrix(1.0I,2,2)],Fill(Matrix(1.0I,2,2), ∞)), 
+                            Vcat([zeros(1,1)], Fill(zeros(2,2), ∞)), 
+                            Vcat([fill(1.0,1,2),Matrix(1.0I,2,2)], Fill(Matrix(1.0I,2,2), ∞)))
+                            
+        @test A isa InfiniteLinearAlgebra.BlockTriPertToeplitz                       
+        @test isblockbanded(A)
 
-    @test A[Block.(1:2),Block(1)] == A[1:3,1:1] == reshape([0.,1.,1.],3,1)
+        @test A[Block.(1:2),Block(1)] == A[1:3,1:1] == reshape([0.,1.,1.],3,1)
 
-    @test BlockBandedMatrix(A)[1:100,1:100] == BlockBandedMatrix(A,(2,1))[1:100,1:100] == BlockBandedMatrix(A,(1,1))[1:100,1:100] == A[1:100,1:100]
+        @test BlockBandedMatrix(A)[1:100,1:100] == BlockBandedMatrix(A,(2,1))[1:100,1:100] == BlockBandedMatrix(A,(1,1))[1:100,1:100] == A[1:100,1:100]
 
-    @test (A - I)[1:100,1:100] == A[1:100,1:100]-I
-    @test (A + I)[1:100,1:100] == A[1:100,1:100]+I
-    @test (I + A)[1:100,1:100] == I+A[1:100,1:100]
-    @test (I - A)[1:100,1:100] == I-A[1:100,1:100]
-
-    A = BandedMatrix(-3 => Fill(7/10,∞), -2 => Fill(1,∞), 1 => Fill(2im,∞))
-    Ac = BandedMatrix(A')
-    At = BandedMatrix(transpose(A))
-    @test Ac[1:10,1:10] ≈ (A')[1:10,1:10] ≈ A[1:10,1:10]'
-    @test At[1:10,1:10] ≈ transpose(A)[1:10,1:10] ≈ transpose(A[1:10,1:10])
+        @test (A - I)[1:100,1:100] == A[1:100,1:100]-I
+        @test (A + I)[1:100,1:100] == A[1:100,1:100]+I
+        @test (I + A)[1:100,1:100] == I+A[1:100,1:100]
+        @test (I - A)[1:100,1:100] == I-A[1:100,1:100]
+    end
+    @testset "BandedMatrix" begin
+        A = BandedMatrix(-3 => Fill(7/10,∞), -2 => Fill(1,∞), 1 => Fill(2im,∞))
+        Ac = BandedMatrix(A')
+        At = BandedMatrix(transpose(A))
+        @test Ac[1:10,1:10] ≈ (A')[1:10,1:10] ≈ A[1:10,1:10]'
+        @test At[1:10,1:10] ≈ transpose(A)[1:10,1:10] ≈ transpose(A[1:10,1:10])
 
-    A = BandedMatrix(-1 => Vcat(Float64[], Fill(1/4,∞)), 0 => Vcat([1.0+im],Fill(0,∞)), 1 => Vcat(Float64[], Fill(1,∞)))
-    Ac = BandedMatrix(A')
-    At = BandedMatrix(transpose(A))
-    @test Ac[1:10,1:10] ≈ (A')[1:10,1:10] ≈ A[1:10,1:10]'
-    @test At[1:10,1:10] ≈ transpose(A)[1:10,1:10] ≈ transpose(A[1:10,1:10])
+        A = BandedMatrix(-1 => Vcat(Float64[], Fill(1/4,∞)), 0 => Vcat([1.0+im],Fill(0,∞)), 1 => Vcat(Float64[], Fill(1,∞)))
+        Ac = BandedMatrix(A')
+        At = BandedMatrix(transpose(A))
+        @test Ac[1:10,1:10] ≈ (A')[1:10,1:10] ≈ A[1:10,1:10]'
+        @test At[1:10,1:10] ≈ transpose(A)[1:10,1:10] ≈ transpose(A[1:10,1:10])
 
-    A = BandedMatrix(-2 => Vcat(Float64[], Fill(1/4,∞)), 0 => Vcat([1.0+im,2,3],Fill(0,∞)), 1 => Vcat(Float64[], Fill(1,∞)))
-    Ac = BandedMatrix(A')
-    At = BandedMatrix(transpose(A))
-    @test Ac[1:10,1:10] ≈ (A')[1:10,1:10] ≈ A[1:10,1:10]'
-    @test At[1:10,1:10] ≈ transpose(A)[1:10,1:10] ≈ transpose(A[1:10,1:10])
+        A = BandedMatrix(-2 => Vcat(Float64[], Fill(1/4,∞)), 0 => Vcat([1.0+im,2,3],Fill(0,∞)), 1 => Vcat(Float64[], Fill(1,∞)))
+        Ac = BandedMatrix(A')
+        At = BandedMatrix(transpose(A))
+        @test Ac[1:10,1:10] ≈ (A')[1:10,1:10] ≈ A[1:10,1:10]'
+        @test At[1:10,1:10] ≈ transpose(A)[1:10,1:10] ≈ transpose(A[1:10,1:10])
 
-    A = _BandedMatrix(Fill(1,4,∞),∞,1,2)
-    @test A*A isa ApplyArray
-    @test (A^2)[1:10,1:10] == (A*A)[1:10,1:10] == (A[1:100,1:100]^2)[1:10,1:10]
-    @test (A^3)[1:10,1:10] == (A*A*A)[1:10,1:10] == (A[1:100,1:100]^3)[1:10,1:10]
+        A = _BandedMatrix(Fill(1,4,∞),∞,1,2)
+        @test A*A isa ApplyArray
+        @test (A^2)[1:10,1:10] == (A*A)[1:10,1:10] == (A[1:100,1:100]^2)[1:10,1:10]
+        @test (A^3)[1:10,1:10] == (A*A*A)[1:10,1:10] == (A[1:100,1:100]^3)[1:10,1:10]
+    end
 
-    @testset "Diagonal" begin
+    @testset "Fill" begin
         A = _BandedMatrix(Ones(1,∞),∞,-1,1)
         @test 1.0 .* A isa BandedMatrix{Float64,<:Fill}
         @test_skip Ones(∞) .* A
         @test 2.0 .* A isa BandedMatrix{Float64,<:Fill}
         @test A .* 2.0 isa BandedMatrix{Float64,<:Fill}
         @test Eye(∞)*A isa BandedMatrix{Float64,<:Fill}
         @test A*Eye(∞) isa BandedMatrix{Float64,<:Fill}
+    end
+
+    @testset "Banded Broadast" begin
         A = _BandedMatrix((1:∞)',∞,-1,1)
         @test 2.0 .* A isa BandedMatrix{Float64,<:Adjoint}
         @test A .* 2.0 isa BandedMatrix{Float64,<:Adjoint}
@@ -65,10 +72,17 @@ import BandedMatrices: bandeddata, _BandedMatrix
         @test A .* 2.0 isa BandedMatrix
         @test Eye(∞) * A isa BandedMatrix
         @test A * Eye(∞) isa BandedMatrix
+        b = 1:∞
+        @test bandwidths(b .* A) == (0,1)
+        @test Base.replace_in_print_matrix(b.*A, 2,1,"0.0") == " ⋅ "
+        @test bandwidths(A .* b) == (0,1)
+        @test A .* b' isa BroadcastArray
+        @test bandwidths(A .* b') == bandwidths(A .* b')
+        @test colsupport(A .* b', 3) == 2:3
     end
-
+    
     @testset "Triangle OP recurrences" begin
-        mortar((n -> 1:n).(1:∞))
+        # mortar((n -> 1:n).(1:∞))
     end
     # Multivariate OPs Corollary (3)
     # n = 5