Fix multiplication of AbstractQs (#46237)

JuliaLang · Aug 22, 2022 · 947c908 · 947c908 · nanosoldier · Aug 22, 2022
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diff --git a/stdlib/LinearAlgebra/src/qr.jl b/stdlib/LinearAlgebra/src/qr.jl
@@ -380,9 +380,9 @@ norm solution.
 
 Multiplication with respect to either full/square or non-full/square `Q` is allowed, i.e. both `F.Q*F.R`
 and `F.Q*A` are supported. A `Q` matrix can be converted into a regular matrix with
-[`Matrix`](@ref).  This operation returns the "thin" Q factor, i.e., if `A` is `m`×`n` with `m>=n`, then
+[`Matrix`](@ref). This operation returns the "thin" Q factor, i.e., if `A` is `m`×`n` with `m>=n`, then
 `Matrix(F.Q)` yields an `m`×`n` matrix with orthonormal columns.  To retrieve the "full" Q factor, an
-`m`×`m` orthogonal matrix, use `F.Q*Matrix(I,m,m)`.  If `m<=n`, then `Matrix(F.Q)` yields an `m`×`m`
+`m`×`m` orthogonal matrix, use `F.Q*I`. If `m<=n`, then `Matrix(F.Q)` yields an `m`×`m`
 orthogonal matrix.
 
 The block size for QR decomposition can be specified by keyword argument

diff --git a/stdlib/LinearAlgebra/src/special.jl b/stdlib/LinearAlgebra/src/special.jl
@@ -347,10 +347,10 @@ end
 *(A::Diagonal, Q::AbstractQ) = _qrmul(A, Q)
 *(A::Diagonal, Q::Adjoint{<:Any,<:AbstractQ}) = _qrmul(A, Q)
 
-*(Q::AbstractQ, B::AbstractQ) = _qlmul(Q, B)
-*(Q::Adjoint{<:Any,<:AbstractQ}, B::AbstractQ) = _qrmul(Q, B)
-*(Q::AbstractQ, B::Adjoint{<:Any,<:AbstractQ}) = _qlmul(Q, B)
-*(Q::Adjoint{<:Any,<:AbstractQ}, B::Adjoint{<:Any,<:AbstractQ}) = _qrmul(Q, B)
+*(Q::AbstractQ, B::AbstractQ) = Q * (B * I)
+*(Q::Adjoint{<:Any,<:AbstractQ}, B::AbstractQ) = Q * (B * I)
+*(Q::AbstractQ, B::Adjoint{<:Any,<:AbstractQ}) = Q * (B * I)
+*(Q::Adjoint{<:Any,<:AbstractQ}, B::Adjoint{<:Any,<:AbstractQ}) = Q * (B * I)
 
 # fill[stored]! methods
 fillstored!(A::Diagonal, x) = (fill!(A.diag, x); A)

diff --git a/stdlib/LinearAlgebra/test/special.jl b/stdlib/LinearAlgebra/test/special.jl
@@ -215,16 +215,29 @@ end
         atri = typ(a)
         matri = Matrix(atri)
         b = rand(n,n)
-        qrb = qr(b, ColumnNorm())
-        @test atri * qrb.Q ≈ matri * qrb.Q ≈ rmul!(copy(atri), qrb.Q)
-        @test atri * qrb.Q' ≈ matri * qrb.Q' ≈ rmul!(copy(atri), qrb.Q')
-        @test qrb.Q * atri ≈ qrb.Q * matri ≈ lmul!(qrb.Q, copy(atri))
-        @test qrb.Q' * atri ≈ qrb.Q' * matri ≈ lmul!(qrb.Q', copy(atri))
-        qrb = qr(b, NoPivot())
-        @test atri * qrb.Q ≈ matri * qrb.Q ≈ rmul!(copy(atri), qrb.Q)
-        @test atri * qrb.Q' ≈ matri * qrb.Q' ≈ rmul!(copy(atri), qrb.Q')
-        @test qrb.Q * atri ≈ qrb.Q * matri ≈ lmul!(qrb.Q, copy(atri))
-        @test qrb.Q' * atri ≈ qrb.Q' * matri ≈ lmul!(qrb.Q', copy(atri))
+        for pivot in (ColumnNorm(), NoPivot())
+            qrb = qr(b, pivot)
+            @test atri * qrb.Q ≈ matri * qrb.Q ≈ rmul!(copy(atri), qrb.Q)
+            @test atri * qrb.Q' ≈ matri * qrb.Q' ≈ rmul!(copy(atri), qrb.Q')
+            @test qrb.Q * atri ≈ qrb.Q * matri ≈ lmul!(qrb.Q, copy(atri))
+            @test qrb.Q' * atri ≈ qrb.Q' * matri ≈ lmul!(qrb.Q', copy(atri))
+        end
+    end
+end
+
+@testset "Multiplication of Qs" begin
+    for pivot in (ColumnNorm(), NoPivot()), A in (rand(5, 3), rand(5, 5), rand(3, 5))
+        Q = qr(A, pivot).Q
+        m = size(A, 1)
+        C = Matrix{Float64}(undef, (m, m))
+        @test Q*Q ≈ (Q*I) * (Q*I) ≈ mul!(C, Q, Q)
+        @test size(Q*Q) == (m, m)
+        @test Q'Q ≈ (Q'*I) * (Q*I) ≈ mul!(C, Q', Q)
+        @test size(Q'Q) == (m, m)
+        @test Q*Q' ≈ (Q*I) * (Q'*I) ≈ mul!(C, Q, Q')
+        @test size(Q*Q') == (m, m)
+        @test Q'Q' ≈ (Q'*I) * (Q'*I) ≈ mul!(C, Q', Q')
+        @test size(Q'Q') == (m, m)
     end
 end