Merge 70442bc into a0f5016

Project.toml

@@ -1,6 +1,6 @@
 name = "LinearMaps"
 uuid = "7a12625a-238d-50fd-b39a-03d52299707e"
-version = "2.5.2"
+version = "2.6"
 
 [deps]
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"

src/LinearMaps.jl

@@ -48,15 +48,17 @@ Base.length(A::LinearMap) = size(A)[1] * size(A)[2]
 
 # check dimension consistency for y = A*x and Y = A*X
 function check_dim_mul(y::AbstractVector, A::LinearMap, x::AbstractVector)
-     m, n = size(A)
-     (m == length(y) && n == length(x)) || throw(DimensionMismatch("mul!"))
-     return nothing
- end
- function check_dim_mul(Y::AbstractMatrix, A::LinearMap, X::AbstractMatrix)
-     m, n = size(A)
-     (m == size(Y, 1) && n == size(X, 1) && size(Y, 2) == size(X, 2)) || throw(DimensionMismatch("mul!"))
-     return nothing
- end
+    # @info "checked vector dimensions" # uncomment for testing
+    m, n = size(A)
+    (m == length(y) && n == length(x)) || throw(DimensionMismatch("mul!"))
+    return nothing
+end
+function check_dim_mul(Y::AbstractMatrix, A::LinearMap, X::AbstractMatrix)
+    # @info "checked matrix dimensions" # uncomment for testing
+    m, n = size(A)
+    (m == size(Y, 1) && n == size(X, 1) && size(Y, 2) == size(X, 2)) || throw(DimensionMismatch("mul!"))
+    return nothing
+end
 
 # conversion of AbstractMatrix to LinearMap
 convert_to_lmaps_(A::AbstractMatrix) = LinearMap(A)
@@ -66,9 +68,12 @@ convert_to_lmaps(A) = (convert_to_lmaps_(A),)
 @inline convert_to_lmaps(A, B, Cs...) =
     (convert_to_lmaps_(A), convert_to_lmaps_(B), convert_to_lmaps(Cs...)...)
 
-Base.:(*)(A::LinearMap, x::AbstractVector) = mul!(similar(x, promote_type(eltype(A), eltype(x)), size(A, 1)), A, x)
+function Base.:(*)(A::LinearMap, x::AbstractVector)
+    size(A, 2) == length(x) || throw(DimensionMismatch("mul!"))
+    return @inbounds mul!(similar(x, promote_type(eltype(A), eltype(x)), size(A, 1)), A, x)
+end
 function LinearAlgebra.mul!(y::AbstractVector, A::LinearMap, x::AbstractVector, α::Number=true, β::Number=false)
-    length(y) == size(A, 1) || throw(DimensionMismatch("mul!"))
+    @boundscheck check_dim_mul(y, A, x)
     if isone(α)
         iszero(β) && (A_mul_B!(y, A, x); return y)
         isone(β) && (y .+= A * x; return y)
@@ -92,8 +97,8 @@ function LinearAlgebra.mul!(y::AbstractVector, A::LinearMap, x::AbstractVector,
     end
 end
 # the following is of interest in, e.g., subspace-iteration methods
-function LinearAlgebra.mul!(Y::AbstractMatrix, A::LinearMap, X::AbstractMatrix, α::Number=true, β::Number=false)
-    (size(Y, 1) == size(A, 1) && size(X, 1) == size(A, 2) && size(Y, 2) == size(X, 2)) || throw(DimensionMismatch("mul!"))
+Base.@propagate_inbounds function LinearAlgebra.mul!(Y::AbstractMatrix, A::LinearMap, X::AbstractMatrix, α::Number=true, β::Number=false)
+    @boundscheck check_dim_mul(Y, A, X)
     @inbounds @views for i = 1:size(X, 2)
         mul!(Y[:, i], A, X[:, i], α, β)
     end

src/blockmap.jl

@@ -1,14 +1,14 @@
-struct BlockMap{T,As<:Tuple{Vararg{LinearMap}},Rs<:Tuple{Vararg{Int}}} <: LinearMap{T}
+struct BlockMap{T,As<:Tuple{Vararg{LinearMap}},Rs<:Tuple{Vararg{Int}},Rranges<:Tuple{Vararg{UnitRange{Int}}},Cranges<:Tuple{Vararg{UnitRange{Int}}}} <: LinearMap{T}
     maps::As
     rows::Rs
-    rowranges::Vector{UnitRange{Int}}
-    colranges::Vector{UnitRange{Int}}
+    rowranges::Rranges
+    colranges::Cranges
     function BlockMap{T,R,S}(maps::R, rows::S) where {T, R<:Tuple{Vararg{LinearMap}}, S<:Tuple{Vararg{Int}}}
         for A in maps
             promote_type(T, eltype(A)) == T || throw(InexactError())
         end
         rowranges, colranges = rowcolranges(maps, rows)
-        return new{T,R,S}(maps, rows, rowranges, colranges)
+        return new{T,R,S,typeof(rowranges),typeof(colranges)}(maps, rows, rowranges, colranges)
     end
 end
 
@@ -28,28 +28,28 @@ Determines the range of rows for each block row and the range of columns for eac
 map in `maps`, according to its position in a virtual matrix representation of the
 block linear map obtained from `hvcat(rows, maps...)`.
 """
-function rowcolranges(maps, rows)::Tuple{Vector{UnitRange{Int}},Vector{UnitRange{Int}}}
-    rowranges = Vector{UnitRange{Int}}(undef, length(rows))
-    colranges = Vector{UnitRange{Int}}(undef, length(maps))
+function rowcolranges(maps, rows)
+    rowranges = ()
+    colranges = ()
     mapind = 0
     rowstart = 1
-    for rowind in 1:length(rows)
-        xinds = vcat(1, map(a -> size(a, 2), maps[mapind+1:mapind+rows[rowind]])...)
+    for row in rows
+        xinds = vcat(1, map(a -> size(a, 2), maps[mapind+1:mapind+row])...)
         cumsum!(xinds, xinds)
         mapind += 1
         rowend = rowstart + size(maps[mapind], 1) - 1
-        rowranges[rowind] = rowstart:rowend
-        colranges[mapind] = xinds[1]:xinds[2]-1
-        for colind in 2:rows[rowind]
+        rowranges = (rowranges..., rowstart:rowend)
+        colranges = (colranges..., xinds[1]:xinds[2]-1)
+        for colind in 2:row
             mapind +=1
-            colranges[mapind] = xinds[colind]:xinds[colind+1]-1
+            colranges = (colranges..., xinds[colind]:xinds[colind+1]-1)
         end
         rowstart = rowend + 1
     end
-    return rowranges, colranges
+    return rowranges::NTuple{length(rows), UnitRange{Int}}, colranges::NTuple{length(maps), UnitRange{Int}}
 end
 
-Base.size(A::BlockMap) = (last(A.rowranges[end]), last(A.colranges[end]))
+Base.size(A::BlockMap) = (last(last(A.rowranges)), last(last(A.colranges)))
 
 ############
 # concatenation
@@ -299,75 +299,82 @@ LinearAlgebra.transpose(A::BlockMap) = TransposeMap(A)
 LinearAlgebra.adjoint(A::BlockMap)  = AdjointMap(A)
 
 ############
-# multiplication with vectors
+# multiplication helper functions
 ############
 
-function A_mul_B!(y::AbstractVector, A::BlockMap, x::AbstractVector)
-    require_one_based_indexing(y, x)
-    m, n = size(A)
-    @boundscheck (m == length(y) && n == length(x)) || throw(DimensionMismatch("A_mul_B!"))
+@inline function _blockmul!(y, A::BlockMap, x, α, β)
     maps, rows, yinds, xinds = A.maps, A.rows, A.rowranges, A.colranges
     mapind = 0
-    @views @inbounds for rowind in 1:length(rows)
-        yrow = y[yinds[rowind]]
+    @views @inbounds for (row, yi) in zip(rows, yinds)
+        yrow = selectdim(y, 1, yi)
         mapind += 1
-        A_mul_B!(yrow, maps[mapind], x[xinds[mapind]])
-        for colind in 2:rows[rowind]
+        mul!(yrow, maps[mapind], selectdim(x, 1, xinds[mapind]), α, β)
+        for _ in 2:row
             mapind +=1
-            mul!(yrow, maps[mapind], x[xinds[mapind]], true, true)
+            mul!(yrow, maps[mapind], selectdim(x, 1, xinds[mapind]), α, true)
         end
     end
     return y
 end
 
-function At_mul_B!(y::AbstractVector, A::BlockMap, x::AbstractVector)
-    require_one_based_indexing(y, x)
-    m, n = size(A)
-    @boundscheck (n == length(y) && m == length(x)) || throw(DimensionMismatch("At_mul_B!"))
+@inline function _transblockmul!(y, A::BlockMap, x, α, β, transform)
     maps, rows, xinds, yinds = A.maps, A.rows, A.rowranges, A.colranges
-    mapind = 0
-    # first block row (rowind = 1) of A, meaning first block column of A', fill all of y
     @views @inbounds begin
-        xcol = x[xinds[1]]
-        for colind in 1:rows[1]
-            mapind +=1
-            A_mul_B!(y[yinds[mapind]], transpose(maps[mapind]), xcol)
+        # first block row (rowind = 1) of A, meaning first block column of A', fill all of y
+        xcol = selectdim(x, 1, first(xinds))
+        for rowind in 1:first(rows)
+            mul!(selectdim(y, 1, yinds[rowind]), transform(maps[rowind]), xcol, α, β)
         end
-        # subsequent block rows of A, add results to corresponding parts of y
-        for rowind in 2:length(rows)
-            xcol = x[xinds[rowind]]
-            for colind in 1:rows[rowind]
+        mapind = first(rows)
+        # subsequent block rows of A (block columns of A'),
+        # add results to corresponding parts of y
+        # TODO: think about multithreading
+        for (row, xi) in zip(Base.tail(rows), Base.tail(xinds))
+            xcol = selectdim(x, 1, xi)
+            for _ in 1:row
                 mapind +=1
-                mul!(y[yinds[mapind]], transpose(maps[mapind]), xcol, true, true)
+                mul!(selectdim(y, 1, yinds[mapind]), transform(maps[mapind]), xcol, α, true)
             end
         end
     end
     return y
 end
 
-function Ac_mul_B!(y::AbstractVector, A::BlockMap, x::AbstractVector)
-    require_one_based_indexing(y, x)
-    m, n = size(A)
-    @boundscheck (n == length(y) && m == length(x)) || throw(DimensionMismatch("At_mul_B!"))
-    maps, rows, xinds, yinds = A.maps, A.rows, A.rowranges, A.colranges
-    mapind = 0
-    # first block row (rowind = 1) of A, fill all of y
-    @views @inbounds begin
-        xcol = x[xinds[1]]
-        for colind in 1:rows[1]
-            mapind +=1
-            A_mul_B!(y[yinds[mapind]], adjoint(maps[mapind]), xcol)
-        end
-        # subsequent block rows of A, add results to corresponding parts of y
-        for rowind in 2:length(rows)
-            xcol = x[xinds[rowind]]
-            for colind in 1:rows[rowind]
-                mapind +=1
-                mul!(y[yinds[mapind]], adjoint(maps[mapind]), xcol, true, true)
-            end
+############
+# multiplication with vectors & matrices
+############
+
+Base.@propagate_inbounds A_mul_B!(y::AbstractVector, A::BlockMap, x::AbstractVector) =
+    mul!(y, A, x)
+
+Base.@propagate_inbounds A_mul_B!(y::AbstractVector, A::TransposeMap{<:Any,<:BlockMap}, x::AbstractVector) =
+    mul!(y, A, x)
+
+Base.@propagate_inbounds At_mul_B!(y::AbstractVector, A::BlockMap, x::AbstractVector) =
+    mul!(y, transpose(A), x)
+
+Base.@propagate_inbounds A_mul_B!(y::AbstractVector, A::AdjointMap{<:Any,<:BlockMap}, x::AbstractVector) =
+    mul!(y, A, x)
+
+Base.@propagate_inbounds Ac_mul_B!(y::AbstractVector, A::BlockMap, x::AbstractVector) =
+    mul!(y, adjoint(A), x)
+
+for Atype in (AbstractVector, AbstractMatrix)
+    @eval Base.@propagate_inbounds function LinearAlgebra.mul!(y::$Atype, A::BlockMap, x::$Atype,
+                        α::Number=true, β::Number=false)
+        require_one_based_indexing(y, x)
+        @boundscheck check_dim_mul(y, A, x)
+        return _blockmul!(y, A, x, α, β)
+    end
+
+    for (maptype, transform) in ((:(TransposeMap{<:Any,<:BlockMap}), :transpose), (:(AdjointMap{<:Any,<:BlockMap}), :adjoint))
+        @eval Base.@propagate_inbounds function LinearAlgebra.mul!(y::$Atype, wrapA::$maptype, x::$Atype,
+                        α::Number=true, β::Number=false)
+            require_one_based_indexing(y, x)
+            @boundscheck check_dim_mul(y, wrapA, x)
+            return _transblockmul!(y, wrapA.lmap, x, α, β, $transform)
         end
     end
-    return y
 end
 
 ############
@@ -388,3 +395,91 @@ end
 #     show(io, T)
 #     print(io, '}')
 # end
+
+############
+# BlockDiagonalMap
+############
+
+struct BlockDiagonalMap{T,As<:Tuple{Vararg{LinearMap}},Ranges<:Tuple{Vararg{UnitRange{Int}}}} <: LinearMap{T}
+    maps::As
+    rowranges::Ranges
+    colranges::Ranges
+    function BlockDiagonalMap{T,As}(maps::As) where {T, As<:Tuple{Vararg{LinearMap}}}
+        for A in maps
+            promote_type(T, eltype(A)) == T || throw(InexactError())
+        end
+        # row ranges
+        inds = vcat(1, size.(maps, 1)...)
+        cumsum!(inds, inds)
+        rowranges = ntuple(i -> inds[i]:inds[i+1]-1, Val(length(maps)))
+        # column ranges
+        inds[2:end] .= size.(maps, 2)
+        cumsum!(inds, inds)
+        colranges = ntuple(i -> inds[i]:inds[i+1]-1, Val(length(maps)))
+        return new{T,As,typeof(rowranges)}(maps, rowranges, colranges)
+    end
+end
+
+BlockDiagonalMap{T}(maps::As) where {T,As<:Tuple{Vararg{LinearMap}}} =
+    BlockDiagonalMap{T,As}(maps)
+BlockDiagonalMap(maps::LinearMap...) =
+    BlockDiagonalMap{promote_type(map(eltype, maps)...)}(maps)
+
+for k in 1:8 # is 8 sufficient?
+    Is = ntuple(n->:($(Symbol(:A,n))::AbstractMatrix), Val(k-1))
+    # yields (:A1, :A2, :A3, ..., :A(k-1))
+    L = :($(Symbol(:A,k))::LinearMap)
+    # yields :Ak
+    mapargs = ntuple(n -> :(LinearMap($(Symbol(:A,n)))), Val(k-1))
+    # yields (:LinearMap(A1), :LinearMap(A2), ..., :LinearMap(A(k-1)))
+
+    @eval begin
+        SparseArrays.blockdiag($(Is...), $L, As::Union{LinearMap,AbstractMatrix}...) =
+            BlockDiagonalMap($(mapargs...), $(Symbol(:A,k)), convert_to_lmaps(As...)...)
+        function Base.cat($(Is...), $L, As::Union{LinearMap,AbstractMatrix}...; dims::Dims{2})
+            if dims == (1,2)
+                return BlockDiagonalMap($(mapargs...), $(Symbol(:A,k)), convert_to_lmaps(As...)...)
+            else
+                throw(ArgumentError("dims keyword in cat of LinearMaps must be (1,2)"))
+            end
+        end
+    end
+end
+
+Base.size(A::BlockDiagonalMap) = (last(A.rowranges[end]), last(A.colranges[end]))
+
+LinearAlgebra.issymmetric(A::BlockDiagonalMap) = all(issymmetric, A.maps)
+LinearAlgebra.ishermitian(A::BlockDiagonalMap{<:Real}) = all(issymmetric, A.maps)
+LinearAlgebra.ishermitian(A::BlockDiagonalMap) = all(ishermitian, A.maps)
+
+LinearAlgebra.adjoint(A::BlockDiagonalMap{T}) where {T} = BlockDiagonalMap{T}(map(adjoint, A.maps))
+LinearAlgebra.transpose(A::BlockDiagonalMap{T}) where {T} = BlockDiagonalMap{T}(map(transpose, A.maps))
+
+Base.:(==)(A::BlockDiagonalMap, B::BlockDiagonalMap) = (eltype(A) == eltype(B) && A.maps == B.maps)
+
+Base.@propagate_inbounds A_mul_B!(y::AbstractVector, A::BlockDiagonalMap, x::AbstractVector) =
+    mul!(y, A, x, true, false)
+
+Base.@propagate_inbounds At_mul_B!(y::AbstractVector, A::BlockDiagonalMap, x::AbstractVector) =
+    mul!(y, transpose(A), x, true, false)
+
+Base.@propagate_inbounds Ac_mul_B!(y::AbstractVector, A::BlockDiagonalMap, x::AbstractVector) =
+    mul!(y, adjoint(A), x, true, false)
+
+for Atype in (AbstractVector, AbstractMatrix)
+    @eval Base.@propagate_inbounds function LinearAlgebra.mul!(y::$Atype, A::BlockDiagonalMap, x::$Atype,
+                        α::Number=true, β::Number=false)
+        require_one_based_indexing(y, x)
+        @boundscheck check_dim_mul(y, A, x)
+        return _blockscaling!(y, A, x, α, β)
+    end
+end
+
+@inline function _blockscaling!(y, A::BlockDiagonalMap, x, α, β)
+    maps, yinds, xinds = A.maps, A.rowranges, A.colranges
+    # TODO: think about multi-threading here
+    @views @inbounds for i in eachindex(yinds, maps, xinds)
+        mul!(selectdim(y, 1, yinds[i]), maps[i], selectdim(x, 1, xinds[i]), α, β)
+    end
+    return y
+end

src/wrappedmap.jl

@@ -30,28 +30,13 @@ Base.:(==)(A::MatrixMap, B::MatrixMap) =
     (eltype(A)==eltype(B) && A.lmap==B.lmap && A._issymmetric==B._issymmetric &&
      A._ishermitian==B._ishermitian && A._isposdef==B._isposdef)
 
-if VERSION ≥ v"1.3.0-alpha.115"
-
-LinearAlgebra.mul!(y::AbstractVector, A::WrappedMap, x::AbstractVector, α::Number=true, β::Number=false) =
-    mul!(y, A.lmap, x, α, β)
-
-LinearAlgebra.mul!(Y::AbstractMatrix, A::MatrixMap, X::AbstractMatrix, α::Number=true, β::Number=false) =
-    mul!(Y, A.lmap, X, α, β)
-
-else
-
-LinearAlgebra.mul!(Y::AbstractMatrix, A::MatrixMap, X::AbstractMatrix) =
-    mul!(Y, A.lmap, X)
-
-end # VERSION
-
 # properties
 Base.size(A::WrappedMap) = size(A.lmap)
 LinearAlgebra.issymmetric(A::WrappedMap) = A._issymmetric
 LinearAlgebra.ishermitian(A::WrappedMap) = A._ishermitian
 LinearAlgebra.isposdef(A::WrappedMap) = A._isposdef
 
-# multiplication with vector
+# multiplication with vectors & matrices
 A_mul_B!(y::AbstractVector, A::WrappedMap, x::AbstractVector) = A_mul_B!(y, A.lmap, x)
 Base.:(*)(A::WrappedMap, x::AbstractVector) = *(A.lmap, x)
 
@@ -61,6 +46,23 @@ At_mul_B!(y::AbstractVector, A::WrappedMap, x::AbstractVector) =
 Ac_mul_B!(y::AbstractVector, A::WrappedMap, x::AbstractVector) =
     ishermitian(A) ? A_mul_B!(y, A.lmap, x) : Ac_mul_B!(y, A.lmap, x)
 
+if VERSION ≥ v"1.3.0-alpha.115"
+    for Atype in (AbstractVector, AbstractMatrix)
+        @eval Base.@propagate_inbounds LinearAlgebra.mul!(y::$Atype, A::WrappedMap, x::$Atype,
+                        α::Number=true, β::Number=false) =
+            mul!(y, A.lmap, x, α, β)
+    end
+else
+# This is somewhat suboptimal, because the absence of 5-arg mul! for MatrixMaps
+# doesn't allow to define a 5-arg mul! for WrappedMaps which do have a 5-arg mul!
+# I'd assume, however, that 5-arg mul! becomes standard in Julia v≥1.3 anyway
+# the idea is to let the fallback handle 5-arg calls
+    for Atype in (AbstractVector, AbstractMatrix)
+        @eval Base.@propagate_inbounds LinearAlgebra.mul!(Y::$Atype, A::WrappedMap, X::$Atype) =
+            mul!(Y, A.lmap, X)
+    end
+end # VERSION
+
 # combine LinearMap and Matrix objects: linear combinations and map composition
 Base.:(+)(A₁::LinearMap, A₂::AbstractMatrix) = +(A₁, WrappedMap(A₂))
 Base.:(+)(A₁::AbstractMatrix, A₂::LinearMap) = +(WrappedMap(A₁), A₂)