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extend sparse map[!]/broadcast[!] to structured matrices #19926

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Jan 11, 2017
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extend sparse map[!]/broadcast[!] to structured matrices #19926

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320ec0e
Extend sparse broadcast (non-!) to structured matrices by promoting s…
Sacha0 Jan 7, 2017
a630a2f
Test sparse broadcast (non-!) over combinations involving structured …
Sacha0 Jan 8, 2017
f997d6f
Extend sparse broadcast! to structured matrices by promoting structur…
Sacha0 Jan 8, 2017
d1dfa54
Test sparse broadcast! over combinations involving structured matrices.
Sacha0 Jan 8, 2017
3ea1d0c
Make tests for sparse broadcast over combinations including structure…
Sacha0 Jan 8, 2017
96ae43e
Extend sparse map[!] to structured matrices by promoting structured m…
Sacha0 Jan 9, 2017
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4 changes: 2 additions & 2 deletions base/broadcast.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -203,8 +203,8 @@ arguments to `f` unless it is also listed in the `As`,
as in `broadcast!(f, A, A, B)` to perform `A[:] = broadcast(f, A, B)`.
"""
@inline broadcast!{N}(f, C::AbstractArray, A, Bs::Vararg{Any,N}) =
broadcast_c!(f, containertype(C, A, Bs...), C, A, Bs...)
@inline function broadcast_c!{N}(f, ::Type, C::AbstractArray, A, Bs::Vararg{Any,N})
broadcast_c!(f, containertype(C), containertype(A, Bs...), C, A, Bs...)
@inline function broadcast_c!{N}(f, ::Type, ::Type, C, A, Bs::Vararg{Any,N})
shape = indices(C)
@boundscheck check_broadcast_indices(shape, A, Bs...)
keeps, Idefaults = map_newindexer(shape, A, Bs)
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54 changes: 52 additions & 2 deletions base/sparse/higherorderfns.jl
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Expand Up @@ -21,7 +21,9 @@ using ..SparseArrays: SparseVector, SparseMatrixCSC, AbstractSparseArray, indtyp
# (6) Define general _map_[not]zeropres! capable of handling >2 (input) sparse vectors/matrices.
# (7) Define _broadcast_[not]zeropres! specialized for a pair of (input) sparse vectors/matrices.
# (8) Define general _broadcast_[not]zeropres! capable of handling >2 (input) sparse vectors/matrices.
# (9) Define methods handling combinations of broadcast scalars and sparse vectors/matrices.
# (9) Define (broadcast[!]) methods handling combinations of broadcast scalars and sparse vectors/matrices.
# (10) Define (broadcast[!]) methods handling combinations of scalars, sparse vectors/matrices, and structured matrices.
# (11) Define (map[!]) methods handling combinations of sparse and structured matrices.


# (1) The definitions below provide a common interface to sparse vectors and matrices
Expand Down Expand Up @@ -853,7 +855,7 @@ promote_containertype(::Type{Tuple}, ::Type{AbstractSparseArray}) = Array
promote_containertype(::Type{AbstractSparseArray}, ::Type{Array}) = Array
promote_containertype(::Type{AbstractSparseArray}, ::Type{Tuple}) = Array

# broadcast[!] entry points for combinations of sparse arrays and other types
# broadcast[!] entry points for combinations of sparse arrays and other (scalar) types
@inline function broadcast_c{N}(f, ::Type{AbstractSparseArray}, mixedargs::Vararg{Any,N})
parevalf, passedargstup = capturescalars(f, mixedargs)
return broadcast(parevalf, passedargstup...)
Expand Down Expand Up @@ -888,4 +890,52 @@ end
broadcast{Tf,T}(f::Tf, ::Type{T}, A::SparseMatrixCSC) = broadcast(y -> f(T, y), A)
broadcast{Tf,T}(f::Tf, A::SparseMatrixCSC, ::Type{T}) = broadcast(x -> f(x, T), A)


# (10) broadcast[!] over combinations of scalars, sparse vectors/matrices, and structured matrices

# structured array container type promotion
immutable StructuredArray end
_containertype{T<:Diagonal}(::Type{T}) = StructuredArray
_containertype{T<:Bidiagonal}(::Type{T}) = StructuredArray
_containertype{T<:Tridiagonal}(::Type{T}) = StructuredArray
_containertype{T<:SymTridiagonal}(::Type{T}) = StructuredArray
promote_containertype(::Type{StructuredArray}, ::Type{StructuredArray}) = StructuredArray
# combinations involving sparse arrays continue in the structured array funnel
promote_containertype(::Type{StructuredArray}, ::Type{AbstractSparseArray}) = StructuredArray
promote_containertype(::Type{AbstractSparseArray}, ::Type{StructuredArray}) = StructuredArray
# combinations involving scalars continue in the structured array funnel
promote_containertype(::Type{StructuredArray}, ::Type{Any}) = StructuredArray
promote_containertype(::Type{Any}, ::Type{StructuredArray}) = StructuredArray
# combinations involving arrays divert to the generic array code
promote_containertype(::Type{StructuredArray}, ::Type{Array}) = Array
promote_containertype(::Type{Array}, ::Type{StructuredArray}) = Array
# combinations involving tuples divert to the generic array code
promote_containertype(::Type{StructuredArray}, ::Type{Tuple}) = Array
promote_containertype(::Type{Tuple}, ::Type{StructuredArray}) = Array

# for combinations involving sparse/structured arrays and scalars only,
# promote all structured arguments to sparse and then rebroadcast
@inline broadcast_c{N}(f, ::Type{StructuredArray}, As::Vararg{Any,N}) =
broadcast(f, map(_sparsifystructured, As)...)
@inline broadcast_c!{N}(f, ::Type{AbstractSparseArray}, ::Type{StructuredArray}, C, B, As::Vararg{Any,N}) =
broadcast!(f, C, _sparsifystructured(B), map(_sparsifystructured, As)...)
@inline broadcast_c!{N}(f, CT::Type, ::Type{StructuredArray}, C, B, As::Vararg{Any,N}) =
broadcast_c!(f, CT, Array, C, B, As...)
@inline _sparsifystructured(S::SymTridiagonal) = SparseMatrixCSC(S)
@inline _sparsifystructured(T::Tridiagonal) = SparseMatrixCSC(T)
@inline _sparsifystructured(B::Bidiagonal) = SparseMatrixCSC(B)
@inline _sparsifystructured(D::Diagonal) = SparseMatrixCSC(D)
@inline _sparsifystructured(A::AbstractSparseArray) = A
@inline _sparsifystructured(x) = x


# (11) map[!] over combinations of sparse and structured matrices
StructuredMatrix = Union{Diagonal,Bidiagonal,Tridiagonal,SymTridiagonal}
SparseOrStructuredMatrix = Union{SparseMatrixCSC,StructuredMatrix}
map{Tf}(f::Tf, A::StructuredMatrix) = _noshapecheck_map(f, _sparsifystructured(A))
map{Tf,N}(f::Tf, A::SparseOrStructuredMatrix, Bs::Vararg{SparseOrStructuredMatrix,N}) =
(_checksameshape(A, Bs...); _noshapecheck_map(f, _sparsifystructured(A), map(_sparsifystructured, Bs)...))
map!{Tf,N}(f::Tf, C::SparseMatrixCSC, A::SparseOrStructuredMatrix, Bs::Vararg{SparseOrStructuredMatrix,N}) =
(_checksameshape(C, A, Bs...); _noshapecheck_map!(f, C, _sparsifystructured(A), map(_sparsifystructured, Bs)...))

end
62 changes: 62 additions & 0 deletions test/sparse/higherorderfns.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -283,6 +283,68 @@ end
end
end

@testset "broadcast[!] over combinations of scalars, structured matrices, and sparse vectors/matrices" begin
N, p = 10, 0.4
s = rand()
V = sprand(N, p)
A = sprand(N, N, p)
Z = copy(A)
sparsearrays = (V, A)
fV, fA = map(Array, sparsearrays)
D = Diagonal(rand(N))
B = Bidiagonal(rand(N), rand(N - 1), true)
T = Tridiagonal(rand(N - 1), rand(N), rand(N - 1))
S = SymTridiagonal(rand(N), rand(N - 1))
structuredarrays = (D, B, T, S)
fstructuredarrays = map(Array, structuredarrays)
for (X, fX) in zip(structuredarrays, fstructuredarrays)
@test (Q = broadcast(sin, X); Q isa SparseMatrixCSC && Q == sparse(broadcast(sin, fX)))
@test broadcast!(sin, Z, X) == sparse(broadcast(sin, fX))
@test (Q = broadcast(cos, X); Q isa SparseMatrixCSC && Q == sparse(broadcast(cos, fX)))
@test broadcast!(cos, Z, X) == sparse(broadcast(cos, fX))
@test (Q = broadcast(*, s, X); Q isa SparseMatrixCSC && Q == sparse(broadcast(*, s, fX)))
@test broadcast!(*, Z, s, X) == sparse(broadcast(*, s, fX))
@test (Q = broadcast(+, V, A, X); Q isa SparseMatrixCSC && Q == sparse(broadcast(+, fV, fA, fX)))
@test broadcast!(+, Z, V, A, X) == sparse(broadcast(+, fV, fA, fX))
@test (Q = broadcast(*, s, V, A, X); Q isa SparseMatrixCSC && Q == sparse(broadcast(*, s, fV, fA, fX)))
@test broadcast!(*, Z, s, V, A, X) == sparse(broadcast(*, s, fV, fA, fX))
for (Y, fY) in zip(structuredarrays, fstructuredarrays)
@test (Q = broadcast(+, X, Y); Q isa SparseMatrixCSC && Q == sparse(broadcast(+, fX, fY)))
@test broadcast!(+, Z, X, Y) == sparse(broadcast(+, fX, fY))
@test (Q = broadcast(*, X, Y); Q isa SparseMatrixCSC && Q == sparse(broadcast(*, fX, fY)))
@test broadcast!(*, Z, X, Y) == sparse(broadcast(*, fX, fY))
end
end
end

@testset "map[!] over combinations of sparse and structured matrices" begin
N, p = 10, 0.4
A = sprand(N, N, p)
Z, fA = copy(A), Array(A)
D = Diagonal(rand(N))
B = Bidiagonal(rand(N), rand(N - 1), true)
T = Tridiagonal(rand(N - 1), rand(N), rand(N - 1))
S = SymTridiagonal(rand(N), rand(N - 1))
structuredarrays = (D, B, T, S)
fstructuredarrays = map(Array, structuredarrays)
for (X, fX) in zip(structuredarrays, fstructuredarrays)
@test (Q = map(sin, X); Q isa SparseMatrixCSC && Q == sparse(map(sin, fX)))
@test map!(sin, Z, X) == sparse(map(sin, fX))
@test (Q = map(cos, X); Q isa SparseMatrixCSC && Q == sparse(map(cos, fX)))
@test map!(cos, Z, X) == sparse(map(cos, fX))
@test (Q = map(+, A, X); Q isa SparseMatrixCSC && Q == sparse(map(+, fA, fX)))
@test map!(+, Z, A, X) == sparse(map(+, fA, fX))
for (Y, fY) in zip(structuredarrays, fstructuredarrays)
@test (Q = map(+, X, Y); Q isa SparseMatrixCSC && Q == sparse(map(+, fX, fY)))
@test map!(+, Z, X, Y) == sparse(map(+, fX, fY))
@test (Q = map(*, X, Y); Q isa SparseMatrixCSC && Q == sparse(map(*, fX, fY)))
@test map!(*, Z, X, Y) == sparse(map(*, fX, fY))
@test (Q = map(+, X, A, Y); Q isa SparseMatrixCSC && Q == sparse(map(+, fX, fA, fY)))
@test map!(+, Z, X, A, Y) == sparse(map(+, fX, fA, fY))
end
end
end

# Older tests of sparse broadcast, now largely covered by the tests above
@testset "assorted tests of sparse broadcast over two input arguments" begin
N, p = 10, 0.3
Expand Down