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Fix array return type #70

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merged 2 commits into from
Jun 9, 2022
Merged

Fix array return type #70

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ce59e8f
fix array return type
GiggleLiu Jun 8, 2022
1774afd
merge
GiggleLiu Jun 8, 2022
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2 changes: 1 addition & 1 deletion Project.toml
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Expand Up @@ -11,7 +11,7 @@ SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"

[compat]
StaticArrays = "0.11, 0.12, 1.0"
StaticArrays = "1"
julia = "1"

[extras]
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5 changes: 4 additions & 1 deletion src/IMatrix.jl
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Expand Up @@ -15,6 +15,9 @@ size(A::IMatrix{N}, i::Int) where {N} = N
size(A::IMatrix{N}) where {N} = (N, N)
getindex(A::IMatrix{N,T}, i::Integer, j::Integer) where {N,T} = T(i == j)

Base.:(==)(d1::IMatrix{Na}, d2::IMatrix{Nb}) where {Na,Nb} = Na == Nb
Base.isapprox(d1::IMatrix{Na}, d2::IMatrix{Nb}; kwargs...) where {Na,Nb} = Na == Nb

####### sparse matrix ######
nnz(M::IMatrix{N}) where {N} = N
nonzeros(M::IMatrix{N,T}) where {N,T} = ones(T, N)
Expand All @@ -23,4 +26,4 @@ ishermitian(D::IMatrix) = true
isdense(::IMatrix) = false

similar(::IMatrix{N,Tv}, ::Type{T}) where {N,Tv,T} = IMatrix{N,T}()
copyto!(A::IMatrix{N}, B::IMatrix{N}) where {N} = A
copyto!(A::IMatrix{N}, B::IMatrix{N}) where {N} = A
3 changes: 3 additions & 0 deletions src/PermMatrix.jl
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Expand Up @@ -44,6 +44,9 @@ function PermMatrix(
PermMatrix{Tv,Ti,Vv,Vi}(perm, vals)
end

Base.:(==)(d1::PermMatrix, d2::PermMatrix) = SparseMatrixCSC(d1) == SparseMatrixCSC(d2)
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Why can't you compare the value directly? Why covert it to CSC?

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@GiggleLiu GiggleLiu Jun 9, 2022 •
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If there are two entries being zero, then their order are not important. This logic is too complicated.
If we ignore this corner case, some tests can not pass.

Base.isapprox(d1::PermMatrix, d2::PermMatrix; kwargs...) = isapprox(SparseMatrixCSC(d1), SparseMatrixCSC(d2); kwargs...)
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Same as above


################# Array Functions ##################

size(M::PermMatrix) = (length(M.perm), length(M.perm))
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64 changes: 37 additions & 27 deletions src/arraymath.jl
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Expand Up @@ -37,38 +37,48 @@ import Base: *, /, ==, +, -, ≈
#+(A::PermMatrix, B::PermMatrix) = PermMatrix(A.dv+B.dv, A.ev+B.ev)
#-(A::PermMatrix, B::PermMatrix) = PermMatrix(A.dv-B.dv, A.ev-B.ev)


const IDP = Union{PermMatrix,IMatrix}

for op in [:+, :-, :(==), :≈]
@eval begin
$op(A::IDP, B::SparseMatrixCSC) = $op(SparseMatrixCSC(A), B)
$op(B::SparseMatrixCSC, A::IDP) = $op(B, SparseMatrixCSC(A))

# intra-IDP
$op(A::PermMatrix, B::IDP) = $op(SparseMatrixCSC(A), SparseMatrixCSC(B))
$op(A::IDP, B::PermMatrix) = $op(SparseMatrixCSC(A), SparseMatrixCSC(B))
$op(A::PermMatrix, B::PermMatrix) = $op(SparseMatrixCSC(A), SparseMatrixCSC(B))
end

# intra-ID
if op in [:+, :-]
@eval begin
$op(d1::Diagonal, d2::IMatrix) = Diagonal($op(d1.diag, diag(d2)))
$op(d1::IMatrix, d2::Diagonal) = Diagonal($op(diag(d1), d2.diag))
end
else
for op in [:+, :-]
for MT in [:IMatrix, :PermMatrix]
@eval begin
$op(d1::IMatrix, d2::Diagonal) = $op(diag(d1), d2.diag)
$op(d1::Diagonal, d2::IMatrix) = $op(d1.diag, diag(d2))
$op(d1::IMatrix{Na}, d2::IMatrix{Nb}) where {Na,Nb} = $op(Na, Nb)
# IMatrix, PermMatrix - SparseMatrixCSC
$op(A::$MT, B::SparseMatrixCSC) = $op(SparseMatrixCSC(A), B)
$op(B::SparseMatrixCSC, A::$MT) = $op(B, SparseMatrixCSC(A))
end
end

@eval begin
# IMatrix, PermMatrix - Diagonal
$op(d1::IMatrix, d2::Diagonal) = Diagonal($op(diag(d1), d2.diag))
$op(d1::Diagonal, d2::IMatrix) = Diagonal($op(d1.diag, diag(d2)))
$op(d1::PermMatrix, d2::Diagonal) = $op(SparseMatrixCSC(d1), d2)
$op(d1::Diagonal, d2::PermMatrix) = $op(d1, SparseMatrixCSC(d2))
# PermMatrix - IMatrix
$op(A::PermMatrix, B::IMatrix) = $op(SparseMatrixCSC(A), SparseMatrixCSC(B))
$op(A::IMatrix, B::PermMatrix) = $op(SparseMatrixCSC(A), SparseMatrixCSC(B))
$op(A::PermMatrix, B::PermMatrix) = $op(SparseMatrixCSC(A), SparseMatrixCSC(B))
end
end

# NOTE: promote 2 at least as an integer
# NOTE: promote to integer
+(d1::IMatrix{Na,Ta}, d2::IMatrix{Nb,Tb}) where {Na,Nb,Ta,Tb} =
d1 == d2 ? Diagonal(fill(promote_type(Ta, Tb, Int)(2), Na)) : throw(DimensionMismatch())
-(d1::IMatrix{Na,Ta}, d2::IMatrix{Nb,Tb}) where {Na,Ta,Nb,Tb} =
d1 == d2 ? spzeros(promote_type(Ta, Tb), Na, Na) : throw(DimensionMismatch())

for MT in [:IMatrix, :PermMatrix]
@eval Base.:(==)(A::$MT, B::SparseMatrixCSC) = SparseMatrixCSC(A) == B
@eval Base.:(==)(A::SparseMatrixCSC, B::$MT) = A == SparseMatrixCSC(B)
end
Base.:(==)(d1::IMatrix, d2::Diagonal) = all(isone, d2.diag)
Base.:(==)(d1::Diagonal, d2::IMatrix) = all(isone, d1.diag)
Base.:(==)(d1::PermMatrix, d2::Diagonal) = SparseMatrixCSC(d1) == SparseMatrixCSC(d2)
Base.:(==)(d1::Diagonal, d2::PermMatrix) = SparseMatrixCSC(d1) == SparseMatrixCSC(d2)
Base.:(==)(A::IMatrix, B::PermMatrix) = SparseMatrixCSC(A) == SparseMatrixCSC(B)
Base.:(==)(A::PermMatrix, B::IMatrix) = SparseMatrixCSC(A) == SparseMatrixCSC(B)

for MT in [:IMatrix, :PermMatrix]
@eval Base.isapprox(A::$MT, B::SparseMatrixCSC; kwargs...) = isapprox(SparseMatrixCSC(A), B)
@eval Base.isapprox(A::SparseMatrixCSC, B::$MT; kwargs...) = isapprox(A, SparseMatrixCSC(B))
@eval Base.isapprox(d1::$MT, d2::Diagonal; kwargs...) = isapprox(diag(d1), d2.diag)
@eval Base.isapprox(d1::Diagonal, d2::$MT; kwargs...) = isapprox(d1.diag, diag(d2))
end
Base.isapprox(A::IMatrix, B::PermMatrix; kwargs...) = isapprox(SparseMatrixCSC(A), SparseMatrixCSC(B); kwargs...)
Base.isapprox(A::PermMatrix, B::IMatrix; kwargs...) = isapprox(SparseMatrixCSC(A), SparseMatrixCSC(B); kwargs...)
5 changes: 3 additions & 2 deletions src/linalg.jl
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Expand Up @@ -95,13 +95,14 @@ end
# to matrix
function *(A::PermMatrix, X::AbstractMatrix)
size(X, 1) == size(A, 2) || throw(DimensionMismatch())
return @views A.vals .* X[A.perm, :] # this may be inefficient for sparse CSC matrix.
return A.vals .* view(X,A.perm,:) # this may be inefficient for sparse CSC matrix.
end

function *(X::AbstractMatrix, A::PermMatrix)
mX, nX = size(X)
nX == size(A, 1) || throw(DimensionMismatch())
return @views (transpose(A.vals) .* X)[:, fast_invperm(A.perm)]
perm = fast_invperm(A.perm)
return transpose(view(A.vals, perm)) .* view(X, :, perm)
end

# NOTE: this is just a temperory fix for v0.7. We should overload mul! in
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13 changes: 12 additions & 1 deletion test/linalg.jl
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Expand Up @@ -35,6 +35,9 @@ end
for source_ in Any[p1, sp, ds, dv, pm]
for target in Any[p1, sp, ds, dv, pm]
for source in Any[source_, source_', transpose(source_)]
@test (source == target) == (Matrix(source) == Matrix(target))
@test (source == target) ≈ (Matrix(source) ≈ Matrix(target))
# *
lres = source * target
rres = target * source
flres = Matrix(source) * Matrix(target)
Expand All @@ -49,6 +52,14 @@ end
@test lres |> isdense == false
@test lres |> isdense == false
end

# +, -
lres2 = source + target
rres2 = target - source
flres2 = Matrix(source) + Matrix(target)
frres2 = Matrix(target) - Matrix(source)
@test lres2 ≈ flres2
@test rres2 ≈ frres2
end
end
end
Expand Down Expand Up @@ -133,4 +144,4 @@ end
pop = sparse([2, 3], [4, 5], [1, √2], 5, 5)
zop = Diagonal([0, 1 / 2, 1, -1 / 2, 0])
@test (pop*zop)[2, 4] == -0.5
end
end