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Deprecate vectorized min and max over pairs of sparse matrices #19713

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Deprecate vectorized min and max over pairs of sparse matrices #19713

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2 changes: 0 additions & 2 deletions base/sparse/sparsematrix.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -2286,8 +2286,6 @@ round{To}(::Type{To}, A::SparseMatrixCSC) = round.(To, A)
(+)(A::SparseMatrixCSC, B::SparseMatrixCSC) = map(+, A, B)
(-)(A::SparseMatrixCSC, B::SparseMatrixCSC) = map(-, A, B)
# TODO: Vectorized min, max, |, and xor should be deprecated in favor of compact-broadcast syntax.
min(A::SparseMatrixCSC, B::SparseMatrixCSC) = map(min, A, B)
max(A::SparseMatrixCSC, B::SparseMatrixCSC) = map(max, A, B)
(&)(A::SparseMatrixCSC, B::SparseMatrixCSC) = map(&, A, B)
(|)(A::SparseMatrixCSC, B::SparseMatrixCSC) = map(|, A, B)
xor(A::SparseMatrixCSC, B::SparseMatrixCSC) = map(xor, A, B)
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22 changes: 11 additions & 11 deletions test/sparse/sparse.jl
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Expand Up @@ -35,8 +35,8 @@ do33 = ones(3)
sqrfloatmat, colfloatmat = sprand(4, 4, 0.5), sprand(4, 1, 0.5)
@test_throws DimensionMismatch (+)(sqrfloatmat, colfloatmat)
@test_throws DimensionMismatch (-)(sqrfloatmat, colfloatmat)
@test_throws DimensionMismatch min(sqrfloatmat, colfloatmat)
@test_throws DimensionMismatch max(sqrfloatmat, colfloatmat)
# @test_throws DimensionMismatch min(sqrfloatmat, colfloatmat) # vectorized min no longer exists
# @test_throws DimensionMismatch max(sqrfloatmat, colfloatmat) # vectorized max no longer exists
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how about testing that map(min, ...) still throws ?

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Sure, though those tests would be redundant with the similar tests #19690 introduces. Preference for redundancy or removal? Thanks!

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I'd prefer redundancy, since spzeros((shapeA .- 1)...) used in those tests isn't quite the same as what this was doing

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(Addressed in #19791. Thanks!)

sqrboolmat, colboolmat = sprand(Bool, 4, 4, 0.5), sprand(Bool, 4, 1, 0.5)
@test_throws DimensionMismatch (&)(sqrboolmat, colboolmat)
@test_throws DimensionMismatch (|)(sqrboolmat, colboolmat)
Expand Down Expand Up @@ -1515,11 +1515,11 @@ end
@test A12118 - B12118 == sparse([1,2,3,4,4,5], [1,2,3,3,4,5], [-1,1,3,1,4,7])
@test typeof(A12118 - B12118) == SparseMatrixCSC{Int,Int}

@test max(A12118, B12118) == sparse([1,2,3,4,5], [1,2,3,4,5], [2,2,3,4,5])
@test typeof(max(A12118, B12118)) == SparseMatrixCSC{Int,Int}
@test max.(A12118, B12118) == sparse([1,2,3,4,5], [1,2,3,4,5], [2,2,3,4,5])
@test typeof(max.(A12118, B12118)) == SparseMatrixCSC{Int,Int}

@test min(A12118, B12118) == sparse([1,2,4,5], [1,2,3,5], [1,1,-1,-2])
@test typeof(min(A12118, B12118)) == SparseMatrixCSC{Int,Int}
@test min.(A12118, B12118) == sparse([1,2,4,5], [1,2,3,5], [1,1,-1,-2])
@test typeof(min.(A12118, B12118)) == SparseMatrixCSC{Int,Int}
end

@testset "sparse matrix norms" begin
Expand Down Expand Up @@ -1598,17 +1598,17 @@ end
@test A13024 ⊻ B13024 == sparse([3,4,4], [3,3,4], fill(true,3), 5, 5)
@test typeof(A13024 ⊻ B13024) == SparseMatrixCSC{Bool,Int}

@test max(A13024, B13024) == sparse([1,2,3,4,4,5], [1,2,3,3,4,5], fill(true,6))
@test typeof(max(A13024, B13024)) == SparseMatrixCSC{Bool,Int}
@test max.(A13024, B13024) == sparse([1,2,3,4,4,5], [1,2,3,3,4,5], fill(true,6))
@test typeof(max.(A13024, B13024)) == SparseMatrixCSC{Bool,Int}

@test min(A13024, B13024) == sparse([1,2,5], [1,2,5], fill(true,3))
@test typeof(min(A13024, B13024)) == SparseMatrixCSC{Bool,Int}
@test min.(A13024, B13024) == sparse([1,2,5], [1,2,5], fill(true,3))
@test typeof(min.(A13024, B13024)) == SparseMatrixCSC{Bool,Int}

for op in (+, -, &, |, xor)
@test op(A13024, B13024) == op(Array(A13024), Array(B13024))
end
for op in (max, min)
@test op(A13024, B13024) == op.(Array(A13024), Array(B13024))
@test op.(A13024, B13024) == op.(Array(A13024), Array(B13024))
end
end

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