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Test generic sparse map[!]/broadcast[!] for sparse vectors/matrices.
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Condense and systematize existing tests for generic sparse map[!]/broadcast[!], and extend to sparse vectors and vector/matrix combinations. Relocate new test code to a separate file test/sparse/higherorderfns.jl corresponding to base/sparse/higherorderfns.jl. (Test/sparse/sparsevector.jl is hypothetically confined to SparseVectors, and test/sparse/sparse.jl mostly dedicated to SparseMatrixCSCs.) Move older tests of sparse broadcast[!] into that new file as well.
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@Sacha0
Sacha0 committed Dec 22, 2016
1 parent 8a19b56 commit 0c539a9
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2 changes: 1 addition & 1 deletion test/choosetests.jl
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Expand Up @@ -102,7 +102,7 @@ function choosetests(choices = [])
end


sparsetests = ["sparse/sparse", "sparse/sparsevector"]
sparsetests = ["sparse/sparse", "sparse/sparsevector", "sparse/higherorderfns"]
if Base.USE_GPL_LIBS
append!(sparsetests, ["sparse/umfpack", "sparse/cholmod", "sparse/spqr"])
end
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254 changes: 254 additions & 0 deletions test/sparse/higherorderfns.jl
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# This file is a part of Julia. License is MIT: http://julialang.org/license
#
# These tests cover the higher order functions specialized for sparse arrays defined in
# base/sparse/higherorderfns.jl, particularly map[!]/broadcast[!] for SparseVectors and
# SparseMatrixCSCs at present.

@testset "map[!] implementation specialized for a single (input) sparse vector/matrix" begin
N, M = 10, 12
# (also the implementation for broadcast[!] over a single (input) sparse vector/matrix)
for shapeA in ((N,), (N, M))
A = sprand(shapeA..., 0.4); fA = Array(A)
# --> test map entry point
@test map(sin, A) == sparse(map(sin, fA))
@test map(cos, A) == sparse(map(cos, fA))
# --> test map! entry point
fX = copy(fA); X = sparse(fX)
map!(sin, X, A); X = sparse(fX) # warmup for @allocated
@test (@allocated map!(sin, X, A)) == 0
@test map!(sin, X, A) == sparse(map!(sin, fX, fA))
@test map!(cos, X, A) == sparse(map!(cos, fX, fA))
@test_throws DimensionMismatch map!(sin, X, spzeros((shapeA .- 1)...))
end
end

@testset "map[!] implementation specialized for a pair of (input) sparse vectors/matrices" begin
N, M = 10, 12
f(x, y) = x + y + 1
for shapeA in ((N,), (N, M))
A, Bo = sprand(shapeA..., 0.3), sprand(shapeA..., 0.3)
B = ndims(Bo) == 1 ? SparseVector{Float32, Int32}(Bo) : SparseMatrixCSC{Float32,Int32}(Bo)
# use different types to check internal type stability via allocation tests below
fA, fB = map(Array, (A, B))
# --> test map entry point
@test map(+, A, B) == sparse(map(+, fA, fB))
@test map(*, A, B) == sparse(map(*, fA, fB))
@test map(f, A, B) == sparse(map(f, fA, fB))
@test_throws DimensionMismatch map(+, A, spzeros((shapeA .- 1)...))
# --> test map! entry point
fX = map(+, fA, fB); X = sparse(fX)
map!(+, X, A, B); X = sparse(fX) # warmup for @allocated
@test (@allocated map!(+, X, A, B)) == 0
@test map!(+, X, A, B) == sparse(map!(+, fX, fA, fB))
fX = map(*, fA, fB); X = sparse(fX)
map!(*, X, A, B); X = sparse(fX) # warmup for @allocated
@test (@allocated map!(*, X, A, B)) == 0
@test map!(*, X, A, B) == sparse(map!(*, fX, fA, fB))
@test map!(f, X, A, B) == sparse(map!(f, fX, fA, fB))
@test_throws DimensionMismatch map!(f, X, A, spzeros((shapeA .- 1)...))
end
end

@testset "map[!] implementation capable of handling >2 (input) sparse vectors/matrices" begin
N, M = 10, 12
f(x, y, z) = x + y + z + 1
for shapeA in ((N,), (N, M))
A, B, Co = sprand(shapeA..., 0.2), sprand(shapeA..., 0.2), sprand(shapeA..., 0.2)
C = ndims(Co) == 1 ? SparseVector{Float32,Int32}(Co) : SparseMatrixCSC{Float32,Int32}(Co)
# use different types to check internal type stability via allocation tests below
fA, fB, fC = map(Array, (A, B, C))
# --> test map entry point
@test map(+, A, B, C) == sparse(map(+, fA, fB, fC))
@test map(*, A, B, C) == sparse(map(*, fA, fB, fC))
@test map(f, A, B, C) == sparse(map(f, fA, fB, fC))
@test_throws DimensionMismatch map(+, A, B, spzeros(N, M - 1))
# --> test map! entry point
fX = map(+, fA, fB, fC); X = sparse(fX)
map!(+, X, A, B, C); X = sparse(fX) # warmup for @allocated
@test (@allocated map!(+, X, A, B, C)) == 0
@test map!(+, X, A, B, C) == sparse(map!(+, fX, fA, fB, fC))
fX = map(*, fA, fB, fC); X = sparse(fX)
map!(*, X, A, B, C); X = sparse(fX) # warmup for @allocated
@test (@allocated map!(*, X, A, B, C)) == 0
@test map!(*, X, A, B, C) == sparse(map!(*, fX, fA, fB, fC))
@test map!(f, X, A, B, C) == sparse(map!(f, fX, fA, fB, fC))
@test_throws DimensionMismatch map!(f, X, A, B, spzeros((shapeA .- 1)...))
end
end

@testset "broadcast[!] implementation specialized for a single (input) sparse vector/matrix" begin
# broadcast[!] for a single sparse vector/matrix falls back to map[!], tested extensively
# above. here we simply lightly exercise the relevant broadcast[!] entry points.
N, M, p = 10, 12, 0.4
a, A = sprand(N, p), sprand(N, M, p)
fa, fA = Array(a), Array(A)
@test broadcast(sin, a) == sparse(broadcast(sin, fa))
@test broadcast(sin, A) == sparse(broadcast(sin, fA))
@test broadcast!(sin, copy(a), a) == sparse(broadcast!(sin, copy(fa), fa))
@test broadcast!(sin, copy(A), A) == sparse(broadcast!(sin, copy(fA), fA))
end

@testset "broadcast[!] implementation specialized for pairs of (input) sparse vectors/matrices" begin
N, M, p = 10, 12, 0.3
f(x, y) = x + y + 1
mats = (sprand(N, M, p), sprand(N, 1, p), sprand(1, M, p), sprand(1, 1, 1.0), spzeros(1, 1))
vecs = (sprand(N, p), sprand(1, 1.0), spzeros(1))
tens = (mats..., vecs...)
for Xo in tens
X = ndims(Xo) == 1 ? SparseVector{Float32,Int32}(Xo) : SparseMatrixCSC{Float32,Int32}(Xo)
# use different types to check internal type stability via allocation tests below
shapeX, fX = size(X), Array(X)
for Y in tens
fY = Array(Y)
# --> test broadcast entry point
@test broadcast(+, X, Y) == sparse(broadcast(+, fX, fY))
@test broadcast(*, X, Y) == sparse(broadcast(*, fX, fY))
@test broadcast(f, X, Y) == sparse(broadcast(f, fX, fY))
try Base.Broadcast.broadcast_indices(spzeros((shapeX .- 1)...), Y)
catch @test_throws DimensionMismatch broadcast(+, spzeros((shapeX .- 1)...), Y) end
# --> test broadcast! entry point / +-like zero-preserving op
fZ = broadcast(+, fX, fY); Z = sparse(fZ)
broadcast!(+, Z, X, Y); Z = sparse(fZ) # warmup for @allocated
@test (@allocated broadcast!(+, Z, X, Y)) == 0
@test broadcast!(+, Z, X, Y) == sparse(broadcast!(+, fZ, fX, fY))
# --> test broadcast! entry point / *-like zero-preserving op
fZ = broadcast(*, fX, fY); Z = sparse(fZ)
broadcast!(*, Z, X, Y); Z = sparse(fZ) # warmup for @allocated
@test (@allocated broadcast!(*, Z, X, Y)) == 0
@test broadcast!(*, Z, X, Y) == sparse(broadcast!(*, fZ, fX, fY))
# --> test broadcast! entry point / not zero-preserving op
fZ = broadcast(f, fX, fY); Z = sparse(fZ)
broadcast!(f, Z, X, Y); Z = sparse(fZ) # warmup for @allocated
@test (@allocated broadcast!(f, Z, X, Y)) == 0
@test broadcast!(f, Z, X, Y) == sparse(broadcast!(f, fZ, fX, fY))
# --> test shape checks for both braodcast and broadcast! entry points
try Base.Broadcast.check_broadcast_indices(indices(Z), spzeros((shapeX .- 1)...), Y)
catch @test_throws DimensionMismatch broadcast!(f, Z, spzeros((shapeX .- 1)...), Y) end
end
end
end

@testset "broadcast[!] implementation capable of handling >2 (input) sparse vectors/matrices" begin
N, M, p = 10, 12, 0.3
f(x, y, z) = x + y + z + 1
mats = (sprand(N, M, p), sprand(N, 1, p), sprand(1, M, p), sprand(1, 1, 1.0), spzeros(1, 1))
vecs = (sprand(N, p), sprand(1, 1.0), spzeros(1))
tens = (mats..., vecs...)
for Xo in tens
X = ndims(Xo) == 1 ? SparseVector{Float32,Int32}(Xo) : SparseMatrixCSC{Float32,Int32}(Xo)
# use different types to check internal type stability via allocation tests below
shapeX, fX = size(X), Array(X)
for Y in tens, Z in tens
fY, fZ = Array(Y), Array(Z)
# --> test broadcast entry point
@test broadcast(+, X, Y, Z) == sparse(broadcast(+, fX, fY, fZ))
@test broadcast(*, X, Y, Z) == sparse(broadcast(*, fX, fY, fZ))
@test broadcast(f, X, Y, Z) == sparse(broadcast(f, fX, fY, fZ))
try Base.Broadcast.broadcast_indices(spzeros((shapeX .- 1)...), Y, Z)
catch @test_throws DimensionMismatch broadcast(+, spzeros((shapeX .- 1)...), Y, Z) end
# --> test broadcast! entry point / +-like zero-preserving op
fQ = broadcast(+, fX, fY, fZ); Q = sparse(fQ)
broadcast!(+, Q, X, Y, Z); Q = sparse(fQ) # warmup for @allocated
@test (@allocated broadcast!(+, Q, X, Y, Z)) == 0
@test broadcast!(+, Q, X, Y, Z) == sparse(broadcast!(+, fQ, fX, fY, fZ))
# --> test broadcast! entry point / *-like zero-preserving op
fQ = broadcast(*, fX, fY, fZ); Q = sparse(fQ)
broadcast!(*, Q, X, Y, Z); Q = sparse(fQ) # warmup for @allocated
@test (@allocated broadcast!(*, Q, X, Y, Z)) == 0
@test broadcast!(*, Q, X, Y, Z) == sparse(broadcast!(*, fQ, fX, fY, fZ))
# --> test broadcast! entry point / not zero-preserving op
fQ = broadcast(f, fX, fY, fZ); Q = sparse(fQ)
broadcast!(f, Q, X, Y, Z); Q = sparse(fQ) # warmup for @allocated
@test_broken (@allocated broadcast!(f, Z, X, Y)) == 0
# the preceding test allocates 16 bytes in the entry point for broadcast!, but
# none of the earlier tests of the same code path allocate. no allocation shows
# up with --track-allocation=user. allocation shows up on the first line of the
# entry point for broadcast! with --track-allocation=all, but that first line
# almost certainly should not allocate. so not certain what's going on.
@test broadcast!(f, Q, X, Y, Z) == sparse(broadcast!(f, fQ, fX, fY, fZ))
# --> test shape checks for both braodcast and broadcast! entry points
try Base.Broadcast.check_broadcast_indices(indices(Q), spzeros((shapeX .- 1)...), Y, Z)
catch @test_throws DimensionMismatch broadcast!(f, Q, spzeros((shapeX .- 1)...), Y, Z) end
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
A, B, CF = sprand(N, N, p), sprand(N, N, p), rand(N, N)
AF, BF, C = Array(A), Array(B), sparse(CF)

@test A .* B == AF .* BF
@test A[1,:] .* B == AF[1,:] .* BF
@test A[:,1] .* B == AF[:,1] .* BF
@test A .* B[1,:] == AF .* BF[1,:]
@test A .* B[:,1] == AF .* BF[:,1]

@test A .* B == AF .* BF
@test A[1,:] .* BF == AF[1,:] .* BF
@test A[:,1] .* BF == AF[:,1] .* BF
@test A .* BF[1,:] == AF .* BF[1,:]
@test A .* BF[:,1] == AF .* BF[:,1]

@test A .* B == AF .* BF
@test AF[1,:] .* B == AF[1,:] .* BF
@test AF[:,1] .* B == AF[:,1] .* BF
@test AF .* B[1,:] == AF .* BF[1,:]
@test AF .* B[:,1] == AF .* BF[:,1]

@test A .* B == AF .* BF
@test A[1,:] .* B == AF[1,:] .* BF
@test A[:,1] .* B == AF[:,1] .* BF
@test A .* B[1,:] == AF .* BF[1,:]
@test A .* B[:,1] == AF .* BF[:,1]

@test A .* 3 == AF .* 3
@test 3 .* A == 3 .* AF
#@test A[1,:] .* 3 == AF[1,:] .* 3
@test all(A[1,:] .* 3 .== AF[1,:] .* 3)
#@test A[:,1] .* 3 == AF[:,1] .* 3
@test all(A[:,1] .* 3 .== AF[:,1] .* 3)
#TODO: simple comparation with == returns false because the left side is a (two-dimensional) SparseMatrixCSC
# while the right side is a Vector

@test A .- 3 == AF .- 3
@test 3 .- A == 3 .- AF
@test A .- B == AF .- BF
@test A - AF == zeros(AF)
@test AF - A == zeros(AF)
@test A[1,:] .- B == AF[1,:] .- BF
@test A[:,1] .- B == AF[:,1] .- BF
@test A .- B[1,:] == AF .- BF[1,:]
@test A .- B[:,1] == AF .- BF[:,1]

@test A .+ 3 == AF .+ 3
@test 3 .+ A == 3 .+ AF
@test A .+ B == AF .+ BF
@test A + AF == AF + A
@test (A .< B) == (AF .< BF)
@test (A .!= B) == (AF .!= BF)

@test A ./ 3 == AF ./ 3
@test A .\ 3 == AF .\ 3
@test 3 ./ A == 3 ./ AF
@test 3 .\ A == 3 .\ AF
@test A .\ C == AF .\ CF
@test A ./ C == AF ./ CF
@test A ./ CF[:,1] == AF ./ CF[:,1]
@test A .\ CF[:,1] == AF .\ CF[:,1]
@test BF ./ C == BF ./ CF
@test BF .\ C == BF .\ CF

@test A .^ 3 == AF .^ 3
@test 3 .^ A == 3 .^ AF
@test A .^ BF[:,1] == AF .^ BF[:,1]
@test BF[:,1] .^ A == BF[:,1] .^ AF

@test spzeros(0,0) + spzeros(0,0) == zeros(0,0)
@test spzeros(0,0) * spzeros(0,0) == zeros(0,0)
@test spzeros(1,0) .+ spzeros(2,1) == zeros(2,0)
@test spzeros(1,0) .* spzeros(2,1) == zeros(2,0)
@test spzeros(1,2) .+ spzeros(0,1) == zeros(0,2)
@test spzeros(1,2) .* spzeros(0,1) == zeros(0,2)
end
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