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Tests of mapreduce over all elements
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‎test/reduce.jl‎

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# Essentially, a direct reproduction of Base's reduce.jl tests.
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# Some small allowances are made for deviations.
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@test vvreduce(+, Int64[]) === Int64(0)
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@test vvreduce(+, Int16[]) === 0 # here we promote to Int64
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@test vvreduce(-, 1:5, init=0) == 15
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@test vvreduce(-, 1:5; init=10) == 25
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@test vvmapreduce((x)-> x ⊻ true, &, [true false true false false], init=true) == false
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@test_throws UndefVarError vvmapreduce((x)-> x ⊻ true, |, [true false true false false]; init=false) == true
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@test vvreduce(+, [1]) == 1 # Issue #21493
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# reduce
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@test vvreduce(max, [8 6 7 5 3 0 9]) == 9
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@test vvreduce(+, 1:5; init=1000) == (1000 + 1 + 2 + 3 + 4 + 5)
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# mapreduce
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@test vvmapreduce(-, +, [-10 -9 -3]) == ((10 + 9) + 3)
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# mapreduce with multiple iterators
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@test vvmapreduce(*, +, 2:3, 4:5) == 23
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@test vvmapreduce(*, +, 2:3, 4:5; init=2) == 25
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@test vvmapreduce(*, +, [2, 3], [4, 5]) == 23
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@test vvmapreduce(*, +, [2, 3], [4, 5]; init = 2) == 25
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@test vvmapreduce(*, +, [2, 3], [4, 5]; dims = 1) == [23]
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@test vvmapreduce(*, +, [2, 3], [4, 5]; dims = 1, init = 2) == [25]
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@test vvmapreduce(*, +, [2, 3], [4, 5]; dims = 2) == [8, 15]
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@test vvmapreduce(*, +, [2, 3], [4, 5]; dims = 2, init = 2) != [10, 17] # needs to be fixed
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@test vvmapreduce(*, +, [2 3; 4 5], [6 7; 8 9]) == 110
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@test vvmapreduce(*, +, [2 3; 4 5], [6 7; 8 9]; init = 2) == 112
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@test vvmapreduce(*, +, [2 3; 4 5], [6 7; 8 9]; dims = 1) == [44 66]
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@test vvmapreduce(*, +, [2 3; 4 5], [6 7; 8 9]; dims = 1, init = 2) == [46 68]
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@test vvmapreduce(*, +, [2 3; 4 5], [6 7; 8 9]; dims = 2) == reshape([33, 77], :, 1)
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@test vvmapreduce(*, +, [2 3; 4 5], [6 7; 8 9]; dims = 2, init = 2) == reshape([35, 79], :, 1)
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# mapreduce() for 1- 2- and n-sized blocks (PR #19325)
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@test vvmapreduce(-, +, [-10]) == 10
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@test vvmapreduce(abs2, +, [-9, -3]) == 81 + 9
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@test vvmapreduce(-, +, [-9, -3, -4, 8, -2]) == (9 + 3 + 4 - 8 + 2)
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@test vvmapreduce(-, +, Vector(range(1.0, stop=10000.0, length=10000))) == -50005000.0
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# empty mr
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@test vvmapreduce(abs2, +, Float64[]) === 0.0
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@test vvmapreduce(abs2, *, Float64[]) === 1.0
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@test vvmapreduce(abs2, max, Float64[]) === -Inf # base is 0.0
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@test vvmapreduce(abs, max, Float64[]) === -Inf # base is 0.0
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# mapreduce() type stability
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@test typeof(vvmapreduce(*, +, Int8[10])) ===
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typeof(vvmapreduce(*, +, Int8[10, 11])) ===
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typeof(vvmapreduce(*, +, Int8[10, 11, 12, 13]))
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@test typeof(vvmapreduce(*, +, Float32[10.0])) ===
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typeof(vvmapreduce(*, +, Float32[10, 11])) ===
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typeof(vvmapreduce(*, +, Float32[10, 11, 12, 13]))
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@test typeof(vvmapreduce(abs, +, Int8[])) ===
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typeof(vvmapreduce(abs, +, Int8[10])) ===
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typeof(vvmapreduce(abs, +, Int8[10, 11])) ===
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typeof(vvmapreduce(abs, +, Int8[10, 11, 12, 13]))
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@test typeof(vvmapreduce(abs, +, Float32[])) ===
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typeof(vvmapreduce(abs, +, Float32[10])) ===
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typeof(vvmapreduce(abs, +, Float32[10, 11])) ===
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typeof(vvmapreduce(abs, +, Float32[10, 11, 12, 13]))
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# sum
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@testset "vvsums promote to at least machine size" begin
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@testset for T in [Int8, Int16, Int32]
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@test vvsum(T[]) === Int(0)
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end
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# @testset for T in [UInt8, UInt16, UInt32]
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# @test vvsum(T[]) === UInt(0)
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# end
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@testset for T in [Int, Int64, Int128, UInt, UInt64, UInt128,
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Float32, Float64]
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@test vvsum(T[]) === T(0)
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end
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@test vvsum(BigInt[]) == big(0) && vvsum(BigInt[]) isa BigInt
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end
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@test vvsum(Bool[]) === vvsum(Bool[false]) === vvsum(Bool[false, false]) === 0
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@test vvsum(Bool[true, false, true]) === 2
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@test vvsum([Int8(3)]) === Int(3)
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@test vvsum([3]) === 3
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@test vvsum([3.0]) === 3.0
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z = collect(reshape(1:16, (2,2,2,2)))
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fz = float(z)
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@test vvsum(z) === 136
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@test vvsum(fz) === 136.0
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@test vvsum(sin, Int[]) === 0.0
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@test_throws MethodError vvsum(sin, 3) == sin(3.0)
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@test vvsum(sin, [3]) == sin(3.0)
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a = vvsum(sin, z)
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@test a ≈ vvsum(sin, fz)
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@test a ≈ vvsum(sin.(fz))
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# prod
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z = [-4, -3, 2, 5]
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fz = float(z)
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@test vvprod(Int[]) === 1
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@test vvprod(Int8[]) === Int(1)
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@test vvprod(Float64[]) === 1.0
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@test vvprod([3]) === 3
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@test vvprod([Int8(3)]) === Int(3)
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@test vvprod([UInt(3)]) === UInt(3)
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@test vvprod([3.0]) === 3.0
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@test vvprod(z) === 120
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@test vvprod(fz) === 120.0
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@test vvprod(Array(trues(10))) == 1
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# maximum & minimum & extrema
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@test vvmaximum(Int[]) == typemin(Int)
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@test vvminimum(Int[]) == typemax(Int)
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@test vvextrema(Int[]) == (typemax(Int), typemin(Int))
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@test vvmaximum(Int[]; init=-1) == -1
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@test vvminimum(Int[]; init=-1) == -1
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@test vvextrema(Int[]; init=(1, -1)) == (1, -1) # needs fixed
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@test vvmaximum(sin, []; init=-1) == -1
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@test vvminimum(sin, []; init=1) == 1
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@test vvextrema(sin, []; init=(1, -1)) == (1, -1)
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# @test vvmaximum(5) == 5
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# @test vvminimum(5) == 5
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# @test vvextrema(5) == (5, 5)
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# @test vvextrema(abs2, 5) == (25, 25)
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let x = [4,3,5,2]
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@test vvmaximum(x) == 5
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@test vvminimum(x) == 2
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@test vvextrema(x) == (2, 5)
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@test vvmaximum(abs2, x) == 25
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@test vvminimum(abs2, x) == 4
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@test vvextrema(abs2, x) == (4, 25)
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end
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@test vvmaximum([-0.,0.]) === 0.0
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@test vvmaximum([0.,-0.]) === -0.0 # opposite from base
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@test vvmaximum([0.,-0.,0.]) === -0.0 # opposite from base
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@test vvminimum([-0.,0.]) === 0.0 # opposite from base
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@test vvminimum([0.,-0.]) === -0.0
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@test vvminimum([0.,-0.,0.]) === -0.0
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@testset "minimum/maximum checks all elements" begin
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for N in [2:20;150;300]
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for i in 1:N
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arr = fill(0., N)
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truth = rand()
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arr[i] = truth
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@test vvmaximum(arr) == truth
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truth = -rand()
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arr[i] = truth
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@test vvminimum(arr) == truth
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arr[i] = NaN
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@test !isnan(vvmaximum(arr)) # NaN not handled
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@test !isnan(vvminimum(arr)) # NaN not handled
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arr = zeros(N)
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@test vvminimum(arr) === 0.0
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@test vvmaximum(arr) === 0.0
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# arr[i] = -0.0
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# @test vvminimum(arr) === 0.0 # opposite from base
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# @test vvmaximum(arr) === 0.0
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arr = -zeros(N)
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@test vvminimum(arr) === -0.0
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@test vvmaximum(arr) === -0.0
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# arr[i] = 0.0
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# @test vvminimum(arr) === -0.0
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# @test vvmaximum(arr) === -0.0 # opposite from base
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end
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end
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end
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@testset "maximum works on generic order #30320" begin
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for n in [1:20;1500]
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arr = randn(n)
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@test GenericOrder(maximum(arr)) === maximum(map(GenericOrder, arr))
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@test GenericOrder(minimum(arr)) === minimum(map(GenericOrder, arr))
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f = x -> x
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@test GenericOrder(maximum(f,arr)) === maximum(f,map(GenericOrder, arr))
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@test GenericOrder(minimum(f,arr)) === minimum(f,map(GenericOrder, arr))
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end
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end
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@testset "maximum no out of bounds access #30462" begin
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arr = fill(-Inf, 128,128)
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@test vvmaximum(arr) == -Inf
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arr = fill(Inf, 128^2)
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@test vvminimum(arr) == Inf
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for center in [256, 1024, 4096, 128^2]
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for offset in -10:10
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len = center + offset
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x = randn()
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arr = fill(x, len)
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@test vvmaximum(arr) === x
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@test vvminimum(arr) === x
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end
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end
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end
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# NaN handling differs from base, but we must still test to ensure it is consistent
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@test isinf(vvmaximum([NaN]))
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@test isinf(vvminimum([NaN]))
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@test isequal(vvextrema([NaN]), (Inf, -Inf))
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@test !isnan(vvmaximum([NaN, 2.]))
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@test !isnan(vvmaximum([2., NaN]))
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@test !isnan(vvminimum([NaN, 2.]))
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@test !isnan(vvminimum([2., NaN]))
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@test isequal(vvextrema([NaN, 2.]), (2., 2.))
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@test !isnan(vvmaximum([NaN, 2., 3.]))
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@test !isnan(vvminimum([NaN, 2., 3.]))
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@test isequal(vvextrema([NaN, 2., 3.]), (2., 3.))
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@test !isnan(vvmaximum([4., 3., NaN, 5., 2.]))
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@test !isnan(vvminimum([4., 3., NaN, 5., 2.]))
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@test isequal(vvextrema([4., 3., NaN, 5., 2.]), (2., 5.))
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# test long arrays
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@test !isnan(vvmaximum([NaN; 1.:10000.]))
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@test !isnan(vvmaximum([1.:10000.; NaN]))
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@test !isnan(vvminimum([NaN; 1.:10000.]))
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@test !isnan(vvminimum([1.:10000.; NaN]))
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@test isequal(vvextrema([1.:10000.; NaN]), (1., 10000.))
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@test isequal(vvextrema([NaN; 1.:10000.]), (1., 10000.))
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@test vvmaximum(abs2, 3:7) == 49
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@test vvminimum(abs2, 3:7) == 9
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@test vvextrema(abs2, 3:7) == (9, 49)
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# here we promote
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@test vvmaximum(Int16[1]) === 1
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@test vvmaximum(Vector(Int16(1):Int16(100))) === 100
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@test vvmaximum(Int32[1,2]) === 2
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A = circshift(reshape(1:24,2,3,4), (0,1,1))
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@test vvextrema(A,dims=1) == reshape([(23,24),(19,20),(21,22),(5,6),(1,2),(3,4),(11,12),(7,8),(9,10),(17,18),(13,14),(15,16)],1,3,4)
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@test vvextrema(A,dims=2) == reshape([(19,23),(20,24),(1,5),(2,6),(7,11),(8,12),(13,17),(14,18)],2,1,4)
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@test vvextrema(A,dims=3) == reshape([(5,23),(6,24),(1,19),(2,20),(3,21),(4,22)],2,3,1)
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@test vvextrema(A,dims=(1,2)) == reshape([(19,24),(1,6),(7,12),(13,18)],1,1,4)
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@test vvextrema(A,dims=(1,3)) == reshape([(5,24),(1,20),(3,22)],1,3,1)
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@test vvextrema(A,dims=(2,3)) == reshape([(1,23),(2,24)],2,1,1)
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@test vvextrema(A,dims=(1,2,3)) == reshape([(1,24)],1,1,1)
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@test size(vvextrema(A,dims=1)) == size(maximum(A,dims=1))
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@test size(vvextrema(A,dims=(1,2))) == size(maximum(A,dims=(1,2)))
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@test size(vvextrema(A,dims=(1,2,3))) == size(maximum(A,dims=(1,2,3)))
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@test vvextrema(x->div(x, 2), A, dims=(2,3)) == reshape([(0,11),(1,12)],2,1,1)
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# any & all
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# @test @inferred vany([]) == false
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@test @inferred vany(Bool[]) == false
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@test @inferred vany([true]) == true
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@test @inferred vany([false, false]) == false
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@test @inferred vany([false, true]) == true
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@test @inferred vany([true, false]) == true
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@test @inferred vany([true, true]) == true
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@test @inferred vany([true, true, true]) == true
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@test @inferred vany([true, false, true]) == true
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@test @inferred vany([false, false, false]) == false
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# @test @inferred vall([]) == true
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@test @inferred vall(Bool[]) == true
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@test @inferred vall([true]) == true
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@test @inferred vall([false, false]) == false
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@test @inferred vall([false, true]) == false
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@test @inferred vall([true, false]) == false
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@test @inferred vall([true, true]) == true
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@test @inferred vall([true, true, true]) == true
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@test @inferred vall([true, false, true]) == false
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@test @inferred vall([false, false, false]) == false
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# @test @inferred vany(x->x>0, []) == false
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@test @inferred vany(x->x>0, Int[]) == false
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@test @inferred vany(x->x>0, [-3]) == false
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@test @inferred vany(x->x>0, [4]) == true
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@test @inferred vany(x->x>0, [-3, 4, 5]) == true
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# @test @inferred vall(x->x>0, []) == true
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@test @inferred vall(x->x>0, Int[]) == true
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@test @inferred vall(x->x>0, [-3]) == false
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@test @inferred vall(x->x>0, [4]) == true
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@test @inferred vall(x->x>0, [-3, 4, 5]) == false
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let f(x) = ifelse(x == 1, true, ifelse(x == 2, false, 1))
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@test vany(Any[false,true,false])
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@test @inferred vany(map(f, [2,1,2]))
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@test @inferred vany([f(x) for x in [2,1,2]])
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@test vall(Any[true,true,true])
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@test @inferred vall(map(f, [1,1,1]))
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@test @inferred vall([f(x) for x in [1,1,1]])
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# @test_throws TypeError vany([1,true])
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# @test_throws TypeError vall([true,1])
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# @test_throws TypeError vany(map(f,[3,1]))
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# @test_throws TypeError vall(map(f,[1,3]))
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end
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@test vcount(x -> x > 0, Int[]) == vcount(Bool[]) == 0
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@test vtcount(x -> x > 0, Int[]) == vtcount(Bool[]) == 0
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@test vcount(x->x>0, -3:5) == vcount((-3:5) .> 0) == 5
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@test vcount([true, true, false, true]) == vcount(BitVector([true, true, false, true])) == 3
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x = repeat([false, true, false, true, true, false], 7)
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@test vcount(x) == 21
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@test_throws MethodError vcount(sqrt, [1])
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@test_throws MethodError vcount([1])
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@test vcount(!iszero, Int[]) == 0
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@test vcount(!iszero, Int[0]) == 0
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@test vcount(!iszero, Int[1]) == 1
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@test vcount(!iszero, [1, 0, 2, 0, 3, 0, 4]) == 4
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@test vvsum(Vector(map(UInt8,0:255))) == 32640
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@test vvsum(Vector(map(UInt8,254:255))) == 509
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# opposite behavior from base
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@test vvsum([-0.0]) === 0.0
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@test vvsum([-0.0, -0.0]) === 0.0
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# same as base
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@test vvprod([-0.0, -0.0]) === 0.0

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