170 lines
6.6 KiB
Julia
170 lines
6.6 KiB
Julia
# This file is a part of Julia. License is MIT: https://julialang.org/license
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using Base.Test
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srand(123)
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@testset "basic functions" begin
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@test I[1,1] == 1 # getindex
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@test I[1,2] == 0 # getindex
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@test I === I' # transpose
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@test ndims(I) == 2
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@test one(UniformScaling{Float32}) == UniformScaling(one(Float32))
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@test zero(UniformScaling{Float32}) == UniformScaling(zero(Float32))
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@test eltype(one(UniformScaling{Float32})) == Float32
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@test zero(UniformScaling(rand(Complex128))) == zero(UniformScaling{Complex128})
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@test one(UniformScaling(rand(Complex128))) == one(UniformScaling{Complex128})
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@test eltype(one(UniformScaling(rand(Complex128)))) == Complex128
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@test -one(UniformScaling(2)) == UniformScaling(-1)
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@test sparse(3I,4,5) == spdiagm(fill(3,4),0,4,5)
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@test sparse(3I,5,4) == spdiagm(fill(3,4),0,5,4)
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end
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@testset "istriu, istril, issymmetric, ishermitian, isapprox" begin
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@test istriu(I)
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@test istril(I)
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@test issymmetric(I)
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@test issymmetric(UniformScaling(complex(1.0,1.0)))
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@test ishermitian(I)
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@test !ishermitian(UniformScaling(complex(1.0,1.0)))
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@test UniformScaling(4.00000000000001) ≈ UniformScaling(4.0)
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@test UniformScaling(4.32) ≈ UniformScaling(4.3) rtol=0.1 atol=0.01
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end
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@testset "* and / with number" begin
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α = randn()
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@test α .* UniformScaling(1.0) == UniformScaling(1.0) .* α
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@test UniformScaling(α)./α == UniformScaling(1.0)
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end
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@test copy(UniformScaling(one(Float64))) == UniformScaling(one(Float64))
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@test sprint(show,UniformScaling(one(Complex128))) == "UniformScaling{Complex{Float64}}\n(1.0 + 0.0im)*I"
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@test sprint(show,UniformScaling(one(Float32))) == "UniformScaling{Float32}\n1.0*I"
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λ = complex(randn(),randn())
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J = UniformScaling(λ)
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@testset "transpose, conj, inv" begin
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@test ndims(J) == 2
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@test transpose(J) == J
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@test J*eye(2) == conj(J'eye(2)) # ctranpose (and A(c)_mul_B)
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@test I + I === UniformScaling(2) # +
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@test inv(I) == I
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@test inv(J) == UniformScaling(inv(λ))
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@test cond(I) == 1
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@test cond(J) == (λ ≠ zero(λ) ? one(real(λ)) : oftype(real(λ), Inf))
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end
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B = bitrand(2,2)
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@test B + I == B + eye(B)
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@test I + B == B + eye(B)
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@testset "binary ops with matrices" begin
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let AA = randn(2, 2)
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for SS in (sprandn(3,3, 0.5), speye(Int, 3))
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@testset for atype in ("Array", "SubArray")
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if atype == "Array"
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A = AA
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S = SS
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else
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A = view(AA, 1:2, 1:2)
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S = view(SS, 1:3, 1:3)
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end
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@test @inferred(A + I) == A + eye(A)
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@test @inferred(I + A) == A + eye(A)
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@test @inferred(I - I) === UniformScaling(0)
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@test @inferred(B - I) == B - eye(B)
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@test @inferred(I - B) == eye(B) - B
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@test @inferred(A - I) == A - eye(A)
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@test @inferred(I - A) == eye(A) - A
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@test @inferred(I*J) === UniformScaling(λ)
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@test @inferred(B*J) == B*λ
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@test @inferred(J*B) == B*λ
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@test @inferred(I*A) !== A # Don't alias
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@test @inferred(I*S) !== S # Don't alias
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@test @inferred(A*I) !== A # Don't alias
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@test @inferred(S*I) !== S # Don't alias
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@test @inferred(S*J) == S*λ
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@test @inferred(J*S) == S*λ
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@test @inferred(A*J) == A*λ
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@test @inferred(J*A) == A*λ
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@test @inferred(J*ones(3)) == ones(3)*λ
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@test @inferred(λ*J) === UniformScaling(λ*J.λ)
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@test @inferred(J*λ) === UniformScaling(λ*J.λ)
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@test @inferred(J/I) === J
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@test @inferred(I/A) == inv(A)
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@test @inferred(A/I) == A
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@test @inferred(I/λ) === UniformScaling(1/λ)
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@test @inferred(I\J) === J
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if atype == "Array"
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T = LowerTriangular(randn(3,3))
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else
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T = LowerTriangular(view(randn(3,3), 1:3, 1:3))
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end
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@test @inferred(T + J) == full(T) + J
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@test @inferred(J + T) == J + full(T)
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@test @inferred(T - J) == full(T) - J
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@test @inferred(J - T) == J - full(T)
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@test @inferred(T\I) == inv(T)
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if atype == "Array"
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T = LinAlg.UnitLowerTriangular(randn(3,3))
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else
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T = LinAlg.UnitLowerTriangular(view(randn(3,3), 1:3, 1:3))
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end
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@test @inferred(T + J) == full(T) + J
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@test @inferred(J + T) == J + full(T)
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@test @inferred(T - J) == full(T) - J
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@test @inferred(J - T) == J - full(T)
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@test @inferred(T\I) == inv(T)
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if atype == "Array"
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T = UpperTriangular(randn(3,3))
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else
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T = UpperTriangular(view(randn(3,3), 1:3, 1:3))
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end
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@test @inferred(T + J) == full(T) + J
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@test @inferred(J + T) == J + full(T)
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@test @inferred(T - J) == full(T) - J
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@test @inferred(J - T) == J - full(T)
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@test @inferred(T\I) == inv(T)
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if atype == "Array"
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T = LinAlg.UnitUpperTriangular(randn(3,3))
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else
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T = LinAlg.UnitUpperTriangular(view(randn(3,3), 1:3, 1:3))
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end
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@test @inferred(T + J) == full(T) + J
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@test @inferred(J + T) == J + full(T)
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@test @inferred(T - J) == full(T) - J
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@test @inferred(J - T) == J - full(T)
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@test @inferred(T\I) == inv(T)
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@test @inferred(I\A) == A
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@test @inferred(A\I) == inv(A)
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@test @inferred(λ\I) === UniformScaling(1/λ)
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end
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end
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end
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end
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@testset "hcat and vcat" begin
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@test_throws ArgumentError hcat(I)
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@test_throws ArgumentError [I I]
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@test_throws ArgumentError vcat(I)
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@test_throws ArgumentError [I; I]
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@test_throws ArgumentError [I I; I]
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for T in (Matrix, SparseMatrixCSC)
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A = T(rand(3,4))
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B = T(rand(3,3))
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@test (hcat(A,2I))::T == hcat(A,2eye(3,3))
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@test (vcat(A,2I))::T == vcat(A,2eye(4,4))
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@test (hcat(I,3I,A,2I))::T == hcat(eye(3,3),3eye(3,3),A,2eye(3,3))
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@test (vcat(I,3I,A,2I))::T == vcat(eye(4,4),3eye(4,4),A,2eye(4,4))
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@test (hvcat((2,1,2),B,2I,I,3I,4I))::T ==
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hvcat((2,1,2),B,2eye(3,3),eye(6,6),3eye(3,3),4eye(3,3))
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end
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end
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