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Run CI on latest released 1.x version (#928)
* Run CI on latest released 1.x version * fix broken tests on v1.6+ * disable `svd` kwarg const-prop test on v1.6 and later * mark `svd` test as broken on v1.6 and later & swap between `@test` and `@test_broken` for `abstractarray.jl` tests
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6 files changed

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‎.github/workflows/ci.yml‎

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@@ -13,6 +13,7 @@ jobs:
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strategy:
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matrix:
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version:
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- '1'
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- '1.0'
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- '1.1'
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- '1.2'

‎test/abstractarray.jl‎

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@@ -185,19 +185,21 @@ using StaticArrays, Test, LinearAlgebra
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@test @inferred(convert(AbstractArray{Float64}, diag)) isa Diagonal{Float64,SVector{2,Float64}}
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@test convert(AbstractArray{Float64}, diag) == diag
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# The following cases currently convert the SMatrix into an MMatrix, because
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# the constructor in Base invokes `similar`, rather than `convert`, on the static array
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# the constructor in Base invokes `similar`, rather than `convert`, on the static
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# array. This was fixed in https://github.com/JuliaLang/julia/pull/40831; so should
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# work from Julia v1.8.0-DEV.55
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trans = Transpose(SVector(1,2))
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@test_broken @inferred(convert(AbstractArray{Float64}, trans)) isa Transpose{Float64,SVector{2,Float64}}
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@test_was_once_broken v"1.8.0-DEV.55" @inferred(convert(AbstractArray{Float64}, trans)) isa Transpose{Float64,SVector{2,Float64}}
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adj = Adjoint(SVector(1,2))
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@test_broken @inferred(convert(AbstractArray{Float64}, adj)) isa Adjoint{Float64,SVector{2,Float64}}
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@test_was_once_broken v"1.8.0-DEV.55" @inferred(convert(AbstractArray{Float64}, adj)) isa Adjoint{Float64,SVector{2,Float64}}
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uptri = UpperTriangular(SA[1 2; 0 3])
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@test_broken @inferred(convert(AbstractArray{Float64}, uptri)) isa UpperTriangular{Float64,SMatrix{2,2,Float64,4}}
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@test_was_once_broken v"1.8.0-DEV.55" @inferred(convert(AbstractArray{Float64}, uptri)) isa UpperTriangular{Float64,SMatrix{2,2,Float64,4}}
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lotri = LowerTriangular(SA[1 0; 2 3])
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@test_broken @inferred(convert(AbstractArray{Float64}, lotri)) isa LowerTriangular{Float64,SMatrix{2,2,Float64,4}}
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@test_was_once_broken v"1.8.0-DEV.55" @inferred(convert(AbstractArray{Float64}, lotri)) isa LowerTriangular{Float64,SMatrix{2,2,Float64,4}}
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unituptri = UnitUpperTriangular(SA[1 2; 0 1])
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@test_broken @inferred(convert(AbstractArray{Float64}, unituptri)) isa UnitUpperTriangular{Float64,SMatrix{2,2,Float64,4}}
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@test_was_once_broken v"1.8.0-DEV.55" @inferred(convert(AbstractArray{Float64}, unituptri)) isa UnitUpperTriangular{Float64,SMatrix{2,2,Float64,4}}
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unitlotri = UnitLowerTriangular(SA[1 0; 2 1])
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@test_broken @inferred(convert(AbstractArray{Float64}, unitlotri)) isa UnitLowerTriangular{Float64,SMatrix{2,2,Float64,4}}
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@test_was_once_broken v"1.8.0-DEV.55" @inferred(convert(AbstractArray{Float64}, unitlotri)) isa UnitLowerTriangular{Float64,SMatrix{2,2,Float64,4}}
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end
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end
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‎test/ambiguities.jl‎

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@@ -10,8 +10,8 @@ const allowable_ambiguities =
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0
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end
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if v"1.6.0-DEV.816" <= VERSION < v"1.6.0-rc"
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# Revisit in 1.6.0-rc1 or before. See
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if VERSION ≥ v"1.6.0"
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# TODO: Revisit and fix. See
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# https://github.com/JuliaLang/julia/pull/36962
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# https://github.com/JuliaLang/julia/issues/36951
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@test_broken length(detect_ambiguities(#=LinearAlgebra, =#StaticArrays)) <= allowable_ambiguities

‎test/arraymath.jl‎

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@@ -86,9 +86,27 @@ import StaticArrays.arithmetic_closure
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@test (t-t) isa T
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@test (t*t) isa T
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@test (t/t) isa T
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end
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if isbitstype(T0)
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@test @allocated(arithmetic_closure(T0)) == 0
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end
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@testset "arithmetic_closure allocation" begin
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# a little icky, but `@allocated` seems to be too fragile to use in a loop with
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# types assigned in variables (see #924); so we write out a test explicitly for
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# every `isbitstype` type of interest
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@test (@allocated arithmetic_closure(UInt128)) == 0
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@test (@allocated arithmetic_closure(UInt16)) == 0
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@test (@allocated arithmetic_closure(UInt32)) == 0
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@test (@allocated arithmetic_closure(UInt64)) == 0
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@test (@allocated arithmetic_closure(UInt8)) == 0
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@test (@allocated arithmetic_closure(Int128)) == 0
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@test (@allocated arithmetic_closure(Int16)) == 0
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@test (@allocated arithmetic_closure(Int32)) == 0
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@test (@allocated arithmetic_closure(Int64)) == 0
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@test (@allocated arithmetic_closure(Int8)) == 0
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@test (@allocated arithmetic_closure(Float16)) == 0
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@test (@allocated arithmetic_closure(Float32)) == 0
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@test (@allocated arithmetic_closure(Float64)) == 0
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@test (@allocated arithmetic_closure(Bool)) == 0
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@test (@allocated arithmetic_closure(Complex{Int64})) == 0
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@test (@allocated arithmetic_closure(ComplexF64)) == 0
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end
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end

‎test/svd.jl‎

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@@ -71,13 +71,18 @@ using StaticArrays, Test, LinearAlgebra
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@testinf svd(m_sing2'; full=Val(true)) \ v2 ≈ svd(Matrix(m_sing2'); full=true) \ Vector(v2)
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@testinf svd(m_sing2; full=Val(true)) \ m23' ≈ svd(Matrix(m_sing2); full=true) \ Matrix(m23')
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@testinf svd(m_sing2'; full=Val(true)) \ m23 ≈ svd(Matrix(m_sing2'); full=true) \ Matrix(m23)
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if VERSION >= v"1.5-DEV"
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if VERSION >= v"1.5"
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# Test that svd of rectangular matrix is inferred.
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# Note the placement of @inferred brackets is important.
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#
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# This only seems to work on >= v"1.5" due to unknown compiler improvements.
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svd_full_false(A) = svd(m_sing2, full=false)
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@test @inferred(svd_full_false(m_sing2)).S ≈ svd(Matrix(m_sing2)).S
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# This only seems to work on v"1.5" due to unknown compiler improvements; seems
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# to have stopped working again on v"1.6" and later?
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svd_full_false(A) = svd(A, full=false)
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if VERSION < v"1.6"
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@test @inferred(svd_full_false(m_sing2)).S ≈ svd(Matrix(m_sing2)).S
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else
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@test_broken @inferred(svd_full_false(m_sing2)).S ≈ svd(Matrix(m_sing2)).S
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end
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end
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@testinf svd(mc_sing) \ v ≈ svd(Matrix(mc_sing)) \ Vector(v)

‎test/testutil.jl‎

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@@ -92,6 +92,23 @@ macro inferred_maybe_allow(allow, ex)
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end
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end
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"""
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@test_was_once_broken good_version ex
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Expands to `@test ex` if `VERSION ≥ good_version` and to `@test_broken ex` if
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`VERSION ≥ good_version`. Useful for tests that are broken on earlier versions of Julia
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that are fixed on later versions.
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"""
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macro test_was_once_broken(good_version, ex)
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esc(quote
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if VERSION < $good_version
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@test_broken $ex
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else
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@test $ex
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end
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end)
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end
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@testset "test utils" begin
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@testset "@testinf" begin
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@testinf [1,2] == [1,2]

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