Allow real and imag functions to return real TensorValue #1080
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Thanks for the PR @ovanvincq , this is good for me. v1 = VectorValue(1+1im)
v2 = VectorValue(1)
@test real(v1) == v2 && eltype(real(v1)) == eltype(v2)
@test imag(v1) == v2 && eltype(imag(v1)) == eltype(v2)
v2 = VectorValue(1-1im)
@test conj(v1) == v2 && eltype(conj(v1)) == eltype(v2)
v1 = VectorValue(1+1im, 1+1im)
v2 = VectorValue(1, 1)
@test real(v1) == v2 && eltype(real(v1)) == eltype(v2)
@test imag(v1) == v2 && eltype(imag(v1)) == eltype(v2)
v2 = VectorValue(1-1im, 1-1im)
@test conj(v1) == v2 && eltype(conj(v1)) == eltype(v2)
v1 = VectorValue(1+1im, 1+1im, 1+1im)
v2 = VectorValue(1, 1, 1)
@test real(v1) == v2 && eltype(real(v1)) == eltype(v2)
@test imag(v1) == v2 && eltype(imag(v1)) == eltype(v2)
v2 = VectorValue(1-1im, 1-1im, 1-1im)
@test conj(v1) == v2 && eltype(conj(v1)) == eltype(v2)
v1 = TensorValue(1+1im, 1+1im, 1+1im, 1+1im)
v2 = TensorValue(1, 1, 1, 1)
@test real(v1) == v2 && eltype(real(v1)) == eltype(v2)
@test imag(v1) == v2 && eltype(imag(v1)) == eltype(v2)
v2 = TensorValue(1-1im, 1-1im, 1-1im, 1-1im)
@test conj(v1) == v2 && eltype(conj(v1)) == eltype(v2)
v1 = SymTracelessTensorValue(1+1im, 1+1im)
v2 = SymTracelessTensorValue(1, 1)
@test real(v1) == v2 && eltype(real(v1)) == eltype(v2)
@test imag(v1) == v2 && eltype(imag(v1)) == eltype(v2)
v2 = SymTracelessTensorValue(1-1im, 1-1im)
@test conj(v1) == v2 && eltype(conj(v1)) == eltype(v2) |
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Are we sure that the changes to
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Oh true julia> my_eltype(op,r,a...) = typeof(reduce(op, zero.(eltype.(a))))
my_eltype (generic function with 1 method)
julia> my_eltype2(op,r,a,b) = typeof(op(zero(eltype(a)),zero(eltype(b))))
my_eltype2 (generic function with 2 methods)
julia> @code_typed my_eltype(+,(1-im,),(1.0-im),(1-im))
CodeInfo(
1 ─ %1 = Core.tuple(a)::Tuple{Tuple{ComplexF64, Complex{Int64}}}
....
│ %11 = Main.reduce(op, %10)::Any
│ %12 = Main.typeof(%11)::DataType # computed at runtime
└── return %12
) => DataType
julia> @code_typed my_eltype2(+,(1-im,),(1.0-im),(1-im))
CodeInfo(
1 ─ return ComplexF64
) => Type{ComplexF64} |
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Ok, I made the requested corrections. |
Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #1080 +/- ##
==========================================
- Coverage 89.06% 89.05% -0.02%
==========================================
Files 197 197
Lines 23927 23938 +11
==========================================
+ Hits 21310 21317 +7
- Misses 2617 2621 +4 ☔ View full report in Codecov by Sentry. |
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@ovanvincq can you add some coverage for the missing lines? It's not critical, but better than not have it. Also, could you add a description of the PR in the |
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@JordiManyer I added some tests for |
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This small PR allows the
realandimagfunctions to return real results like the base Julia functionsreturns