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| TF_actual = Core.Compiler.return_type(Fsymbol, NTuple{6, I}) | ||
| TF_imposed = FusionStyle(I) isa MultiplicityFreeFusion ? Ftype : Array{Ftype, 4} # won't work for sparse arrays (CategoryData) | ||
| @test TF_actual == TF_imposed |
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I don't think this is really what I had in mind, the TF_actual should simply be scalartype(Fsymbol(...)) for concrete values, while the TF_imposed is fusionscalartype(I).
We indeed do not want to put restrictions on the type of object that is output by Fsymbol.
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But this is already being tested in
TensorKitSectors.jl/test/sectors.jl
Lines 19 to 22 in fa3956f
Though I do agree that testing types is not good
| @test size(Fsymbol(a, b, c, d, e, f)) == F_size | ||
| end | ||
| end | ||
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We may also consider adding tests for invalid fusion channels, as I think this would be easier to have uncaught errors in
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This is tied together to a test suite that works for multifusion and fusion categories together, which remains difficult to realise 🫠 but I can differ between SimpleUnit and GenericUnit for this specific test easily if wanted
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Tackles #60. As left as comment, CategoryData stores the
GenericFusiontopological data as sparse arrays, so this will fail. Not sure if it's sufficient to just check whether everything's a subtype ofAbstractArray{T, N}?I also had some fusion ring checks lying around and decided to add them. It might be overkill, since it'll be a bunch of
0=0or1=1equations 🫠