The first one seems intended behaviour, is the second one a bug? julia> rand(3, 3) * [1.0, missing, missing] 3-element Array{Union{Missing, Float64},1}: missing missing missing julia> rand(3, 3) * [1.0f0, missing, missing] 3-element Array{Any,1}: missing missing missing I would expect the s…

The bug appears to have been fixed on master, please check with 1.1.

Rand by default is Float64. Using Float32 gets what you want: julia> rand(Float32, 3, 3) * [1.0f0, missing, missing] 3-element Array{Union{Missing, Float32},1}: missing missing missing Although I’m not sure why that results in Any when you multiply Float32 and Float64. Edit: seems like any co…

[image] Raf: Edit: seems like any combination of two numbers and missing in an array multiplication gives any. julia> [2, 3] * [1.0 missing] 2×2 Array{Any,2}: 2.0 missing 3.0 missing This seems odd, especially because julia> promote_type(Union{Missing, Float32}, Union{Missing, Float64}) …

Especially when: julia> [2, 3] .* [1.0 missing] 2×2 Array{Union{Missing, Float64},2}: 2.0 missing 3.0 missing Edit: with float not all ints!

Yes, is fixed in Julia 1.1, is there going to be a fix for 1.0?

Isn’t 1.0 supposed to be a long term support version?

Yes, but changing return types can break someones code.

Note that there is no commitment to backporting every bug fix (see the “Long term support” part): [image] Proposed release process and schedule Internals & Design Now that we’ve released Julia 1.0 and are close to 1.0.1 and have added some new features and min…

For my usecase, I fixed it with y = mul!(similar(x), A, x) this is not generalizable, but works for my use case.

Typestability in matrix multiplication, intended behaviour or bug?

General Usage

Tamas_Papp January 24, 2019, 7:59am 10

Note that there is no commitment to backporting every bug fix (see the “Long term support” part):

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Typestability in matrix multiplication, intended behaviour or bug?

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