julia> x = manynth(Normal(0, 1), [1,2,3])
Mv{Vector{Int64}, Normal{Float64}}([1, 2, 3], Normal{Float64}(μ=0.0, σ=1.0))
julia> randsample(x)
3-element Vector{Float64}:
0.5329609997818248
0.6091868691905119
-1.1231586242100318
julia> x .== [3,4,5]
ERROR: MethodError: no method matching size(::Mv{Vector{Int64}, Normal{Float64}})
Closest candidates are:
size(::Union{LinearAlgebra.Adjoint{T, var"#s859"}, LinearAlgebra.Transpose{T, var"#s859"}} where {T, var"#s859"<:(AbstractVector)}) at /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/LinearAlgebra/src/adjtrans.jl:172
size(::Union{LinearAlgebra.Adjoint{T, var"#s859"}, LinearAlgebra.Transpose{T, var"#s859"}} where {T, var"#s859"<:(AbstractMatrix)}) at /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/LinearAlgebra/src/adjtrans.jl:173
size(::Union{LinearAlgebra.QR, LinearAlgebra.QRCompactWY, LinearAlgebra.QRPivoted}) at /Applications/Julia-1.7.app/Contents/Resources/julia/share/julia/stdlib/v1.7/LinearAlgebra/src/qr.jl:567
...
Stacktrace:
[1] axes
@ ./abstractarray.jl:95 [inlined]
[2] combine_axes
@ ./broadcast.jl:499 [inlined]
[3] instantiate
@ ./broadcast.jl:281 [inlined]
[4] materialize(bc::Base.Broadcast.Broadcasted{Base.Broadcast.Unknown, Nothing, typeof(==), Tuple{Mv{Vector{Int64}, Normal{Float64}}, Vector{Int64}}})
@ Base.Broadcast ./broadcast.jl:860
[5] top-level scope
@ REPL[29]:1
The issue is that the array is hijacking the broadcasting behavior
The issue is that the array is hijacking the broadcasting behavior