Hello,
On julia 0.5.0, Win64, StaticArrays 0.2.1:
I have 2 types defined as
using StaticArrays
immutable Node <: FieldVector{Float64}
x::Float64
y::Float64
z::Float64
end
immutable Point3 <: FieldVector{Float64}
x::Float64
y::Float64
z::Float64
end
and I’d like to do a vectorized math operation
p = Point3(1.0, 2.0, 3.0); n=Node(2.0, 4.0, 6.0)
d = n.-p
MethodError: no method matching similar_type(::Type{CST_Fields.Node}, ::Type{Float64})
Closest candidates are:
similar_type{SA<:StaticArrays.StaticArray{T,N},N,T}(::Union{SA<:StaticArrays.StaticArray{T,N},Type{SA<:StaticArrays.StaticArray}}, ::Type{T}, !Matched::Tuple{Vararg{Int64,N}}) at c:\Users\phlavenk\Documents\programs\juliadata\v0.5\StaticArrays\src\abstractarray.jl:58
...
in macro expansion at mapreduce.jl:24 [inlined]
in map at mapreduce.jl:17 [inlined]
in macro expansion at mapreduce.jl:246 [inlined]
in broadcast at mapreduce.jl:243 [inlined]
in ./(::CST_Fields.Node, ::CST_Fields.Point3) at arraymath.jl:13
...
Does anyone know, what to do for my types to behave well in the broadcast machinery?
That’s not one I’ve seen before.
Just this week I’ve been working on cleaning up similar_type
- it’s been completely overhauled. Could you please try to checkout the latest prerelease version by typing Pkg.checkout("StaticArrays", "ajf/nopure")
? And let me know if the problem is fixed.
(You can revert to the standard version of StaticArrays with Pkg.free("StaticArrays")
)
PS - in general you can control the output type of operations via creating your own definitions for the similar_type
function. There are brief instructions included with the new branch. Let me know if you need some more specifics.
OK, thank you for help. Hopefuly I understand.
So in my case it is not clear what should be the result type of the math operation. Now, I can get the desired behavior by my own definition
similar_type{SA <: Union{Point3, Vec3, Node}, ElType<:AbstractFloat}(::Type{SA}, s::Type{ElType}) = SVector{Size(SA), ElType)
I think there should be a fallback function that errors with better error message telling what to do.
Because there soon will be huge amount of people relying on this great package.
Thank you.
Petr
Hopefully the improvements in the above-mentioned branch will be available via Pkg.update()
sometime next week.