Let’s assume that X
is a matrix. I want to efficiently compute sum(X.^2)
but without computing X.^2
which will allocate some memory for nothing. So I’m trying to do something like sum(^(2),X)
which throws a method error. I thought this could work because sum(>(0.2),X)
works for instance.
I know that I could easily create an auxillary function f(x)=x^2
and then compute sum(f,X)
. But it’s not the best in terms of readability. So my question is, is there a way to properly use ^(x, y)
to achieve my purpose?
Use an anonymous function.
sum(x -> x^2, X)
You could also do
sum(abs2, X)
which will handle both real- and complex-valued matrices, and should have the same performance as x->x^2
.
I use abs2 simply for ease in this type of situation
You can have a faster sum (not as safe as the default sum, which takes some care to not overflow things), using a parallel sum with @tturbo
:
julia> function mysum(f,x)
s = zero(eltype(f(x[begin])))
@tturbo for i in eachindex(x)
s += f(x[i])
end
return s
end
mysum (generic function with 2 methods)
julia> x = rand(1000,1000);
julia> @btime mysum(abs2,$x) # 4 threads (julia -t4)
83.500 μs (0 allocations: 0 bytes)
333115.0216837497
julia> #vs
@btime sum(abs2,$x)
327.982 μs (0 allocations: 0 bytes)
333115.0216837495
If that is within a peformance critical part of the code and the numbers are well behaved, it is a good alternative.
While the abs2
solution is good enough for this case, I think generalizing the ^(n)
would be a nice addition to Julia, the same as we do sqrt
.
Note that abs2
is actually different from x -> x^2
for complex numbers.
julia> X = rand(ComplexF64, 2, 2)
2×2 Matrix{ComplexF64}:
0.681033+0.323086im 0.756258+0.454746im
0.704345+0.603132im 0.0489073+0.595638im
julia> sum(X.^2)
0.5044940375620476 + 2.035762251252853im
julia> sum(abs2, X)
2.563956079161798
julia> sum(x -> x^2, X)
0.5044940375620476 + 2.035762251252853im
Yeah, that’s sort of what I meant by saying that it also handles complex values. But if the OP actually wants to sum squared complex values, my suggestion won’t fly.
what about LinearAlgerbra.norm
?
I don’t think you need eltype
here, btw.