Oh, yeah. I forgot that .+, .-, etc are not along for the ride yet. I
understand it is pretty much ready for inclusion in 0.6.
There is also a one extra allocation, namely y.', which would not be
necessary in a loop. But this is hardly worse than numpy, right?
On Tuesday, September 13, 2016
So you're saying that abs2.(x .- y.') will not allocate a 2d array and then
pass to abs2? That's great! But how would I know that?
DNF wrote:
> For your particular example, it looks like what you want is (and I am just
> guessing what mag_sqr means):
> dist = abs2.(x .- y.')
> The performance
For your particular example, it looks like what you want is (and I am just
guessing what mag_sqr means):
dist = abs2.(x .- y.')
The performance should be the similar to a hand-written loop on version 0.5.
You can read about it here:
I use a simple function for this:
function newdim(A::AbstractArray, d::Integer)
@assert 0 < d <= ndims(A)+1
dim = size(A)
reshape(A, dim[1:d-1]..., 1, dim[d:end]...)
end
But having syntax for a newaxis would be great. See also:
https://github.com/JuliaLang/julia/issues/5405
*julia> a = rand(3)*
*3-element Array{Float64,1}:*
*0.47428 *
*0.505429*
*0.198919*
*julia> reshape(a, (3,1))*
*3×1 Array{Float64,2}:*
*0.47428 *
*0.505429*
*0.198919*
*julia> reshape(a, (1,3))*
*1×3 Array{Float64,2}:*
*0.47428 0.505429 0.198919*
Is that what you want? (Note that
I haven't studied it, but I guess that newaxis increases the dimensionality,
while specifying 0 for the stride. Can reshape do that?
Tim Holy wrote:
> I'm not certain I understand what `np.newaxis` does, but doesn't `reshape`
> do the same thing? (newaxis does look like a convenient way to
It's pretty close. In Julia 0.5, we have all the parts that are required to
make this a possibility. We have index types that specify both how many
indices in the source array should be consumed (CartesianIndex{N} spans N
dimensions) and types that determine what the dimensionality of the
