I have three vectors x, a, b. I need a new vector Y which has as its k^{th} element the following sum: Y^{}_k = \sum_{i=1}^N x_i \ \mathbb{1}(a_i=a_k, b_i=b_k) i.e., the sum of x from all rows with the same values of a, b as the current row. Is there a more efficient way to implement this than the…

[image] gdalle: julia> N, V = 1000, 3; julia> a, b = rand(1:V, N), rand(1:V, N); If you only have a small number V of possible values of a and b, then you can do much better by first summing into a matrix indexed by values of V, because then the time complexity is \Theta(N) (with space compl…

I thought your code would be easy to optimize because the first line allocates a matrix of size n^2. My loop implementation is indeed faster in some cases, but slower in others, like the one below. Wonder what I’m doing wrong… julia> using BenchmarkTools julia> N, V = 1000, 3; julia> a, b = rand(…

How to compute a conditional sum of a vector efficiently

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How to compute a conditional sum of a vector efficiently

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