I have arrays with 2 dimensions. Elements in the arrays are only considered valid for certain values on the indices. For example, consider the arrays A and B below: A = round.(rand(10, 2) .* 100) A[1:3, 2] .= NaN B = round.(rand(10, 2) .* 100) B[1:3, 2] .= NaN If it helps, you can think of the arr…

Try also Cartesian Indices: CI = filter(x -> x ∉ CartesianIndices((1:3,2:2)), CartesianIndices(A)) s = sum(A[I]*B[I] for I in CI)

julia> sum(x -> isnan(x) ? zero(x) : x, A[i]*B[i] for i in eachindex(A)) 65709.0 julia> C = A .* B; sum(@view C[:,1]) + sum(@view C[4:end, 2]) 65709.0

The Missing type is useful for denoting missing data. Example: A = [a ∈ 1:3 && e == 2 ? missing : 100*rand() for a = 1:10, e = 1:2] B = [a ∈ 1:3 && e == 2 ? missing : 100*rand() for a = 1:10, e = 1:2] sum(skipmissing(A .* B))

How can I build the indices on determined sizes of arrays? For example, I defined A above to be 10-by-2, if I have variables like x = 10, y = 2, how can I build CI using those instead?

[image] amrods: if I have variables like x = 10, y = 2 , how can I build CI using those instead? Not sure if this is what you ask for: CI = filter(x -> x ∉ CartesianIndices((1:3,2:2)), CartesianIndices((1:x,1:y)))

Can I use that CartesianIndices object to iterate inside a sum? something like sum(a*e for (a, e) in CI) is it possible?

got it working like this: sum( *(Tuple(i)...) for i in CI)

Not on the computer, but this doesn’t work? sum(c[1]*c[2] for c in CI)

It does! I didn’t think about that way.

How can I streamline this? using StatsBase L = rand(2, 9, 2, 2, 5) idx0 = sample(0:1, ProbabilityWeights([0.4, 0.6]), size(L)) L .= L .* idx0 skipzeros = filter(x -> x ∉ findall(L .== 0), CartesianIndices((1:2, 1:9, 1:2, 1:2, 1:5))) gaek = ones((2, 9, 2, 5)) for idx in skipzeros g, a, e, _,…

How can I easily skip indices in an array?

General Usage

rafael.guerra October 25, 2021, 11:25pm 8

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How can I easily skip indices in an array?

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