I have this matlab code I want to convert it to julia, but there is no sub2ind in julia. Does anyone have any ideia how i can translate it? ‘’’ for c = 1:num_channels l1_c = sub2ind(size(SAT), row_indices, l_idx, repmat(c, h, w)); u0_c = sub2ind(size(SAT), row_indices, u_idx, repmat(c, h, w)); l0_c = sub2ind(size(SAT), row_indices, l_idx - 1, repmat(c, h, w)); u1_c = sub2ind(size(SAT), row_indices, u_idx + 1, repmat(c, h, w)); l1 = sub2ind(size(SAT), row_indices, l_idx); u0 = sub2ind(size(SAT), row_indices, u_idx); l0 = sub2ind(size(SAT), row_indices, l_idx - 1); u1 = sub2ind(size(SAT), row_indices, u_idx + 1); % Full (center) areas. C = SAT(u0_c) - SAT(l1_c); % Left fractional areas. alpha = (l_pos - xform_domain_position(l0)) ./ (xform_domain_position(l1) - xform_domain_position(l0)); yi = I(l0_c) + alpha .* ( I(l1_c) - I(l0_c) ); L = 0.5 .* (yi + I(l1_c)) .* (1-alpha) .* (xform_domain_position(l1) - xform_domain_position(l0)); % Right fractional areas. alpha = (u_pos - xform_domain_position(u0)) ./ (xform_domain_position(u1) - xform_domain_position(u0)); yi = I(u0_c) + alpha .* ( I(u1_c) - I(u0_c) ); R = 0.5 .* (yi + I(u0_c)) .* (alpha) .* (xform_domain_position(u1) - xform_domain_position(u0)); F(:,:,c) = (L + C + R) / (2 * box_radius); end ‘’’

[image] PSA: replacement of ind2sub/sub2ind in Julia 0.7+ General Usage I’ve now seen a couple of cases where folks seem unhappy about the removal of the functions ind2sub and sub2ind. Some of the concerns may stem from the suggested replacement in the deprecation warning, as the replacement, while “safe,” seems considerably more awkward. This is a short post explaining their replacements and the motivation for the change; once you learn to think in the new way, I’d be surprised if you don’t become a fan of the new approach. In older versions of Julia, the way to c…

Could you give an example of one line of my code using this solution? I really could not implemented it, really new to Julia.

We could give you a better answer if you gave us an executable example. I have no idea what most of the variables above look like. julia> SAT_SIZE = (2,3,5) (2, 3, 5) julia> SAT = reshape(1:prod(SAT_SIZE), SAT_SIZE); julia> linidx = LinearIndices(size(SAT)); julia> linidx[2,3,5] 30 julia> linidx[1,2,4] 21 julia> linidx[1:2, 2:3, 4:5] 2×2×2 Array{Int64, 3}: [:, :, 1] = 21 23 22 24 [:, :, 2] = 27 29 28 30

I came from Scilab where also ind2sub/sub2ind was used. For my uses, I converted that as follows: dims = (10,10,10) # example lindex = LinearIndices((dims[1],dims[2],dims[3])) grid = CartesianIndices((1:dims[1],1:dims[2],1:dims[3]))[lindex] gridx = getindex.(grid,1) gridy = getindex.(grid,2) gridz = getindex.(grid,3) Here lindex can be any linear index you already have into a matrix. To get linear indices from x,y,z locations, julia> grid[50] CartesianIndex(10, 5, 1) julia> lindex[grid[50]] 50 julia> lindex[grid[1:10,5,1]] 10-element Vector{Int64}: 41 42 43 ⋮ 49 50

If you are in a pinch, you can just use the following. julia> function sub2ind(sz, args...) linidx = LinearIndices(sz) getindex.([linidx], args...) end sub2ind (generic function with 1 method) julia> row = [1 2 3 1]; julia> col = [2 2 2 3]; julia> sub2ind((3,3), row, col) 1×4 Matrix{Int64}: 4 5 6 7 julia> I1 = [1 2 1 2]; julia> I2 = [2 2 1 1]; julia> I3 = [1 1 2 2]; julia> sub2ind((2,2,2), I1, I2, I3) 1×4 Matrix{Int64}: 3 4 5 6 julia> sub2ind((3,4,2), 2,1,2) 1-element Vector{Int64}: 14

Looking at your example, it appears that you don’t need a linear index explicitly, but rather the ability to index an array at arbitrary combinations of coordinates. In Julia, CartesianIndex is a great tool for this. For example, I would use l0 = @. CartesianIndex(row_indices, l_idx - 1) (note the @., which makes this equivalent to l0 = CartesianIndex.(row_indices, l_idx .- 1)). Then using these indices is as simple as xform_domain_position[l0].

Sub2ind on julia

New to Julia

Mattriks February 4, 2024, 11:56pm 2

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Sub2ind on julia

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