Creating a sparse matrix from find operation on dense matrix

General Usage
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3

Thanks for the lightning response and the slick one-liner!

Here’s a quick comparison of the hack I have been working with, your two approaches, and one i found here.

using BenchmarkTools, SparseArrays, Unzip
x = rand(1000,1000)
d = 0.01

@btime begin
    m = x .< d
    i,j, = findnz(m)
    xs = sparse(i ,j, view(x, m), size(x)...)
end
# 1.489 ms (38 allocations: 851.00 KiB)

@btime xs = sparse(x .* (x .< d))
# 2.482 ms (12 allocations: 7.79 MiB)

@btime begin
    CI = findall(x .< d)
    i, j = unzip(Tuple.(CI))
    xs = sparse(i, j, view(x, CI), size(x)...)
end
# 1.190 ms (45 allocations: 927.47 KiB)

@btime begin
    CI = findall(x .< d)
    CI′ = reinterpret(Int, reshape(CI, 1, :))
    xs = sparse(view(CI′, 1, :), view(CI′, 2, :), view(x, CI), size(x)...)
end
#  1.044 ms (40 allocations: 617.20 KiB)