using LinearAlgebra

"Sum over array while minimizing catastrophic cancellation as much as possible"
function better_sum(arr::Array{Float64})
    pos_arr = arr[arr .> 0]
    neg_arr = arr[arr .< 0]

    sort!(pos_arr)
    sort!(neg_arr, rev=true)

    return sum(pos_arr) + sum(neg_arr)
end

better_sum(arr::Array{ComplexF64}) = better_sum(real.(arr)) + 1im * better_sum(imag.(arr))

"The triangle inequality for angular momenta"
triangle_ineq(l1, l2, L) = abs(l1 - l2) ≤ L && L ≤ (l1 + l2)

"Index of the nearest value in a list to a given reference point"
nearestIndex(list::Array, ref) = argmin(norm.(list .- ref))

"Nearest value in a list to a given reference point"
nearest(list::Array, ref) = list[nearestIndex(list, ref)]

"Simple implementation of the Kronecker sum"
function kron_sum(A::AbstractMatrix, B::AbstractMatrix)
    @assert size(A, 1) == size(A, 2) && size(B, 1) == size(B, 2) "Matrices should be square"
    return kron(A, I(size(B, 1))) + kron(I(size(A, 1)), B)
end

"Flattened vector version of Iterators.product(...) with index hierachy reversed -- leftmost index has the highest hierachy"
iter_prod(args...) = reverse.(collect(Iterators.product(reverse(args)...))[:])