using Arpack, SparseArrays, LRUCache
include("ho_basis.jl")

Λ = 0
m = 1.0
V_of_r(r) = 2 * exp(-(r-3)^2 / (1.5)^2)

E_max = 30
μω_global = 0.5 * exp(-2im * pi / 9)

# due to Jacobi coordinates
μ1ω1 = μω_global * 1/2
μ2ω2 = μω_global * 2
μ1 = m * 1/2
μ2 = m * 2/3

println("No of threads = ", Threads.nthreads())

@time "Basis" begin
    Es, n1s, l1s, n2s, l2s = get_2p_basis(E_max, Λ)
    l_max = max(maximum(l1s), maximum(l2s))
    n_max = max(maximum(n1s), maximum(n2s))
    mask1 = (n2s .== n2s') .&& (l2s .== l2s')
    mask2 = (n1s .== n1s') .&& (l1s .== l1s')
end

println("Basis size = ", length(Es))

println("Constructing KE matrices")

@time "T1" T1 = get_sp_T_matrix(n1s, l1s; mask=mask1, μω_gen=μ1ω1, μ=μ1)
@time "T2" T2 = get_sp_T_matrix(n2s, l2s; mask=mask2, μω_gen=μ2ω2, μ=μ2)

println("Constructing PE matrices")

@time "V" V = get_jacobi_V_matrix(V_of_r, E_max, Λ, μ1ω1, μω_global)

println("Calculating spectrum")
@time "H" H = T1 + T2 + V
@time "Eigenvalues" evals, _ = eigs(H, nev=5, ncv=50, which=:LI, maxiter=5000, tol=1e-5, ritzvec=false, check=1)

display(evals)