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

Λ = 0
m = 1.0
Va = -2
Ra = 2

E_max = 40
μω_global = 0.3

# due to simple relative coordinates
μω = μω_global * 2
μ = m/2

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

@time "Basis" begin
    Es, n1s, l1s, n2s, l2s = get_2p_basis(E_max, Λ)
    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=μω, μ=μ)
@time "T2" T2 = get_sp_T_matrix(n2s, l2s; mask=mask2, μω_gen=μω, μ=μ)
@time "T_cross" T_cross = get_2p_p1p2_matrix(n1s, l1s, n2s, l2s, Λ, μω, μω) ./ (2*μ)

println("Constructing PE matrices")
V_elem(l, n1, n2) = Va * V_Gaussian(Ra, l, n1, n2; μω_gen=μω)
V_relative_elem(l, n1, n2) = Va * V_Gaussian(Ra, l, n1, n2; μω_gen=μω_global)
@time "V1" V1 = get_sp_V_matrix(V_elem, n1s, l1s; mask=mask1)
@time "V2" V2 = get_sp_V_matrix(V_elem, n2s, l2s; mask=mask2)
@time "V relative" V_relative = get_sp_V_matrix(V_relative_elem, n1s, l1s; mask=mask1)
@time "Moshinsky brackets" U = Moshinsky_transform(Es, n1s, l1s, n2s, l2s, Λ)
@time "V12" V12 =  U' * V_relative * U

println("Calculating spectrum")
@time "H" H = T1 + T2 + T_cross + V1 + V2 + V12
@time "Eigenvalues" evals, _ = eigs(H, nev=3, ncv=30, which=:SR, maxiter=5000, tol=1e-5, ritzvec=false, check=1)

display(evals)