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

E_max = 10
ω = 1.0
Λ = 0
m = 1.0

Va = -5
Ra = sqrt(3)
Vb = 2
Rb = sqrt(10)

μ1 = m * 1/2
μ2 = m * 2/3
c1 = 1/sqrt(2)
c2 = sqrt(2)

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

Es, n1s, l1s, n2s, l2s = get_2p_basis(E_max)
println("Basis size = ", length(Es))

println("Constructing KE matrices")
@time "T1" T1 = sp_T_matrix(n1s, l1s; ω=ω, μ=c1^2 * μ1)
@time "T2" T2 = sp_T_matrix(n2s, l2s; ω=ω, μ=c2^2 * μ2)

println("Constructing PE matrices")
V_l(l, n1, n2) = Va * V_Gaussian(Ra, l, n1, n2; ω=ω) + Vb * V_Gaussian(Rb, l, n1, n2; ω=ω)
@time "V1" V1 = sp_V_matrix(V_l, n1s, l1s)
@time "V_relative" V_relative = V1 + sp_V_matrix(V_l, n2s, l2s)
@time "Moshinsky brackets" Moshinsky_mat = Moshinsky_transform(Es, n1s, l1s, n2s, l2s, Λ)
@time "V2 via transform" V2 = Moshinsky_mat * V_relative

println("Calculating spectrum")
@time "H" H = T1 + T2 + V1 + V2
@time "Eigenvalues" evals, _ = eigs(H, nev=5, which=:SM, maxiter=10000, tol=1e-6, ritzvec=false)

display(evals)