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

E_max = 20
ω = 1.0
Λ = 0
m = 1.0

Va = -2
Ra = 2

μ1 = m * 1/2
μ2 = m * 2/3
c = sqrt(2)
c2 = 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=μ1)
@time "T2" T2 = sp_T_matrix(n2s, l2s; ω=ω, μ=c2^2 * μ2)

println("Constructing PE matrices")
V1_elem(l, n1, n2) = Va * V_Gaussian(Ra, l, n1, n2; ω=ω)
V_relative_elem(l, n1, n2) = Va * V_Gaussian(Ra / c, l, n1, n2; ω=ω)
@time "V1" V1 = sp_V_matrix(V1_elem, n1s, l1s)
@time "V relative" V_relative = sp_V_matrix(V_relative_elem, n1s, l1s) + sp_V_matrix(V_relative_elem, n2s, l2s)
@time "Moshinsky brackets" U = Moshinsky_transform(Es, n1s, l1s, n2s, l2s, Λ)
@time "V2" V2 =  U' * V_relative * U

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

display(evals)