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

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

E_max = 40
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())

basis = ho_basis_2B(E_max, Λ)
l_max = max(maximum(basis.l1s), maximum(basis.l2s))
n_max = max(maximum(basis.n1s), maximum(basis.n2s))

println("Basis size = ", basis.dim)

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

@time "Va" Va = get_jacobi_V_matrix(Va_of_r, basis, μ1ω1, μω_global)
@time "Vb" Vb = get_jacobi_V_matrix(Vb_of_r, basis, μ1ω1, μω_global)

@time "Ha" Ha = T1 + T2 + Va
@time "Eigenvalues" target_evals, _ = eigs(Ha, nev=5, ncv=50, which=:LI, maxiter=5000, tol=1e-5, ritzvec=false, check=1)

display(target_evals)

# free memory
basis = T1 = T2 = V1_cache = V_relative_cache = V1 = V_relative = U = V2 = nothing
GC.gc()

current_E = -0.72763

training_c = [2.0, 1.9, 1.8]
extrapolating_c = 0.0 : 0.2 : 1.2

exact = ComplexF64[]
training = ComplexF64[]
extrapolated = ComplexF64[]
training_vecs = Vector{ComplexF64}[]

for c in training_c
    println("Training for c = $c")
    H = Ha + c .* Vb
    evals, evecs = eigs(H, nev=3, ncv=24, which=:LI, maxiter=5000, tol=1e-5, ritzvec=true, check=1)

    global current_E = nearest(evals, current_E)
    push!(training, current_E)
    push!(training_vecs, evecs[:, nearestIndex(evals, current_E)])
end

# CA-EC
training_vecs = vcat(training_vecs, conj(training_vecs))

EC_basis = hcat(training_vecs...)
N_EC = transpose(EC_basis) * EC_basis
Ha_EC = transpose(EC_basis) * Ha * EC_basis
Vb_EC = transpose(EC_basis) * Vb * EC_basis

current_E = 4.0766890719636635 - 0.01275892774109674im

for c in extrapolating_c
    println("Extrapolating for c = $c")
    H = Ha + c .* Vb
    evals, evecs = eigs(H, nev=3, ncv=24, which=:LI, maxiter=5000, tol=1e-5, ritzvec=true, check=1)

    global current_E = nearest(evals, current_E)
    push!(exact, current_E)

    # extrapolation
    H_EC = Ha_EC + c .* Vb_EC
    evals = eigvals(H_EC, N_EC)
    push!(extrapolated, nearest(evals, current_E))
end

exportCSV("temp/HO_B2R.csv", (training, exact, extrapolated), ("training", "exact", "extrapolated"))

scatter(real.(training),imag.(training), label="training")
scatter!(real.(exact),imag.(exact), label="exact")
scatter!(real.(extrapolated),imag.(extrapolated), label="extrapolated")
savefig("temp/HO_B2R.pdf")