include("../../ho_basis.jl")
include("../../EC.jl")

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

ϕ = 0.1 # DOESN'T WORK WITHOUT ROTATION
μω_global = 0.5 * exp(-2im * ϕ)
E_max = 40

H0 = get_3b_H_matrix(jacobi, V_of_r, μω_global, E_max, Λ, m, true, true)

# Vp = perturbation to make the state artificially bound
Vp_of_r(r) = -exp(-(r/3)^2)
@time "Vp" Vp = get_3b_H_matrix(jacobi, Vp_of_r, μω_global, E_max, Λ, m, false, true)

training_ref = 2 + 0.5im

exact_E = [4.076642792419057-0.012998408352259658im,
    3.6129849325287-0.007397677539402868im,
    3.145212908643357-0.0038660337822150753im,	
    2.6729225739451596-0.0021090370393881063im,	
    2.196385760253282-0.0010430088245526555im,	
    1.7162659936896967-0.0004515351140200029,	
    1.2329926791785895-0.00017698044022813525im]

training_c = [0.6 - 0.16im] .+ 0.04 .* (randn(8) .+ 0.5im * randn(8))
extrapolating_c = 0.0 : 0.2 : 1.2

EC = affine_EC(H0, Vp)
train!(EC, training_c; ref_eval=training_ref, CAEC=false)
extrapolate!(EC, extrapolating_c; precalculated_exact_E=exact_E)

exportCSV(EC, "temp/3b_HO_XZ.csv")
plot(EC, "temp/3b_HO_XZ.pdf")