# -*- coding: utf-8 -*-
"""
Created on Wed Oct  6 16:40:32 2021

@author: Nico
"""
import numpy as np
import matplotlib.pyplot as plt


def GetTemp(Gamma, Det, kb=1.38e-23, hbar=1.03e-34):
    T = (1/4)*(hbar/kb)*Gamma*((Gamma/(-2*Det)) + (-2*Det/Gamma))
    return np.abs(T*1e3)

GammaUV = 2*np.pi*22.4e6

Det = 2*np.pi*np.arange(1e6, 50e6, 0.1e6)

plt.figure()
plt.plot(Det/GammaUV, GetTemp(GammaUV, Det))
plt.axvline(0.5, linestyle='--', linewidth=1)
plt.xlabel('Detuning/Gamma')
plt.ylabel('Final Temp (mK)')

MinTemp = np.min(GetTemp(GammaUV, Det))

print(f'Min temp: {MinTemp} mK')

#%%

from scipy.special import jv
from scipy.optimize import curve_fit

def Lorentzian(f, A, gamma, x0):
    return (A/np.pi)*0.5*gamma/(((f-x0)**2)+((0.5*gamma)**2))

def MicromotionSpectra(det, ftrap, gamma, beta, n):
    P = (jv(0, beta)**2)/((det**2)+(0.5*gamma)**2)
    i = 1
    #print(P)
    while i <= n:
        P = P + ((jv(n, beta))**2)/(((det+n*ftrap)**2)+(0.5*gamma)**2) + ((jv(-n, beta))**2)/(((det-n*ftrap)**2)+(0.5*gamma)**2) 
        i = i + 1
        #print(P)
    return P

Det = np.arange(-50, 50, 0.1)

ftrap = 21
gamma = 22
beta = np.arange(0, 2, 0.05)
n = 1

anchos = []

for b in beta:
    Micromotion = MicromotionSpectra(Det, ftrap, gamma, b, n)
    popt, pcov = curve_fit(Lorentzian, Det, Micromotion)
    anchos.append(popt[1])
    
plt.figure()
plt.plot(beta, anchos, 'o')
plt.xlabel('Micromotion index beta')
plt.ylabel('Apparent linewidth(MHz)')
plt.axhline(22, linewidth=1, linestyle='--')
plt.grid()

#%%
    
#chosenbeta = 1.25

plt.figure()
for chosenbeta in [0, 1, 1.25, 2]:
    plt.plot(Det, MicromotionSpectra(Det, ftrap, gamma, chosenbeta, n), label=f'beta={chosenbeta}')
#plt.ylim(0, 0.005)
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Fluorescencia')
plt.grid()
plt.legend()