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import h5py
import matplotlib.pyplot as plt
import numpy as np
import sys
import re
import ast
from scipy.optimize import curve_fit
import os
from scipy import interpolate
# Solo levanto algunos experimentos
Calib_Files = """000004167-UV_Scan_withcalib_Haeffner
000004168-UV_Scan_withcalib_Haeffner
000004186-UV_Scan_withcalib_Haeffner
000004187-UV_Scan_withcalib_Haeffner
000004188-UV_Scan_withcalib_Haeffner
000004228-UV_Scan_withcalib_Haeffner
000004229-UV_Scan_withcalib_Haeffner
000004230-UV_Scan_withcalib_Haeffner
000004231-UV_Scan_withcalib_Haeffner
000004232-UV_Scan_withcalib_Haeffner
000004233-UV_Scan_withcalib_Haeffner"""
#carpeta pc nico labo escritorio:
#C:\Users\Usuario\Documents\artiq\artiq_experiments\analisis\plots\20211006_EspectrosUV_FixedScript\Data
def SeeKeys(files):
for i, fname in enumerate(files.split()):
data = h5py.File(fname+'.h5', 'r') # Leo el h5: Recordar que nuestros datos estan en 'datasets'
print(fname)
print(list(data['datasets'].keys()))
#%%
Amps = []
Freqs = []
Counts = []
for i, fname in enumerate(Calib_Files.split()):
print(SeeKeys(Calib_Files))
print(i)
print(fname)
data = h5py.File(fname+'.h5', 'r') # Leo el h5: Recordar que nuestros datos estan en 'datasets'
print(list(data['datasets'].keys()))
Amps.append(np.array(data['datasets']['UV_Amplitudes']))
Freqs.append(np.array(data['datasets']['UV_Frequencies']))
Counts.append(np.array(data['datasets']['counts_spectrum']))
#%%
def Lorentzian(f, A, gamma, x0):
return (A/np.pi)*0.5*gamma/(((f-x0)**2)+((0.5*gamma)**2)) + 5
j = 0 #UV_cooling en 100 MHz
UV_cooling = 100
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
popt, pcov = curve_fit(Lorentzian, FreqsChosen, CountsChosen)
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
plt.figure()
plt.plot(FreqsChosen, CountsChosen, 'o', label='2.4 uW')
plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
plt.axvline(2*UV_cooling, linestyle='--', linewidth=1)
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
print(f'Ancho medido: {round(popt[1])} MHz, cooling en {(popt[2]-2*UV_cooling)/23} det/gamma')
def Lorentzian(f, A, gamma, x0):
return (A/np.pi)*0.5*gamma/(((f-x0)**2)+((0.5*gamma)**2)) + 5
j = 1 #UV_cooling en 100 MHz
UV_cooling = 110
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
popt, pcov = curve_fit(Lorentzian, FreqsChosen, CountsChosen)
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
#plt.figure()
plt.plot(FreqsChosen, CountsChosen, 'o', label='2.4 uW')
plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
plt.axvline(2*UV_cooling, linestyle='--', linewidth=1)
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
print(f'Ancho medido: {round(popt[1])} MHz, cooling en {(popt[2]-2*UV_cooling)/23} det/gamma')
#%%
def Lorentzian(f, A, gamma, x0):
return (A/np.pi)*0.5*gamma/(((f-x0)**2)+((0.5*gamma)**2)) + 5
j = 2
UV_cooling = 100
Cool_every = 20
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
popt, pcov = curve_fit(Lorentzian, FreqsChosen, CountsChosen)
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
plt.figure()
plt.plot(FreqsChosen, CountsChosen, 'o', label='Cool_every 20')
plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
plt.axvline(2*UV_cooling, linestyle='--', linewidth=1)
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
print(f'Ancho medido: {round(popt[1])} MHz, cooling en {(popt[2]-2*UV_cooling)/23} det/gamma')
def Lorentzian(f, A, gamma, x0):
return (A/np.pi)*0.5*gamma/(((f-x0)**2)+((0.5*gamma)**2)) + 5
j = 3
UV_cooling = 100
Cool_every = 5
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
popt, pcov = curve_fit(Lorentzian, FreqsChosen, CountsChosen)
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
#plt.figure()
plt.plot(FreqsChosen, CountsChosen, 'o', label='Cool_every 5')
plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
plt.axvline(2*UV_cooling, linestyle='--', linewidth=1)
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
plt.legend()
print(f'Ancho medido: {round(popt[1])} MHz, cooling en {(popt[2]-2*UV_cooling)/23} det/gamma')
j = 4
UV_cooling = 100
Cool_every = 50
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
popt, pcov = curve_fit(Lorentzian, FreqsChosen, CountsChosen)
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
#plt.figure()
plt.plot(FreqsChosen, CountsChosen, 'o', label='Cool_every 50')
plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
plt.axvline(2*UV_cooling, linestyle='--', linewidth=1)
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
plt.legend()
print(f'Ancho medido: {round(popt[1])} MHz, cooling en {(popt[2]-2*UV_cooling)/23} det/gamma')
#%%
m = 6.6e-26
c = 3e8
T = 100e-6
kb=1.38e-23
hbar=1.03e-34
f0 = 755e12
fL = 22
fG = np.sqrt(8*kb*T*np.log(2)/(m*c*c))*f0*1e-6
print(fG)
"""
wl = 589e-9
T = 300
m2 = 3.5e-23
fG2 = 2*np.pi*(4*np.pi/wl)*np.sqrt(kb*T*2*np.log(2)/(m2))*1e-6
print(fG2)
"""
fV = 0.5*fL + np.sqrt((fL**2)/4 + fG**2)
print(fV)
#%% en teoria esto esta "bien compensado" con -1.21 V en dcB
j = 6
UV_cooling = 90
Cool_every = 20
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
lim = len(FreqsChosen)
popt, pcov = curve_fit(Lorentzian, FreqsChosen[0:lim], CountsChosen[0:lim])
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
plt.figure()
plt.plot(FreqsChosen, CountsChosen, 'o', label='dcB=-1.1 V')
#plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
#plt.axvline(2*UV_cooling, linestyle='--', linewidth=1)
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
plt.xlim(170, 270)
plt.grid()
plt.legend()
print(f'Ancho medido: {round(popt[1])} MHz, cooling en {(popt[2]-2*UV_cooling)/23} det/gamma')
j = 7
UV_cooling = 90
Cool_every = 20
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
lim = len(FreqsChosen)
popt, pcov = curve_fit(Lorentzian, FreqsChosen[0:lim], CountsChosen[0:lim])
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
#plt.figure()
plt.plot(FreqsChosen, CountsChosen, 'o', label='dcB=-1.16 V')
plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
#plt.axvline(2*UV_cooling, linestyle='--', linewidth=1)
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
plt.xlim(170, 270)
plt.grid()
plt.legend()
print(f'Ancho medido: {round(popt[1])} MHz, cooling en {(popt[2]-2*UV_cooling)/23} det/gamma')
j = 8
UV_cooling = 90
Cool_every = 20
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
lim = len(FreqsChosen)
popt, pcov = curve_fit(Lorentzian, FreqsChosen[0:lim], CountsChosen[0:lim])
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
#plt.figure()
plt.plot(FreqsChosen, CountsChosen, 'o', label='dcB=-1.20 V')
plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
#plt.axvline(2*UV_cooling, linestyle='--', linewidth=1)
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
plt.xlim(170, 270)
plt.grid()
plt.legend()
print(f'Ancho medido: {round(popt[1])} MHz, cooling en {(popt[2]-2*UV_cooling)/23} det/gamma')
"""
j = 5
UV_cooling = 90
Cool_every = 20
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
popt, pcov = curve_fit(Lorentzian, FreqsChosen, CountsChosen)
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
#plt.figure()
plt.plot(FreqsChosen, CountsChosen, 'o', label='dcB=-1.22 V')
plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
#plt.axvline(2*UV_cooling, linestyle='--', linewidth=1)
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
plt.xlim(170, 270)
plt.legend()
print(f'Ancho medido: {round(popt[1])} MHz, cooling en {(popt[2]-2*UV_cooling)/23} det/gamma')
#en teoria esto esta mal compensado poniendo -1.1 V en dcB
def Lorentzian(f, A, gamma, x0):
return (A/np.pi)*0.5*gamma/(((f-x0)**2)+((0.5*gamma)**2)) + 100
"""
j = 9
UV_cooling = 90
Cool_every = 20
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
lim = len(FreqsChosen)
popt, pcov = curve_fit(Lorentzian, FreqsChosen[0:lim], CountsChosen[0:lim])
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
#plt.figure()
plt.plot(FreqsChosen, CountsChosen, 'o', label='dcB=-1.24 V')
plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
#plt.axvline(2*UV_cooling, linestyle='--', linewidth=1)
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
plt.xlim(170, 270)
plt.grid()
plt.legend()
print(f'Ancho medido: {round(popt[1])} MHz, cooling en {(popt[2]-2*UV_cooling)/23} det/gamma')
j = 10
UV_cooling = 90
Cool_every = 20
FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
CountsChosen = Counts[j]
lim = len(FreqsChosen)
popt, pcov = curve_fit(Lorentzian, FreqsChosen[0:lim], CountsChosen[0:lim])
freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
#plt.figure()
plt.plot(FreqsChosen, CountsChosen, 'o', label='dcB=-1.26 V')
plt.plot(freqslong, Lorentzian(freqslong, *popt))
#plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
#plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
#plt.axvline(2*UV_cooling, linestyle='--', linewidth=1)
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('Cuentas')
plt.xlim(170, 270)
plt.grid()
plt.legend()
print(f'Ancho medido: {round(popt[1])} MHz, cooling en {(popt[2]-2*UV_cooling)/23} det/gamma')