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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
"""
Primero tengo mediciones de espectros cpt de un ion variando la tension dc_A
"""
#C:\Users\Usuario\Documents\artiq\artiq_experiments\analisis\plots\20220106_CPT_DosLaseres_v08_TISA_DR\Data
os.chdir('/home/nico/Documents/artiq_experiments/analisis/plots/20231214_CPTconmicromocioncristals/Data/')
SINGLECPT_FILES = """000016453-IR_Scan_withcal_optimized
000016454-IR_Scan_withcal_optimized
000016455-IR_Scan_withcal_optimized
000016456-IR_Scan_withcal_optimized
000016457-IR_Scan_withcal_optimized
000016458-IR_Scan_withcal_optimized
000016459-IR_Scan_withcal_optimized
000016461-IR_Scan_withcal_optimized
"""
MULTICPT_FILES = """000016460-IR_Scan_withcal_optimized
000016462-IR_Scan_withcal_optimized
000016463-IR_Scan_withcal_optimized
000016464-IR_Scan_withcal_optimized
"""
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()))
#print(SeeKeys(MULTICPT_FILES))
#carpeta pc nico labo escritorio:
#C:\Users\Usuario\Documents\artiq\artiq_experiments\analisis\plots\20211101_CPT_DosLaseres_v03\Data
SingleCounts = []
SingleFreqs = []
MultiCounts = []
MultiFreqs = []
AmpTisa = []
UVCPTAmp = []
No_measures = []
Voltages = []
for i, fname in enumerate(MULTICPT_FILES.split()):
print(str(i) + ' - ' + fname)
#print(fname)
data = h5py.File('Multi/'+fname+'.h5', 'r') # Leo el h5: Recordar que nuestros datos estan en 'datasets'
# Aca hago algo repugnante para poder levantar los strings que dejamos
# que además tenian un error de tipeo al final. Esto no deberá ser necesario
# cuando se solucione el error este del guardado.
MultiFreqs.append(np.array(data['datasets']['IR1_Frequencies']))
MultiCounts.append(np.array(data['datasets']['data_array']))
#AmpTisa.append(np.array(data['datasets']['TISA_CPT_amp']))
UVCPTAmp.append(np.array(data['datasets']['UV_CPT_amp']))
No_measures.append(np.array(data['datasets']['no_measures']))
Voltages.append(np.array(data['datasets']['scanning_voltages']))
for i, fname in enumerate(SINGLECPT_FILES.split()):
print(str(i) + ' - ' + fname)
#print(fname)
data = h5py.File('Single/'+fname+'.h5', 'r') # Leo el h5: Recordar que nuestros datos estan en 'datasets'
SingleFreqs.append(np.array(data['datasets']['IR1_Frequencies']))
SingleCounts.append(np.array(data['datasets']['data_array']))
def Split(array,n):
length=len(array)/n
splitlist = []
jj = 0
while jj<length:
partial = []
ii = 0
while ii < n:
partial.append(array[jj*n+ii])
ii = ii + 1
splitlist.append(partial)
jj = jj + 1
return splitlist
CountsSplit = []
for kk in range(len(MultiCounts)):
CountsSplit.append(Split(MultiCounts[kk],len(MultiFreqs[kk])))
#%%
"""
Ploteo la cpt de referencia / plotting the reference CPT
"""
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plt.figure()
i = 0
for j in jvec:
plt.errorbar([2*f*1e-6 for f in SingleFreqs[j]], SingleCounts[j], yerr=np.sqrt(SingleCounts[j]), fmt='o', capsize=2, markersize=2)
i = i + 1
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('counts')
plt.grid()
#for dr in drs:
# plt.axvline(dr)
#plt.axvline(dr+drive)
plt.legend()
#%%
"""
Ploteo curvas de la multi1
meds:
0: dcA, 11 voltajes
1: dcA, 21 voltajes
2: compOven, 21 voltajes
3: dcA, 31 voltajes
"""
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kk=9
plt.figure()
i = 0
for j in jvec:
plt.errorbar([2*f*1e-6 for f in MultiFreqs[med]], CountsSplit[med][j], yerr=np.sqrt(CountsSplit[med][j]), fmt='o', capsize=2, markersize=2)
#plt.plot([2*f*1e-6 for f in MultiFreqs[med]][kk], CountsSplit[med][j][kk],'o',markersize=10)
i = i + 1
plt.xlabel('Frecuencia (MHz)')
plt.ylabel('counts')
plt.grid()
#for dr in drs:
# plt.axvline(dr)
#plt.axvline(dr+drive)
plt.legend()
print(CountsSplit[med][j][9])
print(CountsSplit[med][j][10])
print(CountsSplit[med][j][11])
print(CountsSplit[med][j][12])
#%%
from EITfit.lolo_modelo_full_8niveles import PerformExperiment_8levels_MM
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from scipy.optimize import curve_fit
import time
"""
MEDICION 1: ajusto una curva con dos iones con un modelo que considera solo uno
"""
phidoppler, titadoppler = 0, 90
phirepump, titarepump = 0, 0
phiprobe = 0
titaprobe = 90
Temp = 0.5e-3
sg = 0.544
sp = 4.5
sr = 0
DetRepump = 0
lw = 0.1
DopplerLaserLinewidth, RepumpLaserLinewidth, ProbeLaserLinewidth = lw, lw, lw #ancho de linea de los laseres
u = 32.5e6
#B = (u/(2*np.pi))/c
gPS, gPD, = 2*np.pi*21.58e6, 2*np.pi*1.35e6
alpha = 0
drivefreq = 2*np.pi*22.135*1e6
selectedcurve=0
FreqsDR = SingleFreqs[selectedcurve]
CountsDR = SingleCounts[selectedcurve]
freqslong = np.arange(min(FreqsDR), max(FreqsDR)+FreqsDR[1]-FreqsDR[0], 0.1*(FreqsDR[1]-FreqsDR[0]))
CircPr = 1
alpha = 0
def FitEIT_MM_1ion(Freqs, offset, DetDoppler, SG, SP, SCALE1, OFFSET, BETA1, TEMP, U, plot=False):
#def FitEIT_MM(freqs, SG, SP, SCALE1, OFFSET, BETA1):
#BETA = 1.8
# SG = 0.6
# SP = 8.1
# TEMP = 0.2e-3
Detunings, Fluorescence1 = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, U, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe, BETA1, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
ScaledFluo1 = np.array([f*SCALE1 + OFFSET for f in Fluorescence1])
if plot:
return ScaledFluo1, Detunings
else:
return ScaledFluo1
#return ScaledFluo1
do_fit = True
if do_fit:
popt_1, pcov_1 = curve_fit(FitEIT_MM_1ion, FreqsDR, CountsDR, p0=[430, -25, 0.9, 6.2, 3e4, 200, 2, (np.pi**2)*1e-3,32.5e6], bounds=((0, -50, 0, 0, 0, 0, 0, 0,30e6), (1000, 0, 2, 20, 5e6, 5e4, 10, (np.pi**2)*10e-3,35e6)))
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FittedEITpi_1_short, Detunings_1_short = FitEIT_MM_1ion(FreqsDR, *popt_1, plot=True)
freqslong = np.arange(min(FreqsDR), max(FreqsDR)+FreqsDR[1]-FreqsDR[0], 0.1*(FreqsDR[1]-FreqsDR[0]))
FittedEITpi_1_long, Detunings_1_long = FitEIT_MM_1ion(freqslong, *popt_1, plot=True)
plt.figure()
plt.errorbar(Detunings_1_short, CountsDR, yerr=2*np.sqrt(CountsDR), fmt='o', color='darkgreen', alpha=0.5, capsize=2, markersize=2)
plt.plot(Detunings_1_long, FittedEITpi_1_long, color='darkolivegreen', linewidth=3, label='med 1')
#plt.title(f'Sdop: {round(popt[0], 2)}, Spr: {round(popt[1], 2)}, T: {round(popt[2]*1e3, 2)} mK, detDop: {DetDoppler} MHz')
plt.xlabel('Detuning (MHz)')
plt.ylabel('Counts')
plt.legend(loc='upper left', fontsize=20)
plt.grid()
#%%
#from EITfit.MM_eightLevel_2repumps_AnalysisFunctions import PerformExperiment_8levels
from scipy.optimize import curve_fit
import time
"""
MEDICION 1: ahora la ajusto pero considerando contribucion de dos iones
"""
phidoppler, titadoppler = 0, 90
phirepump, titarepump = 0, 0
phiprobe = 0
titaprobe = 90
Temp = 0.5e-3
sg = 0.544
sp = 4.5
sr = 0
DetRepump = 0
lw = 0.1
DopplerLaserLinewidth, RepumpLaserLinewidth, ProbeLaserLinewidth = lw, lw, lw #ancho de linea de los laseres
u = 32.5e6
#B = (u/(2*np.pi))/c
gPS, gPD, = 2*np.pi*21.58e6, 2*np.pi*1.35e6
alpha = 0
drivefreq = 2*np.pi*22.135*1e6
selectedcurve=0
FreqsDR = SingleFreqs[selectedcurve]
CountsDR = SingleCounts[selectedcurve]
#freqslong = np.arange(min(FreqsDR)*0.2, max(FreqsDR)*2+FreqsDR[1]-FreqsDR[0], 0.1*(FreqsDR[1]-FreqsDR[0]))
CircPr = 1
alpha = 0
def FitEIT_MM_2ion(Freqs, offset, DetDoppler, SG, SP, SCALE1, SCALE2, BETA1, BETA2, TEMP, U, plot=False, plotsingles=False):
#def FitEIT_MM(freqs, SG, SP, SCALE1, OFFSET, BETA1):
#BETA = 1.8
# SG = 0.6
# SP = 8.1
# TEMP = 0.2e-3
freqs = [2*f*1e-6-offset for f in Freqs]
Detunings, Fluorescence1 = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, U, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe, BETA1, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
Detunings, Fluorescence2 = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, U, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe, BETA2, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
ScaledFluo1 = np.array([f*SCALE1 + 0.5*OFFSET1 for f in Fluorescence1])
ScaledFluo2 = np.array([f*SCALE2 + 0.5*OFFSET1 for f in Fluorescence2])
if plot:
return ScaledFluo1+ScaledFluo2, Detunings
if plotsingles:
return ScaledFluo1, ScaledFluo2, Detunings
else:
return ScaledFluo1+ScaledFluo2
#return ScaledFluo1
do_fit = True
if do_fit:
popt_1_2ion, pcov_1_2ion = curve_fit(FitEIT_MM_2ion, FreqsDR, CountsDR, p0=[445, -32, 0.5, 7, 2e4, 1e4, 2, 1, 0.5e-3, 32e6], bounds=((0, -50, 0, 0, 0, 0, 0,0, 0,30e6), (1000, 0, 2, 20, 5e6, 5e6, 10, 10,20e-3,35e6)))
FittedEITpi_1_short_2ion, Detunings_1_short_2ion = FitEIT_MM_2ion(FreqsDR, *popt_1_2ion, plot=True)
freqslong = np.arange(min(FreqsDR), max(FreqsDR)+FreqsDR[1]-FreqsDR[0], 0.1*(FreqsDR[1]-FreqsDR[0]))
FittedEITpi_1_long_2ion, Detunings_1_long_2ion = FitEIT_MM_2ion(freqslong, *popt_1_2ion, plot=True)
plot_singles=False
if plot_singles:
FittedEITpi_1_short_2ion_ion1, FittedEITpi_1_short_2ion_ion2, Detunings_1_short_2ion = FitEIT_MM_2ion(FreqsDR, *popt_1_2ion, plot=False, plotsingles=True)
plt.figure()
#plt.errorbar(Detunings_1_short_2ion, CountsDR, yerr=2*np.sqrt(CountsDR), fmt='o', color='darkgreen', alpha=0.5, capsize=2, markersize=2)
plt.plot(Detunings_1_short_2ion, FittedEITpi_1_short_2ion_ion1, color='darkolivegreen', linewidth=3, label='med 1')
plt.plot(Detunings_1_short_2ion, FittedEITpi_1_short_2ion_ion2, color='darkolivegreen', linewidth=3, label='med 1')
#plt.title(f'Sdop: {round(popt[0], 2)}, Spr: {round(popt[1], 2)}, T: {round(popt[2]*1e3, 2)} mK, detDop: {DetDoppler} MHz')
plt.xlabel('Detuning (MHz)')
plt.ylabel('Counts')
#plt.xlim(-80,50)
plt.legend(loc='upper left', fontsize=20)
plt.grid()
else:
plt.figure()
plt.errorbar(Detunings_1_short_2ion, CountsDR, yerr=2*np.sqrt(CountsDR), fmt='o', color='darkgreen', alpha=0.5, capsize=2, markersize=2)
plt.plot(Detunings_1_long_2ion, FittedEITpi_1_long_2ion, color='darkolivegreen', linewidth=3, label='med 1')
#plt.title(f'Sdop: {round(popt[0], 2)}, Spr: {round(popt[1], 2)}, T: {round(popt[2]*1e3, 2)} mK, detDop: {DetDoppler} MHz')
plt.xlabel('Detuning (MHz)')
plt.ylabel('Counts')
#plt.xlim(-80,50)
plt.legend(loc='upper left', fontsize=20)
plt.grid()
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#%%
#from EITfit.MM_eightLevel_2repumps_AnalysisFunctions import PerformExperiment_8levels
from scipy.optimize import curve_fit
import time
"""
MEDICION MULTI INDIVIDUAL
VEO EL AJUSTE DE UNA DEL AS CURVAS MULTI PARA VER COMO AJUSTA
"""
phidoppler, titadoppler = 0, 90
phirepump, titarepump = 0, 0
phiprobe = 0
titaprobe = 90
Temp = 0.5e-3
sg = 0.544
sp = 4.5
sr = 0
DetRepump = 0
lw = 0.1
DopplerLaserLinewidth, RepumpLaserLinewidth, ProbeLaserLinewidth = lw, lw, lw #ancho de linea de los laseres
u = 32.5e6
#B = (u/(2*np.pi))/c
gPS, gPD, = 2*np.pi*21.58e6, 2*np.pi*1.35e6
alpha = 0
drivefreq = 2*np.pi*22.135*1e6
measurement = 2
#selectedcurve=10
selectedcurvevec=[10]
#popt_vecs = []
#pcov_vecs = []
for selectedcurve in selectedcurvevec:
FreqsDR = MultiFreqs[measurement]
CountsDR = CountsSplit[measurement][selectedcurve]
if selectedcurve==9 and measurement==1:
CountsDR[10]=4132+89
CountsDR[11]=4132+2*89
freqslong = np.arange(min(FreqsDR), max(FreqsDR)+FreqsDR[1]-FreqsDR[0], 0.1*(FreqsDR[1]-FreqsDR[0]))
CircPr = 1
alpha = 0
def FitEIT_MM_2ion(Freqs, offset, DetDoppler, SG, SP, SCALE1, SCALE2, BETA1, BETA2, TEMP, U, plot=False):
#def FitEIT_MM(freqs, SG, SP, SCALE1, OFFSET, BETA1):
#BETA = 1.8
# SG = 0.6
# SP = 8.1
# TEMP = 0.2e-3
freqs = [2*f*1e-6-offset for f in Freqs]
Detunings, Fluorescence1 = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, U, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe, BETA1, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
Detunings, Fluorescence2 = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, U, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe, BETA2, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
ScaledFluo1 = np.array([f*SCALE1 + 0.5*OFFSET for f in Fluorescence1])
ScaledFluo2 = np.array([f*SCALE2 + 0.5*OFFSET for f in Fluorescence2])
if plot:
return ScaledFluo1+ScaledFluo2, Detunings
else:
return ScaledFluo1+ScaledFluo2
#return ScaledFluo1
def FitEIT_MM_1ion(Freqs, offset, DetDoppler, SG, SP, SCALE1, BETA1, TEMP, U, plot=False):
#def FitEIT_MM(freqs, SG, SP, SCALE1, OFFSET, BETA1):
#BETA = 1.8
# SG = 0.6
# SP = 8.1
# TEMP = 0.2e-3
OFFSET = 300
freqs = [2*f*1e-6-offset for f in Freqs]
Detunings, Fluorescence1 = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, U, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe, BETA1, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
ScaledFluo1 = np.array([f*SCALE1 + 1*OFFSET for f in Fluorescence1])
if plot:
return ScaledFluo1, Detunings
else:
return ScaledFluo1
popt_multi1_1ion_test, pcov_multi1_1ion_test = curve_fit(FitEIT_MM_1ion, FreqsDR, CountsDR, p0=[448.2, -44.8, 0.5, 6.6, 3.8e4, 1, 1e-3, 32e6], bounds=((0, -50, 0, 0, 0, 0, 0, 30e6), (1000, 0, 2, 20, 5e6, 10, 10e-3, 35e6)))
#popt_multi1_2ion_test, pcov_multi1_2ion_test = curve_fit(FitEIT_MM_2ion, FreqsDR, CountsDR, p0=[448.2, -44.8, 0.5, 6.6, 3.8e4, 1.26e5, 4.2, 1.3, 1.4e-3, 32e6], bounds=((0, -50, 0, 0, 0, 0, 0,0, 0, 28e6), (1000, 0, 2, 20, 5e6, 5e6, 10, 10,20e-3,40e6)))
except:
popt_multi1_2ion_test = [0,0,0,0,0,0,0,0,0,0]
pcov_multi1_2ion_test = [0]
FittedEITpi_multi1_short_1ion, Detunings_multi1_short_1ion = FitEIT_MM_1ion(FreqsDR, *popt_multi1_1ion_test, plot=True)
freqslong = np.arange(min(FreqsDR), max(FreqsDR)+FreqsDR[1]-FreqsDR[0], 0.1*(FreqsDR[1]-FreqsDR[0]))
FittedEITpi_multi1_long_1ion, Detunings_multi1_long_1ion = FitEIT_MM_1ion(freqslong, *popt_multi1_1ion_test, plot=True)
# FittedEITpi_multi1_short_2ion, Detunings_multi1_short_2ion = FitEIT_MM_2ion(FreqsDR, *popt_multi1_2ion_test, plot=True)
# freqslong = np.arange(min(FreqsDR), max(FreqsDR)+FreqsDR[1]-FreqsDR[0], 0.1*(FreqsDR[1]-FreqsDR[0]))
# FittedEITpi_multi1_long_2ion, Detunings_multi1_long_2ion = FitEIT_MM_2ion(freqslong, *popt_multi1_2ion_test, plot=True)
#popt_vecs.append(popt_multi1_2ion)
#pcov_vecs.append(pcov_multi1_2ion)
print(f'Listo {selectedcurve}')
plt.figure()
plt.errorbar(Detunings_multi1_short_1ion, CountsDR, yerr=2*np.sqrt(CountsDR), fmt='o', color='darkgreen', alpha=0.5, capsize=2, markersize=2)
plt.plot(Detunings_multi1_long_1ion, FittedEITpi_multi1_long_1ion, color='red', linewidth=3, label=f'selcurve: {selectedcurve}')
plt.title('1 ion model')
plt.xlabel('Detuning (MHz)')
plt.ylabel('Counts')
plt.legend(loc='upper left', fontsize=20)
plt.grid()
# plt.figure()
# plt.errorbar(Detunings_multi1_short_2ion, CountsDR, yerr=2*np.sqrt(CountsDR), fmt='o', color='darkgreen', alpha=0.5, capsize=2, markersize=2)
# plt.plot(Detunings_multi1_long_2ion, FittedEITpi_multi1_long_2ion, color='darkolivegreen', linewidth=3, label=f'selcurve: {selectedcurve}')
# plt.title('2 ion model')
# plt.xlabel('Detuning (MHz)')
# plt.ylabel('Counts')
# plt.legend(loc='upper left', fontsize=20)
# plt.grid()
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# plt.plot(detunings,'o')
#%%
#from EITfit.MM_eightLevel_2repumps_AnalysisFunctions import PerformExperiment_8levels
from scipy.optimize import curve_fit
import time
"""
MEDICION MULTI 1
Cada bloque ajusta un grupo de mediciones porque sino es un lio
"""
phidoppler, titadoppler = 0, 90
phirepump, titarepump = 0, 0
phiprobe = 0
titaprobe = 90
Temp = 0.5e-3
sg = 0.544
sp = 4.5
sr = 0
DetRepump = 0
lw = 0.1
DopplerLaserLinewidth, RepumpLaserLinewidth, ProbeLaserLinewidth = lw, lw, lw #ancho de linea de los laseres
u = 32.5e6
#B = (u/(2*np.pi))/c
gPS, gPD, = 2*np.pi*21.58e6, 2*np.pi*1.35e6
alpha = 0
drivefreq = 2*np.pi*22.135*1e6
measurement = 1
#selectedcurve=10
selectedcurvevec=[7,8,9,10,11,12,13,14]
popt_vecs = []
pcov_vecs = []
for selectedcurve in selectedcurvevec:
FreqsDR = MultiFreqs[measurement]
CountsDR = CountsSplit[measurement][selectedcurve]
freqslong = np.arange(min(FreqsDR), max(FreqsDR)+FreqsDR[1]-FreqsDR[0], 0.1*(FreqsDR[1]-FreqsDR[0]))
CircPr = 1
alpha = 0
def FitEIT_MM_2ion(Freqs, offset, DetDoppler, SG, SP, SCALE1, SCALE2, OFFSET, BETA1, BETA2, TEMP, U, plot=False):
#def FitEIT_MM(freqs, SG, SP, SCALE1, OFFSET, BETA1):
#BETA = 1.8
# SG = 0.6
# SP = 8.1
# TEMP = 0.2e-3
freqs = [2*f*1e-6-offset for f in Freqs]
Detunings, Fluorescence1 = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, U, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe, BETA1, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
Detunings, Fluorescence2 = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, U, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe, BETA2, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
ScaledFluo1 = np.array([f*SCALE1 + 0.5*OFFSET for f in Fluorescence1])
ScaledFluo2 = np.array([f*SCALE2 + 0.5*OFFSET for f in Fluorescence2])
if plot:
return ScaledFluo1+ScaledFluo2, Detunings
else:
return ScaledFluo1+ScaledFluo2
#return ScaledFluo1
do_fit = True
if do_fit:
try:
popt_multi1_2ion, pcov_multi1_2ion = curve_fit(FitEIT_MM_2ion, FreqsDR, CountsDR, p0=[448.2, -44.8, 0.5, 6.6, 3.8e4, 1.26e5, 1.5e-1, 4.2, 1.3, 1.4e-3, 32e6], bounds=((0, -50, 0, 0, 0, 0, 0, 0,0, 0,25e6), (1000, 0, 2, 20, 5e6, 5e6, 5e4, 10, 10,20e-3,40e6)))
except:
popt_multi1_2ion = [0,0,0,0,0,0,0,0,0,0,0]
pcov_multi1_2ion = [0]
FittedEITpi_multi1_short_2ion, Detunings_multi1_short_2ion = FitEIT_MM_2ion(FreqsDR, *popt_multi1_2ion, plot=True)
freqslong = np.arange(min(FreqsDR), max(FreqsDR)+FreqsDR[1]-FreqsDR[0], 0.1*(FreqsDR[1]-FreqsDR[0]))
FittedEITpi_multi1_long_2ion, Detunings_multi1_long_2ion = FitEIT_MM_2ion(freqslong, *popt_multi1_2ion, plot=True)
popt_vecs.append(popt_multi1_2ion)
pcov_vecs.append(pcov_multi1_2ion)
print(f'Listo {selectedcurve}')
plt.figure()
plt.errorbar(Detunings_multi1_short_2ion, CountsDR, yerr=2*np.sqrt(CountsDR), fmt='o', color='darkgreen', alpha=0.5, capsize=2, markersize=2)
plt.plot(Detunings_multi1_long_2ion, FittedEITpi_multi1_long_2ion, color='darkolivegreen', linewidth=3, label=f'selcurve: {selectedcurve}')
#plt.title(f'Sdop: {round(popt[0], 2)}, Spr: {round(popt[1], 2)}, T: {round(popt[2]*1e3, 2)} mK, detDop: {DetDoppler} MHz')
plt.xlabel('Detuning (MHz)')
plt.ylabel('Counts')
plt.legend(loc='upper left', fontsize=20)
plt.grid()
# plt.plot(detunings,'o')
#from EITfit.MM_eightLevel_2repumps_AnalysisFunctions import PerformExperiment_8levels
from scipy.optimize import curve_fit
import time
"""
MEDICION MULTI 1
otras
"""
phidoppler, titadoppler = 0, 90
phirepump, titarepump = 0, 0
phiprobe = 0
titaprobe = 90
Temp = 0.5e-3
sg = 0.544
sp = 4.5
sr = 0
DetRepump = 0
lw = 0.1
DopplerLaserLinewidth, RepumpLaserLinewidth, ProbeLaserLinewidth = lw, lw, lw #ancho de linea de los laseres
u = 32.5e6
#B = (u/(2*np.pi))/c
gPS, gPD, = 2*np.pi*21.58e6, 2*np.pi*1.35e6
alpha = 0
drivefreq = 2*np.pi*22.135*1e6
measurement = 1
#selectedcurve=10
selectedcurvevec=[15,16,17,18]
popt_vecs2 = []
pcov_vecs2 = []
for selectedcurve in selectedcurvevec:
FreqsDR = MultiFreqs[measurement]
CountsDR = CountsSplit[measurement][selectedcurve]
freqslong = np.arange(min(FreqsDR), max(FreqsDR)+FreqsDR[1]-FreqsDR[0], 0.1*(FreqsDR[1]-FreqsDR[0]))
CircPr = 1
alpha = 0
def FitEIT_MM_2ion(Freqs, offset, DetDoppler, SG, SP, SCALE1, SCALE2, OFFSET, BETA1, BETA2, TEMP, U, plot=False):
#def FitEIT_MM(freqs, SG, SP, SCALE1, OFFSET, BETA1):
#BETA = 1.8
# SG = 0.6
# SP = 8.1
# TEMP = 0.2e-3
freqs = [2*f*1e-6-offset for f in Freqs]
Detunings, Fluorescence1 = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, U, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe, BETA1, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
Detunings, Fluorescence2 = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, U, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe, BETA2, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
ScaledFluo1 = np.array([f*SCALE1 + 0.5*OFFSET for f in Fluorescence1])
ScaledFluo2 = np.array([f*SCALE2 + 0.5*OFFSET for f in Fluorescence2])
if plot:
return ScaledFluo1+ScaledFluo2, Detunings
else:
return ScaledFluo1+ScaledFluo2
#return ScaledFluo1
do_fit = True
if do_fit:
try:
popt_multi1_2ion, pcov_multi1_2ion = curve_fit(FitEIT_MM_2ion, FreqsDR, CountsDR, p0=[447.5, -44.0, 0.7, 10, 5.0e4, 6e4, 1.5e-10, 3.7, 1.3, 1.1e-3, 32e6], bounds=((0, -50, 0, 0, 0, 0, 0, 0,0, 0, 25e6), (1000, 0, 2, 20, 5e6, 5e6, 5e4, 10, 10,20e-3, 40e6)))
except:
popt_multi1_2ion = [0,0,0,0,0,0,0,0,0,0,0]
pcov_multi1_2ion = [0]
FittedEITpi_multi1_short_2ion, Detunings_multi1_short_2ion = FitEIT_MM_2ion(FreqsDR, *popt_multi1_2ion, plot=True)
freqslong = np.arange(min(FreqsDR), max(FreqsDR)+FreqsDR[1]-FreqsDR[0], 0.1*(FreqsDR[1]-FreqsDR[0]))
FittedEITpi_multi1_long_2ion, Detunings_multi1_long_2ion = FitEIT_MM_2ion(freqslong, *popt_multi1_2ion, plot=True)
popt_vecs2.append(popt_multi1_2ion)
pcov_vecs2.append(pcov_multi1_2ion)
print(f'Listo {selectedcurve}')
plt.figure()
plt.errorbar(Detunings_multi1_short_2ion, CountsDR, yerr=2*np.sqrt(CountsDR), fmt='o', color='darkgreen', alpha=0.5, capsize=2, markersize=2)
plt.plot(Detunings_multi1_long_2ion, FittedEITpi_multi1_long_2ion, color='darkolivegreen', linewidth=3, label=f'selcurve: {selectedcurve}')
#plt.title(f'Sdop: {round(popt[0], 2)}, Spr: {round(popt[1], 2)}, T: {round(popt[2]*1e3, 2)} mK, detDop: {DetDoppler} MHz')
plt.xlabel('Detuning (MHz)')
plt.ylabel('Counts')
plt.legend(loc='upper left', fontsize=20)
plt.grid()
#%%
#from EITfit.MM_eightLevel_2repumps_AnalysisFunctions import PerformExperiment_8levels
from scipy.optimize import curve_fit
import time
"""
MEDICION MULTI 1
otras
"""
phidoppler, titadoppler = 0, 90
phirepump, titarepump = 0, 0
phiprobe = 0
titaprobe = 90
Temp = 0.5e-3
sg = 0.544
sp = 4.5
sr = 0
DetRepump = 0
lw = 0.1
DopplerLaserLinewidth, RepumpLaserLinewidth, ProbeLaserLinewidth = lw, lw, lw #ancho de linea de los laseres
u = 32.5e6
#B = (u/(2*np.pi))/c
gPS, gPD, = 2*np.pi*21.58e6, 2*np.pi*1.35e6
alpha = 0
drivefreq = 2*np.pi*22.135*1e6
measurement = 1
#selectedcurve=10
selectedcurvevec=[6]
popt_vecs3 = []
pcov_vecs3 = []
for selectedcurve in selectedcurvevec:
FreqsDR = MultiFreqs[measurement]
CountsDR = CountsSplit[measurement][selectedcurve]
freqslong = np.arange(min(FreqsDR), max(FreqsDR)+FreqsDR[1]-FreqsDR[0], 0.1*(FreqsDR[1]-FreqsDR[0]))
CircPr = 1
alpha = 0
def FitEIT_MM_2ion(Freqs, offset, DetDoppler, SG, SP, SCALE1, SCALE2, OFFSET, BETA1, BETA2, TEMP, U, plot=False):
#def FitEIT_MM(freqs, SG, SP, SCALE1, OFFSET, BETA1):
#BETA = 1.8
# SG = 0.6
# SP = 8.1
# TEMP = 0.2e-3
freqs = [2*f*1e-6-offset for f in Freqs]
Detunings, Fluorescence1 = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, U, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe, BETA1, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
Detunings, Fluorescence2 = PerformExperiment_8levels_MM(SG, SP, gPS, gPD, DetDoppler, U, DopplerLaserLinewidth, ProbeLaserLinewidth, TEMP, alpha, phidoppler, titadoppler, phiprobe, titaprobe, BETA2, drivefreq, min(freqs), max(freqs)+(freqs[1]-freqs[0]), freqs[1]-freqs[0], circularityprobe=CircPr, plot=False, solvemode=1, detpvec=None)
ScaledFluo1 = np.array([f*SCALE1 + 0.5*OFFSET for f in Fluorescence1])
ScaledFluo2 = np.array([f*SCALE2 + 0.5*OFFSET for f in Fluorescence2])
if plot:
return ScaledFluo1+ScaledFluo2, Detunings
else:
return ScaledFluo1+ScaledFluo2
#return ScaledFluo1
do_fit = True
if do_fit:
try:
popt_multi1_2ion, pcov_multi1_2ion = curve_fit(FitEIT_MM_2ion, FreqsDR, CountsDR, p0=[448.2, -45.8, 0.6, 10, 7.3e4, 2.9e4, 1.3e3, 3.7, 1.1, 3.4e-3,32e6], bounds=((0, -50, 0, 0, 0, 0, 0, 0,0, 0,25e6), (1000, 0, 2, 20, 5e6, 5e6, 5e4, 10, 10,20e-3,40e6)))
except:
popt_multi1_2ion = [0,0,0,0,0,0,0,0,0,0,0]
pcov_multi1_2ion = [0]
FittedEITpi_multi1_short_2ion, Detunings_multi1_short_2ion = FitEIT_MM_2ion(FreqsDR, *popt_multi1_2ion, plot=True)
freqslong = np.arange(min(FreqsDR), max(FreqsDR)+FreqsDR[1]-FreqsDR[0], 0.1*(FreqsDR[1]-FreqsDR[0]))
FittedEITpi_multi1_long_2ion, Detunings_multi1_long_2ion = FitEIT_MM_2ion(freqslong, *popt_multi1_2ion, plot=True)
popt_vecs3.append(popt_multi1_2ion)
pcov_vecs3.append(pcov_multi1_2ion)
print(f'Listo {selectedcurve}')
plt.figure()
plt.errorbar(Detunings_multi1_short_2ion, CountsDR, yerr=2*np.sqrt(CountsDR), fmt='o', color='darkgreen', alpha=0.5, capsize=2, markersize=2)
plt.plot(Detunings_multi1_long_2ion, FittedEITpi_multi1_long_2ion, color='darkolivegreen', linewidth=3, label=f'selcurve: {selectedcurve}')
#plt.title(f'Sdop: {round(popt[0], 2)}, Spr: {round(popt[1], 2)}, T: {round(popt[2]*1e3, 2)} mK, detDop: {DetDoppler} MHz')
plt.xlabel('Detuning (MHz)')
plt.ylabel('Counts')
plt.legend(loc='upper left', fontsize=20)
plt.grid()
#%%
betas1s = []
betas2s = []
temps = []
detunings = []
# for i in range(len(popt_vecs3)):
# betas1s.append(popt_vecs3[i][7])
# betas2s.append(popt_vecs3[i][8])
# temps.append(popt_vecs3[i][9])
# detunings.append(popt_vecs3[i][6])
for i in range(len(popt_vecs)):
betas1s.append(popt_vecs[i][7])
betas2s.append(popt_vecs[i][8])
temps.append(popt_vecs[i][9])
detunings.append(popt_vecs[i][])
for i in range(len(popt_vecs2)):
betas1s.append(popt_vecs2[i][7])
betas2s.append(popt_vecs2[i][8])
temps.append(popt_vecs2[i][9])
detunings.append(popt_vecs2[i][5])
# plt.figure()
# plt.plot(betas1s,'o')
# plt.plot(betas2s,'o')
plt.figure()
plt.plot(detunings,'o')