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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
#Mediciones barriendo angulo del TISA y viendo kicking de resonancias oscuras
#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/20230707_MotionalSpectrum_v2/Data/')
os.chdir('C://Users//nicon//Doctorado//artiq_experiments//analisis//plots//20240515_MotionalSpectrum_v3_pendientes//Data')
MOTIONAL_FILES = """
000013002-AD9910RAM_andor
000013003-AD9910RAM_andor
000013004-AD9910RAM_andor
"""
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(MOTIONAL_FILES))
#%%
#carpeta pc nico labo escritorio:
#C:\Users\Usuario\Documents\artiq\artiq_experiments\analisis\plots\20211101_CPT_DosLaseres_v03\Data
Counts_roi1 = []
Counts_roi2 = []
RealFreqs = []
IR1_amp_vec = []
for i, fname in enumerate(MOTIONAL_FILES.split()):
print(str(i) + ' - ' + fname)
data = h5py.File(fname+'.h5', 'r')
RealFreqs.append(np.array(data['datasets']['real_freq']))
Counts_roi1.append(np.array(data['datasets']['counts_roi1']))
Counts_roi2.append(np.array(data['datasets']['counts_roi2']))
IR1_amp_vec.append(np.array(data['datasets']['IR1_amp']))
Potencias_IR = [0,20,50]
#%%
"""
Ploteo una curva para buscar su minimo
"""
jvec = [2,1,0]
plt.figure()
i = 0
kmin = 106
for j in jvec:
plt.errorbar([1*f*1e-3 for f in RealFreqs[j]], Counts_roi1[j], yerr=0.1*np.sqrt(Counts_roi1[j]), fmt='o', capsize=2, markersize=2, label=f'IR1 power: {Potencias_IR[j]} uW')
#plt.plot([1*f*1e-3 for f in RealFreqs[j]][kmin], Counts[j][kmin], 'o', markersize=15)
i = i + 1
plt.xlabel('Frecuencia mod IR2 (kHz)')
plt.ylabel('Cuentas/400 ms')
plt.xlim(780,810)
plt.ylim(18680,19650)
plt.grid()
plt.legend(loc='lower left')