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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/20230510_MotionalSpectrum/Data/')
Data = []
for ii in range(1,10):
Data.append(f"ss0{ii}.dat")
for ii in range(10,20):
Data.append(f"ss{ii}.dat")
for ii in range(40,49):
Data.append(f"ss{ii}.dat")
FrequencyVec = []
FluoVec = []
for dd in Data:
data = np.genfromtxt(dd,
skip_header=1,
names=True,
dtype=None,
delimiter=' ')
FrequencyVec.append([data[i][1] for i in range(len(data))])
FluoVec.append([data[i][2] for i in range(len(data))])
#%%
ivec = [21,25]
plt.figure()
for i in ivec:
plt.plot([2*f*1e-6 for f in FrequencyVec[i]], FluoVec[i],'o')
#%%
import scipy
ivec = [9]
plt.figure()
for i in ivec:
pics = scipy.signal.find_peaks([-1*f for f in FluoVec[i]], height=-101.5, distance=300)
plt.plot([1*f*1e-6 for f in FrequencyVec[i]], FluoVec[i],'o')
plt.plot(np.array(FrequencyVec[i])[pics[0]]*1e-6, -pics[1]['peak_heights'],'o')
aspectratio = (np.array(FrequencyVec[i])[pics[0]][-1]*1e-6)/(np.array(FrequencyVec[i])[pics[0]][0]*1e-6)