agrego nuevos archivos para analisis

analisis/plots/20220503_EspectrosUVnuevos/UV_spectrums2.py

+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 = """000007324-UV_Scan_withcalib_Haeffner
+""" 
+
+
+
+#carpeta pc nico labo escritorio:
+#C:\Users\Usuario\Documents\artiq\artiq_experiments\analisis\plots\20220503_EspectrosUVnuevos\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 GetBackground(countsper100ms, )
+
+
+
+#%%
+
+def Lorentzian(f, A, gamma, x0):
+    return (A/np.pi)*0.5*gamma/(((f-x0)**2)+((0.5*gamma)**2)) + 10 #40 es el piso de ruido estimado
+
+j = 0 #UV_cooling en 90 MHz
+
+FreqsChosen = [2*f*1e-6 for f in Freqs[j]]
+CountsChosen = Counts[j]
+
+portion = 0.
+
+popt, pcov = curve_fit(Lorentzian, FreqsChosen[int(portion*len(FreqsChosen)):], CountsChosen[int(portion*len(FreqsChosen)):])
+
+freqslong = np.arange(min(FreqsChosen)-10, max(FreqsChosen)+10, (FreqsChosen[1]-FreqsChosen[0])*0.01)
+
+plt.figure()
+plt.plot(FreqsChosen, CountsChosen, 'o', label='4 uW')
+plt.plot(freqslong, Lorentzian(freqslong, *popt), label=f'FWHM {round(popt[1])} MHz')
+plt.axvline(popt[2]-22.1, linestyle='--', linewidth=1)
+plt.axvline(popt[2]+22.1, linestyle='--', linewidth=1)
+plt.xlabel('Frecuencia (MHz)')
+plt.ylabel('Cuentas')
+plt.legend()
+
+print(f'Ancho medido: {round(popt[1])} MHz') 
+
+