agd

analisis/plots/20230510_MotionalSpectrum/MotionalElectric.py

+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)
+print(aspectratio**(-1))
+
+
+
+