agrego meds xdxd

analisis/plots/20230713_EspectrosCristal6iones/Espectroscpt_cristal.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
+
+#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/20230713_EspectrosCristal6iones/Data/')
+
+
+MOTIONAL_FILES = """000013216-IR_Scan_withcal_optimized_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
+
+CountsRoi1 = []
+CountsRoi2 = []
+CountsRoi3 = []
+CountsRoi4 = []
+CountsRoi5 = []
+CountsRoi6 = []
+CountsRoi7 = []
+#Amplitudes = []
+IR1_Freqs    = []
+#IR_amps    = []
+
+for i, fname in enumerate(MOTIONAL_FILES.split()):
+    print(str(i) + ' - ' + fname)
+    data = h5py.File(fname+'.h5', 'r')
+    #Amplitudes.append(np.array(data['datasets']['amplitudes']))
+    CountsRoi1.append(np.array(data['datasets']['counts_roi1']))
+    #CountsRoi2.append(np.array(data['datasets']['counts_roi2']))
+    #CountsRoi3.append(np.array(data['datasets']['counts_roi3']))
+    #CountsRoi4.append(np.array(data['datasets']['counts_roi4']))
+    #CountsRoi5.append(np.array(data['datasets']['counts_roi5']))
+    #CountsRoi6.append(np.array(data['datasets']['counts_roi6']))
+    #CountsRoi7.append(np.array(data['datasets']['counts_roi7']))
+    IR1_Freqs.append(np.array(data['datasets']['IR1_Frequencies']))
+    #IR_amps.append(np.array(data['datasets']['IR1_measurement_amp']))
+
+
+
+#%%
+
+"""
+En cristal de 7 iones (uno de ellos oscuro) veo espectros. Primero espectros uv.
+La roi1 es la general. Las demas son de cada uno de los 6 ioens brillantes del cristal.
+"""
+
+i = 0
+
+jvec=[0]
+
+#CountsRois = [CountsRoi2, CountsRoi3, CountsRoi4, CountsRoi5, CountsRoi6, CountsRoi7]
+
+CountsRois = [CountsRoi1]
+
+plt.figure()
+
+f=[1]
+for counts in CountsRois:
+    plt.plot(IR1_Freqs[0][1:], [c for c in counts[0][1:]], '-o', markersize=2)
+    i=i+1
+plt.xlabel('Frecuencia')
+plt.ylabel('Cuentas ROI')
+#plt.xlim(0.05,0.23)
+#plt.ylim(15550,16400)
+plt.grid()
+plt.legend()
+
+#%%
+
+#mergeo mediciones porque medi variando el piezoB para tener mas rango
+
+Frequencies_vector = []
+Counts_vector = []
+
+kfin1 = 37
+kin2 = 9
+
+for counts in [CountsRoi1, CountsRoi2, CountsRoi3, CountsRoi4, CountsRoi5, CountsRoi6, CountsRoi7]:
+    Frequencies_vector.append([1e-6*2*f for f in [Desplazamientos[4]+f for f in UV_Freqs[5][1:kfin1]]+list(UV_Freqs[2][kin2:])])
+    Counts_vector.append(list(counts[5][1:kfin1])+list(counts[2][kin2:]))
+
+ivecs = [3,4]
+
+#ivecs = [2, 5, 6]
+
+#ivecs = [1]
+
+plt.figure()
+for i in range(len(Frequencies_vector)):
+    if i in ivecs:
+        plt.plot(Frequencies_vector[i], Counts_vector[i],'-o')
+plt.grid()
+plt.xlabel('Frequency (MHz)')
+plt.ylabel('Counts')
+
+#%%
+ftrap=22.1
+#ahora intento ajustarlos con modelo con micromocion
+
+from scipy.special import jv
+from scipy.optimize import curve_fit
+
+def MicromotionSpectra(det, A, beta, x0, gamma, offset):
+    ftrap=22.1
+    #gamma=30
+    P = A*(jv(0, beta)**2)/(((det-x0)**2)+(0.5*gamma)**2)+offset
+    i = 1
+    #print(P)
+    while i <= 1:
+        P = P + A*((jv(i, beta))**2)/((((det-x0)+i*ftrap)**2)+(0.5*gamma)**2) + A*((jv(-i, beta))**2)/((((det-x0)-i*ftrap)**2)+(0.5*gamma)**2) 
+        i = i + 1
+        #print(P)
+    return P
+
+
+popt_vec = []
+pcov_vec = []
+
+
+#uso como refe k=3
+jref=3
+popt_ref, pcov_ref = curve_fit(MicromotionSpectra, Frequencies_vector[jref], Counts_vector[jref], p0=[1000, 2, 274, 90, 14000], bounds=((0,0,200,20,0),(1e7,100,600,1000,25650)))
+
+freqslong = np.arange(min(Frequencies_vector[jref]), max(Frequencies_vector[jref])+100, (Frequencies_vector[jref][1]-Frequencies_vector[jref][0])*0.01)
+
+print(popt_ref)
+plt.figure()
+for j in range(1,len(Frequencies_vector)):
+    plt.plot(Frequencies_vector[j], Counts_vector[j])
+    if j == jref:
+        plt.plot(freqslong, MicromotionSpectra(freqslong, *popt_ref))
+
+for i in range(5):
+    plt.axvline(popt_ref[2]-i*ftrap, linestyle='dashed', color='black', linewidth=1, zorder=0)
+plt.grid()
+#%%
+for i in range(len(Frequencies_vector)):
+    if i != jref:
+        popt, pcov = curve_fit(MicromotionSpectra, Frequencies_vector[i], Counts_vector[i], p0=[popt_ref[0], 5, popt_ref[2], 60, popt_ref[4]], bounds=((popt_ref[0]-0.001*popt_ref[0],0,popt_ref[2]-0.001*popt_ref[2],0,popt_ref[4]-0.001*popt_ref[4]),(popt_ref[0]+0.001*popt_ref[0],100,popt_ref[2]+0.001*popt_ref[2],300, popt_ref[4]+0.001*popt_ref[4])))
+        popt_vec.append(popt)
+        pcov_vec.append(pcov)
+    else:
+        popt_vec.append(popt_ref)
+        pcov_vec.append(pcov_ref)
+        
+ftrap=22.1
+
+jeval=1
+
+freqslong = np.arange(min(Frequencies_vector[jeval]), max(Frequencies_vector[jeval])+100, (Frequencies_vector[jeval][1]-Frequencies_vector[jeval][0])*0.01)
+
+print(popt_vec[jeval])
+plt.figure()
+plt.plot(Frequencies_vector[jeval], Counts_vector[jeval])
+plt.plot(freqslong, MicromotionSpectra(freqslong, *popt_ref))
+plt.axvline(popt_ref[2], linestyle='dashed')
+plt.axvline(popt_ref[2]-ftrap, linestyle='dashed')
+plt.axvline(popt_ref[2]+ftrap, linestyle='dashed')
+plt.axvline(popt_ref[2]-2*ftrap, linestyle='dashed')
+plt.axvline(popt_ref[2]+2*ftrap, linestyle='dashed')
+plt.axvline(popt_ref[2]-3*ftrap, linestyle='dashed')
+plt.axvline(popt_ref[2]+3*ftrap, linestyle='dashed')
+
+
+
+

analisis/plots/20230720_EspectrosCristal2iones/Espectroscpt_cristal.py

@@ -12,10 +12,14 @@ from scipy import interpolate
 
 #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/20230713_EspectrosCristal6iones/Data/')
+os.chdir('/home/nico/Documents/artiq_experiments/analisis/plots/20230720_EspectrosCristal2iones/Data/')
 
 
-MOTIONAL_FILES = """000013216-IR_Scan_withcal_optimized_andor
+MOTIONAL_FILES = """000013489-IR_Scan_withcal_optimized_andor
+000013490-IR_Scan_withcal_optimized_andor
+000013491-IR_Scan_withcal_optimized_andor
+000013493-IR_Scan_withcal_optimized_andor
+000013494-IR_Scan_withcal_optimized_andor
 """
 
 
@@ -58,16 +62,18 @@ for i, fname in enumerate(MOTIONAL_FILES.split()):
 En cristal de 2 iones veo espectros cpt. 
 """
 
-i = 0
-
-CountsRois = [CountsRoi1, CountsRoi2]
+medvec = [0,1,2,3,4]
 
 plt.figure()
 
-f=[1]
-for counts in CountsRois:
-    plt.plot(IR1_Freqs[0][1:], [c for c in counts[0][1:]], '-o', markersize=2)
-    i=i+1
+
+for med in medvec:
+    #CountsRois = [CountsRoi1[med], CountsRoi2[med]]
+    CountsRois = [CountsRoi2[med]]
+    i=0
+    for counts in CountsRois:
+        plt.plot(IR1_Freqs[0][1:], [c for c in counts[1:]], '-o', markersize=2)
+        i=i+1
 plt.xlabel('Frecuencia')
 plt.ylabel('Cuentas ROI')
 #plt.xlim(0.05,0.23)