todotodo

analisis/plots/20230804_RotationalDopplerShift_v2/RDS_CPT2.py

@@ -241,8 +241,38 @@ plt.legend()
 plt.title('Comparacion de config colineal (insensible) con desplazada (sensible)')
 
 #%%
+"""
+Ploteo una bien linda
+"""
+
+extramedvec = [1]
+
+#AmpsVecs = [0.05, 0.08, 0.12, 0.17, 0.22]
 
+plt.figure()
 
+ftrap = 22.1
+
+DR1 = 435.8
+DR2 = 444.2
+
+freqDR=435.8
+
+secular=False    
+
+
+plt.plot([2*f*1e-6 for f in ExtraIR1_Freqs[1][1:]], [1e-3*c for c in ExtraCounts[1][1:]], '-o', markersize=2, label='Colineales')
+plt.xlabel('Frequency (MHz)', fontname='STIXgeneral',fontsize=15)
+plt.ylabel('kCounts',fontname='STIXgeneral',fontsize=15)
+plt.xlim(425, 455)
+plt.yticks([1,1.5,2,2.5,3],fontname='STIXgeneral',fontsize=15)
+plt.xticks([425,430,435,440,445,450,455],fontname='STIXgeneral',fontsize=15)
+plt.ylim(1.,3.2)
+plt.grid()
+plt.tight_layout()
+plt.savefig('/home/nico/Nextcloud/Nico/Doctorado/Charlas/2023 Europe/DDresonancesexperimental.pdf')
+#plt.legend()
+#plt.title('Comparacion de config colineal (insensible) con desplazada (sensible)')
 
 
 #%%

analisis/plots/20230817_RotationalDopplerShift_v4/RDS_location4.py

@@ -356,6 +356,8 @@ pmlocmedvec = [7]
 mmlocmedvec = [0]
 
 
+fi = 440
+
 paletita = sns.color_palette('rocket')
 
 plt.figure()
@@ -366,7 +368,7 @@ for med in mmlocmedvec:
     print(Countsmm)
     NormCountsmm = normalizeplot(Freqsmm, Countsmm, skip=0)
     NormCountsmm[97]=1
-    plt.plot(Freqsmm, NormCountsmm, '-o', color=paletita[jj], markersize=2, alpha=1, label='+2/+2')
+    plt.plot([f-fi for f in Freqsmm], NormCountsmm, '-o', color=paletita[jj], markersize=2, alpha=1, label='+2/+2')
     #plt.plot(Freqs, sf(NormCounts,5,2), 'o', color=palette[jj], markersize=2, label=f'{LocVecs[jj]}')
     #plt.plot([2*f*1e-6 for f in PmFrequencies[med][1:]][idxtest], [c for c in PmCounts[med][1:]][idxtest], 'o', color=palette[med],markersize=14, label=f'{LocVecs[jj]}')
     jj=jj+1
@@ -381,7 +383,7 @@ for med in pmlocmedvec:
     NormCountspm[214]=1
     NormCountspm[285]=1
     NormCountspm[293]=1
-    plt.plot(Freqspm, NormCountspm, '-o', color=paletita[jj+2], markersize=2, alpha=1, label='+2/-2')
+    plt.plot([f-fi for f in Freqspm], NormCountspm, '-o', color=paletita[jj+2], markersize=2, alpha=1, label='+2/-2')
     #plt.plot(Freqs, sf(NormCounts,5,2), 'o', color=palette[jj], markersize=2, label=f'{LocVecs[jj]}')
     #plt.plot([2*f*1e-6 for f in PmFrequencies[med][1:]][idxtest], [c for c in PmCounts[med][1:]][idxtest], 'o', color=palette[med],markersize=14, label=f'{LocVecs[jj]}')
     jj=jj+1
@@ -389,11 +391,17 @@ for med in pmlocmedvec:
 
 
 #plt.ylim(0,1.2)
-plt.xlabel('IR1 Frequency (MHz)',fontsize=14,fontname='STIXgeneral')
-plt.ylabel('Normalized Counts',fontsize=14,fontname='STIXgeneral')
+plt.xlabel('IR1 Frequency (MHz)',fontsize=15,fontname='STIXgeneral')
+plt.ylabel('Normalized Counts',fontsize=15,fontname='STIXgeneral')
+plt.xticks([-10,-5,0,5,10],fontname='STIXgeneral',fontsize=18)
+plt.yticks([0.4,0.6,0.8,1],fontname='STIXgeneral',fontsize=18)
 plt.ylim(0.3,1.1)
+plt.xlim(-10,7)
 plt.grid()
+plt.tight_layout()
 plt.legend(fontsize=14,markerscale=5)
+plt.savefig('/home/nico/Nextcloud/Nico/Doctorado/Charlas/2023 Europe/sensitivityofparalellantiparalell.pdf')
+
 
 
 

analisis/plots/20230817_RotationalDopplerShift_v5/RDS_locationradial.py

@@ -12,7 +12,7 @@ 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/20230817_RotationalDopplerShift_v5/Data')
+os.chdir('/home/nico/Documents/artiq_experiments/analisis/plots/20230817_RotationalDopplerShift_v5/Data')
 
 
 """

analisis/plots/20230817_RotationalDopplerShift_v5/RDS_piezo.py

@@ -12,7 +12,7 @@ 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/20230817_RotationalDopplerShift_v5/Data')
+os.chdir('/home/nico/Documents/artiq_experiments/analisis/plots/20230817_RotationalDopplerShift_v5/Data')
 
 
 """
@@ -80,11 +80,16 @@ def ErrorDRdepth(p, f, b):
     derivadab = ((p-f)/((f-b)**2))**2
     return 1*np.sqrt(derivadap*ep*ep + derivadaf*ef*ef + derivadab*eb*eb)
 
+def Lorentzian( x, A, B, x0, gam,C):
+    #C=0
+    return A * gam**2 / ( gam**2 + ( x - x0 )**2) + B - C*(x - x0)
+
+
 #%%
 
 import seaborn as sns
 """
-Resonancias DD configuracion +2/-2 colineal variando la ubicacion del ion en los haces
+Resonancias DD configuracion -2/-2 colineal variando la ubicacion del ion en los haces
 
 TODO EL OAM
 """
@@ -151,6 +156,98 @@ for med in pmlocmedvec:
 # #plt.title('Espectros para distintas geometrías')
 
 
+plt.figure()
+plt.errorbar(np.arange(0,len(Intensity),1), [i/np.max(Intensity) for i in Intensity], yerr=[i/np.max(Intensity) for i in errorIntensity], fmt='o',capsize=2, markersize=8)
+plt.errorbar(np.arange(0,len(Intensity),1), [p for p in pmdepthsdr], yerr=errorpmdepthsdr, fmt='o',capsize=2, markersize=8)
+plt.xlabel('Ion position')
+plt.ylabel('Intensity / DR Relative depth')
+#plt.xticks([1,2,3,4,5])
+#plt.xlim(200,3200)
+plt.ylim(-0.1,1.1)
+plt.grid()
+#plt.axvline(3, color='salmon')
+plt.legend()
+
+
+#%%
+
+import seaborn as sns
+"""
+Resonancias DD configuracion +2/-2 colineal variando la ubicacion del ion en los haces
+
+Mismo analisis pero con fiteos
+"""
+
+palette = sns.color_palette("tab10")
+
+pmlocmedvec = list(np.arange(0,12,1))+[13,12]+list(np.arange(15,len(PIEZO1_FILES),1))
+
+"""
+Hay que invertir la 12 con la 13, y la 14 es la misma que la 12, por las dudas
+"""
+
+
+#pmlocmedvec = [30]
+
+
+plt.figure()
+
+bkg = np.min(Piezo1Counts[1])
+
+pmdepthsdr=[]
+errorpmdepthsdr=[]
+
+Intensity = []
+errorIntensity = []
+
+idxtest = 185
+print(idxtest)
+
+Gamas = []
+ErrorGamas = []
+
+jj=0
+for med in pmlocmedvec:
+    print(med)
+    
+    Freqs = [2*f*1e-6 for f in Piezo1Frequencies[med][1:]]
+    Counts = [c for c in Piezo1Counts[med][1:]]
+
+    if med==30:
+        Freqs=Freqs[90:]
+        Counts=Counts[90:]
+        popt, pcov = curve_fit(Lorentzian, np.array(Freqs), np.array(Counts), p0=(-200,2100,435.8,0.05,0.1), bounds=((-10000,0,435.5,0,0),(0,1e4, 436.1, 1,1e4)))
+    else:
+        popt, pcov = curve_fit(Lorentzian, np.array(Freqs), np.array(Counts), p0=(-200,2100,435.8,0.05,0.1), bounds=((-10000,0,435.5,0,0),(0,1e4, 436.1, 1,1e4)))
+
+    pmdepthsdr.append(1-(np.min(Lorentzian(np.array(Freqs),*popt))-bkg)/(popt[1]-bkg))
+    #pmdepthsdr.append(1-(Piezo1Counts[med][1:][idxvecdr[jj]]-bkg)/(np.mean(Piezo1Counts[med][1:][0:20])-bkg))
+    #errorpmdepthsdr.append(ErrorDRdepth(Piezo1Counts[med][1:][idxvecdr[jj]],np.mean(Piezo1Counts[med][1:][0:20]), bkg))
+    errorpmdepthsdr.append(ErrorDRdepth(np.min(Lorentzian(Freqs,*popt)),popt[1], bkg))
+    
+
+    
+    Intens = popt[1]
+    Gamas.append(popt[3])
+    ErrorGamas.append(np.sqrt(pcov[3,3]))
+    Intensity.append(Intens)
+    errorIntensity.append(2*np.sqrt(np.mean(Piezo1Counts[med][1:][0:20]))+np.sqrt(bkg))
+        
+    
+        
+    plt.plot([2*f*1e-6 for f in Piezo1Frequencies[med][1:]], [c for c in Piezo1Counts[med][1:]], '-o', markersize=2, alpha=0.7)
+    plt.plot([f*1 for f in Freqs],Lorentzian(Freqs,*popt))
+
+    #plt.plot([2*f*1e-6 for f in Piezo1Frequencies[med][1:]][idxtest], [c for c in Piezo1Counts[med][1:]][idxtest], 'o',markersize=14)
+    jj=jj+1
+# plt.xlabel('Frecuencia (MHz)')
+# plt.ylabel('Counts')
+# plt.xlim(432, 446.5)
+# plt.grid()
+# plt.legend()
+# #plt.title('Espectros para distintas geometrías')
+
+
 plt.figure()
 plt.errorbar(np.arange(0,len(Intensity),1), [i/np.max(Intensity) for i in Intensity], yerr=[i/np.max(Intensity) for i in errorIntensity], fmt='o',capsize=2, markersize=8)
 plt.errorbar(np.arange(0,len(Intensity),1), [p for p in pmdepthsdr], yerr=errorpmdepthsdr, fmt='o',capsize=2, markersize=8)
@@ -170,6 +267,8 @@ import seaborn as sns
 Resonancias DD configuracion +2/+2 colineal variando la ubicacion del ion en los haces
 
 TODO EL OAM
+
+esto es hecho a mano... se puede ignorar
 """
 
 palette = sns.color_palette("tab10")
@@ -238,21 +337,139 @@ plt.legend()
 
 #%%
 
+import seaborn as sns
+"""
+Resonancias DD configuracion +2/+2 colineal variando la ubicacion del ion en los haces
+
+TODO EL OAM
+
+AHORA CON FITEOS LPM
+"""
+
+palette = sns.color_palette("tab10")
+
+mmlocmedvec = list(np.arange(0,10,1))+[11,10]+list(np.arange(12,len(PIEZO2_FILES),1))
+
+"""
+s
+"""
+plotcurvita=1
+#mmlocmedvec = [37]
 
 plt.figure()
-plt.errorbar(np.arange(0,len(Intensity),1), [i/np.max(Intensity) for i in Intensity], yerr=[i/np.max(Intensity) for i in errorIntensity], fmt='o',capsize=2, markersize=8)
-plt.errorbar(np.arange(0,len(Intensity),1), [p for p in pmdepthsdr], yerr=errorpmdepthsdr, fmt='o',capsize=2, markersize=8)
-plt.errorbar(np.arange(0,len(Intensity),1), [p for p in mmdepthsdr[3:]], yerr=[0.5*m for m in errormmdepthsdr[3:]], fmt='o',capsize=2, markersize=8)
-plt.xlabel('Ion position')
-plt.ylabel('Intensity / DR Relative depth')
-#plt.xticks([1,2,3,4,5])
+
+bkg = np.min(Piezo2Counts[1])
+
+mmdepthsdr=[]
+errormmdepthsdr=[]
+
+Intensity2 = []
+errorIntensity2 = []
+
+
+print(idxtest)
+
+jj=0
+for med in mmlocmedvec:
+    print(med)
+    
+
+    Freqs = [2*f*1e-6 for f in Piezo2Frequencies[med][1:]]
+    Counts = [c for c in Piezo2Counts[med][1:]]
+
+
+    if med==18:
+        popt, pcov = curve_fit(Lorentzian, np.array(Freqs), np.array(Counts), p0=(-200,210,435.8,0.05,0.1), bounds=((-10000,0,435.5,0,0),(0,1e4, 436.1, 1,1e4)))
+    
+    else:
+        popt, pcov = curve_fit(Lorentzian, np.array(Freqs), np.array(Counts), p0=(-200,2100,435.8,0.05,0.1), bounds=((-10000,0,435.5,0,0),(0,1e4, 436.1, 1,1e4)))
+
+    mmdepthsdr.append(1-(np.min(Lorentzian(np.array(Freqs),*popt))-bkg)/(popt[1]-bkg))
+    errormmdepthsdr.append(ErrorDRdepth(np.min(Lorentzian(Freqs,*popt)),popt[1], bkg))
+    
+
+    
+    Intens = popt[1]
+    Gamas.append(popt[3])
+    ErrorGamas.append(np.sqrt(pcov[3,3]))
+    Intensity2.append(Intens)
+    errorIntensity.append(2*np.sqrt(np.mean(Piezo2Counts[med][1:][0:20]))+np.sqrt(bkg))
+        
+    
+        
+    plt.plot([2*f*1e-6 for f in Piezo2Frequencies[med][1:]], [c for c in Piezo2Counts[med][1:]], '-o', markersize=2, alpha=0.7)
+    plt.plot([f*1 for f in Freqs],Lorentzian(Freqs,*popt))
+
+
+    
+        
+    # plt.plot([2*f*1e-6 for f in Piezo2Frequencies[med][1:]], [c for c in Piezo2Counts[med][1:]], '-o', markersize=2, alpha=0.7)
+    # plt.plot([2*f*1e-6 for f in Piezo2Frequencies[med][1:]][idxtest], [c for c in Piezo2Counts[med][1:]][idxtest], 'o',markersize=14)
+    jj=jj+1
+# plt.xlabel('Frecuencia (MHz)')
+# plt.ylabel('Counts')
+# plt.xlim(432, 446.5)
+# plt.grid()
+# plt.legend()
+# #plt.title('Espectros para distintas geometrías')
+
+if plotcurvita:
+    plt.figure()
+    #plt.errorbar(np.arange(0,len(Intensity2),1), [i/np.max(Intensity2) for i in Intensity2], yerr=[i/np.max(Intensity2) for i in errorIntensity2], fmt='o',capsize=2, markersize=8)
+    plt.errorbar(np.arange(0,len(Intensity2),1), [p for p in mmdepthsdr], yerr=errormmdepthsdr, fmt='o',capsize=2, markersize=8)
+    plt.xlabel('Ion position')
+    plt.ylabel('Intensity / DR Relative depth')
+    #plt.xticks([1,2,3,4,5])
+    #plt.xlim(200,3200)
+    plt.ylim(-0.1,1.1)
+    plt.grid()
+    #plt.axvline(3, color='salmon')
+    plt.legend()
+
+#%%
+"""
+graficos de:
+    1) intensidad del haz
+    2) profundidad de las resonancias en caso +2/+2 y en caso +2/-2
+"""
+
+import seaborn as sns
+paletadenico=sns.color_palette('rocket')
+
+plt.figure()
+plt.errorbar(np.arange(-16,18,1), [i/np.max(Intensity) for i in Intensity], yerr=[i/np.max(Intensity) for i in errorIntensity], fmt='o',capsize=2, markersize=8,color=paletadenico[1])
+#plt.errorbar(np.arange(0,len(Intensity),1), [p for p in pmdepthsdr], yerr=errorpmdepthsdr, fmt='o',capsize=2, markersize=8)
+#plt.errorbar(np.arange(0,len(Intensity),1), [p for p in mmdepthsdr[3:]], yerr=[0.5*m for m in errormmdepthsdr[3:]], fmt='o',capsize=2, markersize=8)
+plt.xlabel('Distance to center (motor steps)', fontname='STIXgeneral',fontsize=15)
+plt.ylabel('Beam intensity', fontname='STIXgeneral',fontsize=15)
+plt.xticks([-15,-10,-5,0,5,10,15], fontname='STIXgeneral',fontsize=15)
+plt.yticks([0,0.2,0.4,0.6,0.8,1], fontname='STIXgeneral',fontsize=15)
 #plt.xlim(200,3200)
 plt.ylim(-0.1,1.1)
 plt.grid()
 #plt.axvline(3, color='salmon')
 plt.legend()
+plt.tight_layout()
+plt.savefig('/home/nico/Nextcloud/Nico/Doctorado/Charlas/2023 Europe/beamintensityradial.pdf')
+
 
+#%%
 
+plt.figure()
+#plt.errorbar(np.arange(0,len(Intensity),1), [i/np.max(Intensity) for i in Intensity], yerr=[i/np.max(Intensity) for i in errorIntensity], fmt='o',capsize=2, markersize=8)
+plt.errorbar(np.arange(-16,18,1), [p for p in pmdepthsdr], yerr=errorpmdepthsdr, fmt='o',capsize=2, markersize=8,color=paletadenico[3])
+plt.errorbar(np.arange(-16,18,1), [p for p in mmdepthsdr[2:-1]], yerr=[1*m for m in errormmdepthsdr[2:-1]], fmt='o',capsize=2, markersize=8,color=paletadenico[0])
+plt.xlabel('Distance to center (motor steps)', fontname='STIXgeneral',fontsize=15)
+plt.ylabel('DR Relative depth', fontname='STIXgeneral',fontsize=15)
+plt.xticks([-15,-10,-5,0,5,10,15], fontname='STIXgeneral',fontsize=15)
+plt.yticks([0,0.2,0.4,0.6,0.8,1], fontname='STIXgeneral',fontsize=15)
+#plt.xlim(200,3200)
+plt.ylim(-0.1,1.1)
+plt.grid()
+#plt.axvline(3, color='salmon')
+plt.legend()
+plt.tight_layout()
+plt.savefig('/home/nico/Nextcloud/Nico/Doctorado/Charlas/2023 Europe/depthsradial.pdf')
 #%%
 """
 Intento ajustar un modelo para la profundidad

analisis/plots/20230817_RotationalDopplerShift_v5/RDS_piezoazimut.py

@@ -95,7 +95,7 @@ palette = sns.color_palette("tab10")
 pmlocmedvec = np.arange(0,len(PIEZOAZ_FILES),1)
 
 
-#pmlocmedvec = [14]
+#pmlocmedvec = [15]
 FullCurve = True
 
 Angles = np.arange(0,360,22.5)
@@ -155,23 +155,28 @@ print('')
 print(popt)
 
 AnglesLong = np.arange(-10,370,1)
-
+#%%
 if FullCurve:
     plt.figure()
-    plt.errorbar(Angles, [p for p in pmdepthsdraz], yerr=errorpmdepthsdraz, color='violet', fmt='o', capsize=3, markersize=8, zorder=0)
+    plt.errorbar(Angles, [p for p in pmdepthsdraz], yerr=[1*e for e in errorpmdepthsdraz], color='violet', fmt='o', capsize=3, markersize=8, zorder=0)
     plt.plot(AnglesLong,SinFit(AnglesLong,*popt), color='indigo', linewidth=4)
     
     indang = find_nearest(SinFit(AnglesLong,*popt), np.min(SinFit(AnglesLong,*popt)))
-    plt.axvline(AnglesLong[indang])
-    plt.xlabel('Azimuthal angle (°)')
-    plt.ylabel('DR Relative depth')
-    #plt.xticks([1,2,3,4,5])
+    plt.axvline(74,linestyle='dashed')
+    #plt.axvline(AnglesLong[indang])
+    plt.xlabel('Azimuthal angle (°)',fontname='STIXgeneral',fontsize=14)
+    plt.ylabel('DR Relative depth',fontname='STIXgeneral',fontsize=14)
+    plt.xticks([0,50,100,150,200,250,300,350],fontname='STIXgeneral',fontsize=14)
+    plt.yticks([0.1,0.2,0.3,0.4,0.5],fontname='STIXgeneral',fontsize=14)
     #plt.xlim(200,3200)
     #plt.ylim(-0.1,1.1)
     plt.grid()
     #plt.axvline(3, color='salmon')
     plt.legend()
 
+plt.savefig('/home/nico/Nextcloud/Nico/Doctorado/Charlas/2023 Europe/varyingazimut.pdf')
+
+
 #%%
 """
 Ahora voy a intentar ajustarlas con una lorentziana que es mejor

analisis/plots/20230912_RotationalDopplerShift_v6/RDS_piezobeamsizes.py

@@ -46,8 +46,8 @@ def SeeKeys(files):
         print(fname)
         print(list(data['datasets'].keys()))
 
-def Lorentzian( x, A, B, x0, gam):
-    C=0
+def Lorentzian( x, A, B, x0, gam,C):
+    #C=0
     return A * gam**2 / ( gam**2 + ( x - x0 )**2) + B - C*(x - x0)
 
 
@@ -608,7 +608,7 @@ pmlocmedvec = np.arange(0,len(HS_FILES),1)
 #pmlocmedvec = [-2, -1]
 
 
-plt.figure()
+plt.figure(figsize=(7,8))
 
 #bkg = np.min(PiezoS1Counts[5])
 bkg=200
@@ -642,16 +642,19 @@ for med in pmlocmedvec:
     # Intensityver.append(Intens)
     # errorIntensity.append(2*np.sqrt(np.mean(Piezo1Counts[med][1:][0:20]))+np.sqrt(bkg))
         
-    
+    fi=775
     if med not in [800]:
-        plt.plot([2*f*1e-6 for f in PiezoHSFrequencies[med][1:]], [c for c in PiezoHSCounts[med][1:]], '-o', markersize=2, alpha=0.7)
-        plt.plot([f for f in Freqs],Lorentzian(Freqs,*popt))
+        plt.plot([1e3*(2*f*1e-6-435)-fi for f in PiezoHSFrequencies[med][1:]], [1e-3*c for c in PiezoHSCounts[med][1:]], '-o', markersize=2, alpha=0.7)
+        plt.plot([1e3*(f-435)-fi for f in Freqs],[l*1e-3 for l in Lorentzian(Freqs,*popt)],linewidth=5)
     
     jj=jj+1
-# plt.xlabel('Frecuencia (MHz)')
-# plt.ylabel('Counts')
-#plt.xlim(435.2, 436.5)
+plt.xlabel('Frequency (kHz)',fontname='STIXgeneral',fontsize=50)
+plt.ylabel('kCounts',fontname='STIXgeneral',fontsize=50)
+plt.xticks([-50,-25,0,25,50],fontname='STIXgeneral',fontsize=35)
+plt.yticks([3.5,4,4.5],fontname='STIXgeneral',fontsize=35)
+plt.tight_layout()
 plt.grid()
+plt.savefig('/home/nico/Nextcloud/Nico/Doctorado/Charlas/2023 Europe/DDresonancesexperimental_fine.pdf')
 # plt.legend()
-plt.title(f'Ancho: {round(1e3*popt[3],2)} kHz')
+#plt.title(f'Ancho: {round(1e3*popt[3],2)} kHz')
 

analisis/plots/20230912_RotationalDopplerShift_v7/Data/EITfit/threeLevel_2repumps_CPTPlotter.py

+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Tue Sep  1 17:58:39 2020
+
+@author: oem
+"""
+
+
+
+import os
+import numpy as np
+#os.chdir('/home/oem/Nextcloud/G_liaf/liaf-TrampaAnular/Código General/EIT-CPT/Buenos Aires/Experiment Simulations/CPT scripts/Eight Level 2 repumps')
+from threeLevel_2repumps_AnalysisFunctions import CalculoTeoricoDarkResonances_8levels, GetMinimaInfo, GetPlotsofFluovsAngle_8levels, PerformExperiment_8levels, FindDRFrequencies, FindRelativeFluorescencesOfDR, GenerateNoisyCPT, SmoothNoisyCPT, GetFinalMaps, GenerateNoisyCPT_fixedRabi, GenerateNoisyCPT_fit
+import matplotlib.pyplot as plt
+import time
+from threeLevel_2repumps_AnalysisFunctions import MeasureRelativeFluorescenceFromCPT, IdentifyPolarizationCoincidences, RetrieveAbsoluteCoincidencesBetweenMaps, GetClosestIndex
+
+#C:\Users\Usuario\Nextcloud\G_liaf\liaf-TrampaAnular\Código General\EIT-CPT\Buenos Aires\Experiment Simulations\CPT scripts\Eight Level 2 repumps
+
+ub = 9.27e-24
+h = 6.63e-34
+c = (ub/h)*1e-4 #en unidades de MHz/G
+
+#u = 1e6
+u = 33.5e6
+
+B = (u/(2*np.pi))/c
+
+
+#sg, sp = 0.6, 5  #parámetros de control, saturación del doppler y repump
+#rabG, rabP = sg*gPS, sp*gPD #frecuencias de rabi
+
+gPS, gPD, = 2*np.pi*21.58e6, 2*np.pi*1.35e6 #anchos de linea de las transiciones
+
+
+
+lw = 0.1
+DopplerLaserLinewidth, RepumpLaserLinewidth, ProbeLaserLinewidth = lw, lw, lw #ancho de linea de los laseres
+
+DetDoppler = -36 #42
+DetRepumpVec = [DetDoppler+29.6]
+
+Tvec = [0.7] #temperatura en mK
+alpha = 0*(np.pi/180) #angulo entre los láseres
+
+
+phidoppler, titadoppler = 0, 90
+phirepump, titarepump = 0,  0
+phiprobe = 0
+titaprobe = 90
+
+#Calculo las resonancias oscuras teóricas
+#ResonanciasTeoricas, DRPositivas = CalculoTeoricoDarkResonances_8levels(u/(2*np.pi*1e6), titadoppler, DetDoppler, DetRepump)
+
+#Parametros de la simulacion cpt
+center = -45
+span = 80
+freqMin = center-span*0.5
+freqMax = center+span*0.5
+
+""" parametros para tener espectros coherentes
+freqMin = -56
+freqMax = 14
+"""
+freqStep = 1e-1
+
+noiseamplitude = 0
+
+RelMinMedido0Vector = []
+RelMinMedido1Vector = []
+RelMinMedido2Vector = []
+RelMinMedido3Vector = []
+RelMinMedido4Vector = []
+
+#Sr = np.arange(0, 10, 0.2)
+
+#Sg = np.arange(0.01, 1, 0.05)
+#Sp = np.arange(0.1, 6.1, 1)
+
+#Sg = [0.6**2]
+#Sp = [2.3**2]
+
+
+Sg = [1.4]
+Sp = [6]
+
+Sr = [11]
+
+
+
+
+i = 0
+
+save = False
+
+
+showFigures = True
+
+if not showFigures:
+    plt.ioff()
+else:
+    plt.ion()
+    
+fig1, ax1 = plt.subplots()
+
+offsetx = 464
+
+ax1.plot([f-offsetx for f in FreqsDR], CountsDR, 'o')
+
+run = True
+
+Scale = 730
+Offset = 600 #600 para 20k cuentas aprox
+
+MaxCoherenceValue = []
+
+for sg in Sg:
+    for sp in Sp:
+        rabG, rabP = sg*gPS, sp*gPD
+        for Ti in Tvec:
+            T = Ti*1e-3
+            for DetRepump in DetRepumpVec:
+                print(T)
+                for sr in Sr:
+                
+                    rabR = sr*gPD
+                    
+                    #MeasuredFreq, MeasuredFluo = GenerateNoisyCPT(rabG, rabR, rabP, gPS, gPD, DetDoppler, DetRepump, u, DopplerLaserLinewidth, RepumpLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, [titaprobe], phirepump, titarepump, freqMin, freqMax, freqStep, plot=False, solvemode=1, detpvec=None, noiseamplitude=noiseamplitude)
+                    if run:
+                        MeasuredFreq4, MeasuredFluo4 = GenerateNoisyCPT_fixedRabi(sg, sr, sp, gPS, gPD, DetDoppler, DetRepump, u, DopplerLaserLinewidth, RepumpLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, [titaprobe], phirepump, titarepump, freqMin, freqMax, freqStep, plot=False, solvemode=1, detpvec=None, noiseamplitude=noiseamplitude)
+                    
+                    #SmoothFluo = SmoothNoisyCPT(MeasuredFluo, window=9, poly=2)
+                    SmoothFluo4 = MeasuredFluo4
+                    
+                    #Scale = max(BestC)/max([100*s for s in SmoothFluo4])
+                    ax1.plot(MeasuredFreq4, [Scale*100*f + Offset for f in SmoothFluo4], label=f'Sr = {sr}')
+                    ax1.axvline(DetDoppler, linestyle='--', linewidth=1)
+                    #if sr != 0:
+                        #ax1.axvline(DetRepump, linestyle='--', linewidth=1)
+
+                    MaxCoherenceValue.append(np.max(SmoothFluo4))
+
+                    #print(titaprobe)
+                    ax1.set_xlabel('Detuning Rebombeo (MHz)')
+                    ax1.set_ylabel('Fluorescencia (AU)')
+                    ax1.set_title(f'B: {round(B, 2)} G, Sdop: {round(sg, 2)}, Sp: {round(sp, 2)}, Sr: {round(sr, 2)}, lw: {lw} MHz, T: {Ti} mK')
+                    #ax1.set_ylim(0, 8)
+                    #ax1.axvline(DetDoppler, linestyle='dashed', color='red', linewidth=1)
+                    #ax1.axvline(DetRepump, linestyle='dashed', color='black', linewidth=1)
+                    #ax1.set_title('Pol Doppler y Repump: Sigma+ Sigma-, Pol Probe: PI')
+                    #ax1.legend()
+                    ax1.grid()
+                    print (f'{i+1}/{len(Sg)*len(Sp)}')
+                    i = i + 1
+                    if save:
+                        plt.savefig(f'Mapa_plots_100k_1mk/CPT_SMSM_sdop{round(sg, 2)}_sp{round(sp, 2)}_sr{round(sr, 2)}.jpg')
+                    ax1.legend()
+                    
+"""
+plt.figure()
+plt.plot(Sr, MaxCoherenceValue, 'o')
+plt.xlabel('Sr')
+plt.ylabel('Coherence')
+"""
+
+"""
+                        
+plt.figure()
+plt.plot(MeasuredFreq, [100*f for f in SmoothFluo], color='darkred')
+plt.xlabel('Desintonía 866 (MHz)')
+plt.ylabel('Fluorescencia (A.U.)')
+plt.axvline(-30, color='darkblue', linewidth=1.2, linestyle='--')
+plt.yticks(np.arange(0.4, 1.8, 0.2))
+plt.ylim(0.5, 1.6)
+plt.grid()
+              
+
+
+plt.figure()
+plt.plot(MeasuredFreq4, [100*f for f in SmoothFluo4], color='darkred')
+plt.xlabel('Desintonía 866 (MHz)')
+plt.ylabel('Fluorescencia (A.U.)')
+plt.axvline(-30, color='darkblue', linewidth=1.2, linestyle='--')
+plt.yticks(np.arange(0.8, 2.4, 0.4))
+plt.grid()
+              
+"""
+
+
+
+
+#%%
+from scipy.optimize import curve_fit
+
+T = 0.5e-3
+
+sg = 0.7
+sp = 6
+sr = 0
+DetDoppler = -14
+DetRepump = 0
+
+FitsSp = []
+FitsOffset = []
+
+Sg = [0.87]
+
+def FitEIT(freqs, SP, offset):
+    MeasuredFreq, MeasuredFluo = GenerateNoisyCPT_fit(0.87, sr, SP, gPS, gPD, DetDoppler, DetRepump, u, DopplerLaserLinewidth, RepumpLaserLinewidth, ProbeLaserLinewidth, T, alpha, phidoppler, titadoppler, phiprobe, [titaprobe], phirepump, titarepump, freqs, plot=False, solvemode=1, detpvec=None, noiseamplitude=noiseamplitude)
+    FinalFluo = [f*43000 + 2685 for f in MeasuredFluo]
+    return FinalFluo
+
+freqs = [f-offsetx+32 for f in FreqsDR]
+freqslong = np.arange(min(freqs), max(freqs)+freqs[1]-freqs[0], 0.1*(freqs[1]-freqs[0]))
+
+popt, pcov = curve_fit(FitEIT, freqs, CountsDR, p0=[5, 700], bounds=(0, [10, 1e6]))
+
+FitsSp.append(popt[0])
+FitsOffset.append(popt[1])
+
+print(popt)
+
+FittedEIT = FitEIT(freqslong, *popt)
+
+
+plt.figure()
+plt.errorbar(freqs, CountsDR, yerr=2*np.sqrt(CountsDR), fmt='o', capsize=2, markersize=2)
+plt.plot(freqslong, FitEIT(freqslong, *popt))
+plt.title(f'Sdop: {round(popt[0], 2)}, Spr: {round(popt[1], 2)}, T: {T*1e3} mK, detDop: {DetDoppler} MHz')
+
+np.savetxt('CPT_measured.txt', np.transpose([freqs, CountsDR]))
+np.savetxt('CPT_fitted.txt', np.transpose([freqslong, FittedEIT]))

analisis/plots/20230912_RotationalDopplerShift_v7/RDS_piezobeamsizes_vert2.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/20230912_RotationalDopplerShift_v7/Data')
+
+
+"""
+en este codigo ploteo espectros CPT de resonancias D-D para configuracion +2/+2 y +2/-2 (usando pentaprisma)
+"""
+
+def find_nearest(array, value):
+    array = np.asarray(array)
+    idx = (np.abs(array - value)).argmin()
+    return idx
+
+
+def Split(array,n):
+    length=len(array)/n
+    splitlist = []
+    jj = 0
+    while jj<length:
+        partial = []
+        ii = 0
+        while ii < n:
+            partial.append(array[jj*n+ii])
+            ii = ii + 1
+        splitlist.append(partial)
+        jj = jj + 1
+    return splitlist
+
+
+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()))
+
+def Lorentzian( x, A, B, x0, gam,C):
+    #C=0
+    return A * gam**2 / ( gam**2 + ( x - x0 )**2) + B - C*(x - x0)
+
+def Lorentzian2( x, A, B, x0, gam):
+    C=0
+    A=0
+    return A * gam**2 / ( gam**2 + ( x - x0 )**2) + B - C*(x - x0)
+
+
+Piezo1Counts = []
+Piezo1Frequencies = []
+
+PIEZOS1_FILES = [59,60,62,63,64,65,66,70,71,72,75,76,77,78,79,80,81,82]
+
+
+
+for i in PIEZOS1_FILES:
+    #print(str(i) + ' - ' + fname)
+    if i < 100 and i > 9:
+        data = h5py.File(f'VaryingBeamsize/Size1/0000159{i}-IR_Scan_withcal_optimized'+'.h5', 'r')
+    elif i <= 9:
+        data = h5py.File(f'VaryingBeamsize/Size1/00001570{i}-IR_Scan_withcal_optimized'+'.h5', 'r')
+    else:
+        data = h5py.File(f'VaryingBeamsize/Size4vertical/000015{i}-IR_Scan_withcal_optimized'+'.h5', 'r')
+    Piezo1Counts.append(np.array(data['datasets']['counts_spectrum']))
+    Piezo1Frequencies.append(np.array(data['datasets']['IR1_Frequencies']))
+
+def ErrorDRdepth(p, f, b):
+    ep = np.sqrt(p)
+    ef = np.sqrt(f)
+    eb = np.sqrt(b)
+    derivadap = 1/((f-b)**2)
+    derivadaf = ((p-b)/((f-b)**2))**2
+    derivadab = ((p-f)/((f-b)**2))**2
+    return 2*np.sqrt(derivadap*ep*ep + derivadaf*ef*ef + derivadab*eb*eb)
+
+
+#%%
+"""
+Ahora voy a intentar ajustarlas con una lorentziana que es mejor
+"""
+import seaborn as sns
+"""
+Resonancias DD configuracion +2/-2 colineal variando la ubicacion del ion en los haces
+
+Moviendo VERTICALMENTE el haz, pasos de a 50 (updated), lente 200 mm, haz chiquito
+"""
+
+power=1
+
+palette = sns.color_palette("tab10")
+
+pmlocmedvec2 = np.arange(0,len(PIEZOS1_FILES),1)
+
+pmlocmedvec2 = [0,1,2,3,4,5,6,7,8,9,11,12,13,14,15,16,17,18]
+
+
+#pmlocmedvec2 = []
+
+plotcurvita = 1
+
+plt.figure()
+
+bkg=np.mean(Piezo1Counts[2][64:70])
+
+pmdepthsdrver2=[]
+errorpmdepthsdrver2=[]
+
+Intensityver2 = []
+errorIntensityver2 = []
+
+Gamas2 = []
+ErrorGamas2 = []
+
+jj=0
+for med in pmlocmedvec2:
+
+    if power==0:
+        Freqs = [2*f*1e-6 for f in Piezo1Frequencies[med][1:]]
+        Counts = [c for c in Piezo1Counts[med][1:]]
+    else:
+        Freqs = [2*f*1e-6 for f in Piezo1Frequencies[med][1:]]
+        Counts = [c for c in Piezo1Counts[med][1:]]
+        
+
+    if med == 7:
+        Counts = Counts[20:]
+        Freqs= Freqs[20:]
+       
+        # popt, pcov = curve_fit(Lorentzian, np.array(Freqs), np.array(Counts), p0=(-265,1700,435.5,0.,0), bounds=((-10000,0,435.,0,0),(0,1e4, 436, 100,1)))
+        popt, pcov = curve_fit(Lorentzian, np.array(Freqs), np.array(Counts), p0=(-200,2100,435.8,0.05,0.1), bounds=((-10000,0,435.5,0,0),(0,1e4, 436.1, 1,1)))
+
+    if med == 8:
+        Counts = Counts[20:]
+        Freqs= Freqs[20:]
+       
+        # popt, pcov = curve_fit(Lorentzian, np.array(Freqs), np.array(Counts), p0=(-265,1700,435.5,0.,0), bounds=((-10000,0,435.,0,0),(0,1e4, 436, 100,1)))
+        popt, pcov = curve_fit(Lorentzian, np.array(Freqs), np.array(Counts), p0=(-200,2100,435.8,0.05,0.1), bounds=((-10000,0,435.5,0,0),(0,1e4, 436.1, 1,1)))
+
+
+
+    elif med == 2:
+        Counts = Counts[0:60]
+        Freqs= Freqs[0:60]
+        popt, pcov = curve_fit(Lorentzian, np.array(Freqs), np.array(Counts), p0=(-200,21000,435.8,0.5,0), bounds=((-10000,0,435.5,0.0005,0),(0,1e8, 436.1, 1,1e3)))
+
+
+    elif med == 10:
+        Counts = Counts[20:]
+        Freqs= Freqs[20:]
+        popt, pcov = curve_fit(Lorentzian, np.array(Freqs), np.array(Counts), p0=(-200,21000,435.8,0.05,0), bounds=((-10000,0,435.5,0,0),(0,1e8, 436.1, 1,1e3)))
+
+    elif med == 1114:
+        # Counts = Counts[50:150]
+        # Freqs= Freqs[50:150]
+        popt, pcov = curve_fit(Lorentzian, np.array(Freqs), np.array(Counts), p0=(-200,21000,435.8,0.05,0), bounds=((-10000,0,435.5,0,0),(0,1e4, 436.1, 1,1e4)))
+
+    else:
+        popt, pcov = curve_fit(Lorentzian, np.array(Freqs), np.array(Counts), p0=(-200,21000,435.8,0.05,0.1), bounds=((-10000,0,435.5,0,0),(0,1e8, 436.1, 1,1e4)))
+
+    if med==0:
+        pmdepthsdrver2.append(1-(np.min(Lorentzian(np.array(Freqs),*popt))-bkg)/(popt[1]-bkg))
+        #errorpmdepthsdrver1.append(ErrorDRdepth(np.min(Lorentzian(Freqs,*popt)),popt[1], bkg))
+        errorpmdepthsdrver2.append(ErrorDRdepth(np.min(Lorentzian(Freqs,*popt)),popt[1], bkg))
+    else:
+        pmdepthsdrver2.append(1-(np.min(Lorentzian(np.array(Freqs),*popt))-bkg)/(popt[1]-bkg))
+        #errorpmdepthsdrver1.append(ErrorDRdepth(np.min(Lorentzian(Freqs,*popt)),popt[1], bkg))
+        errorpmdepthsdrver2.append(ErrorDRdepth(np.min(Lorentzian(Freqs,*popt)),popt[1], bkg))
+        
+        
+    Intens2 = popt[1]
+    
+    Gamas2.append(popt[3])
+    ErrorGamas2.append(np.sqrt(pcov[3,3]))
+    Intensityver2.append(Intens2)
+    # errorIntensity.append(2*np.sqrt(np.mean(Piezo1Counts[med][1:][0:20]))+np.sqrt(bkg))
+
+    if med not in [1000]:
+        if power==0:
+            plt.plot([2*f*1e-6 for f in Piezo1Frequencies[med][1:]], [c for c in Piezo1Counts[med][1:]], '-o', markersize=2, alpha=0.7)
+            plt.plot([f*1 for f in Freqs],Lorentzian(Freqs,*popt))
+        else:
+            plt.plot([2*f*1e-6 for f in Piezo1Frequencies[med][1:]], [c for c in Piezo1Counts[med][1:]], '-o', markersize=2, alpha=0.7)
+            plt.plot([f*1 for f in Freqs],Lorentzian(Freqs,*popt))
+
+    plt.axhline(bkg,linestyle='dashed',color='k')
+    jj=jj+1
+plt.grid()
+
+
+if plotcurvita:
+    plt.figure()
+    plt.errorbar(np.arange(0,len(Intensityver2),1), [i/np.max(Intensityver2) for i in Intensityver2], yerr=np.sqrt(Intensityver2)/np.max(Intensityver2), fmt='-o', capsize=3,markersize=8)
+    plt.errorbar(np.arange(0,len(Intensityver2),1), [p for p in pmdepthsdrver2], yerr= errorpmdepthsdrver2, fmt='o', capsize=3, markersize=8)
+    #plt.errorbar(np.arange(0,len(Intensityver2),1), [p for p in Gamas2], yerr=ErrorGamas2, fmt='o', capsize=3, markersize=8)
+    plt.xlabel('Ion position')
+    plt.ylabel('Intensity / DR Relative depth')
+    #plt.xticks([1,2,3,4,5])
+    #plt.xlim(200,3200)
+    plt.ylim(-0.1,1.1)
+    plt.grid()
+    #plt.axvline(3, color='salmon')
+    plt.legend()
+
+# plt.figure()
+# plt.errorbar(np.arange(0,len(Intensityver1)-1,1), [p*1e3 for p in Gamas1[1:]], yerr=[e*1e3 for e in ErrorGamas1[1:]], fmt='o', capsize=3, markersize=3)
+# plt.yscale('log')
+# plt.grid()
+# plt.yticks([1e3, 1e2, 1e1])
+