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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/20230817_RotationalDopplerShift_v5/Data')
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"""
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()))
PiezoVerCounts = []
PiezoVerFrequencies = []
PIEZOVER_FILES = np.arange(922, 948,1)
for i in PIEZOVER_FILES:
#print(str(i) + ' - ' + fname)
data = h5py.File(f'VaryingBeamlocation/Directions/Vertical/000014{i}-IR_Scan_withcal_optimized'+'.h5', 'r')
PiezoVerCounts.append(np.array(data['datasets']['counts_spectrum']))
PiezoVerFrequencies.append(np.array(data['datasets']['IR1_Frequencies']))
PiezoVerDCounts = []
PiezoVerDFrequencies = []
PIEZOVERD_FILES = list(np.arange(70, 97,1))+list(np.arange(99,116))
for i in PIEZOVERD_FILES:
#print(str(i) + ' - ' + fname)
if i <100:
data = h5py.File(f'VaryingBeamlocation/Directions/VerticalDense/0000150{i}-IR_Scan_withcal_optimized'+'.h5', 'r')
else:
data = h5py.File(f'VaryingBeamlocation/Directions/VerticalDense/000015{i}-IR_Scan_withcal_optimized'+'.h5', 'r')
PiezoVerDCounts.append(np.array(data['datasets']['counts_spectrum']))
PiezoVerDFrequencies.append(np.array(data['datasets']['IR1_Frequencies']))
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PiezoDiagCounts = []
PiezoDiagFrequencies = []
PIEZODIAG_FILES = list(np.arange(948, 976,1))
for i in PIEZODIAG_FILES:
#print(str(i) + ' - ' + fname)
data = h5py.File(f'VaryingBeamlocation/Directions/Diagonal/000014{i}-IR_Scan_withcal_optimized'+'.h5', 'r')
PiezoDiagCounts.append(np.array(data['datasets']['counts_spectrum']))
PiezoDiagFrequencies.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)
def Lorentzian( x, A, B, x0, gam ):
return A * gam**2 / ( gam**2 + ( x - x0 )**2) + B
#%%
"""
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
"""
palette = sns.color_palette("tab10")
pmlocmedvec = np.arange(0,len(PIEZOVER_FILES),1)
#pmlocmedvec = [26]
plt.figure()
bkg = np.min(PiezoVerCounts[5])
pmdepthsdrver=[]
errorpmdepthsdrver=[]
Intensityver = []
errorIntensityver = []
jj=0
for med in pmlocmedvec:
Freqs = [2*f*1e-6 for f in PiezoVerFrequencies[med][1:]]
Counts = [c for c in PiezoVerCounts[med][1:]]
popt, pcov = curve_fit(Lorentzian, Freqs, Counts, p0=(-200,2100,435.8,0.05), bounds=((-10000,0,435.5,0),(0,1e4, 436.1, 1)))
pmdepthsdrver.append(1-(np.min(Lorentzian(Freqs,*popt))-bkg)/(popt[1]-bkg))
errorpmdepthsdrver.append(ErrorDRdepth(np.min(Lorentzian(Freqs,*popt)),popt[1], bkg))
Intens = popt[1]
Intensityver.append(Intens)
# errorIntensity.append(2*np.sqrt(np.mean(Piezo1Counts[med][1:][0:20]))+np.sqrt(bkg))
if med not in [800]:
plt.plot([2*f*1e-6 for f in PiezoVerFrequencies[med][1:]], [c for c in PiezoVerCounts[med][1:]], '-o', markersize=2, alpha=0.7)
plt.plot(Freqs,Lorentzian(Freqs,*popt))
jj=jj+1
# plt.xlabel('Frecuencia (MHz)')
# plt.ylabel('Counts')
#plt.xlim(435.2, 436.5)
plt.grid()
# plt.legend()
# #plt.title('Espectros para distintas geometrías')
plt.figure()
plt.plot(np.arange(0,len(Intensityver),1), [i/np.max(Intensityver) for i in Intensityver], '-o',markersize=8)
plt.plot(np.arange(0,len(Intensityver),1), [p for p in pmdepthsdrver], 'o',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()
#%%
"""
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 diagonalmente el haz
"""
palette = sns.color_palette("tab10")
pmlocmedvec = np.arange(0,len(PIEZODIAG_FILES),1)
#pmlocmedvec = [0,1]
plt.figure()
bkg = np.min(PiezoDiagCounts[5])
pmdepthsdrdiag=[]
errorpmdepthsdrdiag=[]
Intensitydiag = []
errorIntensitydiag = []
jj=0
for med in pmlocmedvec:
Freqs = [2*f*1e-6 for f in PiezoDiagFrequencies[med][1:]]
Counts = [c for c in PiezoDiagCounts[med][1:]]
if med==2:
Freqs = Freqs[1:-30]
Counts = Counts[1:-30]
popt, pcov = curve_fit(Lorentzian, Freqs, Counts, p0=(-200,2100,435.8,0.05), bounds=((-10000,0,435.5,0),(0,1e4, 436.1, 1)))
elif med==1:
Freqs = Freqs[10:-30]
Counts = Counts[10:-30]
popt, pcov = curve_fit(Lorentzian, Freqs, Counts, p0=(-200,2100,435.8,0.05), bounds=((-10000,0,435.7,0),(0,1e4, 436.1, 1)))
elif med==5:
Freqs = Freqs[10:-55]+Freqs[-30:-1]
Counts = Counts[10:-55]+Counts[-30:-1]
popt, pcov = curve_fit(Lorentzian, Freqs, Counts, p0=(-200,2100,435.8,0.05), bounds=((-10000,0,435.5,0),(0,1e4, 436.1, 1)))
else:
popt, pcov = curve_fit(Lorentzian, Freqs, Counts, p0=(-200,2100,435.8,0.05), bounds=((-10000,0,435.5,0),(0,1e4, 436.1, 1)))
pmdepthsdrdiag.append(1-(np.min(Lorentzian(Freqs,*popt))-bkg)/(popt[1]-bkg))
errorpmdepthsdrdiag.append(ErrorDRdepth(np.min(Lorentzian(Freqs,*popt)),popt[1], bkg))
Intens = popt[1]
Intensitydiag.append(Intens)
# errorIntensity.append(2*np.sqrt(np.mean(Piezo1Counts[med][1:][0:20]))+np.sqrt(bkg))
if med not in [800]:
plt.plot([2*f*1e-6 for f in PiezoDiagFrequencies[med][1:]], [c for c in PiezoDiagCounts[med][1:]], '-o', markersize=2, alpha=0.7)
plt.plot(Freqs,Lorentzian(Freqs,*popt))
jj=jj+1
# plt.xlabel('Frecuencia (MHz)')
# plt.ylabel('Counts')
#plt.xlim(435.2, 436.5)
plt.grid()
# plt.legend()
# #plt.title('Espectros para distintas geometrías')
plt.figure()
plt.plot(np.arange(0,len(Intensitydiag),1), [i/np.max(Intensitydiag) for i in Intensitydiag], '-o',markersize=8)
plt.plot(np.arange(0,len(Intensitydiag),1), [p for p in pmdepthsdrdiag], 'o',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()
#%%
"""
Ploteo en conjunto. La horizontal sale de RDS_piezo.py
"""
cap=3
plt.figure()
plt.plot(np.arange(0,len(Intensitydiag),1), [i/np.max(Intensitydiag) for i in Intensitydiag], '-o',markersize=8)
#plt.plot(np.arange(0,len(Intensitydiag),1), [p for p in pmdepthsdrdiag], 'o',markersize=8, label='Diagonal')
plt.errorbar(np.arange(0,len(Intensitydiag),1), [p for p in pmdepthsdrdiag], yerr=errorpmdepthsdrdiag, fmt='o',capsize=cap,markersize=8, label='Diagonal')
#plt.plot(np.arange(0,len(Intensityver),1), [i/np.max(Intensityver) for i in Intensityver], '-o',markersize=8)
#plt.plot(np.arange(0,len(Intensityver),1), [p for p in pmdepthsdrver], 'o',markersize=8, label='Vertical')
plt.errorbar(np.arange(0,len(Intensityver),1), [p for p in pmdepthsdrver], yerr=errorpmdepthsdrver, fmt='o', capsize=cap,markersize=8, label='Vertical')
scale = 1.6
#plt.plot([s*scale for s in np.arange(16,len(Intensity),1)-16], [i/np.max(Intensity) for i in Intensity[16:]], '-o',markersize=8)
#plt.plot([s*scale for s in np.arange(16,len(Intensity),1)-16], [p for p in pmdepthsdr[16:]], 'o',markersize=8, label='Horizontal')
plt.errorbar([s*scale for s in np.arange(16,len(Intensity),1)-16], [p for p in pmdepthsdr[16:]], yerr=errorpmdepthsdr[16:], fmt='o', capsize=cap,markersize=8, label='Horizontal')
plt.xlabel('Ion position')
plt.ylabel('Intensity / DR Relative depth')
#plt.xticks([1,2,3,4,5])
plt.xlim(-1,15)
plt.ylim(-0.1,1.1)
plt.grid()
#plt.axvline(3, color='salmon')
plt.legend()
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#%%
import seaborn as sns
"""
Resonancias DD configuracion +2/-2 colineal variando la ubicacion del ion en los haces
Moviendo verticalmente el haz pero con mayor densidad de puuntos
"""
palette = sns.color_palette("tab10")
pmlocmedvec = np.arange(0,len(PIEZOVERD_FILES),1)
#pmlocmedvec = [6]
plt.figure()
#bkg = np.min(PiezoVerDCounts[5])
bkg=150
pmdepthsdrverd=[]
errorpmdepthsdrverd=[]
Intensityverd = []
errorIntensityverd = []
jj=0
for med in pmlocmedvec:
Freqs = [2*f*1e-6 for f in PiezoVerDFrequencies[med][1:]]
Counts = [c for c in PiezoVerDCounts[med][1:]]
popt, pcov = curve_fit(Lorentzian, Freqs, Counts, p0=(-200,2100,435.8,0.05), bounds=((-10000,0,435.5,0),(0,1e4, 436.1, 1)))
pmdepthsdrverd.append(1-(np.min(Lorentzian(Freqs,*popt))-bkg)/(popt[1]-bkg))
errorpmdepthsdrverd.append(ErrorDRdepth(np.min(Lorentzian(Freqs,*popt)),popt[1], bkg))
Intens = popt[1]
Intensityverd.append(Intens)
errorIntensityverd.append(2*np.sqrt(Intens)+np.sqrt(bkg))
if med not in [800]:
plt.plot([2*f*1e-6 for f in PiezoVerDFrequencies[med][1:]], [c for c in PiezoVerDCounts[med][1:]], '-o', markersize=2, alpha=0.7)
plt.plot(Freqs,Lorentzian(Freqs,*popt))
jj=jj+1
# plt.xlabel('Frecuencia (MHz)')
# plt.ylabel('Counts')
#plt.xlim(435.2, 436.5)
plt.grid()
# plt.legend()
# #plt.title('Espectros para distintas geometrías')
plt.figure()
plt.errorbar(np.arange(0,len(Intensityverd),1), [i/np.max(Intensityverd) for i in Intensityverd], yerr=[e/np.max(Intensityverd) for e in errorIntensityverd], fmt='o', capsize=3, markersize=8)
plt.errorbar(np.arange(0,len(Intensityverd),1), [p for p in pmdepthsdrverd], yerr=errorpmdepthsdrverd, fmt='o',color='limegreen',capsize=3,markersize=8)
plt.xlabel('Screw step')
plt.ylabel('Intensity / DR Relative depth')
#plt.xticks([1,2,3,4,5])
plt.xlim(-2,35)
plt.ylim(-0.1,1.1)
plt.grid()
#plt.axvline(3, color='salmon')
plt.legend()