def get_3mmt_data(folder,folder_timestamp,RO_correct=True,ssro_calib_timestamp=None,tomo_bases='XXX',get_title=False,return_orientations=False):
a = CP.ConditionalParityAnalysis(folder)
#a.get_sweep_pts()
a.get_readout_results(name='adwindata', post_select_QEC = True,orientation_correct=True)
orientations = a.orientations
orientation_c = a.orientations[2]
if orientation_c == 'negative':
multiply_by = -1
else:
multiply_by = 1
#print(a.orientations,multiply_by)
if RO_correct == True:
if ssro_calib_timestamp == None:
ssro_calib_folder = toolbox.latest_data('SSRO',older_than=folder_timestamp)
analysis_file=os.path.join(ssro_calib_folder,'analysis.hdf5')
if not os.path.exists(analysis_file):
ssro.ssrocalib(ssro_calib_folder)
else:
ssro_dstmp, ssro_tstmp = toolbox.verify_timestamp(ssro_calib_timestamp)
ssro_calib_folder = toolbox.datadir + '\\'+ssro_dstmp+'\\'+ssro_tstmp+'_AdwinSSRO_SSROCalibration_111_1_sil18'#GHZ_'+tomo_bases
#print ssro_calib_folder
a.get_electron_ROC(ssro_calib_folder = ssro_calib_folder, post_select_QEC = True)
#take the [0,0] part of the arrays right now; no sweep_pts
p0_00,u_p0_00 = multiply_by*(a.p0_00[0,0]-0.5)*2,(2*a.u_p0_00[0,0])
p0_01,u_p0_01 = multiply_by*(a.p0_01[0,0]-0.5)*2,(2*a.u_p0_01[0,0])
p0_10,u_p0_10 = multiply_by*(a.p0_10[0,0]-0.5)*2,(2*a.u_p0_10[0,0])
p0_11,u_p0_11 = multiply_by*(a.p0_11[0,0]-0.5)*2,(2*a.u_p0_11[0,0])
else:
p0_00,u_p0_00 = multiply_by*(a.normalized_ssro_00[0,0]-0.5)*2,(2*a.u_normalized_ssro_00[0,0])
p0_01,u_p0_01 = multiply_by*(a.normalized_ssro_01[0,0]-0.5)*2,(2*a.u_normalized_ssro_01[0,0])
p0_10,u_p0_10 = multiply_by*(a.normalized_ssro_10[0,0]-0.5)*2,(2*a.u_normalized_ssro_10[0,0])
p0_11,u_p0_11 = multiply_by*(a.normalized_ssro_11[0,0]-0.5)*2,(2*a.u_normalized_ssro_11[0,0])
if get_title:
a_list_name = "".join(aa for aa in a.a_list)
b_list_name = "".join(aa for aa in a.b_list)
c_list_name = "".join(aa for aa in a.c_list)
title = a_list_name+' '+b_list_name+' '+c_list_name
else:
title=''
p = (a.p00[0,0],a.p01[0,0],a.p10[0,0],a.p11[0,0])
y = (p0_00,p0_01,p0_10,p0_11)
y_avg = np.mean(y, axis=0)
#print y_avg
y_err = (u_p0_00,u_p0_01,u_p0_10,u_p0_11)
if return_orientations:
return(p,y,y_err,title,orientations)
return(p,y,y_err,title)
def get_debug_data(folder,folder_timestamp,RO_correct=True,ssro_calib_timestamp=None,tomo_bases="XXX"):
a = CP.ConditionalParityAnalysis(folder)
#a.get_sweep_pts()
a.get_readout_results(name='adwindata', post_select = True, orientation_correct=True)
orientation_b = a.orientations[1]
if orientation_b == 'negative':
multiply_by = -1
else:
multiply_by = 1
#print(a.orientations,multiply_by)
if RO_correct == True:
if ssro_calib_timestamp == None:
ssro_calib_folder = toolbox.latest_data('SSRO',older_than=folder_timestamp)
if not os.path.exists(os.path.join(ssro_calib_folder,'analysis.hdf5')):
ssro.ssrocalib(ssro_calib_folder)
else:
ssro_dstmp, ssro_tstmp = toolbox.verify_timestamp(ssro_calib_timestamp)
ssro_calib_folder = toolbox.datadir + '\\'+ssro_dstmp+'\\'+ssro_tstmp+'_AdwinSSRO_SSROCalibration_111_1_sil18'#GHZ_'+tomo_bases
# print ssro_calib_folder
a.get_electron_ROC(ssro_calib_folder = ssro_calib_folder)
#take the [0,0] part of the arrays right now; no sweep_pts
p0_0,u_p0_0 = multiply_by*(a.p0_0[0,0]-0.5)*2,(2*a.u_p0_0[0,0])
p0_1,u_p0_1 = multiply_by*(a.p0_1[0,0]-0.5)*2,(2*a.u_p0_1[0,0])
else:
p0_0,u_p0_0 = multiply_by*(a.normalized_ssro_0[0,0]-0.5)*2,(2*a.u_normalized_ssro_0[0,0])
p0_1,u_p0_1 = multiply_by*(a.normalized_ssro_1[0,0]-0.5)*2,(2*a.u_normalized_ssro_1[0,0])
p = (a.p0,a.p1)
y = (p0_0,p0_1)
y_avg = np.mean(y, axis=0)
#print y_avg
y_err = (u_p0_0,u_p0_1)
return(p,y,y_err)
def append_data(timestamps_1=[None, None],
timestamps_2=[],
timestamps_3=[],
ssro_folder=None,
det=False,
ms=None):
y_total = ([])
y_err_total = ([])
x_total = ([])
x_labels_total = ([])
p0 = ([])
p1 = ([])
time_list = [timestamps_1]
if timestamps_2 != []:
time_list = [timestamps_1, timestamps_2]
if timestamps_3 != []:
time_list = [timestamps_1, timestamps_2, timestamps_3]
for timestamps in time_list:
folder_a = toolbox.data_from_time(timestamps[0])
folder_b = toolbox.data_from_time(timestamps[1])
if det == False:
a = mbi.MBIAnalysis(folder_a)
else:
a = CP.ConditionalParityAnalysis(folder_a)
a.get_sweep_pts()
a.get_readout_results(name='adwindata')
a.get_electron_ROC(ssro_folder)
y_a = ((a.p0.reshape(-1)[:]) - 0.5) * 2
y_err_a = 2 * a.u_p0.reshape(-1)[:]
if det == False:
b = mbi.MBIAnalysis(folder_b)
else:
b = CP.ConditionalParityAnalysis(folder_b)
b.get_sweep_pts()
b.get_readout_results(name='adwindata')
b.get_electron_ROC(ssro_folder)
y_b = ((b.p0.reshape(-1)[:]) - 0.5) * 2
y_err_b = 2 * b.u_p0.reshape(-1)[:]
x_labels = a.sweep_pts.reshape(-1)[:]
# x = range(len(y_a))
y = (y_a - y_b) / 2.
y_err = 1. / 2 * (y_err_a**2 + y_err_b**2)**0.5
if ms == 0:
a = CP.ConditionalParityAnalysis(folder_a)
a.get_sweep_pts()
a.get_readout_results(name='adwindata', post_select=True)
a.get_electron_ROC(ssro_folder)
c0_0_p, u_c0_0_p = a.convert_fidelity_to_contrast(a.p0_0, a.u_p0_0)
c0_1_p, u_c0_1_p = a.convert_fidelity_to_contrast(a.p0_1, a.u_p0_1)
b = CP.ConditionalParityAnalysis(folder_b)
b.get_sweep_pts()
b.get_readout_results(name='adwindata', post_select=True)
b.get_electron_ROC(ssro_folder)
c0_0_n, u_c0_0_n = b.convert_fidelity_to_contrast(b.p0_0, b.u_p0_0)
c0_1_n, u_c0_1_n = b.convert_fidelity_to_contrast(b.p0_1, b.u_p0_1)
## ms=0 data
y = (c0_0_p - c0_0_n) / 2.
y_err = 1. / 2 * (u_c0_0_p**2 + u_c0_0_n**2)**0.5
if ms == 1:
a = CP.ConditionalParityAnalysis(folder_a)
a.get_sweep_pts()
a.get_readout_results(name='adwindata', post_select=True)
a.get_electron_ROC(ssro_folder)
c0_0_p, u_c0_0_p = a.convert_fidelity_to_contrast(a.p0_0, a.u_p0_0)
c0_1_p, u_c0_1_p = a.convert_fidelity_to_contrast(a.p0_1, a.u_p0_1)
b = CP.ConditionalParityAnalysis(folder_b)
b.get_sweep_pts()
b.get_readout_results(name='adwindata', post_select=True)
b.get_electron_ROC(ssro_folder)
c0_0_n, u_c0_0_n = b.convert_fidelity_to_contrast(b.p0_0, b.u_p0_0)
c0_1_n, u_c0_1_n = b.convert_fidelity_to_contrast(b.p0_1, b.u_p0_1)
## ms=1 data
y = (c0_1_p - c0_1_n) / 2.
y_err = 1. / 2 * (u_c0_1_p**2 + u_c0_1_n**2)**0.5
y_total = np.append(y_total, y)
if det == True and ms != None:
print 'PROBABILITIES'
print 1 / 2. * (a.p0 + b.p0)
print 1 / 2. * (a.p1 + b.p1)
p0 = np.append(p0, 1 / 2. * (a.p0 + b.p0))
p1 = np.append(p1, 1 / 2. * (a.p1 + b.p1))
y_err_total = np.append(y_err_total, y_err)
# x_total = np.append(x_total,x)
x_labels_total = np.append(x_labels_total, x_labels)
if det == True and ms != None:
print 'PROBABILITIES'
print p0
print p1
print np.average(p0)
print np.average(p1)
# print 1/2.*(a.p0+b.p0)
# if ms ==1:
# sign = [1,1,1,-1,1,-1,-1,1,-1,-1,1,-1,-1,1,-1]
# print len(sign)
# print len(y_total)
# y_total = [y_total[i]*sign[i] for i in range(len(y_total))]
x_total = range(len(y_total))
return x_total, x_labels_total, y_total, y_err_total
def get_data(folder,folder_timestamp,RO_correct=True,ssro_calib_timestamp=None,tomo_bases='XXX',get_title=False, return_orientations=False, **kw):
evaluate_both = kw.pop('evaluate_both',False)
a = CP.ConditionalParityAnalysis(folder)
#a.get_sweep_pts()
a.get_readout_results(name='adwindata', post_select_GHZ = True)
if a.orientations[3] == 'negative':
multiply_by = -1
else:
multiply_by = 1
print a.orientations
if RO_correct == True:
if ssro_calib_timestamp == None:
ssro_calib_folder = toolbox.latest_data('SSRO',older_than=folder_timestamp)
analysis_file=os.path.join(ssro_calib_folder,'analysis.hdf5')
if not os.path.exists(analysis_file):
ssro.ssrocalib(ssro_calib_folder)
else:
ssro_dstmp, ssro_tstmp = toolbox.verify_timestamp(ssro_calib_timestamp)
ssro_calib_folder = toolbox.datadir + '\\'+ssro_dstmp+'\\'+ssro_tstmp+'_AdwinSSRO_SSROCalibration_111_1_sil18'#GHZ_'+tomo_bases
#print ssro_calib_folder
a.get_electron_ROC(ssro_calib_folder = ssro_calib_folder, post_select_GHZ = True)
#take the [0,0] part of the arrays; there are no sweep_pts
p0_000,u_p0_000 = multiply_by*(a.p0_000[0,0]-0.5)*2,(2*a.u_p0_000[0,0])
p0_001,u_p0_001 = multiply_by*(a.p0_001[0,0]-0.5)*2,(2*a.u_p0_001[0,0])
p0_010,u_p0_010 = multiply_by*(a.p0_010[0,0]-0.5)*2,(2*a.u_p0_010[0,0])
p0_011,u_p0_011 = multiply_by*(a.p0_011[0,0]-0.5)*2,(2*a.u_p0_011[0,0])
p0_100,u_p0_100 = multiply_by*(a.p0_100[0,0]-0.5)*2,(2*a.u_p0_100[0,0])
p0_101,u_p0_101 = multiply_by*(a.p0_101[0,0]-0.5)*2,(2*a.u_p0_101[0,0])
p0_110,u_p0_110 = multiply_by*(a.p0_110[0,0]-0.5)*2,(2*a.u_p0_110[0,0])
p0_111,u_p0_111 = multiply_by*(a.p0_111[0,0]-0.5)*2,(2*a.u_p0_111[0,0])
print "probablity with ROC", a.p0_000[0,0]
print "exp with ROC",p0_000, u_p0_000
if evaluate_both:
#else:
p0_000,u_p0_000 = multiply_by*(a.normalized_ssro_000[0,0]-0.5)*2,(2*a.u_normalized_ssro_000[0,0])
p0_001,u_p0_001 = multiply_by*(a.normalized_ssro_001[0,0]-0.5)*2,(2*a.u_normalized_ssro_001[0,0])
p0_010,u_p0_010 = multiply_by*(a.normalized_ssro_010[0,0]-0.5)*2,(2*a.u_normalized_ssro_010[0,0])
p0_011,u_p0_011 = multiply_by*(a.normalized_ssro_011[0,0]-0.5)*2,(2*a.u_normalized_ssro_011[0,0])
p0_100,u_p0_100 = multiply_by*(a.normalized_ssro_100[0,0]-0.5)*2,(2*a.u_normalized_ssro_100[0,0])
p0_101,u_p0_101 = multiply_by*(a.normalized_ssro_101[0,0]-0.5)*2,(2*a.u_normalized_ssro_101[0,0])
p0_110,u_p0_110 = multiply_by*(a.normalized_ssro_110[0,0]-0.5)*2,(2*a.u_normalized_ssro_110[0,0])
p0_111,u_p0_111 = multiply_by*(a.normalized_ssro_111[0,0]-0.5)*2,(2*a.u_normalized_ssro_111[0,0])
print "prob without ROC", a.normalized_ssro_000[0,0]
print "exp without ROC",p0_000, u_p0_000
print "WARNING WARNING REMOVE THIS STATEMENT. REMOVE EVALUATE_BOTH OPTION"
if get_title:
a_list_name = "".join(aa for aa in a.a_list)
b_list_name = "".join(aa for aa in a.b_list)
c_list_name = "".join(aa for aa in a.c_list)
d_list_name = "".join(aa for aa in a.d_list)
title = a_list_name+' '+b_list_name+' '+c_list_name+' '+d_list_name
else:
title=''
p = (a.p000[0,0],a.p001[0,0],a.p010[0,0],a.p011[0,0],a.p100[0,0],a.p101[0,0],a.p110[0,0],a.p111[0,0])
y = (p0_000,p0_001,p0_010,p0_011,p0_100,p0_101,p0_110,p0_111)
y_err = (u_p0_000,u_p0_001,u_p0_010,u_p0_011,u_p0_100,u_p0_101,u_p0_110,u_p0_111)
if return_orientations:
return(p,y,y_err,title,a.orientations)
return(p,y,y_err,title)
def BarPlotTomo_QEC(timestamp=None,
measurement_name=['adwindata'],
folder_name='Tomo',
plot_post_select=False,
ssro_calib_timestamp=None,
save=True,
do_plots=False,
title=None,
fontsize=10,
post_select_QEC=False):
'''
Function that makes a bar plot with errorbars of MBI type data
'''
plt.rc('font', size=fontsize)
if timestamp == None:
timestamp, folder = toolbox.latest_data(folder_name,
return_timestamp=True)
else:
folder = toolbox.data_from_time(timestamp)
if ssro_calib_timestamp == None:
ssro_calib_folder = toolbox.latest_data('SSRO')
else:
ssro_dstmp, ssro_tstmp = toolbox.verify_timestamp(ssro_calib_timestamp)
ssro_calib_folder = toolbox.datadir + '/' + ssro_dstmp + '/' + ssro_tstmp + '_AdwinSSRO_SSROCalibration_Hans_sil1'
a = CP.ConditionalParityAnalysis(folder)
a.get_sweep_pts()
a.get_readout_results(name='adwindata', post_select_QEC=False)
a.get_electron_ROC(ssro_calib_folder)
x_labels = a.sweep_pts.reshape(-1)
''' all data '''
c0, u_c0 = a.convert_fidelity_to_contrast(a.p0, a.u_p0)
x = range(len(c0))
if do_plots == True:
fig, ax = plt.subplots()
ax.bar(x, c0, yerr=u_c0, align='center', ecolor='k')
ax.set_xticks(x)
if title == None:
ax.set_title(str(folder) + '/' + str(timestamp))
else:
ax.set_title(title)
print x_labels
ax.set_xticklabels(x_labels.tolist())
ax.set_ylim(-1, 1)
ax.hlines([-1, 0, 1], x[0] - 1, x[-1] + 1, linestyles='dotted')
try:
fig.savefig(os.path.join(folder, 'tomo.png'))
fig.savefig(os.path.join(folder, title + '.pdf'),
format='pdf',
bbox_inches='tight')
except:
print 'Figure A has not been saved.'
''' postselected data '''
a = CP.ConditionalParityAnalysis(folder)
a.get_sweep_pts()
a.get_readout_results(name='adwindata', post_select_QEC=True)
a.get_electron_ROC(ssro_calib_folder, post_select_QEC=True)
c0_00, u_c0_00 = a.convert_fidelity_to_contrast(a.p0_00, a.u_p0_00)
c0_01, u_c0_01 = a.convert_fidelity_to_contrast(a.p0_01, a.u_p0_01)
c0_10, u_c0_10 = a.convert_fidelity_to_contrast(a.p0_10, a.u_p0_10)
c0_11, u_c0_11 = a.convert_fidelity_to_contrast(a.p0_11, a.u_p0_11)
x = range(len(c0_00))
if do_plots == True and plot_post_select == True:
fig_00, ax_00 = plt.subplots()
rects = ax_00.bar(x, c0_00, yerr=u_c0_00, align='center', ecolor='k')
# ax_00.bar(x,a.p0_00,yerr = u_c0_00,align = 'center',ecolor = 'k')
ax_00.set_xticks(x)
if title == None:
ax_00.set_title(str(folder) + '/' + str(timestamp) + '0')
else:
ax_00.set_title(str(title) + '0')
ax_00.set_xticklabels(x_labels.tolist())
# ax_00.set_ylim(-1,1)
ax_00.hlines([-1, 0, 1], x[0] - 1, x[-1] + 1, linestyles='dotted')
# print values on bar plot
def autolabel(rects):
for ii, rect in enumerate(rects):
height = rect.get_height()
plt.text(rect.get_x() + rect.get_width() / 2.,
1.02 * height,
str(round(c0_00[ii], 2)) + '(' +
str(int(round(u_c0_00[ii] * 100))) + ')',
ha='center',
va='bottom')
autolabel(rects)
fig_01, ax_01 = plt.subplots()
rects = ax_01.bar(x, c0_01, yerr=u_c0_01, align='center', ecolor='k')
ax_01.set_xticks(x)
if title == None:
ax_01.set_title(str(folder) + '/' + str(timestamp) + '1')
else:
ax_01.set_title(str(title) + '1')
ax_01.set_xticklabels(x_labels.tolist())
# ax_01.set_ylim(-1,1)
ax_01.hlines([-1, 0, 1], x[0] - 1, x[-1] + 1, linestyles='dotted')
# print values on bar plot
def autolabel(rects):
for ii, rect in enumerate(rects):
height = rect.get_height()
plt.text(rect.get_x() + rect.get_width() / 2.,
1.02 * height,
str(round(c0_01[ii], 2)) + '(' +
str(int(round(u_c0_01[ii] * 100))) + ')',
ha='center',
va='bottom')
autolabel(rects)
fig_10, ax_10 = plt.subplots()
rects = ax_10.bar(x, c0_10, yerr=u_c0_10, align='center', ecolor='k')
# ax_10.bar(x,a.p0_10,yerr = u_c0_10,align = 'center',ecolor = 'k')
ax_10.set_xticks(x)
if title == None:
ax_10.set_title(str(folder) + '/' + str(timestamp) + '0')
else:
ax_10.set_title(str(title) + '0')
ax_10.set_xticklabels(x_labels.tolist())
# ax_10.set_ylim(-1,1)
ax_10.hlines([-1, 0, 1], x[0] - 1, x[-1] + 1, linestyles='dotted')
# print values on bar plot
def autolabel(rects):
for ii, rect in enumerate(rects):
height = rect.get_height()
plt.text(rect.get_x() + rect.get_width() / 2.,
1.02 * height,
str(round(c0_10[ii], 2)) + '(' +
str(int(round(u_c0_10[ii] * 100))) + ')',
ha='center',
va='bottom')
autolabel(rects)
fig_11, ax_11 = plt.subplots()
rects = ax_11.bar(x, c0_11, yerr=u_c0_11, align='center', ecolor='k')
ax_11.set_xticks(x)
if title == None:
ax_11.set_title(str(folder) + '/' + str(timestamp) + '1')
else:
ax_11.set_title(str(title) + '1')
ax_11.set_xticklabels(x_labels.tolist())
# ax_11.set_ylim(-1,1)
ax_11.hlines([-1, 0, 1], x[0] - 1, x[-1] + 1, linestyles='dotted')
# print values on bar plot
def autolabel(rects):
for ii, rect in enumerate(rects):
height = rect.get_height()
plt.text(rect.get_x() + rect.get_width() / 2.,
1.02 * height,
str(round(c0_11[ii], 2)) + '(' +
str(int(round(u_c0_11[ii] * 100))) + ')',
ha='center',
va='bottom')
autolabel(rects)
try:
fig_00.savefig(os.path.join(folder,
str(title) + '0.pdf'),
format='pdf',
bbox_inches='tight')
fig_01.savefig(os.path.join(folder,
str(title) + '1.pdf'),
format='pdf',
bbox_inches='tight')
fig_10.savefig(os.path.join(folder,
str(title) + '0.pdf'),
format='pdf',
bbox_inches='tight')
fig_11.savefig(os.path.join(folder,
str(title) + '1.pdf'),
format='pdf',
bbox_inches='tight')
except:
print 'Figure B has not been saved.'
return x, c0, u_c0, c0_00, u_c0_00, c0_01, u_c0_01, c0_10, u_c0_10, c0_11, u_c0_11, x_labels, folder