def calculateGateFidelity(self, std):
''' extract gate fidelity from the *current* stored unitaries '''
# note!!! self.data.pulseseq not self.pulseseq
gatefid = []
for pulse in self.data.pulseseq:
gatefid_pulse = []
if not pulse.use_ideal:
for i in range(self.data.numruns):
chi_id = qproc.Unitary2Chi(pulse.Uidtr)
chi_sim = qproc.Unitary2Chi(pulse.UtrAll[i])
#print "Unitaries:"
#print np.around(chi_id,3) # TEMP
#print np.around(chi_sim,3)
gatefid_pulse.append(U.fidelity(chi_id, chi_sim))
gatefid.append(gatefid_pulse)
gatefid = np.array(gatefid).flatten()
self.gatefidsample = gatefid
fid_mean = np.mean(gatefid)
fid_std = np.std(gatefid)
fid_med = np.median(gatefid)
fid_75qtl = spst.scoreatpercentile(gatefid, 75)
fid_25qtl = spst.scoreatpercentile(gatefid, 25)
if std:
return fid_mean, fid_mean + fid_std, fid_mean - fid_std
else:
return fid_med, fid_75qtl, fid_25qtl
def calcAllFid(rho, rhoexp, displ=1):
''' calculate final fidelity using different measures '''
fidelity_exp = np.zeros(len(rho))
sso_exp = np.zeros(len(rho))
popdist_exp = np.zeros(len(rho))
for i in range(len(rho)):
fidelity_exp[i] = U.fidelity(rho[i], rhoexp[i])
sso_exp[i] = U.sso(rho[i], rhoexp[i])
popdist_exp[i] = U.popdist(rho[i], rhoexp[i])
fig = pl.figure(displ)
fig.clf()
ax = fig.add_subplot(111)
ax.plot(fidelity_exp, '.-')
ax.plot(sso_exp, '.-')
ax.plot(popdist_exp, '.-')
ax.set_ylim([
np.min(np.hstack([fidelity_exp, sso_exp, popdist_exp])) - 0.05, 1
])
ax.set_xlabel('pulse #')
ax.set_ylabel('state fidelity')
ax.legend(['fidelity', 'sso', 'popdist'], loc='lower left')
fig.show()
return fidelity_exp, sso_exp, popdist_exp
def calculateGateFidelity(self, std):
''' extract gate fidelity from the *current* stored unitaries '''
# note!!! self.data.pulseseq not self.pulseseq
gatefid = []
for pulse in self.data.pulseseq:
gatefid_pulse = []
if not pulse.use_ideal:
for i in range(self.data.numruns):
chi_id = qproc.Unitary2Chi(pulse.Uidtr)
chi_sim = qproc.Unitary2Chi(pulse.UtrAll[i])
#print "Unitaries:"
#print np.around(chi_id,3) # TEMP
#print np.around(chi_sim,3)
gatefid_pulse.append(U.fidelity(chi_id, chi_sim))
gatefid.append(gatefid_pulse)
gatefid = np.array(gatefid).flatten()
self.gatefidsample = gatefid
fid_mean = np.mean(gatefid)
fid_std = np.std(gatefid)
fid_med = np.median(gatefid)
fid_75qtl = spst.scoreatpercentile(gatefid, 75)
fid_25qtl = spst.scoreatpercentile(gatefid, 25)
if std:
return fid_mean, fid_mean+fid_std, fid_mean-fid_std
else:
return fid_med, fid_75qtl, fid_25qtl
def calcAllFid(rho, rhoexp, displ=1):
''' calculate final fidelity using different measures '''
fidelity_exp = np.zeros(len(rho))
sso_exp = np.zeros(len(rho))
popdist_exp = np.zeros(len(rho))
for i in range(len(rho)):
fidelity_exp[i] = U.fidelity(rho[i], rhoexp[i])
sso_exp[i] = U.sso(rho[i], rhoexp[i])
popdist_exp[i] = U.popdist(rho[i], rhoexp[i])
fig = pl.figure(displ)
fig.clf()
ax = fig.add_subplot(111)
ax.plot(fidelity_exp, '.-')
ax.plot(sso_exp, '.-')
ax.plot(popdist_exp, '.-')
ax.set_ylim([np.min(np.hstack([fidelity_exp, sso_exp, popdist_exp]))-0.05, 1])
ax.set_xlabel('pulse #')
ax.set_ylabel('state fidelity')
ax.legend(['fidelity', 'sso', 'popdist'], loc='lower left')
fig.show()
return fidelity_exp, sso_exp, popdist_exp
