def loadexpdata(self,
filepath,
timetags,
is_range,
is_pop,
print_fidelities=True):
''' load experimental data and optionally calculate state fidelities (jozsafid) '''
auspath = rd.PathObject(filepath)
self.YRexp = []
self.rhoexp = []
# load populations
if is_pop:
auspath = rd.PathObject(filepath)
if is_range:
dataobj_list = rd.ReadDataMultiple(timetags, is_range=True)
dataobj = dataobj_list.pop()
for item in dataobj_list:
dataobj += item
print(dataobj.parameters['cycles'])
else:
dataobj = rd.ReadData(timetags[0])
self.YRexp = dataobj.data_dict['cprb'][:, 1:]
self.YRexp_err = np.sqrt(self.YRexp * (1 - self.YRexp) /
dataobj.parameters['cycles'])
self.rhoexp = None
# else load densmats
else:
data_list = rd.ReadDataMultiple(timetags, is_range=is_range)
# if len(data) = len(ideal)-1, assume the missing one is the prep'd state
if self.rho != None:
if len(data_list) == np.shape(self.rho)[0] - 1:
self.rhoexp.append(self.rho[0])
elif len(data_list) != np.shape(self.rho)[0]:
print(
"length of data_list and ideal results don't match. Adding initial density matrix."
)
self.rhoexp.append(self.rho[0])
else:
print("ideal densmat not loaded - check len(rhoexp).")
for dat in data_list: #range(len(expfiles)):
rhoexp1 = dmr.IterML.iterfun(dat, 100)
YRexp1 = np.diag(rhoexp1)
self.rhoexp.append(rhoexp1)
self.YRexp.append(YRexp1)
self.YRexp = np.array(self.YRexp)
self.rhoexp = np.array(self.rhoexp)
if print_fidelities:
for i in range(np.min([len(self.rhoexp), len(self.rho)])):
print(i, ": ", U.jozsafid(self.rho[i], self.rhoexp[i]))
self.exploaded = True
def calculateGateFidelityProcTomo(self, ErrorBars=False, ind=None):
''' use proctomo to convert error of gate to fidelity '''
#print "Using ProcTomo to calculate gate fidelity. This may take a while ..."
if ind != None:
indreal = [ind]
if ErrorBars:
indreal = [ind, ind, ind]
elif not ErrorBars:
indreal = [self.error0]
else:
indreal = [self.error0, self.error0max, self.error0min]
result = []
for ind in indreal:
if self.noisetype == 'all':
for noisetype in self.dec.dict_params_static.keys():
self.setNoiseAmp(noisetype, ind)
else:
self.setNoiseAmp(self.noisetype, ind)
if not self.verbose:
widgets = [progressbar.Percentage(), ' ', progressbar.Bar(),' ', progressbar.ETA()]
pbar = progressbar.ProgressBar(widgets=widgets).start()
else:
pbar = None
pos = self.gates[0] # only do it once, for now
newpulseseq = sim.PulseSequence([ copy.deepcopy(self.pulseseq[pos]) ])
self.pulseseq[pos].UtrAll = []
newpulseseq[0].use_ideal=False
ScanObj = ips.ScanParameter_in_Sequence(newpulseseq, self.params, self.dec, np.arange(12**self.params.hspace.nuions),type='ProcTomo', verbose=self.verbose, doPP=True, use_ideal=True, pbar=pbar)
ScanObj.runScan(batchsize=40)
data_proctom = ScanObj.output_dict['qstates_camera']
chi = proctom.proctomo(data_proctom, 100)
chiId = qproc.Unitary2Chi(newpulseseq[0].Uidtr.conjugate())
result.append(U.jozsafid(chiId, chi))
#print "PT:"
#print np.around(chiId,3)
#print np.around(chi,3) # TEMP
if ind != None and ErrorBars:
result.sort()
result.append(result[0])
result.remove(result[0])
if not ErrorBars:
print self._printGatetype(self.gatetype),":", np.around(result[0],4)
return [result[0], result[0], result[0]]
else:
print self._printGatetype(self.gatetype) + " : %0.4f + %0.4f - %0.4f" % (np.around(result[0],4), np.around(result[1]-result[0],4), np.around(result[0]-result[2],4) )
return result
def loadsimdata(self, data, print_fidelities=False):
''' load simulation data directly from variables '''
try: # data is a database object
self.data = data
self.data.RhoPNAll = np.array(self.data.RhoPNAll)
self.rhosim = self.data.RhoPN
except AttributeError: # or it's just the densmats
# make a dummy data object
self.data = sim.database(np.zeros(1), np.zeros(1), sim.hspace(1,2,0,0))
self.data.RhoPNAll = data
self.simloaded = True
if print_fidelities:
for i in range(np.min([len(self.rhosim), len(self.rho)])):
print i, ": ", U.jozsafid(self.rho[i], self.rhosim[i])
def loadexpdata(self, filepath, timetags, is_range, is_pop, print_fidelities = True):
''' load experimental data and optionally calculate state fidelities (jozsafid) '''
auspath = rd.PathObject(filepath)
self.YRexp = []
self.rhoexp = []
# load populations
if is_pop:
auspath = rd.PathObject(filepath)
if is_range:
dataobj_list = rd.ReadDataMultiple(timetags,is_range=True)
dataobj = dataobj_list.pop()
for item in dataobj_list:
dataobj += item
print dataobj.parameters['cycles']
else:
dataobj = rd.ReadData(timetags[0])
self.YRexp = dataobj.data_dict['cprb'][:,1:]
self.YRexp_err = np.sqrt(self.YRexp*(1-self.YRexp) / dataobj.parameters['cycles'] )
self.rhoexp = None
# else load densmats
else:
data_list = rd.ReadDataMultiple(timetags, is_range=is_range)
# if len(data) = len(ideal)-1, assume the missing one is the prep'd state
if self.rho != None:
if len(data_list) == np.shape(self.rho)[0]-1:
self.rhoexp.append(self.rho[0])
elif len(data_list) != np.shape(self.rho)[0]:
print "length of data_list and ideal results don't match. Adding initial density matrix."
self.rhoexp.append(self.rho[0])
else:
print "ideal densmat not loaded - check len(rhoexp)."
for dat in data_list: #range(len(expfiles)):
rhoexp1 = dmr.IterML.iterfun(dat, 100)
YRexp1 = np.diag(rhoexp1)
self.rhoexp.append(rhoexp1)
self.YRexp.append(YRexp1)
self.YRexp = np.array(self.YRexp)
self.rhoexp = np.array(self.rhoexp)
if print_fidelities:
for i in range(np.min([len(self.rhoexp), len(self.rho)])):
print i, ": ", U.jozsafid(self.rho[i], self.rhoexp[i])
self.exploaded = True
def calculateGateFidelityProcTomo(self, ErrorBars=False, ind=None):
''' use proctomo to convert error of gate to fidelity '''
#print "Using ProcTomo to calculate gate fidelity. This may take a while ..."
if ind != None:
indreal = [ind]
if ErrorBars:
indreal = [ind, ind, ind]
elif not ErrorBars:
indreal = [self.error0]
else:
indreal = [self.error0, self.error0max, self.error0min]
result = []
for ind in indreal:
if self.noisetype == 'all':
for noisetype in self.dec.dict_params_static.keys():
self.setNoiseAmp(noisetype, ind)
else:
self.setNoiseAmp(self.noisetype, ind)
if not self.verbose:
widgets = [
progressbar.Percentage(), ' ',
progressbar.Bar(), ' ',
progressbar.ETA()
]
pbar = progressbar.ProgressBar(widgets=widgets).start()
else:
pbar = None
pos = self.gates[0] # only do it once, for now
newpulseseq = sim.PulseSequence(
[copy.deepcopy(self.pulseseq[pos])])
self.pulseseq[pos].UtrAll = []
newpulseseq[0].use_ideal = False
ScanObj = ips.ScanParameter_in_Sequence(
newpulseseq,
self.params,
self.dec,
np.arange(12**self.params.hspace.nuions),
type='ProcTomo',
verbose=self.verbose,
doPP=True,
use_ideal=True,
pbar=pbar)
ScanObj.runScan(batchsize=40)
data_proctom = ScanObj.output_dict['qstates_camera']
chi = proctom.proctomo(data_proctom, 100)
chiId = qproc.Unitary2Chi(newpulseseq[0].Uidtr.conjugate())
result.append(U.jozsafid(chiId, chi))
#print "PT:"
#print np.around(chiId,3)
#print np.around(chi,3) # TEMP
if ind != None and ErrorBars:
result.sort()
result.append(result[0])
result.remove(result[0])
if not ErrorBars:
print self._printGatetype(self.gatetype), ":", np.around(
result[0], 4)
return [result[0], result[0], result[0]]
else:
print self._printGatetype(
self.gatetype) + " : %0.4f + %0.4f - %0.4f" % (np.around(
result[0],
4), np.around(result[1] - result[0],
4), np.around(result[0] - result[2], 4))
return result
