def make_lsgst_lists(opLabels, fiducialList, germList, maxLengthList):
singleOps = pc.circuit_list([(g, ) for g in opLabels])
lgstStrings = pc.list_lgst_circuits(fiducialList, fiducialList,
opLabels)
lsgst_list = pc.circuit_list([
()
]) #running list of all strings so far
if maxLengthList[0] == 0:
lsgst_listOfLists = [lgstStrings]
maxLengthList = maxLengthList[1:]
else:
lsgst_listOfLists = []
for maxLen in maxLengthList:
lsgst_list += pc.create_circuit_list(
"f0+R(germ,N)+f1",
f0=fiducialList,
f1=fiducialList,
germ=germList,
N=maxLen,
R=pc.repeat_with_max_length,
order=('germ', 'f0', 'f1'))
lsgst_listOfLists.append(
pygsti.remove_duplicates(lgstStrings + lsgst_list))
print("%d LSGST sets w/lengths" % len(lsgst_listOfLists),
map(len, lsgst_listOfLists))
return lsgst_listOfLists
def create_fake_dataset(comm):
fidPairList = None
maxLengths = [0, 1, 2, 4, 8, 16]
nSamples = 1000
specs = pygsti.construction.build_spam_specs(
std.fiducials,
prep_labels=std.gs_target.get_prep_labels(),
effect_labels=std.gs_target.get_effect_labels())
rhoStrs, EStrs = pygsti.construction.get_spam_strs(specs)
lgstStrings = pygsti.construction.list_lgst_gatestrings(
specs, list(std.gs_target.gates.keys()))
lsgstStrings = pygsti.construction.make_lsgst_lists(
list(std.gs_target.gates.keys()), rhoStrs, EStrs, std.germs,
maxLengths, fidPairList)
lsgstStringsToUse = lsgstStrings
allRequiredStrs = pygsti.remove_duplicates(lgstStrings + lsgstStrings[-1])
if comm is None or comm.Get_rank() == 0:
gs_dataGen = std.gs_target.depolarize(gate_noise=0.1)
dsFake = pygsti.construction.generate_fake_data(
gs_dataGen,
allRequiredStrs,
nSamples,
sampleError="multinomial",
seed=1234)
dsFake = comm.bcast(dsFake, root=0)
else:
dsFake = comm.bcast(None, root=0)
#for gs in dsFake:
# if abs(dsFake[gs]['plus']-dsFake_cmp[gs]['plus']) > 0.5:
# print("DS DIFF: ",gs, dsFake[gs]['plus'], "vs", dsFake_cmp[gs]['plus'] )
return dsFake, lsgstStrings
def runMC2GSTAnalysis(myspecs,
mygerms,
gsTarget,
seed,
maxLs=[1, 2, 4, 8],
nSamples=1000,
useFreqWeightedChiSq=False,
minProbClipForWeighting=1e-4,
fidPairList=None,
comm=None):
rhoStrs, EStrs = pygsti.construction.get_spam_strs(myspecs)
lgstStrings = pygsti.construction.list_lgst_gatestrings(
myspecs, gsTarget.gates.keys())
lsgstStrings = pygsti.construction.make_lsgst_lists(
gsTarget.gates.keys(), rhoStrs, EStrs, mygerms, maxLs, fidPairList)
print len(myspecs[0]), " rho specifiers"
print len(myspecs[1]), " effect specifiers"
print len(mygerms), " germs"
print len(lgstStrings), " total LGST gate strings"
print len(lsgstStrings[-1]), " LSGST strings before thinning"
lsgstStringsToUse = lsgstStrings
allRequiredStrs = pygsti.remove_duplicates(lgstStrings + lsgstStrings[-1])
gs_dataGen = gsTarget.depolarize(gate_noise=0.1)
dsFake = pygsti.construction.generate_fake_data(gs_dataGen,
allRequiredStrs,
nSamples,
sampleError="multinomial",
seed=seed)
#Run LGST to get starting gate set
gs_lgst = pygsti.do_lgst(dsFake,
myspecs,
gsTarget,
svdTruncateTo=gsTarget.dim,
verbosity=3)
gs_lgst_go = pygsti.optimize_gauge(gs_lgst,
"target",
targetGateset=gs_dataGen)
#Run full iterative LSGST
tStart = time.time()
all_gs_lsgst = pygsti.do_iterative_mc2gst(
dsFake,
gs_lgst_go,
lsgstStringsToUse,
minProbClipForWeighting=minProbClipForWeighting,
probClipInterval=(-1e5, 1e5),
verbosity=1,
memLimit=3 * (1024)**3,
returnAll=True,
useFreqWeightedChiSq=useFreqWeightedChiSq,
comm=comm)
tEnd = time.time()
print "Time = ", (tEnd - tStart) / 3600.0, "hours ( =", (tEnd -
tStart), " secs)"
return all_gs_lsgst, gs_dataGen
def create_fake_dataset(comm):
fidPairList = None
maxLengths = [0,1,2,4,8,16]
nSamples = 1000
specs = pygsti.construction.build_spam_specs(
std.fiducials, prep_labels=std.gs_target.get_prep_labels(),
effect_labels=std.gs_target.get_effect_labels())
rhoStrs, EStrs = pygsti.construction.get_spam_strs(specs)
lgstStrings = pygsti.construction.list_lgst_gatestrings(
specs, list(std.gs_target.gates.keys()))
lsgstStrings = pygsti.construction.make_lsgst_lists(
list(std.gs_target.gates.keys()), rhoStrs, EStrs,
std.germs, maxLengths, fidPairList )
lsgstStringsToUse = lsgstStrings
allRequiredStrs = pygsti.remove_duplicates(lgstStrings + lsgstStrings[-1])
if comm is None or comm.Get_rank() == 0:
gs_dataGen = std.gs_target.depolarize(gate_noise=0.1)
dsFake = pygsti.construction.generate_fake_data(
gs_dataGen, allRequiredStrs, nSamples, sampleError="multinomial",
seed=1234)
dsFake = comm.bcast(dsFake, root=0)
else:
dsFake = comm.bcast(None, root=0)
#for gs in dsFake:
# if abs(dsFake[gs]['plus']-dsFake_cmp[gs]['plus']) > 0.5:
# print("DS DIFF: ",gs, dsFake[gs]['plus'], "vs", dsFake_cmp[gs]['plus'] )
return dsFake, lsgstStrings
def create_fake_dataset(comm):
fidPairList = None
maxLengths = [1,2,4,8,16]
nSamples = 1000
#specs = pygsti.construction.build_spam_specs(
# std.fiducials, prep_labels=std.target_model().get_prep_labels(),
# effect_labels=std.target_model().get_effect_labels())
#rhoStrs, EStrs = pygsti.construction.get_spam_strs(specs)
rhoStrs = EStrs = std.fiducials
lgstStrings = pygsti.construction.list_lgst_circuits(
rhoStrs, EStrs, list(std.target_model().operations.keys()))
lsgstStrings = pygsti.construction.make_lsgst_lists(
list(std.target_model().operations.keys()), rhoStrs, EStrs,
std.germs, maxLengths, fidPairList )
lsgstStringsToUse = lsgstStrings
allRequiredStrs = pygsti.remove_duplicates(lgstStrings + lsgstStrings[-1])
if comm is None or comm.Get_rank() == 0:
mdl_dataGen = std.target_model().depolarize(op_noise=0.1)
dsFake = pygsti.construction.generate_fake_data(
mdl_dataGen, allRequiredStrs, nSamples, sampleError="multinomial",
seed=1234)
dsFake = comm.bcast(dsFake, root=0)
else:
dsFake = comm.bcast(None, root=0)
#for mdl in dsFake:
# if abs(dsFake[mdl]['0']-dsFake_cmp[mdl]['0']) > 0.5:
# print("DS DIFF: ",mdl, dsFake[mdl]['0'], "vs", dsFake_cmp[mdl]['0'] )
return dsFake, lsgstStrings
def runAnalysis(obj, myspecs, mygerms, gsTarget, seed,
maxLs = [1,2,4,8],
nSamples=1000, useFreqWeightedChiSq=False,
minProbClipForWeighting=1e-4, fidPairList=None,
comm=None, distributeMethod="gatestrings"):
rhoStrs, EStrs = pygsti.construction.get_spam_strs(myspecs)
lgstStrings = pygsti.construction.list_lgst_gatestrings(
myspecs, gsTarget.gates.keys())
lsgstStrings = pygsti.construction.make_lsgst_lists(
gsTarget.gates.keys(), rhoStrs, EStrs, mygerms, maxLs, fidPairList )
print len(myspecs[0]), " rho specifiers"
print len(myspecs[1]), " effect specifiers"
print len(mygerms), " germs"
print len(lgstStrings), " total LGST gate strings"
print len(lsgstStrings[-1]), " LSGST strings before thinning"
lsgstStringsToUse = lsgstStrings
allRequiredStrs = pygsti.remove_duplicates(lgstStrings + lsgstStrings[-1])
gs_dataGen = gsTarget.depolarize(gate_noise=0.1)
dsFake = pygsti.construction.generate_fake_data(
gs_dataGen, allRequiredStrs, nSamples, sampleError="multinomial",
seed=seed)
#Run LGST to get starting gate set
gs_lgst = pygsti.do_lgst(dsFake, myspecs, gsTarget,
svdTruncateTo=gsTarget.dim, verbosity=3)
gs_lgst_go = pygsti.optimize_gauge(gs_lgst,"target",
targetGateset=gs_dataGen)
#Run full iterative LSGST
tStart = time.time()
if obj == "chi2":
all_gs_lsgst = pygsti.do_iterative_mc2gst(
dsFake, gs_lgst_go, lsgstStringsToUse,
minProbClipForWeighting=minProbClipForWeighting,
probClipInterval=(-1e5,1e5),
verbosity=1, memLimit=3*(1024)**3, returnAll=True,
useFreqWeightedChiSq=useFreqWeightedChiSq, comm=comm,
distributeMethod=distributeMethod)
elif obj == "logl":
all_gs_lsgst = pygsti.do_iterative_mlgst(
dsFake, gs_lgst_go, lsgstStringsToUse,
minProbClip=minProbClipForWeighting,
probClipInterval=(-1e5,1e5),
verbosity=1, memLimit=3*(1024)**3, returnAll=True,
useFreqWeightedChiSq=useFreqWeightedChiSq, comm=comm,
distributeMethod=distributeMethod)
tEnd = time.time()
print "Time = ",(tEnd-tStart)/3600.0,"hours"
return all_gs_lsgst, gs_dataGen
def make_lsgst_lists(gateLabels, fiducialList, germList, maxLengthList):
singleGates = pc.gatestring_list([(g,) for g in gateLabels])
lgstStrings = pc.list_lgst_gatestrings(pc.build_spam_specs(fiducialList), gateLabels)
lsgst_list = pc.gatestring_list([ () ]) #running list of all strings so far
if maxLengthList[0] == 0:
lsgst_listOfLists = [ lgstStrings ]
maxLengthList = maxLengthList[1:]
else: lsgst_listOfLists = [ ]
for maxLen in maxLengthList:
lsgst_list += pc.create_gatestring_list("f0+R(germ,N)+f1", f0=fiducialList,
f1=fiducialList, germ=germList, N=maxLen,
R=pc.repeat_with_max_length,
order=('germ','f0','f1'))
lsgst_listOfLists.append( pygsti.remove_duplicates(lgstStrings + lsgst_list) )
print("%d LSGST sets w/lengths" % len(lsgst_listOfLists), map(len,lsgst_listOfLists))
return lsgst_listOfLists
