def test_gst(self):
comm = self.ralloc.comm
exp_design = std.get_gst_experiment_design(4)
mdl_datagen = std.target_model().depolarize(op_noise=0.1,
spam_noise=0.01)
ds = pygsti.data.simulate_data(mdl_datagen,
exp_design,
1000,
seed=1234,
comm=comm)
data = pygsti.protocols.ProtocolData(exp_design, ds)
initial_model = std.target_model("full TP")
proto = pygsti.protocols.GateSetTomography(
initial_model,
verbosity=1,
optimizer={
'maxiter': 100,
'serial_solve_proc_threshold': 100
})
results_serial = proto.run(data, comm=None)
results_parallel = proto.run(data, comm=comm)
# compare resulting models
if comm is None or comm.rank == 0:
best_params_serial = results_serial.estimates[
"GateSetTomography"].models['stdgaugeopt'].to_vector()
best_params_parallel = results_parallel.estimates[
"GateSetTomography"].models['stdgaugeopt'].to_vector()
assert np.allclose(best_params_serial, best_params_parallel)
def setUp(self):
self.gst_design = smq1Q_XYI.get_gst_experiment_design(4,
qubit_labels=[0])
nQubits = 2
self.pspec_2Q = QubitProcessorSpec(
nQubits, ('Gx', 'Gy', 'Gcnot'),
geometry="line",
qubit_labels=['qb{}'.format(i) for i in range(nQubits)])
def setUpClass(cls):
cls.gst_design = smq1Q_XYI.get_gst_experiment_design(max_max_length=4)
cls.mdl_target = smq1Q_XYI.target_model()
cls.mdl_datagen = cls.mdl_target.depolarize(op_noise=0.05,
spam_noise=0.025)
ds = simulate_data(cls.mdl_datagen,
cls.gst_design.all_circuits_needing_data,
1000,
sample_error='none')
cls.gst_data = ProtocolData(cls.gst_design, ds)
def setUpClass(cls):
#Construct a results object
gst_design = smq1Q_XYI.get_gst_experiment_design(max_max_length=4)
mdl_target = smq1Q_XYI.target_model()
mdl_datagen = mdl_target.depolarize(op_noise=0.05, spam_noise=0.025)
ds = simulate_data(mdl_datagen,
gst_design.all_circuits_needing_data,
1000,
seed=2020)
data = ProtocolData(gst_design, ds)
cls.results = gst.ModelEstimateResults(data, Protocol("test-protocol"))
cls.results.add_estimate(Estimate.create_gst_estimate(
cls.results,
mdl_target,
mdl_target, [mdl_datagen] * len(gst_design.circuit_lists),
parameters={'objective': 'logl'}),
estimate_key="test-estimate")
cls.target_model = mdl_target
def test_simulate_data(self):
comm = self.ralloc.comm
exp_design = std.get_gst_experiment_design(4)
mdl_datagen = std.target_model().depolarize(op_noise=0.1,
spam_noise=0.01)
ds_serial = pygsti.data.simulate_data(mdl_datagen,
exp_design,
1000,
seed=1234,
comm=None)
ds_parallel = pygsti.data.simulate_data(mdl_datagen,
exp_design,
1000,
seed=1234,
comm=comm)
if comm is None or comm.rank == 0:
assert (set(ds_serial.keys()) == set(ds_parallel.keys()))
for key in ds_serial.keys():
assert (ds_serial[key].to_dict() == ds_parallel[key].to_dict())
def run_objfn_values(self, sim, objfn, natoms):
comm = self.ralloc.comm
mdl = std.target_model()
exp_design = std.get_gst_experiment_design(1)
mdl_datagen = mdl.depolarize(op_noise=0.01, spam_noise=0.01)
ds = pygsti.data.simulate_data(mdl_datagen,
exp_design,
1000,
seed=1234,
comm=comm)
builder = pygsti.objectivefns.ObjectiveFunctionBuilder.create_from(
objfn)
builder.additional_args['array_types'] = ('EP', 'EPP'
) # HACK - todo this better
if sim == 'map':
mdl.sim = pygsti.forwardsims.MapForwardSimulator(num_atoms=natoms)
elif sim == 'matrix':
mdl.sim = pygsti.forwardsims.MatrixForwardSimulator(
num_atoms=natoms)
else:
raise RuntimeError(
"Improper sim type passed by test_objfn_generator")
circuits = exp_design.all_circuits_needing_data[0:10]
objfn_parallel = builder.build(mdl,
ds,
circuits,
self.ralloc,
verbosity=0)
objfn_serial = builder.build(mdl, ds, circuits, None, verbosity=0)
#LSVEC TEST
v_ref = objfn_serial.lsvec()
v = objfn_parallel.lsvec()
globalv = objfn_parallel.layout.gather_local_array('e', v)
if comm is None or comm.rank == 0:
finalv = np.empty_like(globalv)
off = 0
for c in circuits:
indices, outcomes = objfn_parallel.layout.global_layout.indices_and_outcomes(
c)
assert (outcomes == (('0', ), ('1', ))
) # I think this should always be the ordering (?)
finalv[off:off + len(outcomes)] = globalv[indices]
off += len(outcomes)
finalv_ref = np.empty_like(v_ref)
off = 0
for c in circuits:
indices, outcomes = objfn_serial.layout.indices_and_outcomes(c)
assert (outcomes == (('0', ), ('1', ))
) # I think this should always be the ordering (?)
finalv_ref[off:off + len(outcomes)] = v_ref[indices]
off += len(outcomes)
assert np.allclose(finalv, finalv_ref)
#TODO: DLSVEC?
#HESSIAN TEST
hessian_ref = objfn_serial.hessian()
hessian = objfn_parallel.hessian(
) # already a global qty, just on root proc
bhessian_ref = objfn_serial.hessian_brute()
bhessian = objfn_parallel.hessian_brute()
if comm is None or comm.rank == 0:
assert np.allclose(bhessian_ref, hessian_ref)
assert np.allclose(hessian, hessian_ref)
assert np.allclose(bhessian, bhessian_ref)
def setUpClass(cls):
cls.gst_design = std.get_gst_experiment_design(4)
def setUp(self):
self.edesign = smq1Q_XYI.get_gst_experiment_design(max_max_length=2)
self.target_model = smq1Q_XYI.target_model()
