def test_stdpractice_gst_gaugeOptTarget_warns_on_target_override(self):
myGaugeOptSuiteDict = {
'MyGaugeOpt': {
'item_weights': {
'gates': 1,
'spam': 0.0001
},
'target_model': self.
pspec # to test overriding internal target model (prints a warning)
}
}
with self.assertWarns(Warning):
target_model = create_explicit_model(self.pspec,
ideal_gate_type='static')
result = ls.run_stdpractice_gst(self.ds,
target_model,
self.fiducials,
self.fiducials,
self.germs,
self.maxLens,
modes="full TP",
gaugeopt_suite=myGaugeOptSuiteDict,
gaugeopt_target=self.mdl_guess,
comm=None,
mem_limit=None,
verbosity=5)
def test_stdpractice_gst_raises_on_bad_mode(self):
target_model = create_explicit_model(self.pspec,
ideal_gate_type='static')
with self.assertRaises(ValueError):
result = ls.run_stdpractice_gst(self.ds,
target_model,
self.fiducials,
self.fiducials,
self.germs,
self.maxLens,
modes="Foobar")
def test_stdpractice_gst_TP(self):
result = ls.run_stdpractice_gst(
self.ds,
self.pspec,
self.fiducials,
self.fiducials,
self.germs,
self.maxLens,
modes="full TP",
models_to_test={"Test": self.mdl_guess},
comm=None,
mem_limit=None,
verbosity=5)
def test_stdpractice_gst_pickle_output(self):
with BytesIO() as pickle_stream:
target_model = create_explicit_model(self.pspec,
ideal_gate_type='static')
result = ls.run_stdpractice_gst(self.ds,
target_model,
self.fiducials,
self.fiducials,
self.germs,
self.maxLens,
modes="Target",
output_pkl=pickle_stream)
self.assertTrue(len(pickle_stream.getvalue()) > 0)
def test_stdpractice_gst_advanced_options(self):
target_model = create_explicit_model(self.pspec,
ideal_gate_type='static')
result = ls.run_stdpractice_gst(
self.ds,
target_model,
self.fiducials,
self.fiducials,
self.germs,
self.maxLens,
modes="full TP",
comm=None,
mem_limit=None,
advanced_options={
'all': {
'objective': 'chi2',
'bad_fit_threshold':
-100, # so we create a robust estimate and convey guage opt to it.
'on_bad_fit': ["robust"]
}
},
verbosity=5)
def test_stdpractice_gst_gaugeOptTarget(self):
myGaugeOptSuiteDict = {
'MyGaugeOpt': {
'item_weights': {
'gates': 1,
'spam': 0.0001
}
}
}
target_model = create_explicit_model(self.pspec,
ideal_gate_type='static')
result = ls.run_stdpractice_gst(self.ds,
target_model,
self.fiducials,
self.fiducials,
self.germs,
self.maxLens,
modes="full TP",
gaugeopt_suite=myGaugeOptSuiteDict,
gaugeopt_target=self.mdl_guess,
comm=None,
mem_limit=None,
verbosity=5)
def test_stdpractice_gst_file_args(self, ds_path, model_path,
fiducial_path, germ_path):
import pickle
#io.write_model(self.model, model_path)
io.write_dataset(ds_path, self.ds, self.lsgstStrings[-1])
io.write_circuit_list(fiducial_path, self.fiducials)
io.write_circuit_list(germ_path, self.germs)
target_model = create_explicit_model(self.pspec,
ideal_gate_type='static')
io.write_model(target_model, model_path)
#with open(model_path, 'wb') as f:
# pickle.dump(target_model, f)
result = ls.run_stdpractice_gst(ds_path,
model_path,
fiducial_path,
fiducial_path,
germ_path,
self.maxLens,
modes="full TP",
comm=None,
mem_limit=None,
verbosity=5)
