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)