def test_stdpractice_gst_raises_on_bad_mode(self):
with self.assertRaises(ValueError):
result = ls.do_stdpractice_gst(self.ds,
self.model,
self.fiducials,
self.fiducials,
self.germs,
self.maxLens,
modes="Foobar")
def test_stdpractice_gst_pickle_output(self):
with BytesIO() as pickle_stream:
result = ls.do_stdpractice_gst(self.ds,
self.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_Target(self):
result = ls.do_stdpractice_gst(self.ds,
self.model,
self.fiducials,
self.fiducials,
self.germs,
self.maxLens,
modes="Target",
modelsToTest={"Test": self.mdl_guess},
comm=None,
memLimit=None,
verbosity=5)
def test_stdpractice_gst_file_args(self, ds_path, model_path,
fiducial_path, germ_path):
io.write_dataset(ds_path, self.ds, self.lsgstStrings[-1])
io.write_model(self.model, model_path)
io.write_circuit_list(fiducial_path, self.fiducials)
io.write_circuit_list(germ_path, self.germs)
result = ls.do_stdpractice_gst(ds_path,
model_path,
fiducial_path,
fiducial_path,
germ_path,
self.maxLens,
modes="TP",
comm=None,
memLimit=None,
verbosity=5)
def test_stdpractice_gst_advanced_options(self):
result = ls.do_stdpractice_gst(
self.ds,
self.model,
self.fiducials,
self.fiducials,
self.germs,
self.maxLens,
modes="TP",
comm=None,
memLimit=None,
verbosity=5,
advancedOptions={
'all': {
'objective': 'chi2',
'badFitThreshold':
-100, # so we create a robust estimate and convey guage opt to it.
'onBadFit': ["robust"]
}
})
def test_stdpractice_gst_gaugeOptTarget(self):
myGaugeOptSuiteDict = {
'MyGaugeOpt': {
'itemWeights': {
'gates': 1,
'spam': 0.0001
}
}
}
result = ls.do_stdpractice_gst(self.ds,
self.model,
self.fiducials,
self.fiducials,
self.germs,
self.maxLens,
modes="TP",
comm=None,
memLimit=None,
verbosity=5,
gaugeOptTarget=self.mdl_guess,
gaugeOptSuite=myGaugeOptSuiteDict)
def test_stdpractice_gst_gaugeOptTarget_warns_on_target_override(self):
myGaugeOptSuiteDict = {
'MyGaugeOpt': {
'itemWeights': {
'gates': 1,
'spam': 0.0001
},
'targetModel': self.
model # to test overriding internal target model (prints a warning)
}
}
with self.assertWarns(Warning):
result = ls.do_stdpractice_gst(self.ds,
self.model,
self.fiducials,
self.fiducials,
self.germs,
self.maxLens,
modes="TP",
comm=None,
memLimit=None,
verbosity=5,
gaugeOptTarget=self.mdl_guess,
gaugeOptSuite=myGaugeOptSuiteDict)