def test_scoring(self):
eigenvalue_array = np.array([1e-6,1e-4,1.0,2.0])
s0 = scoring.list_score(eigenvalue_array)
self.assertEqual(s0, 1010001.5)
s1 = scoring.list_score(eigenvalue_array, 'all')
self.assertEqual(s1, 1010001.5)
s2 = scoring.list_score(eigenvalue_array, 'worst')
self.assertEqual(s2, 1000000)
with self.assertRaises(ValueError):
scoring.list_score(eigenvalue_array, 'foobar')
def test_helper_functions(self):
""" Mostly test boundary cases of helper fns """
germsToTest = pygsti.construction.list_all_circuits_without_powers_and_cycles(
list(std.target_model().operations.keys()), 2)
maxscore = pygsti.alg.calculate_germset_score(germsToTest, std.target_model(),
neighborhoodSize=5,
randomizationStrength=1e-2, scoreFunc='all',
opPenalty=0.0, l1Penalty=0.0)
#Test failures in get_model_params:
gs1 = std.target_model()
gs2 = std.target_model()
gs3 = std.target_model()
gs4 = std.target_model()
gs1.set_all_parameterizations("full")
gs2.set_all_parameterizations("TP")
gs3.set_all_parameterizations("full")
gs4.set_all_parameterizations("full")
gs3.operations['Gi2'] = np.identity(4,'d') #adds non-gauge params but not gauge params
gs4.operations['Gi2'] = pygsti.obj.StaticDenseOp(np.identity(4,'d')) # keeps param counts the same but adds gate
with self.assertRaises(ValueError):
germsel.get_model_params([gs1,gs2]) # different number of gauge params
with self.assertRaises(ValueError):
germsel.get_model_params([gs1,gs3]) # different number of non-gauge params
with self.assertRaises(ValueError):
germsel.get_model_params([gs1,gs4]) # different number of gates
self.assertWarns(germsel.setup_model_list, [gs1,gs1], randomize=False, randomizationStrength=0,
numCopies=3, seed=0) # warns b/c list len > 1 and numCopies specified
scoreFn = lambda x: scoring.list_score(x, scoreFunc="all")
with self.assertRaises(ValueError):
germsel.compute_composite_germ_score(scoreFn) #need to provide partialDerivDaggerDeriv or partialGermsList
germsel.compute_composite_germ_score(scoreFn, model=gs1, partialGermsList=germsToTest,
eps=1e-5, germLengths=np.array([len(g) for g in germsToTest]))
pDDD = np.zeros( (len(germsToTest),gs1.num_params(),gs1.num_params()), 'd')
with self.assertRaises(ValueError):
germsel.compute_composite_germ_score(scoreFn, partialDerivDaggerDeriv=pDDD) # must specify model ro numGaugeParams
with self.assertRaises(ValueError):
germsel.compute_composite_germ_score(scoreFn, model=gs1, partialDerivDaggerDeriv=pDDD,
opPenalty=1.0) # must specify partialGermLists or germLengths
germsel.compute_composite_germ_score(scoreFn, model=gs1, partialDerivDaggerDeriv=pDDD,
partialGermsList=germsToTest, opPenalty=1.0) # OK
def test_list_score_worst(self):
s2 = scoring.list_score(self.eigvals, 'worst')
self.assertEqual(s2, 1000000)
def test_list_score_raises_on_bad_score_function(self):
with self.assertRaises(ValueError):
scoring.list_score(self.eigvals, 'foobar')
def test_list_score_all(self):
s1 = scoring.list_score(self.eigvals, 'all')
self.assertEqual(s1, 1010001.5)
