def test_model_is_refreshed(self):
"""
After a push and a pop, the model should be updated.
After adding a new assertion, the model should be updated.
"""
TestVariable = z3.Datatype('TestVariable')
TestVariable.declare('test_variable',
('number', z3.IntSort()))
TestVariable = TestVariable.create()
v1 = z3.Const('v1', TestVariable)
v2 = z3.Const('v2', TestVariable)
with solver.context():
solver.add(TestVariable.number(v1) == 42)
m1 = solver.model()
self.assertIsNotNone(m1[v1])
self.assertIsNone(m1[v2])
solver.add(TestVariable.number(v2) == 3)
m2 = solver.model()
self.assertIsNotNone(m2[v1])
self.assertIsNotNone(m2[v2])
m3 = solver.model()
self.assertIsNone(m3[v1])
self.assertIsNone(m3[v2])
def test_model_is_refreshed(self):
"""
After a push and a pop, the model should be updated.
After adding a new assertion, the model should be updated.
"""
TestVariable = z3.Datatype('TestVariable')
TestVariable.declare('test_variable', ('number', z3.IntSort()))
TestVariable = TestVariable.create()
v1 = z3.Const('v1', TestVariable)
v2 = z3.Const('v2', TestVariable)
with solver.context():
solver.add(TestVariable.number(v1) == 42)
m1 = solver.model()
self.assertIsNotNone(m1[v1])
self.assertIsNone(m1[v2])
solver.add(TestVariable.number(v2) == 3)
m2 = solver.model()
self.assertIsNotNone(m2[v1])
self.assertIsNotNone(m2[v2])
m3 = solver.model()
self.assertIsNone(m3[v1])
self.assertIsNone(m3[v2])
def test_named_get_model(self):
v = datatypes.new_variable()
s = "Name"
pred = atomic_predicate.Named(v, s)
z3pred = pred._assert(self.submodel, self.interpretation)
with solver.context():
solver.add(z3pred)
model = solver.model()
self.assertIsNotNone(model[v])
self.assertEquals(model[v], datatypes.Variable.variable(1))
def get_model(self):
# returns a set of sets of <graph, action> pairs, or at the very least
# something that behaves on the surface as such. It might not
# necessarily be a complete set. Actions should also behave as sets
# (sets of atomic actions).
with solver.context():
predicate = self.get_predicate()
solver.add(predicate)
if not solver.check():
raise ValueError("Tried to get model of unsat predicate")
return solver.model()
def get_model(self):
# returns a set of sets of <graph, action> pairs, or at the very least
# something that behaves on the surface as such. It might not
# necessarily be a complete set. Actions should also behave as sets
# (sets of atomic actions).
with solver.context():
predicate = self.get_predicate()
solver.add(predicate)
if not solver.check():
raise ValueError("Tried to get model of unsat predicate")
return solver.model()
def get_model(self):
# returns a set of sets of <graph, action> pairs, or at the very least
# something that behaves on the surface as such. It might not
# necessarily be a complete set. Actions should also behave as sets
# (sets of atomic actions).
with solver.context():
modelset = new_modelset()
interpretation = z3.Function('interpretation', Variable, Node)
predicate = self._assert(modelset, interpretation)
#if DEBUG:
# import pdb; pdb.set_trace()
solver.add(predicate)
if not solver.check():
raise ValueError("Tried to get model of unsat predicate")
return solver.model()
