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import stormpy
import stormpy.info
import stormpy.logic
from helpers.helper import get_example_path
from configurations import pars
@pars
class TestParametric:
def test_constraints_collector(self):
from pycarl.formula import FormulaType, Relation
if stormpy.info.storm_ratfunc_use_cln():
import pycarl.cln.formula
else:
import pycarl.gmp.formula
program = stormpy.parse_prism_program(get_example_path("pdtmc", "brp16_2.pm"))
prop = "P=? [F s=5]"
formulas = stormpy.parse_properties_for_prism_program(prop, program)
model = stormpy.build_parametric_model(program, formulas)
collector = stormpy.ConstraintCollector(model)
constraints_well_formed = collector.wellformed_constraints
for formula in constraints_well_formed:
assert formula.type == FormulaType.CONSTRAINT
constraint = formula.get_constraint()
assert constraint.relation == Relation.LEQ
constraints_graph_preserving = collector.graph_preserving_constraints
for formula in constraints_graph_preserving:
assert formula.type == FormulaType.CONSTRAINT
constraint = formula.get_constraint()
assert constraint.relation == Relation.NEQ
def test_derivatives(self):
program = stormpy.parse_prism_program(get_example_path("pdtmc", "brp16_2.pm"))
prop = "P<=0.84 [F s=5 ]"
formulas = stormpy.parse_properties_for_prism_program(prop, program)
model = stormpy.build_parametric_model(program, formulas)
assert model.nr_states == 613
assert model.nr_transitions == 803
assert model.model_type == stormpy.ModelType.DTMC
assert model.has_parameters
parameters = model.collect_probability_parameters()
assert len(parameters) == 2
derivatives = stormpy.pars.gather_derivatives(model, list(parameters)[0])
assert len(derivatives) == 0