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import stormpy
import stormpy.logic
import math
from helpers.helper import get_example_path
from configurations import pars
@pars
class TestPLA:
def test_pla(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
env = stormpy.Environment()
checker = stormpy.pars.create_region_checker(env, model, formulas[0].raw_formula)
parameters = model.collect_probability_parameters()
assert len(parameters) == 2
region = stormpy.pars.ParameterRegion.create_from_string("0.7<=pL<=0.9,0.75<=pK<=0.95", parameters)
result = checker.check_region(env, region)
assert result == stormpy.pars.RegionResult.ALLSAT
region = stormpy.pars.ParameterRegion.create_from_string("0.4<=pL<=0.65,0.75<=pK<=0.95", parameters)
result = checker.check_region(env, region, stormpy.pars.RegionResultHypothesis.UNKNOWN, stormpy.pars.RegionResult.UNKNOWN, True)
assert result == stormpy.pars.RegionResult.EXISTSBOTH
region = stormpy.pars.ParameterRegion.create_from_string("0.1<=pL<=0.73,0.2<=pK<=0.715", parameters)
result = checker.check_region(env, region)
assert result == stormpy.pars.RegionResult.ALLVIOLATED
def test_pla_region_valuation(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
env = stormpy.Environment()
checker = stormpy.pars.create_region_checker(env, model, formulas[0].raw_formula)
parameters = model.collect_probability_parameters()
assert len(parameters) == 2
for par in parameters:
if par.name == "pL":
pL = par
elif par.name == "pK":
pK = par
else:
assert False
region_valuation = dict()
region_valuation[pL] = (stormpy.RationalRF(0.7), stormpy.RationalRF(0.9))
region_valuation[pK] = (stormpy.RationalRF(0.75), stormpy.RationalRF(0.95))
region = stormpy.pars.ParameterRegion(region_valuation)
result = checker.check_region(env, region)
assert result == stormpy.pars.RegionResult.ALLSAT
region_valuation[pL] = (stormpy.RationalRF(0.4), stormpy.RationalRF(0.65))
region = stormpy.pars.ParameterRegion(region_valuation)
result = checker.check_region(env, region, stormpy.pars.RegionResultHypothesis.UNKNOWN, stormpy.pars.RegionResult.UNKNOWN, True)
assert result == stormpy.pars.RegionResult.EXISTSBOTH
region_valuation[pK] = (stormpy.RationalRF(0.2), stormpy.RationalRF(0.715))
region_valuation[pL] = (stormpy.RationalRF(0.1), stormpy.RationalRF(0.73))
region = stormpy.pars.ParameterRegion(region_valuation)
result = checker.check_region(env, region)
assert result == stormpy.pars.RegionResult.ALLVIOLATED
def test_pla_bounds(self):
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)
assert model.has_parameters
env = stormpy.Environment()
checker = stormpy.pars.create_region_checker(env, model, formulas[0].raw_formula)
parameters = model.collect_probability_parameters()
assert len(parameters) == 2
region = stormpy.pars.ParameterRegion.create_from_string("0.7<=pL<=0.9,0.75<=pK<=0.95", parameters)
result = checker.get_bound(env, region, True)
assert math.isclose(float(result.constant_part()), 0.8369631383670559, rel_tol=1e-6)
result_vec = checker.get_bound_all_states(env, region, True)
result = result_vec.at(model.initial_states[0])
assert math.isclose(result, 0.8369631383670559, rel_tol=1e-6)
def test_pla_manual(self):
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)
assert model.has_parameters
env = stormpy.Environment()
checker = stormpy.pars.DtmcParameterLiftingModelChecker()
checker.specify(env, model, formulas[0].raw_formula)
parameters = model.collect_probability_parameters()
assert len(parameters) == 2
region = stormpy.pars.ParameterRegion.create_from_string("0.7<=pL<=0.9,0.75<=pK<=0.95", parameters)
result = checker.get_bound(env, region, True)
assert math.isclose(float(result.constant_part()), 0.8369631383670559, rel_tol=1e-6)
def test_pla_manual_no_simplification(self):
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)
assert model.has_parameters
env = stormpy.Environment()
checker = stormpy.pars.DtmcParameterLiftingModelChecker()
checker.specify(env, model, formulas[0].raw_formula, allow_model_simplification=False)
parameters = model.collect_probability_parameters()
assert len(parameters) == 2
region = stormpy.pars.ParameterRegion.create_from_string("0.7<=pL<=0.9,0.75<=pK<=0.95", parameters)
result = checker.get_bound(env, region, True)
assert math.isclose(float(result.constant_part()), 0.836963056082918, rel_tol=1e-6)
def test_pla_state_bounds(self):
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)
assert model.has_parameters
env = stormpy.Environment()
checker = stormpy.pars.DtmcParameterLiftingModelChecker()
checker.specify(env, model, formulas[0].raw_formula, allow_model_simplification=False)
parameters = model.collect_probability_parameters()
assert len(parameters) == 2
region = stormpy.pars.ParameterRegion.create_from_string("0.7<=pL<=0.9,0.75<=pK<=0.95", parameters)
result_vec = checker.get_bound_all_states(env, region, True)
assert len(result_vec.get_values()) == model.nr_states
assert math.isclose(result_vec.at(model.initial_states[0]), 0.836963056082918, rel_tol=1e-6)