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)