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							158 lines
						
					
					
						
							7.6 KiB
						
					
					
				| import stormpy | |
| import stormpy.info | |
| import stormpy.logic | |
| from helpers.helper import get_example_path | |
| 
 | |
| from configurations import pars | |
| 
 | |
| 
 | |
| @pars | |
| class TestParametric: | |
|     def test_parametric_model_checking_sparse(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.nr_states == 613 | |
|         assert model.nr_transitions == 803 | |
|         assert model.model_type == stormpy.ModelType.DTMC | |
|         assert model.has_parameters | |
|         initial_state = model.initial_states[0] | |
|         assert initial_state == 0 | |
|         result = stormpy.model_checking(model, formulas[0]) | |
|         func = result.at(initial_state) | |
|         one = stormpy.FactorizedPolynomial(stormpy.RationalRF(1)) | |
|         assert func.denominator == one | |
| 
 | |
|     def test_parametric_model_checking_dd(self): | |
|         program = stormpy.parse_prism_program(get_example_path("pdtmc", "parametric_die.pm")) | |
|         prop = "P=? [F s=5]" | |
|         formulas = stormpy.parse_properties_for_prism_program(prop, program) | |
|         model = stormpy.build_symbolic_parametric_model(program, formulas) | |
|         assert model.nr_states == 11 | |
|         assert model.nr_transitions == 17 | |
|         assert model.model_type == stormpy.ModelType.DTMC | |
|         assert model.has_parameters | |
|         result = stormpy.check_model_dd(model, formulas[0]) | |
|         assert type(result) is stormpy.SymbolicParametricQuantitativeCheckResult | |
| 
 | |
|     def test_parametric_model_checking_hybrid(self): | |
|         program = stormpy.parse_prism_program(get_example_path("pdtmc", "parametric_die.pm")) | |
|         prop = "P=? [F s=5]" | |
|         formulas = stormpy.parse_properties_for_prism_program(prop, program) | |
|         model = stormpy.build_symbolic_parametric_model(program, formulas) | |
|         assert model.nr_states == 11 | |
|         assert model.nr_transitions == 17 | |
|         assert model.model_type == stormpy.ModelType.DTMC | |
|         assert model.has_parameters | |
|         result = stormpy.check_model_hybrid(model, formulas[0]) | |
|         assert type(result) is stormpy.HybridParametricQuantitativeCheckResult | |
|         values = result.get_values() | |
|         assert len(values) == 3 | |
| 
 | |
|     def test_parameters(self): | |
|         program = stormpy.parse_prism_program(get_example_path("pdtmc", "brp16_2.pm")) | |
|         formulas = stormpy.parse_properties_for_prism_program("P=? [F s=5]", program) | |
|         model = stormpy.build_parametric_model(program, formulas) | |
|         model_parameters = model.collect_probability_parameters() | |
|         reward_parameters = model.collect_reward_parameters() | |
|         all_parameters = model.collect_all_parameters() | |
|         assert len(model_parameters) == 2 | |
|         assert len(reward_parameters) == 0 | |
|         assert len(all_parameters) == 2 | |
| 
 | |
|         program_reward = stormpy.parse_prism_program(get_example_path("pdtmc", "brp_rewards16_2.pm")) | |
|         formulas_reward = stormpy.parse_properties_for_prism_program("Rmin=? [ F \"target\" ]", program_reward) | |
|         model = stormpy.build_parametric_model(program_reward, formulas_reward) | |
|         model_parameters = model.collect_probability_parameters() | |
|         reward_parameters = model.collect_reward_parameters() | |
|         all_parameters = model.collect_all_parameters() | |
|         assert len(model_parameters) == 2 | |
|         assert len(reward_parameters) == 2 | |
|         assert len(all_parameters) == 4 | |
| 
 | |
|         model = stormpy.build_symbolic_parametric_model(program, formulas) | |
|         assert len(model.get_parameters()) == 4 | |
| 
 | |
|         model = stormpy.build_symbolic_parametric_model(program_reward, formulas_reward) | |
|         assert len(model.get_parameters()) == 4 | |
| 
 | |
|     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 | |
| 
 | |
|     def test_dtmc_simplification(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) | |
|         formula = formulas[0].raw_formula | |
|         model = stormpy.build_parametric_model(program, formulas) | |
|         assert model.nr_states == 613 | |
|         assert model.nr_transitions == 803 | |
|         model, formula = stormpy.pars.simplify_model(model, formula) | |
|         assert model.nr_states == 193 | |
|         assert model.nr_transitions == 383 | |
| 
 | |
|     def test_mdp_simplification(self): | |
|         program = stormpy.parse_prism_program(get_example_path("pmdp", "two_dice.nm")) | |
|         formulas = stormpy.parse_properties_for_prism_program("Pmin=? [ F \"two\" ]", program) | |
|         formula = formulas[0].raw_formula | |
|         model = stormpy.build_parametric_model(program, formulas) | |
|         assert model.nr_states == 169 | |
|         assert model.nr_transitions == 435 | |
|         model, formula = stormpy.pars.simplify_model(model, formula) | |
|         assert model.nr_states == 17 | |
|         assert model.nr_transitions == 50 | |
| 
 | |
|     def test_region(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) | |
|         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) | |
|         assert region.area == stormpy.RationalRF(1) / stormpy.RationalRF(25) | |
|         for par in parameters: | |
|             if par.name == "pL": | |
|                 pL = par | |
|             elif par.name == "pK": | |
|                 pK = par | |
|             else: | |
|                 assert False | |
|         dec = stormpy.RationalRF(100) | |
|         region_valuation = {pL: (stormpy.RationalRF(70) / dec, stormpy.RationalRF(90) / dec), pK: (stormpy.RationalRF(75) / dec, stormpy.RationalRF(95) / dec)} | |
|         region = stormpy.pars.ParameterRegion(region_valuation) | |
|         assert region.area == stormpy.RationalRF(1) / stormpy.RationalRF(25)
 |