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 build_model(file, hybrid=False, sylvan_threads=1, sylvan_memory=4096):
"""
Build model from file and apply bisimulation.
:param file: File.
:param hybrid: If true, the model is built symbolically with BDDs and in the end converted to a sparse model.
If false, the model is built as a sparse model from the beginning.
:param sylvan_threads: Number of threads to use in Sylvan library.
:param sylvan_memory: Memory available to Sylvan.
:return: Tuple (sparse model, prism program, property, time (s) for building , time (s) for bisimulation).
"""
logging.debug("Build ({}) model for file {}".format("symbolic" if hybrid else "sparse", file))
# Build model
build_start = time.time()
program = stormpy.parse_prism_program(file)
prop = "R=? [F \"stable\"]"
properties = stormpy.parse_properties(prop, program)
assert (len(properties) == 1)
program, properties = stormpy.preprocess_prism_program(program, properties, "")
program = program.as_prism_program()
if hybrid:
# Set number of Sylvan threads to use
stormpy.set_settings(["--sylvan:threads", str(sylvan_threads)])
# Set memory for Sylvan
stormpy.set_settings(["--sylvan:maxmem", str(sylvan_memory)])
model = stormpy.build_symbolic_parametric_model(program, properties)
else:
model = stormpy.build_parametric_model(program, properties)
logging.info("Built ({}) model with {} states and {} transitions.".format("symbolic" if hybrid else "sparse", model.nr_states, model.nr_transitions))
build_end = time.time()
time_build = build_end - build_start
logging.info("Building model took {}s".format(time_build))
# Bisimulation
if hybrid:
# Extract bisimulation quotient as sparse model
stormpy.set_settings(["--bisimulation:quot", "sparse"])
model = stormpy.perform_symbolic_bisimulation(model, properties)
else:
model = stormpy.perform_bisimulation(model, properties, stormpy.BisimulationType.STRONG)
assert type(model) is stormpy.SparseParametricDtmc
logging.info("Model after bisimulation: {} states and {} transitions.".format(model.nr_states, model.nr_transitions))
time_bisim = time.time() - build_end
logging.info("Computing bisimulation quotient took {}s".format(time_bisim))
prop = properties[0]
# Simplify model (by eliminating constant transitions)
# Disabled for the moment as this leads to significantly more transitions in Herman
if False:
model, formula = stormpy.pars.simplify_model(model, prop.raw_formula)
logging.info("Model after simplification: {} states and {} transitions.".format(model.nr_states, model.nr_transitions))
return model, program, prop, time_build, time_bisim
def test_build_parametric_mdp(self):
program = stormpy.parse_prism_program(
get_example_path("pmdp", "two_dice.nm"))
formulas = stormpy.parse_properties_for_prism_program(
"P=? [ F \"two\" ]", program)
model = stormpy.build_symbolic_parametric_model(program, formulas)
assert model.nr_states == 169
assert model.nr_transitions == 435
assert model.model_type == stormpy.ModelType.MDP
assert model.supports_parameters
assert type(model) is stormpy.SymbolicSylvanParametricMdp
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_build_dtmc_supporting_parameters(self):
program = stormpy.parse_prism_program(
get_example_path("dtmc", "die.pm"))
formulas = stormpy.parse_properties_for_prism_program(
"P=? [ F \"one\" ]", program)
model = stormpy.build_symbolic_parametric_model(program, formulas)
assert model.nr_states == 13
assert model.nr_transitions == 20
assert model.model_type == stormpy.ModelType.DTMC
assert model.supports_parameters
assert not model.has_parameters
assert type(model) is stormpy.SymbolicSylvanParametricDtmc
def test_build_parametric_dtmc(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_symbolic_parametric_model(program, formulas)
assert model.nr_states == 613
assert model.nr_transitions == 803
assert model.model_type == stormpy.ModelType.DTMC
assert model.supports_parameters
assert model.has_parameters
assert type(model) is stormpy.SymbolicSylvanParametricDtmc
def test_transform_symbolic_parametric_dtmc_to_sparse(self):
program = stormpy.parse_prism_program(
get_example_path("pdtmc", "parametric_die.pm"))
model = stormpy.build_symbolic_parametric_model(program)
assert model.nr_states == 13
assert model.nr_transitions == 20
assert model.model_type == stormpy.ModelType.DTMC
assert model.supports_parameters
assert type(model) is stormpy.SymbolicSylvanParametricDtmc
symbolic_model = stormpy.transform_to_sparse_model(model)
assert symbolic_model.nr_states == 13
assert symbolic_model.nr_transitions == 20
assert symbolic_model.model_type == stormpy.ModelType.DTMC
assert symbolic_model.supports_parameters
assert type(symbolic_model) is stormpy.SparseParametricDtmc
def test_symbolic_parametric_bisimulation(self):
program = stormpy.parse_prism_program(
get_example_path("pdtmc", "brp16_2.pm"))
prop = "P=? [F \"error\"]"
properties = stormpy.parse_properties_for_prism_program(prop, program)
model = stormpy.build_symbolic_parametric_model(program, properties)
assert model.nr_states == 613
assert model.nr_transitions == 803
assert model.model_type == stormpy.ModelType.DTMC
assert model.has_parameters
model_bisim = stormpy.perform_symbolic_bisimulation(model, properties)
assert model_bisim.nr_states == 326
assert model_bisim.nr_transitions == 454
assert model_bisim.model_type == stormpy.ModelType.DTMC
assert model_bisim.has_parameters
def test_build_parametric_dtmc_preprocess(self):
program = stormpy.parse_prism_program(
get_example_path("pdtmc", "herman5.pm"))
formulas = stormpy.parse_properties_for_prism_program(
"R=? [ F \"stable\" ]", program)
trans_program, trans_formulas = stormpy.preprocess_symbolic_input(
program, formulas, "")
trans_prism = trans_program.as_prism_program()
model = stormpy.build_symbolic_parametric_model(
trans_prism, trans_formulas)
assert model.nr_states == 33
assert model.nr_transitions == 266
assert model.model_type == stormpy.ModelType.DTMC
assert model.supports_parameters
assert model.has_parameters
assert type(model) is stormpy.SymbolicSylvanParametricDtmc
