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 example_schedulers_02():
path = stormpy.examples.files.prism_ma_simple
formula_str = "Tmin=? [ F s=4 ]"
program = stormpy.parse_prism_program(path, False, True)
formulas = stormpy.parse_properties_for_prism_program(formula_str, program)
ma = stormpy.build_model(program, formulas)
assert ma.model_type == stormpy.ModelType.MA
# Convert MA to MDP
mdp, mdp_formulas = stormpy.transform_to_discrete_time_model(ma, formulas)
assert mdp.model_type == stormpy.ModelType.MDP
initial_state = mdp.initial_states[0]
assert initial_state == 0
result = stormpy.model_checking(mdp,
mdp_formulas[0],
extract_scheduler=True)
assert result.has_scheduler
scheduler = result.scheduler
print(scheduler)
assert scheduler.memoryless
assert scheduler.deterministic
for state in mdp.states:
choice = scheduler.get_choice(state)
action = choice.get_deterministic_choice()
print("In state {} choose action {}".format(state, action))
def test_initial_states(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_model(program, formulas)
initial_states = model.initial_states
assert len(initial_states) == 1
assert 0 in initial_states
def example_parametric_models_02():
# Check support for parameters
if not config.storm_with_pars:
print("Support parameters is missing. Try building storm-pars.")
return
import stormpy.pars
from pycarl.formula import FormulaType, Relation
if stormpy.info.storm_ratfunc_use_cln():
import pycarl.cln.formula
else:
import pycarl.gmp.formula
path = stormpy.examples.files.prism_pdtmc_die
prism_program = stormpy.parse_prism_program(path)
formula_str = "P=? [F s=7 & d=2]"
properties = stormpy.parse_properties_for_prism_program(formula_str, prism_program)
model = stormpy.build_parametric_model(prism_program, properties)
initial_state = model.initial_states[0]
result = stormpy.model_checking(model, properties[0])
print("Result: {}".format(result.at(initial_state)))
collector = stormpy.ConstraintCollector(model)
print("Well formed constraints:")
for formula in collector.wellformed_constraints:
print(formula.get_constraint())
print("Graph preserving constraints:")
for formula in collector.graph_preserving_constraints:
print(formula.get_constraint())
def test_bisimulation(self):
program = stormpy.parse_prism_program(
get_example_path("dtmc", "crowds5_5.pm"))
assert program.nr_modules == 1
assert program.model_type == stormpy.PrismModelType.DTMC
prop = "P=? [F \"observe0Greater1\"]"
properties = stormpy.parse_properties_for_prism_program(prop, program)
model = stormpy.build_model(program, properties)
assert model.nr_states == 7403
assert model.nr_transitions == 13041
assert model.model_type == stormpy.ModelType.DTMC
assert not model.supports_parameters
initial_state = model.initial_states[0]
assert initial_state == 0
result = stormpy.model_checking(model, properties[0])
model_bisim = stormpy.perform_bisimulation(
model, properties, stormpy.BisimulationType.STRONG)
assert model_bisim.nr_states == 64
assert model_bisim.nr_transitions == 104
assert model_bisim.model_type == stormpy.ModelType.DTMC
assert not model_bisim.supports_parameters
result_bisim = stormpy.model_checking(model_bisim, properties[0])
initial_state_bisim = model_bisim.initial_states[0]
assert initial_state_bisim == 34
assert math.isclose(result.at(initial_state),
result_bisim.at(initial_state_bisim),
rel_tol=1e-4)
def test_parametric_bisimulation(self):
program = stormpy.parse_prism_program(
get_example_path("pdtmc", "brp16_2.pm"))
assert program.nr_modules == 5
assert program.model_type == stormpy.PrismModelType.DTMC
assert program.has_undefined_constants
assert program.undefined_constants_are_graph_preserving
prop = "P=? [F s=5]"
properties = stormpy.parse_properties_for_prism_program(prop, program)
model = stormpy.build_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
initial_state = model.initial_states[0]
assert initial_state == 0
result = stormpy.model_checking(model, properties[0])
ratFunc = result.at(initial_state)
model_bisim = stormpy.perform_bisimulation(
model, properties, stormpy.BisimulationType.STRONG)
assert model_bisim.nr_states == 324
assert model_bisim.nr_transitions == 452
assert model_bisim.model_type == stormpy.ModelType.DTMC
assert model_bisim.has_parameters
result_bisim = stormpy.model_checking(model_bisim, properties[0])
initial_state_bisim = model_bisim.initial_states[0]
assert initial_state_bisim == 316
ratFunc_bisim = result_bisim.at(initial_state_bisim)
assert ratFunc == ratFunc_bisim
def example_getting_started_02():
path = stormpy.examples.files.prism_dtmc_die
prism_program = stormpy.parse_prism_program(path)
model = stormpy.build_model(prism_program)
print("Number of states: {}".format(model.nr_states))
print("Number of transitions: {}".format(model.nr_transitions))
print("Labels in the model: {}".format(model.labeling.get_labels()))
formula_str = "P=? [F s=2]"
properties = stormpy.parse_properties_for_prism_program(
formula_str, prism_program)
model_for_formula = stormpy.build_model(prism_program, properties)
print("Number of states: {}".format(model_for_formula.nr_states))
print("Number of transitions: {}".format(model_for_formula.nr_transitions))
print("Labels in the model: {}".format(
model_for_formula.labeling.get_labels()))
formula_str_2 = "P=? [F s=7 & d=2]"
properties_2 = stormpy.parse_properties_for_prism_program(
formula_str_2, prism_program)
model_for_formula_2 = stormpy.build_model(prism_program, properties_2)
print("Number of states: {}".format(model_for_formula_2.nr_states))
print("Number of transitions: {}".format(
model_for_formula_2.nr_transitions))
print("Labels in the model: {}".format(
model_for_formula_2.labeling.get_labels()))
def load_sketch_prism(cls, sketch_path):
# read lines
with open(sketch_path) as f:
sketch_lines = f.readlines()
# replace hole definitions with constants
hole_re = re.compile(r'^hole\s+(.*?)\s+(.*?)\s+in\s+\{(.*?)\};$')
sketch_output = []
hole_definitions = {}
for line in sketch_lines:
match = hole_re.search(line)
if match is not None:
hole_type = match.group(1)
hole_name = match.group(2)
hole_options = match.group(3).replace(" ", "")
hole_definitions[hole_name] = hole_options
line = f"const {hole_type} {hole_name};"
sketch_output.append(line)
# store modified sketch to a temporary file
tmp_path = sketch_path + str(uuid.uuid4())
with open(tmp_path, 'w') as f:
for line in sketch_output:
print(line, end="", file=f)
# try to parse temporary sketch and then delete it
try:
prism = stormpy.parse_prism_program(tmp_path, prism_compat=True)
os.remove(tmp_path)
except:
os.remove(tmp_path)
exit(1)
return prism, hole_definitions
def load_sketch(cls, sketch_path):
# read lines
with open(sketch_path) as f:
sketch_lines = f.readlines()
# strip hole definitions
hole_re = re.compile(r'^hole\s+(.*?)\s+(.*?)\s+in\s+\{(.*?)\};$')
sketch_output = []
hole_definitions = OrderedDict()
for line in sketch_lines:
match = hole_re.search(line)
if match is not None:
hole_name = match.group(2)
hole_definitions[hole_name] = match.group(3).replace(" ", "")
line = f"const {match.group(1)} {hole_name};"
sketch_output.append(line)
# store stripped sketch to a temporary file
tmp_path = sketch_path + str(uuid.uuid4())
with open(tmp_path, 'w') as f:
for line in sketch_output:
print(line, end="", file=f)
# parse temporary sketch
program = stormpy.parse_prism_program(tmp_path)
# delete temporary sketch
os.remove(tmp_path)
return program, hole_definitions
def example_building_models_04():
path = stormpy.examples.files.prism_mdp_firewire
prism_program = stormpy.parse_prism_program(path)
prism_program = stormpy.preprocess_symbolic_input(
prism_program, [], "delay=10,fast=0.8")[0].as_prism_program()
options = stormpy.BuilderOptions()
options.set_build_state_valuations()
options.set_build_all_reward_models(True)
options.set_build_choice_labels(True)
def permissive_policy(state_valuation, action_index):
"""
Whether for the given state and action, the action should be allowed in the model.
:param state_valuation:
:param action_index:
:return: True or False
"""
action_name = prism_program.get_action_name(action_index)
print(f"{state_valuation.to_json()}, {action_name}")
# conditions on the action
cond1 = action_name.startswith("snd")
# conditions on the state (efficient)
cond2 = state_valuation.get_integer_value(
prism_program.get_module("node2").get_integer_variable(
"x2").expression_variable) < 20
# conditions on the json repr of the state (inefficient, string handling, etc)
cond3 = json.loads(str(state_valuation.to_json()))["x1"] < 40
return (cond1 or (cond2 and cond3))
constructor = stormpy.make_sparse_model_builder(
prism_program, options,
stormpy.StateValuationFunctionActionMaskDouble(permissive_policy))
model = constructor.build()
print(model)
def example_building_models_03():
path = stormpy.examples.files.prism_pdtmc_brp
prism_program = stormpy.parse_prism_program(path)
formula_str = "P=? [F s=5]"
properties = stormpy.parse_properties_for_prism_program(
formula_str, prism_program)
options = stormpy.BuilderOptions([p.raw_formula for p in properties])
options.set_build_state_valuations()
model = stormpy.build_sparse_parametric_model_with_options(
prism_program, options)
valuations = model.state_valuations
values2 = json.loads(str(valuations.get_json(2)))
print(values2)
integer_variables = []
for module in prism_program.modules:
print("module {}".format(module.name))
integer_variables += module.integer_variables
print(", ".join([
"{}: {}".format(
str(iv.name),
valuations.get_integer_value(2, iv.expression_variable))
for iv in integer_variables
]))
def example_simulator_01():
path = stormpy.examples.files.prism_mdp_maze
prism_program = stormpy.parse_prism_program(path)
model = stormpy.build_model(prism_program)
simulator = stormpy.simulator.create_simulator(model, seed=42)
# 5 paths of at most 20 steps.
paths = []
for m in range(5):
path = []
state = simulator.restart()
path = [f"{state}"]
for n in range(20):
actions = simulator.available_actions()
select_action = random.randint(0,len(actions)-1)
#print(f"Randomly select action nr: {select_action} from actions {actions}")
path.append(f"--act={actions[select_action]}-->")
state = simulator.step(actions[select_action])
#print(state)
path.append(f"{state}")
if simulator.is_done():
#print("Trapped!")
break
paths.append(path)
for path in paths:
print(" ".join(path))
def test_scheduler_ma_via_mdp(self):
program = stormpy.parse_prism_program(get_example_path("ma", "simple.ma"), False, True)
formulas = stormpy.parse_properties_for_prism_program("Tmin=? [ F s=4 ]", program)
ma = stormpy.build_model(program, formulas)
assert ma.nr_states == 5
assert ma.nr_transitions == 8
assert ma.model_type == stormpy.ModelType.MA
# Convert MA to MDP
mdp, mdp_formulas = stormpy.transform_to_discrete_time_model(ma, formulas)
assert mdp.nr_states == 5
assert mdp.nr_transitions == 8
assert mdp.model_type == stormpy.ModelType.MDP
assert len(mdp.initial_states) == 1
initial_state = mdp.initial_states[0]
assert initial_state == 0
result = stormpy.model_checking(mdp, mdp_formulas[0], extract_scheduler=True)
assert math.isclose(result.at(initial_state), 0.08333333333)
assert result.has_scheduler
scheduler = result.scheduler
assert scheduler.memoryless
assert scheduler.memory_size == 1
assert scheduler.deterministic
for state in mdp.states:
choice = scheduler.get_choice(state)
assert choice.defined
assert choice.deterministic
action = choice.get_deterministic_choice()
if state.id == 0:
assert action == 1
else:
assert action == 0
def model_checking(tulip_transys, formula, prism_file_path, extract_policy=False):
"""Model check tulip_transys against formula
@type tulip_transys: either a MarkovChain or MarkovDecisionProcess object.
@type formula: a string describing PCTL formula according to Prism format.
@type prism_file_path: a string indicating the path to export the intermediate
prism file (mostly for debugging purpose)
@type extract_policy: boolean that indicates whether to extract policy
@return result
* If extract_policy = False, then for each state in model.states,
result[state] is the probability of satisfying the formula starting at state.
* If extract_policy = True, then result = (prob,policy) where for each
state in model.states, prob[state] is the probability of satisfying the
formula starting at state and policy[state] is the action to be applied at
state.
"""
assert type(tulip_transys) == MDP or type(tulip_transys) == MC
to_prism_file(tulip_transys, prism_file_path)
prism_program = stormpy.parse_prism_program(prism_file_path)
stormpy_model = stormpy.build_model(prism_program)
properties = stormpy.parse_properties(formula, prism_program)
result = stormpy.model_checking(
stormpy_model, properties[0], extract_scheduler=extract_policy
)
prob = _extract_probability(result, stormpy_model, tulip_transys)
if not extract_policy:
return prob
policy = _extract_policy(result, stormpy_model, tulip_transys)
return (prob, policy)
def test_explicit_builder(self):
path = stormpy.examples.files.prism_dtmc_die
prism_program = stormpy.parse_prism_program(path)
formula_str = "P=? [F s=7 & d=2]"
properties = stormpy.parse_properties_for_prism_program(formula_str, prism_program)
# Fix variables in the program.
module = prism_program.modules[0]
s_var = module.get_integer_variable("s").expression_variable
d_var = module.get_integer_variable("d").expression_variable
# Construct the model
options = stormpy.BuilderOptions([p.raw_formula for p in properties])
options.set_build_state_valuations()
model_builder = stormpy.make_sparse_model_builder(prism_program, options)
model = model_builder.build()
# and export the model from building
state_mapping = model_builder.export_lookup()
#lookup 1
state = { s_var : prism_program.expression_manager.create_integer(3), d_var : prism_program.expression_manager.create_integer(0)}
id = state_mapping.lookup(state)
assert model.state_valuations.get_integer_value(id, s_var) == 3
assert model.state_valuations.get_integer_value(id, d_var) == 0
#lookup 2
state = { s_var : prism_program.expression_manager.create_integer(7), d_var : prism_program.expression_manager.create_integer(3)}
id = state_mapping.lookup(state)
assert model.state_valuations.get_integer_value(id, s_var) == 7
assert model.state_valuations.get_integer_value(id, d_var) == 3
def example_exploration_02():
"""
Example to exploration of POMDPs.
:return:
"""
program = stormpy.parse_prism_program(
stormpy.examples.files.prism_pomdp_maze)
prop = "R=? [F \"goal\"]"
properties = stormpy.parse_properties(prop, program)
model = stormpy.build_model(program, properties)
print(model.model_type)
# Internally, POMDPs are just MDPs with additional observation information.
# Thus, data structure exploration for MDPs can be applied as before.
initial_state = model.initial_states[0]
for state in model.states:
if state.id in model.initial_states:
print(state)
for action in state.actions:
for transition in action.transitions:
print(
"From state {} by action {}, with probability {}, go to state {}"
.format(state, action, transition.value(),
transition.column))
print(model.nr_observations)
for state in model.states:
print("State {} has observation id {}".format(
state.id, model.observations[state.id]))
def test_change_parametric_matrix_modelchecking(self):
import stormpy.logic
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)
initial_state = model.initial_states[0]
assert initial_state == 0
matrix = model.transition_matrix
# Check matrix
one_pol = stormpy.RationalRF(1)
one_pol = stormpy.FactorizedPolynomial(one_pol)
one = stormpy.FactorizedRationalFunction(one_pol, one_pol)
for e in matrix:
assert e.value() == one or len(e.value().gather_variables()) > 0
# First model checking
result = stormpy.model_checking(model, formulas[0])
ratFunc = result.at(initial_state)
assert len(ratFunc.gather_variables()) > 0
# Change probabilities
two_pol = stormpy.RationalRF(2)
two_pol = stormpy.FactorizedPolynomial(two_pol)
new_val = stormpy.FactorizedRationalFunction(one_pol, two_pol)
for e in matrix:
if len(e.value().gather_variables()) > 0:
e.set_value(new_val)
for e in matrix:
assert e.value() == new_val or e.value() == one
# Second model checking
result = stormpy.model_checking(model, formulas[0])
ratFunc = result.at(initial_state)
assert len(ratFunc.gather_variables()) == 0
def example_parametric_models_01():
# Check support for parameters
if not config.storm_with_pars:
print("Support parameters is missing. Try building storm-pars.")
return
import stormpy.pars
path = stormpy.examples.files.prism_pdtmc_die
prism_program = stormpy.parse_prism_program(path)
formula_str = "P=? [F s=7 & d=3]"
properties = stormpy.parse_properties_for_prism_program(formula_str, prism_program)
model = stormpy.build_parametric_model(prism_program, properties)
print("Model supports parameters: {}".format(model.supports_parameters))
parameters = model.collect_probability_parameters()
assert len(parameters) == 2
instantiator = stormpy.pars.PDtmcInstantiator(model)
point = dict()
for x in parameters:
print(x.name)
point[x] = stormpy.RationalRF(0.0)
instantiated_model = instantiator.instantiate(point)
result = stormpy.model_checking(instantiated_model, properties[0])
print(result)
def example_analysis_02():
path = stormpy.examples.files.prism_dtmc_die
prism_program = stormpy.parse_prism_program(path)
formula_str = "P=? [F s=7 & d=2]"
properties = stormpy.parse_properties(formula_str, prism_program)
model = stormpy.build_symbolic_model(prism_program, properties)
result = stormpy.model_checking(model, properties[0])
filter = stormpy.create_filter_initial_states_symbolic(model)
result.filter(filter)
assert result.min == result.max
print(result.min)
# Create an auxiliary mapping to build expressions that matches some state.
variables = dict()
for m in prism_program.modules:
for v in m.integer_variables:
variables[v.name] = v.expression_variable.get_expression()
expr_manager = prism_program.expression_manager
expr_for_state_1 = Expression.Conjunction([
Expression.Eq(variables["s"], expr_manager.create_integer(1)),
Expression.Eq(variables["d"], expr_manager.create_integer(0))
])
expr_for_state_2 = Expression.And(
Expression.Eq(variables["s"], expr_manager.create_integer(4)),
Expression.Eq(variables["d"], expr_manager.create_integer(0)))
result = stormpy.model_checking(model, properties[0])
cached_res = result.clone()
cached_res.filter(stormpy.create_filter_symbolic(model, expr_for_state_1))
print(cached_res.min)
result.filter(stormpy.create_filter_symbolic(model, expr_for_state_2))
assert result.min == result.max
print(result.min)
def test_scheduler_mdp(self):
program = stormpy.parse_prism_program(
get_example_path("mdp", "coin2-2.nm"))
formulas = stormpy.parse_properties_for_prism_program(
"Pmin=? [ F \"finished\" & \"all_coins_equal_1\"]", program)
model = stormpy.build_model(program, formulas)
assert model.nr_states == 272
assert model.nr_transitions == 492
assert len(model.initial_states) == 1
initial_state = model.initial_states[0]
assert initial_state == 0
result = stormpy.model_checking(model,
formulas[0],
extract_scheduler=True)
assert result.has_scheduler
scheduler = result.scheduler
assert scheduler.memoryless
assert scheduler.memory_size == 1
assert scheduler.deterministic
for state in model.states:
choice = scheduler.get_choice(state)
assert choice.defined
assert choice.deterministic
action = choice.get_deterministic_choice()
assert 0 <= action
assert action < len(state.actions)
distribution = choice.get_choice()
assert str(distribution).startswith("{[1:")
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,
splitting_threshold=None)
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,
splitting_threshold=None)
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,
splitting_threshold=None)
result = checker.check_region(env, region)
assert result == stormpy.pars.RegionResult.ALLVIOLATED
def test_apply_scheduler_ma(self):
program = stormpy.parse_prism_program(
get_example_path("ma", "simple.ma"), False, True)
formulas = stormpy.parse_properties_for_prism_program(
"Tmin=? [ F s=4 ]", program)
ma = stormpy.build_model(program, formulas)
assert ma.nr_states == 5
assert ma.nr_transitions == 8
assert ma.model_type == stormpy.ModelType.MA
initial_state = ma.initial_states[0]
assert initial_state == 0
result = stormpy.model_checking(ma,
formulas[0],
extract_scheduler=True)
assert math.isclose(result.at(initial_state), 0.08333333333)
assert result.has_scheduler
scheduler = result.scheduler
assert scheduler.memoryless
assert scheduler.memory_size == 1
assert scheduler.deterministic
intermediate = ma.apply_scheduler(scheduler)
assert intermediate.model_type == stormpy.ModelType.MA
assert intermediate.nr_states == 3
assert intermediate.nr_transitions == 4
for state in intermediate.states:
assert len(state.actions) == 1
def test_apply_scheduler_mdp(self):
program = stormpy.parse_prism_program(
get_example_path("mdp", "coin2-2.nm"))
formulas = stormpy.parse_properties_for_prism_program(
"Pmin=? [ F \"finished\" & \"all_coins_equal_1\"]", program)
model = stormpy.build_model(program, formulas)
assert model.nr_states == 272
assert model.nr_transitions == 492
assert len(model.initial_states) == 1
initial_state = model.initial_states[0]
assert initial_state == 0
result = stormpy.model_checking(model,
formulas[0],
extract_scheduler=True)
assert result.has_scheduler
scheduler = result.scheduler
assert scheduler.memoryless
assert scheduler.memory_size == 1
assert scheduler.deterministic
assert not scheduler.partial
intermediate = model.apply_scheduler(scheduler, True)
assert intermediate.model_type == stormpy.ModelType.DTMC
assert intermediate.nr_states == 126
assert intermediate.nr_transitions == 156
for state in intermediate.states:
assert len(state.actions) == 1
def load_sketch(self,
path,
property_path,
optimality_path=None,
constant_str=""):
logger.info("Load sketch from {} with constants {}".format(
path, constant_str))
prism_program = stormpy.parse_prism_program(path)
self.expression_manager = prism_program.expression_manager
self._load_properties_from_file(prism_program, property_path,
constant_str)
if optimality_path is not None:
self._load_optimality(optimality_path, prism_program)
all_properties = self.properties + [
self._optimality_setting.criterion
]
else:
all_properties = self.properties
self.sketch, all_properties = prism_program.to_jani(all_properties)
if optimality_path is not None:
self.properties = all_properties[:-1]
self._optimality_setting._criterion = all_properties[-1]
else:
self.properties = all_properties
self._set_constants(constant_str)
self._find_holes()
self._annotate_properties(constant_str)
assert self.expression_manager == self.sketch.expression_manager
def _run_pric3(filename, threshold):
settings = Settings(default_oracle_value=Fraction(0),
check_inductiveness_if_property_holds=True,
check_relative_inductiveness_of_frames=False,
obligation_queue_class="RepushingObligationQueue",
oracle_type="perfect",
number_simulations_for_oracle=100000,
max_number_steps_per_simulation=1000000,
simulator="cpp",
propagate=True,
forall_mode=ForallMode.FORALL_GLOBALS.value,
inline_goal=True,
int_to_real=False,
export_to_smt2=False,
store_smt_calls=False,
generalize=False,
depth_for_partly_solving_lqs=200,
generalization_method="Hybrid",
max_num_ctgs=1,
use_states_of_same_kind=True)
prism_program = parse_prism_program(filename)
input_program = InputProgram(prism_program)
smt_program = SmtProgram(input_program, settings.get_smt_settings())
ic3 = PrIC3(smt_program, Fraction(threshold), settings, Statistics(dict()))
return ic3.run()
def example_simulator_01():
path = stormpy.examples.files.prism_dtmc_die
prism_program = stormpy.parse_prism_program(path)
model = stormpy.build_model(prism_program)
simulator = stormpy.simulator.create_simulator(model, seed=42)
final_outcomes = dict()
for n in range(1000):
while not simulator.is_done():
observation = simulator.step()
if observation not in final_outcomes:
final_outcomes[observation] = 1
else:
final_outcomes[observation] += 1
simulator.restart()
print(final_outcomes)
options = stormpy.BuilderOptions([])
options.set_build_state_valuations()
model = stormpy.build_sparse_model_with_options(prism_program, options)
simulator = stormpy.simulator.create_simulator(model, seed=42)
simulator.set_observation_mode(stormpy.simulator.SimulatorObservationMode.PROGRAM_LEVEL)
final_outcomes = dict()
for n in range(1000):
while not simulator.is_done():
observation = simulator.step()
if observation not in final_outcomes:
final_outcomes[observation] = 1
else:
final_outcomes[observation] += 1
simulator.restart()
print(", ".join([f"{str(k)}: {v}" for k,v in final_outcomes.items()]))
def example_highlevel_models():
path = stormpy.examples.files.prism_pdtmc_die
prism_program = stormpy.parse_prism_program(path)
for c in prism_program.constants:
print("constant {} with type {} is {} defined".format(
c.name, c.type, "" if c.defined else "not"))
path = stormpy.examples.files.prism_dtmc_brp
prism_program = stormpy.parse_prism_program(path)
for module in prism_program.modules:
for v in module.integer_variables:
print(
f"Variable {v.name} has bounds {v.lower_bound_expression} and {v.upper_bound_expression}"
)
for v in module.boolean_variables:
print(f"Variable {v.name} is Boolean")
def test_model_checking_prob01(self):
program = stormpy.parse_prism_program(
get_example_path("dtmc", "die.pm"))
formulaPhi = stormpy.parse_properties("true")[0]
formulaPsi = stormpy.parse_properties("\"six\"")[0]
model = stormpy.build_model(program, [formulaPsi])
phiResult = stormpy.model_checking(model, formulaPhi)
phiStates = phiResult.get_truth_values()
assert phiStates.number_of_set_bits() == model.nr_states
psiResult = stormpy.model_checking(model, formulaPsi)
psiStates = psiResult.get_truth_values()
assert psiStates.number_of_set_bits() == 1
(prob0, prob1) = stormpy.compute_prob01_states(model, phiStates,
psiStates)
assert prob0.number_of_set_bits() == 9
assert prob1.number_of_set_bits() == 1
(prob0,
prob1) = stormpy.compute_prob01min_states(model, phiStates, psiStates)
assert prob0.number_of_set_bits() == 9
assert prob1.number_of_set_bits() == 1
(prob0,
prob1) = stormpy.compute_prob01max_states(model, phiStates, psiStates)
assert prob0.number_of_set_bits() == 9
assert prob1.number_of_set_bits() == 1
labelprop = stormpy.core.Property("cora", formulaPsi.raw_formula)
result = stormpy.model_checking(model, labelprop)
assert result.get_truth_values().number_of_set_bits() == 1
def test_transform_continuous_to_discrete_time_model_ma(self):
program = stormpy.parse_prism_program(
get_example_path("ma", "simple.ma"), False, True)
formulas = stormpy.parse_properties_for_prism_program(
"Tmin=? [ F s=4 ]", program)
ma = stormpy.build_model(program, formulas)
assert ma.nr_states == 5
assert ma.nr_transitions == 8
assert ma.model_type == stormpy.ModelType.MA
assert len(ma.initial_states) == 1
initial_state = ma.initial_states[0]
assert initial_state == 0
result = stormpy.model_checking(ma, formulas[0])
assert math.isclose(result.at(initial_state), 0.08333333333)
mdp, mdp_formulas = stormpy.transform_to_discrete_time_model(
ma, formulas)
assert mdp.nr_states == 5
assert mdp.nr_transitions == 8
assert mdp.model_type == stormpy.ModelType.MDP
assert len(mdp.initial_states) == 1
initial_state = mdp.initial_states[0]
assert initial_state == 0
result = stormpy.model_checking(mdp, mdp_formulas[0])
assert math.isclose(result.at(initial_state), 0.08333333333)
def parse_cap_from_prism(filename):
prism_prog = stormpy.parse_prism_program(filename)
for cons in prism_prog.constants:
if cons.name == "capacity":
return cons.definition.evaluate_as_int()
return None
