def prob_TL(self, phi):
model_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
"models")
prism_file_path = os.path.join(model_path, "pedestrian.nm")
path_MC = os.path.join(model_path, "model_MC.nm")
env_MC = os.path.join(model_path, "env_MC.nm")
# Print self markov chain:
# print(self.MC)
# Writing prism files:
stormpy_int.to_prism_file(self.MC, path_MC)
stormpy_int.to_prism_file(self.true_env_MC, env_MC)
composed = synchronous_parallel([self.MC, self.true_env_MC])
# print(composed.transitions)
result = stormpy_int.model_checking(composed, phi, prism_file_path)
# Returns a tulip transys:
# MC_ts = stormpy_int.to_tulip_transys(path_MC)
result = stormpy_int.model_checking(
self.MC, phi, prism_file_path
) # Since there is no moving obstacle, try checking only the pedestrian obstacle
# for state in self.MC.states:
# print(self.MC.states[state]["ap"])
# self.MC.states[state]["ap"] |= {"good"}
# Debugging: print states of result:
# print(self.MC)
# print(result)
# print(" ")
# for state in self.MC.states:
# print(" State {}, with labels {}, Pr = {}".format(state, self.MC.states[state], result[(state, None)]))
# for state in self.MC.states:
# print(" State {}, with labels {}, Pr = {}".format(state, self.MC.states[state]["ap"], result[state]))
return result # Implement this soon: Storm py
def light_analysis_test():
# Build models from prism files
light = stormpy_int.to_tulip_transys(light_path)
# Check properties
formula = 'P=? [ F ("green") ]'
# Model checking
result = stormpy_int.model_checking(light, formula, out_model_path)
os.remove(out_model_path)
assert len(light.states) == 2
expected_result = [
{
"labels": {"green"},
"result": 1.0
},
{
"labels": {"red"},
"result": 1.0
},
]
_check_result(light, result, expected_result)
def compose_test():
# Build models from prism files
mh = stormpy_int.to_tulip_transys(mh_path)
light = stormpy_int.to_tulip_transys(light_path)
# Compose models
composed = synchronous_parallel([mh, light])
# Check properties
formula = 'P=? [ "green" U "h6" ]'
# Model checking
result = stormpy_int.model_checking(composed, formula, out_model_path)
os.remove(out_model_path)
assert len(composed.states) == 14
expected_result = [
{
"labels": {"h6", "green"},
"result": 1.0
},
{
"labels": {"red", "h6"},
"result": 1.0
},
{
"labels": {"h2", "green"},
"result": 0.42122366709344317
},
{
"labels": {"red", "h2"},
"result": 0.0
},
{
"labels": {"h4", "green"},
"result": 0.7256235827664395
},
{
"labels": {"red", "h4"},
"result": 0.0
},
{
"labels": {"h5", "green"},
"result": 0.9523809523809521
},
{
"labels": {"red", "h5"},
"result": 0.0
},
{
"labels": {"green", "h1"},
"result": 0.3209323177854804
},
{
"labels": {"red", "h1"},
"result": 0.0
},
{
"labels": {"h0", "green"},
"result": 0.2445198611698898
},
{
"labels": {"red", "h0"},
"result": 0.0
},
{
"labels": {"green", "h3"},
"result": 0.5528560630601442
},
{
"labels": {"red", "h3"},
"result": 0.0
},
]
_check_result(composed, result, expected_result)
def synthesis_test():
# Build models from prism files
ma = stormpy_int.to_tulip_transys(ma_path)
mh = stormpy_int.to_tulip_transys(mh_path)
light = stormpy_int.to_tulip_transys(light_path)
# Compose models
composed = synchronous_parallel([ma, mh, light])
# Check properties
safety = '!("h4" & "a4") & !("red" & ("a8" | "a4"))'
reach = '"a9"'
formula = "Pmax=? [ ({}) U ({}) ]".format(safety, reach)
# Construct policy
(result, policy) = stormpy_int.model_checking(composed, formula,
out_model_path, True)
os.remove(out_model_path)
assert abs(result[list(composed.states.initial)[0]] -
0.7429340826573935) < 1e-6
# Get the MC induced by applying policy_opt on model
induced_mc = apply_policy(composed, policy)
# Model checking
result = stormpy_int.model_checking(induced_mc, formula, out_model_path)
os.remove(out_model_path)
expected_result = [
{
"labels": {"green", "h5", "a8"},
"result": 0.745341614906832
},
{
"labels": {"h5", "red", "a8"},
"result": 0.0
},
{
"labels": {"green", "h0", "a8"},
"result": 0.7429340826573935
},
{
"labels": {"h0", "red", "a8"},
"result": 0.0
},
{
"labels": {"green", "h1", "a8"},
"result": 0.7287988161717747
},
{
"labels": {"h1", "a8", "red"},
"result": 0.0
},
{
"labels": {"green", "a8", "h4"},
"result": 0.6059687926071806
},
{
"labels": {"red", "a8", "h4"},
"result": 0.0
},
{
"labels": {"green", "a8", "h6"},
"result": 0.745341614906832
},
{
"labels": {"red", "a8", "h6"},
"result": 0.0
},
{
"labels": {"green", "a8", "h3"},
"result": 0.3861264940442798
},
{
"labels": {"red", "a8", "h3"},
"result": 0.0
},
{
"labels": {"green", "h2", "a8"},
"result": 0.6458232194557872
},
{
"labels": {"h2", "a8", "red"},
"result": 0.0
},
{
"labels": {"green", "h5", "a4"},
"result": 0.9523809523809523
},
{
"labels": {"h5", "red", "a4"},
"result": 0.0
},
{
"labels": {"green", "h0", "a4"},
"result": 0.9520897806888625
},
{
"labels": {"h0", "red", "a4"},
"result": 0.0
},
{
"labels": {"green", "h1", "a4"},
"result": 0.9501789664595234
},
{
"labels": {"h1", "a4", "red"},
"result": 0.0
},
{
"labels": {"green", "a4", "h4"},
"result": 0.0
},
{
"labels": {"red", "a4", "h4"},
"result": 0.0
},
{
"labels": {"green", "a4", "h6"},
"result": 0.9523809523809521
},
{
"labels": {"red", "a4", "h6"},
"result": 0.0
},
{
"labels": {"green", "a4", "h3"},
"result": 0.8264462809917354
},
{
"labels": {"red", "a4", "h3"},
"result": 0.0
},
{
"labels": {"green", "h2", "a4"},
"result": 0.9357284338501467
},
{
"labels": {"h2", "a4", "red"},
"result": 0.0
},
{
"labels": {"green", "h5", "a9"},
"result": 1.0
},
{
"labels": {"h5", "a9", "red"},
"result": 1.0
},
{
"labels": {"green", "h0", "a9"},
"result": 1.0
},
{
"labels": {"h0", "a9", "red"},
"result": 1.0
},
{
"labels": {"green", "a9", "h1"},
"result": 1.0
},
{
"labels": {"a9", "red", "h1"},
"result": 1.0
},
{
"labels": {"green", "a9", "h4"},
"result": 1.0
},
{
"labels": {"a9", "red", "h4"},
"result": 1.0
},
{
"labels": {"green", "a9", "h6"},
"result": 1.0
},
{
"labels": {"a9", "h6", "red"},
"result": 1.0
},
{
"labels": {"green", "a9", "h3"},
"result": 1.0
},
{
"labels": {"a9", "h3", "red"},
"result": 1.0
},
{
"labels": {"green", "a9", "h2"},
"result": 1.0
},
{
"labels": {"a9", "h2", "red"},
"result": 1.0
},
]
_check_result(composed, result, expected_result)
def compose_test():
# Build models from prism files
mh = stormpy_int.to_tulip_transys(mh_path)
light = stormpy_int.to_tulip_transys(light_path)
# Compose models
composed = synchronous_parallel([mh, light])
# Check properties
formula = 'P=? [ "green" U "h6" ]'
# Model checking
result = stormpy_int.model_checking(composed, formula, out_model_path)
os.remove(out_model_path)
assert len(composed.states) == 14
expected_result = [
{
"labels": {"h6", "green"},
"result": 1.0
},
{
"labels": {"red", "h6"},
"result": 1.0
},
{
"labels": {"h2", "green"},
"result": 0.421_223_667_093_443_17
},
{
"labels": {"red", "h2"},
"result": 0.0
},
{
"labels": {"h4", "green"},
"result": 0.725_623_582_766_439_5
},
{
"labels": {"red", "h4"},
"result": 0.0
},
{
"labels": {"h5", "green"},
"result": 0.952_380_952_380_952_1
},
{
"labels": {"red", "h5"},
"result": 0.0
},
{
"labels": {"green", "h1"},
"result": 0.320_932_317_785_480_4
},
{
"labels": {"red", "h1"},
"result": 0.0
},
{
"labels": {"h0", "green"},
"result": 0.244_519_861_169_889_8
},
{
"labels": {"red", "h0"},
"result": 0.0
},
{
"labels": {"green", "h3"},
"result": 0.552_856_063_060_144_2
},
{
"labels": {"red", "h3"},
"result": 0.0
},
]
_check_result(composed, result, expected_result)
def synthesis_test():
# Build models from prism files
ma = stormpy_int.to_tulip_transys(ma_path)
mh = stormpy_int.to_tulip_transys(mh_path)
light = stormpy_int.to_tulip_transys(light_path)
# Compose models
composed = synchronous_parallel([ma, mh, light])
# Check properties
safety = '!("h4" & "a4") & !("red" & ("a8" | "a4"))'
reach = '"a9"'
formula = "Pmax=? [ ({}) U ({}) ]".format(safety, reach)
# Construct policy
(result, policy) = stormpy_int.model_checking(composed, formula,
out_model_path, True)
os.remove(out_model_path)
assert abs(result[list(composed.states.initial)[0]] -
0.742_934_082_657_393_5) < 1e-6
# Get the MC induced by applying policy_opt on model
induced_mc = apply_policy(composed, policy)
# Model checking
result = stormpy_int.model_checking(induced_mc, formula, out_model_path)
os.remove(out_model_path)
expected_result = [
{
"labels": {"green", "h5", "a8"},
"result": 0.745_341_614_906_832
},
{
"labels": {"h5", "red", "a8"},
"result": 0.0
},
{
"labels": {"green", "h0", "a8"},
"result": 0.742_934_082_657_393_5
},
{
"labels": {"h0", "red", "a8"},
"result": 0.0
},
{
"labels": {"green", "h1", "a8"},
"result": 0.728_798_816_171_774_7
},
{
"labels": {"h1", "a8", "red"},
"result": 0.0
},
{
"labels": {"green", "a8", "h4"},
"result": 0.605_968_792_607_180_6
},
{
"labels": {"red", "a8", "h4"},
"result": 0.0
},
{
"labels": {"green", "a8", "h6"},
"result": 0.745_341_614_906_832
},
{
"labels": {"red", "a8", "h6"},
"result": 0.0
},
{
"labels": {"green", "a8", "h3"},
"result": 0.386_126_494_044_279_8
},
{
"labels": {"red", "a8", "h3"},
"result": 0.0
},
{
"labels": {"green", "h2", "a8"},
"result": 0.645_823_219_455_787_2
},
{
"labels": {"h2", "a8", "red"},
"result": 0.0
},
{
"labels": {"green", "h5", "a4"},
"result": 0.952_380_952_380_952_3
},
{
"labels": {"h5", "red", "a4"},
"result": 0.0
},
{
"labels": {"green", "h0", "a4"},
"result": 0.952_089_780_688_862_5
},
{
"labels": {"h0", "red", "a4"},
"result": 0.0
},
{
"labels": {"green", "h1", "a4"},
"result": 0.950_178_966_459_523_4
},
{
"labels": {"h1", "a4", "red"},
"result": 0.0
},
{
"labels": {"green", "a4", "h4"},
"result": 0.0
},
{
"labels": {"red", "a4", "h4"},
"result": 0.0
},
{
"labels": {"green", "a4", "h6"},
"result": 0.952_380_952_380_952_1
},
{
"labels": {"red", "a4", "h6"},
"result": 0.0
},
{
"labels": {"green", "a4", "h3"},
"result": 0.826_446_280_991_735_4
},
{
"labels": {"red", "a4", "h3"},
"result": 0.0
},
{
"labels": {"green", "h2", "a4"},
"result": 0.935_728_433_850_146_7
},
{
"labels": {"h2", "a4", "red"},
"result": 0.0
},
{
"labels": {"green", "h5", "a9"},
"result": 1.0
},
{
"labels": {"h5", "a9", "red"},
"result": 1.0
},
{
"labels": {"green", "h0", "a9"},
"result": 1.0
},
{
"labels": {"h0", "a9", "red"},
"result": 1.0
},
{
"labels": {"green", "a9", "h1"},
"result": 1.0
},
{
"labels": {"a9", "red", "h1"},
"result": 1.0
},
{
"labels": {"green", "a9", "h4"},
"result": 1.0
},
{
"labels": {"a9", "red", "h4"},
"result": 1.0
},
{
"labels": {"green", "a9", "h6"},
"result": 1.0
},
{
"labels": {"a9", "h6", "red"},
"result": 1.0
},
{
"labels": {"green", "a9", "h3"},
"result": 1.0
},
{
"labels": {"a9", "h3", "red"},
"result": 1.0
},
{
"labels": {"green", "a9", "h2"},
"result": 1.0
},
{
"labels": {"a9", "h2", "red"},
"result": 1.0
},
]
_check_result(composed, result, expected_result)
import os
from tulip.interfaces import stormpy as stormpy_int
from tulip.transys.compositions import synchronous_parallel
model_path = os.path.join("/home/ubuntu/eeci/c1-probabilistic", "models")
ma_path = os.path.join(model_path, "ma.nm")
mh_path = os.path.join(model_path, "mh.pm")
light_path = os.path.join(model_path, "light.pm")
ma = stormpy_int.to_tulip_transys(ma_path)
mh = stormpy_int.to_tulip_transys(mh_path)
light = stormpy_int.to_tulip_transys(light_path)
composed = synchronous_parallel([mh, light])
formula = 'P=? [ "green" U "h6" ]'
out_model_path = os.path.join(model_path, "out_composed_model.nm")
result = stormpy_int.model_checking(composed, formula, out_model_path)
for state in composed.states:
print(" State {}, with labels {}, Pr = {}".format(state, composed.states[state]["ap"], result[state]))