def repair(self, local_repairer, dtmc_name, policy_name, base_dir):
dtmc = self.dtmc_generator.compute_dtmc()
dtmc.save(dtmc_name, base_dir)
dtmc_tra = os.path.join(base_dir, dtmc_name + '.tra')
dtmc_lab = os.path.join(base_dir, dtmc_name + '.lab')
model = stormpy.build_sparse_model_from_explicit(dtmc_tra, dtmc_lab)
#unsafe_reachability_prob = stormpy.model_checking_all(model, self.formula[0])
unsafe_reachability_prob = stormpy.model_checking(model, self.formula[0])
##unsafe=stormpy.ExplicitQuantitativeCheckResult.get_values(unsafe_reachability_prob)
##print(' Unsafe Prob {}'.format(unsafe))
#init_unsafe_prob = unsafe_reachability_prob[state_mapper.INITIAL_STATE]
init_unsafe_prob = stormpy.ExplicitQuantitativeCheckResult.at(unsafe_reachability_prob,state_mapper.INITIAL_STATE)
print('Init Unsafe Prob {}'.format(init_unsafe_prob))
while init_unsafe_prob > self._lambda and local_repairer.repair(self.dtmc_generator, unsafe_reachability_prob):
dtmc = self.dtmc_generator.compute_dtmc()
dtmc.save(dtmc_name, base_dir)
self.dtmc_generator.save_policy(policy_name, base_dir)
model = stormpy.build_sparse_model_from_explicit(dtmc_tra, dtmc_lab)
#unsafe_reachability_prob = stormpy.model_checking_all(model, self.formula[0])
unsafe_reachability_prob = stormpy.model_checking(model, self.formula[0])
init_unsafe_prob = stormpy.ExplicitQuantitativeCheckResult.at(unsafe_reachability_prob,state_mapper.INITIAL_STATE)
print('(New Init Unsafe)Prob {}'.format(init_unsafe_prob))
print('Final Unsafe Prob {}'.format(init_unsafe_prob))
return dtmc
def test_actions_mdp(self):
model = stormpy.build_sparse_model_from_explicit(
get_example_path("mdp", "two_dice.tra"),
get_example_path("mdp", "two_dice.lab"))
for state in model.states:
assert len(state.actions) == 1 or len(state.actions) == 2
for action in state.actions:
assert action.id == 0 or action.id == 1
def test_actions_dtmc(self):
model = stormpy.build_sparse_model_from_explicit(
get_example_path("dtmc", "die.tra"),
get_example_path("dtmc", "die.lab"))
for state in model.states:
assert len(state.actions) == 1
for action in state.actions:
assert action.id == 0
def test_parse_explicit_mdp(self):
model = stormpy.build_sparse_model_from_explicit(get_example_path("mdp", "two_dice.tra"),
get_example_path("mdp", "two_dice.lab"))
assert model.nr_states == 169
assert model.nr_transitions == 436
assert model.model_type == stormpy.ModelType.MDP
assert not model.supports_parameters
assert type(model) is stormpy.SparseMdp
def test_parse_explicit_dtmc(self):
model = stormpy.build_sparse_model_from_explicit(get_example_path("dtmc", "die.tra"),
get_example_path("dtmc", "die.lab"))
assert model.nr_states == 13
assert model.nr_transitions == 20
assert model.model_type == stormpy.ModelType.DTMC
assert not model.supports_parameters
assert type(model) is stormpy.SparseDtmc
def test_transitions_mdp(self):
model = stormpy.build_sparse_model_from_explicit(
get_example_path("mdp", "two_dice.tra"),
get_example_path("mdp", "two_dice.lab"))
assert model.states[1].id == 1
for state in model.states:
i = 0
for action in state.actions:
i += 1
for transition in action.transitions:
assert transition.value() == 0.5 or transition.value() == 1
assert i == 1 or i == 2
def test_labels_dtmc(self):
model = stormpy.build_sparse_model_from_explicit(
get_example_path("dtmc", "die.tra"),
get_example_path("dtmc", "die.lab"))
labelsOrig = [["init"], [], [], [], [], [], [], ["one", "done"],
["two", "done"], ["three", "done"], ["four", "done"],
["five", "done"], ["six", "done"]]
i = 0
for state in model.states:
labels = state.labels
for label in labelsOrig[i]:
assert label in labels
i += 1
def test_matrix(self):
model = stormpy.build_sparse_model_from_explicit(
get_example_path("dtmc", "die.tra"),
get_example_path("dtmc", "die.lab"))
matrix = model.transition_matrix
assert type(matrix) is stormpy.storage.SparseMatrix
assert matrix.nr_rows == model.nr_states
assert matrix.nr_columns == model.nr_states
assert matrix.nr_entries == 20
assert matrix.nr_entries == model.nr_transitions
for e in matrix:
assert e.value() == 0.5 or e.value() == 0 or (e.value() == 1
and e.column > 6)
def test_states_dtmc(self):
model = stormpy.build_sparse_model_from_explicit(
get_example_path("dtmc", "die.tra"),
get_example_path("dtmc", "die.lab"))
i = 0
states = model.states
assert len(states) == 13
for state in states:
assert state.id == i
i += 1
assert i == model.nr_states
state = model.states[2]
assert state.id == 2
state = states[5]
assert state.id == 5
def test_states_mdp(self):
model = stormpy.build_sparse_model_from_explicit(
get_example_path("mdp", "two_dice.tra"),
get_example_path("mdp", "two_dice.lab"))
i = 0
assert len(model.states) == 169
for state in model.states:
assert state.id == i
i += 1
assert i == model.nr_states
states = model.states
state = model.states[6]
assert state.id == 6
state = states[1]
assert state.id == 1
def test_change_matrix(self):
model = stormpy.build_sparse_model_from_explicit(
get_example_path("dtmc", "die.tra"),
get_example_path("dtmc", "die.lab"))
matrix = model.transition_matrix
for e in matrix:
assert e.value() == 0.5 or e.value() == 0 or e.value() == 1
i = 0
for e in matrix:
e.set_value(i)
i += 0.1
i = 0
for e in matrix:
assert e.value() == i
i += 0.1
def test_change_matrix_modelchecking(self):
import stormpy.logic
model = stormpy.build_sparse_model_from_explicit(
get_example_path("dtmc", "die.tra"),
get_example_path("dtmc", "die.lab"))
matrix = model.transition_matrix
# Check matrix
for e in matrix:
assert e.value() == 0.5 or e.value() == 0 or e.value() == 1
# First model checking
formulas = stormpy.parse_properties("P=? [ F \"one\" ]")
result = stormpy.model_checking(model, formulas[0])
resValue = result.at(model.initial_states[0])
assert math.isclose(resValue, 0.16666666666666663)
# Change probabilities
i = 0
for e in matrix:
if e.value() == 0.5:
if i % 2 == 0:
e.set_value(0.3)
else:
e.set_value(0.7)
i += 1
for e in matrix:
assert e.value() == 0.3 or e.value() == 0.7 or e.value(
) == 1 or e.value() == 0
# Second model checking
result = stormpy.model_checking(model, formulas[0])
resValue = result.at(model.initial_states[0])
assert math.isclose(resValue, 0.06923076923076932)
# Change probabilities again
for state in model.states:
for action in state.actions:
for transition in action.transitions:
if transition.value() == 0.3:
transition.set_value(0.8)
elif transition.value() == 0.7:
transition.set_value(0.2)
# Third model checking
result = stormpy.model_checking(model, formulas[0])
resValue = result.at(model.initial_states[0])
assert math.isclose(resValue, 0.3555555555555556)
def compute_probabilities(self, base_dir='data/repair'):
import stormpy
import stormpy.logic
goal_formula_str = "P=? [ F \"goal\" ]"
goal_formula = stormpy.parse_properties(goal_formula_str)
fallen_formula_str = "P=? [ F \"fallen\" ]"
fallen_formula = stormpy.parse_properties(fallen_formula_str)
far_formula_str = "P=? [ F \"far\" ]"
far_formula = stormpy.parse_properties(far_formula_str)
collided_formula_str = "P=? [ F \"collided\" ]"
collided_formula = stormpy.parse_properties(collided_formula_str)
total_formula_str = "P=? [ F (\"far\" | \"collided\" | \"fallen\")]"
total_formula = stormpy.parse_properties(total_formula_str)
self.save('temp', base_dir)
#model = stormpy.parse_explicit_model(os.path.join(base_dir, 'temp.tra'),
# os.path.join(base_dir, 'temp.lab'))
model = stormpy.build_sparse_model_from_explicit(
os.path.join(base_dir, 'temp.tra'),
os.path.join(base_dir, 'temp.lab'))
goal_prob = stormpy.model_checking(model, goal_formula[0])
goal_prob_Init = stormpy.ExplicitQuantitativeCheckResult.at(
goal_prob, state_mapper.INITIAL_STATE)
fallen_prob = stormpy.model_checking(model, fallen_formula[0])
fallen_prob_Init = stormpy.ExplicitQuantitativeCheckResult.at(
fallen_prob, state_mapper.INITIAL_STATE)
far_prob = stormpy.model_checking(model, far_formula[0])
far_prob_Init = stormpy.ExplicitQuantitativeCheckResult.at(
far_prob, state_mapper.INITIAL_STATE)
collided_prob = stormpy.model_checking(model, collided_formula[0])
collided_prob_Init = stormpy.ExplicitQuantitativeCheckResult.at(
collided_prob, state_mapper.INITIAL_STATE)
total_prob = stormpy.model_checking(model, total_formula[0])
total_prob_Init = stormpy.ExplicitQuantitativeCheckResult.at(
total_prob, state_mapper.INITIAL_STATE)
#print('At Init Probs: goal: {} , fallen: {} far: {} collided : {} total : {}'.format(goal_prob_Init,fallen_prob_Init,far_prob_Init,collided_prob_Init,total_prob_Init))
return {
'goal': goal_prob_Init,
'fallen': fallen_prob_Init,
'far': far_prob_Init,
'collided': collided_prob_Init,
'total': total_prob_Init
}
def test_row_iterator(self):
transitions_orig = [(0, 1, 0.5), (0, 2, 0.5), (1, 3, 0.5), (1, 4, 0.5),
(2, 5, 0.5), (2, 6, 0.5), (3, 1, 0.5), (3, 7, 0.5),
(4, 8, 0.5), (4, 9, 0.5), (5, 10, 0.5),
(5, 11, 0.5), (6, 2, 0.5), (6, 12, 0.5), (7, 7, 1),
(8, 8, 1), (9, 9, 1), (10, 10, 1), (11, 11, 1),
(12, 12, 1)]
model = stormpy.build_sparse_model_from_explicit(
get_example_path("dtmc", "die.tra"),
get_example_path("dtmc", "die.lab"))
i = 0
for state in model.states:
for transition in model.transition_matrix.row_iter(
state.id, state.id):
transition_orig = transitions_orig[i]
i += 1
assert state.id == transition_orig[0]
assert transition.column == transition_orig[1]
assert transition.value() == transition_orig[2]
def test_transitions_dtmc(self):
transitions_orig = [(0, 1, 0.5), (0, 2, 0.5), (1, 3, 0.5), (1, 4, 0.5),
(2, 5, 0.5), (2, 6, 0.5), (3, 1, 0.5), (3, 7, 0.5),
(4, 8, 0.5), (4, 9, 0.5), (5, 10, 0.5),
(5, 11, 0.5), (6, 2, 0.5), (6, 12, 0.5), (7, 7, 1),
(8, 8, 1), (9, 9, 1), (10, 10, 1), (11, 11, 1),
(12, 12, 1)]
model = stormpy.build_sparse_model_from_explicit(
get_example_path("dtmc", "die.tra"),
get_example_path("dtmc", "die.lab"))
i = 0
for state in model.states:
for action in state.actions:
assert (state.id < 7 and len(action.transitions) == 2) or (
state.id >= 7 and len(action.transitions) == 1)
for transition in action.transitions:
transition_orig = transitions_orig[i]
i += 1
assert state.id == transition_orig[0]
assert transition.column == transition_orig[1]
assert transition.value() == transition_orig[2]
def test_submatrix(self):
model = stormpy.build_sparse_model_from_explicit(
get_example_path("dtmc", "die.tra"),
get_example_path("dtmc", "die.lab"))
matrix = model.transition_matrix
assert matrix.nr_rows == 13
assert matrix.nr_columns == 13
assert matrix.nr_entries == 20
assert matrix.nr_entries == model.nr_transitions
for e in matrix:
assert e.value() == 0.5 or e.value() == 0 or (e.value() == 1
and e.column > 6)
row_constraint = stormpy.BitVector(13, [0, 1, 3, 4, 7, 8, 9])
submatrix = matrix.submatrix(row_constraint, row_constraint)
assert submatrix.nr_rows == 7
assert submatrix.nr_columns == 7
assert submatrix.nr_entries == 10
for e in submatrix:
assert e.value() == 0.5 or e.value() == 0 or (e.value() == 1
and e.column > 3)
