def subset_test():
a = SubSet([1, 2, 3, 4, {1: 2}])
print(a)
a.add(1)
a.add_from([1, 2])
a |= [3, 4]
assert (a._set == {1, 2, 3, 4})
a |= [{1: 2}]
assert (a._list == [{1: 2}])
b = SubSet([1, '2'])
b.add('2')
assert (b._set == {'2'})
assert (not bool(b._list))
assert (b._superset == [1, '2'])
superset = [1, 2]
s = SubSet(superset)
s |= [1, 2]
print(s)
assert (s._set == {1, 2})
assert (not bool(s._list))
#s.add(3)
return a
def subset_test():
a = SubSet([1, 2, 3, 4, {1: 2}])
print (a)
a.add(1)
a.add_from([1, 2])
a |= [3, 4]
assert a._set == {1, 2, 3, 4}
a |= [{1: 2}]
assert a._list == [{1: 2}]
b = SubSet([1, "2"])
b.add("2")
assert b._set == {"2"}
assert not bool(b._list)
assert b._superset == [1, "2"]
superset = [1, 2]
s = SubSet(superset)
s |= [1, 2]
print (s)
assert s._set == {1, 2}
assert not bool(s._list)
# s.add(3)
return a
def solve(ks, goal_label, spec):
"""Solve the minimum violation planning problem
This follows from
J. Tumova, G.C Hall, S. Karaman, E. Frazzoli and D. Rus.
Least-violating Control Strategy Synthesis with Safety Rules, HSCC 2013.
@param ks: the Kripke structure
@param goal_label: a label in ks.atomic_propositions that indicates the goal
@param spec: the prioritized safety specification of type
tulip.spec.prioritized_safety.PrioritizedSpecification
@return: (best_cost, best_path, weighted_product_automaton) where
* best_cost is the optimal cost of reaching the goal
* best_path is the optimal path to the goal
* weighted_product_automaton is the weighted product automaton ks times spec
"""
assert isinstance(ks, KS)
assert isinstance(spec, PrioritizedSpecification)
assert ks.atomic_propositions == spec.atomic_propositions
(wpa, null_state) = _construct_weighted_product_automaton(ks, spec)
goal_states = [
state for state in ks.states if goal_label in ks.states[state]["ap"]
]
accepting_goal_states = SubSet(wpa.states.accepting)
accepting_goal_states.add_from(set(product(goal_states,
spec.get_states())))
(cost, product_path) = dijkstra_multiple_sources_multiple_targets(
wpa, wpa.states.initial, accepting_goal_states, cost_key="cost")
state_path = [state[0] for state in product_path if state[0] != null_state]
return (cost, state_path, product_path, wpa)