def setUp(self):
super().setUp()
self.ac_problem = air_cargo_p1()
self.ac_pg_serial = PlanningGraph(self.ac_problem,
self.ac_problem.initial).fill()
# In(C1, P2) and In(C2, P1) have inconsistent support when they first appear in
# the air cargo problem,
self.inconsistent_support_literals = [
expr("In(C1, P2)"), expr("In(C2, P1)")
]
def setUp(self):
self.cake_problem = have_cake()
self.ac_problem_1 = air_cargo_p1()
self.ac_problem_2 = air_cargo_p2()
self.ac_problem_3 = air_cargo_p3()
self.ac_problem_4 = air_cargo_p4()
self.cake_node = Node(self.cake_problem.initial)
self.ac_node_1 = Node(self.ac_problem_1.initial)
self.ac_node_2 = Node(self.ac_problem_2.initial)
self.ac_node_3 = Node(self.ac_problem_3.initial)
self.ac_node_4 = Node(self.ac_problem_4.initial)
def get_prob_specs():
Probs = [acp.air_cargo_p1(), acp.air_cargo_p2(),
acp.air_cargo_p3(), acp.air_cargo_p4()]
problems_specs = {'Problem': [name for name in problems],
'Air cargo problem': [i+1 for i in range(len(problems))],
'Cargos': [len(p.cargos) for p in Probs],
'Planes': [len(p.planes) for p in Probs],
'Airports': [len(p.airports) for p in Probs],
'Goal': [len(p.goal) for p in Probs]}
return pd.DataFrame(problems_specs)
def setUp(self):
self.cake_problem = have_cake()
self.ac_problem_1 = air_cargo_p1()
self.ac_problem_2 = air_cargo_p2()
self.ac_problem_3 = air_cargo_p3()
self.ac_problem_4 = air_cargo_p4()
self.cake_node = Node(self.cake_problem.initial)
self.ac_node_1 = Node(self.ac_problem_1.initial)
self.ac_node_2 = Node(self.ac_problem_2.initial)
self.ac_node_3 = Node(self.ac_problem_3.initial)
self.ac_node_4 = Node(self.ac_problem_4.initial)
self.msg = "Make sure all your mutex tests pass before troubleshooting this function."
def setUp(self):
self.cake_problem = have_cake()
self.cake_pg = PlanningGraph(self.cake_problem,
self.cake_problem.initial,
serialize=False).fill()
eat_action, bake_action = [
a for a in self.cake_pg._actionNodes if not a.no_op
]
no_ops = [a for a in self.cake_pg._actionNodes if a.no_op]
# bake has the effect Have(Cake) which is the logical negation of the effect
# ~Have(cake) from the persistence action ~NoOp::Have(cake)
self.inconsistent_effects_actions = [bake_action, no_ops[3]]
# the persistence action ~NoOp::Have(cake) has the effect ~Have(cake), which is
# the logical negation of Have(cake) -- the precondition for the Eat(cake) action
self.interference_actions = [eat_action, no_ops[3]]
# eat has precondition Have(cake) and bake has precondition ~Have(cake)
# which are logical inverses, so eat & bake should be mutex at every
# level of the planning graph where both actions appear
self.competing_needs_actions = [eat_action, bake_action]
self.ac_problem = air_cargo_p1()
self.ac_pg_serial = PlanningGraph(self.ac_problem,
self.ac_problem.initial).fill()
# In(C1, P2) and In(C2, P1) have inconsistent support when they first appear in
# the air cargo problem,
self.inconsistent_support_literals = [
expr("In(C1, P2)"), expr("In(C2, P1)")
]
# some independent nodes for testing mutexes
at_here = expr('At(here)')
at_there = expr('At(there)')
self.pos_literals = [at_here, at_there]
self.neg_literals = [~x for x in self.pos_literals]
self.literal_layer = LiteralLayer(
self.pos_literals + self.neg_literals, ActionLayer())
self.literal_layer.update_mutexes()
# independent actions for testing mutex
self.actions = [
make_node(
Action(expr('Go(here)'), [set(), set()],
[set([at_here]), set()])),
make_node(
Action(expr('Go(there)'), [set(), set()],
[set([at_there]), set()]))
]
self.no_ops = [
make_node(x)
for x in chain(*(makeNoOp(l) for l in self.pos_literals))
]
self.action_layer = ActionLayer(self.no_ops + self.actions,
self.literal_layer)
self.action_layer.update_mutexes()
for action in self.no_ops + self.actions:
self.action_layer.add_inbound_edges(action, action.preconditions)
self.action_layer.add_outbound_edges(action, action.effects)
# competing needs tests -- build two copies of the planning graph: one where
# A, B, and C are pairwise mutex, and another where they are not
A, B, C = expr('A'), expr('B'), expr('C')
self.fake_competing_needs_actions = [
make_node(
Action(expr('FakeAction(A)'), [set([A]), set()],
[set([A]), set()])),
make_node(
Action(expr('FakeAction(B)'), [set([B]), set()],
[set([B]), set()])),
make_node(
Action(expr('FakeAction(C)'), [set([C]), set()],
[set([C]), set()]))
]
competing_layer = LiteralLayer([A, B, C], ActionLayer())
for a1, a2 in combinations([A, B, C], 2):
competing_layer.set_mutex(a1, a2)
self.competing_action_layer = ActionLayer(competing_layer.parent_layer,
competing_layer, False, True)
for action in self.fake_competing_needs_actions:
self.competing_action_layer.add(action)
competing_layer |= action.effects
competing_layer.add_outbound_edges(action, action.preconditions)
self.competing_action_layer.add_inbound_edges(
action, action.preconditions)
self.competing_action_layer.add_outbound_edges(
action, action.effects)
not_competing_layer = LiteralLayer([A, B, C], ActionLayer())
self.not_competing_action_layer = ActionLayer(
not_competing_layer.parent_layer, not_competing_layer, False, True)
for action in self.fake_competing_needs_actions:
self.not_competing_action_layer.add(action)
not_competing_layer |= action.effects
not_competing_layer.add_outbound_edges(action,
action.preconditions)
self.not_competing_action_layer.add_inbound_edges(
action, action.preconditions)
self.not_competing_action_layer.add_outbound_edges(
action, action.effects)
