def test_value_all_neighbors_received(self):
x1 = Variable("x1", list(range(2)))
x2 = Variable('x2', list(range(2)))
@AsNAryFunctionRelation(x1, x2)
def phi(x1_, x2_):
return x1_ + x2_
computation = Mgm2Computation(x1, [phi],
msg_sender=DummySender(),
comp_def=MagicMock())
computation._state = 'value'
computation.__value__ = 1
computation._handle_value_message('x2', Mgm2ValueMessage(0))
self.assertEqual(computation._state, 'offer')
self.assertEqual(computation._neighbors_values['x2'], 0)
self.assertEqual(computation._potential_gain, 1)
self.assertEqual(computation._potential_value, 0)
computation2 = Mgm2Computation(x1, [phi],
mode='max',
msg_sender=DummySender(),
comp_def=MagicMock())
computation2._state = 'value'
computation2.__value__ = 1
computation2._handle_value_message('x2', Mgm2ValueMessage(0))
self.assertEqual(computation2._state, 'offer')
self.assertEqual(computation2._neighbors_values['x2'], 0)
self.assertEqual(computation2._potential_gain, 0)
self.assertEqual(computation2._potential_value, 1)
def test_current_local_cost_3_ary(self):
x1 = Variable("x1", list(range(2)))
x2 = Variable("x2", list(range(2)))
x3 = Variable("x3", [1])
@AsNAryFunctionRelation(x1, x2, x3)
def phi(x1_, x2_, x3_):
return x1_ + x2_ + x3_
computation = Mgm2Computation(
ComputationDef(
VariableComputationNode(x1, [phi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation.__value__ = 1
computation._neighbors_values["x2"] = 0
computation._neighbors_values["x3"] = 1
computation2 = Mgm2Computation(
ComputationDef(
VariableComputationNode(x1, [phi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation2.__value__ = 0
computation2._neighbors_values["x2"] = 0
computation2._neighbors_values["x3"] = 1
self.assertEqual(computation._current_local_cost(), 2)
self.assertEqual(computation2._current_local_cost(), 1)
def test_offer_already_has_partner(self):
x1 = Variable("x1", list(range(2)))
x2 = Variable('x2', list(range(2)))
x3 = Variable('x3', list(range(2)))
@AsNAryFunctionRelation(x1, x2, x3)
def phi(x1_, x2_, x3_):
return x1_ + x2_ + x3_
# Receives a fake offer
computation = Mgm2Computation(x1, [phi], comp_def=MagicMock())
computation._state = 'offer'
computation._is_offerer = True
computation._handle_offer_msg('x2', Mgm2OfferMessage())
self.assertEqual(computation._state, 'offer')
self.assertEqual(computation._offers, [])
# Received only fake offers
computation2 = Mgm2Computation(x1, [phi],
msg_sender=DummySender(),
comp_def=MagicMock())
computation2._state = 'offer'
computation2.__nb_received_offers__ = 1
computation2._handle_offer_msg('x2', Mgm2OfferMessage())
self.assertEqual(computation2._state, 'gain')
self.assertEqual(computation2._offers, [])
# receives a real offer
computation3 = Mgm2Computation(x1, [phi],
msg_sender=DummySender(),
comp_def=MagicMock())
computation3._state = 'offer'
computation3._is_offerer = True
computation3.__cost__ = 15
computation3._handle_offer_msg(
'x2', Mgm2OfferMessage({(1, 1): 8}, is_offering=True))
self.assertEqual(computation3._state, 'offer')
self.assertEqual(computation3._offers, [])
self.assertEqual(computation3._potential_gain, 0)
self.assertIsNone(computation3._potential_value)
# Receives a real offer which is the last expected one
computation4 = Mgm2Computation(x1, [phi],
msg_sender=DummySender(),
comp_def=MagicMock())
computation4._state = 'offer'
computation4._is_offerer = True
computation4.__nb_received_offers__ = 1
computation4._handle_offer_msg(
'x2', Mgm2OfferMessage({(1, 1): 8}, is_offering=True))
self.assertEqual(computation4._offers, [])
self.assertEqual(computation4._state, 'answer?')
self.assertEqual(computation4._potential_gain, 0)
self.assertIsNone(computation4._potential_value)
def test_enter_offer_state(self):
x1 = Variable("x1", list(range(2)))
x2 = Variable("x2", list(range(2)))
x3 = Variable("x3", list(range(2)))
@AsNAryFunctionRelation(x1, x2, x3)
def phi(x1_, x2_, x3_):
return x1_ + x2_ + x3_
computation = Mgm2Computation(
ComputationDef(
VariableComputationNode(x1, [phi]),
AlgorithmDef.build_with_default_param("mgm2", mode="max"),
))
computation.message_sender = DummySender()
computation._postponed_msg["offer"] = [
("x2", Mgm2OfferMessage({(1, 1): 5}, is_offering=True), 1)
]
computation._enter_state("offer")
self.assertEqual(computation._state, "offer")
self.assertEqual(computation._postponed_msg["offer"], [])
self.assertEqual(computation._offers,
[("x2", Mgm2OfferMessage({(1, 1): 5}, True))])
def test_current_local_cost_binary(self):
x1 = Variable("x1", list(range(2)))
x2 = Variable('x2', list(range(2)))
@AsNAryFunctionRelation(x1, x2)
def phi(x1_, x2_):
return x1_ + x2_
computation = Mgm2Computation(x1, [phi], comp_def=MagicMock())
computation.__value__ = 1
computation._neighbors_values['x2'] = 0
computation2 = Mgm2Computation(x1, [phi], comp_def=MagicMock())
computation2.__value__ = 0
computation2._neighbors_values['x2'] = 0
self.assertEqual(computation._current_local_cost(), 1)
self.assertEqual(computation2._current_local_cost(), 0)
def test_current_local_cost_unary(self):
x = Variable("x", list(range(5)))
# x2 = Variable('x2', list(range(5)))
# @AsNAryFunctionRelation(x, x2)
# def phi(x1_):
# return x1_
phi = UnaryFunctionRelation("phi", x, lambda x_: 1
if x_ in [0, 2, 3] else 0)
computation = Mgm2Computation(x, [phi], comp_def=MagicMock())
computation.__value__ = 0
computation2 = Mgm2Computation(x, [phi], comp_def=MagicMock())
computation2.__value__ = 1
self.assertEqual(computation._current_local_cost(), 1)
self.assertEqual(computation2._current_local_cost(), 0)
def test_3_ary_func(self):
x1 = Variable("x1", list(range(2)))
x2 = Variable('x2', list(range(2)))
x3 = Variable('x3', [1])
@AsNAryFunctionRelation(x1, x2, x3)
def phi(x1_, x2_, x3_):
return x1_ + x2_ + x3_
computation = Mgm2Computation(x1, [phi], comp_def=MagicMock())
self.assertEqual(
computation._compute_cost({
'x1': 0,
'x2': 0,
'x3': 1
}), 1)
self.assertEqual(
computation._compute_cost({
'x1': 0,
'x2': 1,
'x3': 1
}), 2)
self.assertEqual(
computation._compute_cost({
'x1': 1,
'x2': 0,
'x3': 1
}), 2)
self.assertEqual(
computation._compute_cost({
'x1': 1,
'x2': 1,
'x3': 1
}), 3)
def test_compute_offers_max_mode(self):
x1 = Variable("x1", list(range(2)))
x2 = Variable("x2", list(range(2)))
x3 = Variable("x3", list(range(2)))
@AsNAryFunctionRelation(x1, x2, x3)
def phi(x1_, x2_, x3_):
if x1_ == x3_:
return 2
elif x1_ == x2_:
return 1
return 0
computation = Mgm2Computation(
ComputationDef(
VariableComputationNode(x1, [phi]),
AlgorithmDef.build_with_default_param("mgm2", mode="max"),
))
computation._neighbors_values = {"x2": 0, "x3": 0}
computation._partner = x2
computation.__value__ = 1
computation.__cost__ = 0
offers = computation._compute_offers_to_send()
self.assertEqual(offers, {(0, 0): -2, (0, 1): -2, (1, 1): -1})
def test_go_reject_no_postponed_value_message(self):
x1 = Variable("x1", list(range(3)))
x2 = Variable('x2', list(range(2)))
x3 = Variable('x3', list(range(2)))
@AsNAryFunctionRelation(x1, x2)
def phi(x1_, x2_):
if x1_ == x2_:
return 1
return 0
@AsNAryFunctionRelation(x1, x3)
def psi(x1_, x3_):
if x1_ == x3_:
return 8
return 0
computation = Mgm2Computation(x1, [phi, psi],
msg_sender=DummySender(),
comp_def=MagicMock())
computation._neighbors_values = {'x2': 1, 'x3': 1}
computation.__value__ = 1
computation._potential_value = 0
computation._state = 'go?'
# from Response message or accepted offer
computation._handle_go_message('x3', Mgm2GoMessage(False))
self.assertEqual(computation._state, 'value')
self.assertEqual(computation.__value__, 1)
self.test_clear_agent()
def test_gain_not_all_received(self):
x1 = Variable("x1", list(range(3)))
x2 = Variable("x2", list(range(2)))
x3 = Variable("x3", list(range(2)))
@AsNAryFunctionRelation(x1, x2)
def phi(x1_, x2_):
if x1_ == x2_:
return 1
return 0
@AsNAryFunctionRelation(x1, x3)
def psi(x1_, x3_):
if x1_ == x3_:
return 8
return 0
computation = Mgm2Computation(
ComputationDef(
VariableComputationNode(x1, [phi, psi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation.message_sender = DummySender()
computation._state = "gain"
computation.on_gain_msg("x2", Mgm2GainMessage(5), 1)
self.assertEqual(computation._neighbors_gains, {"x2": 5})
def test_go_reject_no_postponed_value_message(self):
x1 = Variable("x1", list(range(3)))
x2 = Variable("x2", list(range(2)))
x3 = Variable("x3", list(range(2)))
@AsNAryFunctionRelation(x1, x2)
def phi(x1_, x2_):
if x1_ == x2_:
return 1
return 0
@AsNAryFunctionRelation(x1, x3)
def psi(x1_, x3_):
if x1_ == x3_:
return 8
return 0
computation = Mgm2Computation(
ComputationDef(
VariableComputationNode(x1, [phi, psi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation.message_sender = DummySender()
computation._neighbors_values = {"x2": 1, "x3": 1}
computation.__value__ = 1
computation._potential_value = 0
computation._state = "go?"
# from Response message or accepted offer
computation._handle_go_message("x3", Mgm2GoMessage(False))
self.assertEqual(computation._state, "value")
self.assertEqual(computation.__value__, 1)
self.test_clear_agent()
def test_response_accept(self):
x1 = Variable("x1", list(range(3)))
x2 = Variable('x2', list(range(2)))
x3 = Variable('x3', list(range(2)))
@AsNAryFunctionRelation(x1, x2)
def phi(x1_, x2_):
if x1_ == x2_:
return 1
return 0
@AsNAryFunctionRelation(x1, x3)
def psi(x1_, x3_):
if x1_ == x3_:
return 8
return 0
computation = Mgm2Computation(x1, [phi, psi],
msg_sender=DummySender(),
comp_def=MagicMock())
computation._state = 'answer?'
computation._is_offerer = True
computation._neighbors_values = {'x2': 1, 'x3': 1}
computation.__value__ = 1
computation.__cost__ = 9
computation._potential_gain = 9 # best unilateral move
computation._potential_value = 2 # best unilateral move
computation._partner = x3
computation._handle_response_msg(
'x3', Mgm2ResponseMessage(True, value=0, gain=10))
self.assertEqual(computation._state, 'gain')
self.assertEqual(computation._potential_gain, 10)
self.assertEqual(computation._potential_value, 0)
def test_offer_has_better_unilateral_move(self):
x1 = Variable("x1", list(range(2)))
x2 = Variable('x2', list(range(2)))
x3 = Variable('x3', list(range(2)))
@AsNAryFunctionRelation(x1, x2)
def phi(x1_, x2_):
if x1_ == x2_:
return 1
return 0
@AsNAryFunctionRelation(x1, x3)
def psi(x1_, x3_):
if x1_ == x3_:
return 8
return 0
# Receives a real offer from last neighbor
computation = Mgm2Computation(x1, [phi, psi],
msg_sender=DummySender(),
comp_def=MagicMock())
computation._state = 'offer'
computation._neighbors_values = {'x2': 1, 'x3': 1}
computation.__value__ = 1
computation.__cost__ = 9
computation._potential_gain = 9 # best unilateral move
computation._potential_value = 0 # best unilateral move
computation.__nb_received_offers__ = 1
computation._handle_offer_msg(
'x2', Mgm2OfferMessage({(0, 1): 1}, is_offering=True))
self.assertEqual(computation._offers, [('x2', {(0, 1): 1})])
self.assertEqual(computation._state, 'gain')
self.assertEqual(computation._potential_gain, 9)
self.assertEqual(computation._potential_value, 0)
def test_offer_has_no_partner_yet(self):
x1 = Variable("x1", list(range(2)))
x2 = Variable('x2', list(range(2)))
x3 = Variable('x3', list(range(2)))
@AsNAryFunctionRelation(x1, x2, x3)
def phi(x1_, x2_, x3_):
return x1_ + x2_ + x3_
# Receives a fake offer
computation = Mgm2Computation(x1, [phi], comp_def=MagicMock())
computation._state = 'offer'
computation._handle_offer_msg('x2', Mgm2OfferMessage())
self.assertEqual(computation._state, 'offer')
self.assertEqual(computation._offers, [])
# Received only fake offers
computation2 = Mgm2Computation(x1, [phi],
msg_sender=DummySender(),
comp_def=MagicMock())
computation2._state = 'offer'
computation2.__nb_received_offers__ = 1
computation2._handle_offer_msg('x2', Mgm2OfferMessage())
self.assertEqual(computation2._state, 'gain')
self.assertEqual(computation2._offers, [])
# Receives a real offer (but still expects other OfferMessages)
computation3 = Mgm2Computation(x1, [phi], comp_def=MagicMock())
computation3._state = 'offer'
computation3._handle_offer_msg(
'x2', Mgm2OfferMessage({(1, 1): 8}, is_offering=True))
self.assertEqual(computation3._state, 'offer')
self.assertEqual(computation3._offers, [('x2', {(1, 1): 8})])
# Receives a real offer and is the last expected OfferMessage
computation4 = Mgm2Computation(x1, [phi],
msg_sender=DummySender(),
comp_def=MagicMock())
computation4._state = 'offer'
computation4._neighbors_values = {'x2': 0, 'x3': 1}
computation4.__value__ = 0
computation4.__cost__ = 1
computation4.__nb_received_offers__ = 1
computation4._handle_offer_msg(
'x2', Mgm2OfferMessage({(1, 1): 8}, is_offering=True))
self.assertEqual(computation4._offers, [('x2', {(1, 1): 8})])
self.assertEqual(computation4._state, 'gain')
self.assertEqual(computation4._potential_gain, 9)
self.assertEqual(computation4._potential_value, 1)
def test_best_unary(self):
x = Variable("x", list(range(5)))
phi = UnaryFunctionRelation("phi", x, lambda x_: 1
if x_ in [0, 2, 3] else 0)
computation = Mgm2Computation(x, [phi], comp_def=MagicMock())
computation.__value__ = 0
bests, best = computation._compute_best_value()
self.assertEqual(best, 0)
self.assertEqual(bests, [1, 4])
def test_go_accept_with_postponed_value_message(self):
x1 = Variable("x1", list(range(3)))
x2 = Variable("x2", list(range(2)))
x3 = Variable("x3", list(range(2)))
@AsNAryFunctionRelation(x1, x2)
def phi(x1_, x2_):
if x1_ == x2_:
return 1
return 0
@AsNAryFunctionRelation(x1, x3)
def psi(x1_, x3_):
if x1_ == x3_:
return 8
return 0
computation = Mgm2Computation(
ComputationDef(
VariableComputationNode(x1, [phi, psi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation.message_sender = DummySender()
computation._neighbors_values = {"x2": 1, "x3": 1}
computation.__value__ = 1
computation.__cost__ = 9
computation._state = "go?"
computation._postponed_msg["value"] = [("x2", Mgm2ValueMessage(1), 1)]
# from Response message or accepted offer
computation._potential_gain = 10
computation._potential_value = 0
computation.on_go_msg("x3", Mgm2GoMessage(True), 1)
# Common tests
self.assertEqual(computation._state, "value")
self.assertEqual(computation._potential_gain, 0)
self.assertIsNone(computation._potential_value)
self.assertEqual(computation._neighbors_values, {"x2": 1})
self.assertEqual(computation._neighbors_gains, dict())
self.assertEqual(computation._offers, [])
self.assertIsNone(computation._partner)
self.assertEqual(computation.__nb_received_offers__, 0)
self.assertFalse(computation._committed)
self.assertFalse(computation._is_offerer)
self.assertFalse(computation._can_move)
# If cannot move
self.assertEqual(computation.current_value, 1)
# If can move
computation._can_move = True
computation._state = "go?"
computation._potential_value = 0
computation.on_go_msg("x3", Mgm2GoMessage(True), 1)
self.assertEqual(computation.current_value, 0)
def test_unary_function_relation(self):
x = Variable("x", list(range(5)))
# x2 = Variable('x2', list(range(5)))
# @AsNAryFunctionRelation(x, x2)
# def phi(x1_):
# return x1_
phi = UnaryFunctionRelation("phi", x, lambda x_: 1
if x_ in [0, 2, 3] else 0)
computation = Mgm2Computation(x, [phi], comp_def=MagicMock())
computation.__value__ = 0
self.assertEqual(computation._compute_cost({'x': 0}), 1)
def test_go_accept_with_postponed_value_message(self):
x1 = Variable("x1", list(range(3)))
x2 = Variable('x2', list(range(2)))
x3 = Variable('x3', list(range(2)))
@AsNAryFunctionRelation(x1, x2)
def phi(x1_, x2_):
if x1_ == x2_:
return 1
return 0
@AsNAryFunctionRelation(x1, x3)
def psi(x1_, x3_):
if x1_ == x3_:
return 8
return 0
computation = Mgm2Computation(x1, [phi, psi],
msg_sender=DummySender(),
comp_def=MagicMock())
computation._neighbors_values = {'x2': 1, 'x3': 1}
computation.__value__ = 1
computation.__cost__ = 9
computation._state = 'go?'
computation._postponed_msg['value'] = [('x2', Mgm2ValueMessage(1))]
# from Response message or accepted offer
computation._potential_gain = 10
computation._potential_value = 0
computation._handle_go_message('x3', Mgm2GoMessage(True))
# Common tests
self.assertEqual(computation._state, 'value')
self.assertEqual(computation._potential_gain, 0)
self.assertIsNone(computation._potential_value)
self.assertEqual(computation._neighbors_values, {'x2': 1})
self.assertEqual(computation._neighbors_gains, dict())
self.assertEqual(computation._offers, [])
self.assertIsNone(computation._partner)
self.assertEqual(computation.__nb_received_offers__, 0)
self.assertFalse(computation._committed)
self.assertFalse(computation._is_offerer)
self.assertFalse(computation._can_move)
#If cannot move
self.assertEqual(computation.current_value, 1)
#If can move
computation._can_move = True
computation._state = 'go?'
computation._potential_value = 0
computation._handle_go_message('x3', Mgm2GoMessage(True))
self.assertEqual(computation.current_value, 0)
def test_clear_agent(self):
x1 = Variable("x1", list(range(3)))
x2 = Variable("x2", list(range(2)))
x3 = Variable("x3", list(range(2)))
@AsNAryFunctionRelation(x1, x2)
def phi(x1_, x2_):
if x1_ == x2_:
return 1
return 0
@AsNAryFunctionRelation(x1, x3)
def psi(x1_, x3_):
if x1_ == x3_:
return 8
return 0
computation = Mgm2Computation(
ComputationDef(
VariableComputationNode(x1, [phi, psi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation.message_sender = DummySender()
computation._neighbors_values = {"x2": 1, "x3": 1}
computation.__value__ = 1
computation.__nb_received_offers__ = 2
computation._partner = x3
computation._state = "go?"
computation._potential_gain = 10
computation._potential_value = 10
computation._neighbors_values = {"x2": 1, "x3": 0}
computation._neighbors_gains = {"x2": 5, "x3": 1}
computation._offers = [(1, 1, "x2")]
computation._committed = True
computation._is_offerer = True
computation._can_move = True
computation._clear_agent()
self.assertEqual(computation._potential_gain, 0)
self.assertEqual(computation._neighbors_values, dict())
self.assertEqual(computation._neighbors_gains, dict())
self.assertEqual(computation._offers, [])
self.assertIsNone(computation._partner)
self.assertEqual(computation.__nb_received_offers__, 0)
self.assertFalse(computation._committed)
self.assertFalse(computation._is_offerer)
self.assertFalse(computation._can_move)
self.assertIsNone(computation._potential_value)
self.assertIsNotNone(computation.current_value)
def test_binary_func_min(self):
x1 = Variable("x1", list(range(2)))
x2 = Variable('x2', list(range(2)))
@AsNAryFunctionRelation(x1, x2)
def phi(x1_, x2_):
return x1_ + x2_
computation = Mgm2Computation(x1, [phi], comp_def=MagicMock())
computation._neighbors_values['x2'] = 1
bests, best = computation._compute_best_value()
self.assertEqual(bests, [0])
self.assertEqual(best, 1)
def test_value_all_neighbors_received(self):
x1 = Variable("x1", list(range(2)))
x2 = Variable("x2", list(range(2)))
@AsNAryFunctionRelation(x1, x2)
def phi(x1_, x2_):
return x1_ + x2_
computation = Mgm2Computation(
ComputationDef(
VariableComputationNode(x1, [phi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation.message_sender = DummySender()
computation._state = "value"
computation.__value__ = 1
computation.on_value_msg("x2", Mgm2ValueMessage(0), 1)
self.assertEqual(computation._state, "offer")
self.assertEqual(computation._neighbors_values["x2"], 0)
self.assertEqual(computation._potential_gain, 1)
self.assertEqual(computation._potential_value, 0)
computation2 = Mgm2Computation(
ComputationDef(
VariableComputationNode(x1, [phi]),
AlgorithmDef.build_with_default_param("mgm2", mode="max"),
))
computation2.message_sender = DummySender()
computation2._state = "value"
computation2.__value__ = 1
computation2.on_value_msg("x2", Mgm2ValueMessage(0), 1)
self.assertEqual(computation2._state, "offer")
self.assertEqual(computation2._neighbors_values["x2"], 0)
self.assertEqual(computation2._potential_gain, 0)
self.assertEqual(computation2._potential_value, 1)
def test_current_local_cost_unary(self):
x = Variable("x", list(range(5)))
# x2 = Variable('x2', list(range(5)))
# @AsNAryFunctionRelation(x, x2)
# def phi(x1_):
# return x1_
phi = UnaryFunctionRelation("phi", x, lambda x_: 1
if x_ in [0, 2, 3] else 0)
computation = Mgm2Computation(
ComputationDef(
VariableComputationNode(x, [phi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation.__value__ = 0
computation2 = Mgm2Computation(
ComputationDef(
VariableComputationNode(x, [phi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation2.__value__ = 1
self.assertEqual(computation._current_local_cost(), 1)
self.assertEqual(computation2._current_local_cost(), 0)
def test_best_unary(self):
x = Variable("x", list(range(5)))
phi = UnaryFunctionRelation("phi", x, lambda x_: 1
if x_ in [0, 2, 3] else 0)
computation = Mgm2Computation(
ComputationDef(
VariableComputationNode(x, [phi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation.__value__ = 0
bests, best = computation._compute_best_value()
self.assertEqual(best, 0)
self.assertEqual(bests, [1, 4])
def test_find_best_offer_max_mode_one_offerer(self):
x1 = Variable("x1", list(range(2)))
x2 = Variable("x2", list(range(2)))
x3 = Variable("x3", list(range(2)))
x4 = Variable("x4", list(range(2)))
@AsNAryFunctionRelation(x1, x2, x3)
def phi(x1_, x2_, x3_):
if x1_ == x3_:
return 2
elif x1_ == x2_:
return 1
return 0
@AsNAryFunctionRelation(x1, x4)
def psi(x1_, x4_):
if x1_ == x4_:
return 1
return 0
computation = Mgm2Computation(
ComputationDef(
VariableComputationNode(x1, [phi, psi]),
AlgorithmDef.build_with_default_param("mgm2", mode="max"),
))
computation._neighbors_values = {"x2": 0, "x3": 1, "x4": 1}
computation.__value__ = 0
computation.__cost__ = 1
bests, best_gain = computation._find_best_offer([("x2", {
(0, 0): -1,
(0, 1): -5,
(1, 0): -3
})])
# global gain: -1 -5 -5
bests2, best_gain2 = computation._find_best_offer([("x2", {
(0, 0): -1,
(0, 1): -5,
(1, 0): -6
})])
# global gain: -1 -5 -5
self.assertEqual(bests, [(0, 1, "x2")])
self.assertEqual(best_gain, -5)
self.assertEqual(set(bests2), {(0, 1, "x2"), (1, 0, "x2")})
self.assertEqual(best_gain2, -5)
def test_enter_answer_state(self):
x1 = Variable("x1", list(range(2)))
x2 = Variable('x2', list(range(2)))
x3 = Variable('x3', list(range(2)))
@AsNAryFunctionRelation(x1, x2, x3)
def phi(x1_, x2_, x3_):
return x1_ + x2_ + x3_
computation = Mgm2Computation(x1, [phi],
mode='max',
comp_def=MagicMock())
computation._enter_state('answer?')
self.assertEqual(computation._state, 'answer?')
def test_clear_agent(self):
x1 = Variable("x1", list(range(3)))
x2 = Variable('x2', list(range(2)))
x3 = Variable('x3', list(range(2)))
@AsNAryFunctionRelation(x1, x2)
def phi(x1_, x2_):
if x1_ == x2_:
return 1
return 0
@AsNAryFunctionRelation(x1, x3)
def psi(x1_, x3_):
if x1_ == x3_:
return 8
return 0
computation = Mgm2Computation(x1, [phi, psi],
msg_sender=DummySender(),
comp_def=MagicMock())
computation._neighbors_values = {'x2': 1, 'x3': 1}
computation.__value__ = 1
computation.__nb_received_offers__ = 2
computation._partner = x3
computation._state = 'go?'
computation._potential_gain = 10
computation._potential_value = 10
computation._neighbors_values = {'x2': 1, 'x3': 0}
computation._neighbors_gains = {'x2': 5, 'x3': 1}
computation._offers = [(1, 1, 'x2')]
computation._committed = True
computation._is_offerer = True
computation._can_move = True
computation._clear_agent()
self.assertEqual(computation._potential_gain, 0)
self.assertEqual(computation._neighbors_values, dict())
self.assertEqual(computation._neighbors_gains, dict())
self.assertEqual(computation._offers, [])
self.assertIsNone(computation._partner)
self.assertEqual(computation.__nb_received_offers__, 0)
self.assertFalse(computation._committed)
self.assertFalse(computation._is_offerer)
self.assertFalse(computation._can_move)
self.assertIsNone(computation._potential_value)
self.assertIsNotNone(computation.current_value)
def test_value_not_all_neighbors_received(self):
x1 = Variable("x1", list(range(2)))
x2 = Variable('x2', list(range(2)))
x3 = Variable('x3', list(range(2)))
@AsNAryFunctionRelation(x1, x2, x3)
def phi(x1_, x2_, x3_):
return x1_ + x2_ + x3_
computation = Mgm2Computation(x1, [phi],
mode='max',
comp_def=MagicMock())
computation._state = 'value'
computation._handle_value_message('x2', Mgm2ValueMessage(0))
self.assertEqual(computation._state, 'value')
self.assertEqual(computation._neighbors_values['x2'], 0)
def test_binary_func(self):
x1 = Variable("x1", list(range(2)))
x2 = Variable("x2", list(range(2)))
@AsNAryFunctionRelation(x1, x2)
def phi(x1_, x2_):
return x1_ + x2_
computation = Mgm2Computation(
ComputationDef(
VariableComputationNode(x1, [phi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
self.assertEqual(computation._compute_cost(**{"x1": 0, "x2": 0}), 0)
self.assertEqual(computation._compute_cost(**{"x1": 0, "x2": 1}), 1)
self.assertEqual(computation._compute_cost(**{"x1": 1, "x2": 0}), 1)
self.assertEqual(computation._compute_cost(**{"x1": 1, "x2": 1}), 2)
def test_no_neighbors():
x1 = Variable("x1", list(range(10)))
cost_x1 = constraint_from_str('cost_x1', 'x1 *2 ', [x1])
computation = Mgm2Computation(x1, [cost_x1],
mode='max',
comp_def=MagicMock())
computation.value_selection = MagicMock()
computation.finished = MagicMock()
vals, cost = computation._compute_best_value()
assert cost == 18
assert set(vals) == {9}
computation.on_start()
computation.value_selection.assert_called_once_with(9, 18)
computation.finished.assert_called_once_with()
def test_find_best_offer_min_mode_2_offerers(self):
x1 = Variable("x1", list(range(2)))
x2 = Variable("x2", list(range(2)))
x3 = Variable("x3", list(range(2)))
x4 = Variable("x4", list(range(2)))
@AsNAryFunctionRelation(x1, x2, x3)
def phi(x1_, x2_, x3_):
if x1_ == x3_:
return 2
elif x1_ == x2_:
return 1
return 0
@AsNAryFunctionRelation(x1, x4)
def psi(x1_, x4_):
if x1_ == x4_:
return 1
return 0
computation = Mgm2Computation(
ComputationDef(
VariableComputationNode(x1, [phi, psi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation._neighbors_values = {"x2": 0, "x3": 0, "x4": 0}
computation.__value__ = 0
computation.__cost__ = 3
bests, best_gain = computation._find_best_offer([
("x2", {
(0, 0): 1,
(0, 1): 5,
(1, 0): 3
}),
("x4", {
(1, 0): 7,
(0, 1): 2,
(1, 1): 3
}),
])
self.assertEqual(set(bests), {(0, 1, "x2"), (1, 0, "x4")})
self.assertEqual(best_gain, 8)