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_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_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_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_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_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_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_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_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_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_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_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_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_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(x1, [phi],
mode='max',
msg_sender=DummySender(),
comp_def=MagicMock())
computation._enter_state('go?')
self.assertEqual(computation._state, 'go?')
def test_enter_go_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._enter_state("go?")
self.assertEqual(computation._state, "go?")
def test_go_accept_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.__cost__ = 9
computation._state = "go?"
# from Response message or accepted offer
computation._potential_gain = 10
computation._potential_value = 0
# Common behavior: clear agent view
computation.on_go_msg("x3", Mgm2GoMessage(True), 1)
self.assertEqual(computation._state, "value")
self.test_clear_agent()
# If cannot move
self.assertEqual(computation.current_value, 1)
# If can move
computation._state = "go?"
computation._can_move = True
computation._potential_value = 0
computation.on_go_msg("x3", Mgm2GoMessage(True), 1)
self.assertEqual(computation.current_value, 0)
def test_enter_gain_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',
msg_sender=DummySender(),
comp_def=MagicMock())
computation._postponed_msg['gain'] = [('x2', Mgm2GainMessage(3))]
computation._enter_state('gain')
self.assertEqual(computation._state, 'gain')
self.assertEqual(computation._postponed_msg['gain'], [])
self.assertEqual(computation._neighbors_gains['x2'], 3)
def test_go_accept_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.__cost__ = 9
computation._state = 'go?'
# from Response message or accepted offer
computation._potential_gain = 10
computation._potential_value = 0
# Common behavior: clear agent view
computation._handle_go_message('x3', Mgm2GoMessage(True))
self.assertEqual(computation._state, 'value')
self.test_clear_agent()
# If cannot move
self.assertEqual(computation.current_value, 1)
# If can move
computation._state = 'go?'
computation._can_move = True
computation._potential_value = 0
computation._handle_go_message('x3', Mgm2GoMessage(True))
self.assertEqual(computation.current_value, 0)
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(x1, [phi],
mode='max',
msg_sender=DummySender(),
comp_def=MagicMock())
computation._postponed_msg['offer'] = \
[('x2', Mgm2OfferMessage({(1, 1): 5}, is_offering=True))]
computation._enter_state('offer')
self.assertEqual(computation._state, 'offer')
self.assertEqual(computation._postponed_msg['offer'], [])
self.assertEqual(computation._offers, [('x2', {(1, 1): 5})])
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(
ComputationDef(
VariableComputationNode(x1, [phi, psi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation.message_sender = DummySender()
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.on_answer_msg("x3",
Mgm2ResponseMessage(True, value=0, gain=10),
1)
self.assertEqual(computation._state, "gain")
self.assertEqual(computation._potential_gain, 10)
self.assertEqual(computation._potential_value, 0)
def test_enter_gain_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["gain"] = [("x2", Mgm2GainMessage(3), 1)]
computation._enter_state("gain")
self.assertEqual(computation._state, "gain")
self.assertEqual(computation._postponed_msg["gain"], [])
self.assertEqual(computation._neighbors_gains["x2"], 3)
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(x1, [phi, psi],
msg_sender=DummySender(),
comp_def=MagicMock())
computation._state = 'gain'
computation._handle_gain_message('x2', Mgm2GainMessage(5))
self.assertEqual(computation._neighbors_gains, {'x2': 5})
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(
ComputationDef(
VariableComputationNode(x1, [phi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation.message_sender = DummySender()
computation._state = "offer"
computation._is_offerer = True
computation.on_offer_msg("x2", Mgm2OfferMessage(), 1)
self.assertEqual(computation._state, "offer")
# self.assertEqual(computation._offers, [])
# Received only fake offers
computation2 = Mgm2Computation(
ComputationDef(
VariableComputationNode(x1, [phi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation2.message_sender = DummySender()
computation2._state = "offer"
computation2.__nb_received_offers__ = 1
computation2.on_offer_msg("x2", Mgm2OfferMessage(), 1)
self.assertEqual(computation2._state, "gain")
self.assertEqual(computation2._offers, [("x2", Mgm2OfferMessage())])
# receives a real offer
computation3 = Mgm2Computation(
ComputationDef(
VariableComputationNode(x1, [phi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation3.message_sender = DummySender()
computation3._state = "offer"
computation3._is_offerer = True
computation3.__cost__ = 15
computation3.on_offer_msg(
"x2", Mgm2OfferMessage({(1, 1): 8}, is_offering=True), 1)
self.assertEqual(computation3._state, "offer")
self.assertEqual(2, len(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(
ComputationDef(
VariableComputationNode(x1, [phi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation4.message_sender = DummySender()
computation4._state = "offer"
computation4._is_offerer = True
computation4.__nb_received_offers__ = 1
computation4.on_offer_msg(
"x2", Mgm2OfferMessage({(1, 1): 8}, is_offering=True), 1)
self.assertEqual(len(computation4), 3)
self.assertEqual(computation4._state, "answer?")
self.assertEqual(computation4._potential_gain, 0)
self.assertIsNone(computation4._potential_value)
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(
ComputationDef(
VariableComputationNode(x1, [phi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation.message_sender = DummySender()
computation._state = "offer"
computation.on_offer_msg("x2", Mgm2OfferMessage(), 1)
self.assertEqual(computation._state, "offer")
self.assertEqual(computation._offers, [])
# Received only fake offers
computation2 = Mgm2Computation(
ComputationDef(
VariableComputationNode(x1, [phi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation2.message_sender = DummySender()
computation2._state = "offer"
computation2.__nb_received_offers__ = 1
computation2.on_offer_msg("x2", Mgm2OfferMessage(), 1)
self.assertEqual(computation2._state, "gain")
self.assertEqual(computation2._offers, [])
# Receives a real offer (but still expects other OfferMessages)
computation3 = Mgm2Computation(
ComputationDef(
VariableComputationNode(x1, [phi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation3.message_sender = DummySender()
computation3._state = "offer"
computation3.on_offer_msg(
"x2", Mgm2OfferMessage({(1, 1): 8}, is_offering=True), 1)
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(
ComputationDef(
VariableComputationNode(x1, [phi]),
AlgorithmDef.build_with_default_param("mgm2"),
))
computation4.message_sender = DummySender()
computation4._state = "offer"
computation4._neighbors_values = {"x2": 0, "x3": 1}
computation4.__value__ = 0
computation4.__cost__ = 1
computation4.__nb_received_offers__ = 1
computation4.on_offer_msg(
"x2", Mgm2OfferMessage({(1, 1): 8}, is_offering=True), 1)
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_gain_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(x1, [phi, psi],
msg_sender=DummySender(),
comp_def=MagicMock())
computation._neighbors_values = {'x2': 1, 'x3': 0}
# If potential gain is 0
computation.__value__ = 1
computation.__cost__ = 1
computation._potential_value = 0
computation._potential_gain = 0
computation._state = 'go?'
computation._neighbors_gains['x3'] = 2
computation._handle_gain_message('x2', Mgm2GainMessage(5))
self.assertEqual(computation.current_value, 1)
self.assertEqual(computation._state, 'value')
self.assertEqual(computation.current_cost, 1)
# If commited and has best gain
computation._state = 'go?'
computation.__value__ = 1
computation.__cost__ = 1
computation._committed = True
computation._partner = x3
computation._potential_gain = 10
computation._neighbors_gains['x3'] = 10
computation._potential_value = 0
computation._handle_gain_message('x2', Mgm2GainMessage(5))
self.assertEqual(computation.current_value, 1)
self.assertEqual(computation.current_cost, 1)
self.assertTrue(computation._can_move)
self.assertEqual(computation._state, 'go?')
# If commited and has not best gain
computation._state = 'go?'
computation.__value__ = 1
computation.__cost__ = 1
computation._committed = True
computation._partner = x3
computation._potential_gain = 1
computation._neighbors_gains['x3'] = 1
computation._potential_value = 0
computation._handle_gain_message('x2', Mgm2GainMessage(5))
self.assertEqual(computation.current_value, 1)
self.assertEqual(computation.current_cost, 1)
self.assertFalse(computation._can_move)
self.assertEqual(computation._state, 'go?')
self.test_clear_agent()
# If not committed and has best gain not alone: no test as it could (in
# the future) be randomly chosen
#If not committed and not best gain
computation._state = 'go?'
computation.__value__ = 1
computation.__cost__ = 1
computation._committed = False
computation._partner = None
computation._potential_gain = 2
computation._neighbors_gains['x3'] = 2
computation._potential_value = 0
computation._handle_gain_message('x2', Mgm2GainMessage(5))
self.assertEqual(computation.current_value, 1)
self.assertEqual(computation.current_cost, 1)
self.assertEqual(computation._state, 'value')
self.test_clear_agent()
def test_gain_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._neighbors_values = {"x2": 1, "x3": 0}
# If potential gain is 0
computation.__value__ = 1
computation.__cost__ = 1
computation._potential_value = 0
computation._potential_gain = 0
computation._state = "gain"
computation._neighbors_gains["x3"] = 2
computation.on_gain_msg("x2", Mgm2GainMessage(5), 1)
self.assertEqual(computation.current_value, 1)
self.assertEqual(computation._state, "value")
self.assertEqual(computation.current_cost, 1)
# If commited and has best gain
computation._state = "gain"
computation.__value__ = 1
computation.__cost__ = 1
computation._committed = True
computation._partner = x3
computation._potential_gain = 10
computation._neighbors_gains["x3"] = 10
computation._potential_value = 0
computation.on_gain_msg("x2", Mgm2GainMessage(5), 1)
self.assertEqual(computation.current_value, 1)
self.assertEqual(computation.current_cost, 1)
self.assertTrue(computation._can_move)
self.assertEqual(computation._state, "go?")
# If commited and has not best gain
computation._state = "gain"
computation.__value__ = 1
computation.__cost__ = 1
computation._committed = True
computation._partner = x3
computation._potential_gain = 1
computation._neighbors_gains["x3"] = 1
computation._potential_value = 0
computation.on_gain_msg("x2", Mgm2GainMessage(5), 1)
self.assertEqual(computation.current_value, 1)
self.assertEqual(computation.current_cost, 1)
self.assertFalse(computation._can_move)
self.assertEqual(computation._state, "go?")
self.test_clear_agent()
# If not committed and has best gain not alone: no test as it could (in
# the future) be randomly chosen
# If not committed and not best gain
computation._state = "gain"
computation.__value__ = 1
computation.__cost__ = 1
computation._committed = False
computation._partner = None
computation._potential_gain = 2
computation._neighbors_gains["x3"] = 2
computation._potential_value = 0
computation.on_gain_msg("x2", Mgm2GainMessage(5), 1)
self.assertEqual(computation.current_value, 1)
self.assertEqual(computation.current_cost, 1)
self.assertEqual(computation._state, "value")
self.test_clear_agent()