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)