def test_init_from_constraints_as_functions(self):
domain = list(range(3))
x1 = Variable('x1', domain)
x2 = Variable('x2', domain)
@AsNAryFunctionRelation(x1, x2)
def phi(x1_, x2_):
return x1_ + x2_
g = GdbaComputation(x1, [phi], comp_def=MagicMock())
m = NAryMatrixRelation.from_func_relation(phi)
(c_mat, mini, maxi) = g.__constraints__[0]
self.assertEqual(c_mat, m)
self.assertEqual(mini, 0)
self.assertEqual(maxi, 4)
def __init__(self,
variable: Variable,
constraints: Iterable[RelationProtocol],
mode='min',
modifier='A',
violation='NZ',
increase_mode='E',
msg_sender=None,
logger=None,
comp_def=None):
"""
:param variable: a variable object for which this computation is
responsible
:param constraints: the list of constraints involving this variable
:param modifier: The manner to modify costs. 'A' (resp. 'M') for
additive (resp. multiplicative) manner. Defaults to 'A'
:param violation: The criteria to determine a constraint violation.
Defaults to 'NZ'
:param increase_mode: The increase mode of a constraint cost
describes which modifiers should be increased.
Defaults to 'E'
"""
super().__init__(variable, comp_def)
self._msg_handlers['gdba_ok'] = self._on_ok_msg
self._msg_handlers['gdba_improve'] = self._on_improve_message
self._msg_sender = msg_sender
self.logger = logger if logger is not None \
else logging.getLogger('pydcop.algo.gdba.' + variable.name)
# Handling messages arriving during wrong mode
self.__postponed_improve_messages__ = []
self.__postponed_ok_messages__ = []
self._waiting_mode = 'starting'
self._mode = mode
self._modifier_mode = modifier
self._violation_mode = violation
self._increase_mode = increase_mode
base_modifier = 0 if self._modifier_mode == 'A' else 1
self.__constraints__ = list()
self.__constraints_modifiers__ = dict()
# Transform the constraints in matrices, with also the min and max
# values recorded
for c in constraints:
if type(c) != NAryMatrixRelation:
rel_mat = NAryMatrixRelation.from_func_relation(c)
c_array = rel_mat._m.flat
maxi = c_array[0]
mini = c_array[0]
for i in c_array:
if i > maxi:
maxi = i
if i < mini:
mini = i
rel = (rel_mat, mini, maxi)
else:
c_array = c._m.flat
maxi = c_array[0]
mini = c_array[0]
for i in c_array:
if i > maxi:
maxi = i
if i < mini:
mini = i
rel = (c, mini, maxi)
self.__constraints__.append(rel)
# The modifiers for constraints. It is a Dictionary of dictionary
# (of dictionary ... regarding the arity of each constraint). It
# represents the value of the modifier for each constraint asgt.
self.__constraints_modifiers__[rel[0]] = defaultdict(
lambda: base_modifier)
self._violated_constraints = []
# some constraints might be unary, and our variable can have several
# constraints involving the same variable
self._neighbors = set(
[v for c in constraints for v in c.dimensions if v != variable])
# Agent view of its neighbors resp. for ok and improve modes
self._neighbors_values = {}
self._neighbors_improvements = {}
self._my_improve = 0 # Possible improvement the agent can realize
self._new_value = None
