Ejemplo n.º 1
0
def _bqm_from_2sat(constraint):
    """create a bqm for a constraint with two variables.

    bqm will have exactly classical gap 2.
    """
    configurations = constraint.configurations
    variables = constraint.variables
    vartype = constraint.vartype
    u, v = constraint.variables

    # if all configurations are present, then nothing is infeasible and the bqm is just all
    # 0.0s
    if len(configurations) == 4:
        return dimod.BinaryQuadraticModel.empty(constraint.vartype)

    # check if the constraint is irreducible, and if so, build the bqm for its two
    # components
    components = irreducible_components(constraint)
    if len(components) > 1:
        const0 = Constraint.from_configurations(
            ((config[0], ) for config in configurations), (u, ), vartype)
        const1 = Constraint.from_configurations(
            ((config[1], ) for config in configurations), (v, ), vartype)
        bqm = _bqm_from_1sat(const0)
        bqm.update(_bqm_from_1sat(const1))
        return bqm

    assert len(
        configurations) > 1, "single configurations should be irreducible"

    # if it is not irreducible, and there are infeasible configurations, then it is time to
    # start building a bqm
    bqm = dimod.BinaryQuadraticModel.empty(vartype)

    # if the constraint is not irreducible and has two configurations, then it is either eq or ne
    if all(operator.eq(*config) for config in configurations):
        bqm.add_interaction(u, v, -1, vartype=dimod.SPIN)  # equality
    elif all(operator.ne(*config) for config in configurations):
        bqm.add_interaction(u, v, +1, vartype=dimod.SPIN)  # inequality
    elif (1, 1) not in configurations:
        bqm.add_interaction(u, v, 2, vartype=dimod.BINARY)  # penalize (1, 1)
    elif (-1, +1) not in configurations and (0, 1) not in configurations:
        bqm.add_interaction(u, v, -2, vartype=dimod.BINARY)
        bqm.add_variable(v, 2, vartype=dimod.BINARY)
    elif (+1, -1) not in configurations and (1, 0) not in configurations:
        bqm.add_interaction(u, v, -2, vartype=dimod.BINARY)
        bqm.add_variable(u, 2, vartype=dimod.BINARY)
    else:
        # (0, 0) not in configurations
        bqm.add_interaction(u, v, 2, vartype=dimod.BINARY)
        bqm.add_variable(u, -2, vartype=dimod.BINARY)
        bqm.add_variable(v, -2, vartype=dimod.BINARY)

    return bqm
Ejemplo n.º 2
0
    def add_constraint(self, constraint, variables=tuple()):
        """Add a constraint.

        Args:
            constraint (function/iterable/:obj:`.Constraint`):
                Constraint definition in one of the supported formats:

                1. Function, with input arguments matching the order and
                   :attr:`~.ConstraintSatisfactionProblem.vartype` type of the `variables`
                   argument, that evaluates True when the constraint is satisfied.
                2. List explicitly specifying each allowed configuration as a tuple.
                3. :obj:`.Constraint` object built either explicitly or by :mod:`dwavebinarycsp.factories`.

            variables(iterable):
                Variables associated with the constraint. Not required when `constraint` is
                a :obj:`.Constraint` object.

        Examples:
            This example defines a function that evaluates True when the constraint is satisfied.
            The function's input arguments match the order and type of the `variables` argument.

            >>> csp = dwavebinarycsp.ConstraintSatisfactionProblem(dwavebinarycsp.BINARY)
            >>> def all_equal(a, b, c):  # works for both dwavebinarycsp.BINARY and dwavebinarycsp.SPIN
            ...     return (a == b) and (b == c)
            >>> csp.add_constraint(all_equal, ['a', 'b', 'c'])
            >>> csp.check({'a': 0, 'b': 0, 'c': 0})
            True
            >>> csp.check({'a': 0, 'b': 0, 'c': 1})
            False

            This example explicitly lists allowed configurations.

            >>> csp = dwavebinarycsp.ConstraintSatisfactionProblem(dwavebinarycsp.SPIN)
            >>> eq_configurations = {(-1, -1), (1, 1)}
            >>> csp.add_constraint(eq_configurations, ['v0', 'v1'])
            >>> csp.check({'v0': -1, 'v1': +1})
            False
            >>> csp.check({'v0': -1, 'v1': -1})
            True

            This example uses a :obj:`.Constraint` object built by :mod:`dwavebinarycsp.factories`.

            >>> import dwavebinarycsp.factories.constraint.gates as gates
            >>> csp = dwavebinarycsp.ConstraintSatisfactionProblem(dwavebinarycsp.BINARY)
            >>> csp.add_constraint(gates.and_gate(['a', 'b', 'c']))  # add an AND gate
            >>> csp.add_constraint(gates.xor_gate(['a', 'c', 'd']))  # add an XOR gate
            >>> csp.check({'a': 1, 'b': 0, 'c': 0, 'd': 1})
            True

        """
        if isinstance(constraint, Constraint):
            if variables and (tuple(variables) != constraint.variables):
                raise ValueError("mismatched variables and Constraint")
        elif isinstance(constraint, Callable):
            constraint = Constraint.from_func(constraint, variables,
                                              self.vartype)
        elif isinstance(constraint, Iterable):
            constraint = Constraint.from_configurations(
                constraint, variables, self.vartype)
        else:
            raise TypeError("Unknown constraint type given")

        self.constraints.append(constraint)
        for v in constraint.variables:
            self.variables[v].append(constraint)