dimod.QuadraticModel.reduce_neighborhood¶
- QuadraticModel.reduce_neighborhood(v: Hashable, function: collections.abc.Callable, initializer: Optional[Union[float, numpy.floating, numpy.integer]] = None) Any [source]¶
Apply function of two arguments cumulatively to the quadratic biases associated with a single variable.
- Parameters
v – Variable in the quadratic model.
function – Function of two arguments to apply to the quadratic biases of variable
v
.initializer – Prefixed in the calculation to the iterable containing the quadratic biases or used as the default if variable
v
has no quadratic biases.
- Returns
Result of applying the specified function to the specified variable’s quadratic biases.
Examples
>>> from dimod import QuadraticModel >>> qm = QuadraticModel({'x': 0.5, 's': 1, 'i': 2}, ... {('x', 'i'): 2, ('s', 'i'): 3}, 0.0, ... {'x': 'BINARY', 's': 'SPIN', 'i': 'INTEGER'}) >>> qm.reduce_neighborhood('i', max) 3.0
For information on the related functional programming method see
functools.reduce()
.