dimod.ConstrainedQuadraticModel.violations

ConstrainedQuadraticModel.violations(sample_like: Union[Sequence[float], Mapping[Hashable, Union[float, numpy.floating, numpy.integer]], Sequence[Sequence[Sequence[Sequence[Sequence[Any]]]]], numpy.typing._array_like._SupportsArray[numpy.dtype], Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]], Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]], Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]]], Sequence[Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]]]], bool, int, float, complex, str, bytes, Sequence[Union[bool, int, float, complex, str, bytes]], Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]], Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]], Sequence[Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]]], Sequence[Sequence[float]], Tuple[Sequence[float], List[Hashable]], Tuple[Sequence[Sequence[float]], List[Hashable]], Sequence[Union[Sequence[float], Mapping[Hashable, Union[float, numpy.floating, numpy.integer]], Sequence[Sequence[Sequence[Sequence[Sequence[Any]]]]], numpy.typing._array_like._SupportsArray[numpy.dtype], Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]], Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]], Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]]], Sequence[Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]]]], bool, int, float, complex, str, bytes, Sequence[Union[bool, int, float, complex, str, bytes]], Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]], Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]], Sequence[Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]]]]], Iterator[Union[Sequence[float], Mapping[Hashable, Union[float, numpy.floating, numpy.integer]], Sequence[Sequence[Sequence[Sequence[Sequence[Any]]]]], numpy.typing._array_like._SupportsArray[numpy.dtype], Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]], Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]], Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]]], Sequence[Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]]]], bool, int, float, complex, str, bytes, Sequence[Union[bool, int, float, complex, str, bytes]], Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]], Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]], Sequence[Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]]]]]], *, skip_satisfied: bool = False, clip: bool = False) → Dict[Hashable, Union[float, numpy.floating, numpy.integer]][source]

Return a dict of violations for all constraints.

The dictionary maps constraint labels to the amount each constraint is violated. This method is a shortcut for dict(cqm.iter_violations(sample)).

Parameters

  • sample_like – A sample. sample-like is an extension of NumPy’s array_like structure. See as_samples()..

  • skip_satisfied – If True, does not yield constraints that are satisfied.

  • clip – If True, negative violations are rounded up to 0.

Returns

A dict of 2-tuples containing the constraint label and the amount of the constraint’s violation.

Examples

This example meets one constraint exactly, is well within the requirement of a second, and violates a third.

>>> i, j, k = dimod.Binaries(['i', 'j', 'k'])
>>> cqm = dimod.ConstrainedQuadraticModel()
>>> cqm.add_constraint(i + j + k == 10, label='equal')
'equal'
>>> cqm.add_constraint(i + j <= 15, label='less equal')
'less equal'
>>> cqm.add_constraint(j - k >= 0, label='greater equal')
'greater equal'
>>> sample = {"i": 3, "j": 2, "k": 5}
>>> cqm.violations(sample)
{'equal': 0.0, 'less equal': -10.0, 'greater equal': 3.0}