BinaryQuadraticModel.normalize(bias_range: Union[float, Tuple[float, float]] = 1, quadratic_range: Optional[Union[float, Tuple[float, float]]] = None, ignored_variables: Optional[Iterable[Hashable]] = None, ignored_interactions: Optional[Iterable[Tuple[Hashable, Hashable]]] = None, ignore_offset: bool = False)[source]

Normalize the biases of a binary quadratic model.

Normalizes the biases to fall in the provided range(s), and adjusts the offset appropriately.

  • bias_range – Value/range that the biases of the BQM are scaled to fit within. If quadratic_range is provided, this range is used to fit the linear biases.

  • quadratic_range – Value/range that quadratic biases of the BQM are scaled to fit within.

  • ignored_variables – Biases associated with these variables are not scaled.

  • ignored_interactions – Biases associated with these interactions, formatted as an iterable of 2-tuples, are not scaled.

  • ignore_offset – If True, the offset is not scaled.