dimod.binary.BinaryQuadraticModel.normalize#

BinaryQuadraticModel.normalize(bias_range: float | Tuple[float, float] = 1, quadratic_range: float | Tuple[float, float] | None = None, ignored_variables: Iterable[Hashable] | None = None, ignored_interactions: Iterable[Tuple[Hashable, Hashable]] | None = 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.

Parameters:

  • 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.