dimod.reference.composites.scalecomposite.ScaleComposite.sample¶
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ScaleComposite.sample(bqm, scalar=None, bias_range=1, quadratic_range=None, ignored_variables=None, ignored_interactions=None, ignore_offset=False, **parameters)[source]¶ Scale and sample from the provided binary quadratic model.
if scalar is not given, problem is scaled based on bias and quadratic ranges. See
BinaryQuadraticModel.scale()andBinaryQuadraticModel.normalize()Parameters: - bqm (
dimod.BinaryQuadraticModel) – Binary quadratic model to be sampled from. - scalar (number) – Value by which to scale the energy range of the binary quadratic model.
- bias_range (number/pair) – Value/range by which to normalize the all the biases, or if quadratic_range is provided, just the linear biases.
- quadratic_range (number/pair) – Value/range by which to normalize the quadratic biases.
- ignored_variables (iterable, optional) – Biases associated with these variables are not scaled.
- ignored_interactions (iterable[tuple], optional) – As an iterable of 2-tuples. Biases associated with these interactions are not scaled.
- ignore_offset (bool, default=False) – If True, the offset is not scaled.
- **parameters – Parameters for the sampling method, specified by the child sampler.
Returns: - bqm (