dimod.reference.samplers.RandomSampler.sample_ising

RandomSampler.sample_ising(h: Union[Mapping[Hashable, Union[float, numpy.floating, numpy.integer]], Sequence[Union[float, numpy.floating, numpy.integer]]], J: Mapping[Tuple[Hashable, Hashable], Union[float, numpy.floating, numpy.integer]], **parameters) dimod.sampleset.SampleSet[source]

Sample from an Ising model using the implemented sample method.

This method is inherited from the Sampler base class.

Converts the Ising model into a BinaryQuadraticModel and then calls sample().

Parameters
  • h – Linear biases of the Ising problem. If a list, indices are the variable labels.

  • J – Quadratic biases of the Ising problem.

  • **kwargs – See the implemented sampling for additional keyword definitions.

Returns: Samples from the Ising model.