dimod.SampleSet.from_samples_bqm

classmethod SampleSet.from_samples_bqm(samples_like, bqm, **kwargs)[source]

Build a sample set from raw samples and a binary quadratic model.

The binary quadratic model is used to calculate energies and set the vartype.

Parameters:
  • samples_like – A collection of raw samples. ‘samples_like’ is an extension of NumPy’s array_like. See as_samples().
  • bqm (BinaryQuadraticModel) – A binary quadratic model.
  • info (dict, optional) – Information about the SampleSet as a whole formatted as a dict.
  • num_occurrences (array_like, optional) – Number of occurrences for each sample. If not provided, defaults to a vector of 1s.
  • aggregate_samples (bool, optional, default=False) – If True, all samples in returned SampleSet are unique, with num_occurrences accounting for any duplicate samples in samples_like.
  • sort_labels (bool, optional, default=True) – Return SampleSet.variables in sorted order. For mixed (unsortable) types, the given order is maintained.
  • **vectors (array_like) – Other per-sample data.
Returns:

SampleSet

Examples

>>> bqm = dimod.BinaryQuadraticModel.from_ising({}, {('a', 'b'): -1})
>>> sampleset = dimod.SampleSet.from_samples_bqm({'a': -1, 'b': 1}, bqm)