dimod.binary.BinaryQuadraticModel.energies#

BinaryQuadraticModel.energies(samples_like, dtype: dtype[Any] | None | type[Any] | _SupportsDType[dtype[Any]] | str | tuple[Any, int] | tuple[Any, SupportsIndex | Sequence[SupportsIndex]] | list[Any] | _DTypeDict | tuple[Any, Any] = None) → ndarray[source]#

Determine the energies of the given samples-like.

Parameters:

  • samples_like (samples_like) – Raw samples. samples_like is an extension of NumPy’s array_like structure. See as_samples().

  • dtype – Desired NumPy data type for the energy. Defaults to float64.

Returns:

Energies for the samples.

Examples

>>> bqm = dimod.BinaryQuadraticModel({}, {("x0", "x1"): -1}, "BINARY")
>>> bqm.energies([{"x0": 1, "x1": 1},{"x0": 0, "x1": 1}])
array([-1.,  0.])

See also the example under energy().