dimod.higherorder.utils.poly_energy

poly_energy(sample_like: Sequence[float | floating | integer] | Mapping[Hashable, float | floating | integer] | Tuple[Sequence[float | floating | integer], Sequence[Hashable]] | Tuple[ndarray, Sequence[Hashable]] | ndarray | Sequence[Sequence[float | floating | integer]] | Tuple[Sequence[Sequence[float | floating | integer]], Sequence[Hashable]] | Sequence[Sequence[float | floating | integer] | Mapping[Hashable, float | floating | integer] | Tuple[Sequence[float | floating | integer], Sequence[Hashable]] | Tuple[ndarray, Sequence[Hashable]] | ndarray] | Iterator[Sequence[float | floating | integer] | Mapping[Hashable, float | floating | integer] | Tuple[Sequence[float | floating | integer], Sequence[Hashable]] | Tuple[ndarray, Sequence[Hashable]] | ndarray], poly: Mapping[Sequence[Hashable], float | floating | integer] | BinaryPolynomial) → float

Calculate energy of a sample from a higher order polynomial.

Parameters:

sample_like –

A raw sample. samples-like is an extension of NumPy’s

array_like structure. See as_samples().

poly (dict):

Either a polynomial, as a dict of form {term: bias, …}, where term is a tuple of one or more variables and bias the associated bias, or a BinaryPolynomial. Variable labeling/indexing here must match that of sample_like

Returns: Energy of the sample.

Examples

>>> poly = dimod.BinaryPolynomial({'a': -1, ('a', 'b'): 1, ('a', 'b', 'c'): -1},
...                               dimod.BINARY)
>>> sample = {'a': 1, 'b': 1, 'c': 0}
>>> dimod.poly_energy(sample, poly)
0.0