dimod.higherorder.utils.poly_energy

poly_energy(sample_like: Union[Sequence[float], Mapping[Hashable, Union[float, numpy.floating, numpy.integer]], Sequence[Sequence[Sequence[Sequence[Sequence[Any]]]]], numpy.typing._array_like._SupportsArray[numpy.dtype], Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]], Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]], Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]]], Sequence[Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]]]], bool, int, float, complex, str, bytes, Sequence[Union[bool, int, float, complex, str, bytes]], Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]], Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]], Sequence[Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]]], Sequence[Sequence[float]], Tuple[Sequence[float], List[Hashable]], Tuple[Sequence[Sequence[float]], List[Hashable]], Sequence[Union[Sequence[float], Mapping[Hashable, Union[float, numpy.floating, numpy.integer]], Sequence[Sequence[Sequence[Sequence[Sequence[Any]]]]], numpy.typing._array_like._SupportsArray[numpy.dtype], Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]], Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]], Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]]], Sequence[Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]]]], bool, int, float, complex, str, bytes, Sequence[Union[bool, int, float, complex, str, bytes]], Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]], Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]], Sequence[Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]]]]], Iterator[Union[Sequence[float], Mapping[Hashable, Union[float, numpy.floating, numpy.integer]], Sequence[Sequence[Sequence[Sequence[Sequence[Any]]]]], numpy.typing._array_like._SupportsArray[numpy.dtype], Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]], Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]], Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]]], Sequence[Sequence[Sequence[Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]]]], bool, int, float, complex, str, bytes, Sequence[Union[bool, int, float, complex, str, bytes]], Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]], Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]], Sequence[Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]]]]]], poly: Union[Mapping[Sequence[Hashable], Union[float, numpy.floating, numpy.integer]], dimod.higherorder.polynomial.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