dimod.higherorder.utils.poly_energies¶
- poly_energies(samples_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]) numpy.ndarray [source]¶
Calculates energy of samples from a higher order polynomial.
- Parameters
samples_like – A collection of raw samples. samples-like is an extension of NumPy’s array_like structure. See
as_samples()
.poly – 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 ofsamples_like
.
Returns: Energies of the samples.
Examples
>>> poly = dimod.BinaryPolynomial({'a': -1, ('a', 'b'): 1, ('a', 'b', 'c'): -1}, ... dimod.BINARY) >>> samples = [{'a': 1, 'b': 1, 'c': 0}, ... {'a': 1, 'b': 1, 'c': 1}] >>> dimod.poly_energies(samples, poly) array([ 0., -1.])