mindquantum.utils.normalize

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mindquantum.utils.normalize(vec_in, axis=0)[source]

Normalize the input vectors based on specified axis.

Parameters

  • vec_in (Union[list[number], numpy.ndarray]) – Vector you want to normalize.

  • axis (int) – Along which axis you want to normalize your vector. Default: 0.

Returns

numpy.ndarray, Vector after normalization.

Examples

>>> from mindquantum.utils import normalize
>>> vec_in = np.array([[1, 2, 3], [4, 5, 6]])
>>> normalize(vec_in)
array([[0.24253563, 0.37139068, 0.4472136 ],
       [0.9701425 , 0.92847669, 0.89442719]])
>>> normalize(vec_in, 1)
array([[0.26726124, 0.53452248, 0.80178373],
       [0.45584231, 0.56980288, 0.68376346]])