brainpy.math.zeros_like#

brainpy.math.zeros_like(a: Union[jax._src.basearray.Array, numpy.ndarray, numpy.bool_, numpy.number, bool, int, float, complex], dtype: Optional[Union[Any, str, numpy.dtype, jax._src.typing.SupportsDType]] = None, shape: Any = None) → jax._src.basearray.Array[source]#

Return an array of zeros with the same shape and type as a given array.

LAX-backend implementation of numpy.zeros_like().

Original docstring below.

Parameters

  • a (array_like) – The shape and data-type of a define these same attributes of the returned array.

  • dtype (data-type, optional) – Overrides the data type of the result.

  • shape (int or sequence of ints, optional.) – Overrides the shape of the result. If order=’K’ and the number of dimensions is unchanged, will try to keep order, otherwise, order=’C’ is implied.

Returns

out – Array of zeros with the same shape and type as a.

Return type

ndarray