Function zeros_like

dask/array/_array_expr/_creation.py:406–458

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

(a, dtype=None, order="C", chunks=None, name=None, shape=None)

def zeros_like(a, dtype=None, order="C", chunks=None, name=None, shape=None):
    """
    Return an array of zeros with the same shape and type as a given array.

    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.
    order : {'C', 'F'}, optional
        Whether to store multidimensional data in C- or Fortran-contiguous
        (row- or column-wise) order in memory.
    chunks : sequence of ints
        The number of samples on each block. Note that the last block will have
        fewer samples if ``len(array) % chunks != 0``.
    name : str, optional
        An optional keyname for the array. Defaults to hashing the input
        keyword arguments.
    shape : int or sequence of ints, optional.
        Overrides the shape of the result.

    Returns
    -------
    out : ndarray
        Array of zeros with the same shape and type as `a`.

    See Also
    --------
    ones_like : Return an array of ones with shape and type of input.
    empty_like : Return an empty array with shape and type of input.
    zeros : Return a new array setting values to zero.
    ones : Return a new array setting values to one.
    empty : Return a new uninitialized array.
    """

    a = asarray(a, name=False)
    shape, chunks = _get_like_function_shapes_chunks(a, chunks, shape)

    # if shape is nan we cannot rely on regular zeros function, we use
    # generic map_blocks.
    if np.isnan(shape).any():
        return a.map_blocks(partial(np.zeros_like, dtype=(dtype or a.dtype)))

    return zeros(
        shape,
        dtype=(dtype or a.dtype),
        order=order,
        chunks=chunks,
        name=name,
        meta=a._meta,
    )


def full(shape, fill_value, *args, **kwargs):