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Fonction zeros_like - module numpy

Signature de la fonction zeros_like

def zeros_like(a, dtype=None, order='K', subok=True, shape=None) 

Description

zeros_like.__doc__

    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.

        .. versionadded:: 1.6.0
    order : {'C', 'F', 'A', or 'K'}, optional
        Overrides the memory layout of the result. 'C' means C-order,
        'F' means F-order, 'A' means 'F' if `a` is Fortran contiguous,
        'C' otherwise. 'K' means match the layout of `a` as closely
        as possible.

        .. versionadded:: 1.6.0
    subok : bool, optional.
        If True, then the newly created array will use the sub-class
        type of `a`, otherwise it will be a base-class array. Defaults
        to True.
    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.

        .. versionadded:: 1.17.0

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

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

    Examples
    --------
    >>> x = np.arange(6)
    >>> x = x.reshape((2, 3))
    >>> x
    array([[0, 1, 2],
           [3, 4, 5]])
    >>> np.zeros_like(x)
    array([[0, 0, 0],
           [0, 0, 0]])

    >>> y = np.arange(3, dtype=float)
    >>> y
    array([0., 1., 2.])
    >>> np.zeros_like(y)
    array([0.,  0.,  0.])