Function sliding_window_view

numpy/lib/_stride_tricks_impl.py:180–444

Create a sliding window view into the array with the given window shape. Also known as rolling or moving window, the window slides across all dimensions of the array and extracts subsets of the array at all window positions. .. versionadded:: 1.20.0 Parameters -------

(x, window_shape, axis=None, *,
                        subok=False, writeable=False)

    _sliding_window_view_dispatcher, module="numpy.lib.stride_tricks"
)
def sliding_window_view(x, window_shape, axis=None, *,
                        subok=False, writeable=False):
    """
    Create a sliding window view into the array with the given window shape.

    Also known as rolling or moving window, the window slides across all
    dimensions of the array and extracts subsets of the array at all window
    positions.

    .. versionadded:: 1.20.0

    Parameters
    ----------
    x : array_like
        Array to create the sliding window view from.
    window_shape : int or tuple of int
        Size of window over each axis that takes part in the sliding window.
        If `axis` is not present, must have same length as the number of input
        array dimensions. Single integers `i` are treated as if they were the
        tuple `(i,)`.
    axis : int or tuple of int, optional
        Axis or axes along which the sliding window is applied.
        By default, the sliding window is applied to all axes and
        `window_shape[i]` will refer to axis `i` of `x`.
        If `axis` is given as a `tuple of int`, `window_shape[i]` will refer to
        the axis `axis[i]` of `x`.
        Single integers `i` are treated as if they were the tuple `(i,)`.
    subok : bool, optional
        If True, sub-classes will be passed-through, otherwise the returned
        array will be forced to be a base-class array (default).
    writeable : bool, optional
        When true, allow writing to the returned view. The default is false,
        as this should be used with caution: the returned view contains the
        same memory location multiple times, so writing to one location will
        cause others to change.

    Returns
    -------
    view : ndarray
        Sliding window view of the array. The sliding window dimensions are
        inserted at the end, and the original dimensions are trimmed as
        required by the size of the sliding window.
        That is, ``view.shape = x_shape_trimmed + window_shape``, where
        ``x_shape_trimmed`` is ``x.shape`` with every entry reduced by one less
        than the corresponding window size.

    See Also
    --------
    lib.stride_tricks.as_strided: A lower-level and less safe routine for
        creating arbitrary views from custom shape and strides. Use the
        ``check_bounds`` parameter for bounds validation.
    broadcast_to: broadcast an array to a given shape.

    Notes
    -----
    .. warning::

       This function creates views with overlapping memory. When