xarray.IndexVariable.rolling_window#

IndexVariable.rolling_window(dim, window, window_dim, *, center=False, fill_value=<NA>, **kwargs)[source] #

Make a rolling_window along dim and add a new_dim to the last place.

Parameters:

• dim (str) – Dimension over which to compute rolling_window. For nd-rolling, should be list of dimensions.

• window (int) – Window size of the rolling For nd-rolling, should be list of integers.

• window_dim (str) – New name of the window dimension. For nd-rolling, should be list of strings.

• center (bool, default: False) – If True, pad fill_value for both ends. Otherwise, pad in the head of the axis.

• fill_value – value to be filled.

• **kwargs – Keyword arguments that should be passed to the underlying array type’s sliding_window_view function.

Returns:

• Variable that is a view of the original array with an added dimension of

• size w.

• The return dim (self.dims + (window_dim, ))

• The return shape (self.shape + (window, ))

See also

numpy.lib.stride_tricks.sliding_window_view, dask.array.lib.stride_tricks.sliding_window_view

Examples

>>> v = Variable(("a", "b"), np.arange(8).reshape((2, 4)))
>>> v.rolling_window("b", 3, "window_dim")
<xarray.Variable (a: 2, b: 4, window_dim: 3)> Size: 192B
array([[[nan, nan, 0.],
 [nan, 0., 1.],
 [ 0., 1., 2.],
 [ 1., 2., 3.]],
 [[nan, nan, 4.],
 [nan, 4., 5.],
 [ 4., 5., 6.],
 [ 5., 6., 7.]]])

>>> v.rolling_window("b", 3, "window_dim", center=True)
<xarray.Variable (a: 2, b: 4, window_dim: 3)> Size: 192B
array([[[nan, 0., 1.],
 [ 0., 1., 2.],
 [ 1., 2., 3.],
 [ 2., 3., nan]],
 [[nan, 4., 5.],
 [ 4., 5., 6.],
 [ 5., 6., 7.],
 [ 6., 7., nan]]])

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