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numpy.roll
- numpy.roll(a, shift, axis=None)[source]
- 
    Roll array elements along a given axis. Elements that roll beyond the last position are re-introduced at the first. - Parameters
- 
      - aarray_like
- 
        Input array. 
- shiftint or tuple of ints
- 
        The number of places by which elements are shifted. If a tuple, then axismust be a tuple of the same size, and each of the given axes is shifted by the corresponding number. If an int whileaxisis a tuple of ints, then the same value is used for all given axes.
- axisint or tuple of ints, optional
- 
        Axis or axes along which elements are shifted. By default, the array is flattened before shifting, after which the original shape is restored. 
 
- Returns
- 
      - resndarray
- 
        Output array, with the same shape as a.
 
 See also - rollaxis
- 
       Roll the specified axis backwards, until it lies in a given position. 
 NotesNew in version 1.12.0. Supports rolling over multiple dimensions simultaneously. Examples>>> x = np.arange(10) >>> np.roll(x, 2) array([8, 9, 0, 1, 2, 3, 4, 5, 6, 7]) >>> np.roll(x, -2) array([2, 3, 4, 5, 6, 7, 8, 9, 0, 1])>>> x2 = np.reshape(x, (2,5)) >>> x2 array([[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]]) >>> np.roll(x2, 1) array([[9, 0, 1, 2, 3], [4, 5, 6, 7, 8]]) >>> np.roll(x2, -1) array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 0]]) >>> np.roll(x2, 1, axis=0) array([[5, 6, 7, 8, 9], [0, 1, 2, 3, 4]]) >>> np.roll(x2, -1, axis=0) array([[5, 6, 7, 8, 9], [0, 1, 2, 3, 4]]) >>> np.roll(x2, 1, axis=1) array([[4, 0, 1, 2, 3], [9, 5, 6, 7, 8]]) >>> np.roll(x2, -1, axis=1) array([[1, 2, 3, 4, 0], [6, 7, 8, 9, 5]])
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 https://numpy.org/doc/1.19/reference/generated/numpy.roll.html