# numpy.ma.atleast_3d

ma.atleast_3d(*args, **kwargs) = <numpy.ma.extras._fromnxfunction_allargs object>

  View inputs as arrays with at least three dimensions.

  Parameters
    arys1, arys2, …array_like

      One or more array-like sequences. Non-array inputs are converted to arrays. Arrays that already have three or more dimensions are preserved.

  Returns
    res1, res2, …ndarray

      An array, or list of arrays, each with `a.ndim >= 3`. Copies are avoided where possible, and views with three or more dimensions are returned. For example, a 1-D array of shape `(N,)` becomes a view of shape `(1, N, 1)`, and a 2-D array of shape `(M, N)` becomes a view of shape `(M, N, 1)`.

  See also

  `atleast_1d`, `atleast_2d`

  Notes

  The function is applied to both the _data and the _mask, if any.

  Examples

      >>> np.atleast_3d(3.0)
      array([[[3.]]])

      >>> x = np.arange(3.0)
      >>> np.atleast_3d(x).shape
      (1, 3, 1)

      >>> x = np.arange(12.0).reshape(4,3)
      >>> np.atleast_3d(x).shape
      (4, 3, 1)
      >>> np.atleast_3d(x).base is x.base  # x is a reshape, so not base itself
      True

      >>> for arr in np.atleast_3d([1, 2], [[1, 2]], [[[1, 2]]]):
      ...     print(arr, arr.shape)
      ...
      [[[1]
        [2]]] (1, 2, 1)
      [[[1]
        [2]]] (1, 2, 1)
      [[[1 2]]] (1, 1, 2)

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