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NotesParametersReturns
atleast_3d(*args, **kwargs)

Notes

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

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) .

View inputs as arrays with at least three dimensions.

See Also

atleast_1d
atleast_2d

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) # doctest: +SKIP ... [[[1] [2]]] (1, 2, 1) [[[1] [2]]] (1, 2, 1) [[[1 2]]] (1, 1, 2)
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GitHub : /numpy/ma/extras.py#None
type: <class 'numpy.ma.extras._fromnxfunction_allargs'>
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