xorbits.numpy.atleast_3d#

xorbits.numpy.atleast_3d(*tensors)[source]#

View inputs as arrays with at least three dimensions.

Parameters

  • arys1 (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.

  • 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.

  • ... (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, … – 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).

Return type

ndarray

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) 
...
[[[1]
  [2]]] (1, 2, 1)
[[[1]
  [2]]] (1, 2, 1)
[[[1 2]]] (1, 1, 2)

This docstring was copied from numpy.