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View inputs as arrays with at least three dimensions.
One or more array-like sequences. Non-array inputs are converted to arrays. Arrays that already have three or more dimensions are preserved.
An array, or tuple 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
Examples
>>> import numpy as np
>>> 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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