numpy.ma.atleast_3d
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numpy.ma.atleast_3d(*args, **kwargs) = <numpy.ma.extras._fromnxfunction_allargs object>
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View inputs as arrays with at least three dimensions.
- Parameters
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arys1, arys2, …array_like
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One or more array-like sequences. Non-array inputs are converted to arrays. Arrays that already have three or more dimensions are preserved.
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- Returns
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res1, res2, …ndarray
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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)
.
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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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https://numpy.org/doc/1.19/reference/generated/numpy.ma.atleast_3d.html