numpy.ma.atleast_3d¶

`numpy.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. 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)`.

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) # doctest: +SKIP
...
[[[1]
[2]]] (1, 2, 1)
[[[1]
[2]]] (1, 2, 1)
[[[1 2]]] (1, 1, 2)
```

Previous topic

numpy.ma.atleast_2d

Next topic

numpy.ma.expand_dims