`numpy.ma.``notmasked_contiguous`(a, axis=None)[source]

Find contiguous unmasked data in a masked array along the given axis.

Parameters: a : array_like The input array. axis : int, optional Axis along which to perform the operation. If None (default), applies to a flattened version of the array, and this is the same as `flatnotmasked_contiguous`. endpoints : list A list of slices (start and end indexes) of unmasked indexes in the array. If the input is 2d and axis is specified, the result is a list of lists.

Notes

Only accepts 2-D arrays at most.

Examples

```>>> a = np.arange(12).reshape((3, 4))
>>> ma
data=[[0, --, 2, 3],
[--, --, --, 7],
[8, --, --, 11]],
[ True,  True,  True, False],
[False,  True,  True, False]],
fill_value=999999)
array([ 0,  2,  3,  7, 8, 11])
```
```>>> np.ma.notmasked_contiguous(ma)
[slice(0, 1, None), slice(2, 4, None), slice(7, 9, None), slice(11, 12, None)]
```
```>>> np.ma.notmasked_contiguous(ma, axis=0)
[[slice(0, 1, None), slice(2, 3, None)],  # column broken into two segments
[slice(0, 1, None)],
[slice(0, 3, None)]]
```
```>>> np.ma.notmasked_contiguous(ma, axis=1)
[[slice(0, 1, None), slice(2, 4, None)],  # row broken into two segments
[slice(3, 4, None)],
[slice(0, 1, None), slice(3, 4, None)]]
```