-
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.
Returns: endpoints : list
A list of slices (start and end indexes) of unmasked indexes in the array.
See also
flatnotmasked_edges
,flatnotmasked_contiguous
,notmasked_edges
,clump_masked
,clump_unmasked
Notes
Only accepts 2-D arrays at most.
Examples
123>>> a
=
np.arange(
9
).reshape((
3
,
3
))
>>> mask
=
np.zeros_like(a)
>>> mask[
1
:,
1
:]
=
1
123>>> ma
=
np.ma.array(a, mask
=
mask)
>>> np.array(ma[~ma.mask])
array([
0
,
1
,
2
,
3
,
6
])
12>>> np.ma.notmasked_contiguous(ma)
[
slice
(
0
,
4
,
None
),
slice
(
6
,
7
,
None
)]
numpy.ma.notmasked_contiguous()

2025-01-10 15:47:30
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