numpy.ma.notmasked_contiguous
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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
>>> a = np.arange(9).reshape((3, 3)) >>> mask = np.zeros_like(a) >>> mask[1:, 1:] = 1
>>> ma = np.ma.array(a, mask=mask) >>> np.array(ma[~ma.mask]) array([0, 1, 2, 3, 6])
>>> np.ma.notmasked_contiguous(ma) [slice(0, 4, None), slice(6, 7, None)]
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Licensed under the NumPy License.
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.ma.notmasked_contiguous.html