flatnotmasked_contiguous(a)
Only accepts 2-D arrays at most.
The input array.
A sorted sequence of :None:None:`slice` objects (start index, end index).
Now returns an empty list instead of None for a fully masked array
Find contiguous unmasked data in a masked array along the given axis.
>>> a = np.ma.arange(10)
... np.ma.flatnotmasked_contiguous(a) [slice(0, 10, None)]
>>> mask = (a < 3) | (a > 8) | (a == 5)
... a[mask] = np.ma.masked
... np.array(a[~a.mask]) array([3, 4, 6, 7, 8])
>>> np.ma.flatnotmasked_contiguous(a) [slice(3, 5, None), slice(6, 9, None)]
>>> a[:] = np.ma.maskedSee :
... np.ma.flatnotmasked_contiguous(a) []
The following pages refer to to this document either explicitly or contain code examples using this.
numpy.ma.extras.clump_unmasked
numpy.ma.extras.notmasked_edges
numpy.ma.extras.notmasked_contiguous
numpy.ma.extras.clump_masked
numpy.ma.extras.flatnotmasked_edges
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