numpy.ma.notmasked_contiguous()

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

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

Parameters:

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.

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.

Only accepts 2-D arrays at most.

>>> 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)]

Links:

doc_NumPy

2017-01-10 18:15:42

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