`numpy.ma.extras:notmasked_contiguous`

source: build-install/usr/lib/python3.14/site-packages/numpy/ma/extras.py:2032

Signature

def notmasked_contiguous(a, axis = None)

Summary

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.

Returns

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

import numpy as np
a = np.arange(12).reshape((3, 4))
mask = np.zeros_like(a)
mask[1:, :-1] = 1; mask[0, 1] = 1; mask[-1, 0] = 0
ma = np.ma.array(a, mask=mask)
ma

✓

masked_array(
  data=[[0, --, 2, 3],
        [--, --, --, 7],
        [8, --, --, 11]],
  mask=[[False,  True, False, False],
        [ True,  True,  True, False],
        [False,  True,  True, False]],
  fill_value=999999)

np.array(ma[~ma.mask])

✗

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)], [], [slice(0, 1, None)], [slice(0, 3, None)]]

np.ma.notmasked_contiguous(ma, axis=1)

✓

[[slice(0, 1, None), slice(2, 4, None)], [slice(3, 4, None)], [slice(0, 1, None), slice(3, 4, None)]]

Aliases

numpy.ma.notmasked_contiguous