numpy.ma.ndenumerate#

ma.ndenumerate(a, compressed=True)[source]#

Multidimensional index iterator.

Return an iterator yielding pairs of array coordinates and values, skipping elements that are masked. With compressed=False, ma.masked is yielded as the value of masked elements. This behavior differs from that of numpy.ndenumerate, which yields the value of the underlying data array.

Parameters

aarray_like: An array with (possibly) masked elements.
compressedbool, optional: If True (default), masked elements are skipped.

See also

numpy.ndenumerate: Equivalent function ignoring any mask.

Notes

New in version 1.23.0.

Examples

>>> a = np.ma.arange(9).reshape((3, 3))
>>> a[1, 0] = np.ma.masked
>>> a[1, 2] = np.ma.masked
>>> a[2, 1] = np.ma.masked
>>> a
masked_array(
  data=[[0, 1, 2],
        [--, 4, --],
        [6, --, 8]],
  mask=[[False, False, False],
        [ True, False,  True],
        [False,  True, False]],
  fill_value=999999)
>>> for index, x in np.ma.ndenumerate(a):
...     print(index, x)
(0, 0) 0
(0, 1) 1
(0, 2) 2
(1, 1) 4
(2, 0) 6
(2, 2) 8

>>> for index, x in np.ma.ndenumerate(a, compressed=False):
...     print(index, x)
(0, 0) 0
(0, 1) 1
(0, 2) 2
(1, 0) --
(1, 1) 4
(1, 2) --
(2, 0) 6
(2, 1) --
(2, 2) 8

numpy.ma.masked_array.mask

numpy.ma.flatnotmasked_contiguous