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 ofnumpy.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
>>> import numpy as np >>> 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