numpy.ma.notmasked_edges#

ma.notmasked_edges(a, axis=None)[source]#

Find the indices of the first and last unmasked values along an axis.

If all values are masked, return None. Otherwise, return a list of two tuples, corresponding to the indices of the first and last unmasked values respectively.

Parameters:

aarray_like: The input array.
axisint, optional: Axis along which to perform the operation. If None (default), applies to a flattened version of the array.

Returns:

edgesndarray or list: An array of start and end indexes if there are any masked data in the array. If there are no masked data in the array, edges is a list of the first and last index.

See also

flatnotmasked_contiguous, flatnotmasked_edges, notmasked_contiguous
clump_masked, clump_unmasked

Examples

>>> import numpy as np
>>> a = np.arange(9).reshape((3, 3))
>>> m = np.zeros_like(a)
>>> m[1:, 1:] = 1

>>> am = np.ma.array(a, mask=m)
>>> np.array(am[~am.mask])
array([0, 1, 2, 3, 6])

>>> np.ma.notmasked_edges(am)
array([0, 6])