numpy.ma.notmasked_edges()

numpy.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:

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:	edges : ndarray 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.

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:

edges : ndarray 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.

Examples

>>> 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(ma)
array([0, 6])

Links:

https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.ma.notmasked_edges.html

doc_NumPy

2025-01-10 15:47:30

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