numpy.ma.sort

numpy.ma.sort(a, axis=-1, kind='quicksort', order=None, endwith=True, fill_value=None)

Sort the array, in-place

Parameters :

a : array_like

Array to be sorted.

axis : int, optional

Axis along which to sort. If None, the array is flattened before sorting. The default is -1, which sorts along the last axis.

kind : {‘quicksort’, ‘mergesort’, ‘heapsort’}, optional

Sorting algorithm. Default is ‘quicksort’.

order : list, optional

When a is a structured array, this argument specifies which fields to compare first, second, and so on. This list does not need to include all of the fields.

endwith : {True, False}, optional

Whether missing values (if any) should be forced in the upper indices (at the end of the array) (True) or lower indices (at the beginning).

fill_value : {var}, optional

Value used internally for the masked values. If fill_value is not None, it supersedes endwith.

Returns :

sorted_array : ndarray

Array of the same type and shape as a.

See also

ndarray.sort

Method to sort an array in-place.

argsort

Indirect sort.

lexsort

Indirect stable sort on multiple keys.

searchsorted

Find elements in a sorted array.

Notes

See sort for notes on the different sorting algorithms.

Examples

>>> a = ma.array([1, 2, 5, 4, 3],mask=[0, 1, 0, 1, 0])
>>> # Default
>>> a.sort()
>>> print a
[1 3 5 -- --]

>>> a = ma.array([1, 2, 5, 4, 3],mask=[0, 1, 0, 1, 0])
>>> # Put missing values in the front
>>> a.sort(endwith=False)
>>> print a
[-- -- 1 3 5]

>>> a = ma.array([1, 2, 5, 4, 3],mask=[0, 1, 0, 1, 0])
>>> # fill_value takes over endwith
>>> a.sort(endwith=False, fill_value=3)
>>> print a
[1 -- -- 3 5]