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’, ‘stable’}, 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 treated as the largest values (True) or the smallest values (False) When the array contains unmasked values at the same extremes of the datatype, the ordering of these values and the masked values is undefined.

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]