numpy.ma.sort¶

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

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 beforesorting. The default is -1, which sorts along the last axis. kind : {‘quicksort’, ‘mergesort’, ‘heapsort’}, optional Sorting algorithm. Default is ‘quicksort’. order : list, optional Whena is a structured array, this argument specifies which fieldsto compare first, second, and so on. This list does not need toinclude 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 thedatatype, the ordering of these values and the masked values isundefined. fill_value : {var}, optional Value used internally for the masked values.Iffill_value is not None, it supersedesendwith.

Returns:

sorted_array : ndarray Array of the same type and shape asa.

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

Seesort 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]