numpy.ma.argsort¶

numpy.ma.argsort(a, axis=None, kind='quicksort', order=None, fill_value=None)[source]¶

Return an ndarray of indices that sort the array along the specified axis. Masked values are filled beforehand to fill_value.

Parameters:

Parameters:	axis : int, optional Axis along which to sort. The default is -1 (last axis). If None, the flattened array is used. fill_value : var, optional Value used to fill the array before sorting. The default is the fill_value attribute of the input array. kind : {‘quicksort’, ‘mergesort’, ‘heapsort’}, optional Sorting algorithm. order : list, optional When a is an array with fields defined, this argument specifies which fields to compare first, second, etc. Not all fields need be specified.
Returns:	index_array : ndarray, int Array of indices that sort a along the specified axis. In other words, `a[index_array]` yields a sorted a.

axis : int, optional

Axis along which to sort. The default is -1 (last axis). If None, the flattened array is used.

fill_value : var, optional

Value used to fill the array before sorting. The default is the fill_value attribute of the input array.

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

Sorting algorithm.

order : list, optional

When a is an array with fields defined, this argument specifies which fields to compare first, second, etc. Not all fields need be specified.

Returns:

index_array : ndarray, int

Array of indices that sort a along the specified axis. In other words, a[index_array] yields a sorted a.

See also

sort: Describes sorting algorithms used.
lexsort: Indirect stable sort with multiple keys.
ndarray.sort: Inplace sort.

Notes

See sort for notes on the different sorting algorithms.

Examples

>>> a = np.ma.array([3,2,1], mask=[False, False, True])
>>> a
masked_array(data = [3 2 --],
             mask = [False False  True],
       fill_value = 999999)
>>> a.argsort()
array([1, 0, 2])