# mxnet.np.argsort¶

argsort(a, axis=-1, descending=False, stable=True)

Returns the indices that sort an array x along a specified axis.

Notes

argsort is a standard API in https://data-apis.org/array-api/latest/API_specification/generated/signatures.sorting_functions.argsort.html instead of an official NumPy operator.

Parameters
• a (ndarray) – Array to sort.

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

• descending (bool, optional) – sort order. If True, the returned indices sort x in descending order (by value). If False, the returned indices sort x in ascending order (by value).Default: False.

• stable (bool, optional) – sort stability. If True, the returned indices must maintain the relative order of x values which compare as equal. If False, the returned indices may or may not maintain the relative order of x values which compare as equal. Default: True.

Returns

index_array – Array of indices that sort a along the specified axis. If a is one-dimensional, a[index_array] yields a sorted a. More generally, np.take_along_axis(a, index_array, axis=axis) always yields the sorted a, irrespective of dimensionality.

Return type

ndarray, int

Notes

This operator does not support different sorting algorithms.

Examples

One dimensional array:

>>> x = np.array([3, 1, 2])
>>> np.argsort(x)
array([1, 2, 0])


Two-dimensional array:

>>> x = np.array([[0, 3], [2, 2]])
>>> x
array([[0, 3],
[2, 2]])
>>> ind = np.argsort(x, axis=0)  # sorts along first axis (down)
>>> ind
array([[0, 1],
[1, 0]])
>>> np.take_along_axis(x, ind, axis=0)  # same as np.sort(x, axis=0)
array([[0, 2],
[2, 3]])
>>> ind = np.argsort(x, axis=1)  # sorts along last axis (across)
>>> ind
array([[0, 1],
[0, 1]])
>>> np.take_along_axis(x, ind, axis=1)  # same as np.sort(x, axis=1)
array([[0, 3],
[2, 2]])


Indices of the sorted elements of a N-dimensional array:

>>> ind = np.unravel_index(np.argsort(x, axis=None), x.shape)
>>> ind
(array([0, 1, 1, 0]), array([0, 0, 1, 1]))
>>> x[ind]  # same as np.sort(x, axis=None)
array([0, 2, 2, 3])