jax.numpy.argsort(a, axis=-1, kind='stable', order=None)[source]#

Returns the indices that would sort an array.

LAX-backend implementation of numpy.argsort().

Only kind='stable' is supported. Other kind values will produce a warning and be treated as if they were 'stable'.

Original docstring below.

Perform an indirect sort along the given axis using the algorithm specified by the kind keyword. It returns an array of indices of the same shape as a that index data along the given axis in sorted order.

  • a (array_like) – 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.

  • kind ({'quicksort', 'mergesort', 'heapsort', 'stable'}, optional) –

    Sorting algorithm. The default is ‘quicksort’. Note that both ‘stable’ and ‘mergesort’ use timsort under the covers and, in general, the actual implementation will vary with data type. The ‘mergesort’ option is retained for backwards compatibility.

    Changed in version 1.15.0.: The ‘stable’ option was added.

  • order (str or list of str, optional) – When a is an array with fields defined, this argument specifies which fields to compare first, second, etc. A single field can be specified as a string, and not all fields need be specified, but unspecified fields will still be used, in the order in which they come up in the dtype, to break ties.


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