dpnp.argsort¶

dpnp.argsort(a, axis=-1, kind=None, order=None, *, descending=False, stable=None)[source]¶

Returns the indices that would sort an array.

For full documentation refer to numpy.argsort.

Parameters:

a{dpnp.ndarray, usm_ndarray}

Array to be sorted.

axis{None, 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.

Default: -1.

kind{None, "stable", "mergesort", "radixsort"}, optional

Sorting algorithm. The default is None, which uses parallel merge-sort or parallel radix-sort algorithms depending on the array data type.

Default: None.

descendingbool, optional

Sort order. If True, the array must be sorted in descending order (by value). If False, the array must be sorted in ascending order (by value).

Default: False.

stable{None, bool}, optional

Sort stability. If True, the returned array will maintain the relative order of a values which compare as equal. The same behavior applies when set to False or None. Internally, this option selects kind="stable".

Default: None.

Returns:

outdpnp.ndarray: Array of indices that sort a along the specified axis. If a is one-dimensional, a[index_array] yields a sorted a. More generally, dpnp.take_along_axis(a, index_array, axis=axis) always yields the sorted a, irrespective of dimensionality. The return array has default array index data type.

Limitations

Parameter order is only supported with its default value. Otherwise NotImplementedError exception will be raised. Sorting algorithms "quicksort" and "heapsort" are not supported.

See also

dpnp.ndarray.argsort: Equivalent method.
dpnp.sort: Return a sorted copy of an array.
dpnp.lexsort: Indirect stable sort with multiple keys.
dpnp.argpartition: Indirect partial sort.
dpnp.take_along_axis: Apply index_array from obj:dpnp.argsort to an array as if by calling sort.

Notes

For zero-dimensional arrays, if axis=None, output is a one-dimensional array with a single zero element. Otherwise, an AxisError is raised.

Examples

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

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

>>> ind = np.argsort(x, axis=0)  # sorts along first axis
>>> 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
>>> 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]])