dpnp.sort
- dpnp.sort(a, axis=-1, kind=None, order=None, *, stable=None)[source]
Return a sorted copy of an array.
For full documentation refer to
numpy.sort
.- 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.kind ({None, "stable", "mergesort", "radixsort"}, optional) -- Sorting algorithm. Default is
None
, which is equivalent to"stable"
.stable ({None, bool}, optional) -- Sort stability. If
True
, the returned array will maintain the relative order ofa
values which compare as equal. The same behavior applies when set toFalse
orNone
. Internally, this option selectskind="stable"
. Default:None
.
- Returns:
out -- Sorted array with the same type and shape as a.
- Return type:
dpnp.ndarray
Notes
For zero-dimensional arrays, if
axis=None
, output is the input array returned as a one-dimensional array. Otherwise, anAxisError
is raised.Limitations
Parameters 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.sort
Sort an array in-place.
dpnp.argsort
Return the indices that would sort an array.
dpnp.lexsort
Indirect stable sort on multiple keys.
dpnp.searchsorted
Find elements in a sorted array.
dpnp.partition
Partial sort.
Examples
>>> import dpnp as np >>> a = np.array([[1,4],[3,1]]) >>> np.sort(a) # sort along the last axis array([[1, 4], [1, 3]]) >>> np.sort(a, axis=None) # sort the flattened array array([1, 1, 3, 4]) >>> np.sort(a, axis=0) # sort along the first axis array([[1, 1], [3, 4]])