numpy.ndarray.partition¶
- ndarray.partition(kth, axis=-1, kind='introselect', order=None)¶
Rearranges the elements in the array in such a way that value of the element in kth position is in the position it would be in a sorted array. All elements smaller than the kth element are moved before this element and all equal or greater are moved behind it. The ordering of the elements in the two partitions is undefined.
New in version 1.8.0.
Parameters: kth : int or sequence of ints
Element index to partition by. The kth element value will be in its final sorted position and all smaller elements will be moved before it and all equal or greater elements behind it. The order all elements in the partitions is undefined. If provided with a sequence of kth it will partition all elements indexed by kth of them into their sorted position at once.
axis : int, optional
Axis along which to sort. Default is -1, which means sort along the last axis.
kind : {‘introselect’}, optional
Selection algorithm. Default is ‘introselect’.
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.
See also
- numpy.partition
- Return a parititioned copy of an array.
- argpartition
- Indirect partition.
- sort
- Full sort.
Notes
See np.partition for notes on the different algorithms.
Examples
>>> a = np.array([3, 4, 2, 1]) >>> a.partition(a, 3) >>> a array([2, 1, 3, 4])
>>> a.partition((1, 3)) array([1, 2, 3, 4])