xorbits.numpy.partition#
- xorbits.numpy.partition(a, kth, axis=- 1, kind='introselect', order=None, **kw)[源代码]#
Return a partitioned copy of an array.
Creates a copy of the array with its elements rearranged in such a way that the value of the element in k-th position is in the position the value would be in a sorted array. In the partitioned array, all elements before the k-th element are less than or equal to that element, and all the elements after the k-th element are greater than or equal to that element. The ordering of the elements in the two partitions is undefined.
1.8.0(numpy) 新版功能.
- 参数
a (array_like) – Array to be sorted.
kth (int or sequence of ints) –
Element index to partition by. The k-th value of the element 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 of all elements in the partitions is undefined. If provided with a sequence of k-th it will partition all elements indexed by k-th of them into their sorted position at once.
1.22.0(numpy) 版后已移除: Passing booleans as index is deprecated.
axis (int or None, 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 ({'introselect'}, optional) – Selection algorithm. Default is ‘introselect’.
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. 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.
- 返回
partitioned_array – Array of the same type and shape as a.
- 返回类型
ndarray
参见
ndarray.partition
Method to sort an array in-place.
argpartition
Indirect partition.
sort
Full sorting
提示
The various selection algorithms are characterized by their average speed, worst case performance, work space size, and whether they are stable. A stable sort keeps items with the same key in the same relative order. The available algorithms have the following properties:
kind
speed
worst case
work space
stable
‘introselect’
1
O(n)
0
no
All the partition algorithms make temporary copies of the data when partitioning along any but the last axis. Consequently, partitioning along the last axis is faster and uses less space than partitioning along any other axis.
The sort order for complex numbers is lexicographic. If both the real and imaginary parts are non-nan then the order is determined by the real parts except when they are equal, in which case the order is determined by the imaginary parts.
实际案例
>>> a = np.array([7, 1, 7, 7, 1, 5, 7, 2, 3, 2, 6, 2, 3, 0]) >>> p = np.partition(a, 4) >>> p array([0, 1, 2, 1, 2, 5, 2, 3, 3, 6, 7, 7, 7, 7])
p[4]
is 2; all elements inp[:4]
are less than or equal top[4]
, and all elements inp[5:]
are greater than or equal top[4]
. The partition is:[0, 1, 2, 1], [2], [5, 2, 3, 3, 6, 7, 7, 7, 7]
The next example shows the use of multiple values passed to kth.
>>> p2 = np.partition(a, (4, 8)) >>> p2 array([0, 1, 2, 1, 2, 3, 3, 2, 5, 6, 7, 7, 7, 7])
p2[4]
is 2 andp2[8]
is 5. All elements inp2[:4]
are less than or equal top2[4]
, all elements inp2[5:8]
are greater than or equal top2[4]
and less than or equal top2[8]
, and all elements inp2[9:]
are greater than or equal top2[8]
. The partition is:[0, 1, 2, 1], [2], [3, 3, 2], [5], [6, 7, 7, 7, 7]
This docstring was copied from numpy.