partition(a, kth, axis=-1, kind='introselect', order=None)
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 it would be in a sorted array. All elements smaller than the k-th 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.
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:
Array to be sorted.
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.
Passing booleans as index is deprecated.
Axis along which to sort. If None, the array is flattened before sorting. The default is -1, which sorts along the last axis.
Selection algorithm. Default is 'introselect'.
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.
Array of the same type and shape as a.
Return a partitioned copy of an array.
argpartition
Indirect partition.
ndarray.partition
Method to sort an array in-place.
sort
Full sorting
>>> a = np.array([3, 4, 2, 1])
... np.partition(a, 3) array([2, 1, 3, 4])
>>> np.partition(a, (1, 3)) array([1, 2, 3, 4])See :
The following pages refer to to this document either explicitly or contain code examples using this.
numpy.argpartition
numpy.core.defchararray.chararray.partition
numpy.sort
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