numpy.argpartition#
- numpy.argpartition(a,kth,axis=-1,kind='introselect',order=None)[source]#
Perform an indirect partition along the given axis using thealgorithm specified by thekind keyword. It returns an array ofindices of the same shape asa that index data along the givenaxis in partitioned order.
- Parameters:
- aarray_like
Array to sort.
- kthint or sequence of ints
Element index to partition by. The k-th element will be in itsfinal sorted position and all smaller elements will be movedbefore it and all larger elements behind it. The order of allelements in the partitions is undefined. If provided with asequence of k-th it will partition all of them into their sortedposition at once.
Deprecated since version 1.22.0:Passing booleans as index is deprecated.
- axisint or None, optional
Axis along which to sort. The default is -1 (the last axis). IfNone, the flattened array is used.
- kind{‘introselect’}, optional
Selection algorithm. Default is ‘introselect’
- orderstr or list of str, optional
Whena is an array with fields defined, this argumentspecifies which fields to compare first, second, etc. A singlefield can be specified as a string, and not all fields need bespecified, but unspecified fields will still be used, in theorder in which they come up in the dtype, to break ties.
- Returns:
- index_arrayndarray, int
Array of indices that partitiona along the specified axis.Ifa is one-dimensional,
a[index_array]yields a partitioneda.More generally,np.take_along_axis(a,index_array,axis=axis)always yields the partitioneda, irrespective of dimensionality.
See also
partitionDescribes partition algorithms used.
ndarray.partitionInplace partition.
argsortFull indirect sort.
take_along_axisApply
index_arrayfrom argpartition to an array as if by calling partition.
Notes
The returned indices are not guaranteed to be sorted according tothe values. Furthermore, the default selection algorithm
introselectis unstable, and hence the returned indices are not guaranteedto be the earliest/latest occurrence of the element.argpartitionworks for real/complex inputs with nan values,seepartitionfor notes on the enhanced sort order anddifferent selection algorithms.Examples
One dimensional array:
>>>importnumpyasnp>>>x=np.array([3,4,2,1])>>>x[np.argpartition(x,3)]array([2, 1, 3, 4]) # may vary>>>x[np.argpartition(x,(1,3))]array([1, 2, 3, 4]) # may vary
>>>x=[3,4,2,1]>>>np.array(x)[np.argpartition(x,3)]array([2, 1, 3, 4]) # may vary
Multi-dimensional array:
>>>x=np.array([[3,4,2],[1,3,1]])>>>index_array=np.argpartition(x,kth=1,axis=-1)>>># below is the same as np.partition(x, kth=1)>>>np.take_along_axis(x,index_array,axis=-1)array([[2, 3, 4], [1, 1, 3]])