Numpy recarray.argpartition() function | Python
Last Updated :
23 Apr, 2019
In numpy, arrays may have a data-types containing fields, analogous to columns in a spreadsheet. An example is [(a, int), (b, float)]
, where each entry in the array is a pair of (int, float). Normally, these attributes are accessed using dictionary lookups such as arr['a'] and arr['b']
.
Record arrays allow the fields to be accessed as members of the array, using arr.a and arr.b
. numpy.recarray.argpartition()
function returns the indices that would partition this array.
Syntax : numpy.recarray.argpartition(kth, axis=-1, kind='introselect', order=None)
Parameters:
kth : [int or sequence of ints ] Element index to partition by.
axis : [int or None] Axis along which to sort. If None, the array is flattened before sorting. The default is -1, which sorts along the last axis.
kind : Selection algorithm. Default is ‘introselect’.
order : [str or list of str] When arr is an array with fields defined, this argument specifies which fields to compare first, second, etc.
Return : [index_array, ndarray] Array of indices that partition arr along the specified axis.
Code #1 :
import numpy as geek
in_arr = geek.array([[( 5.0 , 2 ), ( 3.0 , - 4 ), ( 6.0 , 9 )],
[( 9.0 , 1 ), ( 5.0 , 4 ), ( - 12.0 , - 7 )]],
dtype = [( 'a' , float ), ( 'b' , int )])
print ( "Input array : " , in_arr)
rec_arr = in_arr.view(geek.recarray)
print ( "Record array of float: " , rec_arr.a)
print ( "Record array of int: " , rec_arr.b)
out_arr = geek.recarray.argpartition(rec_arr.a, kth = 1 , axis = 1 )
print ( "Output partitioned array indices along axis 1: " , out_arr)
out_arr = geek.recarray.argpartition(rec_arr.b, kth = 1 , axis = 0 )
print ( "Output partitioned array indices array along axis 0: " , out_arr)
|
Output:
Input array : [[(5.0, 2) (3.0, -4) (6.0, 9)]
[(9.0, 1) (5.0, 4) (-12.0, -7)]]
Record array of float: [[ 5. 3. 6.]
[ 9. 5. -12.]]
Record array of int: [[ 2 -4 9]
[ 1 4 -7]]
Output partitioned array indices along axis 1: [[1 0 2]
[2 1 0]]
Output partitioned array indices array along axis 0: [[1 0 1]
[0 1 0]]
Code #2 :
We are applying numpy.recarray.argpartition()
to whole record array.
import numpy as geek
in_arr = geek.array([[( 5.0 , 2 ), ( 3.0 , 4 ), ( 6.0 , - 7 )],
[( 9.0 , 1 ), ( 6.0 , 4 ), ( - 2.0 , - 7 )]],
dtype = [( 'a' , float ), ( 'b' , int )])
print ( "Input array : " , in_arr)
rec_arr = in_arr.view(geek.recarray)
out_arr = geek.recarray.argpartition(rec_arr, kth = 2 )
print ( "Output array : " , out_arr)
|
Output:
Input array : [[(5.0, 2) (3.0, 4) (6.0, -7)]
[(9.0, 1) (6.0, 4) (-2.0, -7)]]
Output array : [[1 0 2]
[2 1 0]]
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