Numpy recarray.argpartition() function | Python

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 :

 # Python program explaining # numpy.recarray.argpartition() method     # importing numpy as geek import numpy as geek    # creating input array with 2 different field  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)    # convert it to a record array, # using arr.view(np.recarray) rec_arr = in_arr.view(geek.recarray) print("Record array of float: ", rec_arr.a) print("Record array of int: ", rec_arr.b)    # applying recarray.argpartition methods # to float record array along axis 1 out_arr = geek.recarray.argpartition(rec_arr.a, kth = 1, axis = 1) print ("Output partitioned array indices along axis 1: ", out_arr)     # applying recarray.argpartition methods  # to int record array along axis 0 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.

 # Python program explaining # numpy.recarray.argpartition() method     # importing numpy as geek import numpy as geek    # creating input array with 2 different field  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)    # convert it to a record array,  # using arr.view(np.recarray) rec_arr = in_arr.view(geek.recarray)    # applying recarray.argpartition methods to  record array 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]]

My Personal Notes arrow_drop_up Check out this Author's contributed articles.

If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.

Article Tags :

Be the First to upvote.

Please write to us at contribute@geeksforgeeks.org to report any issue with the above content.