Numpy recarray.argmin() 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.argmin() function returns indices of the min element of the array in a particular axis.

Syntax : numpy.recarray.argmin(axis=None, out=None)

Parameters:
axis : [ int, optional] Along a specified axis like 0 or 1
out : [ndarray, optional] A location into which the result is stored.
  -> If provided, it must have a shape that the inputs broadcast to.
  -> If not provided or None, a freshly-allocated array is returned.

Returns : [ndarray of ints] Array of indices into the array with same shape as array.shape with the dimension along axis removed.

Code #1 :

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# Python program explaining
# numpy.recarray.argmin() 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.argmin methods to
# float record array along axis 1
out_arr = geek.recarray.argmin(rec_arr.a, axis = 1)
print ("Output array along axis 1: ", out_arr) 
  
# applying recarray.argmin methods to
# int record array along axis 0
out_arr = geek.recarray.argmin(rec_arr.b, axis = 0)
print ("Output array along axis 0: ", out_arr) 

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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 array along axis 1:  [1 2]
Output array along axis 0:  [1 0 1]

 

Code #2 :

If we apply numpy.recarray.argmin() to whole record array then it will give Type error

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# Python program explaining
# numpy.recarray.argmin() 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.argmin methods to  record array
out_arr = geek.recarray.argmin(rec_arr)

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Output:

TypeError: Cannot cast array data from dtype((numpy.record, [(‘a’, ‘<f8'), ('b', '<i8')])) to dtype('V16') according to the rule 'safe'



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