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 :

 # 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)

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

 # 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)

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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