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