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.argmax() function returns indices of the max element of the array in a particular axis.
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 :
Input array : [[(5.0, 2) (3.0, 4) (6.0, -7)] [(9.0, 1) (6.0, 4) (-2.0, -7)]] Record array of float: [[ 5. 3. 6.] [ 9. 6. -2.]] Record array of int: [[ 2 4 -7] [ 1 4 -7]] Output array along axis 1: [2 0] Output array along axis 0: [0 0 0]
Code #2 :
If we apply
numpy.recarray.argmax() to whole record array then it will give
Type error .
TypeError: Cannot cast array data from dtype((numpy.record, [(‘a’, ‘<f8'), ('b', '<i8')])) to dtype('V16') according to the rule 'safe'