Numpy recarray.prod() 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.prod() function returns the product of the array elements over the given axis.

Syntax : numpy.recarray.prod(axis=None, dtype=None, out=None, keepdims=False)

Parameters:
axis : [None or int or tuple of ints, optional]Axis or axes along which a product is performed. The default, axis=None, will calculate the product of all the elements in the input array. If axis is negative it counts from the last to the first axis.
dtype : [dtype, optional] The type of the returned array.
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.
keepdims : [ bool, optional] If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.

Return : [ndarray] The product of the array elements over the given axis.

Code #1 :

# Python program explaining
# numpy.recarray.prod() 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.prod methods
# to float record array along axis 1
out_arr = rec_arr.a.prod( axis = 1)
print ("Output product array of float along axis 1: ", out_arr)

# applying recarray.prod methods
# to float record array along axis 0
out_arr = rec_arr.a.prod( axis = 0)
print ("Output product array of float along axis 0: ", out_arr)

# applying recarray.prod methods
# to float record array along -1 axis
out_arr = rec_arr.a.prod( axis = -1)
print ("Output product array of float along -1 axis : ", out_arr)


# applying recarray.prod methods
# to int record array along default axis value
out_arr = rec_arr.b.prod()
print ("Output product of int array elements array along default axis: ", out_arr)

Output:

Input array :  [[(  5.,  2) (  3., -4) (  6.,  9)]
 [(  9.,  1) (  5.,  4) (-12., -7)]]
Record array of float:  [[  5.   3.   6.]
 [  9.   5. -12.]]
Record array of int:  [[ 2 -4  9]
 [ 1  4 -7]]
Output product array of float along axis 1:  [  90. -540.]
Output product array of float along axis 0:  [ 45.  15. -72.]
Output product array of float along -1 axis :  [  90. -540.]
Output product of int array elements array along default axis:  2016