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.cumprod() function returns the cumulative product of array elements over a given axis.
Syntax :
numpy.recarray.cumprod(axis=None, dtype=None, out=None)Parameters:
axis : Axis along which the cumulative product is computed. The default is to compute the product of the flattened array.
dtype : Type of the returned array, as well as of the accumulator in which the elements are multiplied.
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.Return : A new array holding the result is returned unless out is specified, in which case it is returned.
Code #1 :
# Python program explaining # numpy.recarray.cumprod() 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.cumprod methods # to float record array along axis 1 out_arr = rec_arr.a.cumprod( axis = 1) print ("Output array along axis 1: ", out_arr)   # applying recarray.cumprod methods # to int record array along axis 0 out_arr = rec_arr.b.cumprod(axis = 0) print ("Output array along axis 0: ", out_arr) |
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 array along axis 1: [[ 5. 15. 90.] [ 9. 45. -540.]] Output array along axis 0: [[ 2 -4 9] [ 2 -16 -63]]
