numpy.multiply() function is used when we want to compute the multiplication of two array. It returns the product of arr1 and arr2, element-wise.
Syntax : numpy.multiply(arr1, arr2, /, out=None, *, where=True, casting=’same_kind’, order=’K’, dtype=None, subok=True[, signature, extobj], ufunc ‘multiply’)
Parameters :
arr1: [array_like or scalar]1st Input array.
arr2: [array_like or scalar]2nd Input array.
dtype: The type of the returned array. By default, the dtype of arr is used.
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.
where: [array_like, optional] Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone.
**kwargs: Allows to pass keyword variable length of argument to a function. Used when we want to handle named argument in a function.Return: [ndarray or scalar] The product of arr1 and arr2, element-wise.
Example #1 :
# Python program explaining# numpy.multiply() function import numpy as geekin_num1 = 4in_num2 = 6 print ("1st Input number : ", in_num1)print ("2nd Input number : ", in_num2) out_num = geek.multiply(in_num1, in_num2) print ("output number : ", out_num) |
1st Input number : 4 2nd Input number : 6 output number : 24
Example #2 :
The following code is also known as the Hadamard product which is nothing but the element-wise-product of the two matrices. It is the most commonly used product for those who are interested in Machine Learning or statistics.
# Python program explaining# numpy.multiply() function import numpy as geek in_arr1 = geek.array([[2, -7, 5], [-6, 2, 0]])in_arr2 = geek.array([[0, -7, 8], [5, -2, 9]]) print ("1st Input array : ", in_arr1)print ("2nd Input array : ", in_arr2) out_arr = geek.multiply(in_arr1, in_arr2) print ("Resultant output array: ", out_arr) |
1st Input array : [[ 2 -7 5] [-6 2 0]] 2nd Input array : [[ 0 -7 8] [ 5 -2 9]] Resultant output array: [[ 0 49 40] [-30 -4 0]]
Another way to find the same is
import numpy as geekin_arr1=geek.matrix([[2, -7, 5], [-6, 2, 0]])in_arr2 = geek.matrix([[0, -7, 8], [5, -2, 9]]) print ("1st Input array : ", in_arr1)print ("2nd Input array : ", in_arr2) out_arr=geek.array(in_arr1)*geek.array(in_arr2)print ("Resultant output array: ", out_arr) |
Output :
1st Input array : [[ 2 -7 5] [-6 2 0]] 2nd Input array : [[ 0 -7 8] [ 5 -2 9]] Resultant output array: [[ 0 49 40] [-30 -4 0]]
