numpy.multiply() in Python
Last Updated :
16 May, 2020
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 :
import numpy as geek
in_num1 = 4
in_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)
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Output :
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.
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)
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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]]
Another way to find the same is
import numpy as geek
in_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)
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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]]
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