python numpy matrix multiplication code example

Example 1: python numpy multiply matrices

a = np.array([[-6, 1], [1, 1]])
b = np.array([[0], [8]])

c = a.dot(b) # multiply matrice a and b

Example 2: matrix multiplication python without numpy

The Numpythonic approach: (using numpy.dot in order to get the dot product of two matrices)

In [1]: import numpy as np

In [3]: np.dot([1,0,0,1,0,0], [[0,1],[1,1],[1,0],[1,0],[1,1],[0,1]])
Out[3]: array([1, 1])
The Pythonic approach:

The length of your second for loop is len(v) and you attempt to indexing v based on that so you got index Error . As a more pythonic way you can use zip function to get the columns of a list then use starmap and mul within a list comprehension:

In [13]: first,second=[1,0,0,1,0,0], [[0,1],[1,1],[1,0],[1,0],[1,1],[0,1]]

In [14]: from itertools import starmap

In [15]: from operator import mul

In [16]: [sum(starmap(mul, zip(first, col))) for col in zip(*second)]
Out[16]: [1, 1]

Example 3: matrix multiplication in python

# input two matrices of size n x m 
matrix1 = [[12,7,3], 
        [4 ,5,6], 
        [7 ,8,9]] 
matrix2 = [[5,8,1], 
        [6,7,3], 
        [4,5,9]] 
  
res = [[0 for x in range(3)] for y in range(3)]  
  
# explicit for loops 
for i in range(len(matrix1)): 
    for j in range(len(matrix2[0])): 
        for k in range(len(matrix2)): 
  
            # resulted matrix 
            res[i][j] += matrix1[i][k] * matrix2[k][j] 
  
print (res)

Example 4: python matrix multiplication

>>> a = np.array([[ 5, 1 ,3], 
                  [ 1, 1 ,1], 
                  [ 1, 2 ,1]])
>>> b = np.array([1, 2, 3])
>>> print a.dot(b)
array([16, 6, 8])