Python 3: Multiply a vector by a matrix without NumPy

I think the problem with your code was that you loop through the rows of the matrix rather than by the columns. Also you don't reset your 'total' variable after each vector*matrix column calculation. This is what you want:

def multiply(v, G):
    result = []
    for i in range(len(G[0])): #this loops through columns of the matrix
        total = 0
        for j in range(len(v)): #this loops through vector coordinates & rows of matrix
            total += v[j] * G[j][i]
        result.append(total)
    return result

i have attached a code for matrix multiplication do follow the example format for one dimensional multiplication (lists of list)

def MM(a,b):
c = []
for i in range(0,len(a)):
    temp=[]
    for j in range(0,len(b[0])):
        s = 0
        for k in range(0,len(a[0])):
            s += a[i][k]*b[k][j]
        temp.append(s)
    c.append(temp)

return c
a=[[1,2]]
b=[[1],[2]]
print(MM(a,b))

result is [[5]]

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]