Matrix Multiplication in pure Python?

matrix-multiplication, python

Solution

If you really don't want to use `numpy` you can do something like this:

def matmult(a,b):
    zip_b = zip(*b)
    # uncomment next line if python 3 : 
    # zip_b = list(zip_b)
    return [[sum(ele_a*ele_b for ele_a, ele_b in zip(row_a, col_b)) 
             for col_b in zip_b] for row_a in a]

x = [[1,2,3],[4,5,6],[7,8,9],[10,11,12]]
y = [[1,2],[1,2],[3,4]]

import numpy as np # I want to check my solution with numpy

mx = np.matrix(x)
my = np.matrix(y)

Result:

>>> matmult(x,y)
[[12, 18], [27, 42], [42, 66], [57, 90]]
>>> mx * my
matrix([[12, 18],
        [27, 42],
        [42, 66],
        [57, 90]])

Problem

I'm trying to multiply two matrices together using pure Python. Input (`X1` is a 3x3 and `Xt` is a 3x2): ``` X1 = [[1.0016, 0.0, -16.0514], [0.0, 10000.0, -40000.0], [-16.0514, -40000.0, 160513.6437]] Xt = [(1.0, 1.0), (0.0, 0.25), (0.0, 0.0625)] ``` where Xt is the zip transpose of another matrix. Now here is the code: ``` def matrixmult (A, B): C = [[0 for row in range(len(A))] for col in range(len(B[0]))] for i in range(len(A)): for j in range(len(B[0])): for k in range(len(B)): C[i][j] += A[i][k]*B[k][j] return C ``` The error that python gives me is this: IndexError: list index out of range. Now I'm not sure if `Xt` is recognised as an matrix and is still a list object, but technically this should work.

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