ejemplo de código de multiplicación de matrices numpy

Ejemplo 1: Python numpy multiplicar matrices

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

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

Ejemplo 2: cómo hacer una multiplicación por elementos en numpy

numpy.multiply(arr1, arr2)

Ejemplo 3: como multiplicar matrices en python

>>> a = np.ones([9, 5, 7, 4])
>>> c = np.ones([9, 5, 4, 3])
>>> np.dot(a, c).shape
(9, 5, 7, 9, 5, 3)
>>> np.matmul(a, c).shape
(9, 5, 7, 3)
>>> # n is 7, k is 4, m is 3

Ejemplo 4: Python de multiplicación de matrices sin 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]

Ejemplo 5: multiplicación de matrices en python

>>> 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])

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