Two Types of Matrix Multiplication Using NumPy

How are two matrices multiplied according to the math rules: Khan Academy

(base) C:\Users\ashish>python
Python 3.7.1 (default, Dec 10 2018, 22:54:23) [MSC v.1915 64 bit (AMD64)] :: Anaconda, Inc. on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
>>> a = [[1, -1], [1, 2]]
>>> b = [[3], [4]]

>>> a * b
Traceback (most recent call last):
  File "[stdin]", line 1, in [module]
TypeError: can't multiply sequence by non-int of type 'list'

>>> a = np.array(a)
>>> b = np.array(b)

>>> a
array([[ 1, -1],
       [ 1,  2]])

>>> b
array([[3],
       [4]])

>>> np.matmul(a,b)
array([[-1],
       [11]])

>>> np.matmul(b, a)
Traceback (most recent call last):
  File "[stdin]", line 1, in [module]
ValueError: shapes (2,1) and (2,2) not aligned: 1 (dim 1) != 2 (dim 0)

>>> a.dot(b)
array([[-1],
       [11]])

>>> np.dot(a, b)
array([[-1],
       [11]])

>>> a.b
Traceback (most recent call last):
  File "[stdin]", line 1, in [module]
AttributeError: 'numpy.ndarray' object has no attribute 'b'

>>> np.dot(b, a)
Traceback (most recent call last):
  File "[stdin]", line 1, in [module]
ValueError: shapes (2,1) and (2,2) not aligned: 1 (dim 1) != 2 (dim 0)

# How about an element to element multiplication?
# Note: this is not how math books do it

>>> np.multiply(a, b)
array([[ 3, -3],
       [ 4,  8]])

>>> np.multiply(b, a)
array([[ 3, -3],
       [ 4,  8]])

>>> a*b
array([[ 3, -3],
       [ 4,  8]])

>>> a = [[1, 1], [2, 2]]
>>> b = [[0, 0], [1, 1]]
>>> a = np.array(a)
>>> b = np.array(b)
>>> a*b
array([[0, 0],
       [2, 2]])

>>> a = [[0, 1], [2, 3]]
>>> a = np.array(a)
>>> b = [[5, 10], [15, 20]]
>>> b = np.array(b)
>>> a*b
array([[ 0, 10],
       [30, 60]])
>>>

Ref: docs.scipy.org

Tags: Technology,Python,NumPy