44.3: Review of Python Numpy Package

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from urllib.request import urlretrieve
urlretrieve('https://raw.githubusercontent.com/colbrydi/jupytercheck/master/answercheck.py', 
            'answercheck.py');

Do This

Watch the following video about the python Numpy package.

Direct Link to the Youtube video.

from IPython.display import YouTubeVideo
YouTubeVideo("_hbWtNgstlI",width=640,height=320, cc_load_policy=True)

The Python Numpy library has a matrix object which can be initialized as follows:

import numpy as np
A = np.matrix([[1,1], [20,25]])
b = np.matrix([[30],[690]])
print("A="+str(A))
print("b="+str(b))

A=[[ 1  1]
 [20 25]]
b=[[ 30]
 [690]]

Python can solve equations in the \(Ax=b\) format with the numpy.linalg library. For example:

import numpy as np

x = np.linalg.solve(A, b)
print("x="+str(x))

x=[[12.]
 [18.]]

The numpy.linalg library is just a subset of the scipy.linalg library.

import scipy.linalg as la

x = la.solve(A, b)
print("X="+str(x))

X=[[12.]
 [18.]]

Do This

Convert the following system of linear equations to numpy matrices and solve it sing a Python linear algebra solver (Store the solutions in a vector named x).

\(18x + 21y = 22672x - 3y = 644\)

##Put your answer to the above question here.

from answercheck import checkanswer

checkanswer.vector(x,'756ca9fa3951fad0e623b2a8315d5fd7');