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Using numpyThe NumPy library is very helpful for solving linear systems in python. For how to install NumPy look here

Matrixes in Python

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language	py
title	Creating a matrix

a = np.array([[1,2],[3,4]])

In Python rows and columns start at 0. For example index the data at first row second column :

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language	py
title	Indexing

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matrix

b = a[0,1]

Linear algebra using NumPy

NumPy has several useful functions for linear algebra built-in. For full list look check the NumPy documentation.

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language	py
title	Solve()
collapse	true

np.linalg.solve(a,b) #where a and b is matrixs


#returns a array with solutions to the system

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language	py
title	Eigenvalues and eigenvectors
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np.linalg.eig(a) # where a is a square matrix


#returns two arrays [v,w]
#v containing the eigenvalues of a
#w containing the eigenvectors of a

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language	py
title	Determinant
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np.linalg.det(a) # where a is a square matrix


#returns the determinant of the matrix a

Example

Code Block

language	py
title	Solving set of equations

import numpy as np

# Solving following system of linear equation
# 5a + 2b = 35
# 1a + 4b = 49

a = np.array([[5, 2],[1,4]]) # Lefthand-side of the equation
b = np.array([35, 94]) #Righthand-side

print(np.linalg.solve(a,b)) #Printing the solution

Eigenvalues and Eigenvectors

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Matrixes in Python

Linear algebra using NumPy

Eigenvalues and Eigenvectors

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