Eigenvalue algorithms demo

Simple command-line app to experiment with matrixes by finding its eigenvalues and eigenvectors

Table of contents

• General info
• Warning
• Technologies
• Features
• Setup
• Invocation Example

General info

At the start, this project was intended to be a university lab with the main purpose of finding eigenvalues and eigenvectors for two fixed matrixes. Additional features like support for CSV matrix input was added to increase the overall usability of the program and to further practice developing CLI command. The main goals of this project apart from being a university lab are improving skills and gaining knowledge related to OOP design, writing git commit messages, command-line program development using Picocli framework.

Warning

This project is intended for demonstration purposes only. This recommendation is based on a fact that there are a lot of inefficiencies related to algorithm implementation.

Technologies

Project is created with:

• Java 8
• EJML library version: 0.39
• Picocli framework version: 4.5.1
• Hibernate Validator library version: 6.0.2.Final
• Apache Commons Configuration 2 library version: 2.7

Project is tested with:

• JUnit 5

Features

• Input matrix in CSV
• Output results in CSV and simple text
• Support for 3 different algorithms: QR, Jacobi, Power iterations

Setup

To run this project, build it using Apache Maven version 3.3.9 or higher and add an alias to simplify command invocation:

$ cd ../demo-eigenvalue-algorithms
$ mvn package
$ alias evad='java -jar "target/eigenvalue-algorithms-demo-1.0-SNAPSHOT-jar-with-dependencies.jar"'

Invocation Example

In this example, we are trying to find eigenvalues and eigenvectors for a given matrix

$ cat matrix.csv
818,-287,-162,184,-383
-287,718,-161,10,3
-162,-161,667,-588,-239
184,10,-588,828,-4
-383,3,-239,-4,843
$ evad matrix.csv -a=QR
{1303.876326208391=[Type = DDRM , rows = 5 , cols = 1
-6.1204E-01 
 3.7468E-01 
-2.5538E-01 
 8.1375E-02 
 6.4279E-01 
], 759.8249095295616=[Type = DDRM , rows = 5 , cols = 1
-1.1415E-01 
 8.0006E-01 
-1.2018E-02 
 5.2663E-02 
-5.8648E-01 
], 1437.953099608692=[Type = DDRM , rows = 5 , cols = 1
 3.6142E-01 
 3.0977E-03 
-6.1439E-01 
 7.0129E-01 
 9.4443E-03 
], 340.2034610028594=[Type = DDRM , rows = 5 , cols = 1
-6.1459E-01 
-3.6715E-01 
 2.6206E-01 
 5.5248E-01 
-3.3700E-01 
], 32.14220364981876=[Type = DDRM , rows = 5 , cols = 1
 3.2254E-01 
 2.9105E-01 
 6.9892E-01 
 4.3996E-01 
 3.5945E-01 
]}