A project for Analyse Numérique, contains sample use cases of algorithms studied in the course
- Chapter 1: root finding algorithms (newton-raphson, dichotomie, point milieu) Used For: Detection of collisions between objects
- Chapter 2: Solving Linear Systems of Equations (lu, gauss, cholesky)
- Chapter 3: Solving Lineas Systems Of Equations (Numeric) (jacobi, gauss-seidel, relaxation) Used For: Finding the origin of a given vector can be applied in reversing the orientation of an image
- Chapter 4: Finding Eigen Values(puissance itérée, déflation, jacobi et rotation de givens) Used For: Image compression
- Chapter 5: interpolation (lagrange, différences divisés, différences finis) Used For: Creating smooth animations from keyframes
- Chapter 6: numerical integration (trapézes, simpson, trapézes composites, simpson composites) Used For: Image blurring
- Chapter 1 and 5 are put into one project as they are both utilized
- the source code of the algorithms is located under
server/src
install plumber, magick
run pip install -r requirements.py.txt located on each folder
make sure to install numpy and matplotlib using pip install numpy matplotlib
run npm install on the root folder
run npm run dev and visit the website at the specified address
Chapter 2 is on the Web site
for Chapter 1-5 run in the animation folder python animaton.py
for Chapter 3 run plot.py after setting the input in input.json if you prefer, else input the data after running the script
for Chapter 6 run Rscript console.r [image path] [sigma (default = 1)]
sample are provided with each chapter's code for ease of viewing