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A collection of exercises about numerical algorithms in engineering in C for educational purposes

C 99.28% CMake 0.72%
gauss jacobi linear-algebra newton-polynomial-interpolation lagrange-polynomial-interpolation matplotlib-pyplot numpy linear-regression exponential-regression power-regression

numerical_algorithms_in_engineering's Introduction

TP Alg Num

To test TP_x, please navigate to the TP_x folder in shell or the command line terminal, then enter the following command (you might have to install GCC first):

  • to compile:

    gcc -Wall main.c -o main -lm
    
  • to execute:

    ./main
    

The related papers, in French:

Sujet_TP_1.pdf

Rapport_TP_1.pdf

Sujet_TP_2.pdf

Rapport_TP_2.pdf

Sujet_TP_3.pdf

Rapport_TP_3.pdf

If you are testing TP_2 specifically, you can have a *...poly.py file appear after execution. If you execute it from shell or cmd, a scatterplot of the initial input will appear together with the graph of the interpolated polynomial function. However, you might need to install Python 3, as well as the numpy, sympy, and matplotlib libraries

If you are testing TP_3 specifically, you can have a .py file appear after execution. If you execute it from shell or cmd, a scatterplot of the initial input will appear together with the graph of the regression curve. However, you might need to install Python 3, as well as the numpy, and matplotlib libraries

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