numerical-methods-python
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Numerical methods implementation in Python.
Numerical Methods
Numerical methods implementation in Python.
For the implementation in MATLAB, see this repository.
Getting Started
Prerequisites
Using Conda (recommended)
conda env create
conda activate numerical-methods-env
Using Pip
pip install -r requirements.txt
Using Ubuntu
This section assumes Ubuntu 16.04 (also tested on Ubuntu 22.04), but the procedure is similar for other Linux distributions.
sudo apt -y install python3-numpy
Running the examples
To run the main example, use:
python3 main.py
Implementations
Solutions of equations
- Bisection method
- Newton method
- Secant method
Interpolation
- Lagrange method
- Neville method
Algorithms for polynomials
- Briot-Ruffini method
- Newton's Divided-Difference method
Numerical differentiation
- Backward-difference method
- Three-Point method
- Five-Point method
Numerical integration
- Composite Trapezoidal method
- Composite 1/3 Simpson's method
Initial-value problems for ordinary differential equations
- Euler's method
- Taylor's (Order Two) method
- Taylor's (Order Four) method
- Runge-Kutta (Order Four) method
Systems of differential equations
- Runge-Kutta (Order Four) method
Methods for Linear Systems
- Gaussian Elimination
- Backward Substitution
- Forward Substitution
Iterative Methods for Linear Systems
- Jacobi method
- Gauss-Seidel method