🚧 This repository is under a major restructuration 🚧
In this repository, you will find Python implementations of commonly used numerical methods. These algorithms are useful for solving a wide range of mathematical problems, including linear algebra, optimization, interpolation, and differential equations. This repository is an active personal project, therefore new numerical methods will be soon uploaded.
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| | By: ruesga-99 | |
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| ___ ___ ___ ___ | | \ | |_ _ _ __ ___ ___ _ __(_) ___ __ _| |
| | 7 | 8 | 9 | | + | | | \| | | | | '_ ` _ \ / _ \ '__| |/ __/ _` | |
| |___|___|___| |___| | | |\ | |_| | | | | | | __/ | | | (_| (_| | |
| | 4 | 5 | 6 | | - | | |_| \_|\__,_|_| |_| |_|\___|_| |_|\___\__,_|_|
| |___|___|___| |___| | | \/ | ___| |_| |__ ___ __| |
| | 1 | 2 | 3 | | x | | | |\/| |/ _ \ __| '_ \ / _ \ / _` / __|
| |___|___|___| |___| | | | | | __/ |_| | | | (_) | (_| \__ \
| | . | 0 | = | | / | | |_| |_|\___|\__|_| |_|\___/ \__,_|___/
| |___|___|___| |___| |
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🧮 Errors:
- ✅ Mean Squared Error
- Root Mean Squared Error
- 📆 Mean Absolut Error
- 📆 Mean Absolut Percentage Error
🧮 Root Finding:
- ✅ Bisection Method (Polynomial Functions)
- ✅ Regula Falsi / False Position Method (Polynomial Functions)
- 📆 Fixed Point Iteration
- 📆 Newton-Rapshon
🧮 Linear Interpolation and Curve Fitting:
- ✅ Lagrange's Polynomial
- ✅ Newton's Divided Differences
- ✅ Newton's Finite Differences
- ✅ Least Squares
🧮 Ordinary Differential Equations with IVP:
- ✅ Euler's Method
- ✅ Heun's Method (Improved Euler's Method)
- ✅ Runge-Kutta Method (RK4)
🧮 Matrix and Systems of Linear Equations:
- ✅ Matrix Class (Squared Matrix)
- 💡 Rectangular Matrix Class
- 📆 Cramer's Rule
- 📆 Gaussian Elimination
- 📆 Gauss-Jordan Method
- 📆 Gauss-Seidel Method
- 📆 Jacobi's Method
- 📆 Gauss-Zamora Method
- 📆 Crout's Method (QR Descomposition)
- 📆 Doolittle's Method (LU Descomposition)
🧮 Numerical Integration:
- 🚧 Closed Newton-Cotes
- 📆 Open Newton-Cote
💡 Numerical Differentiation: (Planning Ongoing)
💡 Partial Differential Equations: (Planning Ongoing)
💡 Nonlinear Optimization: (Planning Ongoing)
🧮 Others:
- ✅ Numeric Errors
- 📆 Tabular Form of the Function
- ✅ Collatz Conjecture (3n+1)
- 🚧 Advanced Operations
Make sure you have the following installed:
- Python 3.x (I'm using 3.12)
This project uses the following Python libraries:
- numpy 2.0.0
- pandas 2.2.2
- matpolib 3.9.0
pip install numpy==2.0.0 pandas==2.2.2 matplotlib==3.9.0
✅ (Completed): This emoji is used to mark tasks that have been finished and require no further work.
📆 (Planned): This emoji is used for tasks that are planned for the future, indicating they are on the work calendar. The corresponding file does not exist within the repository.
🚧 (Under Construction): This emoji indicates tasks that have been implemented but still need further improvements or adjustments. There is already a corresponding file within the repository but hasn't been fully developed.
💡 (Planning Ongoing): This emoji is used for sections that haven't been completely defined on their components.
To use these numerical methods, simply clone the repository and import the desired method into your Python environment. Each method is contained in its own module for easy integration into your projects.
Contributions to this repository are welcome! If you have implemented a numerical method in Python that you would like to share, please feel free to submit a pull request. Your contributions will help make this repository a valuable resource for the community. Different aproaches to an already submitted numerical method just as more efficient algorithms are also apreciated.