NumPixel

NumPixel is an advanced numerical computing platform designed to elevate mathematical computations to new heights. With a sleek and intuitive user interface, real-time visualization tools, and a wide range of interpolation methods, NumPixel provides users with the precision and flexibility they need for complex mathematical analyses.

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Table of Contents

1. Introduction
2. Features
3. Getting Started
4. Usage
5. Interpolation Methods
6. Contributing
7. License

Introduction

NumPixel is developed as a modern solution for mathematical computations, offering users an efficient and user-friendly platform to perform numerical analyses. Whether you're a student, researcher, or professional, NumPixel empowers you to explore mathematical concepts, visualize data, and obtain precise results with ease.

Features

• Immaculate User Interface: Enjoy a well-crafted interface with intuitive layouts and easy-to-access features, providing seamless navigation and an enjoyable user experience.
• Real-time Visualization: Watch mathematical computations come to life with visually captivating real-time representations, including interactive graphs, dynamic updates, and high-quality rendering.
• Wide Range of Interpolation Methods: Explore a diverse array of interpolation methods integrated into the platform, offering precision and flexibility in mathematical computations.

Getting Started

To get started with NumPixel, follow these steps:

1. Clone the repository to your local machine.
2. Install the necessary dependencies using npm install.
3. Start the development server with npm run dev.
4. Run npm run node-sass to compile SCSS files.

Usage

Once you have NumPixel up and running, you can:

• Explore the various features and tools available in the user interface.
• Input your mathematical data and parameters to perform computations.
• Visualize your data in real-time and analyze the results with ease.

Interpolation Methods

NumPixel offers a wide range of interpolation methods, including:

• Newton's Forward
• Stirling's Forward
• Gauss's Forward
• Newton's Backward
• Stirling's Backward
• Gauss's Backward
• Lagrange
• Hermite
• Divided Differences
• Central Difference

Contributing

Welcome for contributions to enhance NumPixel and make it even more powerful. If you'd like to contribute, please follow these guidelines:

1. Fork the repository and create your branch.
2. Make your contributions and ensure they adhere to the project's coding standards.
3. Submit a pull request, describing the changes you've made and their purpose.

License

NumPixel is licensed under the MIT License.