🔢 BSM Numerical Analysis Toolkit

A comprehensive computational mathematics toolkit for solving linear systems, finding roots, and numerical integration

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📋 Overview

This project implements fundamental numerical analysis algorithms with an interactive terminal-based interface. Built for educational purposes, it provides robust implementations of classical numerical methods taught in computational mathematics courses.

✨ Features

🔷 Linear System Solvers

• Gaussian Elimination - Forward elimination with back substitution
• Gauss-Jordan - Row reduction to reduced row echelon form
• GEMPS (Gaussian Elimination with Maximum Partial Pivoting and Scaling)
• MOSS (Method of Successive Substitutions)

🎯 Root Finding Methods

• Half-Interval Method (Bisection Method)
• Newton's Method (Newton-Raphson)
• Method of Successive Substitution (Fixed-Point Iteration)

📊 Numerical Integration

• Trapezoidal Rule - Composite trapezoidal approximation
• Romberg's Method - Richardson extrapolation for high accuracy

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🚀 Getting Started

Prerequisites

• Python 3.13+
• Virtual environment (recommended)

Installation

1. Clone the repository

   git clone https://github.com/Charles787205/BSMProject.git
   cd BSMProject

2. Activate virtual environment

   # Windows
   .\Scripts\activate
   
   # Linux/Mac
   source Scripts/bin/activate

3. Install dependencies

   pip install -r requirements.txt

Running the Application

cd project_files
python main.py

The application will launch in fullscreen mode with an interactive menu system.

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🎮 Usage

Navigate through the terminal interface using:

• Arrow keys or number keys to select methods
• Enter to confirm selection
• Follow on-screen prompts for input

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📦 Dependencies

• pyautogui - GUI automation and fullscreen control
• windows-curses - Terminal UI library (Windows)
• prettytable / tabulate - Formatted output tables
• Pillow - Image processing support
• Additional utilities for enhanced terminal experience

See requirements.txt for complete list.

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🎓 Educational Context

Developed as part of a Numerical Analysis course, this project demonstrates:

• Implementation of classical numerical algorithms
• Computational complexity considerations
• Error analysis and numerical stability
• Interactive educational software design

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👥 Authors

BSM Project Team

• Repository: Charles787205/BSMProject

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📝 License

This project is available for educational purposes.

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Built with 💻 for Numerical Analysis

Learning mathematics through code