suchi-teki: Numerical Analysis Toolkit

suchi-teki is a cross-platform mobile application that solves various numerical analysis problems. It features a Flutter-based UI and a Python backend (using FastAPI, numpy, scipy, and sympy) to implement key methods from numerical analysis, including root-finding algorithms, numerical quadrature, and numerical methods for solving ODEs.

Features

Root-Finding Algorithms:
- Newton-Raphson
- Fixed-Point Iteration
- Secant Method
- Regular Falsi
- Bisection Method
- Durand-Kerner Method
Numerical Quadrature:
- Trapezoidal Rule
- Simpson's Rule
- Finite Method (PDE)
Numerical Methods for ODEs:
- Euler’s Method
- Backward Euler Method
- Trapezoidal Rule
- Runge-Kutta Methods
- Runge-Kutta-Fehlberg Method

Tech Stack

Frontend (Flutter)

Dart: For building a cross-platform mobile app.
Provider or Riverpod: For state management.
http: To handle communication with the backend (Python FastAPI).

Backend (Python)

FastAPI: A modern, fast web framework for building APIs.
Numpy: For numerical operations.
Scipy: For scientific computing.
Sympy: For symbolic mathematics.
Uvicorn: For running the FastAPI server.

Other Tools

Pytest: For testing the backend algorithms.
Matplotlib: Optional for visualizing the numerical solutions.
Docker: Optional for containerizing the application.

Getting Started

Prerequisites

Flutter: Install Flutter
Python 3.8+: Install Python

Backend Setup (Python)

Clone the repository:

git clone https://github.com/your-username/suchi-teki.git
cd suchi-teki/backend

Set up environmenet and install dependencies:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt

Run the FastAPI backend:
```
fastapi dev backend/app/main.py
```

Frontend Setup (Flutter)

Navigate to working directory
Install flutter dependencies
```
flutter pub get
```
Run the App
```
flutter run
```

This README.md gives an overview of the project structure and instructions to set up the backend and frontend.

black-coda/suchi_teki