Metadata-Version: 2.4
Name: numeth
Version: 0.1.5
Summary: A set of core numerical methods used in engineering and applied mathematics
Author-email: Abhisumat Kundu <kunduabhisumat@gmail.com>
License: MIT License
        
        Copyright (c) 2025 Numeth
        
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Project-URL: Repository, https://github.com/AbhisumatK/numeth-Numerical-Methods-Library
Keywords: numerical methods,scientific computing,engineering,applied mathematics,numerical,numeric
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Dynamic: license-file

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</p>

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# numeth

A fully functional Python package implementing core numerical methods for engineering and applied mathematics. Designed for usability and educational clarity.

## Installation

Install via pip:

```
pip install numeth
```

## Quick Start

Here's a simple example using the Newton-Raphson method to find the square root of 2:

```python
from numeth import newton_raphson

def f(x):
    return x**2 - 2

def df(x):
    return 2 * x

root, iterations, converged = newton_raphson(f, df, x0=1.0, tol=1e-6, max_iter=100)
print(f"Root: {root}, Iterations: {iterations}, Converged: {converged}")
# Output: Root: 1.414213562373095, Iterations: 4, Converged: True
```

## Supported Methods

### Integration
- Trapezoidal Rule (single and composite)
- Simpson’s 1/3 Rule (single and composite)
- Simpson’s 3/8 Rule
- Gaussian Quadrature (2-point and 3-point)

### Differentiation
- Forward difference (first derivative)
- Backward difference (first derivative)
- Central difference (first derivative)
- Central difference (second derivative)
- Richardson extrapolation (first derivative)

### Root Finding
- Bisection Method
- Newton-Raphson Method
- Secant Method
- False Position Method

### Interpolation
- Linear Interpolation
- Lagrange Interpolation
- Newton’s Divided Difference Interpolation

### Linear Algebra
- Gauss Elimination with partial pivoting
- LU Decomposition (Doolittle’s method)
- Jacobi Iterative Method
- Gauss-Seidel Iterative Method

### Optimization
- Golden Section Search (minimization)
- Newton’s Method for Optimization (1D)

## How to Contribute or Report Issues

Contributions are welcome! Please submit pull requests or open issues on the [GitHub repository](https://github.com/AbhisumatK/numeth-Numerical-Methods-Library).

## License

This project is licensed under the MIT License - see the [LICENSE](https://github.com/AbhisumatK/numeth-Numerical-Methods-Library/blob/main/LICENSE) file for details.
