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A comprehensive set of core numerical methods used in engineering and applied mathematics

Project description

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:

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.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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