A 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.
Project details
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