optymus 0.1.1

Optimization Methods Library

Welcome to optymus, the Optimization Methods Library for Python! This library provides a comprehensive collection of optimization methods, both with and without constraints, implemented in the Python programming language.

Table of Contents

• Introduction
• Getting Started
• Content
• Contributions
• License

Introduction

optymus is designed to empower users with a versatile set of optimization tools, facilitating the search for optimal solutions in various problem domains. This library covers a range of optimization methods, making it suitable for diverse applications in computer science and engineering.

Getting Started

To begin using optymus, follow these steps:

1. Install optymus:

   pip install --upgrade optymus
   

2. Explore the Documentation: Visit the official documentation to understand the available optimization methods and how to use them effectively.

3. Get Started:

   from optymus.minimize import Optimizer
   
   import numpy as np
   f = lambda x: x[0]**[2]-3*x[0]*x[1]+4*x[1]**2+x[0]-x[1]
   grad = lambda x: np.array([2*x[0]-3*x[1]+1, -3*x[0]+8*x[1]-1])
   hess = lambda x: np.array([[2, -3], [-3, 8]])
   initial_point = np.array([2, 2])
   
   optimizer = Optimizer(f_obj=f,
                        x0=initial_point,
                        grad=grad,
                        hess=hess,
                        method='bfgs')
   
   optimizer.report()
   
   optimizer.plot()
   

Content

optymus includes a rich set of optimization methods, such as:

• Unconstrained Optimization Methods
• Constrained Optimization Methods
• Global Optimization
• Gradient Descent
• Evolutionary Algorithms

Refer to the documentation for detailed information on each method and its application.

Contributions

Contributions to Optymus are highly appreciated! If you have additional optimization methods, improvements, or bug fixes, please submit a pull request following the contribution guidelines.

License

Optymus is licensed under the MIT License, allowing you to use, modify, and distribute the library for both commercial and non-commercial purposes.

Start optimizing with Optymus and unlock the potential for finding optimal solutions in your Python projects!