natureAlgo 0.1.0

Nature Based Algorithm Library

natureAlgo: Nature-Inspired Optimization Library

natureAlgo is a Python library for nature-inspired optimization algorithms. It provides implementations of optimization algorithms inspired by the behavior of natural systems, such as bees. It was created as a demo library to understand how to publish libraries to pypi.

Features

• Implementation of the Artificial Bee Colony (ABC) algorithm.

• Easily extendable for adding more nature-inspired optimization algorithms.

Installation

You can install natureAlgo via pip:

pip install natureAlgo

Usage

import pandas as pd

import numpy as np

from natureAlgo import bee_colony



# Create a sample DataFrame for optimization

data = pd.DataFrame(np.random.rand(10, 2), columns=['Feature1', 'Feature2'])



# Define the objective function

def objective_function(x):

    return sum([x_i ** 2 for x_i in x])



# Initialize the ABC algorithm

abc = bee_colony.ArtificialBeeColony(data, objective_function, max_iterations=100, num_employed=10, num_onlookers=10)



# Run the ABC algorithm

abc.run()



# Get the best solution and its fitness

best_solution = abc.best_solution

best_fitness = abc.best_fitness



print("Best solution:", best_solution)

print("Best fitness:", best_fitness)

Contributing

Contributions are welcome! If you have ideas for new features, improvements, or bug fixes, feel free to open an issue or submit a pull request.

License

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

Credits

The ABC algorithm implementation and README.md template were provided by OpenAI's ChatGPT.