pyreda 0.1.5

A Python Library for Building the Genetic Algorithm.

pyreda

pyreda is a Python library for implementing and running Genetic Algorithms (GAs). It provides an easy-to-use interface to configure and execute GAs with customizable parameters for selection, crossover, and mutation.

Features

• Customizable fitness functions
• Support for tournament selection
• One-point crossover
• Bit-flip mutation
• Configurable mutation rates and number of generations

Installation

You can install pyreda via pip:

pip install pyreda

Usage

Here’s a basic example of how to use pyreda to run a genetic algorithm:

import SimpleGA from pyreda

from pyreda import SimpleGA
import numpy as np

Define a custom fitness function

# Example: Sum of all genes
def custom_fitness(individual):
	return np.sum(individual)

Create an instance of the SimpleGA class

ga = SimpleGA.SimpleGA(
	population_size=10,       # Size of the population
	gene_length=5,             # Length of each individual
	fitness_function=custom_fitness,  # Fitness function to evaluate individuals
	mutation_rate=0.01,        # Mutation rate
	generations=20            # Number of generations to evolve
)

Parameters:

population_size: Number of individuals in the population.
gene_length: Length of the individual’s gene sequence.
fitness_function: Function to evaluate the fitness of an individual.
mutation_rate: Probability of mutation for each gene.
generations: Number of generations for the algorithm to run.

Run the genetic algorithm

ga.run()

Contributing

If you’d like to contribute to the development of pyreda, please fork the repository and submit a pull request. We welcome improvements and bug fixes.

License

pyreda is licensed under the MIT License. See the LICENSE file for details.

Contact

For questions or support, please contact Reda Ghanem at [e-mail].