sequential.py

from genetic_clustering import ClusteringSolution, Point2D, random_index, crossover, mutation
from data import small_dataset_0, generate_dataset, plot_clusters
from itertools import permutations

def sequential_execution(
    dataset: list[tuple], number_of_solutions: int, generations: int, 
    mutation_rate: int, number_of_clusters: int,
):
    """
    Runs the genetic algorithm in a sequential way with a given dataset and parameters.

    Args:
    dataset (list[tuple]): Dataset to use, each tuple representing a point (x, y).
    number_of_solutions (int): Number of solutions in the population.
    generations (int): Number of generations for the genetic algorithm.
    mutation_rate (int): Mutation rate for the genetic algorithm.
    number_of_clusters (int): Number of clusters to form.
    """


    # We cast all point as Point2D objects to be able to use the distance method
    points = [Point2D(x, y) for x, y in dataset]

    # Permutations allows to map a cluster index to another cluster index, for example, (0, 1, 2, 3) -> (3, 2, 1, 0)
    clusters_permutations: list[tuple] = list(
        permutations(list(range(number_of_clusters)))
    )

    # Initialialization
    population: list[ClusteringSolution] = sorted(
        [
            ClusteringSolution.create_random(points, number_of_clusters)
            for i in range(number_of_solutions)
        ],
        key=lambda s: s.quality,
        reverse=True,
    )

    print("Initial solution value : ", population[0].quality)

    for generation_iteration in range(generations):

        good_solution = population[
            random_index(len(population), len(population) // 2, top=True)
        ]
        bad_solution = population[
            random_index(len(population), len(population) // 2, top=False)
        ]
        child_solution = crossover(
            good_solution, bad_solution, clusters_permutations, points
        )
        child_solution = mutation(
            child_solution, mutation_rate, number_of_clusters, points
        )

        random_bad_solution_idx = random_index(
            len(population), len(population) // 2, top=False
        )
        population[random_bad_solution_idx] = child_solution
        population = sorted(population, key=lambda s: s.quality, reverse=True)
        print(
            "Solution value for iteration {}: {}".format(
                generation_iteration, population[0].quality
            )
        )

    print("Final solution value : ", population[0].quality)

    return points, population[0], number_of_clusters


if __name__ == "__main__":
    import sys
    # Check if at least one additional argument is provided
    if len(sys.argv) > 1:
        # Access the first argument (after the script name)
        first_arg = sys.argv[1]

        # Perform different actions based on the argument
        if first_arg == "test":
            # Parameters
            number_of_solutions = 50
            generations = 80
            mutation_rate = 5
            number_of_clusters = 4
            number_of_tasks = 8

            #%%
            points, solution, number_of_clusters = sequential_execution(
                small_dataset_0, number_of_solutions, generations, mutation_rate, number_of_clusters
            )
            plot_clusters(points, solution.assignments, number_of_clusters)
        elif first_arg == "random":
            number_of_clusters = 5

            large_dataset = generate_dataset(num_centers=number_of_clusters, min_points=2, max_points=10)

            # print size of dataset
            print('dataset size', len(large_dataset))


            number_of_solutions = 50
            generations = 200
            mutation_rate = 5

            number_of_tasks = 8

            points, solution, number_of_clusters = sequential_execution(
                large_dataset, number_of_solutions, generations * number_of_tasks, mutation_rate, number_of_clusters
            )
            plot_clusters(points, solution.assignments, number_of_clusters)
        else:
            print("Invalid argument")
    else:
        print("No arguments provided")