main.py

#!/usr/bin/python3

from time import time

import pandas as pd
from scipy.stats import kendalltau

from algorithms.EM import em
from algorithms.PageRank import page_rank
from algorithms.borda_ordering import borda_ordering
from algorithms.random_circle_removal import random_circle_removal
from utils.gradings import get_gradings


def experiment(n, k_list, repetition):
    algos = [random_circle_removal, page_rank, em, borda_ordering]
    algo_names = ['Random Priority', 'Random Walk', 'EM', 'Order Score']

    df = pd.DataFrame(columns=['n', 'k', 'rep', 'algo', 'time', 'distance', 'ranking'])
    for rep in range(repetition):
        for k in k_list:
            gradings = get_gradings(n, k)
            for j in range(len(algos)):
                start = time()
                ranking = algos[j](gradings)
                duration = time() - start
                df.loc[df.index.size] = [n, k, rep, algo_names[j], duration,
                                         kendalltau(list(range(1, n + 1)), ranking)[0], str(ranking)]

        df.to_csv('./out/results_n_{}_k_{}.csv'.format(n, str(k_list)), index=False)



if __name__ == '__main__':
    repetition = 2
    n = 100
    k_list = [6, 8]

    experiment(n, k_list, repetition)