import os
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

nb_files = os.listdir(".." + os.sep + "export")

size = len(nb_files)


def mean_mkn() -> np.ndarray:
    averages_mkn = np.empty((size, 2))
    nb = 0
    for i in nb_files:
        data = pd.read_csv(".." + os.sep + "export" + os.sep + i, delimiter=';').to_numpy()
        rb = data[:, 4]

        total = 0.0
        for x in rb:
            total = total + x
        average = total / len(rb)
        nb_users = i.split(".")[0]
        averages_mkn[nb, 0] = int(nb_users)
        averages_mkn[nb, 1] = average
        nb += 1
    return averages_mkn


averages = mean_mkn()
# Data for plotting
averages.sort(axis=0)
x = averages[:, 0]
y = averages[:, 1]

print(averages)
fig, ax = plt.subplots()
ax.scatter(x, y)

ax.set(xlabel='users', ylabel='ressources (RB)', title='MaxSNR')
ax.grid()

# fig.savefig("test.png")
plt.show()