44 lines
913 B
Python
44 lines
913 B
Python
import os
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import matplotlib.pyplot as plt
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import numpy as np
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import pandas as pd
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nb_files = os.listdir(".." + os.sep + "export")
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size = len(nb_files)
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def mean_mkn() -> np.ndarray:
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averages_mkn = np.empty((size, 2))
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nb = 0
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for i in nb_files:
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data = pd.read_csv(".." + os.sep + "export" + os.sep + i, delimiter=';').to_numpy()
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rb = data[:, 4]
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total = 0.0
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for x in rb:
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total = total + x
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average = total / len(rb)
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nb_users = i.split(".")[0]
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averages_mkn[nb, 0] = int(nb_users)
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averages_mkn[nb, 1] = average
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nb += 1
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return averages_mkn
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averages = mean_mkn()
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# Data for plotting
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averages.sort(axis=0)
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x = averages[:, 0]
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y = averages[:, 1]
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print(averages)
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fig, ax = plt.subplots()
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ax.scatter(x, y)
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ax.set(xlabel='users', ylabel='ressources (RB)', title='MaxSNR')
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ax.grid()
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# fig.savefig("test.png")
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plt.show()
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