Remove interferences for testing, optimize main.py

This commit is contained in:
Quentin Legot 2023-03-31 10:21:49 +02:00
parent 9936d4f1b9
commit faeb49eb32
2 changed files with 18 additions and 21 deletions

View File

@ -8,53 +8,51 @@ nb_files = os.listdir(".." + os.sep + "export")
size = len(nb_files)
def mean_mkn() -> np.ndarray:
def mean_mkn(arr: list[tuple[int, np.ndarray]]) -> 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()
for nb_users, data in arr:
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, 0] = nb_users
averages_mkn[nb, 1] = average
nb += 1
return averages_mkn
def rb_available() -> np.ndarray:
def rb_available(arr: list[tuple[int, np.ndarray]]) -> np.ndarray:
available = np.zeros((size, 2))
nb = 0
for i in nb_files:
data = pd.read_csv(".." + os.sep + "export" + os.sep + i, delimiter=';').to_numpy()
nb_users = i.split(".")[0]
available[nb, 0] = int(nb_users)
for nb_users, data in arr:
available[nb, 0] = nb_users
available[nb, 1] = (data.shape[0] / (200 * 10000)) * 100
nb += 1
return available
def delay() -> np.ndarray:
def delay(arr: list[tuple[int, np.ndarray]]) -> np.ndarray:
delays = np.zeros((size, 2))
nb = 0
for i in nb_files:
data = pd.read_csv(".." + os.sep + "export" + os.sep + i, delimiter=';').to_numpy()
nb_users = i.split(".")[0]
for nb_users, data in arr:
d = data[:, 5]
for x in d:
delays[nb, 0] = int(nb_users)
delays[nb, 0] = nb_users
delays[nb, 1] = float(x)
nb += 1
return delays
averages = mean_mkn()
available = rb_available()
delays = delay()
np_arr: list[tuple[int, np.ndarray]] = list()
for i in nb_files:
np_arr.append((int(i.split(".")[0]), pd.read_csv(".." + os.sep + "export" + os.sep + i, delimiter=';').to_numpy()))
averages = mean_mkn(np_arr)
available = rb_available(np_arr)
delays = delay(np_arr)
delays.sort(axis=0)
# Data for plotting
averages.sort(axis=0)
@ -74,7 +72,6 @@ ax.set(xlabel='number of users', ylabel='RB utilisés', title='Pourcentage de RB
ax.grid()
plt.show()
fig, ax = plt.subplots()
ax.scatter(delays[:, 0], delays[:, 1])
ax.set(xlabel='number of users', ylabel='delays(ms)', title='Delay')

View File

@ -32,7 +32,7 @@ public class AccessPoint {
cell1.schedule(ticks);
cell2.schedule(ticks);
//simulation des interférences
computeInterference();
// computeInterference();
// traite les données et les enregistre dans un fichier
try {
cell1.analyseData(ticks, users);