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Commit 94f38d6a authored by Your Name's avatar Your Name
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Fix

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with 86 additions and 55 deletions
openairinterface5g/carlos_mestrado/medicoes/script_plot_mestrado.py
+ 86
− 55
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......@@ -8,72 +8,103 @@ main_folder = "./"
scenarios = [name for name in os.listdir(main_folder) if os.path.isdir(os.path.join(main_folder, name))]
print(scenarios)
scenarios = sorted(
scenarios,
key=lambda x: (
x != "no_slicing", # Garante que "no_slicing" venha no final
int(x.split('_')[-1]) if x.startswith('scen_') and x.split('_')[-1].isdigit() else float('inf')
)
)
ue_dataframes = {}
for scenario in scenarios:
ue_dataframes[scenario] = {}
scenario_path = main_folder + scenario
ues = [name for name in os.listdir(scenario_path) if os.path.isdir(os.path.join(scenario_path, name))]
for ue in ues:
data = []
cap_confs = [name for name in os.listdir(scenario_path) if os.path.isdir(os.path.join(scenario_path, name))] ## Configuração da capacidade dos slices
for cap_conf in cap_confs:
ue_dataframes[scenario][cap_conf] = {}
cap_path = scenario_path + '/' + cap_conf
ues = [name for name in os.listdir(cap_path) if os.path.isdir(os.path.join(cap_path, name))]
for ue in ues:
data = []
ue_path = cap_path + '/' + ue + '/' + 'job_1.txt'
##Organização do dataframe
# Caminho de cada usuário
with open(ue_path, 'r') as file:
count = 0
data.append({
"Interval": 0,
"Transfer": 0,
"Bandwidth": 0,
"Jitter": 0,
"Packet loss (%)": 0
})
for line in file:
if "[ 3]" in line and "sec" in line and "MBytes" in line:
parts = line.split()
count += 1
if count < 10:
data.append({
"Interval": count,
"Transfer": parts[5],
"Bandwidth": float(parts[7]),
"Jitter": parts[9] if len(parts) > 6 else None,
"Packet loss (%)": float(parts[-1].strip("()%"))
})
elif count <= 60:
data.append({
"Interval": count,
"Transfer": parts[4],
"Bandwidth": float(parts[6]),
"Jitter": parts[8] if len(parts) > 6 else None,
"Packet loss (%)": float(parts[-1].strip("()%"))
})
else:
break
print(ue)
ue_dataframes[scenario][cap_conf][ue] = pd.DataFrame(data)
pl_ue1 = []
pl_ue2 = []
ue_path = scenario_path + '/' + ue + '/' + 'job_1.txt'
for scenario in scenarios:
scenario_path = main_folder + scenario
cap_confs = [name for name in os.listdir(scenario_path) if os.path.isdir(os.path.join(scenario_path, name))] ## Configuração da capacidade dos slices
cap_confs = sorted(cap_confs, key=lambda x: (x == 'no_slicing', x))
for cap_conf in cap_confs:
plt.plot(ue_dataframes[scenario][cap_conf]['ue2']["Interval"], ue_dataframes[scenario][cap_conf]['ue2']["Bandwidth"], marker="o", label="UE2", color = "blue")
plt.plot(ue_dataframes[scenario][cap_conf]['ue1']["Interval"], ue_dataframes[scenario][cap_conf]['ue1']["Bandwidth"], marker="o", label="UE2", color = "red")
y_ticks = np.arange(0, max(ue_dataframes[scenario][cap_conf]['ue2']["Bandwidth"].max(),
ue_dataframes[scenario][cap_conf]['ue1']["Bandwidth"].max()) + 10, 2) # Intervalo de 2 Mbps
plt.yticks(y_ticks) # Define os valores do eixo Y com intervalos mais detalhados
plt.title(scenario)
plt.xlabel("Time (s)")
plt.ylabel("Bandwidth (Mbps)")
plt.grid(True)
plt.legend()
plt.tight_layout()
pl_ue1.append(ue_dataframes[scenario][cap_conf]['ue1']["Packet loss (%)"].mean())
pl_ue2.append(ue_dataframes[scenario][cap_conf]['ue2']["Packet loss (%)"].mean())
print(ue_path)
# Organização do dataframe
plt.show()
with open(ue_path, 'r') as file:
count = 0
data.append({
"Interval": 0,
"Transfer": 0,
"Bandwidth": 0,
"Jitter": 0,
"Lost/Total Datagrams": 0
})
for line in file:
if "[ 3]" in line and "sec" in line and "MBytes" in line:
parts = line.split()
count += 1
if count < 10:
data.append({
"Interval": count,
"Transfer": parts[5],
"Bandwidth": float(parts[7]),
"Jitter": parts[9] if len(parts) > 6 else None,
"Lost/Total Datagrams": parts[-2] if '/' in parts [-2] else parts[-3] + parts[-2]
})
elif count <= 60:
data.append({
"Interval": count,
"Transfer": parts[4],
"Bandwidth": float(parts[6]),
"Jitter": parts[8] if len(parts) > 6 else None,
"Lost/Total Datagrams": parts[-2] if '/' in parts [-2] else parts[-3] + parts[-2]
})
else:
break
# Criação do DataFrame
ue_dataframes[scenario][ue] = pd.DataFrame(data)
# Configurar a posição das barras no eixo x
x = np.arange(len(cap_confs)) # Posições das scenarios
print(x)
largura = 0.4 # Largura das barras
print(ue_dataframes['no_slicing']['ue2']["Bandwidth"])
for scenario in scenarios:
plt.plot(ue_dataframes[scenario]['ue2']["Interval"], ue_dataframes[scenario]['ue2']["Bandwidth"], marker="o", label="Bandwidth", color = "blue")
plt.plot(ue_dataframes[scenario]['ue1']["Interval"], ue_dataframes[scenario]['ue1']["Bandwidth"], marker="o", label="Bandwidth", color = "red")
y_ticks = np.arange(0, max(ue_dataframes[scenario]['ue2']["Bandwidth"].max(),
ue_dataframes[scenario]['ue1']["Bandwidth"].max()) + 10, 2) # Intervalo de 2 Mbps
plt.yticks(y_ticks) # Define os valores do eixo Y com intervalos mais detalhados
plt.title(scenario)
plt.xlabel("Time (s)")
plt.ylabel("Bandwidth (Mbps)")
plt.grid(True)
plt.legend()
plt.tight_layout()
# Criar as barras
plt.bar(x - largura / 2, pl_ue1, width=largura, label='UE1', color='red') # Barras para UE1
plt.bar(x + largura / 2, pl_ue2, width=largura, label='UE2', color='blue') # Barras para UE2
#Exibe o gráfico
# Adicionar rótulos e título
plt.xlabel('Scenarios')
plt.ylabel('Packet Loss (%)')
plt.title('Packet Loss for each capacity configuration')
plt.xticks(x, cap_confs) # Ajustar rótulos do eixo x
plt.legend() # Adicionar legenda
# Exibir o gráfico
plt.tight_layout()
plt.show()
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