Update app.py

app.py

@@ -19,6 +19,13 @@ def generate_data():
             bandwidth_usage = max(1, min(150, bandwidth_usage))  # Keep within a realistic range
             data.append([school, time, bandwidth_usage])
     
+    # Introduce anomalies manually
+    for _ in range(10):  # Increase anomaly occurrences
+        school = np.random.choice(schools)
+        time = np.random.choice(time_range)
+        bandwidth_usage = np.random.choice([1, 160])  # Extreme low or high values
+        data.append([school, time, bandwidth_usage])
+    
     df = pd.DataFrame(data, columns=["School", "Timestamp", "Bandwidth_Usage"])
     df.to_csv("network_data.csv", index=False)
     return df
@@ -56,7 +63,7 @@ def allocate_bandwidth(demand_predictions, total_bandwidth=500):
 def sdn_load_balancer(network_graph, demand_predictions):
     shortest_paths = {}
     for school in demand_predictions.keys():
-        shortest_paths[school] = nx.shortest_path(network_graph, source='Node_A', target=school)
+        shortest_paths[school] = nx.shortest_path(network_graph, source='Node_A', target=school, weight=None)
     return shortest_paths
 
 # Create a complex network topology
@@ -102,4 +109,7 @@ with col3:
 
 with col4:
     st.subheader("Detected Anomalies")
-    st.dataframe(anomalies)
+    if anomalies.empty:
+        st.write("No anomalies detected")
+    else:
+        st.dataframe(anomalies)