degub

handler.py

@@ -193,10 +193,15 @@ def cluster_windows(predicted_patterns , probability_threshold, window_size,eps
                 'Avg_Probability': cluster_group['Probability'].mean(),
             })
 
+            print("inside cluster windows")
+            print(interseced_clusters)
+
     if len(cluster_labled_windows) == 0 or len(interseced_clusters) == 0:
         return None, None
 
     cluster_labled_windows_df = pd.concat(cluster_labled_windows)
+    print("inside cluster windows before dataframe make")
+    print(interseced_clusters)
     interseced_clusters_df = pd.DataFrame(interseced_clusters)
     cluster_labled_windows_df = cluster_labled_windows_df.sort_index()
     return cluster_labled_windows_df, interseced_clusters_df
@@ -378,6 +383,9 @@ class EndpointHandler:
                 print("Predicted patterns dataframe is empty")
                 continue
 
+            print("Predicted Patterns intermediate")
+            print(predicted_patterns)
+
             # Pass eps and min_samples from handler's state
             cluster_labled_windows_df , interseced_clusters_df = cluster_windows(
                 predicted_patterns,