Update app.py

app.py

@@ -102,8 +102,13 @@ def get_anomaly_samples(input_data, n_samples, outliers_fraction):
     # Prepare data with labels
     X, labels = prepare_data(input_data, n_samples, outliers_fraction)
 
-    # Assign anomaly scores (simulated here)
-    scores = np.random.random(len(X))
+    # Assign anomaly scores with higher values for anomalies
+    rng = np.random.default_rng(42)
+    scores = np.where(
+        labels == "Anomaly",
+        rng.uniform(0.7, 1.0, len(labels)),  # Higher scores for anomalies
+        rng.uniform(0.0, 0.7, len(labels)),  # Lower scores for normals
+    )
 
     # Create a DataFrame
     df = pd.DataFrame({