diff --git a/src/utils/post_hoc_plot_utils.py b/src/utils/post_hoc_plot_utils.py
index 25b6c29..3efcda3 100644
--- a/src/utils/post_hoc_plot_utils.py
+++ b/src/utils/post_hoc_plot_utils.py
@@ -67,10 +67,12 @@ def aggregate_metrics_across_users(logs_dir: str, output_dir: Optional[str] = No
 
     # Convert to DataFrame for easier processing
     df_metrics = pd.DataFrame(all_metrics)
-    
+    # Select only numeric columns before calculating mean and std
+    numeric_columns = df_metrics.select_dtypes(include=[np.number])
+
     # Calculate average and standard deviation
-    avg_metrics = df_metrics.mean()
-    std_metrics = df_metrics.std()
+    avg_metrics = numeric_columns.mean()
+    std_metrics = numeric_columns.std()
 
     # Save the DataFrame with per-user metrics
     df_metrics.to_csv(os.path.join(output_dir, 'per_user_metrics.csv'), index=False)
@@ -141,12 +143,9 @@ def plot_metric_per_round(metric_df: pd.DataFrame, rounds: np.ndarray, metric_na
     for col in metric_df.columns:
         plt.plot(rounds, metric_df[col], alpha=0.6, label=f'User {col+1}')
 
-    # Select only numeric columns before calculating mean and std
-    numeric_columns = df_metrics.select_dtypes(include=[np.number])
-
-    # Calculate average and standard deviation
-    avg_metrics = numeric_columns.mean()
-    std_metrics = numeric_columns.std()
+    # Compute mean and std
+    mean_metric = metric_df.mean(axis=1)
+    std_metric = metric_df.std(axis=1)
 
     # Save the mean and std
     if not os.path.exists(output_dir):
@@ -189,8 +188,29 @@ def plot_all_metrics(logs_dir: str, metrics_map: Optional[Dict[str, str]] = None
 
     print("Plots saved as PNG files.")
 
+# Use if you a specific experiment folder
+# if __name__ == "__main__":
+#     # Define the path where your experiment logs are saved
+#     logs_dir = '/mas/camera/Experiments/SONAR/abhi/cifar10_36users_1250_convergence_ringm3_seed2/logs/'
+#     avg_metrics, std_metrics, df_metrics = aggregate_metrics_across_users(logs_dir)
+#     plot_all_metrics(logs_dir)
+
+
+# Use if you want to compute for multiple experiment folders
 if __name__ == "__main__":
-    # Define the path where your experiment logs are saved
-    logs_dir = '/u/jyuan24/sonar/src/expt_dump/1_malicious_exp/cifar10_40users_1250_data_poison_8_malicious_seed1/logs/'
-    avg_metrics, std_metrics, df_metrics = aggregate_metrics_across_users(logs_dir)
-    plot_all_metrics(logs_dir)
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+    # Define the base directory where your experiment logs are saved
+    base_logs_dir = '/mas/camera/Experiments/SONAR/abhi/'
+
+    # Iterate over each subdirectory in the base directory
+    for experiment_folder in os.listdir(base_logs_dir):
+        experiment_path = os.path.join(base_logs_dir, experiment_folder)
+        logs_dir = os.path.join(experiment_path, 'logs')
+
+        if os.path.isdir(logs_dir):
+            try:
+                print(f"Processing logs in: {logs_dir}")
+                avg_metrics, std_metrics, df_metrics = aggregate_metrics_across_users(logs_dir)
+                plot_all_metrics(logs_dir)
+            except Exception as e:
+                print(f"Error processing {logs_dir}: {e}")
+                continue
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