fixing time elapse for plot utils

src/utils/plot_combined_exp.py

@@ -12,6 +12,7 @@ def combine_and_plot(
     xlabels: List[str], 
     ylabels: List[str], 
     output_dir: str, 
+    include_logs: bool = True
 ) -> None:
     """
     Combine and plot metrics from multiple experiments with 95% confidence intervals.
@@ -28,6 +29,9 @@ def combine_and_plot(
     # Ensure the output directory exists
     if not os.path.exists(output_dir):
         os.makedirs(output_dir)
+
+    if not os.path.exists(os.path.join(output_dir, 'plots')):
+        os.makedirs(os.path.join(output_dir, 'plots'))
 
     for metric_index, metric_name in enumerate(metrics_list):
         plt.figure(figsize=(12, 8), dpi=300)
@@ -36,21 +40,21 @@ def combine_and_plot(
             # Load the aggregated metric DataFrame for the experiment
             metric_df = pd.read_csv(os.path.join(experiment_path, f"{metric_name}_avg.csv"))
             # TODO: modify this to be CI
-            std_df = pd.read_csv(os.path.join(experiment_path, f"{metric_name}_std.csv"))
-            # ci_df = pd.read_csv(os.path.join(experiment_path, f"{metric_name}_ci95.csv"))
+            # std_df = pd.read_csv(os.path.join(experiment_path, f"{metric_name}_std.csv"))
+            ci_df = pd.read_csv(os.path.join(experiment_path, f"{metric_name}_ci95.csv"))
 
             # Assuming rounds or time steps are the index
             rounds = np.arange(len(metric_df))
 
             # Plot each experiment's mean with 95% CI
             mean_metric = metric_df.values.flatten()
-            std_metric = std_df.values.flatten()
-            # ci_95 = ci_df.values.flatten()
+            # std_metric = std_df.values.flatten()
+            ci_95 = ci_df.values.flatten()
 
             # Plot the mean with confidence interval as a shaded area
             plt.plot(rounds, mean_metric, label=f'{experiment_key}', linestyle='--', linewidth=1.5)
-            # plt.fill_between(rounds, mean_metric - ci_95, mean_metric + ci_95, alpha=0.2)
-            plt.fill_between(rounds, mean_metric - std_metric, mean_metric + std_metric, alpha=0.2)
+            plt.fill_between(rounds, mean_metric - ci_95, mean_metric + ci_95, alpha=0.2)
+            # plt.fill_between(rounds, mean_metric - std_metric, mean_metric + std_metric, alpha=0.2)
 
         # Plot customization
         plt.xlabel(xlabels[metric_index], fontsize=14)

src/utils/post_hoc_plot_utils.py

@@ -426,11 +426,17 @@ def plot_all_metrics(logs_dir: str, per_round: bool = True, per_time: bool = Tru
                 rounds=all_users_data['rounds'], 
                 metric_name=key, 
                 ylabel=display_name, 
-                output_dir=f'{logs_dir}plots/',
+                output_dir=f'{logs_dir}/plots/',
                 plot_avg_only=plot_avg_only,
                 **kwargs
                 )
+
     if per_time:
+        time_data = os.path.join(logs_dir, 'node_1/csv/time_elapsed.csv')
+        # check if time elapsed data exists
+        if not os.path.exists(time_data):
+            print("Time elapsed data not found. Skipping per-time plotting.")
+            return
         all_users_data = aggregate_per_realtime_data(logs_dir, **kwargs)
 
         for key, display_name in metrics_map.items():
@@ -439,7 +445,7 @@ def plot_all_metrics(logs_dir: str, per_round: bool = True, per_time: bool = Tru
                 time_ticks=all_users_data[key].index.values, 
                 metric_name=key, 
                 ylabel=display_name, 
-                output_dir=f'{logs_dir}plots/',
+                output_dir=f'{logs_dir}/plots/',
                 plot_avg_only=plot_avg_only,
                 **kwargs
                 )
@@ -468,7 +474,7 @@ def plot_all_metrics(logs_dir: str, per_round: bool = True, per_time: bool = Tru
             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)
+                plot_all_metrics(logs_dir, per_round=True, per_time=True, plot_avg_only=True)
             except Exception as e:
                 print(f"Error processing {logs_dir}: {e}")
                 continue