fix: resolve inconsistent variable naming in causal graph (IOI and ravel)

app.py

@@ -214,7 +214,7 @@ LEADERBOARD_DF_MIB_SUBGRAPH_FEQ = get_leaderboard_df_mib_subgraph(EVAL_RESULTS_M
                                                                   metric_type="CMD")
 
 # In app.py, modify the LEADERBOARD initialization
-LEADERBOARD_DF_MIB_CAUSALGRAPH_DETAILED, LEADERBOARD_DF_MIB_CAUSALGRAPH_AGGREGATED, LEADERBOARD_DF_MIB_CAUSALGRAPH_AVERAGED = get_leaderboard_df_mib_causalgraph(
+LEADERBOARD_DF_MIB_CAUSALGRAPH_AGGREGATED, LEADERBOARD_DF_MIB_CAUSALGRAPH_AVERAGED = get_leaderboard_df_mib_causalgraph(
     EVAL_RESULTS_MIB_CAUSALGRAPH_PATH
 )
 

src/leaderboard/read_evals.py

@@ -401,13 +401,12 @@ def get_raw_eval_results_mib_causalgraph(results_path: str) -> Tuple[pd.DataFram
             with open(json_file, 'r') as f:
                 data = json.load(f)
                 
-                # # Check if this is the consolidated format by examining a sample key
-                # sample_key = next(iter(data), None)
-                # if sample_key and isinstance(sample_key, str) and '(' in sample_key and ')' in sample_key:
-                #     raw_data = data
-                #     print(f"Found consolidated data file: {json_file}")
-                #     break
-                raw_data = data
+                # Check if this is the consolidated format by examining a sample key
+                sample_key = next(iter(data), None)
+                if sample_key and isinstance(sample_key, str) and '(' in sample_key and ')' in sample_key:
+                    raw_data = data
+                    print(f"Found consolidated data file: {json_file}")
+
         except Exception as e:
             print(f"Error reading {json_file}: {e}")
     
@@ -513,7 +512,7 @@ def get_raw_eval_results_mib_causalgraph(results_path: str) -> Tuple[pd.DataFram
     # intervention_averaged_mean_df = create_intervention_averaged_df(detailed_df_mean)
     
     # return detailed_df_highest, detailed_df_mean, intervention_averaged_highest_df
-    return detailed_df_highest, detailed_df_highest, detailed_df_mean
+    return detailed_df_highest, detailed_df_mean