Update method names

src/populate.py

@@ -9,6 +9,17 @@ from src.display.utils import EvalQueueColumn
 from src.about import Tasks, SingleTableTasks, SingleColumnTasks
 
 
+# Model name mapping dictionary
+model_names = {
+    'CLAVADDPM': "ClavaDDPM",
+    'RGCLD': "RGCLD",
+    'MOSTLYAI': "TabularARGN",
+    'RCTGAN': "RCTGAN",
+    'REALTABFORMER': "REaLTabFormer",
+    'SDV': "SDV",
+}
+
+
 # def get_leaderboard_df(results_path: str, requests_path: str, cols: list, benchmark_cols: list) -> pd.DataFrame:
 #     """Creates a dataframe from all the individual experiment results"""
 #     raw_data = get_raw_eval_results(results_path, requests_path)
@@ -62,6 +73,9 @@ def get_leaderboard_df(results_path: str, cols: list, benchmark_cols: list) -> p
     # iterate through all json files and add the data to the dataframe
     for data in all_data_json:
         model = data["method_name"]
+        # Rename model if it exists in the mapping dictionary
+        if model.upper() in model_names:
+            model = model_names[model.upper()]
         dataset = data["dataset_name"]
         row = {"Dataset": dataset, "Model": model}
         for metric in multi_table_metrics:
@@ -139,41 +153,3 @@ def get_leaderboard_df(results_path: str, cols: list, benchmark_cols: list) -> p
             
 
     return singlecolumn_df, singletable_df, multitable_df
-
-
-def get_evaluation_queue_df(save_path: str, cols: list) -> list[pd.DataFrame]:
-    """Creates the different dataframes for the evaluation queues requestes"""
-    entries = [entry for entry in os.listdir(save_path) if not entry.startswith(".")]
-    all_evals = []
-
-    for entry in entries:
-        if ".json" in entry:
-            file_path = os.path.join(save_path, entry)
-            with open(file_path) as fp:
-                data = json.load(fp)
-
-            data[EvalQueueColumn.model.name] = make_clickable_model(data["model"])
-            data[EvalQueueColumn.revision.name] = data.get("revision", "main")
-
-            all_evals.append(data)
-        elif ".md" not in entry:
-            # this is a folder
-            sub_entries = [
-                e for e in os.listdir(f"{save_path}/{entry}") if os.path.isfile(e) and not e.startswith(".")
-            ]
-            for sub_entry in sub_entries:
-                file_path = os.path.join(save_path, entry, sub_entry)
-                with open(file_path) as fp:
-                    data = json.load(fp)
-
-                data[EvalQueueColumn.model.name] = make_clickable_model(data["model"])
-                data[EvalQueueColumn.revision.name] = data.get("revision", "main")
-                all_evals.append(data)
-
-    pending_list = [e for e in all_evals if e["status"] in ["PENDING", "RERUN"]]
-    running_list = [e for e in all_evals if e["status"] == "RUNNING"]
-    finished_list = [e for e in all_evals if e["status"].startswith("FINISHED") or e["status"] == "PENDING_NEW_EVAL"]
-    df_pending = pd.DataFrame.from_records(pending_list, columns=cols)
-    df_running = pd.DataFrame.from_records(running_list, columns=cols)
-    df_finished = pd.DataFrame.from_records(finished_list, columns=cols)
-    return df_finished[cols], df_running[cols], df_pending[cols]