working initial data, test subsequent data

app.py

@@ -41,35 +41,34 @@ with gr.Blocks() as demo:
     columns_variable = [i for i in all_columns if i not in columns_fixed]
     
     shot_options = ["0 shot", "1 shot", "5 shots"]
-    metric_columns = [col for col in df.columns if any(shot in col for shot in shot_options)]
+    
 
     def get_columns_for_shots(selected_shots):
         if not selected_shots:
-            return columns_fixed
-        return columns_fixed + [col for col in metric_columns if any(shot in col for shot in selected_shots)]
+            return []
+        return [col for col in all_columns if any(shot in col for shot in selected_shots)]
     
     def get_columns_for_data(selected_data):
         if not selected_data:
-            return columns_fixed
-        return columns_fixed + [col for col in metric_columns if any(data in col for data in selected_data)]
+            return []
+        return [col for col in all_columns if any(data in col for data in selected_data)]
 
     # data_types = sorted(df["data_type"].dropna().unique())
     parameter_options = sorted(df["Parameters"].dropna().unique())
     
     def filter_leaderboard(selected_params, selected_shots, selected_data):
         filtered = df.copy()
-
+        print("Selected Shots:", selected_shots)
         if selected_params:
             filtered = filtered[filtered["Parameters"].isin(selected_params)]
 
-        # Determine which columns to show
         columns_by_shot = get_columns_for_shots(selected_shots)
         columns_by_data = get_columns_for_data(selected_data)
-        additional_columns = [col for col in columns_by_shot + columns_by_data if col in list(df.columns)]
-
-        # Always include fixed columns
+        additional_columns = [col for col in columns_by_shot + columns_by_data if col in df.columns]
         cols_to_show = list(dict.fromkeys(columns_fixed + additional_columns))
-        
+
+        print("COLUMNS TO SHOW:", cols_to_show)
+
         return filtered[cols_to_show]
 
 
@@ -88,10 +87,10 @@ with gr.Blocks() as demo:
             # data_type_filter = gr.CheckboxGroup(choices=data_types, label="Filter by Data Type")
             
 
-
-    leaderboard_table = gr.Dataframe(label="🏅 Leaderboard", interactive=False)
+    initial_data = filter_leaderboard(parameter_options, shot_options, ["Chexpert Plus", "CT Rate"])
+    leaderboard_table = gr.Dataframe(value=initial_data, label="🏅 Leaderboard", interactive=False)
     # Initialize table
-    leaderboard_table.value = filter_leaderboard(parameter_options, shot_options, ["Chexpert Plus", "CT Rate"])
+    
     # dataset_filter.change(
     #     fn=update_leaderboard,
     #     inputs=[column_selector, dataset_filter],
@@ -104,7 +103,7 @@ with gr.Blocks() as demo:
     param_filter.change(fn=filter_leaderboard, inputs=[param_filter, shot_filter, column_selector_data,], outputs=leaderboard_table)
     shot_filter.change(fn=filter_leaderboard, inputs=[param_filter, shot_filter, column_selector_data,], outputs=leaderboard_table)
 
-    
+    # leaderboard_table.value = filter_leaderboard(parameter_options, shot_options, ["Chexpert Plus", "CT Rate"])
     print(leaderboard_table.value)
 
 demo.launch()