Update app.py

app.py

@@ -60,54 +60,59 @@ st.warning("Your CSV file must only contain the following columns:\n\n"
 
 # Form to upload CSV file
 with st.form("submission_form"):
-    username = st.text_input("Username", max_chars=20)
+    username = st.text_input("Username (required)", max_chars=20)
     uploaded_file = st.file_uploader("Upload your prediction CSV file", type="csv")
     submit_button = st.form_submit_button("Submit")
 
 # Process submission
 if submit_button and uploaded_file:
-    predictions = pd.read_csv(uploaded_file)
-
-    # Check if file format is correct
-    if "patient_id" in predictions.columns and "predicted_scores" in predictions.columns:
-        # Merge with ground truth to calculate C-Index
-        merged = pd.merge(ground_truth, predictions, on="patient_id", how="inner")
-        if merged.empty:
-            st.error("No matching patient IDs found between the ground truth and your submission. Please check your patient IDs.")
-        
-        c_index = concordance_index(event_times=merged["survival_time"], 
-                                    predicted_scores=merged["predicted_scores"], 
-                                    event_observed=merged["vital_status"],
-                                    )
-
-        # Save submission to file
-        submission_file = submission_dir / f"{username}_{uploaded_file.name}"
-        predictions.to_csv(submission_file, index=False)
-
-        # Update leaderboard
-        new_entry = pd.DataFrame({
-            "Username": [username],
-            "C-Index": [c_index],
-            "Submission Date": [pd.Timestamp.now()],
-        })
-        leaderboard_df = pd.concat([leaderboard_df, new_entry], ignore_index=True)
-
-        # Save updated leaderboard locally
-        leaderboard_df.to_csv(leaderboard_file_path, index=False)
-
-        # Upload updated leaderboard to Hugging Face
-        upload_file(
-            path_or_fileobj=leaderboard_file_path,
-            path_in_repo="leaderboard.csv",
-            repo_type="dataset",
-            repo_id="HLMCC/tcga-paad-ground-truth",
-            token=hf_token,
-        )
-
-        # Display the calculated C-Index to the user
-        st.success(f"Submission received! Your C-Index score: {c_index:.4f}")
+    if not username.strip():
+        st.error("Username is required. Please enter your username.")
+    elif not uploaded_file:
+        st.error("Please upload your prediction CSV file.")
     else:
-        st.error("Incorrect file format. Ensure columns include 'patient_id' and 'predicted_scores'.")
+        predictions = pd.read_csv(uploaded_file)
+    
+        # Check if file format is correct
+        if "patient_id" in predictions.columns and "predicted_scores" in predictions.columns:
+            # Merge with ground truth to calculate C-Index
+            merged = pd.merge(ground_truth, predictions, on="patient_id", how="inner")
+            if merged.empty:
+                st.error("No matching patient IDs found between the ground truth and your submission. Please check your patient IDs.")
+            
+            c_index = concordance_index(event_times=merged["survival_time"], 
+                                        predicted_scores=merged["predicted_scores"], 
+                                        event_observed=merged["vital_status"],
+                                        )
+    
+            # Save submission to file
+            submission_file = submission_dir / f"{username}_{uploaded_file.name}"
+            predictions.to_csv(submission_file, index=False)
+    
+            # Update leaderboard
+            new_entry = pd.DataFrame({
+                "Username": [username],
+                "C-Index": [c_index],
+                "Submission Date": [pd.Timestamp.now()],
+            })
+            leaderboard_df = pd.concat([leaderboard_df, new_entry], ignore_index=True)
+    
+            # Save updated leaderboard locally
+            leaderboard_df.to_csv(leaderboard_file_path, index=False)
+    
+            # Upload updated leaderboard to Hugging Face
+            upload_file(
+                path_or_fileobj=leaderboard_file_path,
+                path_in_repo="leaderboard.csv",
+                repo_type="dataset",
+                repo_id="HLMCC/tcga-paad-ground-truth",
+                token=hf_token,
+            )
+    
+            # Display the calculated C-Index to the user
+            st.success(f"Submission received! Your C-Index score: {c_index:.4f}")
+        else:
+            st.error("Incorrect file format. Ensure columns include 'patient_id' and 'predicted_scores'.")
 
 # Display the leaderboard
 st.subheader("Leaderboard")