Update app.py

app.py

@@ -14,9 +14,6 @@ from inference import (
 )
 
 
-# ---------------------------------------------------------------------------
-# Choice lists
-# ---------------------------------------------------------------------------
 
 AGEGPFF_CHOICES   = ["<=10", "11-17", "18-29", "30-49", ">=50"]
 SEX_CHOICES       = ["Male", "Female"]
@@ -56,9 +53,7 @@ SCATXRSN_CHOICES  = [
 ]
 
 
-# ---------------------------------------------------------------------------
-# Grouped published-regimen dropdown
-# ---------------------------------------------------------------------------
+
 
 GROUPED_REGIMEN_CHOICES = [
     ("── HLA IDENTICAL ──",                        "__header_hla_identical__"),
@@ -137,9 +132,7 @@ PUBLISHED_PRESETS = {
 }
 
 
-# ---------------------------------------------------------------------------
-# Feature groupings
-# ---------------------------------------------------------------------------
+
 
 PATIENT_FEATURES = ["AGE", "AGEGPFF", "SEX", "KPS", "RCMVPR"]
 DONOR_FEATURES   = ["DONORF", "GRAFTYPE", "HLA_FINAL",
@@ -148,9 +141,7 @@ DISEASE_FEATURES = ["NACS2YR", "EXCHTFPR", "VOC2YPR", "VOCFRQPR", "SCATXRSN"]
 ALL_FEATURES     = PATIENT_FEATURES + DONOR_FEATURES + DISEASE_FEATURES
 
 
-# ---------------------------------------------------------------------------
-# Utility callbacks
-# ---------------------------------------------------------------------------
+
 
 def get_age_group(age):
     if age is None or age == "":
@@ -188,7 +179,7 @@ def apply_grouped_preset(selected_value):
         return [gr.update()] * 7
 
     return [
-        gr.update(),                             # leave dropdown showing selection
+        gr.update(),                            
         gr.update(value=preset["DONORF"]),
         gr.update(value=preset["CONDGRPF"]),
         gr.update(value=preset["CONDGRP_FINAL"]),
@@ -198,9 +189,7 @@ def apply_grouped_preset(selected_value):
     ]
 
 
-# ---------------------------------------------------------------------------
-# Component factory
-# ---------------------------------------------------------------------------
+
 
 def make_component(name: str):
     if name == "AGE":
@@ -247,9 +236,7 @@ def make_component(name: str):
         return gr.Textbox(label=name)
 
 
-# ---------------------------------------------------------------------------
-# Prediction callback
-# ---------------------------------------------------------------------------
+
 
 def predict_gradio(*values):
     try:
@@ -284,7 +271,7 @@ def predict_gradio(*values):
 
         return (
             df,
-            icon_arrays["__grid__"],      # single combined 4×2 grid HTML
+            icon_arrays["__grid__"],      
             shap_plots["DEAD"],
             shap_plots["GF"],
             shap_plots["AGVHD"],
@@ -304,9 +291,7 @@ def predict_gradio(*values):
         raise gr.Error(f"{type(e).__name__}: {str(e)}\n\nSee terminal for full traceback.")
 
 
-# ---------------------------------------------------------------------------
-# CSS
-# ---------------------------------------------------------------------------
+
 
 custom_css = """
 .predict-button {
@@ -322,9 +307,6 @@ custom_css = """
 }
 """
 
-# ---------------------------------------------------------------------------
-# Gradio UI
-# ---------------------------------------------------------------------------
 
 with gr.Blocks(title="HCT Outcome Prediction Model", css=custom_css) as demo:
     gr.Markdown(
@@ -338,13 +320,13 @@ with gr.Blocks(title="HCT Outcome Prediction Model", css=custom_css) as demo:
     inputs_dict = {}
 
     with gr.Row():
-        # ── Patient Characteristics ──────────────────────────────────────
+       
         with gr.Column(scale=1):
             gr.Markdown("### Patient Characteristics")
             for f in PATIENT_FEATURES:
                 inputs_dict[f] = make_component(f)
 
-        # ── Transplant Characteristics ───────────────────────────────────
+      
         with gr.Column(scale=1):
             gr.Markdown("### Transplant Characteristics")
 
@@ -364,13 +346,13 @@ with gr.Blocks(title="HCT Outcome Prediction Model", css=custom_css) as demo:
             gvhd_final    = inputs_dict["GVHD_FINAL"]    = make_component("GVHD_FINAL")
             hla_final     = inputs_dict["HLA_FINAL"]     = make_component("HLA_FINAL")
 
-        # ── Disease Characteristics ──────────────────────────────────────
+        
         with gr.Column(scale=1):
             gr.Markdown("### Disease Characteristics")
             for f in DISEASE_FEATURES:
                 inputs_dict[f] = make_component(f)
 
-    # ── Reactive callbacks ───────────────────────────────────────────────
+    
     inputs_dict["AGE"].change(
         fn=get_age_group,
         inputs=inputs_dict["AGE"],
@@ -383,7 +365,7 @@ with gr.Blocks(title="HCT Outcome Prediction Model", css=custom_css) as demo:
         outputs=inputs_dict["VOCFRQPR"],
     )
 
-    # outputs[0] is the dropdown itself so clicking a header resets it to None
+    
     grouped_regimen_dropdown.change(
         fn=apply_grouped_preset,
         inputs=grouped_regimen_dropdown,
@@ -412,7 +394,7 @@ with gr.Blocks(title="HCT Outcome Prediction Model", css=custom_css) as demo:
     gr.Markdown("---")
     gr.Markdown("## Outcome Probability — Icon Arrays")
   
-    # Single HTML component holds the entire 4×2 grid
+  
     icon_array_grid = gr.HTML(label="")
 
     gr.Markdown("---")