Update app.py

app.py

@@ -2314,7 +2314,9 @@ with tab_predict:
             
             out["risk_band"] = band_one(proba_one)
 
-            # ---- SHAP for single patient (works even without inference Excel) ----
+            
+
+            # ---- SHAP compute only (cache) ----
             X_one_t = transform_before_clf(pipe, X_one)
             
             explainer = st.session_state.get("explainer")
@@ -2340,14 +2342,12 @@ with tab_predict:
                 shap_vals = shap_vals[1]
             
             names = get_final_feature_names(pipe)
-            if len(names) != shap_vals.shape[1]:
-                names = [f"f{i}" for i in range(shap_vals.shape[1])]
             
             try:
                 x_dense = X_one_t.toarray()[0]
             except Exception:
                 x_dense = np.array(X_one_t)[0]
-
+            
             base = explainer.expected_value
             if not np.isscalar(base):
                 base = float(np.array(base).reshape(-1)[0])
@@ -2359,16 +2359,8 @@ with tab_predict:
                 feature_names=names,
             )
             
-            # Plot
-            plt.figure(figsize=FIGSIZE, dpi=plot_dpi_screen)
-            shap.plots.waterfall(exp, show=False, max_display=20)
-            fig_w = plt.gcf()
-            render_plot_with_download(fig_w, title="Single-patient SHAP waterfall", filename="single_patient_shap_waterfall.png", export_dpi=export_dpi, key="dl_sp_wf")
-            
-            plt.figure(figsize=FIGSIZE, dpi=plot_dpi_screen)
-            shap.plots.bar(exp, show=False, max_display=20)
-            fig_b = plt.gcf()
-            render_plot_with_download(fig_b, title="Single-patient SHAP bar", filename="single_patient_shap_bar.png", export_dpi=export_dpi, key="dl_sp_bar")
+            # CACHE ONLY
+            st.session_state.shap_single_exp = exp
 
         
             st.dataframe(out, use_container_width=True)
@@ -2381,6 +2373,42 @@ with tab_predict:
                 key="dl_sp_csv",
             )
 
+            # ---- Always render cached SHAP ----
+            if "shap_single_exp" in st.session_state:
+                exp = st.session_state.shap_single_exp
+            
+                max_display_single = st.slider(
+                    "Top features to display (single patient)",
+                    5, 40, 20, 1,
+                    key="sp_single_max_display"
+                )
+            
+                c1, c2 = st.columns(2)
+            
+                with c1:
+                    plt.figure(figsize=FIGSIZE, dpi=plot_dpi_screen)
+                    shap.plots.waterfall(exp, show=False, max_display=max_display_single)
+                    fig_w = plt.gcf()
+                    render_plot_with_download(
+                        fig_w,
+                        title="Single-patient SHAP waterfall",
+                        filename="single_patient_shap_waterfall.png",
+                        export_dpi=export_dpi,
+                        key="dl_sp_wf"
+                    )
+            
+                with c2:
+                    plt.figure(figsize=FIGSIZE, dpi=plot_dpi_screen)
+                    shap.plots.bar(exp, show=False, max_display=max_display_single)
+                    fig_b = plt.gcf()
+                    render_plot_with_download(
+                        fig_b,
+                        title="Single-patient SHAP bar",
+                        filename="single_patient_shap_bar.png",
+                        export_dpi=export_dpi,
+                        key="dl_sp_bar"
+                    )
+
 
 
     # -----------------------------