[FEAT] Tab4: add Run tab + fix heatmap size + fix export tab reset

tabs/tab4_optimization.py

@@ -588,7 +588,13 @@ def show_heatmap(df_result, resource_caps, method_costs, custom_resources=None,
         customdata=matrix_exact_fmt,
         hovertemplate="<b>%{y}</b><br>%{x}<br>% of cap: %{z:.1f}%<br>Exact: %{customdata}<extra></extra>",
     )
-    apply_chart_style(fig, height=max(400, 60 + 30 * len(df_heat.index)))
+    n_rows = len(df_heat.index)
+    n_cols = len(df_heat.columns)
+    height = max(500, 80 + 50 * n_rows)
+    # For wide heatmaps, force a minimum width so each column stays readable
+    if n_cols > 8:
+        fig.update_layout(width=max(900, 90 * n_cols))
+    apply_chart_style(fig, height=height)
     st.plotly_chart(fig, width='stretch')
 
     resource_to_group = get_resource_to_group()
@@ -1181,7 +1187,7 @@ def confirm_clear_all():
             clear_all_data()
             st.rerun()
     with col2:
-        if st.button("Cancel",width='stretch'):
+        if st.button("Cancel", width='stretch', type="secondary", key="btn-cancel"):
             st.rerun()
 
 def reset_scenario():
@@ -1198,6 +1204,16 @@ def reset_scenario():
         confirm_clear_all()
 
 
+@st.fragment
+def render_export_tab(latest):
+    """Render the full export/save section as a fragment so Save reruns only this area."""
+    save_scenario(latest)
+    export_scenario()
+    export_inputs_only()
+    export_all_charts()
+    reset_scenario()
+
+
 def render_tab():
     """Render the Portfolio Generation tab.
 
@@ -1237,44 +1253,59 @@ def render_tab():
     if "enabled_methods" not in st.session_state:
         st.session_state.enabled_methods = {}
 
-    st.markdown("""
-        <p class="crra-sub-heading">Run optimization</p>""",
-        unsafe_allow_html=True,
-    )
-    col_inputs, col_scenario = st.columns(2, gap="large")
+    tab_run, tab_results, tab_resources, tab_bottleneck, tab_export = st.tabs([
+        "▶️ Run",
+        "📊 Method allocation",
+        "🌿 Resource usage",
+        "🔍 Bottleneck analysis",
+        "💾 Export & Save",
+    ])
 
-    with col_inputs:
+    with tab_run:
         st.markdown("""
-            <p class="crra-sub-sub-heading">From inputs</p>""",
+            <p class="crra-sub-heading">Run optimization</p>""",
             unsafe_allow_html=True,
         )
-        run_clicked = st.button("Run Optimization", icon=":material/play_arrow:", key="btn-run-optimization", type="primary")
-        panel_run_from_tabs()
-        panel_load_from_excel()
+        col_inputs, col_scenario = st.columns(2, gap="large")
 
-    with col_scenario:
-        st.markdown("""
-            <p class="crra-sub-sub-heading">From a saved scenario</p>""",
-            unsafe_allow_html=True,
-        )
-        panel_load_from_json_or_csv()
+        with col_inputs:
+            st.markdown("""
+                <p class="crra-sub-sub-heading">From inputs</p>""",
+                unsafe_allow_html=True,
+            )
+            run_clicked = st.button("Run Optimization", icon=":material/play_arrow:", key="btn-run-optimization", type="primary")
+            panel_run_from_tabs()
+            panel_load_from_excel()
+
+        with col_scenario:
+            st.markdown("""
+                <p class="crra-sub-sub-heading">From a saved scenario</p>""",
+                unsafe_allow_html=True,
+            )
+            panel_load_from_json_or_csv()
 
-    if run_clicked:
-        run_and_store_result()
+        if run_clicked:
+            run_and_store_result()
 
-    if "latest_result" not in st.session_state:
+    _no_results = '<p class="caption">Run the optimization first to see results here.</p>'
+
+    latest = st.session_state.get("latest_result")
+    if not latest:
+        for _tab in [tab_results, tab_resources, tab_bottleneck, tab_export]:
+            with _tab:
+                st.markdown(_no_results, unsafe_allow_html=True)
         return
 
-    latest = st.session_state.latest_result
     allocations = latest["allocations"]
     resource_caps = latest["resource_caps"]
     method_costs = latest["method_costs"]
 
     if not allocations or sum(allocations.values()) == 0:
+        for _tab in [tab_results, tab_resources, tab_bottleneck, tab_export]:
+            with _tab:
+                st.markdown(_no_results, unsafe_allow_html=True)
         return
 
-    show_metrics(latest)
-
     df_result = build_results_df(
         allocations,
         method_constraints=latest.get("method_constraints")
@@ -1284,14 +1315,8 @@ def render_tab():
         lambda x: f"{x:,.4f}" if pd.notna(x) else x
     )
 
-    tab_results, tab_resources, tab_bottleneck, tab_export = st.tabs([
-        "📊 Method allocation",
-        "🌿 Resource usage",
-        "🔍 Bottleneck analysis",
-        "💾 Export & Save",
-    ])
-
     with tab_results:
+        show_metrics(latest)
         st.markdown('<p class="crra-sub-heading">Optimization Summary</p>', unsafe_allow_html=True)
         st.dataframe(df_display, width='stretch')
         st.markdown('<p class="crra-sub-heading">Method allocation breakdown</p>', unsafe_allow_html=True)
@@ -1312,8 +1337,4 @@ def render_tab():
         show_bottleneck_analysis(latest)
 
     with tab_export:
-        save_scenario(latest)
-        export_scenario()
-        export_inputs_only()
-        export_all_charts()
-        reset_scenario()
+        render_export_tab(latest)