remove debug mechanism - fast_bisect wasn't compiling - seems to be fixed now

main.py

@@ -589,19 +589,6 @@ app.layout = html.Div(
                         ),
                     ],
                 ),
-                html.Pre(
-                    id="mm0_debug",
-                    style={
-                        "whiteSpace": "pre-wrap",
-                        "fontSize": "12px",
-                        "maxHeight": "260px",
-                        "overflowY": "auto",
-                        "border": "1px solid #ddd",
-                        "padding": "8px",
-                        "marginTop": "10px",
-                        "backgroundColor": "#fafafa",
-                    },
-                ),
             ],
         ),
     ],
@@ -645,7 +632,6 @@ def toggle_condition2_inputs(mode):
 
 @app.callback(
     Output("mm0_chart", "figure"),
-    Output("mm0_debug", "children"),
     Input("calculate", "n_clicks"),
     State("matrix", "value"),
     State("tg", "value"),
@@ -683,9 +669,6 @@ def update_chart(n_clicks,
     # TODO: replace with logic that uses the form inputs
     # For now, simply return the same figure when "Calculate" is clicked.
 
-    t0 = time.time()
-    debug = [f"click={n_clicks}"]
-
     df = pd.DataFrame()
     df['CASRN'] = soluteData['CASRN'].to_numpy()
 
@@ -718,13 +701,8 @@ def update_chart(n_clicks,
         Iterations = float(c1_iter)
         Lbath = float(c1_volume) / float(surface_area)
 
-        try:
-            medians, lowers, uppers = ExtractMonteCarlo(soluteData, Solvent_PI, w, ExtractionT, Polymer_Tg, Solvent_Name, Solvent_MW,
+        medians, lowers, uppers = ExtractMonteCarlo(soluteData, Solvent_PI, w, ExtractionT, Polymer_Tg, Solvent_Name, Solvent_MW,
                                                     ExtractionTime, Swell, Iterations, CHRIS_category, L, Lbath, N)
-        except Exception:
-            debug.append("c1 FAILED")
-            debug.append(traceback.format_exc())
-            return no_update, "\n".join(debug)
 
     df['Condition 1'] = medians
     df['Cond1_err_plus'] = uppers-medians
@@ -758,8 +736,8 @@ def update_chart(n_clicks,
     df['Cond2_err_minus'] = medians - lowers
 
     fig = build_figure(df)
-    debug.append(f"fig ok total {time.time() - t0:.2f}s")
-    return fig, "\n".join(debug)
+
+    return fig
 
 def ConservativeMonteCarlo(soluteData, CHRIS_category, L, time, N):