Update app.py

app.py

@@ -375,8 +375,10 @@ def predict_inverse(antimicrobial_activity_target, substrate, microorganism, num
                     domain.append({'name': str(one_hot_column), 'type': 'categorical', 'domain': (1.0, 1.0)})
                 else:
                     domain.append({'name': str(one_hot_column), 'type': 'categorical', 'domain': (0.0, 0.0)})
-        #elif df_column == 'Washing_cycles':
-         #   domain.append({'name': str(df_column), 'type': 'categorical', 'domain': (int(num_washing_cycles), int(num_washing_cycles))})
+        elif df_column == 'Washing_cycles':
+            washing_cycles_target_df = pd.DataFrame({'Washing_cycles':[reduction_target]})
+            washing_cycles_target_df = scale_numerical(reduction_target_df, ['Washing_cycles'], scaler=minmax_scaler_targets, fit=False)
+            domain.append({'name': str(df_column), 'type': 'continuous', 'domain': (washing_cycles_target_df, washing_cycles_target_df)})
         elif df_column in numerical_columns:
             domain.append({'name': str(df_column), 'type': 'continuous', 'domain': (0.,1.)})
         else: