Update app.py

app.py

@@ -379,8 +379,8 @@ def predict_inverse(antimicrobial_activity_target, substrate, microorganism, num
             washing_cycles_target_df = pd.DataFrame([[0]*len(numerical_columns)], columns=numerical_columns)
             washing_cycles_target_df['Washing_cycles'].iloc[0] = int(num_washing_cycles)
             washing_cycles_target_df = scale_numerical(washing_cycles_target_df, numerical_columns, scaler=minmax_scaler_inputs, fit=False)
-            domain.append({'name': str(df_column), 'type': 'continuous', 'domain': (washing_cycles_target_df["Washing_cycles"],
-                                                                                    washing_cycles_target_df["Washing_cycles"])})
+            domain.append({'name': str(df_column), 'type': 'continuous', 'domain': (washing_cycles_target_df["Washing_cycles"].iloc[0],
+                                                                                    washing_cycles_target_df["Washing_cycles"].iloc[0])})
         elif df_column in numerical_columns:
             domain.append({'name': str(df_column), 'type': 'continuous', 'domain': (0.,1.)})
         else: