Update app.py

app.py

@@ -421,8 +421,8 @@ def predict_inverse(antimicrobial_activity_target, substrate, microorganism, num
             optimized_x.loc[0, column] = one_hot_mapping[column][int(optimized_x.loc[0, column])]
 
     return (optimized_x['Binder'].iloc[0], optimized_x['NMs_Type'].iloc[0], optimized_x['Primary_Size (nm)'].iloc[0],
-            optimized_x['NM-Shape'].iloc[0], optimized_x['Washing_cycles'].iloc[0], optimized_x['Concetration (µg/mL)'].iloc[0],
-            optimized_x['NPs_Synthesis_method'].iloc[0], optimized_x['Application method\n'].iloc[0],
+            optimized_x['NM-Shape'].iloc[0], optimized_x['Concetration (µg/mL)'].iloc[0],
+            optimized_x['NPs_Synthesis_method'].iloc[0], optimized_x['Application method\n'].iloc[0], optimized_x['Washing_cycles'].iloc[0], 
             optimized_x['Washing_Detergent'].iloc[0], optimized_x['Washing_Temp'].iloc[0])
 
 
@@ -474,15 +474,17 @@ with gr.Blocks(css=css_styling, title=page_title, theme=osium_theme) as demo:
             with gr.Row():
                 with gr.Column():
                     gr.Markdown("### Optimal conditions")
+                    gr.Markdown("### Optimal nanomaterial characteristics")
                     optimal_binder = gr.Text(label="Optimal binder")
                     optimal_nms_type = gr.Text(label="Optimal NMS type")
                     optimal_primary_size = gr.Text(label="Optimal primary size (nm)")
                     optimal_nm_shape = gr.Text(label="Optimal NM shape")
-                    # optimal_test_duration = gr.Text(label="Optimal duration (h)")
-                    optimal_washing_cycles = gr.Text(label="Optimal number of washing cycles")
+                    gr.Markdown("### Optimal nanomaterial application")
                     optimal_concentration = gr.Text(label="Optimal concentration (µg/mL)")
                     optimal_nps_synthesis = gr.Text(label="Optimal nps synthesis method")
                     optimal_application_method = gr.Text(label="Optimal application method")
+                    gr.Markdown("### Optimal washing conditions")
+                    optimal_washing_cycles = gr.Text(label="Optimal number of washing cycles")
                     optimal_washing_detergent = gr.Text(label="Optimal washing detergent")
                     optimal_washing_temperature = gr.Text(label="Optimal washing temperature")
 
@@ -494,9 +496,9 @@ with gr.Blocks(css=css_styling, title=page_title, theme=osium_theme) as demo:
     prediction_button.click(
         fn=predict_inverse,
         inputs=[antimicrobial_activity_target, substrate, microorganism, num_washing_cycles],
-        outputs=[optimal_binder, optimal_nms_type, optimal_primary_size, optimal_nm_shape, optimal_washing_cycles,
-                optimal_concentration, optimal_nps_synthesis, optimal_application_method, optimal_washing_detergent,
-                optimal_washing_temperature],
+        outputs=[optimal_binder, optimal_nms_type, optimal_primary_size, optimal_nm_shape, 
+                optimal_concentration, optimal_nps_synthesis, optimal_application_method, optimal_washing_cycles,
+                optimal_washing_detergent, optimal_washing_temperature],
         show_progress=True,
     )
     clear_button.click(
@@ -505,9 +507,9 @@ with gr.Blocks(css=css_styling, title=page_title, theme=osium_theme) as demo:
         [
             antimicrobial_activity_target,
             substrate, microorganism, num_washing_cycles,
-            optimal_binder, optimal_nms_type, optimal_primary_size, optimal_nm_shape, optimal_washing_cycles,
-            optimal_concentration, optimal_nps_synthesis, optimal_application_method, optimal_washing_detergent,
-            optimal_washing_temperature,
+            optimal_binder, optimal_nms_type, optimal_primary_size, optimal_nm_shape, 
+            optimal_concentration, optimal_nps_synthesis, optimal_application_method, optimal_washing_cycles,
+            optimal_washing_detergent, optimal_washing_temperature,
         ],
     )