Update app.py

app.py

@@ -241,7 +241,7 @@ st.title("Advanced Cell Evolution Simulation")
 
 num_steps = st.slider("Number of simulation steps", 100, 2000, 1000)
 initial_cells = st.slider("Initial number of cells", 10, 200, 100)
-update_interval = st.slider("Update interval (milliseconds)", 50, 500, 100)
+update_interval = st.slider("Update interval (steps)", 1, 50, 10)
 
 if st.button("Run Simulation"):
     env = Environment(100, 100)
@@ -255,31 +255,36 @@ if st.button("Run Simulation"):
     fig = setup_figure(env)
     chart = st.plotly_chart(fig, use_container_width=True)
     
+    # Create a progress bar
+    progress_bar = st.progress(0)
+    
     # Run simulation
     for step in range(num_steps):
         env.update()
         
-        # Update the figure data
-        with fig.batch_update():
-            cell_data, population_history = env.get_visualization_data()
-            for i, (cell_type, data) in enumerate(cell_data.items()):
-                fig.data[i].x = data["x"]
-                fig.data[i].y = data["y"]
-                fig.data[i].marker.size = data["size"]
+        # Update the figure data and chart less frequently
+        if step % update_interval == 0 or step == num_steps - 1:
+            with fig.batch_update():
+                cell_data, population_history = env.get_visualization_data()
+                for i, (cell_type, data) in enumerate(cell_data.items()):
+                    fig.data[i].x = data["x"]
+                    fig.data[i].y = data["y"]
+                    fig.data[i].marker.size = data["size"]
+                
+                for i, (cell_type, counts) in enumerate(population_history.items()):
+                    fig.data[i+5].y = counts  # +5 because we have 5 cell types in the first subplot
+                    if cell_type != "modified" and cell_type != "plant_like":
+                        fig.data[i+10].y = counts  # Update individual population charts
+                    else:
+                        fig.data[13].y = population_history["plant_like"]
+                        fig.data[14].y = population_history["modified"]
             
-            for i, (cell_type, counts) in enumerate(population_history.items()):
-                fig.data[i+5].y = counts  # +5 because we have 5 cell types in the first subplot
-                if cell_type != "modified" and cell_type != "plant_like":
-                    fig.data[i+10].y = counts  # Update individual population charts
-                else:
-                    fig.data[13].y = population_history["plant_like"]
-                    fig.data[14].y = population_history["modified"]
-        
-        fig.layout.title.text = f"Advanced Cell Evolution Simulation (Time: {env.time})"
-        
-        # Update the chart
-        chart.plotly_chart(fig, use_container_width=True)
+            fig.layout.title.text = f"Advanced Cell Evolution Simulation (Time: {env.time})"
+            
+            # Update the chart
+            chart.plotly_chart(fig, use_container_width=True)
         
-        time.sleep(update_interval / 1000)  # Convert milliseconds to seconds
+        # Update progress bar
+        progress_bar.progress((step + 1) / num_steps)
 
     st.write("Simulation complete!")