Update app.py

app.py

@@ -239,11 +239,16 @@ def setup_figure(env):
 # Streamlit app
 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 (steps)", 1, 50, 10)
+update_interval = st.slider("Update interval (seconds)", 0.1, 5.0, 1.0)
 
-if st.button("Run Simulation"):
+# Create a placeholder for the chart
+chart_placeholder = st.empty()
+
+# Create a button to start/stop the simulation
+start_button = st.button("Start Simulation")
+
+if start_button:
     env = Environment(100, 100)
     
     # Add initial cells
@@ -253,38 +258,38 @@ if st.button("Run Simulation"):
     
     # Set up the figure
     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):
+    while True:
         env.update()
         
-        # 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"]
-            
-            fig.layout.title.text = f"Advanced Cell Evolution Simulation (Time: {env.time})"
+        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 chart
-            chart.plotly_chart(fig, use_container_width=True)
+            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"]
         
-        # Update progress bar
-        progress_bar.progress((step + 1) / num_steps)
+        fig.layout.title.text = f"Advanced Cell Evolution Simulation (Time: {env.time})"
+        
+        # Update the chart
+        chart_placeholder.plotly_chart(fig, use_container_width=True)
+        
+        # Wait for the specified interval
+        time.sleep(update_interval)
+
+        # Check if the Streamlit script should stop
+        if not st.session_state.get('run_simulation', True):
+            break
 
-    st.write("Simulation complete!")
+# Add a button to stop the simulation
+if st.button("Stop Simulation"):
+    st.session_state.run_simulation = False