Update app.py

app.py

@@ -296,83 +296,74 @@ def toggle_simulation():
 
 start_stop_button = st.button("Start/Stop Simulation", on_click=toggle_simulation)
 
-def run_simulation():
-    while True:
-        if st.session_state.running:
-            for _ in range(4):  # Update 4 times per frame to increase simulation speed
-                initial_cell_count = len(st.session_state.env.cells)
-                st.session_state.env.update()
-                final_cell_count = len(st.session_state.env.cells)
-                
-                # Check for merges
-                if final_cell_count < initial_cell_count:
-                    merges = initial_cell_count - final_cell_count
-                    st.session_state.total_merges += merges
-                    event_log.appendleft(f"Time {st.session_state.env.time}: {merges} cell merge(s) occurred!")
-
-                # Check for new cell types
-                for cell in st.session_state.env.cells:
-                    if cell.cell_type not in st.session_state.env.population_history:
-                        event_log.appendleft(f"Time {st.session_state.env.time}: New cell type '{cell.cell_type}' emerged!")
-
-        time.sleep(update_interval)
+def run_simulation_step():
+    if st.session_state.running and st.session_state.env is not None:
+        for _ in range(4):  # Update 4 times per frame to increase simulation speed
+            initial_cell_count = len(st.session_state.env.cells)
+            st.session_state.env.update()
+            final_cell_count = len(st.session_state.env.cells)
+            
+            # Check for merges
+            if final_cell_count < initial_cell_count:
+                merges = initial_cell_count - final_cell_count
+                st.session_state.total_merges += merges
+                event_log.appendleft(f"Time {st.session_state.env.time}: {merges} cell merge(s) occurred!")
+
+            # Check for new cell types
+            for cell in st.session_state.env.cells:
+                if cell.cell_type not in st.session_state.env.population_history:
+                    event_log.appendleft(f"Time {st.session_state.env.time}: New cell type '{cell.cell_type}' emerged!")
+
+        update_chart()
 
 def update_chart():
-    while True:
-        if st.session_state.running and st.session_state.fig is not None:
-            with st.session_state.fig.batch_update():
-                cell_data, population_history, colors = st.session_state.env.get_visualization_data()
-                
-                # Update cell distribution
-                for i, (cell_type, data) in enumerate(cell_data.items()):
-                    st.session_state.fig.data[i].x = data["x"]
-                    st.session_state.fig.data[i].y = data["y"]
-                    st.session_state.fig.data[i].marker.size = data["size"]
-                
-                # Update total population
-                total_population = [sum(counts) for counts in zip(*population_history.values())]
-                st.session_state.fig.data[len(cell_data)].y = total_population
-                
-                # Update population by cell type
-                for i, (cell_type, counts) in enumerate(population_history.items()):
-                    st.session_state.fig.data[len(cell_data) + 1 + i].y = counts
-                
-                # Update organelle distribution
-                organelle_counts = {"nucleus": 0, "mitochondria": 0, "chloroplast": 0, "endoplasmic_reticulum": 0, "golgi_apparatus": 0}
-                for cell in st.session_state.env.cells:
-                    for organelle in cell.organelles:
-                        organelle_counts[organelle] += 1
-                st.session_state.fig.data[-1].y = list(organelle_counts.values())
-            
-            # Update live statistics
-            total_cells = len(st.session_state.env.cells)
-            total_cells_text.text(f"Total Cells: {format_number(total_cells)}")
-            
-            cell_type_counts = {cell_type: len([c for c in st.session_state.env.cells if c.cell_type == cell_type]) for cell_type in st.session_state.env.population_history.keys()}
-            cell_type_breakdown.text("Cell Type Breakdown:\n" + "\n".join([f"{cell_type}: {format_number(count)}" for cell_type, count in cell_type_counts.items()]))
+    if st.session_state.running and st.session_state.fig is not None:
+        with st.session_state.fig.batch_update():
+            cell_data, population_history, colors = st.session_state.env.get_visualization_data()
             
-            dominant_type = max(cell_type_counts, key=cell_type_counts.get)
-            dominant_type_text.text(f"Dominant Type: {dominant_type}")
+            # Update cell distribution
+            for i, (cell_type, data) in enumerate(cell_data.items()):
+                st.session_state.fig.data[i].x = data["x"]
+                st.session_state.fig.data[i].y = data["y"]
+                st.session_state.fig.data[i].marker.size = data["size"]
             
-            avg_energy = sum(cell.energy for cell in st.session_state.env.cells) / total_cells if total_cells > 0 else 0
-            avg_energy_text.text(f"Avg Energy: {avg_energy:.2f}")
+            # Update total population
+            total_population = [sum(counts) for counts in zip(*population_history.values())]
+            st.session_state.fig.data[len(cell_data)].y = total_population
             
-            total_merges_text.text(f"Total Merges: {st.session_state.total_merges}")
+            # Update population by cell type
+            for i, (cell_type, counts) in enumerate(population_history.items()):
+                st.session_state.fig.data[len(cell_data) + 1 + i].y = counts
             
-            # Update event log
-            event_log_text.text("Recent Events:\n" + "\n".join(event_log))
-            
-            chart_placeholder.plotly_chart(st.session_state.fig, use_container_width=True)
-
-        time.sleep(update_interval)
-
-# Start the simulation and chart update threads
-simulation_thread = threading.Thread(target=run_simulation)
-chart_thread = threading.Thread(target=update_chart)
-
-simulation_thread.start()
-chart_thread.start()
-
-# Keep the main thread alive
+            # Update organelle distribution
+            organelle_counts = {"nucleus": 0, "mitochondria": 0, "chloroplast": 0, "endoplasmic_reticulum": 0, "golgi_apparatus": 0}
+            for cell in st.session_state.env.cells:
+                for organelle in cell.organelles:
+                    organelle_counts[organelle] += 1
+            st.session_state.fig.data[-1].y = list(organelle_counts.values())
+        
+        # Update live statistics
+        total_cells = len(st.session_state.env.cells)
+        total_cells_text.text(f"Total Cells: {format_number(total_cells)}")
+        
+        cell_type_counts = {cell_type: len([c for c in st.session_state.env.cells if c.cell_type == cell_type]) for cell_type in st.session_state.env.population_history.keys()}
+        cell_type_breakdown.text("Cell Type Breakdown:\n" + "\n".join([f"{cell_type}: {format_number(count)}" for cell_type, count in cell_type_counts.items()]))
+        
+        dominant_type = max(cell_type_counts, key=cell_type_counts.get)
+        dominant_type_text.text(f"Dominant Type: {dominant_type}")
+        
+        avg_energy = sum(cell.energy for cell in st.session_state.env.cells) / total_cells if total_cells > 0 else 0
+        avg_energy_text.text(f"Avg Energy: {avg_energy:.2f}")
+        
+        total_merges_text.text(f"Total Merges: {st.session_state.total_merges}")
+        
+        # Update event log
+        event_log_text.text("Recent Events:\n" + "\n".join(event_log))
+        
+        chart_placeholder.plotly_chart(st.session_state.fig, use_container_width=True)
+
+# Main loop
 while True:
-    time.sleep(1)
+    run_simulation_step()
+    time.sleep(update_interval)
+    st.experimental_rerun()