Update app.py

app.py

@@ -4,6 +4,10 @@ import streamlit as st
 import plotly.graph_objects as go
 from plotly.subplots import make_subplots
 import time
+import threading
+import queue
+
+# Your classes and functions...
 
 class Organelle:
     def __init__(self, type):
@@ -236,15 +240,8 @@ def setup_figure(env):
 
     return fig
 
-import random
-import numpy as np
-import streamlit as st
-import plotly.graph_objects as go
-from plotly.subplots import make_subplots
-import time
-import threading
-
-# Your classes and functions...
+# Create a queue to communicate between the threads
+q = queue.Queue()
 
 # Streamlit app
 st.title("Advanced Cell Evolution Simulation")
@@ -255,53 +252,56 @@ update_interval = st.slider("Update interval (seconds)", 0.1, 5.0, 1.0)
 # Create a placeholder for the chart
 chart_placeholder = st.empty()
 
-# Create a button to start/stop the simulation
-if 'run_simulation' not in st.session_state:
-    st.session_state.run_simulation = False
-if 'env' not in st.session_state:
-    st.session_state.env = None
-if 'fig' not in st.session_state:
-    st.session_state.fig = None
+# Create a function to run the simulation
+def run_simulation():
+    env = Environment(100, 100)
+    for _ in range(initial_cells):
+        cell = Cell(random.uniform(0, env.width), random.uniform(0, env.height))
+        env.add_cell(cell)
+    fig = setup_figure(env)
+    
+    while True:
+        try:
+            q.get(timeout=0.1)
+            break
+        except queue.Empty:
+            pass
+        
+        env.update()
+        
+        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"]
+        
+        q.put(fig)
 
+# Create a function to start the simulation
 def start_simulation():
-    st.session_state.run_simulation = True
-    st.session_state.env = Environment(100, 100)
-    for _ in range(initial_cells):
-        cell = Cell(random.uniform(0, st.session_state.env.width), random.uniform(0, st.session_state.env.height))
-        st.session_state.env.add_cell(cell)
-    st.session_state.fig = setup_figure(st.session_state.env)
     thread = threading.Thread(target=run_simulation)
     thread.start()
 
+# Create a function to stop the simulation
 def stop_simulation():
-    st.session_state.run_simulation = False
+    q.put(None)
 
 start_button = st.button("Start Simulation", on_click=start_simulation)
 stop_button = st.button("Stop Simulation", on_click=stop_simulation)
 
-def run_simulation():
-    while st.session_state.run_simulation:
-        st.session_state.env.update()
-        
-        with st.session_state.fig.batch_update():
-            cell_data, population_history = st.session_state.env.get_visualization_data()
-            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"]
-            
-            for i, (cell_type, counts) in enumerate(population_history.items()):
-                st.session_state.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":
-                    st.session_state.fig.data[i+10].y = counts  # Update individual population charts
-                else:
-                    st.session_state.fig.data[13].y = population_history["plant_like"]
-                    st.session_state.fig.data[14].y = population_history["modified"]
-        
-        st.session_state.fig.layout.title.text = f"Advanced Cell Evolution Simulation (Time: {st.session_state.env.time})"
-        
-        # Update the chart
-        chart_placeholder.plotly_chart(st.session_state.fig, use_container_width=True)
-        
-        # Wait for the specified interval
-        time.sleep(update_interval)
+while True:
+    try:
+        fig = q.get(timeout=0.1)
+        chart_placeholder.plotly_chart(fig, use_container_width=True)
+    except queue.Empty:
+    time.sleep(0.1)
+    continue