Animation in SimPy: Making Simulations Come Alive

Published on February 26, 2026

Static charts tell a story. Animation tells it better. Watch your simulation unfold in real time. <h2 id="why-animate">Why Animate?</h2> <ul> <li>Debug visually - see when things go wrong</li> <li>Present to stakeholders - they understand pictures</li> <li>Build intuition - watch patterns emerge</li> <li>Validate - does the animation match reality?</li> </ul> <h2 id="matplotlib-animation-basics">matplotlib Animation Basics</h2> <div class="code-block"><pre><code>import simpy import matplotlib.pyplot as plt from matplotlib.animation import FuncAnimation import numpy as np class AnimatedSimulation: def __init__(self): self.time_data = [] self.queue_data = [] def run_step(self, env, server): """Run simulation and collect data.""" self.time_data.append(env.now) self.queue_data.append(len(server.queue)) def animate_queue(): fig, ax = plt.subplots() ax.set_xlim(0, 100) ax.set_ylim(0, 20) ax.set_xlabel('Time') ax.set_ylabel('Queue Length') line, = ax.plot([], [], lw=2) sim_data = AnimatedSimulation() def init(): line.set_data([], []) return line, def update(frame): # Update simulation sim_data.time_data.append(frame) sim_data.queue_data.append(np.random.poisson(5)) line.set_data(sim_data.time_data, sim_data.queue_data) return line, ani = FuncAnimation(fig, update, frames=range(100), init_func=init, blit=True, interval=100) plt.show() </code></pre></div> <h2 id="real-time-simulation-display">Real-Time Simulation Display</h2> <div class="code-block"><pre><code>import simpy.rt import matplotlib.pyplot as plt from matplotlib.animation import FuncAnimation import threading import queue class RealTimeDisplay: def __init__(self): self.data_queue = queue.Queue() self.times = [] self.values = [] def update_data(self, time, value): self.data_queue.put((time, value)) def run_animation(self): fig, ax = plt.subplots() ax.set_xlim(0, 100) ax.set_ylim(0, 20) line, = ax.plot([], [], lw=2) def update(frame): while not self.data_queue.empty(): t, v = self.data_queue.get() self.times.append(t) self.values.append(v) line.set_data(self.times, self.values) if self.times: ax.set_xlim(0, max(self.times) + 10) return line, ani = FuncAnimation(fig, update, interval=100) plt.show() # Run simulation in separate thread def simulation_thread(display): env = simpy.rt.RealtimeEnvironment(factor=0.1) server = simpy.Resource(env, capacity=2) def monitor(env, server, display): while True: display.update_data(env.now, len(server.queue)) yield env.timeout(1) env.process(monitor(env, server, display)) # ... add other processes env.run(until=100) display = RealTimeDisplay() sim_thread = threading.Thread(target=simulation_thread, args=(display,)) sim_thread.start() display.run_animation() </code></pre></div> <h2 id="simple-text-animation">Simple Text Animation</h2> For terminal-based visualisation: <div class="code-block"><pre><code>import time import os def clear_screen(): os.system('cls' if os.name == 'nt' else 'clear') def text_animation(env, server): while True: clear_screen() # Draw queue queue_len = len(server.queue) busy = server.count print(f"Time: {env.now:.1f}") print(f"Server: {'[BUSY]' * busy}{'[ ]' * (server.capacity - busy)}") print(f"Queue: {'o' * queue_len}") print(f"\nWaiting: {queue_len}, In service: {busy}") yield env.timeout(0.5) # Use with RealtimeEnvironment env = simpy.rt.RealtimeEnvironment(factor=1) server = simpy.Resource(env, capacity=2) env.process(text_animation(env, server)) </code></pre></div> <h2 id="pygame-visualisation">Pygame Visualisation</h2> For more sophisticated animation: <div class="code-block"><pre><code># Note: Requires pygame import pygame import simpy import random class PygameVisualisation: def __init__(self, width=800, height=600): pygame.init() self.screen = pygame.display.set_mode((width, height)) self.clock = pygame.time.Clock() self.width = width self.height = height # Simulation state self.entities = [] self.server_busy = False def draw(self): self.screen.fill((255, 255, 255)) # Draw server color = (255, 0, 0) if self.server_busy else (0, 255, 0) pygame.draw.rect(self.screen, color, (350, 250, 100, 100)) # Draw queue for i, entity in enumerate(self.entities): pygame.draw.circle(self.screen, (0, 0, 255), (100 + i * 30, 300), 10) # Update display pygame.display.flip() def update(self, queue_length, server_busy): self.entities = list(range(queue_length)) self.server_busy = server_busy # Handle events for event in pygame.event.get(): if event.type == pygame.QUIT: pygame.quit() return False return True # Integration with SimPy def simulation_with_pygame(vis): env = simpy.rt.RealtimeEnvironment(factor=0.5) server = simpy.Resource(env, capacity=1) def display_update(env, server, vis): while True: if not vis.update(len(server.queue), server.count > 0): break vis.draw() yield env.timeout(0.1) env.process(display_update(env, server, vis)) # ... add customers env.run(until=60) </code></pre></div> <h2 id="plotly-animation">Plotly Animation</h2> Interactive web-based animation: <div class="code-block"><pre><code>import plotly.graph_objects as go from plotly.subplots import make_subplots def create_animated_plot(time_series): """Create animated plot with Plotly.""" fig = go.Figure( data=[go.Scatter(x=[], y=[], mode='lines')], layout=go.Layout( xaxis=dict(range=[0, max(r['time'] for r in time_series)]), yaxis=dict(range=[0, max(r['queue'] for r in time_series) + 1]), title="Queue Length Animation", updatemenus=[dict( type="buttons", buttons=[dict(label="Play", method="animate", args=[None, {"frame": {"duration": 100}}])] )] ), frames=[ go.Frame(data=[go.Scatter( x=[r['time'] for r in time_series[:i]], y=[r['queue'] for r in time_series[:i]] )]) for i in range(1, len(time_series)) ] ) fig.write_html('animation.html') fig.show() </code></pre></div> <h2 id="gif-export">GIF Export</h2> <div class="code-block"><pre><code>from matplotlib.animation import FuncAnimation, PillowWriter def create_gif(time_series, filename='simulation.gif'): fig, ax = plt.subplots() times = [r['time'] for r in time_series] queues = [r['queue'] for r in time_series] ax.set_xlim(0, max(times)) ax.set_ylim(0, max(queues) + 1) ax.set_xlabel('Time') ax.set_ylabel('Queue Length') line, = ax.plot([], [], lw=2) def update(frame): line.set_data(times[:frame], queues[:frame]) return line, ani = FuncAnimation(fig, update, frames=len(times), interval=50) ani.save(filename, writer=PillowWriter(fps=20)) print(f"Saved animation to {filename}") </code></pre></div> <h2 id="live-dashboard-with-dash">Live Dashboard with Dash</h2> <div class="code-block"><pre><code># Note: Requires dash from dash import Dash, dcc, html from dash.dependencies import Input, Output import plotly.graph_objs as go app = Dash(__name__) # Shared data simulation_data = {'time': [], 'queue': []} app.layout = html.Div([ dcc.Graph(id='live-graph'), dcc.Interval(id='interval', interval=500) # Update every 500ms ]) @app.callback(Output('live-graph', 'figure'), Input('interval', 'n_intervals')) def update_graph(n): return { 'data': [go.Scatter( x=simulation_data['time'], y=simulation_data['queue'], mode='lines' )], 'layout': go.Layout( title='Live Queue Length', xaxis={'title': 'Time'}, yaxis={'title': 'Queue'} ) } # Run simulation in background, update simulation_data # app.run_server(debug=True) </code></pre></div> <h2 id="summary">Summary</h2> Animation options: - matplotlib - Simple, integrated - Terminal - Text-based, lightweight - Pygame - Game-like, interactive - Plotly - Web-based, interactive - Dash - Live dashboards Pick the right tool for your audience. <h2 id="next-steps">Next Steps</h2> <ul> <li><a href="/blog_posts/simpy-with-matplotlib.html">SimPy with matplotlib</a></li> <li><a href="/blog_posts/simpy-real-time-simulation.html">Real-Time Simulation</a></li> <li><a href="/blog_posts/simpy-visualize-results.html">Visualising Results</a></li> </ul>

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