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# Import necessary packages
import simpy
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D # for 3D plotting
from PIL import Image
import gradio as gr
import io
# Function for jet flight simulation using SimPy with 3D plot
def run_jet_simulation(max_altitude, climb_rate, acceleration, max_speed_kmph):
max_speed_mps = max_speed_kmph * 1000 / 3600
time_log = []
altitude_log = []
speed_log = []
def jet_process(env):
altitude = 0
speed = 0
while True:
if altitude < max_altitude:
altitude += climb_rate
if speed < max_speed_mps:
speed += acceleration
time_log.append(env.now)
altitude_log.append(min(altitude, max_altitude))
speed_log.append(min(speed, max_speed_mps))
yield env.timeout(1)
if altitude >= max_altitude and speed >= max_speed_mps:
break
env = simpy.Environment()
env.process(jet_process(env))
env.run(until=300)
# 3D Plotting
fig = plt.figure(figsize=(8, 6))
ax = fig.add_subplot(111, projection='3d')
ax.plot(time_log, altitude_log, speed_log, color='blue', label='Jet Climb Path')
ax.set_xlabel('Time (s)')
ax.set_ylabel('Altitude (m)')
ax.set_zlabel('Speed (m/s)')
ax.set_title('🛩️ 3D Jet Climb Simulation')
ax.legend()
# Save to buffer
buf = io.BytesIO()
plt.savefig(buf, format='png')
buf.seek(0)
return Image.open(buf)
# Gradio Interface
demo = gr.Interface(
fn=run_jet_simulation,
inputs=[
gr.Number(label="Max Altitude (meters)", value=10000),
gr.Number(label="Climb Rate (m/s)", value=50),
gr.Number(label="Acceleration (m/s²)", value=20),
gr.Number(label="Max Speed (km/h)", value=2500),
],
outputs=gr.Image(type="pil"),
title="🛩️ 3D Fighter Jet Simulation using SimPy",
description="Simulates a fighter jet’s altitude and speed climb in 3D space using SimPy and Matplotlib."
)
demo.launch()
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