l2f 2.0.9

Python bindings for the L2F (Learning to Fly) Simulator

L2F: Learning to Fly Simulator

pip install l2f

This repo contains Python bindings for the simulator introduced in Learning to Fly in Seconds.

Please check the example for how to use it.

CUDA

For the CUDA usage please refer to rl-tools/l2f-benchmark

Getting Started

pip install l2f ui-server

ui-server

import l2f
import asyncio, websockets, json
device = l2f.Device()
rng = l2f.Rng()
env = l2f.Environment()
ui = l2f.UI()
params = l2f.Parameters()
state = l2f.State()
next_state = l2f.State()
l2f.initialize_environment(device, env)
l2f.initialize_rng(device, rng, 0)
l2f.sample_initial_parameters(device, env, params, rng)
l2f.initial_state(device, env, params, state)
async def main():
    uri = "ws://localhost:13337/backend"
    async with websockets.connect(uri) as websocket:
        handshake = json.loads(await websocket.recv(uri))
        assert(handshake["channel"] == "handshake")
        namespace = handshake["data"]["namespace"]
        ui.ns = namespace
        ui_message = l2f.set_ui_message(device, env, ui)
        parameters_message = l2f.set_parameters_message(device, env, params, ui)
        await websocket.send(ui_message)
        await websocket.send(parameters_message)
        for _ in range(100):
            action = [1, 0, 0, 0]
            dt = l2f.step(device, env, params, state, action, next_state, rng)
            state.assign(next_state)
            state_action_message = l2f.set_state_action_message(device, env, params, ui, state, action)
            await websocket.send(state_action_message)
            await asyncio.sleep(dt)
if __name__ == "__main__":
    asyncio.run(main())