| from __future__ import annotations |
|
|
| from pathlib import Path |
|
|
| import gradio as gr |
| import numpy as np |
| import plotly.graph_objects as go |
| from model import HamiltonianNetwork, VectorFieldNetwork |
| from physics import true_energy |
| from safetensors.torch import load_file |
| from train import rollout |
|
|
| ARTIFACT_DIR = Path(__file__).resolve().parent / "artifacts" / "hamiltonian-pocket" |
| HAMILTONIAN = HamiltonianNetwork() |
| HAMILTONIAN.load_state_dict( |
| load_file(ARTIFACT_DIR / "hamiltonian.safetensors") |
| ) |
| HAMILTONIAN.eval() |
| VECTOR_FIELD = VectorFieldNetwork() |
| VECTOR_FIELD.load_state_dict( |
| load_file(ARTIFACT_DIR / "vector_field.safetensors") |
| ) |
| VECTOR_FIELD.eval() |
|
|
|
|
| def simulate(angle: float, momentum: float, seconds: float) -> tuple[go.Figure, dict]: |
| initial = np.asarray([[angle, momentum]], dtype=np.float32) |
| steps = int(float(seconds) / 0.05) |
| trajectories = { |
| "Physics": rollout(None, initial, steps, 0.05)[:, 0], |
| "Hamiltonian network": rollout(HAMILTONIAN, initial, steps, 0.05)[:, 0], |
| "Black-box vector field": rollout( |
| VECTOR_FIELD, initial, steps, 0.05 |
| )[:, 0], |
| } |
| figure = go.Figure() |
| for name, trajectory in trajectories.items(): |
| figure.add_trace( |
| go.Scatter( |
| x=trajectory[:, 0], |
| y=trajectory[:, 1], |
| mode="lines", |
| name=name, |
| ) |
| ) |
| figure.update_layout( |
| title="Learned pendulum phase portrait", |
| xaxis_title="Angle", |
| yaxis_title="Momentum", |
| template="plotly_dark", |
| ) |
| initial_energy = float(true_energy(initial)[0]) |
| return figure, { |
| name: { |
| "final_energy": round(float(true_energy(path[-1:])[0]), 5), |
| "absolute_energy_drift": round( |
| abs(float(true_energy(path[-1:])[0]) - initial_energy), 5 |
| ), |
| } |
| for name, path in trajectories.items() |
| } |
|
|
|
|
| with gr.Blocks(title="Hamiltonian Pocket") as demo: |
| gr.Markdown( |
| "# Hamiltonian Pocket\n" |
| "Compare physics-structured and black-box neural dynamics over a long " |
| "pendulum rollout." |
| ) |
| with gr.Row(): |
| angle = gr.Slider(-3.0, 3.0, 1.5, step=0.1, label="Initial angle") |
| momentum = gr.Slider(-2.0, 2.0, 0.3, step=0.1, label="Initial momentum") |
| seconds = gr.Slider(2, 20, 10, step=1, label="Simulated seconds") |
| run = gr.Button("Roll out dynamics", variant="primary") |
| phase = gr.Plot() |
| energy = gr.JSON() |
| run.click(simulate, [angle, momentum, seconds], [phase, energy]) |
| demo.load(simulate, [angle, momentum, seconds], [phase, energy]) |
|
|
|
|
| if __name__ == "__main__": |
| demo.launch() |
|
|
