| |
| """DTW score: re-simulated trajectories vs baked ground truth, per active object. |
| |
| Usage: |
| python score_dtw.py --world work/B_03/world --sims work/B_03/out_p1 work/B_03/out_p2 |
| """ |
| import argparse |
| import json |
| from pathlib import Path |
|
|
| import numpy as np |
|
|
|
|
| def dtw(a, b): |
| """Mean-per-step DTW cost between two (F,3) trajectories.""" |
| n, m = len(a), len(b) |
| D = np.full((n + 1, m + 1), np.inf) |
| D[0, 0] = 0.0 |
| for i in range(1, n + 1): |
| for j in range(1, m + 1): |
| c = float(np.linalg.norm(a[i - 1] - b[j - 1])) |
| D[i, j] = c + min(D[i - 1, j - 1], D[i, j - 1], D[i - 1, j]) |
| return D[n, m] / (n + m) |
|
|
|
|
| def main(): |
| ap = argparse.ArgumentParser() |
| ap.add_argument("--world", required=True) |
| ap.add_argument("--sims", nargs="+", required=True) |
| ap.add_argument("--out", default=None, help="write JSON here too") |
| args = ap.parse_args() |
|
|
| world = Path(args.world) |
| names = [p.stem for p in (world / "dyn").glob("*.npz")] |
| report = {} |
| for sim in args.sims: |
| traj = np.load(Path(sim) / "simtraj.npz") |
| sim_names = [k for k in traj.files if k in names and k != "Ball"] |
| per = {} |
| for n in sorted(sim_names): |
| truth = np.load(world / "dyn" / f"{n}.npz")["pos"].astype(np.float64).mean(axis=1) |
| sim_t = traj[n].astype(np.float64) |
| per[n] = round(dtw(truth, sim_t), 5) |
| report[sim] = { |
| "per_object": per, |
| "mean": round(float(np.mean(list(per.values()))) if per else None, 5), |
| } |
| print(json.dumps({sim: report[sim]}, indent=1)) |
|
|
| if args.out: |
| Path(args.out).write_text(json.dumps(report, indent=1)) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
