| |
| """Measure motion after the actual PDO target stops; read original native CSV.""" |
| import argparse |
| import hashlib |
| import json |
| from pathlib import Path |
|
|
| import numpy as np |
| import pandas as pd |
|
|
|
|
| def main(): |
| parser = argparse.ArgumentParser(__doc__) |
| parser.add_argument("csv", type=Path) |
| parser.add_argument("--output", required=True, type=Path) |
| args = parser.parse_args() |
| cols = ["elapsed_s", "cycle", "axis", "position_rad", "target_position_rad", |
| "enabled", "fault", "error_code", "active_mode", "operational"] |
| df = pd.read_csv(args.csv, comment="#", usecols=cols) |
| if df.duplicated(["cycle", "axis"]).any(): |
| raise ValueError("duplicate cycle/axis") |
| arrays = {c: df.pivot(index="cycle", columns="axis", values=c).to_numpy() |
| for c in cols if c not in ("cycle", "axis")} |
| if arrays["position_rad"].shape[1] != 6: |
| raise ValueError("expected six axes") |
| t = arrays["elapsed_s"][:, 0] |
| q, u = arrays["position_rad"], arrays["target_position_rad"] |
| valid = (np.isfinite(q).all(axis=1) & np.isfinite(u).all(axis=1) |
| & (arrays["enabled"] == 1).all(axis=1) |
| & (arrays["fault"] == 0).all(axis=1) |
| & (arrays["error_code"] == 0).all(axis=1) |
| & (arrays["active_mode"] == 8).all(axis=1) |
| & (arrays["operational"] == 1).all(axis=1)) |
| constant = np.r_[False, (np.abs(np.diff(u, axis=0)) < 1e-10).all(axis=1)] |
| constant &= valid & np.r_[False, valid[:-1]] |
| constant &= np.r_[False, (np.diff(t) > 0) & (np.diff(t) < .01)] |
| edges = np.diff(np.r_[False, constant, False].astype(int)) |
| records, segments = [], [] |
| for start, end in zip(np.flatnonzero(edges == 1), np.flatnonzero(edges == -1)): |
| if t[end-1] - t[start] < 3: |
| continue |
| local_t = t[start:end] - t[start] |
| actual = np.degrees(q[start:end]) |
| record = {"start_s": float(t[start]), "duration_s": float(local_t[-1])} |
| for name, lo, hi in [("first_3s", 0, 3), ("after_0p5_to_3s", .5, 3), |
| ("after_3s", 3, float("inf"))]: |
| sample = actual[(local_t >= lo) & (local_t < hi)] |
| record[name + "_ptp_deg"] = np.ptp(sample, axis=0).tolist() if len(sample) else None |
| record["final_error_deg"] = np.degrees(u[end-1] - q[end-1]).tolist() |
| |
| |
| record["last_departure_0p02deg_s"] = [ |
| float(local_t[np.flatnonzero(np.abs(actual[:, j]-actual[-1, j]) > .02)[-1]]) |
| if np.any(np.abs(actual[:, j]-actual[-1, j]) > .02) else 0.0 |
| for j in range(6)] |
| records.append(record) |
| segments.append((start, end)) |
| if not records: |
| raise ValueError("no healthy constant-target holds >=3 s") |
| sha = hashlib.sha256() |
| with args.csv.open("rb") as source: |
| for block in iter(lambda: source.read(1024*1024), b""): |
| sha.update(block) |
| report = {"source": str(args.csv), "sha256": sha.hexdigest(), "hold_count": len(records), |
| "max_after_0p5_to_3s_ptp_deg": np.max( |
| [r["after_0p5_to_3s_ptp_deg"] for r in records], axis=0).tolist(), |
| "holds": records} |
| args.output.mkdir(parents=True, exist_ok=True) |
| (args.output / "report.json").write_text(json.dumps(report, indent=2) + "\n") |
| import matplotlib |
| matplotlib.use("Agg") |
| import matplotlib.pyplot as plt |
| worst = int(np.argmax([max(r["after_0p5_to_3s_ptp_deg"]) for r in records])) |
| start, end = segments[worst] |
| fig, axes = plt.subplots(3, 2, figsize=(11, 8), sharex=True) |
| for j, ax in enumerate(axes.flat): |
| ax.plot(t[start:end]-t[start], np.degrees(q[start:end, j]-u[start, j]), label="actual - target") |
| ax.axhline(0, color="black", lw=.7, label="constant PDO target") |
| ax.set(title=f"J{j+1}", ylabel="error (deg)", xlabel="time after target stops (s)") |
| ax.grid(alpha=.3) |
| axes[0, 0].legend() |
| fig.suptitle(f"Native PDO hold at {t[start]:.3f} s; target constant on all six axes") |
| fig.tight_layout() |
| fig.savefig(args.output / "worst_hold.png", dpi=150) |
| print(json.dumps({k: v for k, v in report.items() if k != "holds"}, indent=2)) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
