Files
calibration/imu_lidar/phase_a_replay.py
T

291 lines
9.9 KiB
Python

"""Cached Phase-A replay: rehydrate gyro factors, compare variants, write reports."""
from __future__ import annotations
import json
from collections import defaultdict
from pathlib import Path
from typing import Any
import numpy as np
from .imu_io import load_imu_samples
from .motion_pairs_io import (
build_motion_pairs_payload,
load_motion_pairs,
pair_from_dict,
save_motion_pairs,
)
from .phase_a import (
ProgressCallback,
phase_a_comparison_to_dict,
phase_a_metadata_complete,
rehydrate_phase_a_pairs,
solve_phase_a_comparison,
)
from .vehicle_config import load_vehicle_config, prior_enabled
def _rotation_prior(
vehicle_config_path: Path,
) -> tuple[np.ndarray | None, float]:
config = load_vehicle_config(vehicle_config_path)
if not prior_enabled(config, "rotation_prior"):
return None, 15.0
prior = (config.get("initialization") or {}).get("rotation_prior") or {}
matrix = prior.get("R_IMU_lidar")
if matrix is None:
return None, float(prior.get("sigma_deg", 15.0))
return (
np.asarray(matrix, dtype=float).reshape(3, 3),
float(prior.get("sigma_deg", 15.0)),
)
def _sanitize_json(value: Any) -> Any:
if isinstance(value, dict):
return {str(key): _sanitize_json(item) for key, item in value.items()}
if isinstance(value, (list, tuple)):
return [_sanitize_json(item) for item in value]
if isinstance(value, np.ndarray):
return _sanitize_json(value.tolist())
if isinstance(value, (np.floating, float)):
number = float(value)
return number if np.isfinite(number) else None
if isinstance(value, (np.integer, np.bool_)):
return value.item()
return value
def _write_json(path: Path, payload: Any) -> None:
path.write_text(
json.dumps(_sanitize_json(payload), indent=2, ensure_ascii=False) + "\n",
encoding="utf-8",
)
def _load_cached_sessions(
motion_pairs_path: Path,
) -> tuple[
dict[str, Any],
list,
dict[str, np.ndarray],
dict[str, float],
]:
payload = load_motion_pairs(motion_pairs_path)
pairs = []
biases: dict[str, np.ndarray] = {}
offsets: dict[str, float] = {}
for session in payload.get("sessions") or []:
session_id = str(session["session_id"])
biases[session_id] = np.asarray(
session.get("gyro_bias_rad_s", np.zeros(3)),
dtype=float,
).reshape(3)
offsets[session_id] = float(session.get("delta_t_s", 0.0))
pairs.extend(
pair_from_dict(item)
for item in session.get("pairs") or []
)
if not pairs:
raise ValueError(f"motion-pair cache is empty: {motion_pairs_path}")
return payload, pairs, biases, offsets
def run_phase_a_replay(
*,
motion_pairs_path: Path,
vehicle_config_path: Path,
output_directory: Path,
imu_paths_by_session: dict[str, Path] | None = None,
excluded_sessions: set[str] | None = None,
strong_rotation_min_deg: float = 1.0,
decorrelation_block_s: float = 3.0,
max_pairs_per_block: int = 1,
bias_prior_sigma_rad_s: float = 0.002,
yaw_std_max_deg: float = 0.5,
leave_one_out_yaw_range_max_deg: float = 1.0,
data_prior_difference_max_deg: float = 1.0,
max_nfev: int = 200,
progress_callback: ProgressCallback | None = None,
) -> dict[str, Any]:
"""Run Phase-A only. Existing LiDAR relative motions are never recomputed."""
output_directory.mkdir(parents=True, exist_ok=True)
source_payload, pairs, bias0, offsets = _load_cached_sessions(
motion_pairs_path
)
session_ids = sorted(bias0)
if progress_callback is not None:
progress_callback(
"cache_loaded",
{
"schema_version": source_payload.get("schema_version"),
"sessions": len(session_ids),
"pairs": len(pairs),
},
)
rehydration_report: dict[str, Any] = {
"required": not phase_a_metadata_complete(pairs),
"pair_count": len(pairs),
}
if not phase_a_metadata_complete(pairs):
supplied_paths = {} if imu_paths_by_session is None else imu_paths_by_session
missing = [sid for sid in session_ids if sid not in supplied_paths]
if missing:
raise ValueError(
"v1 cache lacks J_bg/cov; provide --session-imu for: "
+ ", ".join(missing)
)
imu_by_session = {
sid: load_imu_samples(supplied_paths[sid])
for sid in session_ids
}
pairs, details = rehydrate_phase_a_pairs(
pairs,
imu_by_session=imu_by_session,
bias0_by_session=bias0,
progress_callback=progress_callback,
)
rehydration_report.update(details)
if float(details["max_R_A_error_deg"]) > 0.05:
raise ValueError(
"rehydrated IMU rotations do not match cached R_A: "
f"max error={details['max_R_A_error_deg']:.6f} deg; "
"check session-to-IMU path mapping"
)
grouped: dict[str, list] = defaultdict(list)
for pair in pairs:
grouped[pair.session_id].append(pair)
enriched_payload = build_motion_pairs_payload(
prepared_sessions=[
{
"session_id": sid,
"time_offset_s": offsets[sid],
"gyro_bias_rad_s": bias0[sid],
"pairs": tuple(grouped[sid]),
}
for sid in session_ids
]
)
enriched_cache_path = save_motion_pairs(
output_directory / "motion_pairs_phase_a_v2.json",
enriched_payload,
)
rotation_prior, rotation_prior_sigma_deg = _rotation_prior(
vehicle_config_path
)
comparison = solve_phase_a_comparison(
pairs,
gyro_bias_rad_s_by_session=bias0,
rotation_prior=rotation_prior,
rotation_prior_sigma_deg=rotation_prior_sigma_deg,
preexcluded_session_ids=excluded_sessions,
strong_rotation_min_deg=strong_rotation_min_deg,
decorrelation_block_s=decorrelation_block_s,
max_pairs_per_block=max_pairs_per_block,
bias_prior_sigma_rad_s=bias_prior_sigma_rad_s,
yaw_std_max_deg=yaw_std_max_deg,
leave_one_out_yaw_range_max_deg=(
leave_one_out_yaw_range_max_deg
),
data_prior_difference_max_deg=data_prior_difference_max_deg,
run_leave_one_out=True,
max_nfev=max_nfev,
progress_callback=progress_callback,
)
full = phase_a_comparison_to_dict(comparison)
full["input"] = {
"motion_pairs": str(motion_pairs_path),
"source_schema_version": source_payload.get("schema_version"),
"vehicle_config": str(vehicle_config_path),
"session_imu_paths": {
sid: str(path)
for sid, path in (imu_paths_by_session or {}).items()
},
"excluded_sessions": sorted(excluded_sessions or set()),
}
full["rehydration"] = rehydration_report
full["enriched_cache"] = str(enriched_cache_path)
full["parameters"] = {
"strong_rotation_min_deg": strong_rotation_min_deg,
"decorrelation_block_s": decorrelation_block_s,
"max_pairs_per_block": max_pairs_per_block,
"bias_prior_sigma_rad_s": bias_prior_sigma_rad_s,
"rotation_prior_sigma_deg": rotation_prior_sigma_deg,
"yaw_std_max_deg": yaw_std_max_deg,
"leave_one_out_yaw_range_max_deg": (
leave_one_out_yaw_range_max_deg
),
"data_prior_difference_max_deg": (
data_prior_difference_max_deg
),
"max_nfev": max_nfev,
}
variants = full["variants"]
summary = {
"status": comparison.solution_status,
"accepted": comparison.accepted,
"partial_accepted": comparison.partial_accepted,
"acceptance_checks": comparison.acceptance_checks,
"primary_result": comparison.recommended_result,
"variants": {
name: {
"rpy_deg_xyz": item["rpy_deg_xyz"],
"R_IMU_lidar": item["R_IMU_lidar"],
"residual_rms_deg": item["residual_rms_deg"],
"residual_p95_deg": item["residual_p95_deg"],
"accepted": item["accepted"],
"gyro_bias_rad_s_per_session": item[
"gyro_bias_rad_s_per_session"
],
}
for name, item in variants.items()
if item is not None
},
"marginal_observability_A1": full[
"marginal_observability_A1"
],
"data_vs_prior_yaw_diff_deg": (
comparison.data_vs_prior_yaw_diff_deg
),
"data_vs_prior_geodesic_deg": (
comparison.data_vs_prior_geodesic_deg
),
"leave_one_out_yaw_range_deg": (
comparison.leave_one_out_yaw_range_deg
),
"leave_one_out_observable_max_deg": (
comparison.leave_one_out_observable_max_deg
),
"strong_pair_candidate_count": (
comparison.strong_pair_candidate_count
),
"decorrelated_pair_count": comparison.decorrelated_pair_count,
"strong_pair_counts_per_session": (
comparison.strong_pair_counts_per_session
),
"excluded_sessions": list(comparison.excluded_sessions),
"rehydration": rehydration_report,
"comparison_file": "phase_a_comparison.json",
"observability_file": "phase_a_observability.json",
"leave_one_out_file": "phase_a_leave_one_out.json",
"enriched_cache_file": enriched_cache_path.name,
}
_write_json(output_directory / "phase_a_comparison.json", full)
_write_json(
output_directory / "phase_a_observability.json",
full["marginal_observability_A1"],
)
_write_json(
output_directory / "phase_a_leave_one_out.json",
full["leave_one_out"],
)
_write_json(output_directory / "phase_a_summary.json", summary)
return summary