"""Post hoc two-arm weight diagnostic on an already-spent trajectory."""
from pathlib import Path
from datetime import datetime, timezone
from dataclasses import replace
import hashlib
import json
import subprocess
import sys

ROOT = Path(__file__).resolve().parents[1]
SOURCE = ROOT / '.worktrees/ins-stability-dev'
sys.path[:0] = [str(SOURCE/'src'), str(SOURCE)]
import numpy as np
import scipy
from pydantic import BaseModel, ConfigDict
from calibrex.core.ins_lidar_hand_eye import load_ins_lidar_hand_eye
from calibrex.data.kitti_ins_lidar import load_kitti_ins_lidar_drive
from calibrex.evaluation.ins_lidar_hand_eye import (
    InsLidarRunOptions, build_sensor_motions, evaluate_ins_lidar_hand_eye,
    build_ins_lidar_artifact, KITTI_LIMITATIONS,
)
from calibrex.solvers.trajectory_hand_eye_solver import ReferenceTrajectory

def sha(path):
    return hashlib.sha256(path.read_bytes()).hexdigest()

OUT = ROOT/'outputs/ins-lidar-translation-weight-study-v1'
OUT.mkdir(exist_ok=False)
PREVIOUS = ROOT/'outputs/ins-registration-quality-development-v2'
prior = json.loads((PREVIOUS/'report.json').read_text())
baseline = load_ins_lidar_hand_eye(PREVIOUS/'baseline.yaml')
assert sha(PREVIOUS/'odometry.npz') == prior['provenance']['odometry_sha256']
receipt_path = ROOT/'outputs/ins-lidar-sota-evaluation-inputs-v1/2011_09_29_0071/acquisition.json'
receipt = json.loads(receipt_path.read_text())
drive = load_kitti_ins_lidar_drive(receipt_path.parent/receipt['sequence_dir'])
assert hashlib.sha256(drive.input_sha256.encode('ascii')).hexdigest() == baseline.provenance.input_sha256
cache = np.load(PREVIOUS/'odometry.npz', allow_pickle=False)
reference = ReferenceTrajectory(drive.trajectory.times_s, drive.trajectory.poses)
commit = subprocess.check_output(['git','-C',str(SOURCE),'rev-parse','HEAD'],text=True).strip()
assert not subprocess.check_output(['git','-C',str(SOURCE),'status','--porcelain','--','src','tools'])
rows = {}
for label, multiplier in [('baseline',1.0), ('translation_noise_x10',10.0)]:
    opts = InsLidarRunOptions()
    opts = replace(opts, solver=replace(opts.solver,
        translation_sigma_floor_m=opts.solver.translation_sigma_floor_m*multiplier,
        translation_sigma_per_m=opts.solver.translation_sigma_per_m*multiplier))
    motions = build_sensor_motions(cache['times_s'].tolist(), cache['poses'], opts)
    evaluation = evaluate_ins_lidar_hand_eye(reference, motions, opts,
                                            reference_transform=drive.vendor_t_imu_lidar)
    artifact = build_ins_lidar_artifact(evaluation, opts, odometry=baseline.odometry,
        provenance=baseline.provenance.model_copy(update={'generator':Path(__file__).name,
            'git_commit':commit,'command':[Path(__file__).name,label,'POST_HOC_DEVELOPMENT_ONLY'],
            'created_at':datetime.now(timezone.utc).isoformat()}),
        reference_calibration=baseline.reference_calibration, limitations=KITTI_LIMITATIONS)
    artifact.save(OUT/(label+'.yaml'))
    if multiplier == 1:
        assert [d.model_dump() for d in artifact.dofs] == [d.model_dump() for d in baseline.dofs]
    rows[label] = {'translation_noise_multiplier':multiplier,
        'artifact_sha256':sha(OUT/(label+'.yaml')), 'calibrated_dofs':artifact.calibrated_dofs,
        'rotation':[d.model_dump(mode='json') for d in artifact.dofs[:3]]}

class Report(BaseModel):
    model_config = ConfigDict(extra='forbid')
    schema_version: str = 'calibrex.ins_lidar_translation_weight_study/v0.1'
    scope: str
    cases: dict
    provenance: dict

report = Report(scope='POST HOC DEVELOPMENT ONLY, spent KITTI 0071 first 600 scans. '
    'Two arms declared before fitting: existing noise model and translation sigma floor/per-m '
    'terms both multiplied by 10. Same cached LiDAR-only poses, data, block split, clock/scale '
    'nuisance settings, no priors, 0.1 degree observability ceiling, control threshold and '
    'holdout limits. This changes the statistical weighting and must not be interpreted '
    'as new evidence merely because a reported uncertainty changes. No new SOTA claim.',
    cases=rows, provenance={'source_commit':commit,'script_sha256':sha(Path(__file__)),
        'baseline_sha256':sha(PREVIOUS/'baseline.yaml'),'odometry_sha256':sha(PREVIOUS/'odometry.npz'),
        'input_sha256':baseline.provenance.input_sha256,'receipt_sha256':sha(receipt_path),
        'created_at':datetime.now(timezone.utc).isoformat(),'numpy':np.__version__,
        'scipy':scipy.__version__,'new_accuracy_claim':False})
(OUT/'report.json').write_text(report.model_dump_json(indent=2)+'\n',encoding='utf-8')
(OUT/'report.schema.json').write_text(json.dumps(Report.model_json_schema(),indent=2)+'\n',encoding='utf-8')
print(report.model_dump_json(indent=2))