#!/usr/bin/env python3
"""Rebuild the two CSV tables from JSON inside the unchanged scientific ZIP."""
from __future__ import annotations
import argparse
import csv
import hashlib
import json
from pathlib import Path
import statistics
import zipfile


def export(archive, output):
    output.mkdir(parents=True, exist_ok=False)
    prefix = 'Eidrion_v1.0.0/'
    with zipfile.ZipFile(archive) as z:
        aggregate = json.loads(z.read(prefix + 'experiments/final_standard/aggregate_results.json'))
        summary = []
        for dataset, methods in aggregate['groups'].items():
            for method, g in methods.items():
                m = g['metrics']; a = m['final_micro_accuracy']
                summary.append({'dataset': dataset, 'method': method, 'n_seeds': a['n'],
                    'accuracy_mean': a['mean'], 'accuracy_std': a['std'],
                    'accuracy_t95_low': a['t95_low'], 'accuracy_t95_high': a['t95_high'],
                    'peak_persistent_payload_mean_bytes': m['peak_persistent_payload_bytes']['mean'],
                    'protected_class_count_mean': m['protected_class_count']['mean'],
                    'fit_mean_seconds': g['timing_seconds']['fit']['mean'],
                    'calibration_mean_seconds': g['timing_seconds']['calibration']['mean'],
                    'inference_batch1_mean_seconds': g['serial_inference_batch1_seconds']['mean']})
        per_run = []
        for name in sorted(n for n in z.namelist() if n.startswith(prefix + 'experiments/final_standard/runs/') and n.endswith('/result.json')):
            raw = z.read(name); d = json.loads(raw)
            keys = ['dataset', 'method', 'seed', 'status', 'final_micro_accuracy', 'final_macro_accuracy',
                'final_ece15_full10way_softmax', 'average_acquisition_task_accuracy',
                'average_incremental_seen_micro_accuracy', 'backward_transfer', 'forgetting',
                'forward_transfer_relative_to_initialization', 'protected_class_count',
                'peak_persistent_payload_bytes', 'process_peak_rss_kib', 'source_lock_sha256']
            row = {k: d[k] for k in keys}
            row.update(fit_seconds=d['timing_seconds']['fit'], calibration_seconds=d['timing_seconds']['calibration'],
                       source_result_path=name, source_result_sha256=hashlib.sha256(raw).hexdigest())
            per_run.append(row)
    if len(summary) != 26 or len(per_run) != 260:
        raise ValueError('Unexpected captured result coverage')
    for row in summary:
        scores = [r['final_micro_accuracy'] for r in per_run if r['dataset'] == row['dataset'] and r['method'] == row['method']]
        if len(scores) != row['n_seeds'] or abs(statistics.mean(scores) - row['accuracy_mean']) > 1e-12:
            raise ValueError('Per-run accuracy does not agree with captured aggregate')
    for name, rows in [('benchmark_summary.csv', summary), ('per_run_metrics.csv', per_run)]:
        with (output / name).open('w', newline='', encoding='utf-8') as f:
            writer = csv.DictWriter(f, fieldnames=list(rows[0]))
            writer.writeheader(); writer.writerows(rows)
    print('Exported 26 summary rows and 260 per-run rows; group means agree with captured JSON.')


def main():
    root = Path(__file__).resolve().parents[1]
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument('--archive', type=Path, default=root / 'archives/Eidrion_v1.0.0_Research_Package.zip')
    parser.add_argument('--output', type=Path, required=True, help='Fresh output directory')
    args = parser.parse_args()
    export(args.archive, args.output)


if __name__ == '__main__':
    main()