| |
| """List NDL documents by original missing-character ratio with local links. |
| |
| Reads a completed unified audit catalog and writes a Markdown table plus a CSV |
| for an arbitrary [min, max) missing-ratio band. Links point at the pre-clean |
| text (corpus/text/<PID>.txt) and at the post-clean line in build documents. |
| No corpus text is modified. |
| """ |
| import argparse |
| import collections |
| import csv |
| import json |
| from pathlib import Path |
|
|
|
|
| def ratio_band(value, bands): |
| for label, low, high in bands: |
| if low <= value < high: |
| return label |
| return 'other' |
|
|
|
|
| def main(): |
| p = argparse.ArgumentParser(description=__doc__) |
| p.add_argument('--audit', type=Path, required=True) |
| p.add_argument('--min', type=float, required=True, dest='low') |
| p.add_argument('--max', type=float, required=True, dest='high') |
| p.add_argument('--output', type=Path, required=True, help='Markdown output path') |
| args = p.parse_args() |
|
|
| audit = args.audit.resolve() |
| out = args.output.resolve() |
| root = Path(__file__).resolve().parents[1] |
|
|
| rows = [] |
| with (audit / 'catalog.jsonl').open() as f: |
| for line in f: |
| r = json.loads(line) |
| if r['source'] != 'ndl': |
| continue |
| q = r['quality']['original_quality'] |
| ratio = float(q['missing_ratio']) |
| if not (args.low <= ratio < args.high): |
| continue |
| rows.append((r, q)) |
| rows.sort(key=lambda x: (-x[1]['missing_ratio'], x[0]['id'])) |
| if not rows: |
| raise SystemExit('no documents in range') |
|
|
| width = (args.high - args.low) / 5 |
| bands = [] |
| for i in range(5): |
| low = args.low + i * width |
| high = args.low + (i + 1) * width |
| label = f'{low*100:.0f}-{high*100:.0f}%' |
| bands.append((label, low, high)) |
| counts = collections.Counter(ratio_band(q['missing_ratio'], bands) for _, q in rows) |
|
|
| out.parent.mkdir(parents=True, exist_ok=True) |
| csv_path = out.with_suffix('.csv') |
| with csv_path.open('w', newline='') as f: |
| w = csv.writer(f) |
| w.writerow(['id', 'title', 'missing_ratio', 'missing_count', 'nonspace_chars', |
| 'text_path', 'text_line', 'document_path', 'document_line']) |
| for r, q in rows: |
| pid = r['id'].split('/')[1] |
| w.writerow([r['id'], r['title'], f"{q['missing_ratio']:.6f}", q['missing_count'], |
| q['nonspace_chars'], f'corpus/text/{pid}.txt', 1, |
| r['text_ref']['path'], r['text_ref']['line']]) |
|
|
| total_chars = sum(q['nonspace_chars'] for _, q in rows) |
| lines = [ |
| f"# NDL 欠字率 {args.low*100:.0f}–{args.high*100:.0f}% の資料一覧", |
| '', |
| f'- 対象: {len(rows)}資料（`{audit.name}/catalog.jsonl` の original missing_ratio 基準）', |
| f'- 削除前の非空白文字合計: {total_chars:,}字', |
| f'- 書名の種類: {len({r["title"] for r, _ in rows})}', |
| f'- CSV: `{csv_path.name}`', |
| '', |
| '| 欠字率 | 件数 |', |
| '|---|---:|', |
| ] |
| for label, low, high in reversed(bands): |
| lines.append(f'| {label} | {counts[label]} |') |
| lines.extend([ |
| f'| 合計 | {len(rows)} |', |
| '', |
| 'リンク: `txt` は削除前テキスト、`Lxxxx` は削除後本文（documents.jsonl の行）。', |
| '', |
| '| # | ID | 書名 | 欠字率 | 欠字/字数 | 本文 | 後処理 |', |
| '|---|---|---|---:|---:|---|---|', |
| ]) |
| for n, (r, q) in enumerate(rows, 1): |
| pid = r['id'].split('/')[1] |
| title = r['title'].replace('|', '\\|') |
| txt = f'[txt](vscode://file{root}/corpus/text/{pid}.txt:1)' |
| doc = (f'[L{r["text_ref"]["line"]}](vscode://file{root}/' |
| f'{r["text_ref"]["path"]}:{r["text_ref"]["line"]})') |
| lines.append(f'| {n} | {r["id"]} | {title} | {q["missing_ratio"]*100:.1f}% | ' |
| f'{q["missing_count"]}/{q["nonspace_chars"]} | {txt} | {doc} |') |
| out.write_text('\n'.join(lines) + '\n') |
| print(json.dumps(dict(documents=len(rows), chars=total_chars, |
| markdown=str(out), csv=str(csv_path), |
| bands={label: counts[label] for label, _, _ in bands}), |
| ensure_ascii=False)) |
|
|
|
|
| if __name__ == '__main__': |
| main() |
|
|
