diff --git a/paper-releases/pbisc-diffusion/updates/20261015T121654Z-x1-nine-core40-deck/diffusion/dataset/server_1/model8/plans/paper_figures_strictpairs_20261012/recoveries/x1_priority_completion_20261015/PLAN.md b/paper-releases/pbisc-diffusion/updates/20261015T121654Z-x1-nine-core40-deck/diffusion/dataset/server_1/model8/plans/paper_figures_strictpairs_20261012/recoveries/x1_priority_completion_20261015/PLAN.md new file mode 100644 index 0000000000000000000000000000000000000000..861ba9b843bc028685810062a5f6b3482d58aa9d --- /dev/null +++ b/paper-releases/pbisc-diffusion/updates/20261015T121654Z-x1-nine-core40-deck/diffusion/dataset/server_1/model8/plans/paper_figures_strictpairs_20261012/recoveries/x1_priority_completion_20261015/PLAN.md @@ -0,0 +1,32 @@ +# ×1 잔여 실험 우선 완료 및 전체 덱 갱신 + +2026-10-15 사용자 지시: CHILI 3개와 건강인 6개를 ×4 전체 완료보다 먼저 끝내고, 기존 생성 결과의 추가 지표·통계를 평가해 전체 PPTX/PDF를 갱신한다. + +## 완료한 작업 + +- 정확히 같은 기존 실험이 있는지 168개 로컬·14개 원격 RUN 기록과 재사용 registry를 대조했다. 이번 9개와 일치하는 완료 실험은 없었다. 과거 CHILI는 7/8/9 pairs, 과거 건강인은 다른 학습 ID와 추가 validation 7개를 사용했다. +- ×1 LoRA 학습 9회, LoRA 생성 9회, paired calibration 생성 9회를 완료했다. 기존 논문 ×1 parent, 6,000개 gene 순서, rank 16, fixed 3,000 steps를 유지했다. +- ×4의 다음 작업을 배정하는 coordinator만 20:29:38–20:57:58 KST 동안 일시 정지했다. 진행 중이던 GPU/CPU 자식 작업은 정상 종료까지 보존했고, 동일 ×4 프로세스를 재개했다. 이 구간을 포함한 wrapper wall time을 GPU 계산 시간으로 해석하지 않는다. +- 완료된 27개 연산과 54개 출력 파일을 server_2에도 해시 검증하여 반영했다. 원래 실행 함수가 27개 모두를 재사용으로 건너뛰는 것을 확인했다. +- 이미 추론이 끝난 CHILI draw 1 scSemiProfiler는 CPU export와 검증만 마쳤다. Giroux·CHILI의 완료된 생성 출력과 필요한 metadata만 가져왔다. +- ×1 핵심 평가는 40/40개가 준비됐다: 건강인 20개, 질환 20개. 기존 전체 CPU 평가 11개는 그대로 재사용했다. +- 167장 덱에 40개 핵심 결과와 현재 완료된 전체 통계를 반영했다. 기존 156장, 원본 76개 ID, Figure 1과 승인 palette를 유지했다. 원래 156장 파일은 presentation/data/x1_priority_20261015/base/에 보존했다. + +## 계속 실행 중인 작업 + +- CPU worker 0·1이 서로 다른 20개 단위를 맡는다. 모든 ×1 LoRA의 전체 평가를 먼저 완료한 뒤 기존 comparator 출력을 평가한다. 완료된 core/annotation/full metric은 재사용한다. +- 각 전체 평가의 메모리 상한은 16 GiB, thread는 2개다. 두 번째 worker는 16 GiB 핵심 평가 worker가 종료된 뒤 시작했다. ×4 CPU scorer의 32 GiB 상한과 합쳐 과학 계산 CPU 작업 상한은 64 GiB다. 실패 시 자동 증설이나 계산 재시작은 하지 않는다. +- 새 생성 파일을 저장 도중 읽었던 경쟁 조건은 생성 완료 receipt 확인으로 수정했다. 오류 원본은 evaluation/revisions/에 보존했으며 GPU 재실행은 없었다. +- 기존 scSemiProfiler 큐는 새 ×1 diffusion 결과를 재사용하도록 복구했다. 남은 scSemiProfiler 학습은 이전 계획대로 ×4 핵심 계산·HF 백업 완료 후 진행한다. +- 덱 갱신 서비스는 검증된 core와 전체 통계를 구분해 반영한다. 완료 증거가 늘어나면 새 버전을 만들고, 사용자가 지정한 PPTX/PDF 경로를 원자적으로 갱신한다. 두 CPU worker가 현재 준비된 arm을 모두 끝내면 donor 통합 집계와 최종 덱·HF 아카이브를 생성한다. + +## 확인 위치 + +- GPU_STATUS.json, X4_PAUSE.json, X4_RESUMED.json, MIRROR_VERIFIED.json +- evaluation/STATUS.json, CORE_STATUS.json, WORKER_0.json, WORKER_1.json +- FOLLOWUP_STATUS.json, DECK_STATUS.json, DECK_CURRENT.json +- presentation/CURRENT_MASTER.json 및 data/x1_priority_20261015/VERIFIED.json + +## 완료로 표시하지 않은 것 + +추가 CPU 통계는 아직 모두 끝나지 않았다. 새로 학습한 9개 support의 scSemiProfiler 출력은 아직 없으므로 다른 조건의 값을 대신 넣지 않는다. Figure 5의 원 논문 fine-cluster identity와 Figure 6의 임상 결과 재현은 별도 연구 검증이 필요하다. Manuscript·Overleaf는 변경하지 않았다. diff --git a/paper-releases/pbisc-diffusion/updates/20261015T121654Z-x1-nine-core40-deck/diffusion/dataset/server_1/model8/plans/paper_figures_strictpairs_20261012/recoveries/x1_priority_completion_20261015/evaluation/aggregate.py b/paper-releases/pbisc-diffusion/updates/20261015T121654Z-x1-nine-core40-deck/diffusion/dataset/server_1/model8/plans/paper_figures_strictpairs_20261012/recoveries/x1_priority_completion_20261015/evaluation/aggregate.py new file mode 100644 index 0000000000000000000000000000000000000000..aeace4dea69a656d0ab71df50c05b1c43296943c --- /dev/null +++ b/paper-releases/pbisc-diffusion/updates/20261015T121654Z-x1-nine-core40-deck/diffusion/dataset/server_1/model8/plans/paper_figures_strictpairs_20261012/recoveries/x1_priority_completion_20261015/evaluation/aggregate.py @@ -0,0 +1,75 @@ +"""Donor-clustered cross-arm contrasts from completed unit metrics, no cell inference.""" +from pathlib import Path +import sys +import hashlib +import json +from common import ROOT, S, atomic, bind, read, verify_receipt +sys.path.insert(0, str(S / "tools")) +import pandas as pd +import donor_statistics as DS +import numpy as np + + +def matched_draw_metadata(table: pd.DataFrame, arm: str, metric: str, baseline: str = "lora") -> dict: + """Count only draws with a finite matched sample pair for this arm/metric.""" + relevant = table[(table.metric == metric) & table.arm.isin([arm, baseline])].copy() + arm_draws = sorted(relevant.loc[relevant.arm == arm, "draw"].astype(str).unique().tolist()) + baseline_draws = sorted(relevant.loc[relevant.arm == baseline, "draw"].astype(str).unique().tolist()) + relevant["value"] = pd.to_numeric(relevant.value, errors="coerce") + wide = relevant.pivot(index=["draw", "donor_id", "sample_id"], columns="arm", values="value") + matched = [] + if arm in wide and baseline in wide: + paired = wide[[arm, baseline]].replace([np.inf, -np.inf], np.nan).dropna() + matched = sorted(paired.index.get_level_values("draw").astype(str).unique().tolist()) + return {"n_draws_matched": len(matched), "matched_draw_ids": json.dumps(matched), + "n_draws_arm_available": len(arm_draws), "n_draws_baseline_available": len(baseline_draws), + "n_draws_union_available": len(set(arm_draws) | set(baseline_draws))} + + +def main() -> None: + status = read(ROOT / "STATUS.json") + rows = [] + bindings = [] + for unit in status["units"]: + for arm, item in unit["arms"].items(): + if item["state"] not in ("canonical_full_reused", "full_completed"): + continue + receipt = Path(item["receipt"]) + verify_receipt(receipt) + path = Path(item["statistics_status"]).parent / "per_donor_long.csv" + table = pd.read_csv(path) + table = table[table.arm == arm].copy() + table["cohort"] = unit["cohort"] + table["n_pairs"] = unit["n_pairs"] + rows.append(table) + bindings.append(bind(path)) + if not rows: + return + digest = hashlib.sha256(json.dumps(bindings, sort_keys=True).encode()).hexdigest() + out = ROOT / "aggregates" / digest[:16] + if (out / "RECEIPT.json").exists(): + verify_receipt(out / "RECEIPT.json") + return + out.mkdir(parents=True, exist_ok=True) + merged = pd.concat(rows, ignore_index=True) + merged.to_csv(out / "per_donor_long.csv", index=False) + comparisons = [] + for (cohort, n_pairs), table in merged.groupby(["cohort", "n_pairs"], sort=True): + summary = DS.summarize_metrics(table, baseline="lora") + if len(summary): + summary["cohort"] = cohort + summary["n_pairs"] = n_pairs + metadata = pd.DataFrame([matched_draw_metadata(table, row.arm, row.metric) for row in summary.itertuples()]) + summary = pd.concat([summary.reset_index(drop=True), metadata], axis=1) + comparisons.append(summary) + if comparisons: + pd.concat(comparisons, ignore_index=True).to_csv(out / "paired_donor_bootstrap_2000.csv", index=False) + files = sorted(out.glob("*.csv")) + atomic(out / "RECEIPT.json", {"state": "completed", "inputs": bindings, "outputs": [bind(p) for p in files], + "bootstrap_unit": "unique_donor_all_draws_and_visits", "baseline": "lora"}) + atomic(ROOT / "AGGREGATES.json", {"path": str(out), "receipt": str(out / "RECEIPT.json"), + "partial": status["phase"] != "completed", "source_status": bind(ROOT / "STATUS.json")}) + + +if __name__ == "__main__": + main() diff --git a/paper-releases/pbisc-diffusion/updates/20261015T121654Z-x1-nine-core40-deck/diffusion/dataset/server_1/model8/plans/paper_figures_strictpairs_20261012/recoveries/x1_priority_completion_20261015/reuse/REUSE_AUDIT.json b/paper-releases/pbisc-diffusion/updates/20261015T121654Z-x1-nine-core40-deck/diffusion/dataset/server_1/model8/plans/paper_figures_strictpairs_20261012/recoveries/x1_priority_completion_20261015/reuse/REUSE_AUDIT.json new file mode 100644 index 0000000000000000000000000000000000000000..b93ec8bc9150d1383da914c528dfeb4bc8cb8478 --- /dev/null +++ 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Metadata and live host receipts; not a claim about unknown unindexed external storage.", + "no_gpu_launched": true, + "index": { + "path": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/EXPERIMENT_INDEX.md", + "sha256": "676cbf43c17b982034fef30ccc6780a5e8d39864b735e843645d30ca47303e77" + }, + "registry_queries": [ + { + "command": [ + "/home/sj_server_1/miniforge3/bin/python", + "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/scripts/audit_experiment_reuse.py", + "--query", + "ji2025_chili/fewshot_n5", + "--kind", + "metadata", + "--limit", + "10000" + ], + "output": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paper_figures_strictpairs_20261012/recoveries/x1_priority_completion_20261015/reuse/chili_fewshot_registry.jsonl", + "sha256": "1d37049aeeefaa110db00359d45f8d1f194d1845f8744ad214a1e5f329c9148a", + "summary": { + "matches_shown": 605, + "limit": 10000 + } + }, + { + "command": [ + "/home/sj_server_1/miniforge3/bin/python", + "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/scripts/audit_experiment_reuse.py", + "--query", + "lora_n", + "--kind", + "metadata", + "--limit", + "10000" + ], + "output": "/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paper_figures_strictpairs_20261012/recoveries/x1_priority_completion_20261015/reuse/healthy_lora_n_registry.jsonl", + "sha256": "d1166520ec0bce6a61b686da08549f16f9de2e63ecbcb70872463c059e97d831", + "summary": { + "matches_shown": 135, + "limit": 10000 + } + } + ], + "catalogs": [ + { + "path": "/home/sj_server_1/PBISC/paper-release-20260928/CURRENT_MODEL_INDEX.csv", + "sha256": "b350ed1d2baf8d9446b8cf854b63a5e191b28c6c3f7900f25f2854e64fa968b6" + }, + { + "path": "/home/sj_server_1/PBISC/paper-release-20260928/CURRENT_INFERENCE_LOCATIONS.csv", + "sha256": "49f0f5659ce50181ff1d08ab592eb7c2e7667bd862136a52bcb43ee19a862af6" + } + ], + "live_run_counts": { + "server_1": 168, + 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"/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927/runs/immicro/fold1/lora_n40/RUN.json", + "sha256": "0d760f5ad1485b68f89731ccd7b35086a812d45750b79ab8d6b8b9d5a54e4697", + "train_count": 40, + "validation_count": 7, + "train_only_in_historical": [ + "HS10", + "HS11", + "HS110", + "HS18", + "HS19", + "HS29", + "HS3", + "HS30", + "HS32", + "HS34", + "HS41", + "HS42", + "HS49", + "HS59", + "HS6", + "HS61", + "HS64", + "HS70", + "HS71", + "HS74", + "HS76", + "HS80", + "HS82", + "HS86", + "HS88", + "HS94" + ], + "train_only_in_strict": [ + "HS1", + "HS102", + "HS106", + "HS108", + "HS15", + "HS23", + "HS27", + "HS31", + "HS37", + "HS4", + "HS40", + "HS43", + "HS45", + "HS58", + "HS60", + "HS62", + "HS66", + "HS67", + "HS69", + "HS77", + "HS78", + "HS83", + "HS87", + "HS89", + "HS90", + "HS95" + ], + "test_ids_equal": true, + "parent_equal": true, + "seed_equal": true, + "fixed_steps": null, + "selected_step": 19500 + }, + "decision": "no_matching_completed_training_found; authorized_new_strict_training_required" + } + ] +} diff --git a/paper-releases/pbisc-diffusion/updates/20261015T121654Z-x1-nine-core40-deck/diffusion/dataset/server_1/model8/plans/paper_figures_strictpairs_20261012/recoveries/x1_priority_completion_20261015/reuse/REUSE_AUDIT.md b/paper-releases/pbisc-diffusion/updates/20261015T121654Z-x1-nine-core40-deck/diffusion/dataset/server_1/model8/plans/paper_figures_strictpairs_20261012/recoveries/x1_priority_completion_20261015/reuse/REUSE_AUDIT.md new file mode 100644 index 0000000000000000000000000000000000000000..aff1ee2d520a6627cb8abde117034ba8c71201ae --- /dev/null +++ b/paper-releases/pbisc-diffusion/updates/20261015T121654Z-x1-nine-core40-deck/diffusion/dataset/server_1/model8/plans/paper_figures_strictpairs_20261012/recoveries/x1_priority_completion_20261015/reuse/REUSE_AUDIT.md @@ -0,0 +1,27 @@ +# x1 strict-nine reuse audit + +Observed: 2026-10-15T11:28:17.535874+00:00 + +Decision: **pass_no_exact_reuse_found**. + +Both current hosts and the Model 8 registry/catalogs were inspected. No GPU or array-generation operation was launched. + +| Target | Historical training pairs | Historical validation pairs | Selected step | Why not reusable | +|---|---:|---:|---:|---| +| ji2025_chili-disease-draw2 | 7 | 0 | 3000 | Five donors contributed additional visits; strict support retains exactly five pairs. | +| ji2025_chili-disease-draw3 | 8 | 0 | 3000 | Five donors contributed additional visits; strict support retains exactly five pairs. | +| ji2025_chili-disease-draw4 | 9 | 0 | 3000 | Five donors contributed additional visits; strict support retains exactly five pairs. | +| immicro-healthy-fold0-n10 | 10 | 7 | 5750 | Different train IDs; seven extra validation pairs and early-stopped checkpoint selection versus strict fixed3000/no validation. | +| immicro-healthy-fold0-n20 | 20 | 7 | 19750 | Different train IDs; seven extra validation pairs and early-stopped checkpoint selection versus strict fixed3000/no validation. | +| immicro-healthy-fold0-n40 | 40 | 7 | 20000 | Different train IDs; seven extra validation pairs and early-stopped checkpoint selection versus strict fixed3000/no validation. | +| immicro-healthy-fold1-n10 | 10 | 7 | 3250 | Different train IDs; seven extra validation pairs and early-stopped checkpoint selection versus strict fixed3000/no validation. | +| immicro-healthy-fold1-n20 | 20 | 7 | 19500 | Different train IDs; seven extra validation pairs and early-stopped checkpoint selection versus strict fixed3000/no validation. | +| immicro-healthy-fold1-n40 | 40 | 7 | 19500 | Different train IDs; seven extra validation pairs and early-stopped checkpoint selection versus strict fixed3000/no validation. | + +The historical parent checkpoint and training seed agree, but that is insufficient when exposed samples or checkpoint selection differ. CHILI historical draws2/3/4 use7/8/9 pairs, respectively. + +Live RUN records inspected: server_1=168, server_2=14. Per-candidate mismatches and exact support IDs are in REUSE_AUDIT.json; live receipt snapshots are in LIVE_TARGET_RECEIPTS.json. + +The parent uses the paper6k gene panel and original x1 trunk. Its immutable parent SHA and verified gene-position hash bind the intended panel. Incompatible candidates were rejected before any assumption of gene/mask equivalence. No unknown field was treated as an exact match. + +This audit covers the discovered local/remote working trees and current archive catalogs; it cannot prove absence of an unregistered experiment on an unknown external host.