Archive 4 checkpoints (1-4)

paper-releases/pbisc-diffusion/updates/20261005T133325Z-deck-scratch-samepairs-tracking/diffusion/dataset/server_1/model8/plans/paired_finetune_intradataset_20260927/scores_contrast/ji2025_chili/scsemi_cv_20261002/pooled/cat.csv

@@ -0,0 +1,61 @@
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paper-releases/pbisc-diffusion/updates/20261005T133325Z-deck-scratch-samepairs-tracking/diffusion/dataset/server_1/model8/plans/paired_finetune_intradataset_20260927/scores_contrast/ji2025_chili/scsemi_cv_20261002/pooled/ceiling.csv

@@ -0,0 +1,16 @@
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+ji2025_chili,scored,scsemi_cv_20261002/pooled,generated:scsemi__raw,scsemi__raw,NK cell,3051.0,0.15580655368806712,0.006885050027887885,0.06320826056994953,0.013456757261853747,0.15455365249590092,0.051940009522551914,0.16656525032290792,0.08416223774159011,0.151258982500628,0.06737836038511123,0.14889325937650721,0.06101917310563627,0.1577616237443916,0.05154152209485817,,,,,,,,,,,
+ji2025_chili,scored,scsemi_cv_20261002/pooled,broadcast:conditions_pooled_raw.npz@a13338f5,,T cell,3021.0,0.21959070752598212,0.0018957508310978326,0.09915905890125064,0.0008385726212966225,0.2197941403935097,0.09951530532359423,0.2197183107989401,0.09913063535800122,0.21894516682587872,0.09925405188576206,0.2171162647272274,0.09781039847788207,0.22237965488435468,0.10008490346101358,,,,,,,,,,,a13338f530600178689cf085a337667882704cc2bbe48b04ac9a60c9a1fac007
+ji2025_chili,scored,scsemi_cv_20261002/pooled,broadcast:conditions_pooled_raw.npz@a13338f5,,B cell,3245.0,0.12541425495803574,0.011254363578552603,0.036591345783669106,0.009570911339782185,0.13358867682532666,0.04419816614691421,0.11319447053014353,0.025605925532903535,0.11845911833483741,0.03398605742015746,0.14044390844815136,0.0486158757685558,0.12138510065171966,0.030550704049814515,,,,,,,,,,,a13338f530600178689cf085a337667882704cc2bbe48b04ac9a60c9a1fac007
+ji2025_chili,scored,scsemi_cv_20261002/pooled,broadcast:conditions_pooled_raw.npz@a13338f5,,Monocyte,3154.0,0.3953585113304115,0.001476500364600941,0.2242999241874751,0.004518497597061153,0.39429047657840666,0.2277196579761505,0.39449949763493797,0.22234537432562648,0.39613898722709867,0.22116385915703787,0.39426219381841593,0.2198950588281528,0.39760140139319833,0.23037567065040787,,,,,,,,,,,a13338f530600178689cf085a337667882704cc2bbe48b04ac9a60c9a1fac007
+ji2025_chili,scored,scsemi_cv_20261002/pooled,broadcast:conditions_pooled_raw.npz@a13338f5,,NK cell,3051.0,0.19645623091008718,0.00732809336964877,0.07912526762028013,0.007060569169413127,0.19213614757559272,0.07785635192243455,0.19894900124750692,0.08770577666347777,0.18772290543678893,0.07774448277498561,0.2071167113645841,0.08339441428839625,0.19635638892596324,0.06892531245210654,,,,,,,,,,,a13338f530600178689cf085a337667882704cc2bbe48b04ac9a60c9a1fac007
+ji2025_chili,scored,scsemi_cv_20261002/pooled,split_half_A_vs_B,,mean4,,0.8933460729084324,0.003023938509812342,0.7836746479091096,0.005121460495978445,0.8913282209869264,0.7790058887457331,0.8947427867883905,0.79089102056385,0.8974695844469502,0.7865810101878563,0.889669058683188,0.7829128847547115,0.8935207136367067,0.7789824352933968,0.9418625156081898,0.9702277814744693,0.8734115751941388,0.9336448090525581,,,,,,,
+ji2025_chili,scored,scsemi_cv_20261002/pooled,generated:scsemi__raw,scsemi__raw,mean4,,0.26797044874936743,0.0036465726516815285,0.12277677524485113,0.005358189143375955,0.2666243326849235,0.11828620640081541,0.273856801226274,0.13058577480926628,0.2642167916697441,0.1258743986460796,0.2664979233626815,0.11824267600215654,0.2686563948032142,0.12089482036593781,,,,,,,,,,,
+ji2025_chili,scored,scsemi_cv_20261002/pooled,broadcast:conditions_pooled_raw.npz@a13338f5,,mean4,,0.23420492618112912,0.003645011959017163,0.10979389912316875,0.002395891597825257,0.23495236034320893,0.11232237034227338,0.23159032005288213,0.10869692797000226,0.23031654445615093,0.10803711280948575,0.2397347695895947,0.11242893684074673,0.23443063646380896,0.10748414765333562,,,,,,,,,,,a13338f530600178689cf085a337667882704cc2bbe48b04ac9a60c9a1fac007

paper-releases/pbisc-diffusion/updates/20261005T133325Z-deck-scratch-samepairs-tracking/diffusion/dataset/server_1/model8/plans/paired_finetune_intradataset_20260927/tools/build_archive_request.py

@@ -0,0 +1,255 @@
+#!/usr/bin/env python3
+"""Archive-maintenance request for the paired fine-tuning benchmark (PBISC-Diffusion paper, pbisc-diffusion).
+
+Follows paper-release-20260928/maintenance/POLICY.md: every payload is listed explicitly (host, exact path, kind,
+state); generated arrays are not payloads but inference locations with their receipts; work that is still running
+(the scSemiProfiler baseline) is registered as running/planned locations only.
+
+Payloads (completed): code, documents, figures and their source CSVs, score tables, paired-data manifests and
+small data (features, pairs, folds, splits, cell metadata), the condition NPZs every sampler read, run receipts
+(RUN.json / history.json, which carry every fine-tuned checkpoint's sha256), queues, and the recommended-protocol
+LoRA checkpoints (all-training-donor LoRA per fold, and the 5-pair LoRA per draw) on both hosts.
+Not uploaded (location/provenance only): other fine-tuned checkpoints (sha256 in their RUN.json), the per-cell
+count arrays cells_panel6k.npz / cells_full.npz (sha256 in BUILD.json / MANIFEST.json; rebuilt from the datalake
+processing outputs), generated NPZs.
+usage: build_archive_request.py OUT.json
+"""
+from __future__ import annotations
+
+import glob
+import json
+import os
+import subprocess
+import sys
+from pathlib import Path
+
+T = Path("/home/sj_server_1/PBISC/immun-pbmc-fm/model_8_sparse_data_diffusion/plans/paired_finetune_intradataset_20260927")
+DATASETS = ("immicro", "ye2026_sepsis", "imperial_eskd", "giroux2022", "ji2025_chili")
+
+
+def files(patterns, root=T):
+    out = []
+    for p in patterns:
+        for f in sorted(glob.glob(str(root / p), recursive=True)):
+            q = Path(f)
+            if q.is_file() and not q.is_symlink() and "__pycache__" not in q.parts and not q.name.endswith((".bak", ".pyc")) \
+                    and ".bak_" not in q.name:
+                out.append(str(q))
+    return sorted(set(out))
+
+
+def remote_files(patterns):
+    # symlinks are skipped: server_2's Imperial checkpoints point into the archive itself, which prepare refuses
+    cmd = ("cd %s && for p in %s; do for f in $p; do [ -f \"$f\" ] && [ ! -L \"$f\" ] && echo \"$f\"; done; done; true"
+           % (T, " ".join(patterns)))
+    res = subprocess.run(["ssh", "-n", "spark-0110", cmd], capture_output=True, text=True, check=True)
+    return sorted({str(T / l.strip()) for l in res.stdout.splitlines() if l.strip()})
+
+
+def remote_json(path):
+    res = subprocess.run(["ssh", "-n", "spark-0110", f"cat '{path}'"], capture_output=True, text=True)
+    return json.loads(res.stdout) if res.returncode == 0 and res.stdout.strip() else None
+
+
+def main(out: str) -> int:
+    assets = []
+
+    def add(paths, kind, host="server_1", state="completed"):
+        for p in paths:
+            assets.append({"host": host, "source": p, "kind": kind, "state": state})
+
+    add(files(["tools/*.py", "tools/*.sh", "tests/*.py", "figures/make_figures.py",
+               "scsemi/tools/*.py", "scsemi/tools/*.sh", "scsemi/tests/*.py"]), "code")
+    add(files(["README.md", "FEASIBILITY.md", "figures/FIGURES.md", "scsemi/README.md",
+               "data/*/QC_REPORT.md"]), "document")
+    add(files(["figures/*.png", "figures/*.pdf"]), "figure")
+    add(files(["figures/source_data/**/*.csv"]), "table")
+    add(files(["scores/*/*/summary.json", "scores/*/*/per_donor.csv", "scores/*/*/contrast.csv", "scores/*/*/README.md",
+               "scores/*/fewshot_n5/*/summary.json", "scores/*/fewshot_n5/*/per_donor.csv",
+               "scores/*/fewshot_n5/*/contrast.csv", "scores/*/fewshot_n5/*/README.md",
+               "scores/*/AGGREGATE.md", "scores/*/aggregate.json",
+               "scores/*/fewshot_n5/AGGREGATE.md", "scores/*/fewshot_n5/aggregate.json"]), "table")
+    # 2026-10-01: Giroux sex-linked-gene rescoring (scores_nosex, chrY-only sensitivity scores_nochrY) and its gene list
+    add(files([f"{d}/{p}" for d in ("scores_nosex", "scores_nochrY")
+               for p in ("README.md", "**/summary.json", "**/per_donor.csv", "**/contrast.csv", "**/README.md")]), "table")
+    add(files(["data/sex_linked_genes/*.csv", "data/sex_linked_genes/*.md",  # BUILD.json is caught by data/*/BUILD.json
+               "data/sex_linked_genes/sources/*.txt", "data/sex_linked_genes/sources/README*"]), "metadata")
+    # 2026-10-01 LoRA rank sweep (r4/r64) and equal-pair-budget calibration: per-fold and pooled scores + comparison tables
+    add(files([f"scores/*/{d}/*/{p}" for d in ("lora_rank_20261001", "cal_budget_20261001")
+               for p in ("summary.json", "per_donor.csv", "contrast.csv", "README.md")]), "table")
+    add(files(["scores/*/rankcal_20261001.md", "scores/*/rankcal_20261001.json"]), "table")
+    # 2026-10-02 extra realism/diversity metrics (classifier AUC, 1-NN, MMD2, scSemiProfiler E_N, k = 3/5/10 P/C)
+    add(files(["scores_extra/**/*.csv", "scores_extra/**/*.json", "scores_extra/**/*.md"]), "table")
+    add(files(["scores_extra/_code/*.py"]), "code")
+    # 2026-10-04 scSemiProfiler read-out sensitivity (scsemi5nt / scsemi5rt): comparison tables, receipt index, queue log
+    add(files(["scsemi/analysis/output_variants_20261003/*.csv", "scsemi/analysis/output_variants_20261003/*.md",
+               "scsemi/analysis/output_variants_20261003/*.json"]), "table")
+    add(files(["scsemi/logs/output_variants_*.log"]), "log")
+    # 2026-10-05 scSemiProfiler CV / budget: scores (caught by the scores/*/*/... patterns above at depth 3) + summary
+    add(files([f"scores/*/{d}/*/{p}" for d in ("scsemi_cv_20261002", "scsemi_budget_20261002")
+               for p in ("summary.json", "per_donor.csv", "contrast.csv", "README.md")]), "table")
+    # 2026-10-05: rank / limma / CAT metrics of the scSemiProfiler CV arm (contrast_extra.py --design scored)
+    add(files([f"scores_contrast/*/{d}/**/*.{e}" for d in ("scsemi_cv_20261002", "scsemi_budget_20261002")
+               for e in ("csv", "json", "txt", "log")]), "table")
+    add(files(["scsemi/analysis/cv_budget_*/*.csv", "scsemi/analysis/cv_budget_*/*.md",
+               "scsemi/validation/check_units_*.json", "logs/finalize_scsemi_*.log"]), "table")
+    add(files(["logs/extraA_*.log", "logs/extraA_*.jobs", "logs/extraB_*.log", "logs/extraB_*.jobs"]), "log")
+    # equal-pair-budget calibration (alpha fitted on each lora_n<n> run's own pairs)
+    add(files(["data/*/fold*/alpha_n*.npy"]), "data")
+    add(files(["data/*/CAL_BUDGET.json"]), "metadata")
+    add(files(["data/*/features.npz", "data/*/cells_obs.parquet", "data/*/fold*/alpha.npy",
+               "data/*/fewshot_n5/draw*/alpha.npy"]), "data")
+    add(files(["data/*/pairs.csv", "data/*/folds.csv", "data/*/samples.csv", "data/*/identity_*.csv",
+               "data/*/pairs_sensitivity_offday.csv", "data/*/MANIFEST.json", "data/*/PREPARE.json",
+               "data/*/BUILD.json", "data/*/cells_full.BUILD.json", "data/*/fewshot_n5/DRAWS.json",
+               "data/*/fewshot_n5/draw*/*.txt"]), "metadata")
+    add(files(["data/*/conditions_*.npz", "data/*/fold*/*.npz", "data/*/fewshot_n5/*.npz",
+               "data/*/fewshot_n5/draw*/*.npz"]), "condition")
+    add(files(["runs/**/RUN.json", "runs/**/history.json"]), "log")
+    # server_2 ran its own copies of the scSemiProfiler queues (some exist only there): keep them as the as-run record
+    subprocess.run(["rsync", "-a", f"spark-0110:{T}/scsemi/queues/", f"{T}/scsemi/queues/as_run_server2/",
+                    "--include=server2_*.txt", "--exclude=*"], check=True)
+    add(files(["queues/*.txt", "scsemi/queues/*.txt", "scsemi/queues/as_run_server2/*.txt",
+               "scsemi/vendor/compatibility.patch",
+               "scsemi/vendor/source_manifest.json"]), "config")
+    # recommended protocol weights (LoRA merged into the base weights): server_1 datasets here, Imperial on server_2
+    add(files(["runs/*/fold*/real_lora/checkpoint_ft.pt", "runs/*/fewshot_n5/draw*/lora/checkpoint_ft.pt"]), "checkpoint")
+    add(remote_files(["runs/imperial_eskd/fold*/real_lora/checkpoint_ft.pt",
+                      "runs/imperial_eskd/fewshot_n5/draw*/lora/checkpoint_ft.pt"]), "checkpoint", host="server_2")
+    add(remote_files(["runs/imperial_eskd/*/*/RUN.json", "runs/imperial_eskd/*/*/history.json",
+                      "runs/imperial_eskd/fewshot_n5/*/*/RUN.json", "runs/imperial_eskd/fewshot_n5/*/*/history.json"]),
+        "log", host="server_2")
+
+    # ---- inference locations (not payloads) ------------------------------------------------------------------------
+    locs = []
+
+    def receipt_fields(rec: dict | None) -> dict:
+        if not rec:
+            return {}
+        keep = {}
+        for k in ("output_sha256", "checkpoint", "checkpoint_sha256", "input_condition_path", "input_condition_sha256",
+                  "condition_npz", "condition_sha256", "seed", "steps", "generated_counts_rows"):
+            if k in rec and not isinstance(rec[k], (dict, list)):
+                keep[k] = rec[k]
+        if "output_sha256" in keep:
+            keep["sha256"] = keep["output_sha256"]
+        return keep
+
+    seen_locs = set()
+
+    def loc(host, npz, experiment, cohort, rec=None, state="completed"):
+        # one entry per (host, path): a server_2 NPZ can be reached both through its .moved marker on server_1 and
+        # through the server_2 listing (2026-10-04, read-out variants); the first one found is kept
+        if (host, npz) in seen_locs:
+            return
+        seen_locs.add((host, npz))
+        rpath = npz[:-4] + ".log"
+        item = {"host": host, "path": npz, "state": state, "experiment": experiment, "cohort": cohort,
+                "artifact_role": "inference_output"}
+        if state in ("completed", "final"):
+            item["receipt"] = rpath
+        item.update(receipt_fields(rec))
+        locs.append(item)
+
+    for ds in DATASETS:
+        # present on server_1
+        for npz in files([f"generated/{ds}/**/*.npz"]):
+            rel = Path(npz).relative_to(T / "generated" / ds)
+            rp = Path(npz[:-4] + ".log")
+            rec = json.loads(rp.read_text()) if rp.is_file() and rp.stat().st_size else None
+            if rec is None:
+                continue
+            loc("server_1", npz, f"paired_finetune_{rel.parts[0]}", ds, rec)
+        # moved to server_2 (sha-verified move; .moved marker kept on server_1)
+        for mk in files([f"generated/{ds}/**/*.moved"]):
+            npz = mk[:-6] + ".npz"
+            rp = Path(mk[:-6] + ".log")
+            rec = json.loads(rp.read_text()) if rp.is_file() and rp.stat().st_size else None
+            rel = Path(npz).relative_to(T / "generated" / ds)
+            item_state = "completed" if rec else "presence_only"
+            n0 = len(locs)
+            loc("server_2", npz, f"paired_finetune_{rel.parts[0]}", ds, rec, state=item_state)
+            if len(locs) > n0:
+                locs[-1]["move_marker_server_1"] = mk
+    # Imperial outputs live on server_2
+    for npz in remote_files(["generated/imperial_eskd/*/*.npz", "generated/imperial_eskd/fewshot_n5/*/*.npz",
+                             "generated/imperial_eskd/pooled/*.npz"]):
+        rec = remote_json(npz[:-4] + ".log")
+        if rec is None:
+            continue
+        rel = Path(npz).relative_to(T / "generated" / "imperial_eskd")
+        loc("server_2", npz, f"paired_finetune_{rel.parts[0]}", "imperial_eskd", rec)
+    # scSemiProfiler draws of the other datasets that ran on server_2 (queues server2_*.txt)
+    for npz in remote_files([f"generated/{ds}/fewshot_n5/draw*/scsemi5__raw.npz" for ds in DATASETS
+                             if ds != "imperial_eskd"]):
+        rec = remote_json(npz[:-4] + ".log")
+        if rec is None:
+            continue
+        rel = Path(npz).relative_to(T / "generated")
+        loc("server_2", npz, "paired_finetune_fewshot_n5", rel.parts[0], rec)
+    # scSemiProfiler baseline still running: register in-progress / planned draws by their future output path
+    done = {l["path"] for l in locs}
+    run_queues = [T / "scsemi" / "queues" / "server1_fewshot_d0first.txt"] + \
+        sorted((T / "scsemi" / "queues" / "as_run_server2").glob("server2_*.txt"))
+    for qf in run_queues:
+        host = "server_1" if qf.name.startswith("server1_") else "server_2"
+        for line in qf.read_text().splitlines():
+            if not line.startswith("fewshot|"):
+                continue
+            _, ds, j = line.split("|")[:3]
+            npz = str(T / "generated" / ds / "fewshot_n5" / f"draw{j}" / "scsemi5__raw.npz")
+            if npz in done:
+                continue
+            state = "planned"
+            locs.append({"host": host, "path": npz, "state": state, "experiment": "paired_finetune_fewshot_n5_scsemiprofiler",
+                         "cohort": ds, "artifact_role": "inference_output",
+                         "note": "scSemiProfiler 5-pair baseline queued or running on this host at request time"})
+            done.add(npz)
+    # 2026-10-05: the scSemiProfiler 5-fold CV / equal-pair-budget queues (server_1 and server_2) are still running:
+    # every unit without an output yet is a planned location on the host whose queue holds it
+    cvb_queues = [(T / "scsemi" / "queues" / "server1_cv_budget_20261004_no_giroux_imperial.txt", "server_1"),
+                  (T / "scsemi" / "queues" / "server2_cv_giroux_imperial_20261004.txt", "server_2")]
+    for qf, host in cvb_queues:
+        if not qf.exists():
+            continue
+        for line in qf.read_text().splitlines():
+            f = line.split("|")
+            if f[0] not in ("cv", "budget"):
+                continue
+            ds, k = f[1], f[2]
+            name = "scsemi__raw.npz" if f[0] == "cv" else f"scsemi_n{f[4]}__raw.npz"
+            npz = str(T / "generated" / ds / f"fold{k}" / name)
+            if npz in done or (host, npz) in seen_locs:
+                continue
+            locs.append({"host": host, "path": npz, "state": "planned",
+                         "experiment": "paired_finetune_scsemiprofiler_cv_budget_20261002", "cohort": ds,
+                         "artifact_role": "inference_output",
+                         "note": f"scSemiProfiler {'5-fold CV' if f[0] == 'cv' else 'equal pair budget'} unit queued or "
+                                 f"running on this host at request time ({qf.name})"})
+            done.add(npz)
+    req = {
+        "project_id": "pbisc-diffusion",
+        "summary": (
+            "Within-dataset paired fine-tuning benchmark of the final 6k 1x E16 model (plans/paired_finetune_intradataset_20260927): "
+            "LoRA (recommended protocol), full and condition-encoder fine-tuning, sc-only control, LoRA learning curve, "
+            "K-augmentation null, 5-pair deployment scenario, on ImMicro, Ye 2026 sepsis, Imperial ESKD COVID, Giroux 2022 and "
+            "Ji 2025 (whole-blood bulk); scores (scANVI composition, precision/coverage, contrast logFC r, top-50 DEG), figures, "
+            "paired-data manifests, conditions, run receipts and the recommended-protocol LoRA checkpoints. The scSemiProfiler "
+            "5-pair baseline: every finished draw is included as score tables and a completed location; draws not yet "
+            "finished at request time (none on 2026-09-30: 25/25 done) are planned locations. Not uploaded: per-cell count "
+            "arrays and non-recommended fine-tuned checkpoints (sha256 recorded in BUILD/MANIFEST and RUN.json)."),
+        "assets": assets,
+        "inference_locations": locs,
+    }
+    Path(out).write_text(json.dumps(req, indent=1))
+    kinds = {}
+    for a in assets:
+        kinds[(a["host"], a["kind"])] = kinds.get((a["host"], a["kind"]), 0) + 1
+    print(json.dumps({"assets": len(assets), "by_host_kind": {f"{h}/{k}": v for (h, k), v in sorted(kinds.items())},
+                      "locations": len(locs), "location_states": {s: sum(l["state"] == s for l in locs) for s in {l["state"] for l in locs}}},
+                     indent=1))
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main(sys.argv[1]))