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(None)" + }, + { + "old": "results/runtime/interferometer/delaunay/alma/delaunay_local_cpu_mp.json", + "sha256": "319a7c5dfb2342b74f670976efcdfebea84ef9254d75f187e204d950a83553a3", + "group": "setup axis not recorded", + "reason": "dense interferometric transformer not recorded (None)" + }, + { + "old": "results/runtime/interferometer/delaunay/alma_high/delaunay_local_cpu_fp64.unusable.json", + "sha256": "86af4ad63b513369f61aa007f3a8598b28127e61dac1de1baa57dae9ec3f14dc", + "group": "setup axis not recorded", + "reason": "dense interferometric transformer not recorded (None)" + }, + { + "old": "results/runtime/interferometer/delaunay/alma_high/delaunay_local_cpu_mp.unusable.json", + "sha256": "5443c99254df2958451103f404bbf35a354af15871d0e2fabc7de4c41583dc38", + "group": "setup axis not recorded", + "reason": "dense interferometric transformer not recorded (None)" + }, + { + "old": "results/runtime/interferometer/delaunay/sma/delaunay_local_cpu_fp64.json", + "sha256": "ddd7a0f6e76db0f349cb729ca49321202547011fa676078bf9ab232a36ce83c3", + "group": "setup axis not recorded", + "reason": "dense interferometric transformer not recorded (None)" + }, + { + "old": "results/runtime/interferometer/delaunay/sma/delaunay_local_cpu_mp.json", + "sha256": "a3b2d165787e1296e1b0fc15e9dd3be8e43749d4a98d6a773db31bb9a5a9bffe", + "group": "setup axis not recorded", + "reason": "dense interferometric transformer not recorded (None)" + }, + { + "old": "results/runtime/interferometer/pixelization/sma/pixelization_local_cpu_fp64.json", + "sha256": "120c8ae14aba04fd9cb61329c1c8d5176a98e05aebcff3025f65394e63b8e4e2", + "group": "setup axis not recorded", + "reason": "dense interferometric transformer not recorded (None)" + }, + { + "old": "results/runtime/interferometer/pixelization/sma/pixelization_local_cpu_fp64.png", + "sha256": "d91b3a96f4523c57d15335f98d550691a8b2a6cf61c1ecce2370f14ac1616154", + "group": "setup axis not recorded", + "reason": "dense interferometric transformer not recorded (None)" + }, + { + "old": "results/runtime/interferometer/pixelization/sma/pixelization_local_cpu_mp.json", + "sha256": "281bbcdf14a8fe597b5fdf6638c198259463c7b15e089ea2a278a835803d6706", + "group": "setup axis not recorded", + "reason": "dense interferometric transformer not recorded (None)" + }, + { + "old": "results/runtime/interferometer/pixelization/sma/pixelization_local_cpu_mp.png", + "sha256": "737fbb35c15271539720ceb77c54ebbbfcafee8a21bf6e60834f7dad434a7f49", + "group": "setup axis not recorded", + "reason": "dense interferometric transformer not recorded (None)" + } + ] +} diff --git a/scripts/misc/test/test_build_migration_map.py b/scripts/misc/test/test_build_migration_map.py new file mode 100644 index 000000000..6d916c08a --- /dev/null +++ b/scripts/misc/test/test_build_migration_map.py @@ -0,0 +1,201 @@ +"""Day-zero migration map: determinism, coverage, collision refusal and ``--check``.""" + +from __future__ import annotations + +import importlib.util +import json +import shutil +import subprocess +from pathlib import Path + +import pytest + +TOOLING = Path(__file__).resolve().parents[1] / "tooling" +REPO = TOOLING.parents[2] +spec = importlib.util.spec_from_file_location( + "build_migration_map", TOOLING / "build_migration_map.py" +) +mm = importlib.util.module_from_spec(spec) +spec.loader.exec_module(mm) + + +def _git(root, *args): + subprocess.run(["git", *args], cwd=root, check=True, capture_output=True) + + +def write(root, path, value): + target = root / path + target.parent.mkdir(parents=True, exist_ok=True) + target.write_text(value if isinstance(value, str) else json.dumps(value)) + + +def row(**extra): + return {"autolens_version": "2026.10.4.1", "instrument": "hst", **extra} + + +@pytest.fixture +def tree(tmp_path): + """A scratch git checkout with the real route manifest and a handful of results.""" + (tmp_path / "ruff.toml").write_text("") + (tmp_path / "catalogue").mkdir() + shutil.copy(REPO / mm.ROUTES_PATH, tmp_path / mm.ROUTES_PATH) + write(tmp_path, "scripts/imaging/delaunay/likelihood_runtime.py", "") + write(tmp_path, "scripts/interferometer/delaunay/likelihood_breakdown.py", "") + write(tmp_path, "scripts/misc/hazards/run.py", "") + a100 = {"backend": "gpu", "hostname": "euclid-ral-gpu-2"} + write( + tmp_path, + "results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64.json", + row(device=a100, configuration={"inversion_path": "dense"}), + ) + write( + tmp_path, + "results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64_r2026_10_17_1.json", + row(autolens_version="2026.10.17.1", device=a100), + ) + write( + tmp_path, + "results/runtime/imaging/delaunay/hst/delaunay_local_cpu_mp_sparse.json", + row(device={"backend": "cpu"}), + ) + write(tmp_path, "results/runtime/imaging/delaunay/hst/comparison.json", {"configs": {}}) + write(tmp_path, "results/breakdown/imaging/delaunay_hpc_a100_fp64_n3000.json", row()) + write(tmp_path, "results/breakdown/imaging/mystery_hpc_a100_fp64.json", row()) + write(tmp_path, "results/breakdown/imaging/delaunay_hpc_a100_fp64_recon_split.json", row()) + write( + tmp_path, + "results/breakdown/imaging/fixed_light_trace_delaunay_psf_control_hpc_a100_fp64" + "_fixed_light_trace.json", + row(), + ) + write( + tmp_path, + "results/breakdown/imaging/delaunay_breakdown_hst_v2026.8.17.1.json", + row(device={"backend": "cpu"}), + ) + write( + tmp_path, + "results/breakdown/interferometer/sma/delaunay_hpc_ral_cpu_fp64.json", + row( + instrument="sma", + transformer="TransformerNUFFT", + configuration={"inversion_path": "sparse"}, + device={"backend": "cpu", "hostname": "euclid-ral-gpu-1"}, + ), + ) + write( + tmp_path, + "results/runtime/imaging/a100_probes/vmap_probe_delaunay.json", + row(captured_at="2026-10-05T00:00:00Z"), + ) + write(tmp_path, "results/hazards/hazards_index.json", {}) + write(tmp_path, "results/notes/design_lock_in.md", "# ledger\n") + write(tmp_path, "results/notes/numpy_deflections_cpu.md", "# ledger\n") + write(tmp_path, "wiki/campaigns/numpy_deflections_cpu.md", "# page\n") + write(tmp_path, "results/README.md", "# results\n") + _git(tmp_path, "init", "-q") + _git(tmp_path, "add", "-A") + return tmp_path + + +def by_old(doc): + return {e["old"]: e for e in doc["entries"]} + + +def test_every_tracked_file_is_covered_exactly_once(tree): + doc = mm.build(tree) + olds = [e["old"] for e in doc["entries"]] + [u["old"] for u in doc["unresolved"]] + assert sorted(olds) == mm.tracked(tree) + assert len(olds) == len(set(olds)) + assert doc["counts"]["covered"] == doc["counts"]["tracked_files"] == len(olds) + + +def test_mapping_rules(tree): + doc = mm.build(tree) + entries = by_old(doc) + base = "results/imaging/delaunay/hst" + pinned = entries["results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64_r2026_10_17_1.json"] + older = entries["results/runtime/imaging/delaunay/delaunay_hpc_a100_fp64.json"] + assert pinned["kind"] == "mirrored" + assert pinned["new"] == f"{base}/jax_gpu_dense_fp64/hpc_a100/runtime.json" + assert older["kind"] == "history" + assert older["new"].startswith(f"{base}/jax_gpu_dense_fp64/hpc_a100/history/2026.10.4.1_") + laptop = entries["results/runtime/imaging/delaunay/hst/delaunay_local_cpu_mp_sparse.json"] + assert laptop["new"] == f"{base}/jax_cpu_sparse_mixed/local_laptop/runtime.json" + assert entries["results/runtime/imaging/delaunay/hst/comparison.json"]["new"] == ( + f"{base}/comparison.json" + ) + assert entries["results/hazards/hazards_index.json"]["new"] == ( + "results/misc/hazards/hazards_index.json" + ) + probe = entries["results/runtime/imaging/a100_probes/vmap_probe_delaunay.json"] + assert probe["kind"] == "archive" and probe["new"].startswith("archive/2026/10/probes/") + assert entries["results/notes/design_lock_in.md"]["new"] == ( + "wiki/campaigns/misc/design_lock_in.md" + ) + # A ledger that shares a campaign page's name is kept beside it, not merged. + assert entries["results/notes/numpy_deflections_cpu.md"]["new"].endswith( + "lens/deflections/numpy_deflections_cpu_ledger.md" + ) + a100 = f"{base}/jax_gpu_dense_fp64/hpc_a100" + assert entries["results/breakdown/imaging/delaunay_hpc_a100_fp64_n3000.json"]["new"] == ( + f"{a100}/scans/n3000/breakdown.json" + ) + arm = entries["results/breakdown/imaging/delaunay_hpc_a100_fp64_recon_split.json"] + assert arm["kind"] == "experiment" + assert arm["new"] == f"{a100}/experiments/recon_split/breakdown.json" + fixed = next(e for e in doc["entries"] if "fixed_light_trace" in e["old"]) + assert fixed["new"] == f"{a100}/light_fixed/experiments/trace_psf_control/breakdown.json" + assert entries["results/breakdown/imaging/mystery_hpc_a100_fp64.json"]["new"] == ( + "results/misc/likelihood_breakdown/imaging/mystery_hpc_a100_fp64.json" + ) + hostless = entries["results/breakdown/imaging/delaunay_breakdown_hst_v2026.8.17.1.json"] + assert hostless["new"].startswith("archive/2026/08/hostless_summaries/") + # CPU on a RAL GPU node is hpc_ral_cpu; a sparse interferometric row is the W~ route. + wtilde = entries["results/breakdown/interferometer/sma/delaunay_hpc_ral_cpu_fp64.json"] + assert wtilde["new"] == ( + "results/interferometer/delaunay/sma/jax_cpu_sparse_fp64_wtilde/hpc_ral_cpu/breakdown.json" + ) + assert doc["unresolved"] == [] + assert doc["mirror"]["result_variants"] == ["imaging/delaunay", "interferometer/delaunay"] + assert doc["mirror"]["result_variants_without_scripts"] == [] + + +def test_build_is_deterministic(tree): + first = mm.render(mm.build(tree)) + assert mm.render(mm.build(tree)) == first + + +def test_check_detects_a_stale_map(tree, capsys): + assert mm.main(["--root", str(tree)]) == 0 + assert mm.main(["--root", str(tree), "--check"]) == 0 + write(tree, "results/notes/design_lock_in.md", "# ledger, edited\n") + assert mm.main(["--root", str(tree), "--check"]) == 1 + assert "stale" in capsys.readouterr().err + + +def test_collisions_refuse_to_write(tree, monkeypatch, capsys): + write(tree, "results/quick_update/hazards_index.json", {}) + _git(tree, "add", "-A") + monkeypatch.setitem(mm.MISC_GROUPS, "quick_update", "hazards") + doc = mm.build(tree) + assert doc["collisions"] == [ + { + "new": "results/misc/hazards/hazards_index.json", + "old": [ + "results/hazards/hazards_index.json", + "results/quick_update/hazards_index.json", + ], + } + ] + assert mm.main(["--root", str(tree)]) == 1 + assert not (tree / mm.MAP_PATH).exists() + assert "COLLISION" in capsys.readouterr().err + + +def test_repository_map_has_no_collisions_and_covers_the_tree(): + doc = mm.build(REPO) + assert doc["collisions"] == [] + assert doc["counts"]["covered"] == doc["counts"]["tracked_files"] + news = [e["new"] for e in doc["entries"]] + assert len(news) == len(set(news)) diff --git a/scripts/misc/tooling/build_migration_map.py b/scripts/misc/tooling/build_migration_map.py new file mode 100644 index 000000000..e1c06409f --- /dev/null +++ b/scripts/misc/tooling/build_migration_map.py @@ -0,0 +1,1188 @@ +"""Generate the day-zero migration map for ``results/`` (stdlib only). + +Run from the repo root:: + + python scripts/misc/tooling/build_migration_map.py # (re)write the map + python scripts/misc/tooling/build_migration_map.py --check # exit 1 if the map is stale + +The map, ``catalogue/migration_day_zero.json``, names an old -> new path and the +sha256 of the file content for every tracked file under ``results/`` and for every +``wiki/campaigns/*.md`` page. It is the reviewable plan for the move-only PR of the +likelihood-lifecycle epic (phase 0B, autolens_profiling#442); **nothing moves here**. + +Target layout (epic report section 3.7, plus the human rulings of 2026-10-23):: + + = results/////[/] + /. # the current record of the key + /history/_/. # older records, same key + /scans//. # size scans (_nN, _rX, n_sweep/); never current + /experiments//. # arms + experiment scripts; never current + results////comparison. # cross-setup aggregate + results/lens//... results/misc//... + wiki/campaigns///.md (or //, lens/, misc/) + archive/YYYY/MM//... (archive/undated//... when no date is derivable) + +```` is present only for non-default model variants (``light_fixed``, +``rtu`` rectangular mesh, ``mge_mass``). ``setup_id`` is +``___[_]`` (ruling R1); the site/tier +moves to ``host_class``. Rules applied (human rulings, 2026-10-23): + +* host: a CPU measurement is ``hpc_ral_cpu`` whatever RAL node ran it (``hpc_ral_cpu`` + tier on a ``euclid-ral-gpu-*`` host, ``hpc_ral_gpunode_cpu``); a versioned ``_v`` + summary with no host anywhere is archived, month from its ``_v`` release. +* transformer: ``setup_id`` names the likelihood route, not the data-transformer class. + A sparse interferometric row is the W~ route -> ``_wtilde`` (report section 3.3), even + though its JSON records ``TransformerNUFFT``; dense rows keep the recorded class + (``_nufft`` / ``_dft``). + +Every axis is derived from the path (the legacy config grammar, the +``catalogue/script_routes.json`` legacy stems, the ``scripts/
//`` script +names) or from the result JSON. **Nothing is guessed:** a canonical row whose axes cannot +be derived, or whose path and content disagree, is listed under ``unresolved`` with the +reason; a scan/experiment file with no derivable cell goes to ``results/misc//``. +Two old paths mapping to one new path is an error and the map is not written. + +Pure stdlib -- no PyAuto* imports. Dates come only from file names and file content (no +git history), so the map is identical on a shallow CI clone. +""" + +from __future__ import annotations + +import argparse +import hashlib +import json +import os +import re +import subprocess +import sys +from collections import defaultdict +from pathlib import Path, PurePosixPath + +SCHEMA = "autolens-profiling-day-zero-migration" +VERSION = 2 +MAP_PATH = "catalogue/migration_day_zero.json" +ROUTES_PATH = "catalogue/script_routes.json" +ISSUE = "PyAutoLabs/autolens_profiling#442" + +#: Release-dated cut for the "pre-2026-09 series" dead-experiment class. +PRE_SERIES_CUTOFF = "2026-09-01" + +INSTRUMENTS = ("alma_high", "alma", "ao", "euclid", "hst", "jvla", "jwst", "sdp81", "sma", "simple") + +#: Legacy config-grammar host/tier token -> (host_class, device). +TIERS = { + "hpc_ral_cpu_epyc7702": ("hpc_ral_cpu", "cpu"), + "hpc_ral_gpunode_cpu": ("hpc_ral_cpu", "cpu"), # ruling: CPU on any RAL node + "hpc_ral_a100": ("hpc_a100", "gpu"), + "hpc_ral_cpu": ("hpc_ral_cpu", "cpu"), + "hpc_a100": ("hpc_a100", "gpu"), + "local_rtx2060": ("local_gpu", "gpu"), + "local_cpu": ("local_laptop", "cpu"), + "local_gpu": ("local_gpu", "gpu"), + "laptop_cpu": ("local_laptop", "cpu"), +} +TIER_TOKENS = sorted((t.split("_") for t in TIERS), key=len, reverse=True) +PRECISIONS = {"fp64": "fp64", "mp": "mixed", "fp32": None} # fp32 is not a setup precision + +#: Canonical per-likelihood script measurements (from script_routes) -> (backend, +#: model_variant). Any other route measurement is an experiment script. +CELL_MEASUREMENTS = { + "likelihood_runtime": ("jax", None), + "likelihood_breakdown": ("jax", None), + "likelihood_runtime_numba": ("numba", None), + "likelihood_breakdown_numba": ("numba", None), + "likelihood_runtime_jax": ("jax", None), + "likelihood_runtime_solved": ("jax", None), + "likelihood_runtime_numba_mge_mass": ("numba", "mge_mass"), +} +#: File-name tokens that name a model variant (``--rect-mesh rtu`` appends ``_rtu``). +MODEL_VARIANT_TOKENS = {"rtu": "rtu"} +MESHES = (("delaunay", "nn"), ("delaunay",), ("rectangular",)) +#: Fixed-light script tags measuring several backends in one file (no single setup). +MIXED_BACKEND_TAGS = {("cpu", "kernels")} +PURPOSE_TOKENS = {"breakdown", "summary", "likelihood"} +POINT_LIKE = ("point_source_image", "point_source_source", "cluster") +INTERFEROMETRIC = ("interferometer", "datacube") +TRANSFORMERS = {"TransformerNUFFT": "nufft", "TransformerDFT": "dft"} +CATEGORY = {"runtime": "likelihood_runtime", "breakdown": "likelihood_breakdown"} + +#: results/ top-level folders that become results/misc// (group mirrors scripts/misc/). +MISC_GROUPS = { + "hazards": "hazards", + "quick_update": "quick_update", + "logs": "logs", + "sweep": "likelihood_breakdown", + "delaunay_nn": "delaunay_nn", + "nnls_warm_start": "nnls_warm_start", + "simulators": "simulators", + "pipeline_resume": "pipeline_resume", + "parallel_scaling": "parallel_scaling", + "streaming_scaling": "streaming_scaling", +} +FROZEN_PACKS = ("notes/clipper_campaign/", "notes/point_source_cpu_2026_09_17_reported/") +FROZEN_BASELINE = "baselines/PreOptimizationTimes/" +#: Archive months that no file name or content records, with their source. +SLUG_MONTH = { + "PreOptimizationTimes": ("2026/07", "results/notes/design_lock_in.md title (2026-07-08)"), +} +#: Campaign families whose archived files stay together under one slug. +CAMPAIGN_FAMILIES = ("fixed_light",) + +MULTI = "spans several variants" +MULTI_DT = "spans several dataset types" + +#: results/notes/*.md ledgers and wiki/campaigns/*.md pages -> wiki/campaigns/
/. +#: ("misc", None) and ("lens", ) follow section 3.7; (
, MULTI) goes to +#: wiki/campaigns/
/ and (MULTI_DT, None) stays at wiki/campaigns/ (human ruling). +LEDGER_ROUTES = { + # results/notes ledgers + "a100_pixelized_baseline_2026_09": ("imaging", MULTI), + "certified_solver_phase_c1_lane_rate_2026_09": ("imaging", MULTI), + "certified_solver_policy_phase_b_2026_09": ("imaging", MULTI), + "cluster_pointsolver_campaign": ("cluster", "image_plane"), + "critical_curves_dispatch": ("lens", "critical_curves"), + "delaunay_adapt_split_regularization": ("imaging", MULTI), + "delaunay_nn_breakdown": ("imaging", "delaunay_nn"), + "delaunay_nn_cap_audit": ("imaging", "delaunay_nn"), + "delaunay_nn_constant_split_assembly": ("imaging", "delaunay_nn"), + "delaunay_nn_launch_latency": ("imaging", "delaunay_nn"), + "delaunay_walk_early_exit": ("imaging", "delaunay"), + "design_lock_in": ("misc", None), + "fixed_lens_light_hardware_2026_09": ("imaging", MULTI), + "fixed_lens_light_levers_2026_09": ("imaging", MULTI), + "fixed_lens_light_library_path_2026_09": ("imaging", MULTI), + "fixed_lens_light_low_likelihood_draws_2026_09": ("imaging", MULTI), + "fixed_lens_light_numba_2026_09": ("imaging", MULTI), + "fixed_lens_light_numba_memo_2026_09": ("imaging", MULTI), + "fixed_lens_light_numba_memo_policy_2026_09": ("imaging", MULTI), + "fixed_lens_light_numba_scaling_2026_09": ("imaging", MULTI), + "fixed_lens_light_s4_2026_09": ("imaging", "delaunay"), + "fixed_lens_light_source_only_2026_09": ("imaging", MULTI), + "fixed_lens_light_source_pixel_scaling_2026_09": ("imaging", MULTI), + "fixed_lens_light_verdict_2026_09": ("imaging", MULTI), + "hst_gpu_residue_phase1_2026_09": ("imaging", MULTI), + "hst_gpu_residue_phase2_vmap_2026_09": ("imaging", MULTI), + "hst_gpu_residue_phase3_psf_2026_09": ("imaging", MULTI), + "hst_gpu_residue_phase4_logdet_2026_09": ("imaging", MULTI), + "interferometer_direct_conv_symmetric_2026_10": ("interferometer", MULTI), + "interferometer_likelihood_decision_matrix_2026_09": ("interferometer", MULTI), + "interferometer_mesh_a100_breakdown_2026_09": ("interferometer", MULTI), + "interferometer_mesh_cpu_breakdown_2026_09": ("interferometer", MULTI), + "interferometer_mge_breakdown_2026_09": ("interferometer", "mge"), + "interferometer_route_gate_aris_2026_10": ("interferometer", MULTI), + "interferometer_w_tilde_fft_size_levers_2026_10": ("interferometer", MULTI), + "linear_solver_accuracy_2026_09": ("lens", "solver"), + "matrix_free_pixelized_2026_09": ("imaging", MULTI), + "multiband_pyloop_productized": ("misc", None), + "multistart_prodigy_compile_census": ("misc", None), + "nnls_solver_ledger": ("lens", "solver"), + "numba_curvature_matrix_f_split": ("imaging", MULTI), + "numba_interferometer_verdict": ("interferometer", MULTI), + "numpy_deflections_cpu": ("lens", "deflections"), + "point_source_cpu_campaign": ("point_source_image", "image_plane"), + "point_source_defaults_campaign": (MULTI_DT, None), + "point_source_gpu_breakdown_2026_09": (MULTI_DT, None), + "point_source_shared_likelihood_breakdown": (MULTI_DT, None), + "point_source_source_plane_campaign": ("point_source_source", "source_plane"), + "preopt_breakdown_baseline": ("misc", None), + "production_representative_cells": ("imaging", MULTI), + "profiling_campaign_status_2026_09": ("imaging", MULTI), + "sparse_vs_dense_inversion_path": ("imaging", MULTI), + "timing_noise_audit_2026_10": ("misc", None), + "vram_validation_2026_07_08": ("misc", None), + "xla_autotune_triton_gemm": ("misc", None), + # wiki/campaigns pages + "a100_pixelized_baseline": ("imaging", MULTI), + "certified_positive_solver": ("imaging", MULTI), + "cluster_pointsolver": ("cluster", "image_plane"), + "compile_time": ("misc", None), + "critical_curves": ("lens", "critical_curves"), + "delaunay_nn_a100_series": ("imaging", "delaunay_nn"), + "fixed_lens_light": ("imaging", MULTI), + "fixed_light_numba_cpu": ("imaging", MULTI), + "gaussian_deflections_precompute": ("lens", "deflections"), + "hst_gpu_residue": ("imaging", MULTI), + "image_source_mappings": (MULTI_DT, None), + "imaging_over_sampling": ("imaging", MULTI), + "interferometer_likelihood": ("interferometer", MULTI), + "interferometer_streaming": ("interferometer", "delaunay"), + "linear_solver_accuracy": ("lens", "solver"), + "mass_field_profiling": ("misc", None), + "matrix_free_pixelized": ("imaging", MULTI), + "measurement_tools": ("misc", None), + "numba_interferometer_revisit": ("interferometer", MULTI), + "point_source_gpu_breakdown": (MULTI_DT, None), + "point_source_image_plane_cpu": ("point_source_image", "image_plane"), + "point_source_source_plane": ("point_source_source", "source_plane"), + "post_certified_breakdown": ("imaging", MULTI), + "preoptimization_baseline": ("misc", None), + "reference_notes": ("misc", None), + "setup_baseline": ("misc", None), +} + +VERSION_RE = re.compile(r"_v(\d{4})\.(\d{1,2})\.(\d{1,2})\.(\d+)(\+\d+)?") +RPIN_RE = re.compile(r"_r(\d{4})_(\d{1,2})_(\d{1,2})_(\d+)$") +DATED_RE = re.compile(r"(?:^|_)(20\d\d)_(\d\d)(?:_(\d\d))?(?=_|$)") +PROBE_RE = re.compile(r"(?:^|_)probes?(?:_|$)") +LEVER_RE = re.compile(r"(?:^|_)levers?\d*(?:_|$)") +ISO_DATE_RE = re.compile(r"^(20\d\d)-(\d\d)-(\d\d)") +ANY_ISO_RE = re.compile(r"(20\d\d)-(\d\d)-(\d\d)") +SCAN_RE = re.compile(r"^(?:n\d+|r\d+(?:\.\d+)?)$") +SIDECAR_RE = re.compile(r"_jobs?\d*$") +SUFFIXES = ( + ".unusable.json", + ".declaration.json", + ".locked.json", + ".json", + ".png", + ".stdout", + ".out", + ".md", +) + + +def _root() -> Path: + for p in Path(__file__).resolve().parents: + if (p / "ruff.toml").exists(): + return p + raise RuntimeError("autolens_profiling root (ruff.toml) not found") + + +def tracked(root: Path) -> list[str]: + out = subprocess.run( + ["git", "ls-files", "-z", "--", "results", "wiki/campaigns"], + cwd=root, + check=True, + capture_output=True, + ).stdout.decode() + paths = [p for p in out.split("\0") if p] + return sorted( + p + for p in paths + if p.startswith("results/") + or (p.startswith("wiki/campaigns/") and p.count("/") == 2 and p.endswith(".md")) + ) + + +def source_commit(root: Path) -> str | None: + run = subprocess.run(["git", "rev-parse", "HEAD"], cwd=root, capture_output=True, text=True) + return run.stdout.strip() or None + + +def sha256(root: Path, path: str) -> str: + return hashlib.sha256((root / path).read_bytes()).hexdigest() + + +def split_ext(name: str) -> tuple[str, str]: + for suffix in SUFFIXES: + if name.endswith(suffix): + return name[: -len(suffix)], suffix[1:] + stem, dot, ext = name.rpartition(".") + return (stem, ext) if dot else (name, "") + + +def load_json(root: Path, path: str): + try: + return json.loads((root / path).read_text()) + except (OSError, ValueError, UnicodeDecodeError): + return None + + +def companion_json(root: Path, path: str, files: set[str]) -> str | None: + """The JSON a figure/log was written beside (same stem), when tracked.""" + parent, name = path.rsplit("/", 1) + stem, ext = split_ext(name) + if ext.endswith("json"): + return path + for suffix in ("json", "unusable.json"): + candidate = f"{parent}/{stem}.{suffix}" + if candidate in files: + return candidate + return None + + +# --------------------------------------------------------------------------- facts + + +def version_tuple(text: str | None) -> tuple[int, ...] | None: + if not isinstance(text, str): + return None + match = re.match(r"^v?(\d{4})\.(\d{1,2})\.(\d{1,2})\.(\d+)", text) + return tuple(int(g) for g in match.groups()) if match else None + + +def pin_string(vt: tuple[int, ...] | None) -> str | None: + return ".".join(str(v) for v in vt) if vt else None + + +def iso(y, m, d) -> str: + return f"{int(y):04d}-{int(m):02d}-{int(d or 1):02d}" + + +def facts(root: Path, path: str, files: set[str]) -> dict: + """Release pin and dates recorded by the file name or the companion JSON.""" + name = path.rsplit("/", 1)[1] + stem, _ = split_ext(name) + out = {"pin": None, "date": None, "date_basis": None, "doc": None} + jpath = companion_json(root, path, files) + doc = load_json(root, jpath) if jpath else None + out["doc"] = doc if isinstance(doc, dict) else None + if out["doc"]: + d = out["doc"] + out["pin"] = version_tuple(d.get("autolens_version") or d.get("release_version")) + device = d.get("device") if isinstance(d.get("device"), dict) else {} + prov = device.get("provenance") if isinstance(device.get("provenance"), dict) else {} + for basis, value in ( + ("device.provenance.captured_at", prov.get("captured_at")), + ("captured_at", d.get("captured_at")), + ("timestamp", d.get("timestamp")), + ("measured_at", d.get("measured_at")), + ("generated_at", d.get("generated_at")), + ): + match = ISO_DATE_RE.match(value) if isinstance(value, str) else None + if match: + out["date"], out["date_basis"] = iso(*match.groups()), basis + break + vmatch = VERSION_RE.search(stem) + rmatch = RPIN_RE.search(stem) + name_pin = ( + tuple(int(g) for g in vmatch.groups()[:4]) + if vmatch + else tuple(int(g) for g in rmatch.groups()) + if rmatch + else None + ) + out["versioned"] = bool(vmatch) + out["pin"] = out["pin"] or name_pin + if out["date"] is None: + dmatch = DATED_RE.search(VERSION_RE.sub("", stem)) + if dmatch: + out["date"], out["date_basis"] = iso(*dmatch.groups()), "file name date" + # The series date also accepts the file-name release (results/README.md: the version + # string is the release that produced the numbers). A JSON ``autolens_version`` is never + # a date: source checkouts stamp a stale release. + out["series_date"], out["series_basis"] = out["date"], out["date_basis"] + if out["series_date"] is None and vmatch: + out["series_date"] = iso(*vmatch.groups()[:3]) + out["series_basis"] = "file name release" + return out + + +def json_host(doc: dict | None) -> tuple[str | None, str | None, str | None]: + """(host_class, device, basis) from a recorded host name; (None, ...) if unknown.""" + if not doc: + return None, None, None + device = doc.get("device") if isinstance(doc.get("device"), dict) else {} + prov = device.get("provenance") if isinstance(device.get("provenance"), dict) else {} + host = prov.get("host") or device.get("hostname") or doc.get("hostname") + backend = device.get("backend") + dev = "gpu" if backend in ("gpu", "cuda") else "cpu" if backend == "cpu" else None + if not isinstance(host, str) or not host: + return None, dev, None + h = host.lower() + if "ral-gpu" in h: + # Ruling: a CPU measurement is hpc_ral_cpu whatever RAL node ran it. + return ("hpc_a100" if dev == "gpu" else "hpc_ral_cpu"), dev, f"host {host}" + if "ral-compute" in h: + return "hpc_ral_cpu", dev, f"host {host}" + if h.startswith("desktop-") or "laptop" in h: + return ("local_gpu" if dev == "gpu" else "local_laptop"), dev, f"host {host}" + return "unknown_host", dev, f"host {host}" + + +# --------------------------------------------------------------------------- routes + + +def cell_index(root: Path) -> dict: + """{(dataset, legacy category dir): {legacy stem: route}} from script_routes.""" + routes = json.loads((root / ROUTES_PATH).read_text())["routes"] + index: dict = defaultdict(dict) + for row in routes: + parts = PurePosixPath(row["legacy"]).parts + stem = PurePosixPath(row["legacy"]).stem + if len(parts) == 4: + index[(parts[1], parts[2])][stem] = row + elif len(parts) == 5 and parts[3] == "datacube": + index[("datacube", parts[2])][stem] = row + return index + + +def script_index(root: Path) -> dict: + """{dataset: {script stem: variant}} over scripts///*.py.""" + index: dict = defaultdict(dict) + for script in sorted((root / "scripts").glob("*/*/*.py")): + dataset, variant = script.parent.parent.name, script.parent.name + if dataset not in ("misc", "lens") and not script.stem.startswith("_"): + index[dataset][script.stem] = variant + return index + + +def longest_prefix(stems, stem: str) -> str | None: + best = None + for legacy in stems: + if (stem == legacy or stem.startswith(legacy + "_")) and ( + best is None or len(legacy) > len(best) + ): + best = legacy + return best + + +# --------------------------------------------------------------------------- classify + + +class Unresolved(Exception): + def __init__(self, group: str, reason: str, proposed: str | None = None, **extra): + super().__init__(reason) + self.group, self.reason, self.proposed, self.extra = group, reason, proposed, extra + + +def archive_class(rel: str) -> tuple[str, str] | None: + """(slug-class, why) for the listed dead-experiment classes, else None.""" + if rel.startswith(FROZEN_PACKS): + return "frozen_pack", "frozen evidence pack" + if rel.startswith(FROZEN_BASELINE): + return "frozen_baseline", "baselines/PreOptimizationTimes" + body = rel.rsplit(".", 1)[0] + tokens = "/".join(split_ext(part)[0] for part in body.split("/")) + for part in tokens.split("/"): + if PROBE_RE.search(part): + return "probes", "_probe experiment" + if LEVER_RE.search(part): + return "levers", "_lever experiment" + if DATED_RE.search(VERSION_RE.sub("", part)): + return "dated", "dated-suffix snapshot" + return None + + +def slug_for(rel: str, cls: str) -> tuple[str, str]: + """(slug, inner path) of an archived file.""" + if cls == "frozen_pack": + pack = next(p for p in FROZEN_PACKS if rel.startswith(p)) + return pack.split("/")[1], rel[len(pack) :] + if cls == "frozen_baseline": + return "PreOptimizationTimes", rel[len(FROZEN_BASELINE) :] + name = rel.rsplit("/", 1)[1] + family = next((f for f in CAMPAIGN_FAMILIES if name.startswith(f)), None) + return (family or cls), rel + + +def find_config(tokens: list[str]): + """Locate ``[_]`` anywhere in the tokens -> (pre, tier, prec, post).""" + for i in range(len(tokens)): + for tier in TIER_TOKENS: + if tokens[i : i + len(tier)] == tier: + j = i + len(tier) + prec = tokens[j] if j < len(tokens) and tokens[j] in PRECISIONS else None + return tokens[:i], "_".join(tier), prec, tokens[j + (1 if prec else 0) :] + return None + + +def operator_of(doc: dict | None, explicit: str | None, dataset: str) -> tuple[str, str]: + config = (doc or {}).get("configuration") + path = config.get("inversion_path") if isinstance(config, dict) else None + from_doc = None + if isinstance(path, str): + low = path.lower() + from_doc = ( + "sparse" + if "sparse" in low + else "dense" + if ("dense" in low or "mapping" in low) + else None + ) + if from_doc and explicit and from_doc != explicit: + raise Unresolved( + "path/content disagree", + f"operator: file name says {explicit}, configuration.inversion_path={path!r}", + ) + if from_doc: + return from_doc, "configuration.inversion_path" + if explicit: + return explicit, "file name" + if dataset in POINT_LIKE: + return "na", "point-source likelihood (no linear inversion)" + return "dense", "legacy grammar: no _sparse suffix" + + +def precision_of(doc: dict | None, token: str | None, backend: str) -> tuple[str, str]: + mixed = None + if doc: + mixed = doc.get("use_mixed_precision", doc.get("mixed_precision")) + if not isinstance(mixed, bool) and isinstance(doc.get("precision"), dict): + mixed = doc["precision"].get("use_mixed_precision") + from_doc = ("mixed" if mixed else "fp64") if isinstance(mixed, bool) else None + if token is not None: + value = PRECISIONS[token] + if value is None: + raise Unresolved("precision outside setup vocabulary", f"precision token {token!r}") + if from_doc and from_doc != value: + raise Unresolved( + "path/content disagree", f"precision: file name {token}, JSON mixed={mixed}" + ) + return value, "file name" + if from_doc: + return from_doc, "use_mixed_precision" + if backend == "numba": + return "fp64", "numba path is fp64-only" + raise Unresolved("setup axis not recorded", "precision not in file name or JSON") + + +def transformer_of(doc: dict | None, dataset: str, operator: str): + """Likelihood route, not transformer class: sparse interferometric rows are W~.""" + if dataset not in INTERFEROMETRIC: + return None, None + if operator == "sparse": + return "wtilde", "sparse interferometric operator = W~ route (report 3.3)" + name = (doc or {}).get("transformer") + if not isinstance(name, str): + config = (doc or {}).get("configuration") + name = config.get("transformer") if isinstance(config, dict) else None + if name in TRANSFORMERS: + return TRANSFORMERS[name], "transformer" + raise Unresolved( + "setup axis not recorded", f"dense interferometric transformer not recorded ({name!r})" + ) + + +def nested_datasets(value, depth: int = 0) -> set[str]: + """Instrument names recorded under nested ``instrument``/``dataset`` keys, including + dataset paths ``dataset///...``.""" + found: set[str] = set() + if depth > 4: + return found + if isinstance(value, dict): + for key, item in value.items(): + if key in ("instrument", "dataset") and isinstance(item, str): + if item in INSTRUMENTS: + found.add(item) + parts = item.split("/") + if len(parts) > 3 and parts[0] == "dataset" and parts[2] in INSTRUMENTS: + found.add(parts[2]) + else: + found |= nested_datasets(item, depth + 1) + elif isinstance(value, list): + for item in value[:50]: + found |= nested_datasets(item, depth + 1) + return found + + +def instrument_of(doc, from_name, from_dir) -> tuple[str, str]: + candidates = {} + if from_dir: + candidates["directory"] = from_dir + if from_name: + candidates["file name"] = from_name + for key in ("instrument", "dataset"): + recorded = (doc or {}).get(key) + if isinstance(recorded, str) and recorded in INSTRUMENTS: + candidates[f"JSON {key}"] = recorded + if not candidates: + nested = nested_datasets(doc) + if len(nested) == 1: + candidates["JSON nested dataset"] = nested.pop() + values = set(candidates.values()) + if len(values) > 1: + raise Unresolved("path/content disagree", f"instrument: {candidates}") + if not values: + raise Unresolved("setup axis not recorded", "instrument not in path or JSON") + return values.pop(), next(iter(candidates)) + + +def misc_fallback(rel: str, why: str) -> dict: + top, inner = rel.split("/", 1) + group = CATEGORY.get(top, top) + return {"kind": "misc", "new": f"results/misc/{group}/{inner}", "why": why} + + +def strip_tokens(stem: str) -> list[str]: + stem = RPIN_RE.sub("", VERSION_RE.sub("", stem)) + return [t for t in stem.split("_") if t] + + +def cell_identity(rel, stem, dataset, category, routes, scripts): + """(variant, backend, model_variant, arm prefix, legacy, rest tokens) or a fallback dict.""" + if stem.startswith("fixed_light_"): + tokens = strip_tokens(stem)[2:] + for i in range(len(tokens)): + mesh = next((m for m in MESHES if tuple(tokens[i : i + len(m)]) == m), None) + if mesh: + tag = tokens[:i] + rest = [ + t for t in tokens[i + len(mesh) :] if t not in ("fixed", "light") + tuple(tag) + ] + if tuple(tag) in MIXED_BACKEND_TAGS: + return misc_fallback(rel, "fixed-light kernel file measures several backends") + backend = "numba" if "numba" in tag else "jax" + return "_".join(mesh), backend, "light_fixed", tag, "fixed_light", rest + return misc_fallback(rel, "fixed-light file names no mesh") + stems = routes.get((dataset, category), {}) + legacy = longest_prefix(stems, stem) + if legacy: + route = stems[legacy] + rest = strip_tokens(stem[len(legacy) + 1 :]) + cell = CELL_MEASUREMENTS.get(route["measurement"]) + if cell: + return route["model"], cell[0], cell[1], [], legacy, rest + backend = "numba" if "numba" in route["measurement"] else "jax" + variant = route["model"] + if variant == "pixelized": # legacy name retired: the mesh token names the variant + for i in range(len(rest)): + mesh = next((m for m in MESHES if tuple(rest[i : i + len(m)]) == m), None) + if mesh: + variant, rest = "_".join(mesh), rest[:i] + rest[i + len(mesh) :] + break + else: + return misc_fallback(rel, f"{route['path']} output names no mesh") + return variant, backend, None, [route["measurement"]], legacy, rest + script = longest_prefix(scripts.get(dataset, {}), stem) + if script: + rest = strip_tokens(stem[len(script) + 1 :]) + backend = "numba" if "numba" in script else "jax" + return scripts[dataset][script], backend, None, [script], script, rest + return misc_fallback(rel, f"stem {stem!r} matches no route or scripts/{dataset}/ script") + + +def classify_cell(rel, fx, routes, scripts) -> dict: + """runtime/** and breakdown/** -> mirrored / scan / experiment / misc, or Unresolved.""" + parts = rel.split("/") + top, dataset = parts[0], parts[1] + category, measurement = CATEGORY[top], top + stem, ext = split_ext(parts[-1]) + dirs = parts[2:-1] + doc = fx["doc"] + if stem == "comparison": + legacy = longest_prefix(routes.get((dataset, category), {}), dirs[0]) if dirs else None + if len(dirs) != 2 or legacy is None or dirs[1] not in INSTRUMENTS: + return misc_fallback(rel, "cross-setup comparison with no instrument level") + variant = routes[(dataset, category)][legacy]["model"] + return { + "kind": "mirrored", + "aggregate": True, + "dataset_type": dataset, + "variant": variant, + "instrument": dirs[1], + "new": f"results/{dataset}/{variant}/{dirs[1]}/comparison.{ext}", + "basis": {"cell": f"directory {dirs[0]}"}, + } + ident = cell_identity(rel, stem, dataset, category, routes, scripts) + if isinstance(ident, dict): + return ident + variant, backend, model_variant, arm, legacy, tokens = ident + all_legacy = set(routes.get((dataset, category), {})) | {"pixelization"} + dir_inst = next((d for d in dirs if d in INSTRUMENTS), None) + scan_dirs = [d for d in dirs if "sweep" in d] + side_dirs = [ + d for d in dirs if d not in INSTRUMENTS and d not in all_legacy and d not in scan_dirs + ] + basis = {"cell": f"{legacy} ({'route' if legacy in all_legacy else 'script'})"} + found = find_config(tokens) + if found: + pre, tier, prec_token, post = found + else: + pre, tier, prec_token, post = tokens, None, None, [] + extras = pre + post + if fx["versioned"]: + extras = [t for t in extras if t not in PURPOSE_TOKENS] + operator_token = next((t for t in extras if t in ("sparse", "dense")), None) + extras = [t for t in extras if t not in ("sparse", "dense")] + joined = "_".join(extras) + name_inst = None + for inst in INSTRUMENTS: # longest names first ("alma_high" before "alma") + if re.search(rf"(?:^|_){inst}(?:_|$)", joined): + name_inst = inst + joined = re.sub(rf"(?:^|_){inst}(?=_|$)", "", joined, count=1).strip("_") + break + extras = [t for t in joined.split("_") if t] + for token, mv in MODEL_VARIANT_TOKENS.items(): + if token in extras: + extras.remove(token) + model_variant = mv + arm_words = {w for a in arm for w in a.split("_")} + extras = side_dirs + [ + t for t in extras if t not in arm_words + ] # e.g. matrix_free_..._matrix_free + if arm or (extras and not all(SCAN_RE.match(t) for t in extras)): + slot = ("experiments", "_".join(arm + extras)) + elif extras or scan_dirs: + slot = ("scans", "_".join(scan_dirs + extras)) + else: + slot = None + try: + host_doc, dev_doc, host_basis = json_host(doc) + if tier is not None: + host, device = TIERS[tier] + if host_doc and host_doc != host: + raise Unresolved("path/content disagree", f"host: tier {tier}, JSON {host_basis}") + if dev_doc and dev_doc != device: + raise Unresolved("path/content disagree", f"device: tier {tier}, JSON {dev_doc}") + basis["host_class"] = f"tier {tier}" + elif host_doc is None and fx["versioned"]: + return { + "kind": "archive", + "archive_class": "hostless_versioned", + "why": "versioned summary with no host in file name or JSON (ruling)", + "rel": rel, + } + elif host_doc is None: + raise Unresolved("setup axis not recorded", "no host in file name or JSON") + elif host_doc == "unknown_host": + raise Unresolved("host outside host_class vocabulary", host_basis) + else: + host, device, basis["host_class"] = host_doc, dev_doc, host_basis + if device is None: + raise Unresolved("setup axis not recorded", "device not recorded") + operator, basis["operator"] = operator_of(doc, operator_token, dataset) + precision, basis["precision"] = precision_of(doc, prec_token, backend) + transformer, tbasis = transformer_of(doc, dataset, operator) + if tbasis: + basis["transformer"] = tbasis + instrument, basis["instrument"] = instrument_of(doc, name_inst, dir_inst) + except Unresolved as exc: + if slot is None: + raise + return misc_fallback(rel, f"{slot[0][:-1]} with no derivable cell: {exc.reason}") + setup_id = f"{backend}_{device}_{operator}_{precision}" + ( + f"_{transformer}" if transformer else "" + ) + cell = f"results/{dataset}/{variant}/{instrument}/{setup_id}/{host}" + ( + f"/{model_variant}" if model_variant else "" + ) + if slot: + name = slot[1] + (f"_v{pin_string(fx['pin'])}" if fx["versioned"] else "") + return { + "kind": slot[0][:-1] if slot[0] == "scans" else "experiment", + "new": f"{cell}/{slot[0]}/{name}/{measurement}.{ext}", + "cell": cell, + "basis": basis, + } + return { + "kind": "mirrored", + "aggregate": False, + "dataset_type": dataset, + "variant": variant, + "instrument": instrument, + "setup_id": setup_id, + "host_class": host, + "model_variant": model_variant, + "measurement": measurement, + "ext": ext, + "stem": stem, + "cell": cell, + "basis": basis, + } + + +def ledger_target(name: str, out_name: str | None = None) -> str: + """Route a ledger/page; ``out_name`` renames a ledger that shares a page's name.""" + route = LEDGER_ROUTES.get(name) + out = out_name or name + if route is None: + raise Unresolved("ledger not routed", f"no LEDGER_ROUTES row for {name}") + dataset, variant = route + if dataset == MULTI_DT: + return f"wiki/campaigns/{out}.md" + if variant == MULTI: + return f"wiki/campaigns/{dataset}/{out}.md" + if dataset == "misc": + return f"wiki/campaigns/misc/{out}.md" + return f"wiki/campaigns/{dataset}/{variant}/{out}.md" + + +def classify(path, files, routes, scripts, fx) -> dict: + """One file -> {kind, new, ...}; raises Unresolved.""" + if path.startswith("wiki/campaigns/"): + name = path.rsplit("/", 1)[1][:-3] + if name == "_template": + return {"kind": "unchanged", "new": path} + return {"kind": "wiki_campaign", "new": ledger_target(name)} + rel = path[len("results/") :] + top = rel.split("/", 1)[0] + if rel in ("README.md", "provenance_grandfathered.txt"): + return {"kind": "unchanged", "new": path} + if top == "lens": + return {"kind": "lens_component", "new": path} + if top == "notes" and rel.count("/") == 1 and rel.endswith(".md"): + name = rel[6:-3] + # A ledger named like a campaign page keeps both files: the ledger gains _ledger. + out = f"{name}_ledger" if f"wiki/campaigns/{name}.md" in files else name + return {"kind": "wiki_campaign", "new": ledger_target(name, out)} + cls = None if top == "logs" else archive_class(rel) # log names carry their run date + if cls: + return {"kind": "archive", "archive_class": cls[0], "why": cls[1], "rel": rel} + pre_series = (fx["series_date"] or "9999") < PRE_SERIES_CUTOFF + if top in CATEGORY: + name = rel.rsplit("/", 1)[1] + stem, ext = split_ext(name) + if ext in ("out", "stdout"): + folder = rel.split("/")[-2] + campaign = folder if folder == rel.split("/")[1] else f"{rel.split('/')[1]}_{folder}" + return { + "kind": "misc", + "new": f"results/misc/logs/{campaign}/{name}", + "why": "log capture outside results/logs/", + } + if SIDECAR_RE.search(stem): + return {"kind": "sidecar", "rel": rel} + result = classify_cell(rel, fx, routes, scripts) + if result["kind"] in ("scan", "experiment", "misc") and pre_series: + return { + "kind": "archive", + "archive_class": "pre_2026_09", + "why": f"pre-2026-09 series ({result['kind']})", + "rel": rel, + } + return result + if top in MISC_GROUPS: + if VERSION_RE.search(rel) and pre_series: + return { + "kind": "archive", + "archive_class": "pre_2026_09", + "why": "pre-2026-09 versioned series", + "rel": rel, + } + inner = rel.split("/", 1)[1] + return {"kind": "misc", "new": f"results/misc/{MISC_GROUPS[top]}/{inner}"} + raise Unresolved("unknown results folder", f"results/{top}/ has no rule") + + +# --------------------------------------------------------------------------- build + + +def ledger_dates(root: Path, files: set[str]) -> list[tuple[str, str, str]]: + """(ledger path, date, text) for every results/notes ledger with a derivable date.""" + out = [] + for path in sorted(files): + if path.startswith("results/notes/") and path.count("/") == 2 and path.endswith(".md"): + text = (root / path).read_text() + named = DATED_RE.search(path.rsplit("/", 1)[1][:-3]) + heading = ANY_ISO_RE.search(text.split("\n", 1)[0]) + if named: + out.append((path, iso(*named.groups()), text)) + elif heading: + out.append((path, iso(*heading.groups()), text)) + return out + + +def place_sidecar(root, path, classified) -> str | None: + """A job sidecar goes beside the results it names (their common cell directory).""" + doc = load_json(root, path) or {} + text = json.dumps(doc) + names = set((doc.get("artifact_sha256") or {}).keys()) if isinstance(doc, dict) else set() + names |= {p.rsplit("/", 1)[1] for p in re.findall(r"results/[A-Za-z0-9_./+-]+", text)} + by_name = defaultdict(list) + for old, c in classified.items(): + by_name[old.rsplit("/", 1)[1]].append(c) + targets = [] + for name in sorted(names): + for c in by_name.get(name, []): + if c.get("kind") in ("mirrored", "history", "scan", "experiment"): + targets.append(c["new"].rsplit("/", 1)[0]) + if not targets: + return None + common = os.path.commonpath(targets) + for marker in ("/experiments/", "/scans/"): + if marker in common + "/": + common = (common + "/").split(marker)[0] + marker.rstrip("/") + if common.count("/") < 5: + return None + return f"{common}/{path.rsplit('/', 1)[1]}" + + +def build(root: Path) -> dict: + root = Path(root) + paths = tracked(root) + files = set(paths) + routes, scripts = cell_index(root), script_index(root) + unresolved = {} + facts_by = {p: facts(root, p, files) for p in paths} + classified = {} + for path in paths: + try: + classified[path] = classify(path, files, routes, scripts, facts_by[path]) + except Unresolved as exc: + unresolved[path] = exc + + # Archive: month = the file's own date, else the latest date in its slug, else the + # date of a ledger that names the file, else archive/undated//. + slug_dates: dict = defaultdict(list) + for path, c in classified.items(): + if c["kind"] == "archive": + c["slug"], c["inner"] = slug_for(c["rel"], c["archive_class"]) + if c["archive_class"] == "hostless_versioned": + c["slug"] = "hostless_summaries" + if facts_by[path]["series_date"]: + slug_dates[c["slug"]].append(facts_by[path]["series_date"]) + named = DATED_RE.search(c["slug"]) if c["archive_class"] == "frozen_pack" else None + if named: + slug_dates[c["slug"]].append(iso(*named.groups())) + slug_months = {s: max(d)[:7].replace("-", "/") for s, d in slug_dates.items()} + slug_basis = {s: "latest file date in slug" for s in slug_months} + for slug, (month, why) in SLUG_MONTH.items(): + if slug not in slug_months: + slug_months[slug], slug_basis[slug] = month, why + ledgers = ledger_dates(root, files) + packs = {c["slug"] for c in classified.values() if c.get("archive_class") == "frozen_pack"} + for slug in sorted(packs): + if slug not in slug_months: + cite = next(((lp, d) for lp, d, text in ledgers if slug in text), None) + if cite: + slug_months[slug] = cite[1][:7].replace("-", "/") + slug_basis[slug] = f"date of citing ledger {cite[0]}" + for path, c in classified.items(): + if c["kind"] != "archive": + continue + own = facts_by[path]["series_date"] + pack = c["archive_class"] in ("frozen_pack", "frozen_baseline") + month = None if pack or not own else own[:7].replace("-", "/") + if month is None and not pack: + stem = split_ext(path.rsplit("/", 1)[1])[0] + cite = next(((lp, d) for lp, d, text in ledgers if stem in text), None) + if cite: + month = cite[1][:7].replace("-", "/") + c["why"] += f"; month from citing ledger {cite[0]}" + if month is None: + month = slug_months.get(c["slug"]) + if month is None: + month = "undated" + c["new"] = f"archive/{month}/{c['slug']}/{c['inner']}" + + # Mirrored keys: newest record -> current slot, older records -> history/. + records: dict = defaultdict(lambda: defaultdict(list)) + for path, c in classified.items(): + if c["kind"] == "mirrored" and not c["aggregate"]: + key = (c["cell"], c["measurement"]) + record = path.rsplit("/", 1)[0] + "/" + c["stem"] + records[key][record].append(path) + for (cell, measurement), recs in records.items(): + order = [] + for record, members in recs.items(): + fx = next( + (facts_by[m] for m in members if facts_by[m]["doc"] is not None), + facts_by[members[0]], + ) + order.append((fx["pin"] or (), fx["series_date"] or "", record, members, fx)) + order.sort(key=lambda o: (o[0], o[1]), reverse=True) + current = order[0][2] + if len(order) > 1 and (order[0][0], order[0][1]) == (order[1][0], order[1][1]): + tied = [o for o in order if (o[0], o[1]) == (order[0][0], order[0][1])] + for o in tied: + for m in o[3]: + unresolved[m] = Unresolved( + "ambiguous current record", + f"{len(tied)} records share {cell}/{measurement} with the same " + f"release pin and date: {sorted(t[2] for t in tied)}", + ) + del classified[m] + order = [o for o in order if o not in tied] + current = None + for pin, date, record, members, fx in order: + for m in members: + c = classified[m] + c["release_pin"] = pin_string(pin) if pin else None + c["date"] = date or None + c["date_basis"] = fx["series_basis"] + if record == current: + c["new"] = f"{cell}/{measurement}.{c['ext']}" + else: + c["kind"] = "history" + c["new"] = ( + f"{cell}/history/{pin_string(pin) or 'unpinned'}_{date or 'undated'}/" + f"{measurement}.{c['ext']}" + ) + + # Job sidecars go beside the results they describe. + for path, c in list(classified.items()): + if c["kind"] == "sidecar": + target = place_sidecar(root, path, classified) + if target is None: + classified[path] = misc_fallback( + path[len("results/") :], + "job sidecar: the results it names span several cells, or none is tracked", + ) + else: + classified[path] = {"kind": "experiment", "new": target, "why": "job sidecar"} + + # Collisions are errors. + targets: dict = defaultdict(list) + for path, c in classified.items(): + targets[c["new"]].append(path) + collisions = {new: olds for new, olds in targets.items() if len(olds) > 1} + + out_entries = [] + for path in sorted(classified): + c = classified[path] + entry = {"old": path, "new": c["new"], "sha256": sha256(root, path), "kind": c["kind"]} + if c["kind"] in ("mirrored", "history"): + entry["key"] = { + k: c[k] + for k in ( + "dataset_type", + "variant", + "instrument", + "setup_id", + "host_class", + "model_variant", + "measurement", + "release_pin", + "date", + "date_basis", + ) + if c.get(k) is not None + } + if c.get("basis"): + entry["basis"] = c["basis"] + if c["kind"] == "archive": + entry["archive_class"] = c["archive_class"] + if c.get("why"): + entry["why"] = c["why"] + out_entries.append(entry) + out_unresolved = [] + for path in sorted(unresolved): + exc = unresolved[path] + row = {"old": path, "sha256": sha256(root, path), "group": exc.group} + row["reason"] = exc.reason + if exc.proposed: + row["proposed"] = exc.proposed + out_unresolved.append(row) + + # Mirror witness: results/
// vs scripts/
//. + in_tree = ("mirrored", "history", "scan", "experiment") + result_pairs = sorted( + { + (e["new"].split("/")[1], e["new"].split("/")[2]) + for e in out_entries + if e["kind"] in in_tree and not e["new"].startswith("results/misc/") + } + ) + script_pairs = sorted( + (d.parent.name, d.name) + for d in (root / "scripts").glob("*/*") + if d.is_dir() + and d.parent.name not in ("misc", "lens") + and d.name != "__pycache__" + and any(f.suffix == ".py" for f in d.iterdir()) + ) + misc_groups = sorted( + {e["new"].split("/")[2] for e in out_entries if e["new"].startswith("results/misc/")} + ) + script_misc = sorted(d.name for d in (root / "scripts/misc").iterdir() if d.is_dir()) + counts = defaultdict(int) + for e in out_entries: + counts[e["kind"]] += 1 + groups = defaultdict(int) + for row in out_unresolved: + groups[row["group"]] += 1 + covered = len(out_entries) + len(out_unresolved) + cell = "results/////[/]" + return { + "schema": SCHEMA, + "version": VERSION, + "issue": ISSUE, + "generator": "scripts/misc/tooling/build_migration_map.py", + "source_commit": source_commit(root), + "note": ( + "Day-zero migration plan: old -> new path + sha256 for every tracked file under " + "results/ and every wiki/campaigns/*.md page. Nothing has moved. Unresolved rows " + "need a human ruling before the move-only PR." + ), + "layout": { + "cell": cell, + "mirrored": "/. -- the only slot that may become current", + "history": "/history/_/. -- superseded", + "scan": "/scans//. -- size scans; never current", + "experiment": ( + "/experiments//. (and job sidecars in " + "/experiments/) -- arms and experiment scripts; never current" + ), + "aggregate": "results////comparison.", + "setup_id": ( + "___[_]; the transformer " + "names the likelihood route: sparse interferometric = wtilde" + ), + "model_variant": "path segment only for non-default variants (light_fixed, rtu, mge_mass)", + "misc": "results/misc//... -- files with no derivable cell; never current", + "archive": ( + "archive/YYYY/MM//; YYYY/MM is " + "the file's own date (name or JSON), else the latest date in its slug, else a " + "citing ledger's date, else archive/undated//" + ), + "ledgers": ( + "wiki/campaigns///.md | " + "wiki/campaigns//.md (several variants) | " + "wiki/campaigns/.md (several dataset types) | " + "wiki/campaigns/{lens/,misc}/.md" + ), + }, + "counts": { + "tracked_files": len(paths), + "covered": covered, + "by_kind": dict(sorted(counts.items())), + "unresolved": len(out_unresolved), + "unresolved_by_group": dict(sorted(groups.items(), key=lambda kv: (-kv[1], kv[0]))), + }, + "collisions": [ + {"new": new, "old": sorted(olds)} for new, olds in sorted(collisions.items()) + ], + "mirror": { + "result_variants": [f"{a}/{b}" for a, b in result_pairs], + "result_variants_without_scripts": [ + f"{a}/{b}" for a, b in result_pairs if (a, b) not in script_pairs + ], + "script_variants_without_results": [ + f"{a}/{b}" for a, b in script_pairs if (a, b) not in result_pairs + ], + "misc_groups_without_scripts": [g for g in misc_groups if g not in script_misc], + }, + "setup_ids": sorted( + {e["new"].split("/")[4] for e in out_entries if e["kind"] in in_tree} + - {"comparison.json", "comparison.png"} + ), + "archive_slugs": { + s: {"month": slug_months[s], "basis": slug_basis[s]} for s in sorted(slug_months) + }, + "entries": out_entries, + "unresolved": out_unresolved, + } + + +def render(doc: dict) -> str: + return json.dumps(doc, indent=1, sort_keys=False) + "\n" + + +def comparable(doc: dict) -> dict: + return {k: v for k, v in doc.items() if k != "source_commit"} + + +def main(argv=None) -> int: + parser = argparse.ArgumentParser(description=__doc__.split("\n", 1)[0]) + parser.add_argument("--check", action="store_true", help="exit 1 if the map is stale") + parser.add_argument("--root", type=Path, default=None) + args = parser.parse_args(argv) + root = args.root or _root() + doc = build(root) + if doc["collisions"]: + for c in doc["collisions"]: + print(f"COLLISION {c['new']} <- {c['old']}", file=sys.stderr) + print("refusing to write a map with collisions", file=sys.stderr) + return 1 + target = root / MAP_PATH + if args.check: + try: + committed = json.loads(target.read_text()) + except (OSError, ValueError): + print(f"{MAP_PATH} missing or unreadable", file=sys.stderr) + return 1 + if comparable(committed) != comparable(doc): + print(f"{MAP_PATH} is stale: re-run build_migration_map.py", file=sys.stderr) + return 1 + print(f"{MAP_PATH} is current ({doc['counts']['covered']} files)") + return 0 + target.write_text(render(doc)) + c = doc["counts"] + print(f"wrote {MAP_PATH}: {c['covered']}/{c['tracked_files']} files, {c['by_kind']}") + print(f"unresolved {c['unresolved']}: {c['unresolved_by_group']}") + return 0 + + +if __name__ == "__main__": + sys.exit(main())