{
  "date": "2026-10-25",
  "machine": "Apple M4 Pro; 10 performance + 4 efficiency cores; 48 GiB RAM",
  "python": "CPython 3.13.5",
  "numpy": "2.4.2",
  "workers": [
    1,
    2,
    4,
    8
  ],
  "trials_per_point": 2,
  "warm_blocks_per_mode": 3,
  "target_block_s": 0.5,
  "frames_per_batch": 32,
  "bin_count": 2000,
  "unit": "2theta degrees",
  "polarization_factor": 0.965,
  "solid_angle": true,
  "arrays": "Not measured in this paired-file cohort; see the earlier 80-process control cohort in results.json and protocol.json.",
  "files": "Each task reopens and decodes an uncompressed signed-int32 TIFF. Poisson off/on measured in the same process, in reversed mode order across trials; warm filesystem cache.",
  "geometry": "Same equivalent mirrored PONI geometry, masks, radial range and detector images for all backends.",
  "sampling_n": {
    "Pilatus1M": 15,
    "Eiger9M": 5
  },
  "pixel_split": "Geometric pixel splitting has no subpixel count.",
  "dioptrin": "Published PyPI 0.6.1 wheel, generic release build; fast_math=True. Native SHA-256 checked against the freshly installed release verification.",
  "azint": {
    "commit": "4f78cc3b1d8cab67128c9679f55de6340c68f191",
    "compiler": "Homebrew clang 22.1.8",
    "flags": "-O3 -mcpu=native -flto=thin -ffast-math",
    "version": "0.1.dev1+g4f78cc3b1",
    "source": "https://github.com/maxiv-science/azint"
  },
  "pyfai": "Official 2026.9.0 wheel; bbox/CSR/Cython, safe=True; one engine per frame worker. Full CSR is retained only in the earlier control cohort.",
  "threading": "OMP_NUM_THREADS=1 for pyFAI and Dioptrin; equals worker count only for azint matrix construction. Numerical-library helper threads limited to one.",
  "qualification": "Every timing mode must have <=3.6 other busy logical cores. Rejected attempts retained separately; unrelated calculations were not suspended for this final run.",
  "order": "Variant and worker order reverse in the second fresh-process trial.",
  "uncertainty": "Bars are medians of two fresh-process trials; whiskers span their range, not confidence intervals.",
  "memory": "Whole-process RSS sampled every 10 ms. Both modes share a fresh process; mode order is reversed across trials. No preloaded image stack.",
  "dataset_images": {
    "Pilatus1M": "1043x981; 32 separate filenames containing copies of one image",
    "Eiger9M": "3262x3108; 16 distinct real images, each read twice per batch"
  },
  "headline_chart_methods": {
    "dioptrin": "dioptrin_ps",
    "pyfai": "pyfai_bbox",
    "azint": "azint_fast"
  },
  "headline_chart_workers": [
    1,
    8
  ],
  "headline_chart_workload": "Reopen and decode each TIFF and integrate; error estimation off. A second visible chart includes Poisson estimation.",
  "accepted_processes": 48,
  "rejected_attempts": 14,
  "tested_methods": {
    "dioptrin_ps": "Dioptrin 0.6.1",
    "azint_fast": "azint \u00b7 CPU-tuned",
    "pyfai_bbox": "pyFAI 2026.9.0"
  },
  "mode_order": "Off then on in trial one; on then off in trial two.",
  "scope": "Published-library Python file pipelines; not a direct Dioptas application/GUI benchmark.",
  "setup": "Existing initialization creates engines with one Poisson-enabled first image in both cases; warm throughput then toggles error estimation.",
  "first_batch": "First batch in a mode may reuse workers/caches from the preceding mode; not an independent cold-start comparison.",
  "validation": "First batch and post-timing batch in both modes checked byte-for-byte against existing same-build/same-backend references.",
  "harness_sha256": "b08e3c88da7b0b4c7d9b73980a39c56e1147f96cf86d3958164e1c10568b9ed7",
  "imported_harness_sha256": {
    "/Users/clemens/Documents/Codex/2026-10-25/website-file-error-modes/run.py": "b08e3c88da7b0b4c7d9b73980a39c56e1147f96cf86d3958164e1c10568b9ed7",
    "/Users/clemens/Documents/Codex/2026-10-23/can-x20/work/website-final-benchmark/run.py": "9f4df87944d27f6b0324ffcd7d59f86a4da15aa8778941c4a8bb7d7889c1c232",
    "/Users/clemens/Documents/Codex/2026-10-23/can-x20/work/real-world-io/run.py": "5ab71438ba7a575145d131acdb410144f1d25d9db37ee2de7b99c63ac5473ad5",
    "/Users/clemens/Documents/Codex/2026-10-23/can-x20/work/compiler-tuning/run.py": "5d514895ef3f1b89128200cbf0dc2658cb1dbe3093229efbe6dec97197e7ff0b",
    "/Users/clemens/Documents/Codex/2026-10-23/can-x20/work/website-final-benchmark/references.json": "af695e196fa892f3aa1b7d31994b066bb6b94ab4f76dd1d57f08caec1c6b0dc4",
    "/Users/clemens/Documents/Codex/2026-10-23/can-x20/work/real-world-io/datasets.json": "cafba9d3893570089f677ffdb0b5598269774c2f007960ee1fe1d492338fd73e"
  },
  "source_note": "file-benchmark.py records the measured driver; it imports the previous local harnesses and requires the original input files and backend builds. This data bundle is not a standalone runnable environment."
}