grind op• Data kinds: any → table
• Call: import fullseye as fs; fs.ledger.replicate_compare(groups: 'dict', log: 'bool' = True) -> 'dict' (to call the implementation directly, import grind; grind.replicate_compare(groups: 'dict', log: 'bool' = True) -> 'dict'; from the registry, opsdrive.get("replicate_compare"))
> This operator's description has not been translated yet. The original text follows as it is.
独立試行のばらつきと、群(材料)どうしの差を同じ物差しで並べる。
`groups: 名前 → (n_runs, n_conditions) の配列(例: 材料ごとに 3 回 × 7 時点の D50)。全群で n_conditions` が同じ。
`log=True は ln をとってから比べる(径の比のばらつき = 変動係数に近い)。返り: spread(群 → 条件ごとの mean・sd`・
`cv(SD/平均、元の尺度)、cv_pooled(cv の二乗平均の根)、cv_max)、separation`(群の組 → 条件ごとの
`|Δ平均| / √(SE₁² + SE₂²)(SE = SD/√n)と、その最小 min_z。鍵は "名前1|名前2" の文字列)。試行が 2 未満 → ValueError`。
• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).
• Operator provenance and references — the sources of the research/methods this op family came from.
• The canonical algorithm (author, year) and its uses are named in the family usage guide above.
• poc_powder_grinding_ae — py -3.11 examples/poc_powder_grinding_ae.py
table as input)course_layout · course_occupancy · course_contains · world_build · world_camera · world_move · lidar_scan · rss_longitudinal_same
grind)particle_size_read · particle_size_dx · particle_size_oversize · particle_size_synth · comminution_energy · comminution_law_fit · breakage_first_order_fit · ae_read_csv
*Provenance: grind.py — DRIVE operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.