lensglobal optable → tableimport fullseye as fs; fs.ledger.lens_global_search(system=None, variables=None, merit=None, n_starts: 'int' = 8, seed: 'int' = 0, spread: 'float' = 0.5, iterations: 'int' = 40, duplicate_tolerance: 'float' = 0.001) -> 'dict' (実装を直接呼ぶなら import lensglobal; lensglobal.lens_global_search(system=None, variables=None, merit=None, n_starts: 'int' = 8, seed: 'int' = 0, spread: 'float' = 0.5, iterations: 'int' = 40, duplicate_tolerance: 'float' = 0.001) -> 'dict'、台帳から引くなら opsoptics.get("lens_global_search"))多始点の局所最適化(lensopt.optimize_lens)で局所解を集め、merit 順に返す(table)。
Start 0 is system as given; starts 1 .. n_starts-1 move every variable to x (1 + spread u)
with u uniform in [-1, 1] drawn from numpy.random.default_rng(seed) (a variable that is
zero, such as a flat, moves by spread times the typical size of its kind). A perturbed start
that is not a valid prescription is redrawn (up to 25 times, then ValueError). Every start is
optimised by lensopt.optimize_lens with the same merit and the same EFL target (the EFL
of system unless merit["efl_target"] says otherwise), so the optima are comparable.
merit is a dict of fields wavelengths rings efl_target efl_weight field_weights pupil_fill
min_thickness max_thickness min_radius damping tolerance; variables are as in optimize_lens.
Returns {"optima", "best", "n_starts", "n_distinct", "basins", "seed", "spread"}. optima
holds every start’s result sorted by merit (ties by start index): {"start", "merit",
"start_merit", "rms_spot", "efl", "system", "values", "status", "converged", "duplicate_of"}
where duplicate_of is the start of an earlier (better) optimum with the same variables
(every variable within duplicate_tolerance relative, floor 1e-9) or None. basins lists the
distinct optima with the number of starts that reached each. Deterministic for a given seed.
Example::
r = lens_global_search(singlet, ["c0", "c1"], {"efl_target": 100.0}, n_starts=12, seed=3)
r["best"]["merit"], r["n_distinct"]
optics の全 op は入力を検証してから計算する(黙って通さない):
_mm / _um / _deg / _mrad。mm と µm の取り違えは crash ではなく「もっともらしく間違った答え」なので、名前で防ぐ。大きさから単位を推測する処理は一切しない。ValueError — float('50') は成功してしまうため、未パースの設定値が長さとして通り抜ける(実測: thin_lens('50', '200') がもっともらしい 66.667 mm を返していた)。bool も True == 1 の暗黙昇格として拒否。ValueError(実数枠のみ。虚部の無言切り捨て・マスク剥がしを拒否)。NaN/Inf は全入力で ValueError。depth_of_field の過焦点距離以遠の far_mm = inf(それが過焦点距離の定義)と gaussian_beam のウエストでの wavefront_radius_mm = inf(平面波面の曲率半径)。どちらも有限の相棒(far_is_infinite / curvature_per_mm)を併せて返す。それ以外の無言 NaN/Inf は内部で検出して ValueError —「float64 が溢れた」と「答えが無限大」は別の主張なので、後者の顔で前者を返さない。optics.MAX_GRID(4096)、供給された場/PSF/開口は optics.MAX_FIELD_ELEMENTS(2^24)、ABCD 素子列は optics.MAX_SYSTEM_ELEMENTS(1024)、Zernike は MAX_ZERNIKE_TERMS(512)/ MAX_ZERNIKE_ORDER(40)/ MAX_ZERNIKE_BASIS(2^25)。小さな引数から巨大な内部確保が起きる経路(実測: n_max=40 × 4096² で 108 GB)を fail-closed で塞ぐ。| 物理的に不可能な状態も拒否: 偏光度 > 1 の Stokes ベクトル、負の透過率、負の強度、n- | m | が奇数などの不正な Zernike 添字。 |
py -3.11 examples/poc_lens_global_search.pytable を入力に取れる)abcd_matrix · wavefront_stats · sfr_from_edge · paraxial_trace · seidel_coefficients · spot_stats · tolerance_analysis · wavefront_from_opd
lensglobal)glass_nearest · lens_substitute_glasses
Provenance: lensglobal.py — OPTICS operator registry. この per-op ノートは tools/opdocs.py md が自動生成(手編集しない)。
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.