lensmerit op• 数据种类:table → table
• 调用: import fullseye as fs; fs.ledger.optimize_lens_operands(system=None, operands=None, variables=None, iterations: 'int' = 30, fields=None, wavelengths=None, field_weights=None, wavelength_weights=None, damping: 'float' = 0.001, tolerance: 'float' = 1e-07, min_thickness: 'float' = 0.5, max_thickness=None, min_radius: 'float' = 1.0, glass_candidates=None, glass_iterations: 'int' = 12, outer_iterations: 'int' = 3) -> 'dict'(要直接调用实现,import lensmerit; lensmerit.optimize_lens_operands(system=None, operands=None, variables=None, iterations: 'int' = 30, fields=None, wavelengths=None, field_weights=None, wavelength_weights=None, damping: 'float' = 0.001, tolerance: 'float' = 1e-07, min_thickness: 'float' = 0.5, max_thickness=None, min_radius: 'float' = 1.0, glass_candidates=None, glass_iterations: 'int' = 12, outer_iterations: 'int' = 3) -> 'dict';从台账取用则 opsoptics.get("optimize_lens_operands"))
用 LM 法最小化操作数表的评价函数,玻璃也可以作为变量(table)。
> 以下的详细说明为原文 —— 摘要与标题已翻译。
The residual vector is the stack of the table's rows (merit_evaluate); *variables* are those of lensopt.optimize_lens ("c<i>" / "R<i>" curvature, "t<i>", "k<i>", "A4_<i>" ...; default every finite radius) plus glass variables "g<i>". The continuous steps are lensopt's: forward-difference Jacobian, (JtJ + lambda diag(JtJ)) delta = -Jt r, a step is kept only if the merit falls (lambda /3, else x4, six tries), stalled after two iterations without an accepted step. *min_thickness*, *max_thickness* and *min_radius* clamp the variables as in optimize_lens (the table's bound rows are what keep edges, centres and gaps in range). A glass variable moves the glass of surface *i* over *glass_candidates* (a list of media: catalogue names, (n_d, V_d) pairs or raytrace.glass dicts; or a dict "g<i>" -> list) by an outer discrete sweep: after the continuous optimisation has converged each candidate is tried once (swapped in, the continuous variables re-optimised for *glass_iterations* iterations) and the best is kept if it lowers the merit; this repeats up to *outer_iterations* times with a full continuous re-optimisation between sweeps. A candidate equal to the glass already there is skipped, so a list holding only the current glass gives exactly the continuous result.
Returns {"system", "table_before", "table_after", "merit_initial", "merit_final", "history", "iterations", "rejected_steps", "converged", "status", "variables", "glass", "dominant_after", "violated_after"}; table_before / table_after are merit_evaluate results, rejected_steps counts the trial steps refused, glass lists each glass variable with its initial / final medium and every candidate's merit.
Example::
r = optimize_lens_operands(lens, ops, ["c0", "c1", "t0", "g0"], glass_candidates=[(1.52, 64.2), (1.62, 36.4)],
fields=m["fields"])
r["merit_initial"], r["merit_final"], r["glass"][0]["final"]
optics 的每个算子都先校验输入再计算(不让任何东西无声通过):
• 单位写进参数名 —— _mm / _um / _deg / _mrad。把 mm 和 µm 弄混不会崩溃,而是给出「看着合理却是错的答案」,所以用命名来防。这里绝不从数值大小去猜单位。
• 字符串一律 ValueError —— float('50') 会成功,于是未解析的配置值会被当成长度混进来(实测:thin_lens('50', '200') 曾返回看着合理的 66.667 mm)。bool 也按 True == 1 的隐式提升拒绝。
• complex / masked array 一律 ValueError(仅接受实数槽位;拒绝无声丢弃虚部或剥掉掩码)。所有输入中的 NaN/Inf 一律 ValueError。
• 逐项点名拒绝除零及其近亲:焦距 0、曲率半径 0、折射率 <= 0、全不透明光阑(全为 0,归一化变成 0/0)、总和 <= 0 的 PSF、S0 = 0 的 Stokes 矢量、物体位于前焦点(像在无穷远)。
• 只有两个算子会返回非有限值,而且都写进了契约:depth_of_field 在超焦距以外返回 far_mm = inf(这正是超焦距的定义),gaussian_beam 在束腰处返回 wavefront_radius_mm = inf(平面波前的曲率半径)。两者都同时返回一个有限的搭档(far_is_infinite / curvature_per_mm)。除此之外的无声 NaN/Inf 都在内部检出并 ValueError ——「float64 溢出了」和「答案是无穷大」是两种不同的主张,不能拿后者的脸去交付前者。
• 尺寸上限:生成网格受 optics.MAX_GRID(4096)限制,传入的场/PSF/光阑受 optics.MAX_FIELD_ELEMENTS(2^24),ABCD 元件序列受 optics.MAX_SYSTEM_ELEMENTS(1024),Zernike 受 MAX_ZERNIKE_TERMS(512)/ MAX_ZERNIKE_ORDER(40)/ MAX_ZERNIKE_BASIS(2^25)。以 fail-closed 堵住「小参数引发巨大内部分配」的路径(实测:n_max=40 × 4096² 需要 108 GB)。
• 物理上不可能的状态同样拒绝:偏振度 > 1 的 Stokes 矢量、负透过率、负强度、n-|m| 为奇数等非法 Zernike 指标。
• 示例数据目录(下载 URL / 许可证) —— 2-D 用 skimage.data(BSD/公有领域)加合成图,3-D 给出真实数据源(Stanford/PDS 等)的下载 URL。
• 算子来历与参考文献 —— 该算子族所依据的研究/方法出处。
• 算法的正典(作者、年份)与用途见上面的族使用指南。
• optimized_lens_tolerance_sensitivity — py -3.11 examples/optimized_lens_tolerance_sensitivity.py
• poc_lens_merit_operands — py -3.11 examples/poc_lens_merit_operands.py
table 作为输入)abcd_matrix · wavefront_stats · sfr_from_edge · paraxial_trace · seidel_coefficients · spot_stats · tolerance_analysis · wavefront_from_opd
lensmerit)merit_operands_list · merit_evaluate · merit_default · merit_boundary_operands · merit_contributions
*Provenance: lensmerit.py — OPTICS 算子登记表。本条目由 tools/opdocs.py md 自动生成(请勿手工编辑)。*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.