OSLO中的样板数据分析是个鸡肋，功能简单不实用，OSLO的最大缺点是为用户考虑的太少，尽管它的灵活性可以让我为所欲为。当镜头面数很多时，套样板的方法显得至关重要，程序提供自动套样板功能，其结果也许并非最佳结果，但也能相当程度地反应样板套取方法的优劣趋势，设计人员可以在此基础上根据自己的理论知识和经验作进一步的改善优化，鉴于此，用CCL将Zemax的样板套取功能完全复现，除实现了Zemax中的4种算法，还添加了额外3种算法。
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程序的难点有：1、对样板文件的处理，难处是用CCL提供的有限的文件处理命令和就那么几个文本操作函数实现起来，有很多东西要自己代码实现，这里的样板文件格式与Zemax的全同，Zemax的现成样板文件必须拿过来就能用；2、对OSLO中的系统数据的操作，诸如变量的保存、中间优化结果的存储、套样板后数据如何恢复等等，这里涉及的问题，OSLO提供的内部命令及变量都能解决；3、算法问题，也就是该如何套，可以参考Zemax现成的几种算法，<<Modern lens desgin>>一书中提到的算法也尽量实现；4、其他细节问题，如样板半径如何算是符合套样标准（可以参考Zemax的），对文本行的解析得到样板数据等等 T) MZ`dM
程序框架如下： 5wb R}`8
FitGlass(...) %APeQy"6#^
{ 4']eJ==OH
while(1) 'v%v*Ujf[
{ AP0z~e
read_plate_file(...); (4C_Ft*~j
GetOneLine(...); HA ~BXxa/
parse_string_line(...) (~]0)J
//将数据存入样板数组 {r_x\VC=p
.... | |'A9
} _o{w<b&
Fit_ShortToLong(...); %h& F
Fit_LongToShort(...); bjql<x5d
Fit_BestToWorst(...); #=czqZw
Fit_WorstToBest(...); sH :_sOV*
Fit_Power_BigToSmall(...); t ]P^6jw'
Fit_Abr_BigToSmall(...); 1!A 'mkk8
Fit_MF_BigToSmall(...); f#
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//下面开始选择处理结果 0134mw%jk
... /8LTM|(
} 'J_6SD
程序代码量还是很多的，取个中等复杂镜头样板的套取结果例子如下 #F ;@Qi3z
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TestPlate File's name:yangzhou.tpd o| 9Mj71
Init MF Value:0.00062 htOVt\+!34
Method: Short to Long(1) Dj'+,{7,u
Srf Old Radius New Radius MF Value MF Change 0E/16@6=
6 5.57706 5.57000 0.00101 62.51945% Pk )H(,
8 -12.55338 -12.57300 0.00542 771.03542% zUz j
F
9 18.37981 18.36500 0.00202 221.96974% Sw~L
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3 18.58131 18.53500 0.00915 1359.96125% ? ;$f"Wl
7 -24.70139 -24.66000 0.00178 184.01078% II{"6 YI>
5 -28.55608 -28.58000 0.00068 8.79409% HA3d 9`
2 -53.96599 -53.94000 0.00100 59.93393% PPj%.i)
10 57.91138 57.93000 0.00064 2.94712% ;oVFcZSA
1 121.60450 121.89600 0.00175 180.28879% /` b`ai8`8
4 125.85170 122.46000 0.00940 1400.41107% SH;:b Lk_
Final MF Value:0.00064 Relative change:3.07884% B\6% .R
Method: Long to Short(2) NkYC( ;g
Srf Old Radius New Radius MF Value MF Change C*Wyw]:r
4 125.20984 122.46000 0.00768 1133.54154% HD;l1W)
1 121.51149 121.89600 0.00225 260.91411% UI74RP
10 58.31318 57.93000 0.00320 412.26872% Z1R{'@Y0Z
2 -54.00322 -53.94000 0.00200 221.25579% _PGS"O?j
5 -28.87047 -28.76000 0.00137 119.38819% 9bu1Ax1M
7 -24.41613 -24.49000 0.00308 393.92127% diD[/&k#kh
3 18.54773 18.53500 0.00258 313.92207% .t$1B 5
9 18.36134 18.36500 0.00078 25.56252% `0 Xs!f
8 -12.55473 -12.57300 0.00506 710.82362% b2UqN]{
6 5.56698 5.57000 0.00211 -4.68411% Ex4)R2c*
Final MF Value:0.00065 Relative change:3.58804% 3/EJ ^C
Method: Best to Worst(3) R)'[Tt`# R
Srf Old Radius New Radius MF Value MF Change ;!pJ %p0Sc
1 121.74488 121.89600 0.00105 69.09700% $Sc;
9 18.36994 18.36500 0.00089 41.17665% <E\vc6n
2 -54.11743 -53.94000 0.00537 761.51122% jDCf]NvOPM
3 18.56222 18.53500 0.00540 764.71352% zC>zkFT>H
10 58.36529 57.93000 0.00361 479.27779% A9ZK :i 7
6 5.56872 5.57000 0.00064 2.65958% d% Nx/ DS)
4 124.36063 122.46000 0.00536 757.60693% xv 0y?#`z
5 -28.80466 -28.76000 0.00080 27.59264% 4x?4[J~u[
7 -24.45357 -24.49000 0.00161 158.36958% s1
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8 -12.55595 -12.57300 0.00473 656.84819% %(izKJl q
Final MF Value:0.00413 Relative change:562.97392% ?T_bjA LW
Method: Worst to Best(4) Y (h (Z
Srf Old Radius New Radius MF Value MF Change c[;=7-+
8 -12.55755 -12.57300 0.00429 588.97585% YAYwrKt
7 -24.41497 -24.49000 0.00313 395.98642% y{J7^o(_~
5 -28.74963 -28.76000 0.00064 1.64985% &-p!Lg&D
2 -54.11607 -53.94000 0.00534 748.41314% QHw{@*
6 5.58904 5.60000 0.00138 121.28941% $fQ'q3
4 125.16569 122.46000 0.00755 1106.10971% M
nDa ag
10 58.29969 57.93000 0.00309 384.03213% YL9Tsw
3 18.56110 18.53500 0.00520 589.38016% A4f;ftB
9 18.34017 18.36500 0.00328 419.68931% o 5< w2(
1 118.01930 117.83000 0.00130 106.87009% CzG/=#IU
Final MF Value:0.00063 Relative change:0.71571% ?/^{sW'
|
Method: Power_BigToSmall(5) {|R +|ow
Srf Old Radius New Radius MF Value MF Change V*1-wg5>
6 5.57706 5.57000 0.00101 62.51945% tS6r4d%~=
8 -12.55338 -12.57300 0.00542 771.03542% c{wob%!>
9 18.37981 18.36500 0.00202 221.96974% eNFZD1 mS
3 18.58131 18.53500 0.00915 1359.96125% s|-g)
7 -24.70139 -24.66000 0.00178 184.01078% b%|6y
2 -53.96973 -53.94000 0.00109 74.29882% %p
tw=Ju
10 57.90009 57.93000 0.00067 7.45080% ;Wig ${
5 -28.54594 -28.58000 0.00073 17.14607% BaOPtBYA:
1 121.61780 121.89600 0.00169 169.13653% hXQo>t-$
4 125.83316 122.46000 0.00935 1392.62223% [<IJ {yfx
Final MF Value:0.00066 Relative change:5.41330% K"g`,G6S
Method: Abr_BigToSmall(6) G[\3)@I
Srf Old Radius New Radius MF Value MF Change >(e R0. x
1 121.74488 121.89600 0.00105 69.09700% e\ O&Xe
2 -54.12133 -53.94000 0.00546 763.02456% G33'Cgo:,
3 18.56394 18.53500 0.00574 820.72132% 8t1,_,2'
4 124.51666 122.46000 0.00579 828.65062% =xRxr @
5 -28.81629 -28.76000 0.00088 41.21174% E9:p A5H-j
6 5.58064 5.57000 0.00136 115.96495% b h UghHT
9 18.36617 18.36500 0.00064 2.94035% i 2n66d
10 58.33624 57.93000 0.00338 440.27551% Zksow} %
7 -24.39810 -24.32000 0.00637 98.68410% n /Dk~Q)
8 -12.54258 -12.57300 0.00842 1236.91311% |5 me }!C
Final MF Value:0.00069 Relative change:11.14449% Y$N D
Method: MF_BigToSmall(7) Kh PDkD-
Srf Old Radius New Radius MF Value MF Change Y\{&chuF
4 125.20984 122.46000 0.00768 1133.54154% @r xfOc0J#
8 -12.55752 -12.57300 0.00430 589.34823% S")*~)N@
3 18.55995 18.53500 0.00495 689.30381% s ]i<D9h
10 58.46434 58.88000 0.00339 438.53372% DWcEl:
7 -24.41102 -24.49000 0.00329 422.92209% Df= zrs["
1 121.30507 120.78000 0.00305 385.48025% b"&1l2\ A
2 -54.01247 -53.94000 0.00226 260.45623% uU#e54^
5 -28.95689 -29.11000 0.00178 184.06356% ~+O ws
6 5.59661 5.60000 0.00073 16.98172% C Ua`#
9 18.36951 18.36500 0.00086 36.64230% ?Fj >7
Final MF Value:0.00063 Relative change:0.47395% @-L n* 3n
Best Method:Fit_MF_BigToSmall 7A4 6?kfu
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结果一般是Fit_MF_BigToSmall和Fit_WorstToBest方法较好，Fit_MF_BigToSmall算是很BT的方法，其次是ShortToLong和Power_BitToSmall，我比较看重看依据像差来套的方法，但其结果最好时的情况不多，因为这个方法主观因素比较严重，很难用程序去精确实现，这是手动套样板的方法首选。
