[原创]展示最近的一个重量级CCL：各种算法套样板 [复制链接]

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。 q\<NW%KtX  
    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 ,c 0]r;u!  
程序框架如下： z2Z}mktP  
FitGlass(...) YN~1.!F  
{ ,1]VY/  
      while(1) )|#ExyRO  
      { O-box?  
         read_plate_file(...); ,@I\'os  
         GetOneLine(...); MZqHL4<|  
         parse_string_line(...) J% ZM V  
        //将数据存入样板数组 >U?#'e{qW  
         .... {bG.X?b  
       } [z6P]eC7  
      Fit_ShortToLong(...); K92M9=>  
      Fit_LongToShort(...); ~f( #S*Ic  
      Fit_BestToWorst(...); ~M1T @Mv  
      Fit_WorstToBest(...); %d<UMbS^  
      Fit_Power_BigToSmall(...); Z_7TD)  
      Fit_Abr_BigToSmall(...); B*P;*re  
      Fit_MF_BigToSmall(...); %IDl+_j  
      //下面开始选择处理结果 +UX} "m~W  
      ... ~}SQLYy7Z  
} = )4bf"~8  
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 wUfPnAD.'  
r"p"UW9og  
TestPlate File's name:yangzhou.tpd ]\]mwvLT  
Init MF Value:0.00062 %eGD1.R  
Method: Short to Long(1) Xn5LrLM&  
Srf     Old Radius     New Radius     MF Value     MF Change Hl*#iUq  
  6        5.57706        5.57000      0.00101      62.51945% ,dFY]  
  8      -12.55338      -12.57300      0.00542     771.03542% aC<fzUD;  
  9       18.37981       18.36500      0.00202     221.96974% 8ZJ6~~h  
  3       18.58131       18.53500      0.00915    1359.96125% `6LVXDR  
  7      -24.70139      -24.66000      0.00178     184.01078% ldc`Y/:{  
  5      -28.55608      -28.58000      0.00068       8.79409% !!mGsgnW  
  2      -53.96599      -53.94000      0.00100      59.93393% z6h/C{  
10       57.91138       57.93000      0.00064       2.94712% gKgdu($NJ  
  1      121.60450      121.89600      0.00175     180.28879% ey\(*Tu9  
  4      125.85170      122.46000      0.00940    1400.41107% QUF1_Sa  
Final MF Value:0.00064    Relative change:3.07884% ''k}3o.K[  
Method: Long to Short(2) U
o[`AzD3  
Srf     Old Radius     New Radius     MF Value     MF Change VTi;y{  
  4      125.20984      122.46000      0.00768    1133.54154% t+jdV  
  1      121.51149      121.89600      0.00225     260.91411% ]eX(K5 A  
10       58.31318       57.93000      0.00320     412.26872% PWfd<Yf!  
  2      -54.00322      -53.94000      0.00200     221.25579% <l>L8{-3  
  5      -28.87047      -28.76000      0.00137     119.38819% ?ZkVk=t?  
  7      -24.41613      -24.49000      0.00308     393.92127% w;
J#+ik  
  3       18.54773       18.53500      0.00258     313.92207% 'C;KNc  
  9       18.36134       18.36500      0.00078      25.56252% -qLNs_ _k  
  8      -12.55473      -12.57300      0.00506     710.82362% k9c`[M  
  6        5.56698        5.57000      0.00211      -4.68411% 6'e 'UD  
Final MF Value:0.00065    Relative change:3.58804% B*^QTJ  
Method: Best to Worst(3) v[a4d&P  
Srf     Old Radius     New Radius     MF Value     MF Change ): r'IR  
  1      121.74488      121.89600      0.00105      69.09700% +!G)N~o  
  9       18.36994       18.36500      0.00089      41.17665% h(^[WSa  
  2      -54.11743      -53.94000      0.00537     761.51122% s8k4e6ak  
  3       18.56222       18.53500      0.00540     764.71352% k_Lv\'Ok  
10       58.36529       57.93000      0.00361     479.27779% eO{2rV45O  
  6        5.56872        5.57000      0.00064       2.65958% .tK]-f2  
  4      124.36063      122.46000      0.00536     757.60693% :z$+leNH\  
  5      -28.80466      -28.76000      0.00080      27.59264% eEeK ]8@  
  7      -24.45357      -24.49000      0.00161     158.36958% SV^[)p)  
  8      -12.55595      -12.57300      0.00473     656.84819% q@Zeu\T,*#  
Final MF Value:0.00413    Relative change:562.97392% t~Ic{%bdA  
Method: Worst to Best(4) 18y'#<X!  
Srf     Old Radius     New Radius     MF Value     MF Change ^a#W|-:  
  8      -12.55755      -12.57300      0.00429     588.97585% "<"s&ws;k  
  7      -24.41497      -24.49000      0.00313     395.98642% QR$m i1Vv\  
  5      -28.74963      -28.76000      0.00064       1.64985% } OkK@8?0O  
  2      -54.11607      -53.94000      0.00534     748.41314% 7qdB  
  6        5.58904        5.60000      0.00138     121.28941% Ihl]"76q/  
  4      125.16569      122.46000      0.00755    1106.10971% 3p'(E\V
J  
10       58.29969       57.93000      0.00309     384.03213% B""=&(Yu  
  3       18.56110       18.53500      0.00520     589.38016% W@~a#~1O  
  9       18.34017       18.36500      0.00328     419.68931% <S0gIg`)  
  1      118.01930      117.83000      0.00130     106.87009% mH'om SCz  
Final MF Value:0.00063    Relative change:0.71571% '9AYE"7Ydk  
Method: Power_BigToSmall(5) d2g7,axi  
Srf     Old Radius     New Radius     MF Value     MF Change }IKU^0M9<T  
  6        5.57706        5.57000      0.00101      62.51945% <_4'So>  
  8      -12.55338      -12.57300      0.00542     771.03542% $- GwNG  
  9       18.37981       18.36500      0.00202     221.96974% 6O'Y@9#  
  3       18.58131       18.53500      0.00915    1359.96125% 4>]B8ZxH  
  7      -24.70139      -24.66000      0.00178     184.01078% :}o{<U  
  2      -53.96973      -53.94000      0.00109      74.29882% sT91>'&  
10       57.90009       57.93000      0.00067       7.45080%
<In+V  
  5      -28.54594      -28.58000      0.00073      17.14607% 0EC/l OS  
  1      121.61780      121.89600      0.00169     169.13653% yeV|j\TJI.  
  4      125.83316      122.46000      0.00935    1392.62223% /qd~|[Kx:  
Final MF Value:0.00066    Relative change:5.41330% T lB+ tV>  
Method: Abr_BigToSmall(6) KoFWI_(b  
Srf     Old Radius     New Radius     MF Value     MF Change "}<baz  
  1      121.74488      121.89600      0.00105      69.09700% s6I/%R3  
  2      -54.12133      -53.94000      0.00546     763.02456% M7neOQHq  
  3       18.56394       18.53500      0.00574     820.72132% u/5)Yx+5_  
  4      124.51666      122.46000      0.00579     828.65062% PxJvE*6^H  
  5      -28.81629      -28.76000      0.00088      41.21174% XZ|\|(6Cc  
  6        5.58064        5.57000      0.00136     115.96495% 1*B'o<?P1  
  9       18.36617       18.36500      0.00064       2.94035% ,go$6  
10       58.33624       57.93000      0.00338     440.27551% Wk]E6yz6  
  7      -24.39810      -24.32000      0.00637      98.68410% fc%C!^7  
  8      -12.54258      -12.57300      0.00842    1236.91311% Bo/i =/7%  
Final MF Value:0.00069    Relative change:11.14449% wd Di5-A4  
Method: MF_BigToSmall(7) Ia>~ph#]{`  
Srf     Old Radius     New Radius     MF Value     MF Change T?D]]x  
  4      125.20984      122.46000      0.00768    1133.54154% F>5)Clq  
  8      -12.55752      -12.57300      0.00430     589.34823% kyUG+M  
  3       18.55995       18.53500      0.00495     689.30381% S2$r 6T  
10       58.46434       58.88000      0.00339     438.53372% A)kdY!}  
  7      -24.41102      -24.49000      0.00329     422.92209% Kp/l2?J"  
  1      121.30507      120.78000      0.00305     385.48025% =#vU$~a  
  2      -54.01247      -53.94000      0.00226     260.45623% smuQ1.b  
  5      -28.95689      -29.11000      0.00178     184.06356% sQT<I]e  
  6        5.59661        5.60000      0.00073      16.98172% g"D:zK)  
  9       18.36951       18.36500      0.00086      36.64230% vH]2
t.\  
Final MF Value:0.00063    Relative change:0.47395% (}CA?/  
Best Method:Fit_MF_BigToSmall ZZW%6-B  
YU1z\pK  
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。

版主威武

都是手工套的

版主威武

高手贴

好厉害

看看了

很有技术的样子

好厉害的感觉

多谢楼主分享