Changeset 28 for doc/latex

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Timestamp:
02/22/08 16:40:12 (16 years ago)
Author:
smidl
Message:

prelozitelna verze

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doc/latex
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10 modified

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  • doc/latex/classBM.tex

    r22 r28  
    1919 
    2020\begin{CompactList}\small\item\em Default constructor. \item\end{CompactList}\item  
    21 virtual void {\bf bayes} (const vec \&dt, bool evall=true)=0 
     21virtual void {\bf bayes} (const vec \&dt)=0 
    2222\begin{CompactList}\small\item\em Incremental Bayes rule. \item\end{CompactList}\item  
    2323void {\bf bayes} (mat Dt)\label{classBM_87b07867fd4c133aa89a18543f68d9f9} 
    2424 
    25 \begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\end{CompactItemize} 
     25\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item  
     26{\bf epdf} $\ast$ {\bf \_\-epdf} ()\label{classBM_a5b8f6c8a872738cfaa30ab010e8c077} 
     27 
     28\begin{CompactList}\small\item\em Returns a pointer to the \doxyref{epdf}{p.}{classepdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\end{CompactItemize} 
    2629\subsection*{Public Attributes} 
    2730\begin{CompactItemize} 
    … …  
    2932double {\bf ll}\label{classBM_5623fef6572a08c2b53b8c87b82dc979} 
    3033 
    31 \begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\end{CompactItemize} 
     34\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item  
     35bool {\bf evalll}\label{classBM_bf6fb59b30141074f8ee1e2f43d03129} 
     36 
     37\begin{CompactList}\small\item\em If true, the filter will compute likelihood of the data record and store it in {\tt ll} . Set to false if you want to save time. \item\end{CompactList}\end{CompactItemize} 
    3238 
    3339 
    … …  
    3844\index{BM@{BM}!bayes@{bayes}} 
    3945\index{bayes@{bayes}!BM@{BM}} 
    40 \subsubsection{\setlength{\rightskip}{0pt plus 5cm}virtual void BM::bayes (const vec \& {\em dt}, bool {\em evall} = {\tt true})\hspace{0.3cm}{\tt  [pure virtual]}}\label{classBM_c52edf4ad6e1dff9bf64b9e1e0cfb1f0} 
     46\subsubsection{\setlength{\rightskip}{0pt plus 5cm}virtual void BM::bayes (const vec \& {\em dt})\hspace{0.3cm}{\tt  [pure virtual]}}\label{classBM_a892eff438aab2dd1a9e2efcb7fb5bdf} 
    4147 
    4248 
    … …  
    4652\item[Parameters:] 
    4753\begin{description} 
    48 \item[{\em dt}]vector of input data \item[{\em evall}]If true, the filter will compute likelihood of the data record and store it in {\tt ll} \end{description} 
     54\item[{\em dt}]vector of input data \end{description} 
    4955\end{Desc} 
    5056 
    51  
    52 Implemented in {\bf KalmanFull} \doxyref{}{p.}{classKalmanFull_048b13739b94c331cda08249b278552b}, {\bf Kalman$<$ sq\_\-T $>$} \doxyref{}{p.}{classKalman_e945d9205ca14acbd83ba80ea6f72b8e}, {\bf EKF$<$ sq\_\-T $>$} \doxyref{}{p.}{classEKF_fb0a08463f14e5584344ea2df99fe747}, {\bf PF} \doxyref{}{p.}{classPF_eb06bd7d4325f22f54233967295793b9}, {\bf TrivialPF} \doxyref{}{p.}{classTrivialPF_77a92bf054d763f806d27fc37a058389}, and {\bf Kalman$<$ fsqmat $>$} \doxyref{}{p.}{classKalman_e945d9205ca14acbd83ba80ea6f72b8e}. 
    5357 
    5458The documentation for this class was generated from the following file:\begin{CompactItemize} 

  • doc/latex/classKalman.tex

    r22 r28  
    2929 
    3030\begin{CompactList}\small\item\em Full constructor. \item\end{CompactList}\item  
    31 void {\bf bayes} (const vec \&dt, bool evalll=true)\label{classKalman_e945d9205ca14acbd83ba80ea6f72b8e} 
     31void {\bf bayes} (const vec \&dt, bool {\bf evalll}=true)\label{classKalman_e945d9205ca14acbd83ba80ea6f72b8e} 
    3232 
    33 \begin{CompactList}\small\item\em Here dt = [yt;ut] of appropriate dimensions. \item\end{CompactList}\end{CompactItemize} 
     33\begin{CompactList}\small\item\em Here dt = [yt;ut] of appropriate dimensions. \item\end{CompactList}\item  
     34virtual void {\bf bayes} (const vec \&dt)=0 
     35\begin{CompactList}\small\item\em Incremental Bayes rule. \item\end{CompactList}\item  
     36void {\bf bayes} (mat Dt)\label{classBM_87b07867fd4c133aa89a18543f68d9f9} 
     37 
     38\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item  
     39{\bf epdf} $\ast$ {\bf \_\-epdf} ()\label{classBM_a5b8f6c8a872738cfaa30ab010e8c077} 
     40 
     41\begin{CompactList}\small\item\em Returns a pointer to the \doxyref{epdf}{p.}{classepdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\end{CompactItemize} 
    3442\subsection*{Public Attributes} 
    3543\begin{CompactItemize} 
    … …  
    4048sq\_\-T {\bf P}\label{classKalman_188cd5ac1c9e496b1a371eb7c57c97d3} 
    4149 
    42 \begin{CompactList}\small\item\em Mean value of the posterior density. \item\end{CompactList}\end{CompactItemize} 
     50\begin{CompactList}\small\item\em Mean value of the posterior density. \item\end{CompactList}\item  
     51double {\bf ll}\label{classBM_5623fef6572a08c2b53b8c87b82dc979} 
     52 
     53\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item  
     54bool {\bf evalll}\label{classBM_bf6fb59b30141074f8ee1e2f43d03129} 
     55 
     56\begin{CompactList}\small\item\em If true, the filter will compute likelihood of the data record and store it in {\tt ll} . Set to false if you want to save time. \item\end{CompactList}\end{CompactItemize} 
    4357\subsection*{Protected Attributes} 
    4458\begin{CompactItemize} 
    … …  
    96110\doxyref{Kalman}{p.}{classKalman} filter with covariance matrices in square root form.  
    97111 
     112\subsection{Member Function Documentation} 
     113\index{Kalman@{Kalman}!bayes@{bayes}} 
     114\index{bayes@{bayes}!Kalman@{Kalman}} 
     115\subsubsection{\setlength{\rightskip}{0pt plus 5cm}virtual void BM::bayes (const vec \& {\em dt})\hspace{0.3cm}{\tt  [pure virtual, inherited]}}\label{classBM_a892eff438aab2dd1a9e2efcb7fb5bdf} 
     116 
     117 
     118Incremental Bayes rule.  
     119 
     120\begin{Desc} 
     121\item[Parameters:] 
     122\begin{description} 
     123\item[{\em dt}]vector of input data \end{description} 
     124\end{Desc} 
     125 
     126 
    98127The documentation for this class was generated from the following file:\begin{CompactItemize} 
    99128\item  

  • doc/latex/classKalmanFull.tex

    r19 r28  
    2626 
    2727\begin{CompactList}\small\item\em Full constructor. \item\end{CompactList}\item  
    28 void {\bf bayes} (const vec \&dt, bool evalll=true)\label{classKalmanFull_048b13739b94c331cda08249b278552b} 
     28void {\bf bayes} (const vec \&dt, bool {\bf evalll}=true)\label{classKalmanFull_048b13739b94c331cda08249b278552b} 
    2929 
    30 \begin{CompactList}\small\item\em Here dt = [yt;ut] of appropriate dimensions. \item\end{CompactList}\end{CompactItemize} 
     30\begin{CompactList}\small\item\em Here dt = [yt;ut] of appropriate dimensions. \item\end{CompactList}\item  
     31virtual void {\bf bayes} (const vec \&dt)=0 
     32\begin{CompactList}\small\item\em Incremental Bayes rule. \item\end{CompactList}\item  
     33void {\bf bayes} (mat Dt)\label{classBM_87b07867fd4c133aa89a18543f68d9f9} 
     34 
     35\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item  
     36{\bf epdf} $\ast$ {\bf \_\-epdf} ()\label{classBM_a5b8f6c8a872738cfaa30ab010e8c077} 
     37 
     38\begin{CompactList}\small\item\em Returns a pointer to the \doxyref{epdf}{p.}{classepdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\end{CompactItemize} 
    3139\subsection*{Public Attributes} 
    3240\begin{CompactItemize} 
    … …  
    3745mat {\bf P}\label{classKalmanFull_b75dc059e84fa8ffc076203b30f926cc} 
    3846 
    39 \begin{CompactList}\small\item\em Variance of the posterior density. \item\end{CompactList}\end{CompactItemize} 
     47\begin{CompactList}\small\item\em Variance of the posterior density. \item\end{CompactList}\item  
     48double {\bf ll}\label{classBM_5623fef6572a08c2b53b8c87b82dc979} 
     49 
     50\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item  
     51bool {\bf evalll}\label{classBM_bf6fb59b30141074f8ee1e2f43d03129} 
     52 
     53\begin{CompactList}\small\item\em If true, the filter will compute likelihood of the data record and store it in {\tt ll} . Set to false if you want to save time. \item\end{CompactList}\end{CompactItemize} 
    4054\subsection*{Friends} 
    4155\begin{CompactItemize} 
    … …  
    4963Basic \doxyref{Kalman}{p.}{classKalman} filter with full matrices (education purpose only)! Will be deleted soon!  
    5064 
     65\subsection{Member Function Documentation} 
     66\index{KalmanFull@{KalmanFull}!bayes@{bayes}} 
     67\index{bayes@{bayes}!KalmanFull@{KalmanFull}} 
     68\subsubsection{\setlength{\rightskip}{0pt plus 5cm}virtual void BM::bayes (const vec \& {\em dt})\hspace{0.3cm}{\tt  [pure virtual, inherited]}}\label{classBM_a892eff438aab2dd1a9e2efcb7fb5bdf} 
     69 
     70 
     71Incremental Bayes rule.  
     72 
     73\begin{Desc} 
     74\item[Parameters:] 
     75\begin{description} 
     76\item[{\em dt}]vector of input data \end{description} 
     77\end{Desc} 
     78 
     79 
    5180The documentation for this class was generated from the following files:\begin{CompactItemize} 
    5281\item  

  • doc/latex/classPF.tex

    r19 r28  
    2929 
    3030\item  
    31 void {\bf bayes} (const vec \&dt, bool evell) 
    32 \begin{CompactList}\small\item\em Incremental Bayes rule. \item\end{CompactList}\end{CompactItemize} 
     31void \textbf{bayes} (const vec \&dt, bool evell)\label{classPF_eb06bd7d4325f22f54233967295793b9} 
     32 
     33\item  
     34virtual void {\bf bayes} (const vec \&dt)=0 
     35\begin{CompactList}\small\item\em Incremental Bayes rule. \item\end{CompactList}\item  
     36void {\bf bayes} (mat Dt)\label{classBM_87b07867fd4c133aa89a18543f68d9f9} 
     37 
     38\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item  
     39{\bf epdf} $\ast$ {\bf \_\-epdf} ()\label{classBM_a5b8f6c8a872738cfaa30ab010e8c077} 
     40 
     41\begin{CompactList}\small\item\em Returns a pointer to the \doxyref{epdf}{p.}{classepdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\end{CompactItemize} 
     42\subsection*{Public Attributes} 
     43\begin{CompactItemize} 
     44\item  
     45double {\bf ll}\label{classBM_5623fef6572a08c2b53b8c87b82dc979} 
     46 
     47\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item  
     48bool {\bf evalll}\label{classBM_bf6fb59b30141074f8ee1e2f43d03129} 
     49 
     50\begin{CompactList}\small\item\em If true, the filter will compute likelihood of the data record and store it in {\tt ll} . Set to false if you want to save time. \item\end{CompactList}\end{CompactItemize} 
    3351\subsection*{Protected Attributes} 
    3452\begin{CompactItemize} 
    … …  
    5371\index{PF@{PF}!bayes@{bayes}} 
    5472\index{bayes@{bayes}!PF@{PF}} 
    55 \subsubsection{\setlength{\rightskip}{0pt plus 5cm}void PF::bayes (const vec \& {\em dt}, bool {\em evall})\hspace{0.3cm}{\tt  [inline, virtual]}}\label{classPF_eb06bd7d4325f22f54233967295793b9} 
     73\subsubsection{\setlength{\rightskip}{0pt plus 5cm}virtual void BM::bayes (const vec \& {\em dt})\hspace{0.3cm}{\tt  [pure virtual, inherited]}}\label{classBM_a892eff438aab2dd1a9e2efcb7fb5bdf} 
    5674 
    5775 
    … …  
    6179\item[Parameters:] 
    6280\begin{description} 
    63 \item[{\em dt}]vector of input data \item[{\em evall}]If true, the filter will compute likelihood of the data record and store it in {\tt ll} \end{description} 
     81\item[{\em dt}]vector of input data \end{description} 
    6482\end{Desc} 
    6583 
    66  
    67 Implements {\bf BM} \doxyref{}{p.}{classBM_c52edf4ad6e1dff9bf64b9e1e0cfb1f0}. 
    68  
    69 Reimplemented in {\bf TrivialPF} \doxyref{}{p.}{classTrivialPF_77a92bf054d763f806d27fc37a058389}. 
    7084 
    7185The documentation for this class was generated from the following files:\begin{CompactItemize} 

  • doc/latex/classTrivialPF.tex

    r19 r28  
    1717\begin{center} 
    1818\leavevmode 
    19 \includegraphics[width=67pt]{classTrivialPF__coll__graph} 
     19\includegraphics[width=85pt]{classTrivialPF__coll__graph} 
    2020\end{center} 
    2121\end{figure} 
    … …  
    2323\begin{CompactItemize} 
    2424\item  
    25 \textbf{TrivialPF} ({\bf mpdf} \&par, {\bf mpdf} \&obs, {\bf mpdf} \&prop, int n0)\label{classTrivialPF_e6d9e3506da221a10a517bd5712b5a84} 
     25\textbf{TrivialPF} ({\bf mpdf} \&par, {\bf mpdf} \&obs, {\bf BM} \&prop, int n0)\label{classTrivialPF_c5a420747532e24b25cb0d835288795b} 
    2626 
    2727\item  
    … …  
    2929 
    3030\item  
    31 void {\bf bayes} (const vec \&dt, bool evalll) 
    32 \begin{CompactList}\small\item\em Incremental Bayes rule. \item\end{CompactList}\end{CompactItemize} 
     31void \textbf{bayes} (const vec \&dt, bool {\bf evalll})\label{classTrivialPF_77a92bf054d763f806d27fc37a058389} 
     32 
     33\item  
     34ivec {\bf resample} (RESAMPLING\_\-METHOD method=SYSTEMATIC)\label{classPF_a0e26b2f6a5884aca49122f3e4f0cf19} 
     35 
     36\begin{CompactList}\small\item\em Returns indexes of particles that should be resampled. The ordering MUST guarantee inplace replacement. (Important for MPF.). \item\end{CompactList}\item  
     37virtual void {\bf bayes} (const vec \&dt)=0 
     38\begin{CompactList}\small\item\em Incremental Bayes rule. \item\end{CompactList}\item  
     39void {\bf bayes} (mat Dt)\label{classBM_87b07867fd4c133aa89a18543f68d9f9} 
     40 
     41\begin{CompactList}\small\item\em Batch Bayes rule (columns of Dt are observations). \item\end{CompactList}\item  
     42{\bf epdf} $\ast$ {\bf \_\-epdf} ()\label{classBM_a5b8f6c8a872738cfaa30ab010e8c077} 
     43 
     44\begin{CompactList}\small\item\em Returns a pointer to the \doxyref{epdf}{p.}{classepdf} representing posterior density on parameters. Use with care! \item\end{CompactList}\end{CompactItemize} 
     45\subsection*{Public Attributes} 
     46\begin{CompactItemize} 
     47\item  
     48double {\bf ll}\label{classBM_5623fef6572a08c2b53b8c87b82dc979} 
     49 
     50\begin{CompactList}\small\item\em Logarithm of marginalized data likelihood. \item\end{CompactList}\item  
     51bool {\bf evalll}\label{classBM_bf6fb59b30141074f8ee1e2f43d03129} 
     52 
     53\begin{CompactList}\small\item\em If true, the filter will compute likelihood of the data record and store it in {\tt ll} . Set to false if you want to save time. \item\end{CompactList}\end{CompactItemize} 
     54\subsection*{Protected Attributes} 
     55\begin{CompactItemize} 
     56\item  
     57int \textbf{n}\label{classPF_2c2f44ed7a4eaa42e07bdb58d503f280} 
     58 
     59\item  
     60vec \textbf{w}\label{classPF_f6bc92f7979af4513b06b161497ba868} 
     61 
     62\item  
     63Uniform\_\-RNG \textbf{URNG}\label{classPF_3568ca7c3b3175d98b548f496b4c34dd} 
     64 
     65\end{CompactItemize} 
    3366 
    3467 
    … …  
    3972\index{TrivialPF@{TrivialPF}!bayes@{bayes}} 
    4073\index{bayes@{bayes}!TrivialPF@{TrivialPF}} 
    41 \subsubsection{\setlength{\rightskip}{0pt plus 5cm}void TrivialPF::bayes (const vec \& {\em dt}, bool {\em evall})\hspace{0.3cm}{\tt  [virtual]}}\label{classTrivialPF_77a92bf054d763f806d27fc37a058389} 
     74\subsubsection{\setlength{\rightskip}{0pt plus 5cm}virtual void BM::bayes (const vec \& {\em dt})\hspace{0.3cm}{\tt  [pure virtual, inherited]}}\label{classBM_a892eff438aab2dd1a9e2efcb7fb5bdf} 
    4275 
    4376 
    … …  
    4780\item[Parameters:] 
    4881\begin{description} 
    49 \item[{\em dt}]vector of input data \item[{\em evall}]If true, the filter will compute likelihood of the data record and store it in {\tt ll} \end{description} 
     82\item[{\em dt}]vector of input data \end{description} 
    5083\end{Desc} 
    5184 
    52  
    53 Reimplemented from {\bf PF} \doxyref{}{p.}{classPF_eb06bd7d4325f22f54233967295793b9}. 
    5485 
    5586The documentation for this class was generated from the following files:\begin{CompactItemize} 

  • doc/latex/classeEF.tex

    r19 r28  
    2828virtual void \textbf{dupdate} (mat \&v, double nu=1.0)\label{classeEF_5863718c3b2fb1496dece10c5b745d5c} 
    2929 
    30 \end{CompactItemize} 
     30\item  
     31virtual vec {\bf sample} ()=0 
     32\begin{CompactList}\small\item\em Returns the required moment of the \doxyref{epdf}{p.}{classepdf}. \item\end{CompactList}\item  
     33virtual double {\bf eval} (const vec \&val)\label{classepdf_f333ceeb88ebc37d81fcd4cea4526bfc} 
     34 
     35\begin{CompactList}\small\item\em Compute probability of argument {\tt val}. \item\end{CompactList}\end{CompactItemize} 
    3136 
    3237 
    … …  
    3641More?...  
    3742 
     43\subsection{Member Function Documentation} 
     44\index{eEF@{eEF}!sample@{sample}} 
     45\index{sample@{sample}!eEF@{eEF}} 
     46\subsubsection{\setlength{\rightskip}{0pt plus 5cm}virtual vec epdf::sample ()\hspace{0.3cm}{\tt  [pure virtual, inherited]}}\label{classepdf_7f74d871d50b9ff360f1b3879092a9fa} 
     47 
     48 
     49Returns the required moment of the \doxyref{epdf}{p.}{classepdf}.  
     50 
     51Returns a sample from the density, $x \sim epdf(rv)$  
     52 
     53Implemented in {\bf enorm$<$ sq\_\-T $>$} \doxyref{}{p.}{classenorm_6020bcd89db2c9584bd8871001bd2023}. 
     54 
    3855The documentation for this class was generated from the following file:\begin{CompactItemize} 
    3956\item  

  • doc/latex/classfnc.tex

    r22 r28  
    2222 
    2323\begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize} 
     24\subsection*{Protected Attributes} 
     25\begin{CompactItemize} 
     26\item  
     27int \textbf{dimy}\label{classfnc_22d51d10a7901331167f64f80d1af8e9} 
     28 
     29\end{CompactItemize} 
    2430 
    2531 

  • doc/latex/classfsqmat.tex

    r22 r28  
    3333 
    3434\item  
    35 void \textbf{inv} ({\bf fsqmat} \&Inv)\label{classfsqmat_9fa853e1ca28f2a1a1c43377e798ecb1} 
    36  
    37 \item  
    3835void {\bf clear} ()\label{classfsqmat_cfa4c359483d2322f32d1d50050f8ac4} 
    3936 
    … …  
    4239 
    4340\begin{CompactList}\small\item\em Constructor. \item\end{CompactList}\item  
    44 virtual void {\bf inv} ({\bf fsqmat} $\ast$Inv) 
     41virtual void {\bf inv} ({\bf fsqmat} \&Inv) 
    4542\begin{CompactList}\small\item\em Matrix inversion preserving the chosen form. \item\end{CompactList}\item  
    4643double {\bf logdet} ()\label{classfsqmat_bf212272ec195ad2706e2bf4d8e7c9b3} 
    … …  
    6057{\bf fsqmat} \& \textbf{operator $\ast$=} (double x)\label{classfsqmat_8f7ce97628a50e06641281096b2af9b7} 
    6158 
    62 \end{CompactItemize} 
     59\item  
     60int {\bf cols} () const \label{classsqmat_ecc2e2540f95a04f4449842588170f5b} 
     61 
     62\begin{CompactList}\small\item\em Reimplementing common functions of mat: \doxyref{cols()}{p.}{classsqmat_ecc2e2540f95a04f4449842588170f5b}. \item\end{CompactList}\item  
     63int {\bf rows} () const \label{classsqmat_071e80ced9cc3b8cbb360fa7462eb646} 
     64 
     65\begin{CompactList}\small\item\em Reimplementing common functions of mat: \doxyref{cols()}{p.}{classsqmat_ecc2e2540f95a04f4449842588170f5b}. \item\end{CompactList}\end{CompactItemize} 
    6366\subsection*{Protected Attributes} 
    6467\begin{CompactItemize} 
    6568\item  
    6669mat \textbf{M}\label{classfsqmat_a7a1fcb9aae19d1e4daddfc9c22ce453} 
     70 
     71\item  
     72int \textbf{dim}\label{classsqmat_0abed904bdc0882373ba9adba919689d} 
    6773 
    6874\end{CompactItemize} 
    … …  
    103109Implements {\bf sqmat} \doxyref{}{p.}{classsqmat_faa3bc90be142adde9cf74f573c70157}.\index{fsqmat@{fsqmat}!inv@{inv}} 
    104110\index{inv@{inv}!fsqmat@{fsqmat}} 
    105 \subsubsection{\setlength{\rightskip}{0pt plus 5cm}virtual void fsqmat::inv ({\bf fsqmat} $\ast$ {\em Inv})\hspace{0.3cm}{\tt  [virtual]}}\label{classfsqmat_788423cc2679620dd6da8d2fca2e3e4d} 
     111\subsubsection{\setlength{\rightskip}{0pt plus 5cm}void fsqmat::inv ({\bf fsqmat} \& {\em Inv})\hspace{0.3cm}{\tt  [virtual]}}\label{classfsqmat_9fa853e1ca28f2a1a1c43377e798ecb1} 
    106112 
    107113 
    … …  
    124130Implements {\bf sqmat} \doxyref{}{p.}{classsqmat_b5236c8a050199e1a9d338b0da1a08d2}. 
    125131 
    126 The documentation for this class was generated from the following file:\begin{CompactItemize} 
     132The documentation for this class was generated from the following files:\begin{CompactItemize} 
    127133\item  
    128 work/mixpp/bdm/math/{\bf libDC.h}\end{CompactItemize} 
     134work/mixpp/bdm/math/{\bf libDC.h}\item  
     135work/mixpp/bdm/math/libDC.cpp\item  
     136work/mixpp/bdm/math/libDC\_\-.cpp\end{CompactItemize} 

  • doc/latex/doxygen.sty

    r22 r28  
    1111\rhead[\fancyplain{}{\bfseries\leftmark}] 
    1212        {\fancyplain{}{\bfseries\thepage}} 
    13 \rfoot[\fancyplain{}{\bfseries\scriptsize Generated on Sun Feb 17 16:14:14 2008 for mixpp by Doxygen }]{} 
    14 \lfoot[]{\fancyplain{}{\bfseries\scriptsize Generated on Sun Feb 17 16:14:14 2008 for mixpp by Doxygen }} 
     13\rfoot[\fancyplain{}{\bfseries\scriptsize Generated on Mon Feb 18 21:48:39 2008 for mixpp by Doxygen }]{} 
     14\lfoot[]{\fancyplain{}{\bfseries\scriptsize Generated on Mon Feb 18 21:48:39 2008 for mixpp by Doxygen }} 
    1515\cfoot{} 
    1616\newenvironment{Code} 

  • doc/latex/refman.tex

    r22 r28  
    2121{\large Generated by Doxygen 1.5.3}\\ 
    2222\vspace*{0.5cm} 
    23 {\small Sun Feb 17 16:14:14 2008}\\ 
     23{\small Mon Feb 18 21:48:39 2008}\\ 
    2424\end{center} 
    2525\end{titlepage} 
    … …  
    3535\chapter{mixpp File Index} 
    3636\input{files} 
     37\chapter{mixpp Page Index} 
     38\input{pages} 
    3739\chapter{mixpp Class Documentation} 
    3840\input{classbilinfn} 
    … …  
    6365\include{libDS_8h} 
    6466\include{libEF_8h} 
     67\chapter{mixpp Page Documentation} 
     68\input{codingrules} 
    6569\printindex 
    6670\end{document}