LaTeX 算法代码排版 --latex2e范例总结

LaTeX 写作：算法代码排版 --latex2e范例总结

latex2e 宏包的使用范例：

usepackage[ruled]{algorithm2e} %算法排版样式1
usepackage[ruled,vlined]{algorithm2e} %算法排版样式2
usepackage[linesnumbered,boxed]{algorithm2e} %算法排版样式3

使用上述代码中三种不同的宏包编译后的代码排版样式预览：

样式一：

样式二：

样式三：

latex代码排版.tex文件：

documentclass{article}

 usepackage[ruled]{algorithm2e}                 %算法排版样式1
%usepackage[ruled,vlined]{algorithm2e}          %算法排版样式2
%usepackage[linesnumbered,boxed]{algorithm2e}   %算法排版样式3
    
 egin{document}
   
    How to use the algorithm2e in LaTeX ~ file.
        
    Examples: 

%    ------------------------------Example - 1---------------------------------------------
        egin{algorithm}[H]
            caption{How to write algorithms}
            KwIn{this text}
            KwOut{how to write algorithm with LaTeX2e }
            
            initialization;
            While{not at end of this document}{
                read current;
                eIf{understand}
                {
                        go to next section;
                        current section becomes this one;
                }
                {
                    go back to the beginning of current section;
                }
        }
    end{algorithm}
    
%    ---------------------------Example - 2------------------------------------------------
    egin{algorithm} 
%    SetAlgoNoLine  %去掉之前的竖线
     caption{identifyRowContext} 
      KwIn{$r_i$, $Backgrd(T_i)$=${T_1,T_2,ldots ,T_n}$ and similarity threshold $	heta_r$} 
      KwOut{$con(r_i)$} 
        $con(r_i)= Phi$; 
        For{$j=1;j le n;j 
e i$} 
        { 
            float $maxSim=0$; 
            $r^{maxSim}=null$; 
            While{not end of $T_j$} 
            { 
                compute Jaro($r_i,r_m$)($r_min T_j$); 
                If{$(Jaro(r_i,r_m) ge 	heta_r)wedge (Jaro(r_i,r_m)ge r^{maxSim})$} 
                { 
                    replace $r^{maxSim}$ with $r_m$; 
                } 
            } 
            $con(r_i)=con(r_i)cup {r^{maxSim}}$; 
        } 
        return $con(r_i)$; 
    end{algorithm}
    %--------------------------------------------------------------------------------------

 some special information
    The algorithm2e LaTeX package conflicts with several others over the use of the algorithm identifier.  A common indicator is something like this message: 
To resolve the issues, simply put the following just before the inclusion of the algorithm2e package:

%makeatletter
%
ewifif@restonecol
%makeatother
%letalgorithm
elax
%letendalgorithm
elax

end{document}

中文latex模式下，更改Input为输入，更改Output为输出的方法：在算法内部插入、

SetKwInOut{KIN}{输入}

SetKwInOut{KOUT}{输出}

用我们定义的新的宏名“KIN” 在算法开头相应位置替换掉自带的KwInput，用"KOUT" 替换掉KwOutput 即可，实现中文的输入和输出.

具体事例如下：

 1 
enewcommand{algorithmcfname}{算法}
 2 egin{algorithm}[H]
 3 %SetAlgoNoLine
 4 SetKwInOut{KIN}{输入}
 5 SetKwInOut{KOUT}{输出}
 6 %BlankLine  %空一行
 7     caption{标准DE算法 }
 8     label{DE_algo} %
 9     KIN{Population: $ M$; Dimension: $ D $; Genetation: $ T $ }
10     KOUT{The best vector (solution)  $ varDelta $ }
11     $ t leftarrow 1 (initialization) $;
12     For{$i=1$ to $ M $    }
13     {For{$j=1$ to $ D $}
14         {
15             $  {x}_{i,t}^j=x_{min}^j + rand(0,1)cdotp (x_{max}^j-x_{min}^j) $;
16         }
17     }        
18     %--------------------------------------------------    
19 While{$(|f(varDelta)| geqvarepsilon )$      or     $(t leq T )$}
20     {
21         For{$ i=1$  to $M$}
22         {
23 emph{$ lacktriangleright $ (Mutation and Crossover)}\            
24 %	extit{ $ lacktriangleright $ (Mutation and Crossover) }\
25             For{$j=1$ to $ D $}
26             {    
27                 $ v_{i,t}^j =Mutation(x_{i,t}^j)$;    
28                 $ u_{i,t}^j =Crossover(x_{i,t}^j,v_{i,t}^j)$;
29             }
30 emph{$ lacktriangleright $ (Greedy Selection)}\
31             %	extit{ $ lacktriangleright $ (Greedy Selection) }\
32             eIf{$ f(	extbf{u}_{i,t}) <  f(	extbf{x}_{i,t}) $}
33             {
34                 $  	extbf{x}_{i,t} leftarrow	extbf{u}_{i,t}$;    
35                 If{$  f(	extbf{x}_{i,t}) < f(varDelta)$}
36                 {
37                     $ varDelta leftarrow 	extbf{x}_{i,t}$ ;
38                 }
39             }
40             {
41                 $  	extbf{x}_{i,t} leftarrow 	extbf{x}_{i,t} $;
42             }
43         }
44         $ t leftarrow t+1 $;    
45     }    %While        
46     Return the best vector  $varDelta$;
47 end{algorithm}