之前自己尝试用visio+mathtype画算法流程图，但是总是存在着各种各样的问题，今天才知道最好的算法流程图是用latex写出来的，在网上找到相关资源，先记录下来，然后照着实践一下看看效果。

转载自：http://blog.csdn.net/u010485913/article/details/50609623

转自：http://www.myexception.cn/other/1259942.html

LaTeX算法排版例子

1）首先在导言区加入语句：

\usepackage{algorithm}
\usepackage{algorithmic}

2）例1

\begin{algorithm}
\caption{A}
\label{alg:A}
\begin{algorithmic}
\STATE {set $r(t)=x(t)$} 
\REPEAT 
\STATE set $h(t)=r(t)$ 
\REPEAT
\STATE set $h(t)=r(t)$ 
\UNTIL{B} 
\UNTIL{B}
\end{algorithmic}
\end{algorithm}

排版结果如下：

3）例2

\begin{algorithm}
\caption{Calculate $y = x^n$} 
\label{alg1}
\begin{algorithmic}
\REQUIRE $n \geq 0 \vee x \neq 0$ 
\ENSURE $y = x^n$ 
\STATE $y \Leftarrow 1$ 
\IF{$n < 0$} 
\STATE $X \Leftarrow 1 / x$ 
\STATE $N \Leftarrow -n$ 
\ELSE 
\STATE $X \Leftarrow x$ 
\STATE $N \Leftarrow n$
\ENDIF 
\WHILE{$N \neq 0$} 
\IF{$N$ is even} 
\STATE $X \Leftarrow X \times X$ 
\STATE $N \Leftarrow N / 2$ 
\ELSE[$N$ is odd] 
\STATE $y \Leftarrow y \times X$ 
\STATE $N \Leftarrow N - 1$ 
\ENDIF 
\ENDWHILE
\end{algorithmic}
\end{algorithm}

排版结果如下：

4）\renewcommand 改变现有命令的定义。在导言区加入如下语句：

\renewcommand{\algorithmicrequire}{ \textbf{Input:}} %Use Input in the format of Algorithm
\renewcommand{\algorithmicensure}{ \textbf{Output:}} %UseOutput in the format of Algorithm

使得原来软件包中定义的命令\REQUIRE和\ENSURE显示为Input:和Output:

一个例子如下： 

\begin{algorithm}[htb] 
\caption{ Framework of ensemble learning for our system.} 
\label{alg:Framwork} 
\begin{algorithmic}[1] %这个1 表示每一行都显示数字
\REQUIRE ~~\\ %算法的输入参数：Input
The set of positive samples for current batch, $P_n$;\\
The set of unlabelled samples for current batch, $U_n$;\\
Ensemble of classifiers on former batches, $E_{n-1}$;
\ENSURE ~~\\ %算法的输出：Output
Ensemble of classifiers on the current batch, $E_n$;
\STATE Extracting the set of reliable negative and/or positive samples $T_n$ from $U_n$ with help of $P_n$; 
\label{ code:fram:extract }%对此行的标记，方便在文中引用算法的某个步骤
\STATE Training ensemble of classifiers $E$ on $T_n \cup P_n$, with help of data in former batches; 
\label{code:fram:trainbase}
\STATE $E_n=E_{n-1}\cup E$; 
\label{code:fram:add}
\STATE Classifying samples in $U_n-T_n$ by $E_n$; 
\label{code:fram:classify}
\STATE Deleting some weak classifiers in $E_n$ so as to keep the capacity of $E_n$; 
\label{code:fram:select}
\RETURN $E_n$; %算法的返回值
\end{algorithmic}
\end{algorithm}

排版结果如下：

 5）最后一个例子

\begin{algorithm}[h]
\caption{An example for format For \& While Loop in Algorithm}
\begin{algorithmic}[1]
\FOR{each $i \in [1,9]$}
\STATE initialize a tree $T_{i}$ with only a leaf (the root);\
\STATE $T=T \cup T_{i};$\
\ENDFOR
\FORALL {$c$ such that $c \in RecentMBatch(E_{n-1})$} 
\label{code:TrainBase:getc}
\STATE $T=T \cup PosSample(c)$; 
\label{code:TrainBase:pos}
\ENDFOR
\FOR{$i=1$; $i<n$; $i++$ }
\STATE $//$ Your source here;
\ENDFOR
\FOR{$i=1$ to $n$}
\STATE $//$ Your source here;
\ENDFOR
\STATE $//$ Reusing recent base classifiers. 
\label{code:recentStart}
\WHILE {$(|E_n| \leq L_1 )and( D \neq \phi)$}
\STATE Selecting the most recent classifier $c_i$ from $D$;
\STATE $D=D-c_i$;
\STATE $E_n=E_n+c_i$;
\ENDWHILE 
\label{code:recentEnd}
\end{algorithmic}
\end{algorithm}

排版结果如下：