latex算法排版

下给出使用latex进行算法排版的几个例子，以供参考：

\documentclass{article}

\usepackage[english]{babel}

\usepackage{blindtext}

\usepackage{algorithm} %format of the algorithm

\usepackage{algorithmic} %format of the algorithm

<?xml:namespace prefix = o /> 

\begin{document}

\blindtext

 

\begin{algorithm}[htb] %算法的开始

\renewcommand{\algorithmicrequire}{\textbf{Input:}}

\renewcommand\algorithmicensure {\textbf{Output:} }

\caption{ Framework of ensemble learning for our system.} %算法的标题

\label{alg:Framwork} %给算法一个标签，这样方便在文中对算法的引用

\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} %算法的一个陈述，对应算法的一个步骤或公式之类的； 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}

 

\blindtext

\end{document}

=====

2.

\documentclass{article}

\usepackage[english]{babel}

\usepackage{blindtext}

\usepackage{algorithm} %format of the algorithm

\usepackage{algorithmic} %format of the algorithm

\begin{document}

\blindtext

\begin{algorithm}[h]

\caption{An example for format For While Loop in Algorithm}

\begin{algorithmic}[1]

\FOR{each $iin [1,9]$}

\STATE initialize a tree $T_{i}$ with only a leaf (the root);\

\STATE $T_{i};$\

\ENDFOR

\FOR{$i=1$; $i<n$; $i++$ }

\STATE $//$ Your source here;

\ENDFOR

\WHILE {$(|E_n| leq L_1 )and(Deq phi)$}

\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}

\blindtext

\end{document}

===========