doc/algorithms.dox
author deba
Fri, 19 Oct 2007 16:24:31 +0000
changeset 2499 c97596611d59
parent 2470 46818ce27a60
child 2553 bfced05fa852
permissions -rw-r--r--
Planar Grid Embedding
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/* -*- C++ -*-
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 *
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 * This file is a part of LEMON, a generic C++ optimization library
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 *
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 * Copyright (C) 2003-2007
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 * Egervary Jeno Kombinatorikus Optimalizalasi Kutatocsoport
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 * (Egervary Research Group on Combinatorial Optimization, EGRES).
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 *
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 * Permission to use, modify and distribute this software is granted
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 * provided that this copyright notice appears in all copies. For
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 * precise terms see the accompanying LICENSE file.
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 *
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 * This software is provided "AS IS" with no warranty of any kind,
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 * express or implied, and with no claim as to its suitability for any
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 * purpose.
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 *
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 */
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namespace lemon {
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/**
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\page algorithms Algorithms
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\section algo_bfs_dfs Bfs/Dfs
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Both \ref lemon::Bfs "Bfs" and \ref lemon::Dfs "Dfs" are highly adaptable and efficient
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implementations of the well known algorithms. The algorithms are placed most cases in
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separated files named after the algorithm itself but lower case as all other header file names.
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For example the next Bfs class is in the \c lemon/bfs.h.
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\subsection Bfs
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The algorithm is implemented in the \ref lemon::Bfs "Bfs" template class - rather than as function.
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The class has two template parameters: \b GR and \b TR.<br>
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GR is the graph the algorithm runs on. It has \ref lemon::ListGraph "ListGraph" as default type.
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TR is a Traits class commonly used to easy the parametrization of templates. In most cases you
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wont need to modify the default type \ref lemon::BfsDefaultTraits "BfsDefaultTraits<GR>".
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To use the class, declare it!
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\code
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Bfs<ListUGraph>  bfs(gr);
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\endcode
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Note the lack of second template argument because of the default parameter.
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It provides a simple but powerful interface to control the execution.
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\code
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int dist = bfs.run(s,t);
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\endcode
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It finds the shortest path from node \c s to node \c t and returns it, or zero
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if there is no path from \c s to \c t.<br>
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If you want the shortest path from a specified node to all other node, just write:
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\code
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bfs.run(s);
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\endcode
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Now the distances and path information are stored in maps which you can access with
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member functions like \ref lemon::Bfs::distMap "distMap()" or \ref lemon::Bfs::predMap "predMap()".<br>
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Or more directly with other member functions like \ref lemon::Bfs::predNode "predNode()". Once the algorithm
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is finished (or to be precise reached that node) \ref lemon::Bfs::dist "dist()" or \ref lemon::Bfs::predNode
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"predNode()" can be called.
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For an example let's say we want to print the shortest path of those nodes which
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are in a certain distance.
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\code
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bfs.run(s);
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for( ListUGraph::NodeIt  n(gr); n != INVALID; ++n ) {
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  if( bfs.reached(n) && bfs.dist(n) <= max_dist ) {
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    std::cout << gr.id(n);
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    Node  prev = bfs.prevNode(n);
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    while( prev != INVALID ) {
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      std::cout << "<-" << gr.id(prev);
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      prev = bfs.prevNode(n);
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    }
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    std::cout << std::endl;
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  }
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}
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\endcode
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\subsubsection bfs_adv_control Advanced control
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In the previous code we only used \c run(). Now we introduce the way you can directly
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control the execution of the algorithm.
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First you have to initialize the variables with \ref lemon::Bfs::init "init()".
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\code
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  bfs.init();
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\endcode
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Then you add one or more source nodes to the queue. They will be processed, as they would
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be reached by the algorithm before. And yes - you can add more sources during the execution.
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\code
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  bfs.addSource(node_1);
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  bfs.addSource(node_2);
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  ...
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\endcode
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And finally you can start the process with \ref lemon::Bfs::start "start()", or
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you can write your own loop to process the nodes one-by-one.
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\todo Demo for Bfs advanced control.
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\subsection Dfs
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Since Dfs is very similar to Bfs with a few tiny differences we only see a bit more complex example
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to demonstrate Dfs's capabilities.
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We will see a program, which solves the problem of <b>topological ordering</b>.
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We need to know in which order we should put on our clothes. The program will do the following:
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<ol>
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<li>We run the dfs algorithm to all nodes.
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<li>Put every node into a list when processed completely.
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<li>Write out the list in reverse order.
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</ol>
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\dontinclude topological_ordering.cc
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First of all we will need an own \ref lemon::Dfs::ProcessedMap "ProcessedMap". The ordering
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will be done through it.
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\skip MyOrdererMap
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\until };
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The class meets the \ref concepts::WriteMap "WriteMap" concept. In it's \c set() method the only thing
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we need to do is insert the key - that is the node whose processing just finished - into the beginning
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of the list.<br>
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Although we implemented this needed helper class ourselves it was not necessary.
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The \ref lemon::FrontInserterBoolMap "FrontInserterBoolMap" class does exactly
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what we needed. To be correct it's more general - and it's all in \c LEMON. But
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we wanted to show you, how easy is to add additional functionality.
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First we declare the needed data structures: the graph and a map to store the nodes' label.
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\skip ListGraph
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\until label
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Now we build a graph. But keep in mind that it must be DAG because cyclic graphs has no topological
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ordering.
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\skip belt
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\until trousers
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We label them...
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\skip label
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\until trousers
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Then add directed edges which represent the precedences between those items.
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\skip trousers, belt
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\until );
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See how easy is to access the internal information of this algorithm trough maps.
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We only need to set our own map as the class's \ref lemon::Dfs::ProcessedMap "ProcessedMap".
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\skip Dfs
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\until run
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And now comes the third part. Write out the list in reverse order. But the list was
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composed in reverse way (with \c push_front() instead of \c push_back() so we just iterate it.
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\skip std
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\until endl
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The program is to be found in the \ref demo directory: \ref topological_ordering.cc
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\todo Check the linking of the demo file, the code samples are missing.
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More algorithms are described in the \ref algorithms2 "second part".
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*/
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}