doc/groups.dox
author Alpar Juttner <alpar@cs.elte.hu>
Mon, 08 Aug 2011 12:36:16 +0200
branch1.1
changeset 1081 f1398882a928
parent 844 c01a98ce01fd
permissions -rw-r--r--
Unify sources
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/* -*- mode: C++; indent-tabs-mode: nil; -*-
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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) 2003-2011
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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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@defgroup datas Data Structures
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This group contains the several data structures implemented in LEMON.
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*/
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/**
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@defgroup graphs Graph Structures
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@ingroup datas
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\brief Graph structures implemented in LEMON.
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The implementation of combinatorial algorithms heavily relies on
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efficient graph implementations. LEMON offers data structures which are
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planned to be easily used in an experimental phase of implementation studies,
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and thereafter the program code can be made efficient by small modifications.
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The most efficient implementation of diverse applications require the
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usage of different physical graph implementations. These differences
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appear in the size of graph we require to handle, memory or time usage
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limitations or in the set of operations through which the graph can be
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accessed.  LEMON provides several physical graph structures to meet
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the diverging requirements of the possible users.  In order to save on
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running time or on memory usage, some structures may fail to provide
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some graph features like arc/edge or node deletion.
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Alteration of standard containers need a very limited number of
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operations, these together satisfy the everyday requirements.
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In the case of graph structures, different operations are needed which do
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not alter the physical graph, but gives another view. If some nodes or
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arcs have to be hidden or the reverse oriented graph have to be used, then
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this is the case. It also may happen that in a flow implementation
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the residual graph can be accessed by another algorithm, or a node-set
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is to be shrunk for another algorithm.
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LEMON also provides a variety of graphs for these requirements called
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\ref graph_adaptors "graph adaptors". Adaptors cannot be used alone but only
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in conjunction with other graph representations.
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You are free to use the graph structure that fit your requirements
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the best, most graph algorithms and auxiliary data structures can be used
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with any graph structure.
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<b>See also:</b> \ref graph_concepts "Graph Structure Concepts".
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*/
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/**
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@defgroup graph_adaptors Adaptor Classes for Graphs
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@ingroup graphs
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\brief Adaptor classes for digraphs and graphs
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This group contains several useful adaptor classes for digraphs and graphs.
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The main parts of LEMON are the different graph structures, generic
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graph algorithms, graph concepts, which couple them, and graph
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adaptors. While the previous notions are more or less clear, the
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latter one needs further explanation. Graph adaptors are graph classes
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which serve for considering graph structures in different ways.
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A short example makes this much clearer.  Suppose that we have an
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instance \c g of a directed graph type, say ListDigraph and an algorithm
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\code
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template <typename Digraph>
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int algorithm(const Digraph&);
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\endcode
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is needed to run on the reverse oriented graph.  It may be expensive
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(in time or in memory usage) to copy \c g with the reversed
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arcs.  In this case, an adaptor class is used, which (according
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to LEMON \ref concepts::Digraph "digraph concepts") works as a digraph.
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The adaptor uses the original digraph structure and digraph operations when
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methods of the reversed oriented graph are called.  This means that the adaptor
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have minor memory usage, and do not perform sophisticated algorithmic
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actions.  The purpose of it is to give a tool for the cases when a
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graph have to be used in a specific alteration.  If this alteration is
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obtained by a usual construction like filtering the node or the arc set or
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considering a new orientation, then an adaptor is worthwhile to use.
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To come back to the reverse oriented graph, in this situation
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\code
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template<typename Digraph> class ReverseDigraph;
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\endcode
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template class can be used. The code looks as follows
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\code
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ListDigraph g;
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ReverseDigraph<ListDigraph> rg(g);
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int result = algorithm(rg);
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\endcode
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During running the algorithm, the original digraph \c g is untouched.
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This techniques give rise to an elegant code, and based on stable
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graph adaptors, complex algorithms can be implemented easily.
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In flow, circulation and matching problems, the residual
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graph is of particular importance. Combining an adaptor implementing
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this with shortest path algorithms or minimum mean cycle algorithms,
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a range of weighted and cardinality optimization algorithms can be
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obtained. For other examples, the interested user is referred to the
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detailed documentation of particular adaptors.
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The behavior of graph adaptors can be very different. Some of them keep
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capabilities of the original graph while in other cases this would be
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meaningless. This means that the concepts that they meet depend
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on the graph adaptor, and the wrapped graph.
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For example, if an arc of a reversed digraph is deleted, this is carried
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out by deleting the corresponding arc of the original digraph, thus the
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adaptor modifies the original digraph.
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However in case of a residual digraph, this operation has no sense.
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Let us stand one more example here to simplify your work.
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ReverseDigraph has constructor
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\code
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ReverseDigraph(Digraph& digraph);
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\endcode
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This means that in a situation, when a <tt>const %ListDigraph&</tt>
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reference to a graph is given, then it have to be instantiated with
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<tt>Digraph=const %ListDigraph</tt>.
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\code
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int algorithm1(const ListDigraph& g) {
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  ReverseDigraph<const ListDigraph> rg(g);
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  return algorithm2(rg);
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}
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\endcode
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*/
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/**
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@defgroup maps Maps
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@ingroup datas
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\brief Map structures implemented in LEMON.
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This group contains the map structures implemented in LEMON.
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LEMON provides several special purpose maps and map adaptors that e.g. combine
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new maps from existing ones.
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<b>See also:</b> \ref map_concepts "Map Concepts".
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*/
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/**
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@defgroup graph_maps Graph Maps
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@ingroup maps
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\brief Special graph-related maps.
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This group contains maps that are specifically designed to assign
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values to the nodes and arcs/edges of graphs.
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If you are looking for the standard graph maps (\c NodeMap, \c ArcMap,
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\c EdgeMap), see the \ref graph_concepts "Graph Structure Concepts".
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*/
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/**
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\defgroup map_adaptors Map Adaptors
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\ingroup maps
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\brief Tools to create new maps from existing ones
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This group contains map adaptors that are used to create "implicit"
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maps from other maps.
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Most of them are \ref concepts::ReadMap "read-only maps".
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They can make arithmetic and logical operations between one or two maps
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(negation, shifting, addition, multiplication, logical 'and', 'or',
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'not' etc.) or e.g. convert a map to another one of different Value type.
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The typical usage of this classes is passing implicit maps to
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algorithms.  If a function type algorithm is called then the function
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type map adaptors can be used comfortable. For example let's see the
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usage of map adaptors with the \c graphToEps() function.
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\code
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  Color nodeColor(int deg) {
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    if (deg >= 2) {
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      return Color(0.5, 0.0, 0.5);
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    } else if (deg == 1) {
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      return Color(1.0, 0.5, 1.0);
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    } else {
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      return Color(0.0, 0.0, 0.0);
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    }
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  }
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  Digraph::NodeMap<int> degree_map(graph);
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  graphToEps(graph, "graph.eps")
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    .coords(coords).scaleToA4().undirected()
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    .nodeColors(composeMap(functorToMap(nodeColor), degree_map))
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    .run();
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\endcode
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The \c functorToMap() function makes an \c int to \c Color map from the
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\c nodeColor() function. The \c composeMap() compose the \c degree_map
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and the previously created map. The composed map is a proper function to
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get the color of each node.
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The usage with class type algorithms is little bit harder. In this
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case the function type map adaptors can not be used, because the
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function map adaptors give back temporary objects.
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\code
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  Digraph graph;
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  typedef Digraph::ArcMap<double> DoubleArcMap;
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  DoubleArcMap length(graph);
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  DoubleArcMap speed(graph);
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  typedef DivMap<DoubleArcMap, DoubleArcMap> TimeMap;
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  TimeMap time(length, speed);
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  Dijkstra<Digraph, TimeMap> dijkstra(graph, time);
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  dijkstra.run(source, target);
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\endcode
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We have a length map and a maximum speed map on the arcs of a digraph.
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The minimum time to pass the arc can be calculated as the division of
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the two maps which can be done implicitly with the \c DivMap template
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class. We use the implicit minimum time map as the length map of the
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\c Dijkstra algorithm.
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*/
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/**
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@defgroup paths Path Structures
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@ingroup datas
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\brief %Path structures implemented in LEMON.
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This group contains the path structures implemented in LEMON.
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LEMON provides flexible data structures to work with paths.
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All of them have similar interfaces and they can be copied easily with
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assignment operators and copy constructors. This makes it easy and
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efficient to have e.g. the Dijkstra algorithm to store its result in
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any kind of path structure.
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\sa lemon::concepts::Path
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*/
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/**
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@defgroup auxdat Auxiliary Data Structures
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@ingroup datas
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\brief Auxiliary data structures implemented in LEMON.
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This group contains some data structures implemented in LEMON in
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order to make it easier to implement combinatorial algorithms.
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*/
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/**
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@defgroup algs Algorithms
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\brief This group contains the several algorithms
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implemented in LEMON.
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This group contains the several algorithms
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implemented in LEMON.
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*/
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/**
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@defgroup search Graph Search
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@ingroup algs
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\brief Common graph search algorithms.
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This group contains the common graph search algorithms, namely
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\e breadth-first \e search (BFS) and \e depth-first \e search (DFS).
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*/
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/**
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@defgroup shortest_path Shortest Path Algorithms
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@ingroup algs
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\brief Algorithms for finding shortest paths.
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This group contains the algorithms for finding shortest paths in digraphs.
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 - \ref Dijkstra Dijkstra's algorithm for finding shortest paths from a
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   source node when all arc lengths are non-negative.
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 - \ref Suurballe A successive shortest path algorithm for finding
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   arc-disjoint paths between two nodes having minimum total length.
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*/
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/**
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@defgroup max_flow Maximum Flow Algorithms
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@ingroup algs
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\brief Algorithms for finding maximum flows.
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This group contains the algorithms for finding maximum flows and
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feasible circulations.
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The \e maximum \e flow \e problem is to find a flow of maximum value between
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a single source and a single target. Formally, there is a \f$G=(V,A)\f$
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digraph, a \f$cap: A\rightarrow\mathbf{R}^+_0\f$ capacity function and
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\f$s, t \in V\f$ source and target nodes.
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A maximum flow is an \f$f: A\rightarrow\mathbf{R}^+_0\f$ solution of the
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following optimization problem.
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\f[ \max\sum_{sv\in A} f(sv) - \sum_{vs\in A} f(vs) \f]
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\f[ \sum_{uv\in A} f(uv) = \sum_{vu\in A} f(vu)
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    \quad \forall u\in V\setminus\{s,t\} \f]
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\f[ 0 \leq f(uv) \leq cap(uv) \quad \forall uv\in A \f]
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\ref Preflow implements the preflow push-relabel algorithm of Goldberg and
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Tarjan for solving this problem. It also provides functions to query the
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minimum cut, which is the dual problem of maximum flow.
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\ref Circulation is a preflow push-relabel algorithm implemented directly
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for finding feasible circulations, which is a somewhat different problem,
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but it is strongly related to maximum flow.
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For more information, see \ref Circulation.
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*/
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/**
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@defgroup min_cost_flow_algs Minimum Cost Flow Algorithms
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@ingroup algs
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\brief Algorithms for finding minimum cost flows and circulations.
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This group contains the algorithms for finding minimum cost flows and
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circulations. For more information about this problem and its dual
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solution see \ref min_cost_flow "Minimum Cost Flow Problem".
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\ref NetworkSimplex is an efficient implementation of the primal Network
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Simplex algorithm for finding minimum cost flows. It also provides dual
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solution (node potentials), if an optimal flow is found.
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*/
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/**
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@defgroup min_cut Minimum Cut Algorithms
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@ingroup algs
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\brief Algorithms for finding minimum cut in graphs.
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This group contains the algorithms for finding minimum cut in graphs.
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The \e minimum \e cut \e problem is to find a non-empty and non-complete
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\f$X\f$ subset of the nodes with minimum overall capacity on
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outgoing arcs. Formally, there is a \f$G=(V,A)\f$ digraph, a
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\f$cap: A\rightarrow\mathbf{R}^+_0\f$ capacity function. The minimum
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cut is the \f$X\f$ solution of the next optimization problem:
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\f[ \min_{X \subset V, X\not\in \{\emptyset, V\}}
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    \sum_{uv\in A, u\in X, v\not\in X}cap(uv) \f]
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LEMON contains several algorithms related to minimum cut problems:
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- \ref HaoOrlin "Hao-Orlin algorithm" for calculating minimum cut
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  in directed graphs.
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- \ref GomoryHu "Gomory-Hu tree computation" for calculating
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  all-pairs minimum cut in undirected graphs.
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If you want to find minimum cut just between two distinict nodes,
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see the \ref max_flow "maximum flow problem".
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*/
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/**
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@defgroup graph_properties Connectivity and Other Graph Properties
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@ingroup algs
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\brief Algorithms for discovering the graph properties
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This group contains the algorithms for discovering the graph properties
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like connectivity, bipartiteness, euler property, simplicity etc.
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\image html edge_biconnected_components.png
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\image latex edge_biconnected_components.eps "bi-edge-connected components" width=\textwidth
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*/
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/**
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@defgroup matching Matching Algorithms
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@ingroup algs
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\brief Algorithms for finding matchings in graphs and bipartite graphs.
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This group contains the algorithms for calculating matchings in graphs.
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The general matching problem is finding a subset of the edges for which
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each node has at most one incident edge.
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There are several different algorithms for calculate matchings in
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graphs. The goal of the matching optimization
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can be finding maximum cardinality, maximum weight or minimum cost
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matching. The search can be constrained to find perfect or
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maximum cardinality matching.
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The matching algorithms implemented in LEMON:
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- \ref MaxMatching Edmond's blossom shrinking algorithm for calculating
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  maximum cardinality matching in general graphs.
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- \ref MaxWeightedMatching Edmond's blossom shrinking algorithm for calculating
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  maximum weighted matching in general graphs.
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- \ref MaxWeightedPerfectMatching
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  Edmond's blossom shrinking algorithm for calculating maximum weighted
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  perfect matching in general graphs.
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\image html bipartite_matching.png
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\image latex bipartite_matching.eps "Bipartite Matching" width=\textwidth
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*/
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/**
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@defgroup spantree Minimum Spanning Tree Algorithms
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@ingroup algs
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\brief Algorithms for finding minimum cost spanning trees and arborescences.
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This group contains the algorithms for finding minimum cost spanning
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trees and arborescences.
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*/
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/**
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@defgroup auxalg Auxiliary Algorithms
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@ingroup algs
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\brief Auxiliary algorithms implemented in LEMON.
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This group contains some algorithms implemented in LEMON
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in order to make it easier to implement complex algorithms.
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*/
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/**
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@defgroup gen_opt_group General Optimization Tools
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\brief This group contains some general optimization frameworks
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implemented in LEMON.
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This group contains some general optimization frameworks
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implemented in LEMON.
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*/
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/**
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@defgroup lp_group Lp and Mip Solvers
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@ingroup gen_opt_group
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\brief Lp and Mip solver interfaces for LEMON.
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This group contains Lp and Mip solver interfaces for LEMON. The
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various LP solvers could be used in the same manner with this
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interface.
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*/
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/**
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@defgroup utils Tools and Utilities
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\brief Tools and utilities for programming in LEMON
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Tools and utilities for programming in LEMON.
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*/
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/**
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@defgroup gutils Basic Graph Utilities
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@ingroup utils
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\brief Simple basic graph utilities.
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This group contains some simple basic graph utilities.
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*/
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/**
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@defgroup misc Miscellaneous Tools
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@ingroup utils
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\brief Tools for development, debugging and testing.
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This group contains several useful tools for development,
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debugging and testing.
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*/
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/**
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@defgroup timecount Time Measuring and Counting
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@ingroup misc
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\brief Simple tools for measuring the performance of algorithms.
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This group contains simple tools for measuring the performance
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of algorithms.
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*/
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/**
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@defgroup exceptions Exceptions
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@ingroup utils
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\brief Exceptions defined in LEMON.
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This group contains the exceptions defined in LEMON.
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*/
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/**
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@defgroup io_group Input-Output
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\brief Graph Input-Output methods
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This group contains the tools for importing and exporting graphs
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and graph related data. Now it supports the \ref lgf-format
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"LEMON Graph Format", the \c DIMACS format and the encapsulated
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postscript (EPS) format.
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*/
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/**
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@defgroup lemon_io LEMON Graph Format
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@ingroup io_group
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\brief Reading and writing LEMON Graph Format.
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This group contains methods for reading and writing
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\ref lgf-format "LEMON Graph Format".
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*/
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/**
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@defgroup eps_io Postscript Exporting
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@ingroup io_group
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\brief General \c EPS drawer and graph exporter
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This group contains general \c EPS drawing methods and special
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graph exporting tools.
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*/
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/**
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@defgroup dimacs_group DIMACS format
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@ingroup io_group
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\brief Read and write files in DIMACS format
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Tools to read a digraph from or write it to a file in DIMACS format data.
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*/
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/**
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@defgroup nauty_group NAUTY Format
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@ingroup io_group
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\brief Read \e Nauty format
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Tool to read graphs from \e Nauty format data.
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*/
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/**
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@defgroup concept Concepts
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\brief Skeleton classes and concept checking classes
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This group contains the data/algorithm skeletons and concept checking
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classes implemented in LEMON.
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The purpose of the classes in this group is fourfold.
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- These classes contain the documentations of the %concepts. In order
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  to avoid document multiplications, an implementation of a concept
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  simply refers to the corresponding concept class.
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- These classes declare every functions, <tt>typedef</tt>s etc. an
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  implementation of the %concepts should provide, however completely
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  without implementations and real data structures behind the
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  interface. On the other hand they should provide nothing else. All
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  the algorithms working on a data structure meeting a certain concept
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  should compile with these classes. (Though it will not run properly,
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  of course.) In this way it is easily to check if an algorithm
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  doesn't use any extra feature of a certain implementation.
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- The concept descriptor classes also provide a <em>checker class</em>
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  that makes it possible to check whether a certain implementation of a
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  concept indeed provides all the required features.
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- Finally, They can serve as a skeleton of a new implementation of a concept.
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*/
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/**
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@defgroup graph_concepts Graph Structure Concepts
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@ingroup concept
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\brief Skeleton and concept checking classes for graph structures
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This group contains the skeletons and concept checking classes of LEMON's
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graph structures and helper classes used to implement these.
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*/
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/**
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@defgroup map_concepts Map Concepts
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@ingroup concept
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\brief Skeleton and concept checking classes for maps
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   562
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   563
This group contains the skeletons and concept checking classes of maps.
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*/
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   566
/**
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\anchor demoprograms
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   568
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@defgroup demos Demo Programs
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   570
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Some demo programs are listed here. Their full source codes can be found in
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the \c demo subdirectory of the source tree.
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   573
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In order to compile them, use the <tt>make demo</tt> or the
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<tt>make check</tt> commands.
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*/
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   577
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/**
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@defgroup tools Standalone Utility Applications
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   581
Some utility applications are listed here.
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   582
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   583
The standard compilation procedure (<tt>./configure;make</tt>) will compile
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   584
them, as well.
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*/
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}