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kpeter (Peter Kovacs)
kpeter@inf.elte.hu
Various doc improvements (#406)
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8 files changed with 32 insertions and 28 deletions:
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\subsection pri-loc-var Private member variables
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Private member variables should start with underscore
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Private member variables should start with underscore.
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\code
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_start_with_underscores
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_start_with_underscore
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\endcode
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\subsection cs-excep Exceptions
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 - \ref CycleCanceling Cycle-Canceling algorithms, two of which are
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   strongly polynomial \ref klein67primal, \ref goldberg89cyclecanceling.
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In general NetworkSimplex is the most efficient implementation,
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but in special cases other algorithms could be faster.
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In general, \ref NetworkSimplex and \ref CostScaling are the most efficient
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implementations, but the other two algorithms could be faster in special cases.
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For example, if the total supply and/or capacities are rather small,
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CapacityScaling is usually the fastest algorithm (without effective scaling).
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\ref CapacityScaling is usually the fastest algorithm (without effective scaling).
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*/
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/**
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- \ref HowardMmc Howard's policy iteration algorithm
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  \ref dasdan98minmeancycle.
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In practice, the \ref HowardMmc "Howard" algorithm proved to be by far the
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In practice, the \ref HowardMmc "Howard" algorithm turned out to be by far the
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most efficient one, though the best known theoretical bound on its running
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time is exponential.
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Both \ref KarpMmc "Karp" and \ref HartmannOrlinMmc "Hartmann-Orlin" algorithms
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*/
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/**
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@defgroup planar Planarity Embedding and Drawing
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@defgroup planar Planar Embedding and Drawing
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@ingroup algs
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\brief Algorithms for planarity checking, embedding and drawing
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  ///
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  /// \warning Both number types must be signed and all input data must
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  /// be integer.
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  /// \warning This algorithm does not support negative costs for such
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  /// arcs that have infinite upper bound.
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  /// \warning This algorithm does not support negative costs for
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  /// arcs having infinite upper bound.
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#ifdef DOXYGEN
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  template <typename GR, typename V, typename C, typename TR>
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#else
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    /// calling \ref run(), the supply of each node will be set to zero.
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    ///
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    /// Using this function has the same effect as using \ref supplyMap()
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    /// with such a map in which \c k is assigned to \c s, \c -k is
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    /// with a map in which \c k is assigned to \c s, \c -k is
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    /// assigned to \c t and all other nodes have zero supply value.
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    ///
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    /// \param s The source node.
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  }
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  /// Check whether a graph is undirected.
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  /// \brief Check whether a graph is undirected.
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  ///
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  /// This function returns \c true if the given graph is undirected.
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#ifdef DOXYGEN
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  /// can be viewed as the generalization of the \ref Preflow
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  /// "preflow push-relabel" algorithm for the maximum flow problem.
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  ///
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  /// In general, \ref NetworkSimplex and \ref CostScaling are the fastest
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  /// implementations available in LEMON for this problem.
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  ///
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  /// Most of the parameters of the problem (except for the digraph)
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  /// can be given using separate functions, and the algorithm can be
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  /// executed using the \ref run() function. If some parameters are not
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  ///
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  /// \warning Both number types must be signed and all input data must
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  /// be integer.
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  /// \warning This algorithm does not support negative costs for such
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  /// arcs that have infinite upper bound.
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  /// \warning This algorithm does not support negative costs for
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  /// arcs having infinite upper bound.
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  ///
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  /// \note %CostScaling provides three different internal methods,
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  /// from which the most efficient one is used by default.
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    /// in their base operations, which are used in conjunction with the
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    /// relabel operation.
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    /// By default, the so called \ref PARTIAL_AUGMENT
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    /// "Partial Augment-Relabel" method is used, which proved to be
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    /// "Partial Augment-Relabel" method is used, which turned out to be
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    /// the most efficient and the most robust on various test inputs.
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    /// However, the other methods can be selected using the \ref run()
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    /// function with the proper parameter.
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    /// calling \ref run(), the supply of each node will be set to zero.
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    ///
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    /// Using this function has the same effect as using \ref supplyMap()
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    /// with such a map in which \c k is assigned to \c s, \c -k is
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    /// with a map in which \c k is assigned to \c s, \c -k is
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    /// assigned to \c t and all other nodes have zero supply value.
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    ///
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    /// \param s The source node.
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  ///
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  /// \warning Both number types must be signed and all input data must
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  /// be integer.
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  /// \warning This algorithm does not support negative costs for such
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  /// arcs that have infinite upper bound.
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  /// \warning This algorithm does not support negative costs for
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  /// arcs having infinite upper bound.
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  ///
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  /// \note For more information about the three available methods,
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  /// see \ref Method.
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    ///
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    /// \ref CycleCanceling provides three different cycle-canceling
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    /// methods. By default, \ref CANCEL_AND_TIGHTEN "Cancel and Tighten"
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    /// is used, which proved to be the most efficient and the most robust
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    /// on various test inputs.
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    /// is used, which is by far the most efficient and the most robust.
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    /// However, the other methods can be selected using the \ref run()
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    /// function with the proper parameter.
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    enum Method {
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    /// calling \ref run(), the supply of each node will be set to zero.
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    ///
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    /// Using this function has the same effect as using \ref supplyMap()
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    /// with such a map in which \c k is assigned to \c s, \c -k is
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    /// with a map in which \c k is assigned to \c s, \c -k is
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    /// assigned to \c t and all other nodes have zero supply value.
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    ///
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    /// \param s The source node.
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  ///Euler tour iterator for digraphs.
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  /// \ingroup graph_prop
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  /// \ingroup graph_properties
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  ///This iterator provides an Euler tour (Eulerian circuit) of a \e directed
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  ///graph (if there exists) and it converts to the \c Arc type of the digraph.
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  ///
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  /// linear programming simplex method directly for the minimum cost
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  /// flow problem.
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  ///
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  /// In general, %NetworkSimplex is the fastest implementation available
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  /// in LEMON for this problem.
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  /// Moreover, it supports both directions of the supply/demand inequality
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  /// constraints. For more information, see \ref SupplyType.
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  /// In general, \ref NetworkSimplex and \ref CostScaling are the fastest
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  /// implementations available in LEMON for this problem.
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  /// Furthermore, this class supports both directions of the supply/demand
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  /// inequality constraints. For more information, see \ref SupplyType.
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  ///
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  /// Most of the parameters of the problem (except for the digraph)
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  /// can be given using separate functions, and the algorithm can be
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    /// implementations that significantly affect the running time
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    /// of the algorithm.
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    /// By default, \ref BLOCK_SEARCH "Block Search" is used, which
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    /// proved to be the most efficient and the most robust on various
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    /// turend out to be the most efficient and the most robust on various
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    /// test inputs.
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    /// However, another pivot rule can be selected using the \ref run()
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    /// function with the proper parameter.
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    typedef std::vector<Value> ValueVector;
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    typedef std::vector<Cost> CostVector;
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    typedef std::vector<signed char> CharVector;
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    // Note: vector<signed char> is used instead of vector<ArcState> and 
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    // Note: vector<signed char> is used instead of vector<ArcState> and
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    // vector<ArcDirection> for efficiency reasons
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    // State constants for arcs
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    /// of the algorithm.
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    ///
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    /// \return <tt>(*this)</tt>
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    ///
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    /// \sa supplyType()
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    template<typename SupplyMap>
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    NetworkSimplex& supplyMap(const SupplyMap& map) {
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      for (NodeIt n(_graph); n != INVALID; ++n) {
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    /// calling \ref run(), the supply of each node will be set to zero.
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    ///
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    /// Using this function has the same effect as using \ref supplyMap()
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    /// with such a map in which \c k is assigned to \c s, \c -k is
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    /// with a map in which \c k is assigned to \c s, \c -k is
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    /// assigned to \c t and all other nodes have zero supply value.
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    ///
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    /// \param s The source node.
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