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alpar (Alpar Juttner)
alpar@cs.elte.hu
Doc improvements in lemon/max_matching.h
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1 file changed with 35 insertions and 36 deletions:
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@@ -41,7 +41,7 @@
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  ///
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  /// This class provides Edmonds' alternating forest matching
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  /// algorithm. The starting matching (if any) can be passed to the
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  /// algorithm using some of init functions.
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  /// This class implements Edmonds' alternating forest matching
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  /// algorithm. The algorithm can be started from an arbitrary initial
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  /// matching (the default is the empty one)
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  ///
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  /// The dual side of a matching is a map of the nodes to
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  /// The dual solution of the problem is a map of the nodes to
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  /// MaxMatching::Status, having values \c EVEN/D, \c ODD/A and \c
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@@ -51,5 +51,5 @@
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  /// barrier, and the nodes in \c MATCHED/C induce a graph having a
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  /// perfect matching. The number of the fractor critical components
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  /// perfect matching. The number of the factor-critical components
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  /// minus the number of barrier nodes is a lower bound on the
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  /// unmatched nodes, and if the matching is optimal this bound is
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  /// unmatched nodes, and the matching is optimal if and only if this bound is
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  /// tight. This decomposition can be attained by calling \c
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@@ -68,4 +68,3 @@
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    ///
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    ///Indicates the Gallai-Edmonds decomposition of the graph, which
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    ///shows an upper bound on the size of a maximum matching. The
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    ///Indicates the Gallai-Edmonds decomposition of the graph. The
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    ///nodes with Status \c EVEN/D induce a graph with factor-critical
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    /// \name Execution control
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    /// The simplest way to execute the algorithm is to use the member
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    /// The simplest way to execute the algorithm is to use the
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    /// \c run() member function.
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@@ -416,5 +415,5 @@
416 415

	
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    /// If you need more control on the execution, first you must call
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    /// If you need better control on the execution, you must call
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    /// \ref init(), \ref greedyInit() or \ref matchingInit()
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    /// functions, then you can start the algorithm with the \ref
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    /// functions first, then you can start the algorithm with the \ref
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    /// startParse() or startDense() functions.
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@@ -435,5 +434,5 @@
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    ///\brief Finds a greedy matching for initial matching.
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    ///\brief Finds an initial matching in a greedy way
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    ///
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    ///For initial matchig it finds a maximal greedy matching.
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    ///It finds an initial matching in a greedy way.
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    void greedyInit() {
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@@ -461,3 +460,3 @@
461 460

	
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    /// \brief Initialize the matching from the map containing a matching.
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    /// \brief Initialize the matching from a map containing.
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    ///
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@@ -509,3 +508,3 @@
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    /// It runs Edmonds' algorithm with a heuristic of postponing
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    /// shrinks, giving a faster algorithm for dense graphs.
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    /// shrinks, therefore resulting in a faster algorithm for dense graphs.
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    void startDense() {
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    /// \name Primal solution
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    /// Functions for get the primal solution, ie. the matching.
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    /// Functions to get the primal solution, ie. the matching.
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    ///\brief Returns the size of the actual matching stored.
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    ///\brief Returns the size of the current matching.
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    ///
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    ///Returns the size of the actual matching stored. After \ref
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    ///Returns the size of the current matching. After \ref
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    ///run() it returns the size of the maximum matching in the graph.
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@@ -585,3 +584,3 @@
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    /// \name Dual solution
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    /// Functions for get the dual solution, ie. the decomposition.
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    /// Functions to get the dual solution, ie. the decomposition.
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  /// blossomValue() members and \ref MaxWeightedMatching::BlossomIt
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  /// "BlossomIt" nested class which is able to iterate on the nodes
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  /// "BlossomIt" nested class, which is able to iterate on the nodes
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  /// of a blossom. If the value type is integral then the dual
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    /// \name Execution control
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    /// The simplest way to execute the algorithm is to use the member
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    /// The simplest way to execute the algorithm is to use the
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    /// \c run() member function.
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    /// \name Primal solution
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    /// Functions for get the primal solution, ie. the matching.
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    /// Functions to get the primal solution, ie. the matching.
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    /// \brief Returns the matching value.
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    /// \brief Returns the weight of the matching.
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    ///
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    /// Returns the matching value.
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    /// Returns the weight of the matching.
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    Value matchingValue() const {
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    /// \name Dual solution
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    /// Functions for get the dual solution.
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    /// Functions to get the dual solution.
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    /// \brief Lemon iterator for get the items of the blossom.
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    /// \brief Iterator for obtaining the nodes of the blossom.
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    ///
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    /// Lemon iterator for get the nodes of the blossom. This class
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    /// provides a common style lemon iterator which gives back a
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    /// Iterator for obtaining the nodes of the blossom. This class
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    /// provides a common lemon style iterator for listing a
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    /// subset of the nodes.
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      ///
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      /// Constructor for get the nodes of the variable.
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      /// Constructor to get the nodes of the variable.
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      BlossomIt(const MaxWeightedMatching& algorithm, int variable)
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    /// \name Execution control
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    /// The simplest way to execute the algorithm is to use the member
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    /// The simplest way to execute the algorithm is to use the
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    /// \c run() member function.
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    /// \name Primal solution
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    /// Functions for get the primal solution, ie. the matching.
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    /// Functions to get the primal solution, ie. the matching.
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    /// \name Dual solution
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    /// Functions for get the dual solution.
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    /// Functions to get the dual solution.
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    /// \brief Lemon iterator for get the items of the blossom.
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    /// \brief Iterator for obtaining the nodes of the blossom.
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    ///
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    /// Lemon iterator for get the nodes of the blossom. This class
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    /// provides a common style lemon iterator which gives back a
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    /// Iterator for obtaining the nodes of the blossom. This class
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    /// provides a common lemon style iterator for listing a
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    /// subset of the nodes.
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      ///
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      /// Constructor for get the nodes of the variable.
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      /// Constructor to get the nodes of the variable.
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      BlossomIt(const MaxWeightedPerfectMatching& algorithm, int variable)
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