[libdai.git] / include / dai / bipgraph.h

/*  This file is part of libDAI - http://www.libdai.org/
 *
 *  libDAI is licensed under the terms of the GNU General Public License version
 *  2, or (at your option) any later version. libDAI is distributed without any
 *  warranty. See the file COPYING for more details.
 *
 *  Copyright (C) 2006-2009  Joris Mooij  [joris dot mooij at libdai dot org]
 *  Copyright (C) 2006-2007  Radboud University Nijmegen, The Netherlands
 */


/// \file
/// \brief Defines the BipartiteGraph class, which represents a bipartite graph


#ifndef __defined_libdai_bipgraph_h
#define __defined_libdai_bipgraph_h


#include <ostream>
#include <vector>
#include <algorithm>
#include <dai/util.h>
#include <dai/exceptions.h>


namespace dai {


/// Represents the neighborhood structure of nodes in an undirected, bipartite graph.
/** A bipartite graph has two types of nodes: type 1 and type 2. Edges can occur only between
 *  nodes of different type. Nodes are indexed by an unsigned integer. If there are nr1()
 *  nodes of type 1 and nr2() nodes of type 2, the nodes of type 1 are numbered
 *  0,1,2,...,nr1()-1 and the nodes of type 2 are numbered 0,1,2,...,nr2()-1. An edge
 *  between node \a n1 of type 1 and node \a n2 of type 2 is represented by a BipartiteGraph::Edge(\a n1,\a n2).
 *
 *  A BipartiteGraph is implemented as a sparse adjacency list, i.e., it stores for each node a list of
 *  its neighboring nodes. More precisely: it stores for each node of type 1 a vector of Neighbor structures
 *  (accessible by the nb1() method) describing the neighboring nodes of type 2; similarly, for each node
 *  of type 2 it stores a vector of Neighbor structures (accessibly by the nb2() method) describing the
 *  neighboring nodes of type 1.
 *  Thus, each node has an associated variable of type BipartiteGraph::Neighbors, which is a vector of
 *  Neighbor structures, describing its neighboring nodes of the other type.
 *  \idea Cache second-order neighborhoods in BipartiteGraph.
 */
class BipartiteGraph {
    public:
        /// Describes the neighbor relationship of two nodes in a BipartiteGraph.
        /** Sometimes we want to do an action, such as sending a
         *  message, for all edges in a graph. However, most graphs
         *  will be sparse, so we need some way of storing a set of
         *  the neighbors of a node, which is both fast and
         *  memory-efficient. We also need to be able to go between
         *  viewing node \a a as a neighbor of node \a b, and node \a b
         *  as a neighbor of node \a a. The Neighbor struct solves
         *  both of these problems. Each node has a list of neighbors,
         *  stored as a std::vector<\link Neighbor \endlink>, and 
         *  extra information is included in the Neighbor struct which 
         *  allows us to access a node as a neighbor of its neighbor 
         *  (the \c dual member).
         *
         *  By convention, variable identifiers naming indices into a
         *  vector of neighbors are prefixed with an underscore ("_").
         *  The neighbor list which they point into is then understood
         *  from context. For example:
         *
         *  \code
         *  void BP::calcNewMessage( size_t i, size_t _I )
         *  \endcode
         *
         *  Here, \a i is the "absolute" index of node i, but \a _I is
         *  understood as a "relative" index, giving node \a I 's entry in
         *  <tt>nb1(i)</tt>. The corresponding Neighbor structure can be
         *  accessed as <tt>nb1(i,_I)</tt> or <tt>nb1(i)[_I]</tt>. The 
         *  absolute index of \a _I, which would be called \a I, can be 
         *  recovered from the \c node member: <tt>nb1(i,_I).node</tt>. 
         *  The \c iter member gives the relative index \a _I, and the 
         *  \c dual member gives the "dual" relative index, i.e., the 
         *  index of \a i in \a I 's neighbor list.
         *
         *  \code
         *  Neighbor n = nb1(i,_I);
         *  n.node == I &&
         *  n.iter == _I &&
         *  nb2(n.node,n.dual).node == i
         *  \endcode
         *
         *  In a FactorGraph, the nodes of type 1 represent variables, and
         *  the nodes of type 2 represent factors. For convenience, nb1() is 
         *  called FactorGraph::nbV(), and nb2() is called FactorGraph::nbF().
         *
         *  There is no easy way to transform a pair of absolute node
         *  indices \a i and \a I into a Neighbor structure relative
         *  to one of the nodes. Such a feature has never yet been
         *  found to be necessary. Iteration over edges can always be
         *  accomplished using the Neighbor lists, and by writing
         *  functions that accept relative indices:
         *  \code
         *  for( size_t i = 0; i < nrVars(); ++i )
         *      foreach( const Neighbor &I, nbV(i) )
         *          calcNewMessage( i, I.iter );
         *  \endcode
         */
        struct Neighbor {
            /// Corresponds to the index of this Neighbor entry in the vector of neighbors
            size_t iter;
            /// Contains the number of the neighboring node
            size_t node;
            /// Contains the "dual" iter
            size_t dual;

            /// Default constructor
            Neighbor() {}
            /// Constructor that sets the Neighbor members according to the parameters
            Neighbor( size_t iter, size_t node, size_t dual ) : iter(iter), node(node), dual(dual) {}

            /// Cast to \c size_t returns \c node member
            operator size_t () const { return node; }
        };

        /// Describes the neighbors of some node.
        typedef std::vector<Neighbor> Neighbors;

        /// Represents an edge: an Edge(\a n1,\a n2) corresponds to the edge between node \a n1 of type 1 and node \a n2 of type 2.
        typedef std::pair<size_t,size_t> Edge;

    private:
        /// Contains for each node of type 1 a vector of its neighbors
        std::vector<Neighbors> _nb1;

        /// Contains for each node of type 2 a vector of its neighbors
        std::vector<Neighbors> _nb2;

        /// Used internally by isTree()
        struct levelType {
            /// Indices of nodes of type 1
            std::vector<size_t> ind1;       
            /// Indices of nodes of type 2
            std::vector<size_t> ind2;
        };

    // OBSOLETE
    /// \name Backwards compatibility layer (to be removed soon)
        //@{
        /// Enable backwards compatibility layer?
        /** \deprecated Please use the BipartiteGraph::Neighbor interface instead
         */
        bool _edge_indexed;
        /// Call indexEdges() first to initialize these members
        /** \deprecated Please use the BipartiteGraph::Neighbor interface instead
         */
        std::vector<Edge> _edges;
        /// Call indexEdges() first to initialize these members
        /** \deprecated Please use the BipartiteGraph::Neighbor interface instead
         */
        hash_map<Edge,size_t> _vv2e;
    //@}

    public:
    /// \name Constructors and destructors
    //@{
        /// Default constructor (creates an empty bipartite graph)
        BipartiteGraph() : _nb1(), _nb2(), _edge_indexed(false) {}

        /// Constructs BipartiteGraph from a range of edges.
        /** \tparam EdgeInputIterator Iterator that iterates over instances of BipartiteGraph::Edge.
         *  \param nr1 The number of nodes of type 1.
         *  \param nr2 The number of nodes of type 2.
         *  \param begin Points to the first edge.
         *  \param end Points just beyond the last edge.
         */
        template<typename EdgeInputIterator>
        BipartiteGraph( size_t nr1, size_t nr2, EdgeInputIterator begin, EdgeInputIterator end ) : _nb1( nr1 ), _nb2( nr2 ), _edge_indexed(false) {
            construct( nr1, nr2, begin, end );
        }
    //@}

    /// \name Accessors and mutators
    //@{
        /// Returns constant reference to the \a _i2 'th neighbor of node \a i1 of type 1
        const Neighbor & nb1( size_t i1, size_t _i2 ) const {
            DAI_DEBASSERT( i1 < _nb1.size() );
            DAI_DEBASSERT( _i2 < _nb1[i1].size() );
            return _nb1[i1][_i2];
        }
        /// Returns reference to the \a _i2 'th neighbor of node \a i1 of type 1
        Neighbor & nb1( size_t i1, size_t _i2 ) {
            DAI_DEBASSERT( i1 < _nb1.size() );
            DAI_DEBASSERT( _i2 < _nb1[i1].size() );
            return _nb1[i1][_i2];
        }

        /// Returns constant reference to the \a _i1 'th neighbor of node \a i2 of type 2
        const Neighbor & nb2( size_t i2, size_t _i1 ) const {
            DAI_DEBASSERT( i2 < _nb2.size() );
            DAI_DEBASSERT( _i1 < _nb2[i2].size() );
            return _nb2[i2][_i1];
        }
        /// Returns reference to the \a _i1 'th neighbor of node \a i2 of type 2
        Neighbor & nb2( size_t i2, size_t _i1 ) {
            DAI_DEBASSERT( i2 < _nb2.size() );
            DAI_DEBASSERT( _i1 < _nb2[i2].size() );
            return _nb2[i2][_i1];
        }

        /// Returns constant reference to all neighbors of node \a i1 of type 1
        const Neighbors & nb1( size_t i1 ) const {
            DAI_DEBASSERT( i1 < _nb1.size() );
            return _nb1[i1];
        }
        /// Returns reference to all neighbors of node \a i1 of type 1
        Neighbors & nb1( size_t i1 ) {
            DAI_DEBASSERT( i1 < _nb1.size() );
            return _nb1[i1];
        }

        /// Returns constant reference to all neighbors of node \a i2 of type 2
        const Neighbors & nb2( size_t i2 ) const {
            DAI_DEBASSERT( i2 < _nb2.size() );
            return _nb2[i2];
        }
        /// Returns reference to all neighbors of node \a i2 of type 2
        Neighbors & nb2( size_t i2 ) {
            DAI_DEBASSERT( i2 < _nb2.size() );
            return _nb2[i2];
        }
    //@}

    /// \name Adding nodes and edges
    //@{
        /// (Re)constructs BipartiteGraph from a range of edges.
        /** \tparam EdgeInputIterator Iterator that iterates over instances of BipartiteGraph::Edge.
         *  \param nr1 The number of nodes of type 1.
         *  \param nr2 The number of nodes of type 2.
         *  \param begin Points to the first edge.
         *  \param end Points just beyond the last edge.
         */
        template<typename EdgeInputIterator>
        void construct( size_t nr1, size_t nr2, EdgeInputIterator begin, EdgeInputIterator end );

        /// Adds a node of type 1 without neighbors and returns the index of the added node.
        size_t add1() { _nb1.push_back( Neighbors() ); return _nb1.size() - 1; }

        /// Adds a node of type 2 without neighbors and returns the index of the added node.
        size_t add2() { _nb2.push_back( Neighbors() ); return _nb2.size() - 1; }

        /// Adds a node of type 1, with neighbors specified by a range of nodes of type 2.
        /** \tparam NodeInputIterator Iterator that iterates over instances of \c size_t.
         *  \param begin Points to the first index of the nodes of type 2 that should become neighbors of the added node.
         *  \param end Points just beyond the last index of the nodes of type 2 that should become neighbors of the added node.
         *  \param sizeHint For improved efficiency, the size of the range may be specified by \a sizeHint.
         *  \returns Index of the added node.
         */
        template <typename NodeInputIterator>
        size_t add1( NodeInputIterator begin, NodeInputIterator end, size_t sizeHint = 0 ) {
            Neighbors nbs1new;
            nbs1new.reserve( sizeHint );
            size_t iter = 0;
            for( NodeInputIterator it = begin; it != end; ++it ) {
                DAI_ASSERT( *it < nr2() );
                Neighbor nb1new( iter, *it, nb2(*it).size() );
                Neighbor nb2new( nb2(*it).size(), nr1(), iter++ );
                nbs1new.push_back( nb1new );
                nb2( *it ).push_back( nb2new );
            }
            _nb1.push_back( nbs1new );
            return _nb1.size() - 1;
        }

        /// Adds a node of type 2, with neighbors specified by a range of nodes of type 1.
        /** \tparam NodeInputIterator Iterator that iterates over instances of \c size_t.
         *  \param begin Points to the first index of the nodes of type 1 that should become neighbors of the added node.
         *  \param end Points just beyond the last index of the nodes of type 1 that should become neighbors of the added node.
         *  \param sizeHint For improved efficiency, the size of the range may be specified by \a sizeHint.
         *  \returns Index of the added node.
         */
        template <typename NodeInputIterator>
        size_t add2( NodeInputIterator begin, NodeInputIterator end, size_t sizeHint = 0 ) {
            Neighbors nbs2new;
            nbs2new.reserve( sizeHint );
            size_t iter = 0;
            for( NodeInputIterator it = begin; it != end; ++it ) {
                DAI_ASSERT( *it < nr1() );
                Neighbor nb2new( iter, *it, nb1(*it).size() );
                Neighbor nb1new( nb1(*it).size(), nr2(), iter++ );
                nbs2new.push_back( nb2new );
                nb1( *it ).push_back( nb1new );
            }
            _nb2.push_back( nbs2new );
            return _nb2.size() - 1;
        }

        /// Adds an edge between node \a n1 of type 1 and node \a n2 of type 2.
        /** If \a check == \c true, only adds the edge if it does not exist already.
         */
        void addEdge( size_t n1, size_t n2, bool check = true );
    //@}

    /// \name Erasing nodes and edges
    //@{
        /// Removes node \a n1 of type 1 and all incident edges; indices of other nodes are changed accordingly.
        void erase1( size_t n1 );

        /// Removes node \a n2 of type 2 and all incident edges; indices of other nodes are changed accordingly.
        void erase2( size_t n2 );

        /// Removes edge between node \a n1 of type 1 and node \a n2 of type 2.
        void eraseEdge( size_t n1, size_t n2 );
    //@}

    /// \name Queries
    //@{
        /// Returns number of nodes of type 1
        size_t nr1() const { return _nb1.size(); }
        /// Returns number of nodes of type 2
        size_t nr2() const { return _nb2.size(); }

        /// Calculates the number of edges, time complexity: O(nr1())
        size_t nrEdges() const {
            size_t sum = 0;
            for( size_t i1 = 0; i1 < nr1(); i1++ )
                sum += nb1(i1).size();
            return sum;
        }

        /// Calculates second-order neighbors (i.e., neighbors of neighbors) of node \a n1 of type 1.
        /** If \a include == \c true, includes \a n1 itself, otherwise excludes \a n1.
         */
        std::vector<size_t> delta1( size_t n1, bool include = false ) const;

        /// Calculates second-order neighbors (i.e., neighbors of neighbors) of node \a n2 of type 2.
        /** If \a include == \c true, includes \a n2 itself, otherwise excludes \a n2.
         */
        std::vector<size_t> delta2( size_t n2, bool include = false ) const;

        /// Returns true if the graph is connected
        /** \todo Should be optimized by invoking boost::graph library
         */
        bool isConnected() const;

        /// Returns true if the graph is a tree, i.e., if it is singly connected and connected.
        bool isTree() const;

        /// Checks internal consistency
        void checkConsistency() const;
    //@}

    /// \name Input and output
    //@{
        /// Writes this BipartiteGraph to an output stream in GraphViz .dot syntax
        void printDot( std::ostream& os ) const;
    //@}

        // OBSOLETE
    /// \name Backwards compatibility layer (to be removed soon)
    //@{
        /// Prepare backwards compatibility layer for indexed edges
        /** \deprecated Please use the BipartiteGraph::Neighbor interface instead
         */
        void indexEdges() {
            std::cerr << "Warning: this BipartiteGraph edge interface is obsolete!" << std::endl;
            _edges.clear();
            _vv2e.clear();
            size_t i=0;
            foreach(const Neighbors &nb1s, _nb1) {
                foreach(const Neighbor &n2, nb1s) {
                    Edge e(i, n2.node);
                    _edges.push_back(e);
                }
                i++;
            }
            sort(_edges.begin(), _edges.end()); // unnecessary?

            i=0;
            foreach(const Edge& e, _edges) {
                _vv2e[e] = i++;
            }

            _edge_indexed = true;
        }

        /// Returns edge with index \a e
        /** \deprecated Please use the BipartiteGraph::Neighbor interface instead
         */
        const Edge& edge(size_t e) const {
            DAI_ASSERT(_edge_indexed);
            return _edges[e];
        }

        /// Returns all edges
        /** \deprecated Please use the BipartiteGraph::Neighbor interface instead
         */
        const std::vector<Edge>& edges() const {
            return _edges;
        }

        /// Converts a pair of node indices to an edge index
        /** \deprecated Please use the BipartiteGraph::Neighbor interface instead
         */
        size_t VV2E(size_t n1, size_t n2) const {
            DAI_ASSERT(_edge_indexed);
            Edge e(n1,n2);
            hash_map<Edge,size_t>::const_iterator i = _vv2e.find(e);
            DAI_ASSERT(i != _vv2e.end());
            return i->second;
        }

        /// Returns number of edges
        /** \deprecated Please use the BipartiteGraph::Neighbor interface instead
         */
        size_t nr_edges() const {
            DAI_ASSERT(_edge_indexed);
            return _edges.size();
        }
    //@}
};


template<typename EdgeInputIterator>
void BipartiteGraph::construct( size_t nr1, size_t nr2, EdgeInputIterator begin, EdgeInputIterator end ) {
    _nb1.clear();
    _nb1.resize( nr1 );
    _nb2.clear();
    _nb2.resize( nr2 );

    for( EdgeInputIterator e = begin; e != end; e++ ) {
#ifdef DAI_DEBUG
        addEdge( e->first, e->second, true );
#else
        addEdge( e->first, e->second, false );
#endif
    }
}


} // end of namespace dai


/** \example example_bipgraph.cpp
 *  This example deals with the following bipartite graph:
 *  \dot
 *  graph example {
 *    ordering=out;
 *    subgraph cluster_type1 {
 *      node[shape=circle,width=0.4,fixedsize=true,style=filled];
 *      12 [label="2"];
 *      11 [label="1"];
 *      10 [label="0"];
 *    }
 *    subgraph cluster_type2 {
 *      node[shape=polygon,regular=true,sides=4,width=0.4,fixedsize=true,style=filled];
 *      21 [label="1"];
 *      20 [label="0"];
 *    }
 *    10 -- 20;
 *    11 -- 20;
 *    12 -- 20;
 *    11 -- 21;
 *    12 -- 21;
 *  }
 *  \enddot
 *  It has three nodes of type 1 (drawn as circles) and two nodes of type 2 (drawn as rectangles).
 *  Node 0 of type 1 has only one neighbor (node 0 of type 2), but node 0 of type 2 has three neighbors (nodes 0,1,2 of type 1).
 *  The example code shows how to construct a BipartiteGraph object representing this bipartite graph and
 *  how to iterate over nodes and their neighbors.
 *
 *  \section Output
 *  \verbinclude examples/example_bipgraph.out
 *
 *  \section Source
 */


#endif