src/work/athos/preflow_push.hh
author athos
Thu, 15 Apr 2004 17:03:44 +0000
changeset 331 f5461f8bc59b
parent 119 9b3345f9d8ed
child 505 8589c0658839
permissions -rw-r--r--
Elkezdtem atirni a preflow_push-t. Csinaltam egy backupot graph wrapper nelkul (without gw, azaz wogw)
     1 #ifndef HUGO_PREFLOW_PUSH_HH
     2 #define HUGO_PREFLOW_PUSH_HH
     3 
     4 //#include <algorithm>
     5 #include <list>
     6 #include <vector>
     7 #include <queue>
     8 //#include "pf_hiba.hh"
     9 //#include <marci_list_graph.hh>
    10 //#include <marci_graph_traits.hh>
    11 #include <invalid.h>
    12 #include <graph_wrapper.h>
    13 //#include <reverse_bfs.hh>
    14 
    15 using namespace std;
    16 
    17 namespace hugo {
    18 
    19   template <typename Graph, typename T>
    20   class preflow_push {
    21 
    22     //Useful typedefs
    23     typedef typename Graph::Node Node;
    24     typedef typename Graph::NodeIt NodeIt;
    25     typedef typename Graph::Edge Edge;
    26     typedef typename Graph::OutEdgeIt OutEdgeIt;
    27     typedef typename Graph::InEdgeIt InEdgeIt;
    28 
    29 
    30     //---------------------------------------------
    31     //Parameters of the algorithm
    32     //---------------------------------------------
    33     //Fully examine an active node until excess becomes 0
    34     enum node_examination_t {examine_full, examine_to_relabel};
    35     //No more implemented yet:, examine_only_one_edge};
    36     node_examination_t node_examination;
    37     //Which implementation to be used
    38     enum implementation_t {impl_fifo, impl_highest_label};
    39     //No more implemented yet:};
    40     implementation_t implementation;
    41     //---------------------------------------------
    42     //Parameters of the algorithm
    43     //---------------------------------------------
    44  
    45   private:
    46     //input
    47     Graph& G;
    48     Node s;
    49     Node t;
    50     typename Graph::EdgeMap<T> &capacity;
    51 
    52     //output
    53     typename Graph::EdgeMap<T> preflow;
    54     T maxflow_value;
    55   
    56     //auxiliary variables for computation
    57     //The number of the nodes
    58     int number_of_nodes;
    59     //A nodemap for the level
    60     typename Graph::NodeMap<int> level;
    61     //A nodemap for the excess
    62     typename Graph::NodeMap<T> excess;
    63     
    64     //Number of nodes on each level
    65     vector<int> num_of_nodes_on_level;
    66     
    67     //For the FIFO implementation
    68     list<Node> fifo_nodes;
    69     //For 'highest label' implementation
    70     int highest_active;
    71     //int second_highest_active;
    72     vector< list<Node> > active_nodes;
    73 
    74   public:
    75   
    76     //Constructing the object using the graph, source, sink and capacity vector
    77     preflow_push(
    78 		      Graph& _G, 
    79 		      Node _s, 
    80 		      Node _t, 
    81 		      typename Graph::EdgeMap<T> & _capacity)
    82       : G(_G), s(_s), t(_t), 
    83 	capacity(_capacity), 
    84 	preflow(_G),
    85 	//Counting the number of nodes
    86 	//number_of_nodes(count(G.first<EachNodeIt>())),
    87 	number_of_nodes(G.nodeNum()),
    88 
    89 	level(_G),
    90 	excess(_G)//,
    91         // Default constructor: active_nodes()
    92     { 
    93       //Simplest parameter settings
    94       node_examination = examine_full;//examine_to_relabel;//
    95       //Which implementation to be usedexamine_full
    96       implementation = impl_highest_label;//impl_fifo;
    97  
    98       //
    99       num_of_nodes_on_level.resize(2*number_of_nodes-1);
   100       num_of_nodes_on_level.clear();
   101 
   102       switch(implementation){
   103       case impl_highest_label :{
   104 	active_nodes.clear();
   105 	active_nodes.resize(2*number_of_nodes-1);
   106 	
   107 	break;
   108       }
   109       default:
   110 	break;
   111       }
   112 
   113     }
   114 
   115     //Returns the value of a maximal flow 
   116     T run();
   117   
   118     typename Graph::EdgeMap<T>  getmaxflow(){
   119       return preflow;
   120     }
   121 
   122 
   123   private:
   124     //For testing purposes only
   125     //Lists the node_properties
   126     void write_property_vector(typename Graph::NodeMap<T> a,
   127 			       //node_property_vector<Graph, T> a, 
   128 			       char* prop_name="property"){
   129       for(NodeIt i=G.template first<NodeIt>(); G.valid(i); G.next(i)) {
   130 	cout<<"Node id.: "<<G.id(i)<<", "<<prop_name<<" value: "<<a[i]<<endl;
   131       }
   132       cout<<endl;
   133     }
   134 
   135     //Modifies the excess of the node and makes sufficient changes
   136     void modify_excess(const Node& a ,T v){
   137       //T old_value=excess[a];
   138       excess[a] += v;
   139     }
   140   
   141     //This private procedure is supposed to modify the preflow on edge j
   142     //by value v (which can be positive or negative as well) 
   143     //and maintain the excess on the head and tail
   144     //Here we do not check whether this is possible or not
   145     void modify_preflow(Edge j, const T& v){
   146 
   147       //Modifiyng the edge
   148       preflow[j] += v;
   149 
   150 
   151       //Modifiyng the head
   152       modify_excess(G.head(j),v);
   153 	
   154       //Modifiyng the tail
   155       modify_excess(G.tail(j),-v);
   156 
   157     }
   158 
   159     //Gives the active node to work with 
   160     //(depending on the implementation to be used)
   161     Node get_active_node(){
   162       
   163 
   164       switch(implementation) {
   165       case impl_highest_label : {
   166 
   167 	//First need to find the highest label for which there's an active node
   168 	while( highest_active>=0 && active_nodes[highest_active].empty() ){ 
   169 	  --highest_active;
   170 	}
   171 
   172 	if( highest_active>=0) {
   173 	  
   174 
   175 	  Node a=active_nodes[highest_active].front();
   176 	  active_nodes[highest_active].pop_front();
   177 	  
   178 	  return a;
   179 	}
   180 	else {
   181 	  return INVALID;
   182 	}
   183 	
   184 	break;
   185 	
   186       }
   187       case impl_fifo : {
   188 
   189 	if( ! fifo_nodes.empty() ) {
   190 	  Node a=fifo_nodes.front();
   191 	  fifo_nodes.pop_front();
   192 	  return a;
   193 	}
   194 	else {
   195 	  return INVALID;
   196 	}
   197 	break;
   198       }
   199       }
   200       //
   201       return INVALID;
   202     }
   203 
   204     //Puts node 'a' among the active nodes
   205     void make_active(const Node& a){
   206       //s and t never become active
   207       if (a!=s && a!= t){
   208 	switch(implementation){
   209 	case impl_highest_label :
   210 	  active_nodes[level[a]].push_back(a);
   211 	  break;
   212 	case impl_fifo :
   213 	  fifo_nodes.push_back(a);
   214 	  break;
   215 	}
   216 
   217       }
   218 
   219       //Update highest_active label
   220       if (highest_active<level[a]){
   221 	highest_active=level[a];
   222       }
   223 
   224     }
   225 
   226     //Changes the level of node a and make sufficent changes
   227     void change_level_to(Node a, int new_value){
   228       int seged = level[a];
   229       level.set(a,new_value);
   230       --num_of_nodes_on_level[seged];
   231       ++num_of_nodes_on_level[new_value];
   232     }
   233 
   234     //Collection of things useful (or necessary) to do before running
   235 
   236     void preprocess(){
   237 
   238       //---------------------------------------
   239       //Initialize parameters
   240       //---------------------------------------
   241 
   242       //Setting starting preflow, level and excess values to zero
   243       //This can be important, if the algorithm is run more then once
   244       for(NodeIt i=G.template first<NodeIt>(); G.valid(i); G.next(i)) {
   245         level.set(i,0);
   246         excess.set(i,0);
   247 	for(OutEdgeIt j=G.template first<OutEdgeIt>(i); G.valid(j); G.next(j)) 
   248 	  preflow.set(j, 0);
   249       }
   250       num_of_nodes_on_level[0]=number_of_nodes;
   251       highest_active=0;
   252       //---------------------------------------
   253       //Initialize parameters
   254       //---------------------------------------
   255 
   256       
   257       //------------------------------------
   258       //This is the only part that uses BFS
   259       //------------------------------------
   260 
   261       /*Reverse_bfs from t, to find the starting level.*/
   262       //Copyright: Jacint
   263       change_level_to(t,0);
   264 
   265       std::queue<Node> bfs_queue;
   266       bfs_queue.push(t);
   267 
   268       while (!bfs_queue.empty()) {
   269 
   270 	Node v=bfs_queue.front();	
   271 	bfs_queue.pop();
   272 	int l=level[v]+1;
   273 
   274 	InEdgeIt e;
   275 	for(G.first(e,v); G.valid(e); G.next(e)) {
   276 	  Node w=G.tail(e);
   277 	  if ( level[w] == number_of_nodes && w != s ) {
   278 	    bfs_queue.push(w);
   279 	    //Node first=level_list[l];
   280 	    //if ( G.valid(first) ) left.set(first,w);
   281 	    //right.set(w,first);
   282 	    //level_list[l]=w;
   283 	    change_level_to(w, l);
   284 	    //level.set(w, l);
   285 	  }
   286 	}
   287       }
   288       change_level_to(s,number_of_nodes);
   289       //level.set(s,number_of_nodes);
   290 
   291       /*
   292       //Setting starting level values using reverse bfs
   293       reverse_bfs<Graph> rev_bfs(G,t);
   294       rev_bfs.run();
   295       //write_property_vector(rev_bfs.dist,"rev_bfs");
   296       for(NodeIt i=G.template first<NodeIt>(); G.valid(i); G.next(i)) {
   297         change_level_to(i,rev_bfs.dist(i));
   298 	//level.put(i,rev_bfs.dist.get(i));
   299       }
   300       */
   301       //------------------------------------
   302       //This is the only part that uses BFS
   303       //------------------------------------
   304       
   305       
   306       //Starting level of s
   307       change_level_to(s,number_of_nodes);
   308       //level.put(s,number_of_nodes);
   309       
   310       
   311       //we push as much preflow from s as possible to start with
   312       for(OutEdgeIt j=G.template first<OutEdgeIt>(s); G.valid(j); G.next(j)){ 
   313 	modify_preflow(j,capacity[j] );
   314 	make_active(G.head(j));
   315 	int lev=level[G.head(j)];
   316 	if(highest_active<lev){
   317 	  highest_active=lev;
   318 	}
   319       }
   320       //cout<<highest_active<<endl;
   321     } 
   322 
   323     
   324     //If the preflow is less than the capacity on the given edge
   325     //then it is an edge in the residual graph
   326     bool is_admissible_forward_edge(Edge j, int& new_level){
   327 
   328       if (capacity[j]>preflow[j]){
   329 	if(level[G.tail(j)]==level[G.head(j)]+1){
   330 	  return true;
   331 	}
   332 	else{
   333 	  if (level[G.head(j)] < new_level)
   334 	    new_level=level[G.head(j)];
   335 	}
   336       }
   337       return false;
   338     }
   339 
   340     //If the preflow is greater than 0 on the given edge
   341     //then the edge reversd is an edge in the residual graph
   342     bool is_admissible_backward_edge(Edge j, int& new_level){
   343       
   344       if (0<preflow[j]){
   345 	if(level[G.tail(j)]==level[G.head(j)]-1){
   346 	 
   347 	  return true;
   348 	}
   349 	else{
   350 	  if (level[G.tail(j)] < new_level)
   351 	    new_level=level[G.tail(j)];
   352 	}
   353 	
   354       }
   355       return false;
   356     }
   357 
   358  
   359   };  //class preflow_push  
   360 
   361   template<typename Graph, typename T>
   362     T preflow_push<Graph, T>::run() {
   363     
   364     //We need a residual graph
   365     ResGraphType res_graph(G, preflow, capacity);
   366     
   367     preprocess();
   368     //write_property_vector(level,"level");
   369     T e,v;
   370     Node a;
   371     while (a=get_active_node(), G.valid(a)){
   372       
   373       bool go_to_next_node=false;
   374       e = excess[a];
   375       while (!go_to_next_node){
   376 
   377 	//Initial value for the new level for the active node we are dealing with
   378 	int new_level=2*number_of_nodes;
   379 
   380 
   381 	//Out edges from node a
   382 	{
   383 	  OutEdgeIt j=G.template first<OutEdgeIt>(a);
   384 	  while (G.valid(j) && e){
   385 
   386 	    if (is_admissible_forward_edge(j,new_level)){
   387 	      v=min(e,capacity[j] - preflow[j]);
   388 	      e -= v;
   389 	      //New node might become active
   390 	      if (excess[G.head(j)]==0){
   391 		make_active(G.head(j));
   392 	      }
   393 	      modify_preflow(j,v);
   394 	    }
   395 	    G.next(j);
   396 	  }
   397 	}
   398 	//In edges to node a
   399 	{
   400 	  InEdgeIt j=G.template first<InEdgeIt>(a);
   401 	  while (G.valid(j) && e){
   402 	    if (is_admissible_backward_edge(j,new_level)){
   403 	      v=min(e,preflow[j]);
   404 	      e -= v;
   405 	      //New node might become active
   406 	      if (excess[G.tail(j)]==0){
   407 		make_active(G.tail(j));
   408 	      }
   409 	      modify_preflow(j,-v);
   410 	    }
   411 	    G.next(j);
   412 	  }
   413 	}
   414 
   415 	//if (G.id(a)==999)
   416 	//cout<<new_level<<" e: "<<e<<endl;
   417 	//cout<<G.id(a)<<" "<<new_level<<endl;
   418 
   419 	if (0==e){
   420 	  //Saturating push
   421 	  go_to_next_node=true;
   422 	}
   423 	else{//If there is still excess in node a
   424 	  
   425 	  //change_level_to(a,new_level+1);
   426 	  
   427 	  //Level remains empty
   428 	  if (num_of_nodes_on_level[level[a]]==1){
   429 	    change_level_to(a,number_of_nodes);
   430 	    //go_to_next_node=True;
   431 	  }
   432 	  else{
   433 	    change_level_to(a,new_level+1);
   434 	    //increase_level(a);
   435 	  }
   436 	  
   437     
   438 	  
   439 
   440 	  switch(node_examination){
   441 	  case examine_to_relabel:
   442 	    make_active(a);
   443 
   444 	    go_to_next_node = true;
   445 	    break;
   446 	  default:
   447 	    break;
   448 	  }
   449 	  
   450     
   451 	
   452 	}//if (0==e)
   453       }
   454     }
   455     maxflow_value = excess[t];
   456     return maxflow_value;
   457   }//run
   458 
   459 
   460 }//namespace hugo
   461 
   462 #endif //PREFLOW_PUSH_HH