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/*
* $Revision: 3927 $
*
* last checkin:
* $Author: beyer $
* $Date: 2014-02-20 14:03:30 +0100 (Thu, 20 Feb 2014) $
***************************************************************/
/** \file
* \brief Declaration of extended graph algorithms
*
* \author Sebastian Leipert, Karsten Klein, Markus Chimani
*
* \par License:
* This file is part of the Open Graph Drawing Framework (OGDF).
*
* \par
* Copyright (C)<br>
* See README.txt in the root directory of the OGDF installation for details.
*
* \par
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* Version 2 or 3 as published by the Free Software Foundation;
* see the file LICENSE.txt included in the packaging of this file
* for details.
*
* \par
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* \par
* You should have received a copy of the GNU General Public
* License along with this program; if not, write to the Free
* Software Foundation, Inc., 51 Franklin Street, Fifth Floor,
* Boston, MA 02110-1301, USA.
*
* \see http://www.gnu.org/copyleft/gpl.html
***************************************************************/
#ifdef _MSC_VER
#pragma once
#endif
#ifndef OGDF_EXTENDED_GRAPH_ALG_H
#define OGDF_EXTENDED_GRAPH_ALG_H
#include <ogdf/cluster/ClusterGraph.h>
#include <ogdf/basic/BinaryHeap2.h>
#include <ogdf/basic/DisjointSets.h>
#include <ogdf/planarity/BoyerMyrvold.h>
namespace ogdf {
//---------------------------------------------------------
// Methods for induced subgraphs
//---------------------------------------------------------
//! Computes the subgraph induced by a list of nodes.
/**
* @tparam NODELISTITERATOR is the type of iterators for the input list of nodes.
* @param G is the input graph.
* @param start is a list iterator pointing to the first element in a list of nodes, for which
* an induced subgraph shall be computed.
* @param subGraph is assigned the computed subgraph.
*/
template<class LISTITERATOR>
void inducedSubGraph(const Graph &G, LISTITERATOR start, Graph &subGraph)
{
NodeArray<node> nodeTableOrig2New;
inducedSubGraph(G,start,subGraph,nodeTableOrig2New);
}
//! Computes the subgraph induced by a list of nodes (plus a mapping from original nodes to new copies).
/**
* @tparam NODELISTITERATOR is the type of iterators for the input list of nodes.
* @param G is the input graph.
* @param start is a list iterator pointing to the first element in a list of nodes, for which
* an induced subgraph shall be computed.
* @param subGraph is assigned the computed subgraph.
* @param nodeTableOrig2New is assigned a mapping from the nodes in \a G to the nodes in \a subGraph.
*/
template<class LISTITERATOR>
void inducedSubGraph(
const Graph &G,
LISTITERATOR start,
Graph &subGraph,
NodeArray<node> &nodeTableOrig2New)
{
subGraph.clear();
nodeTableOrig2New.init(G,0);
EdgeArray<bool> mark(G,false);
LISTITERATOR its;
for (its = start; its.valid(); its++)
{
node w = (*its);
OGDF_ASSERT(w != 0 && w->graphOf() == &G);
nodeTableOrig2New[w] = subGraph.newNode();
adjEntry adj = w->firstAdj();
forall_adj(adj,w)
{
edge e = adj->theEdge();
if (nodeTableOrig2New[e->source()] && nodeTableOrig2New[e->target()] && !mark[e])
{
subGraph.newEdge(nodeTableOrig2New[e->source()],nodeTableOrig2New[e->target()]);
mark[e] = true;
}
}
}
}
//! Computes the subgraph induced by a list of nodes (plus mappings from original nodes and edges to new copies).
/**
* @tparam NODELISTITERATOR is the type of iterators for the input list of nodes.
* @param G is the input graph.
* @param start is a list iterator pointing to the first element in a list of nodes, for which
* an induced subgraph shall be computed.
* @param subGraph is assigned the computed subgraph.
* @param nodeTableOrig2New is assigned a mapping from the nodes in \a G to the nodes in \a subGraph.
* @param edgeTableOrig2New is assigned a mapping from the edges in \a G to the egdes in \a subGraph.
*/
template<class LISTITERATOR>
void inducedSubGraph(
const Graph &G,
LISTITERATOR start,
Graph &subGraph,
NodeArray<node> &nodeTableOrig2New,
EdgeArray<edge> &edgeTableOrig2New)
{
subGraph.clear();
nodeTableOrig2New.init(G,0);
edgeTableOrig2New.init(G,0);
EdgeArray<bool> mark(G,false);
LISTITERATOR its;
for (its = start; its.valid(); its++)
{
node w = (*its);
OGDF_ASSERT(w != 0 && w->graphOf() == &G);
nodeTableOrig2New[w] = subGraph.newNode();
adjEntry adj = w->firstAdj();
forall_adj(adj,w)
{
edge e = adj->theEdge();
if (nodeTableOrig2New[e->source()] &&
nodeTableOrig2New[e->target()] &&
!mark[e])
{
edgeTableOrig2New[e] =
subGraph.newEdge(
nodeTableOrig2New[e->source()],
nodeTableOrig2New[e->target()]);
mark[e] = true;
}
}
}
}
//! Computes the edges in a node-induced subgraph.
/**
* @tparam NODELISTITERATOR is the type of iterators for the input list of nodes.
* @tparam EDGELIST is the type of the returned edge list.
* @param G is the input graph.
* @param it is a list iterator pointing to the first element in a list of nodes, whose
* induced subgraph is considered.
* @param E is assigned the list of edges in the node-induced subgraph.
*/
template<class NODELISTITERATOR, class EDGELIST>
void inducedSubgraph(Graph &G, NODELISTITERATOR &it, EDGELIST &E)
{
NODELISTITERATOR itBegin = it;
NodeArray<bool> mark(G,false);
for (;it.valid();it++)
mark[(*it)] = true;
it = itBegin;
for (;it.valid();it++)
{
node v = (*it);
adjEntry adj;
forall_adj(adj,v)
{
edge e = adj->theEdge();
if (mark[e->source()] && mark[e->target()])
E.pushBack(e);
}
}
}
//---------------------------------------------------------
// Methods for clustered graphs
//---------------------------------------------------------
//! Returns true iff cluster graph \a C is c-connected.
OGDF_EXPORT bool isCConnected(const ClusterGraph &C);
//! Makes a cluster graph c-connected by adding edges.
/**
* @param C is the input cluster graph.
* @param G is the graph associated with the cluster graph \a C; the function adds new edges to this graph.
* @param addedEdges is assigned the list of newly created edges.
* @param simple selects the method used: If set to true, a simple variant that does not guarantee to preserve
* planarity is used.
*/
OGDF_EXPORT void makeCConnected(
ClusterGraph& C,
Graph& G,
List<edge>& addedEdges,
bool simple = true);
//---------------------------------------------------------
// Methods for st-numbering
//---------------------------------------------------------
//! Computes an st-Numbering of \a G.
/**
* \pre \a G must be biconnected and simple, with the exception that
* the graph is allowed to have isolated nodes. If both \a s and \a t
* are set to nodes (both are not 0), they must be adjacent.
*
* @param G is the input graph.
* @param numbering is assigned the st-number for each node.
* @param s is the source node for the st-numbering.
* @param t is the target node for the st-numbering.
* @param randomized is only used when both \a s and \a t are not set (both are 0);
* in this case a random edge (s,t) is chosen; otherwise the first node s with degree
* > 0 is chosen and its first neighbor is used as t.
* @return the number assigned to \a t, or 0 if no st-numbering could be computed.
*/
OGDF_EXPORT int stNumber(const Graph &G,
NodeArray<int> &numbering,
node s = 0,
node t = 0,
bool randomized = false);
//! Tests, whether a numbering of the nodes is an st-numbering.
/**
* \pre \a G must be biconnected and simple, with the exception that
* the graph is allowed to have isolated nodes.
*/
OGDF_EXPORT bool testSTnumber(const Graph &G, NodeArray<int> &st_no,int max);
//---------------------------------------------------------
// Methods for minimum spanning tree computation
//---------------------------------------------------------
//! Computes a minimum spanning tree using Prim's algorithm
/**
* @tparam T is the numeric type for edge weights.
* @param G is the input graph.
* @param weight is an edge array with the edge weights.
* @param isInTree is assigned the result, i.e. \a isInTree[\a e] is true iff edge \a e is in the computed MST.
* @return the sum of the edge weights in the computed tree.
**/
template<typename T>
T computeMinST(const Graph &G, const EdgeArray<T> &weight, EdgeArray<bool> &isInTree) {
NodeArray<edge> pred(G, 0);
return computeMinST(G.firstNode(), G, weight, pred, isInTree);
}
//! Computes a minimum spanning tree (MST) using Prim's algorithm
/**
* @tparam T is the numeric type for edge weights.
* @param G is the input graph.
* @param weight is an edge array with the edge weights.
* @param isInTree is assigned the result, i.e. \a isInTree[\a e] is true iff edge \a e is in the computed MST.
* @param pred is assigned for each node the edge from its parent in the MST.
* @return the sum of the edge weights in the computed tree.
**/
template<typename T>
T computeMinST(const Graph &G, const EdgeArray<T> &weight, NodeArray<edge> &pred, EdgeArray<bool> &isInTree) {
return computeMinST(G.firstNode(), G, weight, pred, isInTree);
}
//! Computes a minimum spanning tree (MST) using Prim's algorithm
/**
* @tparam T is the numeric type for edge weights.
* @param s is the start node for Prim's algorithm and will be the root of the MST.
* @param G is the input graph.
* @param weight is an edge array with the edge weights.
* @param isInTree is assigned the result, i.e. \a isInTree[\a e] is true iff edge \a e is in the computed MST.
* @param pred is assigned for each node the edge from its parent in the MST.
* @return the sum of the edge weights in the computed tree.
**/
template<typename T>
T computeMinST(node s, const Graph &G, const EdgeArray<T> &weight, NodeArray<edge> &pred, EdgeArray<bool> &isInTree)
{
BinaryHeap2<T, node> pq(G.numberOfNodes()); // priority queue of front vertices
NodeArray<int> pqpos(G, -1); // position of each node in pq
// insert start node
T tmp(0);
pq.insert(s, tmp, &pqpos[s]);
// extract the nodes again along a minimum ST
NodeArray<bool> processed(G, false);
pred.init(G, NULL);
while (!pq.empty()) {
const node v = pq.extractMin();
processed[v] = true;
for (adjEntry adj = v->firstAdj(); adj; adj = adj->succ()) {
const node w = adj->twinNode();
const edge e = adj->theEdge();
const int wPos = pqpos[w];
if (wPos == -1) {
tmp = weight[e];
pq.insert(w, tmp, &pqpos[w]);
pred[w] = e;
} else
if (!processed[w]
&& weight[e] < pq.getPriority(wPos)) {
pq.decreaseKey(wPos, weight[e]);
pred[w] = e;
}
}
}
int rootcount = 0;
T treeWeight = 0;
isInTree.init(G, false);
for (node v = G.firstNode(); v; v = v->succ()) {
if (!pred[v]) {
++rootcount;
} else {
isInTree[pred[v]] = true;
treeWeight += weight[pred[v]];
}
}
OGDF_ASSERT(rootcount == 1); // is connected
return treeWeight;
}//computeMinST
//! Reduce a graph to its minimum spanning tree (MST) using Kruskal's algorithm
/**
* @tparam T is the numeric type for edge weights.
* @param G is the input graph.
* @param weight is an edge array with the edge weights.
* @return the sum of the edge weights in the computed tree.
**/
template<typename T>
T makeMinimumSpanningTree(Graph &G, const EdgeArray<T> &weight)
{
T total(0);
List< Prioritized<edge, T> > sortEdges;
for (edge e = G.firstEdge(); e; e = e->succ()) {
sortEdges.pushBack(Prioritized<edge,T>(e, weight[e]));
}
sortEdges.quicksort();
// now let's do Kruskal's algorithm
NodeArray<int> setID(G);
DisjointSets<> uf(G.numberOfNodes());
for (node v = G.firstNode(); v; v = v->succ()) {
setID[v] = uf.makeSet();
}
for (ListConstIterator< Prioritized<edge,T> > it = sortEdges.begin(); it.valid(); ++it) {
const edge e = (*it).item();
const int v = setID[e->source()];
const int w = setID[e->target()];
if (uf.find(v) != uf.find(w)) {
uf.link(uf.find(v), uf.find(w));
total += weight[e];
} else {
G.delEdge(e);
}
}
return total;
}
//! Returns true, if G is planar, false otherwise.
/**
* This is a shortcut for BoyerMyrvold::isPlanar().
*
* @param G is the input graph.
* @return true if \a G is planar, false otherwise.
*/
inline bool isPlanar(const Graph &G) {
return BoyerMyrvold().isPlanar(G);
}
//! Returns true, if G is planar, false otherwise. If true is returned, G will be planarly embedded.
/**
* This is a shortcut for BoyerMyrvold::planarEmbed
*
* @param G is the input graph.
* @return true if \a G is planar, false otherwise.
*/
inline bool planarEmbed(Graph &G) {
return BoyerMyrvold().planarEmbed(G);
}
//! Constructs a planar embedding of G. It assumes that \a G is planar!
/**
* This routine is slightly faster than planarEmbed(), but requires \a G to be planar.
* If \a G is not planar, the graph will be destroyed while trying to embed it!
*
* This is a shortcut for BoyerMyrvold::planarEmbedPlanarGraph().
*
* @param G is the input graph.
* @return true if the embedding was successful; false, if the given graph was non-planar (in this case
* the graph will be left in an at least partially deleted state).
*
*/
inline bool planarEmbedPlanarGraph(Graph &G) {
return BoyerMyrvold().planarEmbedPlanarGraph(G);
}
} // end namespace ogdf
#endif
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