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Deleting unnecessary class

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Dennis Luxen 2011-07-07 07:44:20 +00:00
parent 943a0203f2
commit 132c25fd3b
1 changed files with 0 additions and 192 deletions
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DataStructures/TurnInfoFactory.h
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@ -1,192 +0,0 @@
/*
open source routing machine
Copyright (C) Dennis Luxen, others 2010
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU AFFERO General Public License as published by
the Free Software Foundation; either version 3 of the License, or
any later version.
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.
You should have received a copy of the GNU Affero General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
or see http://www.gnu.org/licenses/agpl.txt.
*/
#ifndef TURNINFOFACTORY_H_INCLUDED
#define TURNINFOFACTORY_H_INCLUDED
#ifdef _GLIBCXX_PARALLEL
#include <parallel/algorithm>
#else
#include <algorithm>
#endif
#include "StaticGraph.h"
#include "Percent.h"
#include <ctime>
#include <vector>
#include <queue>
#include <set>
#include <stack>
#include <limits>
#include <omp.h>
typedef StaticGraph<MinimalEdgeData>::InputEdge MinimalEdge;
typedef StaticGraph<MinimalEdgeData> _StaticGraph;
//template <typename InputEdge>
class TurnInfoFactory {
public:
TurnInfoFactory( int nodes, std::vector< ImportEdge >& inputEdges ) : _inputEdges (inputEdges) {
std::vector< MinimalEdge > edges;
edges.reserve( 2 * inputEdges.size() );
for ( std::vector< ImportEdge >::const_iterator i = inputEdges.begin(), e = inputEdges.end(); i != e; ++i ) {
MinimalEdge edge;
edge.source = i->source();
edge.target = i->target();
edge.data.distance = std::max((int)i->weight(), 1 );
assert( edge.data.distance > 0 );
if ( edge.data.distance > 24 * 60 * 60 * 10 ) {
cout << "Edge Weight too large -> May lead to invalid CH" << endl;
continue;
}
if ( edge.data.distance <= 0 ) {
cout << "Edge Weight too small -> May lead to invalid CH or Crashes"<< endl;
continue;
}
edge.data.forward = i->isForward();
edge.data.backward = i->isBackward();
edges.push_back( edge );
std::swap( edge.source, edge.target );
edge.data.forward = i->isBackward();
edge.data.backward = i->isForward();
edges.push_back( edge );
}
#ifdef _GLIBCXX_PARALLEL
__gnu_parallel::sort( edges.begin(), edges.end() );
#else
sort( edges.begin(), edges.end() );
#endif
NodeID edge = 0;
for ( NodeID i = 0; i < edges.size(); ) {
const NodeID source = edges[i].source;
const NodeID target = edges[i].target;
//remove eigenloops
if ( source == target ) {
i++;
continue;
}
MinimalEdge forwardEdge;
MinimalEdge backwardEdge;
forwardEdge.source = backwardEdge.source = source;
forwardEdge.target = backwardEdge.target = target;
forwardEdge.data.forward = backwardEdge.data.backward = true;
forwardEdge.data.backward = backwardEdge.data.forward = false;
// forwardEdge.data.type = backwardEdge.data.type = type;
// forwardEdge.data.middleName.nameID = backwardEdge.data.middleName.nameID = middle;
// forwardEdge.data.shortcut = backwardEdge.data.shortcut = false;
// forwardEdge.data.originalEdges = backwardEdge.data.originalEdges = 1;
forwardEdge.data.distance = backwardEdge.data.distance = std::numeric_limits< int >::max();
//remove parallel edges
while ( i < edges.size() && edges[i].source == source && edges[i].target == target ) {
if ( edges[i].data.forward )
forwardEdge.data.distance = std::min( edges[i].data.distance, forwardEdge.data.distance );
if ( edges[i].data.backward )
backwardEdge.data.distance = std::min( edges[i].data.distance, backwardEdge.data.distance );
i++;
}
//merge edges (s,t) and (t,s) into bidirectional edge
if ( forwardEdge.data.distance == backwardEdge.data.distance ) {
if ( (int)forwardEdge.data.distance != std::numeric_limits< int >::max() ) {
forwardEdge.data.backward = true;
edges[edge++] = forwardEdge;
}
} else { //insert seperate edges
if ( (int)forwardEdge.data.distance != std::numeric_limits< int >::max() ) {
edges[edge++] = forwardEdge;
}
if ( (int)backwardEdge.data.distance != std::numeric_limits< int >::max() ) {
edges[edge++] = backwardEdge;
}
}
}
cout << "ok" << endl << "removed " << edges.size() - edge << " edges of " << edges.size() << endl;
edges.resize( edge );
_graph = new _StaticGraph( nodes, edges );
std::vector< MinimalEdge >().swap( edges );
}
~TurnInfoFactory() {
delete _graph;
}
/* check if its possible to turn at the end of an edge */
template< class InputEdge >
void Run () {
unsigned count = 0;
for(unsigned n = 0; n < _inputEdges.size(); n++) {
NodeID target = _inputEdges[n].target();
NodeID source = _inputEdges[n].source();
if(_inputEdges[n].isForward() ) {
EdgeID begin = _graph->BeginEdges(target);
EdgeID end = _graph->EndEdges(target);
if( begin + ( _inputEdges[n].isBackward() ? 2 : 1 ) < end ) {
_inputEdges[n].setForwardTurn( true );
count++;
}
}
if(_inputEdges[n].isBackward() ) {
EdgeID begin = _graph->BeginEdges(source);
EdgeID end = _graph->EndEdges(source);
if( begin + ( _inputEdges[n].isForward() ? 2 : 1 ) < end ) {
_inputEdges[n].setBackwardTurn( true );
count ++;
}
}
}
cout << "allowed turns: " << count << endl;
}
/* check if its possible to turn at the end of an edge */
void Run () {
unsigned count = 0;
for(unsigned n = 0; n < _inputEdges.size(); n++) {
NodeID target = _inputEdges[n].target();
NodeID source = _inputEdges[n].source();
if(_inputEdges[n].isForward() ) {
EdgeID begin = _graph->BeginEdges(target);
EdgeID end = _graph->EndEdges(target);
if( begin + ( _inputEdges[n].isBackward() ? 2 : 1 ) < end ) {
_inputEdges[n].setForwardTurn( true );
count++;
}
}
if(_inputEdges[n].isBackward() ) {
EdgeID begin = _graph->BeginEdges(source);
EdgeID end = _graph->EndEdges(source);
if( begin + ( _inputEdges[n].isForward() ? 2 : 1 ) < end ) {
_inputEdges[n].setBackwardTurn( true );
count ++;
}
}
}
cout << "allowed turns: " << count << endl;
}
private:
_StaticGraph* _graph;
std::vector<NodeID> * _components;
std::vector< ImportEdge >& _inputEdges;
};
#endif // TURNINFOFACTORY_H_INCLUDED