C++ TPt::GetEDat方法代码示例

//! Given pGraph with data about edge weights, computes the distance of the shortest paths from sourceNode
//! and returns the result in the nodes of pDAGGraph.
//! Updates the edges if bUpdateEdges is set to true. Default is false. In that case only the node data is updated with the shortest distance to sourceNode.
//! @note Requires initial values for the nodes of pDAGGraph (edges are not needed)
void Dijkstra(const TPt<TNodeEDatNet<TFlt, TFlt>>& pGraph, int sourceNode, double dThreshold, TPt<TNodeEDatNet<TFlt, TFlt>>& pDAGGraph, bool bUpdateEdges = false)
{
	double logThreshold = log(dThreshold);
	if(dThreshold==0)
		logThreshold=-DBL_MAX;

	// List of visited nodes
	std::map<int, bool> visitedNodes;
	// Stores the edge vertices to build the final DAG
	std::map<int, int> mapPrevious;
	std::priority_queue<std::pair<int,double>, std::vector<std::pair<int,double>>, Order> nodesToVisit;

	// Distance from source node to itself is 0
	pDAGGraph->SetNDat(sourceNode, 0);
	nodesToVisit.push(std::make_pair(sourceNode,0));

	// Beginning of the loop of Dijkstra algorithm

	while(!nodesToVisit.empty())
	{
		// Find the vertex in queue with the smallest distance and remove it
		int iParentID = -1;
		while (!nodesToVisit.empty() && visitedNodes[iParentID = nodesToVisit.top().first])
			nodesToVisit.pop();
		if (iParentID == -1) break;

		// mark the vertex with the shortest distance
		visitedNodes[iParentID]=true;

		auto parent = pGraph->GetNI(iParentID);
		int numChildren = parent.GetOutDeg();
		for(int i = 0; i < numChildren; ++i)
		{
			int iChildID = parent.GetOutNId(i);
			// Accumulate the shortest distance from source
			double alt = pDAGGraph->GetNDat(iParentID) - log(parent.GetOutEDat(i).Val);
			if(alt >= logThreshold)
			{
				auto it = visitedNodes.find(iChildID);
				if (alt < pDAGGraph->GetNDat(iChildID) && it->second == false)
				{
					//1. update distance
					//2. update the predecessor
					//3. push new shortest rank of chidren nodes
					pDAGGraph->SetNDat(iChildID, alt);
					mapPrevious[iChildID]= iParentID;
					nodesToVisit.push(std::make_pair(iChildID,alt));
				}
			}
		}

	}

	if(bUpdateEdges)
		for(auto it=mapPrevious.begin(); it!= mapPrevious.end(); ++it)
		{
			pDAGGraph->AddEdge(it->second, it->first);
			pDAGGraph->SetEDat(it->second,it->first, pGraph->GetEDat(it->second,it->first));
		}
}

TPt<TNodeEDatNet<TFlt, TFlt>> GenerateDAG1(const TPt<TNodeEDatNet<TFlt, TFlt>> &pGraph, const std::vector<int>& seedNodes, double threshold)
{
	// Copy pGraph into pGraph_DAG1
	auto pGraph_DAG1 = TNodeEDatNet<TFlt, TFlt>::New();

	for (auto NI = pGraph->BegNI(); NI < pGraph->EndNI(); NI++)
		pGraph_DAG1->AddNode(NI.GetId());
	
	for (auto EI = pGraph->BegEI(); EI < pGraph->EndEI(); EI++)
	{
		pGraph_DAG1->AddEdge(EI.GetSrcNId(),EI.GetDstNId());
		pGraph_DAG1->SetEDat(EI.GetSrcNId(),EI.GetDstNId(), pGraph->GetEDat(EI.GetSrcNId(),EI.GetDstNId()));
	}

	// Create a super root in order to update in one pass all the shortest paths from vSeedIDs nodes
	int superRootID =  pGraph_DAG1->GetMxNId()+1;
	pGraph_DAG1->AddNode(superRootID);

	for(int srcNode: seedNodes)
	{
		pGraph_DAG1->AddEdge(superRootID, srcNode);
		pGraph_DAG1->SetEDat(superRootID, srcNode, 1.0);
	}
	pGraph_DAG1 = MIOA(pGraph_DAG1, superRootID, threshold);
	// Remove the artificial super root node
	pGraph_DAG1->DelNode(superRootID);


	// Add back other edges with the condition r(u)<r(v)
	for (auto EI = pGraph->BegEI(); EI < pGraph->EndEI(); EI++)
	{
		int u = EI.GetSrcNId(), v = EI.GetDstNId();
		if(pGraph_DAG1->GetNDat(u)< pGraph_DAG1->GetNDat(v))
		{
			if (!pGraph_DAG1->IsEdge(u,v))
			{
				pGraph_DAG1->AddEdge(u,v);
				pGraph_DAG1->SetEDat(u,v,EI.GetDat());
			}
		}
	}
	//Reset Node data from the original graph
	for (auto NI = pGraph->BegNI(); NI < pGraph->EndNI(); NI++)
		pGraph_DAG1->SetNDat(NI.GetId(),NI.GetDat().Val);

	return pGraph_DAG1;
}

//???????
TPt<TNodeEDatNet<TFlt, TFlt>> GenerateDAG2(const TPt<TNodeEDatNet<TFlt, TFlt>>& pGraph, const std::vector<int> &vSeedIDs, double dThreshold)
{
	// Vector of MIOA graphs per seed node
	std::vector<TPt<TNodeEDatNet<TFlt, TFlt>>> vMIOAGraphs;

	// Compute the union of MIOA for each node of vSeedIDs
	for(auto it=vSeedIDs.begin(); it!=vSeedIDs.end(); ++it)
		vMIOAGraphs.push_back(MIOA(pGraph, *it, dThreshold));
	auto pOut = GraphUnion(vMIOAGraphs);

	// Set node data
	for (auto NI = pOut->BegNI(); NI < pOut->EndNI(); NI++)
		pOut->SetNDat(NI.GetId(), FLT_MAX);

	// Copy the edge weights from pGraph
	for (auto EI = pOut->BegEI(); EI < pOut->EndEI(); EI++)
		pOut->SetEDat(EI.GetSrcNId(), EI.GetDstNId(), pGraph->GetEDat(EI.GetSrcNId(), EI.GetDstNId()));

	// Create a super root in order to update in one pass all the shortest paths from vSeedIDs nodes
	int superRootID = pGraph->GetMxNId()+1;
	pOut->AddNode(superRootID);
	for(auto it=vSeedIDs.begin(); it!=vSeedIDs.end(); ++it)
	{
		pOut->AddEdge(superRootID, *it);
		pOut->SetEDat(superRootID, *it, 1.0);
	}
	Dijkstra(pOut, superRootID, dThreshold, pOut);
	// Remove the artificial super root node
	pOut->DelNode(superRootID);

	// Traverse the edges and prune the graph
	for (auto EI = pOut->BegEI(); EI < pOut->EndEI(); EI++)
	{
		if(EI.GetDstNDat().Val < EI.GetSrcNDat().Val)
			pOut->DelEdge(EI.GetSrcNId(), EI.GetDstNId());
	}

	//Reset Node data from the original graph
	for (auto NI = pGraph->BegNI(); NI < pGraph->EndNI(); NI++)
		pOut->SetNDat(NI.GetId(),NI.GetDat().Val);

	return pOut;
}

// Test edge data sorting
TEST(TNodeEdgeNet, SortEdgeData) {
  int NNodes = 10000;
  int NEdges = 100000;

  TPt <TNodeEdgeNet<TInt, TInt> > Net;
  TPt <TNodeEdgeNet<TInt, TInt> > Net1;
  TPt <TNodeEdgeNet<TInt, TInt> > Net2;
  int i;
  int n;
  int x,y;
  bool Sorted;
  int Min;
  int Value;

  Net = TNodeEdgeNet<TInt, TInt>::New();
  EXPECT_EQ(1,Net->Empty());

  // create the nodes with node data x*x % NNodes
  for (i = 0; i < NNodes; i++) {
    x = (i*13) % NNodes;
    Net->AddNode(x, (x*x) % NNodes);
  }
  EXPECT_EQ(0,Net->Empty());
  EXPECT_EQ(NNodes,Net->GetNodes());

  // create random edges with edge data x*y % NEdges
  for (i = 0; i < NEdges; i++) {
    x = (long) (drand48() * NNodes);
    y = (long) (drand48() * NNodes);
    n = Net->AddEdge(x, y, (i*37) % NEdges, (x*y) % NEdges);
  }

  EXPECT_EQ(NEdges,Net->GetEdges());

  EXPECT_EQ(0,Net->Empty());
  EXPECT_EQ(1,Net->IsOk());

  for (i = 0; i < NNodes; i++) {
    EXPECT_EQ(1,Net->IsNode(i));
  }

  EXPECT_EQ(0,Net->IsNode(NNodes));
  EXPECT_EQ(0,Net->IsNode(NNodes+1));
  EXPECT_EQ(0,Net->IsNode(2*NNodes));

  // test node data
  for (TNodeEdgeNet<TInt, TInt>::TNodeI NI = Net->BegNI(); NI < Net->EndNI(); NI++) {
    EXPECT_EQ((NI.GetId()*NI.GetId()) % NNodes, Net->GetNDat(NI.GetId()));
  }

  // test edge data
  for (TNodeEdgeNet<TInt, TInt>::TEdgeI EI = Net->BegEI(); EI < Net->EndEI(); EI++) {
    EXPECT_EQ((EI.GetSrcNId()*EI.GetDstNId()) % NEdges, Net->GetEDat(EI.GetId()));
  }

  // test sorting of edge IDs (unsorted)
  Min = -1;
  Sorted = true;
  for (TNodeEdgeNet<TInt, TInt>::TEdgeI EI = Net->BegEI(); EI < Net->EndEI(); EI++) {
    Value = EI.GetId();
    if (Min > Value) {
      Sorted = false;
    }
    Min = Value;
  }
  EXPECT_EQ(false,Sorted);

  // sort the nodes by edge IDs (sorted)
  Net->SortEIdById();

  // test sorting of edge IDs
  Min = -1;
  Sorted = true;
  for (TNodeEdgeNet<TInt, TInt>::TEdgeI EI = Net->BegEI(); EI < Net->EndEI(); EI++) {
    Value = EI.GetId();
    if (Min > Value) {
      Sorted = false;
    }
    Min = Value;
  }
  EXPECT_EQ(true,Sorted);

  // test sorting of edge data (unsorted)
  Min = -1;
  Sorted = true;
  for (TNodeEdgeNet<TInt, TInt>::TEdgeI EI = Net->BegEI(); EI < Net->EndEI(); EI++) {
    Value = Net->GetEDat(EI.GetId());
    if (Min > Value) {
      Sorted = false;
    }
    Min = Value;
  }
  EXPECT_EQ(false,Sorted);

  // sort the nodes by edge data
  Net->SortEIdByDat();

  // test sorting of edge data (sorted)
  Min = -1;
//.........这里部分代码省略.........

// Test update edge data
TEST(TNodeEdgeNet, UpdateEdgeData) {
  int NNodes = 10000;
  int NEdges = 100000;

  TPt <TNodeEdgeNet<TInt, TInt> > Net;
  TPt <TNodeEdgeNet<TInt, TInt> > Net1;
  TPt <TNodeEdgeNet<TInt, TInt> > Net2;
  int i;
  int n;
  int NCount;
  int x,y;

  Net = TNodeEdgeNet<TInt, TInt>::New();
  EXPECT_EQ(1,Net->Empty());

  // create the nodes
  for (i = 0; i < NNodes; i++) {
    Net->AddNode(i);
  }
  EXPECT_EQ(0,Net->Empty());
  EXPECT_EQ(NNodes,Net->GetNodes());

  // create random edges and edge data x+y+10
  NCount = NEdges;
  while (NCount > 0) {
    x = (long) (drand48() * NNodes);
    y = (long) (drand48() * NNodes);
    n = Net->AddEdge(x, y, -1, x+y+10);
    // printf("0a %d %d %d\n",x,y,n);
    NCount--;
  }

  EXPECT_EQ(NEdges,Net->GetEdges());

  EXPECT_EQ(0,Net->Empty());
  EXPECT_EQ(1,Net->IsOk());

  for (i = 0; i < NNodes; i++) {
    EXPECT_EQ(1,Net->IsNode(i));
  }

  EXPECT_EQ(0,Net->IsNode(NNodes));
  EXPECT_EQ(0,Net->IsNode(NNodes+1));
  EXPECT_EQ(0,Net->IsNode(2*NNodes));

  // add data to nodes, square of node ID
  for (TNodeEdgeNet<TInt, TInt>::TNodeI NI = Net->BegNI(); NI < Net->EndNI(); NI++) {
    Net->SetNDat(NI.GetId(), NI.GetId()*NI.GetId());
  }

  // test node data
  for (TNodeEdgeNet<TInt, TInt>::TNodeI NI = Net->BegNI(); NI < Net->EndNI(); NI++) {
    EXPECT_EQ(NI.GetId()*NI.GetId(), Net->GetNDat(NI.GetId()));
  }

  // verify edge data, x+y+10
  for (TNodeEdgeNet<TInt, TInt>::TEdgeI EI = Net->BegEI(); EI < Net->EndEI(); EI++) {
    EXPECT_EQ(EI.GetSrcNId()+EI.GetDstNId()+10, Net->GetEDat(EI.GetId()));
  }

  // update edge data, x+y+5
  for (TNodeEdgeNet<TInt, TInt>::TEdgeI EI = Net->BegEI(); EI < Net->EndEI(); EI++) {
    Net->SetEDat(EI.GetId(),EI.GetSrcNId()+EI.GetDstNId()+5);
  }

  // verify edge data, x+y+5
  for (TNodeEdgeNet<TInt, TInt>::TEdgeI EI = Net->BegEI(); EI < Net->EndEI(); EI++) {
    EXPECT_EQ(EI.GetSrcNId()+EI.GetDstNId()+5, Net->GetEDat(EI.GetId()));
  }

  // test node data again
  for (TNodeEdgeNet<TInt, TInt>::TNodeI NI = Net->BegNI(); NI < Net->EndNI(); NI++) {
    EXPECT_EQ(NI.GetId()*NI.GetId(), Net->GetNDat(NI.GetId()));
  }
}

// Test update edge data
void UpdateEdgeData() {
  int NNodes = 10000;
  int NEdges = 100000;

  TPt <TNodeEDatNet<TInt, TInt> > Net;
  TPt <TNodeEDatNet<TInt, TInt> > Net1;
  TPt <TNodeEDatNet<TInt, TInt> > Net2;
  int i;
  int n;
  int NCount;
  int x,y;
  bool t;
  int SrcNId;
  int DstNId;
  int EdgeDat;
  int Value;
  bool ok;

  Net = TNodeEDatNet<TInt, TInt>::New();
  t = Net->Empty();

  // create the nodes
  for (i = 0; i < NNodes; i++) {
    Net->AddNode(i);
  }
  t = Net->Empty();
  n = Net->GetNodes();

  // create random edges and edge data x+y+10
  NCount = NEdges;
  while (NCount > 0) {
    x = (long) (drand48() * NNodes);
    y = (long) (drand48() * NNodes);
    // Net->GetEdges() is not correct for the loops (x == y),
    // skip the loops in this test
    if (x != y  &&  !Net->IsEdge(x,y)) {
      n = Net->AddEdge(x, y, x+y+10);
      NCount--;
    }
  }
  PrintNStats("UpdateEdgeData:Net", Net);

  // verify edge data, x+y+10
  ok = true;
  for (TNodeEDatNet<TInt, TInt>::TEdgeI EI = Net->BegEI(); EI < Net->EndEI(); EI++) {
    SrcNId = EI.GetSrcNId();
    DstNId = EI.GetDstNId();
    EdgeDat = Net->GetEDat(SrcNId, DstNId);
    Value = SrcNId+DstNId+10;
    if (EdgeDat != Value) {
      ok = false;
    }
  }
  printf("network UpdateEdgeData:Net, status1 %s\n", (ok == true) ? "ok" : "ERROR");

  // update edge data, x+y+5
  for (TNodeEDatNet<TInt, TInt>::TEdgeI EI = Net->BegEI(); EI < Net->EndEI(); EI++) {
    Net->SetEDat(EI.GetSrcNId(),EI.GetDstNId(),EI.GetSrcNId()+EI.GetDstNId()+5);
  }

  // verify edge data, x+y+5
  ok = true;
  for (TNodeEDatNet<TInt, TInt>::TEdgeI EI = Net->BegEI(); EI < Net->EndEI(); EI++) {
    SrcNId = EI.GetSrcNId();
    DstNId = EI.GetDstNId();
    EdgeDat = Net->GetEDat(SrcNId, DstNId);
    Value = SrcNId+DstNId+5;
    if (EdgeDat != Value) {
      ok = false;
    }
  }
  printf("network UpdateEdgeData:Net, status2 %s\n", (ok == true) ? "ok" : "ERROR");
}