//! 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;
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(true,Sorted);
// 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);
// 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 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 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");
}
