void ReadGraph(TStr& InFile, bool& Directed, bool& Weighted, bool& Verbose, PWNet& InNet) {
TFIn FIn(InFile);
int64 LineCnt = 0;
try {
while (!FIn.Eof()) {
TStr Ln;
FIn.GetNextLn(Ln);
TStr Line, Comment;
Ln.SplitOnCh(Line,'#',Comment);
TStrV Tokens;
Line.SplitOnWs(Tokens);
if(Tokens.Len()<2){ continue; }
int64 SrcNId = Tokens[0].GetInt();
int64 DstNId = Tokens[1].GetInt();
double Weight = 1.0;
if (Weighted) { Weight = Tokens[2].GetFlt(); }
if (!InNet->IsNode(SrcNId)){ InNet->AddNode(SrcNId); }
if (!InNet->IsNode(DstNId)){ InNet->AddNode(DstNId); }
InNet->AddEdge(SrcNId,DstNId,Weight);
if (!Directed){ InNet->AddEdge(DstNId,SrcNId,Weight); }
LineCnt++;
}
if (Verbose) { printf("Read %lld lines from %s\n", (long long)LineCnt, InFile.CStr()); }
} catch (PExcept Except) {
if (Verbose) {
printf("Read %lld lines from %s, then %s\n", (long long)LineCnt, InFile.CStr(),
Except->GetStr().CStr());
}
}
}
void node2vec(PNGraph& InNet, double& ParamP, double& ParamQ, int& Dimensions,
int& WalkLen, int& NumWalks, int& WinSize, int& Iter, bool& Verbose,
bool& OutputWalks, TVVec<TInt, int64>& WalksVV, TIntFltVH& EmbeddingsHV) {
PWNet NewNet = PWNet::New();
for (TNGraph::TEdgeI EI = InNet->BegEI(); EI < InNet->EndEI(); EI++) {
if (!NewNet->IsNode(EI.GetSrcNId())) { NewNet->AddNode(EI.GetSrcNId()); }
if (!NewNet->IsNode(EI.GetDstNId())) { NewNet->AddNode(EI.GetDstNId()); }
NewNet->AddEdge(EI.GetSrcNId(), EI.GetDstNId(), 1.0);
}
node2vec(NewNet, ParamP, ParamQ, Dimensions, WalkLen, NumWalks, WinSize, Iter,
Verbose, OutputWalks, WalksVV, EmbeddingsHV);
}
void node2vec(PNEANet& InNet, double& ParamP, double& ParamQ,
int& Dimensions, int& WalkLen, int& NumWalks, int& WinSize, int& Iter, bool& Verbose,
TIntFltVH& EmbeddingsHV) {
PWNet NewNet = PWNet::New();
for (TNEANet::TEdgeI EI = InNet->BegEI(); EI < InNet->EndEI(); EI++) {
if (!NewNet->IsNode(EI.GetSrcNId())) { NewNet->AddNode(EI.GetSrcNId()); }
if (!NewNet->IsNode(EI.GetDstNId())) { NewNet->AddNode(EI.GetDstNId()); }
NewNet->AddEdge(EI.GetSrcNId(), EI.GetDstNId(), InNet->GetFltAttrDatE(EI,"weight"));
}
node2vec(NewNet, ParamP, ParamQ, Dimensions, WalkLen, NumWalks, WinSize, Iter,
Verbose, EmbeddingsHV);
}
void node2vec(PWNet& InNet, double& ParamP, double& ParamQ, int& Dimensions,
int& WalkLen, int& NumWalks, int& WinSize, int& Iter, bool& Verbose,
bool& OutputWalks, TVVec<TInt, int64>& WalksVV, TIntFltVH& EmbeddingsHV) {
//Preprocess transition probabilities
PreprocessTransitionProbs(InNet, ParamP, ParamQ, Verbose);
TIntV NIdsV;
for (TWNet::TNodeI NI = InNet->BegNI(); NI < InNet->EndNI(); NI++) {
NIdsV.Add(NI.GetId());
}
//Generate random walks
int64 AllWalks = (int64)NumWalks * NIdsV.Len();
WalksVV = TVVec<TInt, int64>(AllWalks,WalkLen);
TRnd Rnd(time(NULL));
int64 WalksDone = 0;
for (int64 i = 0; i < NumWalks; i++) {
NIdsV.Shuffle(Rnd);
#pragma omp parallel for schedule(dynamic)
for (int64 j = 0; j < NIdsV.Len(); j++) {
if ( Verbose && WalksDone%10000 == 0 ) {
printf("\rWalking Progress: %.2lf%%",(double)WalksDone*100/(double)AllWalks);fflush(stdout);
}
TIntV WalkV;
SimulateWalk(InNet, NIdsV[j], WalkLen, Rnd, WalkV);
for (int64 k = 0; k < WalkV.Len(); k++) {
WalksVV.PutXY(i*NIdsV.Len()+j, k, WalkV[k]);
}
WalksDone++;
}
}
if (Verbose) {
printf("\n");
fflush(stdout);
}
//Learning embeddings
if (!OutputWalks) {
LearnEmbeddings(WalksVV, Dimensions, WinSize, Iter, Verbose, EmbeddingsHV);
}
}
