void TGreedyAlg::runGreedyAlgorithm() {
outputGraph = TKColourNet::New();
for (THash<TInt, TNodeInfo>::TIter NI = nodeNmH.BegI(); NI < nodeNmH.EndI(); NI++) {
outputGraph->AddNode(NI.GetKey(), TKColourNode());
printf("Added node %d to output graph\n", (int) NI.GetKey());
}
// for each node i
for (THash<TInt, TNodeInfo>::TIter NI = nodeNmH.BegI(); NI < nodeNmH.EndI(); NI++) {
int nodeI = NI.GetKey();
printf("***** Considering node i: %d *****\n", nodeI);
// initialise unaccounted cascades U
TVec<TCascade> cascades = cascadeV;
// initialise parental neighbourhood
TIntV parentalNeighbourhood;
bool uselessUnaccountedCasacdesLeft = false;
while ((cascades.Len() != 0) && (!uselessUnaccountedCasacdesLeft)) {
// printf("%d Casacdes left...\n", cascades.Len());
// find node j that could possible have infected node i that has been observed for largest number of cascades
int argmax = -1;
int maxNoCascades = 0;
bool areUnaccountedCascadesUseless = true;
for (THash<TInt, TNodeInfo>::TIter LNI = nodeNmH.BegI(); LNI < nodeNmH.EndI(); LNI++) {
int nodeJ = LNI.GetKey();
// printf("nodeJ: %d\n", nodeJ);
int countPotentialNoCascades = 0;
if (nodeI != nodeJ) {
for (int c = 0; c < cascades.Len(); c++) {
TCascade cascade = cascades[c];
if (cascade.IsNode(nodeJ) && cascade.IsNode(nodeI)) {
// if (cascade.GetTm(nodeI) > cascade.GetTm(nodeJ)) {
if (cascade.GetTm(nodeJ) == (cascade.GetTm(nodeI) - 1)) {
countPotentialNoCascades++;
}
}
}
if (countPotentialNoCascades > maxNoCascades) {
maxNoCascades = countPotentialNoCascades;
argmax = nodeJ;
areUnaccountedCascadesUseless = false;
}
else {
areUnaccountedCascadesUseless = areUnaccountedCascadesUseless && true;
}
}
}
if (areUnaccountedCascadesUseless) {
uselessUnaccountedCasacdesLeft = true;
}
if (argmax != -1) {
// printf("argmax (k) = %d, noCasacdesAppearedIn = %d\n", argmax, maxNoCascades);
// add arg max (k) to the set of parental neighbours
parentalNeighbourhood.Add(argmax);
}
// remove the cascades which k belongs to
TIntV cascadesToRemove;
for (int c = 0; c < cascades.Len(); c++) {
TCascade cascade = cascades[c];
if (cascade.IsNode(argmax) && cascade.IsNode(nodeI)) {
if (cascade.GetTm(nodeI) > cascade.GetTm(argmax)) {
cascadesToRemove.Add(c);
}
}
}
cascadesToRemove.Sort();
// printf("cascadesToRemove: ");
for (int i = 0; i < cascadesToRemove.Len(); i++) {
// printf("%d, ", (int) cascadesToRemove[i]);
cascades.Del(cascadesToRemove[i]-i);
}
// printf("\n");
}
// add edges from node i to each of parent
for (int i = 0; i < parentalNeighbourhood.Len(); i++) {
int srcNodeId = parentalNeighbourhood[i];
int dstNodeId = nodeI;
outputGraph->AddEdge(srcNodeId, dstNodeId);
// printf("##### Added Edge: %d -> %d #####\n", srcNodeId, dstNodeId);
}
}
}
void TNetInfBs::GenNoisyCascade(TCascade& C, const int& TModel, const double &window, TIntPrIntH& EdgesUsed,
const double& std_waiting_time, const double& std_beta,
const double& PercRndNodes, const double& PercRndRemoval) {
TIntPrIntH EdgesUsedC; // list of used edges for a single cascade
GenCascade(C, TModel, window, EdgesUsedC, delta, std_waiting_time, std_beta);
// store keys
TIntV KeyV;
C.NIdHitH.GetKeyV(KeyV);
// store first and last time
double tbeg = TFlt::Mx, tend = TFlt::Mn;
for (int i=0; i < KeyV.Len(); i++) {
if (tbeg > C.NIdHitH.GetDat(KeyV[i]).Tm) tbeg = C.NIdHitH.GetDat(KeyV[i]).Tm;
if (tend < C.NIdHitH.GetDat(KeyV[i]).Tm) tend = C.NIdHitH.GetDat(KeyV[i]).Tm;
}
// remove PercRndRemoval% of the nodes of the cascades
if (PercRndRemoval > 0) {
for (int i=KeyV.Len()-1; i >= 0; i--) {
if (TFlt::Rnd.GetUniDev() < PercRndRemoval) {
// remove from the EdgesUsedC the ones affected by the removal
TIntPrV EdgesToRemove;
for (TIntPrIntH::TIter EI = EdgesUsedC.BegI(); EI < EdgesUsedC.EndI(); EI++) {
if ( (KeyV[i]==EI.GetKey().Val1 && C.IsNode(EI.GetKey().Val2) && C.GetTm(KeyV[i]) < C.GetTm(EI.GetKey().Val2)) ||
(KeyV[i]==EI.GetKey().Val2 && C.IsNode(EI.GetKey().Val1) && C.GetTm(KeyV[i]) > C.GetTm(EI.GetKey().Val1)) ) {
EI.GetDat() = EI.GetDat()-1;
if (EI.GetDat()==0)
EdgesToRemove.Add(EI.GetKey());
}
}
for (int er=0; er<EdgesToRemove.Len(); er++)
EdgesUsedC.DelKey(EdgesToRemove[er]);
C.Del(KeyV[i]);
}
}
// defrag the hash table, otherwise other functions can crash
C.NIdHitH.Defrag();
}
// Substitute PercRndNodes% of the nodes for a random node at a random time
if (PercRndNodes > 0) {
for (int i=KeyV.Len()-1; i >= 0; i--) {
if (TFlt::Rnd.GetUniDev() < PercRndNodes) {
// remove from the EdgesUsedC the ones affected by the change
TIntPrV EdgesToRemove;
for (TIntPrIntH::TIter EI = EdgesUsedC.BegI(); EI < EdgesUsedC.EndI(); EI++) {
if ( (KeyV[i]==EI.GetKey().Val1 && C.IsNode(EI.GetKey().Val2) && C.GetTm(KeyV[i]) < C.GetTm(EI.GetKey().Val2)) ||
(KeyV[i]==EI.GetKey().Val2 && C.IsNode(EI.GetKey().Val1) && C.GetTm(KeyV[i]) > C.GetTm(EI.GetKey().Val1)) ) {
EI.GetDat() = EI.GetDat()-1;
if (EI.GetDat()==0)
EdgesToRemove.Add(EI.GetKey());
}
}
for (int er=0; er<EdgesToRemove.Len(); er++)
EdgesUsedC.DelKey(EdgesToRemove[er]);
printf("Old node n:%d t:%f --", KeyV[i].Val, C.GetTm(KeyV[i]));
C.Del(KeyV[i]);
// not repeating a label
double tnew = 0;
int keynew = -1;
do {
tnew = tbeg + TFlt::Rnd.GetUniDev()*(tend-tbeg);
keynew = Graph->GetRndNId();
} while (KeyV.IsIn(keynew));
printf("New node n:%d t:%f\n", keynew, tnew);
C.Add(keynew, tnew);
KeyV.Add(keynew);
}
}
}
// add to the aggregate list (EdgesUsed)
EdgesUsedC.Defrag();
for (int i=0; i<EdgesUsedC.Len(); i++) {
if (!EdgesUsed.IsKey(EdgesUsedC.GetKey(i))) EdgesUsed.AddDat(EdgesUsedC.GetKey(i)) = 0;
EdgesUsed.GetDat(EdgesUsedC.GetKey(i)) += 1;
}
}
