/**
* Exclude i th sample where i is index stored in @param index
* from @param vin, @param phenotypeNameInOrder, @param phenotypeInOrder
* and @param cov
* @return 0 if succeed
*/
int excludeSamplesByIndex(const std::vector<int>& index, GenotypeExtractor* ge,
std::vector<std::string>* phenotypeNameInOrder,
std::vector<double>* phenotypeInOrder, Matrix* cov) {
if (!ge || !phenotypeNameInOrder || !phenotypeInOrder || !cov) {
return -1;
}
ge->excludePeople((*phenotypeNameInOrder), index);
removeByIndex(index, phenotypeNameInOrder);
removeByIndex(index, phenotypeInOrder);
removeByRowIndex(index, cov);
return 0;
}
int TextMatrix::keepCol(const std::vector<std::string>& name) {
const int nc = ncol();
const int nr = nrow();
std::vector<int> indexToRemove;
std::set<std::string> keep;
makeSet(name, &keep);
for (int i = 0; i < nc; ++i) {
if (keep.count(colName[i])) continue;
indexToRemove.push_back(i);
}
removeByIndex(indexToRemove, &colName);
for (int i = 0; i < nr; ++i) {
removeByIndex(indexToRemove, &mat[i]);
}
return 0;
}
int DataLoader::useSexAsCovariate() {
std::vector<int> index; // mark missing samples
int numMissing = findMissingSex(sex, &index);
logger->info("Exclude %d samples with missing sex", numMissing);
removeByIndex(index, &sex);
phenotype.dropRow(index);
covariate.dropRow(index);
covariate.appendCol(sex, "Sex");
// excludeSamplesByIndex(index, &ge, &phenotypeNameInOrder, &phenotypeInOrder,
// &covariate);
// // appendToMatrix("Sex", sex, &covariate);
return 0;
}
void makeBasicScheduling(Core* core, List* alreadyQueue, int policy)
{
Job* job;
switch (policy)
{
case ROUND_ROB:
job = (Job*) get(*alreadyQueue, 0)->value;
removeByIndex(alreadyQueue, 0);
break;
default:
/*obtém o job que mais atendeu o critério de escalonamento*/
job = getGreatestCriterionJob(alreadyQueue);
break;
}
//if(job != NULL)
assignToCore(core, job);
}
// -------------------------------------------------------
//
// -------------------------------------------------------
void ScalingAction::update(SpriteArray& array,float dt,ActionEventBuffer& buffer) {
if (_buffer.size > 0) {
// move
for (int i = 0; i < _buffer.size; ++i) {
array.scale(_ids[i], tweening::interpolate(_tweeningTypes[i], _startScale[i], _endScale[i], _timers[i], _ttl[i]));
_timers[i] += dt;
if ( _timers[i] >= _ttl[i] ) {
if ( _modes[i] < 0 ) {
_timers[i] = 0.0f;
}
else if ( _modes[i] == 0 ) {
array.scale(_ids[i],_endScale[i]);
buffer.add(_ids[i], AT_SCALE, array.getType(_ids[i]));
removeByIndex(i);
}
else {
--_modes[i];
_timers[i] = 0.0f;
}
}
}
}
}
void copyRemoveByIndex(std::vector<T>& vals,
std::vector<T>& newVals,
const std::tr1::unordered_set<size_t> &indices) {
copyByIndex(vals, newVals, indices);
removeByIndex(vals, indices);
}
