void ModelComputationMTStaticSchedule::ThreadRun(int64 taskIdBegin, int64 taskIdEnd) {
for (int64 taskId = taskIdBegin; taskId < taskIdEnd; ++taskId) {
int uid1 = static_cast<int>((Math::Sqrt(8.0 * taskId + 1) + 1) / 2);
int uid2 = taskId - (int64)uid1*(uid1-1)/2;
const UserVec& uv1 = mTrainData->GetUserVector(uid1);
const UserVec& uv2 = mTrainData->GetUserVector(uid2);
float sim = ComputeSimilarity(uv1, uv2);
mModel->Put(uid1, uid2, sim);
}
}
void ModelComputationST::ComputeModel(const TrainOption *option, RatingMatUsers *trainData,
Model *model) {
mTrainOption = option;
mTrainData = trainData;
mModel = model;
AdjustRating();
for (int uid1 = 0; uid1 < mTrainData->NumUser(); ++uid1) {
const UserVec& uv1 = trainData->GetUserVector(uid1);
for (int uid2 = uid1 + 1; uid2 < mTrainData->NumUser(); ++uid2) {
const UserVec& uv2 = trainData->GetUserVector(uid2);
float sim = ComputeSimilarity(uv1, uv2);
mModel->DirectPut(uid2, uid1, sim);
}
}
}
void ModelComputationMT::WorkerRun() {
while (true) {
TaskBundle *currentBundle = mScheduler->WorkerGetTask();
if (currentBundle == nullptr) break;
for (int i = 0; i < currentBundle->size(); ++i) {
Task& task = currentBundle->at(i);
const UserVec& uv1 = mTrainData->GetUserVector(task.uid1);
const UserVec& uv2 = mTrainData->GetUserVector(task.uid2);
task.sim = ComputeSimilarity(uv1, uv2);
mModel->DirectPut(task.uid2, task.uid1, task.sim);
}
mScheduler->WorkerPutTask(currentBundle);
}
mScheduler->WorkerDone();
}
void LocalGeometryRef::ComputeSimilarityMatrix(char dis, int k)
{
this->Normalize();
//initialize similarity matrix
this->similarity_matrix.set_size(this->num_row, this->num_row);
this->similarity_matrix.fill(0);
//searching for the k nearest neighbours
//std::vector<std::vector< std::pair<unsigned int, double> > > kNeighborIDs;
//kNeighborIDs = this->KnnSearch(k);
//starting compute similarity matrix
for(int i = 0; i < this->num_row; i++)
{
for(int j = i + 1; j < this->num_row; j++)
{
vnl_vector<double> dt1 = this->nor_data_matrix.get_row(i);
vnl_vector<double> dt2 = this->nor_data_matrix.get_row(j);
double distance = ComputeSimilarity(dt1,dt2,dis);
similarity_matrix(i,j) = distance;
similarity_matrix(j,i) = distance;
}
}
}
