void KPCA::compPrimalAdd(const float* feature,size_t featureDim_,size_t firstEigen_,size_t eigenCount_)
{
if (featureDim == 0)
compPrimalBegin(featureDim_,firstEigen_,eigenCount_);
if (featureDim != featureDim_)
retinThrowException2("Bad featureDim %d != %d",featureDim_,featureDim);
if (firstEigen != firstEigen_)
retinThrowException2("Bad firstEigen %d != %d",firstEigen_,firstEigen);
if (eigenCount != eigenCount_)
retinThrowException2("Bad eigenCount %d != %d",eigenCount_,eigenCount);
if (featureCount > dim)
retinThrowException1("Wrong number of features (%ld expected)",dim);
vector_add_float(&primalMean[0],feature,featureDim_);
for (size_t j=0;j<eigenCount;j++) {
double eig = 1.0 / sqrt(eigens[firstEigen+j].getValue());
const double* eigv = eigens[firstEigen+j].getVector();
vector_addm_float(&primalVectors[j*featureDim],eigv[featureCount] * eig,feature,featureDim);
}
featureCount ++;
}
size_t SparseVlatCluster::getVlat(float* buf,const std::string& format) const{
size_t featureDim = getTensorDim(1);
size_t vlatDim = getTensorDim(mainOrder);
vector<float> sparseVlat(vlatDim);
vector<int> sparseMask;
if (buf){
memcpy(&sparseVlat[0], &vlat[0], vlatDim*sizeof(float));
vector<pair<size_t, float> > sortTable;
if(mainOrder == 1 || sparsityOn == SparseVlatCluster::sparsityOnDiag){
sortTable.reserve(featureDim);
sparseMask.reserve(featureDim);
for(size_t i = 0 ; i < featureDim ; i++){
sortTable[i].first = i;
sortTable[i].second = varDual[i];
}
sort(sortTable.begin(), sortTable.end(), myfunction);
}
else if(sparsityOn == SparseVlatCluster::sparsityOnFull){
sortTable.reserve(featureDim*featureDim);
sparseMask.reserve(featureDim*featureDim);
for(size_t i = 0 ; i < featureDim*featureDim ; i++){
sortTable[i].first = i;
sortTable[i].second = varDual[i];
}
sort(sortTable.begin(), sortTable.end(), myfunction);
}
if(sparsityStrategy == SparseVlatCluster::sparsityStrategyDim){
for(size_t i = 0 ; i < sparsityDim ; i++)
sparseMask[sortTable[i].first] = 1;
for(size_t i = sparsityDim ; i < sortTable.size() ; i++)
sparseMask[sortTable[i].first] = 0;
}
else if(sparsityStrategy == SparseVlatCluster::sparsityStrategyEnergy){
float sumVar = 0;
for(size_t i = 0 ; i < sortTable.size() ; i++)
sumVar += varDual[i];
size_t i;
float sum;
for(i=0, sum = 0; i < sortTable.size() && sum<sumVar*sparsityEnergy ; i++){
sparseMask[sortTable[i].first] = 1;
sum += sortTable[i].second;
}
for( ; i < sortTable.size() ; i++)
sparseMask[sortTable[i].first] = 0;
}
}
if (mainOrder == 1) {
if (buf){
memcpy(&sparseVlat[0], &vlat[0], featureDim*sizeof(float));
for(size_t i = 0 ; i < featureDim; i++){
if(sparseMask[i] == 0){
sparseVlat[i] = 0.0f;
}
}
memcpy(buf, &sparseVlat[0], featureDim*sizeof(float));
}
return featureDim;
}
else if (mainOrder == 2) {
if (buf){
if(sparsityOn == SparseVlatCluster::sparsityOnDiag){
memcpy(&sparseVlat[0], &vlat[0], vlatDim*sizeof(float));
for(size_t i = 0 ; i < featureDim; i++){
if(sparseMask[i] == 0){
for(size_t j = 0 ; j < featureDim ; j++){
sparseVlat[j+featureDim*i] = 0.0f;
sparseVlat[i+featureDim*j] = 0.0f;
}
}
}
}
else if(sparsityOn == SparseVlatCluster::sparsityOnFull){
memcpy(&sparseVlat[0], &vlat[0], vlatDim*sizeof(float));
for(size_t i = 0 ; i < vlatDim; i++){
if(sparseMask[i] == 0){
sparseVlat[i] = 0.0f;
}
}
}
for(size_t i = 0; i < featureDim ; i++)
sparseVlat[i*featureDim + i] -= counter*L[i];
}
if (format == "full") {
if (buf)
memcpy(buf,&sparseVlat[0],featureDim*featureDim*sizeof(float));
return featureDim*featureDim;
}
else if (format == "LD") {
if (buf) {
for (size_t i=0;i<featureDim;i++) {
for (size_t j=i;j<featureDim;j++)
*buf++ = sparseVlat[i+j*featureDim];
}
}
return (featureDim*(featureDim+1))/2;
}
else if (format == "L") {
if (buf) {
for (size_t i=0;i<featureDim;i++) {
for (size_t j=i+1;j<featureDim;j++)
*buf++ = sparseVlat[i+j*featureDim];
}
}
return (featureDim*(featureDim-1))/2;
}
else {
retinThrowException1("Unsupported format %s", format.c_str());
}
}
else {
retinThrowException1("Unsupported order %d", mainOrder);
}
}
PackedVlatBuilder::PackedVlatBuilder(size_t order,size_t dictSize,size_t featureDim)
: VlatBuilder<PackedVlatCluster>(order,dictSize,featureDim)
{
if (order != 2)
retinThrowException1("Invalid order %d for PackedVlat",order);
}
