Example #1
0
void    KPCA::compPrimalEnd ()
{
    if (featureCount != dim)
        retinThrowException("Wrong number of features");
    for (size_t i=0;i<featureDim;i++)
        primalMean[i] /= dim;
    for (size_t j=0;j<eigenCount;j++)
        primalValues[j] = (float)(eigens[firstEigen+j].getValue() / dim);
}
Example #2
0
 void SparseVlatCluster::setEigenDecomposition(const float* eigenVectors , const float* eigenValues, size_t vectorsDim, size_t vectorsSize){
     if (vectorsDim != vectorsSize)
             retinThrowException("Not square matrix");
     if (vectorsDim != getTensorDim(1))
             retinThrowException2("Invalid dim %d != %d", vectorsDim, getTensorDim(1));
     
     U.resize(vectorsDim*vectorsDim);
     L.resize(vectorsDim);
     memcpy(&U[0], eigenVectors, vectorsDim*vectorsDim * sizeof(float));
     memcpy(&L[0], eigenValues, vectorsDim * sizeof(float));
 }
Example #3
0
void    KPCA::compPrimalBegin(size_t featureDim_,size_t firstEigen_,size_t eigenCount_)
{
    featureCount = 0;
    featureDim = featureDim_;
    firstEigen = firstEigen_;
    eigenCount = eigenCount_;
    if (firstEigen+eigenCount > eigens.size())
        retinThrowException("Invalid eigen dims");
    primalFeature.resize(featureDim);
    primalMean.resize(featureDim);
    primalValues.resize(eigenCount);
    primalVectors.resize(featureDim*eigenCount);

}
Example #4
0
FeatureRef StandardPcaVlatBuilder::getVlat(string & format){
    FeatureRef vlat;
    size_t dim = getDim(format);
    vlat = boost::make_shared<Feature>(dim);
    float * data = vlat->data();
    
    for(size_t i = 0 ; i < clusters.size(); i++){
        FeatureRef subVlat = clusters[i]->getData(format);
        memcpy(data, subVlat->data(), subVlat->dim()*sizeof(float));
        data += subVlat->dim();
        if((size_t)(data - vlat->data()) > dim)
            retinThrowException("StandardPcaVlatCluster::getVlat => data - vlat->data() > dim");
    }
    return vlat;
}
Example #5
0
void StandardPcaVlatCluster::add(const float * f, size_t dim){
    if(dim != dimPrim)
        retinThrowException("StandardPcaVlatCluster::add => dim != dimPrim");
    
    counter++;
    
    for(size_t i = 0 ; i<dimPrim ; i++)
    {
        (*featc)(i,0) = f[i] - (*meanPrim)(i);
        
    }

    for (size_t k = 0; k < dimPrim; k++) {
        (featDual->data())[k] = vector_ps_double(featc->data(), proj->data()+k*dimPrim, dimPrim);
    }

    if(whitening)
        vector_mul_double(featDual->data(), invsqrtvar->data(), dimPrim);

    if(degre == 1)
        vector_add_double(vlat->data(), featDual->data(), dimDual);
    else
        matrix_Cpaat_double(vlat->data(), featDual->data(), dimDual);
}