JNIEXPORT jobject JNICALL Java_retin_feature_vlat_SparseVlatBuilder_runNativeGenerator
(JNIEnv *env, jobject thisObject, jobject nativePointerObj, jstring keyObj, jint degre, jstring formatObj){
RETIN_JAVA_METHOD_BEGIN
JavaEnv je(env);
string key = je.createString(keyObj);
FeatureListRef centers = je.getDocumentField<FeatureList> (thisObject,"centers");
vector<FeatureListRef> tensors;
je.getDocumentField<FeatureList> (tensors,thisObject,"tensors");
vector<FloatMatrixRef> Ls; je.getDocumentField<FloatMatrix> (Ls,thisObject,"Ls");
vector<FloatMatrixRef> Ps; je.getDocumentField<FloatMatrix> (Ps,thisObject,"Ps");
string format = je.createString(formatObj);
NativePointerRef instance = je.createDocument<NativePointer>(nativePointerObj);
NativeDocumentGenerator *ngd = instance->getPointerAs<NativeDocumentGenerator>();
FeatureListRef features = boost::static_pointer_cast<FeatureList>(ngd->computeDocument(key));
SparseVlatBuilder vlat(degre,centers->size(),centers->dim());
vlat.setCenters(centers->data(),centers->size(),centers->dim());
for (int d=0;d<degre;d++) {
FeatureListRef tensor = tensors[d];
vlat.setMeanTensors(d+1,tensor->data(),tensor->size(),tensor->dim());
}
for (int i=0;i<Ls.size();i++) {
vlat.setEigenDecomposition(i, Ps[i]->data(), Ls[i]->data(), Ps[i]->vectorSize(), Ps[i]->vectorCount());
}
vlat.setSparsityOn(je.getField<jint>(thisObject,"sparsityOn"));
vlat.setSparsityStrategy(je.getField<jint>(thisObject,"sparsityStrategy"));
vlat.setDimSparsity(je.getField<jint>(thisObject,"sparsityDim"));
vlat.setEnergySparsity(je.getField<jfloat>(thisObject,"sparsityEnergy"));
vlat.process(features->data(),features->size(),features->dim());
FeatureRef outputRef = boost::make_shared<Feature>(vlat.getVlatDim(format));
vlat.getVlat(outputRef->data(),format);
return je.createObject (outputRef);
RETIN_JAVA_METHOD_END
return NULL;
}
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;
}
void StandardPcaVlatCluster::add(FeatureRef feat){
add(feat->data(), feat->dim());
}
