inline void eliminationOperators(SpMat& A, DynamicVector<size_t>& Cset, size_t fnode,
DynamicVector<double>& q, SpMat& P, size_t& P_col, size_t P_row) {
/* Inizializziamo la riga P_row con A.nonZeros(fnode) - 1 non nulli*/
double scalingFactor = 1.0;
/* Riserviamo spazio in ciascuna colonna di P per un adeguato numero
* di elementi. Il -1 c'è perché (il reciproco del)l'elemento in
* diagonale lo mettiamo in q
*/
P.reserve(P_row, A.nonZeros(fnode) - 1);
/* Per ciascuna f-riga prendo gli elementi in ogni c-colonna */
DynamicVector<size_t>::Iterator ccol = Cset.begin();
for (SpMat::Iterator frow = A.begin(fnode); frow != A.end(fnode); ++frow) {
if (frow->index() == fnode) { //Elemento della diagonale
q[P_row] = (1.0 / frow->value()); //Q ha elementi pari al numero di righe di R
scalingFactor = -(q[P_row]);
} else if (ccol != Cset.end()) {
break; //Non ha senso andare avanti se abbiamo finito i ccol
} else if (frow->index() == (*ccol)) {
/* Elemento fuori della diagonale ed è anche un c-colonna */
P.append(P_row, P_col, frow->value());
P_col++;
ccol++;
}
}
P.finalize(P_row); //Finalizziamo la riga P_row
/* Non dimentichiamo di scalare gli elementi della riga corrente
* per -scalingFactor */
for (SpMat::Iterator it = P.begin(P_row); it != P.end(P_row); it++)
it->value() *= -scalingFactor;
}
DynamicVector<Movie> Controller::findMoviesOfTitle(string title)
{
DynamicVector<Movie> list;
for (int i = 0; i < this->repository.movies.size(); i++)
{
if (this->repository.movies[i].title == title)
{
list.add(this->repository.movies[i]);
}
}
return list;
}
DynamicVector<Movie> Controller::findMoviesOfYear(int year)
{
DynamicVector<Movie> list;
for (int i = 0; i < this->repository.movies.size(); i++)
{
if (this->repository.movies[i].year == year)
{
list.add(this->repository.movies[i]);
}
}
return list;
}
void SetCases()
{
std::string error;
Dynamic table = TABLE;
nkit::TableIndex::Ptr index;
nkit::TableIndex::ConstIterator it;
DynamicVector vargs;
vargs.push_back(Dynamic("NEW"));
vargs.push_back(Dynamic(0));
vargs.push_back(Dynamic(true));
vargs.push_back(Dynamic(0));
vargs.push_back(Dynamic(0.0));
COMMON_TABLE_INIT(table);
index = table.CreateIndex("name,name1", &error);
NKIT_TEST_ASSERT_WITH_TEXT(index, error);
NKIT_TEST_ASSERT(table.SetRow(table.height() / 2, vargs));
DynamicVector::iterator vit = vargs.begin();
for (size_t col = 0; vit != vargs.end(); ++vit, ++col)
{
#if defined(MY_TRACE_)
print(*vit, "", false);
std::cout << " <> ";
print(table.GetCellValue(table.height() / 2, col));
#endif // MY_TRACE_
NKIT_TEST_ASSERT(*vit == table.GetCellValue(table.height() / 2, col));
} // for
NKIT_TEST_ASSERT(index->GetEqual(Dynamic("NEW"),Dynamic(0)) != index->end());
}
/* returns a list of random movies from repo, throws OutOfRangeException */
DynamicVector<Movie> Controller::getRandomMovies(int howMany)
{
if (howMany<0 || howMany > this->repository.movies.size())
{
throw OutOfRangeException("Size is " + this->repository.movies.size());
}
DynamicVector<Movie> list;
DynamicVector<Movie> shuffledOriginalList = this->repository.movies.clone();
shuffledOriginalList.shuffle();
for (int i = 0; i < howMany; i++)
{
list.add(shuffledOriginalList[i]);
}
return list;
}
void encodeDynamicVector(float *buffer, size_t componentsCount, size_t count, const GLTFConverterContext& converterContext) {
GLTFOutputStream *outputStream = converterContext._compressionOutputStream;
Real max[32];
Real min[32];
O3DGCStreamType streamType = converterContext.compressionMode == "ascii" ? O3DGC_STREAM_TYPE_ASCII : O3DGC_STREAM_TYPE_BINARY;
DynamicVector dynamicVector;
dynamicVector.SetVectors(buffer);
dynamicVector.SetDimVector(componentsCount);
dynamicVector.SetMax(max);
dynamicVector.SetMin(min);
dynamicVector.SetNVector(count);
dynamicVector.SetStride(componentsCount);
dynamicVector.ComputeMinMax(O3DGC_SC3DMC_MAX_SEP_DIM);//O3DGC_SC3DMC_MAX_ALL_DIMS
DVEncodeParams params;
params.SetQuantBits(componentsCount == 1 ? 11 : 17); //HACK, if that's 1 component it is the TIME and 10 bits is OK
params.SetStreamType(streamType);
DynamicVectorEncoder encoder;
encoder.SetStreamType(streamType);
Timer timer;
timer.Tic();
BinaryStream bstream(componentsCount * count * 16);
encoder.Encode(params, dynamicVector, bstream);
timer.Toc();
outputStream->write((const char*)bstream.GetBuffer(), bstream.GetSize());
/*
if (componentsCount == 4) {
DynamicVector dynamicVector1;
DynamicVectorDecoder decoder;
decoder.DecodeHeader(dynamicVector1, bstream);
dynamicVector1.SetStride(dynamicVector1.GetDimVector());
std::vector<Real> oDV;
std::vector<Real> oDVMin;
std::vector<Real> oDVMax;
oDV.resize(dynamicVector1.GetNVector() * dynamicVector1.GetDimVector());
oDVMin.resize(dynamicVector1.GetDimVector());
oDVMax.resize(dynamicVector1.GetDimVector());
dynamicVector1.SetVectors(& oDV[0]);
dynamicVector1.SetMin(& oDVMin[0]);
dynamicVector1.SetMax(& oDVMax[0]);
decoder.DecodePlayload(dynamicVector1, bstream);
float* dbuffer = (float*)dynamicVector1.GetVectors();
printf("****dump axis-angle. Axis[3] / Angle[1]\n");
for (int i = 0 ; i < count ; i++) {
int offset = i * 4;
printf("[raw]%f %f %f %f [10bits]%f %f %f %f\n",
buffer[offset+0],buffer[offset+1],buffer[offset+2],buffer[offset+3],
dbuffer[offset+0],dbuffer[offset+1],dbuffer[offset+2],dbuffer[offset+3]);
}
}
*/
}
bool test(const DynamicVector<RealType>& params) const {
for (size_t i=0; i<params.size(); i++) {
if ((params[i] < low_) || (params[i] > high_))
return false;
}
return true;
}
bool test(const DynamicVector<RealType>& params) const {
for (size_t i=0; i<params.size(); ++i) {
if (params[i] <= 0.0)
return false;
}
return true;
}
DynamicVector<Movie> Controller::getSortedMoviesByActor()
{
DynamicVector<Movie> clone = this->repository.movies.clone();
for (int i = 0; i < clone.size() - 1; i++)
{
for (int j = i + 1; j < clone.size(); j++)
{
if (clone[i].actor.compare(clone[j].actor)>0)
{
Movie aux = clone[i];
clone[i] = clone[j];
clone[j] = aux;
}
}
}
return clone;
}
DynamicVector<string> AnagramController::anagramsForWord(string word) {
//add the word as the key and the sorted word as value in the dictionary
for (int i = 0; i<repo->getAll().getSize(); i++){
string key = repo->getAll().elementAtIndex(i);
map.addValueAndKey(key, sortWord(key));
}
word = sortWord(word);
DynamicVector<string> elements = DynamicVector<string>();
Node<string, string> *first = map.getNodeForValue(word);
//find the first node that has as value, the desired sorted word and
//add the key to the elements
while (first != NULL && first->getData()->getValue() == word) {
elements.add(first->getData()->getKey());
first = first->getNext();
}
return elements;
}
int ChParallelDataManager::OutputBlazeVector(DynamicVector<real> src, std::string filename) {
const char* numformat = "%.16g";
ChStreamOutAsciiFile stream(filename.c_str());
stream.SetNumFormat(numformat);
for (int i = 0; i < src.size(); i++)
stream << src[i] << "\n";
return 0;
}
inline void eliminationOperators(DMat& A, DynamicVector<size_t>& Cset, size_t fnode,
DynamicVector<double>& q, SpMat& P, size_t& P_col, size_t P_row) {
double scalingFactor = 1.0;
P.reserve(P_row, A.nonZeros(fnode) - 1);
DynamicVector<size_t>::Iterator ccol = Cset.begin();
for (size_t frow = 0; frow < A.rows(); ++frow) {
if (frow == fnode) { //Elemento sulla diagonale
q[P_row] = (1.0 / A(frow, fnode));
scalingFactor = -(q[P_row]);
} else if (ccol != Cset.end()) {
break; //Non ha senso andare avanti se abbiamo finito i ccol
} else if (frow == (*ccol)) {
P.append(P_row, P_col, A(frow, fnode));
P_col++;
ccol++;
}
}
P.finalize(P_row);
for (SpMat::Iterator it = P.begin(P_row); it != P.end(P_row); it++)
it->value() *= -scalingFactor;
}
DynamicVector<Movie> Controller::getSortedMoviesByYearAndGenre()
{
DynamicVector<Movie> clone = this->repository.movies.clone();
for (int i = 0; i < clone.size() - 1; i++)
{
for (int j = i + 1; j < clone.size(); j++)
{
if (clone[i].year > clone[j].year)
{
Movie aux = clone[i];
clone[i] = clone[j];
clone[j] = aux;
}
else if (clone[i].year == clone[j].year && clone[i].genre.compare(clone[j].genre)> 0)
{
Movie aux = clone[i];
clone[i] = clone[j];
clone[j] = aux;
}
}
}
return clone;
}
void DeleteCases()
{
std::string error;
Dynamic table = TABLE;
nkit::TableIndex::Ptr index;
nkit::TableIndex::ConstIterator it;
COMMON_TABLE_INIT(table);
index = table.CreateIndex("name,name1,name3", &error);
// Fail cases tests
NKIT_TEST_ASSERT(index);
NKIT_TEST_ASSERT(index->GetEqual(Dynamic(3), Dynamic(1)) == index->end());
NKIT_TEST_ASSERT(index->GetEqual(Dynamic("A3"), Dynamic(3)) == index->end());
// Good cases tests
for (size_t ops = 0; ops < TABLE_GROW_SIZE; ++ops)
{
DynamicVector vargs;
vargs.push_back(Dynamic("A3"));
vargs.push_back(Dynamic(3));
vargs.push_back(Dynamic(false));
vargs.push_back(Dynamic(1));
vargs.push_back(Dynamic(double(2.0 + ops)));
NKIT_TEST_ASSERT(table.InsertRow(0, vargs));
}
for (size_t ops = 0; ops < TABLE_GROW_SIZE; ++ops)
NKIT_TEST_ASSERT(table.DeleteRow(0));
it = index->GetEqual(Dynamic("A3"), Dynamic(3), Dynamic(1));
NKIT_TEST_ASSERT(it != index->end());
for (; it != index->end(); ++it)
{
#if defined(MY_TRACE_)
print(it[4]);
#endif // MY_TRACE_
}
NKIT_TEST_ASSERT(table == e);
}
void InsertCases()
{
std::string error;
Dynamic table = TABLE;
nkit::TableIndex::Ptr index;
nkit::TableIndex::ConstIterator it;
COMMON_TABLE_INIT(table);
// Fail cases tests
for (size_t ops = 0; ops < TABLE_GROW_SIZE; ++ops) // wrong type
{
DynamicVector vargs;
vargs.push_back(Dynamic(1));
vargs.push_back(Dynamic(3));
vargs.push_back(Dynamic(false));
vargs.push_back(Dynamic(1));
vargs.push_back(Dynamic("name"));
NKIT_TEST_ASSERT(table.InsertRow(0, vargs) == false);
}
NKIT_TEST_ASSERT(table == e);
index = table.CreateIndex("name,name1,name3", &error);
NKIT_TEST_ASSERT(index);
NKIT_TEST_ASSERT(index->GetEqual(Dynamic(3), Dynamic(1)) == index->end());
NKIT_TEST_ASSERT(index->GetEqual(Dynamic("A3"), Dynamic(3)) == index->end());
// Good cases tests
for (size_t ops = 0; ops < TABLE_GROW_SIZE; ++ops)
{
DynamicVector vargs;
vargs.push_back(Dynamic("A3"));
vargs.push_back(Dynamic(3));
vargs.push_back(Dynamic(false));
vargs.push_back(Dynamic(1));
vargs.push_back(Dynamic(double(2.0 + ops)));
NKIT_TEST_ASSERT(table.InsertRow(0, vargs));
}
it = index->GetEqual(Dynamic("A3"), Dynamic(3), Dynamic(1));
NKIT_TEST_ASSERT(it != index->end());
for (; it != index->end(); ++it)
{
#if defined(MY_TRACE_)
print(it[4]);
#endif // MY_TRACE_
}
for (size_t ops = 0; ops < TABLE_GROW_SIZE; ++ops)
{
DynamicVector vargs;
vargs.push_back(Dynamic("A10"));
vargs.push_back(Dynamic(3));
vargs.push_back(Dynamic(false));
vargs.push_back(Dynamic(1));
vargs.push_back(Dynamic(double(1.0 + ops)));
NKIT_TEST_ASSERT(table.InsertRow(table.height() / 2, vargs));
}
it = index->GetEqual(Dynamic("A10"), Dynamic(3), Dynamic(1));
NKIT_TEST_ASSERT(it != index->end());
for (; it != index->end(); ++it)
{
#if defined(MY_TRACE_)
print(it[4]);
#endif // MY_TRACE_
}
it = index->GetEqual(Dynamic("A"), Dynamic(1), Dynamic(1));
NKIT_TEST_ASSERT(it != index->end());
NKIT_TEST_ASSERT(it[4] == Dynamic(99.0));
it = index->GetEqual(Dynamic("A2"), Dynamic(2), Dynamic::GetDefault(detail::INTEGER));
NKIT_TEST_ASSERT(it != index->end());
it = index->GetEqual(Dynamic("A1"), Dynamic(1), Dynamic::GetDefault(detail::INTEGER));
NKIT_TEST_ASSERT(it != index->end());
}
void VQModel::Adapt(const std::shared_ptr<Model>& other, const std::vector< DynamicVector<Real> >& samples,
unsigned int iterations, Real relevanceFactor)
{
const VQModel* model = dynamic_cast<VQModel*>(other.get());
if (model == nullptr)
{
std::cout << "Not VQModel." << std::endl;
return;
}
SetOrder(model->GetOrder());
Init();
std::vector<unsigned int> indices(samples.size());
// Initialize the feature vectors of the centroids.
for (unsigned int c = 0; c < GetOrder(); c++)
{
mClusterCentroids[c] = model->mClusterCentroids[c];
}
// Do the iterations.
for (unsigned int i = 0; i < iterations; i++)
{
//Find the closest centroid to each sample
for (unsigned int n = 0; n < samples.size(); n++)
{
Real minDist = std::numeric_limits<Real>::max();
for (unsigned int c = 0; c < GetOrder(); c++)
{
Real dist = samples[n].Distance(mClusterCentroids[c]);
if (dist < minDist)
{
minDist = dist;
indices[n] = c;
}
}
}
//Set the centroids to the average of the samples in each centroid
for (unsigned int c = 0; c < GetOrder(); ++c)
{
mClusterCentroids[c].Assign(0.0f);
mClusterSizes[c] = 0;
}
for (unsigned int s = 0; s < samples.size(); ++s)
{
mClusterCentroids[indices[s]].Add(samples[s]);
++mClusterSizes[indices[s]];
}
for (unsigned int c = 0; c < GetOrder(); ++c)
{
if (mClusterSizes[c] > 0)
{
mClusterCentroids[c].Multiply(1.0f / static_cast<Real>(mClusterSizes[c]));
}
}
//Calculate the adapted values
for (unsigned int c = 0; c < GetOrder(); ++c)
{
Real size = static_cast<Real>(mClusterSizes[c]);
Real w = size / (size + static_cast<Real>(relevanceFactor));
DynamicVector<Real> ubmc = model->mClusterCentroids[c];
ubmc.Multiply(1.0f - w);
mClusterCentroids[c].Multiply(w);
mClusterCentroids[c].Add(ubmc);
}
}
}
LevelElimination * LAMGLSSolver::coarsenElimination(const Matrix & finerMatrix) {
cout << "coarsenElimination()" << endl;
//Per salvare i P ed i q
std::vector<qPStage*> cStages;
/* Prealloco spazio per al più SETUP_ELIMINATION_MAX_STAGES così evito
* possibili riallocazioni */
cStages.reserve(SETUP_ELIMINATION_MAX_STAGES);
//Copio la matrice così posso modificarla senza modificare quella del finerLevel
Matrix A(finerMatrix);
Matrix Acc; //Per lo Schur Complement System
Matrix Acf; //Per lo Schur Complement System
// Il numero di stage di eliminazione eseguiti sulla matrice A
size_t stageNum = 0;
/* Vector che vengono riusati*/
DynamicVector<size_t> Cset; //Insieme dei nodi da non eliminare
DynamicVector<size_t> Fset; //Insieme dei nodi da eliminare
DynamicVector<size_t> degree; //Grado di ciascun nodo
DynamicVector<size_t> candidate; //Nodi candidati all'eliminazione
DynamicVector<NodeEliminationStatus> status; //Stato dei nodi
/* P è sempre sparsa anche quando A è densa */
SpMat P;
DynamicVector<double> q;
while (stageNum < SETUP_ELIMINATION_MAX_STAGES) {
size_t A_rows = A.rows();
if (A_rows <= MAX_DIRECT_SOLVE_SIZE)
break;
/* (1) Calcola il vettore degree della matrice. */
degree.resize(A_rows);
for (size_t i = 0; i < A_rows; ++i) {
degree[i] = A.nonZeros(i);
if (A(i, i) != 0)//Tolgo l'elemento sulla diagonale
degree[i]--;
else
cerr << "La diagionale i-esima c'ha lelemento a zero!!! ERRORE MORTALE!!!" << endl;
}
/* (2) [f c ] = lowDegreeNodes(A,degree,MaxDegree) */
candidate.resize(A_rows);
candidate = 0;
/* Individuo i nodi candidati (degree[i] <= MAX_DEGREE) */
size_t cnnZ = 0; //Devo usare questa variabili perché i valori "settati" di candidate comprendono il valore "0" cioè il nodo 0
for (size_t i = 0; i < A_rows; ++i) {
if (degree[i] <= SETUP_ELIMINATION_MAX_DEGREE) {
candidate[cnnZ++] = i;
}
}
/* I primi cnnZ elementi sono stati inizializzati */
candidate.resize(cnnZ, true);
status.resize(A_rows);
status = HIGH_DEGREE; //Tutti gli elementi prendono HIGH_DEGREE
// status(candidate) = 0; % Reset all relevant nodes to "not visited"
for (size_t i = 0; i < candidate.size(); ++i) {
status[candidate[i]] = NOT_DECIDED;
}
for (size_t k = 0; k < candidate.size(); ++k) {
lowdegreesweep(A, candidate[k], status); //Template call
}
/* Adesso devo creare i vettori F e C, inserendovi i nodi che verranno
* o meno eliminati */
size_t nf = 0; //|Fset|
size_t nc = 0; //|Cset|
Cset.resize(A_rows, false);
Fset.resize(A_rows, false);
for (size_t i = 0; i < A_rows; ++i) {
if (status[i] == LOW_DEGREE)
Fset[nf++] = i; //Inserisco il nodo i nell'insieme F
else
Cset[nc++] = i; //Lo inserisco invece in C
}
/* L'insieme C non può mai essere vuoto, dobbiamo lasciargli almeno
* un elemento
*/
if (nc == 0) {
Cset[nc++] = Fset[--nf];
Fset[nf] = 0;
}
Cset.resize(nc, true); //nc non è mai 0
Fset.resize(nf, true);
/* FINE di (2) [f c ] = lowDegreeNodes(A,degree,MaxDegree) */
if ((nf <= SETUP_ELIMINATION_MIN_ELIM_FRACTION * A_rows)) {
/* Il coarsening non è abbastanza efficace perché andiamo ad eliminare
* un numero, nf, di nodi che è inferiore alla minima soglia accettabile
* di eliminazione. Ci fermiamo senza eliminare.*/
break;
}
/* (3) Una volta individuati i nodi da eliminare devo calcolare gli
* operatori P e q che mi consentono di eliminare tutti questi nodi
* [R, q] = eliminationOperators(A, f, index);
*/
/* In MEX si crea una matrice columnMajor che poi verrà trasposta perché
* le matrici di Matlab sono columnMajor e se uno vuole sfruttare la
* rappresentazione interna deve usarle così.
* Noi invece possiamo già generare la matrice trasposta costruendo
* direttamente la matrice rowMajor e "sostituendo" ai termini riga
* quelli colonna.
*/
/* P è sempre una matrice sparsa perché il numero dei suoi nonzero
* e basso anche quando A è densa */
P.resize(nf, nc, false);
q.resize(nf, false);
/* Quanti elemenenti abbiamo salvato in Q (e quante righe di R
* abbiamo costruito)
*/
size_t P_row = 0;
size_t P_col = 0;
/* Per ogni f-riga di A prendi ciascun c-elemento di questa riga e formaci
* la i-esima riga di R. L'inverso dell'f-esimo elemento di ciascuna f-riga
* va messo in q. Inoltre ciascuna riga i di R va scalata di un fattore -q[i]
*/
for (DynamicVector<size_t>::Iterator dvit = Fset.begin(); dvit != Fset.end(); dvit++) {
eliminationOperators(A, Cset, (*dvit), q, P, P_col, P_row);
P_row++; //Passiamo alla prosssima riga
}
//Salvo i dati così creati nel cStages
cStages.push_back(new qPStage(new SpMat(P), new DynamicVector<double>(q),
new DynamicVector<size_t>(Fset), new DynamicVector<size_t>(Cset), (nf + nc)));
/* FINE (03) [R, q] = eliminationOperators(A, f, index);*/
/* (4) Adesso devo calcolare il sistema complementare di Schur dato da
* A = Ac,c + Ac,f*R^t */
/* Acc è la sottomatrice di A che ha come elementi tutti gli a_ij tali
* che (ij) appartiene a Cset x Cset. Quindi per ogni riga crow devo
* prenderci tutti gli elementi che hanno indice pari a ccol */
MtxOps::submatrix(A, Cset, Cset, Acc);
/* Acf invece ha nc righe e nf colonne*/
MtxOps::submatrix(A, Cset, Fset, Acf);
/* Finalmente posso aggiornare A*/
A = Acc + Acf * P;
/* Acc_[nc x nc] + (Acf * P)_[nc x nc].
* Dunque La matrice A risultante diventa una nc x nc e perdiamo esattamente nf nodi.*/
}//Fine while(stageNum...)
/* Usciti dal while dobbiamo creare il livello, se è possibile farlo */
LevelElimination* ret = NULL;
if (stageNum != 0) {
if (useSparse) {
if (isSparseOK(A)) {
ret = new LevelElimination(new SpMat(A), cStages, multiGrid.back());
} else {
useSparse = false;
ret = new LevelElimination(new DMat(A), cStages, multiGrid.back());
}
} else {
ret = new LevelElimination(new DMat(A), cStages, multiGrid.back());
}
}
cout << "coarsenElimination() finito" << endl;
return ret;
}
