void TreeLattice<Impl>::partialRollback(DiscretizedAsset& asset,
Time to) const {
Time from = asset.time();
if (close(from,to))
return;
QL_REQUIRE(from > to,
"cannot roll the asset back to" << to
<< " (it is already at t = " << from << ")");
Integer iFrom = Integer(t_.index(from));
Integer iTo = Integer(t_.index(to));
for (Integer i=iFrom-1; i>=iTo; --i) {
Array newValues(this->impl().size(i));
this->impl().stepback(i, asset.values(), newValues);
asset.time() = t_[i];
asset.values() = newValues;
// skip the very last adjustment
if (i != iTo)
asset.adjustValues();
}
}
void fixedMeanFvPatchField<Type>::updateCoeffs()
{
if (this->updated())
{
return;
}
gpuField<Type> newValues(this->patchInternalField());
Type meanValuePsi =
gSum(this->patch().magSf()*newValues)
/gSum(this->patch().magSf());
if (mag(meanValue_) > SMALL && mag(meanValuePsi)/mag(meanValue_) > 0.5)
{
newValues *= mag(meanValue_)/mag(meanValuePsi);
}
else
{
newValues += (meanValue_ - meanValuePsi);
}
this->operator==(newValues);
fixedValueFvPatchField<Type>::updateCoeffs();
}
TableFunction *Bucket::FastCondition(const list<int> &ordering, const Assignment &cond) {
if (functions.size() == 0)
return new TableFunction();
Scope newDomain;
for (unsigned int i = 0; i < functions.size(); ++i) {
newDomain = newDomain + functions[i]->GetScope();
}
newDomain = newDomain - cond;
newDomain.SetOrdering(ordering);
unsigned int card = newDomain.GetCard();
vector<double> newValues(card, 1);
Assignment a(newDomain);
a.SetAllVal(0);
int idx = 0;
unsigned int ii = cond.GetVal(cond.GetOrdering().back());
do {
assert(idx < int(card));
for (unsigned int i = 0; i < functions.size(); ++i) {
newValues[idx] *= functions[i]->GetValElim(a, ii);
}
idx++;
} while (a.Iterate());
assert(newValues.size() == newDomain.GetCard());
TableFunction *message = new TableFunction(newDomain, newValues);
return message;
}
/**
* Simulates a lineage splitting into two. (IE, the opposite of coalescing).
* @param splitType The type to split.
* @return A new R after this split.
*/
R split(int splitType) {
ValueArray newValues(values);
if (splitType != dims)
newValues[splitType] += 1;
return R(n+1,newValues);
}
void toPieChart::setValues(std::list<double> &values, std::list<QString> &labels)
{
Values = values;
Labels = labels;
emit newValues(values, labels);
update();
}
/**
* Simulates coalescing two of the lineages into one.
* @param coalesceType The type to coalesce.
* @return A new R after coalesing.
*/
R coalesce(int coalesceType) {
ValueArray newValues(values);
if (coalesceType != dims)
newValues[coalesceType] -=1;
return R(n-1,newValues);
}
/**
* Simulates a mutation from the fromType to the toType.
* @param fromType The source lineage type.
* @param toType The destination lineage type.
* @return A new R representing after the mutation.
*/
R transition(int fromType, int toType) {
ValueArray newValues(values);
if (fromType != dims)
newValues[fromType] -=1;
if (toType != dims)
newValues[toType] += 1;
return R(n,newValues);
}
void KernelEstimator::addValue(double data, const double weight) {
if (weight == 0) {
return;
}
data = round(data);
int insertIndex = findNearestValue(data);
if ((mNumValues <= insertIndex) || (mValues[insertIndex] != data)) {
if (mNumValues < mValues.size()) {
int left = mNumValues - insertIndex;
std::cout << "Please cross-check here for array copy";
std::copy(mValues.begin() + insertIndex, mValues.begin() + left, mValues.begin() + insertIndex + 1);
std::copy(mWeights.begin() + insertIndex, mWeights.begin() + left, mWeights.begin() + insertIndex + 1);
mValues[insertIndex] = data;
mWeights[insertIndex] = weight;
mNumValues++;
}
else {
double_array newValues(mValues.size() * 2);
double_array newWeights(mValues.size() * 2);
int left = mNumValues - insertIndex;
std::copy(mValues.begin(), mValues.begin() + insertIndex, newValues.begin());
std::copy(mWeights.begin(), mWeights.begin() + insertIndex, newWeights.begin());
newValues[insertIndex] = data;
newWeights[insertIndex] = weight;
std::copy(mValues.begin() + insertIndex, mValues.begin() + left, newValues.begin() + insertIndex + 1);
std::copy(mWeights.begin() + insertIndex, mWeights.begin() + left, newWeights.begin() + insertIndex + 1);
mNumValues++;
mValues = newValues;
mWeights = newWeights;
}
if (weight != 1) {
mAllWeightsOne = false;
}
}
else {
mWeights[insertIndex] += weight;
mAllWeightsOne = false;
}
mSumOfWeights += weight;
double range = mValues[mNumValues - 1] - mValues[0];
if (range > 0) {
mStandardDev = std::fmax(range / sqrt(mSumOfWeights), mPrecision / (2 * 3));
// allow at most 3 sds within one interval
}
}
void SampledCurve::regrid(const Array &new_grid) {
CubicInterpolation priceSpline(grid_.begin(), grid_.end(),
values_.begin(),
CubicInterpolation::Spline, false,
CubicInterpolation::SecondDerivative, 0.0,
CubicInterpolation::SecondDerivative, 0.0);
priceSpline.update();
Array newValues(new_grid.size());
Array::iterator val;
Array::const_iterator grid;
for (val = newValues.begin(), grid = new_grid.begin() ;
grid != new_grid.end();
++val, ++grid) {
*val = priceSpline(*grid, true);
}
values_.swap(newValues);
grid_ = new_grid;
}
TableFunction *Bucket::FastSumElimination(const list<int> &ordering, const Scope &elimVar) {
if (functions.size() == 0)
return new TableFunction();
Scope newDomain;
for (unsigned int i = 0; i < functions.size(); ++i) {
newDomain = newDomain + functions[i]->GetScope();
}
newDomain = newDomain - elimVar;
newDomain.SetOrdering(ordering);
unsigned int card = newDomain.GetCard();
vector<double> newValues(card, 0);
Assignment a(newDomain);
Assignment e(elimVar);
a.SetAllVal(0);
e.SetAllVal(0);
/*
vector<Assignment> fAssign;
for (unsigned int i = 0; i < functions.size(); ++i) {
fAssign.push_back(Assignment(functions[i]->GetScope()));
}
*/
int idx = 0;
do {
for (unsigned int ii = 0; ii < e.GetCard(); ++ii) {
double combVal = 1;
for (unsigned int i = 0; i < functions.size(); ++i) {
/*
fAssign[i].SetAssign(a);
fAssign[i].SetAssign(e);
*/
combVal *= functions[i]->GetValElim(a, ii);
}
newValues[idx] += combVal;
}
idx++;
} while (a.Iterate());
assert(newValues.size() == newDomain.GetCard());
TableFunction *message = new TableFunction(newDomain, newValues);
return message;
}
ErrorCode Intx2MeshOnSphere::update_tracer_data(EntityHandle out_set, Tag & tagElem, Tag & tagArea)
{
EntityHandle dum = 0;
Tag corrTag;
ErrorCode rval = mb->tag_get_handle(CORRTAGNAME,
1, MB_TYPE_HANDLE, corrTag,
MB_TAG_DENSE, &dum); // it should have been created
ERRORR(rval, "can't get correlation tag");
Tag gid;
rval = mb->tag_get_handle(GLOBAL_ID_TAG_NAME, 1, MB_TYPE_INTEGER, gid, MB_TAG_DENSE);
ERRORR(rval,"can't get global ID tag" );
// get all polygons out of out_set; then see where are they coming from
Range polys;
rval = mb->get_entities_by_dimension(out_set, 2, polys);
ERRORR(rval, "can't get polygons out");
// rs2 is the red range, arrival; rs1 is blue, departure;
// there is a connection between rs1 and rs2, through the corrTag
// corrTag is __correlation
// basically, mb->tag_get_data(corrTag, &(redPoly), 1, &bluePoly);
// also, mb->tag_get_data(corrTag, &(bluePoly), 1, &redPoly);
// we start from rs2 existing, then we have to update something
std::vector<double> currentVals(rs2.size());
rval = mb->tag_get_data(tagElem, rs2, ¤tVals[0]);
ERRORR(rval, "can't get existing tag values");
// for each polygon, we have 2 indices: red and blue parents
// we need index blue to update index red?
std::vector<double> newValues(rs2.size(), 0.);// initialize with 0 all of them
// area of the polygon * conc on red (old) current quantity
// finaly, divide by the area of the red
double check_intx_area=0.;
for (Range::iterator it= polys.begin(); it!=polys.end(); it++)
{
EntityHandle poly=*it;
int blueIndex, redIndex;
rval = mb->tag_get_data(blueParentTag, &poly, 1, &blueIndex);
ERRORR(rval, "can't get blue tag");
EntityHandle blue = rs1[blueIndex];
rval = mb->tag_get_data(redParentTag, &poly, 1, &redIndex);
ERRORR(rval, "can't get red tag");
//EntityHandle red = rs2[redIndex];
// big assumption here, red and blue are "parallel" ;we should have an index from
// blue to red (so a deformed blue corresponds to an arrival red)
double areap = area_spherical_element(mb, poly, R);
check_intx_area+=areap;
// so the departure cell at time t (blueIndex) covers a portion of a redCell
// that quantity will be transported to the redCell at time t+dt
// the blue corresponds to a red arrival
EntityHandle redArr;
rval = mb->tag_get_data(corrTag, &blue, 1, &redArr);
if (0==redArr || MB_TAG_NOT_FOUND==rval)
{
if (!remote_cells)
ERRORR( MB_FAILURE, "no remote cells, failure\n");
// maybe the element is remote, from another processor
int global_id_blue;
rval = mb->tag_get_data(gid, &blue, 1, &global_id_blue);
ERRORR(rval, "can't get arrival red for corresponding blue gid");
// find the
int index_in_remote = remote_cells->find(1, global_id_blue);
if (index_in_remote==-1)
ERRORR( MB_FAILURE, "can't find the global id element in remote cells\n");
remote_cells->vr_wr[index_in_remote] += currentVals[redIndex]*areap;
}
else if (MB_SUCCESS==rval)
{
int arrRedIndex = rs2.index(redArr);
if (-1 == arrRedIndex)
ERRORR(MB_FAILURE, "can't find the red arrival index");
newValues[arrRedIndex] += currentVals[redIndex]*areap;
}
else
ERRORR(rval, "can't get arrival red for corresponding ");
}
// now, send back the remote_cells to the processors they came from, with the updated values for
// the tracer mass in a cell
if (remote_cells)
{
// so this means that some cells will be sent back with tracer info to the procs they were sent from
(parcomm->proc_config().crystal_router())->gs_transfer(1, *remote_cells, 0);
// now, look at the global id, find the proper "red" cell with that index and update its mass
//remote_cells->print("remote cells after routing");
int n = remote_cells->get_n();
for (int j=0; j<n; j++)
{
EntityHandle redCell = remote_cells->vul_rd[j];// entity handle sent back
int arrRedIndex = rs2.index(redCell);
if (-1 == arrRedIndex)
ERRORR(MB_FAILURE, "can't find the red arrival index");
newValues[arrRedIndex] += remote_cells->vr_rd[j];
}
}
// now divide by red area (current)
int j=0;
Range::iterator iter = rs2.begin();
void * data=NULL; //used for stored area
int count =0;
double total_mass_local=0.;
while (iter != rs2.end())
{
rval = mb->tag_iterate(tagArea, iter, rs2.end(), count, data);
ERRORR(rval, "can't tag iterate");
double * ptrArea=(double*)data;
for (int i=0; i<count; i++, iter++, j++, ptrArea++)
{
total_mass_local+=newValues[j];
newValues[j]/= (*ptrArea);
}
}
rval = mb->tag_set_data(tagElem, rs2, &newValues[0]);
ERRORR(rval, "can't set new values tag");
double total_mass=0.;
double total_intx_area =0;
int mpi_err = MPI_Reduce(&total_mass_local, &total_mass, 1, MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);
if (MPI_SUCCESS != mpi_err) return MB_FAILURE;
// now reduce total area
mpi_err = MPI_Reduce(&check_intx_area, &total_intx_area, 1, MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);
if (MPI_SUCCESS != mpi_err) return MB_FAILURE;
if (my_rank==0)
{
std::cout <<"total mass now:" << total_mass << "\n";
std::cout <<"check: total intersection area: (4 * M_PI * R^2): " << total_intx_area << "\n";
}
if (remote_cells)
{
delete remote_cells;
remote_cells=NULL;
}
return MB_SUCCESS;
}
double_array Instance::toDoubleArray() const
{
double_array newValues(mAttValues.size());
std::copy(std::begin(mAttValues), std::end(mAttValues), std::begin(newValues));
return newValues;
}
void Lockin2::interpretInput()
{
QTime time;
time.start();
_timeValue += _outputPeriod;
// récupère les nouvelles valeurs
/*
* le nombre de nouvelle valeurs = outputPeriod * sampleRate / 1000
* outputPeriod (~0.1 s) étant beaucoup plus grand que la periode du chopper (~1/500 s)
* meme dans le cas d'un chopper lent et d'un temps de sortie rapide le nombre de periodes
* du chopper reste elevé. (~50)
* On peut donc garder uniquement les periodes entières
* On a donc une perte de présision de l'ordre de 2/50 = 4%
* Plus outputPeriod et grand et plus le chopper est rapide plus la perte diminue.
* 0.5s 500Hz -> 0.8%
* 1.0s 500Hz -> 0.4%
*/
QList<qreal> leftSignal;
QList<int> chopperSignal;
// les des données et les adapte
// left [-1;+1]
// right -1 ou +1
readSoudCard(leftSignal, chopperSignal);
if (leftSignal.size() == 0 || chopperSignal.size() == 0)
return;
QList<QPair<qreal, qreal> > chopperSinCos = parseChopperSignal(chopperSignal, _phase);
// multiplie le leftSignal ([-1;1]) par chopperSinCos ([-1;1])
for (int i = 0; i < leftSignal.size(); ++i) {
qreal x, y;
if (chopperSinCos[i].first != 3.0) { // 3.0 est la valeur qui indique ignoreValue dans parseChopperSignal(...)
x = chopperSinCos[i].first * leftSignal[i]; // sin
y = chopperSinCos[i].second * leftSignal[i]; // cos
} else {
x = y = 3.0; // ignore value
}
_dataXY << QPair<qreal, qreal>(x, y);
}
// renouvelle le view data (prend la fin des listes, qui correspond aux parties les plus récentes)
if (_vumeterMutex.tryLock()) {
_vumeterData.clear();
for (int i = leftSignal.size() - 1; i >= 0; --i) {
if (_vumeterData.size() >= _sampleVumeter)
break;
if (chopperSinCos[i].first != 3.0) {
_vumeterData.prepend(QPair<qreal, qreal>(leftSignal[i], chopperSinCos[i].first));
}
}
_vumeterMutex.unlock();
} else {
qDebug() << __FUNCTION__ << ": the view Mutex is locked";
}
// le nombre d'échantillons correslondant au temps d'integration
if (_dataXY.size() < _sampleIntegration) {
// pas encore assez d'elements pour faire la moyenne
emit info("wait more input data...");
return;
}
// supprime les valeurs en trop
while (_dataXY.size() > _sampleIntegration)
_dataXY.removeFirst();
qreal dataCount = 0.0;
qreal x = 0.0;
qreal y = 0.0;
for (int i = 0; i < _dataXY.size(); ++i) {
// deux fois 3.0 indique ignoreValue
if (_dataXY[i].first != 3.0) {
x += _dataXY[i].first;
y += _dataXY[i].second;
dataCount += 1.0;
}
}
if (dataCount == 0.0) {
qDebug() << __FUNCTION__ << ": no data usable";
emit info("signal too low");
return;
}
x /= dataCount;
y /= dataCount;
// _values << QPair<qreal, QPair<qreal, qreal> >(_timeValue, QPair<qreal, qreal>(x, y));
_xValue = x;
_yValue = y;
emit newValues(_timeValue, x, y);
qDebug() << __FUNCTION__ << ": execution time " << time.elapsed() << "ms";
}
void GridEditor::EditTool::frame(void)
{
/* Bail out if the tool is not active: */
if(!active)
return;
/* Update the tool's position and radius in model coordinates: */
Vrui::NavTrackerState newTrackerState=getButtonDeviceTransformation(0);
newTrackerState.leftMultiply(Vrui::getInverseNavigationTransformation());
/* Update the brush position and size in model coordinates: */
modelCenter=Point(newTrackerState.getOrigin());
modelRadius=float(influenceRadius*newTrackerState.getScaling());
/* Determine the subdomain of the grid affected by the brush: */
EditableGrid::Index min,max;
for(int i=0;i<3;++i)
{
min[i]=int(Math::floor((modelCenter[i]-modelRadius-fudgeSize)/grid->getCellSize(i)));
if(min[i]<1)
min[i]=1;
max[i]=int(Math::ceil((modelCenter[i]+modelRadius+fudgeSize)/grid->getCellSize(i)));
if(max[i]>grid->getNumVertices(i)-1)
max[i]=grid->getNumVertices(i)-1;
}
/* Update the grid: */
float minr2=modelRadius>fudgeSize?Math::sqr(modelRadius-fudgeSize):0.0f;
float maxr2=Math::sqr(modelRadius+fudgeSize);
switch(editMode)
{
case ADD:
{
for(EditableGrid::Index v=min;v[0]<max[0];v.preInc(min,max))
{
Point p;
float dist=0.0f;
for(int i=0;i<3;++i)
{
p[i]=float(v[i])*grid->getCellSize(i);
dist+=Math::sqr(modelCenter[i]-p[i]);
}
if(dist<maxr2)
{
float val;
if(dist<minr2)
val=1.0f;
else
val=(modelRadius+fudgeSize-Math::sqrt(dist))/(2.0f*fudgeSize);
float oldVal=grid->getValue(v);
if(val>oldVal)
grid->setValue(v,val);
}
}
grid->invalidateVertices(min,max);
break;
}
case SUBTRACT:
{
for(EditableGrid::Index v=min;v[0]<max[0];v.preInc(min,max))
{
Point p;
float dist=0.0f;
for(int i=0;i<3;++i)
{
p[i]=float(v[i])*grid->getCellSize(i);
dist+=Math::sqr(modelCenter[i]-p[i]);
}
if(dist<maxr2)
{
float val;
if(dist<minr2)
val=0.0f;
else
val=1.0f-(modelRadius+fudgeSize-Math::sqrt(dist))/(2.0f*fudgeSize);
float oldVal=grid->getValue(v);
if(val<oldVal)
grid->setValue(v,val);
}
}
grid->invalidateVertices(min,max);
break;
}
case SMOOTH:
{
for(int i=0;i<3;++i)
{
if(min[i]==0)
++min[i];
if(max[i]==grid->getNumVertices(i))
--max[i];
}
for(EditableGrid::Index v=min;v[0]<max[0];v.preInc(min,max))
{
Point p;
float dist=0.0f;
for(int i=0;i<3;++i)
{
p[i]=float(v[i])*grid->getCellSize(i);
dist+=Math::sqr(modelCenter[i]-p[i]);
}
if(dist<maxr2)
{
float avgVal=0.0f;
EditableGrid::Index i;
for(i[0]=v[0]-1;i[0]<=v[0]+1;++i[0])
for(i[1]=v[1]-1;i[1]<=v[1]+1;++i[1])
for(i[2]=v[2]-1;i[2]<=v[2]+1;++i[2])
avgVal+=grid->getValue(i);
avgVal/=27.0f;
if(dist<minr2)
newValues(v)=avgVal;
else
{
float w=(modelRadius+fudgeSize-Math::sqrt(dist))/(2.0f*fudgeSize);
newValues(v)=avgVal*w+grid->getValue(v)*(1.0f-w);
}
}
else
newValues(v)=grid->getValue(v);
}
for(EditableGrid::Index v=min;v[0]<max[0];v.preInc(min,max))
grid->setValue(v,newValues(v));
grid->invalidateVertices(min,max);
/* Request another frame to continue smoothing: */
Vrui::scheduleUpdate(Vrui::getApplicationTime()+1.0/125.0);
break;
}
case DRAG:
{
/* Calculate the incremental tool transformation since the last frame: */
Vrui::NavTrackerState t=lastTrackerState;
t*=Geometry::invert(newTrackerState);
Geometry::OrthogonalTransformation<float,3> pt(t);
float r2=Math::sqr(modelRadius);
for(EditableGrid::Index v=min;v[0]<max[0];v.preInc(min,max))
{
Point p;
float dist=0.0f;
for(int i=0;i<3;++i)
{
p[i]=float(v[i])*grid->getCellSize(i);
dist+=Math::sqr(modelCenter[i]-p[i]);
}
if(dist<r2)
{
/* Compute the dragged position: */
Point dp=pt.transform(p);
float w=Math::sqrt(dist)/modelRadius;
dp=Geometry::affineCombination(dp,p,w);
/* Look up the grid value at the dragged position: */
float dragVal=grid->getValue(dp);
newValues(v)=dragVal;
}
else
newValues(v)=grid->getValue(v);
}
for(EditableGrid::Index v=min;v[0]<max[0];v.preInc(min,max))
grid->setValue(v,newValues(v));
grid->invalidateVertices(min,max);
break;
}
}
lastTrackerState=newTrackerState;
}
OptionalNode FindDivisions(const ast::Operands& operands, eval::SessionEnvironment& sessionEnvironment) {
if ( operands.size() != 2 ) {
sessionEnvironment.raiseMessage( Message(ids::FindDivisions, ids::argrx, {
ast::Node::make<ast::Identifier>( ids::FindDivisions ),
ast::Node::make<math::Rational>( operands.size() ),
ast::Node::make<math::Rational>( 2 )
} ));
return EvaluationFailure();
}
const auto range = operands[0];
const auto numberOfElements = operands[1];
if ( !range.isFunctionCall(ids::List) || range.get<ast::FunctionCall>().getOperands().size() != 2) {
sessionEnvironment.raiseMessage( Message(ids::FindDivisions, ids::fdargs, {
range,
ast::Node::make<ast::FunctionCall>( ids::FindDivisions, operands )
} ));
return EvaluationFailure();
}
if ( !numberOfElements.is<math::Rational>() || !math::isInteger(numberOfElements.get<math::Rational>()) ) {
sessionEnvironment.raiseMessage( Message(ids::FindDivisions, ids::fdargs, {
numberOfElements,
ast::Node::make<ast::FunctionCall>( ids::FindDivisions, operands )
} ));
return EvaluationFailure();
}
std::vector<ast::Node> listParams = range.get<ast::FunctionCall>().getOperands();
auto endIt = std::find_if_not(listParams.begin(), listParams.end(), [](const ast::Node& param) {
return param.isNumeric();
});
if (endIt != listParams.end()) {
sessionEnvironment.raiseMessage( Message(ids::FindDivisions, ids::fdargs, {
*endIt,
ast::Node::make<ast::FunctionCall>( ids::FindDivisions, operands )
} ));
return EvaluationFailure();
}
const math::Real precision = (listParams[1].getNumeric() - listParams[0].getNumeric())/numberOfElements.getInteger();
const math::Rational left = math::findRationalNear(listParams[0].getNumeric(), precision);
const math::Rational right = math::findRationalNear(listParams[1].getNumeric(), precision);
std::vector<math::Rational> intermediates;
// Impl here
intermediates.push_back(left);
const math::Rational distance = right - left;
std::vector<math::Rational> multipliersbase = {1, 2, 5};
std::vector<math::Rational> multipliers;
for(int i=-2;i<2;++i) {
std::vector<math::Rational> newValues(multipliersbase.begin(), multipliersbase.end());
math::Rational magnitude = math::power(math::Rational{10}, i);
for(auto& nv: newValues) { nv*=magnitude; }
multipliers.insert(multipliers.end(), newValues.begin(), newValues.end());
}
const auto multiplierIt = std::find_if(multipliers.begin(), multipliers.end(), [&](const math::Rational& multiplier) {
// return true if multiplier would result in less ticks that requested
return (math::Real{distance}/multiplier) < numberOfElements.getNumeric();
});
const auto multiplier = *(multiplierIt-1);
for(math::Rational next = left + multiplier; next <= right ; next += multiplier) {
intermediates.push_back(next);
}
ast::Operands elements;
for(auto& intermediate: intermediates) {
elements.push_back(ast::Node::make<math::Rational>(intermediate));
}
return ast::Node::make<ast::FunctionCall>(ids::List, elements);
}
void Constraint<Scalar, LocalOrdinal, GlobalOrdinal, Node, LocalMatOps>::Apply(const Matrix& P, Matrix& Projected) const {
const size_t NSDim = X_->getNumVectors();
const size_t numRows = P.getNodeNumRows();
Projected.resumeFill();
Teuchos::SerialDenseVector<LO,SC> BcRow(NSDim, false);
for (size_t i = 0; i < numRows; i++) {
Teuchos::ArrayView<const LO> indices, pindices;
Teuchos::ArrayView<const SC> values, pvalues;
P .getLocalRowView(i, indices, values);
Projected.getLocalRowView(i, pindices, pvalues);
size_t nnz = pindices.size(); // number of nonzeros in the constrained matrix
size_t nnz1 = indices.size(); // number of nonzeros in the supplied matrix
Teuchos::Array<SC> newValues(nnz, Teuchos::ScalarTraits<SC>::zero());
// step 1: fix stencil
// Projected already has the correct stencil
// step 2: copy correct stencil values
for (size_t j = 0; j < nnz1; j++) {
// this might be accelerated if we know smth about ordering
size_t k = 0;
for (; k < nnz; k++)
if (pindices[k] == indices[j])
break;
if (k != nnz) {
// index indices[j] is part of template, copy corresponding value
newValues[k] = values[j];
}
}
// step 3: project to the space
Teuchos::SerialDenseMatrix<LO,SC> locX(NSDim, nnz, false);
for (size_t j = 0; j < nnz; j++) {
for (size_t k = 0; k < NSDim; k++)
BcRow[k] = X_->getData(k)[pindices[j]];
Teuchos::setCol(BcRow, (LO)j, locX);
}
Teuchos::SerialDenseVector<LO,SC> val(nnz, false), val1(NSDim, false), val2(NSDim, false);
for (size_t j = 0; j < nnz; j++)
val[j] = newValues[j];
Teuchos::BLAS<LO,SC> blas;
blas.GEMV(Teuchos::NO_TRANS, NSDim, nnz, Teuchos::ScalarTraits<SC>::one(), locX.values(),
locX.stride(), val.values(), (LO)1, Teuchos::ScalarTraits<SC>::zero(), val1.values(), (LO)1);
blas.GEMV(Teuchos::NO_TRANS, NSDim, NSDim, Teuchos::ScalarTraits<SC>::one(), XXtInv_[i].values(),
XXtInv_[i].stride(), val1.values(), (LO)1, Teuchos::ScalarTraits<SC>::zero(), val2.values(), (LO)1);
blas.GEMV(Teuchos::CONJ_TRANS, NSDim, nnz, Teuchos::ScalarTraits<SC>::one(), locX.values(),
locX.stride(), val2.values(), (LO)1, Teuchos::ScalarTraits<SC>::zero(), val.values(), (LO)1);
for (size_t j = 0; j < nnz; j++)
newValues[j] -= val[j];
Projected.replaceLocalValues(i, pindices, newValues);
}
Projected.fillComplete(Projected.getDomainMap(), Projected.getRangeMap()); //FIXME: maps needed?
}