// only need to accumulate blocks within number of circuit inputs
// returns true if At is modified, false otherwise
bool accumVector(BlockVector<T>& At) {
const auto limit = std::min(At.stopIndex(), m_vec.size());
if (At.startIndex() >= limit) {
return false;
} else {
for (std::size_t i = At.startIndex(); i < limit; ++i) {
m_vec[i] = At[3 + i] * m_random_rA;
#ifdef USE_ASSERT
assert(! m_vec[i].isZero());
#endif
At[3 + i] = T::zero();
}
return true;
}
}
// must accumulate all blocks
void accumVector(const BlockVector<T>& At,
const BlockVector<T>& Bt,
const BlockVector<T>& Ct) {
#ifdef USE_ASSERT
assert(At.space() == Bt.space() &&
Bt.space() == Ct.space() &&
At.block() == Bt.block() &&
Bt.block() == Ct.block());
#endif
for (std::size_t i = At.startIndex(); i < At.stopIndex(); ++i) {
m_vec[i] =
m_random_beta_rA * At[i] +
m_random_beta_rB * Bt[i] +
m_random_beta_rC * Ct[i];
}
}
void computeh(double time, BlockVector& q0, SiconosVector& y)
{
std::cout <<"my_NewtonEulerR:: computeh" << std:: endl;
std::cout <<"q0.size() = " << q0.size() << std:: endl;
double height = q0.getValue(0) - _sBallRadius - q0.getValue(7);
// std::cout <<"my_NewtonEulerR:: computeh _jachq" << std:: endl;
// _jachq->display();
y.setValue(0, height);
_Nc->setValue(0, 1);
_Nc->setValue(1, 0);
_Nc->setValue(2, 0);
_Pc1->setValue(0, q0.getValue(0) - _sBallRadius);
_Pc1->setValue(1, q0.getValue(1));
_Pc1->setValue(2, q0.getValue(2));
_Pc2->setValue(0,q0.getValue(7));
_Pc2->setValue(1,q0.getValue(8));
_Pc2->setValue(2,q0.getValue(9));
//printf("my_NewtonEulerR N, Pc\n");
_Nc->display();
_Pc1->display();
_Pc2->display();
std::cout <<"my_NewtonEulerR:: computeh ends" << std:: endl;
}
void computeh(double time, BlockVector& q0, SiconosVector& y)
{
double height = fabs(q0.getValue(0)) - _sBallRadius;
// std::cout <<"my_NewtonEulerR:: computeh _jachq" << std:: endl;
// _jachq->display();
y.setValue(0, height);
_Nc->setValue(0, 1);
_Nc->setValue(1, 0);
_Nc->setValue(2, 0);
_Pc1->setValue(0, height);
_Pc1->setValue(1, q0.getValue(1));
_Pc1->setValue(2, q0.getValue(2));
//_Pc2->setValue(0,hpc);
//_Pc2->setValue(1,data[q0]->getValue(1));
//_Pc2->setValue(2,data[q0]->getValue(2));
//printf("my_NewtonEulerR N, Pc\n");
//_Nc->display();
//_Pc1->display();
}
void prod(const SiconosMatrix& A, const BlockVector& x, SiconosVector& y, bool init)
{
assert(!(A.isPLUFactorized()) && "A is PLUFactorized in prod !!");
if (init)
y.zero();
unsigned int startRow = 0;
unsigned int startCol = 0;
// In private_addprod, the sum of all blocks of x, x[i], is computed: y = Sum_i (subA x[i]), with subA a submatrix of A,
// starting from position startRow in rows and startCol in columns.
// private_prod takes also into account the fact that each block of x can also be a block.
VectorOfVectors::const_iterator it;
for (it = x.begin(); it != x.end(); ++it)
{
private_addprod(A, startRow, startCol, **it, y);
startCol += (*it)->size();
}
}
void FirstOrderLinearR::computeg(double time, SiconosVector& lambda, SiconosVector& z, BlockVector& r)
{
if (_pluginJacglambda->fPtr)
{
if (!_B)
_B.reset(new SimpleMatrix(r.size(),lambda.size()));
computeB(time, z, *_B);
}
prod(*_B, lambda, r, false);
}
void KneeJointR::computeh(double time, BlockVector& q0, SiconosVector& y)
{
DEBUG_BEGIN("KneeJointR::computeh(double time, BlockVector& q0, SiconosVector& y)\n");
DEBUG_EXPR(q0.display());
double X1 = q0.getValue(0);
double Y1 = q0.getValue(1);
double Z1 = q0.getValue(2);
double q10 = q0.getValue(3);
double q11 = q0.getValue(4);
double q12 = q0.getValue(5);
double q13 = q0.getValue(6);
DEBUG_PRINTF("X1 = %12.8e,\t Y1 = %12.8e,\t Z1 = %12.8e,\n",X1,Y1,Z1);
DEBUG_PRINTF("q10 = %12.8e,\t q11 = %12.8e,\t q12 = %12.8e,\t q13 = %12.8e,\n",q10,q11,q12,q13);
double X2 = 0;
double Y2 = 0;
double Z2 = 0;
double q20 = 1;
double q21 = 0;
double q22 = 0;
double q23 = 0;
if(q0.getNumberOfBlocks()>1)
{
// SP::SiconosVector x2 = _d2->q();
// DEBUG_EXPR( _d2->q()->display(););
X2 = q0.getValue(7);
Y2 = q0.getValue(8);
Z2 = q0.getValue(9);
q20 = q0.getValue(10);
q21 = q0.getValue(11);
q22 = q0.getValue(12);
q23 = q0.getValue(13);
}
y.setValue(0, Hx(X1, Y1, Z1, q10, q11, q12, q13, X2, Y2, Z2, q20, q21, q22, q23));
y.setValue(1, Hy(X1, Y1, Z1, q10, q11, q12, q13, X2, Y2, Z2, q20, q21, q22, q23));
y.setValue(2, Hz(X1, Y1, Z1, q10, q11, q12, q13, X2, Y2, Z2, q20, q21, q22, q23));
DEBUG_EXPR(y.display());
DEBUG_END("KneeJointR::computeh(double time, BlockVector& q0, SiconosVector& y)\n");
}
// Copy from BlockVector
SiconosVector::SiconosVector(const BlockVector & vIn) : std11::enable_shared_from_this<SiconosVector>()
{
if (ask<IsDense>(**(vIn.begin()))) // dense
{
_dense = true;
vect.Dense = new DenseVect(vIn.size());
}
else
{
_dense = false;
vect.Sparse = new SparseVect(vIn.size());
}
VectorOfVectors::const_iterator it;
unsigned int pos = 0;
for (it = vIn.begin(); it != vIn.end(); ++it)
{
setBlock(pos, **it);
pos += (*it)->size();
}
}
//-----------------------------------------------------------------------------
void BlockMatrix::mult(const BlockVector& x, BlockVector& y,
bool transposed) const
{
if (transposed)
{
dolfin_error("BlockMatrix.cpp",
"compute transpose matrix-vector product",
"Not implemented for block matrices");
}
// Create temporary vector
dolfin_assert(matrices[0][0]);
// Loop over block rows
for(std::size_t row = 0; row < matrices.shape()[0]; row++)
{
// RHS sub-vector
GenericVector& _y = *(y.get_block(row));
const GenericMatrix& _matA = *matrices[row][0];
// Resize y and zero
if (_y.empty())
_matA.init_vector(_y, 0);
_y.zero();
// Loop over block columns
std::shared_ptr<GenericVector>
z_tmp = _matA.factory().create_vector();
for(std::size_t col = 0; col < matrices.shape()[1]; ++col)
{
const GenericVector& _x = *(x.get_block(col));
dolfin_assert(matrices[row][col]);
matrices[row][col]->mult(_x, *z_tmp);
_y += *z_tmp;
}
}
}
void FirstOrderLinearR::computeh(double time, BlockVector& x, SiconosVector& lambda,
SiconosVector& z, SiconosVector& y)
{
y.zero();
if (_pluginJachx->fPtr)
{
if (!_C)
_C.reset(new SimpleMatrix(y.size(),x.size()));
computeC(time, z, *_C);
}
if (_pluginJachlambda->fPtr)
{
if (!_D)
_D.reset(new SimpleMatrix(y.size(),lambda.size()));
computeD(time, z, *_D);
}
if (_pluginf->fPtr)
{
if (!_F)
_F.reset(new SimpleMatrix(y.size(),z.size()));
computeF(time, z, *_F);
}
if (_plugine->fPtr)
{
if (!_e)
_e.reset(new SiconosVector(y.size()));
computee(time, z, *_e);
}
if (_C)
prod(*_C, x, y, false);
if (_D)
prod(*_D, lambda, y, false);
if (_e)
y += *_e;
if (_F)
prod(*_F, z, y, false);
}
void accumQuery(const BlockVector<G1>& query,
const BlockVector<Fr>& scalar,
ProgressCallback* callback = nullptr)
{
#ifdef USE_ASSERT
assert(query.space() == scalar.space() &&
query.block() == scalar.block());
#endif
accumQuery(query.vec(),
scalar.vec(),
callback);
}
// Quantise a subband in in-place transform order
// This version of quantise_subbands assumes multiple quantisers per subband.
// It may be used for either quantising slices or for quantising subbands with codeblocks
const Array2D quantise_subbands(const Array2D& coefficients, const BlockVector& qIndices) {
const Index transformHeight = coefficients.shape()[0];
const Index transformWidth = coefficients.shape()[1];
// TO DO: Check numberOfSubbands=3n+1 ?
const int numberOfSubbands = qIndices.size();
const int waveletDepth = (numberOfSubbands-1)/3;
Index stride, offset; // stride is subsampling factor, offset is subsampling phase
Array2D result(coefficients.ranges());
// Create a view of the coefficients, representing the LL subband, quantise it,
// then assign the result a view of the results array. This puts the quantised
// LL subband into the result array in in-place transform order.
// ArrayIndices2D objects specify the subset of array elements within a view,
// that is they specify the subsampling factor and subsampling phase.
stride = pow(2, waveletDepth);
const ArrayIndices2D LLindices = // LLindices specifies the samples in the LL subband
indices[Range(0,transformHeight,stride)][Range(0,transformWidth,stride)];
result[LLindices] =
quantise_LLSubband(coefficients[LLindices], qIndices[0]);
// Next quantise the other subbands
// Note: Level numbers go from zero for the lowest ("DC") frequencies to depth for
// the high frequencies. This corresponds to the convention in the VC-2 specification.
// Subands go from zero ("DC") to numberOfSubbands-1 for HH at the highest level
for (char level=1, band=1; level<=waveletDepth; ++level) {
stride = pow(2, waveletDepth+1-level);
offset = stride/2;
// Create a view of coefficients corresponding to a subband, then quantise it
//Quantise HL subband
const ArrayIndices2D HLindices = // HLindices specifies the samples in the HL subband
indices[Range(0,transformHeight,stride)][Range(offset,transformWidth,stride)];
result[HLindices] = quantise_block(coefficients[HLindices], qIndices[band++]);
//Quantise LH subband
const ArrayIndices2D LHindices = // LHindices specifies the samples in the LH subband
indices[Range(offset,transformHeight,stride)][Range(0,transformWidth,stride)];
result[LHindices] = quantise_block(coefficients[LHindices], qIndices[band++]);
//Quantise HH subband
const ArrayIndices2D HHindices = // HHindices specifies the samples in the HH subband
indices[Range(offset,transformHeight,stride)][Range(offset,transformWidth,stride)];
result[HHindices] = quantise_block(coefficients[HHindices], qIndices[band++]);
}
return result;
}
PPZK_QueryHK(const BlockVector<Fr>& qap_query)
: PPZK_QueryHK{qap_query.space(), qap_query.block()[0]}
{}
//------------------------------------------------------------------------------
bool postdominatesAll(const BasicBlock *block, const BlockVector &blocks,
const PostDominatorTree *pdt) {
return std::all_of(
blocks.begin(), blocks.end(),
[block, pdt](BasicBlock *iter) { return pdt->dominates(block, iter); });
}
// Template specialization for BasicBlock.
template <> void dumpVector(const BlockVector &toDump) {
errs() << "Size: " << toDump.size() << "\n";
for (auto element : toDump)
errs() << element->getName() << " -- ";
errs() << "\n";
}
/** Extract the master block from <code>problem</code>.
* The constructor also sets up the solver for the newly created master
* block. The master block can only be extracted if all sub-blocks have
* already been extracted.
* @param problem The problem from which to extract the master.
* @param blocks The sub blocks that have already been extracted.
*/
BendersOpt::Block::Block(Problem const *problem, BlockVector const &blocks)
: env(), number(-1), vars(0), rows(0), cplex(0), cb(0)
{
IloNumVarArray problemVars = problem->getVariables();
IloRangeArray problemRanges = problem->getRows();
IloExpr masterObj(env);
IloNumVarArray masterVars(env);
IloRangeArray masterRows(env);
// Find columns that do not intersect block variables and
// copy them to the master block.
IdxMap idxMap;
RowSet rowSet;
for (IloInt j = 0; j < problemVars.getSize(); ++j) {
IloNumVar x = problemVars[j];
if ( problem->getBlock(x) < 0 ) {
// Column is not in a block. Copy it to the master.
IloNumVar v(env, x.getLB(), x.getUB(), x.getType(), x.getName());
varMap.insert(VarMap::value_type(v, x));
masterObj += problem->getObjCoef(x) * v;
idxMap[x] = masterVars.getSize();
masterVars.add(v);
}
else {
// Column is in a block. Collect all rows that intersect
// this column.
RowSet const &intersected = problem->getIntersectedRows(x);
for (RowSet::const_iterator it = intersected.begin();
it != intersected.end(); ++it)
rowSet.insert(*it);
idxMap[x] = -1;
}
}
// Pick up the rows that we need to copy.
// These are the rows that are only intersected by master variables,
// that is, the rows that are not in any block's rowset.
for (IloInt i = 0; i < problemRanges.getSize(); ++i) {
IloRange r = problemRanges[i];
if ( rowSet.find(r) == rowSet.end() ) {
IloRange masterRow(env, r.getLB(), r.getUB(), r.getName());
IloExpr lhs(env);
for (IloExpr::LinearIterator it = r.getLinearIterator(); it.ok(); ++it)
{
lhs += it.getCoef() * masterVars[idxMap[it.getVar()]];
}
masterRow.setExpr(lhs);
masterRows.add(masterRow);
}
}
// Adjust variable indices in blocks so that reference to variables
// in the original problem become references to variables in the master.
for (BlockVector::const_iterator b = blocks.begin(); b != blocks.end(); ++b) {
for (std::vector<FixData>::iterator it = (*b)->fixed.begin(); it != (*b)->fixed.end(); ++it)
it->col = idxMap[problemVars[it->col]];
}
// Create the eta variables, one for each block.
// See the comments at the top of this file for details about the
// eta variables.
IloInt const firsteta = masterVars.getSize();
for (BlockVector::size_type i = 0; i < blocks.size(); ++i) {
std::stringstream s;
s << "_eta" << i;
IloNumVar eta(env, 0.0, IloInfinity, s.str().c_str());
masterObj += eta;
masterVars.add(eta);
}
// Create model and solver instance
vars = masterVars;
rows = masterRows;
IloModel model(env);
model.add(obj = IloObjective(env, masterObj, problem->getObjSense()));
model.add(vars);
model.add(rows);
cplex = IloCplex(model);
cplex.use(cb = new (env) LazyConstraintCallback(env, this, blocks,
firsteta));
for (IloExpr::LinearIterator it = obj.getLinearIterator(); it.ok(); ++it)
objMap.insert(ObjMap::value_type(it.getVar(), it.getCoef()));
}
void SFUtils::DoTopologicalSort( SLSF::Subsystem subsystem ) {
int vertexIndex = 0;
VertexIndexBlockMap vertexIndexBlockMap;
BlockVertexIndexMap blockVertexIndexMap;
BlockVector blockVector = subsystem.Block_kind_children();
for( BlockVector::iterator blvItr = blockVector.begin(); blvItr != blockVector.end(); ++blvItr, ++vertexIndex ) {
SLSF::Block block = *blvItr;
vertexIndexBlockMap[ vertexIndex ] = block;
blockVertexIndexMap[ block ] = vertexIndex;
std::string blockType = block.BlockType();
if ( blockType == "UnitDelay" ) { // check on other delay blocks as well ...
++vertexIndex; // UnitDelay is vertexed twice - one for outputs (timestep n-1), and one for inputs: vertexIndex is as destination, vertexIndex + 1 is as source
}
}
Graph graph( vertexIndex );
LineSet lineSet = subsystem.Line_kind_children();
for( LineSet::iterator lnsItr = lineSet.begin(); lnsItr != lineSet.end() ; ++lnsItr ) {
SLSF::Line line = *lnsItr;
SLSF::Port sourcePort = line.srcLine_end();
SLSF::Port destinationPort = line.dstLine_end();
SLSF::Block sourceBlock = sourcePort.Block_parent();
SLSF::Block destinationBlock = destinationPort.Block_parent();
if ( sourceBlock == subsystem || destinationBlock == subsystem ) continue;
int sourceBlockVertexIndex = blockVertexIndexMap[ sourceBlock ];
if ( static_cast< std::string >( sourceBlock.BlockType() ) == "UnitDelay" ) {
++sourceBlockVertexIndex;
}
int destinationBlockVertexIndex = blockVertexIndexMap[ destinationBlock ];
boost::add_edge( sourceBlockVertexIndex, destinationBlockVertexIndex, graph );
}
LoopDetector loopDetector( graph );
if ( loopDetector.check() ) {
// TODO: add support for loops involving integrator and other stateful blocks
// Determine what Blocks caused the loop
typedef std::map< Vertex, int > VertexStrongComponentIndexMap;
VertexStrongComponentIndexMap vertexStrongComponentIndexMap;
boost::associative_property_map< VertexStrongComponentIndexMap > apmVertexStrongComponentIndexMap( vertexStrongComponentIndexMap );
strong_components( graph, apmVertexStrongComponentIndexMap );
typedef std::vector< Vertex > VertexVector;
typedef std::map< int, VertexVector > StrongComponentIndexVertexGroupMap;
StrongComponentIndexVertexGroupMap strongComponentIndexVertexGroupMap;
for( VertexStrongComponentIndexMap::iterator vsmItr = vertexStrongComponentIndexMap.begin(); vsmItr != vertexStrongComponentIndexMap.end(); ++vsmItr ) {
strongComponentIndexVertexGroupMap[ vsmItr->second ].push_back( vsmItr->first );
}
std::string error( "Dataflow Graph '" + static_cast< std::string >( subsystem.Name() ) + "' has unhandled loops: " );
for( StrongComponentIndexVertexGroupMap::iterator svmItr = strongComponentIndexVertexGroupMap.begin(); svmItr != strongComponentIndexVertexGroupMap.end(); ++svmItr ) {
VertexVector vertexVector = svmItr->second;
if ( vertexVector.size() <= 1 ) continue;
error.append( "\n" );
for( VertexVector::iterator vtvItr = vertexVector.begin(); vtvItr != vertexVector.end(); ++vtvItr ) {
error.append( blockVector[ *vtvItr ].getPath("/") );
error.append( ", " );
}
error.erase( error.size() - 2 );
}
throw udm_exception(error);
}
typedef std::set< Vertex > VertexSet;
typedef std::map< int, VertexSet > PriorityVertexSetMap;
PriorityVertexSetMap priorityVertexSetMap;
for( BlockVector::iterator blvItr = blockVector.begin() ; blvItr != blockVector.end() ; ++blvItr ) {
SLSF::Block block = *blvItr;
int priority = block.Priority();
if ( priority == 0 ) continue;
Vertex vertex = blockVertexIndexMap[ block ];
priorityVertexSetMap[ priority ].insert( vertex );
}
if ( priorityVertexSetMap.size() > 1 ) {
PriorityVertexSetMap::iterator lstPvmItr = priorityVertexSetMap.end();
--lstPvmItr;
for( PriorityVertexSetMap::iterator pvmItr = priorityVertexSetMap.begin() ; pvmItr != lstPvmItr ; ) {
PriorityVertexSetMap::iterator nxtPvmItr = pvmItr;
++nxtPvmItr;
VertexSet &higherPriorityVertexSet = pvmItr->second;
VertexSet &lowerPriorityVertexSet = nxtPvmItr->second;
for( VertexSet::iterator hvsItr = higherPriorityVertexSet.begin() ; hvsItr != higherPriorityVertexSet.end() ; ++hvsItr ) {
for( VertexSet::iterator lvsItr = lowerPriorityVertexSet.begin() ; lvsItr != lowerPriorityVertexSet.end() ; ++lvsItr ) {
boost::add_edge( *hvsItr, *lvsItr, graph );
LoopDetector loopDetector( graph );
if ( loopDetector.check( *hvsItr ) ) {
SLSF::Block higherPriorityBlock = vertexIndexBlockMap[ *hvsItr ];
SLSF::Block lowerPriorityBlock = vertexIndexBlockMap[ *lvsItr ];
std::cerr << "WARNING: Cannot implement priority difference between block \"" << higherPriorityBlock.getPath( "/" ) << "\" (Priority = " << *hvsItr << ") and " << std::endl;
std::cerr << " block \"" << lowerPriorityBlock.getPath( "/" ) << "\" (Priority = " << *lvsItr << "): contradicts topology of subsystem or other implemented block priority order." << std::endl;
boost::remove_edge( *hvsItr, *lvsItr, graph );
}
}
}
pvmItr = nxtPvmItr;
}
}
VertexList vertexList;
boost::topological_sort( graph, std::back_inserter( vertexList ) );
/* PUT ALL "DataStoreMemory" BLOCKS AT END OF "C" SO THEY HAVE HIGHEST PRIORITY */
VertexList::reverse_iterator vtlRit = vertexList.rbegin();
while( vtlRit != vertexList.rend() ) {
int index = *vtlRit;
SLSF::Block block = vertexIndexBlockMap[ index ];
(void)++vtlRit;
if ( block != Udm::null && static_cast< std::string >( block.BlockType() ) == "DataStoreMemory" ) {
VertexList::reverse_iterator vtlRit2 = vtlRit;
vertexList.splice( vertexList.end(), vertexList, vtlRit2.base() );
}
}
int priority = 0;
for( VertexList::reverse_iterator vtlRit = vertexList.rbegin() ; vtlRit != vertexList.rend() ; ++vtlRit ) {
int index = *vtlRit;
SLSF::Block block = vertexIndexBlockMap[ index ];
if ( block == Udm::null ) { // unit delay as source is not registered - we will invoke it initially, and invoke it as destination in the priority order
// const std::string& bt = blk.BlockType();
// assert(bt.compare("UnitDelay") == 0);
/* Unit Delay Block as destination */
continue;
}
block.Priority() = priority++;
}
}
