list* addRowToTable(list* row, list* table){ list* tableDown=table->down; if(tableDown==NULL){ tableDown= (list*) malloc(sizeof(list)); table->down= tableDown; } list* searchNode=searchRight(row->nodeName, tableDown); if(searchNode==NULL){ list* newNode=createListNode(row->nodeName); copyAttributes(newNode,row->attrList); addRight(newNode, tableDown); list*rowColumns= row->down; if(rowColumns==NULL || rowColumns->right==NULL){ yyerror("ERROR\n"); } rowColumns= rowColumns->right; while(rowColumns !=NULL){ addColumnToRow(rowColumns, newNode); rowColumns= rowColumns->right; } }else{ yyerror("ERROR\n"); } }
list* addColumnToRow(list* column, list* row){ list* rowDown= row->down; if(rowDown==NULL){ rowDown= (list*)malloc(sizeof(list)); row->down= rowDown; } list* searchNode= searchRight(column->nodeName, rowDown); if(searchNode==NULL){ list* newNode= createListNode(column->nodeName); copyAttributes(newNode, column->attrList); if(column->text!=NULL && column->down!=NULL){ yyerror("ERROR\n"); } else if(column->text!=NULL) newNode->text= strdup(column->text); addRight(newNode, rowDown); if(column->down!=NULL) addTableToColumn(column->down, newNode); }else yyerror("ERROR\n"); }
/// Execute algorithm. void Schrodinger1D::exec() { double startX = get("StartX"); double endX = get("EndX"); if (endX <= startX) { throw std::invalid_argument("StartX must be <= EndX"); } IFunction_sptr VPot = getClass("VPot"); chebfun vpot( 0, startX, endX ); vpot.bestFit( *VPot ); size_t nBasis = vpot.n() + 1; std::cerr << "n=" << nBasis << std::endl; //if (n < 3) { nBasis = 200; vpot.resize( nBasis ); } const double beta = get("Beta"); auto kinet = new ChebCompositeOperator; kinet->addRight( new ChebTimes(-beta) ); kinet->addRight( new ChebDiff2 ); auto hamiltonian = new ChebPlus; hamiltonian->add('+', kinet ); hamiltonian->add('+', new ChebTimes(VPot) ); GSLMatrix L; hamiltonian->createMatrix( vpot.getBase(), L ); GSLVector d; GSLMatrix v; L.diag( d, v ); std::vector<double> norms = vpot.baseNorm(); assert(norms.size() == L.size1()); assert(norms.size() == L.size2()); for(size_t i = 0; i < norms.size(); ++i) { double factor = 1.0 / norms[i]; for(size_t j = i; j < norms.size(); ++j) { v.multiplyBy(i,j,factor); } } // eigenvectors orthogonality check // GSLMatrix v1 = v; // GSLMatrix tst; // tst = Tr(v1) * v; // std::cerr << tst << std::endl; std::vector<size_t> indx(L.size1()); getSortedIndex( d, indx ); auto eigenvalues = API::TableWorkspace_ptr(dynamic_cast<API::TableWorkspace*>( API::WorkspaceFactory::instance().create("TableWorkspace")) ); eigenvalues->setRowCount(nBasis); setProperty("Eigenvalues", eigenvalues); eigenvalues->addColumn("double","N"); auto nColumn = static_cast<API::TableColumn<double>*>(eigenvalues->getColumn("N").get()); nColumn->asNumeric()->setPlotRole(API::NumericColumn::X); auto& nc = nColumn->data(); eigenvalues->addDoubleColumn("Energy"); auto eColumn = static_cast<API::TableColumn<double>*>(eigenvalues->getColumn("Energy").get()); eColumn->asNumeric()->setPlotRole(API::NumericColumn::Y); auto& ec = eigenvalues->getDoubleData("Energy"); boost::scoped_ptr<ChebfunVector> eigenvectors(new ChebfunVector); chebfun fun0(nBasis,startX,endX); ChebFunction_sptr theSum(new ChebFunction(fun0)); // collect indices of spurious eigenvalues to move them to the back std::vector<size_t> spurious; // index for good eigenvalues size_t n = 0; for(size_t j = 0; j < nBasis; ++j) { size_t i = indx[j]; chebfun fun(fun0); fun.setP(v,i); // check eigenvalues for spurious ones chebfun dfun(fun); dfun.square(); double norm = dfun.integr(); // I am not sure that it's a solid condition if ( norm < 0.999999 ) { // bad eigenvalue spurious.push_back(j); } else { nc[n] = double(n); ec[n] = d[i]; eigenvectors->add(ChebFunction_sptr(new ChebFunction(fun))); // test sum of functions squares *theSum += dfun; // chebfun dfun(fun); // hamiltonian->apply(fun,dfun); // dfun *= fun; // std::cerr << "ener["<<n<<"]=" << ec[n] << ' ' << norm << ' ' << dfun.integr() << std::endl; ++n; } } GSLVector eigv; ChebfunVector *eigf = NULL; improve(hamiltonian, eigenvectors.get(), eigv, &eigf); eigenvalues->setRowCount( eigv.size() ); for(size_t i = 0; i < eigv.size(); ++i) { nc[i] = double(i); ec[i] = eigv[i]; } eigf->add(theSum); setProperty("Eigenvectors",ChebfunVector_sptr(eigf)); //makeQuadrature(eigf); }