MueLu_ClassicalPFactory_def.hpp

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#ifndef MUELU_CLASSICALPFACTORY_DEF_HPP
#define MUELU_CLASSICALPFACTORY_DEF_HPP
 
#include <Xpetra_MultiVectorFactory.hpp>
#include <Xpetra_VectorFactory.hpp>
#include <Xpetra_CrsGraphFactory.hpp>
#include <Xpetra_Matrix.hpp>
#include <Xpetra_Map.hpp>
#include <Xpetra_MapFactory.hpp>
#include <Xpetra_Vector.hpp>
#include <Xpetra_Import.hpp>
#include <Xpetra_ImportUtils.hpp>
#include <Xpetra_IO.hpp>
#include <Xpetra_StridedMapFactory.hpp>
 
#include <Teuchos_OrdinalTraits.hpp>
 
#include "MueLu_MasterList.hpp"
#include "MueLu_Monitor.hpp"
#include "MueLu_PerfUtils.hpp"
#include "MueLu_ClassicalPFactory_decl.hpp"
#include "MueLu_ClassicalMapFactory.hpp"
#include "MueLu_AmalgamationInfo.hpp"
#include "MueLu_GraphBase.hpp"
 
 
//#define CMS_DEBUG
//#define CMS_DUMP
 
namespace {
 
template<class SC>
int Sign(SC val) {
  using STS = typename Teuchos::ScalarTraits<SC>;
  typename STS::magnitudeType MT_ZERO = Teuchos::ScalarTraits<typename STS::magnitudeType>::zero();
  if(STS::real(val) > MT_ZERO) return 1;
  else if(STS::real(val) < MT_ZERO) return -1;
  else return 0;
}
 
}// anonymous namepsace
 
namespace MueLu {
 
 
 
 
  template <class Scalar, class LocalOrdinal, class GlobalOrdinal, class Node>
  RCP<const ParameterList> ClassicalPFactory<Scalar, LocalOrdinal, GlobalOrdinal, Node>::GetValidParameterList() const {
    RCP<ParameterList> validParamList = rcp(new ParameterList());
#define SET_VALID_ENTRY(name) validParamList->setEntry(name, MasterList::getEntry(name))
    SET_VALID_ENTRY("aggregation: deterministic");
    SET_VALID_ENTRY("aggregation: coloring algorithm");
    SET_VALID_ENTRY("aggregation: classical scheme");
 
    // To know if we need BlockNumber
    SET_VALID_ENTRY("aggregation: drop scheme");
    {
      typedef Teuchos::StringToIntegralParameterEntryValidator<int> validatorType;
      validParamList->getEntry("aggregation: classical scheme").setValidator(rcp(new validatorType(Teuchos::tuple<std::string>("direct","ext+i","classical modified"), "aggregation: classical scheme")));
                                                                        
    }
 
#undef SET_VALID_ENTRY
    validParamList->set< RCP<const FactoryBase> >("A",              Teuchos::null, "Generating factory of the matrix A");
    //    validParamList->set< RCP<const FactoryBase> >("UnAmalgamationInfo", Teuchos::null, "Generating factory of UnAmalgamationInfo");
    validParamList->set< RCP<const FactoryBase> >("Graph",       null, "Generating factory of the graph");
    validParamList->set< RCP<const FactoryBase> >("DofsPerNode", null, "Generating factory for variable \'DofsPerNode\', usually the same as for \'Graph\'");
    validParamList->set< RCP<const FactoryBase> >("CoarseMap",         Teuchos::null, "Generating factory of the CoarseMap");
    validParamList->set< RCP<const FactoryBase> >("FC Splitting",         Teuchos::null, "Generating factory of the FC Splitting");
    validParamList->set< RCP<const FactoryBase> >("BlockNumber",        Teuchos::null, "Generating factory for Block Number");
    //    validParamList->set< RCP<const FactoryBase> >("Nullspace",      Teuchos::null, "Generating factory of the nullspace");
 
    return validParamList;
  }
 
  template <class Scalar,class LocalOrdinal, class GlobalOrdinal, class Node>
  void ClassicalPFactory<Scalar, LocalOrdinal, GlobalOrdinal, Node>::DeclareInput(Level& fineLevel, Level& /* coarseLevel */) const {
    Input(fineLevel, "A");
    Input(fineLevel, "Graph");
    Input(fineLevel, "DofsPerNode");
    //    Input(fineLevel, "UnAmalgamationInfo");
    Input(fineLevel, "CoarseMap");
    Input(fineLevel, "FC Splitting");
    
    const ParameterList& pL = GetParameterList();
    std::string drop_algo = pL.get<std::string>("aggregation: drop scheme");
    if (drop_algo.find("block diagonal") != std::string::npos || drop_algo == "signed classical") {
      Input(fineLevel, "BlockNumber");
    }
 
  }
 
  template <class Scalar,class LocalOrdinal, class GlobalOrdinal, class Node>
  void ClassicalPFactory<Scalar, LocalOrdinal, GlobalOrdinal, Node>::Build(Level& fineLevel, Level& coarseLevel) const {
    return BuildP(fineLevel, coarseLevel);
  }
 
  template <class Scalar,class LocalOrdinal, class GlobalOrdinal, class Node>
  void ClassicalPFactory<Scalar, LocalOrdinal, GlobalOrdinal, Node>::BuildP(Level& fineLevel, Level& coarseLevel) const {
    FactoryMonitor m(*this, "Build", coarseLevel);
    // using STS = Teuchos::ScalarTraits<SC>;
 
    // We start by assuming that someone did a reasonable strength of connection
    // algorithm before we start to get our Graph, DofsPerNode and UnAmalgamationInfo
 
    // We begin by getting a MIS (from a graph coloring) and then at that point we need
    // to start generating entries for the prolongator.
    RCP<const Matrix>      A        = Get< RCP<Matrix> >(fineLevel, "A");
    RCP<const Map> ownedCoarseMap   = Get<RCP<const Map> >(fineLevel,"CoarseMap");
    RCP<const LocalOrdinalVector> owned_fc_splitting = Get<RCP<LocalOrdinalVector> >(fineLevel,"FC Splitting");
    RCP<const GraphBase> graph      = Get< RCP<GraphBase> >(fineLevel, "Graph");
    //    LO nDofsPerNode                 = Get<LO>(fineLevel, "DofsPerNode");
    //    RCP<AmalgamationInfo> amalgInfo = Get< RCP<AmalgamationInfo> >     (fineLevel, "UnAmalgamationInfo");
    RCP<const Import>    Importer   = A->getCrsGraph()->getImporter();
    Xpetra::UnderlyingLib lib = ownedCoarseMap->lib();
 
    //    RCP<MultiVector> fineNullspace = Get< RCP<MultiVector> > (fineLevel, "Nullspace");
    RCP<Matrix> P;
    //    SC SC_ZERO = STS::zero();
    LO LO_INVALID = Teuchos::OrdinalTraits<LO>::invalid();
    const point_type C_PT = ClassicalMapFactory::C_PT;
    const point_type F_PT = ClassicalMapFactory::F_PT;
    const ParameterList& pL = GetParameterList();
  
    // FIXME: This guy doesn't work right now for NumPDEs != 1
    TEUCHOS_TEST_FOR_EXCEPTION(A->GetFixedBlockSize() != 1, Exceptions::RuntimeError,"ClassicalPFactory: Multiple PDEs per node not supported yet");
 
    // NOTE: Let's hope we never need to deal with this case
    TEUCHOS_TEST_FOR_EXCEPTION(!A->getRowMap()->isSameAs(*A->getDomainMap()),Exceptions::RuntimeError,"ClassicalPFactory: MPI Ranks > 1 not supported yet");
 
    // Do we need ghosts rows of A and myPointType?
    std::string scheme = pL.get<std::string>("aggregation: classical scheme");
    bool need_ghost_rows =false;
    if(scheme == "ext+i")
      need_ghost_rows=true;
    else if(scheme == "direct")
      need_ghost_rows=false;
    else if(scheme == "classical modified")
      need_ghost_rows=true;
    // NOTE: ParameterList validator will check this guy so we don't really need an "else" here
 
    if (GetVerbLevel() & Statistics1) {
      GetOStream(Statistics1) << "ClassicalPFactory: scheme = "<<scheme<<std::endl;
    }
 
    // Ghost the FC splitting and grab the data (if needed)
    RCP<const LocalOrdinalVector> fc_splitting;
    ArrayRCP<const LO> myPointType;
    if(Importer.is_null()) {
      fc_splitting = owned_fc_splitting;
    }
    else {
      RCP<LocalOrdinalVector> fc_splitting_nonconst = LocalOrdinalVectorFactory::Build(A->getCrsGraph()->getColMap());
      fc_splitting_nonconst->doImport(*owned_fc_splitting,*Importer,Xpetra::INSERT);
      fc_splitting = fc_splitting_nonconst;
    }
    myPointType = fc_splitting->getData(0);
 
 
    /* Ghost A (if needed) */
    RCP<const Matrix> Aghost;
    RCP<const LocalOrdinalVector> fc_splitting_ghost;
    ArrayRCP<const LO> myPointType_ghost;
    RCP<const Import> remoteOnlyImporter;
    if(need_ghost_rows && !Importer.is_null()){
      ArrayView<const LO> remoteLIDs = Importer->getRemoteLIDs();
      size_t numRemote = Importer->getNumRemoteIDs();
      Array<GO> remoteRows(numRemote);
      for (size_t i = 0; i < numRemote; i++)
        remoteRows[i] = Importer->getTargetMap()->getGlobalElement(remoteLIDs[i]);
 
      RCP<const Map> remoteRowMap = MapFactory::Build(lib,Teuchos::OrdinalTraits<Xpetra::global_size_t>::invalid(), remoteRows(),
                                                      A->getDomainMap()->getIndexBase(), A->getDomainMap()->getComm());
 
      remoteOnlyImporter = Importer->createRemoteOnlyImport(remoteRowMap);
      RCP<const CrsMatrix> Acrs = rcp_dynamic_cast<const CrsMatrixWrap>(A)->getCrsMatrix();
      RCP<CrsMatrix> Aghost_crs = CrsMatrixFactory::Build(Acrs,*remoteOnlyImporter,A->getDomainMap(),remoteOnlyImporter->getTargetMap());
      Aghost = rcp(new CrsMatrixWrap(Aghost_crs));
      // CAG: It seems that this isn't actually needed?
      // We also may need need to ghost myPointType for Aghost
      // RCP<const Import> Importer2 = Aghost->getCrsGraph()->getImporter();
      // if(Importer2.is_null()) {
      //   RCP<LocalOrdinalVector> fc_splitting_ghost_nonconst = LocalOrdinalVectorFactory::Build(Aghost->getColMap());
      //   fc_splitting_ghost_nonconst->doImport(*owned_fc_splitting,*Importer,Xpetra::INSERT);
      //   fc_splitting_ghost = fc_splitting_ghost_nonconst;
      //   myPointType_ghost  = fc_splitting_ghost->getData(0);
      // }
    }
 
    /* Generate the ghosted Coarse map using the "Tuminaro maneuver" (if needed)*/
    RCP<const Map> coarseMap;
    if(Importer.is_null())
      coarseMap = ownedCoarseMap;
    else {
      // Generate a domain vector with the coarse ID's as entries for C points
      GhostCoarseMap(*A,*Importer,myPointType,ownedCoarseMap,coarseMap);
    }
 
    /* Get the block number, if we need it (and ghost it) */
    RCP<LocalOrdinalVector>  BlockNumber;
    std::string drop_algo = pL.get<std::string>("aggregation: drop scheme");
    if (drop_algo.find("block diagonal") != std::string::npos || drop_algo == "signed classical") {
      RCP<LocalOrdinalVector> OwnedBlockNumber;
      OwnedBlockNumber = Get<RCP<LocalOrdinalVector> >(fineLevel, "BlockNumber");
      if(Importer.is_null())
        BlockNumber = OwnedBlockNumber;
      else{
        BlockNumber = LocalOrdinalVectorFactory::Build(A->getColMap());
        BlockNumber->doImport(*OwnedBlockNumber,*Importer,Xpetra::INSERT);
      }
    }
 
#if defined(CMS_DEBUG) || defined(CMS_DUMP)
    {
      RCP<const CrsMatrix> Acrs = rcp_dynamic_cast<const CrsMatrixWrap>(A)->getCrsMatrix();
      int rank = A->getRowMap()->getComm()->getRank();
      printf("[%d] A local size = %dx%d\n",rank,(int)Acrs->getRowMap()->getLocalNumElements(),(int)Acrs->getColMap()->getLocalNumElements());
 
      printf("[%d] graph local size = %dx%d\n",rank,(int)graph->GetDomainMap()->getLocalNumElements(),(int)graph->GetImportMap()->getLocalNumElements());
 
      std::ofstream ofs(std::string("dropped_graph_") + std::to_string(fineLevel.GetLevelID())+std::string("_") + std::to_string(rank) + std::string(".dat"),std::ofstream::out);
      RCP<Teuchos::FancyOStream> fancy = Teuchos::fancyOStream(Teuchos::rcpFromRef(ofs));
      graph->print(*fancy,Debug);
      std::string out_fc = std::string("fc_splitting_") + std::to_string(fineLevel.GetLevelID()) +std::string("_") + std::to_string(rank)+ std::string(".dat");
      std::string out_block = std::string("block_number_") + std::to_string(fineLevel.GetLevelID()) +std::string("_") + std::to_string(rank)+ std::string(".dat");
 
      // We don't support writing LO vectors in Xpetra (boo!) so....
      using real_type = typename Teuchos::ScalarTraits<SC>::magnitudeType;
      using RealValuedMultiVector = typename Xpetra::MultiVector<real_type,LO,GO,NO>;
      typedef Xpetra::MultiVectorFactory<real_type,LO,GO,NO> RealValuedMultiVectorFactory;
 
      RCP<RealValuedMultiVector> mv = RealValuedMultiVectorFactory::Build(fc_splitting->getMap(),1);
      ArrayRCP<real_type> mv_data= mv->getDataNonConst(0);
 
      // FC Splitting
      ArrayRCP<const LO> fc_data= fc_splitting->getData(0);
      for(LO i=0; i<(LO)fc_data.size(); i++)
        mv_data[i] = Teuchos::as<real_type>(fc_data[i]);
      Xpetra::IO<real_type,LO,GO,NO>::Write(out_fc,*mv);
 
      // Block Number
      if(!BlockNumber.is_null()) {
        RCP<RealValuedMultiVector> mv2 = RealValuedMultiVectorFactory::Build(BlockNumber->getMap(),1);
        ArrayRCP<real_type> mv_data2= mv2->getDataNonConst(0);
        ArrayRCP<const LO> b_data= BlockNumber->getData(0);
        for(LO i=0; i<(LO)b_data.size(); i++) {
          mv_data2[i] = Teuchos::as<real_type>(b_data[i]);
        }
        Xpetra::IO<real_type,LO,GO,NO>::Write(out_block,*mv2);
      }
    }
 
 
#endif
 
  
    /* Generate reindexing arrays */
    // Note: cpoint2pcol is ghosted if myPointType is
    // NOTE: Since the ghosted coarse column map follows the ordering of
    // the fine column map, this *should* work, because it is in local indices.
    // pcol2cpoint - Takes a LCID for P and turns in into an LCID for A.
    // cpoint2pcol - Takes a LCID for A --- if it is a C Point --- and turns in into an LCID for P.
    Array<LO> cpoint2pcol(myPointType.size(),LO_INVALID);
    Array<LO> pcol2cpoint(coarseMap->getLocalNumElements(),LO_INVALID);
    LO num_c_points = 0;
    LO num_f_points =0;
    for(LO i=0; i<(LO) myPointType.size(); i++) {
        if(myPointType[i] == C_PT) {
        cpoint2pcol[i] = num_c_points;
        num_c_points++;
      }
      else if (myPointType[i] == F_PT)
        num_f_points++;
    }
    for(LO i=0; i<(LO)cpoint2pcol.size(); i++) {
      if(cpoint2pcol[i] != LO_INVALID)
        pcol2cpoint[cpoint2pcol[i]] =i;
    }
 
    // Generate edge strength flags (this will make everything easier later)
    // These do *not* need to be ghosted (unlike A)
    Teuchos::Array<size_t> eis_rowptr;
    Teuchos::Array<bool> edgeIsStrong;
    {
      SubFactoryMonitor sfm(*this,"Strength Flags",coarseLevel);
      GenerateStrengthFlags(*A,*graph,eis_rowptr,edgeIsStrong);
    }
 
    // Phase 3: Generate the P matrix
    RCP<const Map> coarseColMap = coarseMap;
    RCP<const Map> coarseDomainMap = ownedCoarseMap;
    if(scheme == "ext+i") {
      SubFactoryMonitor sfm(*this,"Ext+i Interpolation",coarseLevel);
      Coarsen_Ext_Plus_I(*A,Aghost,*graph,coarseColMap,coarseDomainMap,num_c_points,num_f_points,myPointType(),myPointType_ghost(),cpoint2pcol,pcol2cpoint,eis_rowptr,edgeIsStrong,BlockNumber,P);
    }
    else if(scheme == "direct") {
      SubFactoryMonitor sfm(*this,"Direct Interpolation",coarseLevel);
      Coarsen_Direct(*A,Aghost,*graph,coarseColMap,coarseDomainMap,num_c_points,num_f_points,myPointType(),myPointType_ghost(),cpoint2pcol,pcol2cpoint,eis_rowptr,edgeIsStrong,BlockNumber,P);
    }
    else if(scheme == "classical modified") {
      SubFactoryMonitor sfm(*this,"Classical Modified Interpolation",coarseLevel);
      Coarsen_ClassicalModified(*A,Aghost,*graph,coarseColMap,coarseDomainMap,num_c_points,num_f_points,myPointType(),myPointType_ghost(),cpoint2pcol,pcol2cpoint,eis_rowptr,edgeIsStrong,BlockNumber,remoteOnlyImporter,P);
    }
    // NOTE: ParameterList validator will check this guy so we don't really need an "else" here
 
#ifdef CMS_DEBUG
    Xpetra::IO<SC,LO,GO,NO>::Write("classical_p.mat."+std::to_string(coarseLevel.GetLevelID()), *P);
    // Xpetra::IO<SC,LO,GO,NO>::WriteLocal("classical_p.mat."+std::to_string(coarseLevel.GetLevelID()), *P);
#endif
 
    // Save output
    Set(coarseLevel,"P",P);
    RCP<const CrsGraph> pg = P->getCrsGraph();
    Set(coarseLevel,"P Graph",pg);
 
    //RCP<MultiVector> coarseNullspace = MultiVectorFactory::Build(coarseMap, fineNullspace->getNumVectors());
    //    P->apply(*fineNullspace, *coarseNullspace, Teuchos::TRANS, Teuchos::ScalarTraits<SC>::one(), Teuchos::ScalarTraits<SC>::zero());
    //    Set(coarseLevel, "Nullspace", coarseNullspace);
 
    if (IsPrint(Statistics1)) {
      RCP<ParameterList> params = rcp(new ParameterList());
      params->set("printLoadBalancingInfo", true);
      GetOStream(Statistics1) << PerfUtils::PrintMatrixInfo(*P, "P", params);
    }
  }
/* ************************************************************************* */
template <class Scalar,class LocalOrdinal, class GlobalOrdinal, class Node>
void ClassicalPFactory<Scalar, LocalOrdinal, GlobalOrdinal, Node>::
Coarsen_ClassicalModified(const Matrix & A,const RCP<const Matrix> & Aghost, const GraphBase & graph,  RCP<const Map> & coarseColMap, RCP<const Map> & coarseDomainMap, LO num_c_points, LO num_f_points, const Teuchos::ArrayView<const LO> & myPointType, const Teuchos::ArrayView<const LO> & myPointType_ghost, const Teuchos::Array<LO> & cpoint2pcol, const Teuchos::Array<LO> & pcol2cpoint, Teuchos::Array<size_t> & eis_rowptr, Teuchos::Array<bool> & edgeIsStrong, RCP<LocalOrdinalVector> & BlockNumber, RCP<const Import> remoteOnlyImporter,RCP<Matrix> & P) const {
    /* ============================================================= */
    /* Phase 3 : Classical Modified Interpolation                    */
    /* De Sterck, Falgout, Nolting and Yang. "Distance-two           */
    /* interpolation for parallel algebraic multigrid", NLAA 2008    */
    /* 15:115-139                                                    */
    /* ============================================================= */
    /* Definitions:                                                        */
    /* F = F-points                                                        */
    /* C = C-points                                                        */
    /* N_i = non-zero neighbors of node i                                  */
    /* S_i = {j\in N_i | j strongly influences i } [strong neighbors of i] */
    /* F_i^s = F \cap S_i [strong F-neighbors of i]                        */
    /* C_i^s = C \cap S_i [strong C-neighbors of i]                        */
 
    /* N_i^w = N_i\ (F_i^s \cup C_i^s) [weak neighbors of i]               */
    /*         This guy has a typo.  The paper had a \cap instead of \cup  */
    /*         I would note that this set can contain both F-points and    */
    /*         C-points.  They're just weak neighbors of this guy.         */
    /*         Note that N_i^w \cup F_i^s \cup C_i^s = N_i by construction */
 
 
    /* \bar{a}_ij = {    0, if sign(a_ij) == sign(a_ii)                    */
    /*              { a_ij, otherwise                                      */
 
    /* F_i^s\star = {k\in N_i | C_i^s \cap C_k^s = \emptyset}              */
    /*              [set of F-neighbors of i that do not share a strong    */
    /*               C-neighbor with i]                                    */
 
 
    /* Rewritten Equation (9) on p. 120                                    */
    /* \tilde{a}_ii =  (a_ij + \sum_{k\in{N_i^w \cup F_i^s\star}} a_ik     */
    /*                                                                     */
    /* f_ij = \sum_{k\in{F_i^s\setminusF_i^s*}} \frac{a_ik \bar{a}_kj}{\sum_{m\inC_i^s \bar{a}_km}}    */
    /*                                                                     */
    /* w_ij = \frac{1}{\tilde{a}_ii} ( a_ij + f_ij)  for all j in C_i^s    */
  
    //    const point_type F_PT = ClassicalMapFactory::F_PT;
    const point_type C_PT = ClassicalMapFactory::C_PT;
    const point_type DIRICHLET_PT = ClassicalMapFactory::DIRICHLET_PT;
    using STS = typename Teuchos::ScalarTraits<SC>;
    LO LO_INVALID = Teuchos::OrdinalTraits<LO>::invalid();
    //    size_t ST_INVALID = Teuchos::OrdinalTraits<size_t>::invalid();
    SC SC_ZERO = STS::zero();
#ifdef CMS_DEBUG
    int rank = A.getRowMap()->getComm()->getRank();
#endif
 
    // Get the block number if we have it.
    ArrayRCP<const LO> block_id;
    if(!BlockNumber.is_null())
      block_id = BlockNumber->getData(0);
 
    // Initial (estimated) allocation
    // NOTE: If we only used Tpetra, then we could use these guys as is, but because Epetra, we can't, so there
    // needs to be a copy below.
    size_t Nrows = A.getLocalNumRows();
    double c_point_density = (double)num_c_points / (num_c_points+num_f_points);
    double mean_strong_neighbors_per_row = (double) graph.GetNodeNumEdges() / graph.GetNodeNumVertices();
    //    double mean_neighbors_per_row = (double)A.getLocalNumEntries() / Nrows;
    double nnz_per_row_est = c_point_density*mean_strong_neighbors_per_row;
 
    size_t nnz_est = std::max(Nrows,std::min((size_t)A.getLocalNumEntries(),(size_t)(nnz_per_row_est*Nrows)));
    Array<size_t> tmp_rowptr(Nrows+1);
    Array<LO> tmp_colind(nnz_est);
 
    // Algorithm (count+realloc)
    // For each row, i,
    // - Count the number of elements in \hat{C}_j, aka [C-neighbors and C-neighbors of strong F-neighbors of i]
    size_t ct=0;
    for(LO row=0; row < (LO) Nrows; row++) {
      size_t row_start = eis_rowptr[row];
      ArrayView<const LO> indices;
      ArrayView<const SC> vals;
      std::set<LO> C_hat;
      if(myPointType[row] == DIRICHLET_PT) {
        // Dirichlet points get ignored completely
      }
      else if(myPointType[row] == C_PT) {
        // C-Points get a single 1 in their row
        C_hat.insert(cpoint2pcol[row]);
      }
      else {
        // F-Points have a more complicated interpolation
 
        // C-neighbors of row
        A.getLocalRowView(row, indices, vals);
        for(LO j=0; j<indices.size(); j++)
          if(myPointType[indices[j]] == C_PT && edgeIsStrong[row_start + j])
            C_hat.insert(cpoint2pcol[indices[j]]);
      }// end else
      
      // Realloc if needed
      if(ct + (size_t)C_hat.size() > (size_t)tmp_colind.size()) {
        tmp_colind.resize(std::max(ct+(size_t)C_hat.size(),(size_t)2*tmp_colind.size()));
      }
      
      // Copy
      std::copy(C_hat.begin(), C_hat.end(),tmp_colind.begin()+ct);
      ct+=C_hat.size();
      tmp_rowptr[row+1] = tmp_rowptr[row] + C_hat.size();
    }
    // Resize down
    tmp_colind.resize(tmp_rowptr[Nrows]);
 
    RCP<CrsMatrix> Pcrs = CrsMatrixFactory::Build(A.getRowMap(),coarseColMap,0);
    ArrayRCP<size_t>  P_rowptr;
    ArrayRCP<LO>      P_colind;
    ArrayRCP<SC>      P_values;
 
    if (A.getRowMap()->lib() == Xpetra::UseTpetra) {
      P_rowptr = Teuchos::arcpFromArray(tmp_rowptr);
      P_colind = Teuchos::arcpFromArray(tmp_colind);
      P_values.resize(P_rowptr[Nrows]);
    } else {
      // Make the matrix and then get the graph out of it (necessary for Epetra)
      // NOTE: The lack of an Epetra_CrsGraph::ExpertStaticFillComplete makes this
      // impossible to do the obvious way
      Pcrs->allocateAllValues(tmp_rowptr[Nrows],P_rowptr,P_colind,P_values);
      std::copy(tmp_rowptr.begin(),tmp_rowptr.end(), P_rowptr.begin());
      std::copy(tmp_colind.begin(),tmp_colind.end(), P_colind.begin());
      Pcrs->setAllValues(P_rowptr,P_colind,P_values);
      Pcrs->expertStaticFillComplete(/*domain*/coarseDomainMap, /*range*/A.getDomainMap());
    }
 
    // Generate a remote-ghosted version of the graph (if we're in parallel)
    RCP<const CrsGraph> Pgraph;
    RCP<const CrsGraph> Pghost;
    // TODO: We might want to be more efficient here and actually use
    // Pgraph in the matrix constructor.
    ArrayRCP<const size_t> Pghost_rowptr;
    ArrayRCP<const LO> Pghost_colind;
    if(!remoteOnlyImporter.is_null()) {
      if (A.getRowMap()->lib() == Xpetra::UseTpetra) {
        RCP<CrsGraph> tempPgraph = CrsGraphFactory::Build(A.getRowMap(),coarseColMap,P_rowptr,P_colind);
        tempPgraph->fillComplete(coarseDomainMap,A.getDomainMap());
        Pgraph = tempPgraph;
      } else {
        // Epetra does not have a graph constructor that uses rowptr and colind.
        Pgraph = Pcrs->getCrsGraph();
      }
      TEUCHOS_ASSERT(!Pgraph.is_null());
      Pghost = CrsGraphFactory::Build(Pgraph,*remoteOnlyImporter,Pgraph->getDomainMap(),remoteOnlyImporter->getTargetMap());
      Pghost->getAllIndices(Pghost_rowptr,Pghost_colind);
    }
 
    // Gustavson-style perfect hashing
    ArrayRCP<LO> Acol_to_Pcol(A.getColMap()->getLocalNumElements(),LO_INVALID);
 
    // Get a quick reindexing array from Pghost LCIDs to P LCIDs
    ArrayRCP<LO> Pghostcol_to_Pcol;
    if(!Pghost.is_null()) {
      Pghostcol_to_Pcol.resize(Pghost->getColMap()->getLocalNumElements(),LO_INVALID);
      for(LO i=0; i<(LO) Pghost->getColMap()->getLocalNumElements(); i++)
        Pghostcol_to_Pcol[i] = Pgraph->getColMap()->getLocalElement(Pghost->getColMap()->getGlobalElement(i));
    }//end Pghost
 
    // Get a quick reindexing array from Aghost LCIDs to A LCIDs
    ArrayRCP<LO> Aghostcol_to_Acol;
    if(!Aghost.is_null()) {
      Aghostcol_to_Acol.resize(Aghost->getColMap()->getLocalNumElements(),LO_INVALID);
      for(LO i=0; i<(LO)Aghost->getColMap()->getLocalNumElements(); i++)
        Aghostcol_to_Acol[i] = A.getColMap()->getLocalElement(Aghost->getColMap()->getGlobalElement(i));
    }//end Aghost
 
 
    // Algorithm (numeric)
    for(LO i=0; i < (LO)Nrows; i++) {
      if(myPointType[i] == DIRICHLET_PT) {
        // Dirichlet points get ignored completely
#ifdef CMS_DEBUG
        // DEBUG
        printf("[%d] ** A(%d,:) is a Dirichlet-Point.\n",rank,i);
#endif
      }
      else if (myPointType[i] == C_PT) {
        // C Points get a single 1 in their row
        P_values[P_rowptr[i]] = Teuchos::ScalarTraits<SC>::one();
#ifdef CMS_DEBUG
        // DEBUG
        printf("[%d] ** A(%d,:) is a C-Point.\n",rank,i);
#endif
      }
      else {
        // F Points get all of the fancy stuff
#ifdef CMS_DEBUG
        // DEBUG
        printf("[%d] ** A(%d,:) is a F-Point.\n",rank,i);
#endif
        
        // Get all of the relevant information about this row
        ArrayView<const LO> A_indices_i, A_indices_k;
        ArrayView<const SC> A_vals_i, A_vals_k;
        A.getLocalRowView(i, A_indices_i, A_vals_i);
        size_t row_start = eis_rowptr[i];
        
        ArrayView<const LO> P_indices_i  = P_colind.view(P_rowptr[i],P_rowptr[i+1] - P_rowptr[i]);
        ArrayView<SC> P_vals_i     = P_values.view(P_rowptr[i],P_rowptr[i+1] - P_rowptr[i]);
        
        // FIXME: Do we need this?
        for(LO j=0; j<(LO)P_vals_i.size(); j++)
          P_vals_i[j] = SC_ZERO;
 
        // Stash the hash:  Flag any strong C-points with their index into P_colind
        // NOTE:  We'll consider any points that are LO_INVALID or less than P_rowptr[i] as not strong C-points
        for(LO j=0; j<(LO)P_indices_i.size(); j++)  {
          Acol_to_Pcol[pcol2cpoint[P_indices_i[j]]] = P_rowptr[i] + j;
        }
 
        // Loop over the entries in the row
        SC first_denominator  = SC_ZERO;
#ifdef CMS_DEBUG
        SC a_ii = SC_ZERO;
#endif
        for(LO k0=0; k0<(LO)A_indices_i.size(); k0++) {
          LO k      = A_indices_i[k0];
          SC a_ik   = A_vals_i[k0];
          LO pcol_k = Acol_to_Pcol[k];
 
          if(k == i) {
            // Case A: Diagonal value (add to first denominator)
            // FIXME:  Add BlockNumber matching here
            first_denominator += a_ik;
#ifdef CMS_DEBUG
            a_ii = a_ik;
            printf("- A(%d,%d) is the diagonal\n",i,k);
#endif
 
          }
          else if(myPointType[k] == DIRICHLET_PT) {
            // Case B: Ignore dirichlet connections completely
#ifdef CMS_DEBUG
            printf("- A(%d,%d) is a Dirichlet point\n",i,k);
#endif
            
          }
          else if(pcol_k != LO_INVALID && pcol_k >= (LO)P_rowptr[i]) {
            // Case C: a_ik is strong C-Point (goes directly into the weight)
            P_values[pcol_k] += a_ik;
#ifdef CMS_DEBUG
            printf("- A(%d,%d) is a strong C-Point\n",i,k);
#endif
          }
          else if (!edgeIsStrong[row_start + k0]) {
            // Case D: Weak non-Dirichlet neighbor (add to first denominator)
            if(block_id.size() == 0 || block_id[i] == block_id[k])  {
              first_denominator += a_ik;
#ifdef CMS_DEBUG
              printf("- A(%d,%d) is weak adding to diagonal(%d,%d) (%6.4e)\n",i,k,block_id[i],block_id[k],a_ik);
            }
            else {
              printf("- A(%d,%d) is weak but does not match blocks (%d,%d), discarding\n",i,k,block_id[i],block_id[k]);
#endif
            }
            
          }
          else {//Case E
            // Case E: Strong F-Point (adds to the first denominator if we don't share a
            // a strong C-Point with i; adds to the second denominator otherwise)
#ifdef CMS_DEBUG
            printf("- A(%d,%d) is a strong F-Point\n",i,k);
#endif
 
            SC a_kk = SC_ZERO;
            SC second_denominator = SC_ZERO;
            int sign_akk = 0;
            
            if(k < (LO)Nrows) {
              // Grab the diagonal a_kk
              A.getLocalRowView(k, A_indices_k, A_vals_k);
              for(LO m0=0; m0<(LO)A_indices_k.size(); m0++){
                LO m    = A_indices_k[m0];
                if(k == m) {
                  a_kk = A_vals_k[m0];
                  break;
                }
              }//end for A_indices_k
              
              // Compute the second denominator term
              sign_akk = Sign(a_kk);
              for(LO m0=0; m0<(LO)A_indices_k.size(); m0++){
                LO m    = A_indices_k[m0];
                if(m != k && Acol_to_Pcol[A_indices_k[m0]] >=  (LO)P_rowptr[i]) {
                  SC a_km = A_vals_k[m0];
                  second_denominator+= (Sign(a_km) == sign_akk ? SC_ZERO : a_km);
                }
              }//end for A_indices_k
 
              // Now we have the second denominator, for this particular strong F point.
              // So we can now add the sum to the w_ij components for the P values
              if(second_denominator != SC_ZERO) {
                for(LO j0=0; j0<(LO)A_indices_k.size(); j0++) {
                  LO j    = A_indices_k[j0];
                  // NOTE: Row k should be in fis_star, so I should have to check for diagonals here
                  //                  printf("Acol_to_Pcol[%d] = %d P_values.size() = %d\n",j,Acol_to_Pcol[j],(int)P_values.size());
                  if(Acol_to_Pcol[j] >=  (LO)P_rowptr[i]) {
                    SC a_kj = A_vals_k[j0];
                    SC sign_akj_val = sign_akk == Sign(a_kj) ? SC_ZERO : a_kj;
                    P_values[Acol_to_Pcol[j]] += a_ik * sign_akj_val / second_denominator;
#ifdef CMS_DEBUG
                    printf("- - Unscaled P(%d,A-%d) += %6.4e = %5.4e\n",i,j,a_ik * sign_akj_val / second_denominator,P_values[Acol_to_Pcol[j]]);
#endif
                  }
                }//end for A_indices_k
              }//end if second_denominator != 0
              else {
#ifdef CMS_DEBUG
                printf("- - A(%d,%d) second denominator is zero\n",i,k);
#endif
                if(block_id.size() == 0 || block_id[i] == block_id[k])
                  first_denominator += a_ik;
              }//end else second_denominator != 0
            }// end if k < Nrows
            else {
              // Ghost row
              LO kless = k-Nrows;
              // Grab the diagonal a_kk
              // NOTE: ColMap is not locally fitted to the RowMap
              // so we need to check GIDs here
              Aghost->getLocalRowView(kless, A_indices_k, A_vals_k);
              GO k_g = Aghost->getRowMap()->getGlobalElement(kless);
              for(LO m0=0; m0<(LO)A_indices_k.size(); m0++){
                GO m_g    = Aghost->getColMap()->getGlobalElement(A_indices_k[m0]);
                if(k_g == m_g) {
                  a_kk = A_vals_k[m0];
                  break;
                }
              }//end for A_indices_k
 
              // Compute the second denominator term
              sign_akk = Sign(a_kk);
              for(LO m0=0; m0<(LO)A_indices_k.size(); m0++){
                GO m_g    = Aghost->getColMap()->getGlobalElement(A_indices_k[m0]);
                LO mghost = A_indices_k[m0];//Aghost LCID
                LO m = Aghostcol_to_Acol[mghost]; //A's LID (could be LO_INVALID)
                if(m_g != k_g && m != LO_INVALID && Acol_to_Pcol[m] >=  (LO)P_rowptr[i]) {
                  SC a_km = A_vals_k[m0];
                  second_denominator+= (Sign(a_km) == sign_akk ? SC_ZERO : a_km);
                }
              }//end for A_indices_k
              
              
              // Now we have the second denominator, for this particular strong F point.
              // So we can now add the sum to the w_ij components for the P values
              if(second_denominator != SC_ZERO) {
                for(LO j0=0; j0<(LO)A_indices_k.size(); j0++){
                  LO jghost = A_indices_k[j0];//Aghost LCID
                  LO j = Aghostcol_to_Acol[jghost]; //A's LID (could be LO_INVALID)
                  // NOTE: Row k should be in fis_star, so I should have to check for diagonals here
                  if((j != LO_INVALID) && (Acol_to_Pcol[j] >=  (LO)P_rowptr[i])) {
                    SC a_kj = A_vals_k[j0];
                    SC sign_akj_val = sign_akk == Sign(a_kj) ? SC_ZERO : a_kj;
                    P_values[Acol_to_Pcol[j]] += a_ik * sign_akj_val / second_denominator;
#ifdef CMS_DEBUG
                    printf("- - Unscaled P(%d,A-%d) += %6.4e\n",i,j,a_ik * sign_akj_val / second_denominator);
#endif
                  }
 
                }//end for A_indices_k
              }//end if second_denominator != 0
              else {
#ifdef CMS_DEBUG
                printf("- - A(%d,%d) second denominator is zero\n",i,k);
#endif
                if(block_id.size() == 0 || block_id[i] == block_id[k])
                  first_denominator += a_ik;
              }//end else second_denominator != 0
            }//end else k < Nrows
          }//end else Case A,...,E
                           
        }//end for A_indices_i
 
        // Now, downscale by the first_denominator
        if(first_denominator != SC_ZERO) {
          for(LO j0=0; j0<(LO)P_indices_i.size(); j0++)  {
#ifdef CMS_DEBUG
            SC old_pij = P_vals_i[j0];
            P_vals_i[j0] /= -first_denominator;
            printf("P(%d,%d) = %6.4e = %6.4e / (%6.4e + %6.4e)\n",i,P_indices_i[j0],P_vals_i[j0],old_pij,a_ii,first_denominator - a_ii);
#else
            P_vals_i[j0] /= -first_denominator;
#endif
          }//end for P_indices_i
        }//end if first_denominator != 0
 
      }//end else C-Point
 
    }// end if i < Nrows
 
    // Finish up
    Pcrs->setAllValues(P_rowptr,P_colind,P_values);
    Pcrs->expertStaticFillComplete(/*domain*/coarseDomainMap, /*range*/A.getDomainMap());
    // Wrap from CrsMatrix to Matrix
    P = rcp(new CrsMatrixWrap(Pcrs));
 
}//end Coarsen_ClassicalModified
 
 
/* ************************************************************************* */
template <class Scalar,class LocalOrdinal, class GlobalOrdinal, class Node>
void ClassicalPFactory<Scalar, LocalOrdinal, GlobalOrdinal, Node>::
Coarsen_Direct(const Matrix & A,const RCP<const Matrix> & Aghost, const GraphBase & graph,  RCP<const Map> & coarseColMap, RCP<const Map> & coarseDomainMap, LO num_c_points, LO num_f_points, const Teuchos::ArrayView<const LO> & myPointType, const Teuchos::ArrayView<const LO> & myPointType_ghost, const Teuchos::Array<LO> & cpoint2pcol, const Teuchos::Array<LO> & pcol2cpoint, Teuchos::Array<size_t> & eis_rowptr, Teuchos::Array<bool> & edgeIsStrong, RCP<LocalOrdinalVector> & BlockNumber, RCP<Matrix> & P) const {
    /* ============================================================= */
    /* Phase 3 : Direct Interpolation                                */
    /* We do not use De Sterck, Falgout, Nolting and Yang (2008)     */
    /* here.  Instead we follow:                                     */
    /* Trottenberg, Oosterlee and Schueller, Multigrid, 2001.        */
    /* with some modifications inspirted by PyAMG                    */
    /* ============================================================= */
    /* Definitions:                                                        */
    /* F = F-points                                                        */
    /* C = C-points                                                        */
    /* N_i = non-zero neighbors of node i                                  */
    /* S_i = {j\in N_i | j strongly influences i } [strong neighbors of i] */
    /* F_i^s = F \cap S_i [strong F-neighbors of i]                        */
    /* C_i^s = C \cap S_i [strong C-neighbors of i]                        */
    /* P_i = Set of interpolatory variables for row i [here = C_i^s]       */
 
    /* (A.2.17) from p. 426                                                */
    /* a_ij^- = {  a_ij,  if a_ij < 0                                      */
    /*          {     0,  otherwise                                        */
    /* a_ij^+ = {  a_ij,  if a_ij > 0                                      */
    /*          {     0,  otherwise                                        */
    /* P_i^- =  P_i \cap {k | a_ij^- != 0 and a_ij^- = a_ij}               */
    /*          [strong C-neighbors with negative edges]                   */
    /* P_i^+ =  P_i \cap {k | a_ij^+ != 0 and a_ij^+ = a_ij}               */
    /*          [strong C-neighbors with positive edges]                   */
 
 
    /* de Sterck et al., gives us this:                                                      */
    /* Rewritten Equation (6) on p. 119                                                      */
    /* w_ij = - a_ji / a_ii \frac{\sum_{k\in N_i} a_ik} {\sum k\inC_i^s} a_ik},   j\in C_i^s */
 
    /* Trottenberg et al. (A.7.6) and (A.7.7) on p. 479 gives this:                          */
    /* alpha_i = \frac{ \sum_{j\in N_i} a_ij^- }{ \sum_{k\in P_i} a_ik^- }                   */
    /* beta_i  = \frac{ \sum_{j\in N_i} a_ij^+ }{ \sum_{k\in P_i} a_ik^+ }                   */
    /* w_ik    = { - alpha_i (a_ik / a_ii),   if k\in P_i^-                                  */
    /*           { -  beta_i (a_ik / a_ii),   if k\in P_i^+                                  */
    /* NOTE: The text says to modify, if  P_i^+ is zero but it isn't entirely clear how that */
    /* works.  We'll follow the PyAMG implementation in a few important ways.                */
     
    const point_type C_PT = ClassicalMapFactory::C_PT;
    const point_type DIRICHLET_PT = ClassicalMapFactory::DIRICHLET_PT;
   
    // Initial (estimated) allocation
    // NOTE: If we only used Tpetra, then we could use these guys as is, but because Epetra, we can't, so there
    // needs to be a copy below.
    using STS = typename Teuchos::ScalarTraits<SC>;
    using MT  = typename STS::magnitudeType;
    using MTS = typename Teuchos::ScalarTraits<MT>;
    size_t Nrows = A.getLocalNumRows();
    double c_point_density = (double)num_c_points / (num_c_points+num_f_points);
    double mean_strong_neighbors_per_row = (double) graph.GetNodeNumEdges() / graph.GetNodeNumVertices();
    //    double mean_neighbors_per_row = (double)A.getLocalNumEntries() / Nrows;
    double nnz_per_row_est = c_point_density*mean_strong_neighbors_per_row;
 
    size_t nnz_est = std::max(Nrows,std::min((size_t)A.getLocalNumEntries(),(size_t)(nnz_per_row_est*Nrows)));
    SC SC_ZERO = STS::zero();
    MT MT_ZERO = MTS::zero();
    Array<size_t> tmp_rowptr(Nrows+1);
    Array<LO> tmp_colind(nnz_est);
 
    // Algorithm (count+realloc)
    // For each row, i,
    // - Count the number of elements in \hat{C}_j, aka [C-neighbors and C-neighbors of strong F-neighbors of i]
    size_t ct=0;
    for(LO row=0; row < (LO) Nrows; row++) {
      size_t row_start = eis_rowptr[row];
      ArrayView<const LO> indices;
      ArrayView<const SC> vals;
      std::set<LO> C_hat;
      if(myPointType[row] == DIRICHLET_PT) {
        // Dirichlet points get ignored completely
      }
      else if(myPointType[row] == C_PT) {
        // C-Points get a single 1 in their row
        C_hat.insert(cpoint2pcol[row]);
      }
      else {
        // F-Points have a more complicated interpolation
 
        // C-neighbors of row
        A.getLocalRowView(row, indices, vals);
        for(LO j=0; j<indices.size(); j++)
          if(myPointType[indices[j]] == C_PT && edgeIsStrong[row_start + j])
            C_hat.insert(cpoint2pcol[indices[j]]);
      }// end else
      
      // Realloc if needed
      if(ct + (size_t)C_hat.size() > (size_t)tmp_colind.size()) {
        tmp_colind.resize(std::max(ct+(size_t)C_hat.size(),(size_t)2*tmp_colind.size()));
      }
      
      // Copy
      std::copy(C_hat.begin(), C_hat.end(),tmp_colind.begin()+ct);
      ct+=C_hat.size();
      tmp_rowptr[row+1] = tmp_rowptr[row] + C_hat.size();
    }
    // Resize down
    tmp_colind.resize(tmp_rowptr[Nrows]);
 
    // Allocate memory & copy
    P = rcp(new CrsMatrixWrap(A.getRowMap(), coarseColMap, 0));
    RCP<CrsMatrix> PCrs   = rcp_dynamic_cast<CrsMatrixWrap>(P)->getCrsMatrix();
    ArrayRCP<size_t>  P_rowptr;
    ArrayRCP<LO>      P_colind;
    ArrayRCP<SC>      P_values;
 
#ifdef CMS_DEBUG
printf("CMS: Allocating P w/ %d nonzeros\n",(int)tmp_rowptr[Nrows]);
#endif
    PCrs->allocateAllValues(tmp_rowptr[Nrows], P_rowptr, P_colind, P_values);
    TEUCHOS_TEST_FOR_EXCEPTION(tmp_rowptr.size() !=P_rowptr.size(), Exceptions::RuntimeError,"ClassicalPFactory: Allocation size error (rowptr)");
    TEUCHOS_TEST_FOR_EXCEPTION(tmp_colind.size() !=P_colind.size(), Exceptions::RuntimeError,"ClassicalPFactory: Allocation size error (colind)");
    // FIXME:  This can be short-circuited for Tpetra, if we decide we care
    for(LO i=0; i<(LO)Nrows+1; i++)
      P_rowptr[i] = tmp_rowptr[i];
    for(LO i=0; i<(LO)tmp_rowptr[Nrows]; i++)
      P_colind[i] = tmp_colind[i];
 
 
    // Algorithm (numeric)
    for(LO i=0; i < (LO)Nrows; i++) {
      if(myPointType[i] == DIRICHLET_PT) {
        // Dirichlet points get ignored completely
#ifdef CMS_DEBUG
        // DEBUG
        printf("** A(%d,:) is a Dirichlet-Point.\n",i);
#endif
      }
      else if (myPointType[i] == C_PT) {
        // C Points get a single 1 in their row
        P_values[P_rowptr[i]] = Teuchos::ScalarTraits<SC>::one();
#ifdef CMS_DEBUG
        // DEBUG
        printf("** A(%d,:) is a C-Point.\n",i);
#endif
      }
      else {
        /* Trottenberg et al. (A.7.6) and (A.7.7) on p. 479 gives this:                          */
        /* alpha_i = \frac{ \sum_{j\in N_i} a_ij^- }{ \sum_{k\in P_i} a_ik^- }                   */
        /* beta_i  = \frac{ \sum_{j\in N_i} a_ij^+ }{ \sum_{k\in P_i} a_ik^+ }                   */
        /* w_ik    = { - alpha_i (a_ik / a_ii),   if k\in P_i^-                                  */
        /*           { -  beta_i (a_ik / a_ii),   if k\in P_i^+                                  */
        ArrayView<const LO> A_indices_i, A_incides_k;
        ArrayView<const SC> A_vals_i, A_indices_k;
        A.getLocalRowView(i, A_indices_i, A_vals_i);
        size_t row_start = eis_rowptr[i];
        
        ArrayView<LO> P_indices_i  = P_colind.view(P_rowptr[i],P_rowptr[i+1] - P_rowptr[i]);
        ArrayView<SC> P_vals_i     = P_values.view(P_rowptr[i],P_rowptr[i+1] - P_rowptr[i]);
        
#ifdef CMS_DEBUG
        // DEBUG
        {
          char mylabel[5]="FUCD";
          char sw[3]="ws";
          printf("** A(%d,:) = ",i);
          for(LO j=0; j<(LO)A_indices_i.size(); j++){
            printf("%6.4e(%d-%c%c) ",A_vals_i[j],A_indices_i[j],mylabel[1+myPointType[A_indices_i[j]]],sw[(int)edgeIsStrong[row_start+j]]);
          }
          printf("\n");
        }
#endif
                      
        SC a_ii            = SC_ZERO;
        SC pos_numerator   = SC_ZERO, neg_numerator   = SC_ZERO;
        SC pos_denominator = SC_ZERO, neg_denominator = SC_ZERO;
        // Find the diagonal and compute the sum ratio
        for(LO j=0; j<(LO)A_indices_i.size(); j++) {
          SC a_ik = A_vals_i[j];
          LO k = A_indices_i[j];
          
          // Diagonal
          if(i == k) {
            a_ii = a_ik;
          }
          // Only strong C-neighbors are in the denomintor
          if(myPointType[k] == C_PT && edgeIsStrong[row_start + j]) {
            if(STS::real(a_ik) > MT_ZERO) pos_denominator += a_ik;
            else neg_denominator += a_ik;
          }
          
          // All neighbors are in the numerator
          // NOTE: As per PyAMG, this does not include the diagonal
          if(i != k) {
            if(STS::real(a_ik) > MT_ZERO) pos_numerator += a_ik;
            else neg_numerator += a_ik;
          }
        }
        SC alpha = (neg_denominator == MT_ZERO) ? SC_ZERO : (neg_numerator / neg_denominator);
        SC beta  = (pos_denominator == MT_ZERO) ? SC_ZERO : (pos_numerator / pos_denominator);
        alpha /= -a_ii;
        beta  /= -a_ii;
 
        // Loop over the entries
        for(LO p_j=0; p_j<(LO)P_indices_i.size(); p_j++){
          LO P_col = pcol2cpoint[P_indices_i[p_j]];
          SC a_ij = SC_ZERO;
          
          // Find A_ij (if it is there)
          // FIXME: We can optimize this if we assume sorting
          for(LO a_j =0; a_j<(LO)A_indices_i.size(); a_j++) {
            if(A_indices_i[a_j] == P_col) {
              a_ij = A_vals_i[a_j];
              break;
            }
          }
          SC w_ij = (STS::real(a_ij) < 0 ) ? (alpha * a_ij) : (beta * a_ij);
#ifdef CMS_DEBUG
          SC alpha_or_beta = (STS::real(a_ij) < 0 ) ? alpha : beta;
          printf("P(%d,%d/%d) =  - %6.4e  * %6.4e  = %6.4e\n",i,P_indices_i[p_j],pcol2cpoint[P_indices_i[p_j]],alpha_or_beta,a_ij,w_ij);
#endif
          P_vals_i[p_j] = w_ij;
        }//end for A_indices_i
      }//end else C_PT
    }//end for Numrows
 
    // Finish up
    PCrs->setAllValues(P_rowptr, P_colind, P_values);
    PCrs->expertStaticFillComplete(/*domain*/coarseDomainMap, /*range*/A.getDomainMap());
}
 
 
/* ************************************************************************* */
template <class Scalar,class LocalOrdinal, class GlobalOrdinal, class Node>
void ClassicalPFactory<Scalar, LocalOrdinal, GlobalOrdinal, Node>::
Coarsen_Ext_Plus_I(const Matrix & A,const RCP<const Matrix> & Aghost, const GraphBase & graph,  RCP<const Map> & coarseColMap, RCP<const Map> & coarseDomainMap, LO num_c_points, LO num_f_points, const Teuchos::ArrayView<const LO> & myPointType, const Teuchos::ArrayView<const LO> & myPointType_ghost, const Teuchos::Array<LO> & cpoint2pcol, const Teuchos::Array<LO> & pcol2cpoint, Teuchos::Array<size_t> & eis_rowptr, Teuchos::Array<bool> & edgeIsStrong, RCP<LocalOrdinalVector> & BlockNumber, RCP<Matrix> & P) const {
 
    /* ============================================================= */
    /* Phase 3 : Extended+i Interpolation                            */
    /* De Sterck, Falgout, Nolting and Yang. "Distance-two           */
    /* interpolation for parallel algebraic multigrid", NLAA 2008    */
    /* 15:115-139                                                    */
    /* ============================================================= */
    /* Definitions:                                                        */
    /* F = F-points                                                        */
    /* C = C-points                                                        */
    /* N_i = non-zero neighbors of node i                                  */
    /* S_i = {j\in N_i | j strongly influences i } [strong neighbors of i] */
    /* F_i^s = F \cap S_i [strong F-neighbors of i]                        */
    /* C_i^s = C \cap S_i [strong C-neighbors of i]                        */
    /* N_i^w = N_i\ (F_i^s \cup C_i^s) [weak neighbors of i]               */
    /*         This guy has a typo.  The paper had a \cap instead of \cup  */
    /*         I would note that this set can contain both F-points and    */
    /*         C-points.  They're just weak neighbors of this guy.         */
    /*         Note that N_i^w \cup F_i^s \cup C_i^s = N_i by construction */
 
    /* \hat{C}_i = C_i \cup (\bigcup_{j\inF_i^s} C_j)                      */
    /*         [C-neighbors and C-neighbors of strong F-neighbors of i]    */
    /*                                                                     */
 
    /* \bar{a}_ij = {    0, if sign(a_ij) == sign(a_ii)                    */
    /*              { a_ij, otherwise                                      */
 
 
    /* Rewritten Equation (19) on p. 123                                   */
    /* f_ik = \frac{\bar{a}_kj}{\sum{l\in \hat{C}_i\cup {i}} \bar{a}_kl    */
    /* w_ij = -\tilde{a}_ii^{-1} (a_ij + \sum_{k\inF_i^s} a_ik f_ik        */
    /*         for j in \hat{C}_i                                          */
    
    /* Rewritten Equation (20) on p. 124 [for the lumped diagonal]                                  */
    /* g_ik = \frac{\bar{a}_ki}{\sum{l\in \hat{C}_i\cup {i}} \bar{a}_kl                             */
    /* \tilde{a}_ii = a_ii + \sum_{n\inN_i^w\setminus \hat{C}_i} a_in + \sum_{k\inF_i^s} a_ik g_ik  */
    TEUCHOS_TEST_FOR_EXCEPTION(1,std::runtime_error,"ClassicalPFactory: Ext+i not implemented");
 
}
 
 
 
 
/* ************************************************************************* */
template <class Scalar,class LocalOrdinal, class GlobalOrdinal, class Node>
void ClassicalPFactory<Scalar, LocalOrdinal, GlobalOrdinal, Node>::
GenerateStrengthFlags(const Matrix & A,const GraphBase & graph, Teuchos::Array<size_t> & eis_rowptr,Teuchos::Array<bool> & edgeIsStrong) const {
  // To make this easier, we'll create a bool array equal to the nnz in the matrix
  // so we know whether each edge is strong or not.  This will save us a bunch of
  // trying to match the graph and matrix later
  size_t Nrows = A.getLocalNumRows();
  eis_rowptr.resize(Nrows+1);
 
  if(edgeIsStrong.size() == 0) {
    // Preferred
    edgeIsStrong.resize(A.getLocalNumEntries(),false);
  }
  else {
    edgeIsStrong.resize(A.getLocalNumEntries(),false);
    edgeIsStrong.assign(A.getLocalNumEntries(),false);
  }
  
  eis_rowptr[0] = 0;
  for (LO i=0; i<(LO)Nrows; i++) {
    LO rowstart = eis_rowptr[i];
    ArrayView<const LO> A_indices;
    ArrayView<const SC> A_values;
    A.getLocalRowView(i, A_indices, A_values);
    LO A_size = (LO) A_indices.size();
 
    ArrayView<const LO> G_indices = graph.getNeighborVertices(i);
    LO G_size = (LO) G_indices.size();
    
    // Both of these guys should be in the same (sorted) order, but let's check
    bool is_ok=true;
    for(LO j=0; j<A_size-1; j++)
      if (A_indices[j] >= A_indices[j+1]) { is_ok=false; break;}
    for(LO j=0; j<G_size-1; j++)
      if (G_indices[j] >= G_indices[j+1]) { is_ok=false; break;}
    TEUCHOS_TEST_FOR_EXCEPTION(!is_ok, Exceptions::RuntimeError,"ClassicalPFactory: Exected A and Graph to be sorted");
    
    // Now cycle through and set the flags - if the edge is in G it is strong
    for(LO g_idx=0, a_idx=0; g_idx < G_size; g_idx++) {
      LO col = G_indices[g_idx];
      while (A_indices[a_idx] != col && a_idx < A_size) a_idx++;
      if(a_idx == A_size) {is_ok=false;break;}
      edgeIsStrong[rowstart+a_idx] = true;
    }
 
    eis_rowptr[i+1] = eis_rowptr[i] + A_size;
  }
}
   
 
/* ************************************************************************* */
template <class Scalar,class LocalOrdinal, class GlobalOrdinal, class Node>
void ClassicalPFactory<Scalar, LocalOrdinal, GlobalOrdinal, Node>::
GhostCoarseMap(const Matrix &A, const Import & Importer, const ArrayRCP<const LO> myPointType, const RCP<const Map> & coarseMap, RCP<const Map> & coarseColMap) const {
  const point_type C_PT = ClassicalMapFactory::C_PT;
  const GO GO_INVALID = Teuchos::OrdinalTraits<GO>::invalid();
  RCP<GlobalOrdinalVector> d_coarseIds = GlobalOrdinalVectorFactory::Build(A.getRowMap());
  ArrayRCP<GO> d_data = d_coarseIds->getDataNonConst(0);
  LO ct=0;
      
  for(LO i=0; i<(LO)d_data.size(); i++) {
    if(myPointType[i] == C_PT) {
      d_data[i] = coarseMap->getGlobalElement(ct);
      ct++;
    }
    else
      d_data[i] = GO_INVALID;
  }
  
  // Ghost this guy
  RCP<GlobalOrdinalVector> c_coarseIds = GlobalOrdinalVectorFactory::Build(A.getColMap());
  c_coarseIds->doImport(*d_coarseIds,Importer,Xpetra::INSERT);
  
  // If we assume that A is in Aztec ordering, then any subset of A's unknowns will
  // be in Aztec ordering as well, which means we can just condense these guys down
  // Overallocate, count and view
  ArrayRCP<GO> c_data = c_coarseIds->getDataNonConst(0);
  
  Array<GO> c_gids(c_data.size());
  LO count=0;
  
  for(LO i=0; i<(LO)c_data.size(); i++) {
    if(c_data[i] != GO_INVALID) {
      c_gids[count] = c_data[i];
      count++;
    }
  }
  // FIXME: Assumes scalar PDE
  std::vector<size_t> stridingInfo_(1);
  stridingInfo_[0]=1;
  GO domainGIDOffset = 0;
  
  coarseColMap = StridedMapFactory::Build(coarseMap->lib(),
                                          Teuchos::OrdinalTraits<Xpetra::global_size_t>::invalid(),
                                          c_gids.view(0,count),
                                          coarseMap->getIndexBase(),
                                          stridingInfo_,
                                          coarseMap->getComm(),
                                          domainGIDOffset);
  
}
 
 
} //namespace MueLu
 
 
 
#define MUELU_CLASSICALPFACTORY_SHORT
#endif // MUELU_CLASSICALPFACTORY_DEF_HPP