TsqrTpetraTest.hpp

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//                 Anasazi: Block Eigensolvers Package
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#ifndef __TSQR_Trilinos_TsqrTpetraTest_hpp
#define __TSQR_Trilinos_TsqrTpetraTest_hpp
 
#include "AnasaziTpetraAdapter.hpp" // sic (not "-or")
#include "Tsqr_Random_NormalGenerator.hpp"
#include "Teuchos_ParameterList.hpp"
#include "Teuchos_Tuple.hpp"
#include "Teuchos_Time.hpp"
#include <sstream>
#include <stdexcept>
#include <vector>
 
 
namespace TSQR {
  namespace Trilinos {
    namespace Test {
      using Teuchos::RCP;
      using Teuchos::Tuple;
 
      template< class S, class LO, class GO, class Node >
      class TpetraTsqrTest {
      public:
        typedef S scalar_type;
        typedef LO local_ordinal_type;
        typedef GO global_ordinal_type;
        typedef Node node_type;
 
        typedef typename TSQR::ScalarTraits< S >::magnitude_type magnitude_type;
        typedef TSQR::Trilinos::TsqrTpetraAdaptor< S, LO, GO, Node > adaptor_type;
 
        TpetraTsqrTest (const Tpetra::global_size_t nrowsGlobal,
                        const size_t ncols,
                        const Teuchos::RCP< const Teuchos::Comm<int> >& comm,
                        const Teuchos::RCP< Node >& node,
                        const Teuchos::ParameterList& params) :
          results_ (magnitude_type(0), magnitude_type(0))
        {
          using Teuchos::Tuple;
          using Teuchos::Exceptions::InvalidParameter;
          typedef typename adaptor_type::factor_output_type factor_output_type;
          typedef Teuchos::SerialDenseMatrix< LO, S > matrix_type;
 
          bool contiguousCacheBlocks = false;
          try {
            contiguousCacheBlocks = params.get<bool>("contiguousCacheBlocks");
          } catch (InvalidParameter&) {
            contiguousCacheBlocks = false;
          }
 
          triple_type testProblem =
            makeTestProblem (nrowsGlobal, ncols, comm, node, params);
          // A is already filled in with the test problem.  A_copy and
          // Q are just multivectors with the same layout as A.
          // A_copy will be used for temporary storage, and Q will
          // store the (explicitly represented) Q factor output.  R
          // will store the R factor output.
          RCP< MV > A = testProblem[0];
          RCP< MV > A_copy = testProblem[1];
          RCP< MV > Q = testProblem[2];
          matrix_type R (ncols, ncols);
 
          // Adaptor uses one of the multivectors only to reference
          // the underlying communicator object.
          adaptor_type adaptor (*A, params);
          if (contiguousCacheBlocks)
            adaptor.cacheBlock (*A, *A_copy);
 
          factor_output_type factorOutput =
            adaptor.factor (*A_copy, R, contiguousCacheBlocks);
          adaptor.explicitQ (*A_copy, factorOutput, *Q, contiguousCacheBlocks);
          if (contiguousCacheBlocks)
            {
              // Use A_copy as temporary storage for un-cache-blocking
              // Q.  Tpetra::MultiVector objects copy deeply.
              *A_copy = *Q;
              adaptor.unCacheBlock (*A_copy, *Q);
            }
          results_ = adaptor.verify (*A, *Q, R);
        }
 
        std::pair< magnitude_type, magnitude_type >
        getResults() const
        {
          return results_;
        }
 
      private:
        typedef Tpetra::MultiVector< S, LO, GO, Node >   MV;
        typedef Teuchos::Tuple< RCP< MV >, 3 >           triple_type;
        typedef Teuchos::RCP< const Teuchos::Comm<int> > comm_ptr;
        typedef Tpetra::Map< LO, GO, Node >              map_type;
        typedef Teuchos::RCP< const map_type >           map_ptr;
        typedef TSQR::Random::NormalGenerator< LO, S >   normalgen_type;
        typedef Teuchos::RCP< Node >                     node_ptr;
 
        std::pair< magnitude_type, magnitude_type > results_;
 
        static map_ptr
        makeMap (const Tpetra::global_size_t nrowsGlobal,
                 const comm_ptr& comm,
                 const node_ptr& node)
        {
          using Tpetra::createUniformContigMapWithNode;
          return createUniformContigMapWithNode< LO, GO, Node > (nrowsGlobal, comm);
        }
 
        static RCP< MV >
        makeMultiVector (const map_ptr& map,
                         const size_t ncols)
        {
          // "false" means "don't fill with zeros"; we'll fill it in
          // fillTpetraMultiVector().
          return Teuchos::rcp (new MV (map, ncols, false));
        }
 
        static void
        fillMultiVector (const RCP< MV >& mv,
                         const RCP< normalgen_type >& pGen)
        {
          using TSQR::Trilinos::TpetraRandomizer;
          typedef TpetraRandomizer< S, LO, GO, Node, normalgen_type > randomizer_type;
 
          const LO ncols = mv->getNumVectors();
          std::vector< S > singular_values (ncols);
          if (ncols > 0)
            {
              singular_values[0] = S(1);
              for (LO k = 1; k < ncols; ++k)
                singular_values[k] = singular_values[k-1] / S(2);
            }
          randomizer_type randomizer (*mv, pGen);
          randomizer.randomMultiVector (*mv, &singular_values[0]);
        }
 
        static triple_type
        makeTestProblem (const Tpetra::global_size_t nrowsGlobal,
                         const size_t ncols,
                         const comm_ptr& comm,
                         const node_ptr& node,
                         const Teuchos::ParameterList& params)
        {
          using TSQR::Trilinos::TpetraMessenger;
          using TSQR::MessengerBase;
 
          map_ptr map = makeMap (nrowsGlobal, comm, node);
          RCP< MV > A = makeMultiVector (map, ncols);
          RCP< MV > A_copy = makeMultiVector (map, ncols);
          RCP< MV > Q = makeMultiVector (map, ncols);
 
          // Fill A with the random test problem
          RCP< normalgen_type > pGen (new normalgen_type);
          fillMultiVector (A, pGen);
 
          return Teuchos::tuple (A, A_copy, Q);
        }
      };
 
    } // namespace Test
  } // namespace Trilinos
} // namespace TSQR
 
#endif // __TSQR_Trilinos_TsqrTpetraTest_hpp