[suitesparse] Create wrapper for LDL linear solver

Signed-off-by: Christoph Grüninger <gruenich@dune-project.org>

dune/istl/ldl.hh

+// -*- tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 2 -*-
+// vi: set et ts=4 sw=2 sts=2:
+#ifndef DUNE_LDL_HH
+#define DUNE_LDL_HH
+
+#if HAVE_LDL
+
+#include <iostream>
+#include<complex>
+#include<type_traits>
+
+#ifdef __cplusplus
+extern "C"
+{
+#include "ldl.h"
+#include "amd.h"
+}
+#endif
+
+#include<dune/common/exceptions.hh>
+#include<dune/common/unused.hh>
+
+#include<dune/istl/solvers.hh>
+#include<dune/istl/solvertype.hh>
+#include<dune/istl/colcompmatrix.hh>
+
+namespace Dune {
+  /**
+   * @addtogroup ISTL
+   *
+   * @{
+   */
+  /**
+   * @file
+   * @author Marco Agnese, Andrea Sacconi
+   * @brief Class for using LDL with ISTL matrices.
+   */
+
+  // forward declaration
+  template<class M, class T, class TM, class TD, class TA>
+  class SeqOverlappingSchwarz;
+
+  template<class T, bool tag>
+  struct SeqOverlappingSchwarzAssemblerHelper;
+
+  /**
+   * @brief The %LDL direct sparse solver for matrices of type Matrix
+   * Details on LDL can be found on http://www.cise.ufl.edu/research/sparse/ldl/
+   * \note This will only work if dune-istl has been configured to use LDL
+   */
+  template<typename MT>
+  class LDL
+  {
+    public:
+    /** @brief The matrix type. */
+    typedef MT Matrix;
+
+    /** @brief The column-compressed matrix type.*/
+    typedef ColCompMatrix<Matrix> LDLMatrix;
+
+    /**
+     * @brief Construct a solver object.
+     * @param mat the matrix to solve for
+     * @param verbose 0 or 1 set the verbosity level, defaults to 0
+     */
+    LDL(const Matrix& mat, int verbose=0) : isloaded_(false), verbose_(verbose)
+    {
+      setMatrix(mat);
+    }
+
+    /**
+     * @brief Constructor for compatibility with SuperLU standard constructor
+     * @param mat the matrix to solve for
+     * @param verbose 0 or 1 set the verbosity level, defaults to 0
+     */
+    LDL(const Matrix& mat, int verbose, bool) : isloaded_(false), verbose_(verbose)
+    {
+      setMatrix(mat);
+    }
+
+    /** @brief Default constructor. */
+    LDL() : isloaded_(false), verbose_(0)
+    {}
+
+    /** @brief Default constructor. */
+    ~LDL()
+    {
+      if ((mat_.N() + mat_.M() > 0) || isloaded_)
+        free();
+    }
+
+    /** @brief Solve the system Ax=b. */
+    template<class DT,class RT>
+    void apply(DT& x, const RT& b, InverseOperatorResult& res)
+    {
+      const int dimMat(mat_.N());
+      ldl_perm (dimMat, Y_, reinterpret_cast<double*>(&b[0]), P_);
+      ldl_lsolve(dimMat, Y_, Lp_, Li_, Lx_);
+      ldl_dsolve(dimMat, Y_, D_);
+      ldl_ltsolve(dimMat, Y_, Lp_, Li_, Lx_);
+      ldl_permt (dimMat, reinterpret_cast<double*>(&x[0]), Y_, P_);
+      // this is a direct solver
+      res.iterations = 1;
+      res.converged = true;
+    }
+
+    /** @brief Solve the system Ax=b. */
+    template<class DT,class RT>
+    inline void apply(DT& x, const RT& b, double reduction, InverseOperatorResult& res)
+    {
+      DUNE_UNUSED_PARAMETER(reduction);
+      apply(x,b,res);
+    }
+
+    /** @brief Initialize data from given matrix. */
+    void setMatrix(const Matrix& mat)
+    {
+      if ((mat_.N() + mat_.M() > 0) || isloaded_)
+        free();
+      mat_ = mat;
+
+      // set correct dimension for additional vectors (only those before symbolic)
+      const int dimMat(mat_.N());
+      D_ = new double [dimMat];
+      Y_ = new double [dimMat];
+      Lp_ = new int [dimMat + 1];
+      Parent_ = new int [dimMat];
+      Lnz_ = new int [dimMat];
+      Flag_ = new int [dimMat];
+      Pattern_ = new int [dimMat];
+      P_ = new int [dimMat];
+      Pinv_ = new int [dimMat];
+
+      decompose();
+    }
+
+    /**
+     * @brief Sets the verbosity level for the solver.
+     * @param v verbosity level: 0 only error messages, 1 a bit of statistics.
+     */
+    inline void setVerbosity(int v)
+    {
+      verbose_=v;
+    }
+
+    /**
+     * @brief Free allocated space.
+     * @warning Later calling apply will result in an error.
+     */
+    void free()
+    {
+      delete [] D_;
+      delete [] Y_;
+      delete [] Lp_;
+      delete [] Parent_;
+      delete [] Lnz_;
+      delete [] Flag_;
+      delete [] Pattern_;
+      delete [] Lx_;
+      delete [] Li_;
+      delete [] P_;
+      delete [] Pinv_;
+      mat_.free();
+      isloaded_ = false;
+    }
+
+    /** @brief Get method name. */
+    inline const char* name()
+    {
+      return "LDL";
+    }
+
+    /**
+     * @brief Get factorization diagonal matrix D.
+     * @warning It is up to the user to preserve consistency when modifyng it.
+     */
+    inline double* getD(void)
+    {
+      return D_;
+    }
+
+    /**
+     * @brief Get factorization Lp.
+     * @warning It is up to the user to preserve consistency when modifyng it.
+     */
+    inline int* getLp(void)
+    {
+      return Lp_;
+    }
+
+    /**
+     * @brief Get factorization Li.
+     * @warning It is up to the user to preserve consistency when modifyng it.
+     */
+    inline int* getLi(void)
+    {
+      return Li_;
+    }
+
+    /**
+     * @brief Get factorization Lx.
+     * @warning It is up to the user to preserve consistency when modifyng it.
+     */
+    inline double* getLx(void)
+    {
+      return Lx_;
+    }
+
+    private:
+    template<class M,class X, class TM, class TD, class T1>
+    friend class SeqOverlappingSchwarz;
+
+    friend struct SeqOverlappingSchwarzAssemblerHelper<LDL<Matrix>,true>;
+
+    /** @brief Computes the LDL decomposition. */
+    void decompose()
+    {
+      const int dimMat(mat_.N());
+      double Info [AMD_INFO];
+      if (amd_order (dimMat, mat_.getColStart(), mat_.getRowIndex(), P_, (double *) NULL, Info) < AMD_OK)
+        std::cout<<"WARNING: call to AMD failed."<<std::endl;
+      if(verbose_ > 0)
+        amd_info (Info);
+      // compute the symbolic factorisation
+      ldl_symbolic(dimMat, mat_.getColStart(), mat_.getRowIndex(), Lp_, Parent_, Lnz_, Flag_, P_, Pinv_);
+      // initialise those entries of additionalVectors_ whose dimension is known only now
+      Lx_ = new double [Lp_[dimMat]];
+      Li_ = new int [Lp_[dimMat]];
+      // compute the numeric factorisation
+      const int rank(ldl_numeric(dimMat, mat_.getColStart(), mat_.getRowIndex(), mat_.getValues(),
+                                 Lp_, Parent_, Lnz_, Li_, Lx_, D_, Y_, Pattern_, Flag_, P_, Pinv_));
+      if(rank!=dimMat)
+        std::cout<<"WARNING: matrix is singular."<<std::endl;
+    }
+
+    LDLMatrix mat_;
+    bool isloaded_;
+    int verbose_;
+    int* Lp_;
+    int* Parent_;
+    int* Lnz_;
+    int* Flag_;
+    int* Pattern_;
+    int* P_;
+    int* Pinv_;
+    double* D_;
+    double* Y_;
+    double* Lx_;
+    int* Li_;
+  };
+
+  template<typename MT>
+  struct IsDirectSolver<LDL<MT> >
+  {
+    enum {value=true};
+  };
+
+  template<typename MT>
+  struct StoresColumnCompressed<LDL<MT> >
+  {
+    enum {value=true};
+  };
+}
+
+#endif //HAVE_LDL
+#endif //DUNE_LDL_HH