1 files changed, 0 insertions, 200 deletions
diff --git a/eigen/test/eigen2/eigen2_sparse_solvers.cpp b/eigen/test/eigen2/eigen2_sparse_solvers.cpp
deleted file mode 100644
index 3aef27a..0000000
--- a/eigen/test/eigen2/eigen2_sparse_solvers.cpp
+++ /dev/null
@@ -1,200 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Daniel Gomez Ferro <dgomezferro@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#include "sparse.h"
-
-template<typename Scalar> void
-initSPD(double density,
-        Matrix<Scalar,Dynamic,Dynamic>& refMat,
-        SparseMatrix<Scalar>& sparseMat)
-{
-  Matrix<Scalar,Dynamic,Dynamic> aux(refMat.rows(),refMat.cols());
-  initSparse(density,refMat,sparseMat);
-  refMat = refMat * refMat.adjoint();
-  for (int k=0; k<2; ++k)
-  {
-    initSparse(density,aux,sparseMat,ForceNonZeroDiag);
-    refMat += aux * aux.adjoint();
-  }
-  sparseMat.startFill();
-  for (int j=0 ; j<sparseMat.cols(); ++j)
-    for (int i=j ; i<sparseMat.rows(); ++i)
-      if (refMat(i,j)!=Scalar(0))
-        sparseMat.fill(i,j) = refMat(i,j);
-  sparseMat.endFill();
-}
-
-template<typename Scalar> void sparse_solvers(int rows, int cols)
-{
-  double density = std::max(8./(rows*cols), 0.01);
-  typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
-  typedef Matrix<Scalar,Dynamic,1> DenseVector;
-  // Scalar eps = 1e-6;
-
-  DenseVector vec1 = DenseVector::Random(rows);
-
-  std::vector<Vector2i> zeroCoords;
-  std::vector<Vector2i> nonzeroCoords;
-
-  // test triangular solver
-  {
-    DenseVector vec2 = vec1, vec3 = vec1;
-    SparseMatrix<Scalar> m2(rows, cols);
-    DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
-
-    // lower
-    initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular, &zeroCoords, &nonzeroCoords);
-    VERIFY_IS_APPROX(refMat2.template marked<LowerTriangular>().solveTriangular(vec2),
-                     m2.template marked<LowerTriangular>().solveTriangular(vec3));
-
-    // lower - transpose
-    initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeLowerTriangular, &zeroCoords, &nonzeroCoords);
-    VERIFY_IS_APPROX(refMat2.template marked<LowerTriangular>().transpose().solveTriangular(vec2),
-                     m2.template marked<LowerTriangular>().transpose().solveTriangular(vec3));
-
-    // upper
-    initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, &zeroCoords, &nonzeroCoords);
-    VERIFY_IS_APPROX(refMat2.template marked<UpperTriangular>().solveTriangular(vec2),
-                     m2.template marked<UpperTriangular>().solveTriangular(vec3));
-
-    // upper - transpose
-    initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, &zeroCoords, &nonzeroCoords);
-    VERIFY_IS_APPROX(refMat2.template marked<UpperTriangular>().transpose().solveTriangular(vec2),
-                     m2.template marked<UpperTriangular>().transpose().solveTriangular(vec3));
-  }
-
-  // test LLT
-  {
-    // TODO fix the issue with complex (see SparseLLT::solveInPlace)
-    SparseMatrix<Scalar> m2(rows, cols);
-    DenseMatrix refMat2(rows, cols);
-
-    DenseVector b = DenseVector::Random(cols);
-    DenseVector refX(cols), x(cols);
-
-    initSPD(density, refMat2, m2);
-
-    refMat2.llt().solve(b, &refX);
-    typedef SparseMatrix<Scalar,LowerTriangular|SelfAdjoint> SparseSelfAdjointMatrix;
-    if (!NumTraits<Scalar>::IsComplex)
-    {
-      x = b;
-      SparseLLT<SparseSelfAdjointMatrix> (m2).solveInPlace(x);
-      VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: default");
-    }
-    #ifdef EIGEN_CHOLMOD_SUPPORT
-    x = b;
-    SparseLLT<SparseSelfAdjointMatrix,Cholmod>(m2).solveInPlace(x);
-    VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: cholmod");
-    #endif
-    if (!NumTraits<Scalar>::IsComplex)
-    {
-      #ifdef EIGEN_TAUCS_SUPPORT
-      x = b;
-      SparseLLT<SparseSelfAdjointMatrix,Taucs>(m2,IncompleteFactorization).solveInPlace(x);
-      VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (IncompleteFactorization)");
-      x = b;
-      SparseLLT<SparseSelfAdjointMatrix,Taucs>(m2,SupernodalMultifrontal).solveInPlace(x);
-      VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalMultifrontal)");
-      x = b;
-      SparseLLT<SparseSelfAdjointMatrix,Taucs>(m2,SupernodalLeftLooking).solveInPlace(x);
-      VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LLT: taucs (SupernodalLeftLooking)");
-      #endif
-    }
-  }
-
-  // test LDLT
-  if (!NumTraits<Scalar>::IsComplex)
-  {
-    // TODO fix the issue with complex (see SparseLDLT::solveInPlace)
-    SparseMatrix<Scalar> m2(rows, cols);
-    DenseMatrix refMat2(rows, cols);
-
-    DenseVector b = DenseVector::Random(cols);
-    DenseVector refX(cols), x(cols);
-
-    //initSPD(density, refMat2, m2);
-    initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag|MakeUpperTriangular, 0, 0);
-    refMat2 += refMat2.adjoint();
-    refMat2.diagonal() *= 0.5;
-
-    refMat2.ldlt().solve(b, &refX);
-    typedef SparseMatrix<Scalar,UpperTriangular|SelfAdjoint> SparseSelfAdjointMatrix;
-    x = b;
-    SparseLDLT<SparseSelfAdjointMatrix> ldlt(m2);
-    if (ldlt.succeeded())
-      ldlt.solveInPlace(x);
-    VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LDLT: default");
-  }
-
-  // test LU
-  {
-    static int count = 0;
-    SparseMatrix<Scalar> m2(rows, cols);
-    DenseMatrix refMat2(rows, cols);
-
-    DenseVector b = DenseVector::Random(cols);
-    DenseVector refX(cols), x(cols);
-
-    initSparse<Scalar>(density, refMat2, m2, ForceNonZeroDiag, &zeroCoords, &nonzeroCoords);
-
-    LU<DenseMatrix> refLu(refMat2);
-    refLu.solve(b, &refX);
-    #if defined(EIGEN_SUPERLU_SUPPORT) || defined(EIGEN_UMFPACK_SUPPORT)
-    Scalar refDet = refLu.determinant();
-    #endif
-    x.setZero();
-    // // SparseLU<SparseMatrix<Scalar> > (m2).solve(b,&x);
-    // // VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: default");
-    #ifdef EIGEN_SUPERLU_SUPPORT
-    {
-      x.setZero();
-      SparseLU<SparseMatrix<Scalar>,SuperLU> slu(m2);
-      if (slu.succeeded())
-      {
-        if (slu.solve(b,&x)) {
-          VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: SuperLU");
-        }
-        // std::cerr << refDet << " == " << slu.determinant() << "\n";
-        if (count==0) {
-          VERIFY_IS_APPROX(refDet,slu.determinant()); // FIXME det is not very stable for complex
-        }
-      }
-    }
-    #endif
-    #ifdef EIGEN_UMFPACK_SUPPORT
-    {
-      // check solve
-      x.setZero();
-      SparseLU<SparseMatrix<Scalar>,UmfPack> slu(m2);
-      if (slu.succeeded()) {
-        if (slu.solve(b,&x)) {
-          if (count==0) {
-            VERIFY(refX.isApprox(x,test_precision<Scalar>()) && "LU: umfpack");  // FIXME solve is not very stable for complex
-          }
-        }
-        VERIFY_IS_APPROX(refDet,slu.determinant());
-        // TODO check the extracted data
-        //std::cerr << slu.matrixL() << "\n";
-      }
-    }
-    #endif
-    count++;
-  }
-
-}
-
-void test_eigen2_sparse_solvers()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( sparse_solvers<double>(8, 8) );
-    CALL_SUBTEST_2( sparse_solvers<std::complex<double> >(16, 16) );
-    CALL_SUBTEST_1( sparse_solvers<double>(101, 101) );
-  }
-}