1 files changed, 0 insertions, 146 deletions
diff --git a/test/eigen2/eigen2_eigensolver.cpp b/test/eigen2/eigen2_eigensolver.cpp
deleted file mode 100644
index 48b4ace43..000000000
--- a/test/eigen2/eigen2_eigensolver.cpp
+++ /dev/null
@@ -1,146 +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 Gael Guennebaud <g.gael@free.fr>
-//
-// 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 "main.h"
-#include <Eigen/QR>
-
-#ifdef HAS_GSL
-#include "gsl_helper.h"
-#endif
-
-template<typename MatrixType> void selfadjointeigensolver(const MatrixType& m)
-{
-  /* this test covers the following files:
-     EigenSolver.h, SelfAdjointEigenSolver.h (and indirectly: Tridiagonalization.h)
-  */
-  int rows = m.rows();
-  int cols = m.cols();
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-  typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealVectorType;
-  typedef typename std::complex<typename NumTraits<typename MatrixType::Scalar>::Real> Complex;
-
-  RealScalar largerEps = 10*test_precision<RealScalar>();
-
-  MatrixType a = MatrixType::Random(rows,cols);
-  MatrixType a1 = MatrixType::Random(rows,cols);
-  MatrixType symmA =  a.adjoint() * a + a1.adjoint() * a1;
-
-  MatrixType b = MatrixType::Random(rows,cols);
-  MatrixType b1 = MatrixType::Random(rows,cols);
-  MatrixType symmB = b.adjoint() * b + b1.adjoint() * b1;
-
-  SelfAdjointEigenSolver<MatrixType> eiSymm(symmA);
-  // generalized eigen pb
-  SelfAdjointEigenSolver<MatrixType> eiSymmGen(symmA, symmB);
-
-  #ifdef HAS_GSL
-  if (ei_is_same_type<RealScalar,double>::ret)
-  {
-    typedef GslTraits<Scalar> Gsl;
-    typename Gsl::Matrix gEvec=0, gSymmA=0, gSymmB=0;
-    typename GslTraits<RealScalar>::Vector gEval=0;
-    RealVectorType _eval;
-    MatrixType _evec;
-    convert<MatrixType>(symmA, gSymmA);
-    convert<MatrixType>(symmB, gSymmB);
-    convert<MatrixType>(symmA, gEvec);
-    gEval = GslTraits<RealScalar>::createVector(rows);
-
-    Gsl::eigen_symm(gSymmA, gEval, gEvec);
-    convert(gEval, _eval);
-    convert(gEvec, _evec);
-
-    // test gsl itself !
-    VERIFY((symmA * _evec).isApprox(_evec * _eval.asDiagonal(), largerEps));
-
-    // compare with eigen
-    VERIFY_IS_APPROX(_eval, eiSymm.eigenvalues());
-    VERIFY_IS_APPROX(_evec.cwise().abs(), eiSymm.eigenvectors().cwise().abs());
-
-    // generalized pb
-    Gsl::eigen_symm_gen(gSymmA, gSymmB, gEval, gEvec);
-    convert(gEval, _eval);
-    convert(gEvec, _evec);
-    // test GSL itself:
-    VERIFY((symmA * _evec).isApprox(symmB * (_evec * _eval.asDiagonal()), largerEps));
-
-    // compare with eigen
-    MatrixType normalized_eivec = eiSymmGen.eigenvectors()*eiSymmGen.eigenvectors().colwise().norm().asDiagonal().inverse();
-    VERIFY_IS_APPROX(_eval, eiSymmGen.eigenvalues());
-    VERIFY_IS_APPROX(_evec.cwiseAbs(), normalized_eivec.cwiseAbs());
-
-    Gsl::free(gSymmA);
-    Gsl::free(gSymmB);
-    GslTraits<RealScalar>::free(gEval);
-    Gsl::free(gEvec);
-  }
-  #endif
-
-  VERIFY((symmA * eiSymm.eigenvectors()).isApprox(
-          eiSymm.eigenvectors() * eiSymm.eigenvalues().asDiagonal(), largerEps));
-
-  // generalized eigen problem Ax = lBx
-  VERIFY((symmA * eiSymmGen.eigenvectors()).isApprox(
-          symmB * (eiSymmGen.eigenvectors() * eiSymmGen.eigenvalues().asDiagonal()), largerEps));
-
-  MatrixType sqrtSymmA = eiSymm.operatorSqrt();
-  VERIFY_IS_APPROX(symmA, sqrtSymmA*sqrtSymmA);
-  VERIFY_IS_APPROX(sqrtSymmA, symmA*eiSymm.operatorInverseSqrt());
-}
-
-template<typename MatrixType> void eigensolver(const MatrixType& m)
-{
-  /* this test covers the following files:
-     EigenSolver.h
-  */
-  int rows = m.rows();
-  int cols = m.cols();
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-  typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealVectorType;
-  typedef typename std::complex<typename NumTraits<typename MatrixType::Scalar>::Real> Complex;
-
-  // RealScalar largerEps = 10*test_precision<RealScalar>();
-
-  MatrixType a = MatrixType::Random(rows,cols);
-  MatrixType a1 = MatrixType::Random(rows,cols);
-  MatrixType symmA =  a.adjoint() * a + a1.adjoint() * a1;
-
-  EigenSolver<MatrixType> ei0(symmA);
-  VERIFY_IS_APPROX(symmA * ei0.pseudoEigenvectors(), ei0.pseudoEigenvectors() * ei0.pseudoEigenvalueMatrix());
-  VERIFY_IS_APPROX((symmA.template cast<Complex>()) * (ei0.pseudoEigenvectors().template cast<Complex>()),
-    (ei0.pseudoEigenvectors().template cast<Complex>()) * (ei0.eigenvalues().asDiagonal()));
-
-  EigenSolver<MatrixType> ei1(a);
-  VERIFY_IS_APPROX(a * ei1.pseudoEigenvectors(), ei1.pseudoEigenvectors() * ei1.pseudoEigenvalueMatrix());
-  VERIFY_IS_APPROX(a.template cast<Complex>() * ei1.eigenvectors(),
-                   ei1.eigenvectors() * ei1.eigenvalues().asDiagonal());
-
-}
-
-void test_eigen2_eigensolver()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    // very important to test a 3x3 matrix since we provide a special path for it
-    CALL_SUBTEST_1( selfadjointeigensolver(Matrix3f()) );
-    CALL_SUBTEST_2( selfadjointeigensolver(Matrix4d()) );
-    CALL_SUBTEST_3( selfadjointeigensolver(MatrixXf(7,7)) );
-    CALL_SUBTEST_4( selfadjointeigensolver(MatrixXcd(5,5)) );
-    CALL_SUBTEST_5( selfadjointeigensolver(MatrixXd(19,19)) );
-
-    CALL_SUBTEST_6( eigensolver(Matrix4f()) );
-    CALL_SUBTEST_5( eigensolver(MatrixXd(17,17)) );
-  }
-}
-