Removed the deprecated EIGEN2_SUPPORT, as previously announced. A compilation error is raised, if this compile-switch is defined. The documentation references to the corresponding pages from Eigen3.2 now. Also, the Eigen2 testsuite has been removed.

53 files changed, 1 insertions, 6447 deletions

diff --git a/test/CMakeLists.txt b/test/CMakeLists.txt
index c2d827051..62c9c78a6 100644
--- a/test/CMakeLists.txt
+++ b/test/CMakeLists.txt
@@ -157,7 +157,6 @@ ei_add_test(vectorization_logic)
 ei_add_test(basicstuff)
 ei_add_test(linearstructure)
 ei_add_test(integer_types)
-ei_add_test(cwiseop)
 ei_add_test(unalignedcount)
 ei_add_test(exceptions)
 ei_add_test(redux)
@@ -258,8 +257,6 @@ if(QT4_FOUND)
   ei_add_test(qtvector "" "${QT_QTCORE_LIBRARY}")
 endif(QT4_FOUND)
 
-ei_add_test(eigen2support)
-
 if(UMFPACK_FOUND)
   ei_add_test(umfpack_support "" "${UMFPACK_ALL_LIBS}")
 endif()
@@ -303,7 +300,7 @@ ei_add_property(EIGEN_TESTING_SUMMARY "Sparse lib flags:  ${SPARSE_LIBS}\n")
 
 option(EIGEN_TEST_EIGEN2 "Run whole Eigen2 test suite against EIGEN2_SUPPORT" OFF)
 if(EIGEN_TEST_EIGEN2)
-  add_subdirectory(eigen2)
+  message(WARNING "The Eigen2 test suite has been removed")
 endif()
 
 
diff --git a/test/cwiseop.cpp b/test/cwiseop.cpp
deleted file mode 100644
index 247fa2a09..000000000
--- a/test/cwiseop.cpp
+++ /dev/null
@@ -1,182 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@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/.
-
-#define EIGEN2_SUPPORT
-#define EIGEN_NO_STATIC_ASSERT
-#include "main.h"
-#include <functional>
-
-#ifdef min
-#undef min
-#endif
-
-#ifdef max
-#undef max
-#endif
-
-using namespace std;
-
-template<typename Scalar> struct AddIfNull {
-    const Scalar operator() (const Scalar a, const Scalar b) const {return a<=1e-3 ? b : a;}
-    enum { Cost = NumTraits<Scalar>::AddCost };
-};
-
-template<typename MatrixType>
-typename Eigen::internal::enable_if<!NumTraits<typename MatrixType::Scalar>::IsInteger,typename MatrixType::Scalar>::type
-cwiseops_real_only(MatrixType& m1, MatrixType& m2, MatrixType& m3, MatrixType& mones)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  
-  VERIFY_IS_APPROX(m1.cwise() / m2,    m1.cwise() * (m2.cwise().inverse()));
-  m3 = m1.cwise().abs().cwise().sqrt();
-  VERIFY_IS_APPROX(m3.cwise().square(), m1.cwise().abs());
-  VERIFY_IS_APPROX(m1.cwise().square().cwise().sqrt(), m1.cwise().abs());
-  VERIFY_IS_APPROX(m1.cwise().abs().cwise().log().cwise().exp() , m1.cwise().abs());
-
-  VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().square());
-  m3 = (m1.cwise().abs().cwise()<=RealScalar(0.01)).select(mones,m1);
-  VERIFY_IS_APPROX(m3.cwise().pow(-1), m3.cwise().inverse());
-  m3 = m1.cwise().abs();
-  VERIFY_IS_APPROX(m3.cwise().pow(RealScalar(0.5)), m3.cwise().sqrt());
-
-//   VERIFY_IS_APPROX(m1.cwise().tan(), m1.cwise().sin().cwise() / m1.cwise().cos());
-  VERIFY_IS_APPROX(mones, m1.cwise().sin().cwise().square() + m1.cwise().cos().cwise().square());
-  m3 = m1;
-  m3.cwise() /= m2;
-  VERIFY_IS_APPROX(m3, m1.cwise() / m2);
-  
-  return Scalar(0);
-}
-
-template<typename MatrixType>
-typename Eigen::internal::enable_if<NumTraits<typename MatrixType::Scalar>::IsInteger,typename MatrixType::Scalar>::type
-cwiseops_real_only(MatrixType& , MatrixType& , MatrixType& , MatrixType& )
-{
-  return 0;
-}
-
-template<typename MatrixType> void cwiseops(const MatrixType& m)
-{
-  typedef typename MatrixType::Index Index;
-  typedef typename MatrixType::Scalar Scalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-
-  Index rows = m.rows();
-  Index cols = m.cols();
-
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m1bis = m1,
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols),
-             m4(rows, cols),
-             mzero = MatrixType::Zero(rows, cols),
-             mones = MatrixType::Ones(rows, cols),
-             identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
-                              ::Identity(rows, rows);
-  VectorType vzero = VectorType::Zero(rows),
-             vones = VectorType::Ones(rows),
-             v3(rows);
-
-  Index r = internal::random<Index>(0, rows-1),
-        c = internal::random<Index>(0, cols-1);
-
-  Scalar s1 = internal::random<Scalar>();
-
-  // test Zero, Ones, Constant, and the set* variants
-  m3 = MatrixType::Constant(rows, cols, s1);
-  for (int j=0; j<cols; ++j)
-    for (int i=0; i<rows; ++i)
-    {
-      VERIFY_IS_APPROX(mzero(i,j), Scalar(0));
-      VERIFY_IS_APPROX(mones(i,j), Scalar(1));
-      VERIFY_IS_APPROX(m3(i,j), s1);
-    }
-  VERIFY(mzero.isZero());
-  VERIFY(mones.isOnes());
-  VERIFY(m3.isConstant(s1));
-  VERIFY(identity.isIdentity());
-  VERIFY_IS_APPROX(m4.setConstant(s1), m3);
-  VERIFY_IS_APPROX(m4.setConstant(rows,cols,s1), m3);
-  VERIFY_IS_APPROX(m4.setZero(), mzero);
-  VERIFY_IS_APPROX(m4.setZero(rows,cols), mzero);
-  VERIFY_IS_APPROX(m4.setOnes(), mones);
-  VERIFY_IS_APPROX(m4.setOnes(rows,cols), mones);
-  m4.fill(s1);
-  VERIFY_IS_APPROX(m4, m3);
-
-  VERIFY_IS_APPROX(v3.setConstant(rows, s1), VectorType::Constant(rows,s1));
-  VERIFY_IS_APPROX(v3.setZero(rows), vzero);
-  VERIFY_IS_APPROX(v3.setOnes(rows), vones);
-
-  m2 = m2.template binaryExpr<AddIfNull<Scalar> >(mones);
-
-  VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().abs2());
-  VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().square());
-  VERIFY_IS_APPROX(m1.cwise().pow(3), m1.cwise().cube());
-
-  VERIFY_IS_APPROX(m1 + mones, m1.cwise()+Scalar(1));
-  VERIFY_IS_APPROX(m1 - mones, m1.cwise()-Scalar(1));
-  m3 = m1; m3.cwise() += 1;
-  VERIFY_IS_APPROX(m1 + mones, m3);
-  m3 = m1; m3.cwise() -= 1;
-  VERIFY_IS_APPROX(m1 - mones, m3);
-
-  VERIFY_IS_APPROX(m2, m2.cwise() * mones);
-  VERIFY_IS_APPROX(m1.cwise() * m2,  m2.cwise() * m1);
-  m3 = m1;
-  m3.cwise() *= m2;
-  VERIFY_IS_APPROX(m3, m1.cwise() * m2);
-
-  VERIFY_IS_APPROX(mones,    m2.cwise()/m2);
-
-  // check min
-  VERIFY_IS_APPROX( m1.cwise().min(m2), m2.cwise().min(m1) );
-  VERIFY_IS_APPROX( m1.cwise().min(m1+mones), m1 );
-  VERIFY_IS_APPROX( m1.cwise().min(m1-mones), m1-mones );
-
-  // check max
-  VERIFY_IS_APPROX( m1.cwise().max(m2), m2.cwise().max(m1) );
-  VERIFY_IS_APPROX( m1.cwise().max(m1-mones), m1 );
-  VERIFY_IS_APPROX( m1.cwise().max(m1+mones), m1+mones );
-
-  VERIFY( (m1.cwise() == m1).all() );
-  VERIFY( (m1.cwise() != m2).any() );
-  VERIFY(!(m1.cwise() == (m1+mones)).any() );
-  if (rows*cols>1)
-  {
-    m3 = m1;
-    m3(r,c) += 1;
-    VERIFY( (m1.cwise() == m3).any() );
-    VERIFY( !(m1.cwise() == m3).all() );
-  }
-  VERIFY( (m1.cwise().min(m2).cwise() <= m2).all() );
-  VERIFY( (m1.cwise().max(m2).cwise() >= m2).all() );
-  VERIFY( (m1.cwise().min(m2).cwise() < (m1+mones)).all() );
-  VERIFY( (m1.cwise().max(m2).cwise() > (m1-mones)).all() );
-
-  VERIFY( (m1.cwise()<m1.unaryExpr(bind2nd(plus<Scalar>(), Scalar(1)))).all() );
-  VERIFY( !(m1.cwise()<m1bis.unaryExpr(bind2nd(minus<Scalar>(), Scalar(1)))).all() );
-  VERIFY( !(m1.cwise()>m1bis.unaryExpr(bind2nd(plus<Scalar>(), Scalar(1)))).any() );
-  
-  cwiseops_real_only(m1, m2, m3, mones);
-}
-
-void test_cwiseop()
-{
-  for(int i = 0; i < g_repeat ; i++) {
-    CALL_SUBTEST_1( cwiseops(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( cwiseops(Matrix4d()) );
-    CALL_SUBTEST_3( cwiseops(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
-    CALL_SUBTEST_4( cwiseops(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
-    CALL_SUBTEST_5( cwiseops(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
-    CALL_SUBTEST_6( cwiseops(MatrixXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
-  }
-}
diff --git a/test/eigen2/CMakeLists.txt b/test/eigen2/CMakeLists.txt
deleted file mode 100644
index 41a02f4ad..000000000
--- a/test/eigen2/CMakeLists.txt
+++ /dev/null
@@ -1,65 +0,0 @@
-add_custom_target(eigen2_buildtests)
-add_custom_target(eigen2_check COMMAND "ctest -R eigen2")
-add_dependencies(eigen2_check eigen2_buildtests)
-add_dependencies(buildtests eigen2_buildtests)
-
-add_definitions("-DEIGEN2_SUPPORT_STAGE10_FULL_EIGEN2_API")
-
-# Disable unused warnings for this module
-# As EIGEN2 support is deprecated, it is not really worth fixing them
-ei_add_cxx_compiler_flag("-Wno-unused-local-typedefs")
-ei_add_cxx_compiler_flag("-Wno-unused-but-set-variable")
-
-ei_add_test(eigen2_meta)
-ei_add_test(eigen2_sizeof)
-ei_add_test(eigen2_dynalloc)
-ei_add_test(eigen2_nomalloc)
-#ei_add_test(eigen2_first_aligned)
-ei_add_test(eigen2_mixingtypes)
-#ei_add_test(eigen2_packetmath)
-ei_add_test(eigen2_unalignedassert)
-#ei_add_test(eigen2_vectorization_logic)
-ei_add_test(eigen2_basicstuff)
-ei_add_test(eigen2_linearstructure)
-ei_add_test(eigen2_cwiseop)
-ei_add_test(eigen2_sum)
-ei_add_test(eigen2_product_small)
-ei_add_test(eigen2_product_large ${EI_OFLAG})
-ei_add_test(eigen2_adjoint)
-ei_add_test(eigen2_submatrices)
-ei_add_test(eigen2_miscmatrices)
-ei_add_test(eigen2_commainitializer)
-ei_add_test(eigen2_smallvectors)
-ei_add_test(eigen2_map)
-ei_add_test(eigen2_array)
-ei_add_test(eigen2_triangular)
-ei_add_test(eigen2_cholesky " " "${GSL_LIBRARIES}")
-ei_add_test(eigen2_lu ${EI_OFLAG})
-ei_add_test(eigen2_determinant ${EI_OFLAG})
-ei_add_test(eigen2_inverse)
-ei_add_test(eigen2_qr)
-ei_add_test(eigen2_eigensolver " " "${GSL_LIBRARIES}")
-ei_add_test(eigen2_svd)
-ei_add_test(eigen2_geometry)
-ei_add_test(eigen2_geometry_with_eigen2_prefix)
-ei_add_test(eigen2_hyperplane)
-ei_add_test(eigen2_parametrizedline)
-ei_add_test(eigen2_alignedbox)
-ei_add_test(eigen2_regression)
-ei_add_test(eigen2_stdvector)
-ei_add_test(eigen2_newstdvector)
-if(QT4_FOUND)
-  ei_add_test(eigen2_qtvector " " "${QT_QTCORE_LIBRARY}")
-endif(QT4_FOUND)
-# no support for eigen2 sparse module
-# if(NOT EIGEN_DEFAULT_TO_ROW_MAJOR)
-#   ei_add_test(eigen2_sparse_vector)
-#   ei_add_test(eigen2_sparse_basic)
-#   ei_add_test(eigen2_sparse_solvers " " "${SPARSE_LIBS}")
-#   ei_add_test(eigen2_sparse_product)
-# endif()
-ei_add_test(eigen2_swap)
-ei_add_test(eigen2_visitor)
-ei_add_test(eigen2_bug_132)
-
-ei_add_test(eigen2_prec_inverse_4x4 ${EI_OFLAG})
diff --git a/test/eigen2/eigen2_adjoint.cpp b/test/eigen2/eigen2_adjoint.cpp
deleted file mode 100644
index 8ec9c9202..000000000
--- a/test/eigen2/eigen2_adjoint.cpp
+++ /dev/null
@@ -1,101 +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) 2006-2008 Benoit Jacob <jacob.benoit.1@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 "main.h"
-
-template<typename MatrixType> void adjoint(const MatrixType& m)
-{
-  /* this test covers the following files:
-     Transpose.h Conjugate.h Dot.h
-  */
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
-  int rows = m.rows();
-  int cols = m.cols();
-
-  RealScalar largerEps = test_precision<RealScalar>();
-  if (ei_is_same_type<RealScalar,float>::ret)
-    largerEps = RealScalar(1e-3f);
-
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols),
-             mzero = MatrixType::Zero(rows, cols),
-             identity = SquareMatrixType::Identity(rows, rows),
-             square = SquareMatrixType::Random(rows, rows);
-  VectorType v1 = VectorType::Random(rows),
-             v2 = VectorType::Random(rows),
-             v3 = VectorType::Random(rows),
-             vzero = VectorType::Zero(rows);
-
-  Scalar s1 = ei_random<Scalar>(),
-         s2 = ei_random<Scalar>();
-
-  // check basic compatibility of adjoint, transpose, conjugate
-  VERIFY_IS_APPROX(m1.transpose().conjugate().adjoint(),    m1);
-  VERIFY_IS_APPROX(m1.adjoint().conjugate().transpose(),    m1);
-
-  // check multiplicative behavior
-  VERIFY_IS_APPROX((m1.adjoint() * m2).adjoint(),           m2.adjoint() * m1);
-  VERIFY_IS_APPROX((s1 * m1).adjoint(),                     ei_conj(s1) * m1.adjoint());
-
-  // check basic properties of dot, norm, norm2
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  VERIFY(ei_isApprox((s1 * v1 + s2 * v2).eigen2_dot(v3),   s1 * v1.eigen2_dot(v3) + s2 * v2.eigen2_dot(v3), largerEps));
-  VERIFY(ei_isApprox(v3.eigen2_dot(s1 * v1 + s2 * v2),     ei_conj(s1)*v3.eigen2_dot(v1)+ei_conj(s2)*v3.eigen2_dot(v2), largerEps));
-  VERIFY_IS_APPROX(ei_conj(v1.eigen2_dot(v2)),               v2.eigen2_dot(v1));
-  VERIFY_IS_APPROX(ei_real(v1.eigen2_dot(v1)),               v1.squaredNorm());
-  if(NumTraits<Scalar>::HasFloatingPoint)
-    VERIFY_IS_APPROX(v1.squaredNorm(),                      v1.norm() * v1.norm());
-  VERIFY_IS_MUCH_SMALLER_THAN(ei_abs(vzero.eigen2_dot(v1)),  static_cast<RealScalar>(1));
-  if(NumTraits<Scalar>::HasFloatingPoint)
-    VERIFY_IS_MUCH_SMALLER_THAN(vzero.norm(),         static_cast<RealScalar>(1));
-
-  // check compatibility of dot and adjoint
-  VERIFY(ei_isApprox(v1.eigen2_dot(square * v2), (square.adjoint() * v1).eigen2_dot(v2), largerEps));
-
-  // like in testBasicStuff, test operator() to check const-qualification
-  int r = ei_random<int>(0, rows-1),
-      c = ei_random<int>(0, cols-1);
-  VERIFY_IS_APPROX(m1.conjugate()(r,c), ei_conj(m1(r,c)));
-  VERIFY_IS_APPROX(m1.adjoint()(c,r), ei_conj(m1(r,c)));
-
-  if(NumTraits<Scalar>::HasFloatingPoint)
-  {
-    // check that Random().normalized() works: tricky as the random xpr must be evaluated by
-    // normalized() in order to produce a consistent result.
-    VERIFY_IS_APPROX(VectorType::Random(rows).normalized().norm(), RealScalar(1));
-  }
-
-  // check inplace transpose
-  m3 = m1;
-  m3.transposeInPlace();
-  VERIFY_IS_APPROX(m3,m1.transpose());
-  m3.transposeInPlace();
-  VERIFY_IS_APPROX(m3,m1);
-  
-}
-
-void test_eigen2_adjoint()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( adjoint(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( adjoint(Matrix3d()) );
-    CALL_SUBTEST_3( adjoint(Matrix4f()) );
-    CALL_SUBTEST_4( adjoint(MatrixXcf(4, 4)) );
-    CALL_SUBTEST_5( adjoint(MatrixXi(8, 12)) );
-    CALL_SUBTEST_6( adjoint(MatrixXf(21, 21)) );
-  }
-  // test a large matrix only once
-  CALL_SUBTEST_7( adjoint(Matrix<float, 100, 100>()) );
-}
-
diff --git a/test/eigen2/eigen2_alignedbox.cpp b/test/eigen2/eigen2_alignedbox.cpp
deleted file mode 100644
index 35043b958..000000000
--- a/test/eigen2/eigen2_alignedbox.cpp
+++ /dev/null
@@ -1,60 +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/Geometry>
-#include <Eigen/LU>
-#include <Eigen/QR>
-
-template<typename BoxType> void alignedbox(const BoxType& _box)
-{
-  /* this test covers the following files:
-     AlignedBox.h
-  */
-
-  const int dim = _box.dim();
-  typedef typename BoxType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, BoxType::AmbientDimAtCompileTime, 1> VectorType;
-
-  VectorType p0 = VectorType::Random(dim);
-  VectorType p1 = VectorType::Random(dim);
-  RealScalar s1 = ei_random<RealScalar>(0,1);
-
-  BoxType b0(dim);
-  BoxType b1(VectorType::Random(dim),VectorType::Random(dim));
-  BoxType b2;
-
-  b0.extend(p0);
-  b0.extend(p1);
-  VERIFY(b0.contains(p0*s1+(Scalar(1)-s1)*p1));
-  VERIFY(!b0.contains(p0 + (1+s1)*(p1-p0)));
-
-  (b2 = b0).extend(b1);
-  VERIFY(b2.contains(b0));
-  VERIFY(b2.contains(b1));
-  VERIFY_IS_APPROX(b2.clamp(b0), b0);
-
-  // casting
-  const int Dim = BoxType::AmbientDimAtCompileTime;
-  typedef typename GetDifferentType<Scalar>::type OtherScalar;
-  AlignedBox<OtherScalar,Dim> hp1f = b0.template cast<OtherScalar>();
-  VERIFY_IS_APPROX(hp1f.template cast<Scalar>(),b0);
-  AlignedBox<Scalar,Dim> hp1d = b0.template cast<Scalar>();
-  VERIFY_IS_APPROX(hp1d.template cast<Scalar>(),b0);
-}
-
-void test_eigen2_alignedbox()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( alignedbox(AlignedBox<float,2>()) );
-    CALL_SUBTEST_2( alignedbox(AlignedBox<float,3>()) );
-    CALL_SUBTEST_3( alignedbox(AlignedBox<double,4>()) );
-  }
-}
diff --git a/test/eigen2/eigen2_array.cpp b/test/eigen2/eigen2_array.cpp
deleted file mode 100644
index c1ff40ce7..000000000
--- a/test/eigen2/eigen2_array.cpp
+++ /dev/null
@@ -1,142 +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/Array>
-
-template<typename MatrixType> void array(const MatrixType& m)
-{
-  /* this test covers the following files:
-     Array.cpp
-  */
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-
-  int rows = m.rows();
-  int cols = m.cols();
-
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols);
-
-  Scalar  s1 = ei_random<Scalar>(),
-          s2 = ei_random<Scalar>();
-
-  // scalar addition
-  VERIFY_IS_APPROX(m1.cwise() + s1, s1 + m1.cwise());
-  VERIFY_IS_APPROX(m1.cwise() + s1, MatrixType::Constant(rows,cols,s1) + m1);
-  VERIFY_IS_APPROX((m1*Scalar(2)).cwise() - s2, (m1+m1) - MatrixType::Constant(rows,cols,s2) );
-  m3 = m1;
-  m3.cwise() += s2;
-  VERIFY_IS_APPROX(m3, m1.cwise() + s2);
-  m3 = m1;
-  m3.cwise() -= s1;
-  VERIFY_IS_APPROX(m3, m1.cwise() - s1);
-
-  // reductions
-  VERIFY_IS_APPROX(m1.colwise().sum().sum(), m1.sum());
-  VERIFY_IS_APPROX(m1.rowwise().sum().sum(), m1.sum());
-  if (!ei_isApprox(m1.sum(), (m1+m2).sum()))
-    VERIFY_IS_NOT_APPROX(((m1+m2).rowwise().sum()).sum(), m1.sum());
-  VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(internal::scalar_sum_op<Scalar>()));
-}
-
-template<typename MatrixType> void comparisons(const MatrixType& m)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-
-  int rows = m.rows();
-  int cols = m.cols();
-
-  int r = ei_random<int>(0, rows-1),
-      c = ei_random<int>(0, cols-1);
-
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols);
-
-  VERIFY(((m1.cwise() + Scalar(1)).cwise() > m1).all());
-  VERIFY(((m1.cwise() - Scalar(1)).cwise() < m1).all());
-  if (rows*cols>1)
-  {
-    m3 = m1;
-    m3(r,c) += 1;
-    VERIFY(! (m1.cwise() < m3).all() );
-    VERIFY(! (m1.cwise() > m3).all() );
-  }
-  
-  // comparisons to scalar
-  VERIFY( (m1.cwise() != (m1(r,c)+1) ).any() );
-  VERIFY( (m1.cwise() > (m1(r,c)-1) ).any() );
-  VERIFY( (m1.cwise() < (m1(r,c)+1) ).any() );
-  VERIFY( (m1.cwise() == m1(r,c) ).any() );
-  
-  // test Select
-  VERIFY_IS_APPROX( (m1.cwise()<m2).select(m1,m2), m1.cwise().min(m2) );
-  VERIFY_IS_APPROX( (m1.cwise()>m2).select(m1,m2), m1.cwise().max(m2) );
-  Scalar mid = (m1.cwise().abs().minCoeff() + m1.cwise().abs().maxCoeff())/Scalar(2);
-  for (int j=0; j<cols; ++j)
-  for (int i=0; i<rows; ++i)
-    m3(i,j) = ei_abs(m1(i,j))<mid ? 0 : m1(i,j);
-  VERIFY_IS_APPROX( (m1.cwise().abs().cwise()<MatrixType::Constant(rows,cols,mid))
-                        .select(MatrixType::Zero(rows,cols),m1), m3);
-  // shorter versions:
-  VERIFY_IS_APPROX( (m1.cwise().abs().cwise()<MatrixType::Constant(rows,cols,mid))
-                        .select(0,m1), m3);
-  VERIFY_IS_APPROX( (m1.cwise().abs().cwise()>=MatrixType::Constant(rows,cols,mid))
-                        .select(m1,0), m3);
-  // even shorter version:
-  VERIFY_IS_APPROX( (m1.cwise().abs().cwise()<mid).select(0,m1), m3);
-  
-  // count
-  VERIFY(((m1.cwise().abs().cwise()+1).cwise()>RealScalar(0.1)).count() == rows*cols);
-  VERIFY_IS_APPROX(((m1.cwise().abs().cwise()+1).cwise()>RealScalar(0.1)).colwise().count().template cast<int>(), RowVectorXi::Constant(cols,rows));
-  VERIFY_IS_APPROX(((m1.cwise().abs().cwise()+1).cwise()>RealScalar(0.1)).rowwise().count().template cast<int>(), VectorXi::Constant(rows, cols));
-}
-
-template<typename VectorType> void lpNorm(const VectorType& v)
-{
-  VectorType u = VectorType::Random(v.size());
-
-  VERIFY_IS_APPROX(u.template lpNorm<Infinity>(), u.cwise().abs().maxCoeff());
-  VERIFY_IS_APPROX(u.template lpNorm<1>(), u.cwise().abs().sum());
-  VERIFY_IS_APPROX(u.template lpNorm<2>(), ei_sqrt(u.cwise().abs().cwise().square().sum()));
-  VERIFY_IS_APPROX(ei_pow(u.template lpNorm<5>(), typename VectorType::RealScalar(5)), u.cwise().abs().cwise().pow(5).sum());
-}
-
-void test_eigen2_array()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( array(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( array(Matrix2f()) );
-    CALL_SUBTEST_3( array(Matrix4d()) );
-    CALL_SUBTEST_4( array(MatrixXcf(3, 3)) );
-    CALL_SUBTEST_5( array(MatrixXf(8, 12)) );
-    CALL_SUBTEST_6( array(MatrixXi(8, 12)) );
-  }
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( comparisons(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( comparisons(Matrix2f()) );
-    CALL_SUBTEST_3( comparisons(Matrix4d()) );
-    CALL_SUBTEST_5( comparisons(MatrixXf(8, 12)) );
-    CALL_SUBTEST_6( comparisons(MatrixXi(8, 12)) );
-  }
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( lpNorm(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( lpNorm(Vector2f()) );
-    CALL_SUBTEST_3( lpNorm(Vector3d()) );
-    CALL_SUBTEST_4( lpNorm(Vector4f()) );
-    CALL_SUBTEST_5( lpNorm(VectorXf(16)) );
-    CALL_SUBTEST_7( lpNorm(VectorXcd(10)) );
-  }
-}
diff --git a/test/eigen2/eigen2_basicstuff.cpp b/test/eigen2/eigen2_basicstuff.cpp
deleted file mode 100644
index 4fa16d5ae..000000000
--- a/test/eigen2/eigen2_basicstuff.cpp
+++ /dev/null
@@ -1,108 +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) 2006-2008 Benoit Jacob <jacob.benoit.1@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 "main.h"
-
-template<typename MatrixType> void basicStuff(const MatrixType& m)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-
-  int rows = m.rows();
-  int cols = m.cols();
-
-  // this test relies a lot on Random.h, and there's not much more that we can do
-  // to test it, hence I consider that we will have tested Random.h
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols),
-             mzero = MatrixType::Zero(rows, cols),
-             identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
-                              ::Identity(rows, rows),
-             square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>::Random(rows, rows);
-  VectorType v1 = VectorType::Random(rows),
-             v2 = VectorType::Random(rows),
-             vzero = VectorType::Zero(rows);
-
-  Scalar x = ei_random<Scalar>();
-
-  int r = ei_random<int>(0, rows-1),
-      c = ei_random<int>(0, cols-1);
-
-  m1.coeffRef(r,c) = x;
-  VERIFY_IS_APPROX(x, m1.coeff(r,c));
-  m1(r,c) = x;
-  VERIFY_IS_APPROX(x, m1(r,c));
-  v1.coeffRef(r) = x;
-  VERIFY_IS_APPROX(x, v1.coeff(r));
-  v1(r) = x;
-  VERIFY_IS_APPROX(x, v1(r));
-  v1[r] = x;
-  VERIFY_IS_APPROX(x, v1[r]);
-
-  VERIFY_IS_APPROX(               v1,    v1);
-  VERIFY_IS_NOT_APPROX(           v1,    2*v1);
-  VERIFY_IS_MUCH_SMALLER_THAN(    vzero, v1);
-  if(NumTraits<Scalar>::HasFloatingPoint)
-    VERIFY_IS_MUCH_SMALLER_THAN(  vzero, v1.norm());
-  VERIFY_IS_NOT_MUCH_SMALLER_THAN(v1,    v1);
-  VERIFY_IS_APPROX(               vzero, v1-v1);
-  VERIFY_IS_APPROX(               m1,    m1);
-  VERIFY_IS_NOT_APPROX(           m1,    2*m1);
-  VERIFY_IS_MUCH_SMALLER_THAN(    mzero, m1);
-  VERIFY_IS_NOT_MUCH_SMALLER_THAN(m1,    m1);
-  VERIFY_IS_APPROX(               mzero, m1-m1);
-
-  // always test operator() on each read-only expression class,
-  // in order to check const-qualifiers.
-  // indeed, if an expression class (here Zero) is meant to be read-only,
-  // hence has no _write() method, the corresponding MatrixBase method (here zero())
-  // should return a const-qualified object so that it is the const-qualified
-  // operator() that gets called, which in turn calls _read().
-  VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::Zero(rows,cols)(r,c), static_cast<Scalar>(1));
-
-  // now test copying a row-vector into a (column-)vector and conversely.
-  square.col(r) = square.row(r).eval();
-  Matrix<Scalar, 1, MatrixType::RowsAtCompileTime> rv(rows);
-  Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> cv(rows);
-  rv = square.row(r);
-  cv = square.col(r);
-  VERIFY_IS_APPROX(rv, cv.transpose());
-
-  if(cols!=1 && rows!=1 && MatrixType::SizeAtCompileTime!=Dynamic)
-  {
-    VERIFY_RAISES_ASSERT(m1 = (m2.block(0,0, rows-1, cols-1)));
-  }
-
-  VERIFY_IS_APPROX(m3 = m1,m1);
-  MatrixType m4;
-  VERIFY_IS_APPROX(m4 = m1,m1);
-
-  // test swap
-  m3 = m1;
-  m1.swap(m2);
-  VERIFY_IS_APPROX(m3, m2);
-  if(rows*cols>=3)
-  {
-    VERIFY_IS_NOT_APPROX(m3, m1);
-  }
-}
-
-void test_eigen2_basicstuff()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( basicStuff(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( basicStuff(Matrix4d()) );
-    CALL_SUBTEST_3( basicStuff(MatrixXcf(3, 3)) );
-    CALL_SUBTEST_4( basicStuff(MatrixXi(8, 12)) );
-    CALL_SUBTEST_5( basicStuff(MatrixXcd(20, 20)) );
-    CALL_SUBTEST_6( basicStuff(Matrix<float, 100, 100>()) );
-    CALL_SUBTEST_7( basicStuff(Matrix<long double,Dynamic,Dynamic>(10,10)) );
-  }
-}
diff --git a/test/eigen2/eigen2_bug_132.cpp b/test/eigen2/eigen2_bug_132.cpp
deleted file mode 100644
index 7fe3610ce..000000000
--- a/test/eigen2/eigen2_bug_132.cpp
+++ /dev/null
@@ -1,26 +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) 2010 Benoit Jacob <jacob.benoit.1@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 "main.h"
-
-void test_eigen2_bug_132() {
-  int size = 100;
-  MatrixXd A(size, size);
-  VectorXd b(size), c(size);
-  {
-    VectorXd y = A.transpose() * (b-c);  // bug 132: infinite recursion in coeffRef
-    VectorXd z = (b-c).transpose() * A;  // bug 132: infinite recursion in coeffRef
-  }
-
-  // the following ones weren't failing, but let's include them for completeness:
-  {
-    VectorXd y = A * (b-c);
-    VectorXd z = (b-c).transpose() * A.transpose();
-  }
-}
diff --git a/test/eigen2/eigen2_cholesky.cpp b/test/eigen2/eigen2_cholesky.cpp
deleted file mode 100644
index 9c4b6f561..000000000
--- a/test/eigen2/eigen2_cholesky.cpp
+++ /dev/null
@@ -1,113 +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/.
-
-#define EIGEN_NO_ASSERTION_CHECKING
-#include "main.h"
-#include <Eigen/Cholesky>
-#include <Eigen/LU>
-
-#ifdef HAS_GSL
-#include "gsl_helper.h"
-#endif
-
-template<typename MatrixType> void cholesky(const MatrixType& m)
-{
-  /* this test covers the following files:
-     LLT.h LDLT.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, MatrixType::RowsAtCompileTime> SquareMatrixType;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-
-  MatrixType a0 = MatrixType::Random(rows,cols);
-  VectorType vecB = VectorType::Random(rows), vecX(rows);
-  MatrixType matB = MatrixType::Random(rows,cols), matX(rows,cols);
-  SquareMatrixType symm =  a0 * a0.adjoint();
-  // let's make sure the matrix is not singular or near singular
-  MatrixType a1 = MatrixType::Random(rows,cols);
-  symm += a1 * a1.adjoint();
-
-  #ifdef HAS_GSL
-  if (ei_is_same_type<RealScalar,double>::ret)
-  {
-    typedef GslTraits<Scalar> Gsl;
-    typename Gsl::Matrix gMatA=0, gSymm=0;
-    typename Gsl::Vector gVecB=0, gVecX=0;
-    convert<MatrixType>(symm, gSymm);
-    convert<MatrixType>(symm, gMatA);
-    convert<VectorType>(vecB, gVecB);
-    convert<VectorType>(vecB, gVecX);
-    Gsl::cholesky(gMatA);
-    Gsl::cholesky_solve(gMatA, gVecB, gVecX);
-    VectorType vecX(rows), _vecX, _vecB;
-    convert(gVecX, _vecX);
-    symm.llt().solve(vecB, &vecX);
-    Gsl::prod(gSymm, gVecX, gVecB);
-    convert(gVecB, _vecB);
-    // test gsl itself !
-    VERIFY_IS_APPROX(vecB, _vecB);
-    VERIFY_IS_APPROX(vecX, _vecX);
-
-    Gsl::free(gMatA);
-    Gsl::free(gSymm);
-    Gsl::free(gVecB);
-    Gsl::free(gVecX);
-  }
-  #endif
-
-  {
-    LDLT<SquareMatrixType> ldlt(symm);
-    VERIFY(ldlt.isPositiveDefinite());
-    // in eigen3, LDLT is pivoting
-    //VERIFY_IS_APPROX(symm, ldlt.matrixL() * ldlt.vectorD().asDiagonal() * ldlt.matrixL().adjoint());
-    ldlt.solve(vecB, &vecX);
-    VERIFY_IS_APPROX(symm * vecX, vecB);
-    ldlt.solve(matB, &matX);
-    VERIFY_IS_APPROX(symm * matX, matB);
-  }
-
-  {
-    LLT<SquareMatrixType> chol(symm);
-    VERIFY(chol.isPositiveDefinite());
-    VERIFY_IS_APPROX(symm, chol.matrixL() * chol.matrixL().adjoint());
-    chol.solve(vecB, &vecX);
-    VERIFY_IS_APPROX(symm * vecX, vecB);
-    chol.solve(matB, &matX);
-    VERIFY_IS_APPROX(symm * matX, matB);
-  }
-
-#if 0 // cholesky is not rank-revealing anyway
-  // test isPositiveDefinite on non definite matrix
-  if (rows>4)
-  {
-    SquareMatrixType symm =  a0.block(0,0,rows,cols-4) * a0.block(0,0,rows,cols-4).adjoint();
-    LLT<SquareMatrixType> chol(symm);
-    VERIFY(!chol.isPositiveDefinite());
-    LDLT<SquareMatrixType> cholnosqrt(symm);
-    VERIFY(!cholnosqrt.isPositiveDefinite());
-  }
-#endif
-}
-
-void test_eigen2_cholesky()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( cholesky(Matrix<double,1,1>()) );
-    CALL_SUBTEST_2( cholesky(Matrix2d()) );
-    CALL_SUBTEST_3( cholesky(Matrix3f()) );
-    CALL_SUBTEST_4( cholesky(Matrix4d()) );
-    CALL_SUBTEST_5( cholesky(MatrixXcd(7,7)) );
-    CALL_SUBTEST_6( cholesky(MatrixXf(17,17)) );
-    CALL_SUBTEST_7( cholesky(MatrixXd(33,33)) );
-  }
-}
diff --git a/test/eigen2/eigen2_commainitializer.cpp b/test/eigen2/eigen2_commainitializer.cpp
deleted file mode 100644
index e0f901e0b..000000000
--- a/test/eigen2/eigen2_commainitializer.cpp
+++ /dev/null
@@ -1,46 +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"
-
-void test_eigen2_commainitializer()
-{
-  Matrix3d m3;
-  Matrix4d m4;
-
-  VERIFY_RAISES_ASSERT( (m3 << 1, 2, 3, 4, 5, 6, 7, 8) );
-  
-  #ifndef _MSC_VER
-  VERIFY_RAISES_ASSERT( (m3 << 1, 2, 3, 4, 5, 6, 7, 8, 9, 10) );
-  #endif
-
-  double data[] = {1, 2, 3, 4, 5, 6, 7, 8, 9};
-  Matrix3d ref = Map<Matrix<double,3,3,RowMajor> >(data);
-
-  m3 = Matrix3d::Random();
-  m3 << 1, 2, 3, 4, 5, 6, 7, 8, 9;
-  VERIFY_IS_APPROX(m3, ref );
-
-  Vector3d vec[3];
-  vec[0] << 1, 4, 7;
-  vec[1] << 2, 5, 8;
-  vec[2] << 3, 6, 9;
-  m3 = Matrix3d::Random();
-  m3 << vec[0], vec[1], vec[2];
-  VERIFY_IS_APPROX(m3, ref);
-
-  vec[0] << 1, 2, 3;
-  vec[1] << 4, 5, 6;
-  vec[2] << 7, 8, 9;
-  m3 = Matrix3d::Random();
-  m3 << vec[0].transpose(),
-        4, 5, 6,
-        vec[2].transpose();
-  VERIFY_IS_APPROX(m3, ref);
-}
diff --git a/test/eigen2/eigen2_cwiseop.cpp b/test/eigen2/eigen2_cwiseop.cpp
deleted file mode 100644
index 4391d19b4..000000000
--- a/test/eigen2/eigen2_cwiseop.cpp
+++ /dev/null
@@ -1,158 +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>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@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 "main.h"
-#include <functional>
-#include <Eigen/Array>
-
-using namespace std;
-
-template<typename Scalar> struct AddIfNull {
-    const Scalar operator() (const Scalar a, const Scalar b) const {return a<=1e-3 ? b : a;}
-    enum { Cost = NumTraits<Scalar>::AddCost };
-};
-
-template<typename MatrixType> void cwiseops(const MatrixType& m)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-
-  int rows = m.rows();
-  int cols = m.cols();
-
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols),
-             m4(rows, cols),
-             mzero = MatrixType::Zero(rows, cols),
-             mones = MatrixType::Ones(rows, cols),
-             identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
-                              ::Identity(rows, rows),
-             square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>::Random(rows, rows);
-  VectorType v1 = VectorType::Random(rows),
-             v2 = VectorType::Random(rows),
-             vzero = VectorType::Zero(rows),
-             vones = VectorType::Ones(rows),
-             v3(rows);
-
-  int r = ei_random<int>(0, rows-1),
-      c = ei_random<int>(0, cols-1);
-  
-  Scalar s1 = ei_random<Scalar>();
-  
-  // test Zero, Ones, Constant, and the set* variants
-  m3 = MatrixType::Constant(rows, cols, s1);
-  for (int j=0; j<cols; ++j)
-    for (int i=0; i<rows; ++i)
-    {
-      VERIFY_IS_APPROX(mzero(i,j), Scalar(0));
-      VERIFY_IS_APPROX(mones(i,j), Scalar(1));
-      VERIFY_IS_APPROX(m3(i,j), s1);
-    }
-  VERIFY(mzero.isZero());
-  VERIFY(mones.isOnes());
-  VERIFY(m3.isConstant(s1));
-  VERIFY(identity.isIdentity());
-  VERIFY_IS_APPROX(m4.setConstant(s1), m3);
-  VERIFY_IS_APPROX(m4.setConstant(rows,cols,s1), m3);
-  VERIFY_IS_APPROX(m4.setZero(), mzero);
-  VERIFY_IS_APPROX(m4.setZero(rows,cols), mzero);
-  VERIFY_IS_APPROX(m4.setOnes(), mones);
-  VERIFY_IS_APPROX(m4.setOnes(rows,cols), mones);
-  m4.fill(s1);
-  VERIFY_IS_APPROX(m4, m3);
-  
-  VERIFY_IS_APPROX(v3.setConstant(rows, s1), VectorType::Constant(rows,s1));
-  VERIFY_IS_APPROX(v3.setZero(rows), vzero);
-  VERIFY_IS_APPROX(v3.setOnes(rows), vones);
-
-  m2 = m2.template binaryExpr<AddIfNull<Scalar> >(mones);
-
-  VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().abs2());
-  VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().square());
-  VERIFY_IS_APPROX(m1.cwise().pow(3), m1.cwise().cube());
-
-  VERIFY_IS_APPROX(m1 + mones, m1.cwise()+Scalar(1));
-  VERIFY_IS_APPROX(m1 - mones, m1.cwise()-Scalar(1));
-  m3 = m1; m3.cwise() += 1;
-  VERIFY_IS_APPROX(m1 + mones, m3);
-  m3 = m1; m3.cwise() -= 1;
-  VERIFY_IS_APPROX(m1 - mones, m3);
-
-  VERIFY_IS_APPROX(m2, m2.cwise() * mones);
-  VERIFY_IS_APPROX(m1.cwise() * m2,  m2.cwise() * m1);
-  m3 = m1;
-  m3.cwise() *= m2;
-  VERIFY_IS_APPROX(m3, m1.cwise() * m2);
-  
-  VERIFY_IS_APPROX(mones,    m2.cwise()/m2);
-  if(NumTraits<Scalar>::HasFloatingPoint)
-  {
-    VERIFY_IS_APPROX(m1.cwise() / m2,    m1.cwise() * (m2.cwise().inverse()));
-    m3 = m1.cwise().abs().cwise().sqrt();
-    VERIFY_IS_APPROX(m3.cwise().square(), m1.cwise().abs());
-    VERIFY_IS_APPROX(m1.cwise().square().cwise().sqrt(), m1.cwise().abs());
-    VERIFY_IS_APPROX(m1.cwise().abs().cwise().log().cwise().exp() , m1.cwise().abs());
-
-    VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().square());
-    m3 = (m1.cwise().abs().cwise()<=RealScalar(0.01)).select(mones,m1);
-    VERIFY_IS_APPROX(m3.cwise().pow(-1), m3.cwise().inverse());
-    m3 = m1.cwise().abs();
-    VERIFY_IS_APPROX(m3.cwise().pow(RealScalar(0.5)), m3.cwise().sqrt());
-    
-//     VERIFY_IS_APPROX(m1.cwise().tan(), m1.cwise().sin().cwise() / m1.cwise().cos());
-    VERIFY_IS_APPROX(mones, m1.cwise().sin().cwise().square() + m1.cwise().cos().cwise().square());
-    m3 = m1;
-    m3.cwise() /= m2;
-    VERIFY_IS_APPROX(m3, m1.cwise() / m2);
-  }
-
-  // check min
-  VERIFY_IS_APPROX( m1.cwise().min(m2), m2.cwise().min(m1) );
-  VERIFY_IS_APPROX( m1.cwise().min(m1+mones), m1 );
-  VERIFY_IS_APPROX( m1.cwise().min(m1-mones), m1-mones );
-
-  // check max
-  VERIFY_IS_APPROX( m1.cwise().max(m2), m2.cwise().max(m1) );
-  VERIFY_IS_APPROX( m1.cwise().max(m1-mones), m1 );
-  VERIFY_IS_APPROX( m1.cwise().max(m1+mones), m1+mones );
-  
-  VERIFY( (m1.cwise() == m1).all() );
-  VERIFY( (m1.cwise() != m2).any() );
-  VERIFY(!(m1.cwise() == (m1+mones)).any() );
-  if (rows*cols>1)
-  {
-    m3 = m1;
-    m3(r,c) += 1;
-    VERIFY( (m1.cwise() == m3).any() );
-    VERIFY( !(m1.cwise() == m3).all() );
-  }
-  VERIFY( (m1.cwise().min(m2).cwise() <= m2).all() );
-  VERIFY( (m1.cwise().max(m2).cwise() >= m2).all() );
-  VERIFY( (m1.cwise().min(m2).cwise() < (m1+mones)).all() );
-  VERIFY( (m1.cwise().max(m2).cwise() > (m1-mones)).all() );
-
-  VERIFY( (m1.cwise()<m1.unaryExpr(bind2nd(plus<Scalar>(), Scalar(1)))).all() );
-  VERIFY( !(m1.cwise()<m1.unaryExpr(bind2nd(minus<Scalar>(), Scalar(1)))).all() );
-  VERIFY( !(m1.cwise()>m1.unaryExpr(bind2nd(plus<Scalar>(), Scalar(1)))).any() );
-}
-
-void test_eigen2_cwiseop()
-{
-  for(int i = 0; i < g_repeat ; i++) {
-    CALL_SUBTEST_1( cwiseops(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( cwiseops(Matrix4d()) );
-    CALL_SUBTEST_3( cwiseops(MatrixXf(3, 3)) );
-    CALL_SUBTEST_3( cwiseops(MatrixXf(22, 22)) );
-    CALL_SUBTEST_4( cwiseops(MatrixXi(8, 12)) );
-    CALL_SUBTEST_5( cwiseops(MatrixXd(20, 20)) );
-  }
-}
diff --git a/test/eigen2/eigen2_determinant.cpp b/test/eigen2/eigen2_determinant.cpp
deleted file mode 100644
index c7b4ad053..000000000
--- a/test/eigen2/eigen2_determinant.cpp
+++ /dev/null
@@ -1,61 +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 Benoit Jacob <jacob.benoit.1@gmail.com>
-// 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/LU>
-
-template<typename MatrixType> void determinant(const MatrixType& m)
-{
-  /* this test covers the following files:
-     Determinant.h
-  */
-  int size = m.rows();
-
-  MatrixType m1(size, size), m2(size, size);
-  m1.setRandom();
-  m2.setRandom();
-  typedef typename MatrixType::Scalar Scalar;
-  Scalar x = ei_random<Scalar>();
-  VERIFY_IS_APPROX(MatrixType::Identity(size, size).determinant(), Scalar(1));
-  VERIFY_IS_APPROX((m1*m2).determinant(), m1.determinant() * m2.determinant());
-  if(size==1) return;
-  int i = ei_random<int>(0, size-1);
-  int j;
-  do {
-    j = ei_random<int>(0, size-1);
-  } while(j==i);
-  m2 = m1;
-  m2.row(i).swap(m2.row(j));
-  VERIFY_IS_APPROX(m2.determinant(), -m1.determinant());
-  m2 = m1;
-  m2.col(i).swap(m2.col(j));
-  VERIFY_IS_APPROX(m2.determinant(), -m1.determinant());
-  VERIFY_IS_APPROX(m2.determinant(), m2.transpose().determinant());
-  VERIFY_IS_APPROX(ei_conj(m2.determinant()), m2.adjoint().determinant());
-  m2 = m1;
-  m2.row(i) += x*m2.row(j);
-  VERIFY_IS_APPROX(m2.determinant(), m1.determinant());
-  m2 = m1;
-  m2.row(i) *= x;
-  VERIFY_IS_APPROX(m2.determinant(), m1.determinant() * x);
-}
-
-void test_eigen2_determinant()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( determinant(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( determinant(Matrix<double, 2, 2>()) );
-    CALL_SUBTEST_3( determinant(Matrix<double, 3, 3>()) );
-    CALL_SUBTEST_4( determinant(Matrix<double, 4, 4>()) );
-    CALL_SUBTEST_5( determinant(Matrix<std::complex<double>, 10, 10>()) );
-    CALL_SUBTEST_6( determinant(MatrixXd(20, 20)) );
-  }
-  CALL_SUBTEST_6( determinant(MatrixXd(200, 200)) );
-}
diff --git a/test/eigen2/eigen2_dynalloc.cpp b/test/eigen2/eigen2_dynalloc.cpp
deleted file mode 100644
index 1891a9e33..000000000
--- a/test/eigen2/eigen2_dynalloc.cpp
+++ /dev/null
@@ -1,131 +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"
-
-#if EIGEN_ARCH_WANTS_ALIGNMENT
-#define ALIGNMENT 16
-#else
-#define ALIGNMENT 1
-#endif
-
-void check_handmade_aligned_malloc()
-{
-  for(int i = 1; i < 1000; i++)
-  {
-    char *p = (char*)ei_handmade_aligned_malloc(i);
-    VERIFY(std::size_t(p)%ALIGNMENT==0);
-    // if the buffer is wrongly allocated this will give a bad write --> check with valgrind
-    for(int j = 0; j < i; j++) p[j]=0;
-    ei_handmade_aligned_free(p);
-  }
-}
-
-void check_aligned_malloc()
-{
-  for(int i = 1; i < 1000; i++)
-  {
-    char *p = (char*)ei_aligned_malloc(i);
-    VERIFY(std::size_t(p)%ALIGNMENT==0);
-    // if the buffer is wrongly allocated this will give a bad write --> check with valgrind
-    for(int j = 0; j < i; j++) p[j]=0;
-    ei_aligned_free(p);
-  }
-}
-
-void check_aligned_new()
-{
-  for(int i = 1; i < 1000; i++)
-  {
-    float *p = ei_aligned_new<float>(i);
-    VERIFY(std::size_t(p)%ALIGNMENT==0);
-    // if the buffer is wrongly allocated this will give a bad write --> check with valgrind
-    for(int j = 0; j < i; j++) p[j]=0;
-    ei_aligned_delete(p,i);
-  }
-}
-
-void check_aligned_stack_alloc()
-{
-  for(int i = 1; i < 1000; i++)
-  {
-    ei_declare_aligned_stack_constructed_variable(float, p, i, 0);
-    VERIFY(std::size_t(p)%ALIGNMENT==0);
-    // if the buffer is wrongly allocated this will give a bad write --> check with valgrind
-    for(int j = 0; j < i; j++) p[j]=0;
-  }
-}
-
-
-// test compilation with both a struct and a class...
-struct MyStruct
-{
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-  char dummychar;
-  Vector4f avec;
-};
-
-class MyClassA
-{
-  public:
-    EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-    char dummychar;
-    Vector4f avec;
-};
-
-template<typename T> void check_dynaligned()
-{
-  T* obj = new T;
-  VERIFY(std::size_t(obj)%ALIGNMENT==0);
-  delete obj;
-}
-
-void test_eigen2_dynalloc()
-{
-  // low level dynamic memory allocation
-  CALL_SUBTEST(check_handmade_aligned_malloc());
-  CALL_SUBTEST(check_aligned_malloc());
-  CALL_SUBTEST(check_aligned_new());
-  CALL_SUBTEST(check_aligned_stack_alloc());
-
-  for (int i=0; i<g_repeat*100; ++i)
-  {
-    CALL_SUBTEST( check_dynaligned<Vector4f>() );
-    CALL_SUBTEST( check_dynaligned<Vector2d>() );
-    CALL_SUBTEST( check_dynaligned<Matrix4f>() );
-    CALL_SUBTEST( check_dynaligned<Vector4d>() );
-    CALL_SUBTEST( check_dynaligned<Vector4i>() );
-  }
-  
-  // check static allocation, who knows ?
-  {
-    MyStruct foo0;  VERIFY(std::size_t(foo0.avec.data())%ALIGNMENT==0);
-    MyClassA fooA;  VERIFY(std::size_t(fooA.avec.data())%ALIGNMENT==0);
-  }
-
-  // dynamic allocation, single object
-  for (int i=0; i<g_repeat*100; ++i)
-  {
-    MyStruct *foo0 = new MyStruct();  VERIFY(std::size_t(foo0->avec.data())%ALIGNMENT==0);
-    MyClassA *fooA = new MyClassA();  VERIFY(std::size_t(fooA->avec.data())%ALIGNMENT==0);
-    delete foo0;
-    delete fooA;
-  }
-
-  // dynamic allocation, array
-  const int N = 10;
-  for (int i=0; i<g_repeat*100; ++i)
-  {
-    MyStruct *foo0 = new MyStruct[N];  VERIFY(std::size_t(foo0->avec.data())%ALIGNMENT==0);
-    MyClassA *fooA = new MyClassA[N];  VERIFY(std::size_t(fooA->avec.data())%ALIGNMENT==0);
-    delete[] foo0;
-    delete[] fooA;
-  }
-  
-}
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)) );
-  }
-}
-
diff --git a/test/eigen2/eigen2_first_aligned.cpp b/test/eigen2/eigen2_first_aligned.cpp
deleted file mode 100644
index 51bb3cad1..000000000
--- a/test/eigen2/eigen2_first_aligned.cpp
+++ /dev/null
@@ -1,49 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@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 "main.h"
-
-template<typename Scalar>
-void test_eigen2_first_aligned_helper(Scalar *array, int size)
-{
-  const int packet_size = sizeof(Scalar) * ei_packet_traits<Scalar>::size;
-  VERIFY(((std::size_t(array) + sizeof(Scalar) * ei_alignmentOffset(array, size)) % packet_size) == 0);
-}
-
-template<typename Scalar>
-void test_eigen2_none_aligned_helper(Scalar *array, int size)
-{
-  VERIFY(ei_packet_traits<Scalar>::size == 1 || ei_alignmentOffset(array, size) == size);
-}
-
-struct some_non_vectorizable_type { float x; };
-
-void test_eigen2_first_aligned()
-{
-  EIGEN_ALIGN_128 float array_float[100];
-  test_first_aligned_helper(array_float, 50);
-  test_first_aligned_helper(array_float+1, 50);
-  test_first_aligned_helper(array_float+2, 50);
-  test_first_aligned_helper(array_float+3, 50);
-  test_first_aligned_helper(array_float+4, 50);
-  test_first_aligned_helper(array_float+5, 50);
-  
-  EIGEN_ALIGN_128 double array_double[100];
-  test_first_aligned_helper(array_double, 50);
-  test_first_aligned_helper(array_double+1, 50);
-  test_first_aligned_helper(array_double+2, 50);
-  
-  double *array_double_plus_4_bytes = (double*)(std::size_t(array_double)+4);
-  test_none_aligned_helper(array_double_plus_4_bytes, 50);
-  test_none_aligned_helper(array_double_plus_4_bytes+1, 50);
-  
-  some_non_vectorizable_type array_nonvec[100];
-  test_first_aligned_helper(array_nonvec, 100);
-  test_none_aligned_helper(array_nonvec, 100);
-}
diff --git a/test/eigen2/eigen2_geometry.cpp b/test/eigen2/eigen2_geometry.cpp
deleted file mode 100644
index 70b4ab5f1..000000000
--- a/test/eigen2/eigen2_geometry.cpp
+++ /dev/null
@@ -1,431 +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/Geometry>
-#include <Eigen/LU>
-#include <Eigen/SVD>
-
-template<typename Scalar> void geometry(void)
-{
-  /* this test covers the following files:
-     Cross.h Quaternion.h, Transform.cpp
-  */
-
-  typedef Matrix<Scalar,2,2> Matrix2;
-  typedef Matrix<Scalar,3,3> Matrix3;
-  typedef Matrix<Scalar,4,4> Matrix4;
-  typedef Matrix<Scalar,2,1> Vector2;
-  typedef Matrix<Scalar,3,1> Vector3;
-  typedef Matrix<Scalar,4,1> Vector4;
-  typedef Quaternion<Scalar> Quaternionx;
-  typedef AngleAxis<Scalar> AngleAxisx;
-  typedef Transform<Scalar,2> Transform2;
-  typedef Transform<Scalar,3> Transform3;
-  typedef Scaling<Scalar,2> Scaling2;
-  typedef Scaling<Scalar,3> Scaling3;
-  typedef Translation<Scalar,2> Translation2;
-  typedef Translation<Scalar,3> Translation3;
-
-  Scalar largeEps = test_precision<Scalar>();
-  if (ei_is_same_type<Scalar,float>::ret)
-    largeEps = 1e-2f;
-
-  Vector3 v0 = Vector3::Random(),
-    v1 = Vector3::Random(),
-    v2 = Vector3::Random();
-  Vector2 u0 = Vector2::Random();
-  Matrix3 matrot1;
-
-  Scalar a = ei_random<Scalar>(-Scalar(M_PI), Scalar(M_PI));
-
-  // cross product
-  VERIFY_IS_MUCH_SMALLER_THAN(v1.cross(v2).eigen2_dot(v1), Scalar(1));
-  Matrix3 m;
-  m << v0.normalized(),
-      (v0.cross(v1)).normalized(),
-      (v0.cross(v1).cross(v0)).normalized();
-  VERIFY(m.isUnitary());
-
-  // Quaternion: Identity(), setIdentity();
-  Quaternionx q1, q2;
-  q2.setIdentity();
-  VERIFY_IS_APPROX(Quaternionx(Quaternionx::Identity()).coeffs(), q2.coeffs());
-  q1.coeffs().setRandom();
-  VERIFY_IS_APPROX(q1.coeffs(), (q1*q2).coeffs());
-
-  // unitOrthogonal
-  VERIFY_IS_MUCH_SMALLER_THAN(u0.unitOrthogonal().eigen2_dot(u0), Scalar(1));
-  VERIFY_IS_MUCH_SMALLER_THAN(v0.unitOrthogonal().eigen2_dot(v0), Scalar(1));
-  VERIFY_IS_APPROX(u0.unitOrthogonal().norm(), Scalar(1));
-  VERIFY_IS_APPROX(v0.unitOrthogonal().norm(), Scalar(1));
-
-
-  VERIFY_IS_APPROX(v0, AngleAxisx(a, v0.normalized()) * v0);
-  VERIFY_IS_APPROX(-v0, AngleAxisx(Scalar(M_PI), v0.unitOrthogonal()) * v0);
-  VERIFY_IS_APPROX(ei_cos(a)*v0.squaredNorm(), v0.eigen2_dot(AngleAxisx(a, v0.unitOrthogonal()) * v0));
-  m = AngleAxisx(a, v0.normalized()).toRotationMatrix().adjoint();
-  VERIFY_IS_APPROX(Matrix3::Identity(), m * AngleAxisx(a, v0.normalized()));
-  VERIFY_IS_APPROX(Matrix3::Identity(), AngleAxisx(a, v0.normalized()) * m);
-
-  q1 = AngleAxisx(a, v0.normalized());
-  q2 = AngleAxisx(a, v1.normalized());
-
-  // angular distance
-  Scalar refangle = ei_abs(AngleAxisx(q1.inverse()*q2).angle());
-  if (refangle>Scalar(M_PI))
-    refangle = Scalar(2)*Scalar(M_PI) - refangle;
-  
-  if((q1.coeffs()-q2.coeffs()).norm() > 10*largeEps)
-  {
-    VERIFY(ei_isApprox(q1.angularDistance(q2), refangle, largeEps));
-  }
-
-  // rotation matrix conversion
-  VERIFY_IS_APPROX(q1 * v2, q1.toRotationMatrix() * v2);
-  VERIFY_IS_APPROX(q1 * q2 * v2,
-    q1.toRotationMatrix() * q2.toRotationMatrix() * v2);
-
-  VERIFY( (q2*q1).isApprox(q1*q2, largeEps) || !(q2 * q1 * v2).isApprox(
-    q1.toRotationMatrix() * q2.toRotationMatrix() * v2));
-
-  q2 = q1.toRotationMatrix();
-  VERIFY_IS_APPROX(q1*v1,q2*v1);
-
-  matrot1 = AngleAxisx(Scalar(0.1), Vector3::UnitX())
-          * AngleAxisx(Scalar(0.2), Vector3::UnitY())
-          * AngleAxisx(Scalar(0.3), Vector3::UnitZ());
-  VERIFY_IS_APPROX(matrot1 * v1,
-       AngleAxisx(Scalar(0.1), Vector3(1,0,0)).toRotationMatrix()
-    * (AngleAxisx(Scalar(0.2), Vector3(0,1,0)).toRotationMatrix()
-    * (AngleAxisx(Scalar(0.3), Vector3(0,0,1)).toRotationMatrix() * v1)));
-
-  // angle-axis conversion
-  AngleAxisx aa = q1;
-  VERIFY_IS_APPROX(q1 * v1, Quaternionx(aa) * v1);
-  VERIFY_IS_NOT_APPROX(q1 * v1, Quaternionx(AngleAxisx(aa.angle()*2,aa.axis())) * v1);
-
-  // from two vector creation
-  VERIFY_IS_APPROX(v2.normalized(),(q2.setFromTwoVectors(v1,v2)*v1).normalized());
-  VERIFY_IS_APPROX(v2.normalized(),(q2.setFromTwoVectors(v1,v2)*v1).normalized());
-
-  // inverse and conjugate
-  VERIFY_IS_APPROX(q1 * (q1.inverse() * v1), v1);
-  VERIFY_IS_APPROX(q1 * (q1.conjugate() * v1), v1);
-
-  // AngleAxis
-  VERIFY_IS_APPROX(AngleAxisx(a,v1.normalized()).toRotationMatrix(),
-    Quaternionx(AngleAxisx(a,v1.normalized())).toRotationMatrix());
-
-  AngleAxisx aa1;
-  m = q1.toRotationMatrix();
-  aa1 = m;
-  VERIFY_IS_APPROX(AngleAxisx(m).toRotationMatrix(),
-    Quaternionx(m).toRotationMatrix());
-
-  // Transform
-  // TODO complete the tests !
-  a = 0;
-  while (ei_abs(a)<Scalar(0.1))
-    a = ei_random<Scalar>(-Scalar(0.4)*Scalar(M_PI), Scalar(0.4)*Scalar(M_PI));
-  q1 = AngleAxisx(a, v0.normalized());
-  Transform3 t0, t1, t2;
-  // first test setIdentity() and Identity()
-  t0.setIdentity();
-  VERIFY_IS_APPROX(t0.matrix(), Transform3::MatrixType::Identity());
-  t0.matrix().setZero();
-  t0 = Transform3::Identity();
-  VERIFY_IS_APPROX(t0.matrix(), Transform3::MatrixType::Identity());
-
-  t0.linear() = q1.toRotationMatrix();
-  t1.setIdentity();
-  t1.linear() = q1.toRotationMatrix();
-
-  v0 << 50, 2, 1;//= ei_random_matrix<Vector3>().cwiseProduct(Vector3(10,2,0.5));
-  t0.scale(v0);
-  t1.prescale(v0);
-
-  VERIFY_IS_APPROX( (t0 * Vector3(1,0,0)).norm(), v0.x());
-  //VERIFY(!ei_isApprox((t1 * Vector3(1,0,0)).norm(), v0.x()));
-
-  t0.setIdentity();
-  t1.setIdentity();
-  v1 << 1, 2, 3;
-  t0.linear() = q1.toRotationMatrix();
-  t0.pretranslate(v0);
-  t0.scale(v1);
-  t1.linear() = q1.conjugate().toRotationMatrix();
-  t1.prescale(v1.cwise().inverse());
-  t1.translate(-v0);
-
-  VERIFY((t0.matrix() * t1.matrix()).isIdentity(test_precision<Scalar>()));
-
-  t1.fromPositionOrientationScale(v0, q1, v1);
-  VERIFY_IS_APPROX(t1.matrix(), t0.matrix());
-  VERIFY_IS_APPROX(t1*v1, t0*v1);
-
-  t0.setIdentity(); t0.scale(v0).rotate(q1.toRotationMatrix());
-  t1.setIdentity(); t1.scale(v0).rotate(q1);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  t0.setIdentity(); t0.scale(v0).rotate(AngleAxisx(q1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  VERIFY_IS_APPROX(t0.scale(a).matrix(), t1.scale(Vector3::Constant(a)).matrix());
-  VERIFY_IS_APPROX(t0.prescale(a).matrix(), t1.prescale(Vector3::Constant(a)).matrix());
-
-  // More transform constructors, operator=, operator*=
-
-  Matrix3 mat3 = Matrix3::Random();
-  Matrix4 mat4;
-  mat4 << mat3 , Vector3::Zero() , Vector4::Zero().transpose();
-  Transform3 tmat3(mat3), tmat4(mat4);
-  tmat4.matrix()(3,3) = Scalar(1);
-  VERIFY_IS_APPROX(tmat3.matrix(), tmat4.matrix());
-
-  Scalar a3 = ei_random<Scalar>(-Scalar(M_PI), Scalar(M_PI));
-  Vector3 v3 = Vector3::Random().normalized();
-  AngleAxisx aa3(a3, v3);
-  Transform3 t3(aa3);
-  Transform3 t4;
-  t4 = aa3;
-  VERIFY_IS_APPROX(t3.matrix(), t4.matrix());
-  t4.rotate(AngleAxisx(-a3,v3));
-  VERIFY_IS_APPROX(t4.matrix(), Matrix4::Identity());
-  t4 *= aa3;
-  VERIFY_IS_APPROX(t3.matrix(), t4.matrix());
-
-  v3 = Vector3::Random();
-  Translation3 tv3(v3);
-  Transform3 t5(tv3);
-  t4 = tv3;
-  VERIFY_IS_APPROX(t5.matrix(), t4.matrix());
-  t4.translate(-v3);
-  VERIFY_IS_APPROX(t4.matrix(), Matrix4::Identity());
-  t4 *= tv3;
-  VERIFY_IS_APPROX(t5.matrix(), t4.matrix());
-
-  Scaling3 sv3(v3);
-  Transform3 t6(sv3);
-  t4 = sv3;
-  VERIFY_IS_APPROX(t6.matrix(), t4.matrix());
-  t4.scale(v3.cwise().inverse());
-  VERIFY_IS_APPROX(t4.matrix(), Matrix4::Identity());
-  t4 *= sv3;
-  VERIFY_IS_APPROX(t6.matrix(), t4.matrix());
-
-  // matrix * transform
-  VERIFY_IS_APPROX(Transform3(t3.matrix()*t4).matrix(), Transform3(t3*t4).matrix());
-
-  // chained Transform product
-  VERIFY_IS_APPROX(((t3*t4)*t5).matrix(), (t3*(t4*t5)).matrix());
-
-  // check that Transform product doesn't have aliasing problems
-  t5 = t4;
-  t5 = t5*t5;
-  VERIFY_IS_APPROX(t5, t4*t4);
-
-  // 2D transformation
-  Transform2 t20, t21;
-  Vector2 v20 = Vector2::Random();
-  Vector2 v21 = Vector2::Random();
-  for (int k=0; k<2; ++k)
-    if (ei_abs(v21[k])<Scalar(1e-3)) v21[k] = Scalar(1e-3);
-  t21.setIdentity();
-  t21.linear() = Rotation2D<Scalar>(a).toRotationMatrix();
-  VERIFY_IS_APPROX(t20.fromPositionOrientationScale(v20,a,v21).matrix(),
-    t21.pretranslate(v20).scale(v21).matrix());
-
-  t21.setIdentity();
-  t21.linear() = Rotation2D<Scalar>(-a).toRotationMatrix();
-  VERIFY( (t20.fromPositionOrientationScale(v20,a,v21)
-        * (t21.prescale(v21.cwise().inverse()).translate(-v20))).matrix().isIdentity(test_precision<Scalar>()) );
-
-  // Transform - new API
-  // 3D
-  t0.setIdentity();
-  t0.rotate(q1).scale(v0).translate(v0);
-  // mat * scaling and mat * translation
-  t1 = (Matrix3(q1) * Scaling3(v0)) * Translation3(v0);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // mat * transformation and scaling * translation
-  t1 = Matrix3(q1) * (Scaling3(v0) * Translation3(v0));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  t0.setIdentity();
-  t0.prerotate(q1).prescale(v0).pretranslate(v0);
-  // translation * scaling and transformation * mat
-  t1 = (Translation3(v0) * Scaling3(v0)) * Matrix3(q1);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // scaling * mat and translation * mat
-  t1 = Translation3(v0) * (Scaling3(v0) * Matrix3(q1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  t0.setIdentity();
-  t0.scale(v0).translate(v0).rotate(q1);
-  // translation * mat and scaling * transformation
-  t1 = Scaling3(v0) * (Translation3(v0) * Matrix3(q1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // transformation * scaling
-  t0.scale(v0);
-  t1 = t1 * Scaling3(v0);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // transformation * translation
-  t0.translate(v0);
-  t1 = t1 * Translation3(v0);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // translation * transformation
-  t0.pretranslate(v0);
-  t1 = Translation3(v0) * t1;
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // transform * quaternion
-  t0.rotate(q1);
-  t1 = t1 * q1;
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // translation * quaternion
-  t0.translate(v1).rotate(q1);
-  t1 = t1 * (Translation3(v1) * q1);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // scaling * quaternion
-  t0.scale(v1).rotate(q1);
-  t1 = t1 * (Scaling3(v1) * q1);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // quaternion * transform
-  t0.prerotate(q1);
-  t1 = q1 * t1;
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // quaternion * translation
-  t0.rotate(q1).translate(v1);
-  t1 = t1 * (q1 * Translation3(v1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // quaternion * scaling
-  t0.rotate(q1).scale(v1);
-  t1 = t1 * (q1 * Scaling3(v1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // translation * vector
-  t0.setIdentity();
-  t0.translate(v0);
-  VERIFY_IS_APPROX(t0 * v1, Translation3(v0) * v1);
-
-  // scaling * vector
-  t0.setIdentity();
-  t0.scale(v0);
-  VERIFY_IS_APPROX(t0 * v1, Scaling3(v0) * v1);
-
-  // test transform inversion
-  t0.setIdentity();
-  t0.translate(v0);
-  t0.linear().setRandom();
-  VERIFY_IS_APPROX(t0.inverse(Affine), t0.matrix().inverse());
-  t0.setIdentity();
-  t0.translate(v0).rotate(q1);
-  VERIFY_IS_APPROX(t0.inverse(Isometry), t0.matrix().inverse());
-
-  // test extract rotation and scaling
-  t0.setIdentity();
-  t0.translate(v0).rotate(q1).scale(v1);
-  VERIFY_IS_APPROX(t0.rotation() * v1, Matrix3(q1) * v1);
-
-  Matrix3 mat_rotation, mat_scaling;
-  t0.setIdentity();
-  t0.translate(v0).rotate(q1).scale(v1);
-  t0.computeRotationScaling(&mat_rotation, &mat_scaling);
-  VERIFY_IS_APPROX(t0.linear(), mat_rotation * mat_scaling);
-  VERIFY_IS_APPROX(mat_rotation*mat_rotation.adjoint(), Matrix3::Identity());
-  VERIFY_IS_APPROX(mat_rotation.determinant(), Scalar(1));
-  t0.computeScalingRotation(&mat_scaling, &mat_rotation);
-  VERIFY_IS_APPROX(t0.linear(), mat_scaling * mat_rotation);
-  VERIFY_IS_APPROX(mat_rotation*mat_rotation.adjoint(), Matrix3::Identity());
-  VERIFY_IS_APPROX(mat_rotation.determinant(), Scalar(1));
-
-  // test casting
-  Transform<float,3> t1f = t1.template cast<float>();
-  VERIFY_IS_APPROX(t1f.template cast<Scalar>(),t1);
-  Transform<double,3> t1d = t1.template cast<double>();
-  VERIFY_IS_APPROX(t1d.template cast<Scalar>(),t1);
-
-  Translation3 tr1(v0);
-  Translation<float,3> tr1f = tr1.template cast<float>();
-  VERIFY_IS_APPROX(tr1f.template cast<Scalar>(),tr1);
-  Translation<double,3> tr1d = tr1.template cast<double>();
-  VERIFY_IS_APPROX(tr1d.template cast<Scalar>(),tr1);
-
-  Scaling3 sc1(v0);
-  Scaling<float,3> sc1f = sc1.template cast<float>();
-  VERIFY_IS_APPROX(sc1f.template cast<Scalar>(),sc1);
-  Scaling<double,3> sc1d = sc1.template cast<double>();
-  VERIFY_IS_APPROX(sc1d.template cast<Scalar>(),sc1);
-
-  Quaternion<float> q1f = q1.template cast<float>();
-  VERIFY_IS_APPROX(q1f.template cast<Scalar>(),q1);
-  Quaternion<double> q1d = q1.template cast<double>();
-  VERIFY_IS_APPROX(q1d.template cast<Scalar>(),q1);
-
-  AngleAxis<float> aa1f = aa1.template cast<float>();
-  VERIFY_IS_APPROX(aa1f.template cast<Scalar>(),aa1);
-  AngleAxis<double> aa1d = aa1.template cast<double>();
-  VERIFY_IS_APPROX(aa1d.template cast<Scalar>(),aa1);
-
-  Rotation2D<Scalar> r2d1(ei_random<Scalar>());
-  Rotation2D<float> r2d1f = r2d1.template cast<float>();
-  VERIFY_IS_APPROX(r2d1f.template cast<Scalar>(),r2d1);
-  Rotation2D<double> r2d1d = r2d1.template cast<double>();
-  VERIFY_IS_APPROX(r2d1d.template cast<Scalar>(),r2d1);
-
-  m = q1;
-//   m.col(1) = Vector3(0,ei_random<Scalar>(),ei_random<Scalar>()).normalized();
-//   m.col(0) = Vector3(-1,0,0).normalized();
-//   m.col(2) = m.col(0).cross(m.col(1));
-  #define VERIFY_EULER(I,J,K, X,Y,Z) { \
-    Vector3 ea = m.eulerAngles(I,J,K); \
-    Matrix3 m1 = Matrix3(AngleAxisx(ea[0], Vector3::Unit##X()) * AngleAxisx(ea[1], Vector3::Unit##Y()) * AngleAxisx(ea[2], Vector3::Unit##Z())); \
-    VERIFY_IS_APPROX(m,  Matrix3(AngleAxisx(ea[0], Vector3::Unit##X()) * AngleAxisx(ea[1], Vector3::Unit##Y()) * AngleAxisx(ea[2], Vector3::Unit##Z()))); \
-  }
-  VERIFY_EULER(0,1,2, X,Y,Z);
-  VERIFY_EULER(0,1,0, X,Y,X);
-  VERIFY_EULER(0,2,1, X,Z,Y);
-  VERIFY_EULER(0,2,0, X,Z,X);
-
-  VERIFY_EULER(1,2,0, Y,Z,X);
-  VERIFY_EULER(1,2,1, Y,Z,Y);
-  VERIFY_EULER(1,0,2, Y,X,Z);
-  VERIFY_EULER(1,0,1, Y,X,Y);
-
-  VERIFY_EULER(2,0,1, Z,X,Y);
-  VERIFY_EULER(2,0,2, Z,X,Z);
-  VERIFY_EULER(2,1,0, Z,Y,X);
-  VERIFY_EULER(2,1,2, Z,Y,Z);
-
-  // colwise/rowwise cross product
-  mat3.setRandom();
-  Vector3 vec3 = Vector3::Random();
-  Matrix3 mcross;
-  int i = ei_random<int>(0,2);
-  mcross = mat3.colwise().cross(vec3);
-  VERIFY_IS_APPROX(mcross.col(i), mat3.col(i).cross(vec3));
-  mcross = mat3.rowwise().cross(vec3);
-  VERIFY_IS_APPROX(mcross.row(i), mat3.row(i).cross(vec3));
-
-
-}
-
-void test_eigen2_geometry()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( geometry<float>() );
-    CALL_SUBTEST_2( geometry<double>() );
-  }
-}
diff --git a/test/eigen2/eigen2_geometry_with_eigen2_prefix.cpp b/test/eigen2/eigen2_geometry_with_eigen2_prefix.cpp
deleted file mode 100644
index f83b57249..000000000
--- a/test/eigen2/eigen2_geometry_with_eigen2_prefix.cpp
+++ /dev/null
@@ -1,434 +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/.
-
-#define EIGEN2_SUPPORT_STAGE15_RESOLVE_API_CONFLICTS_WARN
-
-#include "main.h"
-#include <Eigen/Geometry>
-#include <Eigen/LU>
-#include <Eigen/SVD>
-
-template<typename Scalar> void geometry(void)
-{
-  /* this test covers the following files:
-     Cross.h Quaternion.h, Transform.cpp
-  */
-
-  typedef Matrix<Scalar,2,2> Matrix2;
-  typedef Matrix<Scalar,3,3> Matrix3;
-  typedef Matrix<Scalar,4,4> Matrix4;
-  typedef Matrix<Scalar,2,1> Vector2;
-  typedef Matrix<Scalar,3,1> Vector3;
-  typedef Matrix<Scalar,4,1> Vector4;
-  typedef eigen2_Quaternion<Scalar> Quaternionx;
-  typedef eigen2_AngleAxis<Scalar> AngleAxisx;
-  typedef eigen2_Transform<Scalar,2> Transform2;
-  typedef eigen2_Transform<Scalar,3> Transform3;
-  typedef eigen2_Scaling<Scalar,2> Scaling2;
-  typedef eigen2_Scaling<Scalar,3> Scaling3;
-  typedef eigen2_Translation<Scalar,2> Translation2;
-  typedef eigen2_Translation<Scalar,3> Translation3;
-
-  Scalar largeEps = test_precision<Scalar>();
-  if (ei_is_same_type<Scalar,float>::ret)
-    largeEps = 1e-2f;
-
-  Vector3 v0 = Vector3::Random(),
-    v1 = Vector3::Random(),
-    v2 = Vector3::Random();
-  Vector2 u0 = Vector2::Random();
-  Matrix3 matrot1;
-
-  Scalar a = ei_random<Scalar>(-Scalar(M_PI), Scalar(M_PI));
-
-  // cross product
-  VERIFY_IS_MUCH_SMALLER_THAN(v1.cross(v2).eigen2_dot(v1), Scalar(1));
-  Matrix3 m;
-  m << v0.normalized(),
-      (v0.cross(v1)).normalized(),
-      (v0.cross(v1).cross(v0)).normalized();
-  VERIFY(m.isUnitary());
-
-  // Quaternion: Identity(), setIdentity();
-  Quaternionx q1, q2;
-  q2.setIdentity();
-  VERIFY_IS_APPROX(Quaternionx(Quaternionx::Identity()).coeffs(), q2.coeffs());
-  q1.coeffs().setRandom();
-  VERIFY_IS_APPROX(q1.coeffs(), (q1*q2).coeffs());
-
-  // unitOrthogonal
-  VERIFY_IS_MUCH_SMALLER_THAN(u0.unitOrthogonal().eigen2_dot(u0), Scalar(1));
-  VERIFY_IS_MUCH_SMALLER_THAN(v0.unitOrthogonal().eigen2_dot(v0), Scalar(1));
-  VERIFY_IS_APPROX(u0.unitOrthogonal().norm(), Scalar(1));
-  VERIFY_IS_APPROX(v0.unitOrthogonal().norm(), Scalar(1));
-
-
-  VERIFY_IS_APPROX(v0, AngleAxisx(a, v0.normalized()) * v0);
-  VERIFY_IS_APPROX(-v0, AngleAxisx(Scalar(M_PI), v0.unitOrthogonal()) * v0);
-  VERIFY_IS_APPROX(ei_cos(a)*v0.squaredNorm(), v0.eigen2_dot(AngleAxisx(a, v0.unitOrthogonal()) * v0));
-  m = AngleAxisx(a, v0.normalized()).toRotationMatrix().adjoint();
-  VERIFY_IS_APPROX(Matrix3::Identity(), m * AngleAxisx(a, v0.normalized()));
-  VERIFY_IS_APPROX(Matrix3::Identity(), AngleAxisx(a, v0.normalized()) * m);
-
-  q1 = AngleAxisx(a, v0.normalized());
-  q2 = AngleAxisx(a, v1.normalized());
-
-  // angular distance
-  Scalar refangle = ei_abs(AngleAxisx(q1.inverse()*q2).angle());
-  if (refangle>Scalar(M_PI))
-    refangle = Scalar(2)*Scalar(M_PI) - refangle;
-  
-  if((q1.coeffs()-q2.coeffs()).norm() > 10*largeEps)
-  {
-    VERIFY(ei_isApprox(q1.angularDistance(q2), refangle, largeEps));
-  }
-
-  // rotation matrix conversion
-  VERIFY_IS_APPROX(q1 * v2, q1.toRotationMatrix() * v2);
-  VERIFY_IS_APPROX(q1 * q2 * v2,
-    q1.toRotationMatrix() * q2.toRotationMatrix() * v2);
-
-  VERIFY( (q2*q1).isApprox(q1*q2, largeEps) || !(q2 * q1 * v2).isApprox(
-    q1.toRotationMatrix() * q2.toRotationMatrix() * v2));
-
-  q2 = q1.toRotationMatrix();
-  VERIFY_IS_APPROX(q1*v1,q2*v1);
-
-  matrot1 = AngleAxisx(Scalar(0.1), Vector3::UnitX())
-          * AngleAxisx(Scalar(0.2), Vector3::UnitY())
-          * AngleAxisx(Scalar(0.3), Vector3::UnitZ());
-  VERIFY_IS_APPROX(matrot1 * v1,
-       AngleAxisx(Scalar(0.1), Vector3(1,0,0)).toRotationMatrix()
-    * (AngleAxisx(Scalar(0.2), Vector3(0,1,0)).toRotationMatrix()
-    * (AngleAxisx(Scalar(0.3), Vector3(0,0,1)).toRotationMatrix() * v1)));
-
-  // angle-axis conversion
-  AngleAxisx aa = q1;
-  VERIFY_IS_APPROX(q1 * v1, Quaternionx(aa) * v1);
-  VERIFY_IS_NOT_APPROX(q1 * v1, Quaternionx(AngleAxisx(aa.angle()*2,aa.axis())) * v1);
-
-  // from two vector creation
-  VERIFY_IS_APPROX(v2.normalized(),(q2.setFromTwoVectors(v1,v2)*v1).normalized());
-  VERIFY_IS_APPROX(v2.normalized(),(q2.setFromTwoVectors(v1,v2)*v1).normalized());
-
-  // inverse and conjugate
-  VERIFY_IS_APPROX(q1 * (q1.inverse() * v1), v1);
-  VERIFY_IS_APPROX(q1 * (q1.conjugate() * v1), v1);
-
-  // AngleAxis
-  VERIFY_IS_APPROX(AngleAxisx(a,v1.normalized()).toRotationMatrix(),
-    Quaternionx(AngleAxisx(a,v1.normalized())).toRotationMatrix());
-
-  AngleAxisx aa1;
-  m = q1.toRotationMatrix();
-  aa1 = m;
-  VERIFY_IS_APPROX(AngleAxisx(m).toRotationMatrix(),
-    Quaternionx(m).toRotationMatrix());
-
-  // Transform
-  // TODO complete the tests !
-  a = 0;
-  while (ei_abs(a)<Scalar(0.1))
-    a = ei_random<Scalar>(-Scalar(0.4)*Scalar(M_PI), Scalar(0.4)*Scalar(M_PI));
-  q1 = AngleAxisx(a, v0.normalized());
-  Transform3 t0, t1, t2;
-  // first test setIdentity() and Identity()
-  t0.setIdentity();
-  VERIFY_IS_APPROX(t0.matrix(), Transform3::MatrixType::Identity());
-  t0.matrix().setZero();
-  t0 = Transform3::Identity();
-  VERIFY_IS_APPROX(t0.matrix(), Transform3::MatrixType::Identity());
-
-  t0.linear() = q1.toRotationMatrix();
-  t1.setIdentity();
-  t1.linear() = q1.toRotationMatrix();
-
-  v0 << 50, 2, 1;//= ei_random_matrix<Vector3>().cwiseProduct(Vector3(10,2,0.5));
-  t0.scale(v0);
-  t1.prescale(v0);
-
-  VERIFY_IS_APPROX( (t0 * Vector3(1,0,0)).norm(), v0.x());
-  //VERIFY(!ei_isApprox((t1 * Vector3(1,0,0)).norm(), v0.x()));
-
-  t0.setIdentity();
-  t1.setIdentity();
-  v1 << 1, 2, 3;
-  t0.linear() = q1.toRotationMatrix();
-  t0.pretranslate(v0);
-  t0.scale(v1);
-  t1.linear() = q1.conjugate().toRotationMatrix();
-  t1.prescale(v1.cwise().inverse());
-  t1.translate(-v0);
-
-  VERIFY((t0.matrix() * t1.matrix()).isIdentity(test_precision<Scalar>()));
-
-  t1.fromPositionOrientationScale(v0, q1, v1);
-  VERIFY_IS_APPROX(t1.matrix(), t0.matrix());
-  VERIFY_IS_APPROX(t1*v1, t0*v1);
-
-  t0.setIdentity(); t0.scale(v0).rotate(q1.toRotationMatrix());
-  t1.setIdentity(); t1.scale(v0).rotate(q1);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  t0.setIdentity(); t0.scale(v0).rotate(AngleAxisx(q1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  VERIFY_IS_APPROX(t0.scale(a).matrix(), t1.scale(Vector3::Constant(a)).matrix());
-  VERIFY_IS_APPROX(t0.prescale(a).matrix(), t1.prescale(Vector3::Constant(a)).matrix());
-
-  // More transform constructors, operator=, operator*=
-
-  Matrix3 mat3 = Matrix3::Random();
-  Matrix4 mat4;
-  mat4 << mat3 , Vector3::Zero() , Vector4::Zero().transpose();
-  Transform3 tmat3(mat3), tmat4(mat4);
-  tmat4.matrix()(3,3) = Scalar(1);
-  VERIFY_IS_APPROX(tmat3.matrix(), tmat4.matrix());
-
-  Scalar a3 = ei_random<Scalar>(-Scalar(M_PI), Scalar(M_PI));
-  Vector3 v3 = Vector3::Random().normalized();
-  AngleAxisx aa3(a3, v3);
-  Transform3 t3(aa3);
-  Transform3 t4;
-  t4 = aa3;
-  VERIFY_IS_APPROX(t3.matrix(), t4.matrix());
-  t4.rotate(AngleAxisx(-a3,v3));
-  VERIFY_IS_APPROX(t4.matrix(), Matrix4::Identity());
-  t4 *= aa3;
-  VERIFY_IS_APPROX(t3.matrix(), t4.matrix());
-
-  v3 = Vector3::Random();
-  Translation3 tv3(v3);
-  Transform3 t5(tv3);
-  t4 = tv3;
-  VERIFY_IS_APPROX(t5.matrix(), t4.matrix());
-  t4.translate(-v3);
-  VERIFY_IS_APPROX(t4.matrix(), Matrix4::Identity());
-  t4 *= tv3;
-  VERIFY_IS_APPROX(t5.matrix(), t4.matrix());
-
-  Scaling3 sv3(v3);
-  Transform3 t6(sv3);
-  t4 = sv3;
-  VERIFY_IS_APPROX(t6.matrix(), t4.matrix());
-  t4.scale(v3.cwise().inverse());
-  VERIFY_IS_APPROX(t4.matrix(), Matrix4::Identity());
-  t4 *= sv3;
-  VERIFY_IS_APPROX(t6.matrix(), t4.matrix());
-
-  // matrix * transform
-  VERIFY_IS_APPROX(Transform3(t3.matrix()*t4).matrix(), Transform3(t3*t4).matrix());
-
-  // chained Transform product
-  VERIFY_IS_APPROX(((t3*t4)*t5).matrix(), (t3*(t4*t5)).matrix());
-
-  // check that Transform product doesn't have aliasing problems
-  t5 = t4;
-  t5 = t5*t5;
-  VERIFY_IS_APPROX(t5, t4*t4);
-
-  // 2D transformation
-  Transform2 t20, t21;
-  Vector2 v20 = Vector2::Random();
-  Vector2 v21 = Vector2::Random();
-  for (int k=0; k<2; ++k)
-    if (ei_abs(v21[k])<Scalar(1e-3)) v21[k] = Scalar(1e-3);
-  t21.setIdentity();
-  t21.linear() = Rotation2D<Scalar>(a).toRotationMatrix();
-  VERIFY_IS_APPROX(t20.fromPositionOrientationScale(v20,a,v21).matrix(),
-    t21.pretranslate(v20).scale(v21).matrix());
-
-  t21.setIdentity();
-  t21.linear() = Rotation2D<Scalar>(-a).toRotationMatrix();
-  VERIFY( (t20.fromPositionOrientationScale(v20,a,v21)
-        * (t21.prescale(v21.cwise().inverse()).translate(-v20))).matrix().isIdentity(test_precision<Scalar>()) );
-
-  // Transform - new API
-  // 3D
-  t0.setIdentity();
-  t0.rotate(q1).scale(v0).translate(v0);
-  // mat * scaling and mat * translation
-  t1 = (Matrix3(q1) * Scaling3(v0)) * Translation3(v0);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // mat * transformation and scaling * translation
-  t1 = Matrix3(q1) * (Scaling3(v0) * Translation3(v0));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  t0.setIdentity();
-  t0.prerotate(q1).prescale(v0).pretranslate(v0);
-  // translation * scaling and transformation * mat
-  t1 = (Translation3(v0) * Scaling3(v0)) * Matrix3(q1);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // scaling * mat and translation * mat
-  t1 = Translation3(v0) * (Scaling3(v0) * Matrix3(q1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  t0.setIdentity();
-  t0.scale(v0).translate(v0).rotate(q1);
-  // translation * mat and scaling * transformation
-  t1 = Scaling3(v0) * (Translation3(v0) * Matrix3(q1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // transformation * scaling
-  t0.scale(v0);
-  t1 = t1 * Scaling3(v0);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // transformation * translation
-  t0.translate(v0);
-  t1 = t1 * Translation3(v0);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-  // translation * transformation
-  t0.pretranslate(v0);
-  t1 = Translation3(v0) * t1;
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // transform * quaternion
-  t0.rotate(q1);
-  t1 = t1 * q1;
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // translation * quaternion
-  t0.translate(v1).rotate(q1);
-  t1 = t1 * (Translation3(v1) * q1);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // scaling * quaternion
-  t0.scale(v1).rotate(q1);
-  t1 = t1 * (Scaling3(v1) * q1);
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // quaternion * transform
-  t0.prerotate(q1);
-  t1 = q1 * t1;
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // quaternion * translation
-  t0.rotate(q1).translate(v1);
-  t1 = t1 * (q1 * Translation3(v1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // quaternion * scaling
-  t0.rotate(q1).scale(v1);
-  t1 = t1 * (q1 * Scaling3(v1));
-  VERIFY_IS_APPROX(t0.matrix(), t1.matrix());
-
-  // translation * vector
-  t0.setIdentity();
-  t0.translate(v0);
-  VERIFY_IS_APPROX(t0 * v1, Translation3(v0) * v1);
-
-  // scaling * vector
-  t0.setIdentity();
-  t0.scale(v0);
-  VERIFY_IS_APPROX(t0 * v1, Scaling3(v0) * v1);
-
-  // test transform inversion
-  t0.setIdentity();
-  t0.translate(v0);
-  t0.linear().setRandom();
-  VERIFY_IS_APPROX(t0.inverse(Affine), t0.matrix().inverse());
-  t0.setIdentity();
-  t0.translate(v0).rotate(q1);
-  VERIFY_IS_APPROX(t0.inverse(Isometry), t0.matrix().inverse());
-
-  // test extract rotation and scaling
-  t0.setIdentity();
-  t0.translate(v0).rotate(q1).scale(v1);
-  VERIFY_IS_APPROX(t0.rotation() * v1, Matrix3(q1) * v1);
-
-  Matrix3 mat_rotation, mat_scaling;
-  t0.setIdentity();
-  t0.translate(v0).rotate(q1).scale(v1);
-  t0.computeRotationScaling(&mat_rotation, &mat_scaling);
-  VERIFY_IS_APPROX(t0.linear(), mat_rotation * mat_scaling);
-  VERIFY_IS_APPROX(mat_rotation*mat_rotation.adjoint(), Matrix3::Identity());
-  VERIFY_IS_APPROX(mat_rotation.determinant(), Scalar(1));
-  t0.computeScalingRotation(&mat_scaling, &mat_rotation);
-  VERIFY_IS_APPROX(t0.linear(), mat_scaling * mat_rotation);
-  VERIFY_IS_APPROX(mat_rotation*mat_rotation.adjoint(), Matrix3::Identity());
-  VERIFY_IS_APPROX(mat_rotation.determinant(), Scalar(1));
-
-  // test casting
-  eigen2_Transform<float,3> t1f = t1.template cast<float>();
-  VERIFY_IS_APPROX(t1f.template cast<Scalar>(),t1);
-  eigen2_Transform<double,3> t1d = t1.template cast<double>();
-  VERIFY_IS_APPROX(t1d.template cast<Scalar>(),t1);
-
-  Translation3 tr1(v0);
-  eigen2_Translation<float,3> tr1f = tr1.template cast<float>();
-  VERIFY_IS_APPROX(tr1f.template cast<Scalar>(),tr1);
-  eigen2_Translation<double,3> tr1d = tr1.template cast<double>();
-  VERIFY_IS_APPROX(tr1d.template cast<Scalar>(),tr1);
-
-  Scaling3 sc1(v0);
-  eigen2_Scaling<float,3> sc1f = sc1.template cast<float>();
-  VERIFY_IS_APPROX(sc1f.template cast<Scalar>(),sc1);
-  eigen2_Scaling<double,3> sc1d = sc1.template cast<double>();
-  VERIFY_IS_APPROX(sc1d.template cast<Scalar>(),sc1);
-
-  eigen2_Quaternion<float> q1f = q1.template cast<float>();
-  VERIFY_IS_APPROX(q1f.template cast<Scalar>(),q1);
-  eigen2_Quaternion<double> q1d = q1.template cast<double>();
-  VERIFY_IS_APPROX(q1d.template cast<Scalar>(),q1);
-
-  eigen2_AngleAxis<float> aa1f = aa1.template cast<float>();
-  VERIFY_IS_APPROX(aa1f.template cast<Scalar>(),aa1);
-  eigen2_AngleAxis<double> aa1d = aa1.template cast<double>();
-  VERIFY_IS_APPROX(aa1d.template cast<Scalar>(),aa1);
-
-  eigen2_Rotation2D<Scalar> r2d1(ei_random<Scalar>());
-  eigen2_Rotation2D<float> r2d1f = r2d1.template cast<float>();
-  VERIFY_IS_APPROX(r2d1f.template cast<Scalar>(),r2d1);
-  eigen2_Rotation2D<double> r2d1d = r2d1.template cast<double>();
-  VERIFY_IS_APPROX(r2d1d.template cast<Scalar>(),r2d1);
-
-  m = q1;
-//   m.col(1) = Vector3(0,ei_random<Scalar>(),ei_random<Scalar>()).normalized();
-//   m.col(0) = Vector3(-1,0,0).normalized();
-//   m.col(2) = m.col(0).cross(m.col(1));
-  #define VERIFY_EULER(I,J,K, X,Y,Z) { \
-    Vector3 ea = m.eulerAngles(I,J,K); \
-    Matrix3 m1 = Matrix3(AngleAxisx(ea[0], Vector3::Unit##X()) * AngleAxisx(ea[1], Vector3::Unit##Y()) * AngleAxisx(ea[2], Vector3::Unit##Z())); \
-    VERIFY_IS_APPROX(m,  Matrix3(AngleAxisx(ea[0], Vector3::Unit##X()) * AngleAxisx(ea[1], Vector3::Unit##Y()) * AngleAxisx(ea[2], Vector3::Unit##Z()))); \
-  }
-  VERIFY_EULER(0,1,2, X,Y,Z);
-  VERIFY_EULER(0,1,0, X,Y,X);
-  VERIFY_EULER(0,2,1, X,Z,Y);
-  VERIFY_EULER(0,2,0, X,Z,X);
-
-  VERIFY_EULER(1,2,0, Y,Z,X);
-  VERIFY_EULER(1,2,1, Y,Z,Y);
-  VERIFY_EULER(1,0,2, Y,X,Z);
-  VERIFY_EULER(1,0,1, Y,X,Y);
-
-  VERIFY_EULER(2,0,1, Z,X,Y);
-  VERIFY_EULER(2,0,2, Z,X,Z);
-  VERIFY_EULER(2,1,0, Z,Y,X);
-  VERIFY_EULER(2,1,2, Z,Y,Z);
-
-  // colwise/rowwise cross product
-  mat3.setRandom();
-  Vector3 vec3 = Vector3::Random();
-  Matrix3 mcross;
-  int i = ei_random<int>(0,2);
-  mcross = mat3.colwise().cross(vec3);
-  VERIFY_IS_APPROX(mcross.col(i), mat3.col(i).cross(vec3));
-  mcross = mat3.rowwise().cross(vec3);
-  VERIFY_IS_APPROX(mcross.row(i), mat3.row(i).cross(vec3));
-
-
-}
-
-void test_eigen2_geometry_with_eigen2_prefix()
-{
-  std::cout << "eigen2 support: " << EIGEN2_SUPPORT_STAGE << std::endl;
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( geometry<float>() );
-    CALL_SUBTEST_2( geometry<double>() );
-  }
-}
diff --git a/test/eigen2/eigen2_hyperplane.cpp b/test/eigen2/eigen2_hyperplane.cpp
deleted file mode 100644
index f3f85e14d..000000000
--- a/test/eigen2/eigen2_hyperplane.cpp
+++ /dev/null
@@ -1,126 +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>
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@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 "main.h"
-#include <Eigen/Geometry>
-#include <Eigen/LU>
-#include <Eigen/QR>
-
-template<typename HyperplaneType> void hyperplane(const HyperplaneType& _plane)
-{
-  /* this test covers the following files:
-     Hyperplane.h
-  */
-
-  const int dim = _plane.dim();
-  typedef typename HyperplaneType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, HyperplaneType::AmbientDimAtCompileTime, 1> VectorType;
-  typedef Matrix<Scalar, HyperplaneType::AmbientDimAtCompileTime,
-                         HyperplaneType::AmbientDimAtCompileTime> MatrixType;
-
-  VectorType p0 = VectorType::Random(dim);
-  VectorType p1 = VectorType::Random(dim);
-
-  VectorType n0 = VectorType::Random(dim).normalized();
-  VectorType n1 = VectorType::Random(dim).normalized();
-
-  HyperplaneType pl0(n0, p0);
-  HyperplaneType pl1(n1, p1);
-  HyperplaneType pl2 = pl1;
-
-  Scalar s0 = ei_random<Scalar>();
-  Scalar s1 = ei_random<Scalar>();
-
-  VERIFY_IS_APPROX( n1.eigen2_dot(n1), Scalar(1) );
-
-  VERIFY_IS_MUCH_SMALLER_THAN( pl0.absDistance(p0), Scalar(1) );
-  VERIFY_IS_APPROX( pl1.signedDistance(p1 + n1 * s0), s0 );
-  VERIFY_IS_MUCH_SMALLER_THAN( pl1.signedDistance(pl1.projection(p0)), Scalar(1) );
-  VERIFY_IS_MUCH_SMALLER_THAN( pl1.absDistance(p1 +  pl1.normal().unitOrthogonal() * s1), Scalar(1) );
-
-  // transform
-  if (!NumTraits<Scalar>::IsComplex)
-  {
-    MatrixType rot = MatrixType::Random(dim,dim).qr().matrixQ();
-    Scaling<Scalar,HyperplaneType::AmbientDimAtCompileTime> scaling(VectorType::Random());
-    Translation<Scalar,HyperplaneType::AmbientDimAtCompileTime> translation(VectorType::Random());
-
-    pl2 = pl1;
-    VERIFY_IS_MUCH_SMALLER_THAN( pl2.transform(rot).absDistance(rot * p1), Scalar(1) );
-    pl2 = pl1;
-    VERIFY_IS_MUCH_SMALLER_THAN( pl2.transform(rot,Isometry).absDistance(rot * p1), Scalar(1) );
-    pl2 = pl1;
-    VERIFY_IS_MUCH_SMALLER_THAN( pl2.transform(rot*scaling).absDistance((rot*scaling) * p1), Scalar(1) );
-    pl2 = pl1;
-    VERIFY_IS_MUCH_SMALLER_THAN( pl2.transform(rot*scaling*translation)
-                                 .absDistance((rot*scaling*translation) * p1), Scalar(1) );
-    pl2 = pl1;
-    VERIFY_IS_MUCH_SMALLER_THAN( pl2.transform(rot*translation,Isometry)
-                                 .absDistance((rot*translation) * p1), Scalar(1) );
-  }
-
-  // casting
-  const int Dim = HyperplaneType::AmbientDimAtCompileTime;
-  typedef typename GetDifferentType<Scalar>::type OtherScalar;
-  Hyperplane<OtherScalar,Dim> hp1f = pl1.template cast<OtherScalar>();
-  VERIFY_IS_APPROX(hp1f.template cast<Scalar>(),pl1);
-  Hyperplane<Scalar,Dim> hp1d = pl1.template cast<Scalar>();
-  VERIFY_IS_APPROX(hp1d.template cast<Scalar>(),pl1);
-}
-
-template<typename Scalar> void lines()
-{
-  typedef Hyperplane<Scalar, 2> HLine;
-  typedef ParametrizedLine<Scalar, 2> PLine;
-  typedef Matrix<Scalar,2,1> Vector;
-  typedef Matrix<Scalar,3,1> CoeffsType;
-
-  for(int i = 0; i < 10; i++)
-  {
-    Vector center = Vector::Random();
-    Vector u = Vector::Random();
-    Vector v = Vector::Random();
-    Scalar a = ei_random<Scalar>();
-    while (ei_abs(a-1) < 1e-4) a = ei_random<Scalar>();
-    while (u.norm() < 1e-4) u = Vector::Random();
-    while (v.norm() < 1e-4) v = Vector::Random();
-
-    HLine line_u = HLine::Through(center + u, center + a*u);
-    HLine line_v = HLine::Through(center + v, center + a*v);
-
-    // the line equations should be normalized so that a^2+b^2=1
-    VERIFY_IS_APPROX(line_u.normal().norm(), Scalar(1));
-    VERIFY_IS_APPROX(line_v.normal().norm(), Scalar(1));
-
-    Vector result = line_u.intersection(line_v);
-
-    // the lines should intersect at the point we called "center"
-    VERIFY_IS_APPROX(result, center);
-
-    // check conversions between two types of lines
-    PLine pl(line_u); // gcc 3.3 will commit suicide if we don't name this variable
-    CoeffsType converted_coeffs(HLine(pl).coeffs());
-    converted_coeffs *= line_u.coeffs()(0)/converted_coeffs(0);
-    VERIFY(line_u.coeffs().isApprox(converted_coeffs));
-  }
-}
-
-void test_eigen2_hyperplane()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( hyperplane(Hyperplane<float,2>()) );
-    CALL_SUBTEST_2( hyperplane(Hyperplane<float,3>()) );
-    CALL_SUBTEST_3( hyperplane(Hyperplane<double,4>()) );
-    CALL_SUBTEST_4( hyperplane(Hyperplane<std::complex<double>,5>()) );
-    CALL_SUBTEST_5( lines<float>() );
-    CALL_SUBTEST_6( lines<double>() );
-  }
-}
diff --git a/test/eigen2/eigen2_inverse.cpp b/test/eigen2/eigen2_inverse.cpp
deleted file mode 100644
index 5de1dfefa..000000000
--- a/test/eigen2/eigen2_inverse.cpp
+++ /dev/null
@@ -1,63 +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>
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@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 "main.h"
-#include <Eigen/LU>
-
-template<typename MatrixType> void inverse(const MatrixType& m)
-{
-  /* this test covers the following files:
-     Inverse.h
-  */
-  int rows = m.rows();
-  int cols = m.cols();
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> VectorType;
-
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2(rows, cols),
-             mzero = MatrixType::Zero(rows, cols),
-             identity = MatrixType::Identity(rows, rows);
-
-  while(ei_abs(m1.determinant()) < RealScalar(0.1) && rows <= 8)
-  {
-    m1 = MatrixType::Random(rows, cols);
-  }
-
-  m2 = m1.inverse();
-  VERIFY_IS_APPROX(m1, m2.inverse() );
-
-  m1.computeInverse(&m2);
-  VERIFY_IS_APPROX(m1, m2.inverse() );
-
-  VERIFY_IS_APPROX((Scalar(2)*m2).inverse(), m2.inverse()*Scalar(0.5));
-
-  VERIFY_IS_APPROX(identity, m1.inverse() * m1 );
-  VERIFY_IS_APPROX(identity, m1 * m1.inverse() );
-
-  VERIFY_IS_APPROX(m1, m1.inverse().inverse() );
-
-  // since for the general case we implement separately row-major and col-major, test that
-  VERIFY_IS_APPROX(m1.transpose().inverse(), m1.inverse().transpose());
-}
-
-void test_eigen2_inverse()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( inverse(Matrix<double,1,1>()) );
-    CALL_SUBTEST_2( inverse(Matrix2d()) );
-    CALL_SUBTEST_3( inverse(Matrix3f()) );
-    CALL_SUBTEST_4( inverse(Matrix4f()) );
-    CALL_SUBTEST_5( inverse(MatrixXf(8,8)) );
-    CALL_SUBTEST_6( inverse(MatrixXcd(7,7)) );
-  }
-}
diff --git a/test/eigen2/eigen2_linearstructure.cpp b/test/eigen2/eigen2_linearstructure.cpp
deleted file mode 100644
index 22f02c396..000000000
--- a/test/eigen2/eigen2_linearstructure.cpp
+++ /dev/null
@@ -1,84 +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) 2006-2008 Benoit Jacob <jacob.benoit.1@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 "main.h"
-
-template<typename MatrixType> void linearStructure(const MatrixType& m)
-{
-  /* this test covers the following files:
-     Sum.h Difference.h Opposite.h ScalarMultiple.h
-  */
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-
-  int rows = m.rows();
-  int cols = m.cols();
-
-  // this test relies a lot on Random.h, and there's not much more that we can do
-  // to test it, hence I consider that we will have tested Random.h
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols),
-             mzero = MatrixType::Zero(rows, cols);
-
-  Scalar s1 = ei_random<Scalar>();
-  while (ei_abs(s1)<1e-3) s1 = ei_random<Scalar>();
-
-  int r = ei_random<int>(0, rows-1),
-      c = ei_random<int>(0, cols-1);
-
-  VERIFY_IS_APPROX(-(-m1),                  m1);
-  VERIFY_IS_APPROX(m1+m1,                   2*m1);
-  VERIFY_IS_APPROX(m1+m2-m1,                m2);
-  VERIFY_IS_APPROX(-m2+m1+m2,               m1);
-  VERIFY_IS_APPROX(m1*s1,                   s1*m1);
-  VERIFY_IS_APPROX((m1+m2)*s1,              s1*m1+s1*m2);
-  VERIFY_IS_APPROX((-m1+m2)*s1,             -s1*m1+s1*m2);
-  m3 = m2; m3 += m1;
-  VERIFY_IS_APPROX(m3,                      m1+m2);
-  m3 = m2; m3 -= m1;
-  VERIFY_IS_APPROX(m3,                      m2-m1);
-  m3 = m2; m3 *= s1;
-  VERIFY_IS_APPROX(m3,                      s1*m2);
-  if(NumTraits<Scalar>::HasFloatingPoint)
-  {
-    m3 = m2; m3 /= s1;
-    VERIFY_IS_APPROX(m3,                    m2/s1);
-  }
-
-  // again, test operator() to check const-qualification
-  VERIFY_IS_APPROX((-m1)(r,c), -(m1(r,c)));
-  VERIFY_IS_APPROX((m1-m2)(r,c), (m1(r,c))-(m2(r,c)));
-  VERIFY_IS_APPROX((m1+m2)(r,c), (m1(r,c))+(m2(r,c)));
-  VERIFY_IS_APPROX((s1*m1)(r,c), s1*(m1(r,c)));
-  VERIFY_IS_APPROX((m1*s1)(r,c), (m1(r,c))*s1);
-  if(NumTraits<Scalar>::HasFloatingPoint)
-    VERIFY_IS_APPROX((m1/s1)(r,c), (m1(r,c))/s1);
-
-  // use .block to disable vectorization and compare to the vectorized version
-  VERIFY_IS_APPROX(m1+m1.block(0,0,rows,cols), m1+m1);
-  VERIFY_IS_APPROX(m1.cwise() * m1.block(0,0,rows,cols), m1.cwise() * m1);
-  VERIFY_IS_APPROX(m1 - m1.block(0,0,rows,cols), m1 - m1);
-  VERIFY_IS_APPROX(m1.block(0,0,rows,cols) * s1, m1 * s1);
-}
-
-void test_eigen2_linearstructure()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( linearStructure(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( linearStructure(Matrix2f()) );
-    CALL_SUBTEST_3( linearStructure(Vector3d()) );
-    CALL_SUBTEST_4( linearStructure(Matrix4d()) );
-    CALL_SUBTEST_5( linearStructure(MatrixXcf(3, 3)) );
-    CALL_SUBTEST_6( linearStructure(MatrixXf(8, 12)) );
-    CALL_SUBTEST_7( linearStructure(MatrixXi(8, 12)) );
-    CALL_SUBTEST_8( linearStructure(MatrixXcd(20, 20)) );
-  }
-}
diff --git a/test/eigen2/eigen2_lu.cpp b/test/eigen2/eigen2_lu.cpp
deleted file mode 100644
index e993b1c7c..000000000
--- a/test/eigen2/eigen2_lu.cpp
+++ /dev/null
@@ -1,122 +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 Benoit Jacob <jacob.benoit.1@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 "main.h"
-#include <Eigen/LU>
-
-template<typename Derived>
-void doSomeRankPreservingOperations(Eigen::MatrixBase<Derived>& m)
-{
-  typedef typename Derived::RealScalar RealScalar;
-  for(int a = 0; a < 3*(m.rows()+m.cols()); a++)
-  {
-    RealScalar d = Eigen::ei_random<RealScalar>(-1,1);
-    int i = Eigen::ei_random<int>(0,m.rows()-1); // i is a random row number
-    int j;
-    do {
-      j = Eigen::ei_random<int>(0,m.rows()-1);
-    } while (i==j); // j is another one (must be different)
-    m.row(i) += d * m.row(j);
-
-    i = Eigen::ei_random<int>(0,m.cols()-1); // i is a random column number
-    do {
-      j = Eigen::ei_random<int>(0,m.cols()-1);
-    } while (i==j); // j is another one (must be different)
-    m.col(i) += d * m.col(j);
-  }
-}
-
-template<typename MatrixType> void lu_non_invertible()
-{
-  /* this test covers the following files:
-     LU.h
-  */
-  // NOTE there seems to be a problem with too small sizes -- could easily lie in the doSomeRankPreservingOperations function
-  int rows = ei_random<int>(20,200), cols = ei_random<int>(20,200), cols2 = ei_random<int>(20,200);
-  int rank = ei_random<int>(1, std::min(rows, cols)-1);
-
-  MatrixType m1(rows, cols), m2(cols, cols2), m3(rows, cols2), k(1,1);
-  m1 = MatrixType::Random(rows,cols);
-  if(rows <= cols)
-    for(int i = rank; i < rows; i++) m1.row(i).setZero();
-  else
-    for(int i = rank; i < cols; i++) m1.col(i).setZero();
-  doSomeRankPreservingOperations(m1);
-
-  LU<MatrixType> lu(m1);
-  typename LU<MatrixType>::KernelResultType m1kernel = lu.kernel();
-  typename LU<MatrixType>::ImageResultType m1image = lu.image();
-
-  VERIFY(rank == lu.rank());
-  VERIFY(cols - lu.rank() == lu.dimensionOfKernel());
-  VERIFY(!lu.isInjective());
-  VERIFY(!lu.isInvertible());
-  VERIFY(lu.isSurjective() == (lu.rank() == rows));
-  VERIFY((m1 * m1kernel).isMuchSmallerThan(m1));
-  VERIFY(m1image.lu().rank() == rank);
-  MatrixType sidebyside(m1.rows(), m1.cols() + m1image.cols());
-  sidebyside << m1, m1image;
-  VERIFY(sidebyside.lu().rank() == rank);
-  m2 = MatrixType::Random(cols,cols2);
-  m3 = m1*m2;
-  m2 = MatrixType::Random(cols,cols2);
-  lu.solve(m3, &m2);
-  VERIFY_IS_APPROX(m3, m1*m2);
-  /* solve now always returns true
-  m3 = MatrixType::Random(rows,cols2);
-  VERIFY(!lu.solve(m3, &m2));
-  */
-}
-
-template<typename MatrixType> void lu_invertible()
-{
-  /* this test covers the following files:
-     LU.h
-  */
-  typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-  int size = ei_random<int>(10,200);
-
-  MatrixType m1(size, size), m2(size, size), m3(size, size);
-  m1 = MatrixType::Random(size,size);
-
-  if (ei_is_same_type<RealScalar,float>::ret)
-  {
-    // let's build a matrix more stable to inverse
-    MatrixType a = MatrixType::Random(size,size*2);
-    m1 += a * a.adjoint();
-  }
-
-  LU<MatrixType> lu(m1);
-  VERIFY(0 == lu.dimensionOfKernel());
-  VERIFY(size == lu.rank());
-  VERIFY(lu.isInjective());
-  VERIFY(lu.isSurjective());
-  VERIFY(lu.isInvertible());
-  VERIFY(lu.image().lu().isInvertible());
-  m3 = MatrixType::Random(size,size);
-  lu.solve(m3, &m2);
-  VERIFY_IS_APPROX(m3, m1*m2);
-  VERIFY_IS_APPROX(m2, lu.inverse()*m3);
-  m3 = MatrixType::Random(size,size);
-  VERIFY(lu.solve(m3, &m2));
-}
-
-void test_eigen2_lu()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( lu_non_invertible<MatrixXf>() );
-    CALL_SUBTEST_2( lu_non_invertible<MatrixXd>() );
-    CALL_SUBTEST_3( lu_non_invertible<MatrixXcf>() );
-    CALL_SUBTEST_4( lu_non_invertible<MatrixXcd>() );
-    CALL_SUBTEST_1( lu_invertible<MatrixXf>() );
-    CALL_SUBTEST_2( lu_invertible<MatrixXd>() );
-    CALL_SUBTEST_3( lu_invertible<MatrixXcf>() );
-    CALL_SUBTEST_4( lu_invertible<MatrixXcd>() );
-  }
-}
diff --git a/test/eigen2/eigen2_map.cpp b/test/eigen2/eigen2_map.cpp
deleted file mode 100644
index 4a1c4e11a..000000000
--- a/test/eigen2/eigen2_map.cpp
+++ /dev/null
@@ -1,114 +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) 2007-2010 Benoit Jacob <jacob.benoit.1@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 "main.h"
-
-template<typename VectorType> void map_class_vector(const VectorType& m)
-{
-  typedef typename VectorType::Scalar Scalar;
-
-  int size = m.size();
-
-  // test Map.h
-  Scalar* array1 = ei_aligned_new<Scalar>(size);
-  Scalar* array2 = ei_aligned_new<Scalar>(size);
-  Scalar* array3 = new Scalar[size+1];
-  Scalar* array3unaligned = std::size_t(array3)%16 == 0 ? array3+1 : array3;
-  
-  Map<VectorType, Aligned>(array1, size) = VectorType::Random(size);
-  Map<VectorType>(array2, size) = Map<VectorType>(array1, size);
-  Map<VectorType>(array3unaligned, size) = Map<VectorType>((const Scalar*)array1, size); // test non-const-correctness support in eigen2
-  VectorType ma1 = Map<VectorType>(array1, size);
-  VectorType ma2 = Map<VectorType, Aligned>(array2, size);
-  VectorType ma3 = Map<VectorType>(array3unaligned, size);
-  VERIFY_IS_APPROX(ma1, ma2);
-  VERIFY_IS_APPROX(ma1, ma3);
-  
-  ei_aligned_delete(array1, size);
-  ei_aligned_delete(array2, size);
-  delete[] array3;
-}
-
-template<typename MatrixType> void map_class_matrix(const MatrixType& m)
-{
-  typedef typename MatrixType::Scalar Scalar;
-
-  int rows = m.rows(), cols = m.cols(), size = rows*cols;
-
-  // test Map.h
-  Scalar* array1 = ei_aligned_new<Scalar>(size);
-  for(int i = 0; i < size; i++) array1[i] = Scalar(1);
-  Scalar* array2 = ei_aligned_new<Scalar>(size);
-  for(int i = 0; i < size; i++) array2[i] = Scalar(1);
-  Scalar* array3 = new Scalar[size+1];
-  for(int i = 0; i < size+1; i++) array3[i] = Scalar(1);
-  Scalar* array3unaligned = std::size_t(array3)%16 == 0 ? array3+1 : array3;
-  Map<MatrixType, Aligned>(array1, rows, cols) = MatrixType::Ones(rows,cols);
-  Map<MatrixType>(array2, rows, cols) = Map<MatrixType>((const Scalar*)array1, rows, cols); // test non-const-correctness support in eigen2
-  Map<MatrixType>(array3unaligned, rows, cols) = Map<MatrixType>(array1, rows, cols);
-  MatrixType ma1 = Map<MatrixType>(array1, rows, cols);
-  MatrixType ma2 = Map<MatrixType, Aligned>(array2, rows, cols);
-  VERIFY_IS_APPROX(ma1, ma2);
-  MatrixType ma3 = Map<MatrixType>(array3unaligned, rows, cols);
-  VERIFY_IS_APPROX(ma1, ma3);
-  
-  ei_aligned_delete(array1, size);
-  ei_aligned_delete(array2, size);
-  delete[] array3;
-}
-
-template<typename VectorType> void map_static_methods(const VectorType& m)
-{
-  typedef typename VectorType::Scalar Scalar;
-
-  int size = m.size();
-
-  // test Map.h
-  Scalar* array1 = ei_aligned_new<Scalar>(size);
-  Scalar* array2 = ei_aligned_new<Scalar>(size);
-  Scalar* array3 = new Scalar[size+1];
-  Scalar* array3unaligned = std::size_t(array3)%16 == 0 ? array3+1 : array3;
-  
-  VectorType::MapAligned(array1, size) = VectorType::Random(size);
-  VectorType::Map(array2, size) = VectorType::Map(array1, size);
-  VectorType::Map(array3unaligned, size) = VectorType::Map(array1, size);
-  VectorType ma1 = VectorType::Map(array1, size);
-  VectorType ma2 = VectorType::MapAligned(array2, size);
-  VectorType ma3 = VectorType::Map(array3unaligned, size);
-  VERIFY_IS_APPROX(ma1, ma2);
-  VERIFY_IS_APPROX(ma1, ma3);
-  
-  ei_aligned_delete(array1, size);
-  ei_aligned_delete(array2, size);
-  delete[] array3;
-}
-
-
-void test_eigen2_map()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( map_class_vector(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( map_class_vector(Vector4d()) );
-    CALL_SUBTEST_3( map_class_vector(RowVector4f()) );
-    CALL_SUBTEST_4( map_class_vector(VectorXcf(8)) );
-    CALL_SUBTEST_5( map_class_vector(VectorXi(12)) );
-
-    CALL_SUBTEST_1( map_class_matrix(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( map_class_matrix(Matrix4d()) );
-    CALL_SUBTEST_6( map_class_matrix(Matrix<float,3,5>()) );
-    CALL_SUBTEST_4( map_class_matrix(MatrixXcf(ei_random<int>(1,10),ei_random<int>(1,10))) );
-    CALL_SUBTEST_5( map_class_matrix(MatrixXi(ei_random<int>(1,10),ei_random<int>(1,10))) );
-
-    CALL_SUBTEST_1( map_static_methods(Matrix<double, 1, 1>()) );
-    CALL_SUBTEST_2( map_static_methods(Vector3f()) );
-    CALL_SUBTEST_7( map_static_methods(RowVector3d()) );
-    CALL_SUBTEST_4( map_static_methods(VectorXcd(8)) );
-    CALL_SUBTEST_5( map_static_methods(VectorXf(12)) );
-  }
-}
diff --git a/test/eigen2/eigen2_meta.cpp b/test/eigen2/eigen2_meta.cpp
deleted file mode 100644
index 1d01bd84d..000000000
--- a/test/eigen2/eigen2_meta.cpp
+++ /dev/null
@@ -1,60 +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"
-
-void test_eigen2_meta()
-{
-  typedef float & FloatRef;
-  typedef const float & ConstFloatRef;
-  
-  VERIFY((ei_meta_if<(3<4),ei_meta_true, ei_meta_false>::ret::ret));
-  VERIFY(( ei_is_same_type<float,float>::ret));
-  VERIFY((!ei_is_same_type<float,double>::ret));
-  VERIFY((!ei_is_same_type<float,float&>::ret));
-  VERIFY((!ei_is_same_type<float,const float&>::ret));
-  
-  VERIFY(( ei_is_same_type<float,ei_cleantype<const float&>::type >::ret));
-  VERIFY(( ei_is_same_type<float,ei_cleantype<const float*>::type >::ret));
-  VERIFY(( ei_is_same_type<float,ei_cleantype<const float*&>::type >::ret));
-  VERIFY(( ei_is_same_type<float,ei_cleantype<float**>::type >::ret));
-  VERIFY(( ei_is_same_type<float,ei_cleantype<float**&>::type >::ret));
-  VERIFY(( ei_is_same_type<float,ei_cleantype<float* const *&>::type >::ret));
-  VERIFY(( ei_is_same_type<float,ei_cleantype<float* const>::type >::ret));
-
-  VERIFY(( ei_is_same_type<float*,ei_unconst<const float*>::type >::ret));
-  VERIFY(( ei_is_same_type<float&,ei_unconst<const float&>::type >::ret));
-  VERIFY(( ei_is_same_type<float&,ei_unconst<ConstFloatRef>::type >::ret));
-  
-  VERIFY(( ei_is_same_type<float&,ei_unconst<float&>::type >::ret));
-  VERIFY(( ei_is_same_type<float,ei_unref<float&>::type >::ret));
-  VERIFY(( ei_is_same_type<const float,ei_unref<const float&>::type >::ret));
-  VERIFY(( ei_is_same_type<float,ei_unpointer<float*>::type >::ret));
-  VERIFY(( ei_is_same_type<const float,ei_unpointer<const float*>::type >::ret));
-  VERIFY(( ei_is_same_type<float,ei_unpointer<float* const >::type >::ret));
-  
-  VERIFY(ei_meta_sqrt<1>::ret == 1);
-  #define VERIFY_META_SQRT(X) VERIFY(ei_meta_sqrt<X>::ret == int(ei_sqrt(double(X))))
-  VERIFY_META_SQRT(2);
-  VERIFY_META_SQRT(3);
-  VERIFY_META_SQRT(4);
-  VERIFY_META_SQRT(5);
-  VERIFY_META_SQRT(6);
-  VERIFY_META_SQRT(8);
-  VERIFY_META_SQRT(9);
-  VERIFY_META_SQRT(15);
-  VERIFY_META_SQRT(16);
-  VERIFY_META_SQRT(17);
-  VERIFY_META_SQRT(255);
-  VERIFY_META_SQRT(256);
-  VERIFY_META_SQRT(257);
-  VERIFY_META_SQRT(1023);
-  VERIFY_META_SQRT(1024);
-  VERIFY_META_SQRT(1025);
-}
diff --git a/test/eigen2/eigen2_miscmatrices.cpp b/test/eigen2/eigen2_miscmatrices.cpp
deleted file mode 100644
index 8bbb20cc8..000000000
--- a/test/eigen2/eigen2_miscmatrices.cpp
+++ /dev/null
@@ -1,48 +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) 2006-2008 Benoit Jacob <jacob.benoit.1@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 "main.h"
-
-template<typename MatrixType> void miscMatrices(const MatrixType& m)
-{
-  /* this test covers the following files:
-     DiagonalMatrix.h Ones.h
-  */
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-  typedef Matrix<Scalar, 1, MatrixType::ColsAtCompileTime> RowVectorType;
-  int rows = m.rows();
-  int cols = m.cols();
-
-  int r = ei_random<int>(0, rows-1), r2 = ei_random<int>(0, rows-1), c = ei_random<int>(0, cols-1);
-  VERIFY_IS_APPROX(MatrixType::Ones(rows,cols)(r,c), static_cast<Scalar>(1));
-  MatrixType m1 = MatrixType::Ones(rows,cols);
-  VERIFY_IS_APPROX(m1(r,c), static_cast<Scalar>(1));
-  VectorType v1 = VectorType::Random(rows);
-  v1[0];
-  Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
-  square = v1.asDiagonal();
-  if(r==r2) VERIFY_IS_APPROX(square(r,r2), v1[r]);
-  else VERIFY_IS_MUCH_SMALLER_THAN(square(r,r2), static_cast<Scalar>(1));
-  square = MatrixType::Zero(rows, rows);
-  square.diagonal() = VectorType::Ones(rows);
-  VERIFY_IS_APPROX(square, MatrixType::Identity(rows, rows));
-}
-
-void test_eigen2_miscmatrices()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( miscMatrices(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( miscMatrices(Matrix4d()) );
-    CALL_SUBTEST_3( miscMatrices(MatrixXcf(3, 3)) );
-    CALL_SUBTEST_4( miscMatrices(MatrixXi(8, 12)) );
-    CALL_SUBTEST_5( miscMatrices(MatrixXcd(20, 20)) );
-  }
-}
diff --git a/test/eigen2/eigen2_mixingtypes.cpp b/test/eigen2/eigen2_mixingtypes.cpp
deleted file mode 100644
index fb5ac5dda..000000000
--- a/test/eigen2/eigen2_mixingtypes.cpp
+++ /dev/null
@@ -1,77 +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>
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@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/.
-
-#ifndef EIGEN_NO_STATIC_ASSERT
-#define EIGEN_NO_STATIC_ASSERT // turn static asserts into runtime asserts in order to check them
-#endif
-
-#ifndef EIGEN_DONT_VECTORIZE
-#define EIGEN_DONT_VECTORIZE // SSE intrinsics aren't designed to allow mixing types
-#endif
-
-#include "main.h"
-
-
-template<int SizeAtCompileType> void mixingtypes(int size = SizeAtCompileType)
-{
-  typedef Matrix<float, SizeAtCompileType, SizeAtCompileType> Mat_f;
-  typedef Matrix<double, SizeAtCompileType, SizeAtCompileType> Mat_d;
-  typedef Matrix<std::complex<float>, SizeAtCompileType, SizeAtCompileType> Mat_cf;
-  typedef Matrix<std::complex<double>, SizeAtCompileType, SizeAtCompileType> Mat_cd;
-  typedef Matrix<float, SizeAtCompileType, 1> Vec_f;
-  typedef Matrix<double, SizeAtCompileType, 1> Vec_d;
-  typedef Matrix<std::complex<float>, SizeAtCompileType, 1> Vec_cf;
-  typedef Matrix<std::complex<double>, SizeAtCompileType, 1> Vec_cd;
-
-  Mat_f mf(size,size);
-  Mat_d md(size,size);
-  Mat_cf mcf(size,size);
-  Mat_cd mcd(size,size);
-  Vec_f vf(size,1);
-  Vec_d vd(size,1);
-  Vec_cf vcf(size,1);
-  Vec_cd vcd(size,1);
-
-  mf+mf;
-  VERIFY_RAISES_ASSERT(mf+md);
-  VERIFY_RAISES_ASSERT(mf+mcf);
-  VERIFY_RAISES_ASSERT(vf=vd);
-  VERIFY_RAISES_ASSERT(vf+=vd);
-  VERIFY_RAISES_ASSERT(mcd=md);
-
-  mf*mf;
-  md*mcd;
-  mcd*md;
-  mf*vcf;
-  mcf*vf;
-  mcf *= mf;
-  vcd = md*vcd;
-  vcf = mcf*vf;
-#if 0
-  // these are know generating hard build errors in eigen3
-  VERIFY_RAISES_ASSERT(mf*md);
-  VERIFY_RAISES_ASSERT(mcf*mcd);
-  VERIFY_RAISES_ASSERT(mcf*vcd);
-  VERIFY_RAISES_ASSERT(vcf = mf*vf);
-
-  vf.eigen2_dot(vf);
-  VERIFY_RAISES_ASSERT(vd.eigen2_dot(vf));
-  VERIFY_RAISES_ASSERT(vcf.eigen2_dot(vf)); // yeah eventually we should allow this but i'm too lazy to make that change now in Dot.h
-  // especially as that might be rewritten as cwise product .sum() which would make that automatic.
-#endif
-}
-
-void test_eigen2_mixingtypes()
-{
-  // check that our operator new is indeed called:
-  CALL_SUBTEST_1(mixingtypes<3>());
-  CALL_SUBTEST_2(mixingtypes<4>());
-  CALL_SUBTEST_3(mixingtypes<Dynamic>(20));
-}
diff --git a/test/eigen2/eigen2_newstdvector.cpp b/test/eigen2/eigen2_newstdvector.cpp
deleted file mode 100644
index 5f9009901..000000000
--- a/test/eigen2/eigen2_newstdvector.cpp
+++ /dev/null
@@ -1,149 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@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/.
-
-#define EIGEN_USE_NEW_STDVECTOR
-#include "main.h"
-#include <Eigen/StdVector>
-#include <Eigen/Geometry>
-
-template<typename MatrixType>
-void check_stdvector_matrix(const MatrixType& m)
-{
-  int rows = m.rows();
-  int cols = m.cols();
-  MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols);
-  std::vector<MatrixType,Eigen::aligned_allocator<MatrixType> > v(10, MatrixType(rows,cols)), w(20, y);
-  v[5] = x;
-  w[6] = v[5];
-  VERIFY_IS_APPROX(w[6], v[5]);
-  v = w;
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], v[i]);
-  }
-
-  v.resize(21);
-  v[20] = x;
-  VERIFY_IS_APPROX(v[20], x);
-  v.resize(22,y);
-  VERIFY_IS_APPROX(v[21], y);
-  v.push_back(x);
-  VERIFY_IS_APPROX(v[22], x);
-  VERIFY((std::size_t)&(v[22]) == (std::size_t)&(v[21]) + sizeof(MatrixType));
-
-  // do a lot of push_back such that the vector gets internally resized
-  // (with memory reallocation)
-  MatrixType* ref = &w[0];
-  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
-    v.push_back(w[i%w.size()]);
-  for(unsigned int i=23; i<v.size(); ++i)
-  {
-    VERIFY(v[i]==w[(i-23)%w.size()]);
-  }
-}
-
-template<typename TransformType>
-void check_stdvector_transform(const TransformType&)
-{
-  typedef typename TransformType::MatrixType MatrixType;
-  TransformType x(MatrixType::Random()), y(MatrixType::Random());
-  std::vector<TransformType,Eigen::aligned_allocator<TransformType> > v(10), w(20, y);
-  v[5] = x;
-  w[6] = v[5];
-  VERIFY_IS_APPROX(w[6], v[5]);
-  v = w;
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], v[i]);
-  }
-
-  v.resize(21);
-  v[20] = x;
-  VERIFY_IS_APPROX(v[20], x);
-  v.resize(22,y);
-  VERIFY_IS_APPROX(v[21], y);
-  v.push_back(x);
-  VERIFY_IS_APPROX(v[22], x);
-  VERIFY((std::size_t)&(v[22]) == (std::size_t)&(v[21]) + sizeof(TransformType));
-
-  // do a lot of push_back such that the vector gets internally resized
-  // (with memory reallocation)
-  TransformType* ref = &w[0];
-  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
-    v.push_back(w[i%w.size()]);
-  for(unsigned int i=23; i<v.size(); ++i)
-  {
-    VERIFY(v[i].matrix()==w[(i-23)%w.size()].matrix());
-  }
-}
-
-template<typename QuaternionType>
-void check_stdvector_quaternion(const QuaternionType&)
-{
-  typedef typename QuaternionType::Coefficients Coefficients;
-  QuaternionType x(Coefficients::Random()), y(Coefficients::Random());
-  std::vector<QuaternionType,Eigen::aligned_allocator<QuaternionType> > v(10), w(20, y);
-  v[5] = x;
-  w[6] = v[5];
-  VERIFY_IS_APPROX(w[6], v[5]);
-  v = w;
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], v[i]);
-  }
-
-  v.resize(21);
-  v[20] = x;
-  VERIFY_IS_APPROX(v[20], x);
-  v.resize(22,y);
-  VERIFY_IS_APPROX(v[21], y);
-  v.push_back(x);
-  VERIFY_IS_APPROX(v[22], x);
-  VERIFY((std::size_t)&(v[22]) == (std::size_t)&(v[21]) + sizeof(QuaternionType));
-
-  // do a lot of push_back such that the vector gets internally resized
-  // (with memory reallocation)
-  QuaternionType* ref = &w[0];
-  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
-    v.push_back(w[i%w.size()]);
-  for(unsigned int i=23; i<v.size(); ++i)
-  {
-    VERIFY(v[i].coeffs()==w[(i-23)%w.size()].coeffs());
-  }
-}
-
-void test_eigen2_newstdvector()
-{
-  // some non vectorizable fixed sizes
-  CALL_SUBTEST_1(check_stdvector_matrix(Vector2f()));
-  CALL_SUBTEST_1(check_stdvector_matrix(Matrix3f()));
-  CALL_SUBTEST_1(check_stdvector_matrix(Matrix3d()));
-
-  // some vectorizable fixed sizes
-  CALL_SUBTEST_2(check_stdvector_matrix(Matrix2f()));
-  CALL_SUBTEST_2(check_stdvector_matrix(Vector4f()));
-  CALL_SUBTEST_2(check_stdvector_matrix(Matrix4f()));
-  CALL_SUBTEST_2(check_stdvector_matrix(Matrix4d()));
-
-  // some dynamic sizes
-  CALL_SUBTEST_3(check_stdvector_matrix(MatrixXd(1,1)));
-  CALL_SUBTEST_3(check_stdvector_matrix(VectorXd(20)));
-  CALL_SUBTEST_3(check_stdvector_matrix(RowVectorXf(20)));
-  CALL_SUBTEST_3(check_stdvector_matrix(MatrixXcf(10,10)));
-
-  // some Transform
-  CALL_SUBTEST_4(check_stdvector_transform(Transform2f()));
-  CALL_SUBTEST_4(check_stdvector_transform(Transform3f()));
-  CALL_SUBTEST_4(check_stdvector_transform(Transform3d()));
-  //CALL_SUBTEST(check_stdvector_transform(Transform4d()));
-
-  // some Quaternion
-  CALL_SUBTEST_5(check_stdvector_quaternion(Quaternionf()));
-  CALL_SUBTEST_5(check_stdvector_quaternion(Quaterniond()));
-}
diff --git a/test/eigen2/eigen2_nomalloc.cpp b/test/eigen2/eigen2_nomalloc.cpp
deleted file mode 100644
index e234abe4b..000000000
--- a/test/eigen2/eigen2_nomalloc.cpp
+++ /dev/null
@@ -1,63 +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>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@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/.
-
-// this hack is needed to make this file compiles with -pedantic (gcc)
-#ifdef __GNUC__
-#define throw(X)
-#endif
-// discard stack allocation as that too bypasses malloc
-#define EIGEN_STACK_ALLOCATION_LIMIT 0
-// any heap allocation will raise an assert
-#define EIGEN_NO_MALLOC
-
-#include "main.h"
-
-template<typename MatrixType> void nomalloc(const MatrixType& m)
-{
-  /* this test check no dynamic memory allocation are issued with fixed-size matrices
-  */
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-
-  int rows = m.rows();
-  int cols = m.cols();
-
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols),
-             mzero = MatrixType::Zero(rows, cols),
-             identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
-                              ::Identity(rows, rows),
-             square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
-                              ::Random(rows, rows);
-  VectorType v1 = VectorType::Random(rows),
-             v2 = VectorType::Random(rows),
-             vzero = VectorType::Zero(rows);
-
-  Scalar s1 = ei_random<Scalar>();
-
-  int r = ei_random<int>(0, rows-1),
-      c = ei_random<int>(0, cols-1);
-
-  VERIFY_IS_APPROX((m1+m2)*s1,              s1*m1+s1*m2);
-  VERIFY_IS_APPROX((m1+m2)(r,c), (m1(r,c))+(m2(r,c)));
-  VERIFY_IS_APPROX(m1.cwise() * m1.block(0,0,rows,cols), m1.cwise() * m1);
-  VERIFY_IS_APPROX((m1*m1.transpose())*m2,  m1*(m1.transpose()*m2));
-}
-
-void test_eigen2_nomalloc()
-{
-  // check that our operator new is indeed called:
-  VERIFY_RAISES_ASSERT(MatrixXd dummy = MatrixXd::Random(3,3));
-  CALL_SUBTEST_1( nomalloc(Matrix<float, 1, 1>()) );
-  CALL_SUBTEST_2( nomalloc(Matrix4d()) );
-  CALL_SUBTEST_3( nomalloc(Matrix<float,32,32>()) );
-}
diff --git a/test/eigen2/eigen2_packetmath.cpp b/test/eigen2/eigen2_packetmath.cpp
deleted file mode 100644
index b1f325fe7..000000000
--- a/test/eigen2/eigen2_packetmath.cpp
+++ /dev/null
@@ -1,132 +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) 2006-2008 Benoit Jacob <jacob.benoit.1@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 "main.h"
-
-// using namespace Eigen;
-
-template<typename Scalar> bool areApprox(const Scalar* a, const Scalar* b, int size)
-{
-  for (int i=0; i<size; ++i)
-    if (!ei_isApprox(a[i],b[i])) return false;
-  return true;
-}
-
-#define CHECK_CWISE(REFOP, POP) { \
-  for (int i=0; i<PacketSize; ++i) \
-    ref[i] = REFOP(data1[i], data1[i+PacketSize]); \
-  ei_pstore(data2, POP(ei_pload(data1), ei_pload(data1+PacketSize))); \
-  VERIFY(areApprox(ref, data2, PacketSize) && #POP); \
-}
-
-#define REF_ADD(a,b) ((a)+(b))
-#define REF_SUB(a,b) ((a)-(b))
-#define REF_MUL(a,b) ((a)*(b))
-#define REF_DIV(a,b) ((a)/(b))
-
-namespace std {
-
-template<> const complex<float>& min(const complex<float>& a, const complex<float>& b)
-{ return a.real() < b.real() ? a : b; }
-
-template<> const complex<float>& max(const complex<float>& a, const complex<float>& b)
-{ return a.real() < b.real() ? b : a; }
-
-}
-
-template<typename Scalar> void packetmath()
-{
-  typedef typename ei_packet_traits<Scalar>::type Packet;
-  const int PacketSize = ei_packet_traits<Scalar>::size;
-
-  const int size = PacketSize*4;
-  EIGEN_ALIGN_128 Scalar data1[ei_packet_traits<Scalar>::size*4];
-  EIGEN_ALIGN_128 Scalar data2[ei_packet_traits<Scalar>::size*4];
-  EIGEN_ALIGN_128 Packet packets[PacketSize*2];
-  EIGEN_ALIGN_128 Scalar ref[ei_packet_traits<Scalar>::size*4];
-  for (int i=0; i<size; ++i)
-  {
-    data1[i] = ei_random<Scalar>();
-    data2[i] = ei_random<Scalar>();
-  }
-
-  ei_pstore(data2, ei_pload(data1));
-  VERIFY(areApprox(data1, data2, PacketSize) && "aligned load/store");
-
-  for (int offset=0; offset<PacketSize; ++offset)
-  {
-    ei_pstore(data2, ei_ploadu(data1+offset));
-    VERIFY(areApprox(data1+offset, data2, PacketSize) && "ei_ploadu");
-  }
-
-  for (int offset=0; offset<PacketSize; ++offset)
-  {
-    ei_pstoreu(data2+offset, ei_pload(data1));
-    VERIFY(areApprox(data1, data2+offset, PacketSize) && "ei_pstoreu");
-  }
-
-  for (int offset=0; offset<PacketSize; ++offset)
-  {
-    packets[0] = ei_pload(data1);
-    packets[1] = ei_pload(data1+PacketSize);
-         if (offset==0) ei_palign<0>(packets[0], packets[1]);
-    else if (offset==1) ei_palign<1>(packets[0], packets[1]);
-    else if (offset==2) ei_palign<2>(packets[0], packets[1]);
-    else if (offset==3) ei_palign<3>(packets[0], packets[1]);
-    ei_pstore(data2, packets[0]);
-
-    for (int i=0; i<PacketSize; ++i)
-      ref[i] = data1[i+offset];
-
-    typedef Matrix<Scalar, PacketSize, 1> Vector;
-    VERIFY(areApprox(ref, data2, PacketSize) && "ei_palign");
-  }
-
-  CHECK_CWISE(REF_ADD,  ei_padd);
-  CHECK_CWISE(REF_SUB,  ei_psub);
-  CHECK_CWISE(REF_MUL,  ei_pmul);
-  #ifndef EIGEN_VECTORIZE_ALTIVEC
-  if (!ei_is_same_type<Scalar,int>::ret)
-    CHECK_CWISE(REF_DIV,  ei_pdiv);
-  #endif
-  CHECK_CWISE(std::min, ei_pmin);
-  CHECK_CWISE(std::max, ei_pmax);
-
-  for (int i=0; i<PacketSize; ++i)
-    ref[i] = data1[0];
-  ei_pstore(data2, ei_pset1(data1[0]));
-  VERIFY(areApprox(ref, data2, PacketSize) && "ei_pset1");
-
-  VERIFY(ei_isApprox(data1[0], ei_pfirst(ei_pload(data1))) && "ei_pfirst");
-
-  ref[0] = 0;
-  for (int i=0; i<PacketSize; ++i)
-    ref[0] += data1[i];
-  VERIFY(ei_isApprox(ref[0], ei_predux(ei_pload(data1))) && "ei_predux");
-
-  for (int j=0; j<PacketSize; ++j)
-  {
-    ref[j] = 0;
-    for (int i=0; i<PacketSize; ++i)
-      ref[j] += data1[i+j*PacketSize];
-    packets[j] = ei_pload(data1+j*PacketSize);
-  }
-  ei_pstore(data2, ei_preduxp(packets));
-  VERIFY(areApprox(ref, data2, PacketSize) && "ei_preduxp");
-}
-
-void test_eigen2_packetmath()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( packetmath<float>() );
-    CALL_SUBTEST_2( packetmath<double>() );
-    CALL_SUBTEST_3( packetmath<int>() );
-    CALL_SUBTEST_4( packetmath<std::complex<float> >() );
-  }
-}
diff --git a/test/eigen2/eigen2_parametrizedline.cpp b/test/eigen2/eigen2_parametrizedline.cpp
deleted file mode 100644
index 814728870..000000000
--- a/test/eigen2/eigen2_parametrizedline.cpp
+++ /dev/null
@@ -1,62 +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>
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@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 "main.h"
-#include <Eigen/Geometry>
-#include <Eigen/LU>
-#include <Eigen/QR>
-
-template<typename LineType> void parametrizedline(const LineType& _line)
-{
-  /* this test covers the following files:
-     ParametrizedLine.h
-  */
-
-  const int dim = _line.dim();
-  typedef typename LineType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, LineType::AmbientDimAtCompileTime, 1> VectorType;
-  typedef Matrix<Scalar, LineType::AmbientDimAtCompileTime,
-                         LineType::AmbientDimAtCompileTime> MatrixType;
-
-  VectorType p0 = VectorType::Random(dim);
-  VectorType p1 = VectorType::Random(dim);
-
-  VectorType d0 = VectorType::Random(dim).normalized();
-
-  LineType l0(p0, d0);
-
-  Scalar s0 = ei_random<Scalar>();
-  Scalar s1 = ei_abs(ei_random<Scalar>());
-
-  VERIFY_IS_MUCH_SMALLER_THAN( l0.distance(p0), RealScalar(1) );
-  VERIFY_IS_MUCH_SMALLER_THAN( l0.distance(p0+s0*d0), RealScalar(1) );
-  VERIFY_IS_APPROX( (l0.projection(p1)-p1).norm(), l0.distance(p1) );
-  VERIFY_IS_MUCH_SMALLER_THAN( l0.distance(l0.projection(p1)), RealScalar(1) );
-  VERIFY_IS_APPROX( Scalar(l0.distance((p0+s0*d0) + d0.unitOrthogonal() * s1)), s1 );
-
-  // casting
-  const int Dim = LineType::AmbientDimAtCompileTime;
-  typedef typename GetDifferentType<Scalar>::type OtherScalar;
-  ParametrizedLine<OtherScalar,Dim> hp1f = l0.template cast<OtherScalar>();
-  VERIFY_IS_APPROX(hp1f.template cast<Scalar>(),l0);
-  ParametrizedLine<Scalar,Dim> hp1d = l0.template cast<Scalar>();
-  VERIFY_IS_APPROX(hp1d.template cast<Scalar>(),l0);
-}
-
-void test_eigen2_parametrizedline()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( parametrizedline(ParametrizedLine<float,2>()) );
-    CALL_SUBTEST_2( parametrizedline(ParametrizedLine<float,3>()) );
-    CALL_SUBTEST_3( parametrizedline(ParametrizedLine<double,4>()) );
-    CALL_SUBTEST_4( parametrizedline(ParametrizedLine<std::complex<double>,5>()) );
-  }
-}
diff --git a/test/eigen2/eigen2_prec_inverse_4x4.cpp b/test/eigen2/eigen2_prec_inverse_4x4.cpp
deleted file mode 100644
index 8bfa55694..000000000
--- a/test/eigen2/eigen2_prec_inverse_4x4.cpp
+++ /dev/null
@@ -1,84 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@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 "main.h"
-#include <Eigen/LU>
-#include <algorithm>
-
-template<typename T> std::string type_name() { return "other"; }
-template<> std::string type_name<float>() { return "float"; }
-template<> std::string type_name<double>() { return "double"; }
-template<> std::string type_name<int>() { return "int"; }
-template<> std::string type_name<std::complex<float> >() { return "complex<float>"; }
-template<> std::string type_name<std::complex<double> >() { return "complex<double>"; }
-template<> std::string type_name<std::complex<int> >() { return "complex<int>"; }
-
-#define EIGEN_DEBUG_VAR(x) std::cerr << #x << " = " << x << std::endl;
-
-template<typename T> inline typename NumTraits<T>::Real epsilon()
-{
- return std::numeric_limits<typename NumTraits<T>::Real>::epsilon();
-}
-
-template<typename MatrixType> void inverse_permutation_4x4()
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::RealScalar RealScalar;
-  Vector4i indices(0,1,2,3);
-  for(int i = 0; i < 24; ++i)
-  {
-    MatrixType m = MatrixType::Zero();
-    m(indices(0),0) = 1;
-    m(indices(1),1) = 1;
-    m(indices(2),2) = 1;
-    m(indices(3),3) = 1;
-    MatrixType inv = m.inverse();
-    double error = double( (m*inv-MatrixType::Identity()).norm() / epsilon<Scalar>() );
-    VERIFY(error == 0.0);
-    std::next_permutation(indices.data(),indices.data()+4);
-  }
-}
-
-template<typename MatrixType> void inverse_general_4x4(int repeat)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::RealScalar RealScalar;
-  double error_sum = 0., error_max = 0.;
-  for(int i = 0; i < repeat; ++i)
-  {
-    MatrixType m;
-    RealScalar absdet;
-    do {
-      m = MatrixType::Random();
-      absdet = ei_abs(m.determinant());
-    } while(absdet < 10 * epsilon<Scalar>());
-    MatrixType inv = m.inverse();
-    double error = double( (m*inv-MatrixType::Identity()).norm() * absdet / epsilon<Scalar>() );
-    error_sum += error;
-    error_max = std::max(error_max, error);
-  }
-  std::cerr << "inverse_general_4x4, Scalar = " << type_name<Scalar>() << std::endl;
-  double error_avg = error_sum / repeat;
-  EIGEN_DEBUG_VAR(error_avg);
-  EIGEN_DEBUG_VAR(error_max);
-  VERIFY(error_avg < (NumTraits<Scalar>::IsComplex ? 8.0 : 1.25));
-  VERIFY(error_max < (NumTraits<Scalar>::IsComplex ? 64.0 : 20.0));
-}
-
-void test_eigen2_prec_inverse_4x4()
-{
-  CALL_SUBTEST_1((inverse_permutation_4x4<Matrix4f>()));
-  CALL_SUBTEST_1(( inverse_general_4x4<Matrix4f>(200000 * g_repeat) ));
-
-  CALL_SUBTEST_2((inverse_permutation_4x4<Matrix<double,4,4,RowMajor> >()));
-  CALL_SUBTEST_2(( inverse_general_4x4<Matrix<double,4,4,RowMajor> >(200000 * g_repeat) ));
-
-  CALL_SUBTEST_3((inverse_permutation_4x4<Matrix4cf>()));
-  CALL_SUBTEST_3((inverse_general_4x4<Matrix4cf>(50000 * g_repeat)));
-}
diff --git a/test/eigen2/eigen2_product_large.cpp b/test/eigen2/eigen2_product_large.cpp
deleted file mode 100644
index 5149ef748..000000000
--- a/test/eigen2/eigen2_product_large.cpp
+++ /dev/null
@@ -1,45 +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) 2006-2008 Benoit Jacob <jacob.benoit.1@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 "product.h"
-
-void test_eigen2_product_large()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( product(MatrixXf(ei_random<int>(1,320), ei_random<int>(1,320))) );
-    CALL_SUBTEST_2( product(MatrixXd(ei_random<int>(1,320), ei_random<int>(1,320))) );
-    CALL_SUBTEST_3( product(MatrixXi(ei_random<int>(1,320), ei_random<int>(1,320))) );
-    CALL_SUBTEST_4( product(MatrixXcf(ei_random<int>(1,50), ei_random<int>(1,50))) );
-    CALL_SUBTEST_5( product(Matrix<float,Dynamic,Dynamic,RowMajor>(ei_random<int>(1,320), ei_random<int>(1,320))) );
-  }
-
-#ifdef EIGEN_TEST_PART_6
-  {
-    // test a specific issue in DiagonalProduct
-    int N = 1000000;
-    VectorXf v = VectorXf::Ones(N);
-    MatrixXf m = MatrixXf::Ones(N,3);
-    m = (v+v).asDiagonal() * m;
-    VERIFY_IS_APPROX(m, MatrixXf::Constant(N,3,2));
-  }
-
-  {
-    // test deferred resizing in Matrix::operator=
-    MatrixXf a = MatrixXf::Random(10,4), b = MatrixXf::Random(4,10), c = a;
-    VERIFY_IS_APPROX((a = a * b), (c * b).eval());
-  }
-
-  {
-    MatrixXf mat1(10,10); mat1.setRandom();
-    MatrixXf mat2(32,10); mat2.setRandom();
-    MatrixXf result = mat1.row(2)*mat2.transpose();
-    VERIFY_IS_APPROX(result, (mat1.row(2)*mat2.transpose()).eval());
-  }
-#endif
-}
diff --git a/test/eigen2/eigen2_product_small.cpp b/test/eigen2/eigen2_product_small.cpp
deleted file mode 100644
index 4cd8c102f..000000000
--- a/test/eigen2/eigen2_product_small.cpp
+++ /dev/null
@@ -1,22 +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) 2006-2008 Benoit Jacob <jacob.benoit.1@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/.
-
-#define EIGEN_NO_STATIC_ASSERT
-#include "product.h"
-
-void test_eigen2_product_small()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( product(Matrix<float, 3, 2>()) );
-    CALL_SUBTEST_2( product(Matrix<int, 3, 5>()) );
-    CALL_SUBTEST_3( product(Matrix3d()) );
-    CALL_SUBTEST_4( product(Matrix4d()) );
-    CALL_SUBTEST_5( product(Matrix4f()) );
-  }
-}
diff --git a/test/eigen2/eigen2_qr.cpp b/test/eigen2/eigen2_qr.cpp
deleted file mode 100644
index 76977e4c1..000000000
--- a/test/eigen2/eigen2_qr.cpp
+++ /dev/null
@@ -1,69 +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>
-
-template<typename MatrixType> void qr(const MatrixType& m)
-{
-  /* this test covers the following files:
-     QR.h
-  */
-  int rows = m.rows();
-  int cols = m.cols();
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, MatrixType::ColsAtCompileTime> SquareMatrixType;
-  typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> VectorType;
-
-  MatrixType a = MatrixType::Random(rows,cols);
-  QR<MatrixType> qrOfA(a);
-  VERIFY_IS_APPROX(a, qrOfA.matrixQ() * qrOfA.matrixR());
-  VERIFY_IS_NOT_APPROX(a+MatrixType::Identity(rows, cols), qrOfA.matrixQ() * qrOfA.matrixR());
-
-  #if 0 // eigenvalues module not yet ready
-  SquareMatrixType b = a.adjoint() * a;
-
-  // check tridiagonalization
-  Tridiagonalization<SquareMatrixType> tridiag(b);
-  VERIFY_IS_APPROX(b, tridiag.matrixQ() * tridiag.matrixT() * tridiag.matrixQ().adjoint());
-
-  // check hessenberg decomposition
-  HessenbergDecomposition<SquareMatrixType> hess(b);
-  VERIFY_IS_APPROX(b, hess.matrixQ() * hess.matrixH() * hess.matrixQ().adjoint());
-  VERIFY_IS_APPROX(tridiag.matrixT(), hess.matrixH());
-  b = SquareMatrixType::Random(cols,cols);
-  hess.compute(b);
-  VERIFY_IS_APPROX(b, hess.matrixQ() * hess.matrixH() * hess.matrixQ().adjoint());
-  #endif
-}
-
-void test_eigen2_qr()
-{
-  for(int i = 0; i < 1; i++) {
-    CALL_SUBTEST_1( qr(Matrix2f()) );
-    CALL_SUBTEST_2( qr(Matrix4d()) );
-    CALL_SUBTEST_3( qr(MatrixXf(12,8)) );
-    CALL_SUBTEST_4( qr(MatrixXcd(5,5)) );
-    CALL_SUBTEST_4( qr(MatrixXcd(7,3)) );
-  }
-
-#ifdef EIGEN_TEST_PART_5
-  // small isFullRank test
-  {
-    Matrix3d mat;
-    mat << 1, 45, 1, 2, 2, 2, 1, 2, 3;
-    VERIFY(mat.qr().isFullRank());
-    mat << 1, 1, 1, 2, 2, 2, 1, 2, 3;
-    //always returns true in eigen2support
-    //VERIFY(!mat.qr().isFullRank());
-  }
-
-#endif
-}
diff --git a/test/eigen2/eigen2_qtvector.cpp b/test/eigen2/eigen2_qtvector.cpp
deleted file mode 100644
index 6cfb58a26..000000000
--- a/test/eigen2/eigen2_qtvector.cpp
+++ /dev/null
@@ -1,158 +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>
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@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/.
-
-#define EIGEN_WORK_AROUND_QT_BUG_CALLING_WRONG_OPERATOR_NEW_FIXED_IN_QT_4_5
-
-#include "main.h"
-
-#include <Eigen/Geometry>
-#include <Eigen/QtAlignedMalloc>
-
-#include <QtCore/QVector>
-
-template<typename MatrixType>
-void check_qtvector_matrix(const MatrixType& m)
-{
-  int rows = m.rows();
-  int cols = m.cols();
-  MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols);
-  QVector<MatrixType> v(10, MatrixType(rows,cols)), w(20, y);
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], y);
-  }
-  v[5] = x;
-  w[6] = v[5];
-  VERIFY_IS_APPROX(w[6], v[5]);
-  v = w;
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], v[i]);
-  }
-
-  v.resize(21);
-  v[20] = x;
-  VERIFY_IS_APPROX(v[20], x);
-  v.fill(y,22);
-  VERIFY_IS_APPROX(v[21], y);
-  v.push_back(x);
-  VERIFY_IS_APPROX(v[22], x);
-  VERIFY((size_t)&(v[22]) == (size_t)&(v[21]) + sizeof(MatrixType));
-
-  // do a lot of push_back such that the vector gets internally resized
-  // (with memory reallocation)
-  MatrixType* ref = &w[0];
-  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
-    v.push_back(w[i%w.size()]);
-  for(int i=23; i<v.size(); ++i)
-  {
-    VERIFY(v[i]==w[(i-23)%w.size()]);
-  }
-}
-
-template<typename TransformType>
-void check_qtvector_transform(const TransformType&)
-{
-  typedef typename TransformType::MatrixType MatrixType;
-  TransformType x(MatrixType::Random()), y(MatrixType::Random());
-  QVector<TransformType> v(10), w(20, y);
-  v[5] = x;
-  w[6] = v[5];
-  VERIFY_IS_APPROX(w[6], v[5]);
-  v = w;
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], v[i]);
-  }
-
-  v.resize(21);
-  v[20] = x;
-  VERIFY_IS_APPROX(v[20], x);
-  v.fill(y,22);
-  VERIFY_IS_APPROX(v[21], y);
-  v.push_back(x);
-  VERIFY_IS_APPROX(v[22], x);
-  VERIFY((size_t)&(v[22]) == (size_t)&(v[21]) + sizeof(TransformType));
-
-  // do a lot of push_back such that the vector gets internally resized
-  // (with memory reallocation)
-  TransformType* ref = &w[0];
-  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
-    v.push_back(w[i%w.size()]);
-  for(unsigned int i=23; int(i)<v.size(); ++i)
-  {
-    VERIFY(v[i].matrix()==w[(i-23)%w.size()].matrix());
-  }
-}
-
-template<typename QuaternionType>
-void check_qtvector_quaternion(const QuaternionType&)
-{
-  typedef typename QuaternionType::Coefficients Coefficients;
-  QuaternionType x(Coefficients::Random()), y(Coefficients::Random());
-  QVector<QuaternionType> v(10), w(20, y);
-  v[5] = x;
-  w[6] = v[5];
-  VERIFY_IS_APPROX(w[6], v[5]);
-  v = w;
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], v[i]);
-  }
-
-  v.resize(21);
-  v[20] = x;
-  VERIFY_IS_APPROX(v[20], x);
-  v.fill(y,22);
-  VERIFY_IS_APPROX(v[21], y);
-  v.push_back(x);
-  VERIFY_IS_APPROX(v[22], x);
-  VERIFY((size_t)&(v[22]) == (size_t)&(v[21]) + sizeof(QuaternionType));
-
-  // do a lot of push_back such that the vector gets internally resized
-  // (with memory reallocation)
-  QuaternionType* ref = &w[0];
-  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
-    v.push_back(w[i%w.size()]);
-  for(unsigned int i=23; int(i)<v.size(); ++i)
-  {
-    VERIFY(v[i].coeffs()==w[(i-23)%w.size()].coeffs());
-  }
-}
-
-void test_eigen2_qtvector()
-{
-  // some non vectorizable fixed sizes
-  CALL_SUBTEST_1(check_qtvector_matrix(Vector2f()));
-  CALL_SUBTEST_1(check_qtvector_matrix(Matrix3f()));
-  CALL_SUBTEST_1(check_qtvector_matrix(Matrix3d()));
-
-  // some vectorizable fixed sizes
-  CALL_SUBTEST_2(check_qtvector_matrix(Matrix2f()));
-  CALL_SUBTEST_2(check_qtvector_matrix(Vector4f()));
-  CALL_SUBTEST_2(check_qtvector_matrix(Matrix4f()));
-  CALL_SUBTEST_2(check_qtvector_matrix(Matrix4d()));
-
-  // some dynamic sizes
-  CALL_SUBTEST_3(check_qtvector_matrix(MatrixXd(1,1)));
-  CALL_SUBTEST_3(check_qtvector_matrix(VectorXd(20)));
-  CALL_SUBTEST_3(check_qtvector_matrix(RowVectorXf(20)));
-  CALL_SUBTEST_3(check_qtvector_matrix(MatrixXcf(10,10)));
-
-  // some Transform
-  CALL_SUBTEST_4(check_qtvector_transform(Transform2f()));
-  CALL_SUBTEST_4(check_qtvector_transform(Transform3f()));
-  CALL_SUBTEST_4(check_qtvector_transform(Transform3d()));
-  //CALL_SUBTEST_4(check_qtvector_transform(Transform4d()));
-
-  // some Quaternion
-  CALL_SUBTEST_5(check_qtvector_quaternion(Quaternionf()));
-  CALL_SUBTEST_5(check_qtvector_quaternion(Quaternionf()));
-}
diff --git a/test/eigen2/eigen2_regression.cpp b/test/eigen2/eigen2_regression.cpp
deleted file mode 100644
index c68b58da8..000000000
--- a/test/eigen2/eigen2_regression.cpp
+++ /dev/null
@@ -1,136 +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 Benoit Jacob <jacob.benoit.1@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 "main.h"
-#include <Eigen/LeastSquares>
-
-template<typename VectorType,
-         typename HyperplaneType>
-void makeNoisyCohyperplanarPoints(int numPoints,
-                                  VectorType **points,
-                                  HyperplaneType *hyperplane,
-                                  typename VectorType::Scalar noiseAmplitude)
-{
-  typedef typename VectorType::Scalar Scalar;
-  const int size = points[0]->size();
-  // pick a random hyperplane, store the coefficients of its equation
-  hyperplane->coeffs().resize(size + 1);
-  for(int j = 0; j < size + 1; j++)
-  {
-    do {
-      hyperplane->coeffs().coeffRef(j) = ei_random<Scalar>();
-    } while(ei_abs(hyperplane->coeffs().coeff(j)) < 0.5);
-  }
-
-  // now pick numPoints random points on this hyperplane
-  for(int i = 0; i < numPoints; i++)
-  {
-    VectorType& cur_point = *(points[i]);
-    do
-    {
-      cur_point = VectorType::Random(size)/*.normalized()*/;
-      // project cur_point onto the hyperplane
-      Scalar x = - (hyperplane->coeffs().start(size).cwise()*cur_point).sum();
-      cur_point *= hyperplane->coeffs().coeff(size) / x;
-    } while( cur_point.norm() < 0.5
-          || cur_point.norm() > 2.0 );
-  }
-
-  // add some noise to these points
-  for(int i = 0; i < numPoints; i++ )
-    *(points[i]) += noiseAmplitude * VectorType::Random(size);
-}
-
-template<typename VectorType>
-void check_linearRegression(int numPoints,
-                            VectorType **points,
-                            const VectorType& original,
-                            typename VectorType::Scalar tolerance)
-{
-  int size = points[0]->size();
-  assert(size==2);
-  VectorType result(size);
-  linearRegression(numPoints, points, &result, 1);
-  typename VectorType::Scalar error = (result - original).norm() / original.norm();
-  VERIFY(ei_abs(error) < ei_abs(tolerance));
-}
-
-template<typename VectorType,
-         typename HyperplaneType>
-void check_fitHyperplane(int numPoints,
-                         VectorType **points,
-                         const HyperplaneType& original,
-                         typename VectorType::Scalar tolerance)
-{
-  int size = points[0]->size();
-  HyperplaneType result(size);
-  fitHyperplane(numPoints, points, &result);
-  result.coeffs() *= original.coeffs().coeff(size)/result.coeffs().coeff(size);
-  typename VectorType::Scalar error = (result.coeffs() - original.coeffs()).norm() / original.coeffs().norm();
-  std::cout << ei_abs(error) << "  xxx   " << ei_abs(tolerance) << std::endl;
-  VERIFY(ei_abs(error) < ei_abs(tolerance));
-}
-
-void test_eigen2_regression()
-{
-  for(int i = 0; i < g_repeat; i++)
-  {
-#ifdef EIGEN_TEST_PART_1
-    {
-      Vector2f points2f [1000];
-      Vector2f *points2f_ptrs [1000];
-      for(int i = 0; i < 1000; i++) points2f_ptrs[i] = &(points2f[i]);
-      Vector2f coeffs2f;
-      Hyperplane<float,2> coeffs3f;
-      makeNoisyCohyperplanarPoints(1000, points2f_ptrs, &coeffs3f, 0.01f);
-      coeffs2f[0] = -coeffs3f.coeffs()[0]/coeffs3f.coeffs()[1];
-      coeffs2f[1] = -coeffs3f.coeffs()[2]/coeffs3f.coeffs()[1];
-      CALL_SUBTEST(check_linearRegression(10, points2f_ptrs, coeffs2f, 0.05f));
-      CALL_SUBTEST(check_linearRegression(100, points2f_ptrs, coeffs2f, 0.01f));
-      CALL_SUBTEST(check_linearRegression(1000, points2f_ptrs, coeffs2f, 0.002f));
-    }
-#endif
-#ifdef EIGEN_TEST_PART_2
-    {
-      Vector2f points2f [1000];
-      Vector2f *points2f_ptrs [1000];
-      for(int i = 0; i < 1000; i++) points2f_ptrs[i] = &(points2f[i]);
-      Hyperplane<float,2> coeffs3f;
-      makeNoisyCohyperplanarPoints(1000, points2f_ptrs, &coeffs3f, 0.01f);
-      CALL_SUBTEST(check_fitHyperplane(10, points2f_ptrs, coeffs3f, 0.05f));
-      CALL_SUBTEST(check_fitHyperplane(100, points2f_ptrs, coeffs3f, 0.01f));
-      CALL_SUBTEST(check_fitHyperplane(1000, points2f_ptrs, coeffs3f, 0.002f));
-    }
-#endif
-#ifdef EIGEN_TEST_PART_3
-    {
-      Vector4d points4d [1000];
-      Vector4d *points4d_ptrs [1000];
-      for(int i = 0; i < 1000; i++) points4d_ptrs[i] = &(points4d[i]);
-      Hyperplane<double,4> coeffs5d;
-      makeNoisyCohyperplanarPoints(1000, points4d_ptrs, &coeffs5d, 0.01);
-      CALL_SUBTEST(check_fitHyperplane(10, points4d_ptrs, coeffs5d, 0.05));
-      CALL_SUBTEST(check_fitHyperplane(100, points4d_ptrs, coeffs5d, 0.01));
-      CALL_SUBTEST(check_fitHyperplane(1000, points4d_ptrs, coeffs5d, 0.002));
-    }
-#endif
-#ifdef EIGEN_TEST_PART_4
-    {
-      VectorXcd *points11cd_ptrs[1000];
-      for(int i = 0; i < 1000; i++) points11cd_ptrs[i] = new VectorXcd(11);
-      Hyperplane<std::complex<double>,Dynamic> *coeffs12cd = new Hyperplane<std::complex<double>,Dynamic>(11);
-      makeNoisyCohyperplanarPoints(1000, points11cd_ptrs, coeffs12cd, 0.01);
-      CALL_SUBTEST(check_fitHyperplane(100, points11cd_ptrs, *coeffs12cd, 0.025));
-      CALL_SUBTEST(check_fitHyperplane(1000, points11cd_ptrs, *coeffs12cd, 0.006));
-      delete coeffs12cd;
-      for(int i = 0; i < 1000; i++) delete points11cd_ptrs[i];
-    }
-#endif
-  }
-}
diff --git a/test/eigen2/eigen2_sizeof.cpp b/test/eigen2/eigen2_sizeof.cpp
deleted file mode 100644
index ec1af5a06..000000000
--- a/test/eigen2/eigen2_sizeof.cpp
+++ /dev/null
@@ -1,31 +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"
-
-template<typename MatrixType> void verifySizeOf(const MatrixType&)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  if (MatrixType::RowsAtCompileTime!=Dynamic && MatrixType::ColsAtCompileTime!=Dynamic)
-    VERIFY(sizeof(MatrixType)==sizeof(Scalar)*MatrixType::SizeAtCompileTime);
-  else
-    VERIFY(sizeof(MatrixType)==sizeof(Scalar*) + 2 * sizeof(typename MatrixType::Index));
-}
-
-void test_eigen2_sizeof()
-{
-  CALL_SUBTEST( verifySizeOf(Matrix<float, 1, 1>()) );
-  CALL_SUBTEST( verifySizeOf(Matrix4d()) );
-  CALL_SUBTEST( verifySizeOf(Matrix<double, 4, 2>()) );
-  CALL_SUBTEST( verifySizeOf(Matrix<bool, 7, 5>()) );
-  CALL_SUBTEST( verifySizeOf(MatrixXcf(3, 3)) );
-  CALL_SUBTEST( verifySizeOf(MatrixXi(8, 12)) );
-  CALL_SUBTEST( verifySizeOf(MatrixXcd(20, 20)) );
-  CALL_SUBTEST( verifySizeOf(Matrix<float, 100, 100>()) );
-}
diff --git a/test/eigen2/eigen2_smallvectors.cpp b/test/eigen2/eigen2_smallvectors.cpp
deleted file mode 100644
index 03962b17d..000000000
--- a/test/eigen2/eigen2_smallvectors.cpp
+++ /dev/null
@@ -1,42 +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) 2006-2008 Benoit Jacob <jacob.benoit.1@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 "main.h"
-
-template<typename Scalar> void smallVectors()
-{
-  typedef Matrix<Scalar, 1, 2> V2;
-  typedef Matrix<Scalar, 3, 1> V3;
-  typedef Matrix<Scalar, 1, 4> V4;
-  Scalar x1 = ei_random<Scalar>(),
-         x2 = ei_random<Scalar>(),
-         x3 = ei_random<Scalar>(),
-         x4 = ei_random<Scalar>();
-  V2 v2(x1, x2);
-  V3 v3(x1, x2, x3);
-  V4 v4(x1, x2, x3, x4);
-  VERIFY_IS_APPROX(x1, v2.x());
-  VERIFY_IS_APPROX(x1, v3.x());
-  VERIFY_IS_APPROX(x1, v4.x());
-  VERIFY_IS_APPROX(x2, v2.y());
-  VERIFY_IS_APPROX(x2, v3.y());
-  VERIFY_IS_APPROX(x2, v4.y());
-  VERIFY_IS_APPROX(x3, v3.z());
-  VERIFY_IS_APPROX(x3, v4.z());
-  VERIFY_IS_APPROX(x4, v4.w());
-}
-
-void test_eigen2_smallvectors()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST( smallVectors<int>() );
-    CALL_SUBTEST( smallVectors<float>() );
-    CALL_SUBTEST( smallVectors<double>() );
-  }
-}
diff --git a/test/eigen2/eigen2_sparse_basic.cpp b/test/eigen2/eigen2_sparse_basic.cpp
deleted file mode 100644
index 049077670..000000000
--- a/test/eigen2/eigen2_sparse_basic.cpp
+++ /dev/null
@@ -1,317 +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 SetterType,typename DenseType, typename Scalar, int Options>
-bool test_random_setter(SparseMatrix<Scalar,Options>& sm, const DenseType& ref, const std::vector<Vector2i>& nonzeroCoords)
-{
-  typedef SparseMatrix<Scalar,Options> SparseType;
-  {
-    sm.setZero();
-    SetterType w(sm);
-    std::vector<Vector2i> remaining = nonzeroCoords;
-    while(!remaining.empty())
-    {
-      int i = ei_random<int>(0,remaining.size()-1);
-      w(remaining[i].x(),remaining[i].y()) = ref.coeff(remaining[i].x(),remaining[i].y());
-      remaining[i] = remaining.back();
-      remaining.pop_back();
-    }
-  }
-  return sm.isApprox(ref);
-}
-
-template<typename SetterType,typename DenseType, typename T>
-bool test_random_setter(DynamicSparseMatrix<T>& sm, const DenseType& ref, const std::vector<Vector2i>& nonzeroCoords)
-{
-  sm.setZero();
-  std::vector<Vector2i> remaining = nonzeroCoords;
-  while(!remaining.empty())
-  {
-    int i = ei_random<int>(0,remaining.size()-1);
-    sm.coeffRef(remaining[i].x(),remaining[i].y()) = ref.coeff(remaining[i].x(),remaining[i].y());
-    remaining[i] = remaining.back();
-    remaining.pop_back();
-  }
-  return sm.isApprox(ref);
-}
-
-template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& ref)
-{
-  const int rows = ref.rows();
-  const int cols = ref.cols();
-  typedef typename SparseMatrixType::Scalar Scalar;
-  enum { Flags = SparseMatrixType::Flags };
-  
-  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;
-
-  SparseMatrixType m(rows, cols);
-  DenseMatrix refMat = DenseMatrix::Zero(rows, cols);
-  DenseVector vec1 = DenseVector::Random(rows);
-  Scalar s1 = ei_random<Scalar>();
-
-  std::vector<Vector2i> zeroCoords;
-  std::vector<Vector2i> nonzeroCoords;
-  initSparse<Scalar>(density, refMat, m, 0, &zeroCoords, &nonzeroCoords);
-  
-  if (zeroCoords.size()==0 || nonzeroCoords.size()==0)
-    return;
-
-  // test coeff and coeffRef
-  for (int i=0; i<(int)zeroCoords.size(); ++i)
-  {
-    VERIFY_IS_MUCH_SMALLER_THAN( m.coeff(zeroCoords[i].x(),zeroCoords[i].y()), eps );
-    if(ei_is_same_type<SparseMatrixType,SparseMatrix<Scalar,Flags> >::ret)
-      VERIFY_RAISES_ASSERT( m.coeffRef(zeroCoords[0].x(),zeroCoords[0].y()) = 5 );
-  }
-  VERIFY_IS_APPROX(m, refMat);
-
-  m.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
-  refMat.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
-
-  VERIFY_IS_APPROX(m, refMat);
-  /*
-  // test InnerIterators and Block expressions
-  for (int t=0; t<10; ++t)
-  {
-    int j = ei_random<int>(0,cols-1);
-    int i = ei_random<int>(0,rows-1);
-    int w = ei_random<int>(1,cols-j-1);
-    int h = ei_random<int>(1,rows-i-1);
-
-//     VERIFY_IS_APPROX(m.block(i,j,h,w), refMat.block(i,j,h,w));
-    for(int c=0; c<w; c++)
-    {
-      VERIFY_IS_APPROX(m.block(i,j,h,w).col(c), refMat.block(i,j,h,w).col(c));
-      for(int r=0; r<h; r++)
-      {
-//         VERIFY_IS_APPROX(m.block(i,j,h,w).col(c).coeff(r), refMat.block(i,j,h,w).col(c).coeff(r));
-      }
-    }
-//     for(int r=0; r<h; r++)
-//     {
-//       VERIFY_IS_APPROX(m.block(i,j,h,w).row(r), refMat.block(i,j,h,w).row(r));
-//       for(int c=0; c<w; c++)
-//       {
-//         VERIFY_IS_APPROX(m.block(i,j,h,w).row(r).coeff(c), refMat.block(i,j,h,w).row(r).coeff(c));
-//       }
-//     }
-  }
-
-  for(int c=0; c<cols; c++)
-  {
-    VERIFY_IS_APPROX(m.col(c) + m.col(c), (m + m).col(c));
-    VERIFY_IS_APPROX(m.col(c) + m.col(c), refMat.col(c) + refMat.col(c));
-  }
-
-  for(int r=0; r<rows; r++)
-  {
-    VERIFY_IS_APPROX(m.row(r) + m.row(r), (m + m).row(r));
-    VERIFY_IS_APPROX(m.row(r) + m.row(r), refMat.row(r) + refMat.row(r));
-  }
-  */
-
-  // test SparseSetters
-  // coherent setter
-  // TODO extend the MatrixSetter
-//   {
-//     m.setZero();
-//     VERIFY_IS_NOT_APPROX(m, refMat);
-//     SparseSetter<SparseMatrixType, FullyCoherentAccessPattern> w(m);
-//     for (int i=0; i<nonzeroCoords.size(); ++i)
-//     {
-//       w->coeffRef(nonzeroCoords[i].x(),nonzeroCoords[i].y()) = refMat.coeff(nonzeroCoords[i].x(),nonzeroCoords[i].y());
-//     }
-//   }
-//   VERIFY_IS_APPROX(m, refMat);
-
-  // random setter
-//   {
-//     m.setZero();
-//     VERIFY_IS_NOT_APPROX(m, refMat);
-//     SparseSetter<SparseMatrixType, RandomAccessPattern> w(m);
-//     std::vector<Vector2i> remaining = nonzeroCoords;
-//     while(!remaining.empty())
-//     {
-//       int i = ei_random<int>(0,remaining.size()-1);
-//       w->coeffRef(remaining[i].x(),remaining[i].y()) = refMat.coeff(remaining[i].x(),remaining[i].y());
-//       remaining[i] = remaining.back();
-//       remaining.pop_back();
-//     }
-//   }
-//   VERIFY_IS_APPROX(m, refMat);
-
-    VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdMapTraits> >(m,refMat,nonzeroCoords) ));
-    #ifdef EIGEN_UNORDERED_MAP_SUPPORT
-    VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdUnorderedMapTraits> >(m,refMat,nonzeroCoords) ));
-    #endif
-    #ifdef _DENSE_HASH_MAP_H_
-    VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleDenseHashMapTraits> >(m,refMat,nonzeroCoords) ));
-    #endif
-    #ifdef _SPARSE_HASH_MAP_H_
-    VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleSparseHashMapTraits> >(m,refMat,nonzeroCoords) ));
-    #endif
-
-    // test fillrand
-    {
-      DenseMatrix m1(rows,cols);
-      m1.setZero();
-      SparseMatrixType m2(rows,cols);
-      m2.startFill();
-      for (int j=0; j<cols; ++j)
-      {
-        for (int k=0; k<rows/2; ++k)
-        {
-          int i = ei_random<int>(0,rows-1);
-          if (m1.coeff(i,j)==Scalar(0))
-            m2.fillrand(i,j) = m1(i,j) = ei_random<Scalar>();
-        }
-      }
-      m2.endFill();
-      VERIFY_IS_APPROX(m2,m1);
-    }
-  
-  // test RandomSetter
-  /*{
-    SparseMatrixType m1(rows,cols), m2(rows,cols);
-    DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
-    initSparse<Scalar>(density, refM1, m1);
-    {
-      Eigen::RandomSetter<SparseMatrixType > setter(m2);
-      for (int j=0; j<m1.outerSize(); ++j)
-        for (typename SparseMatrixType::InnerIterator i(m1,j); i; ++i)
-          setter(i.index(), j) = i.value();
-    }
-    VERIFY_IS_APPROX(m1, m2);
-  }*/
-//   std::cerr << m.transpose() << "\n\n"  << refMat.transpose() << "\n\n";
-//   VERIFY_IS_APPROX(m, refMat);
-
-  // test basic computations
-  {
-    DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refM2 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refM3 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refM4 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m1(rows, rows);
-    SparseMatrixType m2(rows, rows);
-    SparseMatrixType m3(rows, rows);
-    SparseMatrixType m4(rows, rows);
-    initSparse<Scalar>(density, refM1, m1);
-    initSparse<Scalar>(density, refM2, m2);
-    initSparse<Scalar>(density, refM3, m3);
-    initSparse<Scalar>(density, refM4, m4);
-
-    VERIFY_IS_APPROX(m1+m2, refM1+refM2);
-    VERIFY_IS_APPROX(m1+m2+m3, refM1+refM2+refM3);
-    VERIFY_IS_APPROX(m3.cwise()*(m1+m2), refM3.cwise()*(refM1+refM2));
-    VERIFY_IS_APPROX(m1*s1-m2, refM1*s1-refM2);
-
-    VERIFY_IS_APPROX(m1*=s1, refM1*=s1);
-    VERIFY_IS_APPROX(m1/=s1, refM1/=s1);
-    
-    VERIFY_IS_APPROX(m1+=m2, refM1+=refM2);
-    VERIFY_IS_APPROX(m1-=m2, refM1-=refM2);
-    
-    VERIFY_IS_APPROX(m1.col(0).eigen2_dot(refM2.row(0)), refM1.col(0).eigen2_dot(refM2.row(0)));
-    
-    refM4.setRandom();
-    // sparse cwise* dense
-    VERIFY_IS_APPROX(m3.cwise()*refM4, refM3.cwise()*refM4);
-//     VERIFY_IS_APPROX(m3.cwise()/refM4, refM3.cwise()/refM4);
-  }
-
-  // test innerVector()
-  {
-    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m2(rows, rows);
-    initSparse<Scalar>(density, refMat2, m2);
-    int j0 = ei_random(0,rows-1);
-    int j1 = ei_random(0,rows-1);
-    VERIFY_IS_APPROX(m2.innerVector(j0), refMat2.col(j0));
-    VERIFY_IS_APPROX(m2.innerVector(j0)+m2.innerVector(j1), refMat2.col(j0)+refMat2.col(j1));
-    //m2.innerVector(j0) = 2*m2.innerVector(j1);
-    //refMat2.col(j0) = 2*refMat2.col(j1);
-    //VERIFY_IS_APPROX(m2, refMat2);
-  }
-  
-  // test innerVectors()
-  {
-    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m2(rows, rows);
-    initSparse<Scalar>(density, refMat2, m2);
-    int j0 = ei_random(0,rows-2);
-    int j1 = ei_random(0,rows-2);
-    int n0 = ei_random<int>(1,rows-std::max(j0,j1));
-    VERIFY_IS_APPROX(m2.innerVectors(j0,n0), refMat2.block(0,j0,rows,n0));
-    VERIFY_IS_APPROX(m2.innerVectors(j0,n0)+m2.innerVectors(j1,n0),
-                     refMat2.block(0,j0,rows,n0)+refMat2.block(0,j1,rows,n0));
-    //m2.innerVectors(j0,n0) = m2.innerVectors(j0,n0) + m2.innerVectors(j1,n0);
-    //refMat2.block(0,j0,rows,n0) = refMat2.block(0,j0,rows,n0) + refMat2.block(0,j1,rows,n0);
-  }
-
-  // test transpose
-  {
-    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m2(rows, rows);
-    initSparse<Scalar>(density, refMat2, m2);
-    VERIFY_IS_APPROX(m2.transpose().eval(), refMat2.transpose().eval());
-    VERIFY_IS_APPROX(m2.transpose(), refMat2.transpose());
-  }
-  
-  // test prune
-  {
-    SparseMatrixType m2(rows, rows);
-    DenseMatrix refM2(rows, rows);
-    refM2.setZero();
-    int countFalseNonZero = 0;
-    int countTrueNonZero = 0;
-    m2.startFill();
-    for (int j=0; j<m2.outerSize(); ++j)
-      for (int i=0; i<m2.innerSize(); ++i)
-      {
-        float x = ei_random<float>(0,1);
-        if (x<0.1)
-        {
-          // do nothing
-        }
-        else if (x<0.5)
-        {
-          countFalseNonZero++;
-          m2.fill(i,j) = Scalar(0);
-        }
-        else
-        {
-          countTrueNonZero++;
-          m2.fill(i,j) = refM2(i,j) = Scalar(1);
-        }
-      }
-    m2.endFill();
-    VERIFY(countFalseNonZero+countTrueNonZero == m2.nonZeros());
-    VERIFY_IS_APPROX(m2, refM2);
-    m2.prune(1);
-    VERIFY(countTrueNonZero==m2.nonZeros());
-    VERIFY_IS_APPROX(m2, refM2);
-  }
-}
-
-void test_eigen2_sparse_basic()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( sparse_basic(SparseMatrix<double>(8, 8)) );
-    CALL_SUBTEST_2( sparse_basic(SparseMatrix<std::complex<double> >(16, 16)) );
-    CALL_SUBTEST_1( sparse_basic(SparseMatrix<double>(33, 33)) );
-    
-    CALL_SUBTEST_3( sparse_basic(DynamicSparseMatrix<double>(8, 8)) );
-  }
-}
diff --git a/test/eigen2/eigen2_sparse_product.cpp b/test/eigen2/eigen2_sparse_product.cpp
deleted file mode 100644
index d28e76dff..000000000
--- a/test/eigen2/eigen2_sparse_product.cpp
+++ /dev/null
@@ -1,115 +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 SparseMatrixType> void sparse_product(const SparseMatrixType& ref)
-{
-  const int rows = ref.rows();
-  const int cols = ref.cols();
-  typedef typename SparseMatrixType::Scalar Scalar;
-  enum { Flags = SparseMatrixType::Flags };
-
-  double density = std::max(8./(rows*cols), 0.01);
-  typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
-  typedef Matrix<Scalar,Dynamic,1> DenseVector;
-
-  // test matrix-matrix product
-  {
-    DenseMatrix refMat2 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refMat3 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refMat4 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix dm4 = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType m2(rows, rows);
-    SparseMatrixType m3(rows, rows);
-    SparseMatrixType m4(rows, rows);
-    initSparse<Scalar>(density, refMat2, m2);
-    initSparse<Scalar>(density, refMat3, m3);
-    initSparse<Scalar>(density, refMat4, m4);
-    VERIFY_IS_APPROX(m4=m2*m3, refMat4=refMat2*refMat3);
-    VERIFY_IS_APPROX(m4=m2.transpose()*m3, refMat4=refMat2.transpose()*refMat3);
-    VERIFY_IS_APPROX(m4=m2.transpose()*m3.transpose(), refMat4=refMat2.transpose()*refMat3.transpose());
-    VERIFY_IS_APPROX(m4=m2*m3.transpose(), refMat4=refMat2*refMat3.transpose());
-
-    // sparse * dense
-    VERIFY_IS_APPROX(dm4=m2*refMat3, refMat4=refMat2*refMat3);
-    VERIFY_IS_APPROX(dm4=m2*refMat3.transpose(), refMat4=refMat2*refMat3.transpose());
-    VERIFY_IS_APPROX(dm4=m2.transpose()*refMat3, refMat4=refMat2.transpose()*refMat3);
-    VERIFY_IS_APPROX(dm4=m2.transpose()*refMat3.transpose(), refMat4=refMat2.transpose()*refMat3.transpose());
-
-    // dense * sparse
-    VERIFY_IS_APPROX(dm4=refMat2*m3, refMat4=refMat2*refMat3);
-    VERIFY_IS_APPROX(dm4=refMat2*m3.transpose(), refMat4=refMat2*refMat3.transpose());
-    VERIFY_IS_APPROX(dm4=refMat2.transpose()*m3, refMat4=refMat2.transpose()*refMat3);
-    VERIFY_IS_APPROX(dm4=refMat2.transpose()*m3.transpose(), refMat4=refMat2.transpose()*refMat3.transpose());
-
-    VERIFY_IS_APPROX(m3=m3*m3, refMat3=refMat3*refMat3);
-  }
-
-  // test matrix - diagonal product
-  if(false) // it compiles, but the precision is terrible. probably doesn't matter in this branch....
-  {
-    DenseMatrix refM2 = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refM3 = DenseMatrix::Zero(rows, rows);
-    DiagonalMatrix<DenseVector> d1(DenseVector::Random(rows));
-    SparseMatrixType m2(rows, rows);
-    SparseMatrixType m3(rows, rows);
-    initSparse<Scalar>(density, refM2, m2);
-    initSparse<Scalar>(density, refM3, m3);
-    VERIFY_IS_APPROX(m3=m2*d1, refM3=refM2*d1);
-    VERIFY_IS_APPROX(m3=m2.transpose()*d1, refM3=refM2.transpose()*d1);
-    VERIFY_IS_APPROX(m3=d1*m2, refM3=d1*refM2);
-    VERIFY_IS_APPROX(m3=d1*m2.transpose(), refM3=d1 * refM2.transpose());
-  }
-
-  // test self adjoint products
-  {
-    DenseMatrix b = DenseMatrix::Random(rows, rows);
-    DenseMatrix x = DenseMatrix::Random(rows, rows);
-    DenseMatrix refX = DenseMatrix::Random(rows, rows);
-    DenseMatrix refUp = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refLo = DenseMatrix::Zero(rows, rows);
-    DenseMatrix refS = DenseMatrix::Zero(rows, rows);
-    SparseMatrixType mUp(rows, rows);
-    SparseMatrixType mLo(rows, rows);
-    SparseMatrixType mS(rows, rows);
-    do {
-      initSparse<Scalar>(density, refUp, mUp, ForceRealDiag|/*ForceNonZeroDiag|*/MakeUpperTriangular);
-    } while (refUp.isZero());
-    refLo = refUp.transpose().conjugate();
-    mLo = mUp.transpose().conjugate();
-    refS = refUp + refLo;
-    refS.diagonal() *= 0.5;
-    mS = mUp + mLo;
-    for (int k=0; k<mS.outerSize(); ++k)
-      for (typename SparseMatrixType::InnerIterator it(mS,k); it; ++it)
-        if (it.index() == k)
-          it.valueRef() *= 0.5;
-
-    VERIFY_IS_APPROX(refS.adjoint(), refS);
-    VERIFY_IS_APPROX(mS.transpose().conjugate(), mS);
-    VERIFY_IS_APPROX(mS, refS);
-    VERIFY_IS_APPROX(x=mS*b, refX=refS*b);
-    VERIFY_IS_APPROX(x=mUp.template marked<UpperTriangular|SelfAdjoint>()*b, refX=refS*b);
-    VERIFY_IS_APPROX(x=mLo.template marked<LowerTriangular|SelfAdjoint>()*b, refX=refS*b);
-    VERIFY_IS_APPROX(x=mS.template marked<SelfAdjoint>()*b, refX=refS*b);
-  }
-
-}
-
-void test_eigen2_sparse_product()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( sparse_product(SparseMatrix<double>(8, 8)) );
-    CALL_SUBTEST_2( sparse_product(SparseMatrix<std::complex<double> >(16, 16)) );
-    CALL_SUBTEST_1( sparse_product(SparseMatrix<double>(33, 33)) );
-
-    CALL_SUBTEST_3( sparse_product(DynamicSparseMatrix<double>(8, 8)) );
-  }
-}
diff --git a/test/eigen2/eigen2_sparse_solvers.cpp b/test/eigen2/eigen2_sparse_solvers.cpp
deleted file mode 100644
index 3aef27ab4..000000000
--- a/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) );
-  }
-}
diff --git a/test/eigen2/eigen2_sparse_vector.cpp b/test/eigen2/eigen2_sparse_vector.cpp
deleted file mode 100644
index e6d2d77a1..000000000
--- a/test/eigen2/eigen2_sparse_vector.cpp
+++ /dev/null
@@ -1,84 +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 sparse_vector(int rows, int cols)
-{
-  double densityMat = std::max(8./(rows*cols), 0.01);
-  double densityVec = std::max(8./float(rows), 0.1);
-  typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
-  typedef Matrix<Scalar,Dynamic,1> DenseVector;
-  typedef SparseVector<Scalar> SparseVectorType;
-  typedef SparseMatrix<Scalar> SparseMatrixType;
-  Scalar eps = 1e-6;
-
-  SparseMatrixType m1(rows,cols);
-  SparseVectorType v1(rows), v2(rows), v3(rows);
-  DenseMatrix refM1 = DenseMatrix::Zero(rows, cols);
-  DenseVector refV1 = DenseVector::Random(rows),
-    refV2 = DenseVector::Random(rows),
-    refV3 = DenseVector::Random(rows);
-
-  std::vector<int> zerocoords, nonzerocoords;
-  initSparse<Scalar>(densityVec, refV1, v1, &zerocoords, &nonzerocoords);
-  initSparse<Scalar>(densityMat, refM1, m1);
-
-  initSparse<Scalar>(densityVec, refV2, v2);
-  initSparse<Scalar>(densityVec, refV3, v3);
-
-  Scalar s1 = ei_random<Scalar>();
-
-  // test coeff and coeffRef
-  for (unsigned int i=0; i<zerocoords.size(); ++i)
-  {
-    VERIFY_IS_MUCH_SMALLER_THAN( v1.coeff(zerocoords[i]), eps );
-    //VERIFY_RAISES_ASSERT( v1.coeffRef(zerocoords[i]) = 5 );
-  }
-  {
-    VERIFY(int(nonzerocoords.size()) == v1.nonZeros());
-    int j=0;
-    for (typename SparseVectorType::InnerIterator it(v1); it; ++it,++j)
-    {
-      VERIFY(nonzerocoords[j]==it.index());
-      VERIFY(it.value()==v1.coeff(it.index()));
-      VERIFY(it.value()==refV1.coeff(it.index()));
-    }
-  }
-  VERIFY_IS_APPROX(v1, refV1);
-
-  v1.coeffRef(nonzerocoords[0]) = Scalar(5);
-  refV1.coeffRef(nonzerocoords[0]) = Scalar(5);
-  VERIFY_IS_APPROX(v1, refV1);
-
-  VERIFY_IS_APPROX(v1+v2, refV1+refV2);
-  VERIFY_IS_APPROX(v1+v2+v3, refV1+refV2+refV3);
-
-  VERIFY_IS_APPROX(v1*s1-v2, refV1*s1-refV2);
-
-  VERIFY_IS_APPROX(v1*=s1, refV1*=s1);
-  VERIFY_IS_APPROX(v1/=s1, refV1/=s1);
-  
-  VERIFY_IS_APPROX(v1+=v2, refV1+=refV2);
-  VERIFY_IS_APPROX(v1-=v2, refV1-=refV2);
-
-  VERIFY_IS_APPROX(v1.eigen2_dot(v2), refV1.eigen2_dot(refV2));
-  VERIFY_IS_APPROX(v1.eigen2_dot(refV2), refV1.eigen2_dot(refV2));
-
-}
-
-void test_eigen2_sparse_vector()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( sparse_vector<double>(8, 8) );
-    CALL_SUBTEST_2( sparse_vector<std::complex<double> >(16, 16) );
-    CALL_SUBTEST_1( sparse_vector<double>(299, 535) );
-  }
-}
-
diff --git a/test/eigen2/eigen2_stdvector.cpp b/test/eigen2/eigen2_stdvector.cpp
deleted file mode 100644
index 6ab05c20a..000000000
--- a/test/eigen2/eigen2_stdvector.cpp
+++ /dev/null
@@ -1,148 +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 Benoit Jacob <jacob.benoit.1@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 <Eigen/StdVector>
-#include "main.h"
-#include <Eigen/Geometry>
-
-template<typename MatrixType>
-void check_stdvector_matrix(const MatrixType& m)
-{
-  int rows = m.rows();
-  int cols = m.cols();
-  MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols);
-  std::vector<MatrixType, aligned_allocator<MatrixType> > v(10, MatrixType(rows,cols)), w(20, y);
-  v[5] = x;
-  w[6] = v[5];
-  VERIFY_IS_APPROX(w[6], v[5]);
-  v = w;
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], v[i]);
-  }
-
-  v.resize(21);
-  v[20] = x;
-  VERIFY_IS_APPROX(v[20], x);
-  v.resize(22,y);
-  VERIFY_IS_APPROX(v[21], y);
-  v.push_back(x);
-  VERIFY_IS_APPROX(v[22], x);
-  VERIFY((std::size_t)&(v[22]) == (std::size_t)&(v[21]) + sizeof(MatrixType));
-
-  // do a lot of push_back such that the vector gets internally resized
-  // (with memory reallocation)
-  MatrixType* ref = &w[0];
-  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
-    v.push_back(w[i%w.size()]);
-  for(unsigned int i=23; i<v.size(); ++i)
-  {
-    VERIFY(v[i]==w[(i-23)%w.size()]);
-  }
-}
-
-template<typename TransformType>
-void check_stdvector_transform(const TransformType&)
-{
-  typedef typename TransformType::MatrixType MatrixType;
-  TransformType x(MatrixType::Random()), y(MatrixType::Random());
-  std::vector<TransformType, aligned_allocator<TransformType> > v(10), w(20, y);
-  v[5] = x;
-  w[6] = v[5];
-  VERIFY_IS_APPROX(w[6], v[5]);
-  v = w;
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], v[i]);
-  }
-
-  v.resize(21);
-  v[20] = x;
-  VERIFY_IS_APPROX(v[20], x);
-  v.resize(22,y);
-  VERIFY_IS_APPROX(v[21], y);
-  v.push_back(x);
-  VERIFY_IS_APPROX(v[22], x);
-  VERIFY((std::size_t)&(v[22]) == (std::size_t)&(v[21]) + sizeof(TransformType));
-
-  // do a lot of push_back such that the vector gets internally resized
-  // (with memory reallocation)
-  TransformType* ref = &w[0];
-  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
-    v.push_back(w[i%w.size()]);
-  for(unsigned int i=23; i<v.size(); ++i)
-  {
-    VERIFY(v[i].matrix()==w[(i-23)%w.size()].matrix());
-  }
-}
-
-template<typename QuaternionType>
-void check_stdvector_quaternion(const QuaternionType&)
-{
-  typedef typename QuaternionType::Coefficients Coefficients;
-  QuaternionType x(Coefficients::Random()), y(Coefficients::Random());
-  std::vector<QuaternionType, aligned_allocator<QuaternionType> > v(10), w(20, y);
-  v[5] = x;
-  w[6] = v[5];
-  VERIFY_IS_APPROX(w[6], v[5]);
-  v = w;
-  for(int i = 0; i < 20; i++)
-  {
-    VERIFY_IS_APPROX(w[i], v[i]);
-  }
-
-  v.resize(21);
-  v[20] = x;
-  VERIFY_IS_APPROX(v[20], x);
-  v.resize(22,y);
-  VERIFY_IS_APPROX(v[21], y);
-  v.push_back(x);
-  VERIFY_IS_APPROX(v[22], x);
-  VERIFY((std::size_t)&(v[22]) == (std::size_t)&(v[21]) + sizeof(QuaternionType));
-
-  // do a lot of push_back such that the vector gets internally resized
-  // (with memory reallocation)
-  QuaternionType* ref = &w[0];
-  for(int i=0; i<30 || ((ref==&w[0]) && i<300); ++i)
-    v.push_back(w[i%w.size()]);
-  for(unsigned int i=23; i<v.size(); ++i)
-  {
-    VERIFY(v[i].coeffs()==w[(i-23)%w.size()].coeffs());
-  }
-}
-
-void test_eigen2_stdvector()
-{
-  // some non vectorizable fixed sizes
-  CALL_SUBTEST_1(check_stdvector_matrix(Vector2f()));
-  CALL_SUBTEST_1(check_stdvector_matrix(Matrix3f()));
-  CALL_SUBTEST_1(check_stdvector_matrix(Matrix3d()));
-
-  // some vectorizable fixed sizes
-  CALL_SUBTEST_2(check_stdvector_matrix(Matrix2f()));
-  CALL_SUBTEST_2(check_stdvector_matrix(Vector4f()));
-  CALL_SUBTEST_2(check_stdvector_matrix(Matrix4f()));
-  CALL_SUBTEST_2(check_stdvector_matrix(Matrix4d()));
-
-  // some dynamic sizes
-  CALL_SUBTEST_3(check_stdvector_matrix(MatrixXd(1,1)));
-  CALL_SUBTEST_3(check_stdvector_matrix(VectorXd(20)));
-  CALL_SUBTEST_3(check_stdvector_matrix(RowVectorXf(20)));
-  CALL_SUBTEST_3(check_stdvector_matrix(MatrixXcf(10,10)));
-
-  // some Transform
-  CALL_SUBTEST_4(check_stdvector_transform(Transform2f()));
-  CALL_SUBTEST_4(check_stdvector_transform(Transform3f()));
-  CALL_SUBTEST_4(check_stdvector_transform(Transform3d()));
-  //CALL_SUBTEST_4(check_stdvector_transform(Transform4d()));
-
-  // some Quaternion
-  CALL_SUBTEST_5(check_stdvector_quaternion(Quaternionf()));
-  CALL_SUBTEST_5(check_stdvector_quaternion(Quaternionf()));
-}
diff --git a/test/eigen2/eigen2_submatrices.cpp b/test/eigen2/eigen2_submatrices.cpp
deleted file mode 100644
index c5d3f243d..000000000
--- a/test/eigen2/eigen2_submatrices.cpp
+++ /dev/null
@@ -1,148 +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) 2006-2008 Benoit Jacob <jacob.benoit.1@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 "main.h"
-
-// check minor separately in order to avoid the possible creation of a zero-sized
-// array. Comes from a compilation error with gcc-3.4 or gcc-4 with -ansi -pedantic.
-// Another solution would be to declare the array like this: T m_data[Size==0?1:Size]; in ei_matrix_storage
-// but this is probably not bad to raise such an error at compile time...
-template<typename Scalar, int _Rows, int _Cols> struct CheckMinor
-{
-    typedef Matrix<Scalar, _Rows, _Cols> MatrixType;
-    CheckMinor(MatrixType& m1, int r1, int c1)
-    {
-        int rows = m1.rows();
-        int cols = m1.cols();
-
-        Matrix<Scalar, Dynamic, Dynamic> mi = m1.minor(0,0).eval();
-        VERIFY_IS_APPROX(mi, m1.block(1,1,rows-1,cols-1));
-        mi = m1.minor(r1,c1);
-        VERIFY_IS_APPROX(mi.transpose(), m1.transpose().minor(c1,r1));
-        //check operator(), both constant and non-constant, on minor()
-        m1.minor(r1,c1)(0,0) = m1.minor(0,0)(0,0);
-    }
-};
-
-template<typename Scalar> struct CheckMinor<Scalar,1,1>
-{
-    typedef Matrix<Scalar, 1, 1> MatrixType;
-    CheckMinor(MatrixType&, int, int) {}
-};
-
-template<typename MatrixType> void submatrices(const MatrixType& m)
-{
-  /* this test covers the following files:
-     Row.h Column.h Block.h Minor.h DiagonalCoeffs.h
-  */
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::RealScalar RealScalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-  typedef Matrix<Scalar, 1, MatrixType::ColsAtCompileTime> RowVectorType;
-  int rows = m.rows();
-  int cols = m.cols();
-
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols),
-             mzero = MatrixType::Zero(rows, cols),
-             ones = MatrixType::Ones(rows, cols),
-             identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
-                              ::Identity(rows, rows),
-             square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
-                              ::Random(rows, rows);
-  VectorType v1 = VectorType::Random(rows),
-             v2 = VectorType::Random(rows),
-             v3 = VectorType::Random(rows),
-             vzero = VectorType::Zero(rows);
-
-  Scalar s1 = ei_random<Scalar>();
-
-  int r1 = ei_random<int>(0,rows-1);
-  int r2 = ei_random<int>(r1,rows-1);
-  int c1 = ei_random<int>(0,cols-1);
-  int c2 = ei_random<int>(c1,cols-1);
-
-  //check row() and col()
-  VERIFY_IS_APPROX(m1.col(c1).transpose(), m1.transpose().row(c1));
-  VERIFY_IS_APPROX(square.row(r1).eigen2_dot(m1.col(c1)), (square.lazy() * m1.conjugate())(r1,c1));
-  //check operator(), both constant and non-constant, on row() and col()
-  m1.row(r1) += s1 * m1.row(r2);
-  m1.col(c1) += s1 * m1.col(c2);
-
-  //check block()
-  Matrix<Scalar,Dynamic,Dynamic> b1(1,1); b1(0,0) = m1(r1,c1);
-  RowVectorType br1(m1.block(r1,0,1,cols));
-  VectorType bc1(m1.block(0,c1,rows,1));
-  VERIFY_IS_APPROX(b1, m1.block(r1,c1,1,1));
-  VERIFY_IS_APPROX(m1.row(r1), br1);
-  VERIFY_IS_APPROX(m1.col(c1), bc1);
-  //check operator(), both constant and non-constant, on block()
-  m1.block(r1,c1,r2-r1+1,c2-c1+1) = s1 * m2.block(0, 0, r2-r1+1,c2-c1+1);
-  m1.block(r1,c1,r2-r1+1,c2-c1+1)(r2-r1,c2-c1) = m2.block(0, 0, r2-r1+1,c2-c1+1)(0,0);
-
-  //check minor()
-  CheckMinor<Scalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime> checkminor(m1,r1,c1);
-
-  //check diagonal()
-  VERIFY_IS_APPROX(m1.diagonal(), m1.transpose().diagonal());
-  m2.diagonal() = 2 * m1.diagonal();
-  m2.diagonal()[0] *= 3;
-  VERIFY_IS_APPROX(m2.diagonal()[0], static_cast<Scalar>(6) * m1.diagonal()[0]);
-
-  enum {
-    BlockRows = EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::RowsAtCompileTime,2),
-    BlockCols = EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::ColsAtCompileTime,5)
-  };
-  if (rows>=5 && cols>=8)
-  {
-    // test fixed block() as lvalue
-    m1.template block<BlockRows,BlockCols>(1,1) *= s1;
-    // test operator() on fixed block() both as constant and non-constant
-    m1.template block<BlockRows,BlockCols>(1,1)(0, 3) = m1.template block<2,5>(1,1)(1,2);
-    // check that fixed block() and block() agree
-    Matrix<Scalar,Dynamic,Dynamic> b = m1.template block<BlockRows,BlockCols>(3,3);
-    VERIFY_IS_APPROX(b, m1.block(3,3,BlockRows,BlockCols));
-  }
-
-  if (rows>2)
-  {
-    // test sub vectors
-    VERIFY_IS_APPROX(v1.template start<2>(), v1.block(0,0,2,1));
-    VERIFY_IS_APPROX(v1.template start<2>(), v1.start(2));
-    VERIFY_IS_APPROX(v1.template start<2>(), v1.segment(0,2));
-    VERIFY_IS_APPROX(v1.template start<2>(), v1.template segment<2>(0));
-    int i = rows-2;
-    VERIFY_IS_APPROX(v1.template end<2>(), v1.block(i,0,2,1));
-    VERIFY_IS_APPROX(v1.template end<2>(), v1.end(2));
-    VERIFY_IS_APPROX(v1.template end<2>(), v1.segment(i,2));
-    VERIFY_IS_APPROX(v1.template end<2>(), v1.template segment<2>(i));
-    i = ei_random(0,rows-2);
-    VERIFY_IS_APPROX(v1.segment(i,2), v1.template segment<2>(i));
-  }
-
-  // stress some basic stuffs with block matrices
-  VERIFY(ei_real(ones.col(c1).sum()) == RealScalar(rows));
-  VERIFY(ei_real(ones.row(r1).sum()) == RealScalar(cols));
-
-  VERIFY(ei_real(ones.col(c1).eigen2_dot(ones.col(c2))) == RealScalar(rows));
-  VERIFY(ei_real(ones.row(r1).eigen2_dot(ones.row(r2))) == RealScalar(cols));
-}
-
-void test_eigen2_submatrices()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( submatrices(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( submatrices(Matrix4d()) );
-    CALL_SUBTEST_3( submatrices(MatrixXcf(3, 3)) );
-    CALL_SUBTEST_4( submatrices(MatrixXi(8, 12)) );
-    CALL_SUBTEST_5( submatrices(MatrixXcd(20, 20)) );
-    CALL_SUBTEST_6( submatrices(MatrixXf(20, 20)) );
-  }
-}
diff --git a/test/eigen2/eigen2_sum.cpp b/test/eigen2/eigen2_sum.cpp
deleted file mode 100644
index b47057caa..000000000
--- a/test/eigen2/eigen2_sum.cpp
+++ /dev/null
@@ -1,71 +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 Benoit Jacob <jacob.benoit.1@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 "main.h"
-
-template<typename MatrixType> void matrixSum(const MatrixType& m)
-{
-  typedef typename MatrixType::Scalar Scalar;
-
-  int rows = m.rows();
-  int cols = m.cols();
-
-  MatrixType m1 = MatrixType::Random(rows, cols);
-
-  VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::Zero(rows, cols).sum(), Scalar(1));
-  VERIFY_IS_APPROX(MatrixType::Ones(rows, cols).sum(), Scalar(float(rows*cols))); // the float() here to shut up excessive MSVC warning about int->complex conversion being lossy
-  Scalar x = Scalar(0);
-  for(int i = 0; i < rows; i++) for(int j = 0; j < cols; j++) x += m1(i,j);
-  VERIFY_IS_APPROX(m1.sum(), x);
-}
-
-template<typename VectorType> void vectorSum(const VectorType& w)
-{
-  typedef typename VectorType::Scalar Scalar;
-  int size = w.size();
-
-  VectorType v = VectorType::Random(size);
-  for(int i = 1; i < size; i++)
-  {
-    Scalar s = Scalar(0);
-    for(int j = 0; j < i; j++) s += v[j];
-    VERIFY_IS_APPROX(s, v.start(i).sum());
-  }
-
-  for(int i = 0; i < size-1; i++)
-  {
-    Scalar s = Scalar(0);
-    for(int j = i; j < size; j++) s += v[j];
-    VERIFY_IS_APPROX(s, v.end(size-i).sum());
-  }
-
-  for(int i = 0; i < size/2; i++)
-  {
-    Scalar s = Scalar(0);
-    for(int j = i; j < size-i; j++) s += v[j];
-    VERIFY_IS_APPROX(s, v.segment(i, size-2*i).sum());
-  }
-}
-
-void test_eigen2_sum()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( matrixSum(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( matrixSum(Matrix2f()) );
-    CALL_SUBTEST_3( matrixSum(Matrix4d()) );
-    CALL_SUBTEST_4( matrixSum(MatrixXcf(3, 3)) );
-    CALL_SUBTEST_5( matrixSum(MatrixXf(8, 12)) );
-    CALL_SUBTEST_6( matrixSum(MatrixXi(8, 12)) );
-  }
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_5( vectorSum(VectorXf(5)) );
-    CALL_SUBTEST_7( vectorSum(VectorXd(10)) );
-    CALL_SUBTEST_5( vectorSum(VectorXf(33)) );
-  }
-}
diff --git a/test/eigen2/eigen2_svd.cpp b/test/eigen2/eigen2_svd.cpp
deleted file mode 100644
index d4689a56f..000000000
--- a/test/eigen2/eigen2_svd.cpp
+++ /dev/null
@@ -1,87 +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/SVD>
-
-template<typename MatrixType> void svd(const MatrixType& m)
-{
-  /* this test covers the following files:
-     SVD.h
-  */
-  int rows = m.rows();
-  int cols = m.cols();
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  MatrixType a = MatrixType::Random(rows,cols);
-  Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> b =
-    Matrix<Scalar, MatrixType::RowsAtCompileTime, 1>::Random(rows,1);
-  Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> x(cols,1), x2(cols,1);
-
-  RealScalar largerEps = test_precision<RealScalar>();
-  if (ei_is_same_type<RealScalar,float>::ret)
-    largerEps = 1e-3f;
-
-  {
-    SVD<MatrixType> svd(a);
-    MatrixType sigma = MatrixType::Zero(rows,cols);
-    MatrixType matU  = MatrixType::Zero(rows,rows);
-    sigma.block(0,0,cols,cols) = svd.singularValues().asDiagonal();
-    matU.block(0,0,rows,cols) = svd.matrixU();
-    VERIFY_IS_APPROX(a, matU * sigma * svd.matrixV().transpose());
-  }
-
-
-  if (rows==cols)
-  {
-    if (ei_is_same_type<RealScalar,float>::ret)
-    {
-      MatrixType a1 = MatrixType::Random(rows,cols);
-      a += a * a.adjoint() + a1 * a1.adjoint();
-    }
-    SVD<MatrixType> svd(a);
-    svd.solve(b, &x);
-    VERIFY_IS_APPROX(a * x,b);
-  }
-
-
-  if(rows==cols)
-  {
-    SVD<MatrixType> svd(a);
-    MatrixType unitary, positive;
-    svd.computeUnitaryPositive(&unitary, &positive);
-    VERIFY_IS_APPROX(unitary * unitary.adjoint(), MatrixType::Identity(unitary.rows(),unitary.rows()));
-    VERIFY_IS_APPROX(positive, positive.adjoint());
-    for(int i = 0; i < rows; i++) VERIFY(positive.diagonal()[i] >= 0); // cheap necessary (not sufficient) condition for positivity
-    VERIFY_IS_APPROX(unitary*positive, a);
-
-    svd.computePositiveUnitary(&positive, &unitary);
-    VERIFY_IS_APPROX(unitary * unitary.adjoint(), MatrixType::Identity(unitary.rows(),unitary.rows()));
-    VERIFY_IS_APPROX(positive, positive.adjoint());
-    for(int i = 0; i < rows; i++) VERIFY(positive.diagonal()[i] >= 0); // cheap necessary (not sufficient) condition for positivity
-    VERIFY_IS_APPROX(positive*unitary, a);
-  }
-}
-
-void test_eigen2_svd()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( svd(Matrix3f()) );
-    CALL_SUBTEST_2( svd(Matrix4d()) );
-    CALL_SUBTEST_3( svd(MatrixXf(7,7)) );
-    CALL_SUBTEST_4( svd(MatrixXd(14,7)) );
-    // complex are not implemented yet
-//     CALL_SUBTEST( svd(MatrixXcd(6,6)) );
-//     CALL_SUBTEST( svd(MatrixXcf(3,3)) );
-    SVD<MatrixXf> s;
-    MatrixXf m = MatrixXf::Random(10,1);
-    s.compute(m);
-  }
-}
diff --git a/test/eigen2/eigen2_swap.cpp b/test/eigen2/eigen2_swap.cpp
deleted file mode 100644
index f3a8846d9..000000000
--- a/test/eigen2/eigen2_swap.cpp
+++ /dev/null
@@ -1,83 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@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/.
-
-#define EIGEN_NO_STATIC_ASSERT
-#include "main.h"
-
-template<typename T>
-struct other_matrix_type
-{
-  typedef int type;
-};
-
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-struct other_matrix_type<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
-{
-  typedef Matrix<_Scalar, _Rows, _Cols, _Options^RowMajor, _MaxRows, _MaxCols> type;
-};
-
-template<typename MatrixType> void swap(const MatrixType& m)
-{
-  typedef typename other_matrix_type<MatrixType>::type OtherMatrixType;
-  typedef typename MatrixType::Scalar Scalar;
-
-  ei_assert((!ei_is_same_type<MatrixType,OtherMatrixType>::ret));
-  int rows = m.rows();
-  int cols = m.cols();
-  
-  // construct 3 matrix guaranteed to be distinct
-  MatrixType m1 = MatrixType::Random(rows,cols);
-  MatrixType m2 = MatrixType::Random(rows,cols) + Scalar(100) * MatrixType::Identity(rows,cols);
-  OtherMatrixType m3 = OtherMatrixType::Random(rows,cols) + Scalar(200) * OtherMatrixType::Identity(rows,cols);
-  
-  MatrixType m1_copy = m1;
-  MatrixType m2_copy = m2;
-  OtherMatrixType m3_copy = m3;
-  
-  // test swapping 2 matrices of same type
-  m1.swap(m2);
-  VERIFY_IS_APPROX(m1,m2_copy);
-  VERIFY_IS_APPROX(m2,m1_copy);
-  m1 = m1_copy;
-  m2 = m2_copy;
-  
-  // test swapping 2 matrices of different types
-  m1.swap(m3);
-  VERIFY_IS_APPROX(m1,m3_copy);
-  VERIFY_IS_APPROX(m3,m1_copy);
-  m1 = m1_copy;
-  m3 = m3_copy;
-  
-  // test swapping matrix with expression
-  m1.swap(m2.block(0,0,rows,cols));
-  VERIFY_IS_APPROX(m1,m2_copy);
-  VERIFY_IS_APPROX(m2,m1_copy);
-  m1 = m1_copy;
-  m2 = m2_copy;
-
-  // test swapping two expressions of different types
-  m1.transpose().swap(m3.transpose());
-  VERIFY_IS_APPROX(m1,m3_copy);
-  VERIFY_IS_APPROX(m3,m1_copy);
-  m1 = m1_copy;
-  m3 = m3_copy;
-  
-  // test assertion on mismatching size -- matrix case
-  VERIFY_RAISES_ASSERT(m1.swap(m1.row(0)));
-  // test assertion on mismatching size -- xpr case
-  VERIFY_RAISES_ASSERT(m1.row(0).swap(m1));
-}
-
-void test_eigen2_swap()
-{
-  CALL_SUBTEST_1( swap(Matrix3f()) ); // fixed size, no vectorization 
-  CALL_SUBTEST_1( swap(Matrix4d()) ); // fixed size, possible vectorization 
-  CALL_SUBTEST_1( swap(MatrixXd(3,3)) ); // dyn size, no vectorization 
-  CALL_SUBTEST_1( swap(MatrixXf(30,30)) ); // dyn size, possible vectorization 
-}
diff --git a/test/eigen2/eigen2_triangular.cpp b/test/eigen2/eigen2_triangular.cpp
deleted file mode 100644
index 3748c7d71..000000000
--- a/test/eigen2/eigen2_triangular.cpp
+++ /dev/null
@@ -1,158 +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 <gael.guennebaud@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 "main.h"
-
-template<typename MatrixType> void triangular(const MatrixType& m)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
-
-  RealScalar largerEps = 10*test_precision<RealScalar>();
-
-  int rows = m.rows();
-  int cols = m.cols();
-
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols),
-             m4(rows, cols),
-             r1(rows, cols),
-             r2(rows, cols),
-             mzero = MatrixType::Zero(rows, cols),
-             mones = MatrixType::Ones(rows, cols),
-             identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
-                              ::Identity(rows, rows),
-             square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
-                              ::Random(rows, rows);
-  VectorType v1 = VectorType::Random(rows),
-             v2 = VectorType::Random(rows),
-             vzero = VectorType::Zero(rows);
-
-  MatrixType m1up = m1.template part<Eigen::UpperTriangular>();
-  MatrixType m2up = m2.template part<Eigen::UpperTriangular>();
-
-  if (rows*cols>1)
-  {
-    VERIFY(m1up.isUpperTriangular());
-    VERIFY(m2up.transpose().isLowerTriangular());
-    VERIFY(!m2.isLowerTriangular());
-  }
-
-//   VERIFY_IS_APPROX(m1up.transpose() * m2, m1.upper().transpose().lower() * m2);
-
-  // test overloaded operator+=
-  r1.setZero();
-  r2.setZero();
-  r1.template part<Eigen::UpperTriangular>() +=  m1;
-  r2 += m1up;
-  VERIFY_IS_APPROX(r1,r2);
-
-  // test overloaded operator=
-  m1.setZero();
-  m1.template part<Eigen::UpperTriangular>() = (m2.transpose() * m2).lazy();
-  m3 = m2.transpose() * m2;
-  VERIFY_IS_APPROX(m3.template part<Eigen::LowerTriangular>().transpose(), m1);
-
-  // test overloaded operator=
-  m1.setZero();
-  m1.template part<Eigen::LowerTriangular>() = (m2.transpose() * m2).lazy();
-  VERIFY_IS_APPROX(m3.template part<Eigen::LowerTriangular>(), m1);
-
-  VERIFY_IS_APPROX(m3.template part<Diagonal>(), m3.diagonal().asDiagonal());
-
-  m1 = MatrixType::Random(rows, cols);
-  for (int i=0; i<rows; ++i)
-    while (ei_abs2(m1(i,i))<1e-3) m1(i,i) = ei_random<Scalar>();
-
-  Transpose<MatrixType> trm4(m4);
-  // test back and forward subsitution
-  m3 = m1.template part<Eigen::LowerTriangular>();
-  VERIFY(m3.template marked<Eigen::LowerTriangular>().solveTriangular(m3).cwise().abs().isIdentity(test_precision<RealScalar>()));
-  VERIFY(m3.transpose().template marked<Eigen::UpperTriangular>()
-    .solveTriangular(m3.transpose()).cwise().abs().isIdentity(test_precision<RealScalar>()));
-  // check M * inv(L) using in place API
-  m4 = m3;
-  m3.transpose().template marked<Eigen::UpperTriangular>().solveTriangularInPlace(trm4);
-  VERIFY(m4.cwise().abs().isIdentity(test_precision<RealScalar>()));
-
-  m3 = m1.template part<Eigen::UpperTriangular>();
-  VERIFY(m3.template marked<Eigen::UpperTriangular>().solveTriangular(m3).cwise().abs().isIdentity(test_precision<RealScalar>()));
-  VERIFY(m3.transpose().template marked<Eigen::LowerTriangular>()
-    .solveTriangular(m3.transpose()).cwise().abs().isIdentity(test_precision<RealScalar>()));
-  // check M * inv(U) using in place API
-  m4 = m3;
-  m3.transpose().template marked<Eigen::LowerTriangular>().solveTriangularInPlace(trm4);
-  VERIFY(m4.cwise().abs().isIdentity(test_precision<RealScalar>()));
-
-  m3 = m1.template part<Eigen::UpperTriangular>();
-  VERIFY(m2.isApprox(m3 * (m3.template marked<Eigen::UpperTriangular>().solveTriangular(m2)), largerEps));
-  m3 = m1.template part<Eigen::LowerTriangular>();
-  VERIFY(m2.isApprox(m3 * (m3.template marked<Eigen::LowerTriangular>().solveTriangular(m2)), largerEps));
-
-  VERIFY((m1.template part<Eigen::UpperTriangular>() * m2.template part<Eigen::UpperTriangular>()).isUpperTriangular());
-
-  // test swap
-  m1.setOnes();
-  m2.setZero();
-  m2.template part<Eigen::UpperTriangular>().swap(m1);
-  m3.setZero();
-  m3.template part<Eigen::UpperTriangular>().setOnes();
-  VERIFY_IS_APPROX(m2,m3);
-
-}
-
-void selfadjoint()
-{
-  Matrix2i m;
-  m << 1, 2,
-       3, 4;
-
-  Matrix2i m1 = Matrix2i::Zero();
-  m1.part<SelfAdjoint>() = m;
-  Matrix2i ref1;
-  ref1 << 1, 2,
-          2, 4;
-  VERIFY(m1 == ref1);
-  
-  Matrix2i m2 = Matrix2i::Zero();
-  m2.part<SelfAdjoint>() = m.part<UpperTriangular>();
-  Matrix2i ref2;
-  ref2 << 1, 2,
-          2, 4;
-  VERIFY(m2 == ref2);
- 
-  Matrix2i m3 = Matrix2i::Zero();
-  m3.part<SelfAdjoint>() = m.part<LowerTriangular>();
-  Matrix2i ref3;
-  ref3 << 1, 0,
-          0, 4;
-  VERIFY(m3 == ref3);
-  
-  // example inspired from bug 159
-  int array[] = {1, 2, 3, 4};
-  Matrix2i::Map(array).part<SelfAdjoint>() = Matrix2i::Random().part<LowerTriangular>();
-  
-  std::cout << "hello\n" << array << std::endl;
-}
-
-void test_eigen2_triangular()
-{
-  CALL_SUBTEST_8( selfadjoint() );
-  for(int i = 0; i < g_repeat ; i++) {
-    CALL_SUBTEST_1( triangular(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( triangular(Matrix<float, 2, 2>()) );
-    CALL_SUBTEST_3( triangular(Matrix3d()) );
-    CALL_SUBTEST_4( triangular(MatrixXcf(4, 4)) );
-    CALL_SUBTEST_5( triangular(Matrix<std::complex<float>,8, 8>()) );
-    CALL_SUBTEST_6( triangular(MatrixXd(17,17)) );
-    CALL_SUBTEST_7( triangular(Matrix<float,Dynamic,Dynamic,RowMajor>(5, 5)) );
-  }
-}
diff --git a/test/eigen2/eigen2_unalignedassert.cpp b/test/eigen2/eigen2_unalignedassert.cpp
deleted file mode 100644
index d10b6f538..000000000
--- a/test/eigen2/eigen2_unalignedassert.cpp
+++ /dev/null
@@ -1,116 +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 Benoit Jacob <jacob.benoit.1@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 "main.h"
-
-struct Good1
-{
-  MatrixXd m; // good: m will allocate its own array, taking care of alignment.
-  Good1() : m(20,20) {}
-};
-
-struct Good2
-{
-  Matrix3d m; // good: m's size isn't a multiple of 16 bytes, so m doesn't have to be aligned
-};
-
-struct Good3
-{
-  Vector2f m; // good: same reason
-};
-
-struct Bad4
-{
-  Vector2d m; // bad: sizeof(m)%16==0 so alignment is required
-};
-
-struct Bad5
-{
-  Matrix<float, 2, 6> m; // bad: same reason
-};
-
-struct Bad6
-{
-  Matrix<double, 3, 4> m; // bad: same reason
-};
-
-struct Good7
-{
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-  Vector2d m;
-  float f; // make the struct have sizeof%16!=0 to make it a little more tricky when we allow an array of 2 such objects
-};
-
-struct Good8
-{
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
-  float f; // try the f at first -- the EIGEN_ALIGN_128 attribute of m should make that still work
-  Matrix4f m;
-};
-
-struct Good9
-{
-  Matrix<float,2,2,DontAlign> m; // good: no alignment requested
-  float f;
-};
-
-template<bool Align> struct Depends
-{
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(Align)
-  Vector2d m;
-  float f;
-};
-
-template<typename T>
-void check_unalignedassert_good()
-{
-  T *x, *y;
-  x = new T;
-  delete x;
-  y = new T[2];
-  delete[] y;
-}
-
-#if EIGEN_ARCH_WANTS_ALIGNMENT
-template<typename T>
-void check_unalignedassert_bad()
-{
-  float buf[sizeof(T)+16];
-  float *unaligned = buf;
-  while((reinterpret_cast<std::size_t>(unaligned)&0xf)==0) ++unaligned; // make sure unaligned is really unaligned
-  T *x = ::new(static_cast<void*>(unaligned)) T;
-  x->~T();
-}
-#endif
-
-void unalignedassert()
-{
-  check_unalignedassert_good<Good1>();
-  check_unalignedassert_good<Good2>();
-  check_unalignedassert_good<Good3>();
-#if EIGEN_ARCH_WANTS_ALIGNMENT
-  VERIFY_RAISES_ASSERT(check_unalignedassert_bad<Bad4>());
-  VERIFY_RAISES_ASSERT(check_unalignedassert_bad<Bad5>());
-  VERIFY_RAISES_ASSERT(check_unalignedassert_bad<Bad6>());
-#endif
-
-  check_unalignedassert_good<Good7>();
-  check_unalignedassert_good<Good8>();
-  check_unalignedassert_good<Good9>();
-  check_unalignedassert_good<Depends<true> >();
-
-#if EIGEN_ARCH_WANTS_ALIGNMENT
-  VERIFY_RAISES_ASSERT(check_unalignedassert_bad<Depends<false> >());
-#endif
-}
-
-void test_eigen2_unalignedassert()
-{
-  CALL_SUBTEST(unalignedassert());
-}
diff --git a/test/eigen2/eigen2_visitor.cpp b/test/eigen2/eigen2_visitor.cpp
deleted file mode 100644
index 4781991de..000000000
--- a/test/eigen2/eigen2_visitor.cpp
+++ /dev/null
@@ -1,116 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@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 "main.h"
-
-template<typename MatrixType> void matrixVisitor(const MatrixType& p)
-{
-  typedef typename MatrixType::Scalar Scalar;
-
-  int rows = p.rows();
-  int cols = p.cols();
-
-  // construct a random matrix where all coefficients are different
-  MatrixType m;
-  m = MatrixType::Random(rows, cols);
-  for(int i = 0; i < m.size(); i++)
-    for(int i2 = 0; i2 < i; i2++)
-      while(m(i) == m(i2)) // yes, ==
-        m(i) = ei_random<Scalar>();
-  
-  Scalar minc = Scalar(1000), maxc = Scalar(-1000);
-  int minrow=0,mincol=0,maxrow=0,maxcol=0;
-  for(int j = 0; j < cols; j++)
-  for(int i = 0; i < rows; i++)
-  {
-    if(m(i,j) < minc)
-    {
-      minc = m(i,j);
-      minrow = i;
-      mincol = j;
-    }
-    if(m(i,j) > maxc)
-    {
-      maxc = m(i,j);
-      maxrow = i;
-      maxcol = j;
-    }
-  }
-  int eigen_minrow, eigen_mincol, eigen_maxrow, eigen_maxcol;
-  Scalar eigen_minc, eigen_maxc;
-  eigen_minc = m.minCoeff(&eigen_minrow,&eigen_mincol);
-  eigen_maxc = m.maxCoeff(&eigen_maxrow,&eigen_maxcol);
-  VERIFY(minrow == eigen_minrow);
-  VERIFY(maxrow == eigen_maxrow);
-  VERIFY(mincol == eigen_mincol);
-  VERIFY(maxcol == eigen_maxcol);
-  VERIFY_IS_APPROX(minc, eigen_minc);
-  VERIFY_IS_APPROX(maxc, eigen_maxc);
-  VERIFY_IS_APPROX(minc, m.minCoeff());
-  VERIFY_IS_APPROX(maxc, m.maxCoeff());
-}
-
-template<typename VectorType> void vectorVisitor(const VectorType& w)
-{
-  typedef typename VectorType::Scalar Scalar;
-
-  int size = w.size();
-
-  // construct a random vector where all coefficients are different
-  VectorType v;
-  v = VectorType::Random(size);
-  for(int i = 0; i < size; i++)
-    for(int i2 = 0; i2 < i; i2++)
-      while(v(i) == v(i2)) // yes, ==
-        v(i) = ei_random<Scalar>();
-  
-  Scalar minc = Scalar(1000), maxc = Scalar(-1000);
-  int minidx=0,maxidx=0;
-  for(int i = 0; i < size; i++)
-  {
-    if(v(i) < minc)
-    {
-      minc = v(i);
-      minidx = i;
-    }
-    if(v(i) > maxc)
-    {
-      maxc = v(i);
-      maxidx = i;
-    }
-  }
-  int eigen_minidx, eigen_maxidx;
-  Scalar eigen_minc, eigen_maxc;
-  eigen_minc = v.minCoeff(&eigen_minidx);
-  eigen_maxc = v.maxCoeff(&eigen_maxidx);
-  VERIFY(minidx == eigen_minidx);
-  VERIFY(maxidx == eigen_maxidx);
-  VERIFY_IS_APPROX(minc, eigen_minc);
-  VERIFY_IS_APPROX(maxc, eigen_maxc);
-  VERIFY_IS_APPROX(minc, v.minCoeff());
-  VERIFY_IS_APPROX(maxc, v.maxCoeff());
-}
-
-void test_eigen2_visitor()
-{
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_1( matrixVisitor(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST_2( matrixVisitor(Matrix2f()) );
-    CALL_SUBTEST_3( matrixVisitor(Matrix4d()) );
-    CALL_SUBTEST_4( matrixVisitor(MatrixXd(8, 12)) );
-    CALL_SUBTEST_5( matrixVisitor(Matrix<double,Dynamic,Dynamic,RowMajor>(20, 20)) );
-    CALL_SUBTEST_6( matrixVisitor(MatrixXi(8, 12)) );
-  }
-  for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST_7( vectorVisitor(Vector4f()) );
-    CALL_SUBTEST_4( vectorVisitor(VectorXd(10)) );
-    CALL_SUBTEST_4( vectorVisitor(RowVectorXd(10)) );
-    CALL_SUBTEST_8( vectorVisitor(VectorXf(33)) );
-  }
-}
diff --git a/test/eigen2/gsl_helper.h b/test/eigen2/gsl_helper.h
deleted file mode 100644
index d1d854533..000000000
--- a/test/eigen2/gsl_helper.h
+++ /dev/null
@@ -1,175 +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/.
-
-#ifndef EIGEN_GSL_HELPER
-#define EIGEN_GSL_HELPER
-
-#include <Eigen/Core>
-
-#include <gsl/gsl_blas.h>
-#include <gsl/gsl_multifit.h>
-#include <gsl/gsl_eigen.h>
-#include <gsl/gsl_linalg.h>
-#include <gsl/gsl_complex.h>
-#include <gsl/gsl_complex_math.h>
-
-namespace Eigen {
-
-template<typename Scalar, bool IsComplex = NumTraits<Scalar>::IsComplex> struct GslTraits
-{
-  typedef gsl_matrix* Matrix;
-  typedef gsl_vector* Vector;
-  static Matrix createMatrix(int rows, int cols) { return gsl_matrix_alloc(rows,cols); }
-  static Vector createVector(int size) { return gsl_vector_alloc(size); }
-  static void free(Matrix& m) { gsl_matrix_free(m); m=0; }
-  static void free(Vector& m) { gsl_vector_free(m); m=0; }
-  static void prod(const Matrix& m, const Vector& v, Vector& x) { gsl_blas_dgemv(CblasNoTrans,1,m,v,0,x); }
-  static void cholesky(Matrix& m) { gsl_linalg_cholesky_decomp(m); }
-  static void cholesky_solve(const Matrix& m, const Vector& b, Vector& x) { gsl_linalg_cholesky_solve(m,b,x); }
-  static void eigen_symm(const Matrix& m, Vector& eval, Matrix& evec)
-  {
-    gsl_eigen_symmv_workspace * w = gsl_eigen_symmv_alloc(m->size1);
-    Matrix a = createMatrix(m->size1, m->size2);
-    gsl_matrix_memcpy(a, m);
-    gsl_eigen_symmv(a,eval,evec,w);
-    gsl_eigen_symmv_sort(eval, evec, GSL_EIGEN_SORT_VAL_ASC);
-    gsl_eigen_symmv_free(w);
-    free(a);
-  }
-  static void eigen_symm_gen(const Matrix& m, const Matrix& _b, Vector& eval, Matrix& evec)
-  {
-    gsl_eigen_gensymmv_workspace * w = gsl_eigen_gensymmv_alloc(m->size1);
-    Matrix a = createMatrix(m->size1, m->size2);
-    Matrix b = createMatrix(_b->size1, _b->size2);
-    gsl_matrix_memcpy(a, m);
-    gsl_matrix_memcpy(b, _b);
-    gsl_eigen_gensymmv(a,b,eval,evec,w);
-    gsl_eigen_symmv_sort(eval, evec, GSL_EIGEN_SORT_VAL_ASC);
-    gsl_eigen_gensymmv_free(w);
-    free(a);
-  }
-};
-
-template<typename Scalar> struct GslTraits<Scalar,true>
-{
-  typedef gsl_matrix_complex* Matrix;
-  typedef gsl_vector_complex* Vector;
-  static Matrix createMatrix(int rows, int cols) { return gsl_matrix_complex_alloc(rows,cols); }
-  static Vector createVector(int size) { return gsl_vector_complex_alloc(size); }
-  static void free(Matrix& m) { gsl_matrix_complex_free(m); m=0; }
-  static void free(Vector& m) { gsl_vector_complex_free(m); m=0; }
-  static void cholesky(Matrix& m) { gsl_linalg_complex_cholesky_decomp(m); }
-  static void cholesky_solve(const Matrix& m, const Vector& b, Vector& x) { gsl_linalg_complex_cholesky_solve(m,b,x); }
-  static void prod(const Matrix& m, const Vector& v, Vector& x)
-  { gsl_blas_zgemv(CblasNoTrans,gsl_complex_rect(1,0),m,v,gsl_complex_rect(0,0),x); }
-  static void eigen_symm(const Matrix& m, gsl_vector* &eval, Matrix& evec)
-  {
-    gsl_eigen_hermv_workspace * w = gsl_eigen_hermv_alloc(m->size1);
-    Matrix a = createMatrix(m->size1, m->size2);
-    gsl_matrix_complex_memcpy(a, m);
-    gsl_eigen_hermv(a,eval,evec,w);
-    gsl_eigen_hermv_sort(eval, evec, GSL_EIGEN_SORT_VAL_ASC);
-    gsl_eigen_hermv_free(w);
-    free(a);
-  }
-  static void eigen_symm_gen(const Matrix& m, const Matrix& _b, gsl_vector* &eval, Matrix& evec)
-  {
-    gsl_eigen_genhermv_workspace * w = gsl_eigen_genhermv_alloc(m->size1);
-    Matrix a = createMatrix(m->size1, m->size2);
-    Matrix b = createMatrix(_b->size1, _b->size2);
-    gsl_matrix_complex_memcpy(a, m);
-    gsl_matrix_complex_memcpy(b, _b);
-    gsl_eigen_genhermv(a,b,eval,evec,w);
-    gsl_eigen_hermv_sort(eval, evec, GSL_EIGEN_SORT_VAL_ASC);
-    gsl_eigen_genhermv_free(w);
-    free(a);
-  }
-};
-
-template<typename MatrixType>
-void convert(const MatrixType& m, gsl_matrix* &res)
-{
-//   if (res)
-//     gsl_matrix_free(res);
-  res = gsl_matrix_alloc(m.rows(), m.cols());
-  for (int i=0 ; i<m.rows() ; ++i)
-    for (int j=0 ; j<m.cols(); ++j)
-      gsl_matrix_set(res, i, j, m(i,j));
-}
-
-template<typename MatrixType>
-void convert(const gsl_matrix* m, MatrixType& res)
-{
-  res.resize(int(m->size1), int(m->size2));
-  for (int i=0 ; i<res.rows() ; ++i)
-    for (int j=0 ; j<res.cols(); ++j)
-      res(i,j) = gsl_matrix_get(m,i,j);
-}
-
-template<typename VectorType>
-void convert(const VectorType& m, gsl_vector* &res)
-{
-  if (res) gsl_vector_free(res);
-  res = gsl_vector_alloc(m.size());
-  for (int i=0 ; i<m.size() ; ++i)
-      gsl_vector_set(res, i, m[i]);
-}
-
-template<typename VectorType>
-void convert(const gsl_vector* m, VectorType& res)
-{
-  res.resize (m->size);
-  for (int i=0 ; i<res.rows() ; ++i)
-    res[i] = gsl_vector_get(m, i);
-}
-
-template<typename MatrixType>
-void convert(const MatrixType& m, gsl_matrix_complex* &res)
-{
-  res = gsl_matrix_complex_alloc(m.rows(), m.cols());
-  for (int i=0 ; i<m.rows() ; ++i)
-    for (int j=0 ; j<m.cols(); ++j)
-    {
-      gsl_matrix_complex_set(res, i, j,
-        gsl_complex_rect(m(i,j).real(), m(i,j).imag()));
-    }
-}
-
-template<typename MatrixType>
-void convert(const gsl_matrix_complex* m, MatrixType& res)
-{
-  res.resize(int(m->size1), int(m->size2));
-  for (int i=0 ; i<res.rows() ; ++i)
-    for (int j=0 ; j<res.cols(); ++j)
-      res(i,j) = typename MatrixType::Scalar(
-        GSL_REAL(gsl_matrix_complex_get(m,i,j)),
-        GSL_IMAG(gsl_matrix_complex_get(m,i,j)));
-}
-
-template<typename VectorType>
-void convert(const VectorType& m, gsl_vector_complex* &res)
-{
-  res = gsl_vector_complex_alloc(m.size());
-  for (int i=0 ; i<m.size() ; ++i)
-      gsl_vector_complex_set(res, i, gsl_complex_rect(m[i].real(), m[i].imag()));
-}
-
-template<typename VectorType>
-void convert(const gsl_vector_complex* m, VectorType& res)
-{
-  res.resize(m->size);
-  for (int i=0 ; i<res.rows() ; ++i)
-    res[i] = typename VectorType::Scalar(
-        GSL_REAL(gsl_vector_complex_get(m, i)),
-        GSL_IMAG(gsl_vector_complex_get(m, i)));
-}
-
-}
-
-#endif // EIGEN_GSL_HELPER
diff --git a/test/eigen2/main.h b/test/eigen2/main.h
deleted file mode 100644
index ad2ba1994..000000000
--- a/test/eigen2/main.h
+++ /dev/null
@@ -1,399 +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) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-// 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 <cstdlib>
-#include <ctime>
-#include <iostream>
-#include <string>
-#include <vector>
-
-#ifndef EIGEN_TEST_FUNC
-#error EIGEN_TEST_FUNC must be defined
-#endif
-
-#define DEFAULT_REPEAT 10
-
-namespace Eigen
-{
-  static std::vector<std::string> g_test_stack;
-  static int g_repeat;
-}
-
-#define EI_PP_MAKE_STRING2(S) #S
-#define EI_PP_MAKE_STRING(S) EI_PP_MAKE_STRING2(S)
-
-#define EI_PP_CAT2(a,b) a ## b
-#define EI_PP_CAT(a,b) EI_PP_CAT2(a,b)
-
-#ifndef EIGEN_NO_ASSERTION_CHECKING
-
-  namespace Eigen
-  {
-    static const bool should_raise_an_assert = false;
-
-    // Used to avoid to raise two exceptions at a time in which
-    // case the exception is not properly caught.
-    // This may happen when a second exceptions is raise in a destructor.
-    static bool no_more_assert = false;
-
-    struct eigen_assert_exception
-    {
-      eigen_assert_exception(void) {}
-      ~eigen_assert_exception() { Eigen::no_more_assert = false; }
-    };
-  }
-
-  // If EIGEN_DEBUG_ASSERTS is defined and if no assertion is raised while
-  // one should have been, then the list of excecuted assertions is printed out.
-  //
-  // EIGEN_DEBUG_ASSERTS is not enabled by default as it
-  // significantly increases the compilation time
-  // and might even introduce side effects that would hide
-  // some memory errors.
-  #ifdef EIGEN_DEBUG_ASSERTS
-
-    namespace Eigen
-    {
-      static bool ei_push_assert = false;
-      static std::vector<std::string> eigen_assert_list;
-    }
-
-    #define eigen_assert(a)                       \
-      if( (!(a)) && (!no_more_assert) )     \
-      {                                     \
-        Eigen::no_more_assert = true;       \
-        throw Eigen::eigen_assert_exception(); \
-      }                                     \
-      else if (Eigen::ei_push_assert)       \
-      {                                     \
-        eigen_assert_list.push_back(std::string(EI_PP_MAKE_STRING(__FILE__)" ("EI_PP_MAKE_STRING(__LINE__)") : "#a) ); \
-      }
-
-    #define VERIFY_RAISES_ASSERT(a)                                               \
-      {                                                                           \
-        Eigen::no_more_assert = false;                                            \
-        try {                                                                     \
-          Eigen::eigen_assert_list.clear();                                          \
-          Eigen::ei_push_assert = true;                                           \
-          a;                                                                      \
-          Eigen::ei_push_assert = false;                                          \
-          std::cerr << "One of the following asserts should have been raised:\n"; \
-          for (uint ai=0 ; ai<eigen_assert_list.size() ; ++ai)                       \
-            std::cerr << "  " << eigen_assert_list[ai] << "\n";                      \
-          VERIFY(Eigen::should_raise_an_assert && # a);                           \
-        } catch (Eigen::eigen_assert_exception e) {                                  \
-          Eigen::ei_push_assert = false; VERIFY(true);                            \
-        }                                                                         \
-      }
-
-  #else // EIGEN_DEBUG_ASSERTS
-
-    #undef eigen_assert
-
-    // see bug 89. The copy_bool here is working around a bug in gcc <= 4.3
-    #define eigen_assert(a) \
-      if( (!Eigen::internal::copy_bool(a)) && (!no_more_assert) )	\
-      {                                     \
-        Eigen::no_more_assert = true;       \
-        throw Eigen::eigen_assert_exception(); \
-      }
-
-    #define VERIFY_RAISES_ASSERT(a) {                             \
-        Eigen::no_more_assert = false;                            \
-        try { a; VERIFY(Eigen::should_raise_an_assert && # a); }  \
-        catch (Eigen::eigen_assert_exception e) { VERIFY(true); }    \
-      }
-
-  #endif // EIGEN_DEBUG_ASSERTS
-
-  #define EIGEN_USE_CUSTOM_ASSERT
-
-#else // EIGEN_NO_ASSERTION_CHECKING
-
-  #define VERIFY_RAISES_ASSERT(a) {}
-
-#endif // EIGEN_NO_ASSERTION_CHECKING
-
-
-#define EIGEN_INTERNAL_DEBUGGING
-#define EIGEN_NICE_RANDOM
-#include <Eigen/Array>
-
-
-#define VERIFY(a) do { if (!(a)) { \
-    std::cerr << "Test " << g_test_stack.back() << " failed in "EI_PP_MAKE_STRING(__FILE__) << " (" << EI_PP_MAKE_STRING(__LINE__) << ")" \
-      << std::endl << "    " << EI_PP_MAKE_STRING(a) << std::endl << std::endl; \
-    abort(); \
-  } } while (0)
-
-#define VERIFY_IS_APPROX(a, b) VERIFY(test_ei_isApprox(a, b))
-#define VERIFY_IS_NOT_APPROX(a, b) VERIFY(!test_ei_isApprox(a, b))
-#define VERIFY_IS_MUCH_SMALLER_THAN(a, b) VERIFY(test_ei_isMuchSmallerThan(a, b))
-#define VERIFY_IS_NOT_MUCH_SMALLER_THAN(a, b) VERIFY(!test_ei_isMuchSmallerThan(a, b))
-#define VERIFY_IS_APPROX_OR_LESS_THAN(a, b) VERIFY(test_ei_isApproxOrLessThan(a, b))
-#define VERIFY_IS_NOT_APPROX_OR_LESS_THAN(a, b) VERIFY(!test_ei_isApproxOrLessThan(a, b))
-
-#define CALL_SUBTEST(FUNC) do { \
-    g_test_stack.push_back(EI_PP_MAKE_STRING(FUNC)); \
-    FUNC; \
-    g_test_stack.pop_back(); \
-  } while (0)
-
-namespace Eigen {
-
-template<typename T> inline typename NumTraits<T>::Real test_precision();
-template<> inline int test_precision<int>() { return 0; }
-template<> inline float test_precision<float>() { return 1e-3f; }
-template<> inline double test_precision<double>() { return 1e-6; }
-template<> inline float test_precision<std::complex<float> >() { return test_precision<float>(); }
-template<> inline double test_precision<std::complex<double> >() { return test_precision<double>(); }
-template<> inline long double test_precision<long double>() { return 1e-6; }
-
-inline bool test_ei_isApprox(const int& a, const int& b)
-{ return ei_isApprox(a, b, test_precision<int>()); }
-inline bool test_ei_isMuchSmallerThan(const int& a, const int& b)
-{ return ei_isMuchSmallerThan(a, b, test_precision<int>()); }
-inline bool test_ei_isApproxOrLessThan(const int& a, const int& b)
-{ return ei_isApproxOrLessThan(a, b, test_precision<int>()); }
-
-inline bool test_ei_isApprox(const float& a, const float& b)
-{ return ei_isApprox(a, b, test_precision<float>()); }
-inline bool test_ei_isMuchSmallerThan(const float& a, const float& b)
-{ return ei_isMuchSmallerThan(a, b, test_precision<float>()); }
-inline bool test_ei_isApproxOrLessThan(const float& a, const float& b)
-{ return ei_isApproxOrLessThan(a, b, test_precision<float>()); }
-
-inline bool test_ei_isApprox(const double& a, const double& b)
-{ return ei_isApprox(a, b, test_precision<double>()); }
-inline bool test_ei_isMuchSmallerThan(const double& a, const double& b)
-{ return ei_isMuchSmallerThan(a, b, test_precision<double>()); }
-inline bool test_ei_isApproxOrLessThan(const double& a, const double& b)
-{ return ei_isApproxOrLessThan(a, b, test_precision<double>()); }
-
-inline bool test_ei_isApprox(const std::complex<float>& a, const std::complex<float>& b)
-{ return ei_isApprox(a, b, test_precision<std::complex<float> >()); }
-inline bool test_ei_isMuchSmallerThan(const std::complex<float>& a, const std::complex<float>& b)
-{ return ei_isMuchSmallerThan(a, b, test_precision<std::complex<float> >()); }
-
-inline bool test_ei_isApprox(const std::complex<double>& a, const std::complex<double>& b)
-{ return ei_isApprox(a, b, test_precision<std::complex<double> >()); }
-inline bool test_ei_isMuchSmallerThan(const std::complex<double>& a, const std::complex<double>& b)
-{ return ei_isMuchSmallerThan(a, b, test_precision<std::complex<double> >()); }
-
-inline bool test_ei_isApprox(const long double& a, const long double& b)
-{ return ei_isApprox(a, b, test_precision<long double>()); }
-inline bool test_ei_isMuchSmallerThan(const long double& a, const long double& b)
-{ return ei_isMuchSmallerThan(a, b, test_precision<long double>()); }
-inline bool test_ei_isApproxOrLessThan(const long double& a, const long double& b)
-{ return ei_isApproxOrLessThan(a, b, test_precision<long double>()); }
-
-template<typename Type1, typename Type2>
-inline bool test_ei_isApprox(const Type1& a, const Type2& b)
-{
-  return a.isApprox(b, test_precision<typename Type1::Scalar>());
-}
-
-template<typename Derived1, typename Derived2>
-inline bool test_ei_isMuchSmallerThan(const MatrixBase<Derived1>& m1,
-                                   const MatrixBase<Derived2>& m2)
-{
-  return m1.isMuchSmallerThan(m2, test_precision<typename ei_traits<Derived1>::Scalar>());
-}
-
-template<typename Derived>
-inline bool test_ei_isMuchSmallerThan(const MatrixBase<Derived>& m,
-                                   const typename NumTraits<typename ei_traits<Derived>::Scalar>::Real& s)
-{
-  return m.isMuchSmallerThan(s, test_precision<typename ei_traits<Derived>::Scalar>());
-}
-
-} // end namespace Eigen
-
-template<typename T> struct GetDifferentType;
-
-template<> struct GetDifferentType<float> { typedef double type; };
-template<> struct GetDifferentType<double> { typedef float type; };
-template<typename T> struct GetDifferentType<std::complex<T> >
-{ typedef std::complex<typename GetDifferentType<T>::type> type; };
-
-// forward declaration of the main test function
-void EI_PP_CAT(test_,EIGEN_TEST_FUNC)();
-
-using namespace Eigen;
-
-#ifdef EIGEN_TEST_PART_1
-#define CALL_SUBTEST_1(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_1(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_2
-#define CALL_SUBTEST_2(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_2(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_3
-#define CALL_SUBTEST_3(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_3(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_4
-#define CALL_SUBTEST_4(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_4(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_5
-#define CALL_SUBTEST_5(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_5(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_6
-#define CALL_SUBTEST_6(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_6(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_7
-#define CALL_SUBTEST_7(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_7(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_8
-#define CALL_SUBTEST_8(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_8(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_9
-#define CALL_SUBTEST_9(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_9(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_10
-#define CALL_SUBTEST_10(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_10(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_11
-#define CALL_SUBTEST_11(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_11(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_12
-#define CALL_SUBTEST_12(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_12(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_13
-#define CALL_SUBTEST_13(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_13(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_14
-#define CALL_SUBTEST_14(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_14(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_15
-#define CALL_SUBTEST_15(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_15(FUNC)
-#endif
-
-#ifdef EIGEN_TEST_PART_16
-#define CALL_SUBTEST_16(FUNC) CALL_SUBTEST(FUNC)
-#else
-#define CALL_SUBTEST_16(FUNC)
-#endif
-
-
-
-int main(int argc, char *argv[])
-{
-    bool has_set_repeat = false;
-    bool has_set_seed = false;
-    bool need_help = false;
-    unsigned int seed = 0;
-    int repeat = DEFAULT_REPEAT;
-
-    for(int i = 1; i < argc; i++)
-    {
-      if(argv[i][0] == 'r')
-      {
-        if(has_set_repeat)
-        {
-          std::cout << "Argument " << argv[i] << " conflicting with a former argument" << std::endl;
-          return 1;
-        }
-        repeat = std::atoi(argv[i]+1);
-        has_set_repeat = true;
-        if(repeat <= 0)
-        {
-          std::cout << "Invalid \'repeat\' value " << argv[i]+1 << std::endl;
-          return 1;
-        }
-      }
-      else if(argv[i][0] == 's')
-      {
-        if(has_set_seed)
-        {
-          std::cout << "Argument " << argv[i] << " conflicting with a former argument" << std::endl;
-          return 1;
-        }
-        seed = int(std::strtoul(argv[i]+1, 0, 10));
-        has_set_seed = true;
-        bool ok = seed!=0;
-        if(!ok)
-        {
-          std::cout << "Invalid \'seed\' value " << argv[i]+1 << std::endl;
-          return 1;
-        }
-      }
-      else
-      {
-        need_help = true;
-      }
-    }
-
-    if(need_help)
-    {
-      std::cout << "This test application takes the following optional arguments:" << std::endl;
-      std::cout << "  rN     Repeat each test N times (default: " << DEFAULT_REPEAT << ")" << std::endl;
-      std::cout << "  sN     Use N as seed for random numbers (default: based on current time)" << std::endl;
-      return 1;
-    }
-
-    if(!has_set_seed) seed = (unsigned int) std::time(NULL);
-    if(!has_set_repeat) repeat = DEFAULT_REPEAT;
-
-    std::cout << "Initializing random number generator with seed " << seed << std::endl;
-	std::srand(seed);
-    std::cout << "Repeating each test " << repeat << " times" << std::endl;
-
-    Eigen::g_repeat = repeat;
-    Eigen::g_test_stack.push_back(EI_PP_MAKE_STRING(EIGEN_TEST_FUNC));
-
-    EI_PP_CAT(test_,EIGEN_TEST_FUNC)();
-    return 0;
-}
-
-
-
diff --git a/test/eigen2/product.h b/test/eigen2/product.h
deleted file mode 100644
index 2c9604d9a..000000000
--- a/test/eigen2/product.h
+++ /dev/null
@@ -1,132 +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) 2006-2008 Benoit Jacob <jacob.benoit.1@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 "main.h"
-#include <Eigen/Array>
-#include <Eigen/QR>
-
-template<typename Derived1, typename Derived2>
-bool areNotApprox(const MatrixBase<Derived1>& m1, const MatrixBase<Derived2>& m2, typename Derived1::RealScalar epsilon = precision<typename Derived1::RealScalar>())
-{
-  return !((m1-m2).cwise().abs2().maxCoeff() < epsilon * epsilon
-                          * std::max(m1.cwise().abs2().maxCoeff(), m2.cwise().abs2().maxCoeff()));
-}
-
-template<typename MatrixType> void product(const MatrixType& m)
-{
-  /* this test covers the following files:
-     Identity.h Product.h
-  */
-
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::FloatingPoint FloatingPoint;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> RowVectorType;
-  typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> ColVectorType;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> RowSquareMatrixType;
-  typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, MatrixType::ColsAtCompileTime> ColSquareMatrixType;
-  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime,
-                         MatrixType::Options^RowMajor> OtherMajorMatrixType;
-
-  int rows = m.rows();
-  int cols = m.cols();
-
-  // this test relies a lot on Random.h, and there's not much more that we can do
-  // to test it, hence I consider that we will have tested Random.h
-  MatrixType m1 = MatrixType::Random(rows, cols),
-             m2 = MatrixType::Random(rows, cols),
-             m3(rows, cols),
-             mzero = MatrixType::Zero(rows, cols);
-  RowSquareMatrixType
-             identity = RowSquareMatrixType::Identity(rows, rows),
-             square = RowSquareMatrixType::Random(rows, rows),
-             res = RowSquareMatrixType::Random(rows, rows);
-  ColSquareMatrixType
-             square2 = ColSquareMatrixType::Random(cols, cols),
-             res2 = ColSquareMatrixType::Random(cols, cols);
-  RowVectorType v1 = RowVectorType::Random(rows),
-             v2 = RowVectorType::Random(rows),
-             vzero = RowVectorType::Zero(rows);
-  ColVectorType vc2 = ColVectorType::Random(cols), vcres(cols);
-  OtherMajorMatrixType tm1 = m1;
-
-  Scalar s1 = ei_random<Scalar>();
-
-  int r = ei_random<int>(0, rows-1),
-      c = ei_random<int>(0, cols-1);
-
-  // begin testing Product.h: only associativity for now
-  // (we use Transpose.h but this doesn't count as a test for it)
-
-  VERIFY_IS_APPROX((m1*m1.transpose())*m2,  m1*(m1.transpose()*m2));
-  m3 = m1;
-  m3 *= m1.transpose() * m2;
-  VERIFY_IS_APPROX(m3,                      m1 * (m1.transpose()*m2));
-  VERIFY_IS_APPROX(m3,                      m1.lazy() * (m1.transpose()*m2));
-
-  // continue testing Product.h: distributivity
-  VERIFY_IS_APPROX(square*(m1 + m2),        square*m1+square*m2);
-  VERIFY_IS_APPROX(square*(m1 - m2),        square*m1-square*m2);
-
-  // continue testing Product.h: compatibility with ScalarMultiple.h
-  VERIFY_IS_APPROX(s1*(square*m1),          (s1*square)*m1);
-  VERIFY_IS_APPROX(s1*(square*m1),          square*(m1*s1));
-
-  // again, test operator() to check const-qualification
-  s1 += (square.lazy() * m1)(r,c);
-
-  // test Product.h together with Identity.h
-  VERIFY_IS_APPROX(v1,                      identity*v1);
-  VERIFY_IS_APPROX(v1.transpose(),          v1.transpose() * identity);
-  // again, test operator() to check const-qualification
-  VERIFY_IS_APPROX(MatrixType::Identity(rows, cols)(r,c), static_cast<Scalar>(r==c));
-
-  if (rows!=cols)
-     VERIFY_RAISES_ASSERT(m3 = m1*m1);
-
-  // test the previous tests were not screwed up because operator* returns 0
-  // (we use the more accurate default epsilon)
-  if (NumTraits<Scalar>::HasFloatingPoint && std::min(rows,cols)>1)
-  {
-    VERIFY(areNotApprox(m1.transpose()*m2,m2.transpose()*m1));
-  }
-
-  // test optimized operator+= path
-  res = square;
-  res += (m1 * m2.transpose()).lazy();
-  VERIFY_IS_APPROX(res, square + m1 * m2.transpose());
-  if (NumTraits<Scalar>::HasFloatingPoint && std::min(rows,cols)>1)
-  {
-    VERIFY(areNotApprox(res,square + m2 * m1.transpose()));
-  }
-  vcres = vc2;
-  vcres += (m1.transpose() * v1).lazy();
-  VERIFY_IS_APPROX(vcres, vc2 + m1.transpose() * v1);
-  tm1 = m1;
-  VERIFY_IS_APPROX(tm1.transpose() * v1, m1.transpose() * v1);
-  VERIFY_IS_APPROX(v1.transpose() * tm1, v1.transpose() * m1);
-
-  // test submatrix and matrix/vector product
-  for (int i=0; i<rows; ++i)
-    res.row(i) = m1.row(i) * m2.transpose();
-  VERIFY_IS_APPROX(res, m1 * m2.transpose());
-  // the other way round:
-  for (int i=0; i<rows; ++i)
-    res.col(i) = m1 * m2.transpose().col(i);
-  VERIFY_IS_APPROX(res, m1 * m2.transpose());
-
-  res2 = square2;
-  res2 += (m1.transpose() * m2).lazy();
-  VERIFY_IS_APPROX(res2, square2 + m1.transpose() * m2);
-
-  if (NumTraits<Scalar>::HasFloatingPoint && std::min(rows,cols)>1)
-  {
-    VERIFY(areNotApprox(res2,square2 + m2.transpose() * m1));
-  }
-}
-
diff --git a/test/eigen2/sparse.h b/test/eigen2/sparse.h
deleted file mode 100644
index e12f89990..000000000
--- a/test/eigen2/sparse.h
+++ /dev/null
@@ -1,154 +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/.
-
-#ifndef EIGEN_TESTSPARSE_H
-
-#include "main.h"
-
-#if EIGEN_GNUC_AT_LEAST(4,0) && !defined __ICC
-#include <tr1/unordered_map>
-#define EIGEN_UNORDERED_MAP_SUPPORT
-namespace std {
-  using std::tr1::unordered_map;
-}
-#endif
-
-#ifdef EIGEN_GOOGLEHASH_SUPPORT
-  #include <google/sparse_hash_map>
-#endif
-
-#include <Eigen/Cholesky>
-#include <Eigen/LU>
-#include <Eigen/Sparse>
-
-enum {
-  ForceNonZeroDiag = 1,
-  MakeLowerTriangular = 2,
-  MakeUpperTriangular = 4,
-  ForceRealDiag = 8
-};
-
-/* Initializes both a sparse and dense matrix with same random values,
- * and a ratio of \a density non zero entries.
- * \param flags is a union of ForceNonZeroDiag, MakeLowerTriangular and MakeUpperTriangular
- *        allowing to control the shape of the matrix.
- * \param zeroCoords and nonzeroCoords allows to get the coordinate lists of the non zero,
- *        and zero coefficients respectively.
- */
-template<typename Scalar> void
-initSparse(double density,
-           Matrix<Scalar,Dynamic,Dynamic>& refMat,
-           SparseMatrix<Scalar>& sparseMat,
-           int flags = 0,
-           std::vector<Vector2i>* zeroCoords = 0,
-           std::vector<Vector2i>* nonzeroCoords = 0)
-{
-  sparseMat.startFill(int(refMat.rows()*refMat.cols()*density));
-  for(int j=0; j<refMat.cols(); j++)
-  {
-    for(int i=0; i<refMat.rows(); i++)
-    {
-      Scalar v = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0);
-      if ((flags&ForceNonZeroDiag) && (i==j))
-      {
-        v = ei_random<Scalar>()*Scalar(3.);
-        v = v*v + Scalar(5.);
-      }
-      if ((flags & MakeLowerTriangular) && j>i)
-        v = Scalar(0);
-      else if ((flags & MakeUpperTriangular) && j<i)
-        v = Scalar(0);
-      
-      if ((flags&ForceRealDiag) && (i==j))
-        v = ei_real(v);
-        
-      if (v!=Scalar(0))
-      {
-        sparseMat.fill(i,j) = v;
-        if (nonzeroCoords)
-          nonzeroCoords->push_back(Vector2i(i,j));
-      }
-      else if (zeroCoords)
-      {
-        zeroCoords->push_back(Vector2i(i,j));
-      }
-      refMat(i,j) = v;
-    }
-  }
-  sparseMat.endFill();
-}
-
-template<typename Scalar> void
-initSparse(double density,
-           Matrix<Scalar,Dynamic,Dynamic>& refMat,
-           DynamicSparseMatrix<Scalar>& sparseMat,
-           int flags = 0,
-           std::vector<Vector2i>* zeroCoords = 0,
-           std::vector<Vector2i>* nonzeroCoords = 0)
-{
-  sparseMat.startFill(int(refMat.rows()*refMat.cols()*density));
-  for(int j=0; j<refMat.cols(); j++)
-  {
-    for(int i=0; i<refMat.rows(); i++)
-    {
-      Scalar v = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0);
-      if ((flags&ForceNonZeroDiag) && (i==j))
-      {
-        v = ei_random<Scalar>()*Scalar(3.);
-        v = v*v + Scalar(5.);
-      }
-      if ((flags & MakeLowerTriangular) && j>i)
-        v = Scalar(0);
-      else if ((flags & MakeUpperTriangular) && j<i)
-        v = Scalar(0);
-      
-      if ((flags&ForceRealDiag) && (i==j))
-        v = ei_real(v);
-        
-      if (v!=Scalar(0))
-      {
-        sparseMat.fill(i,j) = v;
-        if (nonzeroCoords)
-          nonzeroCoords->push_back(Vector2i(i,j));
-      }
-      else if (zeroCoords)
-      {
-        zeroCoords->push_back(Vector2i(i,j));
-      }
-      refMat(i,j) = v;
-    }
-  }
-  sparseMat.endFill();
-}
-
-template<typename Scalar> void
-initSparse(double density,
-           Matrix<Scalar,Dynamic,1>& refVec,
-           SparseVector<Scalar>& sparseVec,
-           std::vector<int>* zeroCoords = 0,
-           std::vector<int>* nonzeroCoords = 0)
-{
-  sparseVec.reserve(int(refVec.size()*density));
-  sparseVec.setZero();
-  for(int i=0; i<refVec.size(); i++)
-  {
-    Scalar v = (ei_random<double>(0,1) < density) ? ei_random<Scalar>() : Scalar(0);
-    if (v!=Scalar(0))
-    {
-      sparseVec.fill(i) = v;
-      if (nonzeroCoords)
-        nonzeroCoords->push_back(i);
-    }
-    else if (zeroCoords)
-        zeroCoords->push_back(i);
-    refVec[i] = v;
-  }
-}
-
-#endif // EIGEN_TESTSPARSE_H