1 files changed, 0 insertions, 87 deletions
diff --git a/eigen/test/eigen2/eigen2_svd.cpp b/eigen/test/eigen2/eigen2_svd.cpp
deleted file mode 100644
index d4689a5..0000000
--- a/eigen/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);
-  }
-}