1 files changed, 0 insertions, 113 deletions
diff --git a/eigen/test/eigen2/eigen2_cholesky.cpp b/eigen/test/eigen2/eigen2_cholesky.cpp
deleted file mode 100644
index 9c4b6f5..0000000
--- a/eigen/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)) );
-  }
-}