don't index Eigen

1 files changed, 0 insertions, 189 deletions

diff --git a/eigen/unsupported/test/matrix_function.cpp b/eigen/unsupported/test/matrix_function.cpp
deleted file mode 100644
index 6a2b219..0000000
--- a/eigen/unsupported/test/matrix_function.cpp
+++ /dev/null
@@ -1,189 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
-//
-// 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 <unsupported/Eigen/MatrixFunctions>
-
-// Variant of VERIFY_IS_APPROX which uses absolute error instead of
-// relative error.
-#define VERIFY_IS_APPROX_ABS(a, b) VERIFY(test_isApprox_abs(a, b))
-
-template<typename Type1, typename Type2>
-inline bool test_isApprox_abs(const Type1& a, const Type2& b)
-{
-  return ((a-b).array().abs() < test_precision<typename Type1::RealScalar>()).all();
-}
-
-
-// Returns a matrix with eigenvalues clustered around 0, 1 and 2.
-template<typename MatrixType>
-MatrixType randomMatrixWithRealEivals(const typename MatrixType::Index size)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::RealScalar RealScalar;
-  MatrixType diag = MatrixType::Zero(size, size);
-  for (Index i = 0; i < size; ++i) {
-    diag(i, i) = Scalar(RealScalar(internal::random<int>(0,2)))
-      + internal::random<Scalar>() * Scalar(RealScalar(0.01));
-  }
-  MatrixType A = MatrixType::Random(size, size);
-  HouseholderQR<MatrixType> QRofA(A);
-  return QRofA.householderQ().inverse() * diag * QRofA.householderQ();
-}
-
-template <typename MatrixType, int IsComplex = NumTraits<typename internal::traits<MatrixType>::Scalar>::IsComplex>
-struct randomMatrixWithImagEivals
-{
-  // Returns a matrix with eigenvalues clustered around 0 and +/- i.
-  static MatrixType run(const typename MatrixType::Index size);
-};
-
-// Partial specialization for real matrices
-template<typename MatrixType>
-struct randomMatrixWithImagEivals<MatrixType, 0>
-{
-  static MatrixType run(const typename MatrixType::Index size)
-  {
-    typedef typename MatrixType::Scalar Scalar;
-    MatrixType diag = MatrixType::Zero(size, size);
-    Index i = 0;
-    while (i < size) {
-      Index randomInt = internal::random<Index>(-1, 1);
-      if (randomInt == 0 || i == size-1) {
-        diag(i, i) = internal::random<Scalar>() * Scalar(0.01);
-        ++i;
-      } else {
-        Scalar alpha = Scalar(randomInt) + internal::random<Scalar>() * Scalar(0.01);
-        diag(i, i+1) = alpha;
-        diag(i+1, i) = -alpha;
-        i += 2;
-      }
-    }
-    MatrixType A = MatrixType::Random(size, size);
-    HouseholderQR<MatrixType> QRofA(A);
-    return QRofA.householderQ().inverse() * diag * QRofA.householderQ();
-  }
-};
-
-// Partial specialization for complex matrices
-template<typename MatrixType>
-struct randomMatrixWithImagEivals<MatrixType, 1>
-{
-  static MatrixType run(const typename MatrixType::Index size)
-  {
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename MatrixType::RealScalar RealScalar;
-    const Scalar imagUnit(0, 1);
-    MatrixType diag = MatrixType::Zero(size, size);
-    for (Index i = 0; i < size; ++i) {
-      diag(i, i) = Scalar(RealScalar(internal::random<Index>(-1, 1))) * imagUnit
-        + internal::random<Scalar>() * Scalar(RealScalar(0.01));
-    }
-    MatrixType A = MatrixType::Random(size, size);
-    HouseholderQR<MatrixType> QRofA(A);
-    return QRofA.householderQ().inverse() * diag * QRofA.householderQ();
-  }
-};
-
-
-template<typename MatrixType>
-void testMatrixExponential(const MatrixType& A)
-{
-  typedef typename internal::traits<MatrixType>::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef std::complex<RealScalar> ComplexScalar;
-
-  VERIFY_IS_APPROX(A.exp(), A.matrixFunction(internal::stem_function_exp<ComplexScalar>));
-}
-
-template<typename MatrixType>
-void testMatrixLogarithm(const MatrixType& A)
-{
-  typedef typename internal::traits<MatrixType>::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-
-  MatrixType scaledA;
-  RealScalar maxImagPartOfSpectrum = A.eigenvalues().imag().cwiseAbs().maxCoeff();
-  if (maxImagPartOfSpectrum >= RealScalar(0.9L * EIGEN_PI))
-    scaledA = A * RealScalar(0.9L * EIGEN_PI) / maxImagPartOfSpectrum;
-  else
-    scaledA = A;
-
-  // identity X.exp().log() = X only holds if Im(lambda) < pi for all eigenvalues of X
-  MatrixType expA = scaledA.exp();
-  MatrixType logExpA = expA.log();
-  VERIFY_IS_APPROX(logExpA, scaledA);
-}
-
-template<typename MatrixType>
-void testHyperbolicFunctions(const MatrixType& A)
-{
-  // Need to use absolute error because of possible cancellation when
-  // adding/subtracting expA and expmA.
-  VERIFY_IS_APPROX_ABS(A.sinh(), (A.exp() - (-A).exp()) / 2);
-  VERIFY_IS_APPROX_ABS(A.cosh(), (A.exp() + (-A).exp()) / 2);
-}
-
-template<typename MatrixType>
-void testGonioFunctions(const MatrixType& A)
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef std::complex<RealScalar> ComplexScalar;
-  typedef Matrix<ComplexScalar, MatrixType::RowsAtCompileTime, 
-                 MatrixType::ColsAtCompileTime, MatrixType::Options> ComplexMatrix;
-
-  ComplexScalar imagUnit(0,1);
-  ComplexScalar two(2,0);
-
-  ComplexMatrix Ac = A.template cast<ComplexScalar>();
-  
-  ComplexMatrix exp_iA = (imagUnit * Ac).exp();
-  ComplexMatrix exp_miA = (-imagUnit * Ac).exp();
-  
-  ComplexMatrix sinAc = A.sin().template cast<ComplexScalar>();
-  VERIFY_IS_APPROX_ABS(sinAc, (exp_iA - exp_miA) / (two*imagUnit));
-  
-  ComplexMatrix cosAc = A.cos().template cast<ComplexScalar>();
-  VERIFY_IS_APPROX_ABS(cosAc, (exp_iA + exp_miA) / 2);
-}
-
-template<typename MatrixType>
-void testMatrix(const MatrixType& A)
-{
-  testMatrixExponential(A);
-  testMatrixLogarithm(A);
-  testHyperbolicFunctions(A);
-  testGonioFunctions(A);
-}
-
-template<typename MatrixType>
-void testMatrixType(const MatrixType& m)
-{
-  // Matrices with clustered eigenvalue lead to different code paths
-  // in MatrixFunction.h and are thus useful for testing.
-
-  const Index size = m.rows();
-  for (int i = 0; i < g_repeat; i++) {
-    testMatrix(MatrixType::Random(size, size).eval());
-    testMatrix(randomMatrixWithRealEivals<MatrixType>(size));
-    testMatrix(randomMatrixWithImagEivals<MatrixType>::run(size));
-  }
-}
-
-void test_matrix_function()
-{
-  CALL_SUBTEST_1(testMatrixType(Matrix<float,1,1>()));
-  CALL_SUBTEST_2(testMatrixType(Matrix3cf()));
-  CALL_SUBTEST_3(testMatrixType(MatrixXf(8,8)));
-  CALL_SUBTEST_4(testMatrixType(Matrix2d()));
-  CALL_SUBTEST_5(testMatrixType(Matrix<double,5,5,RowMajor>()));
-  CALL_SUBTEST_6(testMatrixType(Matrix4cd()));
-  CALL_SUBTEST_7(testMatrixType(MatrixXd(13,13)));
-}