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							101 lines
						
					
					
						
							4.1 KiB
						
					
					
				| // 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>()) ); | |
| } | |
| 
 |