1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library 2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra. 3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com> 5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla 7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed 8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_NO_STATIC_ASSERT 11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include "main.h" 13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 147faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandeztemplate<bool IsInteger> struct adjoint_specific; 157faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez 167faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandeztemplate<> struct adjoint_specific<true> { 177faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez template<typename Vec, typename Mat, typename Scalar> 187faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez static void run(const Vec& v1, const Vec& v2, Vec& v3, const Mat& square, Scalar s1, Scalar s2) { 197faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY(test_isApproxWithRef((s1 * v1 + s2 * v2).dot(v3), numext::conj(s1) * v1.dot(v3) + numext::conj(s2) * v2.dot(v3), 0)); 207faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY(test_isApproxWithRef(v3.dot(s1 * v1 + s2 * v2), s1*v3.dot(v1)+s2*v3.dot(v2), 0)); 217faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez 227faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez // check compatibility of dot and adjoint 237faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY(test_isApproxWithRef(v1.dot(square * v2), (square.adjoint() * v1).dot(v2), 0)); 247faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez } 257faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez}; 267faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez 277faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandeztemplate<> struct adjoint_specific<false> { 287faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez template<typename Vec, typename Mat, typename Scalar> 297faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez static void run(const Vec& v1, const Vec& v2, Vec& v3, const Mat& square, Scalar s1, Scalar s2) { 307faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez typedef typename NumTraits<Scalar>::Real RealScalar; 317faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez using std::abs; 327faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez 337faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez RealScalar ref = NumTraits<Scalar>::IsInteger ? RealScalar(0) : (std::max)((s1 * v1 + s2 * v2).norm(),v3.norm()); 347faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY(test_isApproxWithRef((s1 * v1 + s2 * v2).dot(v3), numext::conj(s1) * v1.dot(v3) + numext::conj(s2) * v2.dot(v3), ref)); 357faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY(test_isApproxWithRef(v3.dot(s1 * v1 + s2 * v2), s1*v3.dot(v1)+s2*v3.dot(v2), ref)); 367faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez 377faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY_IS_APPROX(v1.squaredNorm(), v1.norm() * v1.norm()); 387faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez // check normalized() and normalize() 397faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY_IS_APPROX(v1, v1.norm() * v1.normalized()); 407faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez v3 = v1; 417faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez v3.normalize(); 427faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY_IS_APPROX(v1, v1.norm() * v3); 437faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY_IS_APPROX(v3, v1.normalized()); 447faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY_IS_APPROX(v3.norm(), RealScalar(1)); 457faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez 467faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez // check compatibility of dot and adjoint 477faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez ref = NumTraits<Scalar>::IsInteger ? 0 : (std::max)((std::max)(v1.norm(),v2.norm()),(std::max)((square * v2).norm(),(square.adjoint() * v1).norm())); 487faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY(internal::isMuchSmallerThan(abs(v1.dot(square * v2) - (square.adjoint() * v1).dot(v2)), ref, test_precision<Scalar>())); 497faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez 507faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez // check that Random().normalized() works: tricky as the random xpr must be evaluated by 517faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez // normalized() in order to produce a consistent result. 527faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY_IS_APPROX(Vec::Random(v1.size()).normalized().norm(), RealScalar(1)); 537faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez } 547faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez}; 557faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez 56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType> void adjoint(const MatrixType& m) 57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath /* this test covers the following files: 59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Transpose.h Conjugate.h Dot.h 60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath */ 617faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez using std::abs; 62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename MatrixType::Index Index; 63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename MatrixType::Scalar Scalar; 64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename NumTraits<Scalar>::Real RealScalar; 65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType; 66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType; 67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index rows = m.rows(); 69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index cols = m.cols(); 70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MatrixType m1 = MatrixType::Random(rows, cols), 72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m2 = MatrixType::Random(rows, cols), 73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3(rows, cols), 74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath square = SquareMatrixType::Random(rows, rows); 75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VectorType v1 = VectorType::Random(rows), 76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath v2 = VectorType::Random(rows), 77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath v3 = VectorType::Random(rows), 78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath vzero = VectorType::Zero(rows); 79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Scalar s1 = internal::random<Scalar>(), 81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath s2 = internal::random<Scalar>(); 82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // check basic compatibility of adjoint, transpose, conjugate 84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1.transpose().conjugate().adjoint(), m1); 85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1.adjoint().conjugate().transpose(), m1); 86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // check multiplicative behavior 88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX((m1.adjoint() * m2).adjoint(), m2.adjoint() * m1); 897faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY_IS_APPROX((s1 * m1).adjoint(), numext::conj(s1) * m1.adjoint()); 90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 917faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez // check basic properties of dot, squaredNorm 927faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY_IS_APPROX(numext::conj(v1.dot(v2)), v2.dot(v1)); 937faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY_IS_APPROX(numext::real(v1.dot(v1)), v1.squaredNorm()); 94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 957faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez adjoint_specific<NumTraits<Scalar>::IsInteger>::run(v1, v2, v3, square, s1, s2); 96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 977faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY_IS_MUCH_SMALLER_THAN(abs(vzero.dot(v1)), static_cast<RealScalar>(1)); 98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // like in testBasicStuff, test operator() to check const-qualification 100c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index r = internal::random<Index>(0, rows-1), 101c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath c = internal::random<Index>(0, cols-1); 1027faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY_IS_APPROX(m1.conjugate()(r,c), numext::conj(m1(r,c))); 1037faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY_IS_APPROX(m1.adjoint()(c,r), numext::conj(m1(r,c))); 104c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 105c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // check inplace transpose 106c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3 = m1; 107c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3.transposeInPlace(); 108c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m3,m1.transpose()); 109c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3.transposeInPlace(); 110c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m3,m1); 111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // check inplace adjoint 113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3 = m1; 114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3.adjointInPlace(); 115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m3,m1.adjoint()); 116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3.transposeInPlace(); 117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m3,m1.conjugate()); 118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // check mixed dot product 120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealVectorType; 121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath RealVectorType rv1 = RealVectorType::Random(rows); 122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(v1.dot(rv1.template cast<Scalar>()), v1.dot(rv1)); 123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(rv1.template cast<Scalar>().dot(v1), rv1.dot(v1)); 124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid test_adjoint() 127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for(int i = 0; i < g_repeat; i++) { 129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_1( adjoint(Matrix<float, 1, 1>()) ); 130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_2( adjoint(Matrix3d()) ); 131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_3( adjoint(Matrix4f()) ); 132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_4( adjoint(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) ); 133c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_5( adjoint(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_6( adjoint(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 135c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // test a large static matrix only once 137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_7( adjoint(Matrix<float, 100, 100>()) ); 138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifdef EIGEN_TEST_PART_4 140c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MatrixXcf a(10,10), b(10,10); 142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_RAISES_ASSERT(a = a.transpose()); 143c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_RAISES_ASSERT(a = a.transpose() + b); 144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_RAISES_ASSERT(a = b + a.transpose()); 145c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_RAISES_ASSERT(a = a.conjugate().transpose()); 146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_RAISES_ASSERT(a = a.adjoint()); 147c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_RAISES_ASSERT(a = a.adjoint() + b); 148c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_RAISES_ASSERT(a = b + a.adjoint()); 149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // no assertion should be triggered for these cases: 151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath a.transpose() = a.transpose(); 152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath a.transpose() += a.transpose(); 153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath a.transpose() += a.transpose() + b; 154c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath a.transpose() = a.adjoint(); 155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath a.transpose() += a.adjoint(); 156c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath a.transpose() += a.adjoint() + b; 157c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 158c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif 159c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 160c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 161