// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // 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/. #define EIGEN_NO_STATIC_ASSERT #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::Index Index; 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; Index rows = m.rows(); Index cols = m.cols(); MatrixType m1 = MatrixType::Random(rows, cols), m2 = MatrixType::Random(rows, cols), m3(rows, cols), square = SquareMatrixType::Random(rows, rows); VectorType v1 = VectorType::Random(rows), v2 = VectorType::Random(rows), v3 = VectorType::Random(rows), vzero = VectorType::Zero(rows); Scalar s1 = internal::random<Scalar>(), s2 = internal::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(), internal::conj(s1) * m1.adjoint()); // check basic properties of dot, norm, norm2 typedef typename NumTraits<Scalar>::Real RealScalar; RealScalar ref = NumTraits<Scalar>::IsInteger ? RealScalar(0) : (std::max)((s1 * v1 + s2 * v2).norm(),v3.norm()); VERIFY(test_isApproxWithRef((s1 * v1 + s2 * v2).dot(v3), internal::conj(s1) * v1.dot(v3) + internal::conj(s2) * v2.dot(v3), ref)); VERIFY(test_isApproxWithRef(v3.dot(s1 * v1 + s2 * v2), s1*v3.dot(v1)+s2*v3.dot(v2), ref)); VERIFY_IS_APPROX(internal::conj(v1.dot(v2)), v2.dot(v1)); VERIFY_IS_APPROX(internal::real(v1.dot(v1)), v1.squaredNorm()); if(!NumTraits<Scalar>::IsInteger) { VERIFY_IS_APPROX(v1.squaredNorm(), v1.norm() * v1.norm()); // check normalized() and normalize() VERIFY_IS_APPROX(v1, v1.norm() * v1.normalized()); v3 = v1; v3.normalize(); VERIFY_IS_APPROX(v1, v1.norm() * v3); VERIFY_IS_APPROX(v3, v1.normalized()); VERIFY_IS_APPROX(v3.norm(), RealScalar(1)); } VERIFY_IS_MUCH_SMALLER_THAN(internal::abs(vzero.dot(v1)), static_cast<RealScalar>(1)); // check compatibility of dot and adjoint ref = NumTraits<Scalar>::IsInteger ? 0 : (std::max)((std::max)(v1.norm(),v2.norm()),(std::max)((square * v2).norm(),(square.adjoint() * v1).norm())); VERIFY(test_isApproxWithRef(v1.dot(square * v2), (square.adjoint() * v1).dot(v2), ref)); // like in testBasicStuff, test operator() to check const-qualification Index r = internal::random<Index>(0, rows-1), c = internal::random<Index>(0, cols-1); VERIFY_IS_APPROX(m1.conjugate()(r,c), internal::conj(m1(r,c))); VERIFY_IS_APPROX(m1.adjoint()(c,r), internal::conj(m1(r,c))); if(!NumTraits<Scalar>::IsInteger) { // 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); // check inplace adjoint m3 = m1; m3.adjointInPlace(); VERIFY_IS_APPROX(m3,m1.adjoint()); m3.transposeInPlace(); VERIFY_IS_APPROX(m3,m1.conjugate()); // check mixed dot product typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealVectorType; RealVectorType rv1 = RealVectorType::Random(rows); VERIFY_IS_APPROX(v1.dot(rv1.template cast<Scalar>()), v1.dot(rv1)); VERIFY_IS_APPROX(rv1.template cast<Scalar>().dot(v1), rv1.dot(v1)); } void test_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(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) ); CALL_SUBTEST_5( adjoint(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); CALL_SUBTEST_6( adjoint(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); } // test a large static matrix only once CALL_SUBTEST_7( adjoint(Matrix<float, 100, 100>()) ); #ifdef EIGEN_TEST_PART_4 { MatrixXcf a(10,10), b(10,10); VERIFY_RAISES_ASSERT(a = a.transpose()); VERIFY_RAISES_ASSERT(a = a.transpose() + b); VERIFY_RAISES_ASSERT(a = b + a.transpose()); VERIFY_RAISES_ASSERT(a = a.conjugate().transpose()); VERIFY_RAISES_ASSERT(a = a.adjoint()); VERIFY_RAISES_ASSERT(a = a.adjoint() + b); VERIFY_RAISES_ASSERT(a = b + a.adjoint()); // no assertion should be triggered for these cases: a.transpose() = a.transpose(); a.transpose() += a.transpose(); a.transpose() += a.transpose() + b; a.transpose() = a.adjoint(); a.transpose() += a.adjoint(); a.transpose() += a.adjoint() + b; } #endif }