// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2008 Gael Guennebaud // // 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 #include "solverbase.h" template void qr(const MatrixType& m) { Index rows = m.rows(); Index cols = m.cols(); typedef typename MatrixType::Scalar Scalar; typedef Matrix MatrixQType; MatrixType a = MatrixType::Random(rows,cols); HouseholderQR qrOfA(a); MatrixQType q = qrOfA.householderQ(); VERIFY_IS_UNITARY(q); MatrixType r = qrOfA.matrixQR().template triangularView(); VERIFY_IS_APPROX(a, qrOfA.householderQ() * r); } template void qr_fixedsize() { enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime }; typedef typename MatrixType::Scalar Scalar; Matrix m1 = Matrix::Random(); HouseholderQR > qr(m1); Matrix r = qr.matrixQR(); // FIXME need better way to construct trapezoid for(int i = 0; i < Rows; i++) for(int j = 0; j < Cols; j++) if(i>j) r(i,j) = Scalar(0); VERIFY_IS_APPROX(m1, qr.householderQ() * r); check_solverbase, Matrix >(m1, qr, Rows, Cols, Cols2); } template void qr_invertible() { using std::log; using std::abs; using std::pow; using std::max; typedef typename NumTraits::Real RealScalar; typedef typename MatrixType::Scalar Scalar; STATIC_CHECK(( internal::is_same::StorageIndex,int>::value )); int size = internal::random(10,50); MatrixType m1(size, size), m2(size, size), m3(size, size); m1 = MatrixType::Random(size,size); if (internal::is_same::value) { // let's build a matrix more stable to inverse MatrixType a = MatrixType::Random(size,size*4); m1 += a * a.adjoint(); } HouseholderQR qr(m1); check_solverbase(m1, qr, size, size, size); // now construct a matrix with prescribed determinant m1.setZero(); for(int i = 0; i < size; i++) m1(i,i) = internal::random(); RealScalar absdet = abs(m1.diagonal().prod()); m3 = qr.householderQ(); // get a unitary m1 = m3 * m1 * m3; qr.compute(m1); VERIFY_IS_APPROX(log(absdet), qr.logAbsDeterminant()); // This test is tricky if the determinant becomes too small. // Since we generate random numbers with magnitude range [0,1], the average determinant is 0.5^size VERIFY_IS_MUCH_SMALLER_THAN( abs(absdet-qr.absDeterminant()), numext::maxi(RealScalar(pow(0.5,size)),numext::maxi(abs(absdet),abs(qr.absDeterminant()))) ); } template void qr_verify_assert() { MatrixType tmp; HouseholderQR qr; VERIFY_RAISES_ASSERT(qr.matrixQR()) VERIFY_RAISES_ASSERT(qr.solve(tmp)) VERIFY_RAISES_ASSERT(qr.transpose().solve(tmp)) VERIFY_RAISES_ASSERT(qr.adjoint().solve(tmp)) VERIFY_RAISES_ASSERT(qr.householderQ()) VERIFY_RAISES_ASSERT(qr.absDeterminant()) VERIFY_RAISES_ASSERT(qr.logAbsDeterminant()) } EIGEN_DECLARE_TEST(qr) { for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( qr(MatrixXf(internal::random(1,EIGEN_TEST_MAX_SIZE),internal::random(1,EIGEN_TEST_MAX_SIZE))) ); CALL_SUBTEST_2( qr(MatrixXcd(internal::random(1,EIGEN_TEST_MAX_SIZE/2),internal::random(1,EIGEN_TEST_MAX_SIZE/2))) ); CALL_SUBTEST_3(( qr_fixedsize, 2 >() )); CALL_SUBTEST_4(( qr_fixedsize, 4 >() )); CALL_SUBTEST_5(( qr_fixedsize, 7 >() )); CALL_SUBTEST_11( qr(Matrix()) ); } for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( qr_invertible() ); CALL_SUBTEST_6( qr_invertible() ); CALL_SUBTEST_7( qr_invertible() ); CALL_SUBTEST_8( qr_invertible() ); } CALL_SUBTEST_9(qr_verify_assert()); CALL_SUBTEST_10(qr_verify_assert()); CALL_SUBTEST_1(qr_verify_assert()); CALL_SUBTEST_6(qr_verify_assert()); CALL_SUBTEST_7(qr_verify_assert()); CALL_SUBTEST_8(qr_verify_assert()); // Test problem size constructors CALL_SUBTEST_12(HouseholderQR(10, 20)); }