| // This file is part of Eigen, a lightweight C++ template library | |
| // for linear algebra. | |
| // | |
| // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> | |
| // Copyright (C) 2009 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" | |
| #include <Eigen/QR> | |
| #include "solverbase.h" | |
| template<typename MatrixType> void qr() | |
| { | |
| STATIC_CHECK(( internal::is_same<typename FullPivHouseholderQR<MatrixType>::StorageIndex,int>::value )); | |
| static const int Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime; | |
| Index max_size = EIGEN_TEST_MAX_SIZE; | |
| Index min_size = numext::maxi(1,EIGEN_TEST_MAX_SIZE/10); | |
| Index rows = Rows == Dynamic ? internal::random<Index>(min_size,max_size) : Rows, | |
| cols = Cols == Dynamic ? internal::random<Index>(min_size,max_size) : Cols, | |
| cols2 = Cols == Dynamic ? internal::random<Index>(min_size,max_size) : Cols, | |
| rank = internal::random<Index>(1, (std::min)(rows, cols)-1); | |
| typedef typename MatrixType::Scalar Scalar; | |
| typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> MatrixQType; | |
| MatrixType m1; | |
| createRandomPIMatrixOfRank(rank,rows,cols,m1); | |
| FullPivHouseholderQR<MatrixType> qr(m1); | |
| VERIFY_IS_EQUAL(rank, qr.rank()); | |
| VERIFY_IS_EQUAL(cols - qr.rank(), qr.dimensionOfKernel()); | |
| VERIFY(!qr.isInjective()); | |
| VERIFY(!qr.isInvertible()); | |
| VERIFY(!qr.isSurjective()); | |
| MatrixType r = qr.matrixQR(); | |
| MatrixQType q = qr.matrixQ(); | |
| VERIFY_IS_UNITARY(q); | |
| // 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); | |
| MatrixType c = qr.matrixQ() * r * qr.colsPermutation().inverse(); | |
| VERIFY_IS_APPROX(m1, c); | |
| // stress the ReturnByValue mechanism | |
| MatrixType tmp; | |
| VERIFY_IS_APPROX(tmp.noalias() = qr.matrixQ() * r, (qr.matrixQ() * r).eval()); | |
| check_solverbase<MatrixType, MatrixType>(m1, qr, rows, cols, cols2); | |
| { | |
| MatrixType m2, m3; | |
| Index size = rows; | |
| do { | |
| m1 = MatrixType::Random(size,size); | |
| qr.compute(m1); | |
| } while(!qr.isInvertible()); | |
| MatrixType m1_inv = qr.inverse(); | |
| m3 = m1 * MatrixType::Random(size,cols2); | |
| m2 = qr.solve(m3); | |
| VERIFY_IS_APPROX(m2, m1_inv*m3); | |
| } | |
| } | |
| template<typename MatrixType> void qr_invertible() | |
| { | |
| using std::log; | |
| using std::abs; | |
| typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar; | |
| typedef typename MatrixType::Scalar Scalar; | |
| Index max_size = numext::mini(50,EIGEN_TEST_MAX_SIZE); | |
| Index min_size = numext::maxi(1,EIGEN_TEST_MAX_SIZE/10); | |
| Index size = internal::random<Index>(min_size,max_size); | |
| MatrixType m1(size, size), m2(size, size), m3(size, size); | |
| m1 = MatrixType::Random(size,size); | |
| if (internal::is_same<RealScalar,float>::value) | |
| { | |
| // let's build a matrix more stable to inverse | |
| MatrixType a = MatrixType::Random(size,size*2); | |
| m1 += a * a.adjoint(); | |
| } | |
| FullPivHouseholderQR<MatrixType> qr(m1); | |
| VERIFY(qr.isInjective()); | |
| VERIFY(qr.isInvertible()); | |
| VERIFY(qr.isSurjective()); | |
| check_solverbase<MatrixType, MatrixType>(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<Scalar>(); | |
| RealScalar absdet = abs(m1.diagonal().prod()); | |
| m3 = qr.matrixQ(); // get a unitary | |
| m1 = m3 * m1 * m3; | |
| qr.compute(m1); | |
| VERIFY_IS_APPROX(absdet, qr.absDeterminant()); | |
| VERIFY_IS_APPROX(log(absdet), qr.logAbsDeterminant()); | |
| } | |
| template<typename MatrixType> void qr_verify_assert() | |
| { | |
| MatrixType tmp; | |
| FullPivHouseholderQR<MatrixType> 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.matrixQ()) | |
| VERIFY_RAISES_ASSERT(qr.dimensionOfKernel()) | |
| VERIFY_RAISES_ASSERT(qr.isInjective()) | |
| VERIFY_RAISES_ASSERT(qr.isSurjective()) | |
| VERIFY_RAISES_ASSERT(qr.isInvertible()) | |
| VERIFY_RAISES_ASSERT(qr.inverse()) | |
| VERIFY_RAISES_ASSERT(qr.absDeterminant()) | |
| VERIFY_RAISES_ASSERT(qr.logAbsDeterminant()) | |
| } | |
| EIGEN_DECLARE_TEST(qr_fullpivoting) | |
| { | |
| for(int i = 0; i < 1; i++) { | |
| CALL_SUBTEST_5( qr<Matrix3f>() ); | |
| CALL_SUBTEST_6( qr<Matrix3d>() ); | |
| CALL_SUBTEST_8( qr<Matrix2f>() ); | |
| CALL_SUBTEST_1( qr<MatrixXf>() ); | |
| CALL_SUBTEST_2( qr<MatrixXd>() ); | |
| CALL_SUBTEST_3( qr<MatrixXcd>() ); | |
| } | |
| for(int i = 0; i < g_repeat; i++) { | |
| CALL_SUBTEST_1( qr_invertible<MatrixXf>() ); | |
| CALL_SUBTEST_2( qr_invertible<MatrixXd>() ); | |
| CALL_SUBTEST_4( qr_invertible<MatrixXcf>() ); | |
| CALL_SUBTEST_3( qr_invertible<MatrixXcd>() ); | |
| } | |
| CALL_SUBTEST_5(qr_verify_assert<Matrix3f>()); | |
| CALL_SUBTEST_6(qr_verify_assert<Matrix3d>()); | |
| CALL_SUBTEST_1(qr_verify_assert<MatrixXf>()); | |
| CALL_SUBTEST_2(qr_verify_assert<MatrixXd>()); | |
| CALL_SUBTEST_4(qr_verify_assert<MatrixXcf>()); | |
| CALL_SUBTEST_3(qr_verify_assert<MatrixXcd>()); | |
| // Test problem size constructors | |
| CALL_SUBTEST_7(FullPivHouseholderQR<MatrixXf>(10, 20)); | |
| CALL_SUBTEST_7((FullPivHouseholderQR<Matrix<float,10,20> >(10,20))); | |
| CALL_SUBTEST_7((FullPivHouseholderQR<Matrix<float,10,20> >(Matrix<float,10,20>::Random()))); | |
| CALL_SUBTEST_7((FullPivHouseholderQR<Matrix<float,20,10> >(20,10))); | |
| CALL_SUBTEST_7((FullPivHouseholderQR<Matrix<float,20,10> >(Matrix<float,20,10>::Random()))); | |
| } |