| // This file is part of Eigen, a lightweight C++ template library | 
 | // for linear algebra. | 
 | // | 
 | // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr> | 
 | // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com> | 
 | // | 
 | // Eigen is free software; you can redistribute it and/or | 
 | // modify it under the terms of the GNU Lesser General Public | 
 | // License as published by the Free Software Foundation; either | 
 | // version 3 of the License, or (at your option) any later version. | 
 | // | 
 | // Alternatively, you can redistribute it and/or | 
 | // modify it under the terms of the GNU General Public License as | 
 | // published by the Free Software Foundation; either version 2 of | 
 | // the License, or (at your option) any later version. | 
 | // | 
 | // Eigen is distributed in the hope that it will be useful, but WITHOUT ANY | 
 | // WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS | 
 | // FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the | 
 | // GNU General Public License for more details. | 
 | // | 
 | // You should have received a copy of the GNU Lesser General Public | 
 | // License and a copy of the GNU General Public License along with | 
 | // Eigen. If not, see <http://www.gnu.org/licenses/>. | 
 |  | 
 | #include "main.h" | 
 | #include <Eigen/QR> | 
 |  | 
 | template<typename MatrixType> void qr() | 
 | { | 
 |   typedef typename MatrixType::Index Index; | 
 |  | 
 |   Index rows = ei_random<Index>(20,200), cols = ei_random<int>(20,200), cols2 = ei_random<int>(20,200); | 
 |   Index rank = ei_random<Index>(1, std::min(rows, cols)-1); | 
 |  | 
 |   typedef typename MatrixType::Scalar Scalar; | 
 |   typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> MatrixQType; | 
 |   typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> VectorType; | 
 |   MatrixType m1; | 
 |   createRandomPIMatrixOfRank(rank,rows,cols,m1); | 
 |   FullPivHouseholderQR<MatrixType> qr(m1); | 
 |   VERIFY(rank == qr.rank()); | 
 |   VERIFY(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); | 
 |  | 
 |   MatrixType m2 = MatrixType::Random(cols,cols2); | 
 |   MatrixType m3 = m1*m2; | 
 |   m2 = MatrixType::Random(cols,cols2); | 
 |   m2 = qr.solve(m3); | 
 |   VERIFY_IS_APPROX(m3, m1*m2); | 
 | } | 
 |  | 
 | template<typename MatrixType> void qr_invertible() | 
 | { | 
 |   typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar; | 
 |   typedef typename MatrixType::Scalar Scalar; | 
 |  | 
 |   int size = ei_random<int>(10,50); | 
 |  | 
 |   MatrixType m1(size, size), m2(size, size), m3(size, size); | 
 |   m1 = MatrixType::Random(size,size); | 
 |  | 
 |   if (ei_is_same_type<RealScalar,float>::ret) | 
 |   { | 
 |     // 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()); | 
 |  | 
 |   m3 = MatrixType::Random(size,size); | 
 |   m2 = qr.solve(m3); | 
 |   VERIFY_IS_APPROX(m3, m1*m2); | 
 |  | 
 |   // now construct a matrix with prescribed determinant | 
 |   m1.setZero(); | 
 |   for(int i = 0; i < size; i++) m1(i,i) = ei_random<Scalar>(); | 
 |   RealScalar absdet = ei_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(ei_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.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()) | 
 | } | 
 |  | 
 | void test_qr_fullpivoting() | 
 | { | 
 |  for(int i = 0; i < 1; i++) { | 
 |     // FIXME : very weird bug here | 
 | //     CALL_SUBTEST(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)); | 
 | } |