| // This file is part of Eigen, a lightweight C++ template library | 
 | // for linear algebra. | 
 | // | 
 | // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr> | 
 | // | 
 | // 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(const MatrixType& m) { | 
 |   Index rows = m.rows(); | 
 |   Index cols = m.cols(); | 
 |  | 
 |   typedef typename MatrixType::Scalar Scalar; | 
 |   typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> MatrixQType; | 
 |  | 
 |   MatrixType a = MatrixType::Random(rows, cols); | 
 |   HouseholderQR<MatrixType> qrOfA(a); | 
 |  | 
 |   MatrixQType q = qrOfA.householderQ(); | 
 |   VERIFY_IS_UNITARY(q); | 
 |  | 
 |   MatrixType r = qrOfA.matrixQR().template triangularView<Upper>(); | 
 |   VERIFY_IS_APPROX(a, qrOfA.householderQ() * r); | 
 | } | 
 |  | 
 | template <typename MatrixType, int Cols2> | 
 | void qr_fixedsize() { | 
 |   enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime }; | 
 |   typedef typename MatrixType::Scalar Scalar; | 
 |   Matrix<Scalar, Rows, Cols> m1 = Matrix<Scalar, Rows, Cols>::Random(); | 
 |   HouseholderQR<Matrix<Scalar, Rows, Cols> > qr(m1); | 
 |  | 
 |   Matrix<Scalar, Rows, Cols> 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<Scalar, Cols, Cols2>, Matrix<Scalar, Rows, Cols2> >(m1, qr, Rows, Cols, Cols2); | 
 | } | 
 |  | 
 | template <typename MatrixType> | 
 | void qr_invertible() { | 
 |   using std::abs; | 
 |   using std::log; | 
 |   using std::max; | 
 |   using std::pow; | 
 |   typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar; | 
 |   typedef typename MatrixType::Scalar Scalar; | 
 |  | 
 |   STATIC_CHECK((internal::is_same<typename HouseholderQR<MatrixType>::StorageIndex, int>::value)); | 
 |  | 
 |   int size = internal::random<int>(10, 50); | 
 |  | 
 |   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 * 4); | 
 |     m1 += a * a.adjoint(); | 
 |   } | 
 |  | 
 |   HouseholderQR<MatrixType> qr(m1); | 
 |  | 
 |   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>(); | 
 |   Scalar det = m1.diagonal().prod(); | 
 |   RealScalar absdet = abs(det); | 
 |   m3 = qr.householderQ();  // get a unitary | 
 |   m1 = m3 * m1 * m3.adjoint(); | 
 |   qr.compute(m1); | 
 |   VERIFY_IS_APPROX(log(absdet), qr.logAbsDeterminant()); | 
 |   VERIFY_IS_APPROX(numext::sign(det), qr.signDeterminant()); | 
 |   // 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 | 
 |   RealScalar tol = | 
 |       numext::maxi(RealScalar(pow(0.5, size)), numext::maxi<RealScalar>(abs(absdet), abs(qr.absDeterminant()))); | 
 |   VERIFY_IS_MUCH_SMALLER_THAN(abs(det - qr.determinant()), tol); | 
 |   VERIFY_IS_MUCH_SMALLER_THAN(abs(absdet - qr.absDeterminant()), tol); | 
 | } | 
 |  | 
 | template <typename MatrixType> | 
 | void qr_verify_assert() { | 
 |   MatrixType tmp; | 
 |  | 
 |   HouseholderQR<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.householderQ()) | 
 |   VERIFY_RAISES_ASSERT(qr.determinant()) | 
 |   VERIFY_RAISES_ASSERT(qr.absDeterminant()) | 
 |   VERIFY_RAISES_ASSERT(qr.signDeterminant()) | 
 | } | 
 |  | 
 | EIGEN_DECLARE_TEST(qr) { | 
 |   for (int i = 0; i < g_repeat; i++) { | 
 |     CALL_SUBTEST_1( | 
 |         qr(MatrixXf(internal::random<int>(1, EIGEN_TEST_MAX_SIZE), internal::random<int>(1, EIGEN_TEST_MAX_SIZE)))); | 
 |     CALL_SUBTEST_2(qr(MatrixXcd(internal::random<int>(1, EIGEN_TEST_MAX_SIZE / 2), | 
 |                                 internal::random<int>(1, EIGEN_TEST_MAX_SIZE / 2)))); | 
 |     CALL_SUBTEST_3((qr_fixedsize<Matrix<float, 3, 4>, 2>())); | 
 |     CALL_SUBTEST_4((qr_fixedsize<Matrix<double, 6, 2>, 4>())); | 
 |     CALL_SUBTEST_5((qr_fixedsize<Matrix<double, 2, 5>, 7>())); | 
 |     CALL_SUBTEST_11(qr(Matrix<float, 1, 1>())); | 
 |   } | 
 |  | 
 |   for (int i = 0; i < g_repeat; i++) { | 
 |     CALL_SUBTEST_1(qr_invertible<MatrixXf>()); | 
 |     CALL_SUBTEST_6(qr_invertible<MatrixXd>()); | 
 |     CALL_SUBTEST_7(qr_invertible<MatrixXcf>()); | 
 |     CALL_SUBTEST_8(qr_invertible<MatrixXcd>()); | 
 |   } | 
 |  | 
 |   CALL_SUBTEST_9(qr_verify_assert<Matrix3f>()); | 
 |   CALL_SUBTEST_10(qr_verify_assert<Matrix3d>()); | 
 |   CALL_SUBTEST_1(qr_verify_assert<MatrixXf>()); | 
 |   CALL_SUBTEST_6(qr_verify_assert<MatrixXd>()); | 
 |   CALL_SUBTEST_7(qr_verify_assert<MatrixXcf>()); | 
 |   CALL_SUBTEST_8(qr_verify_assert<MatrixXcd>()); | 
 |  | 
 |   // Test problem size constructors | 
 |   CALL_SUBTEST_12(HouseholderQR<MatrixXf>(10, 20)); | 
 | } |