// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2008-2009 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" template<typename MatrixType> void syrk(const MatrixType& m) { typedef typename MatrixType::Index Index; typedef typename MatrixType::Scalar Scalar; typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime, RowMajor> RMatrixType; typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic> Rhs1; typedef Matrix<Scalar, Dynamic, MatrixType::RowsAtCompileTime> Rhs2; typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic,RowMajor> Rhs3; Index rows = m.rows(); Index cols = m.cols(); MatrixType m1 = MatrixType::Random(rows, cols), m2 = MatrixType::Random(rows, cols), m3 = MatrixType::Random(rows, cols); RMatrixType rm2 = MatrixType::Random(rows, cols); Rhs1 rhs1 = Rhs1::Random(internal::random<int>(1,320), cols); Rhs1 rhs11 = Rhs1::Random(rhs1.rows(), cols); Rhs2 rhs2 = Rhs2::Random(rows, internal::random<int>(1,320)); Rhs2 rhs22 = Rhs2::Random(rows, rhs2.cols()); Rhs3 rhs3 = Rhs3::Random(internal::random<int>(1,320), rows); Scalar s1 = internal::random<Scalar>(); Index c = internal::random<Index>(0,cols-1); m2.setZero(); VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(rhs2,s1)._expression()), ((s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); m2.setZero(); VERIFY_IS_APPROX(((m2.template triangularView<Lower>() += s1 * rhs2 * rhs22.adjoint()).nestedExpression()), ((s1 * rhs2 * rhs22.adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); m2.setZero(); VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs2,s1)._expression(), (s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<Upper>().toDenseMatrix()); m2.setZero(); VERIFY_IS_APPROX((m2.template triangularView<Upper>() += s1 * rhs22 * rhs2.adjoint()).nestedExpression(), (s1 * rhs22 * rhs2.adjoint()).eval().template triangularView<Upper>().toDenseMatrix()); m2.setZero(); VERIFY_IS_APPROX(m2.template selfadjointView<Lower>().rankUpdate(rhs1.adjoint(),s1)._expression(), (s1 * rhs1.adjoint() * rhs1).eval().template triangularView<Lower>().toDenseMatrix()); m2.setZero(); VERIFY_IS_APPROX((m2.template triangularView<Lower>() += s1 * rhs11.adjoint() * rhs1).nestedExpression(), (s1 * rhs11.adjoint() * rhs1).eval().template triangularView<Lower>().toDenseMatrix()); m2.setZero(); VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs1.adjoint(),s1)._expression(), (s1 * rhs1.adjoint() * rhs1).eval().template triangularView<Upper>().toDenseMatrix()); VERIFY_IS_APPROX((m2.template triangularView<Upper>() = s1 * rhs1.adjoint() * rhs11).nestedExpression(), (s1 * rhs1.adjoint() * rhs11).eval().template triangularView<Upper>().toDenseMatrix()); m2.setZero(); VERIFY_IS_APPROX(m2.template selfadjointView<Lower>().rankUpdate(rhs3.adjoint(),s1)._expression(), (s1 * rhs3.adjoint() * rhs3).eval().template triangularView<Lower>().toDenseMatrix()); m2.setZero(); VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs3.adjoint(),s1)._expression(), (s1 * rhs3.adjoint() * rhs3).eval().template triangularView<Upper>().toDenseMatrix()); m2.setZero(); VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.col(c),s1)._expression()), ((s1 * m1.col(c) * m1.col(c).adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); m2.setZero(); VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.col(c),s1)._expression()), ((s1 * m1.col(c) * m1.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix())); rm2.setZero(); VERIFY_IS_APPROX((rm2.template selfadjointView<Upper>().rankUpdate(m1.col(c),s1)._expression()), ((s1 * m1.col(c) * m1.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix())); m2.setZero(); VERIFY_IS_APPROX((m2.template triangularView<Upper>() += s1 * m3.col(c) * m1.col(c).adjoint()).nestedExpression(), ((s1 * m3.col(c) * m1.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix())); rm2.setZero(); VERIFY_IS_APPROX((rm2.template triangularView<Upper>() += s1 * m1.col(c) * m3.col(c).adjoint()).nestedExpression(), ((s1 * m1.col(c) * m3.col(c).adjoint()).eval().template triangularView<Upper>().toDenseMatrix())); m2.setZero(); VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.col(c).conjugate(),s1)._expression()), ((s1 * m1.col(c).conjugate() * m1.col(c).conjugate().adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); m2.setZero(); VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.col(c).conjugate(),s1)._expression()), ((s1 * m1.col(c).conjugate() * m1.col(c).conjugate().adjoint()).eval().template triangularView<Upper>().toDenseMatrix())); m2.setZero(); VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.row(c),s1)._expression()), ((s1 * m1.row(c).transpose() * m1.row(c).transpose().adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); rm2.setZero(); VERIFY_IS_APPROX((rm2.template selfadjointView<Lower>().rankUpdate(m1.row(c),s1)._expression()), ((s1 * m1.row(c).transpose() * m1.row(c).transpose().adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); m2.setZero(); VERIFY_IS_APPROX((m2.template triangularView<Lower>() += s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint()).nestedExpression(), ((s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); rm2.setZero(); VERIFY_IS_APPROX((rm2.template triangularView<Lower>() += s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint()).nestedExpression(), ((s1 * m3.row(c).transpose() * m1.row(c).transpose().adjoint()).eval().template triangularView<Lower>().toDenseMatrix())); m2.setZero(); VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.row(c).adjoint(),s1)._expression()), ((s1 * m1.row(c).adjoint() * m1.row(c).adjoint().adjoint()).eval().template triangularView<Upper>().toDenseMatrix())); } void test_product_syrk() { for(int i = 0; i < g_repeat ; i++) { int s; s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE); CALL_SUBTEST_1( syrk(MatrixXf(s, s)) ); CALL_SUBTEST_2( syrk(MatrixXd(s, s)) ); TEST_SET_BUT_UNUSED_VARIABLE(s) s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2); CALL_SUBTEST_3( syrk(MatrixXcf(s, s)) ); CALL_SUBTEST_4( syrk(MatrixXcd(s, s)) ); TEST_SET_BUT_UNUSED_VARIABLE(s) } }