diff options
Diffstat (limited to 'eigen/test/product_syrk.cpp')
-rw-r--r-- | eigen/test/product_syrk.cpp | 135 |
1 files changed, 135 insertions, 0 deletions
diff --git a/eigen/test/product_syrk.cpp b/eigen/test/product_syrk.cpp new file mode 100644 index 0000000..73c9500 --- /dev/null +++ b/eigen/test/product_syrk.cpp @@ -0,0 +1,135 @@ +// 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)) ); + s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE); + CALL_SUBTEST_2( syrk(MatrixXd(s, s)) ); + s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2); + CALL_SUBTEST_3( syrk(MatrixXcf(s, s)) ); + s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2); + CALL_SUBTEST_4( syrk(MatrixXcd(s, s)) ); + } +} |