86 lines
3.6 KiB
C++
86 lines
3.6 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#include "main.h"
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template <typename MatrixType>
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void product_selfadjoint(const MatrixType& m) {
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typedef typename MatrixType::Scalar Scalar;
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typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
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typedef Matrix<Scalar, 1, MatrixType::RowsAtCompileTime> RowVectorType;
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typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, Dynamic, RowMajor> RhsMatrixType;
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Index rows = m.rows();
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Index cols = m.cols();
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MatrixType m1 = MatrixType::Random(rows, cols), m2 = MatrixType::Random(rows, cols), m3;
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VectorType v1 = VectorType::Random(rows), v2 = VectorType::Random(rows), v3(rows);
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RowVectorType r1 = RowVectorType::Random(rows), r2 = RowVectorType::Random(rows);
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RhsMatrixType m4 = RhsMatrixType::Random(rows, 10);
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Scalar s1 = internal::random<Scalar>(), s2 = internal::random<Scalar>(), s3 = internal::random<Scalar>();
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m1 = (m1.adjoint() + m1).eval();
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// rank2 update
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m2 = m1.template triangularView<Lower>();
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m2.template selfadjointView<Lower>().rankUpdate(v1, v2);
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VERIFY_IS_APPROX(m2, (m1 + v1 * v2.adjoint() + v2 * v1.adjoint()).template triangularView<Lower>().toDenseMatrix());
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m2 = m1.template triangularView<Upper>();
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m2.template selfadjointView<Upper>().rankUpdate(-v1, s2 * v2, s3);
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VERIFY_IS_APPROX(m2, (m1 + (s3 * (-v1) * (s2 * v2).adjoint() + numext::conj(s3) * (s2 * v2) * (-v1).adjoint()))
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.template triangularView<Upper>()
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.toDenseMatrix());
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m2 = m1.template triangularView<Upper>();
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m2.template selfadjointView<Upper>().rankUpdate(-s2 * r1.adjoint(), r2.adjoint() * s3, s1);
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VERIFY_IS_APPROX(m2, (m1 + s1 * (-s2 * r1.adjoint()) * (r2.adjoint() * s3).adjoint() +
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numext::conj(s1) * (r2.adjoint() * s3) * (-s2 * r1.adjoint()).adjoint())
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.template triangularView<Upper>()
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.toDenseMatrix());
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if (rows > 1) {
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m2 = m1.template triangularView<Lower>();
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m2.block(1, 1, rows - 1, cols - 1)
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.template selfadjointView<Lower>()
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.rankUpdate(v1.tail(rows - 1), v2.head(cols - 1));
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m3 = m1;
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m3.block(1, 1, rows - 1, cols - 1) +=
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v1.tail(rows - 1) * v2.head(cols - 1).adjoint() + v2.head(cols - 1) * v1.tail(rows - 1).adjoint();
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VERIFY_IS_APPROX(m2, m3.template triangularView<Lower>().toDenseMatrix());
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}
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}
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EIGEN_DECLARE_TEST(product_selfadjoint) {
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int s = 0;
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for (int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST_1(product_selfadjoint(Matrix<float, 1, 1>()));
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CALL_SUBTEST_2(product_selfadjoint(Matrix<float, 2, 2>()));
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CALL_SUBTEST_3(product_selfadjoint(Matrix3d()));
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s = internal::random<int>(1, EIGEN_TEST_MAX_SIZE / 2);
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CALL_SUBTEST_4(product_selfadjoint(MatrixXcf(s, s)));
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TEST_SET_BUT_UNUSED_VARIABLE(s)
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s = internal::random<int>(1, EIGEN_TEST_MAX_SIZE / 2);
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CALL_SUBTEST_5(product_selfadjoint(MatrixXcd(s, s)));
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TEST_SET_BUT_UNUSED_VARIABLE(s)
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s = internal::random<int>(1, EIGEN_TEST_MAX_SIZE);
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CALL_SUBTEST_6(product_selfadjoint(MatrixXd(s, s)));
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TEST_SET_BUT_UNUSED_VARIABLE(s)
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s = internal::random<int>(1, EIGEN_TEST_MAX_SIZE);
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CALL_SUBTEST_7(product_selfadjoint(Matrix<float, Dynamic, Dynamic, RowMajor>(s, s)));
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TEST_SET_BUT_UNUSED_VARIABLE(s)
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}
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}
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