|  | // This file is part of Eigen, a lightweight C++ template library | 
|  | // for linear algebra. | 
|  | // | 
|  | // 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" | 
|  | using namespace std; | 
|  | template<typename MatrixType> void diagonalmatrices(const MatrixType& m) | 
|  | { | 
|  | typedef typename MatrixType::Index Index; | 
|  | typedef typename MatrixType::Scalar Scalar; | 
|  | typedef typename MatrixType::RealScalar RealScalar; | 
|  | enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime }; | 
|  | typedef Matrix<Scalar, Rows, 1> VectorType; | 
|  | typedef Matrix<Scalar, 1, Cols> RowVectorType; | 
|  | typedef Matrix<Scalar, Rows, Rows> SquareMatrixType; | 
|  | typedef DiagonalMatrix<Scalar, Rows> LeftDiagonalMatrix; | 
|  | typedef DiagonalMatrix<Scalar, Cols> RightDiagonalMatrix; | 
|  | typedef Matrix<Scalar, Rows==Dynamic?Dynamic:2*Rows, Cols==Dynamic?Dynamic:2*Cols> BigMatrix; | 
|  | Index rows = m.rows(); | 
|  | Index cols = m.cols(); | 
|  |  | 
|  | MatrixType m1 = MatrixType::Random(rows, cols), | 
|  | m2 = MatrixType::Random(rows, cols); | 
|  | VectorType v1 = VectorType::Random(rows), | 
|  | v2 = VectorType::Random(rows); | 
|  | RowVectorType rv1 = RowVectorType::Random(cols), | 
|  | rv2 = RowVectorType::Random(cols); | 
|  | LeftDiagonalMatrix ldm1(v1), ldm2(v2); | 
|  | RightDiagonalMatrix rdm1(rv1), rdm2(rv2); | 
|  |  | 
|  | SquareMatrixType sq_m1 (v1.asDiagonal()); | 
|  | VERIFY_IS_APPROX(sq_m1, v1.asDiagonal().toDenseMatrix()); | 
|  | sq_m1 = v1.asDiagonal(); | 
|  | VERIFY_IS_APPROX(sq_m1, v1.asDiagonal().toDenseMatrix()); | 
|  | SquareMatrixType sq_m2 = v1.asDiagonal(); | 
|  | VERIFY_IS_APPROX(sq_m1, sq_m2); | 
|  |  | 
|  | ldm1 = v1.asDiagonal(); | 
|  | LeftDiagonalMatrix ldm3(v1); | 
|  | VERIFY_IS_APPROX(ldm1.diagonal(), ldm3.diagonal()); | 
|  | LeftDiagonalMatrix ldm4 = v1.asDiagonal(); | 
|  | VERIFY_IS_APPROX(ldm1.diagonal(), ldm4.diagonal()); | 
|  |  | 
|  | sq_m1.block(0,0,rows,rows) = ldm1; | 
|  | VERIFY_IS_APPROX(sq_m1, ldm1.toDenseMatrix()); | 
|  | sq_m1.transpose() = ldm1; | 
|  | VERIFY_IS_APPROX(sq_m1, ldm1.toDenseMatrix()); | 
|  |  | 
|  | Index i = ei_random<Index>(0, rows-1); | 
|  | Index j = ei_random<Index>(0, cols-1); | 
|  |  | 
|  | VERIFY_IS_APPROX( ((ldm1 * m1)(i,j))  , ldm1.diagonal()(i) * m1(i,j) ); | 
|  | VERIFY_IS_APPROX( ((ldm1 * (m1+m2))(i,j))  , ldm1.diagonal()(i) * (m1+m2)(i,j) ); | 
|  | VERIFY_IS_APPROX( ((m1 * rdm1)(i,j))  , rdm1.diagonal()(j) * m1(i,j) ); | 
|  | VERIFY_IS_APPROX( ((v1.asDiagonal() * m1)(i,j))  , v1(i) * m1(i,j) ); | 
|  | VERIFY_IS_APPROX( ((m1 * rv1.asDiagonal())(i,j))  , rv1(j) * m1(i,j) ); | 
|  | VERIFY_IS_APPROX( (((v1+v2).asDiagonal() * m1)(i,j))  , (v1+v2)(i) * m1(i,j) ); | 
|  | VERIFY_IS_APPROX( (((v1+v2).asDiagonal() * (m1+m2))(i,j))  , (v1+v2)(i) * (m1+m2)(i,j) ); | 
|  | VERIFY_IS_APPROX( ((m1 * (rv1+rv2).asDiagonal())(i,j))  , (rv1+rv2)(j) * m1(i,j) ); | 
|  | VERIFY_IS_APPROX( (((m1+m2) * (rv1+rv2).asDiagonal())(i,j))  , (rv1+rv2)(j) * (m1+m2)(i,j) ); | 
|  |  | 
|  | BigMatrix big; | 
|  | big.setZero(2*rows, 2*cols); | 
|  |  | 
|  | big.block(i,j,rows,cols) = m1; | 
|  | big.block(i,j,rows,cols) = v1.asDiagonal() * big.block(i,j,rows,cols); | 
|  |  | 
|  | VERIFY_IS_APPROX((big.block(i,j,rows,cols)) , v1.asDiagonal() * m1 ); | 
|  |  | 
|  | big.block(i,j,rows,cols) = m1; | 
|  | big.block(i,j,rows,cols) = big.block(i,j,rows,cols) * rv1.asDiagonal(); | 
|  | VERIFY_IS_APPROX((big.block(i,j,rows,cols)) , m1 * rv1.asDiagonal() ); | 
|  |  | 
|  | } | 
|  |  | 
|  | void test_diagonalmatrices() | 
|  | { | 
|  | for(int i = 0; i < g_repeat; i++) { | 
|  | CALL_SUBTEST_1( diagonalmatrices(Matrix<float, 1, 1>()) ); | 
|  | CALL_SUBTEST_2( diagonalmatrices(Matrix3f()) ); | 
|  | CALL_SUBTEST_3( diagonalmatrices(Matrix<double,3,3,RowMajor>()) ); | 
|  | CALL_SUBTEST_4( diagonalmatrices(Matrix4d()) ); | 
|  | CALL_SUBTEST_5( diagonalmatrices(Matrix<float,4,4,RowMajor>()) ); | 
|  | CALL_SUBTEST_6( diagonalmatrices(MatrixXcf(3, 5)) ); | 
|  | CALL_SUBTEST_7( diagonalmatrices(MatrixXi(10, 8)) ); | 
|  | CALL_SUBTEST_8( diagonalmatrices(Matrix<double,Dynamic,Dynamic,RowMajor>(20, 20)) ); | 
|  | CALL_SUBTEST_9( diagonalmatrices(MatrixXf(21, 24)) ); | 
|  | } | 
|  | } |