| // 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 = internal::random<Index>(0, rows-1); | |
| Index j = internal::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)) ); | |
| } | |
| } |