| // 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::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; |
| int rows = m.rows(); |
| int 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()); |
| |
| int i = ei_random<int>(0, rows-1); |
| int j = ei_random<int>(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)) ); |
| } |
| } |