|  | // This file is part of Eigen, a lightweight C++ template library | 
|  | // for linear algebra. | 
|  | // | 
|  | // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com> | 
|  | // | 
|  | // 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" | 
|  | using namespace std; | 
|  | template<typename MatrixType> void diagonalmatrices(const MatrixType& m) | 
|  | { | 
|  | typedef typename MatrixType::Scalar Scalar; | 
|  | 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 Matrix<Scalar, Dynamic, Dynamic> DynMatrixType; | 
|  | 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); | 
|  |  | 
|  | Scalar s1 = internal::random<Scalar>(); | 
|  |  | 
|  | 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) ); | 
|  |  | 
|  | if(rows>1) | 
|  | { | 
|  | DynMatrixType tmp = m1.topRows(rows/2), res; | 
|  | VERIFY_IS_APPROX( (res = m1.topRows(rows/2) * rv1.asDiagonal()), tmp * rv1.asDiagonal() ); | 
|  | VERIFY_IS_APPROX( (res = v1.head(rows/2).asDiagonal()*m1.topRows(rows/2)), v1.head(rows/2).asDiagonal()*tmp ); | 
|  | } | 
|  |  | 
|  | 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() ); | 
|  |  | 
|  |  | 
|  | // scalar multiple | 
|  | VERIFY_IS_APPROX(LeftDiagonalMatrix(ldm1*s1).diagonal(), ldm1.diagonal() * s1); | 
|  | VERIFY_IS_APPROX(LeftDiagonalMatrix(s1*ldm1).diagonal(), s1 * ldm1.diagonal()); | 
|  |  | 
|  | VERIFY_IS_APPROX(m1 * (rdm1 * s1), (m1 * rdm1) * s1); | 
|  | VERIFY_IS_APPROX(m1 * (s1 * rdm1), (m1 * rdm1) * s1); | 
|  |  | 
|  | // Diagonal to dense | 
|  | sq_m1.setRandom(); | 
|  | sq_m2 = sq_m1; | 
|  | VERIFY_IS_APPROX( (sq_m1 += (s1*v1).asDiagonal()), sq_m2 += (s1*v1).asDiagonal().toDenseMatrix() ); | 
|  | VERIFY_IS_APPROX( (sq_m1 -= (s1*v1).asDiagonal()), sq_m2 -= (s1*v1).asDiagonal().toDenseMatrix() ); | 
|  | VERIFY_IS_APPROX( (sq_m1 = (s1*v1).asDiagonal()), (s1*v1).asDiagonal().toDenseMatrix() ); | 
|  |  | 
|  | sq_m1.setRandom(); | 
|  | sq_m2 = v1.asDiagonal(); | 
|  | sq_m2 = sq_m1 * sq_m2; | 
|  | VERIFY_IS_APPROX( (sq_m1*v1.asDiagonal()).col(i), sq_m2.col(i) ); | 
|  | VERIFY_IS_APPROX( (sq_m1*v1.asDiagonal()).row(i), sq_m2.row(i) ); | 
|  |  | 
|  | sq_m1 = v1.asDiagonal(); | 
|  | sq_m2 = v2.asDiagonal(); | 
|  | SquareMatrixType sq_m3 = v1.asDiagonal(); | 
|  | VERIFY_IS_APPROX( sq_m3 = v1.asDiagonal() + v2.asDiagonal(), sq_m1 + sq_m2); | 
|  | VERIFY_IS_APPROX( sq_m3 = v1.asDiagonal() - v2.asDiagonal(), sq_m1 - sq_m2); | 
|  | VERIFY_IS_APPROX( sq_m3 = v1.asDiagonal() - 2*v2.asDiagonal() + v1.asDiagonal(), sq_m1 - 2*sq_m2 + sq_m1); | 
|  | } | 
|  |  | 
|  | template<typename MatrixType> void as_scalar_product(const MatrixType& m) | 
|  | { | 
|  | typedef typename MatrixType::Scalar Scalar; | 
|  | typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType; | 
|  | typedef Matrix<Scalar, Dynamic, Dynamic> DynMatrixType; | 
|  | typedef Matrix<Scalar, Dynamic, 1> DynVectorType; | 
|  | typedef Matrix<Scalar, 1, Dynamic> DynRowVectorType; | 
|  |  | 
|  | Index rows = m.rows(); | 
|  | Index depth = internal::random<Index>(1,EIGEN_TEST_MAX_SIZE); | 
|  |  | 
|  | VectorType v1 = VectorType::Random(rows); | 
|  | DynVectorType     dv1  = DynVectorType::Random(depth); | 
|  | DynRowVectorType  drv1 = DynRowVectorType::Random(depth); | 
|  | DynMatrixType     dm1  = dv1; | 
|  | DynMatrixType     drm1 = drv1; | 
|  |  | 
|  | Scalar s = v1(0); | 
|  |  | 
|  | VERIFY_IS_APPROX( v1.asDiagonal() * drv1, s*drv1 ); | 
|  | VERIFY_IS_APPROX( dv1 * v1.asDiagonal(), dv1*s ); | 
|  |  | 
|  | VERIFY_IS_APPROX( v1.asDiagonal() * drm1, s*drm1 ); | 
|  | VERIFY_IS_APPROX( dm1 * v1.asDiagonal(), dm1*s ); | 
|  | } | 
|  |  | 
|  | template<int> | 
|  | void bug987() | 
|  | { | 
|  | Matrix3Xd points = Matrix3Xd::Random(3, 3); | 
|  | Vector2d diag = Vector2d::Random(); | 
|  | Matrix2Xd tmp1 = points.topRows<2>(), res1, res2; | 
|  | VERIFY_IS_APPROX( res1 = diag.asDiagonal() * points.topRows<2>(), res2 = diag.asDiagonal() * tmp1 ); | 
|  | Matrix2d tmp2 = points.topLeftCorner<2,2>(); | 
|  | VERIFY_IS_APPROX(( res1 = points.topLeftCorner<2,2>()*diag.asDiagonal()) , res2 = tmp2*diag.asDiagonal() ); | 
|  | } | 
|  |  | 
|  | EIGEN_DECLARE_TEST(diagonalmatrices) | 
|  | { | 
|  | for(int i = 0; i < g_repeat; i++) { | 
|  | CALL_SUBTEST_1( diagonalmatrices(Matrix<float, 1, 1>()) ); | 
|  | CALL_SUBTEST_1( as_scalar_product(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(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); | 
|  | CALL_SUBTEST_6( as_scalar_product(MatrixXcf(1,1)) ); | 
|  | CALL_SUBTEST_7( diagonalmatrices(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); | 
|  | CALL_SUBTEST_8( diagonalmatrices(Matrix<double,Dynamic,Dynamic,RowMajor>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); | 
|  | CALL_SUBTEST_9( diagonalmatrices(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); | 
|  | CALL_SUBTEST_9( diagonalmatrices(MatrixXf(1,1)) ); | 
|  | CALL_SUBTEST_9( as_scalar_product(MatrixXf(1,1)) ); | 
|  | } | 
|  | CALL_SUBTEST_10( bug987<0>() ); | 
|  | } |