| // 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>() ); |
| } |