| 1 | // This file is part of Eigen, a lightweight C++ template library
|
|---|
| 2 | // for linear algebra.
|
|---|
| 3 | //
|
|---|
| 4 | // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
|
|---|
| 5 | //
|
|---|
| 6 | // This Source Code Form is subject to the terms of the Mozilla
|
|---|
| 7 | // Public License v. 2.0. If a copy of the MPL was not distributed
|
|---|
| 8 | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
|
|---|
| 9 |
|
|---|
| 10 | #include "main.h"
|
|---|
| 11 | using namespace std;
|
|---|
| 12 | template<typename MatrixType> void diagonalmatrices(const MatrixType& m)
|
|---|
| 13 | {
|
|---|
| 14 | typedef typename MatrixType::Index Index;
|
|---|
| 15 | typedef typename MatrixType::Scalar Scalar;
|
|---|
| 16 | enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime };
|
|---|
| 17 | typedef Matrix<Scalar, Rows, 1> VectorType;
|
|---|
| 18 | typedef Matrix<Scalar, 1, Cols> RowVectorType;
|
|---|
| 19 | typedef Matrix<Scalar, Rows, Rows> SquareMatrixType;
|
|---|
| 20 | typedef DiagonalMatrix<Scalar, Rows> LeftDiagonalMatrix;
|
|---|
| 21 | typedef DiagonalMatrix<Scalar, Cols> RightDiagonalMatrix;
|
|---|
| 22 | typedef Matrix<Scalar, Rows==Dynamic?Dynamic:2*Rows, Cols==Dynamic?Dynamic:2*Cols> BigMatrix;
|
|---|
| 23 | Index rows = m.rows();
|
|---|
| 24 | Index cols = m.cols();
|
|---|
| 25 |
|
|---|
| 26 | MatrixType m1 = MatrixType::Random(rows, cols),
|
|---|
| 27 | m2 = MatrixType::Random(rows, cols);
|
|---|
| 28 | VectorType v1 = VectorType::Random(rows),
|
|---|
| 29 | v2 = VectorType::Random(rows);
|
|---|
| 30 | RowVectorType rv1 = RowVectorType::Random(cols),
|
|---|
| 31 | rv2 = RowVectorType::Random(cols);
|
|---|
| 32 | LeftDiagonalMatrix ldm1(v1), ldm2(v2);
|
|---|
| 33 | RightDiagonalMatrix rdm1(rv1), rdm2(rv2);
|
|---|
| 34 |
|
|---|
| 35 | Scalar s1 = internal::random<Scalar>();
|
|---|
| 36 |
|
|---|
| 37 | SquareMatrixType sq_m1 (v1.asDiagonal());
|
|---|
| 38 | VERIFY_IS_APPROX(sq_m1, v1.asDiagonal().toDenseMatrix());
|
|---|
| 39 | sq_m1 = v1.asDiagonal();
|
|---|
| 40 | VERIFY_IS_APPROX(sq_m1, v1.asDiagonal().toDenseMatrix());
|
|---|
| 41 | SquareMatrixType sq_m2 = v1.asDiagonal();
|
|---|
| 42 | VERIFY_IS_APPROX(sq_m1, sq_m2);
|
|---|
| 43 |
|
|---|
| 44 | ldm1 = v1.asDiagonal();
|
|---|
| 45 | LeftDiagonalMatrix ldm3(v1);
|
|---|
| 46 | VERIFY_IS_APPROX(ldm1.diagonal(), ldm3.diagonal());
|
|---|
| 47 | LeftDiagonalMatrix ldm4 = v1.asDiagonal();
|
|---|
| 48 | VERIFY_IS_APPROX(ldm1.diagonal(), ldm4.diagonal());
|
|---|
| 49 |
|
|---|
| 50 | sq_m1.block(0,0,rows,rows) = ldm1;
|
|---|
| 51 | VERIFY_IS_APPROX(sq_m1, ldm1.toDenseMatrix());
|
|---|
| 52 | sq_m1.transpose() = ldm1;
|
|---|
| 53 | VERIFY_IS_APPROX(sq_m1, ldm1.toDenseMatrix());
|
|---|
| 54 |
|
|---|
| 55 | Index i = internal::random<Index>(0, rows-1);
|
|---|
| 56 | Index j = internal::random<Index>(0, cols-1);
|
|---|
| 57 |
|
|---|
| 58 | VERIFY_IS_APPROX( ((ldm1 * m1)(i,j)) , ldm1.diagonal()(i) * m1(i,j) );
|
|---|
| 59 | VERIFY_IS_APPROX( ((ldm1 * (m1+m2))(i,j)) , ldm1.diagonal()(i) * (m1+m2)(i,j) );
|
|---|
| 60 | VERIFY_IS_APPROX( ((m1 * rdm1)(i,j)) , rdm1.diagonal()(j) * m1(i,j) );
|
|---|
| 61 | VERIFY_IS_APPROX( ((v1.asDiagonal() * m1)(i,j)) , v1(i) * m1(i,j) );
|
|---|
| 62 | VERIFY_IS_APPROX( ((m1 * rv1.asDiagonal())(i,j)) , rv1(j) * m1(i,j) );
|
|---|
| 63 | VERIFY_IS_APPROX( (((v1+v2).asDiagonal() * m1)(i,j)) , (v1+v2)(i) * m1(i,j) );
|
|---|
| 64 | VERIFY_IS_APPROX( (((v1+v2).asDiagonal() * (m1+m2))(i,j)) , (v1+v2)(i) * (m1+m2)(i,j) );
|
|---|
| 65 | VERIFY_IS_APPROX( ((m1 * (rv1+rv2).asDiagonal())(i,j)) , (rv1+rv2)(j) * m1(i,j) );
|
|---|
| 66 | VERIFY_IS_APPROX( (((m1+m2) * (rv1+rv2).asDiagonal())(i,j)) , (rv1+rv2)(j) * (m1+m2)(i,j) );
|
|---|
| 67 |
|
|---|
| 68 | BigMatrix big;
|
|---|
| 69 | big.setZero(2*rows, 2*cols);
|
|---|
| 70 |
|
|---|
| 71 | big.block(i,j,rows,cols) = m1;
|
|---|
| 72 | big.block(i,j,rows,cols) = v1.asDiagonal() * big.block(i,j,rows,cols);
|
|---|
| 73 |
|
|---|
| 74 | VERIFY_IS_APPROX((big.block(i,j,rows,cols)) , v1.asDiagonal() * m1 );
|
|---|
| 75 |
|
|---|
| 76 | big.block(i,j,rows,cols) = m1;
|
|---|
| 77 | big.block(i,j,rows,cols) = big.block(i,j,rows,cols) * rv1.asDiagonal();
|
|---|
| 78 | VERIFY_IS_APPROX((big.block(i,j,rows,cols)) , m1 * rv1.asDiagonal() );
|
|---|
| 79 |
|
|---|
| 80 |
|
|---|
| 81 | // scalar multiple
|
|---|
| 82 | VERIFY_IS_APPROX(LeftDiagonalMatrix(ldm1*s1).diagonal(), ldm1.diagonal() * s1);
|
|---|
| 83 | VERIFY_IS_APPROX(LeftDiagonalMatrix(s1*ldm1).diagonal(), s1 * ldm1.diagonal());
|
|---|
| 84 |
|
|---|
| 85 | VERIFY_IS_APPROX(m1 * (rdm1 * s1), (m1 * rdm1) * s1);
|
|---|
| 86 | VERIFY_IS_APPROX(m1 * (s1 * rdm1), (m1 * rdm1) * s1);
|
|---|
| 87 | }
|
|---|
| 88 |
|
|---|
| 89 | void test_diagonalmatrices()
|
|---|
| 90 | {
|
|---|
| 91 | for(int i = 0; i < g_repeat; i++) {
|
|---|
| 92 | CALL_SUBTEST_1( diagonalmatrices(Matrix<float, 1, 1>()) );
|
|---|
| 93 | CALL_SUBTEST_2( diagonalmatrices(Matrix3f()) );
|
|---|
| 94 | CALL_SUBTEST_3( diagonalmatrices(Matrix<double,3,3,RowMajor>()) );
|
|---|
| 95 | CALL_SUBTEST_4( diagonalmatrices(Matrix4d()) );
|
|---|
| 96 | CALL_SUBTEST_5( diagonalmatrices(Matrix<float,4,4,RowMajor>()) );
|
|---|
| 97 | CALL_SUBTEST_6( diagonalmatrices(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
|
|---|
| 98 | CALL_SUBTEST_7( diagonalmatrices(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
|
|---|
| 99 | 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))) );
|
|---|
| 100 | CALL_SUBTEST_9( diagonalmatrices(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
|
|---|
| 101 | }
|
|---|
| 102 | }
|
|---|
