1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library 2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra. 3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com> 5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla 7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed 8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include "main.h" 11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType> void diagonal(const MatrixType& m) 13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename MatrixType::Index Index; 15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename MatrixType::Scalar Scalar; 16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index rows = m.rows(); 18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Index cols = m.cols(); 19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MatrixType m1 = MatrixType::Random(rows, cols), 21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m2 = MatrixType::Random(rows, cols); 22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath //check diagonal() 24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1.diagonal(), m1.transpose().diagonal()); 25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m2.diagonal() = 2 * m1.diagonal(); 26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m2.diagonal()[0] *= 3; 27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath if (rows>2) 29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath enum { 317faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez N1 = MatrixType::RowsAtCompileTime>2 ? 2 : 0, 327faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez N2 = MatrixType::RowsAtCompileTime>1 ? -1 : 0 33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath }; 34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // check sub/super diagonal 367faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez if(MatrixType::SizeAtCompileTime!=Dynamic) 37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY(m1.template diagonal<N1>().RowsAtCompileTime == m1.diagonal(N1).size()); 39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY(m1.template diagonal<N2>().RowsAtCompileTime == m1.diagonal(N2).size()); 40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m2.template diagonal<N1>() = 2 * m1.template diagonal<N1>(); 43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m2.template diagonal<N1>(), static_cast<Scalar>(2) * m1.diagonal(N1)); 44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m2.template diagonal<N1>()[0] *= 3; 45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m2.template diagonal<N1>()[0], static_cast<Scalar>(6) * m1.template diagonal<N1>()[0]); 46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m2.template diagonal<N2>() = 2 * m1.template diagonal<N2>(); 49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m2.template diagonal<N2>()[0] *= 3; 50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m2.template diagonal<N2>()[0], static_cast<Scalar>(6) * m1.template diagonal<N2>()[0]); 51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m2.diagonal(N1) = 2 * m1.diagonal(N1); 537faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY_IS_APPROX(m2.template diagonal<N1>(), static_cast<Scalar>(2) * m1.diagonal(N1)); 54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m2.diagonal(N1)[0] *= 3; 55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m2.diagonal(N1)[0], static_cast<Scalar>(6) * m1.diagonal(N1)[0]); 56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m2.diagonal(N2) = 2 * m1.diagonal(N2); 587faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez VERIFY_IS_APPROX(m2.template diagonal<N2>(), static_cast<Scalar>(2) * m1.diagonal(N2)); 59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m2.diagonal(N2)[0] *= 3; 60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m2.diagonal(N2)[0], static_cast<Scalar>(6) * m1.diagonal(N2)[0]); 61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid test_diagonal() 65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for(int i = 0; i < g_repeat; i++) { 67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_1( diagonal(Matrix<float, 1, 1>()) ); 68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_1( diagonal(Matrix<float, 4, 9>()) ); 69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_1( diagonal(Matrix<float, 7, 3>()) ); 70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_2( diagonal(Matrix4d()) ); 71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_2( diagonal(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_2( diagonal(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_2( diagonal(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_1( diagonal(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_1( diagonal(Matrix<float,Dynamic,4>(3, 4)) ); 76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 78