1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library 2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra. 3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr> 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#include <Eigen/Geometry> 12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar,int Size> void homogeneous(void) 14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath /* this test covers the following files: 16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Homogeneous.h 17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath */ 18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef Matrix<Scalar,Size,Size> MatrixType; 20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef Matrix<Scalar,Size,1, ColMajor> VectorType; 21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef Matrix<Scalar,Size+1,Size> HMatrixType; 23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef Matrix<Scalar,Size+1,1> HVectorType; 24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef Matrix<Scalar,Size,Size+1> T1MatrixType; 26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef Matrix<Scalar,Size+1,Size+1> T2MatrixType; 27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef Matrix<Scalar,Size+1,Size> T3MatrixType; 28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VectorType v0 = VectorType::Random(), 30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath ones = VectorType::Ones(); 31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath HVectorType hv0 = HVectorType::Random(); 33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MatrixType m0 = MatrixType::Random(); 35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath HMatrixType hm0 = HMatrixType::Random(); 37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath hv0 << v0, 1; 39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(v0.homogeneous(), hv0); 40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(v0, hv0.hnormalized()); 412b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang 422b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang VERIFY_IS_APPROX(v0.homogeneous().sum(), hv0.sum()); 432b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang VERIFY_IS_APPROX(v0.homogeneous().minCoeff(), hv0.minCoeff()); 442b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang VERIFY_IS_APPROX(v0.homogeneous().maxCoeff(), hv0.maxCoeff()); 45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath hm0 << m0, ones.transpose(); 47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m0.colwise().homogeneous(), hm0); 48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m0, hm0.colwise().hnormalized()); 49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath hm0.row(Size-1).setRandom(); 50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for(int j=0; j<Size; ++j) 51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m0.col(j) = hm0.col(j).head(Size) / hm0(Size,j); 52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m0, hm0.colwise().hnormalized()); 53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath T1MatrixType t1 = T1MatrixType::Random(); 55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(t1 * (v0.homogeneous().eval()), t1 * v0.homogeneous()); 56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(t1 * (m0.colwise().homogeneous().eval()), t1 * m0.colwise().homogeneous()); 57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath T2MatrixType t2 = T2MatrixType::Random(); 59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(t2 * (v0.homogeneous().eval()), t2 * v0.homogeneous()); 60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(t2 * (m0.colwise().homogeneous().eval()), t2 * m0.colwise().homogeneous()); 612b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang VERIFY_IS_APPROX(t2 * (v0.homogeneous().asDiagonal()), t2 * hv0.asDiagonal()); 622b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang VERIFY_IS_APPROX((v0.homogeneous().asDiagonal()) * t2, hv0.asDiagonal() * t2); 63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX((v0.transpose().rowwise().homogeneous().eval()) * t2, 65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath v0.transpose().rowwise().homogeneous() * t2); 66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX((m0.transpose().rowwise().homogeneous().eval()) * t2, 67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m0.transpose().rowwise().homogeneous() * t2); 68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath T3MatrixType t3 = T3MatrixType::Random(); 70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX((v0.transpose().rowwise().homogeneous().eval()) * t3, 71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath v0.transpose().rowwise().homogeneous() * t3); 72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX((m0.transpose().rowwise().homogeneous().eval()) * t3, 73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m0.transpose().rowwise().homogeneous() * t3); 74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // test product with a Transform object 76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Transform<Scalar, Size, Affine> aff; 77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Transform<Scalar, Size, AffineCompact> caff; 78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Transform<Scalar, Size, Projective> proj; 79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Matrix<Scalar, Size, Dynamic> pts; 80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Matrix<Scalar, Size+1, Dynamic> pts1, pts2; 81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath aff.affine().setRandom(); 83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath proj = caff = aff; 84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath pts.setRandom(Size,internal::random<int>(1,20)); 85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath pts1 = pts.colwise().homogeneous(); 87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(aff * pts.colwise().homogeneous(), (aff * pts1).colwise().hnormalized()); 88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(caff * pts.colwise().homogeneous(), (caff * pts1).colwise().hnormalized()); 89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(proj * pts.colwise().homogeneous(), (proj * pts1)); 902b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang 91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX((aff * pts1).colwise().hnormalized(), aff * pts); 92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX((caff * pts1).colwise().hnormalized(), caff * pts); 93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath pts2 = pts1; 95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath pts2.row(Size).setRandom(); 96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX((aff * pts2).colwise().hnormalized(), aff * pts2.colwise().hnormalized()); 97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX((caff * pts2).colwise().hnormalized(), caff * pts2.colwise().hnormalized()); 98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX((proj * pts2).colwise().hnormalized(), (proj * pts2.colwise().hnormalized().colwise().homogeneous()).colwise().hnormalized()); 992b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang 1002b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang // Test combination of homogeneous 1012b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang 1022b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang VERIFY_IS_APPROX( (t2 * v0.homogeneous()).hnormalized(), 1032b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang (t2.template topLeftCorner<Size,Size>() * v0 + t2.template topRightCorner<Size,1>()) 1042b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang / ((t2.template bottomLeftCorner<1,Size>()*v0).value() + t2(Size,Size)) ); 1052b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang 1062b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang VERIFY_IS_APPROX( (t2 * pts.colwise().homogeneous()).colwise().hnormalized(), 1072b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang (Matrix<Scalar, Size+1, Dynamic>(t2 * pts1).colwise().hnormalized()) ); 1082b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang 1092b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang VERIFY_IS_APPROX( (t2 .lazyProduct( v0.homogeneous() )).hnormalized(), (t2 * v0.homogeneous()).hnormalized() ); 1102b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang VERIFY_IS_APPROX( (t2 .lazyProduct ( pts.colwise().homogeneous() )).colwise().hnormalized(), (t2 * pts1).colwise().hnormalized() ); 1112b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang 1122b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang VERIFY_IS_APPROX( (v0.transpose().homogeneous() .lazyProduct( t2 )).hnormalized(), (v0.transpose().homogeneous()*t2).hnormalized() ); 1132b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang VERIFY_IS_APPROX( (pts.transpose().rowwise().homogeneous() .lazyProduct( t2 )).rowwise().hnormalized(), (pts1.transpose()*t2).rowwise().hnormalized() ); 1142b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang 1152b8756b6f1de65d3f8bffab45be6c44ceb7411fcMiao Wang VERIFY_IS_APPROX( (t2.template triangularView<Lower>() * v0.homogeneous()).eval(), (t2.template triangularView<Lower>()*hv0) ); 116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid test_geo_homogeneous() 119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for(int i = 0; i < g_repeat; i++) { 121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_1(( homogeneous<float,1>() )); 122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_2(( homogeneous<double,3>() )); 123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_3(( homogeneous<double,8>() )); 124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 126