|  | // This file is part of Eigen, a lightweight C++ template library | 
|  | // for linear algebra. | 
|  | // | 
|  | // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr> | 
|  | // | 
|  | // 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" | 
|  | #include <Eigen/Geometry> | 
|  |  | 
|  | template <typename Scalar, int Size> | 
|  | void homogeneous(void) { | 
|  | /* this test covers the following files: | 
|  | Homogeneous.h | 
|  | */ | 
|  |  | 
|  | typedef Matrix<Scalar, Size, Size> MatrixType; | 
|  | typedef Matrix<Scalar, Size, 1, ColMajor> VectorType; | 
|  |  | 
|  | typedef Matrix<Scalar, Size + 1, Size> HMatrixType; | 
|  | typedef Matrix<Scalar, Size + 1, 1> HVectorType; | 
|  |  | 
|  | typedef Matrix<Scalar, Size, Size + 1> T1MatrixType; | 
|  | typedef Matrix<Scalar, Size + 1, Size + 1> T2MatrixType; | 
|  | typedef Matrix<Scalar, Size + 1, Size> T3MatrixType; | 
|  |  | 
|  | VectorType v0 = VectorType::Random(), ones = VectorType::Ones(); | 
|  |  | 
|  | HVectorType hv0 = HVectorType::Random(); | 
|  |  | 
|  | MatrixType m0 = MatrixType::Random(); | 
|  |  | 
|  | HMatrixType hm0 = HMatrixType::Random(); | 
|  |  | 
|  | hv0 << v0, 1; | 
|  | VERIFY_IS_APPROX(v0.homogeneous(), hv0); | 
|  | VERIFY_IS_APPROX(v0, hv0.hnormalized()); | 
|  |  | 
|  | VERIFY_IS_APPROX(v0.homogeneous().sum(), hv0.sum()); | 
|  | VERIFY_IS_APPROX(v0.homogeneous().minCoeff(), hv0.minCoeff()); | 
|  | VERIFY_IS_APPROX(v0.homogeneous().maxCoeff(), hv0.maxCoeff()); | 
|  |  | 
|  | hm0 << m0, ones.transpose(); | 
|  | VERIFY_IS_APPROX(m0.colwise().homogeneous(), hm0); | 
|  | VERIFY_IS_APPROX(m0, hm0.colwise().hnormalized()); | 
|  | hm0.row(Size - 1).setRandom(); | 
|  | for (int j = 0; j < Size; ++j) m0.col(j) = hm0.col(j).head(Size) / hm0(Size, j); | 
|  | VERIFY_IS_APPROX(m0, hm0.colwise().hnormalized()); | 
|  |  | 
|  | T1MatrixType t1 = T1MatrixType::Random(); | 
|  | VERIFY_IS_APPROX(t1 * (v0.homogeneous().eval()), t1 * v0.homogeneous()); | 
|  | VERIFY_IS_APPROX(t1 * (m0.colwise().homogeneous().eval()), t1 * m0.colwise().homogeneous()); | 
|  |  | 
|  | T2MatrixType t2 = T2MatrixType::Random(); | 
|  | VERIFY_IS_APPROX(t2 * (v0.homogeneous().eval()), t2 * v0.homogeneous()); | 
|  | VERIFY_IS_APPROX(t2 * (m0.colwise().homogeneous().eval()), t2 * m0.colwise().homogeneous()); | 
|  | VERIFY_IS_APPROX(t2 * (v0.homogeneous().asDiagonal()), t2 * hv0.asDiagonal()); | 
|  | VERIFY_IS_APPROX((v0.homogeneous().asDiagonal()) * t2, hv0.asDiagonal() * t2); | 
|  |  | 
|  | VERIFY_IS_APPROX((v0.transpose().rowwise().homogeneous().eval()) * t2, v0.transpose().rowwise().homogeneous() * t2); | 
|  | VERIFY_IS_APPROX((m0.transpose().rowwise().homogeneous().eval()) * t2, m0.transpose().rowwise().homogeneous() * t2); | 
|  |  | 
|  | T3MatrixType t3 = T3MatrixType::Random(); | 
|  | VERIFY_IS_APPROX((v0.transpose().rowwise().homogeneous().eval()) * t3, v0.transpose().rowwise().homogeneous() * t3); | 
|  | VERIFY_IS_APPROX((m0.transpose().rowwise().homogeneous().eval()) * t3, m0.transpose().rowwise().homogeneous() * t3); | 
|  |  | 
|  | // test product with a Transform object | 
|  | Transform<Scalar, Size, Affine> aff; | 
|  | Transform<Scalar, Size, AffineCompact> caff; | 
|  | Transform<Scalar, Size, Projective> proj; | 
|  | Matrix<Scalar, Size, Dynamic> pts; | 
|  | Matrix<Scalar, Size + 1, Dynamic> pts1, pts2; | 
|  |  | 
|  | aff.affine().setRandom(); | 
|  | proj = caff = aff; | 
|  | pts.setRandom(Size, internal::random<int>(1, 20)); | 
|  |  | 
|  | pts1 = pts.colwise().homogeneous(); | 
|  | VERIFY_IS_APPROX(aff * pts.colwise().homogeneous(), (aff * pts1).colwise().hnormalized()); | 
|  | VERIFY_IS_APPROX(caff * pts.colwise().homogeneous(), (caff * pts1).colwise().hnormalized()); | 
|  | VERIFY_IS_APPROX(proj * pts.colwise().homogeneous(), (proj * pts1)); | 
|  |  | 
|  | VERIFY_IS_APPROX((aff * pts1).colwise().hnormalized(), aff * pts); | 
|  | VERIFY_IS_APPROX((caff * pts1).colwise().hnormalized(), caff * pts); | 
|  |  | 
|  | pts2 = pts1; | 
|  | pts2.row(Size).setRandom(); | 
|  | VERIFY_IS_APPROX((aff * pts2).colwise().hnormalized(), aff * pts2.colwise().hnormalized()); | 
|  | VERIFY_IS_APPROX((caff * pts2).colwise().hnormalized(), caff * pts2.colwise().hnormalized()); | 
|  | VERIFY_IS_APPROX((proj * pts2).colwise().hnormalized(), | 
|  | (proj * pts2.colwise().hnormalized().colwise().homogeneous()).colwise().hnormalized()); | 
|  |  | 
|  | // Test combination of homogeneous | 
|  |  | 
|  | VERIFY_IS_APPROX((t2 * v0.homogeneous()).hnormalized(), | 
|  | (t2.template topLeftCorner<Size, Size>() * v0 + t2.template topRightCorner<Size, 1>()) / | 
|  | ((t2.template bottomLeftCorner<1, Size>() * v0).value() + t2(Size, Size))); | 
|  |  | 
|  | VERIFY_IS_APPROX((t2 * pts.colwise().homogeneous()).colwise().hnormalized(), | 
|  | (Matrix<Scalar, Size + 1, Dynamic>(t2 * pts1).colwise().hnormalized())); | 
|  |  | 
|  | VERIFY_IS_APPROX((t2.lazyProduct(v0.homogeneous())).hnormalized(), (t2 * v0.homogeneous()).hnormalized()); | 
|  | VERIFY_IS_APPROX((t2.lazyProduct(pts.colwise().homogeneous())).colwise().hnormalized(), | 
|  | (t2 * pts1).colwise().hnormalized()); | 
|  |  | 
|  | VERIFY_IS_APPROX((v0.transpose().homogeneous().lazyProduct(t2)).hnormalized(), | 
|  | (v0.transpose().homogeneous() * t2).hnormalized()); | 
|  | VERIFY_IS_APPROX((pts.transpose().rowwise().homogeneous().lazyProduct(t2)).rowwise().hnormalized(), | 
|  | (pts1.transpose() * t2).rowwise().hnormalized()); | 
|  |  | 
|  | VERIFY_IS_APPROX((t2.template triangularView<Lower>() * v0.homogeneous()).eval(), | 
|  | (t2.template triangularView<Lower>() * hv0)); | 
|  | } | 
|  |  | 
|  | EIGEN_DECLARE_TEST(geo_homogeneous) { | 
|  | for (int i = 0; i < g_repeat; i++) { | 
|  | CALL_SUBTEST_1((homogeneous<float, 1>())); | 
|  | CALL_SUBTEST_2((homogeneous<double, 3>())); | 
|  | CALL_SUBTEST_3((homogeneous<double, 8>())); | 
|  | } | 
|  | } |