| // This file is part of Eigen, a lightweight C++ template library | |
| // for linear algebra. | |
| // | |
| // 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/LU> | |
| namespace { | |
| template <typename Scalar> | |
| void constructors() { | |
| typedef Matrix<Scalar, 3, 1> Vector; | |
| const Vector v = Vector::Random(); | |
| // l-value | |
| const SkewSymmetricMatrix3<Scalar> s1(v); | |
| const Vector& v1 = s1.vector(); | |
| VERIFY_IS_APPROX(v1, v); | |
| VERIFY(s1.cols() == 3); | |
| VERIFY(s1.rows() == 3); | |
| // r-value | |
| const SkewSymmetricMatrix3<Scalar> s2(std::move(v)); | |
| VERIFY_IS_APPROX(v1, s2.vector()); | |
| VERIFY_IS_APPROX(s1.toDenseMatrix(), s2.toDenseMatrix()); | |
| // from scalars | |
| SkewSymmetricMatrix3<Scalar> s4(v1(0), v1(1), v1(2)); | |
| VERIFY_IS_APPROX(v1, s4.vector()); | |
| // constructors with four vectors do not compile | |
| // Matrix<Scalar, 4, 1> vector4 = Matrix<Scalar, 4, 1>::Random(); | |
| // SkewSymmetricMatrix3<Scalar> s5(vector4); | |
| } | |
| template <typename Scalar> | |
| void assignments() { | |
| typedef Matrix<Scalar, 3, 1> Vector; | |
| typedef Matrix<Scalar, 3, 3> SquareMatrix; | |
| const Vector v = Vector::Random(); | |
| // assign to square matrix | |
| SquareMatrix sq; | |
| sq = v.asSkewSymmetric(); | |
| VERIFY(sq.isSkewSymmetric()); | |
| // assign to skew symmetric matrix | |
| SkewSymmetricMatrix3<Scalar> sk; | |
| sk = v.asSkewSymmetric(); | |
| VERIFY_IS_APPROX(v, sk.vector()); | |
| } | |
| template <typename Scalar> | |
| void plusMinus() { | |
| typedef Matrix<Scalar, 3, 1> Vector; | |
| typedef Matrix<Scalar, 3, 3> SquareMatrix; | |
| const Vector v1 = Vector::Random(); | |
| const Vector v2 = Vector::Random(); | |
| SquareMatrix sq1; | |
| sq1 = v1.asSkewSymmetric(); | |
| SquareMatrix sq2; | |
| sq2 = v2.asSkewSymmetric(); | |
| SkewSymmetricMatrix3<Scalar> sk1; | |
| sk1 = v1.asSkewSymmetric(); | |
| SkewSymmetricMatrix3<Scalar> sk2; | |
| sk2 = v2.asSkewSymmetric(); | |
| VERIFY_IS_APPROX((sk1 + sk2).toDenseMatrix(), sq1 + sq2); | |
| VERIFY_IS_APPROX((sk1 - sk2).toDenseMatrix(), sq1 - sq2); | |
| SquareMatrix sq3 = v1.asSkewSymmetric(); | |
| VERIFY_IS_APPROX(sq3 = v1.asSkewSymmetric() + v2.asSkewSymmetric(), sq1 + sq2); | |
| VERIFY_IS_APPROX(sq3 = v1.asSkewSymmetric() - v2.asSkewSymmetric(), sq1 - sq2); | |
| VERIFY_IS_APPROX(sq3 = v1.asSkewSymmetric() - 2 * v2.asSkewSymmetric() + v1.asSkewSymmetric(), sq1 - 2 * sq2 + sq1); | |
| VERIFY_IS_APPROX((sk1 + sk1).vector(), 2 * v1); | |
| VERIFY((sk1 - sk1).vector().isZero()); | |
| VERIFY((sk1 - sk1).toDenseMatrix().isZero()); | |
| } | |
| template <typename Scalar> | |
| void multiplyScale() { | |
| typedef Matrix<Scalar, 3, 1> Vector; | |
| typedef Matrix<Scalar, 3, 3> SquareMatrix; | |
| const Vector v1 = Vector::Random(); | |
| SquareMatrix sq1; | |
| sq1 = v1.asSkewSymmetric(); | |
| SkewSymmetricMatrix3<Scalar> sk1; | |
| sk1 = v1.asSkewSymmetric(); | |
| const Scalar s1 = internal::random<Scalar>(); | |
| VERIFY_IS_APPROX(SkewSymmetricMatrix3<Scalar>(sk1 * s1).vector(), sk1.vector() * s1); | |
| VERIFY_IS_APPROX(SkewSymmetricMatrix3<Scalar>(s1 * sk1).vector(), s1 * sk1.vector()); | |
| VERIFY_IS_APPROX(sq1 * (sk1 * s1), (sq1 * sk1) * s1); | |
| const Vector v2 = Vector::Random(); | |
| SquareMatrix sq2; | |
| sq2 = v2.asSkewSymmetric(); | |
| SkewSymmetricMatrix3<Scalar> sk2; | |
| sk2 = v2.asSkewSymmetric(); | |
| VERIFY_IS_APPROX(sk1 * sk2, sq1 * sq2); | |
| // null space | |
| VERIFY((sk1 * v1).isZero()); | |
| VERIFY((sk2 * v2).isZero()); | |
| } | |
| template <typename Matrix> | |
| void skewSymmetricMultiplication(const Matrix& m) { | |
| typedef Eigen::Matrix<typename Matrix::Scalar, 3, 1> Vector; | |
| const Vector v = Vector::Random(); | |
| const Matrix m1 = Matrix::Random(m.rows(), m.cols()); | |
| const SkewSymmetricMatrix3<typename Matrix::Scalar> sk = v.asSkewSymmetric(); | |
| VERIFY_IS_APPROX(m1.transpose() * (sk * m1), (m1.transpose() * sk) * m1); | |
| VERIFY((m1.transpose() * (sk * m1)).isSkewSymmetric()); | |
| } | |
| template <typename Scalar> | |
| void traceAndDet() { | |
| typedef Matrix<Scalar, 3, 1> Vector; | |
| const Vector v = Vector::Random(); | |
| // this does not work, values larger than 1.e-08 can be seen | |
| // VERIFY_IS_APPROX(sq.determinant(), static_cast<Scalar>(0)); | |
| VERIFY_IS_APPROX(v.asSkewSymmetric().determinant(), static_cast<Scalar>(0)); | |
| VERIFY_IS_APPROX(v.asSkewSymmetric().toDenseMatrix().trace(), static_cast<Scalar>(0)); | |
| } | |
| template <typename Scalar> | |
| void transpose() { | |
| typedef Matrix<Scalar, 3, 1> Vector; | |
| const Vector v = Vector::Random(); | |
| // By definition of a skew symmetric matrix: A^T = -A | |
| VERIFY_IS_APPROX(v.asSkewSymmetric().toDenseMatrix().transpose(), v.asSkewSymmetric().transpose().toDenseMatrix()); | |
| VERIFY_IS_APPROX(v.asSkewSymmetric().transpose().vector(), (-v).asSkewSymmetric().vector()); | |
| } | |
| template <typename Scalar> | |
| void exponentialIdentity() { | |
| typedef Matrix<Scalar, 3, 1> Vector; | |
| const Vector v1 = Vector::Zero(); | |
| VERIFY(v1.asSkewSymmetric().exponential().isIdentity()); | |
| Vector v2 = Vector::Random(); | |
| v2.normalize(); | |
| VERIFY((2 * EIGEN_PI * v2).asSkewSymmetric().exponential().isIdentity()); | |
| Vector v3; | |
| const auto precision = static_cast<Scalar>(1.1) * NumTraits<Scalar>::dummy_precision(); | |
| v3 << 0, 0, precision; | |
| VERIFY(v3.asSkewSymmetric().exponential().isIdentity(precision)); | |
| } | |
| template <typename Scalar> | |
| void exponentialOrthogonality() { | |
| typedef Matrix<Scalar, 3, 1> Vector; | |
| typedef Matrix<Scalar, 3, 3> SquareMatrix; | |
| const Vector v = Vector::Random(); | |
| SquareMatrix sq = v.asSkewSymmetric().exponential(); | |
| VERIFY(sq.isUnitary()); | |
| } | |
| template <typename Scalar> | |
| void exponentialRotation() { | |
| typedef Matrix<Scalar, 3, 1> Vector; | |
| typedef Matrix<Scalar, 3, 3> SquareMatrix; | |
| // rotation axis is invariant | |
| const Vector v1 = Vector::Random(); | |
| const SquareMatrix r1 = v1.asSkewSymmetric().exponential(); | |
| VERIFY_IS_APPROX(r1 * v1, v1); | |
| // rotate around z-axis | |
| Vector v2; | |
| v2 << 0, 0, Scalar(EIGEN_PI); | |
| const SquareMatrix r2 = v2.asSkewSymmetric().exponential(); | |
| VERIFY_IS_APPROX(r2 * (Vector() << 1, 0, 0).finished(), (Vector() << -1, 0, 0).finished()); | |
| VERIFY_IS_APPROX(r2 * (Vector() << 0, 1, 0).finished(), (Vector() << 0, -1, 0).finished()); | |
| } | |
| } // namespace | |
| EIGEN_DECLARE_TEST(skew_symmetric_matrix3) { | |
| for (int i = 0; i < g_repeat; i++) { | |
| CALL_SUBTEST_1(constructors<float>()); | |
| CALL_SUBTEST_1(constructors<double>()); | |
| CALL_SUBTEST_1(assignments<float>()); | |
| CALL_SUBTEST_1(assignments<double>()); | |
| CALL_SUBTEST_2(plusMinus<float>()); | |
| CALL_SUBTEST_2(plusMinus<double>()); | |
| CALL_SUBTEST_2(multiplyScale<float>()); | |
| CALL_SUBTEST_2(multiplyScale<double>()); | |
| CALL_SUBTEST_2(skewSymmetricMultiplication(MatrixXf(3, internal::random<int>(3, EIGEN_TEST_MAX_SIZE)))); | |
| CALL_SUBTEST_2(skewSymmetricMultiplication(MatrixXd(3, internal::random<int>(3, EIGEN_TEST_MAX_SIZE)))); | |
| CALL_SUBTEST_2(traceAndDet<float>()); | |
| CALL_SUBTEST_2(traceAndDet<double>()); | |
| CALL_SUBTEST_2(transpose<float>()); | |
| CALL_SUBTEST_2(transpose<double>()); | |
| CALL_SUBTEST_3(exponentialIdentity<float>()); | |
| CALL_SUBTEST_3(exponentialIdentity<double>()); | |
| CALL_SUBTEST_3(exponentialOrthogonality<float>()); | |
| CALL_SUBTEST_3(exponentialOrthogonality<double>()); | |
| CALL_SUBTEST_3(exponentialRotation<float>()); | |
| CALL_SUBTEST_3(exponentialRotation<double>()); | |
| } | |
| } |