| // 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, 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>(1,EIGEN_TEST_MAX_SIZE)))); |
| CALL_SUBTEST_2(skewSymmetricMultiplication(MatrixXd(3,internal::random<int>(1,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>()); |
| } |
| } |