| // This file is part of Eigen, a lightweight C++ template library | |
| // for linear algebra. | |
| // | |
| // Copyright (C) 2012, 2013 Chen-Pang He <jdh8@ms63.hinet.net> | |
| // | |
| // 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 "matrix_functions.h" | |
| template <typename T> | |
| void test2dRotation(const T& tol) { | |
| Matrix<T, 2, 2> A, B, C; | |
| T angle, c, s; | |
| A << 0, 1, -1, 0; | |
| MatrixPower<Matrix<T, 2, 2> > Apow(A); | |
| for (int i = 0; i <= 20; ++i) { | |
| angle = std::pow(T(10), T(i - 10) / T(5.)); | |
| c = std::cos(angle); | |
| s = std::sin(angle); | |
| B << c, s, -s, c; | |
| C = Apow(std::ldexp(angle, 1) / T(EIGEN_PI)); | |
| std::cout << "test2dRotation: i = " << i << " error powerm = " << relerr(C, B) << '\n'; | |
| VERIFY(C.isApprox(B, tol)); | |
| } | |
| } | |
| template <typename T> | |
| void test2dHyperbolicRotation(const T& tol) { | |
| Matrix<std::complex<T>, 2, 2> A, B, C; | |
| T angle, ch = std::cosh((T)1); | |
| std::complex<T> ish(0, std::sinh((T)1)); | |
| A << ch, ish, -ish, ch; | |
| MatrixPower<Matrix<std::complex<T>, 2, 2> > Apow(A); | |
| for (int i = 0; i <= 20; ++i) { | |
| angle = std::ldexp(static_cast<T>(i - 10), -1); | |
| ch = std::cosh(angle); | |
| ish = std::complex<T>(0, std::sinh(angle)); | |
| B << ch, ish, -ish, ch; | |
| C = Apow(angle); | |
| std::cout << "test2dHyperbolicRotation: i = " << i << " error powerm = " << relerr(C, B) << '\n'; | |
| VERIFY(C.isApprox(B, tol)); | |
| } | |
| } | |
| template <typename T> | |
| void test3dRotation(const T& tol) { | |
| Matrix<T, 3, 1> v; | |
| T angle; | |
| for (int i = 0; i <= 20; ++i) { | |
| v = Matrix<T, 3, 1>::Random(); | |
| v.normalize(); | |
| angle = std::pow(T(10), T(i - 10) / T(5.)); | |
| VERIFY(AngleAxis<T>(angle, v).matrix().isApprox(AngleAxis<T>(1, v).matrix().pow(angle), tol)); | |
| } | |
| } | |
| template <typename MatrixType> | |
| void testGeneral(const MatrixType& m, const typename MatrixType::RealScalar& tol) { | |
| typedef typename MatrixType::RealScalar RealScalar; | |
| MatrixType m1, m2, m3, m4, m5; | |
| RealScalar x, y; | |
| for (int i = 0; i < g_repeat; ++i) { | |
| generateTestMatrix<MatrixType>::run(m1, m.rows()); | |
| MatrixPower<MatrixType> mpow(m1); | |
| x = internal::random<RealScalar>(); | |
| y = internal::random<RealScalar>(); | |
| m2 = mpow(x); | |
| m3 = mpow(y); | |
| m4 = mpow(x + y); | |
| m5.noalias() = m2 * m3; | |
| VERIFY(m4.isApprox(m5, tol)); | |
| m4 = mpow(x * y); | |
| m5 = m2.pow(y); | |
| VERIFY(m4.isApprox(m5, tol)); | |
| m4 = (std::abs(x) * m1).pow(y); | |
| m5 = std::pow(std::abs(x), y) * m3; | |
| VERIFY(m4.isApprox(m5, tol)); | |
| } | |
| } | |
| template <typename MatrixType> | |
| void testSingular(const MatrixType& m_const, const typename MatrixType::RealScalar& tol) { | |
| // we need to pass by reference in order to prevent errors with | |
| // MSVC for aligned data types ... | |
| MatrixType& m = const_cast<MatrixType&>(m_const); | |
| const int IsComplex = NumTraits<typename internal::traits<MatrixType>::Scalar>::IsComplex; | |
| typedef std::conditional_t<IsComplex, TriangularView<MatrixType, Upper>, const MatrixType&> TriangularType; | |
| std::conditional_t<IsComplex, ComplexSchur<MatrixType>, RealSchur<MatrixType> > schur; | |
| MatrixType T; | |
| for (int i = 0; i < g_repeat; ++i) { | |
| m.setRandom(); | |
| m.col(0).fill(0); | |
| schur.compute(m); | |
| T = schur.matrixT(); | |
| const MatrixType& U = schur.matrixU(); | |
| processTriangularMatrix<MatrixType>::run(m, T, U); | |
| MatrixPower<MatrixType> mpow(m); | |
| T = T.sqrt(); | |
| VERIFY(mpow(0.5L).isApprox(U * (TriangularType(T) * U.adjoint()), tol)); | |
| T = T.sqrt(); | |
| VERIFY(mpow(0.25L).isApprox(U * (TriangularType(T) * U.adjoint()), tol)); | |
| T = T.sqrt(); | |
| VERIFY(mpow(0.125L).isApprox(U * (TriangularType(T) * U.adjoint()), tol)); | |
| } | |
| } | |
| template <typename MatrixType> | |
| void testLogThenExp(const MatrixType& m_const, const typename MatrixType::RealScalar& tol) { | |
| // we need to pass by reference in order to prevent errors with | |
| // MSVC for aligned data types ... | |
| MatrixType& m = const_cast<MatrixType&>(m_const); | |
| typedef typename MatrixType::Scalar Scalar; | |
| Scalar x; | |
| for (int i = 0; i < g_repeat; ++i) { | |
| generateTestMatrix<MatrixType>::run(m, m.rows()); | |
| x = internal::random<Scalar>(); | |
| VERIFY(m.pow(x).isApprox((x * m.log()).exp(), tol)); | |
| } | |
| } | |
| typedef Matrix<double, 3, 3, RowMajor> Matrix3dRowMajor; | |
| typedef Matrix<long double, 3, 3> Matrix3e; | |
| typedef Matrix<long double, Dynamic, Dynamic> MatrixXe; | |
| EIGEN_DECLARE_TEST(matrix_power) { | |
| CALL_SUBTEST_2(test2dRotation<double>(1e-13)); | |
| CALL_SUBTEST_1(test2dRotation<float>(2e-5f)); // was 1e-5, relaxed for clang 2.8 / linux / x86-64 | |
| CALL_SUBTEST_9(test2dRotation<long double>(1e-13L)); | |
| CALL_SUBTEST_2(test2dHyperbolicRotation<double>(1e-14)); | |
| CALL_SUBTEST_1(test2dHyperbolicRotation<float>(1e-5f)); | |
| CALL_SUBTEST_9(test2dHyperbolicRotation<long double>(1e-14L)); | |
| CALL_SUBTEST_10(test3dRotation<double>(2e-13)); | |
| CALL_SUBTEST_11(test3dRotation<float>(1e-5f)); | |
| CALL_SUBTEST_12(test3dRotation<long double>(1e-13L)); | |
| CALL_SUBTEST_2(testGeneral(Matrix2d(), 1e-13)); | |
| CALL_SUBTEST_7(testGeneral(Matrix3dRowMajor(), 1e-13)); | |
| CALL_SUBTEST_3(testGeneral(Matrix4cd(), 1e-13)); | |
| CALL_SUBTEST_4(testGeneral(MatrixXd(8, 8), 2e-12)); | |
| CALL_SUBTEST_1(testGeneral(Matrix2f(), 1e-4f)); | |
| CALL_SUBTEST_5(testGeneral(Matrix3cf(), 1e-4f)); | |
| CALL_SUBTEST_8(testGeneral(Matrix4f(), 1e-4f)); | |
| CALL_SUBTEST_6(testGeneral(MatrixXf(2, 2), 1e-3f)); // see bug 614 | |
| CALL_SUBTEST_9(testGeneral(MatrixXe(7, 7), 1e-12L)); | |
| CALL_SUBTEST_10(testGeneral(Matrix3d(), 2e-13)); | |
| CALL_SUBTEST_11(testGeneral(Matrix3f(), 1e-4f)); | |
| CALL_SUBTEST_12(testGeneral(Matrix3e(), 1e-13L)); | |
| CALL_SUBTEST_2(testSingular(Matrix2d(), 1e-13)); | |
| CALL_SUBTEST_7(testSingular(Matrix3dRowMajor(), 1e-13)); | |
| CALL_SUBTEST_3(testSingular(Matrix4cd(), 1e-13)); | |
| CALL_SUBTEST_4(testSingular(MatrixXd(8, 8), 2e-12)); | |
| CALL_SUBTEST_1(testSingular(Matrix2f(), 1e-4f)); | |
| CALL_SUBTEST_5(testSingular(Matrix3cf(), 1e-4f)); | |
| CALL_SUBTEST_8(testSingular(Matrix4f(), 1e-4f)); | |
| CALL_SUBTEST_6(testSingular(MatrixXf(2, 2), 1e-3f)); | |
| CALL_SUBTEST_9(testSingular(MatrixXe(7, 7), 1e-12L)); | |
| CALL_SUBTEST_10(testSingular(Matrix3d(), 2e-13)); | |
| CALL_SUBTEST_11(testSingular(Matrix3f(), 1e-4f)); | |
| CALL_SUBTEST_12(testSingular(Matrix3e(), 1e-13L)); | |
| CALL_SUBTEST_2(testLogThenExp(Matrix2d(), 1e-13)); | |
| CALL_SUBTEST_7(testLogThenExp(Matrix3dRowMajor(), 1e-13)); | |
| CALL_SUBTEST_3(testLogThenExp(Matrix4cd(), 1e-13)); | |
| CALL_SUBTEST_4(testLogThenExp(MatrixXd(8, 8), 2e-12)); | |
| CALL_SUBTEST_1(testLogThenExp(Matrix2f(), 1e-4f)); | |
| CALL_SUBTEST_5(testLogThenExp(Matrix3cf(), 1e-4f)); | |
| CALL_SUBTEST_8(testLogThenExp(Matrix4f(), 1e-4f)); | |
| CALL_SUBTEST_6(testLogThenExp(MatrixXf(2, 2), 1e-3f)); | |
| CALL_SUBTEST_9(testLogThenExp(MatrixXe(7, 7), 1e-12L)); | |
| CALL_SUBTEST_10(testLogThenExp(Matrix3d(), 2e-13)); | |
| CALL_SUBTEST_11(testLogThenExp(Matrix3f(), 1e-4f)); | |
| CALL_SUBTEST_12(testLogThenExp(Matrix3e(), 1e-13L)); | |
| } |