|  | #include <mpreal.h>  // Must be included before main.h. | 
|  | #include "main.h" | 
|  | #include <Eigen/MPRealSupport> | 
|  | #include <Eigen/LU> | 
|  | #include <Eigen/Eigenvalues> | 
|  | #include <sstream> | 
|  |  | 
|  | using namespace mpfr; | 
|  | using namespace Eigen; | 
|  |  | 
|  | EIGEN_DECLARE_TEST(mpreal_support) { | 
|  | // set precision to 256 bits (double has only 53 bits) | 
|  | mpreal::set_default_prec(256); | 
|  | typedef Matrix<mpreal, Eigen::Dynamic, Eigen::Dynamic> MatrixXmp; | 
|  | typedef Matrix<std::complex<mpreal>, Eigen::Dynamic, Eigen::Dynamic> MatrixXcmp; | 
|  |  | 
|  | std::cerr << "epsilon =         " << NumTraits<mpreal>::epsilon() << "\n"; | 
|  | std::cerr << "dummy_precision = " << NumTraits<mpreal>::dummy_precision() << "\n"; | 
|  | std::cerr << "highest =         " << NumTraits<mpreal>::highest() << "\n"; | 
|  | std::cerr << "lowest =          " << NumTraits<mpreal>::lowest() << "\n"; | 
|  | std::cerr << "digits10 =        " << NumTraits<mpreal>::digits10() << "\n"; | 
|  | std::cerr << "max_digits10 =    " << NumTraits<mpreal>::max_digits10() << "\n"; | 
|  |  | 
|  | for (int i = 0; i < g_repeat; i++) { | 
|  | int s = Eigen::internal::random<int>(1, 100); | 
|  | MatrixXmp A = MatrixXmp::Random(s, s); | 
|  | MatrixXmp B = MatrixXmp::Random(s, s); | 
|  | MatrixXmp S = A.adjoint() * A; | 
|  | MatrixXmp X; | 
|  | MatrixXcmp Ac = MatrixXcmp::Random(s, s); | 
|  | MatrixXcmp Bc = MatrixXcmp::Random(s, s); | 
|  | MatrixXcmp Sc = Ac.adjoint() * Ac; | 
|  | MatrixXcmp Xc; | 
|  |  | 
|  | // Basic stuffs | 
|  | VERIFY_IS_APPROX(A.real(), A); | 
|  | VERIFY(Eigen::internal::isApprox(A.array().abs2().sum(), A.squaredNorm())); | 
|  | VERIFY_IS_APPROX(A.array().exp(), exp(A.array())); | 
|  | VERIFY_IS_APPROX(A.array().abs2().sqrt(), A.array().abs()); | 
|  | VERIFY_IS_APPROX(A.array().sin(), sin(A.array())); | 
|  | VERIFY_IS_APPROX(A.array().cos(), cos(A.array())); | 
|  |  | 
|  | // Cholesky | 
|  | X = S.selfadjointView<Lower>().llt().solve(B); | 
|  | VERIFY_IS_APPROX((S.selfadjointView<Lower>() * X).eval(), B); | 
|  |  | 
|  | Xc = Sc.selfadjointView<Lower>().llt().solve(Bc); | 
|  | VERIFY_IS_APPROX((Sc.selfadjointView<Lower>() * Xc).eval(), Bc); | 
|  |  | 
|  | // partial LU | 
|  | X = A.lu().solve(B); | 
|  | VERIFY_IS_APPROX((A * X).eval(), B); | 
|  |  | 
|  | // symmetric eigenvalues | 
|  | SelfAdjointEigenSolver<MatrixXmp> eig(S); | 
|  | VERIFY_IS_EQUAL(eig.info(), Success); | 
|  | VERIFY( | 
|  | (S.selfadjointView<Lower>() * eig.eigenvectors()) | 
|  | .isApprox(eig.eigenvectors() * eig.eigenvalues().asDiagonal(), NumTraits<mpreal>::dummy_precision() * 1e3)); | 
|  | } | 
|  |  | 
|  | { | 
|  | MatrixXmp A(8, 3); | 
|  | A.setRandom(); | 
|  | // test output (interesting things happen in this code) | 
|  | std::stringstream stream; | 
|  | stream << A; | 
|  | } | 
|  | } |