| #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; | 
 |   } | 
 | } |