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#include "main.h"
#include <Eigen/MPRealSupport>
#include <Eigen/LU>
#include <Eigen/Eigenvalues>
#include <sstream>
using namespace mpfr; using namespace std; using namespace Eigen;
void 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;
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";
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; // 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);
// 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_IS_APPROX((S.selfadjointView<Lower>() * eig.eigenvectors()), eig.eigenvectors() * eig.eigenvalues().asDiagonal()); } { MatrixXmp A(8,3); A.setRandom(); // test output (interesting things happen in this code)
std::stringstream stream; stream << A; } }
extern "C" { #include "mpreal/dlmalloc.c"
} #include "mpreal/mpreal.cpp"
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