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 = ei_random<int>(1,100);
MatrixXmp A = MatrixXmp::Random(s,s);
MatrixXmp B = MatrixXmp::Random(s,s);
MatrixXmp S = A.adjoint() * A;
MatrixXmp X;
// 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());
}
}
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( (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;
}
}