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Clang-format tests, examples, libraries, benchmarks, etc.

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This commit is contained in:
Antonio Sánchez
2023-12-05 21:22:55 +00:00
committed by Rasmus Munk Larsen
parent 3252ecc7a4
commit 46e9cdb7fe
876 changed files with 33453 additions and 37795 deletions
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44
unsupported/test/mpreal_support.cpp
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@@ -8,12 +8,11 @@
using namespace mpfr;
using namespace Eigen;
EIGEN_DECLARE_TEST(mpreal_support)
{
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;
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";
@@ -22,44 +21,47 @@ EIGEN_DECLARE_TEST(mpreal_support)
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);
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 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().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()));
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);
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);
VERIFY_IS_APPROX((Sc.selfadjointView<Lower>() * Xc).eval(), Bc);
// partial LU
X = A.lu().solve(B);
VERIFY_IS_APPROX((A*X).eval(),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) );
VERIFY(
(S.selfadjointView<Lower>() * eig.eigenvectors())
.isApprox(eig.eigenvectors() * eig.eigenvalues().asDiagonal(), NumTraits<mpreal>::dummy_precision() * 1e3));
}
{
MatrixXmp A(8,3); A.setRandom();
MatrixXmp A(8, 3);
A.setRandom();
// test output (interesting things happen in this code)
std::stringstream stream;
stream << A;