You can not select more than 25 topics
			Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
		
		
		
		
		
			
		
			
				
					
					
						
							56 lines
						
					
					
						
							1.9 KiB
						
					
					
				
			
		
		
		
			
			
			
				
					
				
				
					
				
			
		
		
	
	
							56 lines
						
					
					
						
							1.9 KiB
						
					
					
				| #include "main.h" | |
| #include <Eigen/MPRealSupport> | |
| #include <Eigen/LU> | |
| #include <Eigen/Eigenvalues> | |
| #include <sstream> | |
|  | |
| using namespace mpfr; | |
| 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( (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; | |
|   } | |
| }
 |