cart-elc

Source code for CART-ELC
git clone git://git.laack.co/cart-elc.git
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mpreal_support.cpp (2439B)


      1 #include <mpreal.h>  // Must be included before main.h.
      2 #include "main.h"
      3 #include <Eigen/MPRealSupport>
      4 #include <Eigen/LU>
      5 #include <Eigen/Eigenvalues>
      6 #include <sstream>
      7 
      8 using namespace mpfr;
      9 using namespace Eigen;
     10 
     11 EIGEN_DECLARE_TEST(mpreal_support)
     12 {
     13   // set precision to 256 bits (double has only 53 bits)
     14   mpreal::set_default_prec(256);
     15   typedef Matrix<mpreal,Eigen::Dynamic,Eigen::Dynamic> MatrixXmp;
     16   typedef Matrix<std::complex<mpreal>,Eigen::Dynamic,Eigen::Dynamic> MatrixXcmp;
     17 
     18   std::cerr << "epsilon =         " << NumTraits<mpreal>::epsilon() << "\n";
     19   std::cerr << "dummy_precision = " << NumTraits<mpreal>::dummy_precision() << "\n";
     20   std::cerr << "highest =         " << NumTraits<mpreal>::highest() << "\n";
     21   std::cerr << "lowest =          " << NumTraits<mpreal>::lowest() << "\n";
     22   std::cerr << "digits10 =        " << NumTraits<mpreal>::digits10() << "\n";
     23 
     24   for(int i = 0; i < g_repeat; i++) {
     25     int s = Eigen::internal::random<int>(1,100);
     26     MatrixXmp A = MatrixXmp::Random(s,s);
     27     MatrixXmp B = MatrixXmp::Random(s,s);
     28     MatrixXmp S = A.adjoint() * A;
     29     MatrixXmp X;
     30     MatrixXcmp Ac = MatrixXcmp::Random(s,s);
     31     MatrixXcmp Bc = MatrixXcmp::Random(s,s);
     32     MatrixXcmp Sc = Ac.adjoint() * Ac;
     33     MatrixXcmp Xc;
     34     
     35     // Basic stuffs
     36     VERIFY_IS_APPROX(A.real(), A);
     37     VERIFY(Eigen::internal::isApprox(A.array().abs2().sum(), A.squaredNorm()));
     38     VERIFY_IS_APPROX(A.array().exp(),         exp(A.array()));
     39     VERIFY_IS_APPROX(A.array().abs2().sqrt(), A.array().abs());
     40     VERIFY_IS_APPROX(A.array().sin(),         sin(A.array()));
     41     VERIFY_IS_APPROX(A.array().cos(),         cos(A.array()));
     42 
     43     // Cholesky
     44     X = S.selfadjointView<Lower>().llt().solve(B);
     45     VERIFY_IS_APPROX((S.selfadjointView<Lower>()*X).eval(),B);
     46 
     47     Xc = Sc.selfadjointView<Lower>().llt().solve(Bc);
     48     VERIFY_IS_APPROX((Sc.selfadjointView<Lower>()*Xc).eval(),Bc);
     49     
     50     // partial LU
     51     X = A.lu().solve(B);
     52     VERIFY_IS_APPROX((A*X).eval(),B);
     53 
     54     // symmetric eigenvalues
     55     SelfAdjointEigenSolver<MatrixXmp> eig(S);
     56     VERIFY_IS_EQUAL(eig.info(), Success);
     57     VERIFY( (S.selfadjointView<Lower>() * eig.eigenvectors()).isApprox(eig.eigenvectors() * eig.eigenvalues().asDiagonal(), NumTraits<mpreal>::dummy_precision()*1e3) );
     58   }
     59   
     60   {
     61     MatrixXmp A(8,3); A.setRandom();
     62     // test output (interesting things happen in this code)
     63     std::stringstream stream;
     64     stream << A;
     65   }
     66 }