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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2016 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#include <sstream>
#ifdef EIGEN_TEST_MAX_SIZE
#undef EIGEN_TEST_MAX_SIZE
#endif
#define EIGEN_TEST_MAX_SIZE 50
#ifdef EIGEN_TEST_PART_1
#include "cholesky.cpp"
#endif
#ifdef EIGEN_TEST_PART_2
#include "lu.cpp"
#endif
#ifdef EIGEN_TEST_PART_3
#include "qr.cpp"
#endif
#ifdef EIGEN_TEST_PART_4
#include "qr_colpivoting.cpp"
#endif
#ifdef EIGEN_TEST_PART_5
#include "qr_fullpivoting.cpp"
#endif
#ifdef EIGEN_TEST_PART_6
#include "eigensolver_selfadjoint.cpp"
#endif
#ifdef EIGEN_TEST_PART_7
#include "eigensolver_generic.cpp"
#endif
#ifdef EIGEN_TEST_PART_8
#include "eigensolver_generalized_real.cpp"
#endif
#ifdef EIGEN_TEST_PART_9
#include "jacobisvd.cpp"
#endif
#ifdef EIGEN_TEST_PART_10
#include "bdcsvd.cpp"
#endif
#ifdef EIGEN_TEST_PART_11
#include "simplicial_cholesky.cpp"
#endif
#include <Eigen/Dense>
#undef min
#undef max
#undef isnan
#undef isinf
#undef isfinite
#undef I
#include <boost/serialization/nvp.hpp>
#include <boost/multiprecision/cpp_dec_float.hpp>
#include <boost/multiprecision/number.hpp>
#include <boost/math/special_functions.hpp>
#include <boost/math/complex.hpp>
namespace mp = boost::multiprecision;
typedef mp::number<mp::cpp_dec_float<100>, mp::et_on> Real;
namespace Eigen {
template<> struct NumTraits<Real> : GenericNumTraits<Real> {
static inline Real dummy_precision() { return 1e-50; }
};
template<typename T1,typename T2,typename T3,typename T4,typename T5>
struct NumTraits<boost::multiprecision::detail::expression<T1,T2,T3,T4,T5> > : NumTraits<Real> {};
template<>
Real test_precision<Real>() { return 1e-50; }
// needed in C++93 mode where number does not support explicit cast.
namespace internal {
template<typename NewType>
struct cast_impl<Real,NewType> {
static inline NewType run(const Real& x) {
return x.template convert_to<NewType>();
}
};
template<>
struct cast_impl<Real,std::complex<Real> > {
static inline std::complex<Real> run(const Real& x) {
return std::complex<Real>(x);
}
};
}
}
namespace boost {
namespace multiprecision {
// to make ADL works as expected:
using boost::math::isfinite;
using boost::math::isnan;
using boost::math::isinf;
using boost::math::copysign;
using boost::math::hypot;
// The following is needed for std::complex<Real>:
Real fabs(const Real& a) { return abs EIGEN_NOT_A_MACRO (a); }
Real fmax(const Real& a, const Real& b) { using std::max; return max(a,b); }
// some specialization for the unit tests:
inline bool test_isMuchSmallerThan(const Real& a, const Real& b) {
return internal::isMuchSmallerThan(a, b, test_precision<Real>());
}
inline bool test_isApprox(const Real& a, const Real& b) {
return internal::isApprox(a, b, test_precision<Real>());
}
inline bool test_isApproxOrLessThan(const Real& a, const Real& b) {
return internal::isApproxOrLessThan(a, b, test_precision<Real>());
}
Real get_test_precision(const Real&) {
return test_precision<Real>();
}
Real test_relative_error(const Real &a, const Real &b) {
using Eigen::numext::abs2;
return sqrt(abs2<Real>(a-b)/Eigen::numext::mini<Real>(abs2(a),abs2(b)));
}
}
}
namespace Eigen {
}
EIGEN_DECLARE_TEST(boostmultiprec)
{
typedef Matrix<Real,Dynamic,Dynamic> Mat;
typedef Matrix<std::complex<Real>,Dynamic,Dynamic> MatC;
std::cout << "NumTraits<Real>::epsilon() = " << NumTraits<Real>::epsilon() << std::endl;
std::cout << "NumTraits<Real>::dummy_precision() = " << NumTraits<Real>::dummy_precision() << std::endl;
std::cout << "NumTraits<Real>::lowest() = " << NumTraits<Real>::lowest() << std::endl;
std::cout << "NumTraits<Real>::highest() = " << NumTraits<Real>::highest() << std::endl;
std::cout << "NumTraits<Real>::digits10() = " << NumTraits<Real>::digits10() << std::endl;
// check stream output
{
Mat A(10,10);
A.setRandom();
std::stringstream ss;
ss << A;
}
{
MatC A(10,10);
A.setRandom();
std::stringstream ss;
ss << A;
}
for(int i = 0; i < g_repeat; i++) {
int s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE);
CALL_SUBTEST_1( cholesky(Mat(s,s)) );
CALL_SUBTEST_2( lu_non_invertible<Mat>() );
CALL_SUBTEST_2( lu_invertible<Mat>() );
CALL_SUBTEST_2( lu_non_invertible<MatC>() );
CALL_SUBTEST_2( lu_invertible<MatC>() );
CALL_SUBTEST_3( qr(Mat(internal::random<int>(1,EIGEN_TEST_MAX_SIZE),internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
CALL_SUBTEST_3( qr_invertible<Mat>() );
CALL_SUBTEST_4( qr<Mat>() );
CALL_SUBTEST_4( cod<Mat>() );
CALL_SUBTEST_4( qr_invertible<Mat>() );
CALL_SUBTEST_5( qr<Mat>() );
CALL_SUBTEST_5( qr_invertible<Mat>() );
CALL_SUBTEST_6( selfadjointeigensolver(Mat(s,s)) );
CALL_SUBTEST_7( eigensolver(Mat(s,s)) );
CALL_SUBTEST_8( generalized_eigensolver_real(Mat(s,s)) );
TEST_SET_BUT_UNUSED_VARIABLE(s)
}
CALL_SUBTEST_9(( jacobisvd(Mat(internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE), internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/2))) ));
CALL_SUBTEST_10(( bdcsvd(Mat(internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE), internal::random<int>(EIGEN_TEST_MAX_SIZE/4, EIGEN_TEST_MAX_SIZE/2))) ));
CALL_SUBTEST_11(( test_simplicial_cholesky_T<Real,int,ColMajor>() ));
}
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