// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <g.gael@free.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 "main.h"
#include <Eigen/Dense>
#define NUMBER_DIRECTIONS
16
#include <unsupported/Eigen/AdolcForward>
template <
typename Vector>
EIGEN_DONT_INLINE
typename Vector::Scalar foo(
const Vector& p)
{
typedef typename Vector::Scalar Scalar;
return (p-Vector(Scalar(-
1 ),Scalar(
1 .))).norm() + (p.array().sqrt().abs() * p.array()
.sin()).sum() + p.dot(p);
}
template <typename _Scalar, int NX=Dynamic, int NY=Dynamic>
struct TestFunc1
{
typedef _Scalar Scalar;
enum {
InputsAtCompileTime = NX,
ValuesAtCompileTime = NY
};
typedef Matrix<Scalar,InputsAtCompileTime,1 > InputType;
typedef Matrix<Scalar,ValuesAtCompileTime,1 > ValueType;
typedef Matrix<Scalar,ValuesAtCompileTime,InputsAtCompileTime> JacobianType;
int m_inputs, m_values;
TestFunc1() : m_inputs(InputsAtCompileTime), m_values(ValuesAtCompileTime) {}
TestFunc1(int inputs_, int values_) : m_inputs(inputs_), m_values(values_) {}
int inputs() const { return m_inputs; }
int values() const { return m_values; }
template <typename T>
void operator () (const Matrix<T,InputsAtCompileTime,1 >& x, Matrix<T,ValuesAtCompileTime,1 >* _v) const
{
Matrix<T,ValuesAtCompileTime,1 >& v = *_v;
v[0 ] = 2 * x[0 ] * x[0 ] + x[0 ] * x[1 ];
v[1 ] = 3 * x[1 ] * x[0 ] + 0 .5 * x[1 ] * x[1 ];
if (inputs()>2 )
{
v[0 ] += 0 .5 * x[2 ];
v[1 ] += x[2 ];
}
if (values()>2 )
{
v[2 ] = 3 * x[1 ] * x[0 ] * x[0 ];
}
if (inputs()>2 && values()>2 )
v[2 ] *= x[2 ];
}
void operator () (const InputType& x, ValueType* v, JacobianType* _j) const
{
(*this )(x, v);
if (_j)
{
JacobianType& j = *_j;
j(0 ,0 ) = 4 * x[0 ] + x[1 ];
j(1 ,0 ) = 3 * x[1 ];
j(0 ,1 ) = x[0 ];
j(1 ,1 ) = 3 * x[0 ] + 2 * 0 .5 * x[1 ];
if (inputs()>2 )
{
j(0 ,2 ) = 0 .5 ;
j(1 ,2 ) = 1 ;
}
if (values()>2 )
{
j(2 ,0 ) = 3 * x[1 ] * 2 * x[0 ];
j(2 ,1 ) = 3 * x[0 ] * x[0 ];
}
if (inputs()>2 && values()>2 )
{
j(2 ,0 ) *= x[2 ];
j(2 ,1 ) *= x[2 ];
j(2 ,2 ) = 3 * x[1 ] * x[0 ] * x[0 ];
j(2 ,2 ) = 3 * x[1 ] * x[0 ] * x[0 ];
}
}
}
};
template <typename Func> void adolc_forward_jacobian(const Func& f)
{
typename Func::InputType x = Func::InputType::Random(f.inputs());
typename Func::ValueType y(f.values()), yref(f.values());
typename Func::JacobianType j(f.values(),f.inputs()), jref(f.values(),f.inputs());
jref.setZero();
yref.setZero();
f(x,&yref,&jref);
// std::cerr << y.transpose() << "\n\n";;
// std::cerr << j << "\n\n";;
j.setZero();
y.setZero();
AdolcForwardJacobian<Func> autoj(f);
autoj(x, &y, &j);
// std::cerr << y.transpose() << "\n\n";;
// std::cerr << j << "\n\n";;
VERIFY_IS_APPROX(y, yref);
VERIFY_IS_APPROX(j, jref);
}
EIGEN_DECLARE_TEST(forward_adolc)
{
adtl::setNumDir(NUMBER_DIRECTIONS);
for (int i = 0 ; i < g_repeat; i++) {
CALL_SUBTEST(( adolc_forward_jacobian(TestFunc1<double ,2 ,2 >()) ));
CALL_SUBTEST(( adolc_forward_jacobian(TestFunc1<double ,2 ,3 >()) ));
CALL_SUBTEST(( adolc_forward_jacobian(TestFunc1<double ,3 ,2 >()) ));
CALL_SUBTEST(( adolc_forward_jacobian(TestFunc1<double ,3 ,3 >()) ));
CALL_SUBTEST(( adolc_forward_jacobian(TestFunc1<double >(3 ,3 )) ));
}
{
// simple instantiation tests
Matrix<adtl::adouble,2 ,1 > x;
foo(x);
Matrix<adtl::adouble,Dynamic,Dynamic> A(4 ,4 );;
A.selfadjointView<Lower>().eigenvalues();
}
}
Messung V0.5 in Prozent C=88 H=89 G=88
¤ Dauer der Verarbeitung: 0.12 Sekunden
(vorverarbeitet am 2026-06-06)
¤
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