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// 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); }
void 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 instanciation tests
Matrix<adtl::adouble,2,1> x; foo(x); Matrix<adtl::adouble,Dynamic,Dynamic> A(4,4);; A.selfadjointView<Lower>().eigenvalues(); } }
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