starting work on a Numerical differenciation module

This commit is contained in:
Thomas Capricelli 2009-09-28 02:43:07 +02:00
parent a453298322
commit 206b5e3972
4 changed files with 241 additions and 0 deletions

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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009 Thomas Capricelli <orzel@freehackers.org>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_NUMERICALDIFF_MODULE
#define EIGEN_NUMERICALDIFF_MODULE
#include <Eigen/Core>
namespace Eigen {
/** \ingroup Unsupported_modules
* \defgroup NumericalDiff_Module Support for numerical differenciation.
* See http://en.wikipedia.org/wiki/Numerical_differentiation
*
* \code
* #include <unsupported/Eigen/NumericalDiff>
* \endcode
*/
//@{
}
#include "src/NumericalDiff/NumericalDiff.h"
namespace Eigen {
//@}
}
#endif // EIGEN_NUMERICALDIFF_MODULE

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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009 Thomas Capricelli <orzel@freehackers.org>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#ifndef EIGEN_NUMERICAL_DIFF_H
#define EIGEN_NUMERICAL_DIFF_H
namespace Eigen
{
template<typename Functor> class NumericalDiff : public Functor
{
public:
typedef typename Functor::Scalar Scalar;
typedef typename Functor::InputType InputType;
typedef typename Functor::ValueType ValueType;
typedef typename Functor::JacobianType JacobianType;
NumericalDiff(Scalar _epsfcn=0.) : Functor(), epsfcn(_epsfcn) {}
NumericalDiff(const Functor& f, Scalar _epsfcn=0.) : Functor(f), epsfcn(_epsfcn) {}
// forward constructors
template<typename T0>
NumericalDiff(const T0& a0) : Functor(a0), epsfcn(0) {}
template<typename T0, typename T1>
NumericalDiff(const T0& a0, const T1& a1) : Functor(a0, a1), epsfcn(0) {}
template<typename T0, typename T1, typename T2>
NumericalDiff(const T0& a0, const T1& a1, const T1& a2) : Functor(a0, a1, a2), epsfcn(0) {}
enum {
InputsAtCompileTime = Functor::InputsAtCompileTime,
ValuesAtCompileTime = Functor::ValuesAtCompileTime
};
/**
* return the number of evaluation of functor
*/
int df(const InputType& _x, JacobianType &jac) const
{
/* Local variables */
Scalar h;
int nfev=0;
const int n = _x.size();
const Scalar eps = ei_sqrt((std::max(epsfcn,epsilon<Scalar>() )));
ValueType val, fx;
InputType x = _x;
// TODO : we should do this only if the size is not already known
val.resize(Functor::values());
fx.resize(Functor::values());
// compute f(x)
Functor::operator()(x, fx);
/* Function Body */
for (int j = 0; j < n; ++j) {
h = eps * ei_abs(x[j]);
if (h == 0.) {
h = eps;
}
x[j] += h;
Functor::operator()(x, val);
nfev++;
x[j] = _x[j];
jac.col(j) = (val-fx)/h;
}
return nfev;
}
private:
Scalar epsfcn;
};
} // namespace
#endif // EIGEN_NUMERICAL_DIFF_H

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@ -16,6 +16,7 @@ else(ADOLC_FOUND)
endif(ADOLC_FOUND)
ei_add_test(NonLinear)
ei_add_test(NumericalDiff)
ei_add_test(autodiff)
ei_add_test(BVH)
#ei_add_test(matrixExponential)

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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009 Thomas Capricelli <orzel@freehackers.org>
#include <stdio.h>
#include "main.h"
#include <unsupported/Eigen/NumericalDiff>
// Generic functor
template<typename _Scalar, int NX=Dynamic, int NY=Dynamic>
struct Functor
{
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;
Functor() : m_inputs(InputsAtCompileTime), m_values(ValuesAtCompileTime) {}
Functor(int inputs, int values) : m_inputs(inputs), m_values(values) {}
int inputs() const { return m_inputs; }
int values() const { return m_values; }
};
struct my_functor : Functor<double>
{
my_functor(void): Functor<double>(3,15) {}
int operator()(const VectorXd &x, VectorXd &fvec) const
{
double tmp1, tmp2, tmp3;
double y[15] = {1.4e-1, 1.8e-1, 2.2e-1, 2.5e-1, 2.9e-1, 3.2e-1, 3.5e-1,
3.9e-1, 3.7e-1, 5.8e-1, 7.3e-1, 9.6e-1, 1.34, 2.1, 4.39};
for (int i = 0; i < values(); i++)
{
tmp1 = i+1;
tmp2 = 16 - i - 1;
tmp3 = (i>=8)? tmp2 : tmp1;
fvec[i] = y[i] - (x[0] + tmp1/(x[1]*tmp2 + x[2]*tmp3));
}
return 0;
}
int df(const VectorXd &x, MatrixXd &fjac) const
{
double tmp1, tmp2, tmp3, tmp4;
for (int i = 0; i < values(); i++)
{
tmp1 = i+1;
tmp2 = 16 - i - 1;
tmp3 = (i>=8)? tmp2 : tmp1;
tmp4 = (x[1]*tmp2 + x[2]*tmp3); tmp4 = tmp4*tmp4;
fjac(i,0) = -1;
fjac(i,1) = tmp1*tmp2/tmp4;
fjac(i,2) = tmp1*tmp3/tmp4;
}
return 0;
}
};
void test_forward()
{
VectorXd x(3);
MatrixXd jac(15,3);
MatrixXd actual_jac(15,3);
my_functor functor;
x << 0.082, 1.13, 2.35;
// real one
functor.df(x, actual_jac);
// std::cout << actual_jac << std::endl << std::endl;
// using NumericalDiff
NumericalDiff<my_functor> numDiff(functor);
numDiff.df(x, jac);
// std::cout << jac << std::endl;
VERIFY_IS_APPROX(jac, actual_jac);
}
void test_NumericalDiff()
{
CALL_SUBTEST(test_forward());
}