numeric-linear-function.cc

Example shows numeric linear function use.

// Copyright (C) 2009 by Thomas Moulard, AIST, CNRS, INRIA.
//
// This file is part of the roboptim.
//
// roboptim 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.
//
// roboptim 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 for more details.
//
// You should have received a copy of the GNU Lesser General Public License
// along with roboptim. If not, see <http://www.gnu.org/licenses/>.
#include "shared-tests/fixture.hh"
#include <iostream>
using namespace roboptim;
typedef DummySolver solver_t;
typedef boost::mpl::list< ::roboptim::EigenMatrixDense,
BOOST_FIXTURE_TEST_SUITE (core, TestSuiteConfiguration)
BOOST_AUTO_TEST_CASE_TEMPLATE (numeric_linear_function, T, functionTypes_t)
{
boost::shared_ptr<boost::test_tools::output_test_stream>
output = retrievePattern ("numeric-linear-function");
typename GenericNumericLinearFunction<T>::matrix_t a (1, 5);
typename GenericNumericLinearFunction<T>::vector_t b (1);
typename GenericNumericLinearFunction<T>::vector_t x (5);
a.setZero ();
b.setZero ();
x.setZero ();
a.coeffRef (0, 0) = 1.2;
a.coeffRef (0, 1) = 3.4;
a.coeffRef (0, 2) = 5.6;
a.coeffRef (0, 3) = 7.8;
b[0] = 1.;
GenericNumericLinearFunction<T> f (a, b);
(*output) << f << std::endl;
x[0] = 0.1;
x[1] = 1.2;
x[2] = 2.3;
x[3] = 3.4;
x[4] = 4.5;
(*output) << "f(x) = " << f (x) << std::endl;
(*output) << "G(x) = " << f.gradient (x, 0) << std::endl;
(*output) << "J(x) = " << f.jacobian (x) << std::endl;
(*output) << "H(x) = " << f.hessian (x) << std::endl;
GenericNumericLinearFunction<T> numericLinearFunction (a, b);
GenericLinearFunction<T>* linearFunction = &numericLinearFunction;
GenericNumericLinearFunction<T> numericLinearFunctionRebuilt (*linearFunction);
BOOST_CHECK (allclose (numericLinearFunction.A (),
numericLinearFunctionRebuilt.A ()));
BOOST_CHECK_EQUAL (numericLinearFunction.b (), numericLinearFunctionRebuilt.b ());
std::cout << output->str () << std::endl;
//BOOST_CHECK (output->match_pattern ());
}
BOOST_AUTO_TEST_SUITE_END ()
DummyDifferentiableSparseSolverLastState::parent_t solver_t
Definition: dummy-d-sparse-laststate.cc:29
defined(EIGEN_RUNTIME_NO_MALLOC) && !defined(ROBOPTIM_DO_NOT_CHECK_ALLOCATION)
Definition: alloc.hh:33
ROBOPTIM_DLLAPI bool allclose(const Eigen::SparseMatrix< double > &a, const Eigen::SparseMatrix< double > &b, double rtol=Eigen::NumTraits< double >::dummy_precision(), double atol=Eigen::NumTraits< double >::epsilon())
Compare sparse vectors (matrices) using both relative and absolute tolerances.
Definition: util.cc:104
Tag type for functions using Eigen dense matrices.
Definition: fwd.hh:59
Tag type for functions using Eigen sparse matrices.
Definition: fwd.hh:61