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								/* ----------------------------------------------------------------------------
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								 * GTSAM Copyright 2010, Georgia Tech Research Corporation, 
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								 * Atlanta, Georgia 30332-0415
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								 * All Rights Reserved
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								 * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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								 * See LICENSE for the license information
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								 * -------------------------------------------------------------------------- */
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								/**
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								 * @file    testGaussianISAM.cpp
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								 * @brief   Unit tests for GaussianISAM
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								 * @author  Michael Kaess
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								 */
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								#include <tests/smallExample.h>
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								#include <gtsam/nonlinear/Ordering.h>
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								#include <gtsam/nonlinear/Symbol.h>
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								#include <gtsam/linear/GaussianBayesNet.h>
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								#include <gtsam/linear/GaussianISAM.h>
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								#include <gtsam/linear/GaussianSequentialSolver.h>
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								#include <gtsam/linear/GaussianMultifrontalSolver.h>
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								#include <gtsam/inference/ISAM.h>
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								#include <gtsam/geometry/Rot2.h>
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								#include <CppUnitLite/TestHarness.h>
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								#include <boost/foreach.hpp>
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								#include <boost/assign/std/list.hpp> // for operator +=
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								using namespace boost::assign;
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								using namespace std;
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								using namespace gtsam;
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								using namespace example;
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								using symbol_shorthand::X;
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								using symbol_shorthand::L;
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								/* ************************************************************************* */
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								// Some numbers that should be consistent among all smoother tests
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								static const double tol = 1e-4;
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								/* ************************************************************************* */
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								TEST( ISAM, iSAM_smoother )
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								{
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								  Ordering ordering;
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								  for (int t = 1; t <= 7; t++) ordering += X(t);
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								  // Create smoother with 7 nodes
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								  GaussianFactorGraph smoother = createSmoother(7, ordering).first;
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								  // run iSAM for every factor
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								  GaussianISAM actual;
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								  BOOST_FOREACH(boost::shared_ptr<GaussianFactor> factor, smoother) {
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								    GaussianFactorGraph factorGraph;
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								    factorGraph.push_back(factor);
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								    actual.update(factorGraph);
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								  }
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								  // Create expected Bayes Tree by solving smoother with "natural" ordering
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								  BayesTree<GaussianConditional>::shared_ptr bayesTree = GaussianMultifrontalSolver(smoother).eliminate();
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								  GaussianISAM expected(*bayesTree);
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								  // Verify sigmas in the bayes tree
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								  BOOST_FOREACH(const GaussianBayesTree::sharedClique& clique, bayesTree->nodes()) {
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								    GaussianConditional::shared_ptr conditional = clique->conditional();
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								    size_t dim = conditional->dim();
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								    EXPECT(assert_equal(gtsam::ones(dim), conditional->get_sigmas(), tol));
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								  }
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								  // Check whether BayesTree is correct
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								  EXPECT(assert_equal(expected, actual));
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								  // obtain solution
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								  VectorValues e(VectorValues::Zero(7,2)); // expected solution
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								  VectorValues optimized = optimize(actual); // actual solution
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								  EXPECT(assert_equal(e, optimized));
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								}
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								/* ************************************************************************* */
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								int main() { TestResult tr; return TestRegistry::runAllTests(tr);}
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								/* ************************************************************************* */
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