85 lines
2.6 KiB
C++
85 lines
2.6 KiB
C++
/**
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* @file testGaussianISAM2.cpp
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* @brief Unit tests for GaussianISAM2
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* @author Michael Kaess
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*/
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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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#include <CppUnitLite/TestHarness.h>
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#include "Ordering.h"
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#include "GaussianBayesNet.h"
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#include "ISAM2-inl.h"
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#include "GaussianISAM2.h"
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#include "smallExample.h"
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using namespace std;
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using namespace gtsam;
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/* ************************************************************************* *
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TEST( ISAM2, ISAM2_smoother )
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{
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// Create smoother with 7 nodes
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ExampleNonlinearFactorGraph smoother;
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VectorConfig poses;
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boost::tie(smoother, poses) = createNonlinearSmoother(7);
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// run ISAM2 for every factor
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GaussianISAM2 actual;
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BOOST_FOREACH(boost::shared_ptr<NonlinearFactor<VectorConfig> > factor, smoother) {
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ExampleNonlinearFactorGraph factorGraph;
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factorGraph.push_back(factor);
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actual.update(factorGraph, poses);
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}
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// Create expected Bayes Tree by solving smoother with "natural" ordering
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Ordering ordering;
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for (int t = 1; t <= 7; t++) ordering += symbol('x', t);
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GaussianISAM2 expected(smoother, ordering, poses);
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// Check whether BayesTree is correct
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CHECK(assert_equal(expected, actual));
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// obtain solution
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VectorConfig e; // expected solution
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Vector v = Vector_(2, 0., 0.);
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for (int i=1; i<=7; i++)
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e.insert(symbol('x', i), v);
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VectorConfig optimized = optimize2(actual); // actual solution
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CHECK(assert_equal(e, optimized));
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}
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/* ************************************************************************* *
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TEST( ISAM2, ISAM2_smoother2 )
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{
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// Create smoother with 7 nodes
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ExampleNonlinearFactorGraph smoother;
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VectorConfig poses;
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boost::tie(smoother, poses) = createNonlinearSmoother(7);
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// Create initial tree from first 4 timestamps in reverse order !
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Ordering ord; ord += "x4","x3","x2","x1";
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ExampleNonlinearFactorGraph factors1;
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for (int i=0;i<7;i++) factors1.push_back(smoother[i]);
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GaussianISAM2 actual(factors1, ord, poses);
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// run ISAM2 with remaining factors
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ExampleNonlinearFactorGraph factors2;
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for (int i=7;i<13;i++) factors2.push_back(smoother[i]);
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actual.update(factors2, poses);
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// Create expected Bayes Tree by solving smoother with "natural" ordering
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Ordering ordering;
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for (int t = 1; t <= 7; t++) ordering += symbol('x', t);
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GaussianISAM2 expected(smoother, ordering, poses);
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CHECK(assert_equal(expected, actual));
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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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