60 lines
1.6 KiB
C++
60 lines
1.6 KiB
C++
/**
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* @file testSymbolicBayesNet.cpp
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* @brief Unit tests for a symbolic Bayes chain
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* @author Frank Dellaert
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*/
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#include <boost/assign/list_inserter.hpp> // for 'insert()'
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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 <gtsam/CppUnitLite/TestHarness.h>
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#define GTSAM_MAGIC_KEY
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#include <gtsam/inference/Ordering.h>
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#include <gtsam/slam/smallExample.h>
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#include <gtsam/inference/SymbolicBayesNet.h>
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#include <gtsam/inference/SymbolicFactorGraph.h>
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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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Symbol _B_('B', 0), _L_('L', 0);
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SymbolicConditional::shared_ptr
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B(new SymbolicConditional(_B_)),
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L(new SymbolicConditional(_L_, _B_));
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/* ************************************************************************* */
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TEST( SymbolicBayesNet, constructor )
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{
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// Create manually
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SymbolicConditional::shared_ptr
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x2(new SymbolicConditional("x2","l1", "x1")),
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l1(new SymbolicConditional("l1","x1")),
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x1(new SymbolicConditional("x1"));
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SymbolicBayesNet expected;
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expected.push_back(x2);
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expected.push_back(l1);
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expected.push_back(x1);
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// Create from a factor graph
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GaussianFactorGraph factorGraph = createGaussianFactorGraph();
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SymbolicFactorGraph fg(factorGraph);
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// eliminate it
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Ordering ordering;
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ordering += "x2","l1","x1";
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SymbolicBayesNet actual = fg.eliminate(ordering);
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CHECK(assert_equal(expected, actual));
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}
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/* ************************************************************************* */
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int main() {
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TestResult tr;
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return TestRegistry::runAllTests(tr);
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}
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/* ************************************************************************* */
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