54 lines
2.0 KiB
C++
54 lines
2.0 KiB
C++
/**
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* @file testInference.cpp
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* @brief Unit tests for functionality declared in inference.h
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* @author Frank Dellaert
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*/
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#include <CppUnitLite/TestHarness.h>
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#include "Ordering.h"
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#include "smallExample.h"
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#include "inference-inl.h"
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using namespace std;
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using namespace gtsam;
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/* ************************************************************************* */
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// The tests below test the *generic* inference algorithms. Some of these have
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// specialized versions in the derived classes GaussianFactorGraph etc...
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/* ************************************************************************* */
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/* ************************************************************************* */
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TEST(GaussianFactorGraph, createSmoother)
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{
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GaussianFactorGraph fg2 = createSmoother(3);
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LONGS_EQUAL(5,fg2.size());
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// eliminate
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Ordering ordering;
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GaussianBayesNet bayesNet = fg2.eliminate(ordering);
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FactorGraph<GaussianFactor> p_x3 = marginalize<GaussianFactor,GaussianConditional>(bayesNet, Ordering("x3"));
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FactorGraph<GaussianFactor> p_x1 = marginalize<GaussianFactor,GaussianConditional>(bayesNet, Ordering("x1"));
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CHECK(assert_equal(p_x1,p_x3)); // should be the same because of symmetry
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}
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/* ************************************************************************* */
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TEST( Inference, marginals )
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{
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// create and marginalize a small Bayes net on "x"
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GaussianBayesNet cbn = createSmallGaussianBayesNet();
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Ordering keys("x");
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FactorGraph<GaussianFactor> fg = marginalize<GaussianFactor, GaussianConditional>(cbn,keys);
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// turn into Bayes net to test easily
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BayesNet<GaussianConditional> actual = eliminate<GaussianFactor,GaussianConditional>(fg,keys);
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// expected is just scalar Gaussian on x
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GaussianBayesNet expected = scalarGaussian("x",4,sqrt(2));
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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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