fix comments
parent
3ee0ec3a6a
commit
e81272b078
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@ -251,8 +251,8 @@ TEST(GaussianMixtureFactor, GaussianMixtureModel) {
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* Gaussian distribution around which we sample z.
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*
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* The resulting factor graph should eliminate to a Bayes net
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* which represents a sigmoid function leaning towards
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* the tighter covariance Gaussian.
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* which represents a Gaussian-like function
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* where m1>m0 close to 3.1333.
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*/
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TEST(GaussianMixtureFactor, GaussianMixtureModel2) {
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double mu0 = 1.0, mu1 = 3.0;
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@ -272,17 +272,16 @@ TEST(GaussianMixtureFactor, GaussianMixtureModel2) {
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hbn.emplace_back(gm);
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hbn.emplace_back(mixing);
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// The result should be a sigmoid leaning towards model1
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// since it has the tighter covariance.
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// So should be m = 0.34/0.66 at z=3.0 - 1.0=2.0
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// The result should be a bell curve like function
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// with m1 > m0 close to 3.1333.
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VectorValues given;
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given.insert(z, Vector1(mu1 - mu0));
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given.insert(z, Vector1(3.133));
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HybridGaussianFactorGraph gfg = hbn.toFactorGraph(given);
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HybridBayesNet::shared_ptr bn = gfg.eliminateSequential();
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HybridBayesNet expected;
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expected.emplace_back(
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new DiscreteConditional(m, "0.338561851224/0.661438148776"));
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new DiscreteConditional(m, "0.325603277954/0.674396722046"));
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EXPECT(assert_equal(expected, *bn));
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}
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