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fix comments

release/4.3a0
Varun Agrawal 2024-08-27 09:55:05 -04:00
parent 3ee0ec3a6a
commit e81272b078
1 changed files with 6 additions and 7 deletions
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13
gtsam/hybrid/tests/testGaussianMixtureFactor.cpp
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@ -251,8 +251,8 @@ TEST(GaussianMixtureFactor, GaussianMixtureModel) {
* Gaussian distribution around which we sample z. * Gaussian distribution around which we sample z.
* *
* The resulting factor graph should eliminate to a Bayes net * The resulting factor graph should eliminate to a Bayes net
* which represents a sigmoid function leaning towards * which represents a Gaussian-like function
* the tighter covariance Gaussian. * where m1>m0 close to 3.1333.
*/ */
TEST(GaussianMixtureFactor, GaussianMixtureModel2) { TEST(GaussianMixtureFactor, GaussianMixtureModel2) {
double mu0 = 1.0, mu1 = 3.0; double mu0 = 1.0, mu1 = 3.0;
@ -272,17 +272,16 @@ TEST(GaussianMixtureFactor, GaussianMixtureModel2) {
hbn.emplace_back(gm); hbn.emplace_back(gm);
hbn.emplace_back(mixing); hbn.emplace_back(mixing);
// The result should be a sigmoid leaning towards model1 // The result should be a bell curve like function
// since it has the tighter covariance. // with m1 > m0 close to 3.1333.
// So should be m = 0.34/0.66 at z=3.0 - 1.0=2.0
VectorValues given; VectorValues given;
given.insert(z, Vector1(mu1 - mu0)); given.insert(z, Vector1(3.133));
HybridGaussianFactorGraph gfg = hbn.toFactorGraph(given); HybridGaussianFactorGraph gfg = hbn.toFactorGraph(given);
HybridBayesNet::shared_ptr bn = gfg.eliminateSequential(); HybridBayesNet::shared_ptr bn = gfg.eliminateSequential();
HybridBayesNet expected; HybridBayesNet expected;
expected.emplace_back( expected.emplace_back(
new DiscreteConditional(m, "0.338561851224/0.661438148776")); new DiscreteConditional(m, "0.325603277954/0.674396722046"));
EXPECT(assert_equal(expected, *bn)); EXPECT(assert_equal(expected, *bn));
} }