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minor edits

release/4.3a0
Varun Agrawal 2024-08-21 20:07:03 -04:00
parent 75d4724668
commit dce56417bd
1 changed files with 6 additions and 8 deletions
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14
gtsam/hybrid/tests/testGaussianMixtureFactor.cpp
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@ -209,14 +209,14 @@ TEST(GaussianMixtureFactor, Error) {
* or both for each hybrid factor component. * or both for each hybrid factor component.
* *
* @param values Initial values for linearization. * @param values Initial values for linearization.
* @param means The mean values for the conditional components. * @param mus The mean values for the conditional components.
* @param sigmas Noise model sigma values (standard deviation). * @param sigmas Noise model sigma values (standard deviation).
* @param m1 The discrete mode key. * @param m1 The discrete mode key.
* @param z1 The measurement value. * @param z1 The measurement value.
* @return HybridGaussianFactorGraph * @return HybridGaussianFactorGraph
*/ */
HybridGaussianFactorGraph GetFactorGraphFromBayesNet( HybridGaussianFactorGraph GetFactorGraphFromBayesNet(
const gtsam::Values &values, const std::vector<double> &means, const gtsam::Values &values, const std::vector<double> &mus,
const std::vector<double> &sigmas, DiscreteKey &m1, double z1 = 0.0) { const std::vector<double> &sigmas, DiscreteKey &m1, double z1 = 0.0) {
// Noise models // Noise models
auto model0 = noiseModel::Isotropic::Sigma(1, sigmas[0]); auto model0 = noiseModel::Isotropic::Sigma(1, sigmas[0]);
@ -224,11 +224,9 @@ HybridGaussianFactorGraph GetFactorGraphFromBayesNet(
auto prior_noise = noiseModel::Isotropic::Sigma(1, 1e-3); auto prior_noise = noiseModel::Isotropic::Sigma(1, 1e-3);
// GaussianMixtureFactor component factors // GaussianMixtureFactor component factors
auto f0 = auto f0 = std::make_shared<BetweenFactor<double>>(X(1), X(2), mus[0], model0);
std::make_shared<BetweenFactor<double>>(X(1), X(2), means[0], model0); auto f1 = std::make_shared<BetweenFactor<double>>(X(1), X(2), mus[1], model1);
auto f1 = // std::vector<NonlinearFactor::shared_ptr> factors{f0, f1};
std::make_shared<BetweenFactor<double>>(X(1), X(2), means[1], model1);
std::vector<NonlinearFactor::shared_ptr> factors{f0, f1};
/// Get terms for each p^m(z1 | x1, x2) /// Get terms for each p^m(z1 | x1, x2)
Matrix H0_1, H0_2, H1_1, H1_2; Matrix H0_1, H0_2, H1_1, H1_2;
@ -275,7 +273,7 @@ HybridGaussianFactorGraph GetFactorGraphFromBayesNet(
* p(Z1 | X1, X2, M1) has 2 factors each for the binary mode m1, with only the * p(Z1 | X1, X2, M1) has 2 factors each for the binary mode m1, with only the
* means being different. * means being different.
*/ */
TEST(GaussianMixtureFactor, DifferentMeansHBN) { TEST(GaussianMixtureFactor, DifferentMeans) {
DiscreteKey m1(M(1), 2); DiscreteKey m1(M(1), 2);
Values values; Values values;