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						a0870fc736
					
				|  | @ -104,6 +104,9 @@ virtual class DiscreteConditional : gtsam::DecisionTreeFactor { | |||
|   DiscreteConditional(const gtsam::DecisionTreeFactor& joint, | ||||
|                       const gtsam::DecisionTreeFactor& marginal, | ||||
|                       const gtsam::Ordering& orderedKeys); | ||||
|   DiscreteConditional(const gtsam::DiscreteKey& key, | ||||
|                       const gtsam::DiscreteKeys& parents, | ||||
|                       const std::vector<double>& table); | ||||
| 
 | ||||
|   // Standard interface | ||||
|   double logNormalizationConstant() const; | ||||
|  |  | |||
|  | @ -66,7 +66,7 @@ void GaussianMixtureFactor::print(const std::string &s, | |||
|         [&](const sharedFactor &gf) -> std::string { | ||||
|           RedirectCout rd; | ||||
|           std::cout << ":\n"; | ||||
|           if (gf && !gf->empty()) { | ||||
|           if (gf) { | ||||
|             gf->print("", formatter); | ||||
|             return rd.str(); | ||||
|           } else { | ||||
|  |  | |||
|  | @ -92,7 +92,10 @@ class GaussianMixture : gtsam::HybridFactor { | |||
|                   const std::vector<gtsam::GaussianConditional::shared_ptr>& | ||||
|                       conditionalsList); | ||||
| 
 | ||||
|   gtsam::GaussianMixtureFactor* likelihood(const gtsam::VectorValues &frontals) const; | ||||
|   gtsam::GaussianMixtureFactor* likelihood( | ||||
|       const gtsam::VectorValues& frontals) const; | ||||
|   double logProbability(const gtsam::HybridValues& values) const; | ||||
|   double evaluate(const gtsam::HybridValues& values) const; | ||||
| 
 | ||||
|   void print(string s = "GaussianMixture\n", | ||||
|              const gtsam::KeyFormatter& keyFormatter = | ||||
|  |  | |||
|  | @ -489,7 +489,7 @@ virtual class GaussianConditional : gtsam::JacobianFactor { | |||
|   GaussianConditional(size_t key, Vector d, Matrix R, size_t name1, Matrix S, | ||||
|                       size_t name2, Matrix T, | ||||
|                       const gtsam::noiseModel::Diagonal* sigmas); | ||||
|   GaussianConditional(const vector<std::pair<gtsam::Key, Matrix>> terms, | ||||
|   GaussianConditional(const std::vector<std::pair<gtsam::Key, Matrix>> terms, | ||||
|                       size_t nrFrontals, Vector d, | ||||
|                       const gtsam::noiseModel::Diagonal* sigmas); | ||||
| 
 | ||||
|  | @ -751,4 +751,4 @@ class KalmanFilter { | |||
|       Vector z, Matrix Q); | ||||
| }; | ||||
| 
 | ||||
| } | ||||
| } | ||||
|  |  | |||
|  | @ -63,6 +63,6 @@ A RegularJacobianFactor that uses some badly documented reduction on the Jacobia | |||
| 
 | ||||
| A RegularJacobianFactor that eliminates a point using sequential elimination. | ||||
| 
 | ||||
| ### JacobianFactorQR | ||||
| ### JacobianFactorSVD | ||||
| 
 | ||||
| A RegularJacobianFactor that uses the "Nullspace Trick" by Mourikis et al. See the documentation in the file, which *is* well documented. | ||||
| A RegularJacobianFactor that uses the "Nullspace Trick" by Mourikis et al. See the documentation in the file, which *is* well documented. | ||||
|  |  | |||
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