minor fixes to unit test
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				|  | @ -12,7 +12,7 @@ | ||||||
| /**
 | /**
 | ||||||
|  * @file    testHybridNonlinearISAM.cpp |  * @file    testHybridNonlinearISAM.cpp | ||||||
|  * @brief   Unit tests for nonlinear incremental inference |  * @brief   Unit tests for nonlinear incremental inference | ||||||
|  * @author  Fan Jiang, Varun Agrawal, Frank Dellaert |  * @author  Varun Agrawal, Fan Jiang, Frank Dellaert | ||||||
|  * @date    Jan 2021 |  * @date    Jan 2021 | ||||||
|  */ |  */ | ||||||
| 
 | 
 | ||||||
|  | @ -391,6 +391,23 @@ TEST(HybridNonlinearISAM, Incremental_approximate) { | ||||||
|       5, bayesTree[X(5)]->conditional()->asMixture()->nrComponents()); |       5, bayesTree[X(5)]->conditional()->asMixture()->nrComponents()); | ||||||
| } | } | ||||||
| 
 | 
 | ||||||
|  | void printConditionals(const HybridNonlinearISAM &inc, const KeyVector &keys) { | ||||||
|  |   HybridGaussianISAM bayesTree = inc.bayesTree(); | ||||||
|  |   for (auto &&key : keys) { | ||||||
|  |     std::cout << DefaultKeyFormatter(key) << std::endl; | ||||||
|  |     auto conditional = bayesTree[key]->conditional(); | ||||||
|  |     conditional->printKeys(); | ||||||
|  |     if (conditional->isHybrid()) { | ||||||
|  |       std::cout << conditional->asMixture()->nrComponents() << std::endl; | ||||||
|  |     } else if (conditional->isDiscrete()) { | ||||||
|  |       std::cout << conditional->asDiscreteConditional()->nrLeaves() | ||||||
|  |                 << std::endl; | ||||||
|  |     } else { | ||||||
|  |       // std::cout << conditional->asGaussian()->nrComponents() << std::endl;
 | ||||||
|  |     } | ||||||
|  |   } | ||||||
|  | } | ||||||
|  | 
 | ||||||
| /* ************************************************************************/ | /* ************************************************************************/ | ||||||
| // A GTSAM-only test for running inference on a single-legged robot.
 | // A GTSAM-only test for running inference on a single-legged robot.
 | ||||||
| // The leg links are represented by the chain X-Y-Z-W, where X is the base and
 | // The leg links are represented by the chain X-Y-Z-W, where X is the base and
 | ||||||
|  | @ -432,9 +449,9 @@ TEST(HybridNonlinearISAM, NonTrivial) { | ||||||
| 
 | 
 | ||||||
|   // Don't run update now since we don't have discrete variables involved.
 |   // Don't run update now since we don't have discrete variables involved.
 | ||||||
| 
 | 
 | ||||||
|   /*************** Run Round 2 ***************/ |  | ||||||
|   using PlanarMotionModel = BetweenFactor<Pose2>; |   using PlanarMotionModel = BetweenFactor<Pose2>; | ||||||
| 
 | 
 | ||||||
|  |   /*************** Run Round 2 ***************/ | ||||||
|   // Add odometry factor with discrete modes.
 |   // Add odometry factor with discrete modes.
 | ||||||
|   Pose2 odometry(1.0, 0.0, 0.0); |   Pose2 odometry(1.0, 0.0, 0.0); | ||||||
|   KeyVector contKeys = {W(0), W(1)}; |   KeyVector contKeys = {W(0), W(1)}; | ||||||
|  |  | ||||||
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