undo test change
parent
e87d1fb1de
commit
99a39e6568
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@ -39,112 +39,114 @@ using symbol_shorthand::Z;
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using namespace serializationTestHelpers;
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// BOOST_CLASS_EXPORT_GUID(Factor, "gtsam_Factor");
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// BOOST_CLASS_EXPORT_GUID(HybridFactor, "gtsam_HybridFactor");
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// BOOST_CLASS_EXPORT_GUID(JacobianFactor, "gtsam_JacobianFactor");
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// BOOST_CLASS_EXPORT_GUID(GaussianConditional, "gtsam_GaussianConditional");
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// BOOST_CLASS_EXPORT_GUID(DiscreteConditional, "gtsam_DiscreteConditional");
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BOOST_CLASS_EXPORT_GUID(Factor, "gtsam_Factor");
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BOOST_CLASS_EXPORT_GUID(HybridFactor, "gtsam_HybridFactor");
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BOOST_CLASS_EXPORT_GUID(JacobianFactor, "gtsam_JacobianFactor");
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BOOST_CLASS_EXPORT_GUID(GaussianConditional, "gtsam_GaussianConditional");
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BOOST_CLASS_EXPORT_GUID(DiscreteConditional, "gtsam_DiscreteConditional");
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// BOOST_CLASS_EXPORT_GUID(DecisionTreeFactor, "gtsam_DecisionTreeFactor");
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// using ADT = AlgebraicDecisionTree<Key>;
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// BOOST_CLASS_EXPORT_GUID(ADT, "gtsam_AlgebraicDecisionTree");
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// BOOST_CLASS_EXPORT_GUID(ADT::Leaf, "gtsam_AlgebraicDecisionTree_Leaf");
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// BOOST_CLASS_EXPORT_GUID(ADT::Choice, "gtsam_AlgebraicDecisionTree_Choice")
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BOOST_CLASS_EXPORT_GUID(DecisionTreeFactor, "gtsam_DecisionTreeFactor");
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using ADT = AlgebraicDecisionTree<Key>;
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BOOST_CLASS_EXPORT_GUID(ADT, "gtsam_AlgebraicDecisionTree");
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BOOST_CLASS_EXPORT_GUID(ADT::Leaf, "gtsam_AlgebraicDecisionTree_Leaf");
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BOOST_CLASS_EXPORT_GUID(ADT::Choice, "gtsam_AlgebraicDecisionTree_Choice")
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// BOOST_CLASS_EXPORT_GUID(HybridGaussianFactor, "gtsam_HybridGaussianFactor");
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// BOOST_CLASS_EXPORT_GUID(HybridGaussianFactor::FactorValuePairs,
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// "gtsam_HybridGaussianFactor_Factors");
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// BOOST_CLASS_EXPORT_GUID(HybridGaussianFactor::FactorValuePairs::Leaf,
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// "gtsam_HybridGaussianFactor_Factors_Leaf");
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// BOOST_CLASS_EXPORT_GUID(HybridGaussianFactor::FactorValuePairs::Choice,
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// "gtsam_HybridGaussianFactor_Factors_Choice");
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BOOST_CLASS_EXPORT_GUID(HybridGaussianFactor, "gtsam_HybridGaussianFactor");
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BOOST_CLASS_EXPORT_GUID(HybridGaussianFactor::FactorValuePairs,
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"gtsam_HybridGaussianFactor_Factors");
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BOOST_CLASS_EXPORT_GUID(HybridGaussianFactor::FactorValuePairs::Leaf,
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"gtsam_HybridGaussianFactor_Factors_Leaf");
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BOOST_CLASS_EXPORT_GUID(HybridGaussianFactor::FactorValuePairs::Choice,
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"gtsam_HybridGaussianFactor_Factors_Choice");
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// BOOST_CLASS_EXPORT_GUID(GaussianFactorGraphValuePair,
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// "gtsam_GaussianFactorGraphValuePair");
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BOOST_CLASS_EXPORT_GUID(GaussianFactorGraphValuePair,
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"gtsam_GaussianFactorGraphValuePair");
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BOOST_CLASS_EXPORT_GUID(HybridGaussianProductFactor,
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"gtsam_HybridGaussianProductFactor");
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// BOOST_CLASS_EXPORT_GUID(HybridGaussianConditional,
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// "gtsam_HybridGaussianConditional");
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// BOOST_CLASS_EXPORT_GUID(HybridGaussianConditional::Conditionals,
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// "gtsam_HybridGaussianConditional_Conditionals");
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// BOOST_CLASS_EXPORT_GUID(HybridGaussianConditional::Conditionals::Leaf,
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// "gtsam_HybridGaussianConditional_Conditionals_Leaf");
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// BOOST_CLASS_EXPORT_GUID(HybridGaussianConditional::Conditionals::Choice,
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// "gtsam_HybridGaussianConditional_Conditionals_Choice");
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// // Needed since GaussianConditional::FromMeanAndStddev uses it
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// BOOST_CLASS_EXPORT_GUID(noiseModel::Isotropic, "gtsam_noiseModel_Isotropic");
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BOOST_CLASS_EXPORT_GUID(HybridGaussianConditional,
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"gtsam_HybridGaussianConditional");
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BOOST_CLASS_EXPORT_GUID(HybridGaussianConditional::Conditionals,
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"gtsam_HybridGaussianConditional_Conditionals");
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BOOST_CLASS_EXPORT_GUID(HybridGaussianConditional::Conditionals::Leaf,
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"gtsam_HybridGaussianConditional_Conditionals_Leaf");
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BOOST_CLASS_EXPORT_GUID(HybridGaussianConditional::Conditionals::Choice,
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"gtsam_HybridGaussianConditional_Conditionals_Choice");
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// Needed since GaussianConditional::FromMeanAndStddev uses it
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BOOST_CLASS_EXPORT_GUID(noiseModel::Isotropic, "gtsam_noiseModel_Isotropic");
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// BOOST_CLASS_EXPORT_GUID(HybridBayesNet, "gtsam_HybridBayesNet");
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BOOST_CLASS_EXPORT_GUID(HybridBayesNet, "gtsam_HybridBayesNet");
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// /* ****************************************************************************/
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// // Test HybridGaussianFactor serialization.
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// TEST(HybridSerialization, HybridGaussianFactor) {
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// DiscreteKey discreteKey{M(0), 2};
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/* ****************************************************************************/
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// Test HybridGaussianFactor serialization.
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TEST(HybridSerialization, HybridGaussianFactor) {
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DiscreteKey discreteKey{M(0), 2};
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// auto A = Matrix::Zero(2, 1);
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// auto b0 = Matrix::Zero(2, 1);
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// auto b1 = Matrix::Ones(2, 1);
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// auto f0 = std::make_shared<JacobianFactor>(X(0), A, b0);
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// auto f1 = std::make_shared<JacobianFactor>(X(0), A, b1);
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// std::vector<GaussianFactor::shared_ptr> factors{f0, f1};
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auto A = Matrix::Zero(2, 1);
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auto b0 = Matrix::Zero(2, 1);
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auto b1 = Matrix::Ones(2, 1);
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auto f0 = std::make_shared<JacobianFactor>(X(0), A, b0);
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auto f1 = std::make_shared<JacobianFactor>(X(0), A, b1);
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std::vector<GaussianFactor::shared_ptr> factors{f0, f1};
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// const HybridGaussianFactor factor(discreteKey, factors);
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const HybridGaussianFactor factor(discreteKey, factors);
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// EXPECT(equalsObj<HybridGaussianFactor>(factor));
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// EXPECT(equalsXML<HybridGaussianFactor>(factor));
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// EXPECT(equalsBinary<HybridGaussianFactor>(factor));
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// }
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EXPECT(equalsObj<HybridGaussianFactor>(factor));
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EXPECT(equalsXML<HybridGaussianFactor>(factor));
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EXPECT(equalsBinary<HybridGaussianFactor>(factor));
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}
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// /* ****************************************************************************/
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// // Test HybridConditional serialization.
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// TEST(HybridSerialization, HybridConditional) {
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// const DiscreteKey mode(M(0), 2);
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// Matrix1 I = Matrix1::Identity();
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// const auto conditional = std::make_shared<GaussianConditional>(
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// GaussianConditional::FromMeanAndStddev(Z(0), I, X(0), Vector1(0), 0.5));
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// const HybridConditional hc(conditional);
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/* ****************************************************************************/
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// Test HybridConditional serialization.
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TEST(HybridSerialization, HybridConditional) {
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const DiscreteKey mode(M(0), 2);
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Matrix1 I = Matrix1::Identity();
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const auto conditional = std::make_shared<GaussianConditional>(
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GaussianConditional::FromMeanAndStddev(Z(0), I, X(0), Vector1(0), 0.5));
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const HybridConditional hc(conditional);
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// EXPECT(equalsObj<HybridConditional>(hc));
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// EXPECT(equalsXML<HybridConditional>(hc));
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// EXPECT(equalsBinary<HybridConditional>(hc));
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// }
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EXPECT(equalsObj<HybridConditional>(hc));
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EXPECT(equalsXML<HybridConditional>(hc));
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EXPECT(equalsBinary<HybridConditional>(hc));
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}
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// /* ****************************************************************************/
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// // Test HybridGaussianConditional serialization.
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// TEST(HybridSerialization, HybridGaussianConditional) {
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// const DiscreteKey mode(M(0), 2);
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// Matrix1 I = Matrix1::Identity();
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// const auto conditional0 = std::make_shared<GaussianConditional>(
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// GaussianConditional::FromMeanAndStddev(Z(0), I, X(0), Vector1(0), 0.5));
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// const auto conditional1 = std::make_shared<GaussianConditional>(
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// GaussianConditional::FromMeanAndStddev(Z(0), I, X(0), Vector1(0), 3));
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// const HybridGaussianConditional gm(mode, {conditional0, conditional1});
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/* ****************************************************************************/
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// Test HybridGaussianConditional serialization.
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TEST(HybridSerialization, HybridGaussianConditional) {
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const DiscreteKey mode(M(0), 2);
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Matrix1 I = Matrix1::Identity();
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const auto conditional0 = std::make_shared<GaussianConditional>(
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GaussianConditional::FromMeanAndStddev(Z(0), I, X(0), Vector1(0), 0.5));
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const auto conditional1 = std::make_shared<GaussianConditional>(
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GaussianConditional::FromMeanAndStddev(Z(0), I, X(0), Vector1(0), 3));
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const HybridGaussianConditional gm(mode, {conditional0, conditional1});
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// EXPECT(equalsObj<HybridGaussianConditional>(gm));
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// EXPECT(equalsXML<HybridGaussianConditional>(gm));
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// EXPECT(equalsBinary<HybridGaussianConditional>(gm));
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// }
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EXPECT(equalsObj<HybridGaussianConditional>(gm));
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EXPECT(equalsXML<HybridGaussianConditional>(gm));
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EXPECT(equalsBinary<HybridGaussianConditional>(gm));
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}
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// /* ****************************************************************************/
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// // Test HybridBayesNet serialization.
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// TEST(HybridSerialization, HybridBayesNet) {
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// Switching s(2);
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// HybridBayesNet hbn = *(s.linearizedFactorGraph.eliminateSequential());
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/* ****************************************************************************/
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// Test HybridBayesNet serialization.
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TEST(HybridSerialization, HybridBayesNet) {
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Switching s(2);
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HybridBayesNet hbn = *(s.linearizedFactorGraph.eliminateSequential());
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// EXPECT(equalsObj<HybridBayesNet>(hbn));
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// EXPECT(equalsXML<HybridBayesNet>(hbn));
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// EXPECT(equalsBinary<HybridBayesNet>(hbn));
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// }
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EXPECT(equalsObj<HybridBayesNet>(hbn));
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EXPECT(equalsXML<HybridBayesNet>(hbn));
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EXPECT(equalsBinary<HybridBayesNet>(hbn));
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}
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// /* ****************************************************************************/
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// // Test HybridBayesTree serialization.
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// TEST(HybridSerialization, HybridBayesTree) {
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// Switching s(2);
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// HybridBayesTree hbt = *(s.linearizedFactorGraph.eliminateMultifrontal());
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/* ****************************************************************************/
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// Test HybridBayesTree serialization.
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TEST(HybridSerialization, HybridBayesTree) {
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Switching s(2);
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HybridBayesTree hbt = *(s.linearizedFactorGraph.eliminateMultifrontal());
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// EXPECT(equalsObj<HybridBayesTree>(hbt));
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// EXPECT(equalsXML<HybridBayesTree>(hbt));
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// EXPECT(equalsBinary<HybridBayesTree>(hbt));
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// }
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EXPECT(equalsObj<HybridBayesTree>(hbt));
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EXPECT(equalsXML<HybridBayesTree>(hbt));
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EXPECT(equalsBinary<HybridBayesTree>(hbt));
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}
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/* ************************************************************************* */
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int main() {
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