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Fix unit tests

release/4.3a0
Frank Dellaert 2025-01-29 23:38:06 -05:00
parent 05ad198ca6
commit e6662b8206
2 changed files with 21 additions and 20 deletions
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37
gtsam/hybrid/tests/testHybridBayesNet.cpp
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@ -166,8 +166,8 @@ TEST(HybridBayesNet, Tiny) {
// prune // prune
auto pruned = bayesNet.prune(1); auto pruned = bayesNet.prune(1);
CHECK(pruned.at(1)->asHybrid()); CHECK(pruned.at(0)->asHybrid());
EXPECT_LONGS_EQUAL(1, pruned.at(1)->asHybrid()->nrComponents()); EXPECT_LONGS_EQUAL(1, pruned.at(0)->asHybrid()->nrComponents());
EXPECT(!pruned.equals(bayesNet)); EXPECT(!pruned.equals(bayesNet));
// error // error
@ -437,20 +437,21 @@ TEST(HybridBayesNet, RemoveDeadNodes) {
const double pruneDeadVariables = 0.99; const double pruneDeadVariables = 0.99;
auto prunedBayesNet = posterior->prune(2, pruneDeadVariables); auto prunedBayesNet = posterior->prune(2, pruneDeadVariables);
// First conditional is still the same: P( x0 | x1 m0)
EXPECT(prunedBayesNet.at(0)->isHybrid());
// Check that hybrid conditional that only depend on M1
// is now Gaussian and not Hybrid
EXPECT(prunedBayesNet.at(1)->isContinuous());
// Third conditional is still Hybrid: P( x1 | m0 m1) -> P( x1 | m0)
EXPECT(prunedBayesNet.at(0)->isHybrid());
// Check that discrete joint only has M0 and not (M0, M1) // Check that discrete joint only has M0 and not (M0, M1)
// since M0 is removed // since M0 is removed
KeyVector actual_keys = prunedBayesNet.at(0)->asDiscrete()->keys(); auto joint = prunedBayesNet.at(3)->asDiscrete();
EXPECT(KeyVector{M(0)} == actual_keys); EXPECT(joint);
EXPECT(joint->keys() == KeyVector{M(0)});
// Check that hybrid conditionals that only depend on M1
// are now Gaussian and not Hybrid
EXPECT(prunedBayesNet.at(0)->isDiscrete());
EXPECT(prunedBayesNet.at(1)->isDiscrete());
EXPECT(prunedBayesNet.at(2)->isHybrid());
// Only P(X2 | X1, M1) depends on M1,
// so it gets convert to a Gaussian P(X2 | X1)
EXPECT(prunedBayesNet.at(3)->isContinuous());
EXPECT(prunedBayesNet.at(4)->isHybrid());
} }
/* ****************************************************************************/ /* ****************************************************************************/
@ -479,13 +480,13 @@ TEST(HybridBayesNet, ErrorAfterPruning) {
const HybridValues hybridValues{delta.continuous(), discrete_values}; const HybridValues hybridValues{delta.continuous(), discrete_values};
double pruned_logProbability = 0; double pruned_logProbability = 0;
pruned_logProbability += pruned_logProbability +=
prunedBayesNet.at(0)->asDiscrete()->logProbability(hybridValues); prunedBayesNet.at(0)->asHybrid()->logProbability(hybridValues);
pruned_logProbability += pruned_logProbability +=
prunedBayesNet.at(1)->asHybrid()->logProbability(hybridValues); prunedBayesNet.at(1)->asHybrid()->logProbability(hybridValues);
pruned_logProbability += pruned_logProbability +=
prunedBayesNet.at(2)->asHybrid()->logProbability(hybridValues); prunedBayesNet.at(2)->asHybrid()->logProbability(hybridValues);
pruned_logProbability += pruned_logProbability +=
prunedBayesNet.at(3)->asHybrid()->logProbability(hybridValues); prunedBayesNet.at(3)->asDiscrete()->logProbability(hybridValues);
double pruned_negLogConstant = prunedBayesNet.negLogConstant(discrete_values); double pruned_negLogConstant = prunedBayesNet.negLogConstant(discrete_values);
@ -548,8 +549,8 @@ TEST(HybridBayesNet, UpdateDiscreteConditionals) {
}; };
// Get the pruned discrete conditionals as an AlgebraicDecisionTree // Get the pruned discrete conditionals as an AlgebraicDecisionTree
CHECK(pruned.at(0)->asDiscrete()); CHECK(pruned.at(4)->asDiscrete());
auto pruned_discrete_conditionals = pruned.at(0)->asDiscrete(); auto pruned_discrete_conditionals = pruned.at(4)->asDiscrete();
auto discrete_conditional_tree = auto discrete_conditional_tree =
std::dynamic_pointer_cast<DecisionTreeFactor::ADT>( std::dynamic_pointer_cast<DecisionTreeFactor::ADT>(
pruned_discrete_conditionals); pruned_discrete_conditionals);

4
gtsam/hybrid/tests/testHybridSmoother.cpp
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@ -103,7 +103,7 @@ TEST(HybridSmoother, IncrementalSmoother) {
} }
EXPECT_LONGS_EQUAL(11, EXPECT_LONGS_EQUAL(11,
smoother.hybridBayesNet().at(3)->asDiscrete()->nrValues()); smoother.hybridBayesNet().at(5)->asDiscrete()->nrValues());
// Get the continuous delta update as well as // Get the continuous delta update as well as
// the optimal discrete assignment. // the optimal discrete assignment.
@ -157,7 +157,7 @@ TEST(HybridSmoother, ValidPruningError) {
} }
EXPECT_LONGS_EQUAL(14, EXPECT_LONGS_EQUAL(14,
smoother.hybridBayesNet().at(6)->asDiscrete()->nrValues()); smoother.hybridBayesNet().at(8)->asDiscrete()->nrValues());
// Get the continuous delta update as well as // Get the continuous delta update as well as
// the optimal discrete assignment. // the optimal discrete assignment.