diff --git a/gtsam/hybrid/tests/testHybridGaussianFactorGraph.cpp b/gtsam/hybrid/tests/testHybridGaussianFactorGraph.cpp index c51d65da1..f4118c0e7 100644 --- a/gtsam/hybrid/tests/testHybridGaussianFactorGraph.cpp +++ b/gtsam/hybrid/tests/testHybridGaussianFactorGraph.cpp @@ -616,7 +616,7 @@ TEST(HybridGaussianFactorGraph, assembleGraphTree) { const int num_measurements = 1; auto fg = tiny::createHybridGaussianFactorGraph( num_measurements, VectorValues{{Z(0), Vector1(5.0)}}); - EXPECT_LONGS_EQUAL(4, fg.size()); + EXPECT_LONGS_EQUAL(3, fg.size()); // Assemble graph tree: auto actual = fg.assembleGraphTree(); @@ -628,7 +628,7 @@ TEST(HybridGaussianFactorGraph, assembleGraphTree) { CHECK(mixture); // Get prior factor: - const auto gf = boost::dynamic_pointer_cast(fg.at(2)); + const auto gf = boost::dynamic_pointer_cast(fg.at(1)); CHECK(gf); using GF = GaussianFactor::shared_ptr; const GF prior = gf->asGaussian(); @@ -701,7 +701,7 @@ TEST(HybridGaussianFactorGraph, EliminateTiny1) { auto bn = tiny::createHybridBayesNet(num_measurements); auto fg = bn.toFactorGraph(measurements); GTSAM_PRINT(bn); - EXPECT_LONGS_EQUAL(4, fg.size()); + EXPECT_LONGS_EQUAL(3, fg.size()); EXPECT(ratioTest(bn, measurements, fg)); @@ -738,7 +738,7 @@ TEST(HybridGaussianFactorGraph, EliminateTiny2) { const VectorValues measurements{{Z(0), Vector1(4.0)}, {Z(1), Vector1(6.0)}}; auto bn = tiny::createHybridBayesNet(num_measurements); auto fg = bn.toFactorGraph(measurements); - EXPECT_LONGS_EQUAL(6, fg.size()); + EXPECT_LONGS_EQUAL(4, fg.size()); // Create expected Bayes Net: HybridBayesNet expectedBayesNet; @@ -775,7 +775,7 @@ TEST(HybridGaussianFactorGraph, EliminateTiny22) { auto bn = tiny::createHybridBayesNet(num_measurements, manyModes); const VectorValues measurements{{Z(0), Vector1(4.0)}, {Z(1), Vector1(6.0)}}; auto fg = bn.toFactorGraph(measurements); - EXPECT_LONGS_EQUAL(7, fg.size()); + EXPECT_LONGS_EQUAL(5, fg.size()); EXPECT(ratioTest(bn, measurements, fg));