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Fixed test to work with "hidden constant" scheme

release/4.3a0
Frank Dellaert 2023-01-16 18:03:51 -08:00
parent 202a5a3264
commit a5951d8d34
1 changed files with 5 additions and 5 deletions
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10
gtsam/hybrid/tests/testHybridGaussianFactorGraph.cpp
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@ -616,7 +616,7 @@ TEST(HybridGaussianFactorGraph, assembleGraphTree) {
const int num_measurements = 1; const int num_measurements = 1;
auto fg = tiny::createHybridGaussianFactorGraph( auto fg = tiny::createHybridGaussianFactorGraph(
num_measurements, VectorValues{{Z(0), Vector1(5.0)}}); num_measurements, VectorValues{{Z(0), Vector1(5.0)}});
EXPECT_LONGS_EQUAL(4, fg.size()); EXPECT_LONGS_EQUAL(3, fg.size());
// Assemble graph tree: // Assemble graph tree:
auto actual = fg.assembleGraphTree(); auto actual = fg.assembleGraphTree();
@ -628,7 +628,7 @@ TEST(HybridGaussianFactorGraph, assembleGraphTree) {
CHECK(mixture); CHECK(mixture);
// Get prior factor: // Get prior factor:
const auto gf = boost::dynamic_pointer_cast<HybridConditional>(fg.at(2)); const auto gf = boost::dynamic_pointer_cast<HybridConditional>(fg.at(1));
CHECK(gf); CHECK(gf);
using GF = GaussianFactor::shared_ptr; using GF = GaussianFactor::shared_ptr;
const GF prior = gf->asGaussian(); const GF prior = gf->asGaussian();
@ -701,7 +701,7 @@ TEST(HybridGaussianFactorGraph, EliminateTiny1) {
auto bn = tiny::createHybridBayesNet(num_measurements); auto bn = tiny::createHybridBayesNet(num_measurements);
auto fg = bn.toFactorGraph(measurements); auto fg = bn.toFactorGraph(measurements);
GTSAM_PRINT(bn); GTSAM_PRINT(bn);
EXPECT_LONGS_EQUAL(4, fg.size()); EXPECT_LONGS_EQUAL(3, fg.size());
EXPECT(ratioTest(bn, measurements, fg)); 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)}}; const VectorValues measurements{{Z(0), Vector1(4.0)}, {Z(1), Vector1(6.0)}};
auto bn = tiny::createHybridBayesNet(num_measurements); auto bn = tiny::createHybridBayesNet(num_measurements);
auto fg = bn.toFactorGraph(measurements); auto fg = bn.toFactorGraph(measurements);
EXPECT_LONGS_EQUAL(6, fg.size()); EXPECT_LONGS_EQUAL(4, fg.size());
// Create expected Bayes Net: // Create expected Bayes Net:
HybridBayesNet expectedBayesNet; HybridBayesNet expectedBayesNet;
@ -775,7 +775,7 @@ TEST(HybridGaussianFactorGraph, EliminateTiny22) {
auto bn = tiny::createHybridBayesNet(num_measurements, manyModes); auto bn = tiny::createHybridBayesNet(num_measurements, manyModes);
const VectorValues measurements{{Z(0), Vector1(4.0)}, {Z(1), Vector1(6.0)}}; const VectorValues measurements{{Z(0), Vector1(4.0)}, {Z(1), Vector1(6.0)}};
auto fg = bn.toFactorGraph(measurements); auto fg = bn.toFactorGraph(measurements);
EXPECT_LONGS_EQUAL(7, fg.size()); EXPECT_LONGS_EQUAL(5, fg.size());
EXPECT(ratioTest(bn, measurements, fg)); EXPECT(ratioTest(bn, measurements, fg));