12345qiupeng
/
gtsam
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

update HybridSmoother tests

release/4.3a0
Varun Agrawal 2025-01-23 21:13:39 -05:00
parent b4020ed67b
commit 8ad3cb6ba1
1 changed files with 4 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

10
gtsam/hybrid/tests/testHybridSmoother.cpp
View File

@ -95,16 +95,15 @@ TEST(HybridSmoother, IncrementalSmoother) {
initial.insert(X(k), switching.linearizationPoint.at<double>(X(k))); initial.insert(X(k), switching.linearizationPoint.at<double>(X(k)));
HybridGaussianFactorGraph linearized = *graph.linearize(initial); HybridGaussianFactorGraph linearized = *graph.linearize(initial);
Ordering ordering = smoother.getOrdering(linearized);
smoother.update(linearized, maxNrLeaves, ordering); smoother.update(linearized, maxNrLeaves);
// Clear all the factors from the graph // Clear all the factors from the graph
graph.resize(0); graph.resize(0);
} }
EXPECT_LONGS_EQUAL(11, EXPECT_LONGS_EQUAL(11,
smoother.hybridBayesNet().at(0)->asDiscrete()->nrValues()); smoother.hybridBayesNet().at(3)->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.
@ -150,16 +149,15 @@ TEST(HybridSmoother, ValidPruningError) {
initial.insert(X(k), switching.linearizationPoint.at<double>(X(k))); initial.insert(X(k), switching.linearizationPoint.at<double>(X(k)));
HybridGaussianFactorGraph linearized = *graph.linearize(initial); HybridGaussianFactorGraph linearized = *graph.linearize(initial);
Ordering ordering = smoother.getOrdering(linearized);
smoother.update(linearized, maxNrLeaves, ordering); smoother.update(linearized, maxNrLeaves);
// Clear all the factors from the graph // Clear all the factors from the graph
graph.resize(0); graph.resize(0);
} }
EXPECT_LONGS_EQUAL(14, EXPECT_LONGS_EQUAL(14,
smoother.hybridBayesNet().at(0)->asDiscrete()->nrValues()); smoother.hybridBayesNet().at(6)->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.