From 5d0bc3191a86b9adb337f88122239c0eae62a973 Mon Sep 17 00:00:00 2001 From: Frank Dellaert Date: Wed, 4 Jan 2023 21:41:22 -0800 Subject: [PATCH] Fix some comments --- .../tests/testHybridGaussianFactorGraph.cpp | 18 ++++++------------ 1 file changed, 6 insertions(+), 12 deletions(-) diff --git a/gtsam/hybrid/tests/testHybridGaussianFactorGraph.cpp b/gtsam/hybrid/tests/testHybridGaussianFactorGraph.cpp index cc4571875..cab867715 100644 --- a/gtsam/hybrid/tests/testHybridGaussianFactorGraph.cpp +++ b/gtsam/hybrid/tests/testHybridGaussianFactorGraph.cpp @@ -764,13 +764,10 @@ TEST(HybridGaussianFactorGraph, EliminateTiny22) { // regression EXPECT_DOUBLES_EQUAL(0.018253037966018862, expected_ratio, 1e-6); - // 3. Do sampling + // Test ratios for a number of independent samples: constexpr int num_samples = 100; for (size_t i = 0; i < num_samples; i++) { - // Sample from the bayes net HybridValues sample = bn.sample(&rng); - - // Check that the ratio is constant. EXPECT_DOUBLES_EQUAL(expected_ratio, compute_ratio(&sample), 1e-6); } } @@ -822,7 +819,7 @@ TEST(HybridGaussianFactorGraph, EliminateSwitchingNetwork) { // Create measurements consistent with moving right every time: const VectorValues measurements{ {Z(0), Vector1(0.0)}, {Z(1), Vector1(1.0)}, {Z(2), Vector1(2.0)}}; - const auto fg = bn.toFactorGraph(measurements); + const HybridGaussianFactorGraph fg = bn.toFactorGraph(measurements); // Create ordering that eliminates in time order, then discrete modes: Ordering ordering; @@ -835,11 +832,11 @@ TEST(HybridGaussianFactorGraph, EliminateSwitchingNetwork) { ordering.push_back(M(1)); ordering.push_back(M(2)); - // Test elimination result has correct size: - const auto posterior = fg.eliminateSequential(ordering); + // Do elimination: + const HybridBayesNet::shared_ptr posterior = fg.eliminateSequential(ordering); // GTSAM_PRINT(*posterior); - // Test elimination result has correct size: + // Test resulting posterior Bayes net has correct size: EXPECT_LONGS_EQUAL(8, posterior->size()); // TODO(dellaert): below is copy/pasta from above, refactor @@ -861,13 +858,10 @@ TEST(HybridGaussianFactorGraph, EliminateSwitchingNetwork) { // regression EXPECT_DOUBLES_EQUAL(0.0094526745785019472, expected_ratio, 1e-6); - // 3. Do sampling + // Test ratios for a number of independent samples: constexpr int num_samples = 100; for (size_t i = 0; i < num_samples; i++) { - // Sample from the bayes net HybridValues sample = bn.sample(&rng); - - // Check that the ratio is constant. EXPECT_DOUBLES_EQUAL(expected_ratio, compute_ratio(&sample), 1e-6); } }