From 3d55fe0d378dff654d8520e9d174b93be22948d5 Mon Sep 17 00:00:00 2001
From: Frank Dellaert <dellaert@gmail.com>
Date: Sun, 29 Sep 2024 22:56:32 -0700
Subject: [PATCH] Finish tests

---
 gtsam/hybrid/tests/testHybridBayesNet.cpp | 36 ++++++++++++++++++-----
 1 file changed, 29 insertions(+), 7 deletions(-)

diff --git a/gtsam/hybrid/tests/testHybridBayesNet.cpp b/gtsam/hybrid/tests/testHybridBayesNet.cpp
index 8988d1e62..ee47a698a 100644
--- a/gtsam/hybrid/tests/testHybridBayesNet.cpp
+++ b/gtsam/hybrid/tests/testHybridBayesNet.cpp
@@ -65,13 +65,18 @@ TEST(HybridBayesNet, Add) {
 // Test API for a pure discrete Bayes net P(Asia).
 TEST(HybridBayesNet, EvaluatePureDiscrete) {
   HybridBayesNet bayesNet;
-  bayesNet.emplace_shared<DiscreteConditional>(Asia, "4/6");
+  const auto pAsia = std::make_shared<DiscreteConditional>(Asia, "4/6");
+  bayesNet.push_back(pAsia);
   HybridValues zero{{}, {{asiaKey, 0}}}, one{{}, {{asiaKey, 1}}};
 
   // choose
   GaussianBayesNet empty;
   EXPECT(assert_equal(empty, bayesNet.choose(zero.discrete()), 1e-9));
 
+  // logProbability
+  EXPECT_DOUBLES_EQUAL(log(0.4), bayesNet.logProbability(zero), 1e-9);
+  EXPECT_DOUBLES_EQUAL(log(0.6), bayesNet.logProbability(one), 1e-9);
+
   // evaluate
   EXPECT_DOUBLES_EQUAL(0.4, bayesNet.evaluate(zero), 1e-9);
   EXPECT_DOUBLES_EQUAL(0.4, bayesNet(zero), 1e-9);
@@ -88,18 +93,35 @@ TEST(HybridBayesNet, EvaluatePureDiscrete) {
 
   // prune
   EXPECT(assert_equal(bayesNet, bayesNet.prune(2)));
-  // EXPECT(assert_equal(bayesNet, bayesNet.prune(1))); Should fail !!!
-  // EXPECT(assert_equal(bayesNet, bayesNet.prune(0))); Should fail !!!
+  EXPECT_LONGS_EQUAL(1, bayesNet.prune(1).at(0)->size());
 
   // errorTree
   AlgebraicDecisionTree<Key> actual = bayesNet.errorTree({});
-  AlgebraicDecisionTree<Key> expected(
+  AlgebraicDecisionTree<Key> expectedErrorTree(
       {Asia}, std::vector<double>{-log(0.4), -log(0.6)});
-  EXPECT(assert_equal(expected, actual));
+  EXPECT(assert_equal(expectedErrorTree, actual));
 
   // error
   EXPECT_DOUBLES_EQUAL(-log(0.4), bayesNet.error(zero), 1e-9);
   EXPECT_DOUBLES_EQUAL(-log(0.6), bayesNet.error(one), 1e-9);
+
+  // logDiscretePosteriorPrime, TODO: useless as -errorTree?
+  AlgebraicDecisionTree<Key> expected({Asia},
+                                      std::vector<double>{log(0.4), log(0.6)});
+  EXPECT(assert_equal(expected, bayesNet.logDiscretePosteriorPrime({})));
+
+  // logProbability
+  EXPECT_DOUBLES_EQUAL(log(0.4), bayesNet.logProbability(zero), 1e-9);
+  EXPECT_DOUBLES_EQUAL(log(0.6), bayesNet.logProbability(one), 1e-9);
+
+  // discretePosterior
+  AlgebraicDecisionTree<Key> expectedPosterior({Asia},
+                                               std::vector<double>{0.4, 0.6});
+  EXPECT(assert_equal(expectedPosterior, bayesNet.discretePosterior({})));
+
+  // toFactorGraph
+  HybridGaussianFactorGraph expectedFG{pAsia}, fg = bayesNet.toFactorGraph({});
+  EXPECT(assert_equal(expectedFG, fg));
 }
 
 /* ****************************************************************************/
@@ -358,7 +380,7 @@ TEST(HybridBayesNet, UpdateDiscreteConditionals) {
   DiscreteConditional expected_discrete_conditionals(1, s.modes, potentials);
 
   // Prune!
-  posterior->prune(maxNrLeaves);
+  auto pruned = posterior->prune(maxNrLeaves);
 
   // Functor to verify values against the expected_discrete_conditionals
   auto checker = [&](const Assignment<Key>& assignment,
@@ -375,7 +397,7 @@ TEST(HybridBayesNet, UpdateDiscreteConditionals) {
   };
 
   // Get the pruned discrete conditionals as an AlgebraicDecisionTree
-  auto pruned_discrete_conditionals = posterior->at(4)->asDiscrete();
+  auto pruned_discrete_conditionals = pruned.at(4)->asDiscrete();
   auto discrete_conditional_tree =
       std::dynamic_pointer_cast<DecisionTreeFactor::ADT>(
           pruned_discrete_conditionals);