fix regressions

Author: varunagrawal

gtsam/discrete/tests/testDiscreteBayesNet.cpp

@@ -99,9 +99,9 @@ TEST(DiscreteBayesNet, Asia) {
 
   // now sample from it
   DiscreteValues expectedSample{{Asia.first, 1},       {Dyspnea.first, 1},
-                                {XRay.first, 1},       {Tuberculosis.first, 0},
-                                {Smoking.first, 1},    {Either.first, 1},
-                                {LungCancer.first, 1}, {Bronchitis.first, 0}};
+                                {XRay.first, 0},       {Tuberculosis.first, 0},
+                                {Smoking.first, 1},    {Either.first, 0},
+                                {LungCancer.first, 0}, {Bronchitis.first, 1}};
   SETDEBUG("DiscreteConditional::sample", false);
   auto actualSample = chordal2->sample();
   EXPECT(assert_equal(expectedSample, actualSample));

gtsam/hybrid/HybridBayesNet.cpp

@@ -188,7 +188,7 @@ HybridValues HybridBayesNet::sample(const HybridValues &given,
     }
   }
   // Sample a discrete assignment.
-  const DiscreteValues assignment = dbn.sample(given.discrete());
+  const DiscreteValues assignment = dbn.sample(given.discrete(), rng);
   // Select the continuous Bayes net corresponding to the assignment.
   GaussianBayesNet gbn = choose(assignment);
   // Sample from the Gaussian Bayes net.

gtsam/hybrid/tests/testHybridBayesNet.cpp

@@ -90,7 +90,7 @@ TEST(HybridBayesNet, EvaluatePureDiscrete) {
 
   // sample
   std::mt19937_64 rng(42);
-  EXPECT(assert_equal(zero, bayesNet.sample(&rng)));
+  EXPECT(assert_equal(one, bayesNet.sample(&rng)));
   EXPECT(assert_equal(one, bayesNet.sample(one, &rng)));
   EXPECT(assert_equal(zero, bayesNet.sample(zero, &rng)));
 
@@ -616,13 +616,13 @@ TEST(HybridBayesNet, Sampling) {
   double discrete_sum =
       std::accumulate(discrete_samples.begin(), discrete_samples.end(),
                       decltype(discrete_samples)::value_type(0));
-  EXPECT_DOUBLES_EQUAL(0.477, discrete_sum / num_samples, 1e-9);
+  EXPECT_DOUBLES_EQUAL(0.519, discrete_sum / num_samples, 1e-9);
 
   VectorValues expected;
   // regression for specific RNG seed
 #if __APPLE__ || _WIN32
-  expected.insert({X(0), Vector1(-0.0131207162712)});
-  expected.insert({X(1), Vector1(-0.499026377568)});
+  expected.insert({X(0), Vector1(0.0252479903896)});
+  expected.insert({X(1), Vector1(-0.513637101911)});
 #elif __linux__
   expected.insert({X(0), Vector1(-0.00799425182219)});
   expected.insert({X(1), Vector1(-0.526463854268)});