diff --git a/gtsam/hybrid/tests/testHybridMotionModel.cpp b/gtsam/hybrid/tests/testHybridMotionModel.cpp
index 5d307e81f..a4de6a17b 100644
--- a/gtsam/hybrid/tests/testHybridMotionModel.cpp
+++ b/gtsam/hybrid/tests/testHybridMotionModel.cpp
@@ -21,8 +21,8 @@
 #include <gtsam/base/Testable.h>
 #include <gtsam/base/TestableAssertions.h>
 #include <gtsam/discrete/DiscreteConditional.h>
-#include <gtsam/discrete/TableDistribution.h>
 #include <gtsam/discrete/DiscreteValues.h>
+#include <gtsam/discrete/TableDistribution.h>
 #include <gtsam/hybrid/HybridBayesNet.h>
 #include <gtsam/hybrid/HybridGaussianConditional.h>
 #include <gtsam/hybrid/HybridGaussianFactor.h>
@@ -145,8 +145,8 @@ TEST(HybridGaussianFactorGraph, TwoStateModel) {
     // Importance sampling run with 100k samples gives 50.051/49.949
     // approximateDiscreteMarginal(hbn, hybridMotionModel, given);
     TableDistribution expected(m1, "50 50");
-    EXPECT(assert_equal(expected,
-                        *(bn->at(2)->asDiscrete<TableDistribution>())));
+    EXPECT(
+        assert_equal(expected, *(bn->at(2)->asDiscrete<TableDistribution>())));
   }
 
   {
@@ -163,8 +163,8 @@ TEST(HybridGaussianFactorGraph, TwoStateModel) {
     // Values taken from an importance sampling run with 100k samples:
     // approximateDiscreteMarginal(hbn, hybridMotionModel, given);
     TableDistribution expected(m1, "44.3854 55.6146");
-    EXPECT(assert_equal(
-        expected, *(bn->at(2)->asDiscrete<TableDistribution>()), 0.02));
+    EXPECT(assert_equal(expected, *(bn->at(2)->asDiscrete<TableDistribution>()),
+                        0.02));
   }
 }
 
@@ -253,8 +253,7 @@ TEST(HybridGaussianFactorGraph, TwoStateModel2) {
     // approximateDiscreteMarginal(hbn, hybridMotionModel, given);
     TableDistribution expected(m1, "48.3158 51.6842");
     EXPECT(assert_equal(
-        expected, *(eliminated->at(2)->asDiscrete<TableDistribution>()),
-        0.02));
+        expected, *(eliminated->at(2)->asDiscrete<TableDistribution>()), 0.02));
   }
 
   {
@@ -269,8 +268,8 @@ TEST(HybridGaussianFactorGraph, TwoStateModel2) {
     // Values taken from an importance sampling run with 100k samples:
     // approximateDiscreteMarginal(hbn, hybridMotionModel, given);
     TableDistribution expected(m1, "55.396 44.604");
-    EXPECT(assert_equal(
-        expected, *(bn->at(2)->asDiscrete<TableDistribution>()), 0.02));
+    EXPECT(assert_equal(expected, *(bn->at(2)->asDiscrete<TableDistribution>()),
+                        0.02));
   }
 }
 
@@ -347,8 +346,8 @@ TEST(HybridGaussianFactorGraph, TwoStateModel3) {
     // Values taken from an importance sampling run with 100k samples:
     // approximateDiscreteMarginal(hbn, hybridMotionModel, given);
     TableDistribution expected(m1, "51.7762 48.2238");
-    EXPECT(assert_equal(
-        expected, *(bn->at(2)->asDiscrete<TableDistribution>()), 0.02));
+    EXPECT(assert_equal(expected, *(bn->at(2)->asDiscrete<TableDistribution>()),
+                        0.02));
   }
 
   {
@@ -363,8 +362,8 @@ TEST(HybridGaussianFactorGraph, TwoStateModel3) {
     // Values taken from an importance sampling run with 100k samples:
     // approximateDiscreteMarginal(hbn, hybridMotionModel, given);
     TableDistribution expected(m1, "49.0762 50.9238");
-    EXPECT(assert_equal(
-        expected, *(bn->at(2)->asDiscrete<TableDistribution>()), 0.05));
+    EXPECT(assert_equal(expected, *(bn->at(2)->asDiscrete<TableDistribution>()),
+                        0.05));
   }
 }
 
@@ -390,8 +389,8 @@ TEST(HybridGaussianFactorGraph, TwoStateModel4) {
   // Values taken from an importance sampling run with 100k samples:
   // approximateDiscreteMarginal(hbn, hybridMotionModel, given);
   TableDistribution expected(m1, "8.91527 91.0847");
-  EXPECT(assert_equal(
-      expected, *(bn->at(2)->asDiscrete<TableDistribution>()), 0.01));
+  EXPECT(assert_equal(expected, *(bn->at(2)->asDiscrete<TableDistribution>()),
+                      0.01));
 }
 
 /* ************************************************************************* */
@@ -496,7 +495,7 @@ TEST(HybridGaussianFactorGraph, DifferentMeans) {
         VectorValues{{X(0), Vector1(0.0)}, {X(1), Vector1(0.25)}},
         DiscreteValues{{M(1), 1}});
 
-    // EXPECT(assert_equal(expected, actual));
+    EXPECT(assert_equal(expected, actual));
 
     {
       DiscreteValues dv{{M(1), 0}};
@@ -546,8 +545,8 @@ TEST(HybridGaussianFactorGraph, DifferentCovariances) {
   DiscreteValues dv0{{M(1), 0}};
   DiscreteValues dv1{{M(1), 1}};
 
-  DiscreteConditional expected_m1(m1, "0.5/0.5");
-  DiscreteConditional actual_m1 = *(hbn->at(2)->asDiscrete());
+  TableDistribution expected_m1(m1, "0.5 0.5");
+  TableDistribution actual_m1 = *(hbn->at(2)->asDiscrete<TableDistribution>());
 
   EXPECT(assert_equal(expected_m1, actual_m1));
 }
diff --git a/gtsam/hybrid/tests/testHybridNonlinearFactorGraph.cpp b/gtsam/hybrid/tests/testHybridNonlinearFactorGraph.cpp
index 5bf97d093..3df03021b 100644
--- a/gtsam/hybrid/tests/testHybridNonlinearFactorGraph.cpp
+++ b/gtsam/hybrid/tests/testHybridNonlinearFactorGraph.cpp
@@ -1063,8 +1063,8 @@ TEST(HybridNonlinearFactorGraph, DifferentCovariances) {
   DiscreteValues dv0{{M(1), 0}};
   DiscreteValues dv1{{M(1), 1}};
 
-  DiscreteConditional expected_m1(m1, "0.5/0.5");
-  DiscreteConditional actual_m1 = *(hbn->at(2)->asDiscrete());
+  TableDistribution expected_m1(m1, "0.5 0.5");
+  TableDistribution actual_m1 = *(hbn->at(2)->asDiscrete<TableDistribution>());
 
   EXPECT(assert_equal(expected_m1, actual_m1));
 }