diff --git a/gtsam/hybrid/tests/Switching.h b/gtsam/hybrid/tests/Switching.h
index a28db4894..76721edc4 100644
--- a/gtsam/hybrid/tests/Switching.h
+++ b/gtsam/hybrid/tests/Switching.h
@@ -130,6 +130,7 @@ struct Switching {
    * @param K The total number of timesteps.
    * @param between_sigma The stddev between poses.
    * @param prior_sigma The stddev on priors (also used for measurements).
+   * @param measurements Vector of measurements for each timestep.
    */
   Switching(size_t K, double between_sigma = 1.0, double prior_sigma = 0.1,
             std::vector<double> measurements = {})
diff --git a/gtsam/hybrid/tests/testHybridEstimation.cpp b/gtsam/hybrid/tests/testHybridEstimation.cpp
index d786528d3..9104ad584 100644
--- a/gtsam/hybrid/tests/testHybridEstimation.cpp
+++ b/gtsam/hybrid/tests/testHybridEstimation.cpp
@@ -201,10 +201,14 @@ TEST(HybridEstimation, Probability) {
     VectorValues values = bayes_net->optimize();
     std::cout << i << " : " << linear_graph->probPrime(values) << std::endl;
   }
-  // std::cout << linear_graph->error(values) << std::endl;
-  // // values.at();
 
-  // // linearizationPoint.retract(values).print();
+  Switching switching(K, between_sigma, measurement_sigma, measurements);
+  auto graph = switching.linearizedFactorGraph;
+  Ordering ordering = getOrdering(graph, HybridGaussianFactorGraph());
+  HybridBayesNet::shared_ptr bayesNet = graph.eliminateSequential(ordering);
+  const DecisionTreeFactor::shared_ptr decisionTree =
+      bayesNet->discreteConditionals();
+  decisionTree->print();
 }
 
 /* ************************************************************************* */