separate MPE method in Hybrid Bayes Net/Tree

gtsam/hybrid/HybridBayesNet.cpp

@@ -124,7 +124,7 @@ GaussianBayesNet HybridBayesNet::choose(
 }
 
 /* ************************************************************************* */
-HybridValues HybridBayesNet::optimize() const {
+DiscreteValues HybridBayesNet::mpe() const {
   // Collect all the discrete factors to compute MPE
   DiscreteFactorGraph discrete_fg;
 
@@ -140,9 +140,13 @@ HybridValues HybridBayesNet::optimize() const {
       }
     }
   }
+  return discrete_fg.optimize();
+}
 
+/* ************************************************************************* */
+HybridValues HybridBayesNet::optimize() const {
   // Solve for the MPE
-  DiscreteValues mpe = discrete_fg.optimize();
+  DiscreteValues mpe = this->mpe();
 
   // Given the MPE, compute the optimal continuous values.
   return HybridValues(optimize(mpe), mpe);

gtsam/hybrid/HybridBayesNet.h

@@ -146,6 +146,14 @@ class GTSAM_EXPORT HybridBayesNet : public BayesNet<HybridConditional> {
     return evaluate(values);
   }
 
+  /**
+   * @brief Compute the Most Probable Explanation (MPE)
+   * of the discrete variables.
+   *
+   * @return DiscreteValues
+   */
+  DiscreteValues mpe() const;
+
   /**
    * @brief Solve the HybridBayesNet by first computing the MPE of all the
    * discrete variables and then optimizing the continuous variables based on

gtsam/hybrid/HybridBayesTree.cpp

@@ -59,7 +59,7 @@ DiscreteValues HybridBayesTree::discreteMaxProduct(
 }
 
 /* ************************************************************************* */
-HybridValues HybridBayesTree::optimize() const {
+DiscreteValues HybridBayesTree::mpe() const {
   DiscreteFactorGraph discrete_fg;
   DiscreteValues mpe;
 
@@ -73,11 +73,16 @@ HybridValues HybridBayesTree::optimize() const {
     discrete_fg.push_back(discrete);
     mpe = discreteMaxProduct(discrete_fg);
   } else {
-    throw std::runtime_error(
-        "HybridBayesTree root is not discrete-only. Please check elimination "
-        "ordering or use continuous factor graph.");
+    mpe = DiscreteValues();
   }
 
+  return mpe;
+}
+
+/* ************************************************************************* */
+HybridValues HybridBayesTree::optimize() const {
+  DiscreteValues mpe = this->mpe();
+
   VectorValues values = optimize(mpe);
   return HybridValues(values, mpe);
 }

gtsam/hybrid/HybridBayesTree.h

@@ -105,6 +105,14 @@ class GTSAM_EXPORT HybridBayesTree : public BayesTree<HybridBayesTreeClique> {
    */
   VectorValues optimize(const DiscreteValues& assignment) const;
 
+  /**
+   * @brief Compute the Most Probable Explanation (MPE)
+   * of the discrete variables.
+   *
+   * @return DiscreteValues
+   */
+  DiscreteValues mpe() const;
+
   /**
    * @brief Prune the underlying Bayes tree.
    *