use DiscreteConditional shared_ptr for dynamic dispatch

gtsam/hybrid/HybridBayesNet.cpp

@@ -56,11 +56,11 @@ HybridBayesNet HybridBayesNet::prune(size_t maxNrLeaves) const {
   }
 
   // Prune the joint. NOTE: again, possibly quite expensive.
-  const DecisionTreeFactor pruned = joint.prune(maxNrLeaves);
+  const DiscreteConditional::shared_ptr pruned = joint.prune(maxNrLeaves);
 
   // Create a the result starting with the pruned joint.
   HybridBayesNet result;
-  result.emplace_shared<DiscreteConditional>(pruned.size(), pruned);
+  result.push_back(std::move(pruned));
 
   /* To prune, we visitWith every leaf in the HybridGaussianConditional.
    * For each leaf, using the assignment we can check the discrete decision tree

gtsam/hybrid/HybridBayesTree.cpp

@@ -181,14 +181,15 @@ VectorValues HybridBayesTree::optimize(const DiscreteValues& assignment) const {
 void HybridBayesTree::prune(const size_t maxNrLeaves) {
   auto discreteProbs = this->roots_.at(0)->conditional()->asDiscrete();
 
-  DecisionTreeFactor prunedDiscreteProbs = discreteProbs->prune(maxNrLeaves);
-  discreteProbs->root_ = prunedDiscreteProbs.root_;
+  DiscreteConditional::shared_ptr prunedDiscreteProbs =
+      discreteProbs->prune(maxNrLeaves);
+  discreteProbs->setData(prunedDiscreteProbs);
 
   /// Helper struct for pruning the hybrid bayes tree.
   struct HybridPrunerData {
     /// The discrete decision tree after pruning.
-    DecisionTreeFactor prunedDiscreteProbs;
-    HybridPrunerData(const DecisionTreeFactor& prunedDiscreteProbs,
+    DiscreteConditional::shared_ptr prunedDiscreteProbs;
+    HybridPrunerData(const DiscreteConditional::shared_ptr& prunedDiscreteProbs,
                      const HybridBayesTree::sharedNode& parentClique)
         : prunedDiscreteProbs(prunedDiscreteProbs) {}
 

gtsam/hybrid/HybridGaussianConditional.cpp

@@ -304,18 +304,18 @@ std::set<DiscreteKey> DiscreteKeysAsSet(const DiscreteKeys &discreteKeys) {
 
 /* *******************************************************************************/
 HybridGaussianConditional::shared_ptr HybridGaussianConditional::prune(
-    const DecisionTreeFactor &discreteProbs) const {
-  // Find keys in discreteProbs.keys() but not in this->keys():
+    const DiscreteConditional::shared_ptr &discreteProbs) const {
+  // Find keys in discreteProbs->keys() but not in this->keys():
   std::set<Key> mine(this->keys().begin(), this->keys().end());
-  std::set<Key> theirs(discreteProbs.keys().begin(),
-                       discreteProbs.keys().end());
+  std::set<Key> theirs(discreteProbs->keys().begin(),
+                       discreteProbs->keys().end());
   std::vector<Key> diff;
   std::set_difference(theirs.begin(), theirs.end(), mine.begin(), mine.end(),
                       std::back_inserter(diff));
 
   // Find maximum probability value for every combination of our keys.
   Ordering keys(diff);
-  auto max = discreteProbs.max(keys);
+  auto max = discreteProbs->max(keys);
 
   // Check the max value for every combination of our keys.
   // If the max value is 0.0, we can prune the corresponding conditional.

gtsam/hybrid/HybridGaussianConditional.h

@@ -23,6 +23,7 @@
 #include <gtsam/discrete/DecisionTree-inl.h>
 #include <gtsam/discrete/DecisionTree.h>
 #include <gtsam/discrete/DecisionTreeFactor.h>
+#include <gtsam/discrete/DiscreteConditional.h>
 #include <gtsam/discrete/DiscreteKey.h>
 #include <gtsam/hybrid/HybridFactor.h>
 #include <gtsam/hybrid/HybridGaussianFactor.h>
@@ -235,7 +236,7 @@ class GTSAM_EXPORT HybridGaussianConditional
    * @return Shared pointer to possibly a pruned HybridGaussianConditional
    */
   HybridGaussianConditional::shared_ptr prune(
-      const DecisionTreeFactor &discreteProbs) const;
+      const DiscreteConditional::shared_ptr &discreteProbs) const;
 
   /// Return true if the conditional has already been pruned.
   bool pruned() const { return pruned_; }