initial changes

gtsam/hybrid/HybridFactorGraph.cpp

@@ -17,7 +17,6 @@
  * @date   January, 2023
  */
 
-#include <gtsam/discrete/DecisionTreeFactor.h>
 #include <gtsam/hybrid/HybridFactorGraph.h>
 
 namespace gtsam {
@@ -26,7 +25,7 @@ namespace gtsam {
 std::set<DiscreteKey> HybridFactorGraph::discreteKeys() const {
   std::set<DiscreteKey> keys;
   for (auto& factor : factors_) {
-    if (auto p = std::dynamic_pointer_cast<DecisionTreeFactor>(factor)) {
+    if (auto p = std::dynamic_pointer_cast<DiscreteFactor>(factor)) {
       for (const DiscreteKey& key : p->discreteKeys()) {
         keys.insert(key);
       }

gtsam/hybrid/HybridGaussianFactorGraph.cpp

@@ -48,8 +48,6 @@
 #include <utility>
 #include <vector>
 
-// #define HYBRID_TIMING
-
 namespace gtsam {
 
 /// Specialize EliminateableFactorGraph for HybridGaussianFactorGraph:
@@ -120,7 +118,7 @@ GaussianFactorGraphTree HybridGaussianFactorGraph::assembleGraphTree() const {
         // TODO(dellaert): in C++20, we can use std::visit.
         continue;
       }
-    } else if (dynamic_pointer_cast<DecisionTreeFactor>(f)) {
+    } else if (dynamic_pointer_cast<DiscreteFactor>(f)) {
       // Don't do anything for discrete-only factors
       // since we want to eliminate continuous values only.
       continue;
@@ -167,8 +165,8 @@ discreteElimination(const HybridGaussianFactorGraph &factors,
   DiscreteFactorGraph dfg;
 
   for (auto &f : factors) {
-    if (auto dtf = dynamic_pointer_cast<DecisionTreeFactor>(f)) {
-      dfg.push_back(dtf);
+    if (auto df = dynamic_pointer_cast<DiscreteFactor>(f)) {
+      dfg.push_back(df);
     } else if (auto orphan = dynamic_pointer_cast<OrphanWrapper>(f)) {
       // Ignore orphaned clique.
       // TODO(dellaert): is this correct? If so explain here.
@@ -262,9 +260,13 @@ hybridElimination(const HybridGaussianFactorGraph &factors,
     };
 
     DecisionTree<Key, double> probabilities(eliminationResults, probability);
+
+    auto dtf =
+        std::make_shared<DecisionTreeFactor>(discreteSeparator, probabilities);
+
     return {
         std::make_shared<HybridConditional>(gaussianMixture),
-        std::make_shared<DecisionTreeFactor>(discreteSeparator, probabilities)};
+        std::make_shared<TableFactor>(discreteSeparator, dtf->probabilities())};
   } else {
     // Otherwise, we create a resulting GaussianMixtureFactor on the separator,
     // taking care to correct for conditional constant.
@@ -433,7 +435,7 @@ AlgebraicDecisionTree<Key> HybridGaussianFactorGraph::error(
       // Add the gaussian factor error to every leaf of the error tree.
       error_tree = error_tree.apply(
           [error](double leaf_value) { return leaf_value + error; });
-    } else if (dynamic_pointer_cast<DecisionTreeFactor>(f)) {
+    } else if (dynamic_pointer_cast<DiscreteFactor>(f)) {
       // If factor at `idx` is discrete-only, we skip.
       continue;
     } else {

gtsam/hybrid/HybridGaussianFactorGraph.h

@@ -40,6 +40,7 @@ class HybridEliminationTree;
 class HybridBayesTree;
 class HybridJunctionTree;
 class DecisionTreeFactor;
+class TableFactor;
 class JacobianFactor;
 class HybridValues;
 

gtsam/hybrid/HybridJunctionTree.cpp

@@ -66,7 +66,7 @@ struct HybridConstructorTraversalData {
         for (auto& k : hf->discreteKeys()) {
           data.discreteKeys.insert(k.first);
         }
-      } else if (auto hf = std::dynamic_pointer_cast<DecisionTreeFactor>(f)) {
+      } else if (auto hf = std::dynamic_pointer_cast<DiscreteFactor>(f)) {
         for (auto& k : hf->discreteKeys()) {
           data.discreteKeys.insert(k.first);
         }
@@ -161,7 +161,7 @@ HybridJunctionTree::HybridJunctionTree(
   Data rootData(0);
   rootData.junctionTreeNode =
       std::make_shared<typename Base::Node>();  // Make a dummy node to gather
-                                                  // the junction tree roots
+                                                // the junction tree roots
   treeTraversal::DepthFirstForest(eliminationTree, rootData,
                                   Data::ConstructorTraversalVisitorPre,
                                   Data::ConstructorTraversalVisitorPost);

gtsam/hybrid/HybridNonlinearFactorGraph.cpp

@@ -17,6 +17,7 @@
  */
 
 #include <gtsam/discrete/DecisionTreeFactor.h>
+#include <gtsam/discrete/TableFactor.h>
 #include <gtsam/hybrid/GaussianMixture.h>
 #include <gtsam/hybrid/HybridGaussianFactorGraph.h>
 #include <gtsam/hybrid/HybridNonlinearFactorGraph.h>
@@ -67,7 +68,7 @@ HybridGaussianFactorGraph::shared_ptr HybridNonlinearFactorGraph::linearize(
     } else if (auto nlf = dynamic_pointer_cast<NonlinearFactor>(f)) {
       const GaussianFactor::shared_ptr& gf = nlf->linearize(continuousValues);
       linearFG->push_back(gf);
-    } else if (dynamic_pointer_cast<DecisionTreeFactor>(f)) {
+    } else if (dynamic_pointer_cast<DiscreteFactor>(f)) {
       // If discrete-only: doesn't need linearization.
       linearFG->push_back(f);
     } else if (auto gmf = dynamic_pointer_cast<GaussianMixtureFactor>(f)) {

gtsam/hybrid/tests/testHybridBayesTree.cpp

@@ -146,7 +146,7 @@ TEST(HybridBayesTree, Optimize) {
 
   DiscreteFactorGraph dfg;
   for (auto&& f : *remainingFactorGraph) {
-    auto discreteFactor = dynamic_pointer_cast<DecisionTreeFactor>(f);
+    auto discreteFactor = dynamic_pointer_cast<DiscreteFactor>(f);
     assert(discreteFactor);
     dfg.push_back(discreteFactor);
   }