add helpers to get different types of keys from the hybrid graph

gtsam/hybrid/HybridGaussianFactorGraph.cpp

@@ -402,14 +402,35 @@ void HybridGaussianFactorGraph::add(DecisionTreeFactor::shared_ptr factor) {
 }
 
 /* ************************************************************************ */
-const Ordering HybridGaussianFactorGraph::getHybridOrdering(
-    OptionalOrderingType orderingType) const {
+const KeySet HybridGaussianFactorGraph::getDiscreteKeys() const {
   KeySet discrete_keys;
   for (auto &factor : factors_) {
     for (const DiscreteKey &k : factor->discreteKeys()) {
       discrete_keys.insert(k.first);
     }
   }
+  return discrete_keys;
+}
+
+/* ************************************************************************ */
+const KeySet HybridGaussianFactorGraph::getContinuousKeys() const {
+  KeySet keys;
+  for (auto &factor : factors_) {
+    for (const Key &key : factor->continuousKeys()) {
+      keys.insert(key);
+    }
+  }
+  return keys;
+}
+
+/* ************************************************************************ */
+const Ordering HybridGaussianFactorGraph::getHybridOrdering() const {
+  KeySet discrete_keys = getDiscreteKeys();
+  for (auto &factor : factors_) {
+    for (const DiscreteKey &k : factor->discreteKeys()) {
+      discrete_keys.insert(k.first);
+    }
+  }
 
   const VariableIndex index(factors_);
   Ordering ordering = Ordering::ColamdConstrainedLast(

gtsam/hybrid/HybridGaussianFactorGraph.h

@@ -161,14 +161,19 @@ class GTSAM_EXPORT HybridGaussianFactorGraph
     }
   }
 
+  /// Get all the discrete keys in the factor graph.
+  const KeySet getDiscreteKeys() const;
+
+  /// Get all the continuous keys in the factor graph.
+  const KeySet getContinuousKeys() const;
+
   /**
-   * @brief 
+   * @brief Return a Colamd constrained ordering where the discrete keys are
+   * eliminated after the continuous keys.
    *
-   * @param orderingType 
    * @return const Ordering
    */
-  const Ordering getHybridOrdering(
-      OptionalOrderingType orderingType = boost::none) const;
+  const Ordering getHybridOrdering() const;
 };
 
 }  // namespace gtsam

gtsam/hybrid/tests/testGaussianHybridFactorGraph.cpp

@@ -184,8 +184,8 @@ TEST(HybridGaussianFactorGraph, eliminateFullMultifrontalSimple) {
   hfg.add(DecisionTreeFactor(m1, {2, 8}));
   hfg.add(DecisionTreeFactor({{M(1), 2}, {M(2), 2}}, "1 2 3 4"));
 
-  HybridBayesTree::shared_ptr result = hfg.eliminateMultifrontal(
-      Ordering::ColamdConstrainedLast(hfg, {M(1), M(2)}));
+  HybridBayesTree::shared_ptr result =
+      hfg.eliminateMultifrontal(hfg.getHybridOrdering());
 
   // The bayes tree should have 3 cliques
   EXPECT_LONGS_EQUAL(3, result->size());
@@ -215,7 +215,7 @@ TEST(HybridGaussianFactorGraph, eliminateFullMultifrontalCLG) {
   hfg.add(HybridDiscreteFactor(DecisionTreeFactor(m, {2, 8})));
 
   // Get a constrained ordering keeping c1 last
-  auto ordering_full = Ordering::ColamdConstrainedLast(hfg, {M(1)});
+  auto ordering_full = hfg.getHybridOrdering();
 
   // Returns a Hybrid Bayes Tree with distribution P(x0|x1)P(x1|c1)P(c1)
   HybridBayesTree::shared_ptr hbt = hfg.eliminateMultifrontal(ordering_full);
@@ -484,8 +484,7 @@ TEST(HybridGaussianFactorGraph, SwitchingTwoVar) {
   }
   HybridBayesNet::shared_ptr hbn;
   HybridGaussianFactorGraph::shared_ptr remaining;
-  std::tie(hbn, remaining) =
-      hfg->eliminatePartialSequential(ordering_partial);
+  std::tie(hbn, remaining) = hfg->eliminatePartialSequential(ordering_partial);
 
   EXPECT_LONGS_EQUAL(14, hbn->size());
   EXPECT_LONGS_EQUAL(11, remaining->size());