Make hybrid elimination a method of HGFG

gtsam/hybrid/HybridGaussianFactorGraph.cpp

@@ -366,18 +366,17 @@ static std::shared_ptr<Factor> createHybridGaussianFactor(
   return std::make_shared<HybridGaussianFactor>(discreteSeparator, newFactors);
 }
 
-static std::pair<HybridConditional::shared_ptr, std::shared_ptr<Factor>>
-hybridElimination(const HybridGaussianFactorGraph &factors,
-                  const Ordering &frontalKeys,
-                  const std::set<DiscreteKey> &discreteSeparatorSet) {
-  // NOTE: since we use the special JunctionTree,
-  // only possibility is continuous conditioned on discrete.
-  DiscreteKeys discreteSeparator(discreteSeparatorSet.begin(),
-                                 discreteSeparatorSet.end());
+std::pair<HybridConditional::shared_ptr, std::shared_ptr<Factor>>
+HybridGaussianFactorGraph::eliminate(const Ordering &keys) const {
+  // Since we eliminate all continuous variables first,
+  // the discrete separator will be *all* the discrete keys.
+  const std::set<DiscreteKey> keysForDiscreteVariables = discreteKeys();
+  DiscreteKeys discreteSeparator(keysForDiscreteVariables.begin(),
+                                 keysForDiscreteVariables.end());
 
   // Collect all the factors to create a set of Gaussian factor graphs in a
   // decision tree indexed by all discrete keys involved.
-  GaussianFactorGraphTree factorGraphTree = factors.assembleGraphTree();
+  GaussianFactorGraphTree factorGraphTree = assembleGraphTree();
 
   // Convert factor graphs with a nullptr to an empty factor graph.
   // This is done after assembly since it is non-trivial to keep track of which
@@ -392,7 +391,7 @@ hybridElimination(const HybridGaussianFactorGraph &factors,
     }
 
     // Expensive elimination of product factor.
-    auto result = EliminatePreferCholesky(graph, frontalKeys);
+    auto result = EliminatePreferCholesky(graph, keys);
 
     // Record whether there any continuous variables left
     someContinuousLeft |= !result.second->empty();
@@ -436,7 +435,7 @@ hybridElimination(const HybridGaussianFactorGraph &factors,
  */
 std::pair<HybridConditional::shared_ptr, std::shared_ptr<Factor>>  //
 EliminateHybrid(const HybridGaussianFactorGraph &factors,
-                const Ordering &frontalKeys) {
+                const Ordering &keys) {
   // NOTE: Because we are in the Conditional Gaussian regime there are only
   // a few cases:
   // 1. continuous variable, make a hybrid Gaussian conditional if there are
@@ -510,20 +509,13 @@ EliminateHybrid(const HybridGaussianFactorGraph &factors,
 
   if (only_discrete) {
     // Case 1: we are only dealing with discrete
-    return discreteElimination(factors, frontalKeys);
+    return discreteElimination(factors, keys);
   } else if (only_continuous) {
     // Case 2: we are only dealing with continuous
-    return continuousElimination(factors, frontalKeys);
+    return continuousElimination(factors, keys);
   } else {
     // Case 3: We are now in the hybrid land!
-    KeySet frontalKeysSet(frontalKeys.begin(), frontalKeys.end());
-
-    // Find all discrete keys.
-    // Since we eliminate all continuous variables first,
-    // the discrete separator will be *all* the discrete keys.
-    std::set<DiscreteKey> discreteSeparator = factors.discreteKeys();
-
-    return hybridElimination(factors, frontalKeys, discreteSeparator);
+    return factors.eliminate(keys);
   }
 }
 

gtsam/hybrid/HybridGaussianFactorGraph.h

@@ -217,6 +217,14 @@ class GTSAM_EXPORT HybridGaussianFactorGraph
    */
   GaussianFactorGraphTree assembleGraphTree() const;
 
+  /**
+   * @brief Eliminate the given continuous keys.
+   *
+   * @param keys The continuous keys to eliminate.
+   * @return The conditional on the  keys and a factor on the separator.
+   */
+  std::pair<std::shared_ptr<HybridConditional>, std::shared_ptr<Factor>>
+  eliminate(const Ordering& keys) const;
   /// @}
 
   /// Get the GaussianFactorGraph at a given discrete assignment.

gtsam/hybrid/tests/testHybridGaussianFactorGraph.cpp

@@ -18,6 +18,7 @@
 #include <CppUnitLite/Test.h>
 #include <CppUnitLite/TestHarness.h>
 #include <gtsam/base/TestableAssertions.h>
+#include <gtsam/base/Vector.h>
 #include <gtsam/discrete/DecisionTreeFactor.h>
 #include <gtsam/discrete/DiscreteKey.h>
 #include <gtsam/discrete/DiscreteValues.h>
@@ -42,6 +43,7 @@
 #include <functional>
 #include <iostream>
 #include <iterator>
+#include <memory>
 #include <numeric>
 #include <vector>
 
@@ -120,6 +122,25 @@ std::vector<GaussianFactor::shared_ptr> components(Key key) {
 }
 }  // namespace two
 
+/* ************************************************************************* */
+TEST(HybridGaussianFactorGraph, hybridEliminationOneFactor) {
+  HybridGaussianFactorGraph hfg;
+  hfg.add(HybridGaussianFactor(m1, two::components(X(1))));
+
+  auto result = hfg.eliminate({X(1)});
+
+  // Check that we have a valid Gaussian conditional.
+  auto hgc = result.first->asHybrid();
+  CHECK(hgc);
+  const HybridValues values{{{X(1), Z_3x1}}, {{M(1), 1}}};
+  EXPECT(HybridConditional::CheckInvariants(*result.first, values));
+
+  // Check that factor is discrete and correct
+  auto factor = std::dynamic_pointer_cast<DecisionTreeFactor>(result.second);
+  CHECK(factor);
+  EXPECT(assert_equal(DecisionTreeFactor{m1, "1 1"}, *factor));
+}
+
 /* ************************************************************************* */
 TEST(HybridGaussianFactorGraph, eliminateFullSequentialEqualChance) {
   HybridGaussianFactorGraph hfg;
@@ -221,20 +242,16 @@ TEST(HybridGaussianFactorGraph, eliminateFullMultifrontalTwoClique) {
   hfg.add(JacobianFactor(X(0), I_3x3, X(1), -I_3x3, Z_3x1));
   hfg.add(JacobianFactor(X(1), I_3x3, X(2), -I_3x3, Z_3x1));
 
-  {
-    hfg.add(HybridGaussianFactor({M(0), 2}, two::components(X(0))));
-    hfg.add(HybridGaussianFactor({M(1), 2}, two::components(X(2))));
-  }
+  hfg.add(HybridGaussianFactor({M(0), 2}, two::components(X(0))));
+  hfg.add(HybridGaussianFactor({M(1), 2}, two::components(X(2))));
 
   hfg.add(DecisionTreeFactor({{M(1), 2}, {M(2), 2}}, "1 2 3 4"));
 
   hfg.add(JacobianFactor(X(3), I_3x3, X(4), -I_3x3, Z_3x1));
   hfg.add(JacobianFactor(X(4), I_3x3, X(5), -I_3x3, Z_3x1));
 
-  {
-    hfg.add(HybridGaussianFactor({M(3), 2}, two::components(X(3))));
-    hfg.add(HybridGaussianFactor({M(2), 2}, two::components(X(5))));
-  }
+  hfg.add(HybridGaussianFactor({M(3), 2}, two::components(X(3))));
+  hfg.add(HybridGaussianFactor({M(2), 2}, two::components(X(5))));
 
   auto ordering_full =
       Ordering::ColamdConstrainedLast(hfg, {M(0), M(1), M(2), M(3)});