Merge pull request #1217 from borglab/previous-hybrid

Improvements

gtsam/discrete/DecisionTree-inl.h

@@ -291,10 +291,7 @@ namespace gtsam {
         }
 
         os << "\"" << this->id() << "\" -> \"" << branch->id() << "\"";
-        if (B == 2) {
+        if (B == 2 && i == 0) os << " [style=dashed]";
-          if (i == 0) os << " [style=dashed]";
-          if (i > 1) os << " [style=bold]";
-        }
         os << std::endl;
         branch->dot(os, labelFormatter, valueFormatter, showZero);
       }

gtsam/discrete/DecisionTree.h

@@ -220,7 +220,7 @@ namespace gtsam {
     /// @{
 
     /// Make virtual
-    virtual ~DecisionTree() {}
+    virtual ~DecisionTree() = default;
 
     /// Check if tree is empty.
     bool empty() const { return !root_; }

gtsam/discrete/DiscreteFactorGraph.h

@@ -209,6 +209,10 @@ class GTSAM_EXPORT DiscreteFactorGraph
   /// @}
 };  // \ DiscreteFactorGraph
 
+std::pair<DiscreteConditional::shared_ptr, DecisionTreeFactor::shared_ptr>  //
+EliminateForMPE(const DiscreteFactorGraph& factors,
+                const Ordering& frontalKeys);
+
 /// traits
 template <>
 struct traits<DiscreteFactorGraph> : public Testable<DiscreteFactorGraph> {};

gtsam/inference/FactorGraph.h

@@ -361,7 +361,7 @@ class FactorGraph {
    * less than the original, factors at the end will be removed.  If the new
    * size is larger than the original, null factors will be appended.
    */
-  void resize(size_t size) { factors_.resize(size); }
+  virtual void resize(size_t size) { factors_.resize(size); }
 
   /** delete factor without re-arranging indexes by inserting a nullptr pointer
    */

gtsam/inference/Ordering.cpp

@@ -283,6 +283,17 @@ void Ordering::print(const std::string& str,
   cout.flush();
 }
 
+/* ************************************************************************* */
+Ordering::This& Ordering::operator+=(KeyVector& keys) {
+  this->insert(this->end(), keys.begin(), keys.end());
+  return *this;
+}
+
+/* ************************************************************************* */
+bool Ordering::contains(const Key& key) const {
+  return std::find(this->begin(), this->end(), key) != this->end();
+}
+
 /* ************************************************************************* */
 bool Ordering::equals(const Ordering& other, double tol) const {
   return (*this) == other;

gtsam/inference/Ordering.h

@@ -70,7 +70,23 @@ public:
         boost::assign_detail::call_push_back<This>(*this))(key);
   }
 
-  /// Invert (not reverse) the ordering - returns a map from key to order position
+  /**
+   * @brief Append new keys to the ordering as `ordering += keys`.
+   *
+   * @param key
+   * @return The ordering variable with appended keys.
+   */
+  This& operator+=(KeyVector& keys);
+
+  /// Check if key exists in ordering.
+  bool contains(const Key& key) const;
+
+  /**
+   * @brief Invert (not reverse) the ordering - returns a map from key to order
+   * position.
+   *
+   * @return FastMap<Key, size_t>
+   */
   FastMap<Key, size_t> invert() const;
 
   /// @name Fill-reducing Orderings @{

gtsam/inference/tests/testOrdering.cpp

@@ -199,6 +199,32 @@ TEST(Ordering, csr_format_3) {
   EXPECT(adjExpected == adjAcutal);
 }
 
+/* ************************************************************************* */
+TEST(Ordering, AppendVector) {
+  using symbol_shorthand::X;
+  Ordering actual;
+  KeyVector keys = {X(0), X(1), X(2)};
+  actual += keys;
+
+  Ordering expected;
+  expected += X(0);
+  expected += X(1);
+  expected += X(2);
+  EXPECT(assert_equal(expected, actual));
+}
+
+/* ************************************************************************* */
+TEST(Ordering, Contains) {
+  using symbol_shorthand::X;
+  Ordering ordering;
+  ordering += X(0);
+  ordering += X(1);
+  ordering += X(2);
+
+  EXPECT(ordering.contains(X(1)));
+  EXPECT(!ordering.contains(X(4)));
+}
+
 /* ************************************************************************* */
 #ifdef GTSAM_SUPPORT_NESTED_DISSECTION
 TEST(Ordering, csr_format_4) {

gtsam/linear/GaussianBayesNet.h

@@ -45,7 +45,7 @@ namespace gtsam {
     /// @name Standard Constructors
     /// @{
 
-    /** Construct empty factor graph */
+    /** Construct empty bayes net */
     GaussianBayesNet() {}
 
     /** Construct from iterator over conditionals */

gtsam/linear/GaussianConditional.cpp

@@ -15,10 +15,10 @@
  * @author Christian Potthast, Frank Dellaert
  */
 
-#include <gtsam/linear/linearExceptions.h>
 #include <gtsam/linear/GaussianConditional.h>
-#include <gtsam/linear/VectorValues.h>
 #include <gtsam/linear/Sampler.h>
+#include <gtsam/linear/VectorValues.h>
+#include <gtsam/linear/linearExceptions.h>
 
 #include <boost/format.hpp>
 #ifdef __GNUC__

gtsam/linear/GaussianConditional.h

@@ -24,6 +24,7 @@
 #include <gtsam/global_includes.h>
 #include <gtsam/linear/JacobianFactor.h>
 #include <gtsam/inference/Conditional.h>
+#include <gtsam/inference/Conditional-inst.h>
 #include <gtsam/linear/VectorValues.h>
 
 #include <random> // for std::mt19937_64