Removed extra code that was needed for variant

gtsam/inference/BayesTree-inst.h

@@ -26,7 +26,6 @@
 #include <gtsam/base/timing.h>
 
 #include <fstream>
-#include <functional>
 
 namespace gtsam {
 
@@ -278,9 +277,8 @@ namespace gtsam {
     FactorGraphType cliqueMarginal = clique->marginal2(function);
 
     // Now, marginalize out everything that is not variable j
-    auto ordering  = Ordering{j};
     BayesNetType marginalBN =
-        *cliqueMarginal.marginalMultifrontalBayesNet(std::cref(ordering), function);
+        *cliqueMarginal.marginalMultifrontalBayesNet(Ordering{j}, function);
 
     // The Bayes net should contain only one conditional for variable j, so return it
     return marginalBN.front();
@@ -402,9 +400,8 @@ namespace gtsam {
       gttoc(Disjoint_marginals);
     }
 
-    auto ordering = Ordering{j1, j2};
     // now, marginalize out everything that is not variable j1 or j2
-    return p_BC1C2.marginalMultifrontalBayesNet(std::cref(ordering), function);
+    return p_BC1C2.marginalMultifrontalBayesNet(Ordering{j1, j2}, function);
   }
 
   /* ************************************************************************* */

gtsam/inference/BayesTreeCliqueBase-inst.h

@@ -20,8 +20,6 @@
 #include <gtsam/inference/FactorGraph-inst.h>
 #include <gtsam/base/timing.h>
 
-#include <functional>
-
 namespace gtsam {
 
   /* ************************************************************************* */
@@ -178,9 +176,8 @@ namespace gtsam {
         // The variables we want to keepSet are exactly the ones in S
         KeyVector indicesS(this->conditional()->beginParents(),
                            this->conditional()->endParents());
-        auto ordering = Ordering(indicesS);
         auto separatorMarginal =
-            p_Cp.marginalMultifrontalBayesNet(std::cref(ordering), function);
+            p_Cp.marginalMultifrontalBayesNet(Ordering(indicesS), function);
         cachedSeparatorMarginal_ = *separatorMarginal;
       }
     }

gtsam/inference/EliminateableFactorGraph-inst.h

@@ -21,15 +21,6 @@
 #include <gtsam/inference/EliminateableFactorGraph.h>
 #include <gtsam/inference/inferenceExceptions.h>
 
-// some helper functions
-namespace {
-  // A function to take a reference_wrapper object and return the underlying pointer
-  template<typename T>
-  T* get_pointer(std::reference_wrapper<T> ref) {
-    return &ref.get();
-  }
-}
-
 namespace gtsam {
 
   /* ************************************************************************* */

gtsam/inference/EliminateableFactorGraph.h

@@ -139,7 +139,7 @@ namespace gtsam {
       OptionalVariableIndex variableIndex = {}) const;
 
     /** Do multifrontal elimination of all variables to produce a Bayes tree.  If an ordering is not
-     *  provided, the ordering will be computed using either COLAMD or METIS, dependeing on
+     *  provided, the ordering will be computed using either COLAMD or METIS, depending on
      *  the parameter orderingType (Ordering::COLAMD or Ordering::METIS)
      *
      *  <b> Example - Full Cholesky elimination in COLAMD order: </b>
@@ -160,7 +160,7 @@ namespace gtsam {
       OptionalVariableIndex variableIndex = {}) const;
 
     /** Do multifrontal elimination of all variables to produce a Bayes tree.  If an ordering is not
-     *  provided, the ordering will be computed using either COLAMD or METIS, dependeing on
+     *  provided, the ordering will be computed using either COLAMD or METIS, depending on
      *  the parameter orderingType (Ordering::COLAMD or Ordering::METIS)
      *
      *  <b> Example - Full QR elimination in specified order:
@@ -273,8 +273,7 @@ namespace gtsam {
      *  COLAMD marginalization order by default
      *  @param variables Determines the *ordered* variables whose marginal to compute, 
      *         will be ordered in the returned BayesNet.
-     *  @param function Optional dense elimination function, if not provided the default will be
+     *  @param function Optional dense elimination function..
-     *         used.
      *  @param variableIndex Optional pre-computed VariableIndex for the factor graph, if not
      *         provided one will be computed. */
     std::shared_ptr<BayesTreeType> marginalMultifrontalBayesTree(
@@ -286,8 +285,7 @@ namespace gtsam {
      *  COLAMD marginalization order by default
      *  @param variables Determines the variables whose marginal to compute, 
      *         will be ordered using constrained COLAMD.
-     *  @param function Optional dense elimination function, if not provided the default will be
+     *  @param function Optional dense elimination function..
-     *         used.
      *  @param variableIndex Optional pre-computed VariableIndex for the factor graph, if not
      *         provided one will be computed. */
     std::shared_ptr<BayesTreeType> marginalMultifrontalBayesTree(
@@ -300,8 +298,7 @@ namespace gtsam {
      *         will be ordered in the returned BayesNet.
      *  @param marginalizedVariableOrdering Ordering for the variables being marginalized out,
      *         i.e. all variables not in \c variables.
-     *  @param function Optional dense elimination function, if not provided the default will be
+     *  @param function Optional dense elimination function..
-     *         used.
      *  @param variableIndex Optional pre-computed VariableIndex for the factor graph, if not
      *         provided one will be computed. */
     std::shared_ptr<BayesTreeType> marginalMultifrontalBayesTree(
@@ -315,8 +312,7 @@ namespace gtsam {
      *         will be ordered using constrained COLAMD.
      *  @param marginalizedVariableOrdering Ordering for the variables being marginalized out,
      *         i.e. all variables not in \c variables.
-     *  @param function Optional dense elimination function, if not provided the default will be
+     *  @param function Optional dense elimination function..
-     *         used.
      *  @param variableIndex Optional pre-computed VariableIndex for the factor graph, if not
      *         provided one will be computed. */
     std::shared_ptr<BayesTreeType> marginalMultifrontalBayesTree(

gtsam/nonlinear/ExtendedKalmanFilter-inl.h

@@ -38,7 +38,7 @@ namespace gtsam {
     Ordering lastKeyAsOrdering;
     lastKeyAsOrdering += lastKey;
     const GaussianConditional::shared_ptr marginal =
-      linearFactorGraph.marginalMultifrontalBayesNet(std::cref(lastKeyAsOrdering))->front();
+      linearFactorGraph.marginalMultifrontalBayesNet(lastKeyAsOrdering)->front();
 
     // Extract the current estimate of x1,P1
     VectorValues result = marginal->solve(VectorValues());