From d70f6b7be44dc52a333a471b1103476d83a1e256 Mon Sep 17 00:00:00 2001
From: dellaert <dellaert@cc.gatech.edu>
Date: Thu, 13 Feb 2014 20:23:06 -0500
Subject: [PATCH] Formatting and comments only

---
 gtsam/linear/HessianFactor.cpp | 29 ++++++++++++++++-------------
 gtsam/linear/HessianFactor.h   | 25 ++++++++++++++++---------
 2 files changed, 32 insertions(+), 22 deletions(-)

diff --git a/gtsam/linear/HessianFactor.cpp b/gtsam/linear/HessianFactor.cpp
index d8344abe1..17727a2a1 100644
--- a/gtsam/linear/HessianFactor.cpp
+++ b/gtsam/linear/HessianFactor.cpp
@@ -62,41 +62,44 @@ string SlotEntry::toString() const {
 }
 
 /* ************************************************************************* */
-Scatter::Scatter(const GaussianFactorGraph& gfg, boost::optional<const Ordering&> ordering)
-{
+Scatter::Scatter(const GaussianFactorGraph& gfg,
+    boost::optional<const Ordering&> ordering) {
   gttic(Scatter_Constructor);
   static const size_t none = std::numeric_limits<size_t>::max();
 
   // First do the set union.
   BOOST_FOREACH(const GaussianFactor::shared_ptr& factor, gfg) {
-    if(factor) {
-      for(GaussianFactor::const_iterator variable = factor->begin(); variable != factor->end(); ++variable) {
+    if (factor) {
+      for (GaussianFactor::const_iterator variable = factor->begin();
+          variable != factor->end(); ++variable) {
         // TODO: Fix this hack to cope with zero-row Jacobians that come from BayesTreeOrphanWrappers
-        const JacobianFactor* asJacobian = dynamic_cast<const JacobianFactor*>(factor.get());
-        if(!asJacobian || asJacobian->cols() > 1)
-          this->insert(make_pair(*variable, SlotEntry(none, factor->getDim(variable))));
+        const JacobianFactor* asJacobian =
+            dynamic_cast<const JacobianFactor*>(factor.get());
+        if (!asJacobian || asJacobian->cols() > 1)
+          this->insert(
+              make_pair(*variable, SlotEntry(none, factor->getDim(variable))));
       }
     }
   }
 
   // If we have an ordering, pre-fill the ordered variables first
   size_t slot = 0;
-  if(ordering) {
+  if (ordering) {
     BOOST_FOREACH(Key key, *ordering) {
       const_iterator entry = find(key);
-      if(entry == end())
+      if (entry == end())
         throw std::invalid_argument(
             "The ordering provided to the HessianFactor Scatter constructor\n"
-            "contained extra variables that did not appear in the factors to combine.");
-      at(key).slot = (slot ++);
+                "contained extra variables that did not appear in the factors to combine.");
+      at(key).slot = (slot++);
     }
   }
 
   // Next fill in the slot indices (we can only get these after doing the set
   // union.
   BOOST_FOREACH(value_type& var_slot, *this) {
-    if(var_slot.second.slot == none)
-      var_slot.second.slot = (slot ++);
+    if (var_slot.second.slot == none)
+      var_slot.second.slot = (slot++);
   }
 }
 
diff --git a/gtsam/linear/HessianFactor.h b/gtsam/linear/HessianFactor.h
index a3a38e4dc..1d4bc2b01 100644
--- a/gtsam/linear/HessianFactor.h
+++ b/gtsam/linear/HessianFactor.h
@@ -41,21 +41,28 @@ namespace gtsam {
   GTSAM_EXPORT std::pair<boost::shared_ptr<GaussianConditional>, boost::shared_ptr<HessianFactor> >
     EliminateCholesky(const GaussianFactorGraph& factors, const Ordering& keys);
 
-  // Definition of Scatter, which is an intermediate data structure used when building a
-  // HessianFactor incrementally, to get the keys in the right order. The "scatter" is a map from
-  // global variable indices to slot indices in the union of involved variables.  We also include
-  // the dimensionality of the variable.
+  /**
+   * One SlotEntry stores the slot index for a variable, as well its dimension.
+   */
   struct GTSAM_EXPORT SlotEntry {
-    size_t slot;
-    size_t dimension;
+    size_t slot, dimension;
     SlotEntry(size_t _slot, size_t _dimension)
     : slot(_slot), dimension(_dimension) {}
     std::string toString() const;
   };
-  class Scatter : public FastMap<Key, SlotEntry> {
+
+  /**
+   * Scatter is an intermediate data structure used when building a HessianFactor
+   * incrementally, to get the keys in the right order. The "scatter" is a map from
+   * global variable indices to slot indices in the union of involved variables.
+   * We also include the dimensionality of the variable.
+   */
+  class Scatter: public FastMap<Key, SlotEntry> {
   public:
-    Scatter() {}
-    Scatter(const GaussianFactorGraph& gfg, boost::optional<const Ordering&> ordering = boost::none);
+    Scatter() {
+    }
+    Scatter(const GaussianFactorGraph& gfg,
+        boost::optional<const Ordering&> ordering = boost::none);
   };
 
   /**