prefer auto in range for loops

gtsam.h

@@ -220,9 +220,9 @@ class FactorIndexSet {
   void clear();
 
   // structure specific methods
-  void insert(size_t factorIdx);
-  bool erase(size_t factorIdx); // returns true if value was removed
-  bool count(size_t factorIdx) const; // returns true if value exists
+  void insert(size_t factorIndex);
+  bool erase(size_t factorIndex); // returns true if value was removed
+  bool count(size_t factorIndex) const; // returns true if value exists
 };
 
 // Actually a vector<FactorIndex>
@@ -239,7 +239,7 @@ class FactorIndices {
   size_t at(size_t i) const;
   size_t front() const;
   size_t back() const;
-  void push_back(size_t factorIdx) const;
+  void push_back(size_t factorIndex) const;
 };
 //*************************************************************************
 // base

gtsam/inference/VariableIndex.cpp

@@ -35,8 +35,8 @@ void VariableIndex::print(const string& str, const KeyFormatter& keyFormatter) c
   cout << "nEntries = " << nEntries() << ", nFactors = " << nFactors() << "\n";
   for(KeyMap::value_type key_factors: index_) {
     cout << "var " << keyFormatter(key_factors.first) << ":";
-    for(const FactorIndex factor: key_factors.second)
-      cout << " " << factor;
+    for(const auto index: key_factors.second)
+      cout << " " << index;
     cout << "\n";
   }
   cout.flush();
@@ -48,8 +48,8 @@ void VariableIndex::outputMetisFormat(ostream& os) const {
   // run over variables, which will be hyper-edges.
   for(KeyMap::value_type key_factors: index_) {
     // every variable is a hyper-edge covering its factors
-    for(const FactorIndex factor: key_factors.second)
-      os << (factor+1) << " "; // base 1
+    for(const auto index: key_factors.second)
+      os << (index+1) << " "; // base 1
     os << "\n";
   }
   os << flush;

gtsam/nonlinear/ISAM2.cpp

@@ -113,7 +113,7 @@ FactorIndexSet ISAM2::getAffectedFactors(const KeyList& keys) const {
   }
   if (debug) cout << "Affected factors are: ";
   if (debug) {
-    for (const FactorIndex index : indices) {
+    for (const auto index : indices) {
       cout << index << " ";
     }
   }
@@ -586,7 +586,7 @@ ISAM2Result ISAM2::update(
   // Remove the removed factors
   NonlinearFactorGraph removeFactors;
   removeFactors.reserve(removeFactorIndices.size());
-  for (FactorIndex index : removeFactorIndices) {
+  for (const auto index : removeFactorIndices) {
     removeFactors.push_back(nonlinearFactors_[index]);
     nonlinearFactors_.remove(index);
     if (params_.cacheLinearizedFactors) linearFactors_.remove(index);
@@ -934,8 +934,8 @@ void ISAM2::marginalizeLeaves(
           }
         }
         // Create factor graph from factor indices
-        for (FactorIndex i : factorsFromMarginalizedInClique_step1) {
-          graph.push_back(nonlinearFactors_[i]->linearize(theta_));
+        for (const auto index: factorsFromMarginalizedInClique_step1) {
+          graph.push_back(nonlinearFactors_[index]->linearize(theta_));
         }
 
         // Reeliminate the linear graph to get the marginal and discard the
@@ -1008,10 +1008,10 @@ void ISAM2::marginalizeLeaves(
   // Remove the factors to remove that have been summarized in the newly-added
   // marginal factors
   NonlinearFactorGraph removedFactors;
-  for (FactorIndex i : factorIndicesToRemove) {
-    removedFactors.push_back(nonlinearFactors_[i]);
-    nonlinearFactors_.remove(i);
-    if (params_.cacheLinearizedFactors) linearFactors_.remove(i);
+  for (const auto index: factorIndicesToRemove) {
+    removedFactors.push_back(nonlinearFactors_[index]);
+    nonlinearFactors_.remove(index);
+    if (params_.cacheLinearizedFactors) linearFactors_.remove(index);
   }
   variableIndex_.remove(factorIndicesToRemove.begin(),
                         factorIndicesToRemove.end(), removedFactors);

gtsam_unstable/discrete/tests/testLoopyBelief.cpp

@@ -175,19 +175,19 @@ private:
 
       // collect all factors involving this key in the original graph
       DiscreteFactorGraph::shared_ptr star(new DiscreteFactorGraph());
-      for(size_t factorIdx: varIndex[key]) {
-        star->push_back(graph.at(factorIdx));
+      for(size_t factorIndex: varIndex[key]) {
+        star->push_back(graph.at(factorIndex));
 
         // accumulate unary factors
-        if (graph.at(factorIdx)->size() == 1) {
+        if (graph.at(factorIndex)->size() == 1) {
           if (!prodOfUnaries)
             prodOfUnaries = boost::dynamic_pointer_cast<DecisionTreeFactor>(
-                graph.at(factorIdx));
+                graph.at(factorIndex));
           else
             prodOfUnaries = boost::make_shared<DecisionTreeFactor>(
                 *prodOfUnaries
                     * (*boost::dynamic_pointer_cast<DecisionTreeFactor>(
-                        graph.at(factorIdx))));
+                        graph.at(factorIndex))));
         }
       }