[mlpack-git] master: Fix compiler warnings (ee2a8a1)

[gitdub at mlpack.org]

Repository : https://github.com/mlpack/mlpack
On branch  : master
Link       : https://github.com/mlpack/mlpack/compare/e434aee1eab9e3ced97cccd840dd383ef8089acf...81c14d9ec8250f8a2caaf1ac06c4be12fc5fd31f

>---------------------------------------------------------------

commit ee2a8a1461a33edd830747dccde117ac2cfb12b7
Author: Mikhail Lozhnikov <lozhnikovma at gmail.com>
Date:   Tue Jul 12 15:46:39 2016 +0300

    Fix compiler warnings


>---------------------------------------------------------------

ee2a8a1461a33edd830747dccde117ac2cfb12b7
 .../core/tree/rectangle_tree/r_plus_tree_split_impl.hpp       | 11 +++++++----
 src/mlpack/methods/adaboost/adaboost_impl.hpp                 |  2 +-
 src/mlpack/methods/ann/layer/one_hot_layer.hpp                |  2 +-
 src/mlpack/methods/ann/layer/vr_class_reward_layer.hpp        |  2 +-
 src/mlpack/methods/perceptron/perceptron_impl.hpp             |  2 +-
 src/mlpack/methods/radical/radical.cpp                        |  2 +-
 6 files changed, 12 insertions(+), 9 deletions(-)

diff --git a/src/mlpack/core/tree/rectangle_tree/r_plus_tree_split_impl.hpp b/src/mlpack/core/tree/rectangle_tree/r_plus_tree_split_impl.hpp
index 8dfc2f2..67025d5 100644
--- a/src/mlpack/core/tree/rectangle_tree/r_plus_tree_split_impl.hpp
+++ b/src/mlpack/core/tree/rectangle_tree/r_plus_tree_split_impl.hpp
@@ -22,6 +22,8 @@ template<typename TreeType>
 void RPlusTreeSplit<SplitPolicyType, SweepType>::
 SplitLeafNode(TreeType* tree, std::vector<bool>& relevels)
 {
+  typedef typename TreeType::ElemType ElemType;
+
   if (tree->Count() == 1)
   {
     // Check if an intermediate node was added during the insertion process.
@@ -64,8 +66,8 @@ SplitLeafNode(TreeType* tree, std::vector<bool>& relevels)
     return;
   }
 
-  size_t cutAxis;
-  typename TreeType::ElemType cut;
+  size_t cutAxis = tree->Bound().Dim();
+  ElemType cut = std::numeric_limits<ElemType>::lowest();
 
   // Try to find a partiotion of the node.
   if (!PartitionNode(tree, cutAxis, cut))
@@ -117,6 +119,7 @@ template<typename TreeType>
 bool RPlusTreeSplit<SplitPolicyType, SweepType>::
 SplitNonLeafNode(TreeType* tree, std::vector<bool>& relevels)
 {
+  typedef typename TreeType::ElemType ElemType;
   // If we are splitting the root node, we need will do things differently so
   // that the constructor and other methods don't confuse the end user by giving
   // an address of another node.
@@ -133,8 +136,8 @@ SplitNonLeafNode(TreeType* tree, std::vector<bool>& relevels)
     RPlusTreeSplit::SplitNonLeafNode(copy,relevels);
     return true;
   }
-  size_t cutAxis;
-  typename TreeType::ElemType cut;
+  size_t cutAxis = tree->Bound().Dim();
+  ElemType cut = std::numeric_limits<ElemType>::lowest();
 
   // Try to find a partiotion of the node.
   if ( !PartitionNode(tree, cutAxis, cut))
diff --git a/src/mlpack/methods/adaboost/adaboost_impl.hpp b/src/mlpack/methods/adaboost/adaboost_impl.hpp
index a692a32..55d77f2 100644
--- a/src/mlpack/methods/adaboost/adaboost_impl.hpp
+++ b/src/mlpack/methods/adaboost/adaboost_impl.hpp
@@ -208,7 +208,7 @@ void AdaBoost<WeakLearnerType, MatType>::Classify(
   }
 
   arma::colvec cMRow;
-  arma::uword maxIndex;
+  arma::uword maxIndex = 0;
 
   for (size_t i = 0; i < predictedLabels.n_cols; i++)
   {
diff --git a/src/mlpack/methods/ann/layer/one_hot_layer.hpp b/src/mlpack/methods/ann/layer/one_hot_layer.hpp
index 99a52da..671696e 100644
--- a/src/mlpack/methods/ann/layer/one_hot_layer.hpp
+++ b/src/mlpack/methods/ann/layer/one_hot_layer.hpp
@@ -58,7 +58,7 @@ class OneHotLayer
     output = inputActivations;
     output.zeros();
 
-    arma::uword maxIndex;
+    arma::uword maxIndex = 0;
     inputActivations.max(maxIndex);
     output(maxIndex) = 1;
   }
diff --git a/src/mlpack/methods/ann/layer/vr_class_reward_layer.hpp b/src/mlpack/methods/ann/layer/vr_class_reward_layer.hpp
index 95692f0..aec0b85 100644
--- a/src/mlpack/methods/ann/layer/vr_class_reward_layer.hpp
+++ b/src/mlpack/methods/ann/layer/vr_class_reward_layer.hpp
@@ -71,7 +71,7 @@ class VRClassRewardLayer
   double Forward(const arma::Mat<eT>& input, const arma::Mat<eT>& target)
   {
     reward = 0;
-    arma::uword index;
+    arma::uword index = 0;
 
     for (size_t i = 0; i < input.n_cols; i++)
     {
diff --git a/src/mlpack/methods/perceptron/perceptron_impl.hpp b/src/mlpack/methods/perceptron/perceptron_impl.hpp
index 68c5f51..2e2948f 100644
--- a/src/mlpack/methods/perceptron/perceptron_impl.hpp
+++ b/src/mlpack/methods/perceptron/perceptron_impl.hpp
@@ -108,7 +108,7 @@ void Perceptron<LearnPolicy, WeightInitializationPolicy, MatType>::Classify(
     arma::Row<size_t>& predictedLabels)
 {
   arma::vec tempLabelMat;
-  arma::uword maxIndex;
+  arma::uword maxIndex = 0;
 
   // Could probably be faster if done in batch.
   for (size_t i = 0; i < test.n_cols; i++)
diff --git a/src/mlpack/methods/radical/radical.cpp b/src/mlpack/methods/radical/radical.cpp
index 18ec45f..816e8e6 100644
--- a/src/mlpack/methods/radical/radical.cpp
+++ b/src/mlpack/methods/radical/radical.cpp
@@ -85,7 +85,7 @@ double Radical::DoRadical2D(const mat& matX)
     values(i) = Vasicek(candidateY1) + Vasicek(candidateY2);
   }
 
-  uword indOpt;
+  uword indOpt = 0;
   values.min(indOpt); // we ignore the return value; we don't care about it
   return (indOpt / (double) angles) * M_PI / 2.0;
 }