Fix cpplint and warnings

git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/trunk@1902 636b058d-ea47-450e-bf9e-a15bfbe3eedb

Former-commit-id: 24c5aacf579eb1ceb35c680770d5168524c4c84b

2 files changed, 16 insertions, 24 deletions

diff --git a/src/Subsampling/example/example_custom_kernel.cpp b/src/Subsampling/example/example_custom_kernel.cpp
index 05797ebe..f87ef0b3 100644
--- a/src/Subsampling/example/example_custom_kernel.cpp
+++ b/src/Subsampling/example/example_custom_kernel.cpp
@@ -7,7 +7,7 @@
 #include <iterator>
 
 
-/* The class Kernel contains a distance function defined on the set of points {0,1,2,3}
+/* The class Kernel contains a distance function defined on the set of points {0, 1, 2, 3}
  * and computes a distance according to the matrix:
  * 0 1 2 4
  * 1 0 4 2
@@ -15,41 +15,35 @@
  * 4 2 1 0
  */
 class Kernel {
-public:
+ public:
   typedef double FT;
   typedef unsigned Point_d;
 
   // Class Squared_distance_d
   class Squared_distance_d {
-  private:
+   private:
     std::vector<std::vector<FT>> matrix_;
-    
-  public:
 
-  Squared_distance_d()
-  {
-    matrix_.push_back(std::vector<FT>({0,1,2,4}));
-    matrix_.push_back(std::vector<FT>({1,0,4,2}));
-    matrix_.push_back(std::vector<FT>({2,4,0,1}));
-    matrix_.push_back(std::vector<FT>({4,2,1,0}));
-  }
-  
-    FT operator()(Point_d p1, Point_d p2)
-    {
+   public:
+    Squared_distance_d() {
+      matrix_.push_back(std::vector<FT>({0,1,2,4}));
+      matrix_.push_back(std::vector<FT>({1,0,4,2}));
+      matrix_.push_back(std::vector<FT>({2,4,0,1}));
+      matrix_.push_back(std::vector<FT>({4,2,1,0}));
+    }
+
+    FT operator()(Point_d p1, Point_d p2) {
       return matrix_[p1][p2];
     }
   };
 
   // Constructor
-  Kernel()
-  {}
+  Kernel() {}
 
   // Object of type Squared_distance_d
-  Squared_distance_d squared_distance_d_object() const
-  {
+  Squared_distance_d squared_distance_d_object() const {
     return Squared_distance_d();
   }
-  
 };
 
 int main(void) {
@@ -57,9 +51,9 @@ int main(void) {
   typedef typename K::Point_d Point_d;
 
   K k;
-  std::vector<Point_d> points = {0,1,2,3};
+  std::vector<Point_d> points = {0, 1, 2, 3};
   std::vector<Point_d> results;
-  
+
   Gudhi::subsampling::choose_n_farthest_points(k, points, 2, std::back_inserter(results));
   std::cout << "Before sparsification: " << points.size() << " points.\n";
   std::cout << "After  sparsification: " << results.size() << " points.\n";
diff --git a/src/Subsampling/include/gudhi/sparsify_point_set.h b/src/Subsampling/include/gudhi/sparsify_point_set.h
index 7ff11b4c..507f8c79 100644
--- a/src/Subsampling/include/gudhi/sparsify_point_set.h
+++ b/src/Subsampling/include/gudhi/sparsify_point_set.h
@@ -64,8 +64,6 @@ sparsify_point_set(
   typedef typename Gudhi::spatial_searching::Kd_tree_search<
       Kernel, Point_range> Points_ds;
 
-  typename Kernel::Squared_distance_d sqdist = k.squared_distance_d_object();
-
 #ifdef GUDHI_SUBSAMPLING_PROFILING
   Gudhi::Clock t;
 #endif