Code review: Use std::clog instead of std::cout

4 files changed, 9 insertions, 9 deletions

diff --git a/src/Subsampling/example/example_choose_n_farthest_points.cpp b/src/Subsampling/example/example_choose_n_farthest_points.cpp
index 5cfeb4d8..27cf5d4e 100644
--- a/src/Subsampling/example/example_choose_n_farthest_points.cpp
+++ b/src/Subsampling/example/example_choose_n_farthest_points.cpp
@@ -23,8 +23,8 @@ int main(void) {
   Gudhi::subsampling::choose_n_farthest_points(k, points, 100,
                                                Gudhi::subsampling::random_starting_point,
                                                std::back_inserter(results));
-  std::cout << "Before sparsification: " << points.size() << " points.\n";
-  std::cout << "After  sparsification: " << results.size() << " points.\n";
+  std::clog << "Before sparsification: " << points.size() << " points.\n";
+  std::clog << "After  sparsification: " << results.size() << " points.\n";
 
   return 0;
 }
diff --git a/src/Subsampling/example/example_custom_kernel.cpp b/src/Subsampling/example/example_custom_kernel.cpp
index f1eb757b..535bf42a 100644
--- a/src/Subsampling/example/example_custom_kernel.cpp
+++ b/src/Subsampling/example/example_custom_kernel.cpp
@@ -55,9 +55,9 @@ int main(void) {
   Gudhi::subsampling::choose_n_farthest_points(k, points, 2,
                                                Gudhi::subsampling::random_starting_point,
                                                std::back_inserter(results));
-  std::cout << "Before sparsification: " << points.size() << " points.\n";
-  std::cout << "After  sparsification: " << results.size() << " points.\n";
-  std::cout << "Result table: {" << results[0] << "," << results[1] << "}\n";
+  std::clog << "Before sparsification: " << points.size() << " points.\n";
+  std::clog << "After  sparsification: " << results.size() << " points.\n";
+  std::clog << "Result table: {" << results[0] << "," << results[1] << "}\n";
 
   return 0;
 }
diff --git a/src/Subsampling/example/example_pick_n_random_points.cpp b/src/Subsampling/example/example_pick_n_random_points.cpp
index 25266403..316feed1 100644
--- a/src/Subsampling/example/example_pick_n_random_points.cpp
+++ b/src/Subsampling/example/example_pick_n_random_points.cpp
@@ -21,8 +21,8 @@ int main(void) {
   K k;
   std::vector<Point_d> results;
   Gudhi::subsampling::pick_n_random_points(points, 100, std::back_inserter(results));
-  std::cout << "Before sparsification: " << points.size() << " points.\n";
-  std::cout << "After  sparsification: " << results.size() << " points.\n";
+  std::clog << "Before sparsification: " << points.size() << " points.\n";
+  std::clog << "After  sparsification: " << results.size() << " points.\n";
 
   return 0;
 }
diff --git a/src/Subsampling/example/example_sparsify_point_set.cpp b/src/Subsampling/example/example_sparsify_point_set.cpp
index a8caa720..1e2c38c1 100644
--- a/src/Subsampling/example/example_sparsify_point_set.cpp
+++ b/src/Subsampling/example/example_sparsify_point_set.cpp
@@ -21,8 +21,8 @@ int main(void) {
   K k;
   std::vector<Point_d> results;
   Gudhi::subsampling::sparsify_point_set(k, points, 0.4, std::back_inserter(results));
-  std::cout << "Before sparsification: " << points.size() << " points.\n";
-  std::cout << "After  sparsification: " << results.size() << " points.\n";
+  std::clog << "Before sparsification: " << points.size() << " points.\n";
+  std::clog << "After  sparsification: " << results.size() << " points.\n";
 
   return 0;
 }