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

2 files changed, 5 insertions, 5 deletions

diff --git a/src/Subsampling/test/test_pick_n_random_points.cpp b/src/Subsampling/test/test_pick_n_random_points.cpp
index 018fb8d2..fafae2af 100644
--- a/src/Subsampling/test/test_pick_n_random_points.cpp
+++ b/src/Subsampling/test/test_pick_n_random_points.cpp
@@ -49,9 +49,9 @@ BOOST_AUTO_TEST_CASE(test_pick_n_random_points)
 
   std::vector<Point_d> results;
   Gudhi::subsampling::pick_n_random_points(vect, 5, std::back_inserter(results));
-  std::cout << "landmark vector contains: ";
+  std::clog << "landmark vector contains: ";
   for (auto l: results)
-    std::cout << l << "\n";
+    std::clog << l << "\n";
   
   BOOST_CHECK(results.size() == 5);
 }
diff --git a/src/Subsampling/test/test_sparsify_point_set.cpp b/src/Subsampling/test/test_sparsify_point_set.cpp
index 587ab3ad..cdcfbff5 100644
--- a/src/Subsampling/test/test_sparsify_point_set.cpp
+++ b/src/Subsampling/test/test_sparsify_point_set.cpp
@@ -34,10 +34,10 @@ BOOST_AUTO_TEST_CASE(test_sparsify_point_set)
   K k;
   std::vector<Point_d> results;
   Gudhi::subsampling::sparsify_point_set(k, points, 0.5, 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";
   //for (auto p : results)
-  //  std::cout << p << "\n";
+  //  std::clog << p << "\n";
 
   BOOST_CHECK(points.size() > results.size());
 }