Removed headers in the examples

git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/subsampling_and_spatialsearching@1339 636b058d-ea47-450e-bf9e-a15bfbe3eedb

Former-commit-id: 835003033dc15ce8fd2d8efdc7bfdf3e0be7760d

1 files changed, 15 insertions, 50 deletions

diff --git a/src/Subsampling/test/test_choose_farthest_point.cpp b/src/Subsampling/test/test_choose_farthest_point.cpp
index dff2cd4e..5f705de6 100644
--- a/src/Subsampling/test/test_choose_farthest_point.cpp
+++ b/src/Subsampling/test/test_choose_farthest_point.cpp
@@ -24,15 +24,14 @@
 // # define TBB_USE_THREADING_TOOL
 // #endif
 
-// #define BOOST_TEST_DYN_LINK
-// #define BOOST_TEST_MODULE "test_choose_farthest_point"
-//#include <boost/test/unit_test.hpp>
-//#include <boost/mpl/list.hpp>
+#define BOOST_TEST_DYN_LINK
+#define BOOST_TEST_MODULE "witness_complex_points"
+#include <boost/test/unit_test.hpp>
+#include <boost/mpl/list.hpp>
 
 #include <gudhi/choose_by_farthest_point.h>
 #include <vector>
 #include <iterator>
-#include <gudhi/Clock.h>
 
 #include <CGAL/Epick_d.h>
 
@@ -41,52 +40,18 @@ typedef typename K::FT                                            FT;
 typedef typename K::Point_d                                       Point_d;
 
 
-//BOOST_AUTO_TEST_CASE(test_choose_farthest_point)
-int main() {
-  std::vector< Point_d > points, results, results2;
-  K k;
-  Clock t;
-  // Add grid points (810000 points)
-  for (FT i = 0; i < 30; i += 1.0)
-    for (FT j = 0; j < 30; j += 1.0)
-      for (FT k = 0; k < 30; k += 1.0)
-        for (FT l = 0; l < 30; l += 1.0)
+BOOST_AUTO_TEST_CASE(test_choose_farthest_point) {
+  std::vector< Point_d > points, landmarks;
+  // Add grid points (625 points)
+  for (FT i = 0; i < 5; i += 1.0)
+    for (FT j = 0; j < 5; j += 1.0)
+      for (FT k = 0; k < 5; k += 1.0)
+        for (FT l = 0; l < 5; l += 1.0)
           points.push_back(Point_d(std::vector<FT>({i, j, k, l})));
 
-  unsigned final_size = 100, numeral = 1;
-  std::cout << "Test   New     Old\n";
-  while (final_size < 100001) {
-    std::cout << final_size << ": ";
-    results.clear();
-    t.begin();
-    Gudhi::subsampling::choose_by_farthest_point(k, points, final_size, 0, std::back_inserter(results));
-    t.end();
-    std::cout << t.num_seconds()  << " s, ";
-  
-  // std::cout << "New algorithm result:\n";
-  // for (auto p: results)
-  //   std::cout << p << std::endl;
-  
-    results2.clear();
-    t.begin();
-    Gudhi::subsampling::choose_by_farthest_point_old(k, points, final_size, 0, std::back_inserter(results2));
-    t.end();
-    std::cout << t.num_seconds()  << " s" << std::endl;
-
-  
-  // std::cout << "Old algorithm result:\n";
-  // for (auto p: results2)
-  //   std::cout << p << std::endl;
+  landmarks.clear();
+  K k;
+  Gudhi::subsampling::choose_by_farthest_point(k, points, 100, std::back_inserter(landmarks));
   
-    assert(results.size() == final_size);
-    assert(results2.size() == final_size);
-    assert(results == results2);
-
-    switch (numeral) {
-    case 1: numeral = 2; final_size *= 2; break;
-    case 2: numeral = 5; final_size = final_size/2*5; break;
-    case 5: numeral = 1; final_size *= 2; break;
-    default: assert(false);
-    }
-  }
+  assert(landmarks.size() == 100);
 }