Copied Clément's example for 2 functions

git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/subsampling_and_spatialsearching@1338 636b058d-ea47-450e-bf9e-a15bfbe3eedb

Former-commit-id: 42f29038057980965bfead2c73cbc013448493fb

1 files changed, 50 insertions, 15 deletions

diff --git a/src/Subsampling/test/test_choose_farthest_point.cpp b/src/Subsampling/test/test_choose_farthest_point.cpp
index 87c2c38d..dff2cd4e 100644
--- a/src/Subsampling/test/test_choose_farthest_point.cpp
+++ b/src/Subsampling/test/test_choose_farthest_point.cpp
@@ -24,14 +24,15 @@
 // # define TBB_USE_THREADING_TOOL
 // #endif
 
-#define BOOST_TEST_DYN_LINK
-#define BOOST_TEST_MODULE "witness_complex_points"
-#include <boost/test/unit_test.hpp>
-#include <boost/mpl/list.hpp>
+// #define BOOST_TEST_DYN_LINK
+// #define BOOST_TEST_MODULE "test_choose_farthest_point"
+//#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>
 
@@ -40,18 +41,52 @@ typedef typename K::FT                                            FT;
 typedef typename K::Point_d                                       Point_d;
 
 
-BOOST_AUTO_TEST_CASE(test_choose_farthest_point) {
-  std::vector< Point_d > points, results;
-  // 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)
+//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)
           points.push_back(Point_d(std::vector<FT>({i, j, k, l})));
 
-  results.clear();
-  K k;
-  Gudhi::subsampling::choose_by_farthest_point(k, points, 100, std::back_inserter(results));
+  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, ";
   
-  assert(results.size() == 100);
+  // 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;
+  
+    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);
+    }
+  }
 }