Spatial_tree_data_structure => Kd_tree_search

git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/subsampling_and_spatialsearching@1538 636b058d-ea47-450e-bf9e-a15bfbe3eedb

Former-commit-id: 095b038d0e4c1c6d78e9aa9efe73447b65dab2b1

1 files changed, 118 insertions, 0 deletions

diff --git a/src/Spatial_searching/test/test_Kd_tree_search.cpp b/src/Spatial_searching/test/test_Kd_tree_search.cpp
new file mode 100644
index 00000000..6f99b288
--- /dev/null
+++ b/src/Spatial_searching/test/test_Kd_tree_search.cpp
@@ -0,0 +1,118 @@
+/*    This file is part of the Gudhi Library. The Gudhi library
+ *    (Geometric Understanding in Higher Dimensions) is a generic C++
+ *    library for computational topology.
+ *
+ *    Author(s):       Clement Jamin
+ *
+ *    Copyright (C) 2016  INRIA Sophia-Antipolis (France)
+ *
+ *    This program is free software: you can redistribute it and/or modify
+ *    it under the terms of the GNU General Public License as published by
+ *    the Free Software Foundation, either version 3 of the License, or
+ *    (at your option) any later version.
+ *
+ *    This program is distributed in the hope that it will be useful,
+ *    but WITHOUT ANY WARRANTY; without even the implied warranty of
+ *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ *    GNU General Public License for more details.
+ *
+ *    You should have received a copy of the GNU General Public License
+ *    along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+
+#define BOOST_TEST_DYN_LINK
+#define BOOST_TEST_MODULE Spatial_searching - test Kd_tree_search
+#include <boost/test/unit_test.hpp>
+
+#include <gudhi/Kd_tree_search.h>
+
+#include <CGAL/Epick_d.h>
+#include <CGAL/Random.h>
+
+#include <array>
+#include <vector>
+
+BOOST_AUTO_TEST_CASE(test_Kd_tree_search)
+{
+  typedef CGAL::Epick_d<CGAL::Dimension_tag<4> >    K;
+  typedef K::FT                                     FT;
+  typedef K::Point_d                                Point;
+  typedef std::vector<Point>                        Points;
+
+  typedef Gudhi::spatial_searching::Kd_tree_search<
+    K, Points>                                      Points_ds;
+  
+  CGAL::Random rd;
+
+  Points points;
+  for (int i = 0 ; i < 500 ; ++i)
+    points.push_back(Point(rd.get_double(-1.,1), rd.get_double(-1.,1), rd.get_double(-1.,1), rd.get_double(-1.,1)));
+
+  Points_ds points_ds(points);
+
+  // Test query_k_nearest_neighbors
+  std::size_t closest_pt_index =
+    points_ds.query_k_nearest_neighbors(points[10], 1, false).begin()->first;
+  BOOST_CHECK(closest_pt_index == 10);
+
+  auto kns_range = points_ds.query_k_nearest_neighbors(points[20], 10, true);
+
+  std::vector<std::size_t> knn_result;
+  FT last_dist = -1.;
+  for (auto const& nghb : kns_range)
+  {
+    BOOST_CHECK(nghb.second > last_dist);
+    knn_result.push_back(nghb.second);
+    last_dist = nghb.second;
+  }
+
+  // Test query_incremental_nearest_neighbors 
+  closest_pt_index =
+    points_ds.query_incremental_nearest_neighbors(points[10]).begin()->first;
+  BOOST_CHECK(closest_pt_index == 10);
+
+  auto ins_range = points_ds.query_incremental_nearest_neighbors(points[20]);
+
+  std::vector<std::size_t> inn_result;
+  last_dist = -1.;
+  auto ins_it = ins_range.begin();
+  for (int i = 0 ; i < 10 ; ++ins_it, ++i)
+  {
+    auto const& nghb = *ins_it;
+    BOOST_CHECK(nghb.second > last_dist);
+    inn_result.push_back(nghb.second);
+    last_dist = nghb.second;
+  }
+
+  // Same result for KNN and INN?
+  BOOST_CHECK(knn_result == inn_result);
+
+  // Test query_k_farthest_neighbors
+  auto kfs_range = points_ds.query_k_farthest_neighbors(points[20], 10, true);
+
+  std::vector<std::size_t> kfn_result;
+  last_dist = kfs_range.begin()->second;
+  for (auto const& nghb : kfs_range)
+  {
+    BOOST_CHECK(nghb.second <= last_dist);
+    kfn_result.push_back(nghb.second);
+    last_dist = nghb.second;
+  }
+
+  // Test query_k_farthest_neighbors
+  auto ifs_range = points_ds.query_incremental_farthest_neighbors(points[20]);
+
+  std::vector<std::size_t> ifn_result;
+  last_dist = ifs_range.begin()->second;
+  auto ifs_it = ifs_range.begin();
+  for (int i = 0; i < 10; ++ifs_it, ++i)
+  {
+    auto const& nghb = *ifs_it;
+    BOOST_CHECK(nghb.second <= last_dist);
+    ifn_result.push_back(nghb.second);
+    last_dist = nghb.second;
+  }
+
+  // Same result for KFN and IFN?
+  BOOST_CHECK(kfn_result == ifn_result);
+}