Add comparison with kdtree for nearest neighbor

Orthtree/benchmark/Orthtree/construction.cpp

@@ -10,7 +10,6 @@
 #include <CGAL/Orthogonal_k_neighbor_search.h>
 
 #include <iostream>
-#include <fstream>
 #include <chrono>
 
 typedef CGAL::Exact_predicates_inexact_constructions_kernel Kernel;

Orthtree/benchmark/Orthtree/nearest_neighbor.cpp

@@ -3,12 +3,13 @@
 
 #include "util.h"
 
-#include <CGAL/Octree.h>
-
 #include <CGAL/Exact_predicates_exact_constructions_kernel.h>
 
+#include <CGAL/Octree.h>
+#include <CGAL/Search_traits_3.h>
+#include <CGAL/Orthogonal_k_neighbor_search.h>
+
 #include <iostream>
-#include <fstream>
 #include <chrono>
 
 typedef CGAL::Exact_predicates_inexact_constructions_kernel Kernel;
@@ -18,21 +19,30 @@ typedef Point_set::Point_map Point_map;
 
 typedef CGAL::Octree<Kernel, Point_set, Point_map> Octree;
 
+typedef CGAL::Search_traits_3<Kernel> Kd_tree_traits;
+typedef CGAL::Orthogonal_k_neighbor_search<Kd_tree_traits> Kd_tree_search;
+typedef Kd_tree_search::Tree Kdtree;
+
 using std::chrono::high_resolution_clock;
 using std::chrono::duration_cast;
 using std::chrono::microseconds;
 
 int main(int argc, char **argv) {
 
+  size_t k = 10;
+
   // Set output file
   std::ofstream file;
   file.open((argc > 1) ? argv[1] : "../nearest_neighbor_benchmark.csv");
 
   // Add header for CSV
-  file << "Number of Points,Search Time (ms) \n";
+  file << "Number of Points,Octree,kDTree \n";
 
   // Perform tests for various dataset sizes
-  for (size_t num_points = 10; num_points < 1000000; num_points *= 1.1) {
+  for (size_t num_points = 100; num_points < 10000000; num_points *= 1.05) {
+
+    file << num_points << ",";
+    std::cout << num_points << std::endl;
 
     // Create a collection of the right number of points
     auto points = generate<Kernel>(num_points);
@@ -40,22 +50,34 @@ int main(int argc, char **argv) {
     // Create a search point
     auto search_point = *generate<Kernel>().points().begin();
 
-    // Build the tree (not timed)
-    Octree octree(points, points.point_map());
-    octree.refine();
+    {
+      // Build the tree (not timed)
+      auto octreePoints = points;
+      Octree octree(octreePoints, octreePoints.point_map());
+      octree.refine();
 
-    auto elapsedTime = bench<microseconds>(
-            [&] {
-              // Find the nearest point to the search point
-              std::vector<Point> nearest_neighbors;
-              octree.nearest_neighbors(search_point, 10, std::back_inserter(nearest_neighbors));
-            }
-    );
+      auto octreeTime = bench<microseconds>(
+              [&] {
+                std::vector<Point> nearest_neighbors;
+                octree.nearest_neighbors(search_point, k, std::back_inserter(nearest_neighbors));
+              }
+      );
+      file << octreeTime.count() << ",";
+    }
 
-    file << num_points << ",";
-    file << elapsedTime.count() << "\n";
+    {
+      auto kdtreePoints = points;
+      Kdtree kdtree(kdtreePoints.points().begin(), kdtreePoints.points().end());
+      kdtree.build();
+
+      auto kdtreeTime = bench<microseconds>(
+              [&] {
+                Kd_tree_search search(kdtree, search_point, k);
+              }
+      );
+      file << kdtreeTime.count() << "\n";
+    }
 
-    std::cout << num_points << std::endl;
   }
 
   file.close();

Orthtree/benchmark/Orthtree/plot_construction_benchmark.p

@@ -10,7 +10,7 @@ set style data lines
 
 set title 'Time to construct a tree from points'
 set xlabel "Number of points"
-set ylabel "Time (ms)"
+set ylabel "Time (us)"
 set key autotitle columnhead
 
 set datafile separator ","

Orthtree/benchmark/Orthtree/plot_nearest_neighbor_benchmark.p

@@ -0,0 +1,17 @@
+
+reset
+
+set terminal png size 800,500
+set output 'nearest_neighbor_benchmark.png'
+
+set grid
+set style data lines
+#set logscale x
+
+set title 'Time to find the neighbors of a point using a tree'
+set xlabel "Number of points"
+set ylabel "Time (us)"
+set key autotitle columnhead
+
+set datafile separator ","
+plot for [col=2:3] 'nearest_neighbor_benchmark.csv' using 1:col