bdf86b0ea4
Vendor ikd-Tree directly instead of as a git submodule so cloning duru_lio_ws needs no --recursive/submodule-init step.
286 lines
11 KiB
C++
286 lines
11 KiB
C++
/*
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Description: An example for using ikd-Tree
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Author: Yixi Cai
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Email: yixicai@connect.hku.hk
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*/
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#include <ikd_Tree.h>
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#include <stdio.h>
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#include <stdlib.h>
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#include <random>
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#include <algorithm>
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using PointType = ikdTree_PointType;
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using PointVector = KD_TREE<PointType>::PointVector;
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#define X_MAX 5.0
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#define X_MIN -5.0
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#define Y_MAX 5.0
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#define Y_MIN -5.0
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#define Z_MAX 5.0
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#define Z_MIN -5.0
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#define Point_Num 20000
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#define New_Point_Num 200
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#define Delete_Point_Num 100
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#define Nearest_Num 5
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#define Test_Time 1000
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#define Search_Counter 200
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#define Box_Length 1.5
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#define Box_Num 4
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#define Delete_Box_Switch true
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#define Add_Box_Switch true
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PointVector point_cloud;
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PointVector cloud_increment;
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PointVector cloud_decrement;
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PointVector cloud_deleted;
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PointVector search_result;
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PointVector raw_cmp_result;
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PointVector DeletePoints;
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PointVector removed_points;
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KD_TREE<ikdTree_PointType> ikd_Tree(0.3,0.6,0.2);
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float rand_float(float x_min, float x_max){
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float rand_ratio = rand()/(float)RAND_MAX;
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return (x_min + rand_ratio * (x_max - x_min));
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}
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/*
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Generate the points to initialize an incremental k-d tree
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*/
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void generate_initial_point_cloud(int num){
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PointVector ().swap(point_cloud);
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PointType new_point;
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for (int i=0;i<num;i++){
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new_point.x = rand_float(X_MIN, X_MAX);
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new_point.y = rand_float(Y_MIN, Y_MAX);
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new_point.z = rand_float(Z_MIN, Z_MAX);
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point_cloud.push_back(new_point);
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}
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return;
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}
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/*
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Generate random new points for point-wise insertion to the incremental k-d tree
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*/
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void generate_increment_point_cloud(int num){
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PointVector ().swap(cloud_increment);
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PointType new_point;
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for (int i=0;i<num;i++){
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new_point.x = rand_float(X_MIN, X_MAX);
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new_point.y = rand_float(Y_MIN, Y_MAX);
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new_point.z = rand_float(Z_MIN, Z_MAX);
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point_cloud.push_back(new_point);
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cloud_increment.push_back(new_point);
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}
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return;
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}
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/*
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Generate random points for point-wise delete on the incremental k-d tree
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*/
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void generate_decrement_point_cloud(int num){
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PointVector ().swap(cloud_decrement);
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auto rng = default_random_engine();
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shuffle(point_cloud.begin(), point_cloud.end(), rng);
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for (int i=0;i<num;i++){
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cloud_decrement.push_back(point_cloud[point_cloud.size()-1]);
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point_cloud.pop_back();
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}
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return;
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}
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/*
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Generate random boxes for box-wise re-insertion on the incremental k-d tree
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*/
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void generate_box_increment(vector<BoxPointType> & Add_Boxes, float box_length, int box_num){
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vector<BoxPointType> ().swap(Add_Boxes);
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float d = box_length/2;
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float x_p, y_p, z_p;
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BoxPointType boxpoint;
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for (int k=0;k < box_num; k++){
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x_p = rand_float(X_MIN, X_MAX);
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y_p = rand_float(Y_MIN, Y_MAX);
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z_p = rand_float(Z_MIN, Z_MAX);
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boxpoint.vertex_min[0] = x_p - d;
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boxpoint.vertex_max[0] = x_p + d;
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boxpoint.vertex_min[1] = y_p - d;
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boxpoint.vertex_max[1] = y_p + d;
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boxpoint.vertex_min[2] = z_p - d;
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boxpoint.vertex_max[2] = z_p + d;
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Add_Boxes.push_back(boxpoint);
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int n = cloud_deleted.size();
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int counter = 0;
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while (counter < n){
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PointType tmp = cloud_deleted[cloud_deleted.size()-1];
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cloud_deleted.pop_back();
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if (tmp.x +EPSS < boxpoint.vertex_min[0] || tmp.x - EPSS > boxpoint.vertex_max[0] || tmp.y + EPSS < boxpoint.vertex_min[1] || tmp.y - EPSS > boxpoint.vertex_max[1] || tmp.z + EPSS < boxpoint.vertex_min[2] || tmp.z - EPSS > boxpoint.vertex_max[2]){
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cloud_deleted.insert(cloud_deleted.begin(),tmp);
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} else {
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point_cloud.push_back(tmp);
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}
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counter += 1;
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}
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}
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}
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/*
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Generate random boxes for box-wise delete on the incremental k-d tree
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*/
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void generate_box_decrement(vector<BoxPointType> & Delete_Boxes, float box_length, int box_num){
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vector<BoxPointType> ().swap(Delete_Boxes);
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float d = box_length/2;
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float x_p, y_p, z_p;
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BoxPointType boxpoint;
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for (int k=0;k < box_num; k++){
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x_p = rand_float(X_MIN, X_MAX);
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y_p = rand_float(Y_MIN, Y_MAX);
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z_p = rand_float(Z_MIN, Z_MAX);
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boxpoint.vertex_min[0] = x_p - d;
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boxpoint.vertex_max[0] = x_p + d;
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boxpoint.vertex_min[1] = y_p - d;
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boxpoint.vertex_max[1] = y_p + d;
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boxpoint.vertex_min[2] = z_p - d;
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boxpoint.vertex_max[2] = z_p + d;
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Delete_Boxes.push_back(boxpoint);
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int n = point_cloud.size();
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int counter = 0;
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while (counter < n){
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PointType tmp = point_cloud[point_cloud.size()-1];
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point_cloud.pop_back();
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if (tmp.x +EPSS < boxpoint.vertex_min[0] || tmp.x - EPSS > boxpoint.vertex_max[0] || tmp.y + EPSS < boxpoint.vertex_min[1] || tmp.y - EPSS > boxpoint.vertex_max[1] || tmp.z + EPSS < boxpoint.vertex_min[2] || tmp.z - EPSS > boxpoint.vertex_max[2]){
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point_cloud.insert(point_cloud.begin(),tmp);
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} else {
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cloud_deleted.push_back(tmp);
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}
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counter += 1;
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}
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}
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}
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/*
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Generate target point for nearest search on the incremental k-d tree
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*/
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PointType generate_target_point(){
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PointType point;
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point.x = rand_float(X_MIN, X_MAX);;
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point.y = rand_float(Y_MIN, Y_MAX);
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point.z = rand_float(Z_MIN, Z_MAX);
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return point;
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}
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int main(int argc, char** argv){
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srand((unsigned) time(NULL));
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printf("Testing ...\n");
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int counter = 0;
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bool flag = true;
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vector<BoxPointType> Delete_Boxes;
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vector<BoxPointType> Add_Boxes;
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vector<float> PointDist;
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float average_total_time = 0.0;
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float box_delete_time = 0.0;
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float box_add_time = 0.0;
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float add_time = 0.0;
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float delete_time = 0.0;
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float search_time = 0.0;
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int box_delete_counter = 0;
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int box_add_counter = 0;
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PointType target;
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// Initialize k-d tree
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generate_initial_point_cloud(Point_Num);
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auto t1 = chrono::high_resolution_clock::now();
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ikd_Tree.Build(point_cloud);
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auto t2 = chrono::high_resolution_clock::now();
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auto build_duration = chrono::duration_cast<chrono::microseconds>(t2-t1).count();
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while (counter < Test_Time){
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printf("Test %d:\n",counter+1);
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// Point-wise Insertion
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generate_increment_point_cloud(New_Point_Num);
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t1 = chrono::high_resolution_clock::now();
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ikd_Tree.Add_Points(cloud_increment, false);
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t2 = chrono::high_resolution_clock::now();
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auto add_duration = chrono::duration_cast<chrono::microseconds>(t2-t1).count();
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auto total_duration = add_duration;
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printf("Add point time cost is %0.3f ms\n",float(add_duration)/1e3);
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// Point-wise Delete
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generate_decrement_point_cloud(Delete_Point_Num);
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t1 = chrono::high_resolution_clock::now();
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ikd_Tree.Delete_Points(cloud_decrement);
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t2 = chrono::high_resolution_clock::now();
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auto delete_duration = chrono::duration_cast<chrono::microseconds>(t2-t1).count();
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total_duration += delete_duration;
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printf("Delete point time cost is %0.3f ms\n",float(delete_duration)/1e3);
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// Box-wise Delete
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auto box_delete_duration = chrono::duration_cast<chrono::microseconds>(t2-t2).count();
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if (Delete_Box_Switch && (counter+1) % 500 == 0){
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printf("Waiting to generate 4 cuboids for box-wise delete test...\n");
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generate_box_decrement(Delete_Boxes, Box_Length, Box_Num);
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t1 = chrono::high_resolution_clock::now();
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ikd_Tree.Delete_Point_Boxes(Delete_Boxes);
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t2 = chrono::high_resolution_clock::now();
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box_delete_counter ++;
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box_delete_duration += chrono::duration_cast<chrono::microseconds>(t2-t1).count();
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printf("Delete box points time cost is %0.3f ms\n",float(box_delete_duration)/1e3);
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}
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total_duration += box_delete_duration;
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// Box-wise Re-insertion
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auto box_add_duration = chrono::duration_cast<chrono::microseconds>(t2-t2).count();
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if (Add_Box_Switch && (counter+1) % 100 == 0){
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generate_box_increment(Add_Boxes, Box_Length, Box_Num);
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t1 = chrono::high_resolution_clock::now();
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ikd_Tree.Add_Point_Boxes(Add_Boxes);
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t2 = chrono::high_resolution_clock::now();
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box_add_counter ++;
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box_add_duration += chrono::duration_cast<chrono::microseconds>(t2-t1).count();
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printf("Add box points time cost is %0.3f ms\n",float(box_add_duration)/1e3);
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}
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total_duration += box_add_duration;
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// Nearest Search
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auto search_duration = chrono::duration_cast<chrono::microseconds>(t2-t2).count();
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for (int k=0;k<Search_Counter;k++){
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PointVector ().swap(search_result);
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target = generate_target_point();
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t1 = chrono::high_resolution_clock::now();
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ikd_Tree.Nearest_Search(target, Nearest_Num, search_result, PointDist);
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t2 = chrono::high_resolution_clock::now();
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search_duration += chrono::duration_cast<chrono::microseconds>(t2-t1).count();
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}
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printf("Search nearest point time cost is %0.3f ms\n",float(search_duration)/1e3);
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total_duration += search_duration;
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printf("Total time is %0.3f ms\n",total_duration/1e3);
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printf("Tree size is: %d\n\n", ikd_Tree.size());
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// If necessary, the removed points can be collected.
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PointVector ().swap(removed_points);
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ikd_Tree.acquire_removed_points(removed_points);
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// Calculate total running time
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average_total_time += float(total_duration)/1e3;
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box_delete_time += float(box_delete_duration)/1e3;
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box_add_time += float(box_add_duration)/1e3;
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add_time += float(add_duration)/1e3;
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delete_time += float(delete_duration)/1e3;
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search_time += float(search_duration)/1e3;
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counter += 1;
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}
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printf("Finished %d times test\n",counter);
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printf("Average Time:\n");
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printf("Total Time is: %0.3fms\n",average_total_time/1e3);
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printf("Point-wise Insertion (%d points): %0.3fms\n",New_Point_Num,add_time/counter);
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printf("Point-wise Delete (%d points): %0.3fms\n", Delete_Point_Num,delete_time/counter);
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printf("Box-wse Delete (%d boxes): %0.3fms\n",Box_Num,box_delete_time/box_delete_counter);
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printf("Box-wse Re-insertion (%d boxes): %0.3fms\n",Box_Num,box_add_time/box_add_counter);
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printf("Nearest Search (%d points): %0.3fms\n", Search_Counter,search_time/counter);
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return 0;
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} |