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// ----------------------------------------------------------------------------
// - Open3D: www.open3d.org -
// ----------------------------------------------------------------------------
// Copyright (c) 2018-2024 www.open3d.org
// SPDX-License-Identifier: MIT
// ----------------------------------------------------------------------------
#include "open3d/geometry/KDTreeFlann.h"
#include "open3d/geometry/PointCloud.h"
#include "open3d/geometry/TriangleMesh.h"
#include "tests/Tests.h"
namespace open3d {
namespace tests {
TEST(KDTreeFlann, DISABLED_Search) { NotImplemented(); }
TEST(KDTreeFlann, SearchKNN) {
std::vector<int> ref_indices = {27, 48, 4, 77, 90, 7, 54, 17, 76, 38,
39, 60, 15, 84, 11, 57, 3, 32, 99, 36,
52, 40, 26, 59, 22, 97, 20, 42, 73, 24};
std::vector<double> ref_distance2 = {
0.000000, 4.684353, 4.996539, 9.191849, 10.034604, 10.466745,
10.649751, 11.434066, 12.089195, 13.345638, 13.696270, 14.016148,
16.851978, 17.073435, 18.254518, 20.019994, 21.496347, 23.077277,
23.692427, 23.809303, 24.104578, 25.005770, 26.952710, 27.487888,
27.998463, 28.262975, 28.581313, 28.816608, 31.603230, 31.610916};
int size = 100;
geometry::PointCloud pc;
Eigen::Vector3d vmin(0.0, 0.0, 0.0);
Eigen::Vector3d vmax(10.0, 10.0, 10.0);
pc.points_.resize(size);
Rand(pc.points_, vmin, vmax, 0);
geometry::KDTreeFlann kdtree(pc);
Eigen::Vector3d query = {1.647059, 4.392157, 8.784314};
int knn = 30;
std::vector<int> indices;
std::vector<double> distance2;
int result = kdtree.SearchKNN(query, knn, indices, distance2);
EXPECT_EQ(result, 30);
ExpectEQ(ref_indices, indices);
ExpectEQ(ref_distance2, distance2);
}
TEST(KDTreeFlann, SearchRadius) {
std::vector<int> ref_indices = {27, 48, 4, 77, 90, 7, 54, 17, 76, 38, 39,
60, 15, 84, 11, 57, 3, 32, 99, 36, 52};
std::vector<double> ref_distance2 = {
0.000000, 4.684353, 4.996539, 9.191849, 10.034604, 10.466745,
10.649751, 11.434066, 12.089195, 13.345638, 13.696270, 14.016148,
16.851978, 17.073435, 18.254518, 20.019994, 21.496347, 23.077277,
23.692427, 23.809303, 24.104578};
int size = 100;
geometry::PointCloud pc;
Eigen::Vector3d vmin(0.0, 0.0, 0.0);
Eigen::Vector3d vmax(10.0, 10.0, 10.0);
pc.points_.resize(size);
Rand(pc.points_, vmin, vmax, 0);
geometry::KDTreeFlann kdtree(pc);
Eigen::Vector3d query = {1.647059, 4.392157, 8.784314};
double radius = 5.0;
std::vector<int> indices;
std::vector<double> distance2;
int result = kdtree.SearchRadius<Eigen::Vector3d>(query, radius, indices,
distance2);
EXPECT_EQ(result, 21);
ExpectEQ(ref_indices, indices);
ExpectEQ(ref_distance2, distance2);
}
TEST(KDTreeFlann, SearchHybrid) {
std::vector<int> ref_indices = {27, 48, 4, 77, 90, 7, 54, 17,
76, 38, 39, 60, 15, 84, 11};
std::vector<double> ref_distance2 = {
0.000000, 4.684353, 4.996539, 9.191849, 10.034604,
10.466745, 10.649751, 11.434066, 12.089195, 13.345638,
13.696270, 14.016148, 16.851978, 17.073435, 18.254518};
int size = 100;
geometry::PointCloud pc;
Eigen::Vector3d vmin(0.0, 0.0, 0.0);
Eigen::Vector3d vmax(10.0, 10.0, 10.0);
pc.points_.resize(size);
Rand(pc.points_, vmin, vmax, 0);
geometry::KDTreeFlann kdtree(pc);
Eigen::Vector3d query = {1.647059, 4.392157, 8.784314};
int max_nn = 15;
double radius = 5.0;
std::vector<int> indices;
std::vector<double> distance2;
int result = kdtree.SearchHybrid<Eigen::Vector3d>(query, radius, max_nn,
indices, distance2);
EXPECT_EQ(result, 15);
ExpectEQ(ref_indices, indices);
ExpectEQ(ref_distance2, distance2);
}
} // namespace tests
} // namespace open3d
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