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/**
* @file rrts02-nearestNeighbors.cpp
* @author Can Erdogan
* @date Feb 04, 2013
* @brief Checks if the nearest neighbor computation done by flann is correct.
*/
#include <iostream>
#include <Eigen/Core>
#include <dart/dart.hpp>
#include <gtest/gtest.h>
#if HAVE_FLANN
# include <flann/flann.hpp>
#endif // HAVE_FLANN
#include "TestHelpers.hpp"
/* *********************************************************************************************
*/
#if HAVE_FLANN
TEST(NEAREST_NEIGHBOR, 2D)
{
// Build the index with the first node
flann::Index<flann::L2<double> > index(
flann::KDTreeSingleIndexParams(10, true));
Eigen::VectorXd p1(2);
p1 << -3.04159, -3.04159;
index.buildIndex(flann::Matrix<double>((double*)p1.data(), 1, p1.size()));
// Add two more points
Eigen::Vector2d p2(-2.96751, -2.97443), p3(-2.91946, -2.88672);
index.addPoints(flann::Matrix<double>((double*)p2.data(), 1, p2.size()));
index.addPoints(flann::Matrix<double>((double*)p3.data(), 1, p3.size()));
// Check the size of the tree
EXPECT_EQ(3, (int)index.size());
// Get the nearest neighbor index for a sample point
Eigen::Vector2d sample(-2.26654, 2.2874);
int nearest;
double distance;
const flann::Matrix<double> queryMatrix(
(double*)sample.data(), 1, sample.size());
flann::Matrix<int> nearestMatrix(&nearest, 1, 1);
flann::Matrix<double> distanceMatrix(flann::Matrix<double>(&distance, 1, 1));
index.knnSearch(
queryMatrix,
nearestMatrix,
distanceMatrix,
1,
flann::SearchParams(flann::FLANN_CHECKS_UNLIMITED));
EXPECT_EQ(2, nearest);
// Get the nearest neighbor
double* point = index.getPoint(nearest);
bool equality = equals(Vector2d(point[0], point[1]), p3, 1e-3);
EXPECT_TRUE(equality);
}
#endif // HAVE_FLANN
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