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 * Software License Agreement (BSD License)
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 * Copyright 2008-2009  Marius Muja (mariusm@cs.ubc.ca). All rights reserved.
 * Copyright 2008-2009  David G. Lowe (lowe@cs.ubc.ca). All rights reserved.
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#ifndef TESTING_H
#define TESTING_H

#include <cstring>
#include <cassert>
#include <cmath>

#include "flann/general.h"
#include "flann/util/matrix.h"
#include "flann/algorithms/nn_index.h"
#include "flann/util/result_set.h"
#include "flann/util/logger.h"
#include "flann/util/timer.h"


namespace flann
{

FLANN_EXPORT int countCorrectMatches(int* neighbors, int* groundTruth, int n);


template <typename Distance>
typename Distance::ResultType computeDistanceRaport(const Matrix<typename Distance::ElementType>& inputData, typename Distance::ElementType* target,
		int* neighbors, int* groundTruth, int veclen, int n, const Distance& distance)
{
	typedef typename Distance::ResultType DistanceType;

	DistanceType ret = 0;
    for (int i=0;i<n;++i) {
    	DistanceType den = distance(inputData[groundTruth[i]], target, veclen);
    	DistanceType num = distance(inputData[neighbors[i]], target, veclen);

        if (den==0 && num==0) {
            ret += 1;
        }
        else {
            ret += num/den;
        }
    }

    return ret;
}

template <typename Distance>
float search_with_ground_truth(NNIndex<Distance>& index, const Matrix<typename Distance::ElementType>& inputData,
		const Matrix<typename Distance::ElementType>& testData, const Matrix<int>& matches, int nn, int checks,
		float& time, typename Distance::ResultType& dist, const Distance& distance, int skipMatches)
{
	typedef typename Distance::ResultType DistanceType;

    if (matches.cols<size_t(nn)) {
        logger.info("matches.cols=%d, nn=%d\n",matches.cols,nn);

        throw FLANNException("Ground truth is not computed for as many neighbors as requested");
    }

    KNNResultSet<DistanceType> resultSet(nn+skipMatches);
    SearchParams searchParams(checks);

    int* indices = new int[nn+skipMatches];
    DistanceType* dists = new DistanceType[nn+skipMatches];
    int* neighbors = indices + skipMatches;

    int correct;
    DistanceType distR;
    StartStopTimer t;
    int repeats = 0;
    while (t.value<0.2) {
        repeats++;
        t.start();
        correct = 0;
        distR = 0;
        for (size_t i = 0; i < testData.rows; i++) {
            resultSet.init(indices, dists);
            index.findNeighbors(resultSet, testData[i], searchParams);

            correct += countCorrectMatches(neighbors,matches[i], nn);
            distR += computeDistanceRaport<Distance>(inputData, testData[i], neighbors, matches[i], testData.cols, nn, distance);
        }
        t.stop();
    }
    time = t.value/repeats;

    delete[] indices;
    delete[] dists;

    float precicion = (float)correct/(nn*testData.rows);

    dist = distR/(testData.rows*nn);

    logger.info("%8d %10.4g %10.5g %10.5g %10.5g\n",
            checks, precicion, time, 1000.0 * time / testData.rows, dist);

    return precicion;
}


template <typename Distance>
float test_index_checks(NNIndex<Distance>& index, const Matrix<typename Distance::ElementType>& inputData,
		const Matrix<typename Distance::ElementType>& testData, const Matrix<int>& matches,
            int checks, float& precision, const Distance& distance, int nn = 1, int skipMatches = 0)
{
	typedef typename Distance::ResultType DistanceType;

    logger.info("  Nodes  Precision(%)   Time(s)   Time/vec(ms)  Mean dist\n");
    logger.info("---------------------------------------------------------\n");

    float time = 0;
    DistanceType dist = 0;
    precision = search_with_ground_truth(index, inputData, testData, matches, nn, checks, time, dist, distance, skipMatches);

    return time;
}

template <typename Distance>
float test_index_precision(NNIndex<Distance>& index, const Matrix<typename Distance::ElementType>& inputData,
		const Matrix<typename Distance::ElementType>& testData, const Matrix<int>& matches,
             float precision, int& checks, const Distance& distance, int nn = 1, int skipMatches = 0)
{
	typedef typename Distance::ResultType DistanceType;
	const float SEARCH_EPS = 0.001;

    logger.info("  Nodes  Precision(%)   Time(s)   Time/vec(ms)  Mean dist\n");
    logger.info("---------------------------------------------------------\n");

    int c2 = 1;
    float p2;
    int c1 = 1;
    float p1;
    float time;
    DistanceType dist;

    p2 = search_with_ground_truth(index, inputData, testData, matches, nn, c2, time, dist, distance, skipMatches);

    if (p2>precision) {
        logger.info("Got as close as I can\n");
        checks = c2;
        return time;
    }

    while (p2<precision) {
        c1 = c2;
        p1 = p2;
        c2 *=2;
        p2 = search_with_ground_truth(index, inputData, testData, matches, nn, c2, time, dist, distance, skipMatches);
    }

    int cx;
    float realPrecision;
    if (fabs(p2-precision)>SEARCH_EPS) {
        logger.info("Start linear estimation\n");
        // after we got to values in the vecinity of the desired precision
        // use linear approximation get a better estimation

        cx = (c1+c2)/2;
        realPrecision = search_with_ground_truth(index, inputData, testData, matches, nn, cx, time, dist, distance, skipMatches);
        while (fabs(realPrecision-precision)>SEARCH_EPS) {

            if (realPrecision<precision) {
                c1 = cx;
            }
            else {
                c2 = cx;
            }
            cx = (c1+c2)/2;
            if (cx==c1) {
                logger.info("Got as close as I can\n");
                break;
            }
            realPrecision = search_with_ground_truth(index, inputData, testData, matches, nn, cx, time, dist, distance, skipMatches);
        }

        c2 = cx;
        p2 = realPrecision;

    } else {
        logger.info("No need for linear estimation\n");
        cx = c2;
        realPrecision = p2;
    }

    checks = cx;
    return time;
}


template <typename Distance>
void test_index_precisions(NNIndex<Distance>& index, const Matrix<typename Distance::ElementType>& inputData,
		const Matrix<typename Distance::ElementType>& testData, const Matrix<int>& matches,
                    float* precisions, int precisions_length, const Distance& distance, int nn = 1, int skipMatches = 0, float maxTime = 0)
{
	typedef typename Distance::ResultType DistanceType;

	const float SEARCH_EPS = 0.001;

    // make sure precisions array is sorted
    std::sort(precisions, precisions+precisions_length);

    int pindex = 0;
    float precision = precisions[pindex];

    logger.info("  Nodes  Precision(%)   Time(s)   Time/vec(ms)  Mean dist\n");
    logger.info("---------------------------------------------------------\n");

    int c2 = 1;
    float p2;

    int c1 = 1;
    float p1;

    float time;
    DistanceType dist;

    p2 = search_with_ground_truth(index, inputData, testData, matches, nn, c2, time, dist, distance, skipMatches);

    // if precision for 1 run down the tree is already
    // better then some of the requested precisions, then
    // skip those
    while (precisions[pindex]<p2 && pindex<precisions_length) {
        pindex++;
    }

    if (pindex==precisions_length) {
        logger.info("Got as close as I can\n");
        return;
    }

    for (int i=pindex;i<precisions_length;++i) {

        precision = precisions[i];
        while (p2<precision) {
            c1 = c2;
            p1 = p2;
            c2 *=2;
            p2 = search_with_ground_truth(index, inputData, testData, matches, nn, c2, time, dist, distance, skipMatches);
            if (maxTime> 0 && time > maxTime && p2<precision) return;
        }

        int cx;
        float realPrecision;
        if (fabs(p2-precision)>SEARCH_EPS) {
            logger.info("Start linear estimation\n");
            // after we got to values in the vecinity of the desired precision
            // use linear approximation get a better estimation

            cx = (c1+c2)/2;
            realPrecision = search_with_ground_truth(index, inputData, testData, matches, nn, cx, time, dist, distance, skipMatches);
            while (fabs(realPrecision-precision)>SEARCH_EPS) {

                if (realPrecision<precision) {
                    c1 = cx;
                }
                else {
                    c2 = cx;
                }
                cx = (c1+c2)/2;
                if (cx==c1) {
                    logger.info("Got as close as I can\n");
                    break;
                }
                realPrecision = search_with_ground_truth(index, inputData, testData, matches, nn, cx, time, dist, distance, skipMatches);
            }

            c2 = cx;
            p2 = realPrecision;

        } else {
            logger.info("No need for linear estimation\n");
            cx = c2;
            realPrecision = p2;
        }

    }
}

}

#endif //TESTING_H