data_association_unittest.cpp

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/* +------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)            |
   |                          http://www.mrpt.org/                          |
   |                                                                        |
   | Copyright (c) 2005-2017, Individual contributors, see AUTHORS file     |
   | See: http://www.mrpt.org/Authors - All rights reserved.                |
   | Released under BSD License. See details in http://www.mrpt.org/License |
   +------------------------------------------------------------------------+ */

#include <mrpt/slam/data_association.h>
#include <gtest/gtest.h>

using namespace mrpt;
using namespace mrpt::slam;
using namespace mrpt::utils;
using namespace mrpt::math;
using namespace std;

TEST(DataAssociation, TestNoICs)
{
        // Try to do DA when no individual compatible pairings exist.
        // Based on test proposed by Mauricio Soto Alvarez:
        // See:
        // https://sourceforge.net/tracker/?func=detail&aid=3562885&group_id=205280&atid=993006

        CMatrixDouble y, y_cov, z;
        y.setSize(1, 1);
        y_cov.setSize(1, 1);
        z.setSize(1, 1);

        y(0, 0) = 0.0;
        y_cov(0, 0) = 1.0;
        z(0, 0) = 10.0;

        const TDataAssociationMethod dams[2] = {assocNN, assocJCBB};
        const TDataAssociationMetric damets[2] = {metricMaha, metricML};

        for (unsigned int da_metric = 0;
                 da_metric < sizeof(damets) / sizeof(damets[0]); ++da_metric)
        {
                const TDataAssociationMetric damet = damets[da_metric];

                for (unsigned int da_method = 0;
                         da_method < sizeof(dams) / sizeof(dams[0]); ++da_method)
                {
                        const TDataAssociationMethod dam = dams[da_method];

                        TDataAssociationResults DAresults;
                        data_association_independent_predictions(
                                z, y, y_cov, DAresults, dam, damet, 0.99, true,
                                std::vector<prediction_index_t>(), metricMaha, 0.0);

                        EXPECT_EQ(0u, DAresults.associations.size())
                                << "For da_method=" << da_method
                                << " and da_metric=" << da_metric << endl;
                }
        }
}