Merge remote-tracking branch 'origin/master' into ribdashboard

2026-10-16 09:11:02 +00:00 · 2015-01-29 10:43:22 +01:00
commit 5bbb80891e
@@ -200,7 +200,7 @@ if [[ "$@" == "release" ]]; then
    RELEASE_NOTES=""
    COMMIT_WEEK_COUNT=4
-	if [ $suppress_confirmation -eq 0 ]; then
+    if [ $suppress_confirmation -eq 0 ]; then
        echo ""
        echo "Please provide me with some notes about this release. You can add more than"
        echo "one line. Please include major changes or new features. After your notes I will"
@@ -357,7 +357,7 @@ if [[ "$@" == "local-deploy" ]]; then
        echo "WARNING: Bundle versions do not differ. Update not needed."
    fi
-	if [ $suppress_confirmation -eq 0 ]; then
+    if [ $suppress_confirmation -eq 0 ]; then
        read -s -n1 -p "Do you really want to locally deploy bundle $OSGI_BUNDLE_NAME to $TARGET_DIR? (y/N): " answer
        case $answer in
        "Y" | "y") echo "Continuing";;
@@ -420,7 +420,7 @@ if [[ "$@" == "hot-deploy" ]]; then
        echo "WARNING: Bundle versions do not differ. Update not needed."
    fi
-	if [ $suppress_confirmation -eq 0 ]; then
+    if [ $suppress_confirmation -eq 0 ]; then
        read -s -n1 -p "Do you really want to hot-deploy bundle $OSGI_BUNDLE_NAME to $SERVERS_HOME/$active_branch? (y/N): " answer
        case $answer in
        "Y" | "y") echo "Continuing";;
@@ -571,13 +571,13 @@ if [[ "$@" == "build" ]] || [[ "$@" == "all" ]]; then
    # back to root!
    cd $PROJECT_HOME
-	if [ $testing -eq 0 ]; then
+    if [ $testing -eq 0 ]; then
 	    echo "INFO: Skipping tests"
 	    extra="$extra -Dmaven.test.skip=true -DskipTests=true"
    else
        extra="$extra -DskipTests=false"
        # TODO: Think about http://maven.apache.org/surefire/maven-surefire-plugin/examples/fork-options-and-parallel-execution.html
-	fi
+    fi
    if [ $android -eq 0 ] && [ $gwtcompile -eq 0 ] && [ $testing -eq 0 ]; then
        parallelexecution=1
@@ -602,8 +602,6 @@ if [[ "$@" == "build" ]] || [[ "$@" == "all" ]]; then
        TRACKING_APP_VERSION=`grep "android:versionCode=" mobile/com.sap.$PROJECT_TYPE.android.tracking.app/AndroidManifest.xml | cut -d "\"" -f 2`
        echo "TRACKING_APP_VERSION=$TRACKING_APP_VERSION"
        extra="$extra -Dtracking-app-version=$TRACKING_APP_VERSION"
    else
        echo "INFO: Deactivating mobile modules"
        extra="$extra -P !with-mobile"
@@ -653,7 +651,7 @@ fi
 if [[ "$@" == "install" ]] || [[ "$@" == "all" ]]; then
-	if [ $suppress_confirmation -eq 0 ]; then
+    if [ $suppress_confirmation -eq 0 ]; then
        read -s -n1 -p "Currently branch $active_branch is active and I will deploy to $ACDIR. Do you want to proceed with $@ (y/N): " answer
        case $answer in
        "Y" | "y") echo "Continuing";;
@@ -777,7 +775,7 @@ if [[ "$@" == "remote-deploy" ]]; then
    REMOTE_HOME=`ssh $REMOTE_SERVER_LOGIN 'echo $HOME/servers'`
    REMOTE_SERVER="$REMOTE_HOME/$SERVER"
-	if [ $suppress_confirmation -eq 0 ]; then
+    if [ $suppress_confirmation -eq 0 ]; then
        read -s -n1 -p "I will deploy the current GIT branch to $REMOTE_SERVER_LOGIN:$REMOTE_SERVER. Is this correct (y/n)? " answer
        case $answer in
        "Y" | "y") OK=1;;
@@ -829,7 +827,7 @@ if [[ "$@" == "remote-deploy" ]]; then
    echo "Deployed successfully. I did NOT change any configuration (no env.sh or config.ini or jetty.xml adaption), only code!"
-	if [ $suppress_confirmation -eq 0 ]; then
+    if [ $suppress_confirmation -eq 0 ]; then
        read -s -n1 -p "Do you want me to restart the remote server (y/n)? " answer
        case $answer in
        "Y" | "y") OK=1;;
@@ -17,14 +17,12 @@ import com.sap.sse.common.TimePoint;
 public class TracTracStartTimeUpdateHandler extends UpdateHandler implements StartTimeChangedListener {
    private static final String ACTION = "update_race_start_time";
    private final TracTracStartTimeResetHandler resetHandler;
    private final static Logger logger = Logger.getLogger(TracTracStartTimeUpdateHandler.class.getName());
    private final static String FIELD_RACE_START_TIME = "race_start_time";
    public TracTracStartTimeUpdateHandler(URI updateURI, String tracTracUsername, String tracTracPassword, Serializable tracTracEventId, Serializable raceId) {
        super(updateURI, ACTION, tracTracUsername, tracTracPassword, tracTracEventId, raceId);
        resetHandler = new TracTracStartTimeResetHandler(updateURI, tracTracUsername, tracTracPassword, tracTracEventId, raceId);
    }
    @Override
@@ -34,8 +32,20 @@ public class TracTracStartTimeUpdateHandler extends UpdateHandler implements Sta
        }
        if (newStartTime == null) {
-            // reset start time with TracTrac
+            /*
-            resetHandler.startTimeChanged(null);
+             * Do not reset start time based on request by Jorge from TracTrac:
             * 
             * """
             * We have detected that when you want to update the race start time your
             * system sends before a message to reset the race start time. When your
             * system invokes the first service our system changes the race start time
             * to null and this value causes some secondary effects in our side.
             * 
             * Can you just send the update_race_start_time without the
             * reset_race_start_time? The reset_race_start_time service has to be used
             * if you want to set the value to null.
             * """
             */
        } else {
            HashMap<String, String> additionalParameters = new HashMap<String, String>();
            additionalParameters.put(FIELD_RACE_START_TIME, String.valueOf(newStartTime.asMillis()));
@@ -674,7 +674,7 @@ public class RaceMap extends AbsolutePanel implements TimeListener, CompetitorSe
                                    WindTrackInfoDTO windTrackInfoDTO = windInfo.windTrackInfoByWindSource.get(windSource);
                                    switch (windSource.getType()) {
                                        case EXPEDITION:
-                                            // we filter out measured wind sources with a very little confidence
+                                            // we filter out measured wind sources with vary low confidence
                                            if (windTrackInfoDTO.minWindConfidence > 0.0001) {
                                                windSourcesToShow.add(new com.sap.sse.common.Util.Pair<WindSource, WindTrackInfoDTO>(windSource, windTrackInfoDTO));
                                            }
@@ -82,7 +82,7 @@ public class TestWindEstimationFromManeuversOnAFew505Races extends OnlineTracTra
            CreateModelException, NotEnoughDataHasBeenAddedException {
        setUp("OBMR 2012", "event_20121031_OBMR-OBMR_2012_VR_Fr_Fleet_1_2");
        Wind average = getManeuverBasedAverageWind();
-        assertEquals(222, average.getFrom().getDegrees(), 5.0); // wind in this race was from 075deg on average
+        assertEquals(222, average.getFrom().getDegrees(), 5.0);
    }
    @Test
@@ -91,7 +91,7 @@ public class TestWindEstimationFromManeuversOnAFew505Races extends OnlineTracTra
            CreateModelException, NotEnoughDataHasBeenAddedException {
        setUp("event_20110609_KielerWoch-505_Race_2");
        Wind average = getManeuverBasedAverageWind();
-        assertEquals(235, average.getFrom().getDegrees(), 5.0); // wind in this race was from 075deg on average
+        assertEquals(235, average.getFrom().getDegrees(), 5.0);
    }
    @Test
@@ -100,7 +100,7 @@ public class TestWindEstimationFromManeuversOnAFew505Races extends OnlineTracTra
            CreateModelException, NotEnoughDataHasBeenAddedException {
        setUp("event_20110609_KielerWoch-505_Race_3");
        Wind average = getManeuverBasedAverageWind();
-        assertEquals(245, average.getFrom().getDegrees(), 5.0); // wind in this race was from 075deg on average
+        assertEquals(245, average.getFrom().getDegrees(), 5.0);
    }
    @Test
@@ -109,7 +109,7 @@ public class TestWindEstimationFromManeuversOnAFew505Races extends OnlineTracTra
            CreateModelException, NotEnoughDataHasBeenAddedException {
        setUp("event_20110609_KielerWoch-505_race_4");
        Wind average = getManeuverBasedAverageWind();
-        assertEquals(275, average.getFrom().getDegrees(), 5.0); // wind in this race was from 075deg on average
+        assertEquals(270, average.getFrom().getDegrees(), 5.0);
    }
    @Test
@@ -139,8 +139,11 @@ public class TestWindEstimationFromManeuversOnAFew505Races extends OnlineTracTra
                .sorted((c1, c2) -> (int) -Math.signum(getAverageLikelihood(c1, ManeuverType.TACK)
                        - getAverageLikelihood(c2, ManeuverType.TACK))).collect(Collectors.toList());
        // expecting a wind direction that is from around 245deg, +/- 10deg
-        assertEquals(245., windTrack.getWeightedAverageMiddleManeuverCOGDeg(clustersSortedByAverageTackLikelihood.get(0), ManeuverType.TACK).getDegrees(), 10.);
+        assertEquals(
-        assertEquals(245., windTrack.getWeightedAverageMiddleManeuverCOGDeg(clustersSortedByAverageTackLikelihood.get(1), ManeuverType.TACK).getDegrees(), 10.);
+                245., windTrack.getWeightedAverageMiddleManeuverCOGDegAndManeuverAngleDeg(
                                clustersSortedByAverageTackLikelihood.get(0), ManeuverType.TACK).getA().getDegrees(), 10.);
        assertEquals(245., windTrack.getWeightedAverageMiddleManeuverCOGDegAndManeuverAngleDeg(
                                clustersSortedByAverageTackLikelihood.get(1), ManeuverType.TACK).getA().getDegrees(), 10.);
    }
    private double getAverageLikelihood(
@@ -70,26 +70,59 @@ public class ManeuverBasedWindEstimationTrackImpl extends WindTrackImpl {
     * for another cluster to be a cluster's opposite tack cluster is determined by first computing the
     * {@link #getClusterDistanceBasedOnAverageManeuverLikelihoodAndWeightedAverageMiddleCOG(Cluster, double, Bearing) angular
     * distance}. For each so many degrees of distance as specified by this constant, the likelihood of the cluster to be the
-     * opposite tack cluster is halved.
+     * opposite tack cluster is halved. This constant can also be used to assign likelihoods for other cluster types
     * based on their distance from an expected configuration of maneuver angle and middle COG.
     */
    private static final double ANGULAR_DISTANCE_FOR_HALF_CONFIDENCE_FOR_OPPOSITE_TACK_CLUSTER_DEG = 20.;
    /**
     * When one or two jibe clusters have been found whose
     * {@link #getLikelihoodOfBeingJibeCluster(Speed, Stream, BoatClass, Set) likelihood of being a jibe cluster} is 100%,
     * this is the boost factor by which the base likelihood for the tack cluster candidate will be increased (up to a
     * maximum of 1.0).
     */
    private static final double BOOST_FACTOR_FOR_FULL_JIBE_CLUSTER_LIKELIHOOD = 0.2;
    /**
     * When one or two head-up / bear-away clusters on the two tacks adjacent to the middle upwind COG have been found
     * whose {@link #getLikelihoodOfClusterBasedOnDistanceFromExpected(double, Bearing, Cluster) likelihood of being
     * such a cluster} is 100%, this is the boost factor by which the base likelihood for the tack cluster candidate
     * will be increased (up to a maximum of 1.0).
     */
    private static final double BOOST_FACTOR_FOR_FULL_HEAD_UP_BEAR_AWAY_CLUSTER_LIKELIHOOD = 0.1;
    /**
     * When looking for the head-up/bear-away clusters, which average maneuver angle should be expected? This is a bit
     * fuzzy because in some cases the head-up and bear-away maneuvers may be grouped into one cluster, resulting in an
     * average maneuver angle that is close to zero whereas in other cases they may form two clusters, one with positive
     * and the other with negative maneuver angles of somewhere between 10-20deg, typically.
     */
    private static final double EXPECTED_AVERAGE_HEAD_UP_AND_BEAR_AWAY_MANEUVER_ANGLE_DEG = 10.;
    /**
     * We're trying to find the jibe cluster based on a candidate for the tack cluster. This constant tells how many degrees
     * the jibe cluster may be off from the reversed tack cluster's centroid in order to be accepted as jibe cluster candidate.
     */
    private static final double THRESHOLD_JIBE_CLUSTER_DIFFERENCE_DEGREES = 20;
    /**
     * For judging the likelihood of a cluster being a speed cluster, the speed ratio of the tack cluster candidate and
     * the jibe cluster candidate is computed and compared to what the polar service predicts. The basic likelihood of the
     * jibe cluster candidate (based on the maneuver angles relative to their speeds) is boosted by this factor for a perfect
     * speed ratio match.
     */
    private static final double BOOST_FACTOR_FOR_JIBE_TACK_SPEED_RATIO_LIKELIHOOD = 0;
    private final PolarDataService polarService;
    private final TrackedRace trackedRace;
    /**
-     * Caches the {@link #getWeightedAverageMiddleManeuverCOGDeg(Cluster, ManeuverType)} results because these values are required several times to
+     * Caches the {@link #getWeightedAverageMiddleManeuverCOGDegAndManeuverAngleDeg(Cluster, ManeuverType)} results because these values are required several times to
     * determine the likelihood with which a cluster is a cluster of tacks or a cluster of jibes. Note that the un-weighted averages can simply be obtained
     * by asking the cluster for its {@link Cluster#getCentroid() centroid}.
     */
-    private final Map<Pair<Cluster<ManeuverClassification, Pair<ScalableBearing, ScalableDouble>, Pair<Bearing, Double>, ScalableBearingAndScalableDouble>, ManeuverType>, Bearing>
+    private final Map<Pair<Cluster<ManeuverClassification, Pair<ScalableBearing, ScalableDouble>, Pair<Bearing, Double>, ScalableBearingAndScalableDouble>, ManeuverType>, Pair<Bearing, Double>>
        weightedAverageMiddleCOGForManeuverType;
    /**
@@ -308,17 +341,16 @@ public class ManeuverBasedWindEstimationTrackImpl extends WindTrackImpl {
     * There are usually no other maneuvers with similar middle COG because boats can't sail straight against the wind.
     * <p>
     * 
-     * We evaluate each cluster's likelihood of being the tack cluster by for each of its maneuvers adding up the
+     * We evaluate each cluster's likelihood of being the tack cluster by computing the average across all its maneuvers
-     * likelihood of that maneuver being a tack, solely based on its maneuver angle, as judged by the polar service. If
+     * for that maneuver being a tack, solely based on its speed and maneuver angle, as
-     * a cluster exists that has approximately the opposite average middle COG (the jibe cluster candidate), the
+     * {@link PolarDataService#getManeuverLikelihoodAndTwsTwa(BoatClass, Speed, double, ManeuverType) judged by the
-     * likelihoods for its maneuvers being a jibe are added. (TODO adding is statistically not adequate here; however,
+     * polar service}. If a cluster exists that has approximately the opposite average middle COG (the jibe cluster
-     * multiplying hundreds if not thousands of probability values would easily lead to a double value going to 0.0
+     * candidate), the {@link #getLikelihoodOfBeingJibeCluster(Speed, Stream, BoatClass, Set) likelihood for its maneuvers
-     * quickly. But is adding adequate to estimate the cluster having the maximum likelihood of being the tack cluster?
+     * being jibes} are determined and may result in a "boost" for the basic probability of up to 20%. Finally, the
-     * We'd only need a monotonous function.) Finally, the resulting likelihood is multiplied by how likely the speed
+     * resulting likelihood is multiplied by how likely the speed ratio between the tack and jibe cluster candidates is,
-     * ratio between the tack and jibe cluster candidates is, based on the polar diagram. For this task, the cluster's
+     * based on the polar diagram. For this task, the cluster's maneuvers' average speed (weighted by each maneuver's
-     * maneuvers' average speed (weighted by each maneuver's likelihood of being a tack) is divided by that of the jibe
+     * likelihood of being a tack) is divided by that of the jibe cluster's maneuvers' average speed (weighted by each
-     * cluster's maneuvers' average speed (weighted by each maneuver's likelihood of being a jibe) and assigned a
+     * maneuver's likelihood of being a jibe) and assigned a likelihood by the polar service.
     * likelihood by the polar service.
     * <p>
     * 
     * The cluster that has the highest likelihood of being the tack cluster is selected. The confidence of the choice
@@ -361,21 +393,22 @@ public class ManeuverBasedWindEstimationTrackImpl extends WindTrackImpl {
        final Map<Cluster<ManeuverClassification, Pair<ScalableBearing, ScalableDouble>, Pair<Bearing, Double>, ScalableBearingAndScalableDouble>, Double>
            likelihoodOfBeingTackCluster = new HashMap<>();
        for (Cluster<ManeuverClassification, Pair<ScalableBearing, ScalableDouble>, Pair<Bearing, Double>, ScalableBearingAndScalableDouble> c : clusters) {
-            likelihoodOfBeingTackCluster.put(c, getLikelihoodOfBeingTackCluster(c, clusters));
+            likelihoodOfBeingTackCluster.put(c,
                    getLikelihoodOfBeingTackCluster(c, clusters));
        }
        // The first two clusters in the resulting list are now our best bet for the tack clusters, assuming that the likelihood for the third element
        // in the list is already much lower. Should there be a significant degradation of likelihood between the first and the second cluster, we
        // will only use the first, particularly if the average middle COGs of the first two clusters differ significantly.
        final List<Cluster<ManeuverClassification, Pair<ScalableBearing, ScalableDouble>, Pair<Bearing, Double>, ScalableBearingAndScalableDouble>> tackClusters =
                clusters.stream()
-                .sorted((c1, c2) -> (int) -Math.signum(likelihoodOfBeingTackCluster.get(c1) // TODO cache result of getLikelihoodOfBeingTackCluster
+                .sorted((c1, c2) -> (int) -Math.signum(likelihoodOfBeingTackCluster.get(c1)
                        - likelihoodOfBeingTackCluster.get(c2))).limit(2).collect(Collectors.toList());
        addWindFixes(tackClusters.stream(), ManeuverType.TACK);
        Bearing estimatedJibeMiddleCOG =
                tackClusters.isEmpty() ? null
-                                       : (tackClusters.size() == 1 ? getWeightedAverageMiddleManeuverCOGDeg(tackClusters.get(0), ManeuverType.TACK)
+                                       : (tackClusters.size() == 1 ? getWeightedAverageMiddleManeuverCOGDegAndManeuverAngleDeg(tackClusters.get(0), ManeuverType.TACK).getA()
-                                                                  : new ScalableBearing(getWeightedAverageMiddleManeuverCOGDeg(tackClusters.get(0), ManeuverType.TACK)).add(
+                                                                  : new ScalableBearing(getWeightedAverageMiddleManeuverCOGDegAndManeuverAngleDeg(tackClusters.get(0), ManeuverType.TACK).getA()).add(
-                                                                          new ScalableBearing(getWeightedAverageMiddleManeuverCOGDeg(tackClusters.get(1), ManeuverType.TACK))).
+                                                                          new ScalableBearing(getWeightedAverageMiddleManeuverCOGDegAndManeuverAngleDeg(tackClusters.get(1), ManeuverType.TACK).getA())).
                                                                          divide(2)).reverse();
        final List<Cluster<ManeuverClassification, Pair<ScalableBearing, ScalableDouble>, Pair<Bearing, Double>, ScalableBearingAndScalableDouble>> jibeClusters =
                getJibeClusters(estimatedJibeMiddleCOG, clusters).collect(Collectors.toList());
@@ -402,12 +435,14 @@ public class ManeuverBasedWindEstimationTrackImpl extends WindTrackImpl {
    /**
     * Determines the likelihood of <code>cluster</code> being a cluster of tacks, based on the average likelihood of
     * the maneuver classifications in <code>cluster</code> to be maneuvers of type {@link ManeuverType#TACK TACK}, in
-     * turn based on what the {@link #polarService} thinks that this likelihood is and based on whether we find other
+     * turn based on what the {@link #polarService} thinks that this
-     * <code>clusters</code> that support this hypothesis. The likelihood is positively affected
+     * {@link PolarDataService#getManeuverLikelihoodAndTwsTwa(BoatClass, Speed, double, ManeuverType) likelihood} is and
     * based on whether we find other <code>clusters</code> that support this hypothesis. The likelihood is positively
     * affected
     * 
     * <ul>
     * <li>if a second cluster with similar average middle COG and a similar average maneuver angle with opposite sign
-     * is found that also has a high average likelihood of the maneuvers contained being tacks</li>
+     * is found that also has a high average likelihood of its maneuvers being tacks</li>
     * <li>if other clusters are found that for the average true wind speed estimated from the maneuvers in
     * <code>cluster</code> seem like head-up/bear-away clusters on port/starboard tack with an average middle COG that
     * is half the tacking angle for that wind speed away from the tack cluster's average middle COG</li>
@@ -423,7 +458,14 @@ public class ManeuverBasedWindEstimationTrackImpl extends WindTrackImpl {
     * apart from the tacks even if they have similar maneuver angles.</li>
     * </ul>
     * 
-     * @return a likelihood between 0..1 (inclusive)
+     * @return a likelihood between 0..1 (inclusive), obtained by multiplying the based likelihood of the
     *         <code>cluster</code> to hold tacks, based on the maneuver angles and their speed and how likely the
     *         {@link #polarService} considers this to be a tack; with boost factors added for the likelihood of having
     *         found a good jibe cluster and boost factors for the likelihoods of having found starboard and port tack
     *         clusters that hold the head-up/bear-away maneuvers. These boosts can add as much as
     *         {@link #BOOST_FACTOR_FOR_FULL_JIBE_CLUSTER_LIKELIHOOD} + 2*
     *         {@link #BOOST_FACTOR_FOR_FULL_HEAD_UP_BEAR_AWAY_CLUSTER_LIKELIHOOD} of the original value but will be
     *         capped at the maximum likelihood of 1.0.
     * 
     * @see ManeuverClassification#getLikelihoodAndTWSBasedOnSpeedAndAngle(ManeuverType)
     * @see PolarDataService#getManeuverLikelihoodAndTwsTwa(BoatClass, Speed, double, ManeuverType)
@@ -433,8 +475,7 @@ public class ManeuverBasedWindEstimationTrackImpl extends WindTrackImpl {
            Set<Cluster<ManeuverClassification, Pair<ScalableBearing, ScalableDouble>, Pair<Bearing, Double>, ScalableBearingAndScalableDouble>> clusters) {
        // start with the average of all of the cluster's maneuvers' likelihood to be a tack
        double averageTackLikelihood = getAverageLikelihoodOfBeingManeuver(ManeuverType.TACK, cluster.stream());
-        final Bearing approximateMiddleCOG = getWeightedAverageMiddleManeuverCOGDeg(cluster, ManeuverType.TACK);
+        final Bearing approximateMiddleCOG = getWeightedAverageMiddleManeuverCOGDegAndManeuverAngleDeg(cluster, ManeuverType.TACK).getA();
        final Bearing approximateMiddleCOGForJibes = approximateMiddleCOG.reverse();
        // search for the opposite tack cluster by finding the one that has the smallest angular distance to the expected
        // middle COG (same as for the candidate cluster) and expected maneuver angle (the cluster's average maneuver angle with inverted sign)
        final Cluster<ManeuverClassification, Pair<ScalableBearing, ScalableDouble>, Pair<Bearing, Double>, ScalableBearingAndScalableDouble> oppositeTackCluster =
@@ -442,11 +483,29 @@ public class ManeuverBasedWindEstimationTrackImpl extends WindTrackImpl {
            getClusterDistanceBasedOnAverageManeuverLikelihoodAndWeightedAverageMiddleCOG(a, -cluster.getCentroid().getB(), approximateMiddleCOG)-
            getClusterDistanceBasedOnAverageManeuverLikelihoodAndWeightedAverageMiddleCOG(b, -cluster.getCentroid().getB(), approximateMiddleCOG))).
            orElse(null);
-        final double likelihoodOfOppositeCluster = getLikelihoodOfOppositeTackCluster(-cluster.getCentroid().getB(), approximateMiddleCOG, oppositeTackCluster);
+        // if the opposite tack cluster is empty, it's pretty unlikely that it's a tack cluster; assign a low default probability of 10%
        final double likelihoodOfOppositeCluster = oppositeTackCluster.isEmpty() ? 0.1 :
            getLikelihoodOfClusterBasedOnDistanceFromExpected(-cluster.getCentroid().getB(), approximateMiddleCOG, oppositeTackCluster);
        // compute weighted averages across the current candidate cluster and its supposed opposite tack cluster where the latter
        // is weighted by the likelihoodOfOppositeCluster whereas the candidate cluster is always weighed as 1.0 for this purpose
        final double averageTackingAngleDeg = (Math.abs(getWeightedAverageMiddleManeuverCOGDegAndManeuverAngleDeg(cluster, ManeuverType.TACK).getB()) +
                likelihoodOfOppositeCluster*Math.abs(getWeightedAverageMiddleManeuverCOGDegAndManeuverAngleDeg(oppositeTackCluster, ManeuverType.TACK).getB()))
                / (1+likelihoodOfOppositeCluster);
        final Bearing averageUpwindCOG = new ScalableBearing(
                getWeightedAverageMiddleManeuverCOGDegAndManeuverAngleDeg(cluster, ManeuverType.TACK).getA()).add(new ScalableBearing(
                getWeightedAverageMiddleManeuverCOGDegAndManeuverAngleDeg(oppositeTackCluster, ManeuverType.TACK).getA()).
                multiply(likelihoodOfOppositeCluster)).divide(1+likelihoodOfOppositeCluster);
-        // TODO search for head-up/bear-away cluster(s) to port and to starboard of cluster's weighted middle COG
+        // Now search for head-up/bear-away cluster(s) to port and to starboard of cluster's weighted middle COG
        final Bearing expectedUpwindStarboardTackCOG = averageUpwindCOG.add(new DegreeBearingImpl(-averageTackingAngleDeg/2.));
        double starboardHeadUpBearAwayClusterLikelihood = getLikelihoodOfBestFittingHeadUpBearAwayCluster(
                clusters.stream().filter(c->c!=cluster), expectedUpwindStarboardTackCOG);
        final Bearing expectedUpwindPortTackCOG = averageUpwindCOG.add(new DegreeBearingImpl(averageTackingAngleDeg/2.));
        double portHeadUpBearAwayClusterLikelihood = getLikelihoodOfBestFittingHeadUpBearAwayCluster(
                clusters.stream().filter(c->c!=cluster), expectedUpwindPortTackCOG);
        // under the assumption that cluster holds tacks, find the clusters that then most likely hold the jibes
        final Bearing approximateMiddleCOGForJibes = averageUpwindCOG.reverse();
        Stream<Cluster<ManeuverClassification, Pair<ScalableBearing, ScalableDouble>, Pair<Bearing, Double>, ScalableBearingAndScalableDouble>> jibeClusters =
                getJibeClusters(approximateMiddleCOGForJibes, clusters);
        // increase cluster's score if "good" jibe clusters are found; quality is defined by how well the angle matches and how well the speed ratio fits
@@ -455,12 +514,14 @@ public class ManeuverBasedWindEstimationTrackImpl extends WindTrackImpl {
        if (tackClusterWeightedAverageSpeed != null) {
            // find out how likely the speed ratio is between the candidate tack cluster and the corresponding
            // hypothetical jibe clusters
-            double tackJibeLikelihoodBasedOnSpeedRatioAndAverageManeuverAngle = getLikelihoodOfBeingJibeCluster(
+            double jibeClusterLikelihood = getLikelihoodOfBeingJibeCluster(
                    tackClusterWeightedAverageSpeed, jibeClusters.map((jc) -> jc.stream()).reduce(Stream::concat)
-                            .orElse(Stream.empty()), getBoatClass());
+                            .orElse(Stream.empty()), getBoatClass(), clusters);
            // Likely jibe clusters may raise the general likelihood by up to 20% of the value so far, but not to over 1.0
            result = Math.min(1.0, averageTackLikelihood * likelihoodOfOppositeCluster *
-                    (1.0 + 0.2 * tackJibeLikelihoodBasedOnSpeedRatioAndAverageManeuverAngle));
+                    (1.0 + BOOST_FACTOR_FOR_FULL_JIBE_CLUSTER_LIKELIHOOD * jibeClusterLikelihood +
                            BOOST_FACTOR_FOR_FULL_HEAD_UP_BEAR_AWAY_CLUSTER_LIKELIHOOD * starboardHeadUpBearAwayClusterLikelihood +
                            BOOST_FACTOR_FOR_FULL_HEAD_UP_BEAR_AWAY_CLUSTER_LIKELIHOOD * portHeadUpBearAwayClusterLikelihood));
        } else {
            result = .1; // no elements in the cluster, therefore no average speed; low propability that this would be a tack cluster
        }
@@ -468,28 +529,86 @@ public class ManeuverBasedWindEstimationTrackImpl extends WindTrackImpl {
    }
    /**
-     * Tells how likely it is that the two clusters are opposite tack clusters. This is determined by looking at the
+     * Determines a likelihood for <code>cluster</code> being a head-up/bear-away cluster for the
-     * {@link #getClusterDistanceBasedOnAverageManeuverLikelihoodAndWeightedAverageMiddleCOG(Cluster, double, Bearing) angular distance}
+     * <code>expectedMiddleCOG</code>.
-     * between the two clusters regarding their middle COG and their average maneuver angles. The likelihood decreases exponentially
+     * 
-     * with increasing angle differences. It is 1.0 for an exact match and reaches 0.5 for an angular distance of 20deg.
+     * @return a value between 0..1 (exclusive)
     * @see #getLikelihoodOfClusterBasedOnDistanceFromExpected(double, Bearing, Cluster)
     */
-    private double getLikelihoodOfOppositeTackCluster(
+    private double getLikelihoodOfBestFittingHeadUpBearAwayCluster(
            Stream<Cluster<ManeuverClassification, Pair<ScalableBearing, ScalableDouble>, Pair<Bearing, Double>, ScalableBearingAndScalableDouble>> clusters,
            final Bearing expectedAverageMiddleCOG) {
        final Cluster<ManeuverClassification, Pair<ScalableBearing, ScalableDouble>, Pair<Bearing, Double>, ScalableBearingAndScalableDouble> starboardTackHeadUpAndBearAwayCluster =
                clusters.max((a, b)->(int) Math.signum(
                        getLikelihoodOfClusterBasedOnDistanceFromExpected(EXPECTED_AVERAGE_HEAD_UP_AND_BEAR_AWAY_MANEUVER_ANGLE_DEG, expectedAverageMiddleCOG, a)-
                        getLikelihoodOfClusterBasedOnDistanceFromExpected(EXPECTED_AVERAGE_HEAD_UP_AND_BEAR_AWAY_MANEUVER_ANGLE_DEG, expectedAverageMiddleCOG, b))).
            orElse(null);
        double starboardHeadUpBearAwayClusterLikelihood = starboardTackHeadUpAndBearAwayCluster == null ? 0.0 :
            getLikelihoodOfClusterBasedOnDistanceFromExpected(
                EXPECTED_AVERAGE_HEAD_UP_AND_BEAR_AWAY_MANEUVER_ANGLE_DEG, expectedAverageMiddleCOG, starboardTackHeadUpAndBearAwayCluster);
        return starboardHeadUpBearAwayClusterLikelihood;
    }
    /**
     * Assigns a likelihood to a cluster based on its
     * {@link #getClusterDistanceBasedOnAverageManeuverLikelihoodAndWeightedAverageMiddleCOG(Cluster, double, Bearing)
     * "angular distance"} from an expected average middle COG and Tells how likely it is that the two clusters are opposite tack clusters. This is determined
     * by looking at the
     * {@link #getClusterDistanceBasedOnAverageManeuverLikelihoodAndWeightedAverageMiddleCOG(Cluster, double, Bearing)
     * angular distance} between the two clusters regarding their middle COG and their average maneuver angles. The
     * likelihood decreases exponentially with increasing angle differences. It is 1.0 for an exact match and reaches
     * 0.5 for an angular distance of 20deg.
     */
    private double getLikelihoodOfClusterBasedOnDistanceFromExpected(
            double expectedManeuverAngleDeg, Bearing expectedApproximateMiddleCOG,
            Cluster<ManeuverClassification, Pair<ScalableBearing, ScalableDouble>, Pair<Bearing, Double>, ScalableBearingAndScalableDouble> oppositeTackCluster) {
-        return Math.exp(Math.log(0.5) * (getClusterDistanceBasedOnAverageManeuverLikelihoodAndWeightedAverageMiddleCOG(
+        final double clusterDistanceFromExpected = getClusterDistanceBasedOnAverageManeuverLikelihoodAndWeightedAverageMiddleCOG(
-                oppositeTackCluster, expectedManeuverAngleDeg, expectedApproximateMiddleCOG) / ANGULAR_DISTANCE_FOR_HALF_CONFIDENCE_FOR_OPPOSITE_TACK_CLUSTER_DEG));
+                        oppositeTackCluster, expectedManeuverAngleDeg, expectedApproximateMiddleCOG);
        return getLikelihoodOfClusterBasedOnDistanceFromExpected(clusterDistanceFromExpected);
    }
    /**
     * Assigns a likelihood to a cluster based on its
     * {@link #getClusterDistanceBasedOnAverageManeuverLikelihoodAndWeightedAverageMiddleCOG(Cluster, double, Bearing)
     * "angular distance"} from an expected average middle COG and Tells how likely it is that the two clusters are
     * opposite tack clusters. This is determined by looking at the
     * {@link #getClusterDistanceBasedOnAverageManeuverLikelihoodAndWeightedAverageMiddleCOG(Cluster, double, Bearing)
     * angular distance} between the two clusters regarding their middle COG and their average maneuver angles. The
     * likelihood decreases exponentially with increasing angle differences. It is 1.0 for an exact match and reaches
     * 0.5 for an angular distance of 20deg (see
     * {@link #ANGULAR_DISTANCE_FOR_HALF_CONFIDENCE_FOR_OPPOSITE_TACK_CLUSTER_DEG}).
     * 
     * @param clusterDistanceFromExpected
     *            an angular distance as computed by {@link #getClusterDistance(double, Bearing, double, Bearing)} and
     *            {@link #getClusterDistanceBasedOnAverageManeuverLikelihoodAndWeightedAverageMiddleCOG(Cluster, double, Bearing)}
     *            .
     */
    private double getLikelihoodOfClusterBasedOnDistanceFromExpected(final double clusterDistanceFromExpected) {
        return Math.exp(Math.log(0.5) * (clusterDistanceFromExpected / ANGULAR_DISTANCE_FOR_HALF_CONFIDENCE_FOR_OPPOSITE_TACK_CLUSTER_DEG));
    }
    /**
     * A euklidian degree distance based on the two degree distances between the maneuver angles and the
     * middle COGs. The expected pair is passed as <code>expcetedManeuverAngleDeg</code> and <code>expectedApproximateMiddleCOG</code> whereas
     * the actuals are determined by computing the {@link ManeuverType#TACK}-weighted average for those values from <code>cluster</code>.
     */
    private double getClusterDistanceBasedOnAverageManeuverLikelihoodAndWeightedAverageMiddleCOG(
            Cluster<ManeuverClassification, Pair<ScalableBearing, ScalableDouble>, Pair<Bearing, Double>, ScalableBearingAndScalableDouble> cluster,
            double expectedManeuverAngleDeg, Bearing expectedApproximateMiddleCOG) {
        final Pair<Bearing, Double> weightedAverageMiddleManeuverCOGDegAndManeuverAngleDeg = getWeightedAverageMiddleManeuverCOGDegAndManeuverAngleDeg(cluster, ManeuverType.TACK);
        final Bearing weightedAverageMiddleCOG = weightedAverageMiddleManeuverCOGDegAndManeuverAngleDeg.getA();
        final Double weightedAverageManeuverAngle = weightedAverageMiddleManeuverCOGDegAndManeuverAngleDeg.getB();
        return getClusterDistance(expectedManeuverAngleDeg, expectedApproximateMiddleCOG, weightedAverageManeuverAngle, weightedAverageMiddleCOG);
    }
    /**
     * A euklidian degree distance based on the two degree distances between the maneuver angles and the
     * middle COGs.
     */
-    private double getClusterDistanceBasedOnAverageManeuverLikelihoodAndWeightedAverageMiddleCOG(
+    private double getClusterDistance(double expectedManeuverAngleDeg, Bearing expectedApproximateMiddleCOG,
-            Cluster<ManeuverClassification, Pair<ScalableBearing, ScalableDouble>, Pair<Bearing, Double>, ScalableBearingAndScalableDouble> cluster,
+            final double weightedAverageManeuverAngle, final Bearing weightedAverageMiddleCOG) {
-            double expectedManeuverAngleDeg, Bearing expectedApproximateMiddleCOG) {
+        double middleCOGDiff = weightedAverageMiddleCOG.getDifferenceTo(expectedApproximateMiddleCOG).getDegrees();
-        final Bearing approximateMiddleCOG = getWeightedAverageMiddleManeuverCOGDeg(cluster, ManeuverType.TACK);
+        double maneuverAngleDiff = weightedAverageManeuverAngle - expectedManeuverAngleDeg;
        double middleCOGDiff = approximateMiddleCOG.getDifferenceTo(expectedApproximateMiddleCOG).getDegrees();
        double maneuverAngleDiff = cluster.getCentroid().getB() - expectedManeuverAngleDeg;
        return Math.sqrt(middleCOGDiff*middleCOGDiff + maneuverAngleDiff*maneuverAngleDiff);
    }
@@ -508,7 +627,7 @@ public class ManeuverBasedWindEstimationTrackImpl extends WindTrackImpl {
    /**
     * Returns at most two clusters that hold maneuvers with the highest average probability of being a jibe and whose
-     * {@link #getWeightedAverageMiddleManeuverCOGDeg(Cluster, ManeuverType) weighted average middle COG} fits that of
+     * {@link #getWeightedAverageMiddleManeuverCOGDegAndManeuverAngleDeg(Cluster, ManeuverType) weighted average middle COG} fits that of
     * the expected value (<code>approximateMiddleCOGForJibes</code>) within
     * {@link #THRESHOLD_JIBE_CLUSTER_DIFFERENCE_DEGREES} degrees.
     */
@@ -519,17 +638,17 @@ public class ManeuverBasedWindEstimationTrackImpl extends WindTrackImpl {
        return clusters.stream().sorted((a, b)->
                    (int) -Math.signum(getAverageLikelihoodOfBeingManeuver(ManeuverType.JIBE, a.stream()) -
                            getAverageLikelihoodOfBeingManeuver(ManeuverType.JIBE, b.stream()))).filter(
-                                    (jibeClusterCandidate)->Math.abs(getWeightedAverageMiddleManeuverCOGDeg(jibeClusterCandidate, ManeuverType.JIBE).
+                                    (jibeClusterCandidate)->Math.abs(getWeightedAverageMiddleManeuverCOGDegAndManeuverAngleDeg(jibeClusterCandidate, ManeuverType.JIBE).getA().
                                                                getDifferenceTo(approximateMiddleCOGForJibes).getDegrees()) < THRESHOLD_JIBE_CLUSTER_DIFFERENCE_DEGREES).
                                                                limit(2);
    }
    /**
     * By looking at the weighted speeds over ground averages, and based on the {@link #polarService} determines how
-     * likely it is that the jibe cluster contents are actually jibes. This is based on the idea that if for the most
+     * {@link PolarDataService#getManeuverLikelihoodAndTwsTwa(BoatClass, Speed, double, ManeuverType) likely} it is that
-     * likely wind speeds the jibes have a different (usually significantly higher) entry speed than the tacks then this
+     * the jibe cluster contents are actually jibes. This is based on the idea that if for the most likely wind speeds
-     * difference show show in the cluster elements. If they don't, then this should give a penalty for the cluster
+     * the jibes have a different (usually significantly higher) entry speed than the tacks then this difference should
-     * likelihoods.
+     * show in the cluster elements. If they don't, then this should give a penalty for the cluster likelihoods.
     * <p>
     * 
     * The weight of a maneuver for computing the weighted speed average is determined to be the
@@ -539,26 +658,48 @@ public class ManeuverBasedWindEstimationTrackImpl extends WindTrackImpl {
    private double getLikelihoodOfBeingJibeCluster(
            Speed tackClusterWeightedAverageSpeed,
            Stream<ManeuverClassification> jibeClustersContent,
-            BoatClass boatClass) {
+            BoatClass boatClass, Set<Cluster<ManeuverClassification, Pair<ScalableBearing, ScalableDouble>, Pair<Bearing, Double>, ScalableBearingAndScalableDouble>> clusters) {
        final int[] count = new int[1];
        final double[] likelihoodSum = new double[1];
        final ScalableBearing[] scaledAverageDownwindCOG = new ScalableBearing[1];
        final double[] scaledAbsJibingAngleSum = new double[1];
        Stream<ManeuverClassification> jibeClustersContentPeeker = jibeClustersContent.peek((mc)->{
            count[0]++;
-            likelihoodSum[0] += mc.getLikelihoodAndTWSBasedOnSpeedAndAngle(ManeuverType.JIBE).getA();
+            final double likelihood = mc.getLikelihoodAndTWSBasedOnSpeedAndAngle(ManeuverType.JIBE).getA();
            likelihoodSum[0] += likelihood;
            final ScalableBearing scaledCOG = new ScalableBearing(mc.getMiddleManeuverCourse()).multiply(likelihood);
            if (scaledAverageDownwindCOG[0] == null) {
                scaledAverageDownwindCOG[0] = scaledCOG;
            } else {
                scaledAverageDownwindCOG[0] = scaledAverageDownwindCOG[0].add(scaledCOG);
            }
            scaledAbsJibingAngleSum[0] += likelihood * Math.abs(mc.getManeuverAngleDeg());
        });
        Speed jibeClusterWeightedAverageSpeed = getWeightedAverageSpeed(jibeClustersContentPeeker, ManeuverType.JIBE);
        Bearing averageDownwindCOG = scaledAverageDownwindCOG[0] == null ? null : scaledAverageDownwindCOG[0].divide(likelihoodSum[0]);
        double absWeightedAverageJibingAbgle = scaledAbsJibingAngleSum[0] / likelihoodSum[0];
        final double result;
        if (jibeClusterWeightedAverageSpeed != null) {
            double tackJibeSpeedRatioLikelihood = polarService.getConfidenceForTackJibeSpeedRatio(
                    tackClusterWeightedAverageSpeed, jibeClusterWeightedAverageSpeed, boatClass);
            if (count[0] > 0) {
                double averageJibeLikelihood = likelihoodSum[0] / count[0];
-                result = averageJibeLikelihood * tackJibeSpeedRatioLikelihood;
+                // Now search for head-up/bear-away cluster(s) to port and to starboard of cluster's weighted middle COG
                final Bearing expectedDownwindStarboardTackCOG = averageDownwindCOG.add(new DegreeBearingImpl(+absWeightedAverageJibingAbgle/2.));
                double starboardHeadUpBearAwayClusterLikelihood = getLikelihoodOfBestFittingHeadUpBearAwayCluster(
                        clusters.stream(), expectedDownwindStarboardTackCOG);
                final Bearing expectedDownwindPortTackCOG = averageDownwindCOG.add(new DegreeBearingImpl(-absWeightedAverageJibingAbgle/2.));
                double portHeadUpBearAwayClusterLikelihood = getLikelihoodOfBestFittingHeadUpBearAwayCluster(
                        clusters.stream(), expectedDownwindPortTackCOG);
                result = Math.min(1.0, averageJibeLikelihood
                        * (1.0 + BOOST_FACTOR_FOR_JIBE_TACK_SPEED_RATIO_LIKELIHOOD * tackJibeSpeedRatioLikelihood +
                                BOOST_FACTOR_FOR_FULL_HEAD_UP_BEAR_AWAY_CLUSTER_LIKELIHOOD * starboardHeadUpBearAwayClusterLikelihood +
                                BOOST_FACTOR_FOR_FULL_HEAD_UP_BEAR_AWAY_CLUSTER_LIKELIHOOD * portHeadUpBearAwayClusterLikelihood));
            } else {
                throw new RuntimeException("Internal error: no maneuvers in jibe cluster candidate but still a valid weighted average speed "+jibeClusterWeightedAverageSpeed);
            }
        } else {
-            result = 0.5; // no maneuvers in the jibe clusters; could be but may also not be a jibe cluster
+            result = 0.1; // no maneuvers in the jibe clusters; could be but may also not be a jibe cluster
        }
        return result;
    }
@@ -606,28 +747,35 @@ public class ManeuverBasedWindEstimationTrackImpl extends WindTrackImpl {
    /**
     * For a cluster of maneuver classifications, clustered two-dimensionally by middle COG and maneuver angle, computes the
-     * weighted average of the middle COG where as the weight of each maneuver the likelihood that the maneuver was of type
+     * weighted average of the middle COG and maneuver angle where as the weight of each maneuver the likelihood that the maneuver was of type
     * <code>maneuverType</code> is used.<p>
     * 
     * The method has default package scope to allow tests in the same package in the test fragment to use it.
     * 
     * @return the weighted average middle COG
     */
-    Bearing getWeightedAverageMiddleManeuverCOGDeg(
+    Pair<Bearing, Double> getWeightedAverageMiddleManeuverCOGDegAndManeuverAngleDeg(
            Cluster<ManeuverClassification, Pair<ScalableBearing, ScalableDouble>, Pair<Bearing, Double>, ScalableBearingAndScalableDouble> cluster,
            ManeuverType maneuverType) {
        Pair<Cluster<ManeuverClassification, Pair<ScalableBearing, ScalableDouble>, Pair<Bearing, Double>, ScalableBearingAndScalableDouble>, ManeuverType> key = new Pair<>(
                cluster, maneuverType);
-        Bearing result = weightedAverageMiddleCOGForManeuverType.get(key);
+        Pair<Bearing, Double> result = weightedAverageMiddleCOGForManeuverType.get(key);
        if (result == null) {
-            ConfidenceBasedAverager<DoublePair, Bearing, Void> averager = ConfidenceFactory.INSTANCE
+            ConfidenceBasedAverager<DoublePair, Bearing, Void> middleCOGAverager = ConfidenceFactory.INSTANCE
                    .createAverager(/* weigher */null);
-            HasConfidence<DoublePair, Bearing, Void> average = averager.getAverage(
+            HasConfidence<DoublePair, Bearing, Void> average = middleCOGAverager.getAverage(
                    cluster.stream()
                            .map(new ManeuverClassificationToHasConfidenceAndIsScalableAdapter<DoublePair, Bearing>(
                                    maneuverType, (mc) -> new ScalableBearing(mc.getMiddleManeuverCourse()),
                                    polarService)).iterator(), /* at */null);
-            result = average.getObject();
+            ConfidenceBasedAverager<Double, Double, Void> maneuverAngleAverager = ConfidenceFactory.INSTANCE
                    .createAverager(/* weigher */null);
            HasConfidence<Double, Double, Void> maneuverAngleAverageDeg = maneuverAngleAverager.getAverage(
                    cluster.stream()
                            .map(new ManeuverClassificationToHasConfidenceAndIsScalableAdapter<Double, Double>(
                                    maneuverType, (mc) -> new ScalableDouble(mc.getManeuverAngleDeg()),
                                    polarService)).iterator(), /* at */null);
            result = new Pair<>(average.getObject(), maneuverAngleAverageDeg.getObject());
            weightedAverageMiddleCOGForManeuverType.put(key, result);
        }
        return result;
@@ -0,0 +1,8 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <classpath>
 	<classpathentry kind="con" path="org.eclipse.jdt.launching.JRE_CONTAINER/org.eclipse.jdt.internal.debug.ui.launcher.StandardVMType/JavaSE-1.8"/>
 	<classpathentry kind="con" path="org.eclipse.pde.core.requiredPlugins"/>
 	<classpathentry kind="src" path="src"/>
 	<classpathentry kind="src" path="resources"/>
 	<classpathentry kind="output" path="bin"/>
 </classpath>
@@ -0,0 +1,28 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <projectDescription>
 	<name>com.sap.sailing.xmlexport.test</name>
 	<comment></comment>
 	<projects>
 	</projects>
 	<buildSpec>
 		<buildCommand>
 			<name>org.eclipse.jdt.core.javabuilder</name>
 			<arguments>
 			</arguments>
 		</buildCommand>
 		<buildCommand>
 			<name>org.eclipse.pde.ManifestBuilder</name>
 			<arguments>
 			</arguments>
 		</buildCommand>
 		<buildCommand>
 			<name>org.eclipse.pde.SchemaBuilder</name>
 			<arguments>
 			</arguments>
 		</buildCommand>
 	</buildSpec>
 	<natures>
 		<nature>org.eclipse.pde.PluginNature</nature>
 		<nature>org.eclipse.jdt.core.javanature</nature>
 	</natures>
 </projectDescription>
@@ -0,0 +1,12 @@
 eclipse.preferences.version=1
 org.eclipse.jdt.core.compiler.codegen.inlineJsrBytecode=enabled
 org.eclipse.jdt.core.compiler.codegen.methodParameters=do not generate
 org.eclipse.jdt.core.compiler.codegen.targetPlatform=1.8
 org.eclipse.jdt.core.compiler.codegen.unusedLocal=preserve
 org.eclipse.jdt.core.compiler.compliance=1.8
 org.eclipse.jdt.core.compiler.debug.lineNumber=generate
 org.eclipse.jdt.core.compiler.debug.localVariable=generate
 org.eclipse.jdt.core.compiler.debug.sourceFile=generate
 org.eclipse.jdt.core.compiler.problem.assertIdentifier=error
 org.eclipse.jdt.core.compiler.problem.enumIdentifier=error
 org.eclipse.jdt.core.compiler.source=1.8
@@ -0,0 +1,3 @@
 eclipse.preferences.version=1
 pluginProject.extensions=false
 resolve.requirebundle=false
@@ -0,0 +1,12 @@
 Manifest-Version: 1.0
 Bundle-ManifestVersion: 2
 Bundle-Name: Test
 Bundle-SymbolicName: com.sap.sailing.xmlexport.test
 Bundle-Version: 1.0.0.qualifier
 Bundle-Vendor: SAP
 Fragment-Host: com.sap.sailing.xmlexport
 Bundle-RequiredExecutionEnvironment: JavaSE-1.8
 Require-Bundle: org.junit4;bundle-version="4.8.2",
 com.sap.sse.common,
 com.sap.sailing.domain.test;bundle-version="1.0.0",
 com.tractrac.clientmodule;bundle-version="3.0.7"
@@ -0,0 +1,5 @@
 source.. = src/,\
           resources/
 output.. = bin/
 bin.includes = META-INF/,\
               .
@@ -0,0 +1,12 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <project xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd" xmlns="http://maven.apache.org/POM/4.0.0"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
  <modelVersion>4.0.0</modelVersion>
  <parent>
    <artifactId>root</artifactId>
    <groupId>com.sap.sailing</groupId>
    <version>1.0.0-SNAPSHOT</version>
  </parent>
  <artifactId>com.sap.sailing.xmlexport.test</artifactId>
  <packaging>eclipse-test-plugin</packaging>
 </project>
@@ -0,0 +1,643 @@
 stored-uri:event_20141001_ESSNice-Race_1.mtb
 StartReplay:1
 // Input from params_static:
 // Input from event_parameters:
 DefaultPanel:
 ReCalcDirAndSpeed:1
 CompMarkerUUID:2dee0384-2c45-11e4-a9f6-14dae9614d7b
 CodanIsSponsor:0
 DefaultTailLength:60
 APzoomChangeTime:2500
 disableAutoProduce:0
 autoProduce:0
 APstartLineShowOfLeg:0.25
 APsideOfStartLine:0.30
 APstartSwitch:0.8
 APwholeLegBehindMarks:0.15
 APmarkSwitch:0.13
 APmarkZoomBehindMarks:0.10
 APmarkZoomInFrontOfMarks:0.20
 PopupMarkerUUID:84199024-2c45-11e4-a9f6-14dae9614d7b
 ManualUrl:http://www.tractrac.com/files/userguide_sailing.pdf
 //live-uri:tcp://192.168.1.203:4400
 //stored-uri:tcp://192.168.1.203:4401
 Marker1UUID:2dee0384-2c45-11e4-a9f6-14dae9614d7b
 Marker1Type:RGBMarkerFactory
 Marker1Directional:1
 Marker1Image:markers/boat_FF0000_big.png
 Marker1Length:5
 Marker1MinPixelSize:30
 Startlocation:7.269026586914038,43.68669104379883
 MaxDiffTime:1200
 MaxMetersPerSecond:20
 PrecisionMeters:20
 ShortAvgTime:180
 LongAvgTime:900
 TimeZone:2
 CompMarkerTimeout:60
 FramesPerSecond:8
 replayspeedup:5
 MatchRaceClock:0
 MatchRaceClockNo:3
 MatchRaceClockSpacing:300
 Minimap:1
 MinimapUseLayers:2
 Minimapgeorect:7.241326904296898,43.705766636035165,7.296516491699208,43.67209091170523
 MinimapMarkerUUID:84199024-2c45-11e4-a9f6-14dae9614d7b
 Marker4UUID:84199024-2c45-11e4-a9f6-14dae9614d7b
 Marker4Type:RGBmarkerFactory
 Marker4Directional:1
 Marker4Image:markers/boat_FF0000_small.png
 MetersPerPixel:18
 MetersPerPixelMax:30
 MetersPerPixelMin:0.2
 isMatchRace:0
 DefaultDistanceUnits:meters
 weatherEnabled:0
 DefaultSpeedUnits:KmH
 showRaceClock:1
 BackGroundImage:graphics/background.jpg
 DisableRotation:0
 ControlPointMarkerRadius:13
 disableselection:0
 disableleaderline:0
 DisableChangeRace:0
 PopUpRow1Name:
 PopUpRow1Type:Name
 PopUpRow2Name:Knots
 PopUpRow2Type:BoatSpeed
 PopUpRow3Name:Ranking
 PopUpRow3Type:RowNumber
 PopUpRow4Name:Sail
 PopUpRow4Type:Ini
 PopUpRow5Name:After
 PopUpRow5Type:BoatAfter
 WindEstimator:0
 MapUrl:http://tile.traclive.dk/ttm
 ResultColumn1Name:#
 ResultColumn1Size:20
 ResultColumn1Type:RowNumber
 ResultColumn2Name:sail
 ResultColumn2Size:45
 ResultColumn2Type:Ini
 ResultColumn3Name:name
 ResultColumn3Size:110
 ResultColumn3Type:Name
 ResultColumn4Name:after
 ResultColumn4Size:45
 ResultColumn4Type:BoatAfter
 ResultColumn5Name:kts
 ResultColumn5Size:40
 ResultColumn5Type:BoatSpeed
 DisableLeaderboard:0
 DisableAnalysis:0
 TableFontSize:11
 compInitialsFontSize:11
 AutoRotate:0
 MassStart:0
 SegmentFile:segments.php
 StartType:Mass
 RaceHandicapSystem:NONE
 TeamCompetitionType:NONE
 LiveDelaySecs: 6
 //-------- AUTO GENERATED PARAMETERS START ----------------
 EventID:8638bc00-2aad-0132-18bc-448a5b8481d8
 EventName:ESS Nice 2014
 EventDB:event_20141001_ESSNice
 EventStartTime:2014-09-30 22:00:00
 EventEndTime:2014-10-05 21:00:00
 EventType:a1b74ca0-fdd8-11dc-8811-005056c00008
 RaceID:09f4b690-2bc6-0132-1eef-10b11c4ed8fd
 RaceName:Race 1
 RaceStartTime:2014-10-02 12:02:00
 RaceEndTime:
 RaceTrackingStartTime:2014-10-02 11:58:14
 RaceTrackingEndTime:2014-10-02 12:17:02
 RaceDefaultRouteUUID:09f125d0-2bc6-0132-1eee-10b11c4ed8fd
 RaceHandicapSystem:NONE
 Image1UUID:64a7b348-83db-11e2-88c0-10bf48d758ce
 Image1Type:Logo
 Image1Description:http://germanmaster.traclive.dk/events/event_20100806_SailforGol/images/SUI.gif
 Image1Image:http://germanmaster.traclive.dk/events/event_20100806_SailforGol/images/SUI.gif
 Image2UUID:64c3a8fa-83db-11e2-88c0-10bf48d758ce
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 ControlPoint19DataSheet:P1.Type=Buoy###BREAKLINE###P1.Color=Green###BREAKLINE###P1.Shape=Conical###BREAKLINE###P1.Name=Green###BREAKLINE###P1.UUID=785c3e44-83be-11e2-88c0-10bf48d758ce###BREAKLINE###P2.Type=Buoy###BREAKLINE###P2.Color=Yellow###BREAKLINE###P2.Shape=Conical###BREAKLINE###P2.Name=Yellow###BREAKLINE###P2.UUID=3fdd2402-83be-11e2-88c0-10bf48d758ce###BREAKLINE###
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 ControlPoint20UUID:a0f71190-7adb-0131-e5ea-60a44ce903c3
 ControlPoint20Name:Blue-Yellow
 ControlPoint20HasTwoPoints:1
 ControlPoint20ShortName:BY
 ControlPoint20DataSheet:P1.Type=Buoy###BREAKLINE###P1.Color=Blue###BREAKLINE###P1.Shape=Conical###BREAKLINE###P1.Name=Blue###BREAKLINE###P1.UUID=1286f15e-83be-11e2-88c0-10bf48d758ce###BREAKLINE###P2.Type=Buoy###BREAKLINE###P2.Color=Yellow###BREAKLINE###P2.Shape=Conical###BREAKLINE###P2.Name=Yellow###BREAKLINE###P2.UUID=3fdd2402-83be-11e2-88c0-10bf48d758ce###BREAKLINE###
 ControlPoint20Mark1Lon:7.269418
 ControlPoint20Mark1Lat:43.687290
 ControlPoint20Mark2Lon:7.269320
 ControlPoint20Mark2Lat:43.687366
 ControlPoint21UUID:a68c6350-7adc-0131-e626-60a44ce903c3
 ControlPoint21Name:RC-Black Conical
 ControlPoint21HasTwoPoints:1
 ControlPoint21ShortName:S
 ControlPoint21DataSheet:P1.Type=StartBoat###BREAKLINE###P1.Name=Race Committee###BREAKLINE###P1.UUID=3e6c1c94-83bf-11e2-88c0-10bf48d758ce###BREAKLINE###P2.Type=Buoy###BREAKLINE###P2.Color=Black###BREAKLINE###P2.Shape=Conical###BREAKLINE###P2.Pattern=Checkered###BREAKLINE###P2.Name=Black Conical###BREAKLINE###P2.UUID=d78695ea-83be-11e2-88c0-10bf48d758ce###BREAKLINE###
 ControlPoint21Mark1Lon:7.267022
 ControlPoint21Mark1Lat:43.691895
 ControlPoint21Mark2Lon:7.272432
 ControlPoint21Mark2Lat:43.692131
 ControlPoint22UUID:b153dfd6-83be-11e2-88c0-10bf48d758ce
 ControlPoint22Name:Black Cylinder
 ControlPoint22HasTwoPoints:0
 ControlPoint22ShortName:B
 ControlPoint22DataSheet:Type=Buoy###BREAKLINE###Color=Black###BREAKLINE###Shape=Cylinder###BREAKLINE###Pattern=Checkered###BREAKLINE###Name=Black Cylinder
 ControlPoint22Mark1Lon:7.269445
 ControlPoint22Mark1Lat:43.687302
 ControlPoint23UUID:b62e0bf0-7adc-0131-e630-60a44ce903c3
 ControlPoint23Name:RC-Black Cylinder
 ControlPoint23HasTwoPoints:1
 ControlPoint23ShortName:S
 ControlPoint23DataSheet:P1.Type=StartBoat###BREAKLINE###P1.Name=Race Committee###BREAKLINE###P1.UUID=3e6c1c94-83bf-11e2-88c0-10bf48d758ce###BREAKLINE###P2.Type=Buoy###BREAKLINE###P2.Color=Black###BREAKLINE###P2.Shape=Cylinder###BREAKLINE###P2.Pattern=Checkered###BREAKLINE###P2.Name=Black Cylinder###BREAKLINE###P2.UUID=b153dfd6-83be-11e2-88c0-10bf48d758ce###BREAKLINE###
 ControlPoint23Mark1Lon:7.267022
 ControlPoint23Mark1Lat:43.691895
 ControlPoint23Mark2Lon:7.269445
 ControlPoint23Mark2Lat:43.687302
 ControlPoint24UUID:bd1fc330-7c10-0131-9c24-10b11c4ed8fd
 ControlPoint24Name:Black Cylinder-Yellow
 ControlPoint24HasTwoPoints:1
 ControlPoint24ShortName:S
 ControlPoint24DataSheet:P1.Type=Buoy###BREAKLINE###P1.Color=Black###BREAKLINE###P1.Shape=Cylinder###BREAKLINE###P1.Pattern=Checkered###BREAKLINE###P1.Name=Black Cylinder###BREAKLINE###P1.UUID=b153dfd6-83be-11e2-88c0-10bf48d758ce###BREAKLINE###P2.Type=Buoy###BREAKLINE###P2.Color=Yellow###BREAKLINE###P2.Shape=Conical###BREAKLINE###P2.Name=Yellow###BREAKLINE###P2.UUID=3fdd2402-83be-11e2-88c0-10bf48d758ce###BREAKLINE###
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 ControlPoint24Mark2Lat:43.687366
 ControlPoint25UUID:bf6777e6-83bd-11e2-88c0-10bf48d758ce
 ControlPoint25Name:White S
 ControlPoint25HasTwoPoints:0
 ControlPoint25ShortName:W
 ControlPoint25DataSheet:Type=Buoy###BREAKLINE###Color=White###BREAKLINE###Shape=Conical###BREAKLINE###Name=White S
 ControlPoint25Mark1Lon:7.268352
 ControlPoint25Mark1Lat:43.691936
 ControlPoint26UUID:cd3c1dc0-7c11-0131-9c2e-10b11c4ed8fd
 ControlPoint26Name:Finish Pole-Conical
 ControlPoint26HasTwoPoints:1
 ControlPoint26ShortName:S
 ControlPoint26DataSheet:P1.Color=Black###BREAKLINE###P1.Type=Landmark###BREAKLINE###P1.Name=Finish Pole###BREAKLINE###P1.UUID=3240586c-83c0-11e2-88c0-10bf48d758ce###BREAKLINE###P2.Type=Buoy###BREAKLINE###P2.Color=Black###BREAKLINE###P2.Shape=Conical###BREAKLINE###P2.Pattern=Checkered###BREAKLINE###P2.Name=Black Conical###BREAKLINE###P2.UUID=d78695ea-83be-11e2-88c0-10bf48d758ce###BREAKLINE###
 ControlPoint26Mark1Lon:7.271342
 ControlPoint26Mark1Lat:43.694851
 ControlPoint26Mark2Lon:7.272432
 ControlPoint26Mark2Lat:43.692131
 ControlPoint27UUID:d39a0d00-7adc-0131-e63a-60a44ce903c3
 ControlPoint27Name:White Gate
 ControlPoint27HasTwoPoints:1
 ControlPoint27ShortName:W
 ControlPoint27DataSheet:P1.Type=Buoy###BREAKLINE###P1.Color=White###BREAKLINE###P1.Shape=Conical###BREAKLINE###P1.Name=White S###BREAKLINE###P1.UUID=bf6777e6-83bd-11e2-88c0-10bf48d758ce###BREAKLINE###P2.Type=Buoy###BREAKLINE###P2.Color=White###BREAKLINE###P2.Shape=Conical###BREAKLINE###P2.Name=White P###BREAKLINE###P2.UUID=e9ec42f8-83bd-11e2-88c0-10bf48d758ce###BREAKLINE###
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 ControlPoint27Mark2Lon:7.271063
 ControlPoint27Mark2Lat:43.691803
 ControlPoint28UUID:d78695ea-83be-11e2-88c0-10bf48d758ce
 ControlPoint28Name:Black Conical
 ControlPoint28HasTwoPoints:0
 ControlPoint28ShortName:B
 ControlPoint28DataSheet:Type=Buoy###BREAKLINE###Color=Black###BREAKLINE###Shape=Conical###BREAKLINE###Pattern=Checkered###BREAKLINE###Name=Black Conical
 ControlPoint28Mark1Lon:7.272432
 ControlPoint28Mark1Lat:43.692131
 ControlPoint29UUID:e9ec42f8-83bd-11e2-88c0-10bf48d758ce
 ControlPoint29Name:White P
 ControlPoint29HasTwoPoints:0
 ControlPoint29ShortName:W
 ControlPoint29DataSheet:Type=Buoy###BREAKLINE###Color=White###BREAKLINE###Shape=Conical###BREAKLINE###Name=White P
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 ControlPoint29Mark1Lat:43.691803
 ControlPoint30UUID:eff23330-7b84-0131-b9d2-10b11c4ed8fd
 ControlPoint30Name:RC-Red
 ControlPoint30HasTwoPoints:1
 ControlPoint30ShortName:S
 ControlPoint30DataSheet:P1.Type=StartBoat###BREAKLINE###P1.Name=Race Committee###BREAKLINE###P1.UUID=3e6c1c94-83bf-11e2-88c0-10bf48d758ce###BREAKLINE###P2.Type=Buoy###BREAKLINE###P2.Color=Red###BREAKLINE###P2.Shape=Conical###BREAKLINE###P2.Name=Red###BREAKLINE###P2.UUID=5427c7d2-83be-11e2-88c0-10bf48d758ce###BREAKLINE###
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 ControlPoint30Mark2Lon:7.273181
 ControlPoint30Mark2Lat:43.688370
 SegmentFile:segments.php
 Route1UUID:09f125d0-2bc6-0132-1eee-10b11c4ed8fd
 Route1Description:Race 1
 Route1Length:0
 Route1DataSheet:CourseDiagram=Course###BREAKLINE###Seq.1=Line###BREAKLINE###Seq.2=Port###BREAKLINE###Seq.3=Gate###BREAKLINE###Seq.4=Port###BREAKLINE###Seq.5=Line###BREAKLINE###
 Route1ControlPoint1UUID:d39a0d00-7adc-0131-e63a-60a44ce903c3
 Route1ControlPoint2UUID:785c3e44-83be-11e2-88c0-10bf48d758ce
 Route1ControlPoint3UUID:2ce99970-2c47-0132-20ce-10b11c4ed8fd
 //-------- AUTO GENERATED PARAMETERS END ------------------
@@ -0,0 +1,76 @@
 package com.sap.sailing.xmlexport.test;
 import static org.junit.Assert.assertNotNull;
 import static org.junit.Assert.assertTrue;
 import static org.junit.Assert.fail;
 import java.io.File;
 import java.net.MalformedURLException;
 import java.net.URI;
 import java.net.URISyntaxException;
 import java.net.URL;
 import org.junit.Test;
 import com.sap.sailing.domain.common.WindSourceType;
 import com.sap.sailing.domain.common.impl.DegreeBearingImpl;
 import com.sap.sailing.domain.common.impl.KnotSpeedWithBearingImpl;
 import com.sap.sailing.domain.common.impl.WindSourceImpl;
 import com.sap.sailing.domain.leaderboard.FlexibleLeaderboard;
 import com.sap.sailing.domain.leaderboard.impl.FlexibleLeaderboardImpl;
 import com.sap.sailing.domain.leaderboard.impl.HighPointFirstGets10LastBreaksTie;
 import com.sap.sailing.domain.leaderboard.impl.ThresholdBasedResultDiscardingRuleImpl;
 import com.sap.sailing.domain.test.OnlineTracTracBasedTest;
 import com.sap.sailing.domain.tracking.impl.WindImpl;
 import com.sap.sailing.domain.tractracadapter.ReceiverType;
 import com.sap.sailing.xmlexport.LeaderboardData;
 public class XMLExportTest extends OnlineTracTracBasedTest {
    public XMLExportTest() throws MalformedURLException, URISyntaxException {
        super();
    }
    private void setUpESS2014Nice(String raceNumber) {
        URI storedUri;
        try {
            storedUri = new URI("file:///" + new File("resources/" + getFileName() + raceNumber + ".mtb").getCanonicalPath().replace('\\', '/'));
            super.setUp(new URL("file:///" + new File("resources/" + getFileName() + raceNumber + ".txt").getCanonicalPath()),
            /* liveUri */null, /* storedUri */storedUri,
                    new ReceiverType[] { ReceiverType.MARKPASSINGS, ReceiverType.RACECOURSE, ReceiverType.MARKPOSITIONS, ReceiverType.RAWPOSITIONS });
        } catch (Exception ex) {
            ex.printStackTrace();
        }
        boolean result = getTrackedRace().recordWind(new WindImpl(/* position */null, getTrackedRace().getStartOfRace(), new KnotSpeedWithBearingImpl(12, new DegreeBearingImpl(65))),
                new WindSourceImpl(WindSourceType.WEB));
        assert result==true;
    }
    protected String getExpectedEventName() {
        return "ESS Nice 2014";
    }
    protected String getFileName() {
        return "event_20141001_ESSNice-Race_";
    }
    @Test
    public void testExportingESSNice2014() { 
        setUpESS2014Nice("1");
        FlexibleLeaderboard leaderboard = new FlexibleLeaderboardImpl("ESS 2014 Nice", new ThresholdBasedResultDiscardingRuleImpl(new int[] {0}), new HighPointFirstGets10LastBreaksTie(), 
                null);
        leaderboard.addRace(getTrackedRace(), "R1", false);
        LeaderboardData leaderboardData = new LeaderboardData(leaderboard);
        try {
            leaderboardData.perform();
        } catch (Exception e) {
            e.printStackTrace();
            fail("No exception should occur");
        }
        String resultData = leaderboardData.getResultXML();
        assertNotNull(resultData);
        assertTrue(resultData.length()>261000);
    }
 }
@@ -1,6 +1,7 @@
 package com.sap.sailing.xmlexport;
 import java.io.IOException;
 import java.io.StringWriter;
 import java.util.List;
 import java.util.NavigableSet;
 import java.util.regex.Matcher;
@@ -41,11 +42,21 @@ public abstract class ExportAction {
    private HttpServletResponse res;
    private RacingEventService service;
    private Leaderboard leaderboard;
    protected final boolean useProvidedLeaderboard;
    private String resultingXMLData;
    public ExportAction(HttpServletRequest req, HttpServletResponse res, RacingEventService service) {
        this.req = req;
        this.res = res;
        this.service = service;
        this.leaderboard = null;
        this.useProvidedLeaderboard = false;
    }
    public ExportAction(Leaderboard leaderboard) {
        this.leaderboard = leaderboard;
        this.useProvidedLeaderboard = true;
    }
    public String getAttribute(String name) {
@@ -56,14 +67,20 @@ public abstract class ExportAction {
        return service;
    }
    public String getResultXML() {
        return resultingXMLData;
    }
    public Leaderboard getLeaderboard() throws IOException, ServletException {
-        final String leaderboardName = getAttribute("name");
+        if (!useProvidedLeaderboard) {
-        if (leaderboardName == null) {
+            final String leaderboardName = getAttribute("name");
-            throw new ServletException("Use the name= parameter to specify the leaderboard");
+            if (leaderboardName == null) {
-        }
+                throw new ServletException("Use the name= parameter to specify the leaderboard");
-        final Leaderboard leaderboard = getService().getLeaderboardByName(leaderboardName); 
+            }
-        if (leaderboard == null) {
+            leaderboard = getService().getLeaderboardByName(leaderboardName); 
-            throw new ServletException("Leaderboard " + leaderboardName + " not found.");
+            if (leaderboard == null) {
                throw new ServletException("Leaderboard " + leaderboardName + " not found.");
            }
        }
        return leaderboard;
    }
@@ -315,13 +332,22 @@ public abstract class ExportAction {
        format.setEncoding("UTF-8");
        XMLOutputter xmlOutputter = new XMLOutputter(format);
-        res.setContentType("text/xml");
+        if (!useProvidedLeaderboard) {
-        res.addHeader("Content-Disposition", "attachment; filename=" + fileName);
+            res.setContentType("text/xml");
-        
+            res.addHeader("Content-Disposition", "attachment; filename=" + fileName);
-        try {
+            try {
-            xmlOutputter.output(element, res.getOutputStream());
+                xmlOutputter.output(element, res.getOutputStream());
-        } catch (IOException e) {
+            } catch (IOException e) {
-            e.printStackTrace();
+                e.printStackTrace();
            }
        } else {
            StringWriter resultStringWriter = new StringWriter();
            try {
                xmlOutputter.output(element, resultStringWriter);
                resultingXMLData = resultStringWriter.toString();
            } catch (IOException e) {
                e.printStackTrace();
            }
        }
    }
@@ -75,6 +75,10 @@ public class LeaderboardData extends ExportAction {
        super(req, res, service);
    }
    public LeaderboardData(Leaderboard leaderboard) {
        super(leaderboard);
    }
    /**
     *  Creates XML for a leaderboard. Expects a list of generated competitors and races XML elements that are associated with the leaderboard.
     *  <pre>
@@ -907,6 +911,7 @@ public class LeaderboardData extends ExportAction {
            }
        }
        log.info("Finished XML export of leaderboard " + leaderboard.getName() + " in " + MillisecondsTimePoint.now().minus(timeSpent.asMillis()).asMillis() + " milliseconds");
-        sendDocument(createLeaderboardXML(leaderboard, competitorElements, racesElements, leaderboardConfidenceAndErrorMessages), leaderboard.getName() + ".xml");
+        Element dataToExport = createLeaderboardXML(leaderboard, competitorElements, racesElements, leaderboardConfidenceAndErrorMessages);
        sendDocument(dataToExport, leaderboard.getName() + ".xml");
    }
 }
@@ -67,6 +67,7 @@
 		<module>com.sap.sailing.www</module>
 		<module>com.sap.sailing.www.events</module>
 		<module>com.sap.sailing.xmlexport</module>
 		<module>com.sap.sailing.xmlexport.test</module>
 		<module>com.google.gwt.osgi</module>
 		<module>com.tractrac.clientmodule</module>
 		<module>org.json.simple</module>