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
@@ -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"
@@ -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
 Image2Type:Logo
 Image2Description:http://germanmaster.traclive.dk/events/event_20100806_SailforGol/images/NZL.gif
 Image2Image:http://germanmaster.traclive.dk/events/event_20100806_SailforGol/images/NZL.gif
 Image3UUID:651130a2-83db-11e2-88c0-10bf48d758ce
 Image3Type:Logo
 Image3Description:http://germanmaster.traclive.dk/events/event_20100806_SailforGol/images/KOR.gif
 Image3Image:http://germanmaster.traclive.dk/events/event_20100806_SailforGol/images/KOR.gif
 Image4UUID:653c1ab0-83db-11e2-88c0-10bf48d758ce
 Image4Type:Logo
 Image4Description:http://germanmaster.traclive.dk/events/event_20100806_SailforGol/images/AUT.gif
 Image4Image:http://germanmaster.traclive.dk/events/event_20100806_SailforGol/images/AUT.gif
 Image5UUID:65637da8-83db-11e2-88c0-10bf48d758ce
 Image5Type:Logo
 Image5Description:http://germanmaster.traclive.dk/events/event_20100806_SailforGol/images/DEN.gif
 Image5Image:http://germanmaster.traclive.dk/events/event_20100806_SailforGol/images/DEN.gif
 Image6UUID:65875138-83db-11e2-88c0-10bf48d758ce
 Image6Type:Logo
 Image6Description:http://germanmaster.traclive.dk/events/event_20100806_SailforGol/images/OMN.gif
 Image6Image:http://germanmaster.traclive.dk/events/event_20100806_SailforGol/images/OMN.gif
 Class1UUID:648ee25a-83db-11e2-88c0-10bf48d758ce
 Class1Name:Extreme40
 Team1UUID:649f1dbe-83db-11e2-88c0-10bf48d758ce
 Team1Name:TeamA
 Team1Comp1UUID:648bd4f2-83db-11e2-88c0-10bf48d758ce
 Team2UUID:64bf0854-83db-11e2-88c0-10bf48d758ce
 Team2Name:TeamB
 Team2Comp1UUID:64bbff7e-83db-11e2-88c0-10bf48d758ce
 Team3UUID:64dd7988-83db-11e2-88c0-10bf48d758ce
 Team3Name:TeamC
 Team3Comp1UUID:64da7c24-83db-11e2-88c0-10bf48d758ce
 Team4UUID:64ffc402-83db-11e2-88c0-10bf48d758ce
 Team4Name:TeamD
 Team5UUID:65351d82-83db-11e2-88c0-10bf48d758ce
 Team5Name:TeamE
 Team5Comp1UUID:65322500-83db-11e2-88c0-10bf48d758ce
 Team6UUID:655ed82a-83db-11e2-88c0-10bf48d758ce
 Team6Name:TeamF
 Team6Comp1UUID:655bd56c-83db-11e2-88c0-10bf48d758ce
 Team7UUID:65829fa8-83db-11e2-88c0-10bf48d758ce
 Team7Name:TeamG
 Team7Comp1UUID:657fa5a0-83db-11e2-88c0-10bf48d758ce
 Team8UUID:e4459a20-83db-11e2-88c0-10bf48d758ce
 Team8Name:TeamH
 Team9UUID:a73aabc0-d6d6-0130-8be2-60a44ce903c3
 Team9Name:TeamI
 Team9Comp1UUID:93085e80-7ad9-0131-e5b3-60a44ce903c3
 Team10UUID:bbf81f60-d6d6-0130-8be3-60a44ce903c3
 Team10Name:TeamJ
 Team10Comp1UUID:f097f4f0-7ad9-0131-e5b4-60a44ce903c3
 Team11UUID:65659280-eda3-0130-c5c0-10b11c4ed8fd
 Team11Name:TeamK
 Team11Comp1UUID:19dc3eb0-7ada-0131-e5b5-60a44ce903c3
 Team12UUID:9ee14560-77af-0131-e5af-60a44ce903c3
 Team12Name:TeamL
 Team12Comp1UUID:5e15e7c0-7ada-0131-e5b6-60a44ce903c3
 Team13UUID:b9677300-7ad7-0131-e5b0-60a44ce903c3
 Team13Name:TeamM
 Team13Comp1UUID:84e68b70-7ada-0131-e5b7-60a44ce903c3
 Team14UUID:c9689a00-7ad7-0131-e5b1-60a44ce903c3
 Team14Name:TeamN
 Team15UUID:d5712f30-7ad7-0131-e5b2-60a44ce903c3
 Team15Name:TeamO
 Comp1UUID:648bd4f2-83db-11e2-88c0-10bf48d758ce
 Comp1Name:Alinghi
 Comp1NameShort:Alinghi
 Comp1Color:00FF00
 Comp1Nationality:SUI
 Comp1Description:
 Comp1Handicap:1.0000000000
 Comp1HandicapDistance:0.00000
 Comp1StartTime:2014-10-02 12:02:00
 Comp1PictureUUID:64a7b348-83db-11e2-88c0-10bf48d758ce
 Comp1ClassUUID:648ee25a-83db-11e2-88c0-10bf48d758ce
 Comp1RouteUUID:09f125d0-2bc6-0132-1eee-10b11c4ed8fd
 Comp2UUID:64bbff7e-83db-11e2-88c0-10bf48d758ce
 Comp2Name:GAC Pindar
 Comp2NameShort:GAC Pindar
 Comp2Color:000080
 Comp2Nationality:AUS
 Comp2Description:
 Comp2Handicap:1.0000000000
 Comp2HandicapDistance:0.00000
 Comp2StartTime:2014-10-02 12:02:00
 Comp2PictureUUID:64c3a8fa-83db-11e2-88c0-10bf48d758ce
 Comp2ClassUUID:648ee25a-83db-11e2-88c0-10bf48d758ce
 Comp2RouteUUID:09f125d0-2bc6-0132-1eee-10b11c4ed8fd
 Comp3UUID:64da7c24-83db-11e2-88c0-10bf48d758ce
 Comp3Name:Realteam by Realstone
 Comp3NameShort:Realstone
 Comp3Color:000000
 Comp3Nationality:AFG
 Comp3Description:
 Comp3Handicap:1.0000000000
 Comp3HandicapDistance:0.00000
 Comp3StartTime:2014-10-02 12:02:00
 Comp3PictureUUID:64a7b348-83db-11e2-88c0-10bf48d758ce
 Comp3ClassUUID:648ee25a-83db-11e2-88c0-10bf48d758ce
 Comp3RouteUUID:09f125d0-2bc6-0132-1eee-10b11c4ed8fd
 Comp4UUID:65322500-83db-11e2-88c0-10bf48d758ce
 Comp4Name:Red Bull Sailing Team
 Comp4NameShort:Red Bull
 Comp4Color:008080
 Comp4Nationality:AUT
 Comp4Description:
 Comp4Handicap:1.0000000000
 Comp4HandicapDistance:0.00000
 Comp4StartTime:2014-10-02 12:02:00
 Comp4PictureUUID:653c1ab0-83db-11e2-88c0-10bf48d758ce
 Comp4ClassUUID:648ee25a-83db-11e2-88c0-10bf48d758ce
 Comp4RouteUUID:09f125d0-2bc6-0132-1eee-10b11c4ed8fd
 Comp5UUID:655bd56c-83db-11e2-88c0-10bf48d758ce
 Comp5Name:SAP Extreme Sailing Team
 Comp5NameShort:SAP
 Comp5Color:FFFFFF
 Comp5Nationality:DEN
 Comp5Description:
 Comp5Handicap:1.0000000000
 Comp5HandicapDistance:0.00000
 Comp5StartTime:2014-10-02 12:02:00
 Comp5PictureUUID:65637da8-83db-11e2-88c0-10bf48d758ce
 Comp5ClassUUID:648ee25a-83db-11e2-88c0-10bf48d758ce
 Comp5RouteUUID:09f125d0-2bc6-0132-1eee-10b11c4ed8fd
 Comp6UUID:657fa5a0-83db-11e2-88c0-10bf48d758ce
 Comp6Name:The Wave, Muscat
 Comp6NameShort:The Wave
 Comp6Color:800080
 Comp6Nationality:OMA
 Comp6Description:
 Comp6Handicap:1.0000000000
 Comp6HandicapDistance:0.00000
 Comp6StartTime:2014-10-02 12:02:00
 Comp6PictureUUID:65875138-83db-11e2-88c0-10bf48d758ce
 Comp6ClassUUID:648ee25a-83db-11e2-88c0-10bf48d758ce
 Comp6RouteUUID:09f125d0-2bc6-0132-1eee-10b11c4ed8fd
 Comp7UUID:93085e80-7ad9-0131-e5b3-60a44ce903c3
 Comp7Name:Emirates Team New Zealand
 Comp7NameShort:Emirates NZ
 Comp7Color:CC9900
 Comp7Nationality:NZL
 Comp7Description:
 Comp7Handicap:1.0000000000
 Comp7HandicapDistance:0.00000
 Comp7StartTime:2014-10-02 12:02:00
 Comp7PictureUUID:64c3a8fa-83db-11e2-88c0-10bf48d758ce
 Comp7ClassUUID:648ee25a-83db-11e2-88c0-10bf48d758ce
 Comp7RouteUUID:09f125d0-2bc6-0132-1eee-10b11c4ed8fd
 Comp8UUID:f097f4f0-7ad9-0131-e5b4-60a44ce903c3
 Comp8Name:Gazprom Team Russia
 Comp8NameShort:Team Russia
 Comp8Color:999900
 Comp8Nationality:RUS
 Comp8Description:
 Comp8Handicap:1.0000000000
 Comp8HandicapDistance:0.00000
 Comp8StartTime:2014-10-02 12:02:00
 Comp8ClassUUID:648ee25a-83db-11e2-88c0-10bf48d758ce
 Comp8RouteUUID:09f125d0-2bc6-0132-1eee-10b11c4ed8fd
 Comp9UUID:19dc3eb0-7ada-0131-e5b5-60a44ce903c3
 Comp9Name:Groupama sailing team
 Comp9NameShort:Groupama
 Comp9Color:33CC00
 Comp9Nationality:AFG
 Comp9Description:
 Comp9Handicap:1.0000000000
 Comp9HandicapDistance:0.00000
 Comp9StartTime:2014-10-02 12:02:00
 Comp9ClassUUID:648ee25a-83db-11e2-88c0-10bf48d758ce
 Comp9RouteUUID:09f125d0-2bc6-0132-1eee-10b11c4ed8fd
 Comp10UUID:5e15e7c0-7ada-0131-e5b6-60a44ce903c3
 Comp10Name:J.P. Morgan BAR
 Comp10NameShort:J.P. Morgan
 Comp10Color:CCFF00
 Comp10Nationality:GBR
 Comp10Description:
 Comp10Handicap:1.0000000000
 Comp10HandicapDistance:0.00000
 Comp10StartTime:2014-10-02 12:02:00
 Comp10ClassUUID:648ee25a-83db-11e2-88c0-10bf48d758ce
 Comp10RouteUUID:09f125d0-2bc6-0132-1eee-10b11c4ed8fd
 Comp11UUID:84e68b70-7ada-0131-e5b7-60a44ce903c3
 Comp11Name:Oman Air
 Comp11NameShort:Oman Air
 Comp11Color:CCFF99
 Comp11Nationality:OMA
 Comp11Description:
 Comp11Handicap:1.0000000000
 Comp11HandicapDistance:0.00000
 Comp11StartTime:2014-10-02 12:02:00
 Comp11PictureUUID:65875138-83db-11e2-88c0-10bf48d758ce
 Comp11ClassUUID:648ee25a-83db-11e2-88c0-10bf48d758ce
 Comp11RouteUUID:09f125d0-2bc6-0132-1eee-10b11c4ed8fd
 ControlPoint1UUID:1100ea60-7adb-0131-e5b8-60a44ce903c3
 ControlPoint1Name:Red-Green
 ControlPoint1HasTwoPoints:1
 ControlPoint1ShortName:RG
 ControlPoint1DataSheet:P1.Type=Buoy###BREAKLINE###P1.Color=Red###BREAKLINE###P1.Shape=Conical###BREAKLINE###P1.Name=Red###BREAKLINE###P1.UUID=5427c7d2-83be-11e2-88c0-10bf48d758ce###BREAKLINE###P2.Type=Buoy###BREAKLINE###P2.Color=Green###BREAKLINE###P2.Shape=Conical###BREAKLINE###P2.Name=Green###BREAKLINE###P2.UUID=785c3e44-83be-11e2-88c0-10bf48d758ce###BREAKLINE###
 ControlPoint1Mark1Lon:7.273181
 ControlPoint1Mark1Lat:43.688370
 ControlPoint1Mark2Lon:7.272257
 ControlPoint1Mark2Lat:43.687305
 ControlPoint2UUID:1286f15e-83be-11e2-88c0-10bf48d758ce
 ControlPoint2Name:Blue
 ControlPoint2HasTwoPoints:0
 ControlPoint2ShortName:Bl
 ControlPoint2DataSheet:Name=Blue###BREAKLINE###Type=Buoy###BREAKLINE###Color=Blue###BREAKLINE###Shape=Conical
 ControlPoint2Mark1Lon:7.269418
 ControlPoint2Mark1Lat:43.687290
 ControlPoint3UUID:1a94c6a0-7adc-0131-e5f4-60a44ce903c3
 ControlPoint3Name:Black Conical-Blue
 ControlPoint3HasTwoPoints:1
 ControlPoint3ShortName:BB
 ControlPoint3DataSheet:P1.Type=Buoy###BREAKLINE###P1.Color=Black###BREAKLINE###P1.Shape=Conical###BREAKLINE###P1.Pattern=Checkered###BREAKLINE###P1.Name=Black Conical###BREAKLINE###P1.UUID=d78695ea-83be-11e2-88c0-10bf48d758ce###BREAKLINE###P2.Type=Buoy###BREAKLINE###P2.Color=Blue###BREAKLINE###P2.Shape=Conical###BREAKLINE###P2.Name=Blue###BREAKLINE###P2.UUID=1286f15e-83be-11e2-88c0-10bf48d758ce###BREAKLINE###
 ControlPoint3Mark1Lon:7.272432
 ControlPoint3Mark1Lat:43.692131
 ControlPoint3Mark2Lon:7.269418
 ControlPoint3Mark2Lat:43.687290
 ControlPoint4UUID:2ce99970-2c47-0132-20ce-10b11c4ed8fd
 ControlPoint4Name:Black Conical-White P
 ControlPoint4HasTwoPoints:1
 ControlPoint4ShortName:F
 ControlPoint4DataSheet:P1.Type=Buoy###BREAKLINE###P1.Color=Black###BREAKLINE###P1.Shape=Conical###BREAKLINE###P1.Pattern=Checkered###BREAKLINE###P1.Name=Black Conical###BREAKLINE###P1.UUID=d78695ea-83be-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###
 ControlPoint4Mark1Lon:7.272432
 ControlPoint4Mark1Lat:43.692131
 ControlPoint4Mark2Lon:7.271063
 ControlPoint4Mark2Lat:43.691803
 ControlPoint5UUID:2dc7d9d0-7b84-0131-b9c3-10b11c4ed8fd
 ControlPoint5Name:Black Cylinder - Black Conical
 ControlPoint5HasTwoPoints:1
 ControlPoint5ShortName:BB
 ControlPoint5DataSheet: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=Black###BREAKLINE###P2.Shape=Conical###BREAKLINE###P2.Pattern=Checkered###BREAKLINE###P2.Name=Black Conical###BREAKLINE###P2.UUID=d78695ea-83be-11e2-88c0-10bf48d758ce
 ControlPoint5Mark1Lon:7.269445
 ControlPoint5Mark1Lat:43.687302
 ControlPoint5Mark2Lon:7.272432
 ControlPoint5Mark2Lat:43.692131
 ControlPoint6UUID:2e37b410-7adc-0131-e5fe-60a44ce903c3
 ControlPoint6Name:Black Conical-Yellow (white S)
 ControlPoint6HasTwoPoints:1
 ControlPoint6ShortName:BY
 ControlPoint6DataSheet:P1.Type=Buoy###BREAKLINE###P1.Color=Black###BREAKLINE###P1.Shape=Conical###BREAKLINE###P1.Pattern=Checkered###BREAKLINE###P1.Name=Black Conical###BREAKLINE###P1.UUID=d78695ea-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###
 ControlPoint6Mark1Lon:7.272432
 ControlPoint6Mark1Lat:43.692131
 ControlPoint6Mark2Lon:7.269320
 ControlPoint6Mark2Lat:43.687366
 ControlPoint7UUID:3240586c-83c0-11e2-88c0-10bf48d758ce
 ControlPoint7Name:Finish Pole
 ControlPoint7HasTwoPoints:0
 ControlPoint7ShortName:F
 ControlPoint7DataSheet:Color=Black###BREAKLINE###Type=Landmark###BREAKLINE###Name=Finish Pole
 ControlPoint7Mark1Lon:7.271467
 ControlPoint7Mark1Lat:43.694897
 ControlPoint8UUID:37cb36e0-7adb-0131-e5c2-60a44ce903c3
 ControlPoint8Name:Red-Blue
 ControlPoint8HasTwoPoints:1
 ControlPoint8ShortName:RB
 ControlPoint8DataSheet:P1.Type=Buoy###BREAKLINE###P1.Color=Red###BREAKLINE###P1.Shape=Conical###BREAKLINE###P1.Name=Red###BREAKLINE###P1.UUID=5427c7d2-83be-11e2-88c0-10bf48d758ce###BREAKLINE###P2.Type=Buoy###BREAKLINE###P2.Color=Blue###BREAKLINE###P2.Shape=Conical###BREAKLINE###P2.Name=Blue###BREAKLINE###P2.UUID=1286f15e-83be-11e2-88c0-10bf48d758ce###BREAKLINE###
 ControlPoint8Mark1Lon:7.273181
 ControlPoint8Mark1Lat:43.688370
 ControlPoint8Mark2Lon:7.269418
 ControlPoint8Mark2Lat:43.687290
 ControlPoint9UUID:3e6c1c94-83bf-11e2-88c0-10bf48d758ce
 ControlPoint9Name:Race Committee
 ControlPoint9HasTwoPoints:0
 ControlPoint9ShortName:RC
 ControlPoint9DataSheet:Type=StartBoat###BREAKLINE###Name=Race Committee
 ControlPoint9Mark1Lon:7.267022
 ControlPoint9Mark1Lat:43.691895
 ControlPoint10UUID:3fdd2402-83be-11e2-88c0-10bf48d758ce
 ControlPoint10Name:Yellow
 ControlPoint10HasTwoPoints:0
 ControlPoint10ShortName:Y
 ControlPoint10DataSheet:Type=Buoy###BREAKLINE###Color=Yellow###BREAKLINE###Shape=Conical###BREAKLINE###Name=Yellow
 ControlPoint10Mark1Lon:7.269320
 ControlPoint10Mark1Lat:43.687366
 ControlPoint11UUID:4c304720-7adc-0131-e608-60a44ce903c3
 ControlPoint11Name:Black Conical-Red
 ControlPoint11HasTwoPoints:1
 ControlPoint11ShortName:BR
 ControlPoint11DataSheet:P1.Type=Buoy###BREAKLINE###P1.Color=Black###BREAKLINE###P1.Shape=Conical###BREAKLINE###P1.Pattern=Checkered###BREAKLINE###P1.Name=Black Conical###BREAKLINE###P1.UUID=d78695ea-83be-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###
 ControlPoint11Mark1Lon:7.272432
 ControlPoint11Mark1Lat:43.692131
 ControlPoint11Mark2Lon:7.273181
 ControlPoint11Mark2Lat:43.688370
 ControlPoint12UUID:4e0c2a90-7adb-0131-e5cc-60a44ce903c3
 ControlPoint12Name:Red-Yellow
 ControlPoint12HasTwoPoints:1
 ControlPoint12ShortName:RY
 ControlPoint12DataSheet:P1.Type=Buoy###BREAKLINE###P1.Color=Red###BREAKLINE###P1.Shape=Conical###BREAKLINE###P1.Name=Red###BREAKLINE###P1.UUID=5427c7d2-83be-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###
 ControlPoint12Mark1Lon:7.273181
 ControlPoint12Mark1Lat:43.688370
 ControlPoint12Mark2Lon:7.269320
 ControlPoint12Mark2Lat:43.687366
 ControlPoint13UUID:5427c7d2-83be-11e2-88c0-10bf48d758ce
 ControlPoint13Name:Red
 ControlPoint13HasTwoPoints:0
 ControlPoint13ShortName:R
 ControlPoint13DataSheet:Type=Buoy###BREAKLINE###Color=Red###BREAKLINE###Shape=Conical###BREAKLINE###Name=Red
 ControlPoint13Mark1Lon:7.273181
 ControlPoint13Mark1Lat:43.688370
 ControlPoint14UUID:621831d0-7adc-0131-e612-60a44ce903c3
 ControlPoint14Name:Black Conical-Green
 ControlPoint14HasTwoPoints:1
 ControlPoint14ShortName:BG
 ControlPoint14DataSheet:P1.Type=Buoy###BREAKLINE###P1.Color=Black###BREAKLINE###P1.Shape=Conical###BREAKLINE###P1.Pattern=Checkered###BREAKLINE###P1.Name=Black Conical###BREAKLINE###P1.UUID=d78695ea-83be-11e2-88c0-10bf48d758ce###BREAKLINE###P2.Type=Buoy###BREAKLINE###P2.Color=Green###BREAKLINE###P2.Shape=Conical###BREAKLINE###P2.Name=Green###BREAKLINE###P2.UUID=785c3e44-83be-11e2-88c0-10bf48d758ce###BREAKLINE###
 ControlPoint14Mark1Lon:7.272432
 ControlPoint14Mark1Lat:43.692131
 ControlPoint14Mark2Lon:7.272257
 ControlPoint14Mark2Lat:43.687305
 ControlPoint15UUID:77b9e620-7adb-0131-e5d6-60a44ce903c3
 ControlPoint15Name:Green-Blue
 ControlPoint15HasTwoPoints:1
 ControlPoint15ShortName:GB
 ControlPoint15DataSheet: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=Blue###BREAKLINE###P2.Shape=Conical###BREAKLINE###P2.Name=Blue###BREAKLINE###P2.UUID=1286f15e-83be-11e2-88c0-10bf48d758ce###BREAKLINE###
 ControlPoint15Mark1Lon:7.272257
 ControlPoint15Mark1Lat:43.687305
 ControlPoint15Mark2Lon:7.269418
 ControlPoint15Mark2Lat:43.687290
 ControlPoint16UUID:785c3e44-83be-11e2-88c0-10bf48d758ce
 ControlPoint16Name:Green
 ControlPoint16HasTwoPoints:0
 ControlPoint16ShortName:G
 ControlPoint16DataSheet:Type=Buoy###BREAKLINE###Color=Green###BREAKLINE###Shape=Conical###BREAKLINE###Name=Green
 ControlPoint16Mark1Lon:7.272257
 ControlPoint16Mark1Lat:43.687305
 ControlPoint17UUID:7d9d1730-b3e8-0131-1d10-10b11c4ed8fd
 ControlPoint17Name:Race Committee - Finish Pole
 ControlPoint17HasTwoPoints:1
 ControlPoint17ShortName:RF
 ControlPoint17DataSheet:P1.Type=StartBoat###BREAKLINE###P1.Name=Race Committee###BREAKLINE###P1.UUID=3e6c1c94-83bf-11e2-88c0-10bf48d758ce###BREAKLINE###P2.Color=Black###BREAKLINE###P2.Type=Landmark###BREAKLINE###P2.Name=Finish Pole###BREAKLINE###P2.UUID=3240586c-83c0-11e2-88c0-10bf48d758ce
 ControlPoint17Mark1Lon:7.267022
 ControlPoint17Mark1Lat:43.691895
 ControlPoint17Mark2Lon:7.271342
 ControlPoint17Mark2Lat:43.694851
 ControlPoint18UUID:88ef6d40-7adc-0131-e61c-60a44ce903c3
 ControlPoint18Name:Finish Pole-Cylinder
 ControlPoint18HasTwoPoints:1
 ControlPoint18ShortName:F
 ControlPoint18DataSheet: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=Cylinder###BREAKLINE###P2.Pattern=Checkered###BREAKLINE###P2.Name=Black Cylinder###BREAKLINE###P2.UUID=b153dfd6-83be-11e2-88c0-10bf48d758ce###BREAKLINE###
 ControlPoint18Mark1Lon:7.271342
 ControlPoint18Mark1Lat:43.694851
 ControlPoint18Mark2Lon:7.269445
 ControlPoint18Mark2Lat:43.687302
 ControlPoint19UUID:8f9a4ee0-7adb-0131-e5e0-60a44ce903c3
 ControlPoint19Name:Green-Yellow
 ControlPoint19HasTwoPoints:1
 ControlPoint19ShortName:GY
 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###
 ControlPoint19Mark1Lon:7.272257
 ControlPoint19Mark1Lat:43.687305
 ControlPoint19Mark2Lon:7.269320
 ControlPoint19Mark2Lat:43.687366
 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###
 ControlPoint24Mark1Lon:7.269445
 ControlPoint24Mark1Lat:43.687302
 ControlPoint24Mark2Lon:7.269320
 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###
 ControlPoint27Mark1Lon:7.268352
 ControlPoint27Mark1Lat:43.691936
 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
 ControlPoint29Mark1Lon:7.271063
 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###
 ControlPoint30Mark1Lon:7.267022
 ControlPoint30Mark1Lat:43.691895
 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) {
@@ -56,15 +67,21 @@ public abstract class ExportAction {
        return service;
    }
    public String getResultXML() {
        return resultingXMLData;
    }
    public Leaderboard getLeaderboard() throws IOException, ServletException {
        if (!useProvidedLeaderboard) {
            final String leaderboardName = getAttribute("name");
            if (leaderboardName == null) {
                throw new ServletException("Use the name= parameter to specify the leaderboard");
            }
-        final Leaderboard leaderboard = getService().getLeaderboardByName(leaderboardName); 
+            leaderboard = getService().getLeaderboardByName(leaderboardName); 
            if (leaderboard == null) {
                throw new ServletException("Leaderboard " + leaderboardName + " not found.");
            }
        }
        return leaderboard;
    }
@@ -315,14 +332,23 @@ public abstract class ExportAction {
        format.setEncoding("UTF-8");
        XMLOutputter xmlOutputter = new XMLOutputter(format);
        if (!useProvidedLeaderboard) {
            res.setContentType("text/xml");
            res.addHeader("Content-Disposition", "attachment; filename=" + fileName);
            try {
                xmlOutputter.output(element, res.getOutputStream());
            } catch (IOException e) {
                e.printStackTrace();
            }
        } else {
            StringWriter resultStringWriter = new StringWriter();
            try {
                xmlOutputter.output(element, resultStringWriter);
                resultingXMLData = resultStringWriter.toString();
            } catch (IOException e) {
                e.printStackTrace();
            }
        }
    }
    protected long handleValue(TimePoint timepoint) {
@@ -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>