/* (non-Javadoc)
* @see java.lang.Runnable#run()
*/
@Override
public void run() {
ICluster cluster = ClusterManager.getCluster();
while (true) {
try {
Thread.sleep(3000); // wait 3 sec.
} catch (InterruptedException e) {
}
try {
ITestClusterService service =
(ITestClusterService) cluster.getClusterService(ITestClusterService.SERVICE_NAME);
if (service == null) {
System.err.println("ERROR: service is null");
} else {
long nextNumber = service.takeNextNumber();
// System.out.println("Next Number is: " + nextNumber);
cluster.sendEvent(
new ClusterEvent("TestNumberSequence", "NumberToken", new Long(nextNumber)), true);
StartTestInstance.addNumber(nextNumber);
}
} catch (Throwable t) {
t.printStackTrace();
}
}
}
/**
* this is what a Mapper does
*
* @param valuein @return iterator over mapped key values
*/
@Override
public Iterable<KeyValueObject<PeakMZKey, ICluster>> mapValues(final ICluster valuein) {
double precursorMZ = valuein.getPrecursorMz();
List<KeyValueObject<PeakMZKey, ICluster>> ret =
new ArrayList<KeyValueObject<PeakMZKey, ICluster>>();
List<ISpectrum> clusteredSpectra = valuein.getClusteredSpectra();
if (!clusteredSpectra.isEmpty() && precursorMZ < MZIntensityUtilities.HIGHEST_USABLE_MZ) {
for (ISpectrum match : clusteredSpectra) {
ICluster cluster = ClusterUtilities.asCluster(match);
for (int peakMz : match.asMajorPeakMZs(Defaults.getMajorPeakCount())) {
PeakMZKey mzKey = new PeakMZKey(peakMz, precursorMZ);
ret.add(new KeyValueObject<PeakMZKey, ICluster>(mzKey, cluster));
}
}
}
return ret;
}
private ICluster mergeCluster(ProximityMatrix m, ICluster c1, ICluster c2) {
// la matrice di prossimità si aggiorna sostituendo i due cluster con un nuovo cluster
// stores distances between the given clusters and each other clusters
Map<ICluster, Float> c1Distances = new HashMap<ICluster, Float>();
Map<ICluster, Float> c2Distances = new HashMap<ICluster, Float>();
for (ICluster cluster : m.getClusters()) {
// does not consider removed clusters
if (!cluster.equals(c1) && !cluster.equals(c2)) {
c1Distances.put(cluster, m.getClustersDistance(c1, cluster));
c2Distances.put(cluster, m.getClustersDistance(c2, cluster));
}
}
// removes the clusters from the matrix
m.removeClusters(c1, c2);
// generates the merged cluster and adds it to the matrix
ICluster mergedCluster = this.getMergedCluster(c1, c2);
m.addCluster(mergedCluster);
// le distanze da tutti gli altri cluster sono date dalla minima delle distanze relative ai
// cluster precedenti
// updates new cluster's distances
for (ICluster cluster : c1Distances.keySet()) {
float c1Distance = c1Distances.get(cluster);
float c2Distance = c2Distances.get(cluster);
float distance = c1Distance < c2Distance ? c1Distance : c2Distance;
m.setClustersDistance(mergedCluster, cluster, distance);
}
return mergedCluster;
}
