public double[] getPrecisions(double[] predictions, Sample sample, TieBreaker tieBreaker)
throws Exception {
RankingSample rankingSample = (RankingSample) sample;
int chunkSize = 1 + (rankingSample.numQueries / mapWorkers.getSize());
int offset = 0;
int workerCount = 0;
for (int i = 0; i < mapWorkers.getSize() && offset < rankingSample.numQueries; i++) {
int endOffset = offset + Math.min(rankingSample.numQueries - offset, chunkSize);
PrecisionWorker worker = mapWorkers.getTask(i);
workerCount++;
worker.init(rankingSample, predictions, offset, endOffset, tieBreaker);
BlockingThreadPoolExecutor.getInstance().execute(worker);
offset += chunkSize;
}
BlockingThreadPoolExecutor.getInstance().await();
double[] result = new double[maxLevels];
for (int i = 0; i < workerCount; i++) {
double[] localResult = mapWorkers.getTask(i).getResult();
for (int p = 0; p < maxLevels; p++) {
result[p] += localResult[p];
}
}
for (int p = 0; p < maxLevels; p++) {
result[p] /= rankingSample.numQueries;
}
return result;
}
public PrecisionEval(int maxDocsPerQuery, int maxLevels, double relevancyThreshold)
throws Exception {
super(true);
this.maxDocsPerQuery = maxDocsPerQuery;
this.maxLevels = maxLevels;
this.relevancyThreshold = relevancyThreshold;
int numWorkers = BlockingThreadPoolExecutor.getInstance().getMaximumPoolSize();
mapWorkers = new TaskCollection<PrecisionEval.PrecisionWorker>();
for (int i = 0; i < numWorkers; i++) {
mapWorkers.addTask(new PrecisionWorker());
}
}
