Examples with DoubleDoublePair de.lmu.ifi.dbs.elki.utilities.pairs.DoubleDoublePair used on opensource projects

Example 1 with DoubleDoublePair

use of de.lmu.ifi.dbs.elki.utilities.pairs.DoubleDoublePair in project elki by elki-project.

the class ComputeOutlierHistogram method evaluateOutlierResult.

/**
 * Evaluate a single outlier result as histogram.
 *
 * @param database Database to process
 * @param or Outlier result
 * @return Result
 */
public HistogramResult evaluateOutlierResult(Database database, OutlierResult or) {
    if (scaling instanceof OutlierScalingFunction) {
        OutlierScalingFunction oscaling = (OutlierScalingFunction) scaling;
        oscaling.prepare(or);
    }
    ModifiableDBIDs ids = DBIDUtil.newHashSet(or.getScores().getDBIDs());
    DBIDs outlierIds = DatabaseUtil.getObjectsByLabelMatch(database, positiveClassName);
    // first value for outliers, second for each object
    // If we have useful (finite) min/max, use these for binning.
    double min = scaling.getMin();
    double max = scaling.getMax();
    final ObjHistogram<DoubleDoublePair> hist;
    if (Double.isInfinite(min) || Double.isNaN(min) || Double.isInfinite(max) || Double.isNaN(max)) {
        hist = new AbstractObjDynamicHistogram<DoubleDoublePair>(bins) {

            @Override
            public DoubleDoublePair aggregate(DoubleDoublePair first, DoubleDoublePair second) {
                first.first += second.first;
                first.second += second.second;
                return first;
            }

            @Override
            protected DoubleDoublePair makeObject() {
                return new DoubleDoublePair(0., 0.);
            }

            @Override
            protected DoubleDoublePair cloneForCache(DoubleDoublePair data) {
                return new DoubleDoublePair(data.first, data.second);
            }

            @Override
            protected DoubleDoublePair downsample(Object[] data, int start, int end, int size) {
                DoubleDoublePair sum = new DoubleDoublePair(0, 0);
                for (int i = start; i < end; i++) {
                    DoubleDoublePair p = (DoubleDoublePair) data[i];
                    if (p != null) {
                        sum.first += p.first;
                        sum.second += p.second;
                    }
                }
                return sum;
            }
        };
    } else {
        hist = new AbstractObjStaticHistogram<DoubleDoublePair>(bins, min, max) {

            @Override
            protected DoubleDoublePair makeObject() {
                return new DoubleDoublePair(0., 0.);
            }

            @Override
            public void putData(double coord, DoubleDoublePair data) {
                DoubleDoublePair exist = get(coord);
                exist.first += data.first;
                exist.second += data.second;
            }
        };
    }
    // first fill histogram only with values of outliers
    DoubleDoublePair negative, positive;
    if (!splitfreq) {
        negative = new DoubleDoublePair(1. / ids.size(), 0);
        positive = new DoubleDoublePair(0, 1. / ids.size());
    } else {
        negative = new DoubleDoublePair(1. / (ids.size() - outlierIds.size()), 0);
        positive = new DoubleDoublePair(0, 1. / outlierIds.size());
    }
    ids.removeDBIDs(outlierIds);
    // fill histogram with values of each object
    for (DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) {
        double result = or.getScores().doubleValue(iter);
        result = scaling.getScaled(result);
        if (result > Double.NEGATIVE_INFINITY && result < Double.POSITIVE_INFINITY) {
            hist.putData(result, negative);
        }
    }
    for (DBIDIter iter = outlierIds.iter(); iter.valid(); iter.advance()) {
        double result = or.getScores().doubleValue(iter);
        result = scaling.getScaled(result);
        if (result > Double.NEGATIVE_INFINITY && result < Double.POSITIVE_INFINITY) {
            hist.putData(result, positive);
        }
    }
    Collection<double[]> collHist = new ArrayList<>(hist.getNumBins());
    for (ObjHistogram.Iter<DoubleDoublePair> iter = hist.iter(); iter.valid(); iter.advance()) {
        DoubleDoublePair data = iter.getValue();
        collHist.add(new double[] { iter.getCenter(), data.first, data.second });
    }
    return new HistogramResult("Outlier Score Histogram", "outlier-histogram", collHist);
}