/** * Add a single point to the list (this does not compute the hull!) * * @param point Point to add */ public void add(double... point) { if(this.ok) { this.points = new ArrayList<>(this.points); this.ok = false; } this.points.add(point); // Update data set extends minmaxX.put(point[0]); minmaxY.put(point[1]); }
@Override public void map(DBIDRef id) { minmax.put(input.doubleValue()); } }
@Override public void map(DBIDRef id) { minmax.put(input.doubleValue()); } }
@Override public void map(DBIDRef id) { minmax.put(input.doubleValue()); } }
private void storeCBLOFScore(WritableDoubleDataStore cblofs, DoubleMinMax cblofMinMax, double cblof, DBIDIter iter) { cblofs.putDouble(iter, cblof); cblofMinMax.put(cblof); }
@Override public <A> void prepare(A array, NumberArrayAdapter<?, A> adapter) { DoubleMinMax mm = new DoubleMinMax(); final int size = adapter.size(array); for (int i = 0; i < size; i++) { double val = adapter.getDouble(array, i); if (!Double.isNaN(val) && !Double.isInfinite(val)) { mm.put(val); } } max = mm.getMax(); mlogmax = -Math.log(mm.getMin() / max); } }
@Override public <A> void prepare(A array, NumberArrayAdapter<?, A> adapter) { DoubleMinMax mm = new DoubleMinMax(); final int size = adapter.size(array); for(int i = 0; i < size; i++) { double val = adapter.getDouble(array, i); if(!Double.isNaN(val) && !Double.isInfinite(val)) { mm.put(val); } } max = mm.getMax(); mlogmax = -FastMath.log(mm.getMin() / max); } }
@Override public <A> UniformDistribution estimate(A data, NumberArrayAdapter<?, A> adapter) { final int len = adapter.size(data); DoubleMinMax mm = new DoubleMinMax(); for (int i = 0; i < len; i++) { final double val = adapter.getDouble(data, i); if (val > Double.NEGATIVE_INFINITY && val < Double.POSITIVE_INFINITY) { mm.put(val); } } return estimate(mm); }
@Override public <A> void prepare(A array, NumberArrayAdapter<?, A> adapter) { DoubleMinMax mm = new DoubleMinMax(); final int size = adapter.size(array); for(int i = 0; i < size; i++) { double val = adapter.getDouble(array, i); if(!Double.isNaN(val) && !Double.isInfinite(val)) { mm.put(val); } } max = mm.getMax(); mlogmax = -FastMath.log(mm.getMin() / max); } }
@Override public void prepare(OutlierResult or) { DoubleMinMax mm = new DoubleMinMax(); DoubleRelation scores = or.getScores(); for (DBIDIter id = scores.iterDBIDs(); id.valid(); id.advance()) { double val = scores.doubleValue(id); if (!Double.isNaN(val) && !Double.isInfinite(val)) { mm.put(val); } } max = mm.getMax(); mlogmax = -Math.log(mm.getMin() / max); }
@Override public <A> UniformDistribution estimate(A data, NumberArrayAdapter<?, A> adapter) { final int len = adapter.size(data); DoubleMinMax mm = new DoubleMinMax(); for (int i = 0; i < len; i++) { final double val = adapter.getDouble(data, i); if (val > Double.NEGATIVE_INFINITY && val < Double.POSITIVE_INFINITY) { mm.put(val); } } return estimate(mm); }
@Override public <A> UniformDistribution estimate(A data, NumberArrayAdapter<?, A> adapter) { final int len = adapter.size(data); DoubleMinMax mm = new DoubleMinMax(); for (int i = 0; i < len; i++) { final double val = adapter.getDouble(data, i); if (val > Double.NEGATIVE_INFINITY && val < Double.POSITIVE_INFINITY) { mm.put(val); } } return estimate(mm); }
@Override public void prepare(OutlierResult or) { DoubleMinMax mm = new DoubleMinMax(); DoubleRelation scores = or.getScores(); for(DBIDIter id = scores.iterDBIDs(); id.valid(); id.advance()) { double val = scores.doubleValue(id); if(!Double.isNaN(val) && !Double.isInfinite(val)) { mm.put(val); } } max = mm.getMax(); mlogmax = -FastMath.log(mm.getMin() / max); }
@Override public void prepare(OutlierResult or) { DoubleMinMax mm = new DoubleMinMax(); DoubleRelation scores = or.getScores(); for(DBIDIter id = scores.iterDBIDs(); id.valid(); id.advance()) { double val = scores.doubleValue(id); if(!Double.isNaN(val) && !Double.isInfinite(val)) { mm.put(val); } } max = mm.getMax(); mlogmax = -FastMath.log(mm.getMin() / max); }
@Override public <A> UniformDistribution estimate(A data, NumberArrayAdapter<?, A> adapter) { final int len = adapter.size(data); DoubleMinMax mm = new DoubleMinMax(); for (int i = 0; i < len; i++) { final double val = adapter.getDouble(data, i); if (val > Double.NEGATIVE_INFINITY && val < Double.POSITIVE_INFINITY) { mm.put(val); } } return estimate(mm.getMin(), mm.getMax(), len); }
@Override public <A> UniformDistribution estimate(A data, NumberArrayAdapter<?, A> adapter) { final int len = adapter.size(data); DoubleMinMax mm = new DoubleMinMax(); for (int i = 0; i < len; i++) { final double val = adapter.getDouble(data, i); if (val > Double.NEGATIVE_INFINITY && val < Double.POSITIVE_INFINITY) { mm.put(val); } } return estimate(mm.getMin(), mm.getMax(), len); }
@Override public <A> UniformDistribution estimate(A data, NumberArrayAdapter<?, A> adapter) { final int len = adapter.size(data); DoubleMinMax mm = new DoubleMinMax(); for (int i = 0; i < len; i++) { final double val = adapter.getDouble(data, i); if (val > Double.NEGATIVE_INFINITY && val < Double.POSITIVE_INFINITY) { mm.put(val); } } return estimate(mm.getMin(), mm.getMax(), len); }