Package de.lmu.ifi.dbs.elki.math

Examples of de.lmu.ifi.dbs.elki.math.DoubleMinMax

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    Element layer = SVGUtil.svgElement(svgp.getDocument(), SVGConstants.SVG_G_TAG);
    final String transform = SVGUtil.makeMarginTransform(task.getWidth(), task.getHeight(), sizex, sizey, margin);
    SVGUtil.setAtt(layer, SVGConstants.SVG_TRANSFORM_ATTRIBUTE, transform);

    // determine scaling
    DoubleMinMax minmaxx = new DoubleMinMax();
    DoubleMinMax minmaxy = new DoubleMinMax();
    for(DoubleDoublePair pair : curve) {
      minmaxx.put(pair.first);
      minmaxy.put(pair.second);
    }
    LinearScale scalex = new LinearScale(minmaxx.getMin(), minmaxx.getMax());
    LinearScale scaley = new LinearScale(minmaxy.getMin(), minmaxy.getMax());
    // plot the line
    SVGPath path = new SVGPath();
    for(DoubleDoublePair pair : curve) {
      final double x = scalex.getScaled(pair.first);
      final double y = 1 - scaley.getScaled(pair.second);
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    final String transform = SVGUtil.makeMarginTransform(task.getWidth(), task.getHeight(), sizex, sizey, margin);
    SVGUtil.setAtt(layer, SVGConstants.SVG_TRANSFORM_ATTRIBUTE, transform);
   
    // find maximum, determine step size
    Integer dim = null;
    DoubleMinMax xminmax = new DoubleMinMax();
    DoubleMinMax yminmax = new DoubleMinMax();
    for(NumberVector<?, ?> vec : curve) {
      xminmax.put(vec.doubleValue(1));
      if(dim == null) {
        dim = vec.getDimensionality();
      }
      else {
        // TODO: test and throw always
        assert (dim == vec.getDimensionality());
      }
      for(int i = 1; i < dim; i++) {
        yminmax.put(vec.doubleValue(i + 1));
      }
    }
    // Minimum should always start at 0 for histograms
    yminmax.put(0.0);
    // remove one dimension which are the x values.
    dim = dim - 1;

    int size = curve.size();
    double range = xminmax.getMax() - xminmax.getMin();
    double binwidth = range / (size - 1);

    LinearScale xscale = new LinearScale(xminmax.getMin() - binwidth / 2, xminmax.getMax() + binwidth / 2);
    LinearScale yscale = new LinearScale(yminmax.getMin(), yminmax.getMax());

    SVGPath[] path = new SVGPath[dim];
    for(int i = 0; i < dim; i++) {
      path[i] = new SVGPath(sizex * xscale.getScaled(xminmax.getMin() - binwidth / 2), sizey);
    }
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   *
   * @param order Cluster order to process
   * @return Scale for value range of cluster order
   */
  protected LinearScale computeScale(List<ClusterOrderEntry<D>> order) {
    DoubleMinMax range = new DoubleMinMax();
    // calculate range
    for(ClusterOrderEntry<D> coe : order) {
      double reach = distanceAdapter.getDoubleForEntry(coe);
      if(!Double.isInfinite(reach) && !Double.isNaN(reach)) {
        range.put(reach);
      }
    }
    // Ensure we have a valid range
    if(!range.isValid()) {
      range.put(0.0);
      range.put(1.0);
    }
    return new LinearScale(range.getMin(), range.getMax());
  }
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      double min = Double.MAX_VALUE;
      double max = Double.MIN_VALUE;
      for(DBID objID : data.iterDBIDs()) {
        O vec = data.get(objID);
        DoubleMinMax mm = VectorUtil.getRangeDouble(vec);
        min = Math.min(min, mm.getMin());
        max = Math.max(max, mm.getMax());
      }
      this.s = new LinearScale(min, max);

      this.frame.setTitle(distanceQuery.getClass().getSimpleName() + " - " + WINDOW_TITLE_BASE);
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   *
   * @param order Cluster order to process
   * @return Scale for value range of cluster order
   */
  protected LinearScale computeScale(List<ClusterOrderEntry<D>> order) {
    DoubleMinMax range = new DoubleMinMax();
    // calculate range
    for(ClusterOrderEntry<D> coe : order) {
      double reach = distanceAdapter.getDoubleForEntry(coe);
      if(!Double.isInfinite(reach) && !Double.isNaN(reach)) {
        range.put(reach);
      }
    }
    // Ensure we have a valid range
    if(range.isValid()) {
      range.put(0.0);
      range.put(1.0);
    }
    return new LinearScale(range.getMin(), range.getMax());
  }
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  public static <O extends NumberVector<?,? extends Number>> LinearScale[] calcScales(Relation<O> db) {
    if (db == null) {
      throw new AbortException("No database was given to Scales.calcScales.");
    }
    int dim = DatabaseUtil.dimensionality(db);
    DoubleMinMax minmax[] = DoubleMinMax.newArray(dim);
    LinearScale scales[] = new LinearScale[dim];
 
    // analyze data
    for(DBID objId : db.iterDBIDs()) {
      O v = db.get(objId);
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  }

  @Override
  public Pair<DoubleMinMax, DoubleMinMax> estimateViewport() {
    final int dim = proj.getDimensionality();
    DoubleMinMax minmaxx = new DoubleMinMax();
    DoubleMinMax minmaxy = new DoubleMinMax();

    // Origin
    Vector orig = new Vector(dim);
    orig = projectScaledToRender(orig);
    minmaxx.put(orig.get(0));
    minmaxy.put(orig.get(1));
    // Diagonal point
    Vector diag = new Vector(dim);
    for(int d2 = 0; d2 < dim; d2++) {
      diag.set(d2, 1);
    }
    diag = projectScaledToRender(diag);
    minmaxx.put(diag.get(0));
    minmaxy.put(diag.get(1));
    // Axis end points
    for(int d = 0; d < dim; d++) {
      Vector v = new Vector(dim);
      v.set(d, 1);
      Vector ax = projectScaledToRender(v);
      minmaxx.put(ax.get(0));
      minmaxy.put(ax.get(1));
    }
    return new Pair<DoubleMinMax, DoubleMinMax>(minmaxx, minmaxy);
  }
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    return actDim;
  }

  @Override
  public Pair<DoubleMinMax, DoubleMinMax> estimateViewport() {
    DoubleMinMax minmaxx = new DoubleMinMax();
    DoubleMinMax minmaxy = new DoubleMinMax();
    minmaxx.put(SCALE * .5);
    minmaxx.put(-SCALE * .5);
    minmaxy.put(SCALE * .5);
    minmaxy.put(-SCALE * .5);
    return new Pair<DoubleMinMax, DoubleMinMax>(minmaxx, minmaxy);
  }
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   * @param vec Vector to process.
   * @param <V> Vector type
   * @return [min, max]
   */
  public static <V extends NumberVector<?, ?>> DoubleMinMax getRangeDouble(V vec) {
    DoubleMinMax minmax = new DoubleMinMax();

    for(int i = 0; i < vec.getDimensionality(); i++) {
      minmax.put(vec.doubleValue(i + 1));
    }

    return minmax;
  }
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      WritableDataStore<Double> new_lofs = lofsAndMax.getFirst();
      for(DBID id : ids) {
        lofResult.getLofs().put(id, new_lofs.get(id));
      }
      // track the maximum value for normalization.
      DoubleMinMax new_lofminmax = lofsAndMax.getSecond();

      // Actualize meta info
      if(new_lofminmax.isValid() && lofResult.getResult().getOutlierMeta().getActualMaximum() < new_lofminmax.getMax()) {
        BasicOutlierScoreMeta scoreMeta = (BasicOutlierScoreMeta) lofResult.getResult().getOutlierMeta();
        scoreMeta.setActualMaximum(new_lofminmax.getMax());
      }

      if(new_lofminmax.isValid() && lofResult.getResult().getOutlierMeta().getActualMinimum() > new_lofminmax.getMin()) {
        BasicOutlierScoreMeta scoreMeta = (BasicOutlierScoreMeta) lofResult.getResult().getOutlierMeta();
        scoreMeta.setActualMinimum(new_lofminmax.getMin());
      }
    }
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