Package de.lmu.ifi.dbs.elki.utilities.scaling

Examples of de.lmu.ifi.dbs.elki.utilities.scaling.LinearScaling

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    else {
      if(min == 0.0 && max == 1.0) {
        innerScaling = new IdentityScaling();
      }
      else {
        innerScaling = new LinearScaling(1.0 / (max - min), -min);
      }
    }

    double posscore = 0.0;
    double negscore = 0.0;
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    double zoom = minmax.getMax() - minmax.getMin();
    if(zoom > 0.0) {
      zoom = 1. / zoom;
    }
    LinearScaling scale = new LinearScaling(zoom, -minmax.getMin() * zoom);
    BufferedImage img = new BufferedImage(size, size, BufferedImage.TYPE_INT_RGB);
    for(int x = 0; x < size; x++) {
      DBID id1 = order.get(x);
      for(int y = x; y < size; y++) {
        DBID id2 = order.get(y);
        double ddist = dq.distance(id1, id2).doubleValue();
        if(ddist > 0.0) {
          ddist = scale.getScaled(ddist);
        }
        // Apply extra scaling
        if(scaling != null) {
          ddist = scaling.getScaled(ddist);
        }
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    else {
      if(min == 0.0 && max == 1.0) {
        innerScaling = new IdentityScaling();
      }
      else {
        innerScaling = new LinearScaling(1.0 / (max - min), -min);
      }
    }

    double posscore = 0.0;
    double negscore = 0.0;
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    double zoom = minmax.getMax() - minmax.getMin();
    if(zoom > 0.0) {
      zoom = 1. / zoom;
    }
    LinearScaling scale = new LinearScaling(zoom, -minmax.getMin() * zoom);
    BufferedImage img = new BufferedImage(size, size, BufferedImage.TYPE_INT_RGB);
    for(int x = 0; x < size; x++) {
      DBID id1 = order.get(x);
      for(int y = x; y < size; y++) {
        DBID id2 = order.get(y);
        double ddist = dq.distance(id1, id2).doubleValue();
        if(ddist > 0.0) {
          ddist = scale.getScaled(ddist);
        }
        // Apply extra scaling
        if(scaling != null) {
          ddist = scaling.getScaled(ddist);
        }
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    }

    logger.verbose(minmax.toString());

    boolean hasneg = (minmax.getMin() < -1E-3);
    LinearScaling scale;
    if(!hasneg) {
      scale = new LinearScaling(minmax);
    }
    else {
      scale = LinearScaling.fromMinMax(0.0, Math.max(minmax.getMax(), -minmax.getMin()));
    }

    BufferedImage img = new BufferedImage(size, size, BufferedImage.TYPE_INT_RGB);
    for(int x = 0; x < size; x++) {
      for(int y = x; y < size; y++) {
        double val = data[x][y];
        val = scale.getScaled(val);
        // Compute color:
        final int col;
        {
          if(!hasneg) {
            int ival = 0xFF & (int) (255 * Math.max(0, val));
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Related Classes of de.lmu.ifi.dbs.elki.utilities.scaling.LinearScaling

  • de.lmu.ifi.dbs.elki.application.greedyensemble.VisualizePairwiseGainMatrix
  • de.lmu.ifi.dbs.elki.evaluation.outlier.JudgeOutlierScores
  • de.lmu.ifi.dbs.elki.evaluation.similaritymatrix.ComputeSimilarityMatrixImage
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