Examples of de.lmu.ifi.dbs.elki.math.statistics.distribution.Distribution

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

Examples of de.lmu.ifi.dbs.elki.math.statistics.distribution.Distribution

de.lmu.ifi.dbs.elki.math.statistics.distribution.Distribution
Interface for a simple distribution generator with a PDF, i.e. it can also compute a density @author Erich Schubert

          outStream.write("## Clipping: " + cmin.toString() + " - " + cmax.toString() + LINE_SEPARATOR);
        }
        outStream.write("## Density correction factor: " + cursclus.getDensityCorrection() + LINE_SEPARATOR);
        outStream.write("## Generators:" + LINE_SEPARATOR);
        for(int i = 0; i < cursclus.getDim(); i++) {
          Distribution gen = cursclus.getDistribution(i);
          outStream.write("##   " + gen.toString() + LINE_SEPARATOR);
        }
        if(cursclus.getTransformation() != null && cursclus.getTransformation().getTransformation() != null) {
          outStream.write("## Affine transformation matrix:" + LINE_SEPARATOR);
          outStream.write(FormatUtil.format(cursclus.getTransformation().getTransformation(), "## ") + LINE_SEPARATOR);
        }

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      max = Double.parseDouble(maxstr);
    }


    // *** new uniform generator
    Random random = cluster.getNewRandomGenerator();
    Distribution generator = new UniformDistribution(min, max, random);
    cluster.addGenerator(generator);


    // TODO: check for unknown attributes.
    for(Node child : new XMLNodeIterator(cur.getFirstChild())) {
      if(child.getNodeType() == Node.ELEMENT_NODE) {

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      stddev = Double.parseDouble(stddevstr);
    }


    // *** New normal distribution generator
    Random random = cluster.getNewRandomGenerator();
    Distribution generator = new NormalDistribution(mean, stddev, random);
    cluster.addGenerator(generator);


    // TODO: check for unknown attributes.
    for(Node child : new XMLNodeIterator(cur.getFirstChild())) {
      if(child.getNodeType() == Node.ELEMENT_NODE) {

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      theta = Double.parseDouble(thetastr);
    }


    // *** New normal distribution generator
    Random random = cluster.getNewRandomGenerator();
    Distribution generator = new GammaDistribution(k, theta, random);
    cluster.addGenerator(generator);


    // TODO: check for unknown attributes.
    for(Node child : new XMLNodeIterator(cur.getFirstChild())) {
      if(child.getNodeType() == Node.ELEMENT_NODE) {

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        }
        final int dim = tv.getDimensionality();
        double lensq = 0.0;
        int norm = 0;
        for(int i = 0; i < dim; i++) {
          Distribution dist = gen.getDistribution(i);
          if(dist instanceof NormalDistribution) {
            NormalDistribution d = (NormalDistribution) dist;
            double delta = (tv.get(i) - d.getMean()) / d.getStddev();
            lensq += delta * delta;
            norm += 1;

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Related Classes of de.lmu.ifi.dbs.elki.math.statistics.distribution.Distribution

de.lmu.ifi.dbs.elki.algorithm.outlier.trivial.TrivialGeneratedOutlier

de.lmu.ifi.dbs.elki.application.GeneratorXMLSpec

de.lmu.ifi.dbs.elki.datasource.GeneratorXMLDatabaseConnection

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