public double cindex()

in samoa-api/src/main/java/org/apache/samoa/evaluation/measures/StatisticalCollection.java [118:184]
59 lines of code
15 McCabe index (conditional complexity)

  public double cindex(Clustering clustering, ArrayList<DataPoint> points) {
    int numClusters = clustering.size();
    double withinClustersDistance = 0;
    int numDistancesWithin = 0;
    double numDistances = 0;

    // double[] withinClusters = new double[numClusters];
    double[] minWithinClusters = new double[numClusters];
    double[] maxWithinClusters = new double[numClusters];
    ArrayList<Integer>[] pointsInClusters = new ArrayList[numClusters];
    for (int c = 0; c < numClusters; c++) {
      pointsInClusters[c] = new ArrayList<>();
      minWithinClusters[c] = Double.MAX_VALUE;
      maxWithinClusters[c] = Double.MIN_VALUE;
    }

    for (int p = 0; p < points.size(); p++) {
      for (int c = 0; c < clustering.size(); c++) {
        if (clustering.get(c).getInclusionProbability(points.get(p)) > 0.8) {
          pointsInClusters[c].add(p);
          numDistances++;
        }
      }
    }

    // calc within cluster distances + min and max values
    for (int c = 0; c < numClusters; c++) {
      int numDistancesInC = 0;
      ArrayList<Integer> pointsInC = pointsInClusters[c];
      for (int p = 0; p < pointsInC.size(); p++) {
        DataPoint point = points.get(pointsInC.get(p));
        for (int p1 = p + 1; p1 < pointsInC.size(); p1++) {
          numDistancesWithin++;
          numDistancesInC++;
          DataPoint point1 = points.get(pointsInC.get(p1));
          double dist = point.getDistance(point1);
          withinClustersDistance += dist;
          if (minWithinClusters[c] > dist)
            minWithinClusters[c] = dist;
          if (maxWithinClusters[c] < dist)
            maxWithinClusters[c] = dist;
        }
      }
    }

    double minWithin = Double.MAX_VALUE;
    double maxWithin = Double.MIN_VALUE;
    for (int c = 0; c < numClusters; c++) {
      if (minWithinClusters[c] < minWithin)
        minWithin = minWithinClusters[c];
      if (maxWithinClusters[c] > maxWithin)
        maxWithin = maxWithinClusters[c];
    }

    double cindex = 0;
    if (numDistancesWithin != 0) {
      double meanWithinClustersDistance = withinClustersDistance / numDistancesWithin;
      cindex = (meanWithinClustersDistance - minWithin) / (maxWithin - minWithin);
    }

    if (debug) {
      System.out.println("Min:" + Arrays.toString(minWithinClusters));
      System.out.println("Max:" + Arrays.toString(maxWithinClusters));
      System.out.println("totalWithin:" + numDistancesWithin);
    }
    return cindex;
  }