samoa-api/src/main/java/org/apache/samoa/moa/clusterers/clustream/Clustream.java [135:183]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        radius = Math.min(distance, radius);
      }
    } else {
      radius = closestKernel.getRadius();
    }

    if (minDistance < radius) {
      // Date fits, put into kernel and be happy
      closestKernel.insert(instance, timestamp);
      return;
    }

    // 3. Date does not fit, we need to free
    // some space to insert a new kernel
    long threshold = timestamp - timeWindow; // Kernels before this can be forgotten

    // 3.1 Try to forget old kernels
    for (int i = 0; i < kernels.length; i++) {
      if (kernels[i].getRelevanceStamp() < threshold) {
        kernels[i] = new ClustreamKernel(instance, dim, timestamp, t, m);
        return;
      }
    }

    // 3.2 Merge closest two kernels
    int closestA = 0;
    int closestB = 0;
    minDistance = Double.MAX_VALUE;
    for (int i = 0; i < kernels.length; i++) {
      double[] centerA = kernels[i].getCenter();
      for (int j = i + 1; j < kernels.length; j++) {
        double dist = distance(centerA, kernels[j].getCenter());
        if (dist < minDistance) {
          minDistance = dist;
          closestA = i;
          closestB = j;
        }
      }
    }
    assert (closestA != closestB);

    kernels[closestA].add(kernels[closestB]);
    kernels[closestB] = new ClustreamKernel(instance, dim, timestamp, t, m);
  }

  @Override
  public Clustering getMicroClusteringResult() {
    if (!initialized) {
      return new Clustering(new Cluster[0]);
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



samoa-api/src/main/java/org/apache/samoa/moa/clusterers/clustream/WithKmeans.java [127:175]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        radius = Math.min(distance, radius);
      }
    } else {
      radius = closestKernel.getRadius();
    }

    if (minDistance < radius) {
      // Date fits, put into kernel and be happy
      closestKernel.insert(instance, timestamp);
      return;
    }

    // 3. Date does not fit, we need to free
    // some space to insert a new kernel
    long threshold = timestamp - timeWindow; // Kernels before this can be forgotten

    // 3.1 Try to forget old kernels
    for (int i = 0; i < kernels.length; i++) {
      if (kernels[i].getRelevanceStamp() < threshold) {
        kernels[i] = new ClustreamKernel(instance, dim, timestamp, t, m);
        return;
      }
    }

    // 3.2 Merge closest two kernels
    int closestA = 0;
    int closestB = 0;
    minDistance = Double.MAX_VALUE;
    for (int i = 0; i < kernels.length; i++) {
      double[] centerA = kernels[i].getCenter();
      for (int j = i + 1; j < kernels.length; j++) {
        double dist = distance(centerA, kernels[j].getCenter());
        if (dist < minDistance) {
          minDistance = dist;
          closestA = i;
          closestB = j;
        }
      }
    }
    assert (closestA != closestB);

    kernels[closestA].add(kernels[closestB]);
    kernels[closestB] = new ClustreamKernel(instance, dim, timestamp, t, m);
  }

  @Override
  public Clustering getMicroClusteringResult() {
    if (!initialized) {
      return new Clustering(new Cluster[0]);
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -