Examples with ClusterPostProcessingTask edu.ucsf.rbvi.clusterMaker2.internal.algorithms.networkClusterers.TransClust.de.layclust.taskmanaging.ClusterPostProcessingTask used on opensource projects

Example 1 with ClusterPostProcessingTask

use of edu.ucsf.rbvi.clusterMaker2.internal.algorithms.networkClusterers.TransClust.de.layclust.taskmanaging.ClusterPostProcessingTask in project clusterMaker2 by RBVI.

the class PP_DivideAndRecluster method run.

public void run() {
    /* print score before any post processing */
    // double scoreAtStart = this.cc.getClusteringScore();
    // System.out.println("Score before post processing: "+scoreAtStart);
    /* merging step */
    ArrayList<ArrayList<Integer>> clusterObject = PostProcessingUtility.createClusterObject(this.cc, false);
    HashSet<String> alreadyCompared = new HashSet<String>();
    ClusterObjectComparator comparator = new ClusterObjectComparator();
    PostProcessingUtility.mergeCluster(clusterObject, alreadyCompared, this.cc, comparator, true);
    this.bestScore = PostProcessingUtility.updateClusterInfoInCC(clusterObject, this.cc);
    /* collection ConnectedComponent objects */
    ArrayList<ConnectedComponent> cCsOfSubgraphs = new ArrayList<ConnectedComponent>();
    /* start a new clustering procedure for clusters larger than 3 */
    for (int i = 0; i < clusterObject.size(); i++) {
        ArrayList<Integer> cluster = clusterObject.get(i);
        int clusterSize = cluster.size();
        /* if the clusters are to small, leave them in the clusters object and continue */
        if (clusterSize <= 3) {
            // System.out.println("cluster too small: "+cluster.toString());
            continue;
        }
        /* remove cluster from cluster object and decrease i */
        // TODO!!
        clusterObject.remove(i);
        --i;
        ConnectedComponent ccForCluster = this.cc.createConnectedComponentForCluster(i, cluster);
        cCsOfSubgraphs.add(ccForCluster);
        ClusterPostProcessingTask clusterTask = new ClusterPostProcessingTask(ccForCluster, this.params, this.layouterEnumTypes);
        clusterTask.run();
    }
    for (int i = 0; i < cCsOfSubgraphs.size(); i++) {
        ConnectedComponent subCC = cCsOfSubgraphs.get(i);
        addClustersToTotalClusters(subCC, clusterObject);
    }
    /* update clustering information */
    this.bestScore = PostProcessingUtility.updateClusterInfoInCC(clusterObject, this.cc);
    /* do post post processing - merge and rearrange */
    PP_RearrangeAndMergeBest postProcess1 = new PP_RearrangeAndMergeBest();
    postProcess1.initPostProcessing(this.cc);
    postProcess1.run();
}

Example 2 with ClusterPostProcessingTask

use of edu.ucsf.rbvi.clusterMaker2.internal.algorithms.networkClusterers.TransClust.de.layclust.taskmanaging.ClusterPostProcessingTask in project clusterMaker2 by RBVI.

the class PP_DivideAndReclusterRecursively method recursiveReclustering.

/**
 * This method goes through each cluster in the tmpClusterObject and
 * re-clusters them. If the clusters have less than 4 objects, then it is
 * added to the finalClusterObject. If after the re-clustering, no changes
 * have occured (it is still one cluster) it is added to the
 * finalClusterObject. Otherwise if changes have occured the sub-clusters
 * are then re-clustered again. This occurs recursively until no more
 * improvements are found.
 *
 * @param finalClusterObject
 *            This should only include finished clusters that can not be
 *            improved anymore by reclustering.
 * @param tmpClusterObject
 *            This includes all clusters that are to be re-clustered.
 */
private void recursiveReclustering(ArrayList<ArrayList<Integer>> finalClusterObject, ArrayList<ArrayList<Integer>> tmpClusterObject) {
    for (int i = 0; i < tmpClusterObject.size(); i++) {
        ArrayList<Integer> cluster = tmpClusterObject.get(i);
        int clusterSize = cluster.size();
        /*all clusters <=3 are taken care of in the rearrange method of
			 * post-processing */
        if (clusterSize <= 3) {
            finalClusterObject.add(cluster);
        } else {
            /* run clustering for this one cluster to see if an improvement can be found */
            ConnectedComponent ccForCluster = this.cc.createConnectedComponentForCluster(i, cluster);
            ClusterPostProcessingTask clusterTask = new ClusterPostProcessingTask(ccForCluster, this.params, this.layouterEnumTypes);
            clusterTask.run();
            /* if there has been no change, add this cluster to the final cluster object */
            if (ccForCluster.getNumberOfClusters() == 1) {
                finalClusterObject.add(cluster);
            /* otherwise recluster */
            } else {
                /* new cluster object for the resulting clusters of the improved cluster */
                ArrayList<ArrayList<Integer>> nextClusterObject = PostProcessingUtility.createClusterObject(ccForCluster, true);
                recursiveReclustering(finalClusterObject, nextClusterObject);
            }
        }
    }
}