コード例 #1
0
        //this functionality is usefull to see the distance matrix computed and to use as in input to other clustering algorithms implementation (R or Python)
        public void CreateCSVMatrixFile(string path)
        {
            File.Delete(path);
            this._BuildSingletonCluster();

            StringBuilder matrix     = new StringBuilder();
            string        headerLine = "AggloCluster";

            foreach (Cluster cluster in _clusters)
            {
                headerLine = headerLine + ", Cluster" + cluster.Id;
            }

            bool writeBlank = false;

            matrix.Append(headerLine);

            double      distanceBetweenTwoClusters;
            ClusterPair clusterPair;

            for (int i = 0; i < _clusters.Count(); i++)
            {
                matrix.Append("\r\n");
                matrix.Append("Cluster" + _clusters.GetCluster(i).Id);
                writeBlank = false;

                for (int j = 0; j < _clusters.Count(); j++)
                {
                    clusterPair          = new ClusterPair();
                    clusterPair.Cluster1 = _clusters.GetCluster(i);
                    clusterPair.Cluster2 = _clusters.GetCluster(j);

                    distanceBetweenTwoClusters = ClusterDistance.ComputeDistance(clusterPair.Cluster1, clusterPair.Cluster2);

                    if (distanceBetweenTwoClusters == 0)
                    {
                        writeBlank = true;
                        matrix.Append(",0");
                    }
                    else
                    {
                        if (writeBlank)
                        {
                            matrix.Append("," + string.Empty);
                        }
                        else
                        {
                            matrix.Append("," + distanceBetweenTwoClusters);
                        }
                    }
                }
            }

            File.AppendAllText(path, matrix.ToString());
        }
コード例 #2
0
        // compute the distance between all pair of clusters and store it on the dissimilarity matrix. this algorithm step is done using parallelization to improve performance.
        private void _BuildDissimilarityMatrixParallel()
        {
            double distanceBetweenTwoClusters;

            _dissimilarityMatrix = new DissimilarityMatrix();

            Parallel.ForEach(_ClusterPairCollection(), clusterPair =>
            {
                distanceBetweenTwoClusters = ClusterDistance.ComputeDistance(clusterPair.Cluster1, clusterPair.Cluster2);
                _dissimilarityMatrix.AddClusterPairAndDistance(clusterPair, distanceBetweenTwoClusters);
            });
        }
コード例 #3
0
        // update dissimilarity matrix with the distance of the new formed cluster
        private void _UpdateDissimilarityMatrix(Cluster newCluster, ClusterDistance.Strategy strategie)
        {
            double distanceBetweenClusters;

            for (int i = 0; i < _clusters.Count(); i++)
            {
                // compute the distance between old clusters to the new cluster
                distanceBetweenClusters = ClusterDistance.ComputeDistance(_clusters.GetCluster(i), newCluster, _dissimilarityMatrix, strategie);
                // insert the new cluster's distance
                _dissimilarityMatrix.AddClusterPairAndDistance(new ClusterPair(newCluster, _clusters.GetCluster(i)), distanceBetweenClusters);
                //remove all old distance values of the old clusters (subclusters of the newcluster)
                _dissimilarityMatrix.RemoveClusterPair(new ClusterPair(newCluster.GetSubCluster(0), _clusters.GetCluster(i)));
                _dissimilarityMatrix.RemoveClusterPair(new ClusterPair(newCluster.GetSubCluster(1), _clusters.GetCluster(i)));
            }

            // finally, remove the distance of the old cluster pair
            _dissimilarityMatrix.RemoveClusterPair(new ClusterPair(newCluster.GetSubCluster(0), newCluster.GetSubCluster(1)));
        }
コード例 #4
0
        // calcula a distancia entre todos os clusters e as armazena na matrix de dissimilaridade
        private void CreateDissimilarityMatrix()
        {
            double distanceBetweenTwoClusters;

            _dissimilarityMatrix = new DissimilarityMatrix();
            ClusterPair clusterPair;

            for (int i = 0; i < _clusters.Count(); i++)
            {
                for (int j = i + 1; j < _clusters.Count(); j++)
                {
                    clusterPair          = new ClusterPair();
                    clusterPair.Cluster1 = _clusters.GetCluster(i);
                    clusterPair.Cluster2 = _clusters.GetCluster(j);

                    distanceBetweenTwoClusters = ClusterDistance.ComputeDistance(clusterPair.Cluster1, clusterPair.Cluster2);
                    _dissimilarityMatrix.AddClusterPairAndDistance(clusterPair, distanceBetweenTwoClusters);
                }
            }
        }