コード例 #1
0
 public object Clone()
 {
     Cluster pRet = new Cluster();
     pRet.m_index = this.m_index;
     pRet.m_name = this.m_name;
     pRet.m_center = (double[])this.Center.Clone();
     if (this.m_elements != null)
     {
         pRet.m_elements = new List<IndivData>();
         foreach (var p in this.m_elements)
         {
             pRet.m_elements.Add((IndivData)p.Clone());
         }
     }
     return pRet;
 }
コード例 #2
0
 private bool initializeCiusters(int nbClusters)
 {
     bool oRet = false;
     var inds = this.Indivs;
     if ((inds == null) || (nbClusters < 2))
     {
         return oRet;
     }
     if (inds.Count < nbClusters)
     {
         return oRet;
     }
     double[] dd = inds.First().DoubleData;
     int nv = dd.Length;
     if (nv < 1)
     {
         return oRet;
     }
     double[,] dLimits = new double[3, nv];
     for (int i = 0; i < nv; ++i)
     {
         double x = dd[i];
         dLimits[0, i] = x;
         dLimits[1, i] = x;
         dLimits[2, i] = 0.0;
     }// i
     int nc = 0;
     foreach (var ind in inds)
     {
         double[] ddx = ind.DoubleData;
         if (ddx.Length < nv)
         {
             continue;
         }
         ++nc;
         for (int i = 0; i < nv; ++i)
         {
             double x = ddx[i];
             if (x < dLimits[0, i])
             {
                 dLimits[0, i] = x;
             }
             else if (x > dLimits[1, i])
             {
                 dLimits[1, i] = x;
             }
         }// i
     }// ind
     if (nc < 1)
     {
         return oRet;
     }
     for (int i = 0; i < nv; ++i)
     {
         double x1 = dLimits[0, i];
         double x2 = dLimits[1, i];
         double step = (x2 - x1) / (nbClusters + 2);
         if (step <= 0.0)
         {
             return oRet;
         }
         dLimits[2, i] = step;
     }// i
     Cluster[] cc = new Cluster[nbClusters];
     for (int i = 0; i < nbClusters; ++i)
     {
         double[] xc = new double[nv];
         for (int j = 0; j < nv; ++j)
         {
             xc[j] = dLimits[0, j] + (i + 1) * dLimits[2, j];
         }// j
         Cluster c = new Cluster();
         c.Index = i;
         c.Name = String.Format("KM{0}", i + 1);
         c.Center = xc;
         cc[i] = c;
     }// i
     this.m_clusters = cc.ToList();
     return true;
 }
コード例 #3
0
 public static CategClusterSet ProcessAsync(OrdModelView model, int nClusters, CancellationToken cancellationToken)
 {
     if ((model == null) || (nClusters < 2))
     {
         return null;
     }
     if (cancellationToken.IsCancellationRequested)
     {
         return null;
     }
     var rd = new Random();
     CategClusterSet oRet = new CategClusterSet(model);
     Cluster[] cc = new Cluster[nClusters];
     IndivData[] inds = oRet.Indivs.ToArray();
     int nMax = inds.Length;
     if (nMax < nClusters)
     {
         return null;
     }
     HashSet<int> oCur = new HashSet<int>();
     for (int i = 0; i < nClusters; ++i)
     {
         int nx = rd.Next(0, nMax);
         while (nx >= nMax)
         {
             nx = rd.Next(nMax);
         }
         IndivData indiv = inds[nx];
         int index = indiv.IndivIndex;
         while (oCur.Contains(index))
         {
             nx = rd.Next(0, nMax);
             while (nx >= nMax)
             {
                 nx = rd.Next(0, nMax);
             }
             indiv = inds[nx];
             index = indiv.IndivIndex;
         }
         oCur.Add(index);
         var xc = new Cluster(indiv, ClassificationType.Utility);
         xc.Name = String.Format("CU{0}", i + 1);
         xc.Index = i;
         cc[i] = xc;
     }// i
     oRet.Clusters = cc.ToList();
     double xx = oRet.compute_global_crit(cancellationToken);
     oRet.GlobalCrit = xx;
     if (cancellationToken.IsCancellationRequested)
     {
         return null;
     }
     foreach (var ind in inds)
     {
         if (cancellationToken.IsCancellationRequested)
         {
             return null;
         }
         if (!oCur.Contains(ind.IndivIndex))
         {
             if (!oRet.processOne(ind, cancellationToken))
             {
                 return null;
             }
         }
     }// inds
     return oRet;
 }
コード例 #4
0
 private bool contains(Cluster oCluster)
 {
     Cluster cluster = null;
     foreach (var ind1 in oCluster.Elements)
     {
         if (cluster != null)
         {
             break;
         }
         int nIndex = ind1.IndivIndex;
         foreach (var c in this.Clusters)
         {
             var q = from x in c.Elements where x.IndivIndex == nIndex select x;
             if (q.Count() > 0)
             {
                 cluster = c;
                 break;
             }
         }// c
     }// ind1
     if (cluster == null)
     {
         return false;
     }
     if (cluster.Count != oCluster.Count)
     {
         return false;
     }
     foreach (var ind1 in oCluster.Elements)
     {
         var q = from x in cluster.Elements where x.IndivIndex == ind1.IndivIndex select x;
         if (q.Count() < 1)
         {
             return false;
         }
     }// ind1
     return true;
 }
コード例 #5
0
 public static Task<CategClusterSet> KMeansAsync(OrdModelView model, int nClusters, int nbIterations, CancellationToken cancellationToken,
     IProgress<Tuple<int, CategClusterSet>> progress)
 {
     return Task.Run<CategClusterSet>(() =>
     {
         CategClusterSet oBest = new CategClusterSet(model);
         oBest.initializeCiusters(nClusters);
         for (int i = 0; i < nbIterations; ++i)
         {
             CategClusterSet pp = new CategClusterSet();
             pp.m_model = oBest.m_model;
             pp.m_nvars = oBest.m_nvars;
             pp.m_indivs = oBest.m_indivs;
             List<Cluster> oList = new List<Cluster>();
             foreach (var c in oBest.Clusters)
             {
                 Cluster cc = new Cluster();
                 cc.Index = c.Index;
                 cc.Name = c.Name;
                 cc.Center = (double[])c.Center.Clone();
                 oList.Add(cc);
             }// c
             pp.Clusters = oList;
             int f = (int)(((double)i / (double)nbIterations) * 100.0 + 0.5);
             if (cancellationToken.IsCancellationRequested)
             {
                 break;
             }
             pp.kmeansstep(cancellationToken);
             if (cancellationToken.IsCancellationRequested)
             {
                 break;
             }
             if (oBest.Equals(pp))
             {
                 break;
             }
             oBest = pp;
             if (progress != null)
             {
                 progress.Report(new Tuple<int, CategClusterSet>(f, pp));
             }
         }// i
         return oBest;
     }, cancellationToken);
 }