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							115 lines
						
					
					
						
							3.3 KiB
						
					
					
				
			
		
		
	
	
							115 lines
						
					
					
						
							3.3 KiB
						
					
					
				//
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// Excerpt from fastcluster_R.cpp
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//
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// Copyright: Daniel Müllner, 2011 <http://danifold.net>
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//
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struct pos_node {
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  t_index pos;
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  int node;
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};
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void order_nodes(const int N, const int * const merge, const t_index * const node_size, int * const order) {
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  /* Parameters:
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     N         : number of data points
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     merge     : (N-1)×2 array which specifies the node indices which are
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                 merged in each step of the clustering procedure.
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                 Negative entries -1...-N point to singleton nodes, while
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                 positive entries 1...(N-1) point to nodes which are themselves
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                 parents of other nodes.
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     node_size : array of node sizes - makes it easier
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     order     : output array of size N
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     Runtime: Θ(N)
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  */
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  auto_array_ptr<pos_node> queue(N/2);
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  int parent;
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  int child;
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  t_index pos = 0;
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  queue[0].pos = 0;
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  queue[0].node = N-2;
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  t_index idx = 1;
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  do {
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    --idx;
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    pos = queue[idx].pos;
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    parent = queue[idx].node;
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    // First child
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    child = merge[parent];
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    if (child<0) { // singleton node, write this into the 'order' array.
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      order[pos] = -child;
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      ++pos;
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    }
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    else { /* compound node: put it on top of the queue and decompose it
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              in a later iteration. */
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      queue[idx].pos = pos;
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      queue[idx].node = child-1; // convert index-1 based to index-0 based
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      ++idx;
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      pos += node_size[child-1];
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    }
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    // Second child
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    child = merge[parent+N-1];
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    if (child<0) {
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      order[pos] = -child;
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    }
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    else {
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      queue[idx].pos = pos;
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      queue[idx].node = child-1;
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      ++idx;
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    }
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  } while (idx>0);
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}
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#define size_(r_) ( ((r_<N) ? 1 : node_size[r_-N]) )
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template <const bool sorted>
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void generate_R_dendrogram(int * const merge, double * const height, int * const order, cluster_result & Z2, const int N) {
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  // The array "nodes" is a union-find data structure for the cluster
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  // identites (only needed for unsorted cluster_result input).
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  union_find nodes(sorted ? 0 : N);
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  if (!sorted) {
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    std::stable_sort(Z2[0], Z2[N-1]);
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  }
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  t_index node1, node2;
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  auto_array_ptr<t_index> node_size(N-1);
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  for (t_index i=0; i<N-1; ++i) {
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    // Get two data points whose clusters are merged in step i.
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    // Find the cluster identifiers for these points.
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    if (sorted) {
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      node1 = Z2[i]->node1;
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      node2 = Z2[i]->node2;
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    }
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    else {
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      node1 = nodes.Find(Z2[i]->node1);
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      node2 = nodes.Find(Z2[i]->node2);
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      // Merge the nodes in the union-find data structure by making them
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      // children of a new node.
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      nodes.Union(node1, node2);
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    }
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    // Sort the nodes in the output array.
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    if (node1>node2) {
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      t_index tmp = node1;
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      node1 = node2;
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      node2 = tmp;
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    }
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    /* Conversion between labeling conventions.
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       Input:  singleton nodes 0,...,N-1
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               compound nodes  N,...,2N-2
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       Output: singleton nodes -1,...,-N
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               compound nodes  1,...,N
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    */
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    merge[i]     = (node1<N) ? -static_cast<int>(node1)-1
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                              : static_cast<int>(node1)-N+1;
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    merge[i+N-1] = (node2<N) ? -static_cast<int>(node2)-1
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                              : static_cast<int>(node2)-N+1;
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    height[i] = Z2[i]->dist;
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    node_size[i] = size_(node1) + size_(node2);
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  }
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  order_nodes(N, merge, node_size, order);
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}
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