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1   // ******************************************************************************
2   //
3   // Title:       Force Field X.
4   // Description: Force Field X - Software for Molecular Biophysics.
5   // Copyright:   Copyright (c) Michael J. Schnieders 2001-2025.
6   //
7   // This file is part of Force Field X.
8   //
9   // Force Field X is free software; you can redistribute it and/or modify it
10  // under the terms of the GNU General Public License version 3 as published by
11  // the Free Software Foundation.
12  //
13  // Force Field X is distributed in the hope that it will be useful, but WITHOUT
14  // ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
15  // FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
16  // details.
17  //
18  // You should have received a copy of the GNU General Public License along with
19  // Force Field X; if not, write to the Free Software Foundation, Inc., 59 Temple
20  // Place, Suite 330, Boston, MA 02111-1307 USA
21  //
22  // Linking this library statically or dynamically with other modules is making a
23  // combined work based on this library. Thus, the terms and conditions of the
24  // GNU General Public License cover the whole combination.
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27  // permission to link this library with independent modules to produce an
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37  // ******************************************************************************
38  package ffx.numerics.clustering;
39  
40  import java.util.List;
41  
42  /**
43   * Defines algorithms that produce hierarchical clusters from distance data.
44   *
45   * @author Lars Behnke, 2013
46   * @author Michael J. Schnieders
47   * @since 1.0
48   */
49  public interface ClusteringAlgorithm {
50  
51    /**
52     * Performs hierarchical agglomerative clustering on a square distance matrix.
53     *
54     * @param distances       an N x N symmetric matrix of pairwise distances (upper triangle used)
55     * @param clusterNames    an array of N names corresponding to rows/columns of distances
56     * @param linkageStrategy the linkage criterion used to update inter-cluster distances
57     * @return the root Cluster of the resulting hierarchy (dendrogram)
58     */
59    Cluster performClustering(double[][] distances, String[] clusterNames,
60                              LinkageStrategy linkageStrategy);
61  
62    /**
63     * Performs hierarchical clustering when each initial element has an associated weight.
64     *
65     * @param distances       an N x N symmetric matrix of pairwise distances
66     * @param clusterNames    an array of N names corresponding to the input elements
67     * @param weights         an array of N non-negative weights for the input elements
68     * @param linkageStrategy the linkage criterion used to update inter-cluster distances
69     * @return the root Cluster of the resulting hierarchy (dendrogram)
70     */
71    Cluster performWeightedClustering(double[][] distances, String[] clusterNames,
72                                      double[] weights, LinkageStrategy linkageStrategy);
73  
74    /**
75     * Performs a flat clustering by agglomerating until the next linkage distance would exceed
76     * the provided threshold, and returns the list of clusters at that cut.
77     *
78     * @param distances       an N x N symmetric matrix of pairwise distances
79     * @param clusterNames    an array of N names corresponding to the input elements
80     * @param linkageStrategy the linkage criterion used to update inter-cluster distances
81     * @param threshold       the maximum allowed inter-cluster linkage distance for merging
82     * @return list of clusters obtained at the specified threshold
83     */
84    List<Cluster> performFlatClustering(double[][] distances,
85                                        String[] clusterNames, LinkageStrategy linkageStrategy, Double threshold);
86  }