| 1 | package vishnu.testvis.dendro;
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| 2 |
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| 3 | import java.awt.*;
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| 4 | import vishnu.testvis.object.*;
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| 5 | import java.util.Vector;
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| 6 |
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| 7 | public class ClusterObj
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| 8 |
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| 9 | {
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| 10 | Cluster cluster;
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| 11 | Point position;
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| 12 | int radius;
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| 13 | boolean inSubCluster;
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| 14 | private boolean orderStatus;
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| 15 | private boolean keywordStatus;
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| 16 | private String[] freqWords;
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| 17 |
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| 18 | DocObj[] _docs; // list of DocObj ref
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| 19 | String _label; // (top 3-5? related words)
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| 20 | DataManager _data;
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| 21 |
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| 22 | public ClusterObj(Cluster c, Point P, int r, DataManager data)
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| 23 | {
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| 24 | cluster = c;
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| 25 | position = P;
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| 26 | radius = r;
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| 27 | inSubCluster = false;
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| 28 | _data = data;
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| 29 | orderStatus = false;
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| 30 | keywordStatus = false;
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| 31 | }
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| 32 |
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| 33 |
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| 34 | public void setPosition(Point p)
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| 35 | {
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| 36 | position = p;
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| 37 | }
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| 38 |
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| 39 | public void setOrderStatus(boolean b)
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| 40 | {
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| 41 | orderStatus = b;
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| 42 | }
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| 43 |
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| 44 | public boolean getOrderStatus()
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| 45 | {
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| 46 | return orderStatus;
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| 47 | }
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| 48 |
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| 49 | public void setFreqWords(String[] str)
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| 50 | {
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| 51 | freqWords = str;
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| 52 | keywordStatus = true;
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| 53 | }
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| 54 |
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| 55 | public String[] getFreqWords()
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| 56 | {
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| 57 | return freqWords;
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| 58 | }
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| 59 |
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| 60 | public boolean getKeywordStatus()
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| 61 | {
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| 62 | return keywordStatus;
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| 63 | }
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| 64 |
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| 65 | public void setIsSubset(boolean b)
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| 66 | {
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| 67 | inSubCluster = b;
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| 68 | }
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| 69 |
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| 70 | public boolean getIsSubset()
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| 71 | {
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| 72 | return inSubCluster;
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| 73 | }
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| 74 |
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| 75 | public boolean inCircle(int x, int y)
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| 76 | {
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| 77 | double dist_sqr = (x-position.x)*(x-position.x) + (y-position.y)*(y-position.y);
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| 78 | return (dist_sqr <= (4*radius*radius)) ? true : false;
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| 79 | }
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| 80 |
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| 81 |
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| 82 | public void setDocObjs(DocObj[] docArray)
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| 83 | {
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| 84 | _docs = docArray;
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| 85 | }
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| 86 |
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| 87 |
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| 88 | public int getX()
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| 89 | {
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| 90 | return position.x;
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| 91 | }
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| 92 |
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| 93 | public int getY()
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| 94 | {
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| 95 | return position.y;
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| 96 | }
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| 97 |
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| 98 | public int getRad()
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| 99 | {
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| 100 | return radius;
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| 101 | }
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| 102 |
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| 103 |
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| 104 | public ClusterObj(DocObj[] d, String t, DataManager dm)
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| 105 | {
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| 106 | _docs=d; _label=t;
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| 107 | _data = dm;
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| 108 | }
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| 109 |
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| 110 |
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| 111 | public int getDocsSize(){return _docs.length;}
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| 112 |
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| 113 | public String getLabel(){return _label;}
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| 114 |
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| 115 | public String getLabel1(){return getDocsSize() + " documents found";}
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| 116 | public String getLabel2(){return getLabel();}
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| 117 |
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| 118 |
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| 119 | public String getInfo(){
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| 120 | return getDocsSize() + " documents found\n" + getLabel();
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| 121 | }
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| 122 |
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| 123 |
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| 124 |
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| 125 | /**
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| 126 | * This returns a list of list of documents. The inner list of documents represents
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| 127 | * which documents have the corresponding related word
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| 128 | * pre: _docs can't be null
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| 129 | * @return a vector (same length as the related words) of
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| 130 | * vectors (arbitrary length)
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| 131 | *
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| 132 | */
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| 133 | public Vector getHitDocFreq()
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| 134 | {
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| 135 | int s = _data.getWordCount();
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| 136 |
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| 137 | Vector rwVec = new Vector(s);
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| 138 |
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| 139 | for(int i=0;i<s;i++)
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| 140 | {
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| 141 | rwVec.addElement(new Vector(0));
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| 142 | for(int j=0;j<_docs.length;j++)
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| 143 | {
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| 144 | if ( _docs[j].getWeights(i) > 0 )
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| 145 | ((Vector) rwVec.elementAt(i)).addElement(_docs[j]);
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| 146 | }
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| 147 | }
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| 148 | return rwVec;
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| 149 | }
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| 150 |
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| 151 |
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| 152 | public int getDocSize()
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| 153 | {
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| 154 | return cluster._items;
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| 155 | }
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| 156 |
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| 157 |
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| 158 | public String formatDocs()
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| 159 | {
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| 160 | int l = getDocsSize();
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| 161 | String s = "<html><font face=Arial size=-1> "+ l +" documents found\n";
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| 162 | for(int i=0;i<l;i++)
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| 163 | {
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| 164 | s += _docs[i].format4Fields();
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| 165 | }
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| 166 | s += "</font></html>\n";
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| 167 | return s;
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| 168 | }
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| 169 |
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| 170 |
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| 171 | }
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