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  1. Project Clover database Thu Nov 7 2024 13:01:17 GMT
  2. Package jalview.analysis

File AverageDistanceEngine.java

 

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../../img/srcFileCovDistChart10.png
0% of files have more coverage

Code metrics

58
114
10
1
394
253
44
0.39
11.4
10
4.4

Classes

Class Line # Actions
AverageDistanceEngine 39 114 44
0.9450549594.5%
 

Contributing tests

This file is covered by 3 tests. .

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1    /*
2    * Jalview - A Sequence Alignment Editor and Viewer ($$Version-Rel$$)
3    * Copyright (C) $$Year-Rel$$ The Jalview Authors
4    *
5    * This file is part of Jalview.
6    *
7    * Jalview is free software: you can redistribute it and/or
8    * modify it under the terms of the GNU General Public License
9    * as published by the Free Software Foundation, either version 3
10    * of the License, or (at your option) any later version.
11    *
12    * Jalview is distributed in the hope that it will be useful, but
13    * WITHOUT ANY WARRANTY; without even the implied warranty
14    * of MERCHANTABILITY or FITNESS FOR A PARTICULAR
15    * PURPOSE. See the GNU General Public License for more details.
16    *
17    * You should have received a copy of the GNU General Public License
18    * along with Jalview. If not, see <http://www.gnu.org/licenses/>.
19    * The Jalview Authors are detailed in the 'AUTHORS' file.
20    */
21    package jalview.analysis;
22   
23    import java.util.ArrayList;
24    import java.util.BitSet;
25    import java.util.List;
26    import java.util.Vector;
27   
28    import jalview.datamodel.AlignmentAnnotation;
29    import jalview.datamodel.BinaryNode;
30    import jalview.datamodel.ContactListI;
31    import jalview.datamodel.ContactMatrixI;
32    import jalview.math.Matrix;
33    import jalview.viewmodel.AlignmentViewport;
34   
35    /**
36    * This class implements distance calculations used in constructing a Average
37    * Distance tree (also known as UPGMA)
38    */
 
39    public class AverageDistanceEngine extends TreeEngine
40    {
41    ContactMatrixI cm;
42   
43    AlignmentViewport av;
44   
45    AlignmentAnnotation aa;
46   
47    // 0 - normalised dot product
48    // 1 - L1 - ie (abs(v_1-v_2)/dim(v))
49    // L1 is more rational - since can reason about value of difference,
50    // normalised dot product might give cleaner clusters, but more difficult to
51    // understand.
52   
53    int mode = 1;
54   
55    /**
56    * compute cosine distance matrix for a given contact matrix and create a
57    * UPGMA tree
58    *
59    * @param cm
60    * @param cosineOrDifference
61    * false - dot product : true - L1
62    */
 
63  3 toggle public AverageDistanceEngine(AlignmentViewport av, AlignmentAnnotation aa,
64    ContactMatrixI cm, boolean cosineOrDifference)
65    {
66  3 this.av = av;
67  3 this.aa = aa;
68  3 this.cm = cm;
69  3 mode = (cosineOrDifference) ? 1 : 0;
70  3 calculate(cm);
71   
72    }
73   
 
74  3 toggle public void calculate(ContactMatrixI cm)
75    {
76  3 this.cm = cm;
77  3 node = new Vector<BinaryNode>();
78  3 clusters = new Vector<BitSet>();
79  3 distances = new Matrix(new double[cm.getWidth()][cm.getWidth()]);
80  3 noseqs = cm.getWidth();
81  3 done = new BitSet();
82  3 double moduli[] = new double[cm.getWidth()];
83  3 double max;
84  3 if (mode == 0)
85    {
86  1 max = 1;
87    }
88    else
89    {
90  2 max = cm.getMax() * cm.getMax();
91    }
92   
93  78 for (int i = 0; i < cm.getWidth(); i++)
94    {
95    // init the tree engine node for this column
96  75 BinaryNode cnode = new BinaryNode();
97  75 cnode.setElement(Integer.valueOf(i));
98  75 cnode.setName("c" + i);
99  75 node.addElement(cnode);
100  75 BitSet bs = new BitSet();
101  75 bs.set(i);
102  75 clusters.addElement(bs);
103   
104    // compute distance matrix element
105  75 ContactListI ith = cm.getContactList(i);
106  75 distances.setValue(i, i, 0);
107  75 if (ith == null)
108    {
109  0 continue;
110    }
111  1851 for (int j = 0; j < i; j++)
112    {
113  1776 ContactListI jth = cm.getContactList(j);
114  1776 if (jth == null)
115    {
116  0 break;
117    }
118  1776 double prd = 0;
119  103380 for (int indx = 0; indx < cm.getHeight(); indx++)
120    {
121  101604 if (mode == 0)
122    {
123  100949 if (j == 0)
124    {
125  3422 moduli[i] += ith.getContactAt(indx) * ith.getContactAt(indx);
126    }
127  100949 prd += ith.getContactAt(indx) * jth.getContactAt(indx);
128    }
129    else
130    {
131  655 prd += Math
132    .abs(ith.getContactAt(indx) - jth.getContactAt(indx));
133    }
134    }
135  1776 if (mode == 0)
136    {
137  1711 if (j == 0)
138    {
139  58 moduli[i] = Math.sqrt(moduli[i]);
140    }
141  1711 prd = (moduli[i] != 0 && moduli[j] != 0)
142    ? prd / (moduli[i] * moduli[j])
143    : 0;
144  1711 prd = 1 - prd;
145    }
146    else
147    {
148  65 prd /= cm.getHeight();
149    }
150  1776 distances.setValue(i, j, prd);
151  1776 distances.setValue(j, i, prd);
152    }
153    }
154   
155  3 noClus = clusters.size();
156  3 cluster();
157    }
158   
159    /**
160    * Calculates and saves the distance between the combination of cluster(i) and
161    * cluster(j) and all other clusters. An average of the distances from
162    * cluster(i) and cluster(j) is calculated, weighted by the sizes of each
163    * cluster.
164    *
165    * @param i
166    * @param j
167    */
 
168  72 toggle @Override
169    protected void findClusterDistance(int i, int j)
170    {
171  72 int noi = clusters.elementAt(i).cardinality();
172  72 int noj = clusters.elementAt(j).cardinality();
173   
174    // New distances from cluster i to others
175  72 double[] newdist = new double[noseqs];
176   
177  3624 for (int l = 0; l < noseqs; l++)
178    {
179  3552 if ((l != i) && (l != j))
180    {
181  3408 newdist[l] = ((distances.getValue(i, l) * noi)
182    + (distances.getValue(j, l) * noj)) / (noi + noj);
183    }
184    else
185    {
186  144 newdist[l] = 0;
187    }
188    }
189   
190  3624 for (int ii = 0; ii < noseqs; ii++)
191    {
192  3552 distances.setValue(i, ii, newdist[ii]);
193  3552 distances.setValue(ii, i, newdist[ii]);
194    }
195    }
196   
197    /**
198    * {@inheritDoc}
199    */
 
200  69 toggle @Override
201    protected double findMinDistance()
202    {
203  69 double min = Double.MAX_VALUE;
204   
205  3477 for (int i = 0; i < (noseqs - 1); i++)
206    {
207  101460 for (int j = i + 1; j < noseqs; j++)
208    {
209  98052 if (!done.get(i) && !done.get(j))
210    {
211  34457 if (distances.getValue(i, j) < min)
212    {
213  355 mini = i;
214  355 minj = j;
215   
216  355 min = distances.getValue(i, j);
217    }
218    }
219    }
220    }
221  69 return min;
222    }
223   
224    /**
225    * {@inheritDoc}
226    */
 
227  72 toggle @Override
228    protected void findNewDistances(BinaryNode nodei, BinaryNode nodej,
229    double dist)
230    {
231  72 double ih = 0;
232  72 double jh = 0;
233   
234  72 BinaryNode sni = nodei;
235  72 BinaryNode snj = nodej;
236   
237  218 while (sni != null)
238    {
239  146 ih = ih + sni.dist;
240  146 sni = (BinaryNode) sni.left();
241    }
242   
243  203 while (snj != null)
244    {
245  131 jh = jh + snj.dist;
246  131 snj = (BinaryNode) snj.left();
247    }
248   
249  72 nodei.dist = ((dist / 2) - ih);
250  72 nodej.dist = ((dist / 2) - jh);
251    }
252   
253    /***
254    * not the right place - OH WELL!
255    */
256   
257    /**
258    * Makes a list of groups, where each group is represented by a node whose
259    * height (distance from the root node), as a fraction of the height of the
260    * whole tree, is greater than the given threshold. This corresponds to
261    * selecting the nodes immediately to the right of a vertical line
262    * partitioning the tree (if the tree is drawn with root to the left). Each
263    * such node represents a group that contains all of the sequences linked to
264    * the child leaf nodes.
265    *
266    * @param threshold
267    * @see #getGroups()
268    */
 
269  3 toggle public List<BinaryNode> groupNodes(float threshold)
270    {
271  3 List<BinaryNode> groups = new ArrayList<BinaryNode>();
272  3 _groupNodes(groups, getTopNode(), threshold);
273  3 return groups;
274    }
275   
 
276  11 toggle protected void _groupNodes(List<BinaryNode> groups, BinaryNode nd,
277    float threshold)
278    {
279  11 if (nd == null)
280    {
281  0 return;
282    }
283   
284  11 if ((nd.height / maxheight) > threshold)
285    {
286  7 groups.add(nd);
287    }
288    else
289    {
290  4 _groupNodes(groups, nd.left(), threshold);
291  4 _groupNodes(groups, nd.right(), threshold);
292    }
293    }
294   
295    /**
296    * DOCUMENT ME!
297    *
298    * @param nd
299    * DOCUMENT ME!
300    *
301    * @return DOCUMENT ME!
302    */
 
303  294 toggle public double findHeight(BinaryNode nd)
304    {
305  294 if (nd == null)
306    {
307  0 return maxheight;
308    }
309   
310  294 if ((nd.left() == null) && (nd.right() == null))
311    {
312  150 nd.height = ((BinaryNode) nd.parent()).height + nd.dist;
313   
314  150 if (nd.height > maxheight)
315    {
316  6 return nd.height;
317    }
318    else
319    {
320  144 return maxheight;
321    }
322    }
323    else
324    {
325  144 if (nd.parent() != null)
326    {
327  138 nd.height = ((BinaryNode) nd.parent()).height + nd.dist;
328    }
329    else
330    {
331  6 maxheight = 0;
332  6 nd.height = (float) 0.0;
333    }
334   
335  144 maxheight = findHeight((BinaryNode) (nd.left()));
336  144 maxheight = findHeight((BinaryNode) (nd.right()));
337    }
338   
339  144 return maxheight;
340    }
341   
342    /**
343    * Search for leaf nodes below (or at) the given node
344    *
345    * @param top2
346    * root node to search from
347    *
348    * @return
349    */
 
350  7 toggle public Vector<BinaryNode> findLeaves(BinaryNode top2)
351    {
352  7 Vector<BinaryNode> leaves = new Vector<BinaryNode>();
353  7 findLeaves(top2, leaves);
354  7 return leaves;
355    }
356   
357    /**
358    * Search for leaf nodes.
359    *
360    * @param nd
361    * root node to search from
362    * @param leaves
363    * Vector of leaves to add leaf node objects too.
364    *
365    * @return Vector of leaf nodes on binary tree
366    */
 
367  143 toggle Vector<BinaryNode> findLeaves(BinaryNode nd, Vector<BinaryNode> leaves)
368    {
369  143 if (nd == null)
370    {
371  0 return leaves;
372    }
373   
374  143 if ((nd.left() == null) && (nd.right() == null)) // Interior node
375    // detection
376    {
377  75 leaves.addElement(nd);
378   
379  75 return leaves;
380    }
381    else
382    {
383    /*
384    * TODO: Identify internal nodes... if (node.isSequenceLabel()) {
385    * leaves.addElement(node); }
386    */
387  68 findLeaves(nd.left(), leaves);
388  68 findLeaves(nd.right(), leaves);
389    }
390   
391  68 return leaves;
392    }
393   
394    }