import jalview.datamodel.SeqCigar;
import jalview.datamodel.SequenceFeature;
-import java.util.ArrayList;
-import java.util.Hashtable;
+import java.util.HashMap;
+import java.util.HashSet;
import java.util.List;
+import java.util.Map;
+import java.util.Set;
public class FeatureScoreModel implements ScoreModelI, ViewBasedAnalysisI
{
return true;
}
+ /**
+ * Calculates a distance measure [i][j] between each pair of sequences as the
+ * average number of features they have but do not share. That is, find the
+ * features each sequence pair has at each column, ignore feature types they
+ * have in common, and count the rest. The totals are normalised by the number
+ * of columns processed.
+ */
@Override
public float[][] findDistances(AlignmentView seqData)
{
- int nofeats = 0;
List<String> dft = fr.getDisplayedFeatureTypes();
- nofeats = dft.size();
SeqCigar[] seqs = seqData.getSequences();
int noseqs = seqs.length;
int cpwidth = 0;// = seqData.getWidth();
float[][] distance = new float[noseqs][noseqs];
- if (nofeats == 0)
+ if (dft.isEmpty())
{
- for (float[] d : distance)
- {
- for (int i = 0; i < d.length; d[i++] = 0f)
- {
- ;
- }
- }
return distance;
}
+
// need to get real position for view position
int[] viscont = seqData.getVisibleContigs();
+
+ /*
+ * scan each column, compute and add to each distance[i, j]
+ * the number of feature types that seqi and seqj do not share
+ */
for (int vc = 0; vc < viscont.length; vc += 2)
{
-
for (int cpos = viscont[vc]; cpos <= viscont[vc + 1]; cpos++)
{
cpwidth++;
- // get visible features at cpos under view's display settings and
- // compare them
- List<Hashtable<String, SequenceFeature>> sfap = new ArrayList<Hashtable<String, SequenceFeature>>();
- for (int i = 0; i < noseqs; i++)
- {
- Hashtable<String, SequenceFeature> types = new Hashtable<String, SequenceFeature>();
- int spos = seqs[i].findPosition(cpos);
- if (spos != -1)
- {
- List<SequenceFeature> sfs = fr.findFeaturesAtRes(
- seqs[i].getRefSeq(), spos);
- for (SequenceFeature sf : sfs)
- {
- types.put(sf.getType(), sf);
- }
- }
- sfap.add(types);
- }
+
+ /*
+ * first pass: record features types in column for each sequence
+ */
+ Map<SeqCigar, Set<String>> sfap = findFeatureTypesAtColumn(
+ seqs, cpos);
+
+ /*
+ * count feature types on either i'th or j'th sequence but not both
+ * and add this 'distance' measure to the total for [i, j] for j > i
+ */
for (int i = 0; i < (noseqs - 1); i++)
{
- if (cpos == 0)
- {
- distance[i][i] = 0f;
- }
for (int j = i + 1; j < noseqs; j++)
{
- int sfcommon = 0;
- // compare the two lists of features...
- Hashtable<String, SequenceFeature> fi = sfap.get(i), fk, fj = sfap
- .get(j);
- if (fi.size() > fj.size())
- {
- fk = fj;
- }
- else
- {
- fk = fi;
- fi = fj;
- }
- for (String k : fi.keySet())
- {
- SequenceFeature sfj = fk.get(k);
- if (sfj != null)
- {
- sfcommon++;
- }
- }
- distance[i][j] += (fi.size() + fk.size() - 2f * sfcommon);
- distance[j][i] += distance[i][j];
+ int seqDistance = countUnsharedFeatureTypes(sfap.get(seqs[i]),
+ sfap.get(seqs[j]));
+ distance[i][j] += seqDistance;
+ // distance[j][i] += distance[i][j];
}
}
}
}
+
+ /*
+ * normalise the distance scores (summed over columns) by the
+ * number of visible columns used in the calculation
+ */
for (int i = 0; i < noseqs; i++)
{
for (int j = i + 1; j < noseqs; j++)
return distance;
}
+ /**
+ * Returns the count of values that are set1 or set2 but not in both
+ *
+ * @param set1
+ * @param set2
+ * @return
+ */
+ protected int countUnsharedFeatureTypes(Set<String> set1, Set<String> set2)
+ {
+ int size1 = set1.size();
+ int size2 = set2.size();
+ Set<String> smallerSet = size1 < size2 ? set1 : set2;
+ Set<String> largerSet = (smallerSet == set1 ? set2 : set1);
+ int inCommon = 0;
+ for (String k : smallerSet)
+ {
+ if (largerSet.contains(k))
+ {
+ inCommon++;
+ }
+ }
+
+ int notInCommon = (size1 - inCommon) + (size2 - inCommon);
+ return notInCommon;
+ }
+
+ /**
+ * Builds and returns a list (one per SeqCigar) of visible feature types at
+ * the given column position
+ *
+ * @param seqs
+ * @param columnPosition
+ * @return
+ */
+ protected Map<SeqCigar, Set<String>> findFeatureTypesAtColumn(
+ SeqCigar[] seqs, int columnPosition)
+ {
+ Map<SeqCigar, Set<String>> sfap = new HashMap<SeqCigar, Set<String>>();
+ for (SeqCigar seq : seqs)
+ {
+ Set<String> types = new HashSet<String>();
+ int spos = seq.findPosition(columnPosition);
+ if (spos != -1)
+ {
+ List<SequenceFeature> sfs = fr.findFeaturesAtRes(seq.getRefSeq(),
+ spos);
+ for (SequenceFeature sf : sfs)
+ {
+ types.add(sf.getType());
+ }
+ }
+ sfap.put(seq, types);
+ }
+ return sfap;
+ }
+
@Override
public String getName()
{
*/
package jalview.analysis.scoremodels;
+import static org.testng.Assert.assertEquals;
+
import jalview.datamodel.AlignmentI;
import jalview.datamodel.SequenceFeature;
import jalview.datamodel.SequenceI;
int[] sf3 = new int[] { -1, -1, -1, -1, -1, -1, 76, 77 };
+ /**
+ * <pre>
+ * Load test alignment and add features to sequences:
+ * FER1_MESCR FER1_SPIOL FER3_RAPSA FER1_MAIZE
+ * sf1 X X X
+ * sf2 X X
+ * sf3 X
+ * </pre>
+ *
+ * @return
+ */
public AlignFrame getTestAlignmentFrame()
{
AlignFrame alf = new FileLoader(false).LoadFileWaitTillLoaded(
Assert.assertTrue(fsm.configureFromAlignmentView(alf.getCurrentView()
.getAlignPanel()));
alf.selectAllSequenceMenuItem_actionPerformed(null);
+
float[][] dm = fsm.findDistances(alf.getViewport().getAlignmentView(
true));
Assert.assertTrue(dm[0][2] == 0f,
.size(), 0);
}
+ @Test(groups = { "Functional" })
+ public void testFindDistances() throws Exception
+ {
+ String seqs = ">s1\nABCDE\n>seq2\nABCDE\n";
+ AlignFrame alf = new FileLoader().LoadFileWaitTillLoaded(seqs,
+ DataSourceType.PASTE);
+ SequenceI s1 = alf.getViewport().getAlignment().getSequenceAt(0);
+ SequenceI s2 = alf.getViewport().getAlignment().getSequenceAt(1);
+
+ /*
+ * set domain and variant features thus:
+ * ----5
+ * s1 ddd..
+ * s1 .vvv.
+ * s1 ..vvv
+ * s2 .ddd.
+ * s2 vv..v
+ * The number of unshared feature types per column is
+ * 20120 (two features of the same type doesn't affect score)
+ * giving an average (pairwise distance) of 5/5 or 1.0
+ */
+ s1.addSequenceFeature(new SequenceFeature("domain", null, 1, 3, 0f,
+ null));
+ s1.addSequenceFeature(new SequenceFeature("variant", null, 2, 4, 0f,
+ null));
+ s1.addSequenceFeature(new SequenceFeature("variant", null, 3, 5, 0f,
+ null));
+ s2.addSequenceFeature(new SequenceFeature("domain", null, 2, 4, 0f,
+ null));
+ s2.addSequenceFeature(new SequenceFeature("variant", null, 1, 2, 0f,
+ null));
+ s2.addSequenceFeature(new SequenceFeature("variant", null, 5, 5, 0f,
+ null));
+ alf.setShowSeqFeatures(true);
+ alf.getFeatureRenderer().findAllFeatures(true);
+
+ FeatureScoreModel fsm = new FeatureScoreModel();
+ Assert.assertTrue(fsm.configureFromAlignmentView(alf.getCurrentView()
+ .getAlignPanel()));
+ alf.selectAllSequenceMenuItem_actionPerformed(null);
+
+ float[][] distances = fsm.findDistances(alf.getViewport()
+ .getAlignmentView(true));
+ assertEquals(distances.length, 2);
+ assertEquals(distances[0][0], 0f);
+ assertEquals(distances[1][1], 0f);
+ // these left to fail pending resolution of
+ // JAL-2424 (dividing score by 6, not 5)
+ assertEquals(distances[0][1], 1f);
+ assertEquals(distances[1][0], 1f);
+ }
+
}
git://source.jalview.org / jalview.git / commitdiff