+/*
+ * Jalview - A Sequence Alignment Editor and Viewer (Version 2.7)
+ * Copyright (C) 2011 J Procter, AM Waterhouse, J Engelhardt, LM Lui, G Barton, M Clamp, S Searle
+ *
+ * This file is part of Jalview.
+ *
+ * Jalview is free software: you can redistribute it and/or
+ * modify it under the terms of the GNU General Public License
+ * as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
+ *
+ * Jalview is distributed in the hope that it will be useful, but
+ * WITHOUT ANY WARRANTY; without even the implied warranty
+ * of MERCHANTABILITY or FITNESS FOR A PARTICULAR
+ * PURPOSE. See the GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License along with Jalview. If not, see <http://www.gnu.org/licenses/>.
+ */
package jalview.analysis;
import jalview.datamodel.AlignmentI;
import java.util.Vector;
/**
- * various methods for defining groups on an alignment based on some other properties
+ * various methods for defining groups on an alignment based on some other
+ * properties
+ *
* @author JimP
- *
+ *
*/
public class Grouping
{
/**
- * Divide the given sequences based on the equivalence of their corresponding selectedChars string. If exgroups is provided, existing groups will be subdivided.
+ * Divide the given sequences based on the equivalence of their corresponding
+ * selectedChars string. If exgroups is provided, existing groups will be
+ * subdivided.
+ *
* @param sequences
* @param selectedChars
* @param exgroups
* @return
*/
- public static SequenceGroup[] makeGroupsFrom(SequenceI[] sequences, String[] selectedChars, Vector exgroups)
+ public static SequenceGroup[] makeGroupsFrom(SequenceI[] sequences,
+ String[] selectedChars, Vector exgroups)
{
- // TODO: determine how to get/recover input data for group generation
+ // TODO: determine how to get/recover input data for group generation
Hashtable gps = new Hashtable();
- int width = 0,i;
+ int width = 0, i;
Hashtable pgroup = new Hashtable();
- if (exgroups!=null)
+ if (exgroups != null)
{
SequenceGroup sg;
- for (Enumeration g=exgroups.elements(); g.hasMoreElements(); )
+ for (Enumeration g = exgroups.elements(); g.hasMoreElements();)
{
sg = (SequenceGroup) g.nextElement();
- for (Enumeration sq = sg.getSequences(null).elements(); sq.hasMoreElements(); )
+ for (Enumeration sq = sg.getSequences(null).elements(); sq
+ .hasMoreElements();)
pgroup.put(sq.nextElement().toString(), sg);
}
}
for (i = 0; i < sequences.length; i++)
{
String schar = selectedChars[i];
- SequenceGroup pgp = (SequenceGroup) pgroup.get(((Object) sequences[i]).toString());
- if (pgp!=null)
+ SequenceGroup pgp = (SequenceGroup) pgroup
+ .get(((Object) sequences[i]).toString());
+ if (pgp != null)
{
- schar = pgp.getName()+":"+schar;
+ schar = pgp.getName() + ":" + schar;
}
Vector svec = (Vector) gps.get(schar);
if (svec == null)
svec = new Vector();
gps.put(schar, svec);
}
- if (width<sequences[i].getLength())
+ if (width < sequences[i].getLength())
{
width = sequences[i].getLength();
}
// make some groups
java.util.Enumeration sge = gps.keys();
SequenceGroup[] groups = new SequenceGroup[gps.size()];
- i=0;
- while (sge.hasMoreElements()) {
+ i = 0;
+ while (sge.hasMoreElements())
+ {
String key = (String) sge.nextElement();
- SequenceGroup group = new SequenceGroup((Vector) gps.get(key), "Subseq: "+key, null, true, true,
- false, 0, width - 1);
-
+ SequenceGroup group = new SequenceGroup((Vector) gps.get(key),
+ "Subseq: " + key, null, true, true, false, 0, width - 1);
+
groups[i++] = group;
}
gps.clear();
pgroup.clear();
return groups;
}
+
/**
- * subdivide the given sequences based on the distribution of features
- * @param featureLabels - null or one or more feature types to filter on.
- * @param groupLabels - null or set of groups to filter features on
- * @param start - range for feature filter
- * @param stop - range for feature filter
- * @param sequences - sequences to be divided
- * @param exgroups - existing groups to be subdivided
- * @param method - density, description, score
+ * subdivide the given sequences based on the distribution of features
+ *
+ * @param featureLabels
+ * - null or one or more feature types to filter on.
+ * @param groupLabels
+ * - null or set of groups to filter features on
+ * @param start
+ * - range for feature filter
+ * @param stop
+ * - range for feature filter
+ * @param sequences
+ * - sequences to be divided
+ * @param exgroups
+ * - existing groups to be subdivided
+ * @param method
+ * - density, description, score
*/
- public static void divideByFeature(String[] featureLabels, String[] groupLabels, int start, int stop,
- SequenceI[] sequences, Vector exgroups, String method)
+ public static void divideByFeature(String[] featureLabels,
+ String[] groupLabels, int start, int stop, SequenceI[] sequences,
+ Vector exgroups, String method)
{
// TODO implement divideByFeature
/*
- if (method!=AlignmentSorter.FEATURE_SCORE && method!=AlignmentSorter.FEATURE_LABEL && method!=AlignmentSorter.FEATURE_DENSITY)
- {
- throw new Error("Implementation Error - sortByFeature method must be one of FEATURE_SCORE, FEATURE_LABEL or FEATURE_DENSITY.");
- }
- boolean ignoreScore=method!=AlignmentSorter.FEATURE_SCORE;
- StringBuffer scoreLabel = new StringBuffer();
- scoreLabel.append(start+stop+method);
- // This doesn't work yet - we'd like to have a canonical ordering that can be preserved from call to call
- for (int i=0;featureLabels!=null && i<featureLabels.length; i++)
- {
- scoreLabel.append(featureLabels[i]==null ? "null" : featureLabels[i]);
- }
- for (int i=0;groupLabels!=null && i<groupLabels.length; i++)
- {
- scoreLabel.append(groupLabels[i]==null ? "null" : groupLabels[i]);
- }
- SequenceI[] seqs = alignment.getSequencesArray();
-
- boolean[] hasScore = new boolean[seqs.length]; // per sequence score
- // presence
- int hasScores = 0; // number of scores present on set
- double[] scores = new double[seqs.length];
- int[] seqScores = new int[seqs.length];
- Object[] feats = new Object[seqs.length];
- double min = 0, max = 0;
- for (int i = 0; i < seqs.length; i++)
- {
- SequenceFeature[] sf = seqs[i].getSequenceFeatures();
- if (sf==null && seqs[i].getDatasetSequence()!=null)
- {
- sf = seqs[i].getDatasetSequence().getSequenceFeatures();
- }
- if (sf==null)
- {
- sf = new SequenceFeature[0];
- } else {
- SequenceFeature[] tmp = new SequenceFeature[sf.length];
- for (int s=0; s<tmp.length;s++)
- {
- tmp[s] = sf[s];
- }
- sf = tmp;
- }
- int sstart = (start==-1) ? start : seqs[i].findPosition(start);
- int sstop = (stop==-1) ? stop : seqs[i].findPosition(stop);
- seqScores[i]=0;
- scores[i]=0.0;
- int n=sf.length;
- for (int f=0;f<sf.length;f++)
- {
- // filter for selection criteria
- if (
- // ignore features outwith alignment start-stop positions.
- (sf[f].end < sstart || sf[f].begin > sstop)
- ||
- // or ignore based on selection criteria
- (featureLabels != null && !AlignmentSorter.containsIgnoreCase(sf[f].type, featureLabels))
- || (groupLabels != null
- // problem here: we cannot eliminate null feature group features
- && (sf[f].getFeatureGroup() != null
- && !AlignmentSorter.containsIgnoreCase(sf[f].getFeatureGroup(), groupLabels))))
- {
- // forget about this feature
- sf[f] = null;
- n--;
- } else {
- // or, also take a look at the scores if necessary.
- if (!ignoreScore && sf[f].getScore()!=Float.NaN)
- {
- if (seqScores[i]==0)
- {
- hasScores++;
- }
- seqScores[i]++;
- hasScore[i] = true;
- scores[i] += sf[f].getScore(); // take the first instance of this
- // score.
- }
- }
- }
- SequenceFeature[] fs;
- feats[i] = fs = new SequenceFeature[n];
- if (n>0)
- {
- n=0;
- for (int f=0;f<sf.length;f++)
- {
- if (sf[f]!=null)
- {
- ((SequenceFeature[]) feats[i])[n++] = sf[f];
- }
- }
- if (method==FEATURE_LABEL)
- {
- // order the labels by alphabet
- String[] labs = new String[fs.length];
- for (int l=0;l<labs.length; l++)
- {
- labs[l] = (fs[l].getDescription()!=null ? fs[l].getDescription() : fs[l].getType());
- }
- jalview.util.QuickSort.sort(labs, ((Object[]) feats[i]));
- }
- }
- if (hasScore[i])
- {
- // compute average score
- scores[i]/=seqScores[i];
- // update the score bounds.
- if (hasScores == 1)
- {
- max = min = scores[i];
- }
- else
- {
- if (max < scores[i])
- {
- max = scores[i];
- }
- if (min > scores[i])
- {
- min = scores[i];
- }
- }
- }
- }
-
- if (method==FEATURE_SCORE)
- {
- if (hasScores == 0)
- {
- return; // do nothing - no scores present to sort by.
- }
- // pad score matrix
- if (hasScores < seqs.length)
- {
- for (int i = 0; i < seqs.length; i++)
- {
- if (!hasScore[i])
- {
- scores[i] = (max + i);
- } else {
- int nf=(feats[i]==null) ? 0 :((SequenceFeature[]) feats[i]).length;
- System.err.println("Sorting on Score: seq "+seqs[i].getName()+ " Feats: "+nf+" Score : "+scores[i]);
- }
- }
- }
-
- jalview.util.QuickSort.sort(scores, seqs);
- }
- else
- if (method==FEATURE_DENSITY)
- {
-
- // break ties between equivalent numbers for adjacent sequences by adding 1/Nseq*i on the original order
- double fr = 0.9/(1.0*seqs.length);
- for (int i=0;i<seqs.length; i++)
- {
- double nf;
- scores[i] = (0.05+fr*i)+(nf=((feats[i]==null) ? 0.0 :1.0*((SequenceFeature[]) feats[i]).length));
- System.err.println("Sorting on Density: seq "+seqs[i].getName()+ " Feats: "+nf+" Score : "+scores[i]);
- }
- jalview.util.QuickSort.sort(scores, seqs);
- }
- else {
- if (method==FEATURE_LABEL)
- {
- throw new Error("Not yet implemented.");
- }
- }
- if (lastSortByFeatureScore ==null || scoreLabel.equals(lastSortByFeatureScore))
- {
- setOrder(alignment, seqs);
- }
- else
- {
- setReverseOrder(alignment, seqs);
- }
- lastSortByFeatureScore = scoreLabel.toString(); */
+ * if (method!=AlignmentSorter.FEATURE_SCORE &&
+ * method!=AlignmentSorter.FEATURE_LABEL &&
+ * method!=AlignmentSorter.FEATURE_DENSITY) { throw newError(
+ * "Implementation Error - sortByFeature method must be one of FEATURE_SCORE, FEATURE_LABEL or FEATURE_DENSITY."
+ * ); } boolean ignoreScore=method!=AlignmentSorter.FEATURE_SCORE;
+ * StringBuffer scoreLabel = new StringBuffer();
+ * scoreLabel.append(start+stop+method); // This doesn't work yet - we'd
+ * like to have a canonical ordering that can be preserved from call to call
+ * for (int i=0;featureLabels!=null && i<featureLabels.length; i++) {
+ * scoreLabel.append(featureLabels[i]==null ? "null" : featureLabels[i]); }
+ * for (int i=0;groupLabels!=null && i<groupLabels.length; i++) {
+ * scoreLabel.append(groupLabels[i]==null ? "null" : groupLabels[i]); }
+ * SequenceI[] seqs = alignment.getSequencesArray();
+ *
+ * boolean[] hasScore = new boolean[seqs.length]; // per sequence score //
+ * presence int hasScores = 0; // number of scores present on set double[]
+ * scores = new double[seqs.length]; int[] seqScores = new int[seqs.length];
+ * Object[] feats = new Object[seqs.length]; double min = 0, max = 0; for
+ * (int i = 0; i < seqs.length; i++) { SequenceFeature[] sf =
+ * seqs[i].getSequenceFeatures(); if (sf==null &&
+ * seqs[i].getDatasetSequence()!=null) { sf =
+ * seqs[i].getDatasetSequence().getSequenceFeatures(); } if (sf==null) { sf
+ * = new SequenceFeature[0]; } else { SequenceFeature[] tmp = new
+ * SequenceFeature[sf.length]; for (int s=0; s<tmp.length;s++) { tmp[s] =
+ * sf[s]; } sf = tmp; } int sstart = (start==-1) ? start :
+ * seqs[i].findPosition(start); int sstop = (stop==-1) ? stop :
+ * seqs[i].findPosition(stop); seqScores[i]=0; scores[i]=0.0; int
+ * n=sf.length; for (int f=0;f<sf.length;f++) { // filter for selection
+ * criteria if ( // ignore features outwith alignment start-stop positions.
+ * (sf[f].end < sstart || sf[f].begin > sstop) || // or ignore based on
+ * selection criteria (featureLabels != null &&
+ * !AlignmentSorter.containsIgnoreCase(sf[f].type, featureLabels)) ||
+ * (groupLabels != null // problem here: we cannot eliminate null feature
+ * group features && (sf[f].getFeatureGroup() != null &&
+ * !AlignmentSorter.containsIgnoreCase(sf[f].getFeatureGroup(),
+ * groupLabels)))) { // forget about this feature sf[f] = null; n--; } else
+ * { // or, also take a look at the scores if necessary. if (!ignoreScore &&
+ * sf[f].getScore()!=Float.NaN) { if (seqScores[i]==0) { hasScores++; }
+ * seqScores[i]++; hasScore[i] = true; scores[i] += sf[f].getScore(); //
+ * take the first instance of this // score. } } } SequenceFeature[] fs;
+ * feats[i] = fs = new SequenceFeature[n]; if (n>0) { n=0; for (int
+ * f=0;f<sf.length;f++) { if (sf[f]!=null) { ((SequenceFeature[])
+ * feats[i])[n++] = sf[f]; } } if (method==FEATURE_LABEL) { // order the
+ * labels by alphabet String[] labs = new String[fs.length]; for (int
+ * l=0;l<labs.length; l++) { labs[l] = (fs[l].getDescription()!=null ?
+ * fs[l].getDescription() : fs[l].getType()); }
+ * jalview.util.QuickSort.sort(labs, ((Object[]) feats[i])); } } if
+ * (hasScore[i]) { // compute average score scores[i]/=seqScores[i]; //
+ * update the score bounds. if (hasScores == 1) { max = min = scores[i]; }
+ * else { if (max < scores[i]) { max = scores[i]; } if (min > scores[i]) {
+ * min = scores[i]; } } } }
+ *
+ * if (method==FEATURE_SCORE) { if (hasScores == 0) { return; // do nothing
+ * - no scores present to sort by. } // pad score matrix if (hasScores <
+ * seqs.length) { for (int i = 0; i < seqs.length; i++) { if (!hasScore[i])
+ * { scores[i] = (max + i); } else { int nf=(feats[i]==null) ? 0
+ * :((SequenceFeature[]) feats[i]).length;
+ * System.err.println("Sorting on Score: seq "+seqs[i].getName()+
+ * " Feats: "+nf+" Score : "+scores[i]); } } }
+ *
+ * jalview.util.QuickSort.sort(scores, seqs); } else if
+ * (method==FEATURE_DENSITY) {
+ *
+ * // break ties between equivalent numbers for adjacent sequences by adding
+ * 1/Nseq*i on the original order double fr = 0.9/(1.0*seqs.length); for
+ * (int i=0;i<seqs.length; i++) { double nf; scores[i] =
+ * (0.05+fr*i)+(nf=((feats[i]==null) ? 0.0 :1.0*((SequenceFeature[])
+ * feats[i]).length));
+ * System.err.println("Sorting on Density: seq "+seqs[i].getName()+
+ * " Feats: "+nf+" Score : "+scores[i]); }
+ * jalview.util.QuickSort.sort(scores, seqs); } else { if
+ * (method==FEATURE_LABEL) { throw new Error("Not yet implemented."); } } if
+ * (lastSortByFeatureScore ==null ||
+ * scoreLabel.equals(lastSortByFeatureScore)) { setOrder(alignment, seqs); }
+ * else { setReverseOrder(alignment, seqs); } lastSortByFeatureScore =
+ * scoreLabel.toString();
+ */
}
-
}
git://source.jalview.org / jalview.git / blobdiff