package jalview.datamodel.features;
+import jalview.datamodel.ContiguousI;
import jalview.datamodel.SequenceFeature;
import java.util.ArrayList;
*/
abstract boolean compare(SequenceFeature entry);
+ /**
+ * serves a search condition for finding the first feature whose start
+ * position follows a given target location
+ *
+ * @param target
+ * @return
+ */
static SearchCriterion byStart(final long target)
{
return new SearchCriterion() {
};
}
+ /**
+ * serves a search condition for finding the first feature whose end
+ * position is at or follows a given target location
+ *
+ * @param target
+ * @return
+ */
static SearchCriterion byEnd(final long target)
{
return new SearchCriterion()
};
}
+ /**
+ * serves a search condition for finding the first feature which follows the
+ * given range as determined by a supplied comparator
+ *
+ * @param target
+ * @return
+ */
static SearchCriterion byFeature(final ContiguousI to,
final Comparator<ContiguousI> rc)
{
}
}
- Comparator<ContiguousI> startOrdering = new RangeComparator(true);
-
- Comparator<ContiguousI> endOrdering = new RangeComparator(false);
-
/*
* Non-positional features have no (zero) start/end position.
* Kept as a separate list in case this criterion changes in future.
*/
int totalExtent;
+ float positionalMinScore;
+
+ float positionalMaxScore;
+
+ float nonPositionalMinScore;
+
+ float nonPositionalMaxScore;
+
/**
* Constructor
*/
{
nonNestedFeatures = new ArrayList<SequenceFeature>();
positionalFeatureGroups = new HashSet<String>();
+ nonPositionalFeatureGroups = new HashSet<String>();
+ positionalMinScore = Float.NaN;
+ positionalMaxScore = Float.NaN;
+ nonPositionalMinScore = Float.NaN;
+ nonPositionalMaxScore = Float.NaN;
// we only construct nonPositionalFeatures, contactFeatures
// or the NCList if we need to
*/
public boolean addFeature(SequenceFeature feature)
{
+ if (contains(feature))
+ {
+ return false;
+ }
+
/*
* keep a record of feature groups
*/
}
else
{
- if (!nonNestedFeatures.contains(feature))
+ added = addNonNestedFeature(feature);
+ if (!added)
+ {
+ /*
+ * detected a nested feature - put it in the NCList structure
+ */
+ added = addNestedFeature(feature);
+ }
+ }
+
+ if (added)
+ {
+ /*
+ * record the total extent of positional features, to make
+ * getTotalFeatureLength possible; we count the length of a
+ * contact feature as 1
+ */
+ totalExtent += getFeatureLength(feature);
+
+ /*
+ * record the minimum and maximum score for positional
+ * and non-positional features
+ */
+ float score = feature.getScore();
+ if (!Float.isNaN(score))
{
- added = addNonNestedFeature(feature);
- if (!added)
+ if (feature.isNonPositional())
+ {
+ nonPositionalMinScore = min(nonPositionalMinScore, score);
+ nonPositionalMaxScore = max(nonPositionalMaxScore, score);
+ }
+ else
{
- /*
- * detected a nested feature - put it in the NCList structure
- */
- added = addNestedFeature(feature);
+ positionalMinScore = min(positionalMinScore, score);
+ positionalMaxScore = max(positionalMaxScore, score);
}
}
}
- /*
- * record the total extent of positional features, to make
- * getAverageFeatureLength possible; we count the length of a
- * contact feature as 1
- */
- if (added && !feature.isNonPositional())
+ return added;
+ }
+
+ /**
+ * Answers true if this store contains the given feature (testing by
+ * SequenceFeature.equals), else false
+ *
+ * @param feature
+ * @return
+ */
+ public boolean contains(SequenceFeature feature)
+ {
+ if (feature.isNonPositional())
{
- int featureLength = feature.isContactFeature() ? 1 : 1
- + feature.getEnd() - feature.getBegin();
- totalExtent += featureLength;
+ return nonPositionalFeatures == null ? false : nonPositionalFeatures
+ .contains(feature);
}
- return added;
+ if (feature.isContactFeature())
+ {
+ return contactFeatureStarts == null ? false : listContains(
+ contactFeatureStarts, feature);
+ }
+
+ if (listContains(nonNestedFeatures, feature))
+ {
+ return true;
+ }
+
+ return nestedFeatures == null ? false : nestedFeatures
+ .contains(feature);
+ }
+
+ /**
+ * Answers the 'length' of the feature, counting 0 for non-positional features
+ * and 1 for contact features
+ *
+ * @param feature
+ * @return
+ */
+ protected static int getFeatureLength(SequenceFeature feature)
+ {
+ if (feature.isNonPositional())
+ {
+ return 0;
+ }
+ if (feature.isContactFeature())
+ {
+ return 1;
+ }
+ return 1 + feature.getEnd() - feature.getBegin();
}
/**
* Adds the feature to the list of non-positional features (with lazy
- * instantiation of the list if it is null), and returns true. If the
- * non-positional features already include the new feature (by equality test),
- * then it is not added, and this method returns false. The feature group is
- * added to the set of distinct feature groups for non-positional features.
+ * instantiation of the list if it is null), and returns true. The feature
+ * group is added to the set of distinct feature groups for non-positional
+ * features. This method allows duplicate features, so test before calling to
+ * prevent this.
*
* @param feature
*/
if (nonPositionalFeatures == null)
{
nonPositionalFeatures = new ArrayList<SequenceFeature>();
- nonPositionalFeatureGroups = new HashSet<String>();
- }
- if (nonPositionalFeatures.contains(feature))
- {
- return false;
}
nonPositionalFeatures.add(feature);
{
if (nestedFeatures == null)
{
- nestedFeatures = new NCList<SequenceFeature>(feature);
+ nestedFeatures = new NCList<>(feature);
return true;
}
return nestedFeatures.add(feature, false);
* find the first stored feature which doesn't precede the new one
*/
int insertPosition = binarySearch(nonNestedFeatures,
- SearchCriterion.byFeature(feature, startOrdering));
+ SearchCriterion.byFeature(feature, RangeComparator.BY_START_POSITION));
/*
* fail if we detect feature enclosure - of the new feature by
/**
* Add a contact feature to the lists that hold them ordered by start (first
* contact) and by end (second contact) position, ensuring the lists remain
- * ordered, and returns true. If the contact feature lists already contain the
- * given feature (by test for equality), does not add it and returns false.
+ * ordered, and returns true. This method allows duplicate features to be
+ * added, so test before calling to avoid this.
*
* @param feature
* @return
contactFeatureEnds = new ArrayList<SequenceFeature>();
}
- // TODO binary search for insertion points!
- if (contactFeatureStarts.contains(feature))
+ /*
+ * binary search the sorted list to find the insertion point
+ */
+ int insertPosition = binarySearch(contactFeatureStarts,
+ SearchCriterion.byFeature(feature,
+ RangeComparator.BY_START_POSITION));
+ contactFeatureStarts.add(insertPosition, feature);
+ // and resort to mak siccar...just in case insertion point not quite right
+ Collections.sort(contactFeatureStarts, RangeComparator.BY_START_POSITION);
+
+ insertPosition = binarySearch(contactFeatureStarts,
+ SearchCriterion.byFeature(feature,
+ RangeComparator.BY_END_POSITION));
+ contactFeatureEnds.add(feature);
+ Collections.sort(contactFeatureEnds, RangeComparator.BY_END_POSITION);
+
+ return true;
+ }
+
+ /**
+ * Answers true if the list contains the feature, else false. This method is
+ * optimised for the condition that the list is sorted on feature start
+ * position ascending, and will give unreliable results if this does not hold.
+ *
+ * @param features
+ * @param feature
+ * @return
+ */
+ protected static boolean listContains(List<SequenceFeature> features,
+ SequenceFeature feature)
+ {
+ if (features == null || feature == null)
{
return false;
}
- contactFeatureStarts.add(feature);
- Collections.sort(contactFeatureStarts, startOrdering);
- contactFeatureEnds.add(feature);
- Collections.sort(contactFeatureEnds, endOrdering);
-
- return true;
+ /*
+ * locate the first entry in the list which does not precede the feature
+ */
+ int pos = binarySearch(features,
+ SearchCriterion.byFeature(feature, RangeComparator.BY_START_POSITION));
+ int len = features.size();
+ while (pos < len)
+ {
+ SequenceFeature sf = features.get(pos);
+ if (sf.getBegin() > feature.getBegin())
+ {
+ return false; // no match found
+ }
+ if (sf.equals(feature))
+ {
+ return true;
+ }
+ pos++;
+ }
+ return false;
}
/**
*/
public List<SequenceFeature> findOverlappingFeatures(long start, long end)
{
- List<SequenceFeature> result = new ArrayList<SequenceFeature>();
+ List<SequenceFeature> result = new ArrayList<>();
findNonNestedFeatures(start, end, result);
protected void findNonNestedFeatures(long from, long to,
List<SequenceFeature> result)
{
+ /*
+ * find the first feature whose end position is
+ * after the target range start
+ */
int startIndex = binarySearch(nonNestedFeatures,
SearchCriterion.byEnd(from));
- findNonNestedFeatures(startIndex, from, to, result);
- }
-
- /**
- * Scans the list of non-nested features, starting from startIndex, to find
- * those that overlap the from-to range, and adds them to the result list.
- * Returns the index of the first feature whose start position is after the
- * target range (or the length of the whole list if none such feature exists).
- *
- * @param startIndex
- * @param from
- * @param to
- * @param result
- * @return
- */
- protected int findNonNestedFeatures(final int startIndex, long from,
- long to, List<SequenceFeature> result)
- {
- int i = startIndex;
+ final int startIndex1 = startIndex;
+ int i = startIndex1;
while (i < nonNestedFeatures.size())
{
SequenceFeature sf = nonNestedFeatures.get(i);
{
break;
}
- int start = sf.getBegin();
- int end = sf.getEnd();
- if (start <= to && end >= from)
+ if (sf.getBegin() <= to && sf.getEnd() >= from)
{
result.add(sf);
}
i++;
}
- return i;
}
/**
/*
* add non-nested features (may be all features for many cases)
*/
- List<SequenceFeature> result = new ArrayList<SequenceFeature>();
+ List<SequenceFeature> result = new ArrayList<>();
result.addAll(nonNestedFeatures);
/*
{
return Collections.emptyList();
}
- return new ArrayList<SequenceFeature>(contactFeatureStarts);
+ return new ArrayList<>(contactFeatureStarts);
}
/**
{
return Collections.emptyList();
}
- return new ArrayList<SequenceFeature>(nonPositionalFeatures);
+ return new ArrayList<>(nonPositionalFeatures);
}
/**
if (removed)
{
- rebuildFeatureGroups(sf.getFeatureGroup(), removedNonPositional);
- // TODO and recalculate totalExtent (feature may have changed length!)
+ rescanAfterDelete();
}
return removed;
}
/**
- * Check whether the given feature group is still represented, in either
- * positional or non-positional features, and if not, remove it from the set
- * of feature groups
+ * Rescan all features to recompute any cached values after an entry has been
+ * deleted. This is expected to be an infrequent event, so performance here is
+ * not critical.
+ */
+ protected synchronized void rescanAfterDelete()
+ {
+ positionalFeatureGroups.clear();
+ nonPositionalFeatureGroups.clear();
+ totalExtent = 0;
+ positionalMinScore = Float.NaN;
+ positionalMaxScore = Float.NaN;
+ nonPositionalMinScore = Float.NaN;
+ nonPositionalMaxScore = Float.NaN;
+
+ /*
+ * scan non-positional features for groups and scores
+ */
+ for (SequenceFeature sf : getNonPositionalFeatures())
+ {
+ nonPositionalFeatureGroups.add(sf.getFeatureGroup());
+ float score = sf.getScore();
+ nonPositionalMinScore = min(nonPositionalMinScore, score);
+ nonPositionalMaxScore = max(nonPositionalMaxScore, score);
+ }
+
+ /*
+ * scan positional features for groups, scores and extents
+ */
+ for (SequenceFeature sf : getPositionalFeatures())
+ {
+ positionalFeatureGroups.add(sf.getFeatureGroup());
+ float score = sf.getScore();
+ positionalMinScore = min(positionalMinScore, score);
+ positionalMaxScore = max(positionalMaxScore, score);
+ totalExtent += getFeatureLength(sf);
+ }
+ }
+
+ /**
+ * A helper method to return the minimum of two floats, where a non-NaN value
+ * is treated as 'less than' a NaN value (unlike Math.min which does the
+ * opposite)
*
- * @param featureGroup
- * @param nonPositional
+ * @param f1
+ * @param f2
*/
- protected void rebuildFeatureGroups(String featureGroup,
- boolean nonPositional)
+ protected static float min(float f1, float f2)
{
- if (nonPositional && nonPositionalFeatures != null)
+ if (Float.isNaN(f1))
{
- boolean found = false;
- for (SequenceFeature sf : nonPositionalFeatures)
- {
- String group = sf.getFeatureGroup();
- if (featureGroup == group
- || (featureGroup != null && featureGroup.equals(group)))
- {
- found = true;
- break;
- }
- }
- if (!found)
- {
- nonPositionalFeatureGroups.remove(featureGroup);
- }
+ return Float.isNaN(f2) ? f1 : f2;
}
- else if (!findFeatureGroup(featureGroup))
+ else
{
- positionalFeatureGroups.remove(featureGroup);
+ return Float.isNaN(f2) ? f1 : Math.min(f1, f2);
}
}
/**
- * Scans all positional features to check whether the given feature group is
- * found, and returns true if found, else false
+ * A helper method to return the maximum of two floats, where a non-NaN value
+ * is treated as 'greater than' a NaN value (unlike Math.max which does the
+ * opposite)
*
- * @param featureGroup
- * @return
+ * @param f1
+ * @param f2
*/
- protected boolean findFeatureGroup(String featureGroup)
+ protected static float max(float f1, float f2)
{
- for (SequenceFeature sf : getPositionalFeatures())
+ if (Float.isNaN(f1))
{
- String group = sf.getFeatureGroup();
- if (group == featureGroup
- || (group != null && group.equals(featureGroup)))
- {
- return true;
- }
+ return Float.isNaN(f2) ? f1 : f2;
+ }
+ else
+ {
+ return Float.isNaN(f2) ? f1 : Math.max(f1, f2);
}
- return false;
}
/**
* @param sc
* @return
*/
- protected int binarySearch(List<SequenceFeature> features,
+ protected static int binarySearch(List<SequenceFeature> features,
SearchCriterion sc)
{
int start = 0;
}
/**
- * Answers the number of positional (or non-positional) features stored
+ * Answers the number of positional (or non-positional) features stored.
+ * Contact features count as 1.
*
* @param positional
* @return
*/
- public int size(boolean positional)
+ public int getFeatureCount(boolean positional)
{
if (!positional)
{
}
/**
- * Answers the average length of positional features (or zero if there are
- * none). Contact features contribute a value of 1 to the average.
+ * Answers the total length of positional features (or zero if there are
+ * none). Contact features contribute a value of 1 to the total.
+ *
+ * @return
+ */
+ public int getTotalFeatureLength()
+ {
+ return totalExtent;
+ }
+
+ /**
+ * Answers the minimum score held for positional or non-positional features.
+ * This may be Float.NaN if there are no features, are none has a non-NaN
+ * score.
*
+ * @param positional
* @return
*/
- public float getAverageFeatureLength()
+ public float getMinimumScore(boolean positional)
{
- int d = size(true);
- return d == 0 ? 0f : (float) totalExtent / d;
+ return positional ? positionalMinScore : nonPositionalMinScore;
+ }
+
+ /**
+ * Answers the maximum score held for positional or non-positional features.
+ * This may be Float.NaN if there are no features, are none has a non-NaN
+ * score.
+ *
+ * @param positional
+ * @return
+ */
+ public float getMaximumScore(boolean positional)
+ {
+ return positional ? positionalMaxScore : nonPositionalMaxScore;
+ }
+
+ /**
+ * Answers a list of all either positional or non-positional features whose
+ * feature group matches the given group (which may be null)
+ *
+ * @param positional
+ * @param group
+ * @return
+ */
+ public List<SequenceFeature> getFeaturesForGroup(boolean positional,
+ String group)
+ {
+ List<SequenceFeature> result = new ArrayList<>();
+
+ /*
+ * if we know features don't include the target group, no need
+ * to inspect them for matches
+ */
+ if (positional && !positionalFeatureGroups.contains(group)
+ || !positional && !nonPositionalFeatureGroups.contains(group))
+ {
+ return result;
+ }
+
+ List<SequenceFeature> sfs = positional ? getPositionalFeatures()
+ : getNonPositionalFeatures();
+ for (SequenceFeature sf : sfs)
+ {
+ String featureGroup = sf.getFeatureGroup();
+ if (group == null && featureGroup == null || group != null
+ && group.equals(featureGroup))
+ {
+ result.add(sf);
+ }
+ }
+ return result;
+ }
+
+ /**
+ * Adds the shift value to the start and end of all positional features.
+ * Returns true if at least one feature was updated, else false.
+ *
+ * @param shift
+ * @return
+ */
+ public synchronized boolean shiftFeatures(int shift)
+ {
+ /*
+ * Because begin and end are final fields (to ensure the data store's
+ * integrity), we have to delete each feature and re-add it as amended.
+ * (Although a simple shift of all values would preserve data integrity!)
+ */
+ boolean modified = false;
+ for (SequenceFeature sf : getPositionalFeatures())
+ {
+ modified = true;
+ int newBegin = sf.getBegin() + shift;
+ int newEnd = sf.getEnd() + shift;
+
+ /*
+ * sanity check: don't shift left of the first residue
+ */
+ if (newEnd > 0)
+ {
+ newBegin = Math.max(1, newBegin);
+ SequenceFeature sf2 = new SequenceFeature(sf, newBegin, newEnd,
+ sf.getFeatureGroup(), sf.getScore());
+ addFeature(sf2);
+ }
+ delete(sf);
+ }
+ return modified;
}
}
git://source.jalview.org / jalview.git / blobdiff