*/
package jalview.datamodel.features;
-import jalview.datamodel.SequenceFeature;
-import jalview.io.gff.SequenceOntologyFactory;
-import jalview.io.gff.SequenceOntologyI;
-
import java.util.ArrayList;
import java.util.Arrays;
+import java.util.Collections;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.TreeMap;
import intervalstore.api.IntervalI;
+import jalview.datamodel.SequenceFeature;
+import jalview.io.gff.SequenceOntologyFactory;
+import jalview.io.gff.SequenceOntologyI;
/**
* A class that stores sequence features in a way that supports efficient
*/
public class SequenceFeatures implements SequenceFeaturesI
{
-
/*
* map from feature type to structured store of features for that type
* null types are permitted (but not a good idea!)
return new ArrayList<>();
}
- return getAllFeatures(featureTypes.toArray(new String[featureTypes
- .size()]));
+ return getAllFeatures(
+ featureTypes.toArray(new String[featureTypes.size()]));
}
/**
* {@inheritDoc}
*/
@Override
+ public List<Integer> getFeatureExtent(String... type)
+ {
+ Integer from = 0, to = 0;
+
+ for (FeatureStore featureSet : varargToTypes(type))
+ {
+ if (from == 0)
+ {
+ from = featureSet.getBegin();
+ to = featureSet.getEnd();
+ }
+ else
+ {
+ from = Math.min(from, featureSet.getBegin());
+ to = Math.max(to, featureSet.getEnd());
+ }
+ }
+ return Arrays.asList(from, to);
+ }
+
+ /**
+ * {@inheritDoc}
+ */
+ @Override
public List<SequenceFeature> getPositionalFeatures(String... type)
{
List<SequenceFeature> result = new ArrayList<>();
/**
* A convenience method that converts a vararg for feature types to an
- * Iterable over matched feature sets in key order
+ * Iterable over matched feature sets. If no types are specified, all feature
+ * sets are returned. If one or more types are specified, feature sets for
+ * those types are returned, preserving the order of the types.
*
* @param type
* @return
}
List<FeatureStore> types = new ArrayList<>();
- List<String> args = Arrays.asList(type);
- for (Entry<String, FeatureStore> featureType : featureStore.entrySet())
+ for (String theType : type)
{
- if (args.contains(featureType.getKey()))
+ if (theType != null && featureStore.containsKey(theType))
{
- types.add(featureType.getValue());
+ types.add(featureStore.get(theType));
}
}
return types;
for (Entry<String, FeatureStore> featureType : featureStore.entrySet())
{
- Set<String> featureGroups = featureType.getValue().getFeatureGroups(
- positionalFeatures);
+ Set<String> featureGroups = featureType.getValue()
+ .getFeatureGroups(positionalFeatures);
for (String group : groups)
{
if (featureGroups.contains(group))
@Override
public float getMinimumScore(String type, boolean positional)
{
- return featureStore.containsKey(type) ? featureStore.get(type)
- .getMinimumScore(positional) : Float.NaN;
+ return featureStore.containsKey(type)
+ ? featureStore.get(type).getMinimumScore(positional)
+ : Float.NaN;
}
/**
@Override
public float getMaximumScore(String type, boolean positional)
{
- return featureStore.containsKey(type) ? featureStore.get(type)
- .getMaximumScore(positional) : Float.NaN;
+ return featureStore.containsKey(type)
+ ? featureStore.get(type).getMaximumScore(positional)
+ : Float.NaN;
}
/**
public static void sortFeatures(List<? extends IntervalI> features,
final boolean forwardStrand)
{
- IntervalI.sortIntervals(features, forwardStrand);
+ Collections.sort(features,
+ forwardStrand ? IntervalI.COMPARE_BEGIN_ASC_END_DESC
+ : IntervalI.COMPARE_END_DESC);
}
/**