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elki-project/elki | elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/ELKIServiceLoader.java | ELKIServiceLoader.parseLine | private static void parseLine(Class<?> parent, char[] line, int begin, int end) {
while(begin < end && line[begin] == ' ') {
begin++;
}
if(begin >= end || line[begin] == '#') {
return; // Empty/comment lines are okay, continue
}
// Find end of class name:
int cend = begin + 1;
while(cend < end && line[cend] != ' ') {
cend++;
}
// Class name:
String cname = new String(line, begin, cend - begin);
ELKIServiceRegistry.register(parent, cname);
for(int abegin = cend + 1, aend = -1; abegin < end; abegin = aend + 1) {
// Skip whitespace:
while(abegin < end && line[abegin] == ' ') {
abegin++;
}
// Find next whitespace:
aend = abegin + 1;
while(aend < end && line[aend] != ' ') {
aend++;
}
ELKIServiceRegistry.registerAlias(parent, new String(line, abegin, aend - abegin), cname);
}
return;
} | java | private static void parseLine(Class<?> parent, char[] line, int begin, int end) {
while(begin < end && line[begin] == ' ') {
begin++;
}
if(begin >= end || line[begin] == '#') {
return; // Empty/comment lines are okay, continue
}
// Find end of class name:
int cend = begin + 1;
while(cend < end && line[cend] != ' ') {
cend++;
}
// Class name:
String cname = new String(line, begin, cend - begin);
ELKIServiceRegistry.register(parent, cname);
for(int abegin = cend + 1, aend = -1; abegin < end; abegin = aend + 1) {
// Skip whitespace:
while(abegin < end && line[abegin] == ' ') {
abegin++;
}
// Find next whitespace:
aend = abegin + 1;
while(aend < end && line[aend] != ' ') {
aend++;
}
ELKIServiceRegistry.registerAlias(parent, new String(line, abegin, aend - abegin), cname);
}
return;
} | [
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elki-project/elki | elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/rdknn/RdKNNLeafEntry.java | RdKNNLeafEntry.readExternal | @Override
public void readExternal(ObjectInput in) throws IOException, ClassNotFoundException {
super.readExternal(in);
this.knnDistance = in.readDouble();
} | java | @Override
public void readExternal(ObjectInput in) throws IOException, ClassNotFoundException {
super.readExternal(in);
this.knnDistance = in.readDouble();
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elki-project/elki | elki-outlier/src/main/java/de/lmu/ifi/dbs/elki/algorithm/outlier/lof/OnlineLOF.java | OnlineLOF.getKNNAndRkNNQueries | private Pair<Pair<KNNQuery<O>, KNNQuery<O>>, Pair<RKNNQuery<O>, RKNNQuery<O>>> getKNNAndRkNNQueries(Database database, Relation<O> relation, StepProgress stepprog) {
DistanceQuery<O> drefQ = database.getDistanceQuery(relation, referenceDistanceFunction);
// Use "HEAVY" flag, since this is an online algorithm
KNNQuery<O> kNNRefer = database.getKNNQuery(drefQ, krefer, DatabaseQuery.HINT_HEAVY_USE, DatabaseQuery.HINT_OPTIMIZED_ONLY, DatabaseQuery.HINT_NO_CACHE);
RKNNQuery<O> rkNNRefer = database.getRKNNQuery(drefQ, DatabaseQuery.HINT_HEAVY_USE, DatabaseQuery.HINT_OPTIMIZED_ONLY, DatabaseQuery.HINT_NO_CACHE);
// No optimized kNN query or RkNN query - use a preprocessor!
if(kNNRefer == null || rkNNRefer == null) {
if(stepprog != null) {
stepprog.beginStep(1, "Materializing neighborhood w.r.t. reference neighborhood distance function.", LOG);
}
MaterializeKNNAndRKNNPreprocessor<O> preproc = new MaterializeKNNAndRKNNPreprocessor<>(relation, referenceDistanceFunction, krefer);
kNNRefer = preproc.getKNNQuery(drefQ, krefer, DatabaseQuery.HINT_HEAVY_USE);
rkNNRefer = preproc.getRKNNQuery(drefQ, krefer, DatabaseQuery.HINT_HEAVY_USE);
// add as index
database.getHierarchy().add(relation, preproc);
}
else {
if(stepprog != null) {
stepprog.beginStep(1, "Optimized neighborhood w.r.t. reference neighborhood distance function provided by database.", LOG);
}
}
DistanceQuery<O> dreachQ = database.getDistanceQuery(relation, reachabilityDistanceFunction);
KNNQuery<O> kNNReach = database.getKNNQuery(dreachQ, kreach, DatabaseQuery.HINT_HEAVY_USE, DatabaseQuery.HINT_OPTIMIZED_ONLY, DatabaseQuery.HINT_NO_CACHE);
RKNNQuery<O> rkNNReach = database.getRKNNQuery(dreachQ, DatabaseQuery.HINT_HEAVY_USE, DatabaseQuery.HINT_OPTIMIZED_ONLY, DatabaseQuery.HINT_NO_CACHE);
if(kNNReach == null || rkNNReach == null) {
if(stepprog != null) {
stepprog.beginStep(2, "Materializing neighborhood w.r.t. reachability distance function.", LOG);
}
ListParameterization config = new ListParameterization();
config.addParameter(AbstractMaterializeKNNPreprocessor.Factory.DISTANCE_FUNCTION_ID, reachabilityDistanceFunction);
config.addParameter(AbstractMaterializeKNNPreprocessor.Factory.K_ID, kreach);
MaterializeKNNAndRKNNPreprocessor<O> preproc = new MaterializeKNNAndRKNNPreprocessor<>(relation, reachabilityDistanceFunction, kreach);
kNNReach = preproc.getKNNQuery(dreachQ, kreach, DatabaseQuery.HINT_HEAVY_USE);
rkNNReach = preproc.getRKNNQuery(dreachQ, kreach, DatabaseQuery.HINT_HEAVY_USE);
// add as index
database.getHierarchy().add(relation, preproc);
}
Pair<KNNQuery<O>, KNNQuery<O>> kNNPair = new Pair<>(kNNRefer, kNNReach);
Pair<RKNNQuery<O>, RKNNQuery<O>> rkNNPair = new Pair<>(rkNNRefer, rkNNReach);
return new Pair<>(kNNPair, rkNNPair);
} | java | private Pair<Pair<KNNQuery<O>, KNNQuery<O>>, Pair<RKNNQuery<O>, RKNNQuery<O>>> getKNNAndRkNNQueries(Database database, Relation<O> relation, StepProgress stepprog) {
DistanceQuery<O> drefQ = database.getDistanceQuery(relation, referenceDistanceFunction);
// Use "HEAVY" flag, since this is an online algorithm
KNNQuery<O> kNNRefer = database.getKNNQuery(drefQ, krefer, DatabaseQuery.HINT_HEAVY_USE, DatabaseQuery.HINT_OPTIMIZED_ONLY, DatabaseQuery.HINT_NO_CACHE);
RKNNQuery<O> rkNNRefer = database.getRKNNQuery(drefQ, DatabaseQuery.HINT_HEAVY_USE, DatabaseQuery.HINT_OPTIMIZED_ONLY, DatabaseQuery.HINT_NO_CACHE);
// No optimized kNN query or RkNN query - use a preprocessor!
if(kNNRefer == null || rkNNRefer == null) {
if(stepprog != null) {
stepprog.beginStep(1, "Materializing neighborhood w.r.t. reference neighborhood distance function.", LOG);
}
MaterializeKNNAndRKNNPreprocessor<O> preproc = new MaterializeKNNAndRKNNPreprocessor<>(relation, referenceDistanceFunction, krefer);
kNNRefer = preproc.getKNNQuery(drefQ, krefer, DatabaseQuery.HINT_HEAVY_USE);
rkNNRefer = preproc.getRKNNQuery(drefQ, krefer, DatabaseQuery.HINT_HEAVY_USE);
// add as index
database.getHierarchy().add(relation, preproc);
}
else {
if(stepprog != null) {
stepprog.beginStep(1, "Optimized neighborhood w.r.t. reference neighborhood distance function provided by database.", LOG);
}
}
DistanceQuery<O> dreachQ = database.getDistanceQuery(relation, reachabilityDistanceFunction);
KNNQuery<O> kNNReach = database.getKNNQuery(dreachQ, kreach, DatabaseQuery.HINT_HEAVY_USE, DatabaseQuery.HINT_OPTIMIZED_ONLY, DatabaseQuery.HINT_NO_CACHE);
RKNNQuery<O> rkNNReach = database.getRKNNQuery(dreachQ, DatabaseQuery.HINT_HEAVY_USE, DatabaseQuery.HINT_OPTIMIZED_ONLY, DatabaseQuery.HINT_NO_CACHE);
if(kNNReach == null || rkNNReach == null) {
if(stepprog != null) {
stepprog.beginStep(2, "Materializing neighborhood w.r.t. reachability distance function.", LOG);
}
ListParameterization config = new ListParameterization();
config.addParameter(AbstractMaterializeKNNPreprocessor.Factory.DISTANCE_FUNCTION_ID, reachabilityDistanceFunction);
config.addParameter(AbstractMaterializeKNNPreprocessor.Factory.K_ID, kreach);
MaterializeKNNAndRKNNPreprocessor<O> preproc = new MaterializeKNNAndRKNNPreprocessor<>(relation, reachabilityDistanceFunction, kreach);
kNNReach = preproc.getKNNQuery(dreachQ, kreach, DatabaseQuery.HINT_HEAVY_USE);
rkNNReach = preproc.getRKNNQuery(dreachQ, kreach, DatabaseQuery.HINT_HEAVY_USE);
// add as index
database.getHierarchy().add(relation, preproc);
}
Pair<KNNQuery<O>, KNNQuery<O>> kNNPair = new Pair<>(kNNRefer, kNNReach);
Pair<RKNNQuery<O>, RKNNQuery<O>> rkNNPair = new Pair<>(rkNNRefer, rkNNReach);
return new Pair<>(kNNPair, rkNNPair);
} | [
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] | b54673327e76198ecd4c8a2a901021f1a9174498 | https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-outlier/src/main/java/de/lmu/ifi/dbs/elki/algorithm/outlier/lof/OnlineLOF.java#L121-L165 | train |
elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/gdbscan/COPACNeighborPredicate.java | COPACNeighborPredicate.instantiate | public COPACNeighborPredicate.Instance instantiate(Database database, Relation<V> relation) {
DistanceQuery<V> dq = database.getDistanceQuery(relation, EuclideanDistanceFunction.STATIC);
KNNQuery<V> knnq = database.getKNNQuery(dq, settings.k);
WritableDataStore<COPACModel> storage = DataStoreUtil.makeStorage(relation.getDBIDs(), DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_TEMP, COPACModel.class);
Duration time = LOG.newDuration(this.getClass().getName() + ".preprocessing-time").begin();
FiniteProgress progress = LOG.isVerbose() ? new FiniteProgress(this.getClass().getName(), relation.size(), LOG) : null;
for(DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) {
DoubleDBIDList ref = knnq.getKNNForDBID(iditer, settings.k);
storage.put(iditer, computeLocalModel(iditer, ref, relation));
LOG.incrementProcessed(progress);
}
LOG.ensureCompleted(progress);
LOG.statistics(time.end());
return new Instance(relation.getDBIDs(), storage);
} | java | public COPACNeighborPredicate.Instance instantiate(Database database, Relation<V> relation) {
DistanceQuery<V> dq = database.getDistanceQuery(relation, EuclideanDistanceFunction.STATIC);
KNNQuery<V> knnq = database.getKNNQuery(dq, settings.k);
WritableDataStore<COPACModel> storage = DataStoreUtil.makeStorage(relation.getDBIDs(), DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_TEMP, COPACModel.class);
Duration time = LOG.newDuration(this.getClass().getName() + ".preprocessing-time").begin();
FiniteProgress progress = LOG.isVerbose() ? new FiniteProgress(this.getClass().getName(), relation.size(), LOG) : null;
for(DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) {
DoubleDBIDList ref = knnq.getKNNForDBID(iditer, settings.k);
storage.put(iditer, computeLocalModel(iditer, ref, relation));
LOG.incrementProcessed(progress);
}
LOG.ensureCompleted(progress);
LOG.statistics(time.end());
return new Instance(relation.getDBIDs(), storage);
} | [
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/gdbscan/COPACNeighborPredicate.java | COPACNeighborPredicate.computeLocalModel | protected COPACModel computeLocalModel(DBIDRef id, DoubleDBIDList knnneighbors, Relation<V> relation) {
PCAResult epairs = settings.pca.processIds(knnneighbors, relation);
int pdim = settings.filter.filter(epairs.getEigenvalues());
PCAFilteredResult pcares = new PCAFilteredResult(epairs.getEigenPairs(), pdim, 1., 0.);
double[][] mat = pcares.similarityMatrix();
double[] vecP = relation.get(id).toArray();
if(pdim == vecP.length) {
// Full dimensional - noise!
return new COPACModel(pdim, DBIDUtil.EMPTYDBIDS);
}
// Check which neighbors survive
HashSetModifiableDBIDs survivors = DBIDUtil.newHashSet();
for(DBIDIter neighbor = relation.iterDBIDs(); neighbor.valid(); neighbor.advance()) {
double[] diff = minusEquals(relation.get(neighbor).toArray(), vecP);
double cdistP = transposeTimesTimes(diff, mat, diff);
if(cdistP <= epsilonsq) {
survivors.add(neighbor);
}
}
return new COPACModel(pdim, survivors);
} | java | protected COPACModel computeLocalModel(DBIDRef id, DoubleDBIDList knnneighbors, Relation<V> relation) {
PCAResult epairs = settings.pca.processIds(knnneighbors, relation);
int pdim = settings.filter.filter(epairs.getEigenvalues());
PCAFilteredResult pcares = new PCAFilteredResult(epairs.getEigenPairs(), pdim, 1., 0.);
double[][] mat = pcares.similarityMatrix();
double[] vecP = relation.get(id).toArray();
if(pdim == vecP.length) {
// Full dimensional - noise!
return new COPACModel(pdim, DBIDUtil.EMPTYDBIDS);
}
// Check which neighbors survive
HashSetModifiableDBIDs survivors = DBIDUtil.newHashSet();
for(DBIDIter neighbor = relation.iterDBIDs(); neighbor.valid(); neighbor.advance()) {
double[] diff = minusEquals(relation.get(neighbor).toArray(), vecP);
double cdistP = transposeTimesTimes(diff, mat, diff);
if(cdistP <= epsilonsq) {
survivors.add(neighbor);
}
}
return new COPACModel(pdim, survivors);
} | [
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@param id Query object
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@param relation Data relation
@return COPAC object model | [
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] | b54673327e76198ecd4c8a2a901021f1a9174498 | https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/gdbscan/COPACNeighborPredicate.java#L141-L163 | train |
elki-project/elki | elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/AbstractRStarTreeNode.java | AbstractRStarTreeNode.computeMBR | public ModifiableHyperBoundingBox computeMBR() {
E firstEntry = getEntry(0);
if(firstEntry == null) {
return null;
}
// Note: we deliberately get a cloned copy here, since we will modify it.
ModifiableHyperBoundingBox mbr = new ModifiableHyperBoundingBox(firstEntry);
for(int i = 1; i < numEntries; i++) {
mbr.extend(getEntry(i));
}
return mbr;
} | java | public ModifiableHyperBoundingBox computeMBR() {
E firstEntry = getEntry(0);
if(firstEntry == null) {
return null;
}
// Note: we deliberately get a cloned copy here, since we will modify it.
ModifiableHyperBoundingBox mbr = new ModifiableHyperBoundingBox(firstEntry);
for(int i = 1; i < numEntries; i++) {
mbr.extend(getEntry(i));
}
return mbr;
} | [
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elki-project/elki | addons/joglvis/src/main/java/de/lmu/ifi/dbs/elki/joglvis/SimpleCamera3D.java | SimpleCamera3D.applyCamera | public void applyCamera(GL2 gl) {
// Setup projection.
gl.glMatrixMode(GL2.GL_PROJECTION);
gl.glLoadIdentity();
glu.gluPerspective(45f, // fov,
width / (float) height, // ratio
0.f, 10.f); // near, far clipping
eye[0] = (float) Math.sin(theta) * 2.f;
eye[1] = .5f;
eye[2] = (float) Math.cos(theta) * 2.f;
glu.gluLookAt(eye[0], eye[1], eye[2], // eye
.0f, .0f, 0.f, // center
0.f, 1.f, 0.f); // up
gl.glMatrixMode(GL2.GL_MODELVIEW);
gl.glLoadIdentity();
gl.glViewport(0, 0, width, height);
} | java | public void applyCamera(GL2 gl) {
// Setup projection.
gl.glMatrixMode(GL2.GL_PROJECTION);
gl.glLoadIdentity();
glu.gluPerspective(45f, // fov,
width / (float) height, // ratio
0.f, 10.f); // near, far clipping
eye[0] = (float) Math.sin(theta) * 2.f;
eye[1] = .5f;
eye[2] = (float) Math.cos(theta) * 2.f;
glu.gluLookAt(eye[0], eye[1], eye[2], // eye
.0f, .0f, 0.f, // center
0.f, 1.f, 0.f); // up
gl.glMatrixMode(GL2.GL_MODELVIEW);
gl.glLoadIdentity();
gl.glViewport(0, 0, width, height);
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elki-project/elki | elki-database/src/main/java/de/lmu/ifi/dbs/elki/database/query/knn/LinearScanDistanceKNNQuery.java | LinearScanDistanceKNNQuery.linearScanBatchKNN | private void linearScanBatchKNN(ArrayDBIDs ids, List<KNNHeap> heaps) {
final DistanceQuery<O> dq = distanceQuery;
// The distance is computed on database IDs
for(DBIDIter iter = getRelation().getDBIDs().iter(); iter.valid(); iter.advance()) {
int index = 0;
for(DBIDIter iter2 = ids.iter(); iter2.valid(); iter2.advance(), index++) {
KNNHeap heap = heaps.get(index);
heap.insert(dq.distance(iter2, iter), iter);
}
}
} | java | private void linearScanBatchKNN(ArrayDBIDs ids, List<KNNHeap> heaps) {
final DistanceQuery<O> dq = distanceQuery;
// The distance is computed on database IDs
for(DBIDIter iter = getRelation().getDBIDs().iter(); iter.valid(); iter.advance()) {
int index = 0;
for(DBIDIter iter2 = ids.iter(); iter2.valid(); iter2.advance(), index++) {
KNNHeap heap = heaps.get(index);
heap.insert(dq.distance(iter2, iter), iter);
}
}
} | [
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elki-project/elki | elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/distancefunction/colorhistogram/RGBHistogramQuadraticDistanceFunction.java | RGBHistogramQuadraticDistanceFunction.computeWeightMatrix | public static double[][] computeWeightMatrix(int bpp) {
final int dim = bpp * bpp * bpp;
final double[][] m = new double[dim][dim];
// maximum occurring distance in manhattan between bins:
final double max = 3. * (bpp - 1.);
for(int x = 0; x < dim; x++) {
final int rx = (x / bpp) / bpp;
final int gx = (x / bpp) % bpp;
final int bx = x % bpp;
for(int y = x; y < dim; y++) {
final int ry = (y / bpp) / bpp;
final int gy = (y / bpp) % bpp;
final int by = y % bpp;
final double dr = Math.abs(rx - ry);
final double dg = Math.abs(gx - gy);
final double db = Math.abs(bx - by);
final double val = 1 - (dr + dg + db) / max;
m[x][y] = m[y][x] = val;
}
}
return m;
} | java | public static double[][] computeWeightMatrix(int bpp) {
final int dim = bpp * bpp * bpp;
final double[][] m = new double[dim][dim];
// maximum occurring distance in manhattan between bins:
final double max = 3. * (bpp - 1.);
for(int x = 0; x < dim; x++) {
final int rx = (x / bpp) / bpp;
final int gx = (x / bpp) % bpp;
final int bx = x % bpp;
for(int y = x; y < dim; y++) {
final int ry = (y / bpp) / bpp;
final int gy = (y / bpp) % bpp;
final int by = y % bpp;
final double dr = Math.abs(rx - ry);
final double dg = Math.abs(gx - gy);
final double db = Math.abs(bx - by);
final double val = 1 - (dr + dg + db) / max;
m[x][y] = m[y][x] = val;
}
}
return m;
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elki-project/elki | elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/statistics/HopkinsStatisticClusteringTendency.java | HopkinsStatisticClusteringTendency.initializeDataExtends | protected void initializeDataExtends(Relation<NumberVector> relation, int dim, double[] min, double[] extend) {
assert (min.length == dim && extend.length == dim);
// if no parameter for min max compute min max values for each dimension
// from dataset
if(minima == null || maxima == null || minima.length == 0 || maxima.length == 0) {
double[][] minmax = RelationUtil.computeMinMax(relation);
final double[] dmin = minmax[0], dmax = minmax[1];
for(int d = 0; d < dim; d++) {
min[d] = dmin[d];
extend[d] = dmax[d] - dmin[d];
}
return;
}
if(minima.length == dim) {
System.arraycopy(minima, 0, min, 0, dim);
}
else if(minima.length == 1) {
Arrays.fill(min, minima[0]);
}
else {
throw new AbortException("Invalid minima specified: expected " + dim + " got minima dimensionality: " + minima.length);
}
if(maxima.length == dim) {
for(int d = 0; d < dim; d++) {
extend[d] = maxima[d] - min[d];
}
return;
}
else if(maxima.length == 1) {
for(int d = 0; d < dim; d++) {
extend[d] = maxima[0] - min[d];
}
return;
}
else {
throw new AbortException("Invalid maxima specified: expected " + dim + " got maxima dimensionality: " + maxima.length);
}
} | java | protected void initializeDataExtends(Relation<NumberVector> relation, int dim, double[] min, double[] extend) {
assert (min.length == dim && extend.length == dim);
// if no parameter for min max compute min max values for each dimension
// from dataset
if(minima == null || maxima == null || minima.length == 0 || maxima.length == 0) {
double[][] minmax = RelationUtil.computeMinMax(relation);
final double[] dmin = minmax[0], dmax = minmax[1];
for(int d = 0; d < dim; d++) {
min[d] = dmin[d];
extend[d] = dmax[d] - dmin[d];
}
return;
}
if(minima.length == dim) {
System.arraycopy(minima, 0, min, 0, dim);
}
else if(minima.length == 1) {
Arrays.fill(min, minima[0]);
}
else {
throw new AbortException("Invalid minima specified: expected " + dim + " got minima dimensionality: " + minima.length);
}
if(maxima.length == dim) {
for(int d = 0; d < dim; d++) {
extend[d] = maxima[d] - min[d];
}
return;
}
else if(maxima.length == 1) {
for(int d = 0; d < dim; d++) {
extend[d] = maxima[0] - min[d];
}
return;
}
else {
throw new AbortException("Invalid maxima specified: expected " + dim + " got maxima dimensionality: " + maxima.length);
}
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elki-project/elki | elki-index-preprocessed/src/main/java/de/lmu/ifi/dbs/elki/distance/similarityfunction/SharedNearestNeighborSimilarityFunction.java | SharedNearestNeighborSimilarityFunction.countSharedNeighbors | static protected int countSharedNeighbors(DBIDs neighbors1, DBIDs neighbors2) {
int intersection = 0;
DBIDIter iter1 = neighbors1.iter();
DBIDIter iter2 = neighbors2.iter();
while(iter1.valid() && iter2.valid()) {
final int comp = DBIDUtil.compare(iter1, iter2);
if(comp == 0) {
intersection++;
iter1.advance();
iter2.advance();
}
else if(comp < 0) {
iter1.advance();
}
else // iter2 < iter1
{
iter2.advance();
}
}
return intersection;
} | java | static protected int countSharedNeighbors(DBIDs neighbors1, DBIDs neighbors2) {
int intersection = 0;
DBIDIter iter1 = neighbors1.iter();
DBIDIter iter2 = neighbors2.iter();
while(iter1.valid() && iter2.valid()) {
final int comp = DBIDUtil.compare(iter1, iter2);
if(comp == 0) {
intersection++;
iter1.advance();
iter2.advance();
}
else if(comp < 0) {
iter1.advance();
}
else // iter2 < iter1
{
iter2.advance();
}
}
return intersection;
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elki-project/elki | elki/src/main/java/de/lmu/ifi/dbs/elki/index/idistance/InMemoryIDistanceIndex.java | InMemoryIDistanceIndex.rankReferencePoints | protected static <O> DoubleIntPair[] rankReferencePoints(DistanceQuery<O> distanceQuery, O obj, ArrayDBIDs referencepoints) {
DoubleIntPair[] priority = new DoubleIntPair[referencepoints.size()];
// Compute distances to reference points.
for(DBIDArrayIter iter = referencepoints.iter(); iter.valid(); iter.advance()) {
final int i = iter.getOffset();
final double dist = distanceQuery.distance(obj, iter);
priority[i] = new DoubleIntPair(dist, i);
}
Arrays.sort(priority);
return priority;
} | java | protected static <O> DoubleIntPair[] rankReferencePoints(DistanceQuery<O> distanceQuery, O obj, ArrayDBIDs referencepoints) {
DoubleIntPair[] priority = new DoubleIntPair[referencepoints.size()];
// Compute distances to reference points.
for(DBIDArrayIter iter = referencepoints.iter(); iter.valid(); iter.advance()) {
final int i = iter.getOffset();
final double dist = distanceQuery.distance(obj, iter);
priority[i] = new DoubleIntPair(dist, i);
}
Arrays.sort(priority);
return priority;
} | [
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@param distanceQuery Distance query
@param obj Query object
@param referencepoints Iterator for reference points
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elki-project/elki | elki/src/main/java/de/lmu/ifi/dbs/elki/index/idistance/InMemoryIDistanceIndex.java | InMemoryIDistanceIndex.binarySearch | protected static void binarySearch(ModifiableDoubleDBIDList index, DoubleDBIDListIter iter, double val) {
// Binary search. TODO: move this into the DoubleDBIDList class.
int left = 0, right = index.size();
while(left < right) {
final int mid = (left + right) >>> 1;
final double curd = iter.seek(mid).doubleValue();
if(val < curd) {
right = mid;
}
else if(val > curd) {
left = mid + 1;
}
else {
left = mid;
break;
}
}
if(left >= index.size()) {
--left;
}
iter.seek(left);
} | java | protected static void binarySearch(ModifiableDoubleDBIDList index, DoubleDBIDListIter iter, double val) {
// Binary search. TODO: move this into the DoubleDBIDList class.
int left = 0, right = index.size();
while(left < right) {
final int mid = (left + right) >>> 1;
final double curd = iter.seek(mid).doubleValue();
if(val < curd) {
right = mid;
}
else if(val > curd) {
left = mid + 1;
}
else {
left = mid;
break;
}
}
if(left >= index.size()) {
--left;
}
iter.seek(left);
} | [
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elki-project/elki | elki/src/main/java/de/lmu/ifi/dbs/elki/workflow/AlgorithmStep.java | AlgorithmStep.runAlgorithms | public Result runAlgorithms(Database database) {
ResultHierarchy hier = database.getHierarchy();
if(LOG.isStatistics()) {
boolean first = true;
for(It<Index> it = hier.iterDescendants(database).filter(Index.class); it.valid(); it.advance()) {
if(first) {
LOG.statistics("Index statistics before running algorithms:");
first = false;
}
it.get().logStatistics();
}
}
stepresult = new BasicResult("Algorithm Step", "algorithm-step");
for(Algorithm algorithm : algorithms) {
Thread.currentThread().setName(algorithm.toString());
Duration duration = LOG.isStatistics() ? LOG.newDuration(algorithm.getClass().getName() + ".runtime").begin() : null;
Result res = algorithm.run(database);
if(duration != null) {
LOG.statistics(duration.end());
}
if(LOG.isStatistics()) {
boolean first = true;
for(It<Index> it = hier.iterDescendants(database).filter(Index.class); it.valid(); it.advance()) {
if(first) {
LOG.statistics("Index statistics after running algorithm " + algorithm.toString() + ":");
first = false;
}
it.get().logStatistics();
}
}
if(res != null) {
// Make sure the result is attached, but usually this is a noop:
hier.add(database, res);
}
}
return stepresult;
} | java | public Result runAlgorithms(Database database) {
ResultHierarchy hier = database.getHierarchy();
if(LOG.isStatistics()) {
boolean first = true;
for(It<Index> it = hier.iterDescendants(database).filter(Index.class); it.valid(); it.advance()) {
if(first) {
LOG.statistics("Index statistics before running algorithms:");
first = false;
}
it.get().logStatistics();
}
}
stepresult = new BasicResult("Algorithm Step", "algorithm-step");
for(Algorithm algorithm : algorithms) {
Thread.currentThread().setName(algorithm.toString());
Duration duration = LOG.isStatistics() ? LOG.newDuration(algorithm.getClass().getName() + ".runtime").begin() : null;
Result res = algorithm.run(database);
if(duration != null) {
LOG.statistics(duration.end());
}
if(LOG.isStatistics()) {
boolean first = true;
for(It<Index> it = hier.iterDescendants(database).filter(Index.class); it.valid(); it.advance()) {
if(first) {
LOG.statistics("Index statistics after running algorithm " + algorithm.toString() + ":");
first = false;
}
it.get().logStatistics();
}
}
if(res != null) {
// Make sure the result is attached, but usually this is a noop:
hier.add(database, res);
}
}
return stepresult;
} | [
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elki-project/elki | elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/statistics/DistanceQuantileSampler.java | DistanceQuantileSampler.run | public CollectionResult<double[]> run(Database database, Relation<O> rel) {
DistanceQuery<O> dq = rel.getDistanceQuery(getDistanceFunction());
int size = rel.size();
long pairs = (size * (long) size) >> 1;
final long ssize = sampling <= 1 ? (long) Math.ceil(sampling * pairs) : (long) sampling;
if(ssize > Integer.MAX_VALUE) {
throw new AbortException("Sampling size too large.");
}
final int qsize = quantile <= 0 ? 1 : (int) Math.ceil(quantile * ssize);
DoubleMaxHeap heap = new DoubleMaxHeap(qsize);
ArrayDBIDs ids = DBIDUtil.ensureArray(rel.getDBIDs());
DBIDArrayIter i1 = ids.iter(), i2 = ids.iter();
Random r = rand.getSingleThreadedRandom();
FiniteProgress prog = LOG.isVerbose() ? new FiniteProgress("Sampling", (int) ssize, LOG) : null;
for(long i = 0; i < ssize; i++) {
int x = r.nextInt(size - 1) + 1, y = r.nextInt(x);
double dist = dq.distance(i1.seek(x), i2.seek(y));
// Skip NaN, and/or zeros.
if(dist != dist || (nozeros && dist < Double.MIN_NORMAL)) {
continue;
}
heap.add(dist, qsize);
LOG.incrementProcessed(prog);
}
LOG.statistics(new DoubleStatistic(PREFIX + ".quantile", quantile));
LOG.statistics(new LongStatistic(PREFIX + ".samplesize", ssize));
LOG.statistics(new DoubleStatistic(PREFIX + ".distance", heap.peek()));
LOG.ensureCompleted(prog);
Collection<String> header = Arrays.asList(new String[] { "Distance" });
Collection<double[]> data = Arrays.asList(new double[][] { new double[] { heap.peek() } });
return new CollectionResult<double[]>("Distances sample", "distance-sample", data, header);
} | java | public CollectionResult<double[]> run(Database database, Relation<O> rel) {
DistanceQuery<O> dq = rel.getDistanceQuery(getDistanceFunction());
int size = rel.size();
long pairs = (size * (long) size) >> 1;
final long ssize = sampling <= 1 ? (long) Math.ceil(sampling * pairs) : (long) sampling;
if(ssize > Integer.MAX_VALUE) {
throw new AbortException("Sampling size too large.");
}
final int qsize = quantile <= 0 ? 1 : (int) Math.ceil(quantile * ssize);
DoubleMaxHeap heap = new DoubleMaxHeap(qsize);
ArrayDBIDs ids = DBIDUtil.ensureArray(rel.getDBIDs());
DBIDArrayIter i1 = ids.iter(), i2 = ids.iter();
Random r = rand.getSingleThreadedRandom();
FiniteProgress prog = LOG.isVerbose() ? new FiniteProgress("Sampling", (int) ssize, LOG) : null;
for(long i = 0; i < ssize; i++) {
int x = r.nextInt(size - 1) + 1, y = r.nextInt(x);
double dist = dq.distance(i1.seek(x), i2.seek(y));
// Skip NaN, and/or zeros.
if(dist != dist || (nozeros && dist < Double.MIN_NORMAL)) {
continue;
}
heap.add(dist, qsize);
LOG.incrementProcessed(prog);
}
LOG.statistics(new DoubleStatistic(PREFIX + ".quantile", quantile));
LOG.statistics(new LongStatistic(PREFIX + ".samplesize", ssize));
LOG.statistics(new DoubleStatistic(PREFIX + ".distance", heap.peek()));
LOG.ensureCompleted(prog);
Collection<String> header = Arrays.asList(new String[] { "Distance" });
Collection<double[]> data = Arrays.asList(new double[][] { new double[] { heap.peek() } });
return new CollectionResult<double[]>("Distances sample", "distance-sample", data, header);
} | [
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elki-project/elki | elki-input/src/main/java/de/lmu/ifi/dbs/elki/datasource/parser/NumberVectorLabelParser.java | NumberVectorLabelParser.parseLineInternal | protected boolean parseLineInternal() {
// Split into numerical attributes and labels
int i = 0;
for(/* initialized by nextLineExceptComents()! */; tokenizer.valid(); tokenizer.advance(), i++) {
if(!isLabelColumn(i) && !tokenizer.isQuoted()) {
try {
attributes.add(tokenizer.getDouble());
continue;
}
catch(NumberFormatException e) {
if(!warnedPrecision && (e == ParseUtil.PRECISION_OVERFLOW || e == ParseUtil.EXPONENT_OVERFLOW)) {
getLogger().warning("Too many digits in what looked like a double number - treating as string: " + tokenizer.getSubstring());
warnedPrecision = true;
}
// Ignore attempt, add to labels below.
}
}
// Else: labels.
String lbl = tokenizer.getStrippedSubstring();
if(lbl.length() > 0) {
haslabels = true;
lbl = unique.addOrGet(lbl);
labels.add(lbl);
}
}
// Maybe a label row?
if(curvec == null && attributes.size == 0) {
columnnames = new ArrayList<>(labels);
haslabels = false;
curvec = null;
curlbl = null;
labels.clear();
return false;
}
// Pass outside via class variables
curvec = createVector();
curlbl = LabelList.make(labels);
attributes.clear();
labels.clear();
return true;
} | java | protected boolean parseLineInternal() {
// Split into numerical attributes and labels
int i = 0;
for(/* initialized by nextLineExceptComents()! */; tokenizer.valid(); tokenizer.advance(), i++) {
if(!isLabelColumn(i) && !tokenizer.isQuoted()) {
try {
attributes.add(tokenizer.getDouble());
continue;
}
catch(NumberFormatException e) {
if(!warnedPrecision && (e == ParseUtil.PRECISION_OVERFLOW || e == ParseUtil.EXPONENT_OVERFLOW)) {
getLogger().warning("Too many digits in what looked like a double number - treating as string: " + tokenizer.getSubstring());
warnedPrecision = true;
}
// Ignore attempt, add to labels below.
}
}
// Else: labels.
String lbl = tokenizer.getStrippedSubstring();
if(lbl.length() > 0) {
haslabels = true;
lbl = unique.addOrGet(lbl);
labels.add(lbl);
}
}
// Maybe a label row?
if(curvec == null && attributes.size == 0) {
columnnames = new ArrayList<>(labels);
haslabels = false;
curvec = null;
curlbl = null;
labels.clear();
return false;
}
// Pass outside via class variables
curvec = createVector();
curlbl = LabelList.make(labels);
attributes.clear();
labels.clear();
return true;
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elki-project/elki | elki-input/src/main/java/de/lmu/ifi/dbs/elki/datasource/parser/NumberVectorLabelParser.java | NumberVectorLabelParser.getTypeInformation | SimpleTypeInformation<V> getTypeInformation(int mindim, int maxdim) {
if(mindim > maxdim) {
throw new AbortException("No vectors were read from the input file - cannot determine vector data type.");
}
if(mindim == maxdim) {
String[] colnames = null;
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continue;
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colnames[j] = columnnames.get(i);
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}
if(j != mindim) {
colnames = null; // Did not work
}
}
return new VectorFieldTypeInformation<>(factory, mindim, colnames);
}
// Variable dimensionality - return non-vector field type
return new VectorTypeInformation<>(factory, factory.getDefaultSerializer(), mindim, maxdim);
} | java | SimpleTypeInformation<V> getTypeInformation(int mindim, int maxdim) {
if(mindim > maxdim) {
throw new AbortException("No vectors were read from the input file - cannot determine vector data type.");
}
if(mindim == maxdim) {
String[] colnames = null;
if(columnnames != null && mindim <= columnnames.size()) {
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int j = 0;
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continue;
}
colnames[j] = columnnames.get(i);
j++;
}
if(j != mindim) {
colnames = null; // Did not work
}
}
return new VectorFieldTypeInformation<>(factory, mindim, colnames);
}
// Variable dimensionality - return non-vector field type
return new VectorTypeInformation<>(factory, factory.getDefaultSerializer(), mindim, maxdim);
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elki-project/elki | elki-index-preprocessed/src/main/java/de/lmu/ifi/dbs/elki/index/preprocessed/knn/MaterializeKNNAndRKNNPreprocessor.java | MaterializeKNNAndRKNNPreprocessor.materializeKNNAndRKNNs | private void materializeKNNAndRKNNs(ArrayDBIDs ids, FiniteProgress progress) {
// add an empty list to each rknn
for(DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) {
if(materialized_RkNN.get(iter) == null) {
materialized_RkNN.put(iter, new TreeSet<DoubleDBIDPair>());
}
}
// knn query
List<? extends KNNList> kNNList = knnQuery.getKNNForBulkDBIDs(ids, k);
for(DBIDArrayIter id = ids.iter(); id.valid(); id.advance()) {
KNNList kNNs = kNNList.get(id.getOffset());
storage.put(id, kNNs);
for(DoubleDBIDListIter iter = kNNs.iter(); iter.valid(); iter.advance()) {
materialized_RkNN.get(iter).add(DBIDUtil.newPair(iter.doubleValue(), id));
}
LOG.incrementProcessed(progress);
}
LOG.ensureCompleted(progress);
} | java | private void materializeKNNAndRKNNs(ArrayDBIDs ids, FiniteProgress progress) {
// add an empty list to each rknn
for(DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) {
if(materialized_RkNN.get(iter) == null) {
materialized_RkNN.put(iter, new TreeSet<DoubleDBIDPair>());
}
}
// knn query
List<? extends KNNList> kNNList = knnQuery.getKNNForBulkDBIDs(ids, k);
for(DBIDArrayIter id = ids.iter(); id.valid(); id.advance()) {
KNNList kNNs = kNNList.get(id.getOffset());
storage.put(id, kNNs);
for(DoubleDBIDListIter iter = kNNs.iter(); iter.valid(); iter.advance()) {
materialized_RkNN.get(iter).add(DBIDUtil.newPair(iter.doubleValue(), id));
}
LOG.incrementProcessed(progress);
}
LOG.ensureCompleted(progress);
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elki-project/elki | elki-index-preprocessed/src/main/java/de/lmu/ifi/dbs/elki/index/preprocessed/knn/MaterializeKNNAndRKNNPreprocessor.java | MaterializeKNNAndRKNNPreprocessor.getRKNN | public DoubleDBIDList getRKNN(DBIDRef id) {
TreeSet<DoubleDBIDPair> rKNN = materialized_RkNN.get(id);
if(rKNN == null) {
return null;
}
ModifiableDoubleDBIDList ret = DBIDUtil.newDistanceDBIDList(rKNN.size());
for(DoubleDBIDPair pair : rKNN) {
ret.add(pair);
}
ret.sort();
return ret;
} | java | public DoubleDBIDList getRKNN(DBIDRef id) {
TreeSet<DoubleDBIDPair> rKNN = materialized_RkNN.get(id);
if(rKNN == null) {
return null;
}
ModifiableDoubleDBIDList ret = DBIDUtil.newDistanceDBIDList(rKNN.size());
for(DoubleDBIDPair pair : rKNN) {
ret.add(pair);
}
ret.sort();
return ret;
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/hierarchical/birch/CFTree.java | CFTree.insert | public void insert(NumberVector nv) {
final int dim = nv.getDimensionality();
// No root created yet:
if(root == null) {
ClusteringFeature leaf = new ClusteringFeature(dim);
leaf.addToStatistics(nv);
root = new TreeNode(dim, capacity);
root.children[0] = leaf;
root.addToStatistics(nv);
++leaves;
return;
}
TreeNode other = insert(root, nv);
// Handle root overflow:
if(other != null) {
TreeNode newnode = new TreeNode(dim, capacity);
newnode.addToStatistics(newnode.children[0] = root);
newnode.addToStatistics(newnode.children[1] = other);
root = newnode;
}
} | java | public void insert(NumberVector nv) {
final int dim = nv.getDimensionality();
// No root created yet:
if(root == null) {
ClusteringFeature leaf = new ClusteringFeature(dim);
leaf.addToStatistics(nv);
root = new TreeNode(dim, capacity);
root.children[0] = leaf;
root.addToStatistics(nv);
++leaves;
return;
}
TreeNode other = insert(root, nv);
// Handle root overflow:
if(other != null) {
TreeNode newnode = new TreeNode(dim, capacity);
newnode.addToStatistics(newnode.children[0] = root);
newnode.addToStatistics(newnode.children[1] = other);
root = newnode;
}
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/hierarchical/birch/CFTree.java | CFTree.rebuildTree | protected void rebuildTree() {
final int dim = root.getDimensionality();
double t = estimateThreshold(root) / leaves;
t *= t;
// Never decrease the threshold.
thresholdsq = t > thresholdsq ? t : thresholdsq;
LOG.debug("New squared threshold: " + thresholdsq);
LeafIterator iter = new LeafIterator(root); // Will keep the old root.
assert (iter.valid());
ClusteringFeature first = iter.get();
leaves = 0;
// Make a new root node:
root = new TreeNode(dim, capacity);
root.children[0] = first;
root.addToStatistics(first);
++leaves;
for(iter.advance(); iter.valid(); iter.advance()) {
TreeNode other = insert(root, iter.get());
// Handle root overflow:
if(other != null) {
TreeNode newnode = new TreeNode(dim, capacity);
newnode.addToStatistics(newnode.children[0] = root);
newnode.addToStatistics(newnode.children[1] = other);
root = newnode;
}
}
} | java | protected void rebuildTree() {
final int dim = root.getDimensionality();
double t = estimateThreshold(root) / leaves;
t *= t;
// Never decrease the threshold.
thresholdsq = t > thresholdsq ? t : thresholdsq;
LOG.debug("New squared threshold: " + thresholdsq);
LeafIterator iter = new LeafIterator(root); // Will keep the old root.
assert (iter.valid());
ClusteringFeature first = iter.get();
leaves = 0;
// Make a new root node:
root = new TreeNode(dim, capacity);
root.children[0] = first;
root.addToStatistics(first);
++leaves;
for(iter.advance(); iter.valid(); iter.advance()) {
TreeNode other = insert(root, iter.get());
// Handle root overflow:
if(other != null) {
TreeNode newnode = new TreeNode(dim, capacity);
newnode.addToStatistics(newnode.children[0] = root);
newnode.addToStatistics(newnode.children[1] = other);
root = newnode;
}
}
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/hierarchical/birch/CFTree.java | CFTree.insert | private TreeNode insert(TreeNode node, NumberVector nv) {
// Find closest child:
ClusteringFeature[] cfs = node.children;
assert (cfs[0] != null) : "Unexpected empty node!";
// Find the best child:
ClusteringFeature best = cfs[0];
double bestd = distance.squaredDistance(nv, best);
for(int i = 1; i < cfs.length; i++) {
ClusteringFeature cf = cfs[i];
if(cf == null) {
break;
}
double d2 = distance.squaredDistance(nv, cf);
if(d2 < bestd) {
best = cf;
bestd = d2;
}
}
// Leaf node:
if(!(best instanceof TreeNode)) {
// Threshold constraint satisfied?
if(absorption.squaredCriterion(best, nv) <= thresholdsq) {
best.addToStatistics(nv);
node.addToStatistics(nv);
return null;
}
best = new ClusteringFeature(nv.getDimensionality());
best.addToStatistics(nv);
++leaves;
if(add(node.children, best)) {
node.addToStatistics(nv); // Update statistics
return null;
}
return split(node, best);
}
assert (best instanceof TreeNode) : "Node is neither child nor inner?";
TreeNode newchild = insert((TreeNode) best, nv);
if(newchild == null || add(node.children, newchild)) {
node.addToStatistics(nv); // Update statistics
return null;
}
return split(node, newchild);
} | java | private TreeNode insert(TreeNode node, NumberVector nv) {
// Find closest child:
ClusteringFeature[] cfs = node.children;
assert (cfs[0] != null) : "Unexpected empty node!";
// Find the best child:
ClusteringFeature best = cfs[0];
double bestd = distance.squaredDistance(nv, best);
for(int i = 1; i < cfs.length; i++) {
ClusteringFeature cf = cfs[i];
if(cf == null) {
break;
}
double d2 = distance.squaredDistance(nv, cf);
if(d2 < bestd) {
best = cf;
bestd = d2;
}
}
// Leaf node:
if(!(best instanceof TreeNode)) {
// Threshold constraint satisfied?
if(absorption.squaredCriterion(best, nv) <= thresholdsq) {
best.addToStatistics(nv);
node.addToStatistics(nv);
return null;
}
best = new ClusteringFeature(nv.getDimensionality());
best.addToStatistics(nv);
++leaves;
if(add(node.children, best)) {
node.addToStatistics(nv); // Update statistics
return null;
}
return split(node, best);
}
assert (best instanceof TreeNode) : "Node is neither child nor inner?";
TreeNode newchild = insert((TreeNode) best, nv);
if(newchild == null || add(node.children, newchild)) {
node.addToStatistics(nv); // Update statistics
return null;
}
return split(node, newchild);
} | [
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/hierarchical/birch/CFTree.java | CFTree.add | private boolean add(ClusteringFeature[] children, ClusteringFeature child) {
for(int i = 0; i < children.length; i++) {
if(children[i] == null) {
children[i] = child;
return true;
}
}
return false;
} | java | private boolean add(ClusteringFeature[] children, ClusteringFeature child) {
for(int i = 0; i < children.length; i++) {
if(children[i] == null) {
children[i] = child;
return true;
}
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return false;
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/hierarchical/birch/CFTree.java | CFTree.printDebug | protected StringBuilder printDebug(StringBuilder buf, ClusteringFeature n, int d) {
FormatUtil.appendSpace(buf, d).append(n.n);
for(int i = 0; i < n.getDimensionality(); i++) {
buf.append(' ').append(n.centroid(i));
}
buf.append(" - ").append(n.n).append('\n');
if(n instanceof TreeNode) {
ClusteringFeature[] children = ((TreeNode) n).children;
for(int i = 0; i < children.length; i++) {
ClusteringFeature c = children[i];
if(c != null) {
printDebug(buf, c, d + 1);
}
}
}
return buf;
} | java | protected StringBuilder printDebug(StringBuilder buf, ClusteringFeature n, int d) {
FormatUtil.appendSpace(buf, d).append(n.n);
for(int i = 0; i < n.getDimensionality(); i++) {
buf.append(' ').append(n.centroid(i));
}
buf.append(" - ").append(n.n).append('\n');
if(n instanceof TreeNode) {
ClusteringFeature[] children = ((TreeNode) n).children;
for(int i = 0; i < children.length; i++) {
ClusteringFeature c = children[i];
if(c != null) {
printDebug(buf, c, d + 1);
}
}
}
return buf;
} | [
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] | b54673327e76198ecd4c8a2a901021f1a9174498 | https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/hierarchical/birch/CFTree.java#L577-L593 | train |
elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/StudentsTDistribution.java | StudentsTDistribution.cdf | public static double cdf(double val, int v) {
double x = v / (val * val + v);
return 1 - (0.5 * BetaDistribution.regularizedIncBeta(x, v * .5, 0.5));
} | java | public static double cdf(double val, int v) {
double x = v / (val * val + v);
return 1 - (0.5 * BetaDistribution.regularizedIncBeta(x, v * .5, 0.5));
} | [
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] | b54673327e76198ecd4c8a2a901021f1a9174498 | https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/StudentsTDistribution.java#L136-L139 | train |
elki-project/elki | elki-timeseries/src/main/java/de/lmu/ifi/dbs/elki/algorithm/timeseries/ChangePoints.java | ChangePoints.add | public void add(DBIDRef iter, int column, double score) {
changepoints.add(new ChangePoint(iter, column, score));
} | java | public void add(DBIDRef iter, int column, double score) {
changepoints.add(new ChangePoint(iter, column, score));
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elki-project/elki | elki-core-data/src/main/java/de/lmu/ifi/dbs/elki/data/spatial/PolygonsObject.java | PolygonsObject.appendToBuffer | public void appendToBuffer(StringBuilder buf) {
Iterator<Polygon> iter = polygons.iterator();
while(iter.hasNext()) {
Polygon poly = iter.next();
poly.appendToBuffer(buf);
if(iter.hasNext()) {
buf.append(" -- ");
}
}
} | java | public void appendToBuffer(StringBuilder buf) {
Iterator<Polygon> iter = polygons.iterator();
while(iter.hasNext()) {
Polygon poly = iter.next();
poly.appendToBuffer(buf);
if(iter.hasNext()) {
buf.append(" -- ");
}
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elki-project/elki | elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/io/Tokenizer.java | Tokenizer.initialize | public void initialize(CharSequence input, int begin, int end) {
this.input = input;
this.send = end;
this.matcher.reset(input).region(begin, end);
this.index = begin;
advance();
} | java | public void initialize(CharSequence input, int begin, int end) {
this.input = input;
this.send = end;
this.matcher.reset(input).region(begin, end);
this.index = begin;
advance();
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elki-project/elki | elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/io/Tokenizer.java | Tokenizer.getStrippedSubstring | public String getStrippedSubstring() {
// TODO: detect Java <6 and make sure we only return the substring?
// With java 7, String.substring will arraycopy the characters.
int sstart = start, send = end;
while(sstart < send) {
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break;
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break;
}
}
++send;
return (sstart < send) ? input.subSequence(sstart, send).toString() : "";
} | java | public String getStrippedSubstring() {
// TODO: detect Java <6 and make sure we only return the substring?
// With java 7, String.substring will arraycopy the characters.
int sstart = start, send = end;
while(sstart < send) {
char c = input.charAt(sstart);
if(c != ' ' || c != '\n' || c != '\r' || c != '\t') {
break;
}
++sstart;
}
while(--send >= sstart) {
char c = input.charAt(send);
if(c != ' ' || c != '\n' || c != '\r' || c != '\t') {
break;
}
}
++send;
return (sstart < send) ? input.subSequence(sstart, send).toString() : "";
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elki-project/elki | elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/io/Tokenizer.java | Tokenizer.isQuote | private char isQuote(int index) {
if(index >= input.length()) {
return 0;
}
char c = input.charAt(index);
for(int i = 0; i < quoteChars.length; i++) {
if(c == quoteChars[i]) {
return c;
}
}
return 0;
} | java | private char isQuote(int index) {
if(index >= input.length()) {
return 0;
}
char c = input.charAt(index);
for(int i = 0; i < quoteChars.length; i++) {
if(c == quoteChars[i]) {
return c;
}
}
return 0;
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elki-project/elki | elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/datastore/DataStoreUtil.java | DataStoreUtil.makeRecordStorage | public static WritableRecordStore makeRecordStorage(DBIDs ids, int hints, Class<?>... dataclasses) {
return DataStoreFactory.FACTORY.makeRecordStorage(ids, hints, dataclasses);
} | java | public static WritableRecordStore makeRecordStorage(DBIDs ids, int hints, Class<?>... dataclasses) {
return DataStoreFactory.FACTORY.makeRecordStorage(ids, hints, dataclasses);
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elki-project/elki | elki-core-data/src/main/java/de/lmu/ifi/dbs/elki/data/projection/random/RandomSubsetProjectionFamily.java | RandomSubsetProjectionFamily.randomPermutation | public static int[] randomPermutation(final int[] out, Random random) {
for(int i = out.length - 1; i > 0; i--) {
// Swap with random preceeding element.
int ri = random.nextInt(i + 1);
int tmp = out[ri];
out[ri] = out[i];
out[i] = tmp;
}
return out;
} | java | public static int[] randomPermutation(final int[] out, Random random) {
for(int i = out.length - 1; i > 0; i--) {
// Swap with random preceeding element.
int ri = random.nextInt(i + 1);
int tmp = out[ri];
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return out;
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/batikutil/JSVGUpdateSynchronizer.java | JSVGUpdateSynchronizer.makeRunnerIfNeeded | protected void makeRunnerIfNeeded() {
// We don't need to make a SVG runner when there are no pending updates.
boolean stop = true;
for(WeakReference<UpdateRunner> wur : updaterunner) {
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}
// Synchronize with all layers:
synchronized(this) {
synchronized(component) {
UpdateManager um = component.getUpdateManager();
if(um != null) {
synchronized(um) {
if(um.isRunning()) {
// Create and insert a runner.
Runnable newrunner = new Runnable() {
@Override
public void run() {
if(pending.compareAndSet(this, null)) {
// Wake up all runners
for(WeakReference<UpdateRunner> wur : updaterunner) {
UpdateRunner ur = wur.get();
if(ur == null || ur.isEmpty()) {
continue;
}
ur.runQueue();
}
}
}
};
pending.set(newrunner);
um.getUpdateRunnableQueue().invokeLater(newrunner);
return;
}
}
}
}
}
} | java | protected void makeRunnerIfNeeded() {
// We don't need to make a SVG runner when there are no pending updates.
boolean stop = true;
for(WeakReference<UpdateRunner> wur : updaterunner) {
UpdateRunner ur = wur.get();
if(ur == null) {
updaterunner.remove(wur);
}
else if(!ur.isEmpty()) {
stop = false;
}
}
if(stop) {
return;
}
// We only need a new runner when we don't have one in the queue yet!
if(pending.get() != null) {
return;
}
// We need a component
JSVGComponent component = this.cref.get();
if(component == null) {
return;
}
// Synchronize with all layers:
synchronized(this) {
synchronized(component) {
UpdateManager um = component.getUpdateManager();
if(um != null) {
synchronized(um) {
if(um.isRunning()) {
// Create and insert a runner.
Runnable newrunner = new Runnable() {
@Override
public void run() {
if(pending.compareAndSet(this, null)) {
// Wake up all runners
for(WeakReference<UpdateRunner> wur : updaterunner) {
UpdateRunner ur = wur.get();
if(ur == null || ur.isEmpty()) {
continue;
}
ur.runQueue();
}
}
}
};
pending.set(newrunner);
um.getUpdateRunnableQueue().invokeLater(newrunner);
return;
}
}
}
}
}
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/visualizers/thumbs/ThumbnailVisualization.java | ThumbnailVisualization.fullRedraw | @Override
public void fullRedraw() {
if(!(getWidth() > 0 && getHeight() > 0)) {
LoggingUtil.warning("Thumbnail of zero size requested: " + visFactory);
return;
}
if(thumbid < 0) {
// LoggingUtil.warning("Generating new thumbnail " + this);
layer.appendChild(SVGUtil.svgWaitIcon(plot.getDocument(), 0, 0, getWidth(), getHeight()));
if(pendingThumbnail == null) {
pendingThumbnail = ThumbnailThread.queue(this);
}
return;
}
// LoggingUtil.warning("Injecting Thumbnail " + this);
Element i = plot.svgElement(SVGConstants.SVG_IMAGE_TAG);
SVGUtil.setAtt(i, SVGConstants.SVG_X_ATTRIBUTE, 0);
SVGUtil.setAtt(i, SVGConstants.SVG_Y_ATTRIBUTE, 0);
SVGUtil.setAtt(i, SVGConstants.SVG_WIDTH_ATTRIBUTE, getWidth());
SVGUtil.setAtt(i, SVGConstants.SVG_HEIGHT_ATTRIBUTE, getHeight());
i.setAttributeNS(SVGConstants.XLINK_NAMESPACE_URI, SVGConstants.XLINK_HREF_QNAME, ThumbnailRegistryEntry.INTERNAL_PROTOCOL + ":" + thumbid);
layer.appendChild(i);
} | java | @Override
public void fullRedraw() {
if(!(getWidth() > 0 && getHeight() > 0)) {
LoggingUtil.warning("Thumbnail of zero size requested: " + visFactory);
return;
}
if(thumbid < 0) {
// LoggingUtil.warning("Generating new thumbnail " + this);
layer.appendChild(SVGUtil.svgWaitIcon(plot.getDocument(), 0, 0, getWidth(), getHeight()));
if(pendingThumbnail == null) {
pendingThumbnail = ThumbnailThread.queue(this);
}
return;
}
// LoggingUtil.warning("Injecting Thumbnail " + this);
Element i = plot.svgElement(SVGConstants.SVG_IMAGE_TAG);
SVGUtil.setAtt(i, SVGConstants.SVG_X_ATTRIBUTE, 0);
SVGUtil.setAtt(i, SVGConstants.SVG_Y_ATTRIBUTE, 0);
SVGUtil.setAtt(i, SVGConstants.SVG_WIDTH_ATTRIBUTE, getWidth());
SVGUtil.setAtt(i, SVGConstants.SVG_HEIGHT_ATTRIBUTE, getHeight());
i.setAttributeNS(SVGConstants.XLINK_NAMESPACE_URI, SVGConstants.XLINK_HREF_QNAME, ThumbnailRegistryEntry.INTERNAL_PROTOCOL + ":" + thumbid);
layer.appendChild(i);
} | [
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/Centroid.java | Centroid.make | public static Centroid make(Relation<? extends NumberVector> relation, DBIDs ids) {
final int dim = RelationUtil.dimensionality(relation);
Centroid c = new Centroid(dim);
double[] elems = c.elements;
int count = 0;
for(DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) {
NumberVector v = relation.get(iter);
for(int i = 0; i < dim; i++) {
elems[i] += v.doubleValue(i);
}
count += 1;
}
if(count == 0) {
return c;
}
for(int i = 0; i < dim; i++) {
elems[i] /= count;
}
c.wsum = count;
return c;
} | java | public static Centroid make(Relation<? extends NumberVector> relation, DBIDs ids) {
final int dim = RelationUtil.dimensionality(relation);
Centroid c = new Centroid(dim);
double[] elems = c.elements;
int count = 0;
for(DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) {
NumberVector v = relation.get(iter);
for(int i = 0; i < dim; i++) {
elems[i] += v.doubleValue(i);
}
count += 1;
}
if(count == 0) {
return c;
}
for(int i = 0; i < dim; i++) {
elems[i] /= count;
}
c.wsum = count;
return c;
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elki-project/elki | elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/distancefunction/timeseries/DTWDistanceFunction.java | DTWDistanceFunction.firstRow | protected void firstRow(double[] buf, int band, NumberVector v1, NumberVector v2, int dim2) {
// First cell:
final double val1 = v1.doubleValue(0);
buf[0] = delta(val1, v2.doubleValue(0));
// Width of valid area:
final int w = (band >= dim2) ? dim2 - 1 : band;
// Fill remaining part of buffer:
for(int j = 1; j <= w; j++) {
buf[j] = buf[j - 1] + delta(val1, v2.doubleValue(j));
}
} | java | protected void firstRow(double[] buf, int band, NumberVector v1, NumberVector v2, int dim2) {
// First cell:
final double val1 = v1.doubleValue(0);
buf[0] = delta(val1, v2.doubleValue(0));
// Width of valid area:
final int w = (band >= dim2) ? dim2 - 1 : band;
// Fill remaining part of buffer:
for(int j = 1; j <= w; j++) {
buf[j] = buf[j - 1] + delta(val1, v2.doubleValue(j));
}
} | [
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] | b54673327e76198ecd4c8a2a901021f1a9174498 | https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/distancefunction/timeseries/DTWDistanceFunction.java#L137-L148 | train |
elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/pca/weightfunctions/GaussStddevWeight.java | GaussStddevWeight.getWeight | @Override
public double getWeight(double distance, double max, double stddev) {
if(stddev <= 0) {
return 1;
}
double normdistance = distance / stddev;
return scaling * FastMath.exp(-.5 * normdistance * normdistance) / stddev;
} | java | @Override
public double getWeight(double distance, double max, double stddev) {
if(stddev <= 0) {
return 1;
}
double normdistance = distance / stddev;
return scaling * FastMath.exp(-.5 * normdistance * normdistance) / stddev;
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elki-project/elki | elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/io/TokenizedReader.java | TokenizedReader.nextLineExceptComments | public boolean nextLineExceptComments() throws IOException {
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGArrow.java | SVGArrow.makeArrow | public static Element makeArrow(SVGPlot svgp, Direction dir, double x, double y, double size) {
final double hs = size / 2.;
switch(dir){
case LEFT:
return new SVGPath().drawTo(x + hs, y + hs).drawTo(x - hs, y).drawTo(x + hs, y - hs).drawTo(x + hs, y + hs).close().makeElement(svgp);
case DOWN:
return new SVGPath().drawTo(x - hs, y - hs).drawTo(x + hs, y - hs).drawTo(x, y + hs).drawTo(x - hs, y - hs).close().makeElement(svgp);
case RIGHT:
return new SVGPath().drawTo(x - hs, y - hs).drawTo(x + hs, y).drawTo(x - hs, y + hs).drawTo(x - hs, y - hs).close().makeElement(svgp);
case UP:
return new SVGPath().drawTo(x - hs, y + hs).drawTo(x, y - hs).drawTo(x + hs, y + hs).drawTo(x - hs, y + hs).close().makeElement(svgp);
default:
throw new IllegalArgumentException("Unexpected direction: " + dir);
}
} | java | public static Element makeArrow(SVGPlot svgp, Direction dir, double x, double y, double size) {
final double hs = size / 2.;
switch(dir){
case LEFT:
return new SVGPath().drawTo(x + hs, y + hs).drawTo(x - hs, y).drawTo(x + hs, y - hs).drawTo(x + hs, y + hs).close().makeElement(svgp);
case DOWN:
return new SVGPath().drawTo(x - hs, y - hs).drawTo(x + hs, y - hs).drawTo(x, y + hs).drawTo(x - hs, y - hs).close().makeElement(svgp);
case RIGHT:
return new SVGPath().drawTo(x - hs, y - hs).drawTo(x + hs, y).drawTo(x - hs, y + hs).drawTo(x - hs, y - hs).close().makeElement(svgp);
case UP:
return new SVGPath().drawTo(x - hs, y + hs).drawTo(x, y - hs).drawTo(x + hs, y + hs).drawTo(x - hs, y + hs).close().makeElement(svgp);
default:
throw new IllegalArgumentException("Unexpected direction: " + dir);
}
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elki-project/elki | elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/distancefunction/set/HammingDistanceFunction.java | HammingDistanceFunction.hammingDistanceNumberVector | private double hammingDistanceNumberVector(NumberVector o1, NumberVector o2) {
final int d1 = o1.getDimensionality(), d2 = o2.getDimensionality();
int differences = 0;
int d = 0;
for(; d < d1 && d < d2; d++) {
double v1 = o1.doubleValue(d), v2 = o2.doubleValue(d);
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continue;
}
if(v1 != v2) {
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double v2 = o2.doubleValue(d);
if(v2 != 0. && v2 == v2 /* not NaN */) {
++differences;
}
}
return differences;
} | java | private double hammingDistanceNumberVector(NumberVector o1, NumberVector o2) {
final int d1 = o1.getDimensionality(), d2 = o2.getDimensionality();
int differences = 0;
int d = 0;
for(; d < d1 && d < d2; d++) {
double v1 = o1.doubleValue(d), v2 = o2.doubleValue(d);
if(v1 != v1 || v2 != v2) { /* NaN */
continue;
}
if(v1 != v2) {
++differences;
}
}
for(; d < d1; d++) {
double v1 = o1.doubleValue(d);
if(v1 != 0. && v1 == v1 /* not NaN */) {
++differences;
}
}
for(; d < d2; d++) {
double v2 = o2.doubleValue(d);
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++differences;
}
}
return differences;
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/spacefillingcurves/HilbertSpatialSorter.java | HilbertSpatialSorter.interleaveBits | public static long[] interleaveBits(long[] coords, int iter) {
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// convert longValues into zValues
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if((coords[dim] & mask) != 0) {
BitsUtil.setI(bitset, dim);
}
}
return bitset;
} | java | public static long[] interleaveBits(long[] coords, int iter) {
final int numdim = coords.length;
final long[] bitset = BitsUtil.zero(numdim);
// convert longValues into zValues
final long mask = 1L << 63 - iter;
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/VisualizationTree.java | VisualizationTree.visChanged | public void visChanged(VisualizationItem item) {
for(int i = vlistenerList.size(); --i >= 0;) {
final VisualizationListener listener = vlistenerList.get(i);
if(listener != null) {
listener.visualizationChanged(item);
}
}
} | java | public void visChanged(VisualizationItem item) {
for(int i = vlistenerList.size(); --i >= 0;) {
final VisualizationListener listener = vlistenerList.get(i);
if(listener != null) {
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/VisualizationTree.java | VisualizationTree.setVisible | public static void setVisible(VisualizerContext context, VisualizationTask task, boolean visibility) {
// Hide other tools
if(visibility && task.isTool()) {
Hierarchy<Object> vistree = context.getVisHierarchy();
for(It<VisualizationTask> iter2 = vistree.iterAll().filter(VisualizationTask.class); iter2.valid(); iter2.advance()) {
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if(other != task && other.isTool() && other.isVisible()) {
context.visChanged(other.visibility(false));
}
}
}
context.visChanged(task.visibility(visibility));
} | java | public static void setVisible(VisualizerContext context, VisualizationTask task, boolean visibility) {
// Hide other tools
if(visibility && task.isTool()) {
Hierarchy<Object> vistree = context.getVisHierarchy();
for(It<VisualizationTask> iter2 = vistree.iterAll().filter(VisualizationTask.class); iter2.valid(); iter2.advance()) {
VisualizationTask other = iter2.get();
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}
context.visChanged(task.visibility(visibility));
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/hierarchical/AGNES.java | AGNES.findMerge | protected int findMerge(int end, MatrixParadigm mat, PointerHierarchyRepresentationBuilder builder) {
assert (end > 0);
final DBIDArrayIter ix = mat.ix, iy = mat.iy;
final double[] matrix = mat.matrix;
double mindist = Double.POSITIVE_INFINITY;
int x = -1, y = -1;
// Find minimum:
for(int ox = 0, xbase = 0; ox < end; xbase += ox++) {
// Skip if object has already joined a cluster:
if(builder.isLinked(ix.seek(ox))) {
continue;
}
assert (xbase == MatrixParadigm.triangleSize(ox));
for(int oy = 0; oy < ox; oy++) {
// Skip if object has already joined a cluster:
if(builder.isLinked(iy.seek(oy))) {
continue;
}
final double dist = matrix[xbase + oy];
if(dist <= mindist) { // Prefer later on ==, to truncate more often.
mindist = dist;
x = ox;
y = oy;
}
}
}
assert (x >= 0 && y >= 0);
assert (y < x); // We could swap otherwise, but this shouldn't arise.
merge(end, mat, builder, mindist, x, y);
return x;
} | java | protected int findMerge(int end, MatrixParadigm mat, PointerHierarchyRepresentationBuilder builder) {
assert (end > 0);
final DBIDArrayIter ix = mat.ix, iy = mat.iy;
final double[] matrix = mat.matrix;
double mindist = Double.POSITIVE_INFINITY;
int x = -1, y = -1;
// Find minimum:
for(int ox = 0, xbase = 0; ox < end; xbase += ox++) {
// Skip if object has already joined a cluster:
if(builder.isLinked(ix.seek(ox))) {
continue;
}
assert (xbase == MatrixParadigm.triangleSize(ox));
for(int oy = 0; oy < ox; oy++) {
// Skip if object has already joined a cluster:
if(builder.isLinked(iy.seek(oy))) {
continue;
}
final double dist = matrix[xbase + oy];
if(dist <= mindist) { // Prefer later on ==, to truncate more often.
mindist = dist;
x = ox;
y = oy;
}
}
}
assert (x >= 0 && y >= 0);
assert (y < x); // We could swap otherwise, but this shouldn't arise.
merge(end, mat, builder, mindist, x, y);
return x;
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/em/TextbookMultivariateGaussianModel.java | TextbookMultivariateGaussianModel.updateCholesky | private void updateCholesky() {
// TODO: further improve handling of degenerated cases?
CholeskyDecomposition chol = new CholeskyDecomposition(covariance);
if(!chol.isSPD()) {
// Add a small value to the diagonal, to reduce some rounding problems.
double s = 0.;
for(int i = 0; i < covariance.length; i++) {
s += covariance[i][i];
}
s *= SINGULARITY_CHEAT / covariance.length;
for(int i = 0; i < covariance.length; i++) {
covariance[i][i] += s;
}
chol = new CholeskyDecomposition(covariance);
}
if(!chol.isSPD()) {
LOG.warning("A cluster has degenerated, likely due to lack of variance in a subset of the data or too extreme magnitude differences.\n" + //
"The algorithm will likely stop without converging, and fail to produce a good fit.");
chol = this.chol != null ? this.chol : chol; // Prefer previous
}
this.chol = chol;
logNormDet = FastMath.log(weight) - .5 * logNorm - getHalfLogDeterminant(this.chol);
} | java | private void updateCholesky() {
// TODO: further improve handling of degenerated cases?
CholeskyDecomposition chol = new CholeskyDecomposition(covariance);
if(!chol.isSPD()) {
// Add a small value to the diagonal, to reduce some rounding problems.
double s = 0.;
for(int i = 0; i < covariance.length; i++) {
s += covariance[i][i];
}
s *= SINGULARITY_CHEAT / covariance.length;
for(int i = 0; i < covariance.length; i++) {
covariance[i][i] += s;
}
chol = new CholeskyDecomposition(covariance);
}
if(!chol.isSPD()) {
LOG.warning("A cluster has degenerated, likely due to lack of variance in a subset of the data or too extreme magnitude differences.\n" + //
"The algorithm will likely stop without converging, and fail to produce a good fit.");
chol = this.chol != null ? this.chol : chol; // Prefer previous
}
this.chol = chol;
logNormDet = FastMath.log(weight) - .5 * logNorm - getHalfLogDeterminant(this.chol);
} | [
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elki-project/elki | elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/optionhandling/parameters/ClassParameter.java | ClassParameter.validate | @Override
public boolean validate(Class<? extends C> obj) throws ParameterException {
if(obj == null) {
throw new UnspecifiedParameterException(this);
}
if(!restrictionClass.isAssignableFrom(obj)) {
throw new WrongParameterValueException(this, obj.getName(), "Given class not a subclass / implementation of " + restrictionClass.getName());
}
return super.validate(obj);
} | java | @Override
public boolean validate(Class<? extends C> obj) throws ParameterException {
if(obj == null) {
throw new UnspecifiedParameterException(this);
}
if(!restrictionClass.isAssignableFrom(obj)) {
throw new WrongParameterValueException(this, obj.getName(), "Given class not a subclass / implementation of " + restrictionClass.getName());
}
return super.validate(obj);
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/visualizers/AbstractVisualization.java | AbstractVisualization.addListeners | protected void addListeners() {
// Listen for result changes, including the one we monitor
context.addResultListener(this);
context.addVisualizationListener(this);
// Listen for database events only when needed.
if(task.has(UpdateFlag.ON_DATA)) {
context.addDataStoreListener(this);
}
} | java | protected void addListeners() {
// Listen for result changes, including the one we monitor
context.addResultListener(this);
context.addVisualizationListener(this);
// Listen for database events only when needed.
if(task.has(UpdateFlag.ON_DATA)) {
context.addDataStoreListener(this);
}
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elki-project/elki | elki-data-generator/src/main/java/de/lmu/ifi/dbs/elki/data/synthetic/bymodel/GeneratorSingleCluster.java | GeneratorSingleCluster.addGenerator | public void addGenerator(Distribution gen) {
if(trans != null) {
throw new AbortException("Generators may no longer be added when transformations have been applied.");
}
axes.add(gen);
dim++;
} | java | public void addGenerator(Distribution gen) {
if(trans != null) {
throw new AbortException("Generators may no longer be added when transformations have been applied.");
}
axes.add(gen);
dim++;
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elki-project/elki | elki-data-generator/src/main/java/de/lmu/ifi/dbs/elki/data/synthetic/bymodel/GeneratorSingleCluster.java | GeneratorSingleCluster.addRotation | public void addRotation(int axis1, int axis2, double angle) {
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trans = new AffineTransformation(dim);
}
trans.addRotation(axis1, axis2, angle);
} | java | public void addRotation(int axis1, int axis2, double angle) {
if(trans == null) {
trans = new AffineTransformation(dim);
}
trans.addRotation(axis1, axis2, angle);
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elki-project/elki | elki-data-generator/src/main/java/de/lmu/ifi/dbs/elki/data/synthetic/bymodel/GeneratorSingleCluster.java | GeneratorSingleCluster.addTranslation | public void addTranslation(double[] v) {
if(trans == null) {
trans = new AffineTransformation(dim);
}
trans.addTranslation(v);
} | java | public void addTranslation(double[] v) {
if(trans == null) {
trans = new AffineTransformation(dim);
}
trans.addTranslation(v);
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elki-project/elki | elki-data-generator/src/main/java/de/lmu/ifi/dbs/elki/data/synthetic/bymodel/GeneratorSingleCluster.java | GeneratorSingleCluster.generate | @Override
public List<double[]> generate(int count) {
ArrayList<double[]> result = new ArrayList<>(count);
while(result.size() < count) {
double[] d = new double[dim];
for(int i = 0; i < dim; i++) {
d[i] = axes.get(i).nextRandom();
}
if(trans != null) {
d = trans.apply(d);
}
if(testClipping(d)) {
if(--retries < 0) {
throw new AbortException("Maximum retry count in generator exceeded.");
}
continue;
}
result.add(d);
}
return result;
} | java | @Override
public List<double[]> generate(int count) {
ArrayList<double[]> result = new ArrayList<>(count);
while(result.size() < count) {
double[] d = new double[dim];
for(int i = 0; i < dim; i++) {
d[i] = axes.get(i).nextRandom();
}
if(trans != null) {
d = trans.apply(d);
}
if(testClipping(d)) {
if(--retries < 0) {
throw new AbortException("Maximum retry count in generator exceeded.");
}
continue;
}
result.add(d);
}
return result;
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elki-project/elki | addons/tutorial/src/main/java/tutorial/clustering/SameSizeKMeansAlgorithm.java | SameSizeKMeansAlgorithm.run | @Override
public Clustering<MeanModel> run(Database database, Relation<V> relation) {
// Database objects to process
final DBIDs ids = relation.getDBIDs();
// Choose initial means
double[][] means = initializer.chooseInitialMeans(database, relation, k, getDistanceFunction());
// Setup cluster assignment store
List<ModifiableDBIDs> clusters = new ArrayList<>();
for(int i = 0; i < k; i++) {
clusters.add(DBIDUtil.newHashSet(relation.size() / k + 2));
}
// Meta data storage
final WritableDataStore<Meta> metas = initializeMeta(relation, means);
// Perform the initial assignment
ArrayModifiableDBIDs tids = initialAssignment(clusters, metas, ids);
// Recompute the means after the initial assignment
means = means(clusters, means, relation);
// Refine the result via k-means like iterations
means = refineResult(relation, means, clusters, metas, tids);
// Wrap result
Clustering<MeanModel> result = new Clustering<>("k-Means Samesize Clustering", "kmeans-samesize-clustering");
for(int i = 0; i < clusters.size(); i++) {
result.addToplevelCluster(new Cluster<>(clusters.get(i), new MeanModel(means[i])));
}
return result;
} | java | @Override
public Clustering<MeanModel> run(Database database, Relation<V> relation) {
// Database objects to process
final DBIDs ids = relation.getDBIDs();
// Choose initial means
double[][] means = initializer.chooseInitialMeans(database, relation, k, getDistanceFunction());
// Setup cluster assignment store
List<ModifiableDBIDs> clusters = new ArrayList<>();
for(int i = 0; i < k; i++) {
clusters.add(DBIDUtil.newHashSet(relation.size() / k + 2));
}
// Meta data storage
final WritableDataStore<Meta> metas = initializeMeta(relation, means);
// Perform the initial assignment
ArrayModifiableDBIDs tids = initialAssignment(clusters, metas, ids);
// Recompute the means after the initial assignment
means = means(clusters, means, relation);
// Refine the result via k-means like iterations
means = refineResult(relation, means, clusters, metas, tids);
// Wrap result
Clustering<MeanModel> result = new Clustering<>("k-Means Samesize Clustering", "kmeans-samesize-clustering");
for(int i = 0; i < clusters.size(); i++) {
result.addToplevelCluster(new Cluster<>(clusters.get(i), new MeanModel(means[i])));
}
return result;
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elki-project/elki | addons/tutorial/src/main/java/tutorial/clustering/SameSizeKMeansAlgorithm.java | SameSizeKMeansAlgorithm.initializeMeta | protected WritableDataStore<Meta> initializeMeta(Relation<V> relation, double[][] means) {
NumberVectorDistanceFunction<? super V> df = getDistanceFunction();
// The actual storage
final WritableDataStore<Meta> metas = DataStoreUtil.makeStorage(relation.getDBIDs(), DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_TEMP, Meta.class);
// Build the metadata, track the two nearest cluster centers.
for(DBIDIter id = relation.iterDBIDs(); id.valid(); id.advance()) {
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V fv = relation.get(id);
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if(i > 0) {
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c.primary = i;
}
else if(d > c.dists[c.secondary]) {
c.secondary = i;
}
}
}
metas.put(id, c);
}
return metas;
} | java | protected WritableDataStore<Meta> initializeMeta(Relation<V> relation, double[][] means) {
NumberVectorDistanceFunction<? super V> df = getDistanceFunction();
// The actual storage
final WritableDataStore<Meta> metas = DataStoreUtil.makeStorage(relation.getDBIDs(), DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_TEMP, Meta.class);
// Build the metadata, track the two nearest cluster centers.
for(DBIDIter id = relation.iterDBIDs(); id.valid(); id.advance()) {
Meta c = new Meta(k);
V fv = relation.get(id);
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c.secondary = i;
}
}
}
metas.put(id, c);
}
return metas;
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elki-project/elki | addons/tutorial/src/main/java/tutorial/clustering/SameSizeKMeansAlgorithm.java | SameSizeKMeansAlgorithm.transfer | protected void transfer(final WritableDataStore<Meta> metas, Meta meta, ModifiableDBIDs src, ModifiableDBIDs dst, DBIDRef id, int dstnum) {
src.remove(id);
dst.add(id);
meta.primary = dstnum;
metas.put(id, meta); // Make sure the storage is up to date.
} | java | protected void transfer(final WritableDataStore<Meta> metas, Meta meta, ModifiableDBIDs src, ModifiableDBIDs dst, DBIDRef id, int dstnum) {
src.remove(id);
dst.add(id);
meta.primary = dstnum;
metas.put(id, meta); // Make sure the storage is up to date.
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/dependence/HoeffdingsDDependenceMeasure.java | HoeffdingsDDependenceMeasure.toPValue | public double toPValue(double d, int n) {
double b = d / 30 + 1. / (36 * n);
double z = .5 * MathUtil.PISQUARE * MathUtil.PISQUARE * n * b;
// Exponential approximation
if(z < 1.1 || z > 8.5) {
double e = FastMath.exp(0.3885037 - 1.164879 * z);
return (e > 1) ? 1 : (e < 0) ? 0 : e;
}
// Tabular approximation
for(int i = 0; i < 86; i++) {
if(TABPOS[i] >= z) {
// Exact table value
if(TABPOS[i] == z) {
return TABVAL[i];
}
// Linear interpolation
double x1 = TABPOS[i], x0 = TABPOS[i - 1];
double y1 = TABVAL[i], y0 = TABVAL[i - 1];
return y0 + (y1 - y0) * (z - x0) / (x1 - x0);
}
}
return -1;
} | java | public double toPValue(double d, int n) {
double b = d / 30 + 1. / (36 * n);
double z = .5 * MathUtil.PISQUARE * MathUtil.PISQUARE * n * b;
// Exponential approximation
if(z < 1.1 || z > 8.5) {
double e = FastMath.exp(0.3885037 - 1.164879 * z);
return (e > 1) ? 1 : (e < 0) ? 0 : e;
}
// Tabular approximation
for(int i = 0; i < 86; i++) {
if(TABPOS[i] >= z) {
// Exact table value
if(TABPOS[i] == z) {
return TABVAL[i];
}
// Linear interpolation
double x1 = TABPOS[i], x0 = TABPOS[i - 1];
double y1 = TABVAL[i], y0 = TABVAL[i - 1];
return y0 + (y1 - y0) * (z - x0) / (x1 - x0);
}
}
return -1;
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elki-project/elki | elki-core-parallel/src/main/java/de/lmu/ifi/dbs/elki/parallel/ParallelExecutor.java | ParallelExecutor.run | public static void run(DBIDs ids, Processor... procs) {
ParallelCore core = ParallelCore.getCore();
core.connect();
try {
// TODO: try different strategies anyway!
ArrayDBIDs aids = DBIDUtil.ensureArray(ids);
final int size = aids.size();
int numparts = core.getParallelism();
// TODO: are there better heuristics for choosing this?
numparts = (size > numparts * numparts * 16) ? numparts * Math.max(1, numparts - 1) : numparts;
final int blocksize = (size + (numparts - 1)) / numparts;
List<Future<ArrayDBIDs>> parts = new ArrayList<>(numparts);
for(int i = 0; i < numparts; i++) {
final int start = i * blocksize;
final int end = Math.min(start + blocksize, size);
Callable<ArrayDBIDs> run = new BlockArrayRunner(aids, start, end, procs);
parts.add(core.submit(run));
}
for(Future<ArrayDBIDs> fut : parts) {
fut.get();
}
}
catch(ExecutionException e) {
throw new RuntimeException("Processor execution failed.", e);
}
catch(InterruptedException e) {
throw new RuntimeException("Parallel execution interrupted.");
}
finally {
core.disconnect();
}
} | java | public static void run(DBIDs ids, Processor... procs) {
ParallelCore core = ParallelCore.getCore();
core.connect();
try {
// TODO: try different strategies anyway!
ArrayDBIDs aids = DBIDUtil.ensureArray(ids);
final int size = aids.size();
int numparts = core.getParallelism();
// TODO: are there better heuristics for choosing this?
numparts = (size > numparts * numparts * 16) ? numparts * Math.max(1, numparts - 1) : numparts;
final int blocksize = (size + (numparts - 1)) / numparts;
List<Future<ArrayDBIDs>> parts = new ArrayList<>(numparts);
for(int i = 0; i < numparts; i++) {
final int start = i * blocksize;
final int end = Math.min(start + blocksize, size);
Callable<ArrayDBIDs> run = new BlockArrayRunner(aids, start, end, procs);
parts.add(core.submit(run));
}
for(Future<ArrayDBIDs> fut : parts) {
fut.get();
}
}
catch(ExecutionException e) {
throw new RuntimeException("Processor execution failed.", e);
}
catch(InterruptedException e) {
throw new RuntimeException("Parallel execution interrupted.");
}
finally {
core.disconnect();
}
} | [
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/opticsplot/OPTICSPlot.java | OPTICSPlot.replot | public void replot() {
width = co.size();
height = (int) Math.ceil(width * .2);
ratio = width / (double) height;
height = height < MIN_HEIGHT ? MIN_HEIGHT : height > MAX_HEIGHT ? MAX_HEIGHT : height;
if(scale == null) {
scale = computeScale(co);
}
BufferedImage img = new BufferedImage(width, height, BufferedImage.TYPE_INT_ARGB);
int x = 0;
for(DBIDIter it = co.iter(); it.valid(); it.advance()) {
double reach = co.getReachability(it);
final int y = scaleToPixel(reach);
try {
int col = colors.getColorForDBID(it);
for(int y2 = height - 1; y2 >= y; y2--) {
img.setRGB(x, y2, col);
}
}
catch(ArrayIndexOutOfBoundsException e) {
LOG.error("Plotting out of range: " + x + "," + y + " >= " + width + "x" + height);
}
x++;
}
plot = img;
} | java | public void replot() {
width = co.size();
height = (int) Math.ceil(width * .2);
ratio = width / (double) height;
height = height < MIN_HEIGHT ? MIN_HEIGHT : height > MAX_HEIGHT ? MAX_HEIGHT : height;
if(scale == null) {
scale = computeScale(co);
}
BufferedImage img = new BufferedImage(width, height, BufferedImage.TYPE_INT_ARGB);
int x = 0;
for(DBIDIter it = co.iter(); it.valid(); it.advance()) {
double reach = co.getReachability(it);
final int y = scaleToPixel(reach);
try {
int col = colors.getColorForDBID(it);
for(int y2 = height - 1; y2 >= y; y2--) {
img.setRGB(x, y2, col);
}
}
catch(ArrayIndexOutOfBoundsException e) {
LOG.error("Plotting out of range: " + x + "," + y + " >= " + width + "x" + height);
}
x++;
}
plot = img;
} | [
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/opticsplot/OPTICSPlot.java | OPTICSPlot.scaleToPixel | public int scaleToPixel(double reach) {
return (Double.isInfinite(reach) || Double.isNaN(reach)) ? 0 : //
(int) Math.round(scale.getScaled(reach, height - .5, .5));
} | java | public int scaleToPixel(double reach) {
return (Double.isInfinite(reach) || Double.isNaN(reach)) ? 0 : //
(int) Math.round(scale.getScaled(reach, height - .5, .5));
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/opticsplot/OPTICSPlot.java | OPTICSPlot.getSVGPlotURI | public String getSVGPlotURI() {
if(plotnum < 0) {
plotnum = ThumbnailRegistryEntry.registerImage(plot);
}
return ThumbnailRegistryEntry.INTERNAL_PREFIX + plotnum;
} | java | public String getSVGPlotURI() {
if(plotnum < 0) {
plotnum = ThumbnailRegistryEntry.registerImage(plot);
}
return ThumbnailRegistryEntry.INTERNAL_PREFIX + plotnum;
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/opticsplot/OPTICSPlot.java | OPTICSPlot.plotForClusterOrder | public static OPTICSPlot plotForClusterOrder(ClusterOrder co, VisualizerContext context) {
// Check for an existing plot
// ArrayList<OPTICSPlot<D>> plots = ResultUtil.filterResults(co,
// OPTICSPlot.class);
// if (plots.size() > 0) {
// return plots.get(0);
// }
final StylingPolicy policy = context.getStylingPolicy();
OPTICSPlot opticsplot = new OPTICSPlot(co, policy);
// co.addChildResult(opticsplot);
return opticsplot;
} | java | public static OPTICSPlot plotForClusterOrder(ClusterOrder co, VisualizerContext context) {
// Check for an existing plot
// ArrayList<OPTICSPlot<D>> plots = ResultUtil.filterResults(co,
// OPTICSPlot.class);
// if (plots.size() > 0) {
// return plots.get(0);
// }
final StylingPolicy policy = context.getStylingPolicy();
OPTICSPlot opticsplot = new OPTICSPlot(co, policy);
// co.addChildResult(opticsplot);
return opticsplot;
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/LUDecomposition.java | LUDecomposition.inverse | public double[][] inverse() {
// Build permuted identity matrix efficiently:
double[][] b = new double[piv.length][m];
for(int i = 0; i < piv.length; i++) {
b[piv[i]][i] = 1.;
}
return solveInplace(b);
} | java | public double[][] inverse() {
// Build permuted identity matrix efficiently:
double[][] b = new double[piv.length][m];
for(int i = 0; i < piv.length; i++) {
b[piv[i]][i] = 1.;
}
return solveInplace(b);
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elki-project/elki | elki-input/src/main/java/de/lmu/ifi/dbs/elki/datasource/parser/SimplePolygonParser.java | SimplePolygonParser.parseLine | private boolean parseLine() {
cureid = null;
curpoly = null;
curlbl = null;
polys.clear();
coords.clear();
labels.clear();
Matcher m = COORD.matcher(reader.getBuffer());
for(/* initialized by nextLineExceptComments */; tokenizer.valid(); tokenizer.advance()) {
m.region(tokenizer.getStart(), tokenizer.getEnd());
if(m.find()) {
try {
double c1 = ParseUtil.parseDouble(m.group(1));
double c2 = ParseUtil.parseDouble(m.group(2));
if(m.group(3) != null) {
double c3 = ParseUtil.parseDouble(m.group(3));
coords.add(new double[] { c1, c2, c3 });
}
else {
coords.add(new double[] { c1, c2 });
}
continue;
}
catch(NumberFormatException e) {
LOG.warning("Looked like a coordinate pair but didn't parse: " + tokenizer.getSubstring());
}
}
// Match polygon separator:
// FIXME: Avoid unnecessary subSequence call.
final int len = tokenizer.getEnd() - tokenizer.getStart();
if(POLYGON_SEPARATOR.length() == len && //
reader.getBuffer().subSequence(tokenizer.getStart(), tokenizer.getEnd()).equals(POLYGON_SEPARATOR)) {
if(!coords.isEmpty()) {
polys.add(new Polygon(new ArrayList<>(coords)));
}
continue;
}
String cur = tokenizer.getSubstring();
// First label will become the External ID
if(cureid == null) {
cureid = new ExternalID(cur);
}
else {
labels.add(cur);
}
}
// Complete polygon
if(!coords.isEmpty()) {
polys.add(new Polygon(coords));
}
curpoly = new PolygonsObject(polys);
curlbl = (haslabels || !labels.isEmpty()) ? LabelList.make(labels) : null;
return true;
} | java | private boolean parseLine() {
cureid = null;
curpoly = null;
curlbl = null;
polys.clear();
coords.clear();
labels.clear();
Matcher m = COORD.matcher(reader.getBuffer());
for(/* initialized by nextLineExceptComments */; tokenizer.valid(); tokenizer.advance()) {
m.region(tokenizer.getStart(), tokenizer.getEnd());
if(m.find()) {
try {
double c1 = ParseUtil.parseDouble(m.group(1));
double c2 = ParseUtil.parseDouble(m.group(2));
if(m.group(3) != null) {
double c3 = ParseUtil.parseDouble(m.group(3));
coords.add(new double[] { c1, c2, c3 });
}
else {
coords.add(new double[] { c1, c2 });
}
continue;
}
catch(NumberFormatException e) {
LOG.warning("Looked like a coordinate pair but didn't parse: " + tokenizer.getSubstring());
}
}
// Match polygon separator:
// FIXME: Avoid unnecessary subSequence call.
final int len = tokenizer.getEnd() - tokenizer.getStart();
if(POLYGON_SEPARATOR.length() == len && //
reader.getBuffer().subSequence(tokenizer.getStart(), tokenizer.getEnd()).equals(POLYGON_SEPARATOR)) {
if(!coords.isEmpty()) {
polys.add(new Polygon(new ArrayList<>(coords)));
}
continue;
}
String cur = tokenizer.getSubstring();
// First label will become the External ID
if(cureid == null) {
cureid = new ExternalID(cur);
}
else {
labels.add(cur);
}
}
// Complete polygon
if(!coords.isEmpty()) {
polys.add(new Polygon(coords));
}
curpoly = new PolygonsObject(polys);
curlbl = (haslabels || !labels.isEmpty()) ? LabelList.make(labels) : null;
return true;
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elki-project/elki | elki/src/main/java/de/lmu/ifi/dbs/elki/workflow/OutputStep.java | OutputStep.runResultHandlers | public void runResultHandlers(ResultHierarchy hier, Database db) {
// Run result handlers
for(ResultHandler resulthandler : resulthandlers) {
Thread.currentThread().setName(resulthandler.toString());
resulthandler.processNewResult(hier, db);
}
} | java | public void runResultHandlers(ResultHierarchy hier, Database db) {
// Run result handlers
for(ResultHandler resulthandler : resulthandlers) {
Thread.currentThread().setName(resulthandler.toString());
resulthandler.processNewResult(hier, db);
}
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elki-project/elki | elki/src/main/java/de/lmu/ifi/dbs/elki/workflow/OutputStep.java | OutputStep.setDefaultHandlerVisualizer | @SuppressWarnings("unchecked")
public static void setDefaultHandlerVisualizer() {
defaultHandlers = new ArrayList<>(1);
Class<? extends ResultHandler> clz;
try {
clz = (Class<? extends ResultHandler>) Thread.currentThread().getContextClassLoader().loadClass(//
"de.lmu.ifi.dbs.elki.result.AutomaticVisualization");
}
catch(ClassNotFoundException e) {
clz = ResultWriter.class;
}
defaultHandlers.add(clz);
} | java | @SuppressWarnings("unchecked")
public static void setDefaultHandlerVisualizer() {
defaultHandlers = new ArrayList<>(1);
Class<? extends ResultHandler> clz;
try {
clz = (Class<? extends ResultHandler>) Thread.currentThread().getContextClassLoader().loadClass(//
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}
catch(ClassNotFoundException e) {
clz = ResultWriter.class;
}
defaultHandlers.add(clz);
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elki-project/elki | elki-core-parallel/src/main/java/de/lmu/ifi/dbs/elki/parallel/ParallelCore.java | ParallelCore.connect | public synchronized void connect() {
if(executor == null) {
executor = new ThreadPoolExecutor(0, processors, 10L, TimeUnit.MILLISECONDS, new LinkedBlockingQueue<Runnable>());
executor.allowCoreThreadTimeOut(true);
}
if(++connected == 1) {
executor.allowCoreThreadTimeOut(false);
executor.setCorePoolSize(executor.getMaximumPoolSize());
}
} | java | public synchronized void connect() {
if(executor == null) {
executor = new ThreadPoolExecutor(0, processors, 10L, TimeUnit.MILLISECONDS, new LinkedBlockingQueue<Runnable>());
executor.allowCoreThreadTimeOut(true);
}
if(++connected == 1) {
executor.allowCoreThreadTimeOut(false);
executor.setCorePoolSize(executor.getMaximumPoolSize());
}
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/geometry/XYCurve.java | XYCurve.add | public void add(double x, double y) {
data.add(x);
data.add(y);
minx = Math.min(minx, x);
maxx = Math.max(maxx, x);
miny = Math.min(miny, y);
maxy = Math.max(maxy, y);
} | java | public void add(double x, double y) {
data.add(x);
data.add(y);
minx = Math.min(minx, x);
maxx = Math.max(maxx, x);
miny = Math.min(miny, y);
maxy = Math.max(maxy, y);
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/geometry/XYCurve.java | XYCurve.addAndSimplify | public void addAndSimplify(double x, double y) {
// simplify curve when possible:
final int len = data.size();
if (len >= 4) {
// Look at the previous 2 points
final double l1x = data.get(len - 4);
final double l1y = data.get(len - 3);
final double l2x = data.get(len - 2);
final double l2y = data.get(len - 1);
// Differences:
final double ldx = l2x - l1x;
final double ldy = l2y - l1y;
final double cdx = x - l2x;
final double cdy = y - l2y;
// X simplification
if ((ldx == 0) && (cdx == 0)) {
data.remove(len - 2, 2);
}
// horizontal simplification
else if ((ldy == 0) && (cdy == 0)) {
data.remove(len - 2, 2);
}
// diagonal simplification
else if (ldy > 0 && cdy > 0) {
if (Math.abs((ldx / ldy) - (cdx / cdy)) < THRESHOLD) {
data.remove(len - 2, 2);
}
}
}
add(x, y);
} | java | public void addAndSimplify(double x, double y) {
// simplify curve when possible:
final int len = data.size();
if (len >= 4) {
// Look at the previous 2 points
final double l1x = data.get(len - 4);
final double l1y = data.get(len - 3);
final double l2x = data.get(len - 2);
final double l2y = data.get(len - 1);
// Differences:
final double ldx = l2x - l1x;
final double ldy = l2y - l1y;
final double cdx = x - l2x;
final double cdy = y - l2y;
// X simplification
if ((ldx == 0) && (cdx == 0)) {
data.remove(len - 2, 2);
}
// horizontal simplification
else if ((ldy == 0) && (cdy == 0)) {
data.remove(len - 2, 2);
}
// diagonal simplification
else if (ldy > 0 && cdy > 0) {
if (Math.abs((ldx / ldy) - (cdx / cdy)) < THRESHOLD) {
data.remove(len - 2, 2);
}
}
}
add(x, y);
} | [
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/geometry/XYCurve.java | XYCurve.rescale | public void rescale(double sx, double sy) {
for (int i = 0; i < data.size(); i += 2) {
data.set(i, sx * data.get(i));
data.set(i + 1, sy * data.get(i + 1));
}
maxx *= sx;
maxy *= sy;
} | java | public void rescale(double sx, double sy) {
for (int i = 0; i < data.size(); i += 2) {
data.set(i, sx * data.get(i));
data.set(i + 1, sy * data.get(i + 1));
}
maxx *= sx;
maxy *= sy;
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elki-project/elki | elki-index-mtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/metrical/mtreevariants/strategies/insert/MinimumEnlargementInsert.java | MinimumEnlargementInsert.choosePath | private IndexTreePath<E> choosePath(AbstractMTree<?, N, E, ?> tree, E object, IndexTreePath<E> subtree) {
N node = tree.getNode(subtree.getEntry());
// leaf
if(node.isLeaf()) {
return subtree;
}
// Initialize from first:
int bestIdx = 0;
E bestEntry = node.getEntry(0);
double bestDistance = tree.distance(object.getRoutingObjectID(), bestEntry.getRoutingObjectID());
// Iterate over remaining
for(int i = 1; i < node.getNumEntries(); i++) {
E entry = node.getEntry(i);
double distance = tree.distance(object.getRoutingObjectID(), entry.getRoutingObjectID());
if(distance < bestDistance) {
bestIdx = i;
bestEntry = entry;
bestDistance = distance;
}
}
return choosePath(tree, object, new IndexTreePath<>(subtree, bestEntry, bestIdx));
} | java | private IndexTreePath<E> choosePath(AbstractMTree<?, N, E, ?> tree, E object, IndexTreePath<E> subtree) {
N node = tree.getNode(subtree.getEntry());
// leaf
if(node.isLeaf()) {
return subtree;
}
// Initialize from first:
int bestIdx = 0;
E bestEntry = node.getEntry(0);
double bestDistance = tree.distance(object.getRoutingObjectID(), bestEntry.getRoutingObjectID());
// Iterate over remaining
for(int i = 1; i < node.getNumEntries(); i++) {
E entry = node.getEntry(i);
double distance = tree.distance(object.getRoutingObjectID(), entry.getRoutingObjectID());
if(distance < bestDistance) {
bestIdx = i;
bestEntry = entry;
bestDistance = distance;
}
}
return choosePath(tree, object, new IndexTreePath<>(subtree, bestEntry, bestIdx));
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elki-project/elki | elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/optionhandling/parameterization/MergedParameterization.java | MergedParameterization.rewind | public void rewind() {
synchronized(used) {
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synchronized(used) {
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used.clear();
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/estimator/UniformEnhancedMinMaxEstimator.java | UniformEnhancedMinMaxEstimator.estimate | public UniformDistribution estimate(double min, double max, final int count) {
double grow = (count > 1) ? 0.5 * (max - min) / (count - 1) : 0.;
return new UniformDistribution(Math.max(min - grow, -Double.MAX_VALUE), Math.min(max + grow, Double.MAX_VALUE));
} | java | public UniformDistribution estimate(double min, double max, final int count) {
double grow = (count > 1) ? 0.5 * (max - min) / (count - 1) : 0.;
return new UniformDistribution(Math.max(min - grow, -Double.MAX_VALUE), Math.min(max + grow, Double.MAX_VALUE));
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/WeibullDistribution.java | WeibullDistribution.cdf | public static double cdf(double val, double k, double lambda, double theta) {
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} | java | public static double cdf(double val, double k, double lambda, double theta) {
return (val > theta) ? //
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/WeibullDistribution.java | WeibullDistribution.quantile | public static double quantile(double val, double k, double lambda, double theta) {
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}
} | java | public static double quantile(double val, double k, double lambda, double theta) {
if(val < 0.0 || val > 1.0) {
return Double.NaN;
}
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return 0.0;
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}
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/pca/PCARunner.java | PCARunner.processIds | public PCAResult processIds(DBIDs ids, Relation<? extends NumberVector> database) {
return processCovarMatrix(covarianceMatrixBuilder.processIds(ids, database));
} | java | public PCAResult processIds(DBIDs ids, Relation<? extends NumberVector> database) {
return processCovarMatrix(covarianceMatrixBuilder.processIds(ids, database));
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/pca/PCARunner.java | PCARunner.processQueryResult | public PCAResult processQueryResult(DoubleDBIDList results, Relation<? extends NumberVector> database) {
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} | java | public PCAResult processQueryResult(DoubleDBIDList results, Relation<? extends NumberVector> database) {
return processCovarMatrix(covarianceMatrixBuilder.processQueryResults(results, database));
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/QRDecomposition.java | QRDecomposition.isFullRank | public boolean isFullRank() {
// Find maximum:
double t = 0.;
for(int j = 0; j < n; j++) {
double v = Rdiag[j];
if(v == 0) {
return false;
}
v = Math.abs(v);
t = v > t ? v : t;
}
t *= 1e-15; // Numerical precision threshold.
for(int j = 1; j < n; j++) {
if(Math.abs(Rdiag[j]) < t) {
return false;
}
}
return true;
} | java | public boolean isFullRank() {
// Find maximum:
double t = 0.;
for(int j = 0; j < n; j++) {
double v = Rdiag[j];
if(v == 0) {
return false;
}
v = Math.abs(v);
t = v > t ? v : t;
}
t *= 1e-15; // Numerical precision threshold.
for(int j = 1; j < n; j++) {
if(Math.abs(Rdiag[j]) < t) {
return false;
}
}
return true;
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/QRDecomposition.java | QRDecomposition.rank | public int rank(double t) {
int rank = n;
for(int j = 0; j < n; j++) {
if(Math.abs(Rdiag[j]) <= t) {
--rank;
}
}
return rank;
} | java | public int rank(double t) {
int rank = n;
for(int j = 0; j < n; j++) {
if(Math.abs(Rdiag[j]) <= t) {
--rank;
}
}
return rank;
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/visualizers/visunproj/XYPlotVisualization.java | XYPlotVisualization.setupCSS | private void setupCSS(VisualizerContext context, SVGPlot svgp, XYPlot plot) {
StyleLibrary style = context.getStyleLibrary();
for(XYPlot.Curve curve : plot) {
CSSClass csscls = new CSSClass(this, SERIESID + curve.getColor());
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csscls.setStatement(SVGConstants.SVG_FILL_ATTRIBUTE, SVGConstants.SVG_NONE_VALUE);
style.lines().formatCSSClass(csscls, curve.getColor(), style.getLineWidth(StyleLibrary.XYCURVE));
svgp.addCSSClassOrLogError(csscls);
}
// Axis label
CSSClass label = new CSSClass(this, CSS_AXIS_LABEL);
label.setStatement(SVGConstants.CSS_FILL_PROPERTY, style.getTextColor(StyleLibrary.XYCURVE));
label.setStatement(SVGConstants.CSS_FONT_FAMILY_PROPERTY, style.getFontFamily(StyleLibrary.XYCURVE));
label.setStatement(SVGConstants.CSS_FONT_SIZE_PROPERTY, style.getTextSize(StyleLibrary.XYCURVE));
label.setStatement(SVGConstants.CSS_TEXT_ANCHOR_PROPERTY, SVGConstants.CSS_MIDDLE_VALUE);
svgp.addCSSClassOrLogError(label);
svgp.updateStyleElement();
} | java | private void setupCSS(VisualizerContext context, SVGPlot svgp, XYPlot plot) {
StyleLibrary style = context.getStyleLibrary();
for(XYPlot.Curve curve : plot) {
CSSClass csscls = new CSSClass(this, SERIESID + curve.getColor());
// csscls.setStatement(SVGConstants.SVG_STROKE_WIDTH_ATTRIBUTE, "0.2%");
csscls.setStatement(SVGConstants.SVG_FILL_ATTRIBUTE, SVGConstants.SVG_NONE_VALUE);
style.lines().formatCSSClass(csscls, curve.getColor(), style.getLineWidth(StyleLibrary.XYCURVE));
svgp.addCSSClassOrLogError(csscls);
}
// Axis label
CSSClass label = new CSSClass(this, CSS_AXIS_LABEL);
label.setStatement(SVGConstants.CSS_FILL_PROPERTY, style.getTextColor(StyleLibrary.XYCURVE));
label.setStatement(SVGConstants.CSS_FONT_FAMILY_PROPERTY, style.getFontFamily(StyleLibrary.XYCURVE));
label.setStatement(SVGConstants.CSS_FONT_SIZE_PROPERTY, style.getTextSize(StyleLibrary.XYCURVE));
label.setStatement(SVGConstants.CSS_TEXT_ANCHOR_PROPERTY, SVGConstants.CSS_MIDDLE_VALUE);
svgp.addCSSClassOrLogError(label);
svgp.updateStyleElement();
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/pca/EigenPair.java | EigenPair.compareTo | @Override
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return 0;
} | java | @Override
public int compareTo(EigenPair o) {
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return -1;
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return +1;
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elki-project/elki | elki-outlier/src/main/java/de/lmu/ifi/dbs/elki/utilities/scaling/outlier/MixtureModelOutlierScaling.java | MixtureModelOutlierScaling.calcPosterior | protected static double calcPosterior(double f, double alpha, double mu, double sigma, double lambda) {
final double pi = calcP_i(f, mu, sigma);
final double qi = calcQ_i(f, lambda);
return (alpha * pi) / (alpha * pi + (1.0 - alpha) * qi);
} | java | protected static double calcPosterior(double f, double alpha, double mu, double sigma, double lambda) {
final double pi = calcP_i(f, mu, sigma);
final double qi = calcQ_i(f, lambda);
return (alpha * pi) / (alpha * pi + (1.0 - alpha) * qi);
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] | b54673327e76198ecd4c8a2a901021f1a9174498 | https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-outlier/src/main/java/de/lmu/ifi/dbs/elki/utilities/scaling/outlier/MixtureModelOutlierScaling.java#L129-L133 | train |
elki-project/elki | elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/cash/CASHInterval.java | CASHInterval.split | public void split() {
if(hasChildren()) {
return;
}
final boolean issplit = (maxSplitDimension >= (getDimensionality() - 1));
final int childLevel = issplit ? level + 1 : level;
final int splitDim = issplit ? 0 : maxSplitDimension + 1;
final double splitPoint = getMin(splitDim) + (getMax(splitDim) - getMin(splitDim)) * .5;
// left and right child
for(int i = 0; i < 2; i++) {
double[] min = SpatialUtil.getMin(this); // clone
double[] max = SpatialUtil.getMax(this); // clone
// right child
if(i == 0) {
min[splitDim] = splitPoint;
}
// left child
else {
max[splitDim] = splitPoint;
}
ModifiableDBIDs childIDs = split.determineIDs(getIDs(), new HyperBoundingBox(min, max), d_min, d_max);
if(childIDs != null) {
// right child
if(i == 0) {
rightChild = new CASHInterval(min, max, split, childIDs, splitDim, childLevel, d_min, d_max);
}
// left child
else {
leftChild = new CASHInterval(min, max, split, childIDs, splitDim, childLevel, d_min, d_max);
}
}
}
if(LOG.isDebuggingFine()) {
StringBuilder msg = new StringBuilder();
msg.append("Child level ").append(childLevel).append(", split Dim ").append(splitDim);
if(leftChild != null) {
msg.append("\nleft ").append(leftChild);
}
if(rightChild != null) {
msg.append("\nright ").append(rightChild);
}
LOG.fine(msg.toString());
}
} | java | public void split() {
if(hasChildren()) {
return;
}
final boolean issplit = (maxSplitDimension >= (getDimensionality() - 1));
final int childLevel = issplit ? level + 1 : level;
final int splitDim = issplit ? 0 : maxSplitDimension + 1;
final double splitPoint = getMin(splitDim) + (getMax(splitDim) - getMin(splitDim)) * .5;
// left and right child
for(int i = 0; i < 2; i++) {
double[] min = SpatialUtil.getMin(this); // clone
double[] max = SpatialUtil.getMax(this); // clone
// right child
if(i == 0) {
min[splitDim] = splitPoint;
}
// left child
else {
max[splitDim] = splitPoint;
}
ModifiableDBIDs childIDs = split.determineIDs(getIDs(), new HyperBoundingBox(min, max), d_min, d_max);
if(childIDs != null) {
// right child
if(i == 0) {
rightChild = new CASHInterval(min, max, split, childIDs, splitDim, childLevel, d_min, d_max);
}
// left child
else {
leftChild = new CASHInterval(min, max, split, childIDs, splitDim, childLevel, d_min, d_max);
}
}
}
if(LOG.isDebuggingFine()) {
StringBuilder msg = new StringBuilder();
msg.append("Child level ").append(childLevel).append(", split Dim ").append(splitDim);
if(leftChild != null) {
msg.append("\nleft ").append(leftChild);
}
if(rightChild != null) {
msg.append("\nright ").append(rightChild);
}
LOG.fine(msg.toString());
}
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elki-project/elki | elki-data-generator/src/main/java/de/lmu/ifi/dbs/elki/application/GeneratorXMLSpec.java | GeneratorXMLSpec.run | @Override
public void run() {
MultipleObjectsBundle data = generator.loadData();
if(LOG.isVerbose()) {
LOG.verbose("Writing output ...");
}
try {
if(outputFile.exists() && LOG.isVerbose()) {
LOG.verbose("The file " + outputFile + " already exists, " + "the generator result will be APPENDED.");
}
try (OutputStreamWriter outStream = new FileWriter(outputFile, true)) {
writeClusters(outStream, data);
}
}
catch(IOException e) {
throw new AbortException("IO Error in data generator.", e);
}
if(LOG.isVerbose()) {
LOG.verbose("Done.");
}
} | java | @Override
public void run() {
MultipleObjectsBundle data = generator.loadData();
if(LOG.isVerbose()) {
LOG.verbose("Writing output ...");
}
try {
if(outputFile.exists() && LOG.isVerbose()) {
LOG.verbose("The file " + outputFile + " already exists, " + "the generator result will be APPENDED.");
}
try (OutputStreamWriter outStream = new FileWriter(outputFile, true)) {
writeClusters(outStream, data);
}
}
catch(IOException e) {
throw new AbortException("IO Error in data generator.", e);
}
if(LOG.isVerbose()) {
LOG.verbose("Done.");
}
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elki-project/elki | elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/random/RandomFactory.java | RandomFactory.getGlobalSeed | private static long getGlobalSeed() {
String sseed = System.getProperty("elki.seed");
return (sseed != null) ? Long.parseLong(sseed) : System.nanoTime();
} | java | private static long getGlobalSeed() {
String sseed = System.getProperty("elki.seed");
return (sseed != null) ? Long.parseLong(sseed) : System.nanoTime();
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elki-project/elki | elki-index-mtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/metrical/mtreevariants/strategies/split/distribution/Assignments.java | Assignments.computeFirstCover | public double computeFirstCover(boolean leaf) {
double max = 0.;
for(DistanceEntry<E> e : firstAssignments) {
double cover = leaf ? e.getDistance() : (e.getEntry().getCoveringRadius() + e.getDistance());
max = cover > max ? cover : max;
}
return max;
} | java | public double computeFirstCover(boolean leaf) {
double max = 0.;
for(DistanceEntry<E> e : firstAssignments) {
double cover = leaf ? e.getDistance() : (e.getEntry().getCoveringRadius() + e.getDistance());
max = cover > max ? cover : max;
}
return max;
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elki-project/elki | elki-index-mtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/metrical/mtreevariants/strategies/split/distribution/Assignments.java | Assignments.computeSecondCover | public double computeSecondCover(boolean leaf) {
double max = 0.;
for(DistanceEntry<E> e : secondAssignments) {
double cover = leaf ? e.getDistance() : (e.getEntry().getCoveringRadius() + e.getDistance());
max = cover > max ? cover : max;
}
return max;
} | java | public double computeSecondCover(boolean leaf) {
double max = 0.;
for(DistanceEntry<E> e : secondAssignments) {
double cover = leaf ? e.getDistance() : (e.getEntry().getCoveringRadius() + e.getDistance());
max = cover > max ? cover : max;
}
return max;
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elki-project/elki | elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/datastructures/heap/UpdatableHeap.java | UpdatableHeap.offerAt | protected void offerAt(final int pos, O e) {
if(pos == NO_VALUE) {
// resize when needed
if(size + 1 > queue.length) {
resize(size + 1);
}
index.put(e, size);
size++;
heapifyUp(size - 1, e);
heapModified();
return;
}
assert (pos >= 0) : "Unexpected negative position.";
assert (queue[pos].equals(e));
// Did the value improve?
if(comparator.compare(e, queue[pos]) >= 0) {
return;
}
heapifyUp(pos, e);
heapModified();
return;
} | java | protected void offerAt(final int pos, O e) {
if(pos == NO_VALUE) {
// resize when needed
if(size + 1 > queue.length) {
resize(size + 1);
}
index.put(e, size);
size++;
heapifyUp(size - 1, e);
heapModified();
return;
}
assert (pos >= 0) : "Unexpected negative position.";
assert (queue[pos].equals(e));
// Did the value improve?
if(comparator.compare(e, queue[pos]) >= 0) {
return;
}
heapifyUp(pos, e);
heapModified();
return;
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elki-project/elki | elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/datastructures/heap/UpdatableHeap.java | UpdatableHeap.removeObject | public O removeObject(O e) {
int pos = index.getInt(e);
return (pos >= 0) ? removeAt(pos) : null;
} | java | public O removeObject(O e) {
int pos = index.getInt(e);
return (pos >= 0) ? removeAt(pos) : null;
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/dependence/HSMDependenceMeasure.java | HSMDependenceMeasure.sumMatrix | private long sumMatrix(int[][] mat) {
long ret = 0;
for(int i = 0; i < mat.length; i++) {
final int[] row = mat[i];
for(int j = 0; j < row.length; j++) {
ret += row[j];
}
}
return ret;
} | java | private long sumMatrix(int[][] mat) {
long ret = 0;
for(int i = 0; i < mat.length; i++) {
final int[] row = mat[i];
for(int j = 0; j < row.length; j++) {
ret += row[j];
}
}
return ret;
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/dependence/HSMDependenceMeasure.java | HSMDependenceMeasure.countAboveThreshold | private int countAboveThreshold(int[][] mat, double threshold) {
int ret = 0;
for(int i = 0; i < mat.length; i++) {
int[] row = mat[i];
for(int j = 0; j < row.length; j++) {
if(row[j] >= threshold) {
ret++;
}
}
}
return ret;
} | java | private int countAboveThreshold(int[][] mat, double threshold) {
int ret = 0;
for(int i = 0; i < mat.length; i++) {
int[] row = mat[i];
for(int j = 0; j < row.length; j++) {
if(row[j] >= threshold) {
ret++;
}
}
}
return ret;
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/dependence/HSMDependenceMeasure.java | HSMDependenceMeasure.houghTransformation | private int[][] houghTransformation(boolean[][] mat) {
final int xres = mat.length, yres = mat[0].length;
final double tscale = STEPS * .66 / (xres + yres);
final int[][] ret = new int[STEPS][STEPS];
for(int x = 0; x < mat.length; x++) {
final boolean[] row = mat[x];
for(int y = 0; y < mat[0].length; y++) {
if(row[y]) {
for(int i = 0; i < STEPS; i++) {
final int d = (STEPS >> 1) + (int) (tscale * (x * table.cos(i) + y * table.sin(i)));
if(d > 0 && d < STEPS) {
ret[d][i]++;
}
}
}
}
}
return ret;
} | java | private int[][] houghTransformation(boolean[][] mat) {
final int xres = mat.length, yres = mat[0].length;
final double tscale = STEPS * .66 / (xres + yres);
final int[][] ret = new int[STEPS][STEPS];
for(int x = 0; x < mat.length; x++) {
final boolean[] row = mat[x];
for(int y = 0; y < mat[0].length; y++) {
if(row[y]) {
for(int i = 0; i < STEPS; i++) {
final int d = (STEPS >> 1) + (int) (tscale * (x * table.cos(i) + y * table.sin(i)));
if(d > 0 && d < STEPS) {
ret[d][i]++;
}
}
}
}
}
return ret;
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/dependence/HSMDependenceMeasure.java | HSMDependenceMeasure.drawLine | private static void drawLine(int x0, int y0, int x1, int y1, boolean[][] pic) {
final int xres = pic.length, yres = pic[0].length;
// Ensure bounds
y0 = (y0 < 0) ? 0 : (y0 >= yres) ? (yres - 1) : y0;
y1 = (y1 < 0) ? 0 : (y1 >= yres) ? (yres - 1) : y1;
x0 = (x0 < 0) ? 0 : (x0 >= xres) ? (xres - 1) : x0;
x1 = (x1 < 0) ? 0 : (x1 >= xres) ? (xres - 1) : x1;
// Default slope
final int dx = +Math.abs(x1 - x0), sx = x0 < x1 ? 1 : -1;
final int dy = -Math.abs(y1 - y0), sy = y0 < y1 ? 1 : -1;
// Error counter
int err = dx + dy;
for(;;) {
pic[x0][y0] = true;
if(x0 == x1 && y0 == y1) {
break;
}
final int e2 = err << 1;
if(e2 > dy) {
err += dy;
x0 += sx;
}
if(e2 < dx) {
err += dx;
y0 += sy;
}
}
} | java | private static void drawLine(int x0, int y0, int x1, int y1, boolean[][] pic) {
final int xres = pic.length, yres = pic[0].length;
// Ensure bounds
y0 = (y0 < 0) ? 0 : (y0 >= yres) ? (yres - 1) : y0;
y1 = (y1 < 0) ? 0 : (y1 >= yres) ? (yres - 1) : y1;
x0 = (x0 < 0) ? 0 : (x0 >= xres) ? (xres - 1) : x0;
x1 = (x1 < 0) ? 0 : (x1 >= xres) ? (xres - 1) : x1;
// Default slope
final int dx = +Math.abs(x1 - x0), sx = x0 < x1 ? 1 : -1;
final int dy = -Math.abs(y1 - y0), sy = y0 < y1 ? 1 : -1;
// Error counter
int err = dx + dy;
for(;;) {
pic[x0][y0] = true;
if(x0 == x1 && y0 == y1) {
break;
}
final int e2 = err << 1;
if(e2 > dy) {
err += dy;
x0 += sx;
}
if(e2 < dx) {
err += dx;
y0 += sy;
}
}
} | [
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@param x0 Start X
@param y0 Start Y
@param x1 End X
@param y1 End Y
@param pic Picture array | [
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elki-project/elki | elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/optionhandling/parameters/EnumParameter.java | EnumParameter.getPossibleValues | public Collection<String> getPossibleValues() {
// Convert to string array
final E[] enums = enumClass.getEnumConstants();
ArrayList<String> values = new ArrayList<>(enums.length);
for(E t : enums) {
values.add(t.name());
}
return values;
} | java | public Collection<String> getPossibleValues() {
// Convert to string array
final E[] enums = enumClass.getEnumConstants();
ArrayList<String> values = new ArrayList<>(enums.length);
for(E t : enums) {
values.add(t.name());
}
return values;
} | [
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elki-project/elki | elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/optionhandling/parameters/EnumParameter.java | EnumParameter.joinEnumNames | private String joinEnumNames(String separator) {
E[] enumTypes = enumClass.getEnumConstants();
StringBuilder sb = new StringBuilder();
for(int i = 0; i < enumTypes.length; ++i) {
if(i > 0) {
sb.append(separator);
}
sb.append(enumTypes[i].name());
}
return sb.toString();
} | java | private String joinEnumNames(String separator) {
E[] enumTypes = enumClass.getEnumConstants();
StringBuilder sb = new StringBuilder();
for(int i = 0; i < enumTypes.length; ++i) {
if(i > 0) {
sb.append(separator);
}
sb.append(enumTypes[i].name());
}
return sb.toString();
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@param separator char sequence to use as a separator for enum values.
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elki-project/elki | elki-index-mtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/metrical/mtreevariants/mktrees/mkmax/MkMaxTree.java | MkMaxTree.preInsert | @Override
protected void preInsert(MkMaxEntry entry) {
KNNHeap knns_o = DBIDUtil.newHeap(getKmax());
preInsert(entry, getRootEntry(), knns_o);
} | java | @Override
protected void preInsert(MkMaxEntry entry) {
KNNHeap knns_o = DBIDUtil.newHeap(getKmax());
preInsert(entry, getRootEntry(), knns_o);
} | [
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elki-project/elki | addons/xtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/xtree/util/SplitHistory.java | SplitHistory.getCommonDimensions | public static IntIterator getCommonDimensions(Collection<SplitHistory> splitHistories) {
Iterator<SplitHistory> it = splitHistories.iterator();
long[] checkSet = BitsUtil.copy(it.next().dimBits);
while(it.hasNext()) {
SplitHistory sh = it.next();
BitsUtil.andI(checkSet, sh.dimBits);
}
return new BitsetIterator(checkSet);
} | java | public static IntIterator getCommonDimensions(Collection<SplitHistory> splitHistories) {
Iterator<SplitHistory> it = splitHistories.iterator();
long[] checkSet = BitsUtil.copy(it.next().dimBits);
while(it.hasNext()) {
SplitHistory sh = it.next();
BitsUtil.andI(checkSet, sh.dimBits);
}
return new BitsetIterator(checkSet);
} | [
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/batikutil/ThumbnailRegistryEntry.java | ThumbnailRegistryEntry.handleURL | public static Filter handleURL(ParsedURL url) {
if(LOG.isDebuggingFiner()) {
LOG.debugFiner("handleURL " + url.toString());
}
if(!isCompatibleURLStatic(url)) {
return null;
}
int id;
try {
id = ParseUtil.parseIntBase10(url.getPath());
}
catch(NumberFormatException e) {
return null;
}
SoftReference<RenderedImage> ref = images.get(id);
if(ref != null) {
RenderedImage ri = ref.get();
if(ri == null) {
LOG.warning("Referenced image has expired from the cache!");
}
else {
return new RedRable(GraphicsUtil.wrap(ri));
}
}
// Image not found in registry.
return null;
} | java | public static Filter handleURL(ParsedURL url) {
if(LOG.isDebuggingFiner()) {
LOG.debugFiner("handleURL " + url.toString());
}
if(!isCompatibleURLStatic(url)) {
return null;
}
int id;
try {
id = ParseUtil.parseIntBase10(url.getPath());
}
catch(NumberFormatException e) {
return null;
}
SoftReference<RenderedImage> ref = images.get(id);
if(ref != null) {
RenderedImage ri = ref.get();
if(ri == null) {
LOG.warning("Referenced image has expired from the cache!");
}
else {
return new RedRable(GraphicsUtil.wrap(ri));
}
}
// Image not found in registry.
return null;
} | [
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... | Statically handle the URL access.
@param url URL to access
@return Image, or null | [
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] | b54673327e76198ecd4c8a2a901021f1a9174498 | https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/batikutil/ThumbnailRegistryEntry.java#L161-L187 | train |
elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/evaluation/clustering/internal/EvaluateVarianceRatioCriteria.java | EvaluateVarianceRatioCriteria.globalCentroid | public static int globalCentroid(Centroid overallCentroid, Relation<? extends NumberVector> rel, List<? extends Cluster<?>> clusters, NumberVector[] centroids, NoiseHandling noiseOption) {
int clustercount = 0;
Iterator<? extends Cluster<?>> ci = clusters.iterator();
for(int i = 0; ci.hasNext(); i++) {
Cluster<?> cluster = ci.next();
if(cluster.size() <= 1 || cluster.isNoise()) {
switch(noiseOption){
case IGNORE_NOISE:
continue; // Ignore completely
case TREAT_NOISE_AS_SINGLETONS:
clustercount += cluster.size();
// Update global centroid:
for(DBIDIter it = cluster.getIDs().iter(); it.valid(); it.advance()) {
overallCentroid.put(rel.get(it));
}
continue; // With NEXT cluster.
case MERGE_NOISE:
break; // Treat as cluster below:
}
}
// Update centroid:
assert (centroids[i] != null);
overallCentroid.put(centroids[i], cluster.size());
++clustercount;
}
return clustercount;
} | java | public static int globalCentroid(Centroid overallCentroid, Relation<? extends NumberVector> rel, List<? extends Cluster<?>> clusters, NumberVector[] centroids, NoiseHandling noiseOption) {
int clustercount = 0;
Iterator<? extends Cluster<?>> ci = clusters.iterator();
for(int i = 0; ci.hasNext(); i++) {
Cluster<?> cluster = ci.next();
if(cluster.size() <= 1 || cluster.isNoise()) {
switch(noiseOption){
case IGNORE_NOISE:
continue; // Ignore completely
case TREAT_NOISE_AS_SINGLETONS:
clustercount += cluster.size();
// Update global centroid:
for(DBIDIter it = cluster.getIDs().iter(); it.valid(); it.advance()) {
overallCentroid.put(rel.get(it));
}
continue; // With NEXT cluster.
case MERGE_NOISE:
break; // Treat as cluster below:
}
}
// Update centroid:
assert (centroids[i] != null);
overallCentroid.put(centroids[i], cluster.size());
++clustercount;
}
return clustercount;
} | [
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@param overallCentroid Centroid to udpate
@param rel Data relation
@param clusters Clusters
@param centroids Cluster centroids
@return Number of clusters | [
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] | b54673327e76198ecd4c8a2a901021f1a9174498 | https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/evaluation/clustering/internal/EvaluateVarianceRatioCriteria.java#L190-L216 | train |
elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/hierarchical/PointerPrototypeHierarchyRepresentationResult.java | PointerPrototypeHierarchyRepresentationResult.findPrototype | public DBID findPrototype(DBIDs members) {
// Find the last merge within the cluster.
// The object with maximum priority will merge outside of the cluster,
// So we need the second largest priority.
DBIDIter it = members.iter();
DBIDVar proto = DBIDUtil.newVar(it), last = DBIDUtil.newVar(it);
int maxprio = Integer.MIN_VALUE, secprio = Integer.MIN_VALUE;
for(; it.valid(); it.advance()) {
int prio = mergeOrder.intValue(it);
if(prio > maxprio) {
secprio = maxprio;
proto.set(last);
maxprio = prio;
last.set(it);
}
else if(prio > secprio) {
secprio = prio;
proto.set(it);
}
}
return DBIDUtil.deref(prototypes.assignVar(proto, proto));
} | java | public DBID findPrototype(DBIDs members) {
// Find the last merge within the cluster.
// The object with maximum priority will merge outside of the cluster,
// So we need the second largest priority.
DBIDIter it = members.iter();
DBIDVar proto = DBIDUtil.newVar(it), last = DBIDUtil.newVar(it);
int maxprio = Integer.MIN_VALUE, secprio = Integer.MIN_VALUE;
for(; it.valid(); it.advance()) {
int prio = mergeOrder.intValue(it);
if(prio > maxprio) {
secprio = maxprio;
proto.set(last);
maxprio = prio;
last.set(it);
}
else if(prio > secprio) {
secprio = prio;
proto.set(it);
}
}
return DBIDUtil.deref(prototypes.assignVar(proto, proto));
} | [
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@param members Cluster members
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elki-project/elki | elki-index-various/src/main/java/de/lmu/ifi/dbs/elki/index/tree/metrical/covertree/SimplifiedCoverTree.java | SimplifiedCoverTree.bulkLoad | public void bulkLoad(DBIDs ids) {
if(ids.size() == 0) {
return;
}
assert (root == null) : "Tree already initialized.";
DBIDIter it = ids.iter();
DBID first = DBIDUtil.deref(it);
// Compute distances to all neighbors:
ModifiableDoubleDBIDList candidates = DBIDUtil.newDistanceDBIDList(ids.size() - 1);
for(it.advance(); it.valid(); it.advance()) {
candidates.add(distance(first, it), it);
}
root = bulkConstruct(first, Integer.MAX_VALUE, candidates);
} | java | public void bulkLoad(DBIDs ids) {
if(ids.size() == 0) {
return;
}
assert (root == null) : "Tree already initialized.";
DBIDIter it = ids.iter();
DBID first = DBIDUtil.deref(it);
// Compute distances to all neighbors:
ModifiableDoubleDBIDList candidates = DBIDUtil.newDistanceDBIDList(ids.size() - 1);
for(it.advance(); it.valid(); it.advance()) {
candidates.add(distance(first, it), it);
}
root = bulkConstruct(first, Integer.MAX_VALUE, candidates);
} | [
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] | b54673327e76198ecd4c8a2a901021f1a9174498 | https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-index-various/src/main/java/de/lmu/ifi/dbs/elki/index/tree/metrical/covertree/SimplifiedCoverTree.java#L179-L192 | train |
elki-project/elki | elki-index-various/src/main/java/de/lmu/ifi/dbs/elki/index/tree/metrical/covertree/SimplifiedCoverTree.java | SimplifiedCoverTree.checkCoverTree | private void checkCoverTree(Node cur, int[] counts, int depth) {
counts[0] += 1; // Node count
counts[1] += depth; // Sum of depth
counts[2] = depth > counts[2] ? depth : counts[2]; // Max depth
counts[3] += cur.singletons.size() - 1;
counts[4] += cur.singletons.size() - (cur.children == null ? 0 : 1);
if(cur.children != null) {
++depth;
for(Node chi : cur.children) {
checkCoverTree(chi, counts, depth);
}
assert (!cur.children.isEmpty()) : "Empty childs list.";
}
} | java | private void checkCoverTree(Node cur, int[] counts, int depth) {
counts[0] += 1; // Node count
counts[1] += depth; // Sum of depth
counts[2] = depth > counts[2] ? depth : counts[2]; // Max depth
counts[3] += cur.singletons.size() - 1;
counts[4] += cur.singletons.size() - (cur.children == null ? 0 : 1);
if(cur.children != null) {
++depth;
for(Node chi : cur.children) {
checkCoverTree(chi, counts, depth);
}
assert (!cur.children.isEmpty()) : "Empty childs list.";
}
} | [
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@param cur Current node
@param counts Counter set
@param depth Current depth | [
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"."
] | b54673327e76198ecd4c8a2a901021f1a9174498 | https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-index-various/src/main/java/de/lmu/ifi/dbs/elki/index/tree/metrical/covertree/SimplifiedCoverTree.java#L269-L282 | train |
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