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elki-project/elki | elki-core-api/src/main/java/de/lmu/ifi/dbs/elki/datasource/bundle/MultipleObjectsBundle.java | MultipleObjectsBundle.getRow | public Object[] getRow(int row) {
Object[] ret = new Object[columns.size()];
for(int c = 0; c < columns.size(); c++) {
ret[c] = data(row, c);
}
return ret;
} | java | public Object[] getRow(int row) {
Object[] ret = new Object[columns.size()];
for(int c = 0; c < columns.size(); c++) {
ret[c] = data(row, c);
}
return ret;
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elki-project/elki | elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/query/RStarTreeKNNQuery.java | RStarTreeKNNQuery.batchNN | protected void batchNN(AbstractRStarTreeNode<?, ?> node, Map<DBID, KNNHeap> knnLists) {
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final DBID q = ent.getKey();
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if(node.isLeaf()) {
for(int i = 0; i < node.getNumEntries(); i++) {
SpatialEntry p = node.getEntry(i);
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elki-project/elki | elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/query/RStarTreeKNNQuery.java | RStarTreeKNNQuery.getSortedEntries | protected List<DoubleDistanceEntry> getSortedEntries(AbstractRStarTreeNode<?, ?> node, DBIDs ids) {
List<DoubleDistanceEntry> result = new ArrayList<>();
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SpatialEntry entry = node.getEntry(i);
double minMinDist = Double.MAX_VALUE;
for(DBIDIter i... | java | protected List<DoubleDistanceEntry> getSortedEntries(AbstractRStarTreeNode<?, ?> node, DBIDs ids) {
List<DoubleDistanceEntry> result = new ArrayList<>();
for(int i = 0; i < node.getNumEntries(); i++) {
SpatialEntry entry = node.getEntry(i);
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/geometry/FilteredConvexHull2D.java | FilteredConvexHull2D.checkCandidateUpdate | private boolean checkCandidateUpdate(double[] point) {
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topy = bottomy = y;
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final double x = point[0], y = point[1];
if(points.isEmpty()) {
leftx = rightx = x;
topy = bottomy = y;
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/CLARA.java | CLARA.randomSample | static DBIDs randomSample(DBIDs ids, int samplesize, Random rnd, DBIDs previous) {
if(previous == null) {
return DBIDUtil.randomSample(ids, samplesize, rnd);
}
ModifiableDBIDs sample = DBIDUtil.newHashSet(samplesize);
sample.addDBIDs(previous);
sample.addDBIDs(DBIDUtil.randomSample(ids, sample... | java | static DBIDs randomSample(DBIDs ids, int samplesize, Random rnd, DBIDs previous) {
if(previous == null) {
return DBIDUtil.randomSample(ids, samplesize, rnd);
}
ModifiableDBIDs sample = DBIDUtil.newHashSet(samplesize);
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elki-project/elki | elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/configurator/FileParameterConfigurator.java | FileParameterConfigurator.actionPerformed | @Override
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// Use a new JFileChooser. Inconsistent behaviour otherwise!
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fc.setSelectedFile(param.getValue());
}
if(e.getSource() == button) {
int returnVal = fc... | java | @Override
public void actionPerformed(ActionEvent e) {
// Use a new JFileChooser. Inconsistent behaviour otherwise!
final JFileChooser fc = new JFileChooser(new File("."));
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/batikutil/CloneInlineImages.java | CloneInlineImages.inlineThumbnail | protected Node inlineThumbnail(Document doc, ParsedURL urldata, Node eold) {
RenderableImage img = ThumbnailRegistryEntry.handleURL(urldata);
if(img == null) {
LoggingUtil.warning("Image not found in registry: " + urldata.toString());
return null;
}
ByteArrayOutputStream os = new ByteArrayOu... | java | protected Node inlineThumbnail(Document doc, ParsedURL urldata, Node eold) {
RenderableImage img = ThumbnailRegistryEntry.handleURL(urldata);
if(img == null) {
LoggingUtil.warning("Image not found in registry: " + urldata.toString());
return null;
}
ByteArrayOutputStream os = new ByteArrayOu... | [
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elki-project/elki | elki-precomputed/src/main/java/de/lmu/ifi/dbs/elki/application/cache/PrecomputeDistancesAsciiApplication.java | PrecomputeDistancesAsciiApplication.openStream | private static PrintStream openStream(File out) throws IOException {
OutputStream os = new FileOutputStream(out);
os = out.getName().endsWith(GZIP_POSTFIX) ? new GZIPOutputStream(os) : os;
return new PrintStream(os);
} | java | private static PrintStream openStream(File out) throws IOException {
OutputStream os = new FileOutputStream(out);
os = out.getName().endsWith(GZIP_POSTFIX) ? new GZIPOutputStream(os) : os;
return new PrintStream(os);
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elki-project/elki | elki-core-data/src/main/java/de/lmu/ifi/dbs/elki/data/SparseShortVector.java | SparseShortVector.setDimensionality | @Override
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public void setDimensionality(int dimensionality) throws IllegalArgumentException {
final int maxdim = getMaxDim();
if(maxdim > dimensionality) {
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elki-project/elki | elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/AbstractRStarTree.java | AbstractRStarTree.findPathToObject | protected IndexTreePath<E> findPathToObject(IndexTreePath<E> subtree, SpatialComparable mbr, DBIDRef id) {
N node = getNode(subtree.getEntry());
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for(int i = 0; i < node.getNumEntries(); i++) {
if(DBIDUtil.equal(((LeafEntry) node.getEntry(i)).getDBID(), id)) {
return n... | java | protected IndexTreePath<E> findPathToObject(IndexTreePath<E> subtree, SpatialComparable mbr, DBIDRef id) {
N node = getNode(subtree.getEntry());
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for(int i = 0; i < node.getNumEntries(); i++) {
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elki-project/elki | elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/AbstractRStarTree.java | AbstractRStarTree.deletePath | protected void deletePath(IndexTreePath<E> deletionPath) {
N leaf = getNode(deletionPath.getParentPath().getEntry());
int index = deletionPath.getIndex();
// delete o
E entry = leaf.getEntry(index);
leaf.deleteEntry(index);
writeNode(leaf);
// condense the tree
Stack<N> stack = new Sta... | java | protected void deletePath(IndexTreePath<E> deletionPath) {
N leaf = getNode(deletionPath.getParentPath().getEntry());
int index = deletionPath.getIndex();
// delete o
E entry = leaf.getEntry(index);
leaf.deleteEntry(index);
writeNode(leaf);
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elki-project/elki | elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/AbstractRStarTree.java | AbstractRStarTree.createBulkLeafNodes | protected List<E> createBulkLeafNodes(List<E> objects) {
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int minEntries = leafMinimum;
int maxEntries = leafCapacity;
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List<List<E>> partitions = settings.bulkSplitter.partition(objects, minEntries, maxEntries);
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elki-project/elki | elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/AbstractRStarTree.java | AbstractRStarTree.choosePath | protected IndexTreePath<E> choosePath(IndexTreePath<E> subtree, SpatialComparable mbr, int depth, int cur) {
if(getLogger().isDebuggingFiner()) {
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if(getLogger().isDebuggingFiner()) {
getLogger().debugFiner("node " + subtree + ", depth " + depth);
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elki-project/elki | elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/AbstractRStarTree.java | AbstractRStarTree.split | private N split(N node) {
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// choose the split dimension and the split point
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elki-project/elki | elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/AbstractRStarTree.java | AbstractRStarTree.reInsert | public void reInsert(N node, IndexTreePath<E> path, int[] offs) {
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elki-project/elki | elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/AbstractRStarTree.java | AbstractRStarTree.condenseTree | private void condenseTree(IndexTreePath<E> subtree, Stack<N> stack) {
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elki-project/elki | elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/AbstractRStarTree.java | AbstractRStarTree.getLeafNodes | private void getLeafNodes(N node, List<E> result, int currentLevel) {
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// Level 1 are the leaf nodes, Level 2 is the one atop!
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elki-project/elki | elki-core-api/src/main/java/de/lmu/ifi/dbs/elki/data/VectorUtil.java | VectorUtil.angleDense | public static double angleDense(NumberVector v1, NumberVector v2) {
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final int mindim = (dim1 <= dim2) ? dim1 : dim2;
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final int dim1 = v1.getDimensionality(), dim2 = v2.getDimensionality();
final int mindim = (dim1 <= dim2) ? dim1 : dim2;
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elki-project/elki | elki-core-api/src/main/java/de/lmu/ifi/dbs/elki/data/VectorUtil.java | VectorUtil.angleSparse | public static double angleSparse(SparseNumberVector v1, SparseNumberVector v2) {
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double l1 = 0., l2 = 0., cross = 0.;
int i1 = v1.iter(), i2 = v2.iter();
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// TODO: exploit precomputed length, when available?
double l1 = 0., l2 = 0., cross = 0.;
int i1 = v1.iter(), i2 = v2.iter();
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elki-project/elki | elki-core-api/src/main/java/de/lmu/ifi/dbs/elki/data/VectorUtil.java | VectorUtil.angleSparseDense | public static double angleSparseDense(SparseNumberVector v1, NumberVector v2) {
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double l1 = 0., l2 = 0., cross = 0.;
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// TODO: exploit precomputed length, when available.
final int dim2 = v2.getDimensionality();
double l1 = 0., l2 = 0., cross = 0.;
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elki-project/elki | elki-core-api/src/main/java/de/lmu/ifi/dbs/elki/data/VectorUtil.java | VectorUtil.cosAngle | public static double cosAngle(NumberVector v1, NumberVector v2) {
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// Java Hotspot appears to optimize these better than if-then-else:
return v1 instanceof SparseNumberVector ? //
v2 instanceof SparseNumberVector ? //
angleSparse((SparseNumberVector) v1, (SparseNumberVector) v2) : //
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elki-project/elki | elki-core-api/src/main/java/de/lmu/ifi/dbs/elki/data/VectorUtil.java | VectorUtil.minCosAngle | public static double minCosAngle(SpatialComparable v1, SpatialComparable v2) {
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}
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final int mindim = (dim1 <=... | java | public static double minCosAngle(SpatialComparable v1, SpatialComparable v2) {
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}
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elki-project/elki | elki-core-api/src/main/java/de/lmu/ifi/dbs/elki/data/VectorUtil.java | VectorUtil.angle | public static double angle(NumberVector v1, NumberVector v2, NumberVector o) {
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final int mindim = (dim1 <= dim2) ? dim1 : dim2;
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elki-project/elki | elki-core-api/src/main/java/de/lmu/ifi/dbs/elki/data/VectorUtil.java | VectorUtil.dotDense | public static double dotDense(NumberVector v1, NumberVector v2) {
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double dot = 0;
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elki-project/elki | elki-core-api/src/main/java/de/lmu/ifi/dbs/elki/data/VectorUtil.java | VectorUtil.dotSparse | public static double dotSparse(SparseNumberVector v1, SparseNumberVector v2) {
double dot = 0.;
int i1 = v1.iter(), i2 = v2.iter();
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if(d1 < d2) {
i1 = v1.iterAdvance(i1);
}
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double dot = 0.;
int i1 = v1.iter(), i2 = v2.iter();
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elki-project/elki | elki-core-api/src/main/java/de/lmu/ifi/dbs/elki/data/VectorUtil.java | VectorUtil.dotSparseDense | public static double dotSparseDense(SparseNumberVector v1, NumberVector v2) {
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final int dim2 = v2.getDimensionality();
double dot = 0.;
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elki-project/elki | elki-core-api/src/main/java/de/lmu/ifi/dbs/elki/data/VectorUtil.java | VectorUtil.dot | public static double dot(NumberVector v1, NumberVector v2) {
// Java Hotspot appears to optimize these better than if-then-else:
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dot... | java | public static double dot(NumberVector v1, NumberVector v2) {
// Java Hotspot appears to optimize these better than if-then-else:
return v1 instanceof SparseNumberVector ? //
v2 instanceof SparseNumberVector ? //
dotSparse((SparseNumberVector) v1, (SparseNumberVector) v2) : //
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elki-project/elki | elki-core-api/src/main/java/de/lmu/ifi/dbs/elki/data/VectorUtil.java | VectorUtil.minDot | public static double minDot(SpatialComparable v1, SpatialComparable v2) {
if(v1 instanceof NumberVector && v2 instanceof NumberVector) {
return dot((NumberVector) v1, (NumberVector) v2);
}
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if(v1 instanceof NumberVector && v2 instanceof NumberVector) {
return dot((NumberVector) v1, (NumberVector) v2);
}
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elki-project/elki | elki-core-api/src/main/java/de/lmu/ifi/dbs/elki/data/VectorUtil.java | VectorUtil.project | public static <V extends NumberVector> V project(V v, long[] selectedAttributes, NumberVector.Factory<V> factory) {
int card = BitsUtil.cardinality(selectedAttributes);
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final SparseNumberVector.Factory<?> sfactory = (SparseNumberVector.Factory<?>) factor... | java | public static <V extends NumberVector> V project(V v, long[] selectedAttributes, NumberVector.Factory<V> factory) {
int card = BitsUtil.cardinality(selectedAttributes);
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/gdbscan/util/Core.java | Core.mergeWith | public void mergeWith(Core o) {
o.num = this.num = (num < o.num ? num : o.num);
} | java | public void mergeWith(Core o) {
o.num = this.num = (num < o.num ? num : o.num);
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/trivial/ByLabelClustering.java | ByLabelClustering.run | public Clustering<Model> run(Relation<?> relation) {
HashMap<String, DBIDs> labelMap = multiple ? multipleAssignment(relation) : singleAssignment(relation);
ModifiableDBIDs noiseids = DBIDUtil.newArray();
Clustering<Model> result = new Clustering<>("By Label Clustering", "bylabel-clustering");
for(Entr... | java | public Clustering<Model> run(Relation<?> relation) {
HashMap<String, DBIDs> labelMap = multiple ? multipleAssignment(relation) : singleAssignment(relation);
ModifiableDBIDs noiseids = DBIDUtil.newArray();
Clustering<Model> result = new Clustering<>("By Label Clustering", "bylabel-clustering");
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/trivial/ByLabelClustering.java | ByLabelClustering.singleAssignment | private HashMap<String, DBIDs> singleAssignment(Relation<?> data) {
HashMap<String, DBIDs> labelMap = new HashMap<>();
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assign(... | java | private HashMap<String, DBIDs> singleAssignment(Relation<?> data) {
HashMap<String, DBIDs> labelMap = new HashMap<>();
for(DBIDIter iditer = data.iterDBIDs(); iditer.valid(); iditer.advance()) {
final Object val = data.get(iditer);
String label = (val != null) ? val.toString() : null;
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/trivial/ByLabelClustering.java | ByLabelClustering.multipleAssignment | private HashMap<String, DBIDs> multipleAssignment(Relation<?> data) {
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assign(... | java | private HashMap<String, DBIDs> multipleAssignment(Relation<?> data) {
HashMap<String, DBIDs> labelMap = new HashMap<>();
for(DBIDIter iditer = data.iterDBIDs(); iditer.valid(); iditer.advance()) {
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/trivial/ByLabelClustering.java | ByLabelClustering.assign | private void assign(HashMap<String, DBIDs> labelMap, String label, DBIDRef id) {
if(labelMap.containsKey(label)) {
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if(exist instanceof DBID) {
ModifiableDBIDs n = DBIDUtil.newHashSet();
n.add((DBID) exist);
n.add(id);
labelMap.put(label,... | java | private void assign(HashMap<String, DBIDs> labelMap, String label, DBIDRef id) {
if(labelMap.containsKey(label)) {
DBIDs exist = labelMap.get(label);
if(exist instanceof DBID) {
ModifiableDBIDs n = DBIDUtil.newHashSet();
n.add((DBID) exist);
n.add(id);
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/DoubleMinMax.java | DoubleMinMax.put | public void put(double val) {
min = val < min ? val : min;
max = val > max ? val : max;
} | java | public void put(double val) {
min = val < min ? val : min;
max = val > max ? val : max;
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGEffects.java | SVGEffects.addShadowFilter | public static void addShadowFilter(SVGPlot svgp) {
Element shadow = svgp.getIdElement(SHADOW_ID);
if(shadow == null) {
shadow = svgp.svgElement(SVGConstants.SVG_FILTER_TAG);
shadow.setAttribute(SVGConstants.SVG_ID_ATTRIBUTE, SHADOW_ID);
shadow.setAttribute(SVGConstants.SVG_WIDTH_ATTRIBUTE, "14... | java | public static void addShadowFilter(SVGPlot svgp) {
Element shadow = svgp.getIdElement(SHADOW_ID);
if(shadow == null) {
shadow = svgp.svgElement(SVGConstants.SVG_FILTER_TAG);
shadow.setAttribute(SVGConstants.SVG_ID_ATTRIBUTE, SHADOW_ID);
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGEffects.java | SVGEffects.addLightGradient | public static void addLightGradient(SVGPlot svgp) {
Element gradient = svgp.getIdElement(LIGHT_GRADIENT_ID);
if(gradient == null) {
gradient = svgp.svgElement(SVGConstants.SVG_LINEAR_GRADIENT_TAG);
gradient.setAttribute(SVGConstants.SVG_ID_ATTRIBUTE, LIGHT_GRADIENT_ID);
gradient.setAttribute(S... | java | public static void addLightGradient(SVGPlot svgp) {
Element gradient = svgp.getIdElement(LIGHT_GRADIENT_ID);
if(gradient == null) {
gradient = svgp.svgElement(SVGConstants.SVG_LINEAR_GRADIENT_TAG);
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGEffects.java | SVGEffects.makeCheckmark | public static Element makeCheckmark(SVGPlot svgp) {
Element checkmark = svgp.svgElement(SVGConstants.SVG_PATH_TAG);
checkmark.setAttribute(SVGConstants.SVG_D_ATTRIBUTE, SVG_CHECKMARK_PATH);
checkmark.setAttribute(SVGConstants.SVG_FILL_ATTRIBUTE, SVGConstants.CSS_BLACK_VALUE);
checkmark.setAttribute(SVGC... | java | public static Element makeCheckmark(SVGPlot svgp) {
Element checkmark = svgp.svgElement(SVGConstants.SVG_PATH_TAG);
checkmark.setAttribute(SVGConstants.SVG_D_ATTRIBUTE, SVG_CHECKMARK_PATH);
checkmark.setAttribute(SVGConstants.SVG_FILL_ATTRIBUTE, SVGConstants.CSS_BLACK_VALUE);
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/projections/CanvasSize.java | CanvasSize.continueToMargin | public double continueToMargin(double[] origin, double[] delta) {
assert (delta.length == 2 && origin.length == 2);
double factor = Double.POSITIVE_INFINITY;
if(delta[0] > 0) {
factor = Math.min(factor, (maxx - origin[0]) / delta[0]);
}
else if(delta[0] < 0) {
factor = Math.min(factor, (... | java | public double continueToMargin(double[] origin, double[] delta) {
assert (delta.length == 2 && origin.length == 2);
double factor = Double.POSITIVE_INFINITY;
if(delta[0] > 0) {
factor = Math.min(factor, (maxx - origin[0]) / delta[0]);
}
else if(delta[0] < 0) {
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elki-project/elki | elki/src/main/java/de/lmu/ifi/dbs/elki/persistent/PersistentPageFile.java | PersistentPageFile.clear | @Override
public void clear() {
try {
file.setLength(header.size());
}
catch(IOException e) {
throw new RuntimeException(e);
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try {
file.setLength(header.size());
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throw new RuntimeException(e);
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/LMCLUS.java | LMCLUS.deviation | private double deviation(double[] delta, double[][] beta) {
final double a = squareSum(delta);
final double b = squareSum(transposeTimes(beta, delta));
return (a > b) ? FastMath.sqrt(a - b) : 0.;
} | java | private double deviation(double[] delta, double[][] beta) {
final double a = squareSum(delta);
final double b = squareSum(transposeTimes(beta, delta));
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/LMCLUS.java | LMCLUS.findSeparation | private Separation findSeparation(Relation<NumberVector> relation, DBIDs currentids, int dimension, Random r) {
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elki-project/elki | elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/similarityfunction/kernel/KernelMatrix.java | KernelMatrix.getDistance | public double getDistance(final DBIDRef o1, final DBIDRef o2) {
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elki-project/elki | elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/similarityfunction/kernel/KernelMatrix.java | KernelMatrix.getSquaredDistance | public double getSquaredDistance(final DBIDRef id1, final DBIDRef id2) {
final int o1 = idmap.getOffset(id1), o2 = idmap.getOffset(id2);
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final int o1 = idmap.getOffset(id1), o2 = idmap.getOffset(id2);
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elki-project/elki | elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/similarityfunction/kernel/KernelMatrix.java | KernelMatrix.getSimilarity | public double getSimilarity(DBIDRef id1, DBIDRef id2) {
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/AbstractKMeans.java | AbstractKMeans.initialMeans | protected double[][] initialMeans(Database database, Relation<V> relation) {
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double[][] means = initializer.chooseInitialMeans(database, relation, k, getDistanceFunction());
getLogger().statistics(inittime.end());
ret... | java | protected double[][] initialMeans(Database database, Relation<V> relation) {
Duration inittime = getLogger().newDuration(initializer.getClass() + ".time").begin();
double[][] means = initializer.chooseInitialMeans(database, relation, k, getDistanceFunction());
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/AbstractKMeans.java | AbstractKMeans.plusEquals | public static void plusEquals(double[] sum, NumberVector vec) {
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}
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/AbstractKMeans.java | AbstractKMeans.minusEquals | public static void minusEquals(double[] sum, NumberVector vec) {
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/AbstractKMeans.java | AbstractKMeans.plusMinusEquals | public static void plusMinusEquals(double[] add, double[] sub, NumberVector vec) {
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/AbstractKMeans.java | AbstractKMeans.incrementalUpdateMean | protected static void incrementalUpdateMean(double[] mean, NumberVector vec, int newsize, double op) {
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}
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} | java | protected static void incrementalUpdateMean(double[] mean, NumberVector vec, int newsize, double op) {
if(newsize == 0) {
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}
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elki-project/elki | elki-index-lsh/src/main/java/de/lmu/ifi/dbs/elki/index/lsh/hashfunctions/MultipleProjectionsLocalitySensitiveHashFunction.java | MultipleProjectionsLocalitySensitiveHashFunction.fastModPrime | public static int fastModPrime(long data) {
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... | java | public static int fastModPrime(long data) {
// Mix high and low 32 bit:
int high = (int) (data >>> 32);
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int alpha = ((int) data) + (high << 2 + high);
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elki-project/elki | elki-index-mtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/metrical/mtreevariants/query/MTreeRangeQuery.java | MTreeRangeQuery.doRangeQuery | private void doRangeQuery(DBID o_p, AbstractMTreeNode<O, ?, ?> node, O q, double r_q, ModifiableDoubleDBIDList result) {
double d1 = 0.;
if(o_p != null) {
d1 = distanceQuery.distance(o_p, q);
index.statistics.countDistanceCalculation();
}
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double d1 = 0.;
if(o_p != null) {
d1 = distanceQuery.distance(o_p, q);
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/GumbelDistribution.java | GumbelDistribution.pdf | public static double pdf(double x, double mu, double beta) {
final double z = (x - mu) / beta;
if(x == Double.NEGATIVE_INFINITY) {
return 0.;
}
return FastMath.exp(-z - FastMath.exp(-z)) / beta;
} | java | public static double pdf(double x, double mu, double beta) {
final double z = (x - mu) / beta;
if(x == Double.NEGATIVE_INFINITY) {
return 0.;
}
return FastMath.exp(-z - FastMath.exp(-z)) / beta;
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@param mu Mode
@param beta Shape
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/GumbelDistribution.java | GumbelDistribution.logpdf | public static double logpdf(double x, double mu, double beta) {
if(x == Double.NEGATIVE_INFINITY) {
return Double.NEGATIVE_INFINITY;
}
final double z = (x - mu) / beta;
return -z - FastMath.exp(-z) - FastMath.log(beta);
} | java | public static double logpdf(double x, double mu, double beta) {
if(x == Double.NEGATIVE_INFINITY) {
return Double.NEGATIVE_INFINITY;
}
final double z = (x - mu) / beta;
return -z - FastMath.exp(-z) - FastMath.log(beta);
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/GumbelDistribution.java | GumbelDistribution.cdf | public static double cdf(double val, double mu, double beta) {
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/GumbelDistribution.java | GumbelDistribution.quantile | public static double quantile(double val, double mu, double beta) {
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elki-project/elki | elki-index-various/src/main/java/de/lmu/ifi/dbs/elki/index/vafile/VAFile.java | VAFile.setPartitions | public void setPartitions(Relation<V> relation) throws IllegalArgumentException {
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throw new IllegalArgumentException("Number of partitions must be a power of 2!");
}
final int dimensions = Relatio... | java | public void setPartitions(Relation<V> relation) throws IllegalArgumentException {
if((FastMath.log(partitions) / FastMath.log(2)) != (int) (FastMath.log(partitions) / FastMath.log(2))) {
throw new IllegalArgumentException("Number of partitions must be a power of 2!");
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elki-project/elki | elki-index-various/src/main/java/de/lmu/ifi/dbs/elki/index/vafile/VAFile.java | VAFile.getScannedPages | public long getScannedPages() {
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long vasize = (long) Math.ceil((vectorApprox.size()) / (1.0 * vacapacity));
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int vacapacity = pageSize / VectorApproximation.byteOnDisk(splitPositions.length, partitions);
long vasize = (long) Math.ceil((vectorApprox.size()) / (1.0 * vacapacity));
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/EigenvalueDecomposition.java | EigenvalueDecomposition.hqr2BackTransformation | private void hqr2BackTransformation(int nn, int low, int high) {
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for(int j = nn - 1; j >= low; j--) {
final int last = j < high ? j : high;
for(int i = low; i <= high; i++) {
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double sum = 0.;
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/GammaDistribution.java | GammaDistribution.gammaQuantileNewtonRefinement | protected static double gammaQuantileNewtonRefinement(final double logpt, final double k, final double theta, final int maxit, double x) {
final double EPS_N = 1e-15; // Precision threshold
// 0 is not possible, try MIN_NORMAL instead
if(x <= 0) {
x = Double.MIN_NORMAL;
}
// Current estimation... | java | protected static double gammaQuantileNewtonRefinement(final double logpt, final double k, final double theta, final int maxit, double x) {
final double EPS_N = 1e-15; // Precision threshold
// 0 is not possible, try MIN_NORMAL instead
if(x <= 0) {
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/style/marker/CircleMarkers.java | CircleMarkers.useMarker | @Override
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/hierarchical/extraction/HDBSCANHierarchyExtraction.java | HDBSCANHierarchyExtraction.run | public Clustering<DendrogramModel> run(PointerHierarchyRepresentationResult pointerresult) {
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result.addChildResult(pointerresult);
return result;
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/NormalDistribution.java | NormalDistribution.erf | public static double erf(double x) {
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double y;
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double t = w * w;
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t -= k;
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final double w = x < 0 ? -x : x;
double y;
if(w < 2.2) {
double t = w * w;
int k = (int) t;
t -= k;
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/NormalDistribution.java | NormalDistribution.standardNormalQuantile | public static double standardNormalQuantile(double d) {
return (d == 0) ? Double.NEGATIVE_INFINITY : //
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(Double.isNaN(d) || d < 0 || d > 1) ? Double.NaN //
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} | java | public static double standardNormalQuantile(double d) {
return (d == 0) ? Double.NEGATIVE_INFINITY : //
(d == 1) ? Double.POSITIVE_INFINITY : //
(Double.isNaN(d) || d < 0 || d > 1) ? Double.NaN //
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elki-project/elki | elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/strategies/bulk/MaxExtensionBulkSplit.java | MaxExtensionBulkSplit.partition | @Override
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... | java | @Override
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List<N> objects = new ArrayList<>(spatialObjects);
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elki-project/elki | elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/strategies/bulk/MaxExtensionBulkSplit.java | MaxExtensionBulkSplit.chooseMaximalExtendedSplitAxis | private int chooseMaximalExtendedSplitAxis(List<? extends SpatialComparable> objects) {
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int dimension = objects.get(0).getDimensionality();
double[] maxExtension = new double[dimension];
double[] minExtension = new double[dimension];
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// maximum and minimum value for the extension
int dimension = objects.get(0).getDimensionality();
double[] maxExtension = new double[dimension];
double[] minExtension = new double[dimension];
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elki-project/elki | elki-logging/src/main/java/de/lmu/ifi/dbs/elki/logging/progress/MutableProgress.java | MutableProgress.setTotal | public void setTotal(int total) throws IllegalArgumentException {
if(getProcessed() > total) {
throw new IllegalArgumentException(getProcessed() + " exceeds total: " + total);
}
this.total = total;
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elki-project/elki | elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/datastore/memory/MapRecordStore.java | MapRecordStore.get | @SuppressWarnings("unchecked")
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elki-project/elki | elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/datastore/memory/MapRecordStore.java | MapRecordStore.set | @SuppressWarnings("unchecked")
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/estimator/UniformMinMaxEstimator.java | UniformMinMaxEstimator.estimate | public UniformDistribution estimate(DoubleMinMax mm) {
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elki-project/elki | addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/visualizers/scatterplot/index/TreeSphereVisualization.java | TreeSphereVisualization.canVisualize | public static boolean canVisualize(Relation<?> rel, AbstractMTree<?, ?, ?, ?> tree) {
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if(!TypeUtil.NUMBER_VECTOR_FIELD.isAssignableFromType(rel.getDataTypeInformation())) {
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elki-project/elki | elki-input/src/main/java/de/lmu/ifi/dbs/elki/datasource/filter/transform/NumberVectorRandomFeatureSelectionFilter.java | NumberVectorRandomFeatureSelectionFilter.initializeRandomAttributes | void initializeRandomAttributes(SimpleTypeInformation<V> in) {
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int d = ((VectorFieldTypeInformation<V>) in).getDimensionality();
selectedAttributes = BitsUtil.random(k, d, rnd.getSingleThreadedRandom());
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elki-project/elki | elki/src/main/java/de/lmu/ifi/dbs/elki/application/greedyensemble/GreedyEnsembleExperiment.java | GreedyEnsembleExperiment.singleEnsemble | protected void singleEnsemble(final double[] ensemble, final NumberVector vec) {
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double[] buf = new double[1];
for(int i = 0; i < ensemble.length; i++) {
buf[0] = vec.doubleValue(i);
ensemble[i] = voting.combine(buf, 1);
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elki-project/elki | elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/optionhandling/OptionUtil.java | OptionUtil.getFullDescription | public static String getFullDescription(Parameter<?> param) {
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elki-project/elki | elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/optionhandling/OptionUtil.java | OptionUtil.println | private static void println(StringBuilder buf, int width, String data) {
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}
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if(!line.endsWith(FormatUtil.NEWLINE)) {
buf.append(FormatUtil.NEWLINE);
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elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/evaluation/clustering/internal/EvaluateSimplifiedSilhouette.java | EvaluateSimplifiedSilhouette.centroids | public static int centroids(Relation<? extends NumberVector> rel, List<? extends Cluster<?>> clusters, NumberVector[] centroids, NoiseHandling noiseOption) {
assert (centroids.length == clusters.size());
int ignorednoise = 0;
Iterator<? extends Cluster<?>> ci = clusters.iterator();
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assert (centroids.length == clusters.size());
int ignorednoise = 0;
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/LaplaceDistribution.java | LaplaceDistribution.cdf | public static double cdf(double val, double rate) {
final double v = .5 * FastMath.exp(-rate * Math.abs(val));
return (v == Double.POSITIVE_INFINITY) ? ((val <= 0) ? 0 : 1) : //
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} | java | public static double cdf(double val, double rate) {
final double v = .5 * FastMath.exp(-rate * Math.abs(val));
return (v == Double.POSITIVE_INFINITY) ? ((val <= 0) ? 0 : 1) : //
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elki-project/elki | elki-index-various/src/main/java/de/lmu/ifi/dbs/elki/index/tree/metrical/covertree/AbstractCoverTree.java | AbstractCoverTree.maxDistance | protected double maxDistance(DoubleDBIDList elems) {
double max = 0;
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final double v = it.doubleValue();
max = max > v ? max : v;
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return max;
} | java | protected double maxDistance(DoubleDBIDList elems) {
double max = 0;
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final double v = it.doubleValue();
max = max > v ? max : v;
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elki-project/elki | elki-index-various/src/main/java/de/lmu/ifi/dbs/elki/index/tree/metrical/covertree/AbstractCoverTree.java | AbstractCoverTree.excludeNotCovered | protected void excludeNotCovered(ModifiableDoubleDBIDList candidates, double fmax, ModifiableDoubleDBIDList collect) {
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}
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if(it.doubleValue() > fmax) {
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elki-project/elki | elki-index-various/src/main/java/de/lmu/ifi/dbs/elki/index/tree/metrical/covertree/AbstractCoverTree.java | AbstractCoverTree.collectByCover | protected void collectByCover(DBIDRef cur, ModifiableDoubleDBIDList candidates, double fmax, ModifiableDoubleDBIDList collect) {
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assert (collect.size() == 0) : "Not empty";
DoubleDBIDListIter it = candidates.iter().advance(); // Except first = cur!
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/KernelDensityEstimator.java | KernelDensityEstimator.process | private void process(double[] data, double min, double max, KernelDensityFunction kernel, int window, double epsilon) {
dens = new double[data.length];
var = new double[data.length];
// This is the desired bandwidth of the kernel.
double halfwidth = ((max - min) / window) * .5;
for (int current = ... | java | private void process(double[] data, double min, double max, KernelDensityFunction kernel, int window, double epsilon) {
dens = new double[data.length];
var = new double[data.length];
// This is the desired bandwidth of the kernel.
double halfwidth = ((max - min) / window) * .5;
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elki-project/elki | addons/3dpc/src/main/java/de/lmu/ifi/dbs/elki/visualization/parallel3d/layout/AbstractLayout3DPC.java | AbstractLayout3DPC.computeSimilarityMatrix | public static double[] computeSimilarityMatrix(DependenceMeasure sim, Relation<? extends NumberVector> rel) {
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elki-project/elki | addons/3dpc/src/main/java/de/lmu/ifi/dbs/elki/visualization/parallel3d/layout/AbstractLayout3DPC.java | AbstractLayout3DPC.buildSpanningTree | protected N buildSpanningTree(int dim, double[] mat, Layout layout) {
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elki-project/elki | addons/3dpc/src/main/java/de/lmu/ifi/dbs/elki/visualization/parallel3d/layout/AbstractLayout3DPC.java | AbstractLayout3DPC.buildTree | protected N buildTree(int[] msg, int cur, int parent, ArrayList<N> nodes) {
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elki-project/elki | addons/3dpc/src/main/java/de/lmu/ifi/dbs/elki/visualization/parallel3d/layout/AbstractLayout3DPC.java | AbstractLayout3DPC.maxDepth | protected int maxDepth(Layout.Node node) {
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elki-project/elki | elki-index/src/main/java/de/lmu/ifi/dbs/elki/index/tree/IndexTree.java | IndexTree.initialize | @Override
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elki-project/elki | elki-index/src/main/java/de/lmu/ifi/dbs/elki/index/tree/IndexTree.java | IndexTree.getNode | public N getNode(int nodeID) {
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elki-project/elki | elki-index/src/main/java/de/lmu/ifi/dbs/elki/index/tree/IndexTree.java | IndexTree.initializeFromFile | public void initializeFromFile(TreeIndexHeader header, PageFile<N> file) {
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elki-project/elki | elki-index/src/main/java/de/lmu/ifi/dbs/elki/index/tree/IndexTree.java | IndexTree.initialize | protected final void initialize(E exampleLeaf) {
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/MeanVarianceMinMax.java | MeanVarianceMinMax.newArray | public static MeanVarianceMinMax[] newArray(int dimensionality) {
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/pca/weightfunctions/ExponentialStddevWeight.java | ExponentialStddevWeight.getWeight | @Override
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/dependence/AbstractDependenceMeasure.java | AbstractDependenceMeasure.sortedIndex | protected static <A> int[] sortedIndex(final NumberArrayAdapter<?, A> adapter, final A data, int len) {
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elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/dependence/AbstractDependenceMeasure.java | AbstractDependenceMeasure.discretize | protected static <A> int[] discretize(NumberArrayAdapter<?, A> adapter, A data, final int len, final int bins) {
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elki-project/elki | elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/configurator/AbstractParameterConfigurator.java | AbstractParameterConfigurator.finishGridRow | protected void finishGridRow() {
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elki-project/elki | elki-input/src/main/java/de/lmu/ifi/dbs/elki/datasource/filter/normalization/columnwise/AttributeWiseVarianceNormalization.java | AttributeWiseVarianceNormalization.normalize | private double normalize(int d, double val) {
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... | Normalize a single dimension.
@param d Dimension
@param val Value
@return Normalized value | [
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] | b54673327e76198ecd4c8a2a901021f1a9174498 | https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-input/src/main/java/de/lmu/ifi/dbs/elki/datasource/filter/normalization/columnwise/AttributeWiseVarianceNormalization.java#L170-L173 | train |
elki-project/elki | elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/pca/PCAResult.java | PCAResult.processDecomposition | private static EigenPair[] processDecomposition(EigenvalueDecomposition evd) {
double[] eigenvalues = evd.getRealEigenvalues();
double[][] eigenvectors = evd.getV();
EigenPair[] eigenPairs = new EigenPair[eigenvalues.length];
for(int i = 0; i < eigenvalues.length; i++) {
double e = Math.abs(eigen... | java | private static EigenPair[] processDecomposition(EigenvalueDecomposition evd) {
double[] eigenvalues = evd.getRealEigenvalues();
double[][] eigenvectors = evd.getV();
EigenPair[] eigenPairs = new EigenPair[eigenvalues.length];
for(int i = 0; i < eigenvalues.length; i++) {
double e = Math.abs(eigen... | [
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@param evd Eigenvalue decomposition
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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/linearalgebra/pca/PCAResult.java#L85-L97 | train |
elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/parallel/KMeansProcessor.java | KMeansProcessor.nextIteration | public void nextIteration(double[][] means) {
this.means = means;
changed = false;
final int k = means.length;
final int dim = means[0].length;
centroids = new double[k][dim];
sizes = new int[k];
Arrays.fill(varsum, 0.);
} | java | public void nextIteration(double[][] means) {
this.means = means;
changed = false;
final int k = means.length;
final int dim = means[0].length;
centroids = new double[k][dim];
sizes = new int[k];
Arrays.fill(varsum, 0.);
} | [
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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/kmeans/parallel/KMeansProcessor.java#L118-L126 | train |
elki-project/elki | elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/parallel/KMeansProcessor.java | KMeansProcessor.getMeans | public double[][] getMeans() {
double[][] newmeans = new double[centroids.length][];
for(int i = 0; i < centroids.length; i++) {
if(sizes[i] == 0) {
newmeans[i] = means[i]; // Keep old mean.
continue;
}
newmeans[i] = centroids[i];
}
return newmeans;
} | java | public double[][] getMeans() {
double[][] newmeans = new double[centroids.length][];
for(int i = 0; i < centroids.length; i++) {
if(sizes[i] == 0) {
newmeans[i] = means[i]; // Keep old mean.
continue;
}
newmeans[i] = centroids[i];
}
return newmeans;
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elki-project/elki | elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/io/FormatUtil.java | FormatUtil.format | public static String format(double[] v, int w, int d) {
DecimalFormat format = new DecimalFormat();
format.setDecimalFormatSymbols(new DecimalFormatSymbols(Locale.US));
format.setMinimumIntegerDigits(1);
format.setMaximumFractionDigits(d);
format.setMinimumFractionDigits(d);
format.setGroupingUs... | java | public static String format(double[] v, int w, int d) {
DecimalFormat format = new DecimalFormat();
format.setDecimalFormatSymbols(new DecimalFormatSymbols(Locale.US));
format.setMinimumIntegerDigits(1);
format.setMaximumFractionDigits(d);
format.setMinimumFractionDigits(d);
format.setGroupingUs... | [
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@param w column width
@param d number of digits after the decimal
@return a string representation of this matrix | [
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] | b54673327e76198ecd4c8a2a901021f1a9174498 | https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/io/FormatUtil.java#L240-L257 | train |
elki-project/elki | elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/io/FormatUtil.java | FormatUtil.formatTo | public static StringBuilder formatTo(StringBuilder buf, double[] d, String sep) {
if(d == null) {
return buf.append("null");
}
if(d.length == 0) {
return buf;
}
buf.append(d[0]);
for(int i = 1; i < d.length; i++) {
buf.append(sep).append(d[i]);
}
return buf;
} | java | public static StringBuilder formatTo(StringBuilder buf, double[] d, String sep) {
if(d == null) {
return buf.append("null");
}
if(d.length == 0) {
return buf;
}
buf.append(d[0]);
for(int i = 1; i < d.length; i++) {
buf.append(sep).append(d[i]);
}
return buf;
} | [
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@param buf String builder to append to
@param d the double array to be formatted
@param sep separator between the single values of the array, e.g. ','
@return Output buffer buf | [
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] | b54673327e76198ecd4c8a2a901021f1a9174498 | https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/io/FormatUtil.java#L267-L279 | train |
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