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elki-project/elki
elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/ELKIServiceScanner.java
ELKIServiceScanner.load
public static void load(Class<?> restrictionClass) { if(MASTER_CACHE == null) { initialize(); } if(MASTER_CACHE.isEmpty()) { return; } Iterator<Class<?>> iter = MASTER_CACHE.iterator(); while(iter.hasNext()) { Class<?> clazz = iter.next(); // Skip other classes. if(!restrictionClass.isAssignableFrom(clazz)) { continue; } // skip abstract / private classes. if(Modifier.isInterface(clazz.getModifiers()) || Modifier.isAbstract(clazz.getModifiers()) || Modifier.isPrivate(clazz.getModifiers())) { continue; } boolean instantiable = false; try { instantiable = clazz.getConstructor() != null; } catch(Exception | Error e) { // ignore } try { instantiable = instantiable || ClassGenericsUtil.getParameterizer(clazz) != null; } catch(Exception | Error e) { // ignore } if(!instantiable) { continue; } ELKIServiceRegistry.register(restrictionClass, clazz); } }
java
public static void load(Class<?> restrictionClass) { if(MASTER_CACHE == null) { initialize(); } if(MASTER_CACHE.isEmpty()) { return; } Iterator<Class<?>> iter = MASTER_CACHE.iterator(); while(iter.hasNext()) { Class<?> clazz = iter.next(); // Skip other classes. if(!restrictionClass.isAssignableFrom(clazz)) { continue; } // skip abstract / private classes. if(Modifier.isInterface(clazz.getModifiers()) || Modifier.isAbstract(clazz.getModifiers()) || Modifier.isPrivate(clazz.getModifiers())) { continue; } boolean instantiable = false; try { instantiable = clazz.getConstructor() != null; } catch(Exception | Error e) { // ignore } try { instantiable = instantiable || ClassGenericsUtil.getParameterizer(clazz) != null; } catch(Exception | Error e) { // ignore } if(!instantiable) { continue; } ELKIServiceRegistry.register(restrictionClass, clazz); } }
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Load classes via linear scanning. @param restrictionClass Class to find subclasses for.
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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/ELKIServiceScanner.java#L76-L112
train
elki-project/elki
elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/ELKIServiceScanner.java
ELKIServiceScanner.comparePackageClass
private static int comparePackageClass(Class<?> o1, Class<?> o2) { return o1.getPackage() == o2.getPackage() ? // o1.getCanonicalName().compareTo(o2.getCanonicalName()) // : o1.getPackage() == null ? -1 : o2.getPackage() == null ? +1 // : o1.getPackage().getName().compareTo(o2.getPackage().getName()); }
java
private static int comparePackageClass(Class<?> o1, Class<?> o2) { return o1.getPackage() == o2.getPackage() ? // o1.getCanonicalName().compareTo(o2.getCanonicalName()) // : o1.getPackage() == null ? -1 : o2.getPackage() == null ? +1 // : o1.getPackage().getName().compareTo(o2.getPackage().getName()); }
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Compare two classes, by package name first. @param o1 First class @param o2 Second class @return Comparison result
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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/ELKIServiceScanner.java#L274-L279
train
elki-project/elki
elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/ELKIServiceScanner.java
ELKIServiceScanner.classPriority
private static int classPriority(Class<?> o1) { Priority p = o1.getAnnotation(Priority.class); if(p == null) { Class<?> pa = o1.getDeclaringClass(); p = (pa != null) ? pa.getAnnotation(Priority.class) : null; } return p != null ? p.value() : Priority.DEFAULT; }
java
private static int classPriority(Class<?> o1) { Priority p = o1.getAnnotation(Priority.class); if(p == null) { Class<?> pa = o1.getDeclaringClass(); p = (pa != null) ? pa.getAnnotation(Priority.class) : null; } return p != null ? p.value() : Priority.DEFAULT; }
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Get the priority of a class, or its outer class. @param o1 Class @return Priority
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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/ELKIServiceScanner.java#L287-L294
train
elki-project/elki
elki-core/src/main/java/de/lmu/ifi/dbs/elki/utilities/datastructures/unionfind/WeightedQuickUnionInteger.java
WeightedQuickUnionInteger.nextIndex
public int nextIndex(int weight) { if(used == parent.length) { int nsize = used + (used >> 1); this.weight = Arrays.copyOf(this.weight, nsize); this.parent = Arrays.copyOf(this.parent, nsize); } this.weight[used] = weight; this.parent[used] = used; return used++; }
java
public int nextIndex(int weight) { if(used == parent.length) { int nsize = used + (used >> 1); this.weight = Arrays.copyOf(this.weight, nsize); this.parent = Arrays.copyOf(this.parent, nsize); } this.weight[used] = weight; this.parent[used] = used; return used++; }
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Occupy the next unused index. @param weight Initial weight. @return Next unused index.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core/src/main/java/de/lmu/ifi/dbs/elki/utilities/datastructures/unionfind/WeightedQuickUnionInteger.java#L84-L93
train
elki-project/elki
elki-core/src/main/java/de/lmu/ifi/dbs/elki/utilities/datastructures/unionfind/WeightedQuickUnionInteger.java
WeightedQuickUnionInteger.find
public int find(int cur) { assert (cur >= 0 && cur < parent.length); int p = parent[cur], tmp; while(cur != p) { tmp = p; p = parent[cur] = parent[p]; // Perform simple path compression. cur = tmp; } return cur; }
java
public int find(int cur) { assert (cur >= 0 && cur < parent.length); int p = parent[cur], tmp; while(cur != p) { tmp = p; p = parent[cur] = parent[p]; // Perform simple path compression. cur = tmp; } return cur; }
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Find the parent of an object. @param cur Current entry @return Parent entry
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core/src/main/java/de/lmu/ifi/dbs/elki/utilities/datastructures/unionfind/WeightedQuickUnionInteger.java#L101-L110
train
elki-project/elki
elki-core/src/main/java/de/lmu/ifi/dbs/elki/utilities/datastructures/unionfind/WeightedQuickUnionInteger.java
WeightedQuickUnionInteger.union
public int union(int first, int second) { int firstComponent = find(first), secondComponent = find(second); if(firstComponent == secondComponent) { return firstComponent; } final int w1 = weight[firstComponent], w2 = weight[secondComponent]; if(w1 > w2) { parent[secondComponent] = firstComponent; weight[firstComponent] += w2; return firstComponent; } else { parent[firstComponent] = secondComponent; weight[secondComponent] += w1; return secondComponent; } }
java
public int union(int first, int second) { int firstComponent = find(first), secondComponent = find(second); if(firstComponent == secondComponent) { return firstComponent; } final int w1 = weight[firstComponent], w2 = weight[secondComponent]; if(w1 > w2) { parent[secondComponent] = firstComponent; weight[firstComponent] += w2; return firstComponent; } else { parent[firstComponent] = secondComponent; weight[secondComponent] += w1; return secondComponent; } }
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Join the components of elements p and q. @param first First element @param second Second element @return Component id.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core/src/main/java/de/lmu/ifi/dbs/elki/utilities/datastructures/unionfind/WeightedQuickUnionInteger.java#L119-L135
train
elki-project/elki
elki-core/src/main/java/de/lmu/ifi/dbs/elki/utilities/datastructures/unionfind/WeightedQuickUnionInteger.java
WeightedQuickUnionInteger.getRoots
public IntList getRoots() { IntList roots = new IntArrayList(); for(int i = 0; i < used; i++) { // roots or one element in component if(parent[i] == i) { roots.add(i); } } return roots; }
java
public IntList getRoots() { IntList roots = new IntArrayList(); for(int i = 0; i < used; i++) { // roots or one element in component if(parent[i] == i) { roots.add(i); } } return roots; }
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Collect all component root elements. @return Root elements
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core/src/main/java/de/lmu/ifi/dbs/elki/utilities/datastructures/unionfind/WeightedQuickUnionInteger.java#L153-L162
train
elki-project/elki
addons/xtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/xtree/AbstractXTreeNode.java
AbstractXTreeNode.growSuperNode
public int growSuperNode() { if(getNumEntries() < getCapacity()) { throw new IllegalStateException("This node is not yet overflowing (only " + getNumEntries() + " of " + getCapacity() + " entries)"); } Entry[] old_nodes = super.entries.clone(); assert old_nodes[old_nodes.length - 1] != null; super.entries = (Entry[]) java.util.Arrays.copyOfRange(old_nodes, 0, getCapacity() * 2 - 1, entries.getClass()); assert super.entries.length == old_nodes.length * 2 - 1; return getCapacity(); }
java
public int growSuperNode() { if(getNumEntries() < getCapacity()) { throw new IllegalStateException("This node is not yet overflowing (only " + getNumEntries() + " of " + getCapacity() + " entries)"); } Entry[] old_nodes = super.entries.clone(); assert old_nodes[old_nodes.length - 1] != null; super.entries = (Entry[]) java.util.Arrays.copyOfRange(old_nodes, 0, getCapacity() * 2 - 1, entries.getClass()); assert super.entries.length == old_nodes.length * 2 - 1; return getCapacity(); }
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Grows the supernode by duplicating its capacity. @return the new page capacity of this node
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/xtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/xtree/AbstractXTreeNode.java#L90-L99
train
elki-project/elki
addons/xtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/xtree/AbstractXTreeNode.java
AbstractXTreeNode.readSuperNode
public <T extends AbstractXTree<N>> void readSuperNode(ObjectInput in, T tree) throws IOException, ClassNotFoundException { readExternal(in); if(capacity_to_be_filled <= 0 || !isSuperNode()) { throw new IllegalStateException("This node does not appear to be a supernode"); } if(isLeaf) { throw new IllegalStateException("A supernode is cannot be a leaf"); } // TODO: verify entries = new Entry[capacity_to_be_filled]; // old way: // entries = (E[]) new XDirectoryEntry[capacity_to_be_filled]; capacity_to_be_filled = 0; for(int i = 0; i < numEntries; i++) { SpatialEntry s = new SpatialDirectoryEntry(); s.readExternal(in); entries[i] = s; } N n = tree.getSupernodes().put((long) getPageID(), (N) this); if(n != null) { Logging.getLogger(this.getClass()).fine("Warning: this supernode should only be read once. Now a node of size " + entries.length + " has replaced a node of size " + n.entries.length + " for id " + getPageID()); } }
java
public <T extends AbstractXTree<N>> void readSuperNode(ObjectInput in, T tree) throws IOException, ClassNotFoundException { readExternal(in); if(capacity_to_be_filled <= 0 || !isSuperNode()) { throw new IllegalStateException("This node does not appear to be a supernode"); } if(isLeaf) { throw new IllegalStateException("A supernode is cannot be a leaf"); } // TODO: verify entries = new Entry[capacity_to_be_filled]; // old way: // entries = (E[]) new XDirectoryEntry[capacity_to_be_filled]; capacity_to_be_filled = 0; for(int i = 0; i < numEntries; i++) { SpatialEntry s = new SpatialDirectoryEntry(); s.readExternal(in); entries[i] = s; } N n = tree.getSupernodes().put((long) getPageID(), (N) this); if(n != null) { Logging.getLogger(this.getClass()).fine("Warning: this supernode should only be read once. Now a node of size " + entries.length + " has replaced a node of size " + n.entries.length + " for id " + getPageID()); } }
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Reads the id of this supernode, the numEntries and the entries array from the specified stream. @param in the stream to read data from in order to restore the object @param tree the tree this supernode is to be assigned to @throws java.io.IOException if I/O errors occur @throws ClassNotFoundException If the class for an object being restored cannot be found. @throws IllegalStateException if the parameters of the file's supernode do not match this
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/xtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/xtree/AbstractXTreeNode.java#L238-L260
train
elki-project/elki
elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java
DBIDUtil.compare
public static int compare(DBIDRef id1, DBIDRef id2) { return DBIDFactory.FACTORY.compare(id1, id2); }
java
public static int compare(DBIDRef id1, DBIDRef id2) { return DBIDFactory.FACTORY.compare(id1, id2); }
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Compare two DBIDs. @param id1 First ID @param id2 Second ID @return Comparison result
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java#L95-L97
train
elki-project/elki
elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java
DBIDUtil.equal
public static boolean equal(DBIDRef id1, DBIDRef id2) { return DBIDFactory.FACTORY.equal(id1, id2); }
java
public static boolean equal(DBIDRef id1, DBIDRef id2) { return DBIDFactory.FACTORY.equal(id1, id2); }
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Test two DBIDs for equality. @param id1 First ID @param id2 Second ID @return Comparison result
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java#L106-L108
train
elki-project/elki
elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java
DBIDUtil.deref
public static DBID deref(DBIDRef ref) { return ref instanceof DBID ? (DBID) ref : importInteger(ref.internalGetIndex()); }
java
public static DBID deref(DBIDRef ref) { return ref instanceof DBID ? (DBID) ref : importInteger(ref.internalGetIndex()); }
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Dereference a DBID reference. @param ref DBID reference @return DBID
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java#L116-L118
train
elki-project/elki
elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java
DBIDUtil.union
public static ModifiableDBIDs union(DBIDs ids1, DBIDs ids2) { ModifiableDBIDs result = DBIDUtil.newHashSet(Math.max(ids1.size(), ids2.size())); result.addDBIDs(ids1); result.addDBIDs(ids2); return result; }
java
public static ModifiableDBIDs union(DBIDs ids1, DBIDs ids2) { ModifiableDBIDs result = DBIDUtil.newHashSet(Math.max(ids1.size(), ids2.size())); result.addDBIDs(ids1); result.addDBIDs(ids2); return result; }
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Returns the union of the two specified collection of IDs. @param ids1 the first collection @param ids2 the second collection @return the union of ids1 and ids2 without duplicates
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java#L398-L403
train
elki-project/elki
elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java
DBIDUtil.difference
public static ModifiableDBIDs difference(DBIDs ids1, DBIDs ids2) { ModifiableDBIDs result = DBIDUtil.newHashSet(ids1); result.removeDBIDs(ids2); return result; }
java
public static ModifiableDBIDs difference(DBIDs ids1, DBIDs ids2) { ModifiableDBIDs result = DBIDUtil.newHashSet(ids1); result.removeDBIDs(ids2); return result; }
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Returns the difference of the two specified collection of IDs. @param ids1 the first collection @param ids2 the second collection @return the difference of ids1 minus ids2
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java#L412-L416
train
elki-project/elki
elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java
DBIDUtil.ensureArray
public static ArrayDBIDs ensureArray(DBIDs ids) { return ids instanceof ArrayDBIDs ? (ArrayDBIDs) ids : newArray(ids); }
java
public static ArrayDBIDs ensureArray(DBIDs ids) { return ids instanceof ArrayDBIDs ? (ArrayDBIDs) ids : newArray(ids); }
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Ensure that the given DBIDs are array-indexable. @param ids IDs @return Array DBIDs.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java#L434-L436
train
elki-project/elki
elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java
DBIDUtil.ensureSet
public static SetDBIDs ensureSet(DBIDs ids) { return ids instanceof SetDBIDs ? (SetDBIDs) ids : newHashSet(ids); }
java
public static SetDBIDs ensureSet(DBIDs ids) { return ids instanceof SetDBIDs ? (SetDBIDs) ids : newHashSet(ids); }
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Ensure that the given DBIDs support fast "contains" operations. @param ids IDs @return Set DBIDs.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java#L444-L446
train
elki-project/elki
elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java
DBIDUtil.ensureModifiable
public static ModifiableDBIDs ensureModifiable(DBIDs ids) { return ids instanceof ModifiableDBIDs ? (ModifiableDBIDs) ids : // ids instanceof HashSetDBIDs ? newHashSet(ids) : newArray(ids); }
java
public static ModifiableDBIDs ensureModifiable(DBIDs ids) { return ids instanceof ModifiableDBIDs ? (ModifiableDBIDs) ids : // ids instanceof HashSetDBIDs ? newHashSet(ids) : newArray(ids); }
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Ensure modifiable. @param ids IDs @return Modifiable DBIDs.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java#L454-L457
train
elki-project/elki
elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java
DBIDUtil.newPair
public static DBIDPair newPair(DBIDRef id1, DBIDRef id2) { return DBIDFactory.FACTORY.newPair(id1, id2); }
java
public static DBIDPair newPair(DBIDRef id1, DBIDRef id2) { return DBIDFactory.FACTORY.newPair(id1, id2); }
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Make a DBID pair. @param id1 first ID @param id2 second ID @return DBID pair
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java#L467-L469
train
elki-project/elki
elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java
DBIDUtil.newPair
public static DoubleDBIDPair newPair(double val, DBIDRef id) { return DBIDFactory.FACTORY.newPair(val, id); }
java
public static DoubleDBIDPair newPair(double val, DBIDRef id) { return DBIDFactory.FACTORY.newPair(val, id); }
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Make a DoubleDBIDPair. @param val double value @param id ID @return new pair
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/ids/DBIDUtil.java#L478-L480
train
elki-project/elki
elki-core-dbids-int/src/main/java/de/lmu/ifi/dbs/elki/database/ids/integer/IntegerDBIDArrayQuickSort.java
IntegerDBIDArrayQuickSort.sort
public static void sort(int[] data, Comparator<? super DBIDRef> comp) { sort(data, 0, data.length, comp); }
java
public static void sort(int[] data, Comparator<? super DBIDRef> comp) { sort(data, 0, data.length, comp); }
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Sort the full array using the given comparator. @param data Data to sort @param comp Comparator
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-dbids-int/src/main/java/de/lmu/ifi/dbs/elki/database/ids/integer/IntegerDBIDArrayQuickSort.java#L68-L70
train
elki-project/elki
elki-core-dbids-int/src/main/java/de/lmu/ifi/dbs/elki/database/ids/integer/IntegerDBIDArrayQuickSort.java
IntegerDBIDArrayQuickSort.compare
private static int compare(IntegerDBIDVar i1, int p1, IntegerDBIDVar i2, int p2, Comparator<? super DBIDRef> comp) { i1.internalSetIndex(p1); i2.internalSetIndex(p2); return comp.compare(i1, i2); }
java
private static int compare(IntegerDBIDVar i1, int p1, IntegerDBIDVar i2, int p2, Comparator<? super DBIDRef> comp) { i1.internalSetIndex(p1); i2.internalSetIndex(p2); return comp.compare(i1, i2); }
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Compare two elements. @param i1 First scratch variable @param p1 Value for first @param i2 Second scratch variable @param p2 Value for second @param comp Comparator @return Comparison result
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-dbids-int/src/main/java/de/lmu/ifi/dbs/elki/database/ids/integer/IntegerDBIDArrayQuickSort.java#L256-L260
train
elki-project/elki
addons/xtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/xtree/AbstractXTree.java
AbstractXTree.computeHeight
@Override protected int computeHeight() { N node = getRoot(); int tHeight = 1; // compute height while(!node.isLeaf() && node.getNumEntries() != 0) { SpatialEntry entry = node.getEntry(0); node = getNode(entry); tHeight++; } return tHeight; }
java
@Override protected int computeHeight() { N node = getRoot(); int tHeight = 1; // compute height while(!node.isLeaf() && node.getNumEntries() != 0) { SpatialEntry entry = node.getEntry(0); node = getNode(entry); tHeight++; } return tHeight; }
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Computes the height of this XTree. Is called by the constructor. and should be overwritten by subclasses if necessary. @return the height of this XTree
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/xtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/xtree/AbstractXTree.java#L170-L182
train
elki-project/elki
addons/xtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/xtree/AbstractXTree.java
AbstractXTree.commit
public long commit() throws IOException { final PageFile<N> file = super.getFile(); if(!(file instanceof PersistentPageFile)) { throw new IllegalStateException("Trying to commit a non-persistent XTree"); } long npid = file.getNextPageID(); XTreeHeader ph = (XTreeHeader) ((PersistentPageFile<?>) file).getHeader(); long offset = (ph.getReservedPages() + npid) * ph.getPageSize(); ph.setSupernode_offset(npid * ph.getPageSize()); ph.setNumberOfElements(num_elements); RandomAccessFile ra_file = ((PersistentPageFile<?>) file).getFile(); ph.writeHeader(ra_file); ra_file.seek(offset); long nBytes = 0; for(Iterator<N> iterator = supernodes.values().iterator(); iterator.hasNext();) { N supernode = iterator.next(); ByteArrayOutputStream baos = new ByteArrayOutputStream(); ObjectOutputStream oos = new ObjectOutputStream(baos); supernode.writeSuperNode(oos); oos.close(); baos.close(); byte[] array = baos.toByteArray(); byte[] sn_array = new byte[getPageSize() * (int) Math.ceil((double) supernode.getCapacity() / dirCapacity)]; if(array.length > sn_array.length) { throw new IllegalStateException("Supernode is too large for fitting in " + ((int) Math.ceil((double) supernode.getCapacity() / dirCapacity)) + " pages of total size " + sn_array.length); } System.arraycopy(array, 0, sn_array, 0, array.length); // file.countWrite(); ra_file.write(sn_array); nBytes += sn_array.length; } return nBytes; }
java
public long commit() throws IOException { final PageFile<N> file = super.getFile(); if(!(file instanceof PersistentPageFile)) { throw new IllegalStateException("Trying to commit a non-persistent XTree"); } long npid = file.getNextPageID(); XTreeHeader ph = (XTreeHeader) ((PersistentPageFile<?>) file).getHeader(); long offset = (ph.getReservedPages() + npid) * ph.getPageSize(); ph.setSupernode_offset(npid * ph.getPageSize()); ph.setNumberOfElements(num_elements); RandomAccessFile ra_file = ((PersistentPageFile<?>) file).getFile(); ph.writeHeader(ra_file); ra_file.seek(offset); long nBytes = 0; for(Iterator<N> iterator = supernodes.values().iterator(); iterator.hasNext();) { N supernode = iterator.next(); ByteArrayOutputStream baos = new ByteArrayOutputStream(); ObjectOutputStream oos = new ObjectOutputStream(baos); supernode.writeSuperNode(oos); oos.close(); baos.close(); byte[] array = baos.toByteArray(); byte[] sn_array = new byte[getPageSize() * (int) Math.ceil((double) supernode.getCapacity() / dirCapacity)]; if(array.length > sn_array.length) { throw new IllegalStateException("Supernode is too large for fitting in " + ((int) Math.ceil((double) supernode.getCapacity() / dirCapacity)) + " pages of total size " + sn_array.length); } System.arraycopy(array, 0, sn_array, 0, array.length); // file.countWrite(); ra_file.write(sn_array); nBytes += sn_array.length; } return nBytes; }
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Writes all supernodes to the end of the file. This is only supposed to be used for a final saving of an XTree. If another page is added to this tree, the supernodes written to file by this operation are over-written. @return the number of bytes written to file for this tree's supernodes @throws IOException if there are any io problems when writing the tree's supernodes
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/xtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/xtree/AbstractXTree.java#L298-L330
train
elki-project/elki
elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/deliclu/DeLiCluTree.java
DeLiCluTree.setExpanded
public void setExpanded(SpatialEntry entry1, SpatialEntry entry2) { IntSet exp1 = expanded.get(getPageID(entry1)); if(exp1 == null) { exp1 = new IntOpenHashSet(); expanded.put(getPageID(entry1), exp1); } exp1.add(getPageID(entry2)); }
java
public void setExpanded(SpatialEntry entry1, SpatialEntry entry2) { IntSet exp1 = expanded.get(getPageID(entry1)); if(exp1 == null) { exp1 = new IntOpenHashSet(); expanded.put(getPageID(entry1), exp1); } exp1.add(getPageID(entry2)); }
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Marks the nodes with the specified ids as expanded. @param entry1 the first node @param entry2 the second node
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/deliclu/DeLiCluTree.java#L72-L79
train
elki-project/elki
elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/deliclu/DeLiCluTree.java
DeLiCluTree.getExpanded
public IntSet getExpanded(SpatialEntry entry) { IntSet exp = expanded.get(getPageID(entry)); return (exp != null) ? exp : IntSets.EMPTY_SET; }
java
public IntSet getExpanded(SpatialEntry entry) { IntSet exp = expanded.get(getPageID(entry)); return (exp != null) ? exp : IntSets.EMPTY_SET; }
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Returns the nodes which are already expanded with the specified node. @param entry the id of the node for which the expansions should be returned @return the nodes which are already expanded with the specified node
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/deliclu/DeLiCluTree.java#L87-L90
train
elki-project/elki
elki-core/src/main/java/de/lmu/ifi/dbs/elki/utilities/datastructures/histogram/DoubleHistogram.java
DoubleHistogram.increment
public void increment(double coord, double val) { int bin = getBinNr(coord); if (bin < 0) { if (size - bin > data.length) { // Reallocate. TODO: use an arraylist-like grow strategy! double[] tmpdata = new double[growSize(data.length, size - bin)]; System.arraycopy(data, 0, tmpdata, -bin, size); data = tmpdata; } else { // Shift in place and clear head System.arraycopy(data, 0, data, -bin, size); Arrays.fill(data, 0, -bin, (double) 0); } data[0] = val; // Note that bin is negative, -bin is the shift offset! assert (data.length >= size - bin); offset -= bin; size -= bin; // TODO: modCounter++; and have iterators fast-fail } else if (bin >= data.length) { double[] tmpdata = new double[growSize(data.length, bin + 1)]; System.arraycopy(data, 0, tmpdata, 0, size); tmpdata[bin] = val; data = tmpdata; size = bin + 1; // TODO: modCounter++; and have iterators fast-fail // Unset max value when resizing max = Double.MAX_VALUE; } else { if (bin >= size) { // TODO: reset bins to 0 first? size = bin + 1; } data[bin] += val; } }
java
public void increment(double coord, double val) { int bin = getBinNr(coord); if (bin < 0) { if (size - bin > data.length) { // Reallocate. TODO: use an arraylist-like grow strategy! double[] tmpdata = new double[growSize(data.length, size - bin)]; System.arraycopy(data, 0, tmpdata, -bin, size); data = tmpdata; } else { // Shift in place and clear head System.arraycopy(data, 0, data, -bin, size); Arrays.fill(data, 0, -bin, (double) 0); } data[0] = val; // Note that bin is negative, -bin is the shift offset! assert (data.length >= size - bin); offset -= bin; size -= bin; // TODO: modCounter++; and have iterators fast-fail } else if (bin >= data.length) { double[] tmpdata = new double[growSize(data.length, bin + 1)]; System.arraycopy(data, 0, tmpdata, 0, size); tmpdata[bin] = val; data = tmpdata; size = bin + 1; // TODO: modCounter++; and have iterators fast-fail // Unset max value when resizing max = Double.MAX_VALUE; } else { if (bin >= size) { // TODO: reset bins to 0 first? size = bin + 1; } data[bin] += val; } }
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Increment the value of a bin. @param coord Coordinate @param val Value
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core/src/main/java/de/lmu/ifi/dbs/elki/utilities/datastructures/histogram/DoubleHistogram.java#L58-L93
train
elki-project/elki
elki-core/src/main/java/de/lmu/ifi/dbs/elki/utilities/datastructures/histogram/DoubleHistogram.java
DoubleHistogram.get
public double get(double coord) { int bin = getBinNr(coord); return (bin < 0 || bin >= size) ? 0 : data[bin]; }
java
public double get(double coord) { int bin = getBinNr(coord); return (bin < 0 || bin >= size) ? 0 : data[bin]; }
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Get the value at a particular position. @param coord Coordinate @return Value
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core/src/main/java/de/lmu/ifi/dbs/elki/utilities/datastructures/histogram/DoubleHistogram.java#L101-L104
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/gdbscan/util/MultiBorder.java
MultiBorder.update
public Assignment update(Border border) { Arrays.sort(cs); int j = 1; boolean found = (cs[0].core == border.core); for(int i = 1; i < cs.length; i++) { if(cs[i].core != cs[i - 1].core) { cs[j++] = cs[i]; } found |= (cs[i].core == border.core); } if(found) { if(j == 1) { Border r = cs[0]; cs = null; // Prevent further use return r; } if(j < cs.length) { cs = Arrays.copyOf(cs, j); } return this; } if(j + 1 != cs.length) { cs = Arrays.copyOf(cs, j + 1); } cs[j] = border; return this; }
java
public Assignment update(Border border) { Arrays.sort(cs); int j = 1; boolean found = (cs[0].core == border.core); for(int i = 1; i < cs.length; i++) { if(cs[i].core != cs[i - 1].core) { cs[j++] = cs[i]; } found |= (cs[i].core == border.core); } if(found) { if(j == 1) { Border r = cs[0]; cs = null; // Prevent further use return r; } if(j < cs.length) { cs = Arrays.copyOf(cs, j); } return this; } if(j + 1 != cs.length) { cs = Arrays.copyOf(cs, j + 1); } cs[j] = border; return this; }
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Add a new border to the existing borders. @param border New border.
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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/util/MultiBorder.java#L53-L79
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/gdbscan/util/MultiBorder.java
MultiBorder.getCore
public Core getCore() { Core a = cs[0].core; for(int i = 1; i < cs.length; i++) { Core v = cs[i].core; a = a.num > v.num ? a : v; // max, of negative values } return a; }
java
public Core getCore() { Core a = cs[0].core; for(int i = 1; i < cs.length; i++) { Core v = cs[i].core; a = a.num > v.num ? a : v; // max, of negative values } return a; }
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Get the core this is assigned to. @return Core
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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/util/MultiBorder.java#L86-L93
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/KMedoidsPark.java
KMedoidsPark.currentCluster
protected int currentCluster(List<? extends ModifiableDBIDs> clusters, DBIDRef id) { for(int i = 0; i < k; i++) { if(clusters.get(i).contains(id)) { return i; } } return -1; }
java
protected int currentCluster(List<? extends ModifiableDBIDs> clusters, DBIDRef id) { for(int i = 0; i < k; i++) { if(clusters.get(i).contains(id)) { return i; } } return -1; }
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Find the current cluster assignment. @param clusters Clusters @param id Current object @return Current cluster assignment.
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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/KMedoidsPark.java#L286-L293
train
elki-project/elki
elki-outlier/src/main/java/de/lmu/ifi/dbs/elki/algorithm/outlier/lof/INFLO.java
INFLO.computeINFLO
protected void computeINFLO(Relation<O> relation, ModifiableDBIDs pruned, KNNQuery<O> knnq, WritableDataStore<ModifiableDBIDs> rNNminuskNNs, WritableDoubleDataStore inflos, DoubleMinMax inflominmax) { FiniteProgress prog = LOG.isVerbose() ? new FiniteProgress("Computing INFLOs", relation.size(), LOG) : null; HashSetModifiableDBIDs set = DBIDUtil.newHashSet(); for(DBIDIter iter = relation.iterDBIDs(); iter.valid(); iter.advance()) { if(pruned.contains(iter)) { inflos.putDouble(iter, 1.); inflominmax.put(1.); LOG.incrementProcessed(prog); continue; } final KNNList knn = knnq.getKNNForDBID(iter, kplus1); if(knn.getKNNDistance() == 0.) { inflos.putDouble(iter, 1.); inflominmax.put(1.); LOG.incrementProcessed(prog); continue; } set.clear(); set.addDBIDs(knn); set.addDBIDs(rNNminuskNNs.get(iter)); // Compute mean density of NN \cup RNN double sum = 0.; int c = 0; for(DBIDIter niter = set.iter(); niter.valid(); niter.advance()) { if(DBIDUtil.equal(iter, niter)) { continue; } final double kdist = knnq.getKNNForDBID(niter, kplus1).getKNNDistance(); if(kdist <= 0) { sum = Double.POSITIVE_INFINITY; c++; break; } sum += 1. / kdist; c++; } sum *= knn.getKNNDistance(); final double inflo = sum == 0 ? 1. : sum / c; inflos.putDouble(iter, inflo); inflominmax.put(inflo); LOG.incrementProcessed(prog); } LOG.ensureCompleted(prog); }
java
protected void computeINFLO(Relation<O> relation, ModifiableDBIDs pruned, KNNQuery<O> knnq, WritableDataStore<ModifiableDBIDs> rNNminuskNNs, WritableDoubleDataStore inflos, DoubleMinMax inflominmax) { FiniteProgress prog = LOG.isVerbose() ? new FiniteProgress("Computing INFLOs", relation.size(), LOG) : null; HashSetModifiableDBIDs set = DBIDUtil.newHashSet(); for(DBIDIter iter = relation.iterDBIDs(); iter.valid(); iter.advance()) { if(pruned.contains(iter)) { inflos.putDouble(iter, 1.); inflominmax.put(1.); LOG.incrementProcessed(prog); continue; } final KNNList knn = knnq.getKNNForDBID(iter, kplus1); if(knn.getKNNDistance() == 0.) { inflos.putDouble(iter, 1.); inflominmax.put(1.); LOG.incrementProcessed(prog); continue; } set.clear(); set.addDBIDs(knn); set.addDBIDs(rNNminuskNNs.get(iter)); // Compute mean density of NN \cup RNN double sum = 0.; int c = 0; for(DBIDIter niter = set.iter(); niter.valid(); niter.advance()) { if(DBIDUtil.equal(iter, niter)) { continue; } final double kdist = knnq.getKNNForDBID(niter, kplus1).getKNNDistance(); if(kdist <= 0) { sum = Double.POSITIVE_INFINITY; c++; break; } sum += 1. / kdist; c++; } sum *= knn.getKNNDistance(); final double inflo = sum == 0 ? 1. : sum / c; inflos.putDouble(iter, inflo); inflominmax.put(inflo); LOG.incrementProcessed(prog); } LOG.ensureCompleted(prog); }
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Compute the final INFLO scores. @param relation Data relation @param pruned Pruned objects @param knnq kNN query @param rNNminuskNNs reverse kNN storage @param inflos INFLO score storage @param inflominmax Output of minimum and maximum
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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/INFLO.java#L225-L268
train
elki-project/elki
addons/tutorial/src/main/java/tutorial/outlier/ODIN.java
ODIN.run
public OutlierResult run(Database database, Relation<O> relation) { // Get the query functions: DistanceQuery<O> dq = database.getDistanceQuery(relation, getDistanceFunction()); KNNQuery<O> knnq = database.getKNNQuery(dq, k); // Get the objects to process, and a data storage for counting and output: DBIDs ids = relation.getDBIDs(); WritableDoubleDataStore scores = DataStoreUtil.makeDoubleStorage(ids, DataStoreFactory.HINT_DB, 0.); // Process all objects for(DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) { // Find the nearest neighbors (using an index, if available!) KNNList neighbors = knnq.getKNNForDBID(iter, k); // For each neighbor, except ourselves, increase the in-degree: for(DBIDIter nei = neighbors.iter(); nei.valid(); nei.advance()) { if(DBIDUtil.equal(iter, nei)) { continue; } scores.put(nei, scores.doubleValue(nei) + 1); } } // Compute maximum double min = Double.POSITIVE_INFINITY, max = 0.0; for(DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) { min = Math.min(min, scores.doubleValue(iter)); max = Math.max(max, scores.doubleValue(iter)); } // Wrap the result and add metadata. // By actually specifying theoretical min, max and baseline, we get a better // visualization (try it out - or see the screenshots in the tutorial)! OutlierScoreMeta meta = new InvertedOutlierScoreMeta(min, max, 0., ids.size() - 1, k); DoubleRelation rel = new MaterializedDoubleRelation("ODIN In-Degree", "odin", scores, ids); return new OutlierResult(meta, rel); }
java
public OutlierResult run(Database database, Relation<O> relation) { // Get the query functions: DistanceQuery<O> dq = database.getDistanceQuery(relation, getDistanceFunction()); KNNQuery<O> knnq = database.getKNNQuery(dq, k); // Get the objects to process, and a data storage for counting and output: DBIDs ids = relation.getDBIDs(); WritableDoubleDataStore scores = DataStoreUtil.makeDoubleStorage(ids, DataStoreFactory.HINT_DB, 0.); // Process all objects for(DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) { // Find the nearest neighbors (using an index, if available!) KNNList neighbors = knnq.getKNNForDBID(iter, k); // For each neighbor, except ourselves, increase the in-degree: for(DBIDIter nei = neighbors.iter(); nei.valid(); nei.advance()) { if(DBIDUtil.equal(iter, nei)) { continue; } scores.put(nei, scores.doubleValue(nei) + 1); } } // Compute maximum double min = Double.POSITIVE_INFINITY, max = 0.0; for(DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) { min = Math.min(min, scores.doubleValue(iter)); max = Math.max(max, scores.doubleValue(iter)); } // Wrap the result and add metadata. // By actually specifying theoretical min, max and baseline, we get a better // visualization (try it out - or see the screenshots in the tutorial)! OutlierScoreMeta meta = new InvertedOutlierScoreMeta(min, max, 0., ids.size() - 1, k); DoubleRelation rel = new MaterializedDoubleRelation("ODIN In-Degree", "odin", scores, ids); return new OutlierResult(meta, rel); }
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Run the ODIN algorithm Tutorial note: the <em>signature</em> of this method depends on the types that we requested in the {@link #getInputTypeRestriction} method. Here we requested a single relation of type {@code O} , the data type of our distance function. @param database Database to run on. @param relation Relation to process. @return ODIN outlier result.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/tutorial/src/main/java/tutorial/outlier/ODIN.java#L107-L141
train
elki-project/elki
elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/icons/StockIcon.java
StockIcon.getStockIcon
public static Icon getStockIcon(String name) { SoftReference<Icon> ref = iconcache.get(name); if(ref != null) { Icon icon = ref.get(); if(icon != null) { return icon; } } java.net.URL imgURL = StockIcon.class.getResource(name + ".png"); if(imgURL != null) { Icon icon = new ImageIcon(imgURL); iconcache.put(name, new SoftReference<>(icon)); return icon; } LoggingUtil.warning("Could not find stock icon: " + name); return null; }
java
public static Icon getStockIcon(String name) { SoftReference<Icon> ref = iconcache.get(name); if(ref != null) { Icon icon = ref.get(); if(icon != null) { return icon; } } java.net.URL imgURL = StockIcon.class.getResource(name + ".png"); if(imgURL != null) { Icon icon = new ImageIcon(imgURL); iconcache.put(name, new SoftReference<>(icon)); return icon; } LoggingUtil.warning("Could not find stock icon: " + name); return null; }
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Get a particular stock icon. @param name Icon name @return Icon
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/icons/StockIcon.java#L109-L125
train
elki-project/elki
elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/flat/FlatRStarTree.java
FlatRStarTree.initializeFromFile
@Override public void initializeFromFile(TreeIndexHeader header, PageFile<FlatRStarTreeNode> file) { super.initializeFromFile(header, file); // reconstruct root int nextPageID = file.getNextPageID(); dirCapacity = nextPageID; root = createNewDirectoryNode(); for(int i = 1; i < nextPageID; i++) { FlatRStarTreeNode node = getNode(i); root.addDirectoryEntry(createNewDirectoryEntry(node)); } if(LOG.isDebugging()) { LOG.debugFine("root: " + root + " with " + nextPageID + " leafNodes."); } }
java
@Override public void initializeFromFile(TreeIndexHeader header, PageFile<FlatRStarTreeNode> file) { super.initializeFromFile(header, file); // reconstruct root int nextPageID = file.getNextPageID(); dirCapacity = nextPageID; root = createNewDirectoryNode(); for(int i = 1; i < nextPageID; i++) { FlatRStarTreeNode node = getNode(i); root.addDirectoryEntry(createNewDirectoryEntry(node)); } if(LOG.isDebugging()) { LOG.debugFine("root: " + root + " with " + nextPageID + " leafNodes."); } }
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Initializes the flat RTree from an existing persistent file.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/flat/FlatRStarTree.java#L68-L84
train
elki-project/elki
elki-index-various/src/main/java/de/lmu/ifi/dbs/elki/index/tree/metrical/covertree/CoverTree.java
CoverTree.bulkConstruct
protected Node bulkConstruct(DBIDRef cur, int maxScale, double parentDist, ModifiableDoubleDBIDList elems) { assert (!elems.contains(cur)); final double max = maxDistance(elems); final int scale = Math.min(distToScale(max) - 1, maxScale); final int nextScale = scale - 1; // Leaf node, because points coincide, we are too deep, or have too few // elements remaining: if(max <= 0 || scale <= scaleBottom || elems.size() < truncate) { return new Node(cur, max, parentDist, elems); } // Find neighbors in the cover of the current object: ModifiableDoubleDBIDList candidates = DBIDUtil.newDistanceDBIDList(); excludeNotCovered(elems, scaleToDist(scale), candidates); // If no elements were not in the cover, build a compact tree: if(candidates.size() == 0) { LOG.warning("Scale not chosen appropriately? " + max + " " + scaleToDist(scale)); return bulkConstruct(cur, nextScale, parentDist, elems); } // We will have at least one other child, so build the parent: Node node = new Node(cur, max, parentDist); // Routing element now is a singleton: final boolean curSingleton = elems.size() == 0; if(!curSingleton) { // Add node for the routing object: node.children.add(bulkConstruct(cur, nextScale, 0, elems)); } final double fmax = scaleToDist(nextScale); // Build additional cover nodes: for(DoubleDBIDListIter it = candidates.iter(); it.valid();) { assert (it.getOffset() == 0); DBID t = DBIDUtil.deref(it); elems.clear(); // Recycle. collectByCover(it, candidates, fmax, elems); assert (DBIDUtil.equal(t, it)) : "First element in candidates must not change!"; if(elems.size() == 0) { // Singleton node.singletons.add(it.doubleValue(), it); } else { // Build a full child node: node.children.add(bulkConstruct(it, nextScale, it.doubleValue(), elems)); } candidates.removeSwap(0); } assert (candidates.size() == 0); // Routing object is not yet handled: if(curSingleton) { if(node.isLeaf()) { node.children = null; // First in leaf is enough. } else { node.singletons.add(parentDist, cur); // Add as regular singleton. } } // TODO: improve recycling of lists? return node; }
java
protected Node bulkConstruct(DBIDRef cur, int maxScale, double parentDist, ModifiableDoubleDBIDList elems) { assert (!elems.contains(cur)); final double max = maxDistance(elems); final int scale = Math.min(distToScale(max) - 1, maxScale); final int nextScale = scale - 1; // Leaf node, because points coincide, we are too deep, or have too few // elements remaining: if(max <= 0 || scale <= scaleBottom || elems.size() < truncate) { return new Node(cur, max, parentDist, elems); } // Find neighbors in the cover of the current object: ModifiableDoubleDBIDList candidates = DBIDUtil.newDistanceDBIDList(); excludeNotCovered(elems, scaleToDist(scale), candidates); // If no elements were not in the cover, build a compact tree: if(candidates.size() == 0) { LOG.warning("Scale not chosen appropriately? " + max + " " + scaleToDist(scale)); return bulkConstruct(cur, nextScale, parentDist, elems); } // We will have at least one other child, so build the parent: Node node = new Node(cur, max, parentDist); // Routing element now is a singleton: final boolean curSingleton = elems.size() == 0; if(!curSingleton) { // Add node for the routing object: node.children.add(bulkConstruct(cur, nextScale, 0, elems)); } final double fmax = scaleToDist(nextScale); // Build additional cover nodes: for(DoubleDBIDListIter it = candidates.iter(); it.valid();) { assert (it.getOffset() == 0); DBID t = DBIDUtil.deref(it); elems.clear(); // Recycle. collectByCover(it, candidates, fmax, elems); assert (DBIDUtil.equal(t, it)) : "First element in candidates must not change!"; if(elems.size() == 0) { // Singleton node.singletons.add(it.doubleValue(), it); } else { // Build a full child node: node.children.add(bulkConstruct(it, nextScale, it.doubleValue(), elems)); } candidates.removeSwap(0); } assert (candidates.size() == 0); // Routing object is not yet handled: if(curSingleton) { if(node.isLeaf()) { node.children = null; // First in leaf is enough. } else { node.singletons.add(parentDist, cur); // Add as regular singleton. } } // TODO: improve recycling of lists? return node; }
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Bulk-load the cover tree. This bulk-load is slightly simpler than the one used in the original cover-tree source: We do not look back into the "far" set of candidates. @param cur Current routing object @param maxScale Maximum scale @param elems Candidates @return Root node of subtree
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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/CoverTree.java#L223-L278
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/pca/weightfunctions/QuadraticWeight.java
QuadraticWeight.getWeight
@Override public double getWeight(double distance, double max, double stddev) { if(max <= 0) { return 1.0; } double relativedistance = distance / max; return 1.0 - 0.9 * relativedistance * relativedistance; }
java
@Override public double getWeight(double distance, double max, double stddev) { if(max <= 0) { return 1.0; } double relativedistance = distance / max; return 1.0 - 0.9 * relativedistance * relativedistance; }
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Evaluate quadratic weight. stddev is ignored.
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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/weightfunctions/QuadraticWeight.java#L36-L43
train
elki-project/elki
elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/distancefunction/minkowski/EuclideanDistanceFunction.java
EuclideanDistanceFunction.maxDist
public double maxDist(SpatialComparable mbr1, SpatialComparable mbr2) { final int dim1 = mbr1.getDimensionality(), dim2 = mbr2.getDimensionality(); final int mindim = dim1 < dim2 ? dim1 : dim2; double agg = 0.; for(int d = 0; d < mindim; d++) { double d1 = mbr1.getMax(d) - mbr2.getMin(d); double d2 = mbr2.getMax(d) - mbr1.getMin(d); double delta = d1 > d2 ? d1 : d2; agg += delta * delta; } for(int d = mindim; d < dim1; d++) { double d1 = Math.abs(mbr1.getMin(d)), d2 = Math.abs(mbr1.getMax(d)); double delta = d1 > d2 ? d1 : d2; agg += delta * delta; } for(int d = mindim; d < dim2; d++) { double d1 = Math.abs(mbr2.getMin(d)), d2 = Math.abs(mbr2.getMax(d)); double delta = d1 > d2 ? d1 : d2; agg += delta * delta; } return FastMath.sqrt(agg); }
java
public double maxDist(SpatialComparable mbr1, SpatialComparable mbr2) { final int dim1 = mbr1.getDimensionality(), dim2 = mbr2.getDimensionality(); final int mindim = dim1 < dim2 ? dim1 : dim2; double agg = 0.; for(int d = 0; d < mindim; d++) { double d1 = mbr1.getMax(d) - mbr2.getMin(d); double d2 = mbr2.getMax(d) - mbr1.getMin(d); double delta = d1 > d2 ? d1 : d2; agg += delta * delta; } for(int d = mindim; d < dim1; d++) { double d1 = Math.abs(mbr1.getMin(d)), d2 = Math.abs(mbr1.getMax(d)); double delta = d1 > d2 ? d1 : d2; agg += delta * delta; } for(int d = mindim; d < dim2; d++) { double d1 = Math.abs(mbr2.getMin(d)), d2 = Math.abs(mbr2.getMax(d)); double delta = d1 > d2 ? d1 : d2; agg += delta * delta; } return FastMath.sqrt(agg); }
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Maximum distance of two objects. @param mbr1 First object @param mbr2 Second object
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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/minkowski/EuclideanDistanceFunction.java#L160-L182
train
elki-project/elki
elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/util/DynamicParameters.java
DynamicParameters.updateFromTrackParameters
public synchronized void updateFromTrackParameters(TrackParameters track) { parameters.clear(); for(TrackedParameter p : track.getAllParameters()) { Parameter<?> option = p.getParameter(); String value = null; if(option.isDefined()) { if(option.tookDefaultValue()) { value = DynamicParameters.STRING_USE_DEFAULT + option.getDefaultValueAsString(); } else { value = option.getValueAsString(); } } if(value == null) { value = (option instanceof Flag) ? Flag.NOT_SET : ""; } int bits = 0; if(option.isOptional()) { bits |= BIT_OPTIONAL; } if(option.hasDefaultValue() && option.tookDefaultValue()) { bits |= BIT_DEFAULT_VALUE; } if(value.length() <= 0) { if((bits & BIT_DEFAULT_VALUE) == 0 && (bits & BIT_OPTIONAL) == 0) { bits |= BIT_INCOMPLETE; } } else { try { if(!option.tookDefaultValue() && !option.isValid(value)) { bits |= BIT_INVALID; } } catch(ParameterException e) { bits |= BIT_INVALID; } } int depth = 0; { Object pos = track.getParent(option); while(pos != null) { pos = track.getParent(pos); depth += 1; if(depth > 10) { break; } } } parameters.add(new Node(option, value, bits, depth)); } }
java
public synchronized void updateFromTrackParameters(TrackParameters track) { parameters.clear(); for(TrackedParameter p : track.getAllParameters()) { Parameter<?> option = p.getParameter(); String value = null; if(option.isDefined()) { if(option.tookDefaultValue()) { value = DynamicParameters.STRING_USE_DEFAULT + option.getDefaultValueAsString(); } else { value = option.getValueAsString(); } } if(value == null) { value = (option instanceof Flag) ? Flag.NOT_SET : ""; } int bits = 0; if(option.isOptional()) { bits |= BIT_OPTIONAL; } if(option.hasDefaultValue() && option.tookDefaultValue()) { bits |= BIT_DEFAULT_VALUE; } if(value.length() <= 0) { if((bits & BIT_DEFAULT_VALUE) == 0 && (bits & BIT_OPTIONAL) == 0) { bits |= BIT_INCOMPLETE; } } else { try { if(!option.tookDefaultValue() && !option.isValid(value)) { bits |= BIT_INVALID; } } catch(ParameterException e) { bits |= BIT_INVALID; } } int depth = 0; { Object pos = track.getParent(option); while(pos != null) { pos = track.getParent(pos); depth += 1; if(depth > 10) { break; } } } parameters.add(new Node(option, value, bits, depth)); } }
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Update the Parameter list from the collected options of an ELKI context @param track Tracked Parameters
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/util/DynamicParameters.java#L137-L188
train
elki-project/elki
elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/util/DynamicParameters.java
DynamicParameters.addParameter
public synchronized void addParameter(Parameter<?> option, String value, int bits, int depth) { parameters.add(new Node(option, value, bits, depth)); }
java
public synchronized void addParameter(Parameter<?> option, String value, int bits, int depth) { parameters.add(new Node(option, value, bits, depth)); }
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Add a single parameter to the list @param option Option @param value Value @param bits Bits @param depth Depth
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/util/DynamicParameters.java#L198-L200
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/data/Clustering.java
Clustering.getClusteringResults
public static List<Clustering<? extends Model>> getClusteringResults(Result r) { if(r instanceof Clustering<?>) { List<Clustering<?>> crs = new ArrayList<>(1); crs.add((Clustering<?>) r); return crs; } if(r instanceof HierarchicalResult) { return ResultUtil.filterResults(((HierarchicalResult) r).getHierarchy(), r, Clustering.class); } return Collections.emptyList(); }
java
public static List<Clustering<? extends Model>> getClusteringResults(Result r) { if(r instanceof Clustering<?>) { List<Clustering<?>> crs = new ArrayList<>(1); crs.add((Clustering<?>) r); return crs; } if(r instanceof HierarchicalResult) { return ResultUtil.filterResults(((HierarchicalResult) r).getHierarchy(), r, Clustering.class); } return Collections.emptyList(); }
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Collect all clustering results from a Result @param r Result @return List of clustering results
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/data/Clustering.java#L167-L177
train
elki-project/elki
addons/tutorial/src/main/java/tutorial/javaapi/GeoIndexing.java
GeoIndexing.randomLatitudeLongitude
private static double[] randomLatitudeLongitude(Random r) { // Make marginally more realistic looking data by non-uniformly sampling // latitude, since Earth is a sphere, and there is not much at the poles double lat = Math.pow(1. - r.nextDouble() * 2., 2) / 2. * 180; double lng = (.5 - r.nextDouble()) * 360.; return new double[] { lat, lng }; }
java
private static double[] randomLatitudeLongitude(Random r) { // Make marginally more realistic looking data by non-uniformly sampling // latitude, since Earth is a sphere, and there is not much at the poles double lat = Math.pow(1. - r.nextDouble() * 2., 2) / 2. * 180; double lng = (.5 - r.nextDouble()) * 360.; return new double[] { lat, lng }; }
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Generate random coordinates. @param r Random generator @return Latitude, Longitude array.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/tutorial/src/main/java/tutorial/javaapi/GeoIndexing.java#L138-L144
train
elki-project/elki
elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/distancefunction/correlation/AbsolutePearsonCorrelationDistanceFunction.java
AbsolutePearsonCorrelationDistanceFunction.distance
@Override public double distance(NumberVector v1, NumberVector v2) { return 1 - Math.abs(PearsonCorrelation.coefficient(v1, v2)); }
java
@Override public double distance(NumberVector v1, NumberVector v2) { return 1 - Math.abs(PearsonCorrelation.coefficient(v1, v2)); }
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Computes the absolute Pearson correlation distance for two given feature vectors. The absolute Pearson correlation distance is computed from the Pearson correlation coefficient <code>r</code> as: <code>1-abs(r)</code>. Hence, possible values of this distance are between 0 and 1. @param v1 first feature vector @param v2 second feature vector @return the absolute Pearson correlation distance for two given feature vectors v1 and v2
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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/correlation/AbsolutePearsonCorrelationDistanceFunction.java#L71-L74
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/HaltonUniformDistribution.java
HaltonUniformDistribution.inverse
private long inverse(double current) { // Represent to base b. short[] digits = new short[maxi]; for(int j = 0; j < maxi; j++) { current *= base; digits[j] = (short) current; current -= digits[j]; if(current <= 1e-10) { break; } } long inv = 0; for(int j = maxi - 1; j >= 0; j--) { inv = inv * base + digits[j]; } return inv; }
java
private long inverse(double current) { // Represent to base b. short[] digits = new short[maxi]; for(int j = 0; j < maxi; j++) { current *= base; digits[j] = (short) current; current -= digits[j]; if(current <= 1e-10) { break; } } long inv = 0; for(int j = maxi - 1; j >= 0; j--) { inv = inv * base + digits[j]; } return inv; }
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Compute the inverse with respect to the given base. @param current Current value @return Integer inverse
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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/HaltonUniformDistribution.java#L240-L256
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/HaltonUniformDistribution.java
HaltonUniformDistribution.radicalInverse
private double radicalInverse(long i) { double digit = 1.0 / (double) base; double radical = digit; double inverse = 0.0; while(i > 0) { inverse += digit * (double) (i % base); digit *= radical; i /= base; } return inverse; }
java
private double radicalInverse(long i) { double digit = 1.0 / (double) base; double radical = digit; double inverse = 0.0; while(i > 0) { inverse += digit * (double) (i % base); digit *= radical; i /= base; } return inverse; }
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Compute the radical inverse of i. @param i Input long value @return Double radical inverse
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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/HaltonUniformDistribution.java#L264-L274
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/HaltonUniformDistribution.java
HaltonUniformDistribution.nextRadicalInverse
private double nextRadicalInverse() { counter++; // Do at most MAXFAST appromate steps if(counter >= MAXFAST) { counter = 0; inverse += MAXFAST; current = radicalInverse(inverse); return current; } // Fast approximation: double nextInverse = current + invbase; if(nextInverse < ALMOST_ONE) { current = nextInverse; return current; } else { double digit1 = invbase, digit2 = invbase * invbase; while(current + digit2 >= ALMOST_ONE) { digit1 = digit2; digit2 *= invbase; } current += (digit1 - 1.0) + digit2; return current; } }
java
private double nextRadicalInverse() { counter++; // Do at most MAXFAST appromate steps if(counter >= MAXFAST) { counter = 0; inverse += MAXFAST; current = radicalInverse(inverse); return current; } // Fast approximation: double nextInverse = current + invbase; if(nextInverse < ALMOST_ONE) { current = nextInverse; return current; } else { double digit1 = invbase, digit2 = invbase * invbase; while(current + digit2 >= ALMOST_ONE) { digit1 = digit2; digit2 *= invbase; } current += (digit1 - 1.0) + digit2; return current; } }
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Compute the next radical inverse. @return Next inverse
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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/HaltonUniformDistribution.java#L281-L305
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/data/Subspace.java
Subspace.dimensonsToString
public String dimensonsToString(String sep) { StringBuilder result = new StringBuilder(100).append('['); for(int dim = BitsUtil.nextSetBit(dimensions, 0); dim >= 0; dim = BitsUtil.nextSetBit(dimensions, dim + 1)) { result.append(dim + 1).append(sep); } if(result.length() > sep.length()) { // Un-append last separator result.setLength(result.length() - sep.length()); } return result.append(']').toString(); }
java
public String dimensonsToString(String sep) { StringBuilder result = new StringBuilder(100).append('['); for(int dim = BitsUtil.nextSetBit(dimensions, 0); dim >= 0; dim = BitsUtil.nextSetBit(dimensions, dim + 1)) { result.append(dim + 1).append(sep); } if(result.length() > sep.length()) { // Un-append last separator result.setLength(result.length() - sep.length()); } return result.append(']').toString(); }
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Returns a string representation of the dimensions of this subspace. @param sep the separator between the dimensions @return a string representation of the dimensions of this subspace
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/data/Subspace.java#L129-L138
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/data/Subspace.java
Subspace.isSubspace
public boolean isSubspace(Subspace subspace) { return this.dimensionality <= subspace.dimensionality && // BitsUtil.intersectionSize(dimensions, subspace.dimensions) == dimensionality; }
java
public boolean isSubspace(Subspace subspace) { return this.dimensionality <= subspace.dimensionality && // BitsUtil.intersectionSize(dimensions, subspace.dimensions) == dimensionality; }
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Returns true if this subspace is a subspace of the specified subspace, i.e. if the set of dimensions building this subspace are contained in the set of dimensions building the specified subspace. @param subspace the subspace to test @return true if this subspace is a subspace of the specified subspace, false otherwise
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/data/Subspace.java#L149-L152
train
elki-project/elki
elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/strategies/split/AngTanLinearSplit.java
AngTanLinearSplit.computeOverlap
protected <E extends SpatialComparable, A> double computeOverlap(A entries, ArrayAdapter<E, A> getter, long[] assign) { ModifiableHyperBoundingBox mbr1 = null, mbr2 = null; for(int i = 0; i < getter.size(entries); i++) { E e = getter.get(entries, i); if(BitsUtil.get(assign, i)) { if(mbr1 == null) { mbr1 = new ModifiableHyperBoundingBox(e); } else { mbr1.extend(e); } } else { if(mbr2 == null) { mbr2 = new ModifiableHyperBoundingBox(e); } else { mbr2.extend(e); } } } if(mbr1 == null || mbr2 == null) { throw new AbortException("Invalid state in split: one of the sets is empty."); } return SpatialUtil.overlap(mbr1, mbr2); }
java
protected <E extends SpatialComparable, A> double computeOverlap(A entries, ArrayAdapter<E, A> getter, long[] assign) { ModifiableHyperBoundingBox mbr1 = null, mbr2 = null; for(int i = 0; i < getter.size(entries); i++) { E e = getter.get(entries, i); if(BitsUtil.get(assign, i)) { if(mbr1 == null) { mbr1 = new ModifiableHyperBoundingBox(e); } else { mbr1.extend(e); } } else { if(mbr2 == null) { mbr2 = new ModifiableHyperBoundingBox(e); } else { mbr2.extend(e); } } } if(mbr1 == null || mbr2 == null) { throw new AbortException("Invalid state in split: one of the sets is empty."); } return SpatialUtil.overlap(mbr1, mbr2); }
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Compute overlap of assignment @param entries Entries @param getter Entry accessor @param assign Assignment @return Overlap amount
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-index-rtree/src/main/java/de/lmu/ifi/dbs/elki/index/tree/spatial/rstarvariants/strategies/split/AngTanLinearSplit.java#L150-L175
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/spacefillingcurves/BinarySplitSpatialSorter.java
BinarySplitSpatialSorter.binarySplitSort
private void binarySplitSort(List<? extends SpatialComparable> objs, final int start, final int end, int depth, final int numdim, int[] dims, Sorter comp) { final int mid = start + ((end - start) >>> 1); // Make invariant comp.setDimension(dims != null ? dims[depth] : depth); QuickSelect.quickSelect(objs, comp, start, end, mid); // Recurse final int nextdim = (depth + 1) % numdim; if(start < mid - 1) { binarySplitSort(objs, start, mid, nextdim, numdim, dims, comp); } if(mid + 2 < end) { binarySplitSort(objs, mid + 1, end, nextdim, numdim, dims, comp); } }
java
private void binarySplitSort(List<? extends SpatialComparable> objs, final int start, final int end, int depth, final int numdim, int[] dims, Sorter comp) { final int mid = start + ((end - start) >>> 1); // Make invariant comp.setDimension(dims != null ? dims[depth] : depth); QuickSelect.quickSelect(objs, comp, start, end, mid); // Recurse final int nextdim = (depth + 1) % numdim; if(start < mid - 1) { binarySplitSort(objs, start, mid, nextdim, numdim, dims, comp); } if(mid + 2 < end) { binarySplitSort(objs, mid + 1, end, nextdim, numdim, dims, comp); } }
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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/spacefillingcurves/BinarySplitSpatialSorter.java#L86-L99
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java
SVGUtil.svgElement
public static Element svgElement(Document document, String name) { return document.createElementNS(SVGConstants.SVG_NAMESPACE_URI, name); }
java
public static Element svgElement(Document document, String name) { return document.createElementNS(SVGConstants.SVG_NAMESPACE_URI, name); }
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Create a SVG element in appropriate namespace @param document containing document @param name node name @return new SVG element.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java#L283-L285
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java
SVGUtil.setStyle
public static void setStyle(Element el, String d) { el.setAttribute(SVGConstants.SVG_STYLE_ATTRIBUTE, d); }
java
public static void setStyle(Element el, String d) { el.setAttribute(SVGConstants.SVG_STYLE_ATTRIBUTE, d); }
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Set a SVG style attribute @param el element @param d style value
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java#L326-L328
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java
SVGUtil.addCSSClass
public static void addCSSClass(Element e, String cssclass) { String oldval = e.getAttribute(SVGConstants.SVG_CLASS_ATTRIBUTE); if(oldval == null || oldval.length() == 0) { setAtt(e, SVGConstants.SVG_CLASS_ATTRIBUTE, cssclass); return; } String[] classes = oldval.split(" "); for(String c : classes) { if(c.equals(cssclass)) { return; } } setAtt(e, SVGConstants.SVG_CLASS_ATTRIBUTE, oldval + " " + cssclass); }
java
public static void addCSSClass(Element e, String cssclass) { String oldval = e.getAttribute(SVGConstants.SVG_CLASS_ATTRIBUTE); if(oldval == null || oldval.length() == 0) { setAtt(e, SVGConstants.SVG_CLASS_ATTRIBUTE, cssclass); return; } String[] classes = oldval.split(" "); for(String c : classes) { if(c.equals(cssclass)) { return; } } setAtt(e, SVGConstants.SVG_CLASS_ATTRIBUTE, oldval + " " + cssclass); }
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Add a CSS class to an Element. @param e Element @param cssclass class to add.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java#L347-L360
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java
SVGUtil.removeCSSClass
public static void removeCSSClass(Element e, String cssclass) { String oldval = e.getAttribute(SVGConstants.SVG_CLASS_ATTRIBUTE); if(oldval == null) { return; } String[] classes = oldval.split(" "); if(classes.length == 1) { if(cssclass.equals(classes[0])) { e.removeAttribute(SVGConstants.SVG_CLASS_ATTRIBUTE); } } else if(classes.length == 2) { if(cssclass.equals(classes[0])) { if(cssclass.equals(classes[1])) { e.removeAttribute(SVGConstants.SVG_CLASS_ATTRIBUTE); } else { e.setAttribute(SVGConstants.SVG_CLASS_ATTRIBUTE, classes[1]); } } else if(cssclass.equals(classes[1])) { e.setAttribute(SVGConstants.SVG_CLASS_ATTRIBUTE, classes[0]); } } else { StringBuilder joined = new StringBuilder(); for(String c : classes) { if(!c.equals(cssclass)) { if(joined.length() > 0) { joined.append(' '); } joined.append(c); } } e.setAttribute(SVGConstants.SVG_CLASS_ATTRIBUTE, joined.toString()); } }
java
public static void removeCSSClass(Element e, String cssclass) { String oldval = e.getAttribute(SVGConstants.SVG_CLASS_ATTRIBUTE); if(oldval == null) { return; } String[] classes = oldval.split(" "); if(classes.length == 1) { if(cssclass.equals(classes[0])) { e.removeAttribute(SVGConstants.SVG_CLASS_ATTRIBUTE); } } else if(classes.length == 2) { if(cssclass.equals(classes[0])) { if(cssclass.equals(classes[1])) { e.removeAttribute(SVGConstants.SVG_CLASS_ATTRIBUTE); } else { e.setAttribute(SVGConstants.SVG_CLASS_ATTRIBUTE, classes[1]); } } else if(cssclass.equals(classes[1])) { e.setAttribute(SVGConstants.SVG_CLASS_ATTRIBUTE, classes[0]); } } else { StringBuilder joined = new StringBuilder(); for(String c : classes) { if(!c.equals(cssclass)) { if(joined.length() > 0) { joined.append(' '); } joined.append(c); } } e.setAttribute(SVGConstants.SVG_CLASS_ATTRIBUTE, joined.toString()); } }
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Remove a CSS class from an Element. @param e Element @param cssclass class to remove.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java#L368-L404
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java
SVGUtil.makeStyleElement
public static Element makeStyleElement(Document document) { Element style = SVGUtil.svgElement(document, SVGConstants.SVG_STYLE_TAG); style.setAttribute(SVGConstants.SVG_TYPE_ATTRIBUTE, SVGConstants.CSS_MIME_TYPE); return style; }
java
public static Element makeStyleElement(Document document) { Element style = SVGUtil.svgElement(document, SVGConstants.SVG_STYLE_TAG); style.setAttribute(SVGConstants.SVG_TYPE_ATTRIBUTE, SVGConstants.CSS_MIME_TYPE); return style; }
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Make a new CSS style element for the given Document. @param document document (factory) @return new CSS style element.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java#L412-L416
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java
SVGUtil.svgRect
public static Element svgRect(Document document, double x, double y, double w, double h) { Element rect = SVGUtil.svgElement(document, SVGConstants.SVG_RECT_TAG); SVGUtil.setAtt(rect, SVGConstants.SVG_X_ATTRIBUTE, x); SVGUtil.setAtt(rect, SVGConstants.SVG_Y_ATTRIBUTE, y); SVGUtil.setAtt(rect, SVGConstants.SVG_WIDTH_ATTRIBUTE, w); SVGUtil.setAtt(rect, SVGConstants.SVG_HEIGHT_ATTRIBUTE, h); return rect; }
java
public static Element svgRect(Document document, double x, double y, double w, double h) { Element rect = SVGUtil.svgElement(document, SVGConstants.SVG_RECT_TAG); SVGUtil.setAtt(rect, SVGConstants.SVG_X_ATTRIBUTE, x); SVGUtil.setAtt(rect, SVGConstants.SVG_Y_ATTRIBUTE, y); SVGUtil.setAtt(rect, SVGConstants.SVG_WIDTH_ATTRIBUTE, w); SVGUtil.setAtt(rect, SVGConstants.SVG_HEIGHT_ATTRIBUTE, h); return rect; }
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Create a SVG rectangle element. @param document document to create in (factory) @param x X coordinate @param y Y coordinate @param w Width @param h Height @return new element
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java#L428-L435
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java
SVGUtil.svgCircle
public static Element svgCircle(Document document, double cx, double cy, double r) { Element circ = SVGUtil.svgElement(document, SVGConstants.SVG_CIRCLE_TAG); SVGUtil.setAtt(circ, SVGConstants.SVG_CX_ATTRIBUTE, cx); SVGUtil.setAtt(circ, SVGConstants.SVG_CY_ATTRIBUTE, cy); SVGUtil.setAtt(circ, SVGConstants.SVG_R_ATTRIBUTE, r); return circ; }
java
public static Element svgCircle(Document document, double cx, double cy, double r) { Element circ = SVGUtil.svgElement(document, SVGConstants.SVG_CIRCLE_TAG); SVGUtil.setAtt(circ, SVGConstants.SVG_CX_ATTRIBUTE, cx); SVGUtil.setAtt(circ, SVGConstants.SVG_CY_ATTRIBUTE, cy); SVGUtil.setAtt(circ, SVGConstants.SVG_R_ATTRIBUTE, r); return circ; }
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Create a SVG circle element. @param document document to create in (factory) @param cx center X @param cy center Y @param r radius @return new element
[ "Create", "a", "SVG", "circle", "element", "." ]
b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java#L446-L452
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java
SVGUtil.svgLine
public static Element svgLine(Document document, double x1, double y1, double x2, double y2) { Element line = SVGUtil.svgElement(document, SVGConstants.SVG_LINE_TAG); SVGUtil.setAtt(line, SVGConstants.SVG_X1_ATTRIBUTE, x1); SVGUtil.setAtt(line, SVGConstants.SVG_Y1_ATTRIBUTE, y1); SVGUtil.setAtt(line, SVGConstants.SVG_X2_ATTRIBUTE, x2); SVGUtil.setAtt(line, SVGConstants.SVG_Y2_ATTRIBUTE, y2); return line; }
java
public static Element svgLine(Document document, double x1, double y1, double x2, double y2) { Element line = SVGUtil.svgElement(document, SVGConstants.SVG_LINE_TAG); SVGUtil.setAtt(line, SVGConstants.SVG_X1_ATTRIBUTE, x1); SVGUtil.setAtt(line, SVGConstants.SVG_Y1_ATTRIBUTE, y1); SVGUtil.setAtt(line, SVGConstants.SVG_X2_ATTRIBUTE, x2); SVGUtil.setAtt(line, SVGConstants.SVG_Y2_ATTRIBUTE, y2); return line; }
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Create a SVG line element. Do not confuse this with path elements. @param document document to create in (factory) @param x1 first point x @param y1 first point y @param x2 second point x @param y2 second point y @return new element
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java#L464-L471
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java
SVGUtil.stringToColor
public static Color stringToColor(String str) { int icol = SVG_COLOR_NAMES.getInt(str.toLowerCase()); if(icol != NO_VALUE) { return new Color(icol, false); } return colorLookupStylesheet.stringToColor(str); }
java
public static Color stringToColor(String str) { int icol = SVG_COLOR_NAMES.getInt(str.toLowerCase()); if(icol != NO_VALUE) { return new Color(icol, false); } return colorLookupStylesheet.stringToColor(str); }
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Convert a color name from SVG syntax to an AWT color object. @param str Color name @return Color value
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java#L528-L534
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java
SVGUtil.colorToString
public static String colorToString(int col) { final char[] buf = new char[] { '#', 'X', 'X', 'X', 'X', 'X', 'X' }; for(int i = 6; i > 0; i--) { final int v = (col & 0xF); buf[i] = (char) ((v < 10) ? ('0' + v) : ('a' + v - 10)); col >>>= 4; } return new String(buf); }
java
public static String colorToString(int col) { final char[] buf = new char[] { '#', 'X', 'X', 'X', 'X', 'X', 'X' }; for(int i = 6; i > 0; i--) { final int v = (col & 0xF); buf[i] = (char) ((v < 10) ? ('0' + v) : ('a' + v - 10)); col >>>= 4; } return new String(buf); }
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Convert a color name from an integer RGB color to CSS syntax Note: currently only RGB (from ARGB order) are supported. The alpha channel will be ignored. @param col Color value @return Color string
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java#L557-L565
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java
SVGUtil.elementCoordinatesFromEvent
public static SVGPoint elementCoordinatesFromEvent(Document doc, Element tag, Event evt) { try { DOMMouseEvent gnme = (DOMMouseEvent) evt; SVGMatrix mat = ((SVGLocatable) tag).getScreenCTM(); SVGMatrix imat = mat.inverse(); SVGPoint cPt = ((SVGDocument) doc).getRootElement().createSVGPoint(); cPt.setX(gnme.getClientX()); cPt.setY(gnme.getClientY()); return cPt.matrixTransform(imat); } catch(Exception e) { LoggingUtil.warning("Error getting coordinates from SVG event.", e); return null; } }
java
public static SVGPoint elementCoordinatesFromEvent(Document doc, Element tag, Event evt) { try { DOMMouseEvent gnme = (DOMMouseEvent) evt; SVGMatrix mat = ((SVGLocatable) tag).getScreenCTM(); SVGMatrix imat = mat.inverse(); SVGPoint cPt = ((SVGDocument) doc).getRootElement().createSVGPoint(); cPt.setX(gnme.getClientX()); cPt.setY(gnme.getClientY()); return cPt.matrixTransform(imat); } catch(Exception e) { LoggingUtil.warning("Error getting coordinates from SVG event.", e); return null; } }
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Convert the coordinates of an DOM Event from screen into element coordinates. @param doc Document context @param tag Element containing the coordinate system @param evt Event to interpret @return coordinates
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java#L627-L641
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java
SVGUtil.removeLastChild
public static void removeLastChild(Element tag) { final Node last = tag.getLastChild(); if(last != null) { tag.removeChild(last); } }
java
public static void removeLastChild(Element tag) { final Node last = tag.getLastChild(); if(last != null) { tag.removeChild(last); } }
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Remove last child of an element, when present @param tag Parent
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java#L648-L653
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java
SVGUtil.removeFromParent
public static void removeFromParent(Element elem) { if(elem != null && elem.getParentNode() != null) { elem.getParentNode().removeChild(elem); } }
java
public static void removeFromParent(Element elem) { if(elem != null && elem.getParentNode() != null) { elem.getParentNode().removeChild(elem); } }
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Remove an element from its parent, if defined. @param elem Element to remove
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java#L660-L664
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java
SVGUtil.svgCircleSegment
public static Element svgCircleSegment(SVGPlot svgp, double centerx, double centery, double angleStart, double angleDelta, double innerRadius, double outerRadius) { final DoubleWrapper tmp = new DoubleWrapper(); // To return cosine double sin1st = FastMath.sinAndCos(angleStart, tmp); double cos1st = tmp.value; double sin2nd = FastMath.sinAndCos(angleStart + angleDelta, tmp); double cos2nd = tmp.value; // Note: tmp is modified! double inner1stx = centerx + (innerRadius * sin1st); double inner1sty = centery - (innerRadius * cos1st); double outer1stx = centerx + (outerRadius * sin1st); double outer1sty = centery - (outerRadius * cos1st); double inner2ndx = centerx + (innerRadius * sin2nd); double inner2ndy = centery - (innerRadius * cos2nd); double outer2ndx = centerx + (outerRadius * sin2nd); double outer2ndy = centery - (outerRadius * cos2nd); double largeArc = angleDelta >= Math.PI ? 1 : 0; SVGPath path = new SVGPath(inner1stx, inner1sty).lineTo(outer1stx, outer1sty) // .ellipticalArc(outerRadius, outerRadius, 0, largeArc, 1, outer2ndx, outer2ndy) // .lineTo(inner2ndx, inner2ndy); if(innerRadius > 0) { path.ellipticalArc(innerRadius, innerRadius, 0, largeArc, 0, inner1stx, inner1sty); } return path.makeElement(svgp); }
java
public static Element svgCircleSegment(SVGPlot svgp, double centerx, double centery, double angleStart, double angleDelta, double innerRadius, double outerRadius) { final DoubleWrapper tmp = new DoubleWrapper(); // To return cosine double sin1st = FastMath.sinAndCos(angleStart, tmp); double cos1st = tmp.value; double sin2nd = FastMath.sinAndCos(angleStart + angleDelta, tmp); double cos2nd = tmp.value; // Note: tmp is modified! double inner1stx = centerx + (innerRadius * sin1st); double inner1sty = centery - (innerRadius * cos1st); double outer1stx = centerx + (outerRadius * sin1st); double outer1sty = centery - (outerRadius * cos1st); double inner2ndx = centerx + (innerRadius * sin2nd); double inner2ndy = centery - (innerRadius * cos2nd); double outer2ndx = centerx + (outerRadius * sin2nd); double outer2ndy = centery - (outerRadius * cos2nd); double largeArc = angleDelta >= Math.PI ? 1 : 0; SVGPath path = new SVGPath(inner1stx, inner1sty).lineTo(outer1stx, outer1sty) // .ellipticalArc(outerRadius, outerRadius, 0, largeArc, 1, outer2ndx, outer2ndy) // .lineTo(inner2ndx, inner2ndy); if(innerRadius > 0) { path.ellipticalArc(innerRadius, innerRadius, 0, largeArc, 0, inner1stx, inner1sty); } return path.makeElement(svgp); }
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Create a circle segment. @param svgp Plot to draw to @param centerx Center X position @param centery Center Y position @param angleStart Starting angle @param angleDelta Angle delta @param innerRadius inner radius @param outerRadius outer radius @return SVG element representing this circle segment
[ "Create", "a", "circle", "segment", "." ]
b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGUtil.java#L678-L705
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/hierarchical/AbstractHDBSCAN.java
AbstractHDBSCAN.computeCoreDists
protected WritableDoubleDataStore computeCoreDists(DBIDs ids, KNNQuery<O> knnQ, int minPts) { final Logging LOG = getLogger(); final WritableDoubleDataStore coredists = DataStoreUtil.makeDoubleStorage(ids, DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_DB); FiniteProgress cprog = LOG.isVerbose() ? new FiniteProgress("Computing core sizes", ids.size(), LOG) : null; for(DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) { coredists.put(iter, knnQ.getKNNForDBID(iter, minPts).getKNNDistance()); LOG.incrementProcessed(cprog); } LOG.ensureCompleted(cprog); return coredists; }
java
protected WritableDoubleDataStore computeCoreDists(DBIDs ids, KNNQuery<O> knnQ, int minPts) { final Logging LOG = getLogger(); final WritableDoubleDataStore coredists = DataStoreUtil.makeDoubleStorage(ids, DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_DB); FiniteProgress cprog = LOG.isVerbose() ? new FiniteProgress("Computing core sizes", ids.size(), LOG) : null; for(DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) { coredists.put(iter, knnQ.getKNNForDBID(iter, minPts).getKNNDistance()); LOG.incrementProcessed(cprog); } LOG.ensureCompleted(cprog); return coredists; }
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Compute the core distances for all objects. @param ids Objects @param knnQ kNN query @param minPts Minimum neighborhood size @return Data store with core distances
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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/AbstractHDBSCAN.java#L91-L101
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/hierarchical/AbstractHDBSCAN.java
AbstractHDBSCAN.convertToPointerRepresentation
protected void convertToPointerRepresentation(ArrayDBIDs ids, DoubleLongHeap heap, WritableDBIDDataStore pi, WritableDoubleDataStore lambda) { final Logging LOG = getLogger(); // Initialize parent array: for(DBIDArrayIter iter = ids.iter(); iter.valid(); iter.advance()) { pi.put(iter, iter); // Initialize } DBIDVar p = DBIDUtil.newVar(), q = DBIDUtil.newVar(), n = DBIDUtil.newVar(); FiniteProgress pprog = LOG.isVerbose() ? new FiniteProgress("Converting MST to pointer representation", heap.size(), LOG) : null; while(!heap.isEmpty()) { final double dist = heap.peekKey(); final long pair = heap.peekValue(); final int i = (int) (pair >>> 31), j = (int) (pair & 0x7FFFFFFFL); ids.assignVar(i, p); // Follow p to its parent. while(!DBIDUtil.equal(p, pi.assignVar(p, n))) { p.set(n); } // Follow q to its parent. ids.assignVar(j, q); while(!DBIDUtil.equal(q, pi.assignVar(q, n))) { q.set(n); } // By definition of the pointer representation, the largest element in // each cluster is the cluster lead. // The extraction methods currently rely on this! int c = DBIDUtil.compare(p, q); if(c < 0) { // p joins q: pi.put(p, q); lambda.put(p, dist); } else { assert (c != 0) : "This should never happen!"; // q joins p: pi.put(q, p); lambda.put(q, dist); } heap.poll(); LOG.incrementProcessed(pprog); } LOG.ensureCompleted(pprog); // Hack to ensure a valid pointer representation: // If distances are tied, the heap may return edges such that the n-way join // does not fulfill the property that the last element has the largest id. for(DBIDArrayIter iter = ids.iter(); iter.valid(); iter.advance()) { double d = lambda.doubleValue(iter); // Parent: pi.assignVar(iter, p); q.set(p); // Follow parent while tied. while(d >= lambda.doubleValue(q) && !DBIDUtil.equal(q, pi.assignVar(q, n))) { q.set(n); } if(!DBIDUtil.equal(p, q)) { if(LOG.isDebuggingFinest()) { LOG.finest("Correcting parent: " + p + " -> " + q); } pi.put(iter, q); } } }
java
protected void convertToPointerRepresentation(ArrayDBIDs ids, DoubleLongHeap heap, WritableDBIDDataStore pi, WritableDoubleDataStore lambda) { final Logging LOG = getLogger(); // Initialize parent array: for(DBIDArrayIter iter = ids.iter(); iter.valid(); iter.advance()) { pi.put(iter, iter); // Initialize } DBIDVar p = DBIDUtil.newVar(), q = DBIDUtil.newVar(), n = DBIDUtil.newVar(); FiniteProgress pprog = LOG.isVerbose() ? new FiniteProgress("Converting MST to pointer representation", heap.size(), LOG) : null; while(!heap.isEmpty()) { final double dist = heap.peekKey(); final long pair = heap.peekValue(); final int i = (int) (pair >>> 31), j = (int) (pair & 0x7FFFFFFFL); ids.assignVar(i, p); // Follow p to its parent. while(!DBIDUtil.equal(p, pi.assignVar(p, n))) { p.set(n); } // Follow q to its parent. ids.assignVar(j, q); while(!DBIDUtil.equal(q, pi.assignVar(q, n))) { q.set(n); } // By definition of the pointer representation, the largest element in // each cluster is the cluster lead. // The extraction methods currently rely on this! int c = DBIDUtil.compare(p, q); if(c < 0) { // p joins q: pi.put(p, q); lambda.put(p, dist); } else { assert (c != 0) : "This should never happen!"; // q joins p: pi.put(q, p); lambda.put(q, dist); } heap.poll(); LOG.incrementProcessed(pprog); } LOG.ensureCompleted(pprog); // Hack to ensure a valid pointer representation: // If distances are tied, the heap may return edges such that the n-way join // does not fulfill the property that the last element has the largest id. for(DBIDArrayIter iter = ids.iter(); iter.valid(); iter.advance()) { double d = lambda.doubleValue(iter); // Parent: pi.assignVar(iter, p); q.set(p); // Follow parent while tied. while(d >= lambda.doubleValue(q) && !DBIDUtil.equal(q, pi.assignVar(q, n))) { q.set(n); } if(!DBIDUtil.equal(p, q)) { if(LOG.isDebuggingFinest()) { LOG.finest("Correcting parent: " + p + " -> " + q); } pi.put(iter, q); } } }
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Convert spanning tree to a pointer representation. Note: the heap must use the correct encoding of indexes. @param ids IDs indexed @param heap Heap @param pi Parent array @param lambda Distance array
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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/AbstractHDBSCAN.java#L214-L275
train
elki-project/elki
elki-core-dbids-int/src/main/java/de/lmu/ifi/dbs/elki/database/ids/integer/DoubleIntegerDBIDKNNHeap.java
DoubleIntegerDBIDKNNHeap.updateHeap
private void updateHeap(final double distance, final int iid) { final double prevdist = kdist; final int previd = heap.peekValue(); heap.replaceTopElement(distance, iid); kdist = heap.peekKey(); // If the kdist improved, zap ties. if(kdist < prevdist) { numties = 0; } else { addToTies(previd); } }
java
private void updateHeap(final double distance, final int iid) { final double prevdist = kdist; final int previd = heap.peekValue(); heap.replaceTopElement(distance, iid); kdist = heap.peekKey(); // If the kdist improved, zap ties. if(kdist < prevdist) { numties = 0; } else { addToTies(previd); } }
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Do a full update for the heap. @param distance Distance @param iid Object id
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-dbids-int/src/main/java/de/lmu/ifi/dbs/elki/database/ids/integer/DoubleIntegerDBIDKNNHeap.java#L145-L157
train
elki-project/elki
elki-core-dbids-int/src/main/java/de/lmu/ifi/dbs/elki/database/ids/integer/DoubleIntegerDBIDKNNHeap.java
DoubleIntegerDBIDKNNHeap.addToTies
private void addToTies(int id) { if(ties.length == numties) { ties = Arrays.copyOf(ties, (ties.length << 1) + 1); // grow. } ties[numties] = id; ++numties; }
java
private void addToTies(int id) { if(ties.length == numties) { ties = Arrays.copyOf(ties, (ties.length << 1) + 1); // grow. } ties[numties] = id; ++numties; }
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Ensure the ties array has capacity for at least one more element. @param id Id to add
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-dbids-int/src/main/java/de/lmu/ifi/dbs/elki/database/ids/integer/DoubleIntegerDBIDKNNHeap.java#L165-L171
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/quality/AbstractKMeansQualityMeasure.java
AbstractKMeansQualityMeasure.numberOfFreeParameters
public static int numberOfFreeParameters(Relation<? extends NumberVector> relation, Clustering<? extends MeanModel> clustering) { // number of clusters int m = clustering.getAllClusters().size(); // num_ctrs // dimensionality of data points int dim = RelationUtil.dimensionality(relation); // num_dims // number of free parameters return (m - 1) + m * dim + m; }
java
public static int numberOfFreeParameters(Relation<? extends NumberVector> relation, Clustering<? extends MeanModel> clustering) { // number of clusters int m = clustering.getAllClusters().size(); // num_ctrs // dimensionality of data points int dim = RelationUtil.dimensionality(relation); // num_dims // number of free parameters return (m - 1) + m * dim + m; }
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Compute the number of free parameters. @param relation Data relation (for dimensionality) @param clustering Set of clusters @return Number of free parameters
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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/quality/AbstractKMeansQualityMeasure.java#L181-L190
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/result/ClusteringVectorDumper.java
ClusteringVectorDumper.dumpClusteringOutput
protected void dumpClusteringOutput(PrintStream writer, ResultHierarchy hierarchy, Clustering<?> c) { DBIDRange ids = null; for(It<Relation<?>> iter = hierarchy.iterParents(c).filter(Relation.class); iter.valid(); iter.advance()) { DBIDs pids = iter.get().getDBIDs(); if(pids instanceof DBIDRange) { ids = (DBIDRange) pids; break; } LOG.warning("Parent result " + iter.get().getLongName() + " has DBID type " + pids.getClass()); } // Fallback: try to locate a database. if(ids == null) { for(It<Database> iter = hierarchy.iterAll().filter(Database.class); iter.valid(); iter.advance()) { DBIDs pids = iter.get().getRelation(TypeUtil.ANY).getDBIDs(); if(pids instanceof DBIDRange) { ids = (DBIDRange) pids; break; } LOG.warning("Parent result " + iter.get().getLongName() + " has DBID type " + pids.getClass()); } } if(ids == null) { LOG.warning("Cannot dump cluster assignment, as I do not have a well-defined DBIDRange to use for a unique column assignment. DBIDs must be a continuous range."); return; } WritableIntegerDataStore map = DataStoreUtil.makeIntegerStorage(ids, DataStoreFactory.HINT_TEMP); int cnum = 0; for(Cluster<?> clu : c.getAllClusters()) { for(DBIDIter iter = clu.getIDs().iter(); iter.valid(); iter.advance()) { map.putInt(iter, cnum); } ++cnum; } for(DBIDArrayIter iter = ids.iter(); iter.valid(); iter.advance()) { if(iter.getOffset() > 0) { writer.append(' '); } writer.append(Integer.toString(map.intValue(iter))); } if(forceLabel != null) { if(forceLabel.length() > 0) { writer.append(' ').append(forceLabel); } } else { writer.append(' ').append(c.getLongName()); } writer.append('\n'); }
java
protected void dumpClusteringOutput(PrintStream writer, ResultHierarchy hierarchy, Clustering<?> c) { DBIDRange ids = null; for(It<Relation<?>> iter = hierarchy.iterParents(c).filter(Relation.class); iter.valid(); iter.advance()) { DBIDs pids = iter.get().getDBIDs(); if(pids instanceof DBIDRange) { ids = (DBIDRange) pids; break; } LOG.warning("Parent result " + iter.get().getLongName() + " has DBID type " + pids.getClass()); } // Fallback: try to locate a database. if(ids == null) { for(It<Database> iter = hierarchy.iterAll().filter(Database.class); iter.valid(); iter.advance()) { DBIDs pids = iter.get().getRelation(TypeUtil.ANY).getDBIDs(); if(pids instanceof DBIDRange) { ids = (DBIDRange) pids; break; } LOG.warning("Parent result " + iter.get().getLongName() + " has DBID type " + pids.getClass()); } } if(ids == null) { LOG.warning("Cannot dump cluster assignment, as I do not have a well-defined DBIDRange to use for a unique column assignment. DBIDs must be a continuous range."); return; } WritableIntegerDataStore map = DataStoreUtil.makeIntegerStorage(ids, DataStoreFactory.HINT_TEMP); int cnum = 0; for(Cluster<?> clu : c.getAllClusters()) { for(DBIDIter iter = clu.getIDs().iter(); iter.valid(); iter.advance()) { map.putInt(iter, cnum); } ++cnum; } for(DBIDArrayIter iter = ids.iter(); iter.valid(); iter.advance()) { if(iter.getOffset() > 0) { writer.append(' '); } writer.append(Integer.toString(map.intValue(iter))); } if(forceLabel != null) { if(forceLabel.length() > 0) { writer.append(' ').append(forceLabel); } } else { writer.append(' ').append(c.getLongName()); } writer.append('\n'); }
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Dump a single clustering result. @param writer Output writer @param hierarchy Cluster hierarchy to process @param c Clustering result
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/result/ClusteringVectorDumper.java#L145-L194
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/CovarianceMatrix.java
CovarianceMatrix.getMeanVector
public <F extends NumberVector> F getMeanVector(Relation<? extends F> relation) { return RelationUtil.getNumberVectorFactory(relation).newNumberVector(mean); }
java
public <F extends NumberVector> F getMeanVector(Relation<? extends F> relation) { return RelationUtil.getNumberVectorFactory(relation).newNumberVector(mean); }
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Get the mean as vector. @param relation Data relation @param <F> vector type @return Mean vector
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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/CovarianceMatrix.java#L258-L260
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/CovarianceMatrix.java
CovarianceMatrix.reset
public void reset() { Arrays.fill(mean, 0.); Arrays.fill(nmea, 0.); if(elements != null) { for(int i = 0; i < elements.length; i++) { Arrays.fill(elements[i], 0.); } } else { elements = new double[mean.length][mean.length]; } wsum = 0.; }
java
public void reset() { Arrays.fill(mean, 0.); Arrays.fill(nmea, 0.); if(elements != null) { for(int i = 0; i < elements.length; i++) { Arrays.fill(elements[i], 0.); } } else { elements = new double[mean.length][mean.length]; } wsum = 0.; }
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Reset the covariance matrix. This function <em>may</em> be called after a "destroy".
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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/CovarianceMatrix.java#L335-L347
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/CovarianceMatrix.java
CovarianceMatrix.make
public static CovarianceMatrix make(Relation<? extends NumberVector> relation) { int dim = RelationUtil.dimensionality(relation); CovarianceMatrix c = new CovarianceMatrix(dim); double[] mean = c.mean; int count = 0; // Compute mean first: for(DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) { NumberVector vec = relation.get(iditer); for(int i = 0; i < dim; i++) { mean[i] += vec.doubleValue(i); } count++; } if(count == 0) { return c; } // Normalize mean for(int i = 0; i < dim; i++) { mean[i] /= count; } // Compute covariances second // Two-pass approach is numerically okay and fast, when possible. double[] tmp = c.nmea; // Scratch space double[][] elems = c.elements; for(DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) { NumberVector vec = relation.get(iditer); for(int i = 0; i < dim; i++) { tmp[i] = vec.doubleValue(i) - mean[i]; } for(int i = 0; i < dim; i++) { for(int j = i; j < dim; j++) { elems[i][j] += tmp[i] * tmp[j]; } } } // Restore symmetry. for(int i = 0; i < dim; i++) { for(int j = i + 1; j < dim; j++) { elems[j][i] = elems[i][j]; } } c.wsum = count; return c; }
java
public static CovarianceMatrix make(Relation<? extends NumberVector> relation) { int dim = RelationUtil.dimensionality(relation); CovarianceMatrix c = new CovarianceMatrix(dim); double[] mean = c.mean; int count = 0; // Compute mean first: for(DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) { NumberVector vec = relation.get(iditer); for(int i = 0; i < dim; i++) { mean[i] += vec.doubleValue(i); } count++; } if(count == 0) { return c; } // Normalize mean for(int i = 0; i < dim; i++) { mean[i] /= count; } // Compute covariances second // Two-pass approach is numerically okay and fast, when possible. double[] tmp = c.nmea; // Scratch space double[][] elems = c.elements; for(DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) { NumberVector vec = relation.get(iditer); for(int i = 0; i < dim; i++) { tmp[i] = vec.doubleValue(i) - mean[i]; } for(int i = 0; i < dim; i++) { for(int j = i; j < dim; j++) { elems[i][j] += tmp[i] * tmp[j]; } } } // Restore symmetry. for(int i = 0; i < dim; i++) { for(int j = i + 1; j < dim; j++) { elems[j][i] = elems[i][j]; } } c.wsum = count; return c; }
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Static Constructor from a full relation. @param relation Relation to use. @return Covariance matrix
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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/CovarianceMatrix.java#L355-L398
train
elki-project/elki
elki-logging/src/main/java/de/lmu/ifi/dbs/elki/logging/progress/FiniteProgress.java
FiniteProgress.appendToBuffer
@Override public StringBuilder appendToBuffer(StringBuilder buf) { String processedString = Integer.toString(getProcessed()); int percentage = (int) (getProcessed() * 100.0 / total); buf.append(getTask()); buf.append(": "); for(int i = 0; i < totalLength - processedString.length(); i++) { buf.append(' '); } buf.append(getProcessed()); buf.append(" ["); if(percentage < 100) { buf.append(' '); } if(percentage < 10) { buf.append(' '); } buf.append(percentage); buf.append("%]"); if(ratems > 0. && getProcessed() < total) { buf.append(' '); int secs = (int) Math.round((total - getProcessed()) / ratems / 1000. + .2); if(secs > 300) { buf.append(secs / 60); buf.append(" min remaining"); } else { buf.append(secs); buf.append(" sec remaining"); } } return buf; }
java
@Override public StringBuilder appendToBuffer(StringBuilder buf) { String processedString = Integer.toString(getProcessed()); int percentage = (int) (getProcessed() * 100.0 / total); buf.append(getTask()); buf.append(": "); for(int i = 0; i < totalLength - processedString.length(); i++) { buf.append(' '); } buf.append(getProcessed()); buf.append(" ["); if(percentage < 100) { buf.append(' '); } if(percentage < 10) { buf.append(' '); } buf.append(percentage); buf.append("%]"); if(ratems > 0. && getProcessed() < total) { buf.append(' '); int secs = (int) Math.round((total - getProcessed()) / ratems / 1000. + .2); if(secs > 300) { buf.append(secs / 60); buf.append(" min remaining"); } else { buf.append(secs); buf.append(" sec remaining"); } } return buf; }
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Append a string representation of the progress to the given string buffer. @param buf Buffer to serialize to @return Buffer the data was serialized to.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-logging/src/main/java/de/lmu/ifi/dbs/elki/logging/progress/FiniteProgress.java#L97-L129
train
elki-project/elki
elki-logging/src/main/java/de/lmu/ifi/dbs/elki/logging/progress/FiniteProgress.java
FiniteProgress.ensureCompleted
public void ensureCompleted(Logging logger) { if(!isComplete()) { logger.warning("Progress had not completed automatically as expected: " + getProcessed() + "/" + total, new Throwable()); setProcessed(getTotal()); logger.progress(this); } }
java
public void ensureCompleted(Logging logger) { if(!isComplete()) { logger.warning("Progress had not completed automatically as expected: " + getProcessed() + "/" + total, new Throwable()); setProcessed(getTotal()); logger.progress(this); } }
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Ensure that the progress was completed, to make progress bars disappear @param logger Logger to report to.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-logging/src/main/java/de/lmu/ifi/dbs/elki/logging/progress/FiniteProgress.java#L153-L159
train
elki-project/elki
elki-outlier/src/main/java/de/lmu/ifi/dbs/elki/algorithm/outlier/DWOF.java
DWOF.clusterData
private void clusterData(DBIDs ids, RangeQuery<O> rnnQuery, WritableDoubleDataStore radii, WritableDataStore<ModifiableDBIDs> labels) { FiniteProgress clustProg = LOG.isVerbose() ? new FiniteProgress("Density-Based Clustering", ids.size(), LOG) : null; // Iterate over all objects for(DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) { if(labels.get(iter) != null) { continue; } ModifiableDBIDs newCluster = DBIDUtil.newArray(); newCluster.add(iter); labels.put(iter, newCluster); LOG.incrementProcessed(clustProg); // container of the points to be added and their radii neighbors to the // cluster ModifiableDBIDs nChain = DBIDUtil.newArray(); nChain.add(iter); // iterate over nChain for(DBIDIter toGetNeighbors = nChain.iter(); toGetNeighbors.valid(); toGetNeighbors.advance()) { double range = radii.doubleValue(toGetNeighbors); DoubleDBIDList nNeighbors = rnnQuery.getRangeForDBID(toGetNeighbors, range); for(DoubleDBIDListIter iter2 = nNeighbors.iter(); iter2.valid(); iter2.advance()) { if(DBIDUtil.equal(toGetNeighbors, iter2)) { continue; } if(labels.get(iter2) == null) { newCluster.add(iter2); labels.put(iter2, newCluster); nChain.add(iter2); LOG.incrementProcessed(clustProg); } else if(labels.get(iter2) != newCluster) { ModifiableDBIDs toBeDeleted = labels.get(iter2); newCluster.addDBIDs(toBeDeleted); for(DBIDIter iter3 = toBeDeleted.iter(); iter3.valid(); iter3.advance()) { labels.put(iter3, newCluster); } toBeDeleted.clear(); } } } } LOG.ensureCompleted(clustProg); }
java
private void clusterData(DBIDs ids, RangeQuery<O> rnnQuery, WritableDoubleDataStore radii, WritableDataStore<ModifiableDBIDs> labels) { FiniteProgress clustProg = LOG.isVerbose() ? new FiniteProgress("Density-Based Clustering", ids.size(), LOG) : null; // Iterate over all objects for(DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) { if(labels.get(iter) != null) { continue; } ModifiableDBIDs newCluster = DBIDUtil.newArray(); newCluster.add(iter); labels.put(iter, newCluster); LOG.incrementProcessed(clustProg); // container of the points to be added and their radii neighbors to the // cluster ModifiableDBIDs nChain = DBIDUtil.newArray(); nChain.add(iter); // iterate over nChain for(DBIDIter toGetNeighbors = nChain.iter(); toGetNeighbors.valid(); toGetNeighbors.advance()) { double range = radii.doubleValue(toGetNeighbors); DoubleDBIDList nNeighbors = rnnQuery.getRangeForDBID(toGetNeighbors, range); for(DoubleDBIDListIter iter2 = nNeighbors.iter(); iter2.valid(); iter2.advance()) { if(DBIDUtil.equal(toGetNeighbors, iter2)) { continue; } if(labels.get(iter2) == null) { newCluster.add(iter2); labels.put(iter2, newCluster); nChain.add(iter2); LOG.incrementProcessed(clustProg); } else if(labels.get(iter2) != newCluster) { ModifiableDBIDs toBeDeleted = labels.get(iter2); newCluster.addDBIDs(toBeDeleted); for(DBIDIter iter3 = toBeDeleted.iter(); iter3.valid(); iter3.advance()) { labels.put(iter3, newCluster); } toBeDeleted.clear(); } } } } LOG.ensureCompleted(clustProg); }
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This method applies a density based clustering algorithm. It looks for an unclustered object and builds a new cluster for it, then adds all the points within its radius to that cluster. nChain represents the points to be added to the cluster and its radius-neighbors @param ids Database IDs to process @param rnnQuery Data to process @param radii Radii to cluster accordingly @param labels Label storage.
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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/DWOF.java#L242-L283
train
elki-project/elki
elki-outlier/src/main/java/de/lmu/ifi/dbs/elki/algorithm/outlier/DWOF.java
DWOF.updateSizes
private int updateSizes(DBIDs ids, WritableDataStore<ModifiableDBIDs> labels, WritableIntegerDataStore newSizes) { // to count the unclustered all over int countUnmerged = 0; for(DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) { // checking the point's new cluster size after the clustering step int newClusterSize = labels.get(iter).size(); newSizes.putInt(iter, newClusterSize); // the point is alone in the cluster --> not merged with other points if(newClusterSize == 1) { countUnmerged++; } } return countUnmerged; }
java
private int updateSizes(DBIDs ids, WritableDataStore<ModifiableDBIDs> labels, WritableIntegerDataStore newSizes) { // to count the unclustered all over int countUnmerged = 0; for(DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) { // checking the point's new cluster size after the clustering step int newClusterSize = labels.get(iter).size(); newSizes.putInt(iter, newClusterSize); // the point is alone in the cluster --> not merged with other points if(newClusterSize == 1) { countUnmerged++; } } return countUnmerged; }
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This method updates each object's cluster size after the clustering step. @param ids Object IDs to process @param labels references for each object's cluster @param newSizes the sizes container to be updated @return the number of unclustered objects
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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/DWOF.java#L293-L306
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/hierarchical/SLINK.java
SLINK.run
public PointerHierarchyRepresentationResult run(Database database, Relation<O> relation) { DBIDs ids = relation.getDBIDs(); WritableDBIDDataStore pi = DataStoreUtil.makeDBIDStorage(ids, DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_STATIC); WritableDoubleDataStore lambda = DataStoreUtil.makeDoubleStorage(ids, DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_STATIC, Double.POSITIVE_INFINITY); // Temporary storage for m. WritableDoubleDataStore m = DataStoreUtil.makeDoubleStorage(ids, DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_TEMP); final Logging log = getLogger(); // To allow CLINK logger override FiniteProgress progress = log.isVerbose() ? new FiniteProgress("Running SLINK", ids.size(), log) : null; ArrayDBIDs aids = DBIDUtil.ensureArray(ids); // First element is trivial/special: DBIDArrayIter id = aids.iter(), it = aids.iter(); // Step 1: initialize for(; id.valid(); id.advance()) { // P(n+1) = n+1: pi.put(id, id); // L(n+1) = infinity already. } // First element is finished already (start at seek(1) below!) log.incrementProcessed(progress); // Optimized branch if(getDistanceFunction() instanceof PrimitiveDistanceFunction) { PrimitiveDistanceFunction<? super O> distf = (PrimitiveDistanceFunction<? super O>) getDistanceFunction(); for(id.seek(1); id.valid(); id.advance()) { step2primitive(id, it, id.getOffset(), relation, distf, m); process(id, aids, it, id.getOffset(), pi, lambda, m); // SLINK or CLINK log.incrementProcessed(progress); } } else { // Fallback branch DistanceQuery<O> distQ = database.getDistanceQuery(relation, getDistanceFunction()); for(id.seek(1); id.valid(); id.advance()) { step2(id, it, id.getOffset(), distQ, m); process(id, aids, it, id.getOffset(), pi, lambda, m); // SLINK or CLINK log.incrementProcessed(progress); } } log.ensureCompleted(progress); // We don't need m anymore. m.destroy(); m = null; return new PointerHierarchyRepresentationResult(ids, pi, lambda, getDistanceFunction().isSquared()); }
java
public PointerHierarchyRepresentationResult run(Database database, Relation<O> relation) { DBIDs ids = relation.getDBIDs(); WritableDBIDDataStore pi = DataStoreUtil.makeDBIDStorage(ids, DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_STATIC); WritableDoubleDataStore lambda = DataStoreUtil.makeDoubleStorage(ids, DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_STATIC, Double.POSITIVE_INFINITY); // Temporary storage for m. WritableDoubleDataStore m = DataStoreUtil.makeDoubleStorage(ids, DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_TEMP); final Logging log = getLogger(); // To allow CLINK logger override FiniteProgress progress = log.isVerbose() ? new FiniteProgress("Running SLINK", ids.size(), log) : null; ArrayDBIDs aids = DBIDUtil.ensureArray(ids); // First element is trivial/special: DBIDArrayIter id = aids.iter(), it = aids.iter(); // Step 1: initialize for(; id.valid(); id.advance()) { // P(n+1) = n+1: pi.put(id, id); // L(n+1) = infinity already. } // First element is finished already (start at seek(1) below!) log.incrementProcessed(progress); // Optimized branch if(getDistanceFunction() instanceof PrimitiveDistanceFunction) { PrimitiveDistanceFunction<? super O> distf = (PrimitiveDistanceFunction<? super O>) getDistanceFunction(); for(id.seek(1); id.valid(); id.advance()) { step2primitive(id, it, id.getOffset(), relation, distf, m); process(id, aids, it, id.getOffset(), pi, lambda, m); // SLINK or CLINK log.incrementProcessed(progress); } } else { // Fallback branch DistanceQuery<O> distQ = database.getDistanceQuery(relation, getDistanceFunction()); for(id.seek(1); id.valid(); id.advance()) { step2(id, it, id.getOffset(), distQ, m); process(id, aids, it, id.getOffset(), pi, lambda, m); // SLINK or CLINK log.incrementProcessed(progress); } } log.ensureCompleted(progress); // We don't need m anymore. m.destroy(); m = null; return new PointerHierarchyRepresentationResult(ids, pi, lambda, getDistanceFunction().isSquared()); }
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Performs the SLINK algorithm on the given database. @param database Database to process @param relation Data relation to use
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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/SLINK.java#L101-L149
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/hierarchical/SLINK.java
SLINK.process
protected void process(DBIDRef id, ArrayDBIDs ids, DBIDArrayIter it, int n, WritableDBIDDataStore pi, WritableDoubleDataStore lambda, WritableDoubleDataStore m) { slinkstep3(id, it, n, pi, lambda, m); slinkstep4(id, it, n, pi, lambda); }
java
protected void process(DBIDRef id, ArrayDBIDs ids, DBIDArrayIter it, int n, WritableDBIDDataStore pi, WritableDoubleDataStore lambda, WritableDoubleDataStore m) { slinkstep3(id, it, n, pi, lambda, m); slinkstep4(id, it, n, pi, lambda); }
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SLINK main loop. @param id Current object @param ids All objects @param it Array iterator @param n Last object to process at this run @param pi Parent @param lambda Height @param m Distance
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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/SLINK.java#L200-L203
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/optics/ClusterOrder.java
ClusterOrder.add
public void add(DBIDRef id, double reach, DBIDRef pre) { ids.add(id); reachability.putDouble(id, reach); if(pre == null || pre instanceof DBIDVar && !((DBIDVar) pre).isSet()) { return; } predecessor.putDBID(id, pre); }
java
public void add(DBIDRef id, double reach, DBIDRef pre) { ids.add(id); reachability.putDouble(id, reach); if(pre == null || pre instanceof DBIDVar && !((DBIDVar) pre).isSet()) { return; } predecessor.putDBID(id, pre); }
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Add an object to the cluster order. @param id Object id @param reach Reachability @param pre Predecessor
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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/optics/ClusterOrder.java#L111-L118
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/optics/ClusterOrder.java
ClusterOrder.order
@Override public ArrayModifiableDBIDs order(DBIDs ids) { ArrayModifiableDBIDs res = DBIDUtil.newArray(ids.size()); for(DBIDIter it = this.ids.iter(); it.valid(); it.advance()) { if(ids.contains(it)) { res.add(it); } } return res; }
java
@Override public ArrayModifiableDBIDs order(DBIDs ids) { ArrayModifiableDBIDs res = DBIDUtil.newArray(ids.size()); for(DBIDIter it = this.ids.iter(); it.valid(); it.advance()) { if(ids.contains(it)) { res.add(it); } } return res; }
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Use the cluster order to sort the given collection ids. Implementation of the {@link OrderingResult} interface.
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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/optics/ClusterOrder.java#L137-L146
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/optics/ClusterOrder.java
ClusterOrder.getPredecessor
public void getPredecessor(DBIDRef id, DBIDVar out) { if(predecessor == null) { out.unset(); return; } predecessor.assignVar(id, out); }
java
public void getPredecessor(DBIDRef id, DBIDVar out) { if(predecessor == null) { out.unset(); return; } predecessor.assignVar(id, out); }
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Get the predecessor. @param id Current id. @param out Output variable to store the predecessor.
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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/optics/ClusterOrder.java#L173-L179
train
elki-project/elki
elki-outlier/src/main/java/de/lmu/ifi/dbs/elki/algorithm/outlier/lof/COF.java
COF.run
public OutlierResult run(Database database, Relation<O> relation) { StepProgress stepprog = LOG.isVerbose() ? new StepProgress("COF", 3) : null; DistanceQuery<O> dq = database.getDistanceQuery(relation, getDistanceFunction()); LOG.beginStep(stepprog, 1, "Materializing COF neighborhoods."); KNNQuery<O> knnq = DatabaseUtil.precomputedKNNQuery(database, relation, dq, k); DBIDs ids = relation.getDBIDs(); LOG.beginStep(stepprog, 2, "Computing Average Chaining Distances."); WritableDoubleDataStore acds = DataStoreUtil.makeDoubleStorage(ids, DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_TEMP); computeAverageChainingDistances(knnq, dq, ids, acds); // compute COF_SCORE of each db object LOG.beginStep(stepprog, 3, "Computing Connectivity-based Outlier Factors."); WritableDoubleDataStore cofs = DataStoreUtil.makeDoubleStorage(ids, DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_DB); // track the maximum value for normalization. DoubleMinMax cofminmax = new DoubleMinMax(); computeCOFScores(knnq, ids, acds, cofs, cofminmax); LOG.setCompleted(stepprog); // Build result representation. DoubleRelation scoreResult = new MaterializedDoubleRelation("Connectivity-Based Outlier Factor", "cof-outlier", cofs, ids); OutlierScoreMeta scoreMeta = new QuotientOutlierScoreMeta(cofminmax.getMin(), cofminmax.getMax(), 0.0, Double.POSITIVE_INFINITY, 1.0); return new OutlierResult(scoreMeta, scoreResult); }
java
public OutlierResult run(Database database, Relation<O> relation) { StepProgress stepprog = LOG.isVerbose() ? new StepProgress("COF", 3) : null; DistanceQuery<O> dq = database.getDistanceQuery(relation, getDistanceFunction()); LOG.beginStep(stepprog, 1, "Materializing COF neighborhoods."); KNNQuery<O> knnq = DatabaseUtil.precomputedKNNQuery(database, relation, dq, k); DBIDs ids = relation.getDBIDs(); LOG.beginStep(stepprog, 2, "Computing Average Chaining Distances."); WritableDoubleDataStore acds = DataStoreUtil.makeDoubleStorage(ids, DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_TEMP); computeAverageChainingDistances(knnq, dq, ids, acds); // compute COF_SCORE of each db object LOG.beginStep(stepprog, 3, "Computing Connectivity-based Outlier Factors."); WritableDoubleDataStore cofs = DataStoreUtil.makeDoubleStorage(ids, DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_DB); // track the maximum value for normalization. DoubleMinMax cofminmax = new DoubleMinMax(); computeCOFScores(knnq, ids, acds, cofs, cofminmax); LOG.setCompleted(stepprog); // Build result representation. DoubleRelation scoreResult = new MaterializedDoubleRelation("Connectivity-Based Outlier Factor", "cof-outlier", cofs, ids); OutlierScoreMeta scoreMeta = new QuotientOutlierScoreMeta(cofminmax.getMin(), cofminmax.getMax(), 0.0, Double.POSITIVE_INFINITY, 1.0); return new OutlierResult(scoreMeta, scoreResult); }
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Runs the COF algorithm on the given database. @param database Database to query @param relation Data to process @return COF outlier result
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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/COF.java#L104-L128
train
elki-project/elki
elki-outlier/src/main/java/de/lmu/ifi/dbs/elki/algorithm/outlier/lof/COF.java
COF.computeCOFScores
private void computeCOFScores(KNNQuery<O> knnq, DBIDs ids, DoubleDataStore acds, WritableDoubleDataStore cofs, DoubleMinMax cofminmax) { FiniteProgress progressCOFs = LOG.isVerbose() ? new FiniteProgress("COF for objects", ids.size(), LOG) : null; for(DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) { final KNNList neighbors = knnq.getKNNForDBID(iter, k); // Aggregate the average chaining distances of all neighbors: double sum = 0.; for(DBIDIter neighbor = neighbors.iter(); neighbor.valid(); neighbor.advance()) { // skip the point itself if(DBIDUtil.equal(neighbor, iter)) { continue; } sum += acds.doubleValue(neighbor); } final double cof = (sum > 0.) ? (acds.doubleValue(iter) * k / sum) : (acds.doubleValue(iter) > 0. ? Double.POSITIVE_INFINITY : 1.); cofs.putDouble(iter, cof); // update minimum and maximum cofminmax.put(cof); LOG.incrementProcessed(progressCOFs); } LOG.ensureCompleted(progressCOFs); }
java
private void computeCOFScores(KNNQuery<O> knnq, DBIDs ids, DoubleDataStore acds, WritableDoubleDataStore cofs, DoubleMinMax cofminmax) { FiniteProgress progressCOFs = LOG.isVerbose() ? new FiniteProgress("COF for objects", ids.size(), LOG) : null; for(DBIDIter iter = ids.iter(); iter.valid(); iter.advance()) { final KNNList neighbors = knnq.getKNNForDBID(iter, k); // Aggregate the average chaining distances of all neighbors: double sum = 0.; for(DBIDIter neighbor = neighbors.iter(); neighbor.valid(); neighbor.advance()) { // skip the point itself if(DBIDUtil.equal(neighbor, iter)) { continue; } sum += acds.doubleValue(neighbor); } final double cof = (sum > 0.) ? (acds.doubleValue(iter) * k / sum) : (acds.doubleValue(iter) > 0. ? Double.POSITIVE_INFINITY : 1.); cofs.putDouble(iter, cof); // update minimum and maximum cofminmax.put(cof); LOG.incrementProcessed(progressCOFs); } LOG.ensureCompleted(progressCOFs); }
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Compute Connectivity outlier factors. @param knnq KNN query @param ids IDs to process @param acds Average chaining distances @param cofs Connectivity outlier factor storage @param cofminmax Score minimum/maximum tracker
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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/COF.java#L203-L224
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/UpdateRunner.java
UpdateRunner.invokeLater
public void invokeLater(Runnable r) { queue.add(r); synchronized(this) { if(synchronizer == null) { runQueue(); } else { synchronizer.activate(); } } }
java
public void invokeLater(Runnable r) { queue.add(r); synchronized(this) { if(synchronizer == null) { runQueue(); } else { synchronizer.activate(); } } }
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Add a new update to run at any appropriate time. @param r New runnable to perform the update
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/UpdateRunner.java#L67-L77
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/UpdateRunner.java
UpdateRunner.runQueue
public void runQueue() { synchronized(sync) { while(!queue.isEmpty()) { Runnable r = queue.poll(); if(r != null) { try { r.run(); } catch(Exception e) { // Alternatively, we could allow the specification of exception // handlers for each runnable in the API. For now we'll just log. // TODO: handle exceptions here better! LoggingUtil.exception(e); } } else { LoggingUtil.warning("Tried to run a 'null' Object."); } } } }
java
public void runQueue() { synchronized(sync) { while(!queue.isEmpty()) { Runnable r = queue.poll(); if(r != null) { try { r.run(); } catch(Exception e) { // Alternatively, we could allow the specification of exception // handlers for each runnable in the API. For now we'll just log. // TODO: handle exceptions here better! LoggingUtil.exception(e); } } else { LoggingUtil.warning("Tried to run a 'null' Object."); } } } }
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Run the processing queue now. This should usually be only invoked by the UpdateSynchronizer
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/UpdateRunner.java#L83-L103
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/UpdateRunner.java
UpdateRunner.synchronizeWith
public synchronized void synchronizeWith(UpdateSynchronizer newsync) { // LoggingUtil.warning("Synchronizing: " + sync + " " + newsync, new // Throwable()); if(synchronizer == newsync) { LoggingUtil.warning("Double-synced to the same plot!", new Throwable()); return; } if(synchronizer != null) { LoggingUtil.warning("Attempting to synchronize to more than one synchronizer."); return; } synchronizer = newsync; newsync.addUpdateRunner(this); }
java
public synchronized void synchronizeWith(UpdateSynchronizer newsync) { // LoggingUtil.warning("Synchronizing: " + sync + " " + newsync, new // Throwable()); if(synchronizer == newsync) { LoggingUtil.warning("Double-synced to the same plot!", new Throwable()); return; } if(synchronizer != null) { LoggingUtil.warning("Attempting to synchronize to more than one synchronizer."); return; } synchronizer = newsync; newsync.addUpdateRunner(this); }
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Set a new update synchronizer. @param newsync Update synchronizer
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/UpdateRunner.java#L126-L139
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/UpdateRunner.java
UpdateRunner.unsynchronizeWith
public synchronized void unsynchronizeWith(UpdateSynchronizer oldsync) { if(synchronizer == null) { LoggingUtil.warning("Warning: was not synchronized."); return; } if(synchronizer != oldsync) { LoggingUtil.warning("Warning: was synchronized differently!"); return; } // LoggingUtil.warning("Unsynchronizing: " + sync + " " + oldsync); synchronizer = null; runQueue(); }
java
public synchronized void unsynchronizeWith(UpdateSynchronizer oldsync) { if(synchronizer == null) { LoggingUtil.warning("Warning: was not synchronized."); return; } if(synchronizer != oldsync) { LoggingUtil.warning("Warning: was synchronized differently!"); return; } // LoggingUtil.warning("Unsynchronizing: " + sync + " " + oldsync); synchronizer = null; runQueue(); }
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Remove an update synchronizer @param oldsync Update synchronizer to remove
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/UpdateRunner.java#L146-L158
train
elki-project/elki
elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/projection/PerplexityAffinityMatrixBuilder.java
PerplexityAffinityMatrixBuilder.estimateInitialBeta
protected static double estimateInitialBeta(double[] dist_i, double perplexity) { double sum = 0.; for(double d : dist_i) { double d2 = d * d; sum += d2 < Double.POSITIVE_INFINITY ? d2 : 0.; } return sum > 0 && sum < Double.POSITIVE_INFINITY ? .5 / sum * perplexity * (dist_i.length - 1.) : 1.; }
java
protected static double estimateInitialBeta(double[] dist_i, double perplexity) { double sum = 0.; for(double d : dist_i) { double d2 = d * d; sum += d2 < Double.POSITIVE_INFINITY ? d2 : 0.; } return sum > 0 && sum < Double.POSITIVE_INFINITY ? .5 / sum * perplexity * (dist_i.length - 1.) : 1.; }
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Estimate beta from the distances in a row. This lacks a mathematical argument, but is a handcrafted heuristic to avoid numerical problems. The average distance is usually too large, so we scale the average distance by 2*N/perplexity. Then estimate beta as 1/x. @param dist_i Distances @param perplexity Desired perplexity @return Estimated beta.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/projection/PerplexityAffinityMatrixBuilder.java#L206-L213
train
elki-project/elki
elki-core/src/main/java/de/lmu/ifi/dbs/elki/result/ResultUtil.java
ResultUtil.getRelations
public static List<Relation<?>> getRelations(Result r) { if(r instanceof Relation<?>) { List<Relation<?>> anns = new ArrayList<>(1); anns.add((Relation<?>) r); return anns; } if(r instanceof HierarchicalResult) { return filterResults(((HierarchicalResult) r).getHierarchy(), r, Relation.class); } return Collections.emptyList(); }
java
public static List<Relation<?>> getRelations(Result r) { if(r instanceof Relation<?>) { List<Relation<?>> anns = new ArrayList<>(1); anns.add((Relation<?>) r); return anns; } if(r instanceof HierarchicalResult) { return filterResults(((HierarchicalResult) r).getHierarchy(), r, Relation.class); } return Collections.emptyList(); }
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Collect all Annotation results from a Result @param r Result @return List of all annotation results
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core/src/main/java/de/lmu/ifi/dbs/elki/result/ResultUtil.java#L53-L63
train
elki-project/elki
elki-core/src/main/java/de/lmu/ifi/dbs/elki/result/ResultUtil.java
ResultUtil.getOrderingResults
public static List<OrderingResult> getOrderingResults(Result r) { if(r instanceof OrderingResult) { List<OrderingResult> ors = new ArrayList<>(1); ors.add((OrderingResult) r); return ors; } if(r instanceof HierarchicalResult) { return filterResults(((HierarchicalResult) r).getHierarchy(), r, OrderingResult.class); } return Collections.emptyList(); }
java
public static List<OrderingResult> getOrderingResults(Result r) { if(r instanceof OrderingResult) { List<OrderingResult> ors = new ArrayList<>(1); ors.add((OrderingResult) r); return ors; } if(r instanceof HierarchicalResult) { return filterResults(((HierarchicalResult) r).getHierarchy(), r, OrderingResult.class); } return Collections.emptyList(); }
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Collect all ordering results from a Result @param r Result @return List of ordering results
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core/src/main/java/de/lmu/ifi/dbs/elki/result/ResultUtil.java#L71-L81
train
elki-project/elki
elki-core/src/main/java/de/lmu/ifi/dbs/elki/result/ResultUtil.java
ResultUtil.getCollectionResults
public static List<CollectionResult<?>> getCollectionResults(Result r) { if(r instanceof CollectionResult<?>) { List<CollectionResult<?>> crs = new ArrayList<>(1); crs.add((CollectionResult<?>) r); return crs; } if(r instanceof HierarchicalResult) { return filterResults(((HierarchicalResult) r).getHierarchy(), r, CollectionResult.class); } return Collections.emptyList(); }
java
public static List<CollectionResult<?>> getCollectionResults(Result r) { if(r instanceof CollectionResult<?>) { List<CollectionResult<?>> crs = new ArrayList<>(1); crs.add((CollectionResult<?>) r); return crs; } if(r instanceof HierarchicalResult) { return filterResults(((HierarchicalResult) r).getHierarchy(), r, CollectionResult.class); } return Collections.emptyList(); }
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Collect all collection results from a Result @param r Result @return List of collection results
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core/src/main/java/de/lmu/ifi/dbs/elki/result/ResultUtil.java#L89-L99
train
elki-project/elki
elki-core/src/main/java/de/lmu/ifi/dbs/elki/result/ResultUtil.java
ResultUtil.getIterableResults
public static List<IterableResult<?>> getIterableResults(Result r) { if(r instanceof IterableResult<?>) { List<IterableResult<?>> irs = new ArrayList<>(1); irs.add((IterableResult<?>) r); return irs; } if(r instanceof HierarchicalResult) { return filterResults(((HierarchicalResult) r).getHierarchy(), r, IterableResult.class); } return Collections.emptyList(); }
java
public static List<IterableResult<?>> getIterableResults(Result r) { if(r instanceof IterableResult<?>) { List<IterableResult<?>> irs = new ArrayList<>(1); irs.add((IterableResult<?>) r); return irs; } if(r instanceof HierarchicalResult) { return filterResults(((HierarchicalResult) r).getHierarchy(), r, IterableResult.class); } return Collections.emptyList(); }
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Return all Iterable results @param r Result @return List of iterable results
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core/src/main/java/de/lmu/ifi/dbs/elki/result/ResultUtil.java#L107-L117
train
elki-project/elki
elki-core/src/main/java/de/lmu/ifi/dbs/elki/result/ResultUtil.java
ResultUtil.filterResults
public static <C extends Result> ArrayList<C> filterResults(ResultHierarchy hier, Result r, Class<? super C> restrictionClass) { ArrayList<C> res = new ArrayList<>(); final It<C> it = hier.iterDescendantsSelf(r).filter(restrictionClass); it.forEach(res::add); return res; }
java
public static <C extends Result> ArrayList<C> filterResults(ResultHierarchy hier, Result r, Class<? super C> restrictionClass) { ArrayList<C> res = new ArrayList<>(); final It<C> it = hier.iterDescendantsSelf(r).filter(restrictionClass); it.forEach(res::add); return res; }
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Return only results of the given restriction class @param <C> Class type @param hier Result hierarchy @param r Starting position @param restrictionClass Class restriction @return filtered results list
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core/src/main/java/de/lmu/ifi/dbs/elki/result/ResultUtil.java#L128-L133
train
elki-project/elki
elki-core/src/main/java/de/lmu/ifi/dbs/elki/result/ResultUtil.java
ResultUtil.addChildResult
public static void addChildResult(HierarchicalResult parent, Result child) { parent.getHierarchy().add(parent, child); }
java
public static void addChildResult(HierarchicalResult parent, Result child) { parent.getHierarchy().add(parent, child); }
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Add a child result. @param parent Parent @param child Child
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core/src/main/java/de/lmu/ifi/dbs/elki/result/ResultUtil.java#L156-L158
train
elki-project/elki
elki-core/src/main/java/de/lmu/ifi/dbs/elki/result/ResultUtil.java
ResultUtil.findDatabase
public static Database findDatabase(ResultHierarchy hier, Result baseResult) { final List<Database> dbs = filterResults(hier, baseResult, Database.class); return (!dbs.isEmpty()) ? dbs.get(0) : null; }
java
public static Database findDatabase(ResultHierarchy hier, Result baseResult) { final List<Database> dbs = filterResults(hier, baseResult, Database.class); return (!dbs.isEmpty()) ? dbs.get(0) : null; }
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Find the first database result in the tree. @param baseResult Result tree base. @return Database
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core/src/main/java/de/lmu/ifi/dbs/elki/result/ResultUtil.java#L166-L169
train
elki-project/elki
elki-core/src/main/java/de/lmu/ifi/dbs/elki/result/ResultUtil.java
ResultUtil.removeRecursive
public static void removeRecursive(ResultHierarchy hierarchy, Result child) { for(It<Result> iter = hierarchy.iterParents(child); iter.valid(); iter.advance()) { hierarchy.remove(iter.get(), child); } for(It<Result> iter = hierarchy.iterChildren(child); iter.valid(); iter.advance()) { removeRecursive(hierarchy, iter.get()); } }
java
public static void removeRecursive(ResultHierarchy hierarchy, Result child) { for(It<Result> iter = hierarchy.iterParents(child); iter.valid(); iter.advance()) { hierarchy.remove(iter.get(), child); } for(It<Result> iter = hierarchy.iterChildren(child); iter.valid(); iter.advance()) { removeRecursive(hierarchy, iter.get()); } }
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Recursively remove a result and its children. @param hierarchy Result hierarchy @param child Result to remove
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core/src/main/java/de/lmu/ifi/dbs/elki/result/ResultUtil.java#L188-L195
train
elki-project/elki
elki-input/src/main/java/de/lmu/ifi/dbs/elki/datasource/filter/transform/FastMultidimensionalScalingTransform.java
FastMultidimensionalScalingTransform.findEigenVectors
protected void findEigenVectors(double[][] imat, double[][] evs, double[] lambda) { final int size = imat.length; Random rnd = random.getSingleThreadedRandom(); double[] tmp = new double[size]; FiniteProgress prog = LOG.isVerbose() ? new FiniteProgress("Learning projections", tdim, LOG) : null; for(int d = 0; d < tdim;) { final double[] cur = evs[d]; randomInitialization(cur, rnd); double l = multiply(imat, cur, tmp); for(int iter = 0; iter < 100; iter++) { // This will scale "tmp" to unit length, and copy it to cur: double delta = updateEigenvector(tmp, cur, l); if(delta < 1e-10) { break; } l = multiply(imat, cur, tmp); } lambda[d++] = l = estimateEigenvalue(imat, cur); LOG.incrementProcessed(prog); if(d == tdim) { break; } // Update matrix updateMatrix(imat, cur, l); } LOG.ensureCompleted(prog); }
java
protected void findEigenVectors(double[][] imat, double[][] evs, double[] lambda) { final int size = imat.length; Random rnd = random.getSingleThreadedRandom(); double[] tmp = new double[size]; FiniteProgress prog = LOG.isVerbose() ? new FiniteProgress("Learning projections", tdim, LOG) : null; for(int d = 0; d < tdim;) { final double[] cur = evs[d]; randomInitialization(cur, rnd); double l = multiply(imat, cur, tmp); for(int iter = 0; iter < 100; iter++) { // This will scale "tmp" to unit length, and copy it to cur: double delta = updateEigenvector(tmp, cur, l); if(delta < 1e-10) { break; } l = multiply(imat, cur, tmp); } lambda[d++] = l = estimateEigenvalue(imat, cur); LOG.incrementProcessed(prog); if(d == tdim) { break; } // Update matrix updateMatrix(imat, cur, l); } LOG.ensureCompleted(prog); }
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Find the first eigenvectors and eigenvalues using power iterations. @param imat Matrix (will be modified!) @param evs Eigenvectors output @param lambda Eigenvalues output
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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/transform/FastMultidimensionalScalingTransform.java#L178-L204
train
elki-project/elki
elki-input/src/main/java/de/lmu/ifi/dbs/elki/datasource/filter/transform/FastMultidimensionalScalingTransform.java
FastMultidimensionalScalingTransform.randomInitialization
protected void randomInitialization(double[] out, Random rnd) { double l2 = 0.; while(!(l2 > 0)) { for(int d = 0; d < out.length; d++) { final double val = rnd.nextDouble(); out[d] = val; l2 += val * val; } } // Standardize: final double s = 1. / FastMath.sqrt(l2); for(int d = 0; d < out.length; d++) { out[d] *= s; } }
java
protected void randomInitialization(double[] out, Random rnd) { double l2 = 0.; while(!(l2 > 0)) { for(int d = 0; d < out.length; d++) { final double val = rnd.nextDouble(); out[d] = val; l2 += val * val; } } // Standardize: final double s = 1. / FastMath.sqrt(l2); for(int d = 0; d < out.length; d++) { out[d] *= s; } }
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Choose a random vector of unit norm for power iterations. @param out Output storage @param rnd Random source.
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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/transform/FastMultidimensionalScalingTransform.java#L212-L226
train
elki-project/elki
elki-input/src/main/java/de/lmu/ifi/dbs/elki/datasource/filter/transform/FastMultidimensionalScalingTransform.java
FastMultidimensionalScalingTransform.updateEigenvector
protected double updateEigenvector(double[] in, double[] out, double l) { double s = 1. / (l > 0. ? l : l < 0. ? -l : 1.); s = (in[0] > 0.) ? s : -s; // Reduce flipping vectors double diff = 0.; for(int d = 0; d < in.length; d++) { in[d] *= s; // Scale to unit length // Compute change from previous iteration: double delta = in[d] - out[d]; diff += delta * delta; out[d] = in[d]; // Update output storage } return diff; }
java
protected double updateEigenvector(double[] in, double[] out, double l) { double s = 1. / (l > 0. ? l : l < 0. ? -l : 1.); s = (in[0] > 0.) ? s : -s; // Reduce flipping vectors double diff = 0.; for(int d = 0; d < in.length; d++) { in[d] *= s; // Scale to unit length // Compute change from previous iteration: double delta = in[d] - out[d]; diff += delta * delta; out[d] = in[d]; // Update output storage } return diff; }
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Compute the change in the eigenvector, and normalize the output vector while doing so. @param in Input vector @param out Output vector @param l Eigenvalue @return Change
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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/transform/FastMultidimensionalScalingTransform.java#L260-L272
train
elki-project/elki
elki-input/src/main/java/de/lmu/ifi/dbs/elki/datasource/filter/transform/FastMultidimensionalScalingTransform.java
FastMultidimensionalScalingTransform.updateMatrix
protected void updateMatrix(double[][] mat, final double[] evec, double eval) { final int size = mat.length; for(int i = 0; i < size; i++) { final double[] mati = mat[i]; final double eveci = evec[i]; for(int j = 0; j < size; j++) { mati[j] -= eval * eveci * evec[j]; } } }
java
protected void updateMatrix(double[][] mat, final double[] evec, double eval) { final int size = mat.length; for(int i = 0; i < size; i++) { final double[] mati = mat[i]; final double eveci = evec[i]; for(int j = 0; j < size; j++) { mati[j] -= eval * eveci * evec[j]; } } }
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Update matrix, by removing the effects of a known Eigenvector. @param mat Matrix @param evec Known normalized Eigenvector @param eval Eigenvalue
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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/transform/FastMultidimensionalScalingTransform.java#L304-L313
train