Uses of Class
de.lmu.ifi.dbs.elki.math.linearalgebra.Vector

Packages that use Vector

Package	Description
de.lmu.ifi.dbs.elki.algorithm	Algorithms suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation	Correlation clustering algorithms
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash	Helper classes for the CASH algorithm.
de.lmu.ifi.dbs.elki.algorithm.clustering.em	Expectation-Maximization clustering algorithm.
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans	K-means clustering and variations.
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization	Initialization strategies for k-means.
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel	Parallelized implementations of k-means.
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace	Axis-parallel subspace clustering algorithms.
de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain	Clustering algorithms for uncertain data.
de.lmu.ifi.dbs.elki.algorithm.outlier.lof	LOF family of outlier detection algorithms.
de.lmu.ifi.dbs.elki.algorithm.outlier.subspace	Subspace outlier detection methods.
de.lmu.ifi.dbs.elki.data	Basic classes for different data types, database object types and label types.
de.lmu.ifi.dbs.elki.data.model	Cluster models classes for various algorithms.
de.lmu.ifi.dbs.elki.data.spatial	Spatial data types - interfaces and utilities.
de.lmu.ifi.dbs.elki.data.synthetic.bymodel	Generator using a distribution model specified in an XML configuration file.
de.lmu.ifi.dbs.elki.data.type	Data type information, also used for type restrictions.
de.lmu.ifi.dbs.elki.datasource	Data normalization (and reconstitution) of data sets.
de.lmu.ifi.dbs.elki.datasource.parser	Parsers for different file formats and data types.
de.lmu.ifi.dbs.elki.evaluation.outlier	Evaluate an outlier score using a misclassification based cost model.
de.lmu.ifi.dbs.elki.index.tree.spatial	Tree-based index structures for spatial indexing.
de.lmu.ifi.dbs.elki.math	Mathematical operations and utilities used throughout the framework.
de.lmu.ifi.dbs.elki.math.geometry	Algorithms from computational geometry.
de.lmu.ifi.dbs.elki.math.linearalgebra	Linear Algebra package provides classes and computational methods for operations on matrices.
de.lmu.ifi.dbs.elki.math.statistics	Statistical tests and methods.
de.lmu.ifi.dbs.elki.result.textwriter.writers	Serialization handlers for individual data types.
de.lmu.ifi.dbs.elki.utilities	Utility and helper classes - commonly used data structures, output formatting, exceptions, ...
de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike	Common API for accessing objects that are "array-like", including lists, numerical vectors, database vectors and arrays.
de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters	Classes for various typed parameters.
de.lmu.ifi.dbs.elki.visualization.svg	Base SVG functionality (generation, markers, thumbnails, export, ...).
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster	Visualizers for clustering results based on 2D projections.
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.outlier	Visualizers for outlier scores based on 2D projections.
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection	Visualizers for object selection based on 2D projections.

Uses of Vector in de.lmu.ifi.dbs.elki.algorithm

Methods in de.lmu.ifi.dbs.elki.algorithm with parameters of type Vector

Modifier and Type	Method and Description
CorrelationAnalysisSolution<V>	DependencyDerivator.generateModel(Relation<V> db, DBIDs ids, Vector centroid) Runs the pca on the given set of IDs and for the given centroid.

Uses of Vector in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation declared as Vector

Modifier and Type	Field and Description
(package private) Vector	LMCLUS.Separation.originV Origin vector

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation with parameters of type Vector

Modifier and Type	Method and Description
private void	HiCO.adjust(Matrix v, Matrix e_czech, Vector vector, int corrDim) Inserts the specified vector into the given orthonormal matrix v at column corrDim.
private double	LMCLUS.deviation(Vector delta, Matrix beta) Deviation from a manifold described by beta.

Method parameters in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation with type arguments of type Vector

Modifier and Type	Method and Description
private Matrix	LMCLUS.generateOrthonormalBasis(List<Vector> vectors) This Method generates an orthonormal basis from a set of Vectors.

Uses of Vector in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash that return Vector

Modifier and Type	Method and Description
Vector	ParameterizationFunction.getColumnVector() Get the actual vector used.

Uses of Vector in de.lmu.ifi.dbs.elki.algorithm.clustering.em

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.em declared as Vector

Modifier and Type	Field and Description
(package private) Vector	SphericalGaussianModel.mean Mean vector.
(package private) Vector	MultivariateGaussianModel.mean Mean vector.
(package private) Vector	DiagonalGaussianModel.mean Mean vector.

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.em with parameters of type Vector

Modifier and Type	Method and Description
double	SphericalGaussianModel.mahalanobisDistance(Vector vec) Compute the Mahalanobis distance from the centroid for a given vector.
double	MultivariateGaussianModel.mahalanobisDistance(Vector vec) Compute the Mahalanobis distance from the centroid for a given vector.
double	DiagonalGaussianModel.mahalanobisDistance(Vector vec) Compute the Mahalanobis distance from the centroid for a given vector.

Constructors in de.lmu.ifi.dbs.elki.algorithm.clustering.em with parameters of type Vector

Constructor and Description
DiagonalGaussianModel(double weight, Vector mean) Constructor.
DiagonalGaussianModel(double weight, Vector mean, double norm) Constructor.
MultivariateGaussianModel(double weight, Vector mean) Constructor.
MultivariateGaussianModel(double weight, Vector mean, double norm) Constructor.
SphericalGaussianModel(double weight, Vector mean) Constructor.
SphericalGaussianModel(double weight, Vector mean, double norm) Constructor.

Uses of Vector in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans that return types with arguments of type Vector

Modifier and Type	Method and Description
protected List<Vector>	AbstractKMeans.means(List<? extends DBIDs> clusters, List<? extends NumberVector> means, Relation<V> database) Returns the mean vectors of the given clusters in the given database.
protected List<Vector>	AbstractKMeans.medians(List<? extends DBIDs> clusters, List<Vector> medians, Relation<V> database) Returns the median vectors of the given clusters in the given database.

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans with parameters of type Vector

Modifier and Type	Method and Description
protected void	AbstractKMeans.incrementalUpdateMean(Vector mean, V vec, int newsize, double op) Compute an incremental update for the mean.

Method parameters in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans with type arguments of type Vector

Modifier and Type	Method and Description
private int	KMeansElkan.assignToNearestCluster(Relation<V> relation, List<Vector> means, List<Vector> sums, List<ModifiableDBIDs> clusters, WritableIntegerDataStore assignment, double[] sep, double[][] cdist, WritableDoubleDataStore upper, WritableDataStore<double[]> lower) Reassign objects, but only if their bounds indicate it is necessary to do so.
private int	KMeansElkan.assignToNearestCluster(Relation<V> relation, List<Vector> means, List<Vector> sums, List<ModifiableDBIDs> clusters, WritableIntegerDataStore assignment, double[] sep, double[][] cdist, WritableDoubleDataStore upper, WritableDataStore<double[]> lower) Reassign objects, but only if their bounds indicate it is necessary to do so.
private int	KMeansHamerly.assignToNearestCluster(Relation<V> relation, List<Vector> means, List<Vector> sums, List<ModifiableDBIDs> clusters, WritableIntegerDataStore assignment, double[] sep, WritableDoubleDataStore upper, WritableDoubleDataStore lower) Reassign objects, but only if their bounds indicate it is necessary to do so.
private int	KMeansHamerly.assignToNearestCluster(Relation<V> relation, List<Vector> means, List<Vector> sums, List<ModifiableDBIDs> clusters, WritableIntegerDataStore assignment, double[] sep, WritableDoubleDataStore upper, WritableDoubleDataStore lower) Reassign objects, but only if their bounds indicate it is necessary to do so.
private int	KMeansElkan.initialAssignToNearestCluster(Relation<V> relation, List<Vector> means, List<Vector> sums, List<ModifiableDBIDs> clusters, WritableIntegerDataStore assignment, WritableDoubleDataStore upper, WritableDataStore<double[]> lower) Reassign objects, but only if their bounds indicate it is necessary to do so.
private int	KMeansElkan.initialAssignToNearestCluster(Relation<V> relation, List<Vector> means, List<Vector> sums, List<ModifiableDBIDs> clusters, WritableIntegerDataStore assignment, WritableDoubleDataStore upper, WritableDataStore<double[]> lower) Reassign objects, but only if their bounds indicate it is necessary to do so.
private int	KMeansHamerly.initialAssignToNearestCluster(Relation<V> relation, List<Vector> means, List<Vector> sums, List<ModifiableDBIDs> clusters, WritableIntegerDataStore assignment, WritableDoubleDataStore upper, WritableDoubleDataStore lower) Reassign objects, but only if their bounds indicate it is necessary to do so.
private int	KMeansHamerly.initialAssignToNearestCluster(Relation<V> relation, List<Vector> means, List<Vector> sums, List<ModifiableDBIDs> clusters, WritableIntegerDataStore assignment, WritableDoubleDataStore upper, WritableDoubleDataStore lower) Reassign objects, but only if their bounds indicate it is necessary to do so.
protected boolean	AbstractKMeans.macQueenIterate(Relation<V> relation, List<Vector> means, List<ModifiableDBIDs> clusters, WritableIntegerDataStore assignment, double[] varsum) Perform a MacQueen style iteration.
private double	KMeansHamerly.maxMoved(List<Vector> means, List<Vector> newmeans, double[] dists) Maximum distance moved.
private double	KMeansHamerly.maxMoved(List<Vector> means, List<Vector> newmeans, double[] dists) Maximum distance moved.
private double	KMeansElkan.maxMoved(List<Vector> means, List<Vector> newmeans, double[] dists) Maximum distance moved.
private double	KMeansElkan.maxMoved(List<Vector> means, List<Vector> newmeans, double[] dists) Maximum distance moved.
protected List<Vector>	AbstractKMeans.medians(List<? extends DBIDs> clusters, List<Vector> medians, Relation<V> database) Returns the median vectors of the given clusters in the given database.
private void	KMeansHamerly.recomputeSeperation(List<Vector> means, double[] sep) Recompute the separation of cluster means.
private void	KMeansElkan.recomputeSeperation(List<Vector> means, double[] sep, double[][] cdist) Recompute the separation of cluster means.
private boolean	AbstractKMeans.updateMeanAndAssignment(List<ModifiableDBIDs> clusters, List<Vector> means, int minIndex, V fv, DBIDIter iditer, WritableIntegerDataStore assignment) Try to update the cluster assignment.
protected void	KMeansBatchedLloyd.updateMeans(List<Vector> means, double[][] meanshift, List<ModifiableDBIDs> clusters, int[] changesize) Merge changes into mean vectors.

Uses of Vector in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization with type parameters of type Vector

Modifier and Type	Field and Description
protected List<Vector>	PredefinedInitialMeans.Parameterizer.initialMeans Initial means.

Uses of Vector in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel declared as Vector

Modifier and Type	Field and Description
private Vector[]	KMeansProcessor.Instance.means Current mean vectors.

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel with type parameters of type Vector

Modifier and Type	Field and Description
(package private) List<Vector>	KMeansProcessor.means Mean vectors.

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel that return types with arguments of type Vector

Modifier and Type	Method and Description
List<Vector>	KMeansProcessor.getMeans() Get the new means.

Method parameters in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel with type arguments of type Vector

Modifier and Type	Method and Description
void	KMeansProcessor.nextIteration(List<Vector> means) Initialize for a new iteration.

Uses of Vector in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace declared as Vector

Modifier and Type	Field and Description
(package private) Vector	PROCLUS.PROCLUSCluster.centroid The centroids of this cluster along each dimension.

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace that return types with arguments of type Vector

Modifier and Type	Method and Description
private List<Pair<Vector,long[]>>	PROCLUS.findDimensions(ArrayList<PROCLUS.PROCLUSCluster> clusters, Relation<V> database) Refinement step that determines the set of correlated dimensions for each cluster centroid.

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace with parameters of type Vector

Modifier and Type	Method and Description
private double	PROCLUS.avgDistance(Vector centroid, DBIDs objectIDs, Relation<V> database, int dimension) Computes the average distance of the objects to the centroid along the specified dimension.

Method parameters in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace with type arguments of type Vector

Modifier and Type	Method and Description
private List<PROCLUS.PROCLUSCluster>	PROCLUS.finalAssignment(List<Pair<Vector,long[]>> dimensions, Relation<V> database) Refinement step to assign the objects to the final clusters.

Constructors in de.lmu.ifi.dbs.elki.algorithm.clustering.subspace with parameters of type Vector

Constructor and Description
PROCLUS.PROCLUSCluster(ModifiableDBIDs objectIDs, long[] dimensions, Vector centroid) Constructor.

Uses of Vector in de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain that return types with arguments of type Vector

Modifier and Type	Method and Description
protected List<Vector>	UKMeans.means(List<? extends ModifiableDBIDs> clusters, List<? extends NumberVector> means, Relation<DiscreteUncertainObject> database) Returns the mean vectors of the given clusters in the given database.

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain with parameters of type Vector

Modifier and Type	Method and Description
protected double	UKMeans.getExpectedRepDistance(Vector rep, DiscreteUncertainObject uo) Get expected distance between a Vector and an uncertain object

Method parameters in de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain with type arguments of type Vector

Modifier and Type	Method and Description
protected boolean	UKMeans.assignToNearestCluster(Relation<DiscreteUncertainObject> relation, List<Vector> means, List<? extends ModifiableDBIDs> clusters, WritableIntegerDataStore assignment, double[] varsum) Returns a list of clusters.

Uses of Vector in de.lmu.ifi.dbs.elki.algorithm.outlier.lof

Fields in de.lmu.ifi.dbs.elki.algorithm.outlier.lof declared as Vector

Modifier and Type	Field and Description
(package private) Vector	ALOCI.Node.center Center vector

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.lof that return Vector

Modifier and Type	Method and Description
Vector	ALOCI.Node.getCenter() Return center vector

Constructors in de.lmu.ifi.dbs.elki.algorithm.outlier.lof with parameters of type Vector

Constructor and Description
ALOCI.Node(int code, Vector center, int count, int level, List<ALOCI.Node> children) Constructor.

Uses of Vector in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace

Fields in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace declared as Vector

Modifier and Type	Field and Description
private Vector	SOD.SODModel.center Center vector

Methods in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace with parameters of type Vector

Modifier and Type	Method and Description
private static double[]	SOD.computePerDimensionVariances(Relation<? extends NumberVector> relation, Vector center, DBIDs neighborhood) Compute the per-dimension variances for the given neighborhood and center.
private double	SOD.subspaceOutlierDegree(V queryObject, Vector center, long[] weightVector) Compute SOD score.

Constructors in de.lmu.ifi.dbs.elki.algorithm.outlier.subspace with parameters of type Vector

Constructor and Description
SOD.SODModel(Vector center, long[] weightVector) Initialize SOD Model

Uses of Vector in de.lmu.ifi.dbs.elki.data

Methods in de.lmu.ifi.dbs.elki.data that return Vector

Modifier and Type	Method and Description
static Vector	VectorUtil.computeMedoid(Relation<? extends NumberVector> relation, DBIDs sample) Compute medoid for a given subset.
Vector	SparseShortVector.getColumnVector()
Vector	SparseIntegerVector.getColumnVector()
Vector	SparseFloatVector.getColumnVector()
Vector	SparseDoubleVector.getColumnVector()
Vector	SparseByteVector.getColumnVector()
Vector	ShortVector.getColumnVector()
Vector	OneDimensionalDoubleVector.getColumnVector()
Vector	NumberVector.getColumnVector() Returns a Vector representing in one column and getDimensionality() rows the values of this NumberVector of V.
Vector	IntegerVector.getColumnVector()
Vector	FloatVector.getColumnVector()
Vector	DoubleVector.getColumnVector()
Vector	ByteVector.getColumnVector()
Vector	BitVector.getColumnVector() Returns a Vector representing in one column and getDimensionality() rows the values of this BitVector as double values.

Methods in de.lmu.ifi.dbs.elki.data with parameters of type Vector

Modifier and Type	Method and Description
static double	VectorUtil.angle(NumberVector v1, NumberVector v2, Vector o) Compute the angle between two vectors.

Constructors in de.lmu.ifi.dbs.elki.data with parameters of type Vector

Constructor and Description
DoubleVector(Vector columnMatrix) Expects a matrix of one column.
FloatVector(Vector columnMatrix) Expects a matrix of one column.

Uses of Vector in de.lmu.ifi.dbs.elki.data.model

Fields in de.lmu.ifi.dbs.elki.data.model declared as Vector

Modifier and Type	Field and Description
private Vector	CorrelationAnalysisSolution.centroid The centroid if the objects belonging to the hyperplane induced by the correlation.

Methods in de.lmu.ifi.dbs.elki.data.model that return Vector

Modifier and Type	Method and Description
Vector	CorrelationAnalysisSolution.dataVector(V p) Returns the data vectors after projection.
Vector	CorrelationAnalysisSolution.errorVector(V p) Returns the error vectors after projection.
Vector	CorrelationAnalysisSolution.getCentroid() Returns the centroid of this model.
Vector	MeanModel.getMean()

Methods in de.lmu.ifi.dbs.elki.data.model with parameters of type Vector

Modifier and Type	Method and Description
private double	CorrelationAnalysisSolution.distance(Vector p) Returns the distance of Matrix p from the hyperplane underlying this solution.

Constructors in de.lmu.ifi.dbs.elki.data.model with parameters of type Vector

Constructor and Description
CorrelationAnalysisSolution(LinearEquationSystem solution, Relation<V> db, Matrix strongEigenvectors, Matrix weakEigenvectors, Matrix similarityMatrix, Vector centroid) Provides a new CorrelationAnalysisSolution holding the specified matrix.
CorrelationAnalysisSolution(LinearEquationSystem solution, Relation<V> db, Matrix strongEigenvectors, Matrix weakEigenvectors, Matrix similarityMatrix, Vector centroid, NumberFormat nf) Provides a new CorrelationAnalysisSolution holding the specified matrix and number format.
EMModel(Vector mean, Matrix covarianceMatrix) Constructor.
KMeansModel(Vector mean, double varsum) Constructor with mean.
MeanModel(Vector mean) Constructor with mean
SubspaceModel(Subspace subspace, Vector mean) Creates a new SubspaceModel for the specified subspace with the given cluster mean.

Uses of Vector in de.lmu.ifi.dbs.elki.data.spatial

Fields in de.lmu.ifi.dbs.elki.data.spatial with type parameters of type Vector

Modifier and Type	Field and Description
private List<Vector>	Polygon.points The actual points

Methods in de.lmu.ifi.dbs.elki.data.spatial that return Vector

Modifier and Type	Method and Description
Vector	Polygon.get(int idx) Get a vector by index.

Methods in de.lmu.ifi.dbs.elki.data.spatial that return types with arguments of type Vector

Modifier and Type	Method and Description
ArrayListIter<Vector>	Polygon.iter() Get an iterator to the vector contents.

Methods in de.lmu.ifi.dbs.elki.data.spatial with parameters of type Vector

Modifier and Type	Method and Description
boolean	Polygon.containsPoint2D(Vector v) Point in polygon test, based on http://www.ecse.rpi.edu/Homepages/wrf/Research/Short_Notes/pnpoly.html by W.

Constructor parameters in de.lmu.ifi.dbs.elki.data.spatial with type arguments of type Vector

Constructor and Description
Polygon(List<Vector> points) Constructor.
Polygon(List<Vector> points, double minx, double maxx, double miny, double maxy)

Uses of Vector in de.lmu.ifi.dbs.elki.data.synthetic.bymodel

Fields in de.lmu.ifi.dbs.elki.data.synthetic.bymodel declared as Vector

Modifier and Type	Field and Description
private Vector	GeneratorSingleCluster.clipmax
private Vector	GeneratorSingleCluster.clipmin Clipping vectors.

Fields in de.lmu.ifi.dbs.elki.data.synthetic.bymodel with type parameters of type Vector

Modifier and Type	Field and Description
List<Vector>	GeneratorStatic.points Cluster points

Methods in de.lmu.ifi.dbs.elki.data.synthetic.bymodel that return Vector

Modifier and Type	Method and Description
Vector	GeneratorSingleCluster.getClipmax() Return a copy of the 'clipping maximum' vector
Vector	GeneratorSingleCluster.getClipmin() Return a copy of the 'clipping minimum' vector.

Methods in de.lmu.ifi.dbs.elki.data.synthetic.bymodel that return types with arguments of type Vector

Modifier and Type	Method and Description
List<Vector>	GeneratorStatic.generate(int count) "Generate" new cluster points.
List<Vector>	GeneratorSingleCluster.generate(int count) Generate the given number of additional points.
List<Vector>	GeneratorInterface.generate(int count) Generate a specified number of points

Methods in de.lmu.ifi.dbs.elki.data.synthetic.bymodel with parameters of type Vector

Modifier and Type	Method and Description
void	GeneratorSingleCluster.addTranslation(Vector v) Add a translation to the generator
double	GeneratorStatic.getDensity(Vector p)
double	GeneratorSingleCluster.getDensity(Vector p) Compute density for cluster model at given vector p-
double	GeneratorInterface.getDensity(Vector p) Get the density of the given vector
void	GeneratorSingleCluster.setClipping(Vector min, Vector max) Set a clipping box. min needs to be smaller than max in each component.
private boolean	GeneratorSingleCluster.testClipping(Vector p) Test if a point is to be clipped

Constructor parameters in de.lmu.ifi.dbs.elki.data.synthetic.bymodel with type arguments of type Vector

Constructor and Description
GeneratorStatic(String name, List<Vector> points) Construct generator using given name and points

Uses of Vector in de.lmu.ifi.dbs.elki.data.type

Fields in de.lmu.ifi.dbs.elki.data.type with type parameters of type Vector

Modifier and Type	Field and Description
static SimpleTypeInformation<Vector>	TypeUtil.VECTOR Vector type.

Uses of Vector in de.lmu.ifi.dbs.elki.datasource

Methods in de.lmu.ifi.dbs.elki.datasource that return Vector

Modifier and Type	Method and Description
private Vector	GeneratorXMLDatabaseConnection.parseVector(String s) Parse a string into a vector.

Method parameters in de.lmu.ifi.dbs.elki.datasource with type arguments of type Vector

Modifier and Type	Method and Description
private void	GeneratorXMLDatabaseConnection.processElementPoint(List<Vector> points, Node cur) Parse a 'point' element (point vector for a static cluster)

Uses of Vector in de.lmu.ifi.dbs.elki.datasource.parser

Fields in de.lmu.ifi.dbs.elki.datasource.parser with type parameters of type Vector

Modifier and Type	Field and Description
private List<Vector>	SimplePolygonParser.coords (Reused) storage of coordinates.

Uses of Vector in de.lmu.ifi.dbs.elki.evaluation.outlier

Constructor parameters in de.lmu.ifi.dbs.elki.evaluation.outlier with type arguments of type Vector

Constructor and Description
JudgeOutlierScores.ScoreResult(Collection<Vector> col) Constructor.

Uses of Vector in de.lmu.ifi.dbs.elki.index.tree.spatial

Methods in de.lmu.ifi.dbs.elki.index.tree.spatial that return Vector

Modifier and Type	Method and Description
Vector	SpatialPointLeafEntry.getColumnVector()

Uses of Vector in de.lmu.ifi.dbs.elki.math

Methods in de.lmu.ifi.dbs.elki.math with parameters of type Vector

Modifier and Type	Method and Description
static double	MathUtil.angle(Vector v1, Vector v2) Compute the angle between two vectors.
static double	MathUtil.angle(Vector v1, Vector v2, Vector o) Compute the angle between two vectors.
static double	MathUtil.mahalanobisDistance(Matrix weightMatrix, Vector o1_minus_o2) Compute the Mahalanobis distance using the given weight matrix.
static double	MathUtil.mahalanobisDistance(Matrix weightMatrix, Vector o1, Vector o2) Compute the Mahalanobis distance using the given weight matrix.

Uses of Vector in de.lmu.ifi.dbs.elki.math.geometry

Fields in de.lmu.ifi.dbs.elki.math.geometry declared as Vector

Modifier and Type	Field and Description
Vector	SweepHullDelaunay2D.Triangle.m Center vector

Fields in de.lmu.ifi.dbs.elki.math.geometry with type parameters of type Vector

Modifier and Type	Field and Description
private List<Vector>	SweepHullDelaunay2D.points The current set of points.
private List<Vector>	GrahamScanConvexHull2D.points The current set of points
private List<Vector>	AlphaShape.points Points

Methods in de.lmu.ifi.dbs.elki.math.geometry with parameters of type Vector

Modifier and Type	Method and Description
void	SweepHullDelaunay2D.add(Vector point) Add a single point to the list (this does not compute or update the triangulation!)
void	GrahamScanConvexHull2D.add(Vector point) Add a single point to the list (this does not compute the hull!)
private double	GrahamScanConvexHull2D.getRX(Vector a, Vector origin) Get the relative X coordinate to the origin.
private double	GrahamScanConvexHull2D.getRY(Vector a, Vector origin) Get the relative Y coordinate to the origin.
boolean	SweepHullDelaunay2D.Triangle.inCircle(Vector opp) Test whether a point is within the circumference circle.
private boolean	GrahamScanConvexHull2D.isConvex(Vector a, Vector b, Vector c) Simple convexity test.
protected int	GrahamScanConvexHull2D.isLeft(Vector a, Vector b, Vector o) Test whether a point is left of the other wrt. the origin.
(package private) boolean	SweepHullDelaunay2D.leftOf(Vector a, Vector b, Vector d) Test if the vector AD is right of AB.
private double	GrahamScanConvexHull2D.mdist(Vector a, Vector b) Manhattan distance.
static double	SweepHullDelaunay2D.quadraticEuclidean(Vector v1, Vector v2) Squared euclidean distance. 2d.

Method parameters in de.lmu.ifi.dbs.elki.math.geometry with type arguments of type Vector

Modifier and Type	Method and Description
(package private) boolean	SweepHullDelaunay2D.Triangle.isClockwise(List<Vector> points) Verify that the triangle is clockwise
(package private) void	SweepHullDelaunay2D.Triangle.makeClockwise(List<Vector> points) Make the triangle clockwise
private void	AlphaShape.processNeighbor(List<Vector> cur, long[] used, int i, int ab, int b)
(package private) boolean	SweepHullDelaunay2D.Triangle.updateCircumcircle(List<Vector> points) Recompute the location and squared radius of circumcircle.

Constructor parameters in de.lmu.ifi.dbs.elki.math.geometry with type arguments of type Vector

Constructor and Description
AlphaShape(List<Vector> points, double alpha)
SweepHullDelaunay2D(List<Vector> points) Constructor.

Uses of Vector in de.lmu.ifi.dbs.elki.math.linearalgebra

Subclasses of Vector in de.lmu.ifi.dbs.elki.math.linearalgebra

Modifier and Type	Class and Description
class	Centroid Class to compute the centroid of some data.
class	ProjectedCentroid Centroid only using a subset of dimensions.

Fields in de.lmu.ifi.dbs.elki.math.linearalgebra declared as Vector

Modifier and Type	Field and Description
private Vector	EigenPair.eigenvector The eigenvector as a matrix.

Fields in de.lmu.ifi.dbs.elki.math.linearalgebra with type parameters of type Vector

Modifier and Type	Field and Description
static ByteBufferSerializer<Vector>	Vector.BYTE_SERIALIZER Serializer for up to 127 dimensions.
static ByteBufferSerializer<Vector>	Vector.SHORT_SERIALIZER Serializer for up to 2^15-1 dimensions.
static ByteBufferSerializer<Vector>	Vector.VARIABLE_SERIALIZER Serializer using varint encoding.

Methods in de.lmu.ifi.dbs.elki.math.linearalgebra that return Vector

Modifier and Type	Method and Description
Vector	AffineTransformation.apply(Vector v) Apply the transformation onto a vector
Vector	AffineTransformation.applyInverse(Vector v) Apply the inverse transformation onto a vector
Vector	AffineTransformation.applyRelative(Vector v) Apply the transformation onto a vector
Vector	AffineTransformation.applyRelativeInverse(Vector v) Apply the inverse transformation onto a vector
Vector	Vector.clone()
Vector	Vector.copy() Returns a copy of this vector.
Vector	Vector.cross3D(Vector other) Cross product for 3d vectors, i.e.
Vector	Vector.SmallSerializer.fromByteBuffer(ByteBuffer buffer)
Vector	Vector.ShortSerializer.fromByteBuffer(ByteBuffer buffer)
Vector	Vector.VariableSerializer.fromByteBuffer(ByteBuffer buffer)
Vector	Matrix.getCol(int j) Returns the jth column of this matrix as vector.
Vector	Vector.getColumnVector()
Vector	EigenPair.getEigenvector() Returns the eigenvector.
Vector	CovarianceMatrix.getMeanVector() Get the mean as vector.
Vector	Matrix.getRow(int i) Returns the ith row of this matrix as vector.
Vector	AffineTransformation.homogeneRelativeVector(Vector v) Transform a relative vector into homogeneous coordinates.
Vector	AffineTransformation.homogeneVector(Vector v) Transform an absolute vector into homogeneous coordinates.
Vector	Vector.minus(Vector v) Returns this vector minus the specified vector v.
Vector	Vector.minusEquals(double d) Subtract a constant value from all dimensions.
Vector	Vector.minusEquals(Vector b) a = a - b.
Vector	Vector.minusTimes(Vector v, double s) Returns this vector minus the specified vector v times s.
Vector	Vector.minusTimesEquals(Vector b, double s) a = a - s * b.
<A> Vector	Vector.Factory.newFeatureVector(A array, ArrayAdapter<? extends Number,A> adapter)
<A> Vector	Vector.Factory.newNumberVector(A array, NumberArrayAdapter<?,? super A> adapter)
Vector	Vector.Factory.newNumberVector(double[] values)
Vector	Vector.Factory.newNumberVector(NumberVector values)
Vector	Vector.normalize() Normalizes this vector to the length of 1.0.
Vector	Vector.plus(Vector v) Returns a new vector which is the result of this vector plus the specified vector.
Vector	Vector.plusEquals(double d) Add a constant value to all dimensions.
Vector	Vector.plusEquals(Vector b) a = a + b.
Vector	Vector.plusTimes(Vector v, double s) Returns a new vector which is the result of this vector plus the specified vector times the given factor.
Vector	Vector.plusTimesEquals(Vector b, double s) a = a + s * b.
Vector	Vector.projection(Matrix v) Projects this row vector into the subspace formed by the specified matrix v.
static Vector	Vector.randomNormalizedVector(int dimensionality) Returns a randomly created vector of length 1.0.
Vector	Vector.rotate90Equals() Rotate vector by 90 degrees.
Vector	Vector.set(int i, double value) Sets the value at the specified row.
Vector	Vector.set(Vector v) Copy the values of another vector into the current vector.
Vector	Vector.times(double s) Returns a new vector which is the result of this vector multiplied by the specified scalar.
Vector	Matrix.times(Vector B) Linear algebraic matrix multiplication, A * B
Vector	Vector.timesEquals(double s) Multiply a matrix by a scalar in place, A = s*A.
Vector	Matrix.transposeTimes(Vector B) Linear algebraic matrix multiplication, AT * B
Vector	AffineTransformation.unhomogeneRelativeVector(Vector v) Project an homogeneous vector back into the original space.
Vector	AffineTransformation.unhomogeneVector(Vector v) Project an homogeneous vector back into the original space.
static Vector	Vector.unitVector(int dimensionality, int i) Returns the ith unit vector of the specified dimensionality.

Methods in de.lmu.ifi.dbs.elki.math.linearalgebra that return types with arguments of type Vector

Modifier and Type	Method and Description
ByteBufferSerializer<Vector>	Vector.Factory.getDefaultSerializer()
Class<? super Vector>	Vector.Factory.getRestrictionClass()

Methods in de.lmu.ifi.dbs.elki.math.linearalgebra with parameters of type Vector

Modifier and Type	Method and Description
void	AffineTransformation.addTranslation(Vector v) Add a translation operation to the matrix
Vector	AffineTransformation.apply(Vector v) Apply the transformation onto a vector
Vector	AffineTransformation.applyInverse(Vector v) Apply the inverse transformation onto a vector
Vector	AffineTransformation.applyRelative(Vector v) Apply the transformation onto a vector
Vector	AffineTransformation.applyRelativeInverse(Vector v) Apply the inverse transformation onto a vector
Vector	Vector.cross3D(Vector other) Cross product for 3d vectors, i.e.
static Matrix	Matrix.diagonal(Vector diagonal) Returns a quadratic Matrix consisting of zeros and of the given values on the diagonal.
int	Vector.SmallSerializer.getByteSize(Vector vec)
int	Vector.ShortSerializer.getByteSize(Vector vec)
int	Vector.VariableSerializer.getByteSize(Vector vec)
Vector	AffineTransformation.homogeneRelativeVector(Vector v) Transform a relative vector into homogeneous coordinates.
Vector	AffineTransformation.homogeneVector(Vector v) Transform an absolute vector into homogeneous coordinates.
Vector	Vector.minus(Vector v) Returns this vector minus the specified vector v.
Vector	Vector.minusEquals(Vector b) a = a - b.
Vector	Vector.minusTimes(Vector v, double s) Returns this vector minus the specified vector v times s.
Vector	Vector.minusTimesEquals(Vector b, double s) a = a - s * b.
Vector	Vector.plus(Vector v) Returns a new vector which is the result of this vector plus the specified vector.
Vector	Vector.plusEquals(Vector b) a = a + b.
Vector	Vector.plusTimes(Vector v, double s) Returns a new vector which is the result of this vector plus the specified vector times the given factor.
Vector	Vector.plusTimesEquals(Vector b, double s) a = a + s * b.
void	CovarianceMatrix.put(Vector val) Add a single value with weight 1.0.
void	Centroid.put(Vector val) Add a single value with weight 1.0.
void	CovarianceMatrix.put(Vector val, double weight) Add data with a given weight.
void	Centroid.put(Vector val, double weight) Add data with a given weight.
Vector	Vector.set(Vector v) Copy the values of another vector into the current vector.
void	Matrix.setCol(int j, Vector column) Sets the jth column of this matrix to the specified column.
void	Matrix.setRow(int j, Vector row) Sets the jth row of this matrix to the specified vector.
Vector	Matrix.times(Vector B) Linear algebraic matrix multiplication, A * B
Matrix	Vector.timesTranspose(Vector B) Linear algebraic matrix multiplication, A * B^T.
void	Vector.SmallSerializer.toByteBuffer(ByteBuffer buffer, Vector vec)
void	Vector.ShortSerializer.toByteBuffer(ByteBuffer buffer, Vector vec)
void	Vector.VariableSerializer.toByteBuffer(ByteBuffer buffer, Vector vec)
double	Vector.transposeTimes(Vector B) Linear algebraic matrix multiplication, AT * B.
Vector	Matrix.transposeTimes(Vector B) Linear algebraic matrix multiplication, AT * B
double	Vector.transposeTimesTimes(Matrix B, Vector c) Linear algebraic matrix multiplication, aT * B * c.
Vector	AffineTransformation.unhomogeneRelativeVector(Vector v) Project an homogeneous vector back into the original space.
Vector	AffineTransformation.unhomogeneVector(Vector v) Project an homogeneous vector back into the original space.

Constructors in de.lmu.ifi.dbs.elki.math.linearalgebra with parameters of type Vector

Constructor and Description
EigenPair(Vector eigenvector, double eigenvalue) Creates a new EigenPair object.

Uses of Vector in de.lmu.ifi.dbs.elki.math.statistics

Fields in de.lmu.ifi.dbs.elki.math.statistics declared as Vector

Modifier and Type	Field and Description
private Vector	MultipleLinearRegression.b The (p+1 x 1) - vector holding the estimated b-values (b0, b1, ..., bp)^T.
private Vector	MultipleLinearRegression.e The (n x 1) - vector holding the estimated residuals (e1, ..., en)^T.
private Vector	MultipleLinearRegression.y The (n x 1) - vector holding the y-values (y1, ..., yn)^T.

Methods in de.lmu.ifi.dbs.elki.math.statistics that return Vector

Modifier and Type	Method and Description
Vector	MultipleLinearRegression.getEstimatedCoefficients() Returns the estimated coefficients
Vector	MultipleLinearRegression.getEstimatedResiduals() Returns the estimated residuals

Methods in de.lmu.ifi.dbs.elki.math.statistics with parameters of type Vector

Modifier and Type	Method and Description
private static Matrix	PolynomialRegression.xMatrix(Vector x, int p)

Constructors in de.lmu.ifi.dbs.elki.math.statistics with parameters of type Vector

Constructor and Description
MultipleLinearRegression(Vector y, Matrix x) Constructor.
PolynomialRegression(Vector y, Vector x, int p) Constructor.

Uses of Vector in de.lmu.ifi.dbs.elki.result.textwriter.writers

Methods in de.lmu.ifi.dbs.elki.result.textwriter.writers with parameters of type Vector

Modifier and Type	Method and Description
void	TextWriterVector.write(TextWriterStream out, String label, Vector v) Serialize an object into the inline section.

Uses of Vector in de.lmu.ifi.dbs.elki.utilities

Methods in de.lmu.ifi.dbs.elki.utilities with parameters of type Vector

Modifier and Type	Method and Description
static String	FormatUtil.format(Vector m) Returns String-representation of Vector.
static String	FormatUtil.format(Vector v, int w, int d) Returns a string representation of this matrix.
static String	FormatUtil.format(Vector m, NumberFormat nf) returns String-representation of Vector.
static String	FormatUtil.format(Vector v, String pre) Returns a string representation of this matrix.

Uses of Vector in de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike

Fields in de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike with type parameters of type Vector

Modifier and Type	Field and Description
static NumberArrayAdapter<Double,Vector>	ArrayLikeUtil.VECTORADAPTER Adapter for vectors.

Methods in de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike with parameters of type Vector

Modifier and Type	Method and Description
Double	VectorAdapter.get(Vector array, int off) Deprecated.
byte	VectorAdapter.getByte(Vector array, int off)
double	VectorAdapter.getDouble(Vector array, int off)
float	VectorAdapter.getFloat(Vector array, int off)
int	VectorAdapter.getInteger(Vector array, int off)
long	VectorAdapter.getLong(Vector array, int off)
short	VectorAdapter.getShort(Vector array, int off)
int	VectorAdapter.size(Vector array)

Uses of Vector in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters

Methods in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters that return types with arguments of type Vector

Modifier and Type	Method and Description
protected List<Vector>	VectorListParameter.parseValue(Object obj)

Constructor parameters in de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters with type arguments of type Vector

Constructor and Description
VectorListParameter(OptionID optionID, ParameterConstraint<List<Vector>> constraint) Constructs a vector list parameter with the given name and description.
VectorListParameter(OptionID optionID, ParameterConstraint<List<Vector>> constraint, boolean optional) Constructs a vector list parameter with the given name and description.
VectorListParameter(OptionID optionID, ParameterConstraint<List<Vector>> constraint, List<Vector> defaultValue) Constructs a vector list parameter with the given name and description.
VectorListParameter(OptionID optionID, ParameterConstraint<List<Vector>> constraint, List<Vector> defaultValue) Constructs a vector list parameter with the given name and description.

Uses of Vector in de.lmu.ifi.dbs.elki.visualization.svg

Methods in de.lmu.ifi.dbs.elki.visualization.svg with parameters of type Vector

Modifier and Type	Method and Description
SVGPath	SVGPath.cubicTo(Vector c1xy, Vector c2xy, Vector xy) Cubic Bezier line to the given coordinates.
SVGPath	SVGPath.drawTo(Vector xy) Draw a line given a series of coordinates.
SVGPath	SVGPath.ellipticalArc(Vector rxy, double ar, double la, double sp, Vector xy) Elliptical arc curve to the given coordinates.
SVGPath	SVGPath.lineTo(Vector xy) Draw a line to the given coordinates.
SVGPath	SVGPath.moveTo(Vector xy) Move to the given coordinates.
SVGPath	SVGPath.quadTo(Vector c1xy, Vector xy) Quadratic Bezier line to the given coordinates.
SVGPath	SVGPath.relativeCubicTo(Vector c1xy, Vector c2xy, Vector xy) Cubic Bezier line to the given relative coordinates.
SVGPath	SVGPath.relativeEllipticalArc(Vector rxy, double ar, double la, double sp, Vector xy) Elliptical arc curve to the given relative coordinates.
SVGPath	SVGPath.relativeLineTo(Vector xy) Draw a line to the given relative coordinates.
SVGPath	SVGPath.relativeMoveTo(Vector xy) Move to the given relative coordinates.
SVGPath	SVGPath.relativeQuadTo(Vector c1xy, Vector xy) Quadratic Bezier line to the given relative coordinates.
SVGPath	SVGPath.relativeSmoothCubicTo(Vector c2xy, Vector xy) Smooth Cubic Bezier line to the given relative coordinates.
SVGPath	SVGPath.relativeSmoothQuadTo(Vector xy) Smooth quadratic Bezier line to the given relative coordinates.
SVGPath	SVGPath.smoothCubicTo(Vector c2xy, Vector xy) Smooth Cubic Bezier line to the given coordinates.
SVGPath	SVGPath.smoothQuadTo(Vector xy) Smooth quadratic Bezier line to the given coordinates.

Uses of Vector in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster

Methods in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster with parameters of type Vector

Modifier and Type	Method and Description
private void	EMClusterVisualization.Instance.drawArc(SVGPath path, Vector cent, Vector pre, Vector nex, Vector oPrev, Vector oNext, double scale) Draw an arc to simulate the hyper ellipse.
protected void	EMClusterVisualization.Instance.drawHullArc(String sname, Vector cent, Polygon chres) Approximate the hull using arcs.
protected void	EMClusterVisualization.Instance.drawHullLines(String sname, Vector cent, Polygon chres) Approximate by convex hull.
protected void	EMClusterVisualization.Instance.drawSphere2D(String sname, Vector cent, Vector[] pc) Draw by approximating a sphere via cubic splines
protected void	EMClusterVisualization.Instance.drawSphere2D(String sname, Vector cent, Vector[] pc) Draw by approximating a sphere via cubic splines
protected Polygon	EMClusterVisualization.Instance.makeHull(Vector[] pc) Build a convex hull to approximate the sphere.
protected Polygon	EMClusterVisualization.Instance.makeHullComplex(Vector[] pc) Build a convex hull to approximate the sphere.

Method parameters in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.cluster with type arguments of type Vector

Modifier and Type	Method and Description
private double	ClusterHullVisualization.Instance.addRecursively(ArrayList<Vector> hull, Hierarchy<Cluster<Model>> hier, Cluster<Model> clus) Recursively add a cluster and its children.

Uses of Vector in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.outlier

Fields in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.outlier with type parameters of type Vector

Modifier and Type	Field and Description
protected Relation<Vector>	COPVectorVisualization.Instance.result The outlier result to visualize

Uses of Vector in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection

Methods in de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot.selection with parameters of type Vector

Modifier and Type	Method and Description
private void	MoveObjectsToolVisualization.Instance.updateDB(DBIDs dbids, Vector movingVector) Updates the objects with the given DBIDs It will be moved depending on the given Vector