Uses of Class
at.tuwien.ifs.somtoolbox.layers.metrics.MetricException

Packages that use MetricException
at.tuwien.ifs.somtoolbox.apps.analysis   
at.tuwien.ifs.somtoolbox.data Classes in this package implement reading, storing and providing of different data needed for the SOM, e.g. 
at.tuwien.ifs.somtoolbox.data.distance   
at.tuwien.ifs.somtoolbox.layers Provides the basic classes constituting SOM-based neural networks. 
at.tuwien.ifs.somtoolbox.layers.metrics This package contains the metrics used for distance calculation during training and for mapping data onto maps. 
at.tuwien.ifs.somtoolbox.layers.quality Classes in this package implement various quality measures, indicating the quality of the SOM mapping. 
at.tuwien.ifs.somtoolbox.util Provides various helper classes. 
at.tuwien.ifs.somtoolbox.visualization Provides classes creating visualisations of trained SOMs. 
at.tuwien.ifs.somtoolbox.visualization.clustering Contains classes implementing clustering methods on the SOM. 
at.tuwien.ifs.somtoolbox.visualization.comparison   
 

Uses of MetricException in at.tuwien.ifs.somtoolbox.apps.analysis
 

Methods in at.tuwien.ifs.somtoolbox.apps.analysis that throw MetricException
private  void PlaylistAnalysis.analyse(File[] listFiles, boolean rawVal)
           
private  void PlaylistAnalysis.analyse(File file, boolean rawVal)
           
private  void PlaylistAnalysis.analyseDir(File file, boolean rawVal)
           
 

Uses of MetricException in at.tuwien.ifs.somtoolbox.data
 

Methods in at.tuwien.ifs.somtoolbox.data that throw MetricException
 InputDatum[] AbstractSOMLibSparseInputData.getByNameDistanceSorted(double[] vector, Collection<String> inputNames, DistanceMetric metric)
          Retrieves the InputDatum corresponding to the given input names, and sorted by their distance to the given vector.
 ArrayList<InputDistance> AbstractSOMLibSparseInputData.getDistances(int inputIndex, DistanceMetric metric)
          Returns the distances to the index of the given vector of the dataset.
 InputDatum[] AbstractSOMLibSparseInputData.getNearestN(double[] vector, DistanceMetric metric, int number)
          Retrieves the given number of InputDatum that are closest to the given vector.
 InputDatum[] AbstractSOMLibSparseInputData.getNearestN(int inputIndex, DistanceMetric metric, int number)
          Returns the n nearest input vectors for the index of the given vector of the dataset.
 InputDatum[] AbstractSOMLibSparseInputData.getNearestNUnsorted(int inputIndex, DistanceMetric metric, int number)
           
 void AbstractSOMLibSparseInputData.initDistanceMatrix(DistanceMetric metric)
          Calculates the AbstractSOMLibSparseInputData.distanceMatrix - careful, this is a lengthy process and should be done only if needed.
 

Uses of MetricException in at.tuwien.ifs.somtoolbox.data.distance
 

Methods in at.tuwien.ifs.somtoolbox.data.distance that throw MetricException
static void DistanceMatrixWriter.writeOrangeFileInputVectorDistanceMatrix(InputData data, String fileName, DistanceMetric metric)
          Write input distance matrix to an ASCII file for the Orange data mining toolkit ((http://www.ailab.si/orange/), computing distances on the fly.
static void DistanceMatrixWriter.writePlainFileInputVectorDistanceMatrix(InputData data, String fileName, DistanceMetric metric)
          Write input distance matrix to an ASCII file in plain format, computing distances on the fly.
static void DistanceMatrixWriter.writeRandomAccessFileInputVectorDistanceMatrix(double[][] distances, String fileName, DistanceMetric metric)
          Write pre-calculated input distance matrix to a binary file.
static void DistanceMatrixWriter.writeRandomAccessFileInputVectorDistanceMatrix(InputData data, String fileName, DistanceMetric metric)
          Write input distance matrix to a binary file, computing distances on the fly.
static void DistanceMatrixWriter.writeSOMLibFileInputVectorDistanceMatrix(double[][] distances, String fileName, DistanceMetric metric, boolean gzip)
          Write pre-calculated input distance matrix to an ASCII file in SOMLib format.
static void DistanceMatrixWriter.writeSOMLibFileInputVectorDistanceMatrix(InputData data, String fileName, DistanceMetric metric)
          Write input distance matrix to ASCII file, computing distances on the fly.
static void DistanceMatrixWriter.writeSOMLibFileInputVectorDistanceMatrix(InputData data, String fileName, DistanceMetric metric, boolean gzip)
          Write input distance matrix to ASCII file, computing distances on the fly.
 

Constructors in at.tuwien.ifs.somtoolbox.data.distance that throw MetricException
AbstractMemoryInputVectorDistanceMatrix(InputData data, DistanceMetric metric)
          Constructs the distance matrix by computing the distances on the fly.
FullMemoryInputVectorDistanceMatrix(InputData data, DistanceMetric metric)
           
LeightWeightMemoryInputVectorDistanceMatrix(InputData data, DistanceMetric metric)
           
 

Uses of MetricException in at.tuwien.ifs.somtoolbox.layers
 

Methods in at.tuwien.ifs.somtoolbox.layers that throw MetricException
 String[] GrowingLayer.getNNearestInputs(String datumlabel, int n, InputData data)
           
 

Uses of MetricException in at.tuwien.ifs.somtoolbox.layers.metrics
 

Methods in at.tuwien.ifs.somtoolbox.layers.metrics that throw MetricException
protected  void AbstractMetric.checkDimensions(double[] vector1, double[] vector2)
          Performs a check on wether the given vectors have the same dimension.
protected  void AbstractMetric.checkDimensions(cern.colt.matrix.DoubleMatrix1D vector1, cern.colt.matrix.DoubleMatrix1D vector2)
          Performs a check on wether the given vectors have the same dimension.
 double DistanceMetric.distance(double[] vector1, double[] vector2)
          Calculates the distance between two vectors provided by argument vector1 and vector2.
abstract  double AbstractMetric.distance(double[] vector1, double[] vector2)
           
 double L2MetricSparse.distance(double[] vector1, double[] vector2)
           
 double LnAlphaMetric.distance(double[] vector1, double[] vector2)
           
 double CosineMetric.distance(double[] vector1, double[] vector2)
           
 double L1Metric.distance(double[] vector1, double[] vector2)
           
 double MissingValueMetricWrapper.distance(double[] vector1, double[] vector2)
           
 double MahalanobisMetric.distance(double[] vector1, double[] vector2)
           
 double LnMetric.distance(double[] vector1, double[] vector2)
           
 double L2Metric.distance(double[] vector1, double[] vector2)
           
 double L2MetricFast.distance(double[] vector1, double[] vector2)
           
 double LInfinityMetric.distance(double[] vector1, double[] vector2)
           
 double AbstractWeightedMetric.distance(double[] vector1, double[] vector2)
           
 double L2MetricWeighted.distance(double[] vector1, double[] vector2, double[] featureWeights)
           
abstract  double AbstractWeightedMetric.distance(double[] vector1, double[] vector2, double[] weights)
           
 double DistanceMetric.distance(double[] vector1, cern.colt.matrix.DoubleMatrix1D vector2)
          Calculates the distance between two vectors provided by argument vector1 and vector2.
 double AbstractMetric.distance(double[] vector1, cern.colt.matrix.DoubleMatrix1D vector2)
           
 double DistanceMetric.distance(double[] vector, InputDatum datum)
          Calculates the distance between two vectors provided by argument vector and datum.
 double AbstractMetric.distance(double[] vector, InputDatum data)
           
 double AbstractWeightedMetric.distance(double[] vector, Unit unit)
           
 double DistanceMetric.distance(cern.colt.matrix.DoubleMatrix1D vector1, double[] vector2)
          Calculates the distance between two vectors provided by argument vector1 and vector2.
 double AbstractMetric.distance(cern.colt.matrix.DoubleMatrix1D vector1, double[] vector2)
           
 double DistanceMetric.distance(cern.colt.matrix.DoubleMatrix1D vector1, cern.colt.matrix.DoubleMatrix1D vector2)
          Calculates the distance between two vectors provided by argument vector1 and vector2.
 double AbstractMetric.distance(cern.colt.matrix.DoubleMatrix1D vector1, cern.colt.matrix.DoubleMatrix1D vector2)
           
 double CosineMetric.distance(cern.colt.matrix.DoubleMatrix1D vector1, cern.colt.matrix.DoubleMatrix1D vector2)
           
 double L1Metric.distance(cern.colt.matrix.DoubleMatrix1D vector1, cern.colt.matrix.DoubleMatrix1D vector2)
           
 double LnMetric.distance(cern.colt.matrix.DoubleMatrix1D vector1, cern.colt.matrix.DoubleMatrix1D vector2)
           
 double DistanceMetric.distance(cern.colt.matrix.DoubleMatrix1D vector, InputDatum datum)
          Calculates the distance between two vectors provided by argument vector and datum.
 double AbstractMetric.distance(cern.colt.matrix.DoubleMatrix1D vector, InputDatum datum)
           
 double DistanceMetric.distance(InputDatum datum, double[] vector)
          Calculates the distance between two vectors provided by argument datum and vector.
 double AbstractMetric.distance(InputDatum data, double[] vector)
           
 double DistanceMetric.distance(InputDatum datum, cern.colt.matrix.DoubleMatrix1D vector)
          Calculates the distance between two vectors provided by argument datum and vector.
 double AbstractMetric.distance(InputDatum datum, cern.colt.matrix.DoubleMatrix1D vector)
           
 double DistanceMetric.distance(InputDatum datum, InputDatum datum2)
          Calculates the distance between two vectors provided by argument datum and datum2.
 double AbstractMetric.distance(InputDatum datum, InputDatum datum2)
           
 double MnemonicSOMMetric.distance(InputDatum datum1, InputDatum datum2)
           
 double AbstractWeightedMetric.distance(InputDatum inputDatum, Unit unit)
           
 double LnAlphaMetric.distanceFromPrecalc(double[] vector1, double[] vector2)
           
static void CosineMetric.main(String[] args)
          Main method to test the metric.
static double[] AbstractMetric.meanVector(double[] vector1, double[] vector2)
          Calculates the mean vector of two double array vectors.
 void LnAlphaMetric.setMetricParams(String metricParamString)
          Sets specific parameters for the LnAlpha metric, namely alpha and n.
 

Uses of MetricException in at.tuwien.ifs.somtoolbox.layers.quality
 

Methods in at.tuwien.ifs.somtoolbox.layers.quality that throw MetricException
private  double SOMDistortion.squaredDistance(InputDatum datum, double[] vector2)
           
 

Uses of MetricException in at.tuwien.ifs.somtoolbox.util
 

Methods in at.tuwien.ifs.somtoolbox.util that throw MetricException
static double[] VectorTools.multiply(double[] a, double[] b)
           
 

Uses of MetricException in at.tuwien.ifs.somtoolbox.visualization
 

Methods in at.tuwien.ifs.somtoolbox.visualization that throw MetricException
private  void FlowBorderlineVisualizer.calculateFlows()
          Formel 8, 9 10, 11, 12, 13, 14, 15, 16
 cern.colt.matrix.DoubleMatrix2D PMatrix.createPMatrix(GrowingSOM gsom)
           
 cern.colt.matrix.DoubleMatrix2D PMatrix.createUStarMatrix(GrowingSOM gsom)
           
private  double FlowBorderlineVisualizer.df(int x1, int y1, int x2, int y2)
          Formel 1 distance in feature space
 

Uses of MetricException in at.tuwien.ifs.somtoolbox.visualization.clustering
 

Methods in at.tuwien.ifs.somtoolbox.visualization.clustering that throw MetricException
 double LabelCoordinates.distance(LabelCoordinates other)
          Calculate euclidean distance between this point and the other point
 

Uses of MetricException in at.tuwien.ifs.somtoolbox.visualization.comparison
 

Methods in at.tuwien.ifs.somtoolbox.visualization.comparison that throw MetricException
static double[][] SOMComparison.calculcateIntraSOMDistanceMatrix(LabelCoordinates[] coords)
          Calculate the distance matrix for all mapped vectors from the information where the inputs are mapped