comirva.config
Class ProbabilisticNetworkConfig

java.lang.Object
  comirva.config.ProbabilisticNetworkConfig

Direct Known Subclasses:

ProbabilisticNetworkDefaultConfig

public class ProbabilisticNetworkConfig
extends Object

This class represents a configuration for a Probabilistic-Network-Visualization. It is used to pass a configuration to the visualization pane.

Constructor Summary

ProbabilisticNetworkConfig(int maxEdgeThickness, int maxDistReduction, int maxVertexDiameter, int minVertexDiameter, double probCorrection, int adaptationRunsEpochs, double adaptationThreshold, int gridSize)
Creates a new instance of a Probabilistic-Network-Configuration.

Method Summary

int	getAdaptationRunsEpochs() Returns the number of iterations in epochs the adaptation process is performed.
double	getAdaptationThreshold() Returns the adaptation threshold.
int	getGridSize() Returns the grid size used for vertex placement.
int	getMaxDistReduction() Returns the maximum distance reduction between two data points in the adaptation process.
int	getMaxEdgeThickness() Returns the maximum thickness for an edge.
int	getMaxVertexDiameter() Returns the maximum vertex diameter for a data point.
int	getMinVertexDiameter() Returns the minimum vertex diameter for a data point.
double	getProbCorrection() Returns the probability correction for drawing edges.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

ProbabilisticNetworkConfig

public ProbabilisticNetworkConfig(int maxEdgeThickness,
                                  int maxDistReduction,
                                  int maxVertexDiameter,
                                  int minVertexDiameter,
                                  double probCorrection,
                                  int adaptationRunsEpochs,
                                  double adaptationThreshold,
                                  int gridSize)

Creates a new instance of a Probabilistic-Network-Configuration.

Parameters:

maxEdgeThickness - the maximum thickness of an edge

maxDistReduction - the maximum distance reduction between two vertices in each adaptation iteration

maxVertexDiameter - the maximum diameter for the data points (vertices)

minVertexDiameter - the minimum diameter for the data points (vertices)

probCorrection - the probability correction (PC) for drawing edges; edge(i,j) is drawn if similarity(i,j) > randomValue[0,1]*PC

adaptationRunsEpochs - the number of adaptation iterations in epochs (1 epoch = number of data items ^ 2 runs)

adaptationThreshold - adaptation threshold (AT); distance(i,j) is adapted only if similarity(i,j) > AT

gridSize - the grid size in pixels; data points are snapped to the grid automatically

Method Detail

getMaxEdgeThickness

public int getMaxEdgeThickness()

Returns the maximum thickness for an edge.

Returns:

the maximum thickness for an edge

getMaxDistReduction

public int getMaxDistReduction()

Returns the maximum distance reduction between two data points in the adaptation process.

Returns:

the maximum distance reduction

getMaxVertexDiameter

public int getMaxVertexDiameter()

Returns the maximum vertex diameter for a data point.

Returns:

the maximum diameter for a vertex

getMinVertexDiameter

public int getMinVertexDiameter()

Returns the minimum vertex diameter for a data point.

Returns:

the minimum diameter for a vertex

getProbCorrection

public double getProbCorrection()

Returns the probability correction for drawing edges. An edge between data point (vertex) i and j is drawn with a probability that equals the similarity between i and j multiplied with the probability correction.

Returns:

the probability correction

getAdaptationRunsEpochs

public int getAdaptationRunsEpochs()

Returns the number of iterations in epochs the adaptation process is performed. One epoch means that, on average, each pair of data items is selected for adaptation once. Thus, one epoch means that the adaptation is iterated numberOfDataItems^2 times.

Returns:

the number of epochs the adaptation process is performed

getAdaptationThreshold

public double getAdaptationThreshold()

Returns the adaptation threshold. The output distance is adapted only for those data items i, j that have a similarity greater than the adaptation threshold.

Returns:

the adaptation threshold

getGridSize

public int getGridSize()

Returns the grid size used for vertex placement.

Returns:

the grid size in pixels