de.lmu.ifi.dbs.elki.math.dimensionsimilarity

Class HSMDimensionSimilarity

java.lang.Object

de.lmu.ifi.dbs.elki.math.dimensionsimilarity.HSMDimensionSimilarity

All Implemented Interfaces:

DimensionSimilarity<NumberVector<?>>, Parameterizable

@Reference(authors="A. Tatu, G. Albuquerque, M. Eisemann, P. Bak, H. Theisel, M. A. Magnor, and D. A. Keim.",
           title="Automated Analytical Methods to Support Visual Exploration of High-Dimensional Data",
           booktitle="IEEE Trans. Visualization and Computer Graphics, 2011",
           url="http://dx.doi.org/10.1109/TVCG.2010.242")
public class HSMDimensionSimilarity
extends Object
implements DimensionSimilarity<NumberVector<?>>

Compute the similarity of dimensions by using a hough transformation. Reference:

A. Tatu, G. Albuquerque, M. Eisemann, P. Bak, H. Theisel, M. A. Magnor, and D. A. Keim.
Automated Analytical Methods to Support Visual Exploration of High- Dimensional Data.
IEEEVisualization and Computer Graphics, 2011.

FIXME: This needs serious TESTING before release. Large parts have been rewritten, but could not be tested at the time of rewriting.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	HSMDimensionSimilarity.Parameterizer Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
static HSMDimensionSimilarity	STATIC Static instance.
private static int	STEPS Angular resolution.
private static SinCosTable	table Precompute sinus and cosinus

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	HSMDimensionSimilarity() Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
void	computeDimensionSimilarites(Database database, Relation<? extends NumberVector<?>> relation, DBIDs subset, DimensionSimilarityMatrix matrix) Compute the dimension similarity matrix
private int	countAboveThreshold(int[][] mat, double threshold) Count the number of cells above the threshold.
private static void	drawLine(int x0, int y0, int x1, int y1, boolean[][] pic) Draw a line onto the array, using the classic Bresenham algorithm.
private int[][]	houghTransformation(boolean[][] mat) Perform a hough transformation on the binary image in "mat".
private long	sumMatrix(int[][] mat) Compute the sum of a matrix.

Methods inherited from class java.lang.Object

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

Field Detail

STATIC

public static final HSMDimensionSimilarity STATIC

Static instance.

STEPS

private static final int STEPS

Angular resolution. Best if divisible by 4: smaller tables. The original publication used 50.

See Also:

Constant Field Values

table

private static final SinCosTable table

Precompute sinus and cosinus

Constructor Detail

HSMDimensionSimilarity

protected HSMDimensionSimilarity()

Constructor. Use static instance instead!

Method Detail

computeDimensionSimilarites

public void computeDimensionSimilarites(Database database,
                               Relation<? extends NumberVector<?>> relation,
                               DBIDs subset,
                               DimensionSimilarityMatrix matrix)

Description copied from interface: DimensionSimilarity

Compute the dimension similarity matrix

Specified by:

computeDimensionSimilarites in interface DimensionSimilarity<NumberVector<?>>

Parameters:

database - Database context

relation - Relation

subset - DBID subset (for sampling / selection)

matrix - Matrix to fill

sumMatrix

private long sumMatrix(int[][] mat)

Compute the sum of a matrix.

Parameters:

mat - Matrix

Returns:

Sum of all elements

countAboveThreshold

private int countAboveThreshold(int[][] mat,
                      double threshold)

Count the number of cells above the threshold.

Parameters:

mat - Matrix

threshold - Threshold

Returns:

Number of elements above the threshold.

houghTransformation

private int[][] houghTransformation(boolean[][] mat)

Perform a hough transformation on the binary image in "mat".

Parameters:

mat - Binary image

Returns:

Hough transformation of image.

drawLine

private static void drawLine(int x0,
            int y0,
            int x1,
            int y1,
            boolean[][] pic)

Draw a line onto the array, using the classic Bresenham algorithm.

Parameters:

x0 - Start X

y0 - Start Y

x1 - End X

y1 - End Y

pic - Picture array