com.tagtraum.jipes.audio

Class Novelty.NormGaussianCheckerboardKernel

java.lang.Object

com.tagtraum.jipes.audio.Novelty.GaussianCheckerboardKernel

com.tagtraum.jipes.audio.Novelty.NormGaussianCheckerboardKernel

All Implemented Interfaces:

Novelty.Kernel, FloatAggregateFunction<Matrix>

Enclosing class:

Novelty<I extends AudioBuffer>

public static class Novelty.NormGaussianCheckerboardKernel
extends Novelty.GaussianCheckerboardKernel

Normalized Gaussian checkerboard kernel.
Aggregate values are divided by the maximal possible value a Novelty.GaussianCheckerboardKernel would deliver before they are returned, assuming the input values are between -1 and 1.

Constructor Summary

Constructors

Constructor and Description
NormGaussianCheckerboardKernel(int size)

Method Summary

Modifier and Type	Method and Description
float	aggregate(Matrix distances) Maps a collection (usually an array, an RealAudioBuffer or a List) to a single float value.
static Novelty.NormGaussianCheckerboardKernel	getInstance(int dimension) Creates a normalized Gaussian checkerboard kernel with the given dimension.

Methods inherited from class com.tagtraum.jipes.audio.Novelty.GaussianCheckerboardKernel

getKernel, size, toString

Methods inherited from class java.lang.Object

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

Constructor Detail

NormGaussianCheckerboardKernel

public NormGaussianCheckerboardKernel(int size)

Method Detail

getInstance

public static Novelty.NormGaussianCheckerboardKernel getInstance(int dimension)

Creates a normalized Gaussian checkerboard kernel with the given dimension.

Parameters:

dimension - dimension, preferably even

Returns:

kernel

aggregate

public float aggregate(Matrix distances)

Description copied from interface: FloatAggregateFunction

Maps a collection (usually an array, an RealAudioBuffer or a List) to a single float value.

Specified by:

aggregate in interface FloatAggregateFunction<Matrix>

Overrides:

aggregate in class Novelty.GaussianCheckerboardKernel

Parameters:

distances - collection

Returns:

aggregation value