JSci.maths.wavelet

Class SparseDiscreteFunction

java.lang.Object

JSci.maths.wavelet.MultiscaleFunction

JSci.maths.wavelet.DiscreteFunction

JSci.maths.wavelet.SparseDiscreteFunction

All Implemented Interfaces:

java.lang.Cloneable

public class SparseDiscreteFunction
extends DiscreteFunction
implements java.lang.Cloneable

Field Summary

Fields

Modifier and Type	Field and Description
DoubleSparseVector	Data

Constructor Summary

Constructors

Constructor and Description
SparseDiscreteFunction(double[] v)

Method Summary

Methods

Modifier and Type	Method and Description
java.lang.Object	clone() Return a copy of this object
int	dimension() Tells you how many samples you'll get from this function
int	dimension(int jfin) Tells you how many samples you'll get from this function (will not depend on the parameter)
boolean	equals(java.lang.Object a) Check if another object is equal to this DiscreteFunction object
double[]	evaluate() Return as an array the sampled values of the function
double[]	evaluate(int j1) Return as an array the sampled values of the function
int	getFilterType() This method is used to compute how the number of scaling functions changes from on scale to the other.
double	mass(double a, double b, int jfin) Compute the mass (integral)
double	norm() Compute the L2 norm of the signal
double	norm(int j) Compute the L2 norm of the function The parameter doesn't do anything.
void	normalize() Makes the L2norm of the internal array=1.
void	setData(double[] v)
java.lang.String	toString() Return a String representation of the object

Methods inherited from class JSci.maths.wavelet.MultiscaleFunction

mass

Methods inherited from class java.lang.Object

finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Detail

Data

public DoubleSparseVector Data

Constructor Detail

SparseDiscreteFunction

public SparseDiscreteFunction(double[] v)

Method Detail

toString

public java.lang.String toString()

Return a String representation of the object

Overrides:

toString in class DiscreteFunction

normalize

public void normalize()

Makes the L2norm of the internal array=1.

Overrides:

normalize in class DiscreteFunction

setData

public void setData(double[] v)

Overrides:

setData in class DiscreteFunction

evaluate

public double[] evaluate()

Return as an array the sampled values of the function

Overrides:

evaluate in class DiscreteFunction

equals

public boolean equals(java.lang.Object a)

Check if another object is equal to this DiscreteFunction object

Overrides:

equals in class DiscreteFunction

evaluate

public double[] evaluate(int j1)

Return as an array the sampled values of the function

Overrides:

evaluate in class DiscreteFunction

Parameters:

j - number of iterations (doesn't do anything)

mass

public double mass(double a,
          double b,
          int jfin)

Compute the mass (integral)

Overrides:

mass in class DiscreteFunction

Parameters:

a - left boundary of the interval

b - right boundary of the interval

jfin - number of iterations to consider (precision)

norm

public double norm()

Compute the L2 norm of the signal

Overrides:

norm in class DiscreteFunction

norm

public double norm(int j)

Compute the L2 norm of the function The parameter doesn't do anything.

Overrides:

norm in class DiscreteFunction

Parameters:

j - number of iterations

clone

public java.lang.Object clone()

Return a copy of this object

Overrides:

clone in class DiscreteFunction

dimension

public int dimension(int jfin)

Tells you how many samples you'll get from this function (will not depend on the parameter)

Overrides:

dimension in class DiscreteFunction

dimension

public int dimension()

Tells you how many samples you'll get from this function

Overrides:

dimension in class DiscreteFunction

getFilterType

public int getFilterType()

This method is used to compute how the number of scaling functions changes from on scale to the other. Basically, if you have k scaling function and a Filter of type t, you'll have 2*k+t scaling functions at the next scale (dyadic case). Notice that this method assumes that one is working with the dyadic grid while the method "previousDimension" define in the interface "Filter" doesn't.

Overrides:

getFilterType in class DiscreteFunction