JSci.maths.wavelet
Class DiscreteFunction

java.lang.Object
  JSci.maths.wavelet.MultiscaleFunction
      JSci.maths.wavelet.DiscreteFunction

All Implemented Interfaces:

java.lang.Cloneable

Direct Known Subclasses:

SparseDiscreteFunction

public class DiscreteFunction

extends MultiscaleFunction

implements java.lang.Cloneable

This class is used to be able to mix the wavelet and other type of functions such as given signals.

Field Summary

protected AbstractDoubleVector

data

Constructor Summary

DiscreteFunction(double[] v)

Method Summary

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
void	normalize() Makes the L2 norm of the internal array equal to 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

protected AbstractDoubleVector data

Constructor Detail

DiscreteFunction

public DiscreteFunction(double[] v)

Method Detail

setData

public void setData(double[] v)

toString

public java.lang.String toString()

Return a String representation of the object

Specified by:

toString in class MultiscaleFunction

normalize

public final void normalize()

Makes the L2 norm of the internal array equal to 1.

evaluate

public final double[] evaluate()

Return as an array the sampled values of the function

equals

public final boolean equals(java.lang.Object a)

Check if another object is equal to this DiscreteFunction object

Specified by:

equals in class MultiscaleFunction

evaluate

public double[] evaluate(int j1)

Return as an array the sampled values of the function

Specified by:

evaluate in class MultiscaleFunction

mass

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

Compute the mass (integral)

Overrides:

mass in class MultiscaleFunction

Parameters:

a - left boundary of the interval

b - right boundary of the interval

jfin - number of iterations to consider (precision)

norm

public final double norm()

Compute the L2 norm of the signal

norm

public double norm(int j)

Compute the L2 norm of the function

Parameters:

j - number of iterations

clone

public java.lang.Object clone()

Return a copy of this object

Overrides:

clone in class MultiscaleFunction

dimension

public int dimension(int jfin)

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

Specified by:

dimension in class MultiscaleFunction

dimension

public final int dimension()

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

Specified by:

dimension in class MultiscaleFunction

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.

Specified by:

getFilterType in class MultiscaleFunction