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# Class JSci.maths.wavelet.DiscreteFunction

    java.lang.Object
       |
       +----JSci.maths.wavelet.MultiscaleFunction
               |
               +----JSci.maths.wavelet.DiscreteFunction

public class DiscreteFunction
extends MultiscaleFunction
implements Cloneable

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

##

DiscreteFunction()
DiscreteFunction(double[])

##

clone()
  Return a copy of this object
dimension()
  Tells you how many samples you'll get from this function
dimension(int)
  Tells you how many samples you'll get from this function (will not depend on the parameter)
equals(Object)
  Check if another object is equal to this DiscreteFunction object
evaluate()
  Return as an array the sampled values of the function
evaluate(int)
  Return as an array the sampled values of the function
getFilterType()
  This method is used to compute how the number of scaling functions changes from on scale to the other.
mass(double, double, int)
  Compute the mass (integral)
norm()
  Compute the L2 norm of the signal
norm(int)
  Compute the L2 norm of the function
normalize()
  Makes the L2 norm of the internal array equal to 1.
setData(double[])
toString()
  Return a String representation of the object

##

DiscreteFunction

     protected DiscreteFunction()

DiscreteFunction

     public DiscreteFunction(double v[])

##

toString

     public String toString()

  Return a String representation of the object

  Overrides:
    toString in class MultiscaleFunction

normalize

     public void normalize()

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

setData

     public void setData(double v[])

evaluate

     public double[] evaluate()

  Return as an array the sampled values of the function

equals

     public boolean equals(Object a)

  Check if another object is equal to this DiscreteFunction object

  Overrides:
    equals in class MultiscaleFunction

evaluate

     public double[] evaluate(int j1)

  Return as an array the sampled values of the function

  Parameters:
    j - number of iterations (doesn't do anything)
  Overrides:
    evaluate in class MultiscaleFunction

mass

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

  Compute the mass (integral)

  Parameters:
    a - left boundary of the interval
    b - right boundary of the interval
    jfin - number of iterations to consider (precision)
  Overrides:
    mass in class MultiscaleFunction

norm

     public 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 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)

  Overrides:
    dimension in class MultiscaleFunction

dimension

     public int dimension()

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

  Overrides:
    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.

  Overrides:
    getFilterType in class MultiscaleFunction

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