public SweetSpotSimilarity() 
{
    
    super();
}

 public float baselineTf(float freq) 
{
    if (0.0f == freq) return 0.0f;
    return (freq < = tf_min)
      ? tf_base
      : (float)Math.sqrt(freq + (tf_base * tf_base) - tf_min);
}

Implemented as: (x <= min) ? base : sqrt(x+(base**2)-min) ...but with a special case check for 0.

This degrates to sqrt(x) when min and base are both 0

 public float hyperbolicTf(float freq) 
{
    if (0.0f == freq) return 0.0f;
    final float min = tf_hyper_min;
    final float max = tf_hyper_max;
    final double base = tf_hyper_base;
    final float xoffset = tf_hyper_xoffset;
    final double x = (double)(freq - xoffset);
    final float result = min +
      (float)(
              (max-min) / 2.0f
              *
              (
               ( ( Math.pow(base,x) - Math.pow(base,-x) )
                 / ( Math.pow(base,x) + Math.pow(base,-x) )
                 )
               + 1.0d
               )
              );
    return Float.isNaN(result) ? max : result;
}

Uses a hyperbolic tangent function that allows for a hard max... tf(x)=min+(max-min)/2*(((base**(x-xoffset)-base**-(x-xoffset))/(base**(x-xoffset)+base**-(x-xoffset)))+1)

This code is provided as a convincience for subclasses that want to use a hyperbolic tf function.

 public float lengthNorm(String fieldName,
    int numTerms) 
{
    int l = ln_min;
    int h = ln_max;
    float s = ln_steep;
    if (ln_mins.containsKey(fieldName)) {
      l = ((Number)ln_mins.get(fieldName)).intValue();
    }
    if (ln_maxs.containsKey(fieldName)) {
      h = ((Number)ln_maxs.get(fieldName)).intValue();
    }
    if (ln_steeps.containsKey(fieldName)) {
      s = ((Number)ln_steeps.get(fieldName)).floatValue();
    }
    return (float)
      (1.0f /
       Math.sqrt
       (
        (
         s *
         (float)(Math.abs(numTerms - l) + Math.abs(numTerms - h) - (h-l))
         )
        + 1.0f
        )
       );
}

Implemented as: 1/sqrt( steepness * (abs(x-min) + abs(x-max) - (max-min)) + 1 ) .

This degrades to 1/sqrt(x) when min and max are both 1 and steepness is 0.5

:TODO: potential optimiation is to just flat out return 1.0f if numTerms is between min and max.

 public  void setBaselineTfFactors(float base,
    float min) 
{
    tf_min = min;
    tf_base = base;
}

Sets the baseline and minimum function variables for baselineTf

 public  void setHyperbolicTfFactors(float min,
    float max,
    double base,
    float xoffset) 
{
    tf_hyper_min = min;
    tf_hyper_max = max;
    tf_hyper_base = base;
    tf_hyper_xoffset = xoffset;
}

Sets the function variables for the hyperbolicTf functions

 public  void setLengthNormFactors(int min,
    int max,
    float steepness) 
{
    this.ln_min = min;
    this.ln_max = max;
    this.ln_steep = steepness;
}

Sets the default function variables used by lengthNorm when no field specifc variables have been set.

 public  void setLengthNormFactors(String field,
    int min,
    int max,
    float steepness) 
{
    ln_mins.put(field, new Integer(min));
    ln_maxs.put(field, new Integer(max));
    ln_steeps.put(field, new Float(steepness));
}

Sets the function variables used by lengthNorm for a specific named field

 public float tf(int freq) 
{
    return baselineTf(freq);
}

Delegates to baselineTf