private void computeScores(){
  final int max=getMaxValue();
  m_lMax=Math.log(max);
  m_llMax=-Math.log((double)max / mPoints);
  if (max > m_minimalMax && ((double)mPoints) / mPointDifferences.size() > m_minimalConcentration) {
    m_pointScores=new TreeMap<Integer,Double>();
    for (    Entry<Integer,Integer> entry : mPointDifferences.entrySet()) {
      final Integer v=entry.getValue();
      if (v > 1) {
        m_pointScores.put(entry.getKey(),m_lMax - Math.log(v));
      }
    }
  }
}

private void computeScores ( ) { final int max = getMaxValue ( ) ; m_lMax = Math . log ( max ) ; m_llMax = - Math . log ( ( double ) max / mPoints ) ; if ( max > m_minimalMax && ( ( double ) mPoints ) / mPointDifferences . size ( ) > m_minimalConcentration ) { m_pointScores = new TreeMap < Integer , Double > ( ) ; for ( Entry < Integer , Integer > entry : mPointDifferences . entrySet ( ) ) { final Integer v = entry . getValue ( ) ; if ( v > 1 ) { m_pointScores . put ( entry . getKey ( ) , m_lMax - Math . log ( v ) ) ; } } } }
calculate the scores for each point in " mpointdifferences " where the score is the log of the ratio between max value and a point ' s value . ( max is the time difference that occurs the most in mpointdifferences and a point ' s value is the number of occurrences for this time difference / point ) . only attempt this calculation if it satistifies the minimal requirements as specified by the property values and if the value is greater than 1 .
