Power-law apache.commons

powerlaw.scala

import org.apache.commons.math3.distribution.ZipfDistribution

var zipfGenerator : ZipfDistribution = null

/*
assume that B never changes, thus we need to initialize the zipfGenerator only once
we do it the first time we try to get a value for zipfDistribution
x0 -> from (1)
x1 -> to   (n/2)
b  -> beta (1.5) // in paper it's -1.5 but here it should be positive and produces same values

can be rewritten with specific (init) function which takes x0, x1, beta and creates generator
later getZipf can be completely replaced by zipfGenerator.sample()
*/
def getZipf(x0 : Int, x1 : Int, b : Double) : Int = {
  if (zipfGenerator == null) {
    initZipf(x0, x1, b)
  }
  zipfGenerator.sample()
}

def initZipf(x0: Int, x1 : Int, b : Double) : Unit = {
  zipfGenerator = new ZipfDistribution(1+x1-x0, b)
}

def fastMutate(source : MatrixGraph, beta : Double) : MatrixGraph = {
  /*...*/
  val len = source.capacities.size()
  val fastNumber = MathUtil.getZipf(1, len, beta)
  val numberToMutate = MathUtil.getBinomial(len, 1.0*fastNumber/len)
  val positions = MathUtil.getChangePositions(numberToMutate, source.capacities.size)
  /*...*/
}