run_test.py

#!/usr/bin/env python

import math

from blb import *

def mean(sample):
  return sum(sample)*1.0/len(sample)

def stddev(sample):
  mn = mean(sample)
  return math.sqrt(sum([(x-mn)*(x-mn) for x in sample])*1.0/(len(sample)-1))

class MeanMean_BLB(BLB):
  def compute_estimate(self, sample):
    return mean(sample)

  def reduce_bootstraps(self, sample):
    return mean(sample)

  def average(self, sample):
    return mean(sample)

class SDMean_BLB(BLB):
  def compute_estimate(self, sample):
    return mean(sample)

  def reduce_bootstraps(self, sample):
    return stddev(sample)

  def average(self, sample):
    return mean(sample)

class MeanSD_BLB(BLB):
  def compute_estimate(self, sample):
    return stddev(sample)

  def reduce_bootstraps(self, sample):
    return mean(sample)

  def average(self, sample):
    return mean(sample)

class SDSD_BLB(BLB):
  def compute_estimate(self, sample):
    return stddev(sample)

  def reduce_bootstraps(self, sample):
    return stddev(sample)

  def average(self, sample):
    return mean(sample)


data = range(10000)

blb = MeanMean_BLB()
result = blb.run(data)
print ("Mean of Mean: ", result)

blb = SDMean_BLB()
result = blb.run(data)
print ("SD of Mean: ", result)

blb = MeanSD_BLB()
result = blb.run(data)
print ("Mean of SD: ", result)

blb = SDSD_BLB()
result = blb.run(data)
print ("SD of SD: ", result)