lotto.py

#!/usr/bin/env python3

import random
from statistics import *

def game (days, hitrate, moneypart):
  money=1
  for i in range(days):
    if random.random()<hitrate:
      money*=1+moneypart
    else:
      money*=1-moneypart
  return money

def statfor(days, hitrate, moneypart, games):
  return Statistics((game(days, hitrate, moneypart) for i in range(games)),)

statistics.py

#!/usr/bin/env python3

from sortedcontainers import SortedList

class Statistics:
  CUT_PERCENTAGE=0.05 # from each side
  def __init__ (self, elements=[]):
    self.__sum=0
    self.__multiply=1
    self.__zeroes_count=0
    self.__square_sum=0
    self.__edges=0
    self.__edges_count=0
    self.__median_index=0
    self.__deviation=0
    self.__deviation_computed=False
    self.__nums=SortedList()
    self.count=0
    for e in elements:
      self.insert(e)

  def __repr__ (self):
    return "<Statistics of: {}>".format(self.__nums.as_list())

  def insert (self, element):
    self.count+=1
    self.__nums.add(element)
    self.__sum+=element
    if element!=0:
      self.__multiply*=element
    else:
      self.__zeroes_count+=1
    self.__square_sum+=element**2
    self.__deviation_computed=False

  def erase (self, element):
    if element not in self.__nums:
      return
    self.count-=1
    self.__nums.discard(element)
    self.__sum-=element
    if element!=0:
      self.__multiply/=element
    else:
      self.__zeroes_count-=1
    self.__square_sum-=element**2
    self.__deviation_computed=False

  def aritmetic_average (self):
    if self.count==0:
      return float("nan")
    else:
      return self.__sum/self.count

  def geometric_average (self):
    if self.count==0:
      return float("nan")
    elif self.__zeroes_count!=0:
      return 0
    else:
      return self.__multiply**(1/self.count)

  def square_average (self):
    if self.count==0:
      return float("nan")
    else:
      return (self.__square_sum/self.count)**0.5

  def median (self):
    if self.count==0:
      return float("nan")
    else:
      return self.__nums[self.__median_index]

  def standard_deviation (self):
    if self.count==0:
      return float("nan")
    else:
      if not self.__deviation_computed:
        self.__deviation_computed=True
        self.__deviation=0
        average=self.aritmetic_average()
        for e in self.__nums:
          self.__deviation+=(e-average)**2
        self.__deviation/=self.count
        self.__deviation**=0.5
      return self.__deviation

  def minimum (self):
    if self.count==0:
      return float("nan")
    else:
      return self.__nums[0]

  def percentage_minimum (self, p):
    if self.count==0:
      return float("nan")
    else:
      return self.__nums[int(self.count*p/100)]

  def maximum (self):
    if self.count==0:
      return float("nan")
    else:
      return self.__nums[-1]

  def percentage_maximum (self, p):
    if self.count==0:
      return float("nan")
    else:
      return self.__nums[-1-int(self.count*p/100)]