hashgraph_gossip.py

import numpy as np
import sys

from random import randint
from math import ceil

def run_simulation(N, sims):
  threshold = int(0.5 + 2. * N / 3)
  print('{} / {}'.format(threshold, N))
  results = []

  for i in range(sims):
    infections = [False] * N
    infections[0] = True

    n = 0
    while True:
      num_infected = sum(infections)

      if num_infected >= threshold:
        results.append(n)
        break

      next_infections = infections.copy()
      for node in range(N):
        if infections[node]:
          peer = randint(0, N - 2)
          if peer >= node:
            peer += 1
          next_infections[peer] = True

      infections = next_infections
      n += 1

  results = np.array(results)
  print('Results from {} sims'.format(sims))
  print('Mean: {}'.format(results.mean()))
  print('Min: {}'.format(results.min()))
  print('Max: {}'.format(results.max()))

  return results.mean()


if __name__ == '__main__':
  N = int(sys.argv[1]) if len(sys.argv) > 1 else 50
  sims = int(sys.argv[2]) if len(sys.argv) > 1 else 100

  print('Running {} sims with N = {}'.format(sims, N))
  run_simulation(N, sims)