text: import matplotlib.pyplot as plt
  import random
  import math
  
  rate = 1
  def exponentialRandom():
      uniform = random.random()
      return -math.log(uniform) / rate
  
  samples = []
  
  N = 1000
  for i in range(N):
      samples.append(exponentialRandom())
  
  fig, axs = plt.subplots(1, 1, sharey=True, tight_layout=True)
  
  axs.set_title("Clover spawning")
  axs.set_ylabel("Number of instances (N = {})".format(N))
  axs.set_xlabel("Distance from parent")
  
  axs.hist(samples, bins=15)
  
  plt.show()
  