code: def __call__(self, i):
      # This way the plot can continuously run and we just keep
      # watching new realizations of the process
      if i == 0:
          self.success = 0
          self.line.set_data([], [])
          return (self.line,)
  
      # Choose success based on exceed a threshold with a uniform pick
      if np.random.rand() < self.prob:
          self.success += 1
      y = beta_pdf(self.x, self.success + 1, (i - self.success) + 1)
      self.line.set_data(self.x, y)
      return (self.line,)
  
file_path: matplotlib/galleries/examples/animation/bayes_update.py
imports: import math
  import matplotlib.pyplot
  import numpy
  from matplotlib.animation import FuncAnimation
label_desc: Use image node_id 3 for calling the UpdateDist obj's underlying member method code with example usage: obj.__call__(i) and returns: self, self