class_docstr: Base class for Continuous distributions 
class_docstr_tok: ["Base","class","for","Continuous","distributions"]
docstr: Returns samples drawn from distribution. 
docstr_tok: ["Returns","samples","drawn","from","distribution","."]
code: def draw_samples(self, method, size=None, init_sample=None, *args):
      """Returns samples drawn from distribution."""
      if method == "random":
          return self.draw_samples_random(size)
      elif method == "nuts":
          return self.draw_samples_nuts(size, init_sample, *args)
      elif method == "slice":
          return self.draw_samples_slice(size, init_sample, *args)
      elif method == "metropolis":
          return self.draw_samples_metropolis(size, init_sample, *args)
  
imports: from ..sampling.slice import Slice
  from ..sampling.metropolis import Metropolis, BinaryMetropolis
  from ..sampling.nuts import NoUTurnSamplerDA, LeapFrog
label_desc: Use image node_id 3 for calling the Continuous obj's underlying member method code with example usage: obj.draw_samples(method, size, init_sample) and returns: self, self, self, self