class_docstr: Base class for a sampler from the interventional distribution.
class_docstr_tok: ["Base","class","for","a","sampler","from","the","interventional","distribution","."]
code: def do_sample(self, x):
      self.reset()
      self.disrupt_causes()
      self.make_treatment_effective(x)
      if self.point_sampler:
          self.point_sample()
      else:
          self.sample()
      return self._df
  
file_path: dowhy/dowhy/do_sampler.py
imports: import logging
  from typing import List
  import networkx
  import numpy
  import pandas
  from dowhy import EstimandType, identify_effect_auto
  from dowhy.utils.api import parse_state
label_desc: Use image node_id 8 for calling the DoSampler obj's underlying member method code with example usage: obj.do_sample(x) and returns: self