class_docstr: Implements a data generating process that returns data having quadratic relationship between the treatment, outcome and confounders
class_docstr_tok: ["Implements","a","data","generating","process","that","returns","data","having","quadratic","relationship","between","the","treatment",",","outcome","and","confounders"]
code: def generation_process(self):
      self.weights["confounder=>treatment"] = self.generate_weights(
          (len(self.confounder), len(self.treatment))
      )
      self.weights["confounder=>outcome"] = self.generate_weights(
          (len(self.confounder), len(self.outcome))
      )
      self.weights["effect_modifier=>outcome"] = self.generate_weights(
          (len(self.effect_modifier), len(self.outcome))
      )
      self.weights["treatment=>outcome"] = self.generate_weights(
          (len(self.treatment), len(self.outcome))
      )
  
      self.bias["confounder=>treatment"] = self.generate_bias(
          len(self.treatment)
      )
      self.bias["confounder=>outcome"] = self.generate_bias(
          len(self.outcome)
      )
  
file_path: dowhy/dowhy/utils/dgps/quadratic_dgp.py
imports: import numpy
  import pandas
  from dowhy.utils.dgp import DataGeneratingProcess
label_desc: Use image node_id 3 for calling the QuadraticDataGeneratingProcess obj's underlying member method code with example usage: obj.generation_process() without return types