code: def assemble_transition_model_from_gradable_adjectives(self):
          
  
          df = pd.read_sql_table("gradableAdjectiveData", con=engine)
          gb = df.groupby("adjective")
  
          rs = gaussian_kde(
              flatMap(
                  lambda g: gaussian_kde(get_respdevs(g[1]))
                  .resample(self.res)[0]
                  .tolist(),
                  gb,
              )
          ).resample(self.res)[0]
  
          for edge in self.edges(data=True):
              edge[2]["ConditionalProbability"] = constructConditionalPDF(
                  gb, rs, edge
              )
              edge[2]["βs"] = np.tan(
                  edge[2]["ConditionalProbability"].resample(self.res)[0]
              )
docs: Add probability distribution functions constructed from gradable
          adjective data to the edges of the analysis graph data structure.
  
          Args:
              adjective_data
              res