code: def do_bestfit(self):
          
          self.check_important_variables()
          logx = np.log(self.args["x"])
          logy = np.log(self.args["y"])
          self.fit_args_log = np.polyfit(logx, logy, 1)
          self.fit_args = self.fit_args_log[:]
          self.fit_args[1] = np.exp(self.fit_args[1])
          self.done_bestfit = True
          return self.fit_args
docs: Method to get fit_args after getting necessary variables