b191f4c981d748e945ab6da4115b36d6d68ce589,cde/evaluation/GoodnessOfFit.py,GoodnessOfFit,fit_estimator,#GoodnessOfFit#Any#,53

Before Change

      self.estimator.fit(self.X, self.Y, verbose=False)
      self.time_to_fit = (time.time() - t_start) * self.n_observations / 1000  // time to fit per 1000 samples

    if print_fit_result: //TODO handle storing plots via the logger --> use logger.log_pyplot()
      self.probabilistic_model.plot(mode="pdf")
      self.estimator.plot()

  def kolmogorov_smirnov_cdf(self, x_cond, n_samples=10**6):
     Calculates Kolmogorov-Smirnov Statistics

    Args:

After Change

        self.plot_true_cond_distr_3d = plt3d_true
        logger.log_pyplot(key=self.task_name, fig=plt3d_true)

      if self.estimator.ndim_x == 1 and self.estimator.ndim_y == 1:
        plt2d = self.estimator.plot2d(show=False)
        plt3d = self.estimator.plot3d(show=False)
        self.plot_fitted_cond_distr_2d = plt2d
        self.plot_fitted_cond_distr_3d = plt3d
        logger.log_pyplot(key=self.task_name + "_fitted_cond_distr_2d", fig=plt2d)
        logger.log_pyplot(key=self.task_name + "_fitted_cond_distr_3d", fig=plt3d)

  def kolmogorov_smirnov_cdf(self, x_cond, n_samples=10**6):
     Calculates Kolmogorov-Smirnov Statistics

    Args:

Instances