Missing transpose in is_training_ill_conditioned method?

[thartland]

I see in krg_based.py the following method

  def is_training_ill_conditioned(self):
        """
        Check if the training dataset could be an issue and print both
        the dataset correlation matrix condition number and
        minimal distance between two points.
        ----
        Returns true if R is ill_conditionned
        """
        R = self.optimal_par["C"] @ self.optimal_par["C"]

Since C comes from a Cholesky factorization of the matrix R, shouldn't it be the case that R = self.optimal_par["C"] @ self.optimal_par["C"].T? That is $R=CC^{\top}$. Let me know if I'm mistaken and any comments to help clear up my confusion would, as always, be appreciated.