code: def probability_density(self, X):
          
          self.check_fit()
  
          # make cov positive semi-definite
          covariance = self.covariance * np.identity(self.covariance.shape[0])
          return stats.multivariate_normal.pdf(X, cov=covariance)
docs: Compute probability density function for given copula family.
  
          Args:
              X: `numpy.ndarray` or `pandas.DataFrame`
  
          Returns:
              np.array: Probability density for the input values.