code: def get_correlations(self, chain=0, parameters=None):
          
          parameters, cov = self.get_covariance(chain=chain, parameters=parameters)
          diag = np.sqrt(np.diag(cov))
          divisor = diag[None, :] * diag[:, None]
          correlations = cov / divisor
          return parameters, correlations
docs: Takes a chain and returns the correlation between chain parameters.
  
          Parameters
          ----------
          chain : int|str, optional
              The chain index or name. Defaults to first chain.
          parameters : list[str], optional
              The list of parameters to compute correlations. Defaults to all parameters
              for the given chain.
  
          Returns
          -------
              tuple
                  The first index giving a list of parameter names, the second index being the
                  2D correlation matrix.