docs: def get_normed_x(self, rows=None, cols=None):
          """ Returns the normalized input data requested by the user
              @ In, rows, a list of non-negative integers specifying the
              row indices to return
              @ In, cols, a list of non-negative integers specifying the
              column indices to return
              @ Out, a matrix of floating point values specifying the
              normalized data values used in internal computations
              filtered by the three input parameters.
          """
          if rows is None:
              rows = list(range(0, self.get_sample_size()))
          if cols is None:
              cols = list(range(0, self.get_dimensionality()))
  
          if not hasattr(rows, "__iter__"):
              rows = [rows]
          rows = sorted(list(set(rows)))
  
          retValue = self.Xnorm[rows, :]
          return retValue[:, cols]