docs: def impute(self, M_c, X_L, X_D, Y, Q, seed, n):
          """Impute values from predictive distribution of the given latent state.
  
          :param Y: A list of constraints to apply when sampling.  Each constraint
              is a triplet of (r,d,v): r is the row index, d is the column
              index and v is the value of the constraint
          :type Y: list of lists
          :param Q: A list of values to sample.  Each value is doublet of (r, d):
                    r is the row index, d is the column index
          :type Q: list of lists
          :param n: the number of samples to use in the imputation
          :type n: int
  
          :returns: list of floats -- imputed values in the same order as
              specified by Q
          """
          get_next_seed = make_get_next_seed(seed)
          e = su.impute(M_c, X_L, X_D, Y, Q, n, get_next_seed)
          return e