code: def _stats_from_measurements(bs_results: np.ndarray, qubit_index_map: Dict,
                               setting: ExperimentSetting, n_shots: int,
                               coeff: float = 1.0) -> Tuple[float]:
      
      # Identify classical register indices to select
      idxs = [qubit_index_map[q] for q, _ in setting.out_operator]
      # Pick columns corresponding to qubits with a non-identity out_operation
      obs_strings = bs_results[:, idxs]
      # Transform bits to eigenvalues; ie (+1, -1)
      my_obs_strings = 1 - 2 * obs_strings
      # Multiply row-wise to get operator values. Do statistics. Return result.
      obs_vals = coeff * np.prod(my_obs_strings, axis=1)
      obs_mean = np.mean(obs_vals)
      obs_var = np.var(obs_vals) / n_shots
  
      return obs_mean, obs_var
docs: :param bs_results: results from running `qc.run`
      :param qubit_index_map: dict mapping qubit to classical register index
      :param setting: ExperimentSetting
      :param n_shots: number of shots in the measurement process
      :param coeff: coefficient of the operator being estimated
      :return: tuple specifying (mean, variance)