code: def read_evokeds_mff(
      fname,
      condition=None,
      channel_naming="E%d",
      baseline=None,
      verbose=None,
  ):
      """Read averaged MFF file as EvokedArray or list of EvokedArray.
  
      Parameters
      ----------
      fname : path-like
          File path to averaged MFF file. Should end in ``.mff``.
      condition : int or str | list of int or str | None
          The index (indices) or category (categories) from which to read in
          data. Averaged MFF files can contain separate averages for different
          categories. These can be indexed by the block number or the category
          name. If ``condition`` is a list or None, a list of EvokedArray objects
          is returned.
      channel_naming : str
          Channel naming convention for EEG channels. Defaults to 'E%%d'
          (resulting in channel names 'E1', 'E2', 'E3'...).
      baseline : None (default) or tuple of length 2
          The time interval to apply baseline correction. If None do not apply
          it. If baseline is (a, b) the interval is between "a (s)" and "b (s)".
          If a is None the beginning of the data is used and if b is None then b
          is set to the end of the interval. If baseline is equal to (None, None)
          all the time interval is used. Correction is applied by computing mean
          of the baseline period and subtracting it from the data. The baseline
          (a, b) includes both endpoints, i.e. all timepoints t such that
          a <= t <= b.
      %(verbose)s
  
      Returns
      -------
      evoked : EvokedArray or list of EvokedArray
          The evoked dataset(s); one EvokedArray if condition is int or str,
          or list of EvokedArray if condition is None or list.
  
      Raises
      ------
      ValueError
          If ``fname`` has file extension other than '.mff'.
      ValueError
          If the MFF file specified by ``fname`` is not averaged.
      ValueError
          If no categories.xml file in MFF directory specified by ``fname``.
  
      See Also
      --------
      Evoked, EvokedArray, create_info
  
      Notes
      -----
      .. versionadded:: 0.22
      """
      mffpy = _import_mffpy()
      # Confirm `fname` is a path to an MFF file
      fname = Path(fname)  # should be replace with _check_fname
      if not fname.suffix == ".mff":
          raise ValueError(
              'fname must be an MFF file with extension ".mff".'
          )
      # Confirm the input MFF is averaged
      mff = mffpy.Reader(fname)
      try:
          flavor = mff.mff_flavor
      except AttributeError:  # < 6.3
          flavor = mff.flavor
      if flavor not in ("averaged", "segmented"):  # old, new names
          raise ValueError(
              f"{fname} is a {flavor} MFF file. "
              "fname must be the path to an averaged MFF file."
          )
      # Check for categories.xml file
      if "categories.xml" not in mff.directory.listdir():
          raise ValueError(
              "categories.xml not found in MFF directory. "
              f"{fname} may not be an averaged MFF file."
          )
      return_list = True
      if condition is None:
          categories = mff.categories.categories
          condition = list(categories.keys())
      elif not isinstance(condition, list):
          condition = [condition]
          return_list = False
      logger.info(
          f"Reading {len(condition)} evoked datasets from {fname} ..."
      )
      output = [
          _read_evoked_mff(
              fname, c, channel_naming=channel_naming, verbose=verbose
          ).apply_baseline(baseline)
          for c in condition
      ]
      return output if return_list else output[0]
  
imports: import datetime
  import math
  import os.path
  import re
  from collections import OrderedDict
  from pathlib import Path
  import numpy
  from ..._fiff.constants import FIFF
  from ..._fiff.meas_info import _empty_info, _ensure_meas_date_none_or_dt, create_info
  from ..._fiff.proj import setup_proj
  from ..._fiff.utils import _create_chs, _mult_cal_one
  from ...annotations import Annotations
  from ...channels.montage import make_dig_montage
  from ...evoked import EvokedArray
  from ...utils import _check_fname, _check_option, _soft_import, logger, verbose, warn
  from ..base import BaseRaw
  from .events import _combine_triggers, _read_events
  from .general import _block_r, _extract, _get_blocks, _get_ep_info, _get_gains, _get_signalfname
label_desc: Use image node_id 7 for calling a global function with example usage: read_evokeds_mff(fname, condition, channel_naming, baseline, verbose) and returns: unknown