code: def _normalise_psf_ctf(funcs, norm):
      """Normalise PSFs/CTFs in _get_psf_ctf()."""
      # normalise PSFs/CTFs if specified
      if norm == "max":
          maxval = max(-funcs.min(), funcs.max())
          funcs = funcs / maxval
      elif norm == "norm":  # normalise to maximum norm across columns
          norms = np.linalg.norm(funcs, axis=0)
          funcs = funcs / norms.max()
  
      return funcs
  
imports: from copy import deepcopy
  import numpy
  from mne.minimum_norm.inverse import InverseOperator
  from .._fiff.constants import FIFF
  from .._fiff.pick import pick_channels_forward
  from ..evoked import EvokedArray
  from ..forward.forward import Forward, convert_forward_solution
  from ..label import Label
  from ..source_estimate import _get_src_type, _make_stc, _prepare_label_extraction
  from ..source_space._source_space import SourceSpaces, _get_vertno
  from ..utils import _validate_type, logger, verbose
  from .inverse import apply_inverse
label_desc: Use image node_id 5 for calling a global function with example usage: _normalise_psf_ctf(funcs, norm) and returns: funcs