code: def read_lta(fname, verbose=None):
      """Read a Freesurfer linear transform array file.
  
      Parameters
      ----------
      fname : path-like
          The transform filename.
      %(verbose)s
  
      Returns
      -------
      affine : ndarray
          The affine transformation described by the lta file.
      """
      _check_fname(fname, "read", must_exist=True)
      with open(fname) as fid:
          lines = fid.readlines()
      # 0 is linear vox2vox, 1 is linear ras2ras
      trans_type = int(lines[0].split("=")[1].strip()[0])
      assert trans_type in (0, 1)
      affine = np.loadtxt(lines[5:9])
      if trans_type == 1:
          return affine
  
      src_affine = _get_affine_from_lta_info(lines[12:18])
      dst_affine = _get_affine_from_lta_info(lines[21:27])
  
      # don't compute if src and dst are already identical
      if np.allclose(src_affine, dst_affine):
          return affine
  
      ras2ras = (
          src_affine @ np.linalg.inv(affine) @ np.linalg.inv(dst_affine)
      )
      affine = np.linalg.inv(
          np.linalg.inv(src_affine) @ ras2ras @ src_affine
      )
      return affine
  
imports: import os.path
  from gzip import GzipFile
  from pathlib import Path
  import numpy
  from ._fiff.constants import FIFF
  from ._fiff.meas_info import read_fiducials
  from .surface import _read_mri_surface, read_surface
  from .transforms import Transform, _ensure_trans, apply_trans, combine_transforms, invert_transform, read_ras_mni_t
  from .utils import _check_fname, _check_option, _import_nibabel, _validate_type, get_subjects_dir, logger, verbose
label_desc: Use image node_id 16 for calling a global function with example usage: read_lta(fname, verbose) and returns: affine, affine, affine