code: def read_inverse_operator(fname, *, verbose=None):
      """Read the inverse operator decomposition from a FIF file.
  
      Parameters
      ----------
      fname : path-like
          The name of the FIF file, which ends with ``-inv.fif`` or
          ``-inv.fif.gz``.
      %(verbose)s
  
      Returns
      -------
      inv : instance of InverseOperator
          The inverse operator.
  
      See Also
      --------
      write_inverse_operator, make_inverse_operator
      """
      check_fname(
          fname,
          "inverse operator",
          ("-inv.fif", "-inv.fif.gz", "_inv.fif", "_inv.fif.gz"),
      )
      fname = _check_fname(
          fname=fname, must_exist=True, overwrite="read"
      )
      #
      #   Open the file, create directory
      #
      logger.info(
          "Reading inverse operator decomposition from %s..." % fname
      )
      f, tree, _ = fiff_open(fname)
      with f as fid:
          #
          #   Find all inverse operators
          #
          invs = dir_tree_find(tree, FIFF.FIFFB_MNE_INVERSE_SOLUTION)
          if invs is None or len(invs) < 1:
              raise Exception("No inverse solutions in %s" % fname)
  
          invs = invs[0]
          #
          #   Parent MRI data
          #
          parent_mri = dir_tree_find(
              tree, FIFF.FIFFB_MNE_PARENT_MRI_FILE
          )
          if len(parent_mri) == 0:
              raise Exception("No parent MRI information in %s" % fname)
          parent_mri = parent_mri[0]  # take only first one
  
          logger.info("    Reading inverse operator info...")
          #
          #   Methods and source orientations
          #
          tag = find_tag(fid, invs, FIFF.FIFF_MNE_INCLUDED_METHODS)
          if tag is None:
              raise Exception("Modalities not found")
  
          inv = dict()
          inv["methods"] = int(tag.data.item())
  
          tag = find_tag(fid, invs, FIFF.FIFF_MNE_SOURCE_ORIENTATION)
          if tag is None:
              raise Exception(
                  "Source orientation constraints not found"
              )
  
          inv["source_ori"] = int(tag.data.item())
  
          tag = find_tag(fid, invs, FIFF.FIFF_MNE_SOURCE_SPACE_NPOINTS)
          if tag is None:
              raise Exception("Number of sources not found")
  
          inv["nsource"] = int(tag.data.item())
          inv["nchan"] = 0
          #
          #   Coordinate frame
          #
          tag = find_tag(fid, invs, FIFF.FIFF_MNE_COORD_FRAME)
          if tag is None:
              raise Exception("Coordinate frame tag not found")
  
          inv["coord_frame"] = tag.data
  
          #
          #   Units
          #
          tag = find_tag(fid, invs, FIFF.FIFF_MNE_INVERSE_SOURCE_UNIT)
          unit_dict = {
              FIFF.FIFF_UNIT_AM: "Am",
              FIFF.FIFF_UNIT_AM_M2: "Am/m^2",
              FIFF.FIFF_UNIT_AM_M3: "Am/m^3",
          }
          inv["units"] = unit_dict.get(
              int(getattr(tag, "data", np.array([-1])).item()), None
          )
  
          #
          #   The actual source orientation vectors
          #
          tag = find_tag(
              fid, invs, FIFF.FIFF_MNE_INVERSE_SOURCE_ORIENTATIONS
          )
          if tag is None:
              raise Exception(
                  "Source orientation information not found"
              )
  
          inv["source_nn"] = tag.data
          logger.info("    [done]")
          #
          #   The SVD decomposition...
          #
          logger.info("    Reading inverse operator decomposition...")
          tag = find_tag(fid, invs, FIFF.FIFF_MNE_INVERSE_SING)
          if tag is None:
              raise Exception("Singular values not found")
  
          inv["sing"] = tag.data
          inv["nchan"] = len(inv["sing"])
          #
          #   The eigenleads and eigenfields
          #
          inv["eigen_leads_weighted"] = False
          inv["eigen_leads"] = _read_named_matrix(
              fid, invs, FIFF.FIFF_MNE_INVERSE_LEADS, transpose=True
          )
          if inv["eigen_leads"] is None:
              inv["eigen_leads_weighted"] = True
              inv["eigen_leads"] = _read_named_matrix(
                  fid,
                  invs,
                  FIFF.FIFF_MNE_INVERSE_LEADS_WEIGHTED,
                  transpose=True,
              )
          if inv["eigen_leads"] is None:
              raise ValueError(
                  "Eigen leads not found in inverse operator."
              )
          #
          #   Having the eigenleads as cols is better for the inverse calcs
          #
          inv["eigen_fields"] = _read_named_matrix(
              fid, invs, FIFF.FIFF_MNE_INVERSE_FIELDS
          )
          logger.info("    [done]")
          #
          #   Read the covariance matrices
          #
          inv["noise_cov"] = Covariance(
              **_read_cov(
                  fid, invs, FIFF.FIFFV_MNE_NOISE_COV, limited=True
              )
          )
          logger.info("    Noise covariance matrix read.")
  
          inv["source_cov"] = _read_cov(
              fid, invs, FIFF.FIFFV_MNE_SOURCE_COV
          )
          logger.info("    Source covariance matrix read.")
          #
          #   Read the various priors
          #
          inv["orient_prior"] = _read_cov(
              fid, invs, FIFF.FIFFV_MNE_ORIENT_PRIOR_COV
          )
          if inv["orient_prior"] is not None:
              logger.info("    Orientation priors read.")
  
          inv["depth_prior"] = _read_cov(
              fid, invs, FIFF.FIFFV_MNE_DEPTH_PRIOR_COV
          )
          if inv["depth_prior"] is not None:
              logger.info("    Depth priors read.")
  
          inv["fmri_prior"] = _read_cov(
              fid, invs, FIFF.FIFFV_MNE_FMRI_PRIOR_COV
          )
          if inv["fmri_prior"] is not None:
              logger.info("    fMRI priors read.")
  
          #
          #   Read the source spaces
          #
          inv["src"] = _read_source_spaces_from_tree(
              fid, tree, patch_stats=False
          )
  
          for s in inv["src"]:
              s["id"] = find_source_space_hemi(s)
  
          #
          #   Get the MRI <-> head coordinate transformation
          #
          tag = find_tag(fid, parent_mri, FIFF.FIFF_COORD_TRANS)
          if tag is None:
              raise Exception(
                  "MRI/head coordinate transformation not found"
              )
          mri_head_t = _ensure_trans(tag.data, "mri", "head")
  
          inv["mri_head_t"] = mri_head_t
  
          #
          # get parent MEG info
          #
          inv["info"] = _read_forward_meas_info(tree, fid)
  
          #
          #   Transform the source spaces to the correct coordinate frame
          #   if necessary
          #
          if inv["coord_frame"] not in (
              FIFF.FIFFV_COORD_MRI,
              FIFF.FIFFV_COORD_HEAD,
          ):
              raise Exception(
                  "Only inverse solutions computed in MRI or "
                  "head coordinates are acceptable"
              )
  
          #
          #  Number of averages is initially one
          #
          inv["nave"] = 1
          #
          #  We also need the SSP operator
          #
          inv["projs"] = _read_proj(fid, tree)
  
          #
          #  Some empty fields to be filled in later
          #
          inv["proj"] = []  # This is the projector to apply to the data
          inv["whitener"] = []  # This whitens the data
          # This the diagonal matrix implementing regularization and the inverse
          inv["reginv"] = []
          inv[
              "noisenorm"
          ] = []  # These are the noise-normalization factors
          #
          nuse = 0
          for k in range(len(inv["src"])):
              try:
                  inv["src"][k] = transform_surface_to(
                      inv["src"][k], inv["coord_frame"], mri_head_t
                  )
              except Exception as inst:
                  raise Exception(
                      "Could not transform source space (%s)" % inst
                  )
  
              nuse += inv["src"][k]["nuse"]
  
          logger.info(
              "    Source spaces transformed to the inverse solution "
              "coordinate frame"
          )
          #
          #   Done!
          #
  
      return InverseOperator(inv)
  
imports: from copy import deepcopy
  from math import sqrt
  import numpy
  from scipy import linalg
  from scipy.stats import chi2
  from .._fiff.constants import FIFF
  from .._fiff.matrix import _read_named_matrix, _transpose_named_matrix, write_named_matrix
  from .._fiff.open import fiff_open
  from .._fiff.pick import channel_type, pick_channels, pick_info, pick_types
  from .._fiff.proj import _electrode_types, _needs_eeg_average_ref_proj, _read_proj, _write_proj, make_projector
  from .._fiff.tag import find_tag
  from .._fiff.tree import dir_tree_find
  from .._fiff.write import end_block, start_and_end_file, start_block, write_coord_trans, write_float, write_float_matrix, write_int, write_string
  from ..cov import Covariance, _read_cov, _write_cov, compute_whitener, prepare_noise_cov
  from ..epochs import BaseEpochs, EpochsArray
  from ..evoked import Evoked, EvokedArray
  from ..fixes import _safe_svd
  from ..forward import _read_forward_meas_info, _select_orient_forward, compute_depth_prior, compute_orient_prior, convert_forward_solution, is_fixed_orient
  from ..forward.forward import _triage_loose, write_forward_meas_info
  from ..html_templates import _get_html_template
  from ..io import BaseRaw
  from ..source_estimate import _get_src_type, _make_stc
  from ..source_space._source_space import _get_src_nn, _get_vertno, _read_source_spaces_from_tree, _write_source_spaces_to_fid, find_source_space_hemi, label_src_vertno_sel
  from ..surface import _normal_orth
  from ..time_frequency.tfr import _check_tfr_complex
  from ..transforms import _ensure_trans, transform_surface_to
  from ..utils import _check_compensation_grade, _check_depth, _check_fname, _check_option, _check_src_normal, _validate_type, _verbose_safe_false, check_fname, logger, repr_html, verbose, warn
  from ._eloreta import _compute_eloreta
label_desc: Use image node_id 2 for calling a global function with example usage: read_inverse_operator(fname) and returns: InverseOperator