code: def test_localization_bias_free(
      bias_params_free,
      method,
      lower,
      upper,
      lower_ori,
      upper_ori,
      kwargs,
      depth,
      loose,
  ):
      """Test inverse localization bias for free minimum-norm solvers."""
      evoked, fwd, noise_cov, _, want = bias_params_free
      inv_free = make_inverse_operator(
          evoked.info, fwd, noise_cov, loose=loose, depth=depth
      )
      loc = apply_inverse(
          evoked,
          inv_free,
          lambda2,
          method,
          pick_ori="vector",
          verbose="debug",
          **kwargs,
      ).data
      ori = loc / np.linalg.norm(loc, axis=1, keepdims=True)
      loc = np.linalg.norm(loc, axis=1)
      # Compute the percentage of sources for which there is no loc bias:
      max_idx = np.argmax(loc, axis=0)
      perc = (want == max_idx).mean() * 100
      assert lower <= perc <= upper, method
      _assert_free_ori_match(ori, max_idx, lower_ori, upper_ori)
  
imports: import copy
  import re
  from pathlib import Path
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_array_equal, assert_array_less, assert_equal
  from scipy import sparse
  import mne
  from mne import Covariance, EvokedArray, SourceEstimate, combine_evoked, compute_raw_covariance, convert_forward_solution, make_ad_hoc_cov, make_forward_solution, make_sphere_model, pick_channels_forward, pick_types, pick_types_forward, read_cov, read_evokeds, read_forward_solution
  from mne.datasets import testing
  from mne.epochs import Epochs, EpochsArray, make_fixed_length_epochs
  from mne.event import read_events
  from mne.forward import apply_forward, is_fixed_orient, restrict_forward_to_stc
  from mne.io import read_info, read_raw_fif
  from mne.label import label_sign_flip, read_label
  from mne.minimum_norm import INVERSE_METHODS, apply_inverse, apply_inverse_cov, apply_inverse_epochs, apply_inverse_raw, apply_inverse_tfr_epochs, compute_rank_inverse, make_inverse_operator, prepare_inverse_operator, read_inverse_operator, write_inverse_operator
  from mne.source_estimate import VolSourceEstimate, read_source_estimate
  from mne.source_space._source_space import _get_src_nn
  from mne.surface import _normal_orth
  from mne.time_frequency import EpochsTFR
  from mne.utils import _record_warnings, catch_logging
label_desc: Use image node_id 11 for calling a global function with example usage: test_localization_bias_free(bias_params_free, method, lower, upper, lower_ori, upper_ori, kwargs, depth, loose) without return types