code: def report_flm_bids_features():  # pragma: no cover # noqa
      data_dir = _fetch_bids_data()
      model, subject = _make_flm(data_dir)
      title = "FLM Bids Features Stat maps"
      report = make_glm_report(
          model=model,
          contrasts="StopSuccess - Go",
          title=title,
          cluster_threshold=3,
      )
      output_filename = "generated_report_flm_bids_features.html"
      output_filepath = os.path.join(REPORTS_DIR, output_filename)
      report.save_as_html(output_filepath)
      report.get_iframe()
  
imports: import os
  import numpy
  import pandas
  import nilearn
  from nilearn import datasets
  from nilearn.glm.first_level import FirstLevelModel, first_level_from_bids
  from nilearn.glm.first_level.design_matrix import make_first_level_design_matrix
  from nilearn.glm.second_level import SecondLevelModel
  from nilearn.image import resample_to_img
  from nilearn.interfaces.fsl import get_design_from_fslmat
  from nilearn.maskers import NiftiSpheresMasker
  from nilearn.reporting import make_glm_report
label_desc: Use image node_id 5 for calling a global function with example usage: report_flm_bids_features() without return types