code: def basic_paradigm(condition_names_have_spaces=False):
      """Generate basic paradigm.
  
      Parameters
      ----------
      condition_names_have_spaces : :obj:`bool`, default=False
          Check for spaces in condition names.
  
      Returns
      -------
      events : pd.DataFrame
          Basic experimental paradigm with events data.
  
      """
      conditions = [
          "c 0",
          "c 0",
          "c 0",
          "c 1",
          "c 1",
          "c 1",
          "c 2",
          "c 2",
          "c 2",
      ]
  
      if not condition_names_have_spaces:
          conditions = [c.replace(" ", "") for c in conditions]
      onsets = [30, 70, 100, 10, 30, 90, 30, 40, 60]
      durations = 1 * np.ones(9)
      events = pd.DataFrame(
          {
              "trial_type": conditions,
              "onset": onsets,
              "duration": durations,
          }
      )
      return events
  
imports: from __future__ import annotations
  import itertools
  import json
  import string
  from pathlib import Path
  import numpy
  import pandas
  import scipy.linalg
  import scipy.signal
  from nibabel import Nifti1Image
  from scipy.ndimage import binary_dilation
  from nilearn import datasets, image, maskers, masking
  from nilearn._utils import as_ndarray, logger
  from nilearn.interfaces.bids.utils import bids_entities, check_bids_label, create_bids_filename
  from nilearn.interfaces.fmriprep.tests._testing import get_legal_confound
label_desc: Use image node_id 13 for calling a global function with example usage: basic_paradigm(condition_names_have_spaces) and returns: events