code: def compute_fixed_effect_contrast(
      labels, results, con_vals, stat_type=None
  ):
      """Compute the summary contrast assuming fixed effects.
  
      Adds the same contrast applied to all labels and results lists.
  
      """
      contrast = None
      n_contrasts = 0
      for i, (lab, res, con_val) in enumerate(
          zip(labels, results, con_vals)
      ):
          if np.all(con_val == 0):
              warn(f"Contrast for run {int(i)} is null.")
              continue
          contrast_ = compute_contrast(lab, res, con_val, stat_type)
          contrast = (
              contrast_ if contrast is None else contrast + contrast_
          )
          n_contrasts += 1
      if contrast is None:
          raise ValueError(
              "All contrasts provided were null contrasts."
          )
      return contrast * (1.0 / n_contrasts)
  
imports: from warnings import warn
  import numpy
  import pandas
  import scipy.stats
  from nilearn._utils import rename_parameters
  from nilearn.glm._utils import pad_contrast, z_score
  from nilearn.maskers import NiftiMasker
label_desc: Use image node_id 3 for calling a global function with example usage: compute_fixed_effect_contrast(labels, results, con_vals, stat_type) and returns: unknown