code: def glover_hrf(tr, oversampling=50, time_length=32.0, onset=0.0):
      """Implement the Glover :term:`HRF` model.
  
      Parameters
      ----------
      tr : float
          :term:`Repetition time<TR>`, in seconds (sampling period).
  
      oversampling : int, default=50
          Temporal oversampling factor.
  
      time_length : float, default=32
          :term:`HRF` kernel length, in seconds.
  
      onset : float, default=0
          Onset of the response.
  
      Returns
      -------
      hrf : array of shape(length / tr * oversampling, dtype=float)
           :term:`HRF` sampling on the oversampled time grid.
  
      """
      return _gamma_difference_hrf(
          tr,
          oversampling,
          time_length,
          onset,
          delay=6,
          undershoot=12.0,
          dispersion=0.9,
          u_dispersion=0.9,
          ratio=0.35,
      )
  
imports: import warnings
  from collections.abc import Iterable
  import numpy
  from scipy.stats import gamma
  from nilearn._utils import fill_doc
label_desc: Use image node_id 3 for calling a global function with example usage: glover_hrf(tr, oversampling, time_length, onset) and returns: _gamma_difference_hrf