code: def bootstrap_group(nsubj, ngroups):
      """Split the proposed group into redundant subgroups by bootstrap
  
      Parameters
      ----------
      nsubj (int) the number of subjects in the population
      ngroups(int) Number of subbgroups to be drawn
  
      Returns
      -------
      samples: a list of ngroups arrays containing
               the indexes of the subjects in each subgroup
      """
      groupsize = nsubj
      samples = [
          (groupsize * np.random.rand(groupsize)).astype(np.int_)
          for i in range(ngroups)
      ]
      return samples
  
imports: import numpy
  from nipy.io.nibcompat import get_affine
  from nipy.labs.spatial_models.discrete_domain import grid_domain_from_binary_array
label_desc: Use image node_id 5 for calling a global function with example usage: bootstrap_group(nsubj, ngroups) and returns: samples