code: def _jointly_reduce_data(data1, data2, chunksize):
      lnvox = data1.shape[0]
      aux = np.argsort(rand(lnvox))[: int(np.minimum(chunksize, lnvox))]
      rdata1 = data1[aux]
      rdata2 = data2[aux]
      return rdata1, rdata2
  
file_path: nipy/nipy/labs/spatial_models/hierarchical_parcellation.py
imports: from warnings import warn
  import numpy
  from numpy.random import rand
  from nipy.algorithms.clustering.utils import kmeans, voronoi
  from nipy.algorithms.graph.field import Field
  from nipy.algorithms.graph.graph import wgraph_from_coo_matrix
  from .parcellation import MultiSubjectParcellation
label_desc: Use image node_id 1 for calling a global function with example usage: _jointly_reduce_data(data1, data2, chunksize) and returns: rdata1,  rdata2