code: def make_data():
      dimt = 100
      dimx = 10
      dimy = 11
      dimz = 12
      y = np.random.randn(dimt, dimx, dimy, dimz)
      X = np.array([np.ones(dimt), list(range(dimt))])
      X = X.transpose()  ## the design matrix X must have dimt lines
      return y, X
  
file_path: nipy/nipy/labs/glm/benchmarks/bench_glm.py
imports: import numpy
  from ..glm import glm
label_desc: Use image node_id 1 for calling a global function with example usage: make_data() and returns: y,  X