code: def remake_images():
      # Get group data
      group_data = example_data.get_filename(
          "neurospin", "language_babies", "offset_002.npz"
      )
      f = np.load(group_data)
      data, vardata, xyz = f["mat"], f["var"], f["xyz"]
      dX = xyz[0].max() + 1
      dY = xyz[1].max() + 1
      dZ = xyz[2].max() + 1
      aux = np.zeros([dX, dY, dZ])
      data_images = []
      vardata_images = []
      mask_images = []
      indices = tuple(xyz)
      for i in range(data.shape[0]):
          aux[indices] = data[i]
          data_images.append(Image(aux.copy(), np.eye(4)))
          aux[indices] = vardata[i]
          vardata_images.append(Image(aux.copy(), np.eye(4)))
          aux[indices] = 1
          mask_images.append(aux)
  
      return data_images, vardata_images, mask_images
  
imports: import numpy
  from nibabel import Nifti1Image
  import nipy.labs.statistical_mapping
  from nipy.utils import example_data
label_desc: Use image node_id 1 for calling a global function with example usage: remake_images() and returns: data_images,  vardata_images,  mask_images