class_docstr: Parameters
  ----------
  fmri_image : `FmriImageList`
     object returning 4D array from ``np.asarray``, having attribute
     ``volume_start_times`` (if `volume_start_times` is None), and
     such that ``object[0]`` returns something with attributes ``shape``
  formula :  :class:`nipy.algorithms.statistics.formula.Formula`
  sigma :
  outputs :
  volume_start_times :
class_docstr_tok: ["Parameters","--","--","--","--","--","fmri_image",":","`","FmriImageList","`","object","returning","4D","array","from","``","np.asarray","``",",","having","attribute","``","volume_start_times","``","(","if","`","volume_start_times","`","is","None",")",",","and","such","that","``","object","[","0","]","``","returns","something","with","attributes","``","shape","``","formula",":",":","class",":","`","nipy.algorithms.statistics.formula.Formula","`","sigma",":","outputs",":","volume_start_times",":"]
code: def __init__(
      self,
      fmri_image,
      formula,
      sigma,
      outputs=[],
      volume_start_times=None,
  ):
      self.fmri_image = fmri_image
      self.data = np.asarray(fmri_image)
      self.formula = formula
      self.outputs = outputs
      self.sigma = sigma
  
      if volume_start_times is None:
          self.volume_start_times = self.fmri_image.volume_start_times
      else:
          self.volume_start_times = volume_start_times
  
file_path: nipy/nipy/modalities/fmri/spm/model.py
imports: import numpy
  import numpy.linalg
  from scipy.stats import f
  from nipy.algorithms.statistics.models.regression import GLSModel, OLSModel
  from nipy.core.api import Image
  from nipy.modalities.fmri.fmristat import model
  from nipy.modalities.fmri.fmristat.model import OLS
  from .None import correlation, reml
label_desc: Use image node_id 1 to create a new SecondStage object  with example: obj = SecondStage(fmri_image, formula, sigma, outputs, volume_start_times)