text: '''Parallel utility function using joblib
  
  copied from https://github.com/mne-tools/mne-python
  
  Author: Alexandre Gramfort <gramfort@nmr.mgh.harvard.edu>
  License: Simplified BSD
  
  changes for statsmodels (Josef Perktold)
  - try import from joblib directly, (doesn't import all of sklearn)
  
  '''
  
  
  def parallel_func(func, n_jobs, verbose=5):
      """Return parallel instance with delayed function
  
      Util function to use joblib only if available
  
      Parameters
      ----------
      func: callable
          A function
      n_jobs: int
          Number of jobs to run in parallel
      verbose: int
          Verbosity level
  
      Returns
      -------
      parallel: instance of joblib.Parallel or list
          The parallel object
      my_func: callable
          func if not parallel or delayed(func)
      n_jobs: int
          Number of jobs >= 0
  
      Examples
      --------
      >>> from math import sqrt
      >>> from statsmodels.tools.parallel import parallel_func
      >>> parallel, p_func, n_jobs = parallel_func(sqrt, n_jobs=-1, verbose=0)
      >>> print n_jobs
      >>> parallel(p_func(i**2) for i in range(10))
      """
      try:
          try:
              from joblib import Parallel, delayed
          except ImportError:
              from sklearn.externals.joblib import Parallel, delayed
  
          parallel = Parallel(n_jobs, verbose=verbose)
          my_func = delayed(func)
  
          if n_jobs == -1:
              try:
                  import multiprocessing
                  n_jobs = multiprocessing.cpu_count()
              except (ImportError, NotImplementedError):
                  print "multiprocessing not installed. Cannot run in parallel."
                  n_jobs = 1
  
      except ImportError:
          print "joblib not installed. Cannot run in parallel."
          n_jobs = 1
          my_func = func
          parallel = list
      return parallel, my_func, n_jobs
  