code: def convdicts():
      
  
      pth = os.path.join(os.path.dirname(__file__), 'data', 'convdict.npz')
      npz = np.load(pth)
      cdd = {}
      for k in list(npz.keys()):
          cdd[k] = npz[k]
      return cdd
docs: Access a set of example learned convolutional dictionaries.
  
      Returns
      -------
      cdd : dict
        A dict associating description strings with dictionaries represented
        as ndarrays
  
      Examples
      --------
      Print the dict keys to obtain the identifiers of the available
      dictionaries
  
      >>> from sporco import util
      >>> cd = util.convdicts()
      >>> print(cd.keys())
      ['G:12x12x72', 'G:8x8x16,12x12x32,16x16x48', ...]
  
      Select a specific example dictionary using the corresponding identifier
  
      >>> D = cd['G:8x8x96']