class_docstr: Data from file should have a valid file path
  (are files on hard drive) and a name.
class_docstr_tok: ["Data","from","file","should","have","a","valid","file","path","(","are","files","on","hard","drive",")","and","a","name","."]
code: def file_path(self, path_array):
      if isinstance(path_array, string_types):
          path_array = (path_array,)
      home_folder = NiftyNetGlobalConfig().get_niftynet_home_folder()
      try:
          self._file_path = tuple(
              resolve_file_name(path, (".", home_folder))
              for path in path_array
          )
      except (TypeError, AssertionError, AttributeError, IOError):
          tf.logging.fatal(
              "unrecognised file path format, should be a valid filename,"
              "or a sequence of filenames %s",
              path_array,
          )
          raise IOError
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from abc import ABCMeta, abstractmethod
  import nibabel
  import numpy
  import tensorflow
  from six import with_metaclass, string_types
  import niftynet.io.misc_io
  from niftynet.io.image_loader import load_image_obj
  from niftynet.io.misc_io import resolve_file_name, dtype_casting
  from niftynet.utilities.niftynet_global_config import NiftyNetGlobalConfig
label_desc: Use image node_id 4 for calling the DataFromFile obj's underlying member method code with example usage: obj.file_path(path_array) without return types