class_docstr: 2D images, axcodes specifications are ignored when
  loading. (Resampling to new pixdims is currently not supported).
class_docstr_tok: ["2D","images",",","axcodes","specifications","are","ignored","when","loading",".","(","Resampling","to","new","pixdims","is","currently","not","supported",")","."]
code: def get_data(self):
      if len(self._file_path) > 1:
          image_data = []
          for file_path, loader, dtype in zip(
              self._file_path, self.loader, self.dtype
          ):
              data_array = self._load_single_file(
                  file_path, loader, dtype
              )
              image_data.append(data_array)
          try:
              return np.concatenate(image_data, axis=4)
          except ValueError:
              tf.logging.fatal(
                  "multi-modal data shapes not consistent -- trying to "
                  "concat {}.".format([mod.shape for mod in image_data])
              )
              raise
      image_data = self._load_single_file(
          self.file_path[0], self.loader[0], self.dtype[0]
      )
      return image_data
  
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 17 for calling the SpatialImage2D obj's underlying member method code with example usage: obj.get_data() and returns: image_data, np