code: def _normalise_5d(self, data_array, mask_array):
      assert self.modalities
      assert data_array.ndim == 5
      assert data_array.shape[4] <= len(self.modalities)
  
      if not self.mapping:
          tf.logging.fatal(
              "calling normaliser with empty mapping,"
              "probably {} is not loaded".format(self.model_file)
          )
          raise RuntimeError
      mask_array = np.asarray(mask_array, dtype=np.bool)
      for mod_id, mod_name in enumerate(self.modalities):
          if not np.any(data_array[..., mod_id]):
              continue  # missing modality
          data_array[..., mod_id] = self.__normalise(
              data_array[..., mod_id],
              mask_array[..., mod_id],
              self.mapping[mod_name],
          )
      return data_array
  
file_path: NiftyNet/niftynet/layer/histogram_normalisation.py
imports: from __future__ import absolute_import, print_function, division
  import os
  import numpy
  import tensorflow
  import niftynet.utilities.histogram_standardisation
  from niftynet.layer.base_layer import DataDependentLayer
  from niftynet.layer.binary_masking import BinaryMaskingLayer
label_desc: Use image node_id 6 for calling the HistogramNormalisationLayer obj's underlying member method code with example usage: obj._normalise_5d(data_array, mask_array) and returns: data_array