class_docstr: BaseApplication represents an interface.
  
  Each application ``type_str`` should support to use
  the standard training and inference driver.
class_docstr_tok: ["BaseApplication","represents","an","interface",".","Each","application","``","type_str","``","should","support","to","use","the","standard","training","and","inference","driver","."]
docstr: Samplers take ``self.reader`` as input and generates
  sequences of ImageWindow that will be fed to the networks
  
  This function sets ``self.sampler``.
docstr_tok: ["Samplers","take","``","self.reader","``","as","input","and","generates","sequences","of","ImageWindow","that","will","be","fed","to","the","networks","This","function","sets","``","self.sampler","``","."]
code: def initialise_sampler(self):
      """
      Samplers take ``self.reader`` as input and generates
      sequences of ImageWindow that will be fed to the networks
  
      This function sets ``self.sampler``.
      """
      raise NotImplementedError
  
imports: import os
  from argparse import Namespace
  import tensorflow
  from six import with_metaclass
  from niftynet.engine.signal import TRAIN, INFER, EVAL
label_desc: Use image node_id 2 for calling the BaseApplication obj's underlying member method code with example usage: obj.initialise_sampler() without return types