class_docstr: This class is responsible for the search of the appropriate files to use
  as input based on the constraints given in the config file.
docstr: Formatting the class as an intuitive string for printing.
  
  :return:
docstr_tok: ["Formatting","the","class","as","an","intuitive","string","for","printing",".",":","return",":"]
code: def to_string(self):
      """
      Formatting the class as an intuitive string for printing.
  
      :return:
      """
      summary_str = (
          "\n\nMatch file names and extract subject_ids from: \n"
      )
      if self.path_to_search:
          summary_str += "-- path to search: {}\n".format(
              self.path_to_search
          )
      if self.filename_contains:
          summary_str += "-- filename contains: {}\n".format(
              self.filename_contains
          )
      if self.filename_not_contains:
          summary_str += "-- filename not contains: {}\n".format(
              self.filename_not_contains
          )
      if self.filename_toremove_fromid:
          summary_str += "-- filename to remove from id: {}\n".format(
              self.filename_toremove_fromid
          )
      return summary_str
  
file_path: NiftyNet/niftynet/utilities/filename_matching.py
imports: from __future__ import absolute_import, print_function
  import os
  import re
  import six
  import niftynet.io.misc_io
  import tensorflow
label_desc: Use image node_id 8 for calling the KeywordsMatching obj's underlying member method code with example usage: obj.to_string() and returns: summary_str