class_docstr: This class maintains a pandas.dataframe of filenames for all input sections.
  The list of filenames are obtained by searching the specified folders
  or loading from an existing csv file.
  
  Users can query a subset of the dataframe by train/valid/infer partition
  label and input section names.
docstr: Print summary of the partitioner.
docstr_tok: ["Print","summary","of","the","partitioner","."]
code: def to_string(self):
      """
      Print summary of the partitioner.
      """
      n_subjects = self.number_of_subjects()
      summary_str = "\n\nNumber of subjects {}, ".format(n_subjects)
      if self._file_list is not None:
          summary_str += "input section names: {}\n".format(
              list(self._file_list)
          )
      if self._partition_ids is not None and n_subjects > 0:
          n_train = self.number_of_subjects(TRAIN)
          n_valid = self.number_of_subjects(VALID)
          n_infer = self.number_of_subjects(INFER)
          summary_str += (
              "Dataset partitioning:\n"
              "-- {} {} cases ({:.2f}%),\n"
              "-- {} {} cases ({:.2f}%),\n"
              "-- {} {} cases ({:.2f}%).\n".format(
                  TRAIN,
                  n_train,
                  float(n_train) / float(n_subjects) * 100.0,
                  VALID,
                  n_valid,
                  float(n_valid) / float(n_subjects) * 100.0,
                  INFER,
                  n_infer,
                  float(n_infer) / float(n_subjects) * 100.0,
              )
          )
      else:
          summary_str += (
              "-- using all subjects " "(without data partitioning).\n"
          )
      return summary_str
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import os
  import random
  import shutil
  import pandas
  import tensorflow
  from niftynet.engine.signal import TRAIN, VALID, INFER, ALL
  from niftynet.utilities.decorators import singleton
  from niftynet.utilities.filename_matching import KeywordsMatching
  from niftynet.utilities.niftynet_global_config import NiftyNetGlobalConfig
  from niftynet.utilities.util_common import look_up_operations
  from niftynet.utilities.util_csv import match_and_write_filenames_to_csv
  from niftynet.utilities.util_csv import write_csv
label_desc: Use image node_id 8 for calling the ImageSetsPartitioner obj's underlying member method code with example usage: obj.to_string() and returns: summary_str