code: def reset(self, augmentation_num=0):
      self.patch_regions = []
      region_input_data = {
          label: self.data_groups[label].augmentation_cases[
              augmentation_num
          ]
          for label in list(self.data_groups.keys())
      }
  
      if self.patch_region_conditions is not None:
          for region_condition in self.patch_region_conditions:
              self.patch_regions += [
                  np.where(region_condition[0](region_input_data))
              ]
              # self.patch_regions += self.get_indices_sparse(region_condition[0](region_input_data))
  
      return
  
imports: import numpy
  from random import shuffle
  from scipy.sparse import csr_matrix
  from deepneuro.utilities.util import add_parameter
  from deepneuro.augmentation.augment import Augmentation
label_desc: Use image node_id 4 for calling the ExtractPatches obj's underlying member method code with example usage: obj.reset(augmentation_num) without return types