class_docstr: TODO: extend to be more flexible and useful.
  Ponder about how best to apply to multiple dimensions
class_docstr_tok: ["TODO",":","extend","to","be","more","flexible","and","useful",".","Ponder","about","how","best","to","apply","to","multiple","dimensions"]
code: def augment(self, augmentation_num=0):
      for label, data_group in list(self.data_groups.items()):
          input_data = data_group.augmentation_cases[augmentation_num]
  
          if self.available_transforms[
              self.iteration % self.total_transforms, 0
          ]:
              data_group.augmentation_cases[
                  augmentation_num + 1
              ] = np.flip(input_data, self.flip_axis)
              input_data = data_group.augmentation_cases[
                  augmentation_num + 1
              ]
          else:
              data_group.augmentation_cases[
                  augmentation_num + 1
              ] = input_data
  
          if self.available_transforms[
              self.iteration % self.total_transforms, 1
          ]:
              data_group.augmentation_cases[
                  augmentation_num + 1
              ] = np.rot90(
                  input_data,
                  self.available_transforms[
                      self.iteration % self.total_transforms, 1
                  ],
                  axes=self.rotate_axis,
              )
  
imports: import numpy
  from deepneuro.utilities.util import add_parameter
label_desc: Use image node_id 3 for calling the Flip_Rotate_2D obj's underlying member method code with example usage: obj.augment(augmentation_num) without return types