class_docstr: generate randomised rotation matrix for data augmentation
class_docstr_tok: ["generate","randomised","rotation","matrix","for","data","augmentation"]
code: def init_uniform_angle(self, rotation_angle=(-10.0, 10.0)):
      assert rotation_angle[0] < rotation_angle[1]
      self.min_angle = float(rotation_angle[0])
      self.max_angle = float(rotation_angle[1])
  
file_path: NiftyNet/niftynet/layer/rand_rotation.py
imports: from __future__ import absolute_import, print_function
  import numpy
  import scipy.ndimage
  from niftynet.layer.base_layer import RandomisedLayer
label_desc: Use image node_id 2 for calling the RandomRotationLayer obj's underlying member method code with example usage: obj.init_uniform_angle(rotation_angle) without return types