class_docstr: generate randomised bias field transformation for data augmentation
class_docstr_tok: ["generate","randomised","bias","field","transformation","for","data","augmentation"]
code: def init_uniform_coeff(self, coeff_range=(-10.0, 10.0)):
      assert coeff_range[0] < coeff_range[1]
      self.min_coeff = float(coeff_range[0])
      self.max_coeff = float(coeff_range[1])
  
file_path: NiftyNet/niftynet/layer/rand_bias_field.py
imports: from __future__ import absolute_import, print_function
  import numpy
  from niftynet.layer.base_layer import RandomisedLayer
label_desc: Use image node_id 2 for calling the RandomBiasFieldLayer obj's underlying member method code with example usage: obj.init_uniform_coeff(coeff_range) without return types