code: def test_sofm_std_parameter(self):
      default_params = dict(
          n_inputs=2, n_outputs=3, learning_radius=1, weight=self.weight
      )
  
      sofm_1 = algorithms.SOFM(std=1, **default_params)
      sofm_1.train(X[:1], epochs=1)
      dist_1 = np.linalg.norm(sofm_1.weight[0, :] - sofm_1.weight[1, :])
  
      sofm_0 = algorithms.SOFM(std=0.1, **default_params)
      sofm_0.train(X[:1], epochs=1)
      dist_0 = np.linalg.norm(sofm_0.weight[0, :] - sofm_0.weight[1, :])
  
      # Since SOFM-1 has bigger std than SOFM-0, two updated
      # neurons should be closer to each other for SOFM-1 than
      # for SOFM-0
      self.assertLess(dist_1, dist_0)
  
imports: import math
  import numpy
  from neupy import algorithms
  from neupy.exceptions import WeightInitializationError
  from neupy.algorithms.competitive import sofm
  from neupy.algorithms.competitive.neighbours import gaussian_df
  from base import BaseTestCase
label_desc: Use image node_id 12 for calling the SOFMTestCase obj's underlying member method code with example usage: obj.test_sofm_std_parameter() without return types