code: def test_check_limit_option(self):
      data = np.matrix(
          [
              [1, 1, 0, 1],
              [1, 0, 1, 1],
              [0, 0, 1, 1],
          ]
      )
  
      with self.assertRaises(ValueError):
          # To many data samples compare to the number of feature
          dhnet = algorithms.DiscreteHopfieldNetwork(check_limit=True)
          dhnet.train(data)
  
      # The same must be OK without validation
      dhnet = algorithms.DiscreteHopfieldNetwork(check_limit=False)
      dhnet.train(data)
  
file_path: neupy/tests/algorithms/memory/test_discrete_hn.py
imports: import numpy
  from neupy import algorithms
  from algorithms.memory.data import zero, one, two, half_one, half_zero, half_two
  from base import BaseTestCase
label_desc: Use image node_id 2 for calling the DiscreteHopfieldNetworkTestCase obj's underlying member method code with example usage: obj.test_check_limit_option() without return types