old_contents: __author__ = 'intsco'
  
  import cPickle
  from engine.pyIMS.image_measures.level_sets_measure import measure_of_chaos_dict
  from unittest import TestCase
  import unittest
  from os.path import join, realpath, dirname
  
  
  class MeasureOfChaosDictTest(TestCase):
  
      def setUp(self):
          self.rows, self.cols = 65, 65
          self.input_fn = join(dirname(realpath(__file__)), 'data/measure_of_chaos_dict_test_input.pkl')
          with open(self.input_fn) as f:
              self.input_data = cPickle.load(f)
  
      def testMOCBoundaries(self):
          for img_d in self.input_data:
              if len(img_d) > 0:
                  assert 0 <= measure_of_chaos_dict(img_d, self.rows, self.cols) <= 1
  
      def testEmptyInput(self):
          # print measure_of_chaos_dict({}, self.cols, self.cols)
          self.assertRaises(Exception, measure_of_chaos_dict, {}, self.cols, self.cols)
          self.assertRaises(Exception, measure_of_chaos_dict, None, self.cols, self.cols)
          self.assertRaises(Exception, measure_of_chaos_dict, (), self.cols, self.cols)
          self.assertRaises(Exception, measure_of_chaos_dict, [], self.cols, self.cols)
  
      def testMaxInputDictKeyVal(self):
          max_key_val = self.rows * self.cols - 1
          self.assertRaises(Exception, measure_of_chaos_dict, {max_key_val + 10: 1}, self.rows, self.cols)
  
  
  if __name__ == '__main__':
      unittest.main()
  
new_contents: import unittest
  
  import numpy as np
  
  from ..image_measures.level_sets_measure import measure_of_chaos, _nan_to_zero
  
  
  class MeasureOfChaosTest(unittest.TestCase):
      def test__nan_to_zero_with_ge_zero(self):
          ids = (
              np.zeros(1),
              np.ones(range(1, 10)),
              np.arange(1024 * 1024)
          )
          for id_ in ids:
              before = id_.copy()
              _nan_to_zero(id_)
              np.testing.assert_array_equal(before, id_)
  
      def test__nan_to_zero_with_negatives(self):
          negs = (
              np.array([-1]),
              -np.arange(1, 1024 * 1024 + 1).reshape((1024, 1024)),
              np.linspace(0, -20, 201)
          )
          for neg in negs:
              sh = neg.shape
              _nan_to_zero(neg)
              np.testing.assert_array_equal(neg, np.zeros(sh))
  
  if __name__ == '__main__':
      unittest.main()
  
subject: Implement first tests for _nan_to_zero