old_contents: from __future__ import unicode_literals
  from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  from future import standard_library
  standard_library.install_aliases()
  import unittest
  
  import numpy as np
  
  from chainerrl.explorers.additive_ou import AdditiveOU
  
  
  class TestAdditiveOU(unittest.TestCase):
  
      def test(self):
  
          action_size = 3
  
          def greedy_action_func():
              return np.asarray([0] * action_size, dtype=np.float32)
  
          explorer = AdditiveOU()
  
          for t in range(100):
              a = explorer.select_action(t, greedy_action_func)
              print(t, a)
  
new_contents: from __future__ import unicode_literals
  from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  from future import standard_library
  standard_library.install_aliases()
  import unittest
  
  from chainer import testing
  import numpy as np
  
  from chainerrl.explorers.additive_ou import AdditiveOU
  
  
  @testing.parameterize(*testing.product({
      'action_size': [1, 3],
      'sigma_type': ['scalar', 'ndarray'],
  }))
  class TestAdditiveOU(unittest.TestCase):
  
      def test(self):
  
          def greedy_action_func():
              return np.asarray([0] * self.action_size, dtype=np.float32)
  
          if self.sigma_type == 'scalar':
              sigma = np.random.rand()
          elif self.sigma_type == 'ndarray':
              sigma = np.random.rand(self.action_size)
          theta = np.random.rand()
  
          explorer = AdditiveOU(theta=theta, sigma=sigma)
  
          print('theta:', theta, 'sigma', sigma)
          for t in range(100):
              a = explorer.select_action(t, greedy_action_func)
              print(t, a)
  
subject: Add tests of non-scalar sigma for AddtiveOU