old_contents: from __future__ import division
  
  import numpy.testing as npt
  
  from numpy.random import RandomState
  from numpy import exp
  
  from optimix import check_grad
  
  from lim.cov import EyeCov
  from lim.util.fruits import Oranges
  from lim.util.fruits import Apples
  
  
  def test_eye_value():
      cov = EyeCov()
      cov.scale = 2.1
      o = Oranges(None)
      npt.assert_almost_equal(2.1, cov.value(o, o))
  #
  #
  # def test_eye_gradient_1():
  #     cov = EyeCov()
  #     cov.scale = 2.1
  #     a = Apples(None)
  #     cov.set_data((a, a))
  #
  #     def func(x):
  #         cov.scale = exp(x[0])
  #         return cov.feed().value()
  #
  #     def grad(x):
  #         cov.scale = exp(x[0])
  #         return cov.feed().gradient()
  #
  #     npt.assert_almost_equal(check_grad(func, grad, [0.1]), 0)
  #
  #
  # def test_eye_gradient_2():
  #     cov = EyeCov()
  #     cov.scale = 2.1
  #     a = Apples(5)
  #     cov.set_data((a, a))
  #
  #     def func(x):
  #         cov.scale = exp(x[0])
  #         return cov.feed().value()
  #
  #     def grad(x):
  #         cov.scale = exp(x[0])
  #         return cov.feed().gradient()
  #
  #     npt.assert_almost_equal(check_grad(func, grad, [0.1]), 0)
  #
  #
  # def test_eye_gradient_3():
  #     cov = EyeCov()
  #     cov.scale = 2.1
  #     a = Apples(5)
  #     o = Oranges(4)
  #     cov.set_data((a, o))
  #
  #     def func(x):
  #         cov.scale = exp(x[0])
  #         return cov.feed().value()
  #
  #     def grad(x):
  #         cov.scale = exp(x[0])
  #         return cov.feed().gradient()
  #
  #     npt.assert_almost_equal(check_grad(func, grad, [0.1]), 0)
  #
  
  if __name__ == '__main__':
      __import__('pytest').main([__file__, '-s'])
  
new_contents: from __future__ import division
  
  import numpy.testing as npt
  
  from numpy.random import RandomState
  from numpy import exp
  
  from optimix import check_grad
  
  from lim.cov import EyeCov
  from lim.util.fruits import Oranges
  from lim.util.fruits import Apples
  
  
  def test_eye_value():
      cov = EyeCov()
      cov.scale = 2.1
      o = Oranges(None)
      npt.assert_almost_equal(2.1, cov.value(o, o))
  
  def test_eye_gradient_1():
      cov = EyeCov()
      cov.scale = 2.1
      a = Apples(None)
      cov.set_data((a, a))
  
      def func(x):
          cov.scale = exp(x[0])
          return cov.feed().value()
  
      def grad(x):
          cov.scale = exp(x[0])
          return cov.feed().gradient()
  
      npt.assert_almost_equal(check_grad(func, grad, [0.1]), 0)
  
  def test_eye_gradient_2():
      cov = EyeCov()
      cov.scale = 2.1
      a = Apples(5)
      cov.set_data((a, a))
  
      def func(x):
          cov.scale = exp(x[0])
          return cov.feed().value()
  
      def grad(x):
          cov.scale = exp(x[0])
          return cov.feed().gradient()
  
      npt.assert_almost_equal(check_grad(func, grad, [0.1]), 0)
  
  
  def test_eye_gradient_3():
      cov = EyeCov()
      cov.scale = 2.1
      a = Apples(5)
      o = Oranges(4)
      cov.set_data((a, o))
  
      def func(x):
          cov.scale = exp(x[0])
          return cov.feed().value()
  
      def grad(x):
          cov.scale = exp(x[0])
          return cov.feed().gradient()
  
      npt.assert_almost_equal(check_grad(func, grad, [0.1]), 0)
  
  
  if __name__ == '__main__':
      __import__('pytest').main([__file__, '-s'])
  
subject: test eye