def test_modelrecreation(self):
par = toy_model()
pcopy = GPRegression(par.X.copy(),
par.Y.copy(),
kernel=par.kern.copy())
np.testing.assert_allclose(par.param_array, pcopy.param_array)
np.testing.assert_allclose(par.gradient_full, pcopy.gradient_full)
self.assertSequenceEqual(str(par), str(pcopy))
self.assertIsNot(par.param_array, pcopy.param_array)
self.assertIsNot(par.gradient_full, pcopy.gradient_full)
self.assertTrue(pcopy.checkgrad())
self.assert_(np.any(pcopy.gradient != 0.0))
np.testing.assert_allclose(pcopy.param_array,
par.param_array,
atol=1e-6)
par.randomize()
with tempfile.TemporaryFile('w+b') as f:
par.pickle(f)
f.seek(0)
pcopy = pickle.load(f)
np.testing.assert_allclose(par.param_array, pcopy.param_array)
np.testing.assert_allclose(par.gradient_full,
pcopy.gradient_full,
atol=1e-6)
self.assertSequenceEqual(str(par), str(pcopy))
self.assert_(pcopy.checkgrad())
def test_modelrecreation(self):
par = toy_model()
pcopy = GPRegression(par.X.copy(), par.Y.copy(), kernel=par.kern.copy())
np.testing.assert_allclose(par.param_array, pcopy.param_array)
np.testing.assert_allclose(par.gradient_full, pcopy.gradient_full)
self.assertSequenceEqual(str(par), str(pcopy))
self.assertIsNot(par.param_array, pcopy.param_array)
self.assertIsNot(par.gradient_full, pcopy.gradient_full)
self.assertTrue(pcopy.checkgrad())
self.assert_(np.any(pcopy.gradient!=0.0))
np.testing.assert_allclose(pcopy.param_array, par.param_array, atol=1e-6)
par.randomize()
with tempfile.TemporaryFile('w+b') as f:
par.pickle(f)
f.seek(0)
pcopy = pickle.load(f)
np.testing.assert_allclose(par.param_array, pcopy.param_array)
np.testing.assert_allclose(par.gradient_full, pcopy.gradient_full, atol=1e-6)
self.assertSequenceEqual(str(par), str(pcopy))
self.assert_(pcopy.checkgrad())
def test_add_observer(self):
par = toy_model()
par.name = "original"
par.count = 0
par.add_observer(self, self._callback, 1)
pcopy = GPRegression(par.X.copy(), par.Y.copy(), kernel=par.kern.copy())
self.assertNotIn(par.observers[0], pcopy.observers)
pcopy = par.copy()
pcopy.name = "copy"
self.assertTrue(par.checkgrad())
self.assertTrue(pcopy.checkgrad())
self.assertTrue(pcopy.kern.checkgrad())
import ipdb;ipdb.set_trace()
self.assertIn(par.observers[0], pcopy.observers)
self.assertEqual(par.count, 3)
self.assertEqual(pcopy.count, 6) # 3 of each call to checkgrad
def test_add_observer(self):
par = toy_model()
par.name = "original"
par.count = 0
par.add_observer(self, self._callback, 1)
pcopy = GPRegression(par.X.copy(),
par.Y.copy(),
kernel=par.kern.copy())
self.assertNotIn(par.observers[0], pcopy.observers)
pcopy = par.copy()
pcopy.name = "copy"
self.assertTrue(par.checkgrad())
self.assertTrue(pcopy.checkgrad())
self.assertTrue(pcopy.kern.checkgrad())
import ipdb
ipdb.set_trace()
self.assertIn(par.observers[0], pcopy.observers)
self.assertEqual(par.count, 3)
self.assertEqual(pcopy.count, 6) # 3 of each call to checkgrad
