def test_posterior(self):
X = np.random.randn(3,5)
Xv = np.random.rand(*X.shape)
par = NormalPosterior(X,Xv)
par.gradient = 10
pcopy = par.copy()
pcopy.gradient = 10
self.assertListEqual(par.param_array.tolist(), pcopy.param_array.tolist())
self.assertListEqual(par.gradient_full.tolist(), pcopy.gradient_full.tolist())
self.assertSequenceEqual(str(par), str(pcopy))
self.assertIsNot(par.param_array, pcopy.param_array)
self.assertIsNot(par.gradient_full, pcopy.gradient_full)
with tempfile.TemporaryFile('w+b') as f:
par.pickle(f)
f.seek(0)
pcopy = pickle.load(f)
self.assertListEqual(par.param_array.tolist(), pcopy.param_array.tolist())
pcopy.gradient = 10
np.testing.assert_allclose(par.gradient_full, pcopy.gradient_full)
np.testing.assert_allclose(pcopy.mean.gradient_full, 10)
self.assertSequenceEqual(str(par), str(pcopy))
def test_posterior(self):
X = np.random.randn(3,5)
Xv = np.random.rand(*X.shape)
par = NormalPosterior(X,Xv)
par.gradient = 10
pcopy = par.copy()
pcopy.gradient = 10
self.assertListEqual(par.param_array.tolist(), pcopy.param_array.tolist())
self.assertListEqual(par.gradient_full.tolist(), pcopy.gradient_full.tolist())
self.assertSequenceEqual(str(par), str(pcopy))
self.assertIsNot(par.param_array, pcopy.param_array)
self.assertIsNot(par.gradient_full, pcopy.gradient_full)
with tempfile.TemporaryFile('w+b') as f:
par.pickle(f)
f.seek(0)
pcopy = pickle.load(f)
self.assertListEqual(par.param_array.tolist(), pcopy.param_array.tolist())
pcopy.gradient = 10
np.testing.assert_allclose(par.gradient_full, pcopy.gradient_full)
np.testing.assert_allclose(pcopy.mean.gradient_full, 10)
self.assertSequenceEqual(str(par), str(pcopy))
