def test_linear_weight_init_in_sofm(self):
sofm = algorithms.SOFM(
n_inputs=4,
features_grid=(3, 3),
weight='init_pca',
)
X = np.random.random((100, 4))
self.assertTrue(callable(sofm.weight))
sofm.init_weights(X)
self.assertFalse(callable(sofm.weight))
self.assertEqual(sofm.weight.shape, (4, 9))
for row in (0, 3, 6):
left = sofm.weight[:, row]
center = sofm.weight[:, row + 1]
right = sofm.weight[:, row + 2]
self.assertLess(np.linalg.norm((left - center)**2),
np.linalg.norm((left - right)**2))
for i in range(3):
top = sofm.weight[:, i]
center = sofm.weight[:, i + 3]
bottom = sofm.weight[:, i + 6]
self.assertLess(np.linalg.norm((top - center)**2),
np.linalg.norm((top - bottom)**2))
def test_sofm_double_initialization_exception(self):
sofm = algorithms.SOFM(n_inputs=2,
n_outputs=3,
verbose=False,
weight='sample_from_data')
sofm.init_weights(X)
with self.assertRaises(WeightInitializationError):
sofm.init_weights(X)
def test_sample_data_weight_init_in_sofm(self):
sofm = algorithms.SOFM(
n_inputs=4,
n_outputs=7,
weight='sample_from_data',
)
X = np.random.random((10, 4))
self.assertTrue(callable(sofm.weight))
sofm.init_weights(X)
self.assertFalse(callable(sofm.weight))
self.assertEqual(sofm.weight.shape, (4, 7))
