def test_bootstrap_replicate_01(self):
np.random.seed(42)
matrix = np.random.uniform(-1, 1, 9).reshape(3, 3)
weights = np.ones((3, 1)) / 3
ss = Subspaces(dim=1)
wei = ss._bootstrap_replicate(matrix, weights)[1]
np.testing.assert_array_almost_equal(weights, wei)
def test_partition_03(self):
np.random.seed(42)
matrix = np.random.uniform(-1, 1, 9).reshape(3, 3)
ss = Subspaces()
ss.evects = matrix
with self.assertRaises(TypeError):
ss.partition(dim=2.0)
def test_partition_02(self):
np.random.seed(42)
matrix = np.random.uniform(-1, 1, 9).reshape(3, 3)
ss = Subspaces(dim=2)
ss.evects = matrix
ss._partition()
np.testing.assert_array_almost_equal(matrix[:, 2:], ss.W2)
def test_partition_05(self):
np.random.seed(42)
matrix = np.random.uniform(-1, 1, 9).reshape(3, 3)
ss = Subspaces(dim=4)
ss.evects = matrix
with self.assertRaises(ValueError):
ss._partition()
def test_plot_sufficient_summary(self):
ss = Subspaces(dim=1)
inputs = np.diag(np.ones(3))
outputs = np.ones(3).reshape(3, 1)
with self.assertRaises(ValueError):
ss.plot_sufficient_summary(inputs,
outputs,
figsize=(7, 7),
title='Sufficient_summary_plots')
def test_bootstrap_replicate_02(self):
np.random.seed(42)
matrix = np.random.uniform(-1, 1, 9).reshape(3, 3)
weights = np.ones((3, 1)) / 3
ss = Subspaces(dim=1)
mat = ss._bootstrap_replicate(matrix, weights)[0]
true_matrix = np.array([[-0.88383278, 0.73235229, 0.20223002],
[0.19731697, -0.68796272, -0.68801096],
[-0.25091976, 0.90142861, 0.46398788]])
np.testing.assert_array_almost_equal(true_matrix, mat)
def test_init_W1(self):
ss = Subspaces(dim=1)
self.assertIsNone(ss.W1)
def test_inverse_transform(self):
ss = Subspaces(dim=1)
with self.assertRaises(NotImplementedError):
ss.inverse_transform(10, 10)
def test_init_dim(self):
ss = Subspaces()
self.assertIsNone(ss.dim)
def test_fit(self):
ss = Subspaces(dim=1)
with self.assertRaises(NotImplementedError):
ss.fit()
def test_transform(self):
ss = Subspaces(dim=1)
with self.assertRaises(NotImplementedError):
ss.transform(42)
def test_init_subs_br(self):
ss = Subspaces(dim=1)
self.assertIsNone(ss.subs_br)
def test_init_dim(self):
ss = Subspaces(dim=1)
self.assertEqual(ss.dim, 1)
def test_init_cov_matrix(self):
ss = Subspaces()
self.assertIsNone(ss.cov_matrix)
def test_init_evals_br(self):
ss = Subspaces()
self.assertIsNone(ss.evals_br)
def test_plot_eigenvectors(self):
ss = Subspaces(dim=1)
with self.assertRaises(ValueError):
ss.plot_eigenvectors(n_evects=2, title='Eigenvectors')
def test_plot_eigenvalues(self):
ss = Subspaces(dim=1)
with self.assertRaises(ValueError):
ss.plot_eigenvalues(figsize=(7, 7), title='Eigenvalues')
def test_compute(self):
ss = Subspaces()
with self.assertRaises(NotImplementedError):
ss.compute()
def test_backward(self):
ss = Subspaces()
with self.assertRaises(NotImplementedError):
ss.backward(10, 10)
def test_forward(self):
ss = Subspaces()
with self.assertRaises(NotImplementedError):
ss.forward(42)
def test_init_evects(self):
ss = Subspaces(dim=1)
self.assertIsNone(ss.evects)
def test_init_W2(self):
ss = Subspaces()
self.assertIsNone(ss.W2)