def test_update_M_inv(self):
data = np.array([[1, 3], [1, 6]])
mixture = PCAMixture(data, 1, 2)
model = PCAModel(mixture, 2)
model.var = 3
model.W = np.array([[1, 2], [2, 1], [1, 3]])
model.update_M_inv()
M_inv = np.array([[17, -7], [-7, 9]]) / 104
res = np.isclose(model.M_inv, M_inv)
self.assertTrue(res.all())
def test_set_C_det(self):
data = np.array([[1, 3], [1, 6]])
var = 2
W = np.array([[2, 3], [1, 0], [2, 1]])
mixture = PCAMixture(data, 1, 2)
model = PCAModel(mixture, 2)
model.var = var
model.W = W
model.set_C_det()
C_det = 136
self.assertAlmostEqual(model.C_det, C_det)
def test_set_var(self):
S = np.array([[0, 0], [0, 2]])
data = np.array([[1, 3], [1, 6]])
mixture = PCAMixture(data, 1, 2)
model = PCAModel(mixture, 2)
model.S = S
W_old = np.array([[1, 1], [3, 2]])
M_inv_old = np.array([[17, -7], [-7, 9]]) / 104
model.W = np.array([[0, 0], [104 / 87, 208 / 261]])
model.set_var(W_old, M_inv_old)
self.assertAlmostEqual(model.var, 52 / 87)
def test_set_C_inv(self):
data = np.array([[1, 3], [1, 6]])
M_inv = np.array([[17, -7], [-7, 9]]) / 104
W = np.array([[0, 0], [104 / 87, 208 / 261]])
var = 1 + 2 / 87
mixture = PCAMixture(data, 1, 2)
model = PCAModel(mixture, 2)
model.M_inv = M_inv
model.W = W
model.var = var
model.set_C_inv()
C_inv = np.array([[1, 0], [0, 19067 / 22707]]) / var
res = np.isclose(model.C_inv, C_inv)
self.assertTrue(res.all())
def test_set_W(self):
S = np.array([[0, 0], [0, 2]])
M_inv = np.array([[17, -7], [-7, 9]]) / 104
W = np.array([[1, 1], [3, 2]])
data = np.array([[1, 3], [1, 6]])
mixture = PCAMixture(data, 1, 2)
model = PCAModel(mixture, 2)
model.var = 3
model.S = S
model.M_inv = M_inv
model.W = W
model.set_W()
new_W = model.W
#print(new_W)
res = np.isclose(new_W, np.array([[0, 0], [104 / 87, 208 / 261]]))
self.assertTrue(res.all())