def test_custom_init(self):
A, B = self._get_AB()
n = len(A)
pi = np.array([7, 5, 1, 3, 10, 4, 8, 6, 9, 11, 2, 12]) - [1] * n
custom_init = np.eye(n)
custom_init = custom_init[pi]
gm = GMP(n_init=1,
init=custom_init,
max_iter=30,
shuffle_input=True,
gmp=False)
gm.fit(A, B)
self.assertTrue((gm.perm_inds_ == pi).all())
self.assertEqual(gm.score_, 11156)
def test_custom_init_seeds(self):
A, B = self._get_AB()
n = len(A)
pi_original = np.array([7, 5, 1, 3, 10, 4, 8, 6, 9, 11, 2, 12]) - 1
pi = np.array([5, 1, 3, 10, 4, 8, 6, 9, 11, 2, 12]) - 1
pi[pi > 6] -= 1
# use seed 0 in A to 7 in B
seeds_A = [0]
seeds_B = [6]
custom_init = np.eye(n - 1)
custom_init = custom_init[pi]
gm = GMP(n_init=1,
init=custom_init,
max_iter=30,
shuffle_input=True,
gmp=False)
gm.fit(A, B, seeds_A=seeds_A, seeds_B=seeds_B)
self.assertTrue((gm.perm_inds_ == pi_original).all())
self.assertEqual(gm.score_, 11156)
def test_SGM_inputs(self):
with pytest.raises(TypeError):
GMP(n_init=-1.5)
with pytest.raises(ValueError):
GMP(init_method="random")
with pytest.raises(TypeError):
GMP(max_iter=-1.5)
with pytest.raises(TypeError):
GMP(shuffle_input="hey")
with pytest.raises(TypeError):
GMP(eps=-1)
with pytest.raises(TypeError):
GMP(gmp="hey")
with pytest.raises(TypeError):
GMP(padding=2)
with pytest.raises(ValueError):
GMP(padding="hey")
with pytest.raises(ValueError):
GMP().fit(
np.random.random((3, 4)),
np.random.random((3, 4)),
np.arange(2),
np.arange(2),
)
with pytest.raises(ValueError):
GMP().fit(
np.random.random((3, 4)),
np.random.random((3, 4)),
np.arange(2),
np.arange(2),
)
with pytest.raises(ValueError):
GMP().fit(np.identity(3), np.identity(3), np.identity(3),
np.arange(2))
with pytest.raises(ValueError):
GMP().fit(np.identity(3), np.identity(3), np.arange(1),
np.arange(2))
with pytest.raises(ValueError):
GMP().fit(np.identity(3), np.identity(3), np.arange(5),
np.arange(5))
with pytest.raises(ValueError):
GMP().fit(np.identity(3), np.identity(3), -1 * np.arange(2),
-1 * np.arange(2))
def setup_class(cls):
cls.barycenter = GMP(gmp=False)
cls.rand = GMP(n_init=100, init_method="rand", gmp=False)
cls.barygm = GMP(gmp=True)
def setUpClass(cls) -> None:
cls.barycenter = GMP(gmp=False)
cls.rand = GMP(n_init=100, init="rand", gmp=False)
cls.barygm = GMP(gmp=True)
def test_parallel(self):
A, B = self._get_AB()
gmp = GMP(gmp=False, n_init=2, n_jobs=2)
gmp.fit(A, B)
score = gmp.score_
self.assertTrue(11156 <= score < 13500)