def test_direct_with_without_rowvar():
"""Tests the direct method, with and without rowvar, works correctly."""
np.random.seed(1)
data = np.random.normal(size=(10, 50))
pc1 = PrincipalComponents(data)
pc2 = PrincipalComponents(data.T, rowvar=True)
pc1._direct()
pc2._direct()
check_cols_match_except_sign(pc1._eigvec, pc2._eigvec)
def test_em_with_without_rowvar():
"""Tests the EM method, with and without rowvar, works correctly."""
np.random.seed(1)
data = np.random.normal(size=(20, 50))
pc1 = PrincipalComponents(data)
pc2 = PrincipalComponents(data.T, rowvar=True)
pc1._expectation_maximization(10)
pc2._expectation_maximization(10)
check_cols_match_except_sign(pc1._eigvec, pc2._eigvec)
def test_em_vs_snapshot_pc_rowvar_false():
"""Tests that EM and snapshot agree."""
np.random.seed(1)
data = np.random.normal(size=(10, 50))
pc1 = PrincipalComponents(data)
pc2 = PrincipalComponents(data)
pc1._snapshot()
pc2._expectation_maximization(5)
check_cols_match_except_sign(pc1._eigvec[:, :5], pc2._eigvec)
def test_snapshot_vs_direct_pc_rowvar_false():
"""Tests that snapshot and direct agree."""
np.random.seed(1)
data = np.random.normal(size=(10, 50))
pc1 = PrincipalComponents(data)
pc2 = PrincipalComponents(data)
pc1._direct()
pc2._snapshot()
check_cols_match_except_sign(pc1._eigvec[:, :4], pc2._eigvec[:, :4])
def test_project_with_without_rowvar():
"""Tests the project works with rowvar correctly."""
np.random.seed(1)
data = np.random.normal(size=(10, 50))
pc1 = PrincipalComponents(data)
pc2 = PrincipalComponents(data.T, rowvar=True)
pc1._direct()
pc2._direct()
check_cols_match_except_sign(pc1.project(3), pc2.project(3).T)
check_cols_match_except_sign(pc1.project(3), pc2.project(3).T)
def __init__(self, npc=None, *args, **keywords):
self._pc = PrincipalComponents(data)
self._pc._direct()
if npc is None:
npc = len(self._pc._eigval)
data = self._pc.project(npc)
super(SplineModelPCAGaussianMixture, self).__init__(ncomponent,
data,
norm=False,
*args,
**keywords)
def test_ndim_property():
"""Tests the ndim property works with rowvar correctly."""
data = np.zeros((10, 50))
pc1 = PrincipalComponents(data)
pc2 = PrincipalComponents(data.T, rowvar=True)
assert pc1.ndim == pc2.ndim
