def test_set_components():
from pymks import MKSStructureAnalysis
from pymks import PrimitiveBasis
p_basis = PrimitiveBasis(2)
model = MKSStructureAnalysis(basis=p_basis)
X = np.random.randint(2, size=(50, 10, 10))
model.fit(X)
components = model.components_
model.components_ = components * 2
assert np.allclose(model.components_, components * 2)
def test_set_components():
from pymks import MKSStructureAnalysis
from pymks import PrimitiveBasis
p_basis = PrimitiveBasis(2)
model = MKSStructureAnalysis(basis=p_basis)
X = np.random.randint(2, size=(50, 10, 10))
model.fit(X)
components = model.components_
model.components_ = components * 2
assert np.allclose(model.components_, components * 2)
def test_store_correlations():
from pymks import MKSStructureAnalysis
from pymks import PrimitiveBasis
from pymks.stats import correlate
p_basis = PrimitiveBasis(2)
model = MKSStructureAnalysis(basis=p_basis, store_correlations=True)
X = np.random.randint(2, size=(2, 4, 4))
model.fit(X)
X = correlate(X, p_basis, correlations=[(0, 0), (0, 1)])
assert np.allclose(X, model.fit_correlations)
X_0 = np.random.randint(2, size=(2, 4, 4))
model.transform(X_0)
X_corr_0 = correlate(X_0, p_basis, correlations=[(0, 0), (0, 1)])
assert np.allclose(X_corr_0, model.transform_correlations)
X_1 = np.random.randint(2, size=(2, 4, 4))
model.transform(X_1)
X_corr_1 = correlate(X_1, p_basis, correlations=[(0, 0), (0, 1)])
X_corr_ = np.concatenate((X_corr_0, X_corr_1))
assert np.allclose(X_corr_, model.transform_correlations)