def test_soft_conv_10(self): # Difference between two arrays equals tolerance, # (would not be enough to reach convergence by itself) # but amount of observations must also be taken into account! labels = [0.99, 0.99, 0.1, 0.1, 0.005] pre_labels = [0.99, 0.99, 0.1, 0.1, 0.01] tol = 5e-3 converged = corrmut.has_converged(labels, pre_labels, "soft", tol=tol) assert converged
def test_hard_conv_2(self): labels = [0] * 10 pre_labels = [0] * 10 converged = corrmut.has_converged(labels, pre_labels, "hard") assert converged
def test_soft_conv_9(self): labels = [0.99, 0.95, 0.90, 0.95, 0.1, 0.1, 0.001, 1e-3] pre_labels = [[0.99, 0.95, 0.90, 0.95, 0.1, 0.1, 0.001, 1e-32]] tol = 5e-3 converged = corrmut.has_converged(labels, pre_labels, "soft", tol=tol) assert converged
def test_soft_conv_7(self): labels = [1, 1, 1, 0, 0, 0] pre_labels = [1, 1, 1, 0, 0, 0] converged = corrmut.has_converged(labels, pre_labels, "soft") assert converged
def test_soft_conv_4(self): labels = [0] * 10 pre_labels = [1] * 10 converged = corrmut.has_converged(labels, pre_labels, "soft") assert not converged
def test_hard_conv_7(self): labels = [1, 1, 1, 0, 0, 0] pre_labels = [1, 1, 1, 0, 0, 0] converged = corrmut.has_converged(labels, pre_labels, "hard") assert converged