def test_linear_fit(): X = np.arange(-2, 2, .01)[:, np.newaxis] idxs = range(X.shape[0]) idxs = random.sample(idxs, 200) X = X[idxs] Z = np.sin(X) X, Z = theano_floatx(X, Z) glm = Linear(1, 1, max_iter=10) glm.fit(X, Z)
def test_linear_iter_fit(): X = np.arange(-2, 2, .01)[:, np.newaxis] idxs = range(X.shape[0]) idxs = random.sample(idxs, 200) X = X[idxs] Z = np.sin(X) X, Z = theano_floatx(X, Z) glm = Linear(1, 1, max_iter=10) for i, info in enumerate(glm.iter_fit(X, Z)): if i >= 10: break