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
