def test_streaming_linear_regression(self):
X0 = numpy.array([[1, 0.5, 10., 5., -2.], [0, 0.4, 20, 4., 2.],
[0, 0.4, 19, 4.2, 2.], [0, 0.7, 18, 4.1, 1.4]],
dtype=float).T
y0 = numpy.array([1., 2.1, 3.1, 3.9, 5.])
for dim in (2, 3, 4):
X = X0[:, :dim]
y = y0
algo1 = []
for i in range(dim, X.shape[0] + 1):
bk = linear_regression(X[:i], y[:i])
algo1.append(bk)
algo2 = []
self.assertRaise(
lambda: list(streaming_linear_regression(X.T, y)), # pylint: disable=W0640
RuntimeError)
for i, bk in enumerate(streaming_linear_regression(X, y)):
algo2.append(bk.copy())
self.assertNotEmpty(bk)
self.assertEqualArray(algo1[i], algo2[i])
self.assertEqual(len(algo1), len(algo2))
def test_profile(self):
N = 1000
X = rnd.randn(N, 10)
eps = rnd.randn(N, 1) / 3
y = X.sum(axis=1).reshape((X.shape[0], 1)) + eps
y = y.ravel()
res = self.profile(
lambda: list(streaming_linear_regression_gram_schmidt(X, y)))
if __name__ == "__main__":
print(res[1])
self.assertIn("streaming", res[1])
res = self.profile(lambda: list(streaming_linear_regression(X, y)))
if __name__ == "__main__":
print(res[1])
self.assertIn("streaming", res[1])