def test_intercept_lstsq_regression(self):
a = DenseMatrix(np.matrix([[1, 1],[2, 3],[4, 6]]))
b = DenseMatrix(np.matrix([[12, 15, 18],[21, 27, 33],[35, 46, 57]]))
res = DenseMatrix(np.matrix([[1, 2, 3],[4, 5, 6],[7, 8, 9]]))
res1 = Linalg.lstsq_regression(a, b)
res2 = Linalg.lstsq_regression(a, b, intercept=True)
np.testing.assert_array_almost_equal(res2.mat[:-1,:], res[0:2,:].mat, 6)
np.testing.assert_array_almost_equal(res2.mat[-1,:], res[2:3,:].mat, 6)
new_a = a.hstack(DenseMatrix(np.ones((a.shape[0], 1))))
self.assertGreater(((a * res1) - b).norm(), ((new_a * res2) - b).norm())
def test_intercept_lstsq_regression(self):
a = DenseMatrix(np.matrix([[1, 1], [2, 3], [4, 6]]))
b = DenseMatrix(np.matrix([[12, 15, 18], [21, 27, 33], [35, 46, 57]]))
res = DenseMatrix(np.matrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]]))
res1 = Linalg.lstsq_regression(a, b)
res2 = Linalg.lstsq_regression(a, b, intercept=True)
np.testing.assert_array_almost_equal(res2.mat[:-1, :], res[0:2, :].mat,
6)
np.testing.assert_array_almost_equal(res2.mat[-1, :], res[2:3, :].mat,
6)
new_a = a.hstack(DenseMatrix(np.ones((a.shape[0], 1))))
self.assertGreater(((a * res1) - b).norm(),
((new_a * res2) - b).norm())
