def test_row_combine_called(self):
A = np.array([[1, 2], [4, 3]])
ls = LinearSystem(A)
ls.row_combine = MagicMock()
ls.row_echelon()
assert ls.row_combine.called
def test_inverse_private(self):
A = np.array([[11, 2, 5],[51, 22, 17],[11, 7, 1]])
ls = LinearSystem(A)
np.testing.assert_array_almost_equal(ls.inverse(),
np.linalg.inv(A),
decimal=6)
def test_gauss_solve(self):
A = np.array([[1, 3, 5],[5, 2, 2],[1, 7, 1]])
b = np.array([1, 3, 4])
ls = LinearSystem(A, b)
np.testing.assert_array_almost_equal(ls.gauss_solve(),
np.linalg.solve(A, b),
decimal=6)
def test_reduced_row_echelon(self):
A = np.array([[1, 3, 5],[5, 2, 2],[1, 7, 1]])
b = np.array([1, 3, 4])
ls = LinearSystem(A, b)
ls.reduced_row_echelon()
np.testing.assert_array_almost_equal(ls.mat[:,-1],
np.linalg.solve(A, b),
decimal=6)
def test_back_substitute(self):
A = np.array([[1, 3, 5],[5, 2, 2],[1, 7, 1]])
b = np.array([1, 3, 4])
ls = LinearSystem(A, b)
ls.row_echelon()
np.testing.assert_array_almost_equal(ls.back_substitute(),
np.linalg.solve(A, b),
decimal=6)
def test_row_echelon(self):
A = np.array([[1, 3, 4],[5, 4, 2],[1, 7, 9]])
ls = LinearSystem(A)
ls.row_echelon()
np.testing.assert_array_almost_equal(ls.mat,
np.array([[ 5., 4., 2.],
[0., 6.2, 8.6],
[ 0., 0., 0.5483871]]), decimal=6)
def test_row_echelon_private(self):
A = np.array([[1, 3, 5],[5, 2, 2],[1, 7, 1]])
ls = LinearSystem(A)
ls.row_echelon()
np.testing.assert_array_almost_equal(ls.mat,
np.array([[5., 2., 2.],
[0., 6.6, 0.6],
[0., 0., 4.36363636]]), decimal=6)