def test_lesq_solution2():
# Exactly constrained.
N = np.array([22, 23, 34])
DE = np.matrix([[1, 0, 0], [0, 1, 0], [1, 1, 1]])
b_true = np.array([1.234, 1.456, 1.789])
dd_obs = bl.predict_carrier_obs_(N, DE, b_true)
code, b, resid = bl.lesq_solution_float_(dd_obs, N, DE)
assert code == 0
assert np.allclose(b, b_true)
def test_lesq_solution2():
# Exactly constrained.
N = np.array([22, 23, 34])
DE = np.matrix([[1, 0, 0],
[0, 1, 0],
[1, 1, 1]])
b_true = np.array([1.234, 1.456, 1.789])
dd_obs = bl.predict_carrier_obs_(N, DE, b_true)
code, b, resid = bl.lesq_solution_float_(dd_obs, N, DE)
assert code == 0
assert np.allclose(b, b_true)
def test_lesq_solution5():
# Over constrained with non-zero residuals
N = np.array([0, 0, 0, 0])
DE = np.matrix([[1, 0, 0], [0, 1, 0], [0, 0, 1], [1, 0, 0]])
b_true = np.array([0, 0, 0])
dd_obs = np.array([0, 0, 0, 1])
code, b, resid = bl.lesq_solution_float_(dd_obs, N, DE)
b_expected = np.array([0.5 * c.GPS_L1_LAMBDA_NO_VAC_, 0, 0])
resid_expected = np.array([-0.5, 0, 0, 0.5])
assert code == 0, "solution returned error %d" % code
np.allclose(b, b_true)
np.allclose(resid, resid_expected)
def test_lesq_solution5():
# Over constrained with non-zero residuals
N = np.array([0, 0, 0, 0])
DE = np.matrix([[1, 0, 0],
[0, 1, 0],
[0, 0, 1],
[1, 0, 0]])
b_true = np.array([0, 0, 0])
dd_obs = np.array([0, 0, 0, 1])
code, b, resid = bl.lesq_solution_float_(dd_obs, N, DE)
b_expected = np.array([0.5*c.GPS_L1_LAMBDA_NO_VAC_, 0, 0])
resid_expected = np.array([-0.5, 0, 0, 0.5])
assert code == 0, "solution returned error %d" % code
np.allclose(b, b_true)
np.allclose(resid, resid_expected)