def test_utmrowlist_to_npmatrix(self):
mat = priority.utmrowlist_to_npmatrix([2, 6, 3])
npt.assert_almost_equal(mat,
[[1, 2, 6], [1 / 2, 1, 3], [1 / 6, 1 / 3, 1]],
decimal=7)
mat = priority.utmrowlist_to_npmatrix([2, 6, 0])
npt.assert_almost_equal(mat, [[1, 2, 6], [1 / 2, 1, 0], [1 / 6, 0, 1]],
decimal=7)
def test_harker_fix(self):
mat = priority.utmrowlist_to_npmatrix([2, 6, 0])
fixed = priority.harker_fix(mat)
npt.assert_almost_equal(fixed, [[1, 2, 6], [0.5, 2, 0], [1 / 6, 0, 2]],
decimal=7)
mat = priority.utmrowlist_to_npmatrix([3, 6, 1 / 7])
fixed = priority.harker_fix(mat)
npt.assert_almost_equal(fixed,
[[1, 3, 6], [1 / 3, 1, 1 / 7], [1 / 6, 7, 1]],
decimal=7)
def test_prerr_euclidratio(self):
mat = priority.utmrowlist_to_npmatrix([2, 6, 3])
vec = np.array([1, 1, 1])
err = priority.prerr_euclidratio(mat, vec)
expected = ((2 - 1)**2 + (1 / 2 - 1)**2 + (6 - 1)**2 + (1 / 6 - 1)**2 +
(3 - 1)**2 + (1 / 3 - 1)**2)**(1 / 2)
npt.assert_almost_equal(err, expected, decimal=7)
def test_pri_llsm(self):
#Try a standard completely consistent matrix
mat = priority.utmrowlist_to_npmatrix([2, 6, 3])
result = priority.pri_llsm(mat)
npt.assert_almost_equal(result, [0.6, 0.3, 0.1], 7)
#Try slightly inconsistent 3x3
mat = priority.utmrowlist_to_npmatrix([2, 4, 3])
result = priority.pri_llsm(mat)
expected = [0.5584245, 0.3196183, 0.1219572]
npt.assert_almost_equal(result, expected, 7)
#Now this agrees with expeigen for 3x3, let's try a 4x4
mat = priority.utmrowlist_to_npmatrix([2, 3, 4, 2, 5, 3])
result = priority.pri_llsm(mat)
expected = [0.4508867, 0.3046191, 0.1712999, 0.0731942]
npt.assert_almost_equal(result, expected, 7)
#Try a 5x5
mat = priority.utmrowlist_to_npmatrix(
[1 / 2, 1 / 3, 1 / 4, 1 / 5, 2, 3, 4, 2, 5, 3])
result = priority.pri_llsm(mat)
expected = [0.0636715, 0.3597739, 0.2851016, 0.1905405, 0.1009125]
npt.assert_almost_equal(result, expected, 7)
def test_pri_expeigen(self):
#Try a standard completely consistent matrix
mat = priority.utmrowlist_to_npmatrix([2, 6, 3])
result = priority.pri_expeigen(mat)
npt.assert_almost_equal(result, [0.6, 0.3, 0.1], 7)
#Try slightly inconsistent 3x3
mat = priority.utmrowlist_to_npmatrix([2, 4, 3])
result = priority.pri_expeigen(mat)
expected = [0.5722136, 0.3011777, 0.1266087]
npt.assert_almost_equal(result, expected, 7)
#Let's try a 4x4
mat = priority.utmrowlist_to_npmatrix([2, 3, 4, 2, 5, 3])
result = priority.pri_expeigen(mat)
expected = [0.4842086, 0.273452, 0.1595522, 0.0827873]
npt.assert_almost_equal(result, expected, 7)
#Try a 5x5
mat = priority.utmrowlist_to_npmatrix(
[1 / 2, 1 / 3, 1 / 4, 1 / 5, 2, 3, 4, 2, 5, 3])
result = priority.pri_expeigen(mat)
expected = [0.0940351, 0.4047186, 0.2545017, 0.1592964, 0.0874481]
npt.assert_almost_equal(result, expected, 7)
def test_prerr_ratio_prod(self):
mat = priority.utmrowlist_to_npmatrix([2, 6, 3])
# Try against unit vector
vec = np.array([1, 1, 1])
err = priority.prerr_ratio_prod(mat, vec)
expected = 36**(1 / 3)
npt.assert_almost_equal(err, expected, decimal=7)
# Try against a slightly more complicated vector
vec = np.array([5, 2, 10])
err = priority.prerr_ratio_prod(mat, vec)
expected = 6.0822019955733992
npt.assert_almost_equal(err, expected, decimal=7)
def test_pri_eigen(self):
mat = priority.utmrowlist_to_npmatrix([2, 6, 3])
eig = priority.pri_eigen(mat)
npt.assert_almost_equal(eig, [0.6, 0.3, 0.1], 7)
val = priority.pri_eigen(mat, return_eigenval=True)
npt.assert_almost_equal(val, 3.0, decimal=7)
def test_prerr_ratio_avg(self):
mat = priority.utmrowlist_to_npmatrix([2, 6, 3])
vec = np.array([1, 1, 1])
err = priority.prerr_ratio_avg(mat, vec)
expected = ((2 - 1) * 2 + (6 - 1) * 2 + (3 - 1) * 2) / 6
npt.assert_almost_equal(err, expected, decimal=7)
def test_incon_std(self):
mat = priority.utmrowlist_to_npmatrix([2, 6, 3])
npt.assert_almost_equal(priority.incon_std(mat), 0, decimal=7)
mat = priority.utmrowlist_to_npmatrix([2, 1 / 6, 3])
actual = 1.5430583470604067
npt.assert_almost_equal(priority.incon_std(mat), actual, decimal=7)