def test_M2(self):
for L in [2, 4, 8]:
self.assertEqual(isUnitary(generateADSMCodes(2, "PSK", L)), True)
mind = getMinimumEuclideanDistance(generateADSMCodes(2, "PSK", 2))
self.assertAlmostEqual(mind, 4.0)
mind = getMinimumEuclideanDistance(generateADSMCodes(2, "PSK", 2, 2.0 * np.pi / 4.0))
self.assertAlmostEqual(mind, 2.0)
def test_M4(self):
codes = generateTASTCodes(4, 1, 2)
self.assertGreater(getMinimumEuclideanDistance(codes), 0.0)
self.assertEqual(isUnitary(codes), True)
codes = generateTASTCodes(4, 2, 2)
self.assertGreater(getMinimumEuclideanDistance(codes), 0.0)
self.assertEqual(isUnitary(codes), True)
codes = generateTASTCodes(4, 2, 4)
self.assertGreater(getMinimumEuclideanDistance(codes), 0.0)
self.assertEqual(isUnitary(codes), True)
def test_getMinimumEuclideanDistance(self):
codes = mod.generatePSKSymbols(4).reshape(4, 1, 1)
med = me.getMinimumEuclideanDistance(np.array(codes))
self.assertAlmostEqual(med, 2.0)
codes = mod.generateStarQAMSymbols(16).reshape(16, 1, 1)
med = me.getMinimumEuclideanDistance(np.array(codes))
self.assertAlmostEqual(med, 0.2343145750507619)
codes = im.generateIMCodes("opt", 4, 2, 4, "PSK", 4, 1)
med = me.getMinimumEuclideanDistance(np.array(codes))
self.assertAlmostEqual(med, 1.0)
codes = im.generateIMCodes("opt", 8, 4, 64, "PSK", 2, 1)
med = me.getMinimumEuclideanDistance(np.array(codes))
self.assertAlmostEqual(med, 0.5)
def test_M2(self):
codes = generateIMCodes("opt", 2, 1, 2, "PSK", 1, 1)
np.testing.assert_almost_equal(codes,
np.array([[[1.], [0.]], [[0.], [1.]]]))
codes = generateIMCodes("dic", 4, 1, 4, "PSK", 1, 1)
np.testing.assert_almost_equal(
codes,
np.array([[[1.], [0.], [0.], [0.]], [[0.], [1.], [0.], [0.]],
[[0.], [0.], [1.], [0.]], [[0.], [0.], [0.], [1.]]]))
codes = generateIMCodes("wen", 4, 2, 4, "PSK", 1, 1)
np.testing.assert_almost_equal(
codes,
np.array([[[0.70710678], [0.70710678], [0.], [0.]],
[[0.], [0.70710678], [0.70710678], [0.]],
[[0.], [0.], [0.70710678], [0.70710678]],
[[0.70710678], [0.], [0.], [0.70710678]]]))
codes = generateIMCodes("dic", 8, 4, 8, "PSK", 2, 1)
self.assertAlmostEqual(getMinimumEuclideanDistance(codes), 0.5)
codes = generateIMCodes("opt", 8, 4, 8, "PSK", 2, 1)
self.assertAlmostEqual(getMinimumEuclideanDistance(codes), 1.0)
def test_QAM(self):
for L in 2**np.arange(2, 8, 2):
symbols = generateQAMSymbols(L)
meanNorm = np.mean(np.square(np.abs(symbols)))
self.assertAlmostEqual(meanNorm,
1.0,
msg="The mean power of QAM(" + str(L) +
") symbols differs from 1.0")
med = getMinimumEuclideanDistance(symbols.reshape(L, 1, 1))
self.assertGreater(med,
0,
msg="The minimum Euclidean distance of QAM(" +
str(L) + ") symbols is too small")