diff options
Diffstat (limited to 'gr-digital/python/digital/qa_linear_equalizer.py')
| -rwxr-xr-x | gr-digital/python/digital/qa_linear_equalizer.py | 36 |
1 files changed, 28 insertions, 8 deletions
diff --git a/gr-digital/python/digital/qa_linear_equalizer.py b/gr-digital/python/digital/qa_linear_equalizer.py index 1ad3c3bece..64fd84d2f3 100755 --- a/gr-digital/python/digital/qa_linear_equalizer.py +++ b/gr-digital/python/digital/qa_linear_equalizer.py @@ -105,22 +105,42 @@ class qa_linear_equalizer(gr_unittest.TestCase): def tearDown(self): self.tb = None - def transform(self, src_data, gain, const): - SRC = blocks.vector_source_c(src_data, False) - EQU = digital.lms_dd_equalizer_cc(4, gain, 1, const.base()) - DST = blocks.vector_sink_c() - self.tb.connect(SRC, EQU, DST) + def transform(self, src_data, const, alg): + src = blocks.vector_source_c(src_data, False) + leq = digital.linear_equalizer( + 4, + 1, + alg, + True, + [], + '') + dst = blocks.vector_sink_c() + self.tb.connect(src, leq, dst) self.tb.run() - return DST.data() + return dst.data() + + def test_001_identity_lms(self): + # Constant modulus signal so no adjustments + const = digital.constellation_qpsk() + src_data = const.points() * 1000 + alg = digital.adaptive_algorithm_lms(const, .1).base() + + N = 100 # settling time + expected_data = src_data[N:] + result = self.transform(src_data, const, alg)[N:] + + N = -500 + self.assertComplexTuplesAlmostEqual(expected_data[N:], result[N:], 5) - def test_001_identity(self): + def test_002_identity_cma(self): # Constant modulus signal so no adjustments const = digital.constellation_qpsk() src_data = const.points() * 1000 + alg = digital.adaptive_algorithm_cma(const, .001, 4).base() N = 100 # settling time expected_data = src_data[N:] - result = self.transform(src_data, 0.1, const)[N:] + result = self.transform(src_data, const, alg)[N:] N = -500 self.assertComplexTuplesAlmostEqual(expected_data[N:], result[N:], 5) |