From 31c4a701e6b6fdf84bb1385663a0b707dd40a766 Mon Sep 17 00:00:00 2001
From: Josh Morman <jmorman@perspectalabs.com>
Date: Thu, 25 Mar 2021 16:27:51 -0400
Subject: digital: fix qa for equalizers
Signed-off-by: Josh Morman <jmorman@perspectalabs.com>
---
gr-digital/python/digital/qa_linear_equalizer.py | 36 ++++++++++++++++++------
1 file changed, 28 insertions(+), 8 deletions(-)
(limited to 'gr-digital/python/digital/qa_linear_equalizer.py')
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)
--
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