1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
|
#!/usr/bin/env python
#
# Copyright 2013 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# GNU Radio is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3, or (at your option)
# any later version.
#
# GNU Radio is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with GNU Radio; see the file COPYING. If not, write to
# the Free Software Foundation, Inc., 51 Franklin Street,
# Boston, MA 02110-1301, USA.
#
from gnuradio import gr, gr_unittest
import blocks_swig as blocks
import math, random
def make_random_complex_tuple(L, scale=1):
result = []
for x in range(L):
result.append(scale*complex(2*random.random()-1,
2*random.random()-1))
return tuple(result)
def make_random_float_tuple(L, scale=1):
result = []
for x in range(L):
result.append(scale*(2*random.random()-1))
return tuple(result)
class test_moving_average(gr_unittest.TestCase):
def setUp(self):
self.tb = gr.top_block()
def tearDown(self):
self.tb = None
def test_01(self):
tb = self.tb
N = 10000
seed = 0
data = make_random_float_tuple(N, 1)
expected_result = N*[0,]
src = gr.vector_source_f(data, False)
op = blocks.moving_average_ff(100, 0.001)
dst = gr.vector_sink_f()
tb.connect(src, op)
tb.connect(op, dst)
tb.run()
dst_data = dst.data()
# make sure result is close to zero
self.assertFloatTuplesAlmostEqual(expected_result, dst_data, 1)
def test_02(self):
tb = self.tb
N = 10000
seed = 0
data = make_random_complex_tuple(N, 1)
expected_result = N*[0,]
src = gr.vector_source_c(data, False)
op = blocks.moving_average_cc(100, 0.001)
dst = gr.vector_sink_c()
tb.connect(src, op)
tb.connect(op, dst)
tb.run()
dst_data = dst.data()
# make sure result is close to zero
self.assertComplexTuplesAlmostEqual(expected_result, dst_data, 1)
if __name__ == '__main__':
gr_unittest.run(test_moving_average, "test_moving_average.xml")
|