def test_003 (self):
stream = [ [float(0)]*10, [float(1)]*10, [float(2)]*10 ]
mux = [ 0,2,2,1,1,2,0,2,0,0,
1,0,1,0,1,2,1,2,1,1,
2,0,0,2,1,2,0,1,2,0 ]
imux = []
for x in mux:
imux.append(int(x))
data = [gr.vector_source_f(stream[0]),
gr.vector_source_f(stream[1]),
gr.vector_source_f(stream[2])]
dst = gr.vector_sink_f()
uut = ofdm.static_mux_v(gr.sizeof_float, imux)
self.fg.connect(data[0], (uut,0))
self.fg.connect(data[1], (uut,1))
self.fg.connect(data[2], (uut,2))
self.fg.connect(uut,dst)
self.fg.run()
self.assertEqual(map(float,mux),list(dst.data()))
def test_002_t(self):
"""
Defined source data for three incoming port
For one port src_data0
For N port src_data0,src_data1,src_data2,.......,src_dataN.
"""
src_data0 = (1,2,3,1)
src_data1 = (2,7,3,0)
src_data2 = (1,2,2,3)
src_data3 = (25,16,4,81)
expected_result = (8,20,13,12)
src0 = gr.vector_source_f(src_data0)
src1 = gr.vector_source_f(src_data1)
src2 = gr.vector_source_f(src_data2)
src3 = gr.vector_source_f(src_data3)
cal_ref = Calculator("(a0*a1)+a2+sqrt(a3)",4)
dst = gr.vector_sink_f()
self.tb.connect(src0,(cal_ref,0))
self.tb.connect(src1,(cal_ref,1))
self.tb.connect(src2,(cal_ref,2))
self.tb.connect(src3,(cal_ref,3))
self.tb.connect(cal_ref,dst)
self.tb.run()
result_data = dst.data()
print "Result data is : ",result_data
self.assertFloatTuplesAlmostEqual(expected_result,result_data,6)
def test_001(self):
fg = self.fg
src1_data = (0,0.2,-0.3,0,12,0)
src2_data = (0,0.0,3.0,0,10,0)
src3_data = (0,0.0,3.0,0,1,0)
src1 = gr.vector_source_f (src1_data)
s2v1 = gr.stream_to_vector(gr.sizeof_float, len(src1_data))
fg.connect( src1, s2v1 )
src2 = gr.vector_source_f (src2_data)
s2v2 = gr.stream_to_vector(gr.sizeof_float, len(src1_data))
fg.connect( src2, s2v2 )
src3 = gr.vector_source_f (src3_data)
s2v3 = gr.stream_to_vector(gr.sizeof_float, len(src1_data))
fg.connect( src3, s2v3 )
dst1 = gr.vector_sink_s ()
dst2 = gr.vector_sink_s ()
argmax = gr.argmax_fs (len(src1_data))
fg.connect (s2v1, (argmax, 0))
fg.connect (s2v2, (argmax, 1))
fg.connect (s2v3, (argmax, 2))
fg.connect ((argmax,0), dst1)
fg.connect ((argmax,1), dst2)
fg.run ()
index = dst1.data ()
source = dst2.data ()
self.assertEqual ( index, (4,))
self.assertEqual ( source, (0,))
def __init__(self): grc_wxgui.top_block_gui.__init__(self, title="Top Block") ################################################## # Variables ################################################## self.samp_rate = samp_rate = 32000 ################################################## # Blocks ################################################## self.gr_vector_source_x_0_0 = gr.vector_source_f((40,50,60), True, 1) self.gr_vector_source_x_0 = gr.vector_source_f((4,5,6), True, 1) self.gr_vector_sink_x_0 = gr.vector_sink_f(1) self.gr_sbhs_0 = gr_sbhs.gr_sbhs() self.gr_sbhs_0.set_parameters(1) self.gr_file_sink_0 = gr.file_sink(gr.sizeof_float*1, "ne2.txt") self.gr_file_sink_0.set_unbuffered(True) ################################################## # Connections ################################################## self.connect((self.gr_vector_source_x_0, 0), (self.gr_sbhs_0, 0)) self.connect((self.gr_vector_source_x_0_0, 0), (self.gr_sbhs_0, 1)) self.connect((self.gr_sbhs_0, 0), (self.gr_vector_sink_x_0, 0)) self.connect((self.gr_sbhs_0, 0), (self.gr_file_sink_0, 0))
def test_stretch_01(self):
tb = self.tb
data = 10*[1,]
data0 = map(lambda x: x/20.0, data)
data1 = map(lambda x: x/10.0, data)
expected_result0 = 10*[0.05,]
expected_result1 = 10*[0.1,]
src0 = gr.vector_source_f(data0, False)
src1 = gr.vector_source_f(data1, False)
inter = gr.streams_to_vector(gr.sizeof_float, 2)
op = blocks.stretch_ff(0.1, 2)
deinter = gr.vector_to_streams(gr.sizeof_float, 2)
dst0 = gr.vector_sink_f()
dst1 = gr.vector_sink_f()
tb.connect(src0, (inter,0))
tb.connect(src1, (inter,1))
tb.connect(inter, op)
tb.connect(op, deinter)
tb.connect((deinter,0), dst0)
tb.connect((deinter,1), dst1)
tb.run()
dst0_data = dst0.data()
dst1_data = dst1.data()
self.assertFloatTuplesAlmostEqual(expected_result0, dst0_data, 4)
self.assertFloatTuplesAlmostEqual(expected_result1, dst1_data, 4)
def test_interleaving(self):
# Takes 3 streams (a, b and c)
# Outputs 2 streams.
# First (d) is interleaving of a and b.
# Second (e) is interleaving of a and b and c. c is taken in
# chunks of 2 which are reversed.
A = (1, 2, 3, 4, 5)
B = (11, 12, 13, 14, 15)
C = (99, 98, 97, 96, 95, 94, 93, 92, 91, 90)
expected_D = (1, 11, 2, 12, 3, 13, 4, 14, 5, 15)
expected_E = (1, 11, 98, 99, 2, 12, 96, 97, 3, 13, 94, 95,
4, 14, 92, 93, 5, 15, 90, 91)
mapping = [[(0, 0), (1, 0)], # mapping to produce D
[(0, 0), (1, 0), (2, 1), (2, 0)], # mapping to produce E
]
srcA = gr.vector_source_f(A, False, 1)
srcB = gr.vector_source_f(B, False, 1)
srcC = gr.vector_source_f(C, False, 2)
vmap = gr.vector_map(gr.sizeof_int, (1, 1, 2), mapping)
dstD = gr.vector_sink_f(2)
dstE = gr.vector_sink_f(4)
self.tb.connect(srcA, (vmap, 0))
self.tb.connect(srcB, (vmap, 1))
self.tb.connect(srcC, (vmap, 2))
self.tb.connect((vmap, 0), dstD)
self.tb.connect((vmap, 1), dstE)
self.tb.run()
self.assertEqual(expected_D, dstD.data())
self.assertEqual(expected_E, dstE.data())
def test_add_f32(self):
tb = gr.top_block()
src0 = gr.vector_source_f([1, 3, 5, 7, 9], False)
src1 = gr.vector_source_f([0, 2, 4, 6, 8], False)
adder = add_2_f32_1_f32()
sink = gr.vector_sink_f()
tb.connect((src0, 0), (adder, 0))
tb.connect((src1, 0), (adder, 1))
tb.connect(adder, sink)
tb.run()
self.assertEqual(sink.data(), (1, 5, 9, 13, 17))
def test_float_to_complex_2(self):
src1_data = (1.0, 3.0, 5.0, 7.0, 9.0)
src2_data = (2.0, 4.0, 6.0, 8.0, 10.0)
expected_data = (1+2j, 3+4j, 5+6j, 7+8j, 9+10j)
src1 = gr.vector_source_f(src1_data)
src2 = gr.vector_source_f(src2_data)
op = blocks_swig.float_to_complex()
dst = gr.vector_sink_c()
self.tb.connect(src1, (op, 0))
self.tb.connect(src2, (op, 1))
self.tb.connect(op, dst)
self.tb.run()
self.assertFloatTuplesAlmostEqual(expected_data, dst.data())
def help_stream_2ff(self, N, stream_sizes):
v0 = gr.vector_source_f(N*[1,], False)
v1 = gr.vector_source_f(N*[2,], False)
mux = gr.stream_mux(gr.sizeof_float, stream_sizes)
dst = gr.vector_sink_f ()
self.tb.connect (v0, (mux,0))
self.tb.connect (v1, (mux,1))
self.tb.connect (mux, dst)
self.tb.run ()
return dst.data ()
def test_002_interp(self):
taps = random_floats(31)
#src_data = random_floats(10000) # FIXME the 10k case fails!
src_data = random_floats(1000)
interpolation = 3
expected_result = reference_interp_filter(src_data, interpolation, taps)
tb = gr.top_block()
src = gr.vector_source_f(src_data)
op = gr.rational_resampler_base_fff(interpolation, 1, taps)
dst = gr.vector_sink_f()
tb.connect(src, op)
tb.connect(op, dst)
tb.run()
result_data = dst.data()
L1 = len(result_data)
L2 = len(expected_result)
L = min(L1, L2)
if False:
sys.stderr.write('delta = %2d: ntaps = %d interp = %d ilen = %d\n' %
(L2 - L1, len(taps), interpolation, len(src_data)))
sys.stderr.write(' len(result_data) = %d len(expected_result) = %d\n' %
(len(result_data), len(expected_result)))
#self.assertEqual(expected_result[0:L], result_data[0:L])
# FIXME check first 3 answers
self.assertEqual(expected_result[3:L], result_data[3:L])
def xtest_004_decim_random_vals(self):
MAX_TAPS = 9
MAX_DECIM = 7
OUTPUT_LEN = 9
random.seed(0) # we want reproducibility
for ntaps in xrange(1, MAX_TAPS + 1):
for decim in xrange(1, MAX_DECIM+1):
for ilen in xrange(ntaps + decim, ntaps + OUTPUT_LEN*decim):
src_data = random_floats(ilen)
taps = random_floats(ntaps)
expected_result = reference_dec_filter(src_data, decim, taps)
tb = gr.top_block()
src = gr.vector_source_f(src_data)
op = gr.rational_resampler_base_fff(1, decim, taps)
dst = gr.vector_sink_f()
tb.connect(src, op, dst)
tb.run()
tb = None
result_data = dst.data()
L1 = len(result_data)
L2 = len(expected_result)
L = min(L1, L2)
if False:
sys.stderr.write('delta = %2d: ntaps = %d decim = %d ilen = %d\n' % (L2 - L1, ntaps, decim, ilen))
sys.stderr.write(' len(result_data) = %d len(expected_result) = %d\n' %
(len(result_data), len(expected_result)))
self.assertEqual(expected_result[0:L], result_data[0:L])
def xtest_005_interp_random_vals(self):
MAX_TAPS = 9
MAX_INTERP = 7
INPUT_LEN = 9
random.seed(0) # we want reproducibility
for ntaps in xrange(1, MAX_TAPS + 1):
for interp in xrange(1, MAX_INTERP+1):
for ilen in xrange(ntaps, ntaps + INPUT_LEN):
src_data = random_floats(ilen)
taps = random_floats(ntaps)
expected_result = reference_interp_filter(src_data, interp, taps)
tb = gr.top_block()
src = gr.vector_source_f(src_data)
op = gr.rational_resampler_base_fff(interp, 1, taps)
dst = gr.vector_sink_f()
tb.connect(src, op, dst)
tb.run()
tb = None
result_data = dst.data()
L1 = len(result_data)
L2 = len(expected_result)
L = min(L1, L2)
#if True or abs(L1-L2) > 1:
if False:
sys.stderr.write('delta = %2d: ntaps = %d interp = %d ilen = %d\n' % (L2 - L1, ntaps, interp, ilen))
#sys.stderr.write(' len(result_data) = %d len(expected_result) = %d\n' %
# (len(result_data), len(expected_result)))
#self.assertEqual(expected_result[0:L], result_data[0:L])
# FIXME check first ntaps+1 answers
self.assertEqual(expected_result[ntaps+1:L], result_data[ntaps+1:L])
def transform(self, src_data, rate, freq):
src = gr.vector_source_f(src_data, False)
dft = gr.goertzel_fc(rate, rate, freq)
dst = gr.vector_sink_c()
self.tb.connect(src, dft, dst)
self.tb.run()
return dst.data()
def xtest_fff_003(self):
random.seed(0)
for i in xrange(25):
sys.stderr.write("\n>>> Loop = %d\n" % (i,))
src_len = 4096
src_data = make_random_float_tuple(src_len)
ntaps = int(random.uniform(2, 1000))
taps = make_random_float_tuple(ntaps)
expected_result = reference_filter_fff(1, taps, src_data)
src = gr.vector_source_f(src_data)
op = gr.fft_filter_fff(1, taps)
dst = gr.vector_sink_f()
tb = gr.top_block()
tb.connect(src, op, dst)
tb.run()
result_data = dst.data()
#print "src_len =", src_len, " ntaps =", ntaps
try:
self.assert_fft_float_ok2(expected_result, result_data, abs_eps=1.0)
except:
expected = open('expected', 'w')
for x in expected_result:
expected.write(`x` + '\n')
actual = open('actual', 'w')
for x in result_data:
actual.write(`x` + '\n')
raise
def test_002(self):
udp_rcv = gr.udp_source( gr.sizeof_float, '0.0.0.0', 0, eof=False )
rcv_port = udp_rcv.get_port()
udp_snd = gr.udp_sink( gr.sizeof_float, '127.0.0.1', 65500 )
udp_snd.connect( 'localhost', rcv_port )
n_data = 16
src_data = [float(x) for x in range(n_data)]
expected_result = tuple(src_data)
src = gr.vector_source_f(src_data)
dst = gr.vector_sink_f()
self.tb_snd.connect( src, udp_snd )
self.tb_rcv.connect( udp_rcv, dst )
self.tb_rcv.start()
self.tb_snd.run()
udp_snd.disconnect()
self.timeout = False
q = Timer(3.0,self.stop_rcv)
q.start()
self.tb_rcv.wait()
q.cancel()
result_data = dst.data()
self.assertEqual(expected_result, result_data)
self.assert_(self.timeout) # source ignores EOF?
def test_deint_001 (self):
lenx = 64
src0 = gr.vector_source_f (range (lenx))
op = gr.deinterleave (gr.sizeof_float,4)
dst0 = gr.vector_sink_f ()
dst1 = gr.vector_sink_f ()
dst2 = gr.vector_sink_f ()
dst3 = gr.vector_sink_f ()
self.tb.connect (src0, op)
op.connect(dst0,usesPortName="float_out_1")
op.connect(dst1,usesPortName="float_out_2")
op.connect(dst2,usesPortName="float_out_3")
op.connect(dst3,usesPortName="float_out_4")
self.tb.run ()
expected_result0 = tuple (range (0, lenx, 4))
expected_result1 = tuple (range (1, lenx, 4))
expected_result2 = tuple (range (2, lenx, 4))
expected_result3 = tuple (range (3, lenx, 4))
self.assertFloatTuplesAlmostEqual (expected_result0, dst0.data())
self.assertFloatTuplesAlmostEqual (expected_result1, dst1.data())
self.assertFloatTuplesAlmostEqual (expected_result2, dst2.data ())
self.assertFloatTuplesAlmostEqual (expected_result3, dst3.data ())
def test_deint_001 (self):
lenx = 64
src = gr.vector_source_f (range (lenx))
op = gr.deinterleave (gr.sizeof_float)
dst0 = gr.vector_sink_f ()
dst1 = gr.vector_sink_f ()
dst2 = gr.vector_sink_f ()
dst3 = gr.vector_sink_f ()
self.tb.connect (src, op)
self.tb.connect ((op, 0), dst0)
self.tb.connect ((op, 1), dst1)
self.tb.connect ((op, 2), dst2)
self.tb.connect ((op, 3), dst3)
self.tb.run ()
expected_result0 = tuple (range (0, lenx, 4))
expected_result1 = tuple (range (1, lenx, 4))
expected_result2 = tuple (range (2, lenx, 4))
expected_result3 = tuple (range (3, lenx, 4))
self.assertFloatTuplesAlmostEqual (expected_result0, dst0.data ())
self.assertFloatTuplesAlmostEqual (expected_result1, dst1.data ())
self.assertFloatTuplesAlmostEqual (expected_result2, dst2.data ())
self.assertFloatTuplesAlmostEqual (expected_result3, dst3.data ())
def test_fir_filter_fcc_002(self):
self.generate_fcc_source()
expected_data = ((-6.94218761055e-05-9.90489479591e-06j),
(-2.56973435171e-05+8.05932795629e-05j),
(7.01698663761e-05+7.36373840482e-05j),
(7.57163215894e-05-4.65324592369e-05j),
(-3.01657128148e-05-0.000122838056996j),
(-9.53659764491e-05-3.73945695173e-05j),
(-2.33501577895e-05+0.000109135726234j),
(6.65136758471e-05+0.000125709688291j),
(3.08501912514e-05-9.16842873266e-06j),
(-2.64703612629e-05-0.000135892929393j),
(0.000136643866426-0.000162003751029j),
(0.000501801609062-0.000185820827028j),
(0.000694551155902-0.000299874518532j),
(0.000424396857852-0.00038379128091j),
(-9.1786707344e-05-0.000242479465669j),
(-0.000337087287335+7.45999423089e-05j),
(-0.000116414521472+0.000258556567132j),
(0.000215422536712+0.000116706112749j),
(0.000224391726078-0.000156330308528j),
(-5.96956087975e-05-0.000211163976928j))
src = gr.vector_source_f(self.src_data)
op = filter.freq_xlating_fir_filter_fcc(4, self.taps, self.fc, self.fs)
dst = gr.vector_sink_c()
self.tb.connect(src, op, dst)
self.tb.run()
result_data = dst.data()
self.assertComplexTuplesAlmostEqual(expected_data, result_data[-20:], 5)
def test_fir_filter_fcf_001(self):
self.generate_fcf_source()
expected_data = ((0.000247188087087-0.000157509770361j),
(-0.000155229790835-0.000246197130764j),
(-0.000264906557277+0.000174603672349j),
(6.99016964063e-05+0.000174961372977j),
(-5.48477692064e-05-0.0001131295503j),
(-0.000237467131228+0.000118011368613j),
(0.000136614587973+0.000229531884543j),
(0.000229347482673-0.000166581812664j),
(-0.000106010869786-0.000150042149471j),
(2.92293734674e-05+0.000142060467624j),
(0.000228707227507-9.30760797928e-05j),
(-0.000124306126963-0.000216641055886j),
(-0.000204823678359+0.00016052465071j),
(0.00012825592421+0.000133123627165j),
(-1.18284006021e-05-0.000159015646204j),
(-0.000219973371713+7.5438656495e-05j),
(0.000114713984658+0.000205190401175j),
(0.000185727752978-0.000154630601173j),
(-0.000141745767905-0.000120098840853j),
(-3.9850056055e-07+0.000168364742422j))
src = gr.vector_source_f(self.src_data)
op = filter.freq_xlating_fir_filter_fcf(1, self.taps, self.fc, self.fs)
dst = gr.vector_sink_c()
self.tb.connect(src, op, dst)
self.tb.run()
result_data = dst.data()
self.assertComplexTuplesAlmostEqual(expected_data, result_data[-20:], 5)
def test_006_interp_decim(self):
taps = (0,1,0,0)
src_data = range(10000)
interp = 3
decimation = 2
expected_result = reference_interp_dec_filter(src_data, interp, decimation, taps)
tb = gr.top_block()
src = gr.vector_source_f(src_data)
op = gr.rational_resampler_base_fff(interp, decimation, taps)
dst = gr.vector_sink_f()
tb.connect(src, op)
tb.connect(op, dst)
tb.run()
result_data = dst.data()
L1 = len(result_data)
L2 = len(expected_result)
L = min(L1, L2)
if False:
sys.stderr.write('delta = %2d: ntaps = %d decim = %d ilen = %d\n' %
(L2 - L1, len(taps), decimation, len(src_data)))
sys.stderr.write(' len(result_data) = %d len(expected_result) = %d\n' %
(len(result_data), len(expected_result)))
self.assertEqual(expected_result[1:L], result_data[1:L])
def xtest_004(self):
vlen = 4
tune = counter4(self, 1)
tune_delay = 1
dwell_delay = 2
msgq = gr.msg_queue()
src_data = tuple([float(x) for x in
( 1, 2, 3, 4,
9, 6, 11, 8,
5, 10, 7, 12,
13, 14, 15, 16
)])
expected_results = tuple([float(x) for x in
( 9, 10, 11, 12)])
src = gr.vector_source_f(src_data, False)
s2v = gr.stream_to_vector(gr.sizeof_float, vlen)
stats = gr.bin_statistics_f(vlen, msgq, tune, tune_delay, dwell_delay)
self.tb.connect(src, s2v, stats)
self.tb.run()
self.assertEqual(1, msgq.count())
for i in range(1):
m = parse_msg(msgq.delete_head())
#print "m =", m.center_freq, m.data
self.assertEqual(expected_results[vlen*i:vlen*i + vlen], m.data)
def test_001_t (self):
src_data = [0]*10
src_data1 = [1]*20
src_data = src_data+src_data1
#expected_result = (-2.0, 0.0, 5.0, 8.0, 9.0, 11.0, 14.0, 18.0)
src0 = gr.vector_source_f(src_data)
sqr = dsim()
sqr.set_parameters(2,0.5,1,.1,10,1)
#Preload
sqr.input_config(1).preload_items = 1
dst = gr.vector_sink_f()
self.tb.connect(src0, (sqr,0)) # src0(vector_source) -> sqr_input_0
self.tb.connect((sqr,0), (sqr,1)) # sqr_output_0 -> sqr_input_1
self.tb.connect(sqr,dst) # sqr_output_0 -> dst (vector_source)
self.tb.run()
result_data = dst.data()
import matplotlib.pyplot as plt
plt.plot(result_data)
print "result", result_data
plt.show()
def test_fir_filter_fcf_002(self):
self.generate_fcf_source()
expected_data = ((7.3052920925e-05-3.91741014028e-06j),
(3.11913172482e-05-0.000109872074972j),
(-0.000128646017401-3.49857727997e-05j),
(-5.49546712136e-05+8.96326746442e-05j),
(5.14321582159e-05+9.64698920143e-05j),
(0.000120189361041+2.4231892894e-05j),
(0.000100405508419-0.000223224604269j),
(-0.000274751859251-2.33274622587e-05j),
(1.52600114234e-06+0.000133301247843j),
(3.77224641852e-05+5.29596509296e-05j),
(-3.60160379387e-06+0.000247975171078j),
(0.00113093166146-0.000663110695314j),
(0.00059568521101-0.00099650840275j),
(-0.000475480686873+0.000250602373853j),
(0.000191397906747+0.000271986238658j),
(0.000247183139436-0.000157510468853j),
(-5.48357638763e-05-0.000113135029096j),
(-0.00010601492977-0.00015005269961j),
(-0.000204817260965+0.000160534662427j),
(0.000114742244477+0.000205190313864j))
src = gr.vector_source_f(self.src_data)
op = filter.freq_xlating_fir_filter_fcf(4, self.taps, self.fc, self.fs)
dst = gr.vector_sink_c()
self.tb.connect(src, op, dst)
self.tb.run()
result_data = dst.data()
self.assertComplexTuplesAlmostEqual(expected_data, result_data[-20:], 5)
def test02(self):
# Test float/float version
omega = 2
gain_omega = 0.01
mu = 0.5
gain_mu = 0.01
omega_rel_lim = 0.001
self.test = digital_swig.clock_recovery_mm_ff(omega, gain_omega, mu, gain_mu, omega_rel_lim)
data = 100 * [1]
self.src = gr.vector_source_f(data, False)
self.snk = gr.vector_sink_f()
self.tb.connect(self.src, self.test, self.snk)
self.tb.run()
expected_result = 100 * [0.99972] # doesn't quite get to 1.0
dst_data = self.snk.data()
# Only compare last Ncmp samples
Ncmp = 30
len_e = len(expected_result)
len_d = len(dst_data)
expected_result = expected_result[len_e - Ncmp :]
dst_data = dst_data[len_d - Ncmp :]
# print expected_result
# print dst_data
self.assertFloatTuplesAlmostEqual(expected_result, dst_data, 5)
def test_fir_filter_fcc_001(self):
self.generate_fcc_source()
expected_data = ((-0.000337088305969+7.46004516259e-05j),
(-5.63409266761e-05+0.000301144464174j),
(9.16960561881e-05-2.89259278361e-05j),
(-0.000231866899412-6.25764005235e-05j),
(-0.000116414688819+0.000258557556663j),
(0.000206079319469+5.05045172758e-05j),
(-3.85114690289e-05-0.00019276549574j),
(-0.000146380873048+0.000112079876999j),
(0.000215423395275+0.000116706331028j),
(0.000136050162837-0.000232611957472j),
(-0.000155499437824-5.41604022146e-05j),
(0.000106907449663+0.00016310159117j),
(0.000224392410018-0.000156331108883j),
(-0.000131131906528-0.000172063446371j),
(-5.92393880652e-05+0.00016801241145j),
(0.000214921761653-5.32235890205e-06j),
(-5.96960526309e-05-0.000211164733628j),
(-0.000193948610104+0.000113364716526j),
(0.000134820176754+0.000142527525895j),
(4.74465123261e-05-0.000175131688593j))
src = gr.vector_source_f(self.src_data)
op = filter.freq_xlating_fir_filter_fcc(1, self.taps, self.fc, self.fs)
dst = gr.vector_sink_c()
self.tb.connect(src, op, dst)
self.tb.run()
result_data = dst.data()
self.assertComplexTuplesAlmostEqual(expected_data, result_data[-20:], 5)
def test_001_codeallr2m3 (self):
""" Check Golay-SD-decoding m=3 for all possible inputs """
src_data = ( 0.648,0.680,0.636,0.946,0.209,0.710,0.237,0.120,
0.608,0.451,0.459,0.662,0.771,0.351,0.663,0.417,
0.842,0.833,0.257,0.614,0.583,0.541,0.870,0.265,
0.319,0.120,0.940,0.646,0.480,0.640,0.545,0.648,
0.544,0.722,0.523,0.994,0.219,0.106,0.110,0.064)
expected_data = ( 6,
0,
14,
1,
22)
src1 = gr.vector_source_f(src_data,0,8)
coding_action = chancoding.rmg_decoder_sd_vfi(3,1)
sink = gr.vector_sink_i()
self.tb.connect(src1, coding_action)
self.tb.connect(coding_action, sink)
self.tb.run()
self.assertEqual( coding_action.get_vlen_in(), 8)
self.assertEqual( coding_action.get_vlen_out(), 1)
self.assertEqual( coding_action.get_num_bits_out(), 5)
for i in range( len(expected_data) ):
self.assertEqual( sink.data()[i] , expected_data[i], i)
def test_005_(self):
src_data = (1.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0)
dwav = numpy.array(src_data)
wvps = numpy.zeros(3)
# wavelet power spectrum
scl = 1.0/sqr(dwav[0])
k = 1
for e in range(len(wvps)):
wvps[e] = scl*sqr(dwav[k:k+(01<<e)]).sum()
k += 01<<e
src = gr.vector_source_f(src_data, False, len(src_data))
kon = wavelet_swig.wvps_ff(len(src_data))
dst = gr.vector_sink_f(int(math.ceil(math.log(len(src_data), 2))))
self.tb.connect(src, kon)
self.tb.connect(kon, dst)
self.tb.run()
snk_data = dst.data()
sum = 0
for (u,v) in zip(snk_data, wvps):
w = u - v
sum += w * w
sum /= float(len(snk_data))
assert sum < 1e-6
def test_001(self):
port = 65500
n_data = 16
src_data = [float(x) for x in range(n_data)]
expected_result = tuple(src_data)
src = gr.vector_source_f(src_data)
udp_snd = gr.udp_sink( gr.sizeof_float, 'localhost', port )
self.tb_snd.connect( src, udp_snd )
udp_rcv = gr.udp_source( gr.sizeof_float, 'localhost', port )
dst = gr.vector_sink_f()
self.tb_rcv.connect( udp_rcv, dst )
self.tb_rcv.start()
self.tb_snd.run()
udp_snd.disconnect()
self.timeout = False
q = Timer(3.0,self.stop_rcv)
q.start()
self.tb_rcv.wait()
q.cancel()
result_data = dst.data()
self.assertEqual(expected_result, result_data)
self.assert_(not self.timeout)
def __init__(self):
gr.top_block.__init__(self)
parser = OptionParser(option_class=eng_option)
parser.add_option("-I", "--audio-input", type="string", default="",
help="pcm input device name. E.g., hw:0,0 or /dev/dsp")
parser.add_option("-O", "--audio-output", type="string", default="",
help="pcm output device name. E.g., hw:0,0 or /dev/dsp")
parser.add_option("-r", "--sample-rate", type="eng_float", default=8000,
help="set sample rate to RATE (8000)")
(options, args) = parser.parse_args ()
if len(args) != 0:
parser.print_help()
raise SystemExit, 1
sample_rate = int(options.sample_rate)
src = audio.source (sample_rate, options.audio_input)
dst = audio.sink (sample_rate, options.audio_output)
vec1 = [1, -1]
vsource = gr.vector_source_f(vec1, True)
multiply = gr.multiply_ff()
self.connect(src, (multiply, 0))
self.connect(vsource, (multiply, 1))
self.connect(multiply, dst)
def test_fir_filter_fff_001(self):
src_data = 40*[1, 2, 3, 4]
expected_data = (0.5, 1.5, 3.0, 5.0, 5.5, 6.5, 8.0, 10.0,
10.5, 11.5, 13.0, 15.0, 15.5, 16.5, 18.0,
20.0, 20.5, 21.5, 23.0, 25.0, 25.5, 26.5,
28.0, 30.0, 30.5, 31.5, 33.0, 35.0, 35.5,
36.5, 38.0, 40.0, 40.5, 41.5, 43.0, 45.0,
45.5, 46.5, 48.0, 50.0, 50.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0, 50.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0, 50.0)
src = gr.vector_source_f(src_data)
op = filter.fir_filter_fff(1, 20*[0.5, 0.5])
dst = gr.vector_sink_f()
self.tb.connect(src, op, dst)
self.tb.run()
result_data = dst.data()
self.assertFloatTuplesAlmostEqual(expected_data, result_data, 5)
def test_01(self):
tb = self.tb
data = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0]
expected_result = (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0)
src = gr.vector_source_f(data, False)
regen = blocks.peak_detector_fb()
dst = gr.vector_sink_b()
tb.connect(src, regen)
tb.connect(regen, dst)
tb.run()
dst_data = dst.data()
self.assertEqual(expected_result, dst_data)
def add_source(self, signal=None):
try:
if signal is None:
src = gr.message_source(gr.sizeof_float,
1) # queue depth 1, MUST BE 1
self.sources.append(src)
self.lengths.append(0)
self.is_const.append(False)
else:
src = gr.vector_source_f(list(signal), True)
self.sources.append(src)
self.lengths.append(len(signal))
self.is_const.append(True)
id = len(self.sources) - 1
self.tb.connect(src, (self.mux, id))
except Exception, ex:
print repr(ex)
raise RuntimeError, "Could not connect new source to mux"
def test_031_multiple_internal_inputs(self):
tb = gr.top_block()
src = gr.vector_source_f([
1.0,
])
hb = gr.hier_block2("hb", gr.io_signature(1, 1, gr.sizeof_float),
gr.io_signature(1, 1, gr.sizeof_float))
m1 = gr.multiply_const_ff(1.0)
m2 = gr.multiply_const_ff(2.0)
add = gr.add_ff()
hb.connect(hb, m1) # m1 is connected to hb external input #0
hb.connect(hb, m2) # m2 is also connected to hb external input #0
hb.connect(m1, (add, 0))
hb.connect(m2, (add, 1))
hb.connect(add, hb) # add is connected to hb external output #0
dst = gr.vector_sink_f()
tb.connect(src, hb, dst)
tb.run()
self.assertEquals(dst.data(), (3.0, ))
def xtest_fff_005(self):
random.seed(0)
for i in xrange(25):
sys.stderr.write("\n>>> Loop = %d\n" % (i,))
src_len = 4*1024
src_data = make_random_float_tuple(src_len)
ntaps = int(random.uniform(2, 1000))
taps = make_random_float_tuple(ntaps)
expected_result = reference_filter_fff(1, taps, src_data)
src = gr.vector_source_f(src_data)
op = gr.fft_filter_fff(1, taps)
dst = gr.vector_sink_f()
tb = gr.top_block()
tb.connect(src, op, dst)
tb.run()
result_data = dst.data()
self.assert_fft_float_ok2(expected_result, result_data, abs_eps=2.0)
def test_000(self):
num_msgs = 10
msg_interval = 1000
msg_list = []
for i in range(num_msgs):
msg_list.append(pmt.pmt_from_long(i))
# Create vector source with dummy data to trigger messages
src_data = []
for i in range(num_msgs * msg_interval):
src_data.append(float(i))
src = gr.vector_source_f(src_data, False)
msg_gen = message_generator(msg_list, msg_interval)
msg_cons = message_consumer()
# Connect vector source to message gen
self.tb.connect(src, msg_gen)
# Connect message generator to message consumer
self.tb.msg_connect(msg_gen, 'out_port', msg_cons, 'in_port')
# Verify that the messgae port query functions work
self.assertEqual(
pmt.pmt_symbol_to_string(
pmt.pmt_vector_ref(msg_gen.message_ports_out(), 0)),
'out_port')
self.assertEqual(
pmt.pmt_symbol_to_string(
pmt.pmt_vector_ref(msg_cons.message_ports_in(), 0)), 'in_port')
# Run to verify message passing
self.tb.start()
# Wait for all messages to be sent
while msg_gen.msg_ctr < num_msgs:
time.sleep(0.5)
self.tb.stop()
self.tb.wait()
# Verify that the message consumer got all the messages
self.assertEqual(num_msgs, len(msg_cons.msg_list))
for i in range(num_msgs):
self.assertTrue(pmt.pmt_equal(msg_list[i], msg_cons.msg_list[i]))
def test_006(self):
vlen = 128
syms = 4
bin1 = vlen / 2 - vlen / 4
bin2 = vlen / 2 + vlen / 3
bin1_val = 1.0j
bin2_val = -1.0
vec = numpy.array(numpy.zeros(vlen), numpy.complex)
vec[bin1] = bin1_val
vec[bin2] = bin2_val
vec = concatenate([vec] * syms)
epsilon = [1, -4, 5, 2]
frame_trigger = [1] * syms
expec = numpy.array(numpy.zeros(vlen * syms), numpy.complex)
for i in range(syms):
expec[bin1 + i * vlen + epsilon[i]] = bin1_val
expec[bin2 + i * vlen + epsilon[i]] = bin2_val
freq_shift = ofdm.frequency_shift_vcc(vlen, 1.0 / vlen)
fft = gr.fft_vcc(vlen, True, [], True) # natural order, dc = vlen / 2
ifft = gr.fft_vcc(vlen, False, [], True)
fft_scale = gr.multiply_const_vcc([1.0 / vlen] * vlen)
src = gr.vector_source_c(vec)
dst = gr.vector_sink_c()
s2v = gr.stream_to_vector(gr.sizeof_gr_complex, vlen)
v2s = gr.vector_to_stream(gr.sizeof_gr_complex, vlen)
eps = gr.vector_source_f(epsilon)
trig = gr.vector_source_b(frame_trigger)
self.fg.connect(src, s2v, ifft, (freq_shift, 0))
self.fg.connect(eps, (freq_shift, 1))
self.fg.connect(trig, (freq_shift, 2))
self.fg.connect(freq_shift, fft, fft_scale, v2s, dst)
self.fg.run()
self.assertComplexTuplesAlmostEqual2(expec, dst.data(), 1e-5)
def test_008(self):
vlen = 128
syms = 4
bin1 = vlen / 2 + 4
bin1_val = 1.0
cp_length = vlen / 4
expec = numpy.array(numpy.zeros(vlen), numpy.complex)
expec[bin1] = bin1_val
expec = concatenate([expec] * syms)
epsilon = [-0.5]
frame_trigger = numpy.concatenate([[1], [0] * (syms - 1)])
freq_shift = ofdm.frequency_shift_vcc(vlen, 1.0 / vlen, cp_length)
fft = gr.fft_vcc(vlen, True, [], True) # natural order, dc = vlen / 2
fft_scale = gr.multiply_const_vcc([1.0 / vlen] * vlen)
sampler = ofdm.vector_sampler(gr.sizeof_gr_complex, vlen)
trigger_vec = concatenate([[0] * (vlen + cp_length - 1), [1]])
trigger_vec = concatenate([trigger_vec] * syms)
trigger = gr.vector_source_b(trigger_vec.tolist())
src = gr.sig_source_c(vlen, gr.GR_COS_WAVE, 4.5, 1.0,
0.0) # bin vlen/2 + 4.5
dst = gr.vector_sink_c()
v2s = gr.vector_to_stream(gr.sizeof_gr_complex, vlen)
eps = gr.vector_source_f(epsilon)
trig = gr.vector_source_b(frame_trigger.tolist())
self.fg.connect(src, (sampler, 0))
self.fg.connect(trigger, (sampler, 1))
self.fg.connect(sampler, (freq_shift, 0))
self.fg.connect(eps, (freq_shift, 1))
self.fg.connect(trig, (freq_shift, 2))
self.fg.connect(freq_shift, fft, fft_scale, v2s, dst)
self.fg.run()
self.assertComplexTuplesAlmostEqual2(expec, dst.data(), 1e-5, 1e-5)
def test_002(self):
# Need to add padding to keep proper alignment
padding = tuple([0 for i in range(2)])
src_data = (2147483647, 2147483648, 2200000000, -2147483648,
-2147483649, -2200000000) + padding
expected_result = [
2147483647, 2147483647, 2147483647, -2147483647, -2147483647,
-2147483647
]
expected_result.extend(padding)
src = gr.vector_source_f(src_data)
op = gr.float_to_int()
dst = gr.vector_sink_i()
self.tb.connect(src, op, dst)
self.tb.run()
result_data = list(dst.data())
self.assertEqual(expected_result, result_data)
def setUp(self):
self.tb = gr.top_block()
print "qa_descrambling_vfvf START"
cell_id = 124
inf = open('/home/demel/exchange/matlab_pbch_demod_p.txt')
intu = range(480)
for i in range(480):
intu[i] = float(inf.readline())
self.src = gr.vector_source_f(intu, True, 480)
self.ld = lte_swig.descrambling_vfvf()
self.ld.set_cell_id(cell_id)
self.sink = gr.vector_sink_f(120)
self.head = gr.head(480 * 4, 10)
self.tb.connect(self.src, self.head, self.ld, self.sink)
def setUp (self):
print "qa_lte_rate_unmatch_vff START"
inf=open('/home/demel/exchange/matlab_pbch_descr.txt')
intu=range(120)
for i in range(120):
intu[i]=float(inf.readline())
#print line
#intu[i]=float(line)
invec=intu # invec is a sample vector interleaved from Matlab
self.tb = gr.top_block ()
self.src = gr.vector_source_f( invec, True, 40)
self.vtos = gr.vector_to_stream(1*gr.sizeof_float,40)
self.stov = gr.stream_to_vector(1*gr.sizeof_float,1*120)
self.head = gr.head(120*4,1)
self.lru = lte_swig.rate_unmatch_vff() # 124
self.sink = gr.vector_sink_f(120)
self.tb.connect(self.src, self.vtos, self.stov, self.head, self.lru, self.sink)
def test_004(self):
''' Test impulse response - short form, ff '''
src_data = [
1,
] + 100 * [
0,
]
expected_result = ((-0.029296875), (-0.0302734375), (0.96875),
(-0.0302734375), (-0.029296875))
src = gr.vector_source_f(src_data)
op = gr.dc_blocker_ff(32, False)
dst = gr.vector_sink_f()
self.tb.connect(src, op, dst)
self.tb.run()
# only test samples around D-1
result_data = dst.data()[29:34]
self.assertFloatTuplesAlmostEqual(expected_result, result_data)
def xtest_003_interp(self):
taps = random_floats(9)
src_data = random_floats(10000)
decimation = 3
expected_result = reference_dec_filter(src_data, decimation, taps)
tb = gr.top_block()
src = gr.vector_source_f(src_data)
op = filter.rational_resampler_base_fff(1, decimation, taps)
dst = gr.vector_sink_f()
tb.connect(src, op)
tb.connect(op, dst)
tb.run()
result_data = dst.data()
N = 10
offset = 10#len(taps)-1
print expected_result[100+offset:100+offset+N]
print result_data[100:100+N]
def test_006_interp_decim(self):
taps = random_floats(31)
src_data = random_floats(10000)
interp = 3
decimation = 2
expected_result = reference_interp_dec_filter(src_data, interp, decimation, taps)
tb = gr.top_block()
src = gr.vector_source_f(src_data)
op = filter.rational_resampler_base_fff(interp, decimation, taps)
dst = gr.vector_sink_f()
tb.connect(src, op)
tb.connect(op, dst)
tb.run()
result_data = dst.data()
N = 1000
offset = len(taps)/2
self.assertFloatTuplesAlmostEqual(expected_result[offset:offset+N], result_data[0:N], 5)
def test_pwr_squelch_004(self):
alpha = 0.0001
thr = -25
src_data = map(lambda x: float(x) / 10.0, range(1, 40))
src = gr.vector_source_f(src_data)
op = analog.pwr_squelch_ff(thr, alpha)
dst = gr.vector_sink_f()
self.tb.connect(src, op)
self.tb.connect(op, dst)
self.tb.run()
expected_result = src_data
expected_result[0:20] = 20 * [
0,
]
result_data = dst.data()
self.assertFloatTuplesAlmostEqual(expected_result, result_data, 4)
def test_003(self):
''' Test impulse response - long form, ff '''
src_data = [
1,
] + 100 * [
0,
]
expected_result = ((-0.02072429656982422), (-0.02081298828125),
(0.979156494140625), (-0.02081298828125),
(-0.02072429656982422))
src = gr.vector_source_f(src_data)
op = gr.dc_blocker_ff(32, True)
dst = gr.vector_sink_f()
self.tb.connect(src, op, dst)
self.tb.run()
# only test samples around 2D-2
result_data = dst.data()[60:65]
self.assertFloatTuplesAlmostEqual(expected_result, result_data)
def test_001(self):
src_data = 200 * [
0,
] + 200 * [
0.5,
] + 200 * [
1,
]
expected_result = 200*[1,] + \
sig_source_f(1, 0.125, 1, 200) + \
sig_source_f(1, 0.25, 1, 200)
src = gr.vector_source_f(src_data)
op = blocks_swig.vco_f(1, math.pi / 2.0, 1)
dst = gr.vector_sink_f()
self.tb.connect(src, op, dst)
self.tb.run()
result_data = dst.data()
self.assertFloatTuplesAlmostEqual(expected_result, result_data, 5)
def test_deint_001(self):
lenx = 63
src0 = gr.vector_source_f(range(lenx))
op = gr.deinterleave(gr.sizeof_float, 3)
dst0 = gr.vector_sink_f()
dst1 = gr.vector_sink_f()
dst2 = gr.vector_sink_f()
self.tb.connect(src0, op)
op.connect(dst0, usesPortName="float_out_1")
op.connect(dst1, usesPortName="float_out_2")
op.connect(dst2, usesPortName="float_out_3")
self.tb.run()
expected_result0 = tuple(range(0, lenx, 3))
expected_result1 = tuple(range(1, lenx, 3))
expected_result2 = tuple(range(2, lenx, 3))
self.assertFloatTuplesAlmostEqual(expected_result0, dst0.data())
self.assertFloatTuplesAlmostEqual(expected_result1, dst1.data())
self.assertFloatTuplesAlmostEqual(expected_result2, dst2.data())
def test_001_t(self):
src_data = (0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1)
expected_result = (-2.0, 0.0, 5.0, 8.0, 9.0, 11.0, 14.0, 18.0)
src0 = gr.vector_source_f(src_data)
sqr = square3_ff()
#Preload
sqr.input_config(1).preload_items = 1
dst = gr.vector_sink_f()
self.tb.connect(src0, (sqr, 0)) # src0(vector_source) -> sqr_input_0
#self.tb.connect((sqr,0), (sqr,1)) # sqr_output_0 -> sqr_input_1
self.tb.connect(sqr, dst) # sqr_output_0 -> dst (vector_source)
self.tb.run()
result_data = dst.data()
print str(result_data), "Result data"
print str(expected_result), "expected "
def test_003_f_1(self):
#Test streams_to_vector (using stream_to_streams & vector_to_stream).
n = 1
src_len = n * 8
src_data = tuple(range(src_len))
expected_results = src_data
src = gr.vector_source_f(src_data)
op1 = gr.stream_to_streams_comp(gr.sizeof_float, n)
op2 = gr.streams_to_vector_comp(gr.sizeof_float, n)
op3 = gr.vector_to_stream_comp(gr.sizeof_float, n)
dst = gr.vector_sink_f()
self.tb.connect(src, op1)
for i in range(n):
self.tb.connect((op1, i), (op2, i))
self.tb.connect(op2, op3, dst)
self.tb.run()
self.assertEqual(expected_results, dst.data())
def test_001_t (self):
src0 = numpy.arange(0,3.1416,1)
src0 = gr.vector_source_f(src0)
expected_result = (0.0, 0.8414709568023682, 0.9092974066734314, 0.14112000167369843)
sqr = generic()
sqr.set_parameters("sin",1)
dst = gr.vector_sink_f()
self.tb.connect(src0, (sqr,0)) # src0(vector_source) -> sqr_input_0
self.tb.connect(sqr,dst) # sqr_output_0 -> dst (vector_source)
self.tb.run()
result_data = dst.data()
print result_data, "Result data"
self.assertFloatTuplesAlmostEqual(expected_result, result_data, 6)
def run_test (fo,fi,interleaver,Kb,bitspersymbol,K,dimensionality,constellation,N0,seed):
tb = gr.top_block ()
# TX
src = gr.lfsr_32k_source_s()
src_head = gr.head (gr.sizeof_short,Kb/16) # packet size in shorts
s2fsmi = gr.packed_to_unpacked_ss(bitspersymbol,gr.GR_MSB_FIRST) # unpack shorts to symbols compatible with the outer FSM input cardinality
enc_out = trellis.encoder_ss(fo,0) # initial state = 0
inter = trellis.permutation(interleaver.K(),interleaver.INTER(),1,gr.sizeof_short)
enc_in = trellis.encoder_ss(fi,0) # initial state = 0
mod = gr.chunks_to_symbols_sf(constellation,dimensionality)
# CHANNEL
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN,math.sqrt(N0/2),seed)
# RX
metrics_in = trellis.metrics_f(fi.O(),dimensionality,constellation,trellis.TRELLIS_EUCLIDEAN) # data preprocessing to generate metrics for innner Viterbi
gnd = gr.vector_source_f([0],True);
siso_in = trellis.siso_f(fi,K,0,-1,True,False,trellis.TRELLIS_MIN_SUM) # Put -1 if the Initial/Final states are not set.
deinter = trellis.permutation(interleaver.K(),interleaver.DEINTER(),fi.I(),gr.sizeof_float)
va_out = trellis.viterbi_s(fo,K,0,-1) # Put -1 if the Initial/Final states are not set.
fsmi2s = gr.unpacked_to_packed_ss(bitspersymbol,gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s()
tb.connect (src,src_head,s2fsmi,enc_out,inter,enc_in,mod)
tb.connect (mod,(add,0))
tb.connect (noise,(add,1))
tb.connect (add,metrics_in)
tb.connect (gnd,(siso_in,0))
tb.connect (metrics_in,(siso_in,1))
tb.connect (siso_in,deinter,va_out,fsmi2s,dst)
tb.run()
ntotal = dst.ntotal ()
nright = dst.nright ()
runlength = dst.runlength ()
return (ntotal,ntotal-nright)
def test_003(self):
scale = 2
vlen = 3
# Pad source data becasue of gr_sptr->output_multiple
src_data = (0.0, 1.1, 2.2,0,0,0,0,0,0,0,0,0,0,0,0,0, \
3.3, 4.4, 5.5,0,0,0,0,0,0,0,0,0,0,0,0,0, \
-1.1, -2.2, -3.30,0,0,0,0,0,0,0,0,0,0,0,0,0)
expected_result = [0, 2, 4,0,0,0,0,0,0,0,0,0,0,0,0,0, \
7, 9, 11,0,0,0,0,0,0,0,0,0,0,0,0,0,\
-2, -4, -7,0,0,0,0,0,0,0,0,0,0,0,0,0]
src = gr.vector_source_f(src_data)
s2v = gr.stream_to_vector(gr.sizeof_float, vlen)
op = gr.float_to_short(vlen, scale)
v2s = gr.vector_to_stream(gr.sizeof_short, vlen)
dst = gr.vector_sink_s()
self.tb.connect(src, s2v, op, v2s, dst)
self.tb.run()
result_data = list(dst.data())
self.assertEqual(expected_result, result_data)
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_001_interp(self):
taps = [1, 10, 100, 1000, 10000]
src_data = (0, 2, 3, 5, 7, 11, 13, 17)
interpolation = 3
xr = (0,2,20,200,2003,20030,
300,3005,30050,
500,5007,50070,
700,7011,70110,
1100,11013,110130,
1300,13017,130170,
1700.0,17000.0,170000.0)
expected_result = tuple([float(x) for x in xr])
tb = gr.top_block()
src = gr.vector_source_f(src_data)
op = filter.rational_resampler_base_fff(interpolation, 1, taps)
dst = gr.vector_sink_f()
tb.connect(src, op)
tb.connect(op, dst)
tb.run()
result_data = dst.data()
self.assertEqual(expected_result, result_data)
def __init__(self): grc_wxgui.top_block_gui.__init__(self, title="Corr Test Gui") _icon_path = "/usr/share/icons/hicolor/32x32/apps/gnuradio-grc.png" self.SetIcon(wx.Icon(_icon_path, wx.BITMAP_TYPE_ANY)) ################################################## # Variables ################################################## self.samp_rate = samp_rate = 32000 ################################################## # Blocks ################################################## self.wxgui_scopesink2_0 = scopesink2.scope_sink_f( self.GetWin(), title="Scope Plot", sample_rate=samp_rate, v_scale=0, v_offset=0, t_scale=0, ac_couple=False, xy_mode=False, num_inputs=2, trig_mode=gr.gr_TRIG_MODE_AUTO, y_axis_label="Counts", ) self.Add(self.wxgui_scopesink2_0.win) self.gr_vector_source_x_0 = gr.vector_source_f((concatenate((ones(10),zeros(200)),1)), True, 1) self.gr_throttle_0 = gr.throttle(gr.sizeof_float*1, samp_rate) self.fir_filter_xxx_0 = filter.fir_filter_fff(1, (ones(10))) ################################################## # Connections ################################################## self.connect((self.gr_vector_source_x_0, 0), (self.gr_throttle_0, 0)) self.connect((self.gr_throttle_0, 0), (self.fir_filter_xxx_0, 0)) self.connect((self.fir_filter_xxx_0, 0), (self.wxgui_scopesink2_0, 0)) self.connect((self.gr_throttle_0, 0), (self.wxgui_scopesink2_0, 1))
def test_001_t (self):
""" Simplest possible test: put in zeros, then header,
then payload, trigger signal, try to demux.
The return signal from the header parser is faked via _post()
"""
n_zeros = 100
header = (1, 2, 3)
payload = tuple(range(17))
data_signal = (0,) * n_zeros + header + payload
trigger_signal = [0,] * len(data_signal)
trigger_signal[n_zeros] = 1
data_src = gr.vector_source_f(data_signal, False)
trigger_src = gr.vector_source_b(trigger_signal, False)
hpd = digital.header_payload_demux(
len(header), 1, 0, "frame_len", "detect", False, gr.sizeof_float
)
self.assertEqual(pmt.pmt_length(hpd.message_ports_in()), 1)
header_sink = gr.vector_sink_f()
payload_sink = gr.vector_sink_f()
self.tb.connect(data_src, (hpd, 0))
self.tb.connect(trigger_src, (hpd, 1))
self.tb.connect((hpd, 0), header_sink)
self.tb.connect((hpd, 1), payload_sink)
self.tb.start()
time.sleep(.2) # Need this, otherwise, the next message is ignored
hpd.to_basic_block()._post(
pmt.pmt_intern('header_data'),
pmt.pmt_from_long(len(payload))
)
while len(payload_sink.data()) < len(payload):
time.sleep(.2)
self.tb.stop()
self.tb.wait()
self.assertEqual(header_sink.data(), header)
self.assertEqual(payload_sink.data(), payload)
def make_rx(tb,fo,fi,dimensionality,tot_constellation,K,interleaver,IT,Es,N0,type):
metrics_in = trellis.metrics_f(fi.O(),dimensionality,tot_constellation,digital.TRELLIS_EUCLIDEAN) # data preprocessing to generate metrics for innner SISO
scale = gr.multiply_const_ff(1.0/N0)
gnd = gr.vector_source_f([0],True);
inter=[]
deinter=[]
siso_in=[]
siso_out=[]
# generate all blocks
for it in range(IT):
inter.append( trellis.permutation(interleaver.K(),interleaver.INTER(),fi.I(),gr.sizeof_float) )
siso_in.append( trellis.siso_f(fi,K,0,-1,True,False,type) )
deinter.append( trellis.permutation(interleaver.K(),interleaver.DEINTER(),fi.I(),gr.sizeof_float) )
if it < IT-1:
siso_out.append( trellis.siso_f(fo,K,0,-1,False,True,type) )
else:
siso_out.append( trellis.viterbi_s(fo,K,0,-1) ) # no soft outputs needed
# connect first stage
tb.connect (gnd,inter[0])
tb.connect (metrics_in,scale)
tb.connect (scale,(siso_in[0],1))
# connect the rest
for it in range(IT):
if it < IT-1:
tb.connect (metrics_in,(siso_in[it+1],1))
tb.connect (siso_in[it],deinter[it],(siso_out[it],1))
tb.connect (gnd,(siso_out[it],0))
tb.connect (siso_out[it],inter[it+1])
tb.connect (inter[it],(siso_in[it],0))
else:
tb.connect (siso_in[it],deinter[it],siso_out[it])
tb.connect (inter[it],(siso_in[it],0))
return (metrics_in,siso_out[IT-1])
def test_001(self):
src_data = range(1000)
expected_result = range(1000)
filename = "tmp.32f"
src = gr.vector_source_f(src_data)
snk = blocks.file_sink(gr.sizeof_float, filename)
snk.set_unbuffered(True)
src2 = blocks.file_source(gr.sizeof_float, filename)
snk2 = gr.vector_sink_f()
self.tb.connect(src, snk)
self.tb.run()
self.tb.disconnect(src, snk)
self.tb.connect(src2, snk2)
self.tb.run()
os.remove(filename)
result_data = snk2.data()
self.assertFloatTuplesAlmostEqual(expected_result, result_data)
def test_001_f(self):
#Test stream_to_streams.
n = 4
src_len = n * 8
src_data = range(src_len)
expected_results = calc_expected_result(src_data, n)
src = gr.vector_source_f(src_data)
op = gr.stream_to_streams_comp(gr.sizeof_float, n)
self.tb.connect(src, op)
dsts = []
for i in range(n):
dst = gr.vector_sink_f()
self.tb.connect((op, i), (dst, 0))
dsts.append(dst)
self.tb.run()
for d in range(n):
self.assertEqual(expected_results[d], dsts[d].data())
def test_001_codeallr2m3(self):
""" Check Golay-SD-decoding m=3 for all possible inputs """
src_data = (0.648, 0.680, 0.636, 0.946, 0.209, 0.710, 0.237, 0.120,
0.608, 0.451, 0.459, 0.662, 0.771, 0.351, 0.663, 0.417,
0.842, 0.833, 0.257, 0.614, 0.583, 0.541, 0.870, 0.265,
0.319, 0.120, 0.940, 0.646, 0.480, 0.640, 0.545, 0.648,
0.544, 0.722, 0.523, 0.994, 0.219, 0.106, 0.110, 0.064)
expected_data = (6, 0, 14, 1, 22)
src1 = gr.vector_source_f(src_data, 0, 8)
coding_action = chancoding.rmg_decoder_sd_vfi(3, 1)
sink = gr.vector_sink_i()
self.tb.connect(src1, coding_action)
self.tb.connect(coding_action, sink)
self.tb.run()
self.assertEqual(coding_action.get_vlen_in(), 8)
self.assertEqual(coding_action.get_vlen_out(), 1)
self.assertEqual(coding_action.get_num_bits_out(), 5)
for i in range(len(expected_data)):
self.assertEqual(sink.data()[i], expected_data[i], i)
