def test_006(self):
''' Test the complex AGC loop (attack and decay rate inputs) '''
tb = self.tb
sampling_freq = 100
N = int(5 * sampling_freq)
src1 = analog.sig_source_c(sampling_freq, analog.GR_SIN_WAVE,
sampling_freq * 0.10, 100)
dst1 = blocks.vector_sink_c()
head = blocks.head(gr.sizeof_gr_complex, N)
ref = 1
agc = analog.agc3_cc(1e-2, 1e-3, ref)
tb.connect(src1, head)
tb.connect(head, agc)
tb.connect(agc, dst1)
tb.run()
dst_data = dst1.data()
M = 100
result = map(lambda x: abs(x), dst_data[N - M:])
self.assertFloatTuplesAlmostEqual(result, M * [
ref,
], 4)
def test_000(self):
N = 1000 # number of samples to use
fs = 1000 # baseband sampling rate
freq = 100
signal = analog.sig_source_c(fs, analog.GR_SIN_WAVE, freq, 1)
head = blocks.head(gr.sizeof_gr_complex, N)
op = channels.channel_model(0.0, 0.0, 1.0, [
1,
], 0)
snk = blocks.vector_sink_c()
snk1 = blocks.vector_sink_c()
op.set_noise_voltage(0.0)
op.set_frequency_offset(0.0)
op.set_taps([
1,
])
op.set_timing_offset(1.0)
self.tb.connect(signal, head, op, snk)
self.tb.connect(op, snk1)
self.tb.run()
dst_data = snk.data()
exp_data = snk1.data()
self.assertComplexTuplesAlmostEqual(exp_data, dst_data, 5)
def test_sqr_c(self):
tb = self.tb #arg6 is a bit before -PI/2
expected_result = (1j, 1j, 0, 0, 1, 1, 1+0j, 1+1j, 1j)
src1 = analog.sig_source_c(8, analog.GR_SQR_WAVE, 1.0, 1.0)
op = blocks.head(gr.sizeof_gr_complex, 9)
dst1 = blocks.vector_sink_c()
tb.connect(src1, op)
tb.connect(op, dst1)
tb.run()
dst_data = dst1.data()
self.assertEqual(expected_result, dst_data)
def test_saw_c(self):
tb = self.tb
expected_result = (.5+.25j, .625+.375j, .75+.5j, .875+.625j,
0+.75j, .125+.875j, .25+1j, .375+.125j, .5+.25j)
src1 = analog.sig_source_c(8, analog.GR_SAW_WAVE, 1.0, 1.0)
op = gr.head(gr.sizeof_gr_complex, 9)
dst1 = gr.vector_sink_c()
tb.connect(src1, op)
tb.connect(op, dst1)
tb.run()
dst_data = dst1.data()
self.assertComplexTuplesAlmostEqual(expected_result, dst_data, 5)
def test_tri_c(self):
tb = self.tb
expected_result = (1+.5j, .75+.75j, .5+1j, .25+.75j, 0+.5j,
.25+.25j, .5+0j, .75+.25j, 1+.5j)
src1 = analog.sig_source_c(8, analog.GR_TRI_WAVE, 1.0, 1.0)
op = blocks.head(gr.sizeof_gr_complex, 9)
dst1 = blocks.vector_sink_c()
tb.connect(src1, op)
tb.connect(op, dst1)
tb.run()
dst_data = dst1.data()
self.assertComplexTuplesAlmostEqual(expected_result, dst_data, 5)
def test_saw_c(self):
tb = self.tb
expected_result = (.5 + .25j, .625 + .375j, .75 + .5j, .875 + .625j,
0 + .75j, .125 + .875j, .25 + 1j, .375 + .125j,
.5 + .25j)
src1 = analog.sig_source_c(8, analog.GR_SAW_WAVE, 1.0, 1.0)
op = gr.head(gr.sizeof_gr_complex, 9)
dst1 = gr.vector_sink_c()
tb.connect(src1, op)
tb.connect(op, dst1)
tb.run()
dst_data = dst1.data()
self.assertComplexTuplesAlmostEqual(expected_result, dst_data, 5)
def test_004_connect (self):
"""
Advanced test:
- Allocator -> IFFT -> Frequency offset -> FFT -> Serializer
- FFT does shift (moves DC to middle)
- Make sure input == output
- Frequency offset is -2 carriers
"""
fft_len = 8
n_syms = 1
carr_offset = -2
freq_offset = 1.0 / fft_len * carr_offset # Normalized frequency
occupied_carriers = ((-2, -1, 1, 2),)
pilot_carriers = ((-3,),(3,))
pilot_symbols = ((1j,),(-1j,))
tx_data = (1, 2, 3, 4)
tag_name = "len"
tag = gr.tag_t()
tag.offset = 0
tag.key = pmt.string_to_symbol(tag_name)
tag.value = pmt.from_long(len(tx_data))
offsettag = gr.tag_t()
offsettag.offset = 0
offsettag.key = pmt.string_to_symbol("ofdm_sync_carr_offset")
offsettag.value = pmt.from_long(carr_offset)
src = blocks.vector_source_c(tx_data, False, 1, (tag, offsettag))
alloc = digital.ofdm_carrier_allocator_cvc(fft_len,
occupied_carriers,
pilot_carriers,
pilot_symbols, (),
tag_name)
tx_ifft = fft.fft_vcc(fft_len, False, (1.0/fft_len,)*fft_len, True)
oscillator = analog.sig_source_c(1.0, analog.GR_COS_WAVE, freq_offset, 1.0/fft_len)
mixer = blocks.multiply_cc()
rx_fft = fft.fft_vcc(fft_len, True, (), True)
sink2 = blocks.vector_sink_c(fft_len)
self.tb.connect(rx_fft, sink2)
serializer = digital.ofdm_serializer_vcc(
alloc, "", 0, "ofdm_sync_carr_offset", True
)
sink = blocks.vector_sink_c()
self.tb.connect(
src, alloc, tx_ifft,
blocks.vector_to_stream(gr.sizeof_gr_complex, fft_len),
(mixer, 0),
blocks.stream_to_vector(gr.sizeof_gr_complex, fft_len),
rx_fft, serializer, sink
)
self.tb.connect(oscillator, (mixer, 1))
self.tb.run ()
self.assertComplexTuplesAlmostEqual(sink.data()[-len(occupied_carriers[0]):], tx_data, places=4)
def est_fmdet_cf_002(self):
N = 100
src = analog.sig_source_c(1, analog.GR_SIN_WAVE, 0.2, 1)
head = blocks.head(gr.sizeof_gr_complex, N)
op = analog.fmdet_cf(1, 0.1, 0.3, 0.1)
dst = blocks.vector_sink_f()
self.tb.connect(src, head, op)
self.tb.connect(op, dst)
self.tb.run()
result_data = dst.data()[4:N]
expected_result = (100-4)*[-0.21755,]
self.assertFloatTuplesAlmostEqual(expected_result, result_data, 4)
def test01(self):
sps = 4
rolloff = 0.35
bw = 2 * math.pi / 100.0
ntaps = 45
# Create pulse shape filter
rrc_taps = filter.firdes.root_raised_cosine(sps, sps, 1.0, rolloff,
ntaps)
# The frequency offset to correct
foffset = 0.2 / (2.0 * math.pi)
# Create a set of 1's and -1's, pulse shape and interpolate to sps
random.seed(0)
data = [2.0 * random.randint(0, 2) - 1.0 for i in xrange(200)]
self.src = blocks.vector_source_c(data, False)
self.rrc = filter.interp_fir_filter_ccf(sps, rrc_taps)
# Mix symbols with a complex sinusoid to spin them
self.nco = analog.sig_source_c(1, analog.GR_SIN_WAVE, foffset, 1)
self.mix = blocks.multiply_cc()
# FLL will despin the symbols to an arbitrary phase
self.fll = digital.fll_band_edge_cc(sps, rolloff, ntaps, bw)
# Create sinks for all outputs of the FLL
# we will only care about the freq and error outputs
self.vsnk_frq = blocks.vector_sink_f()
self.nsnk_fll = blocks.null_sink(gr.sizeof_gr_complex)
self.nsnk_phs = blocks.null_sink(gr.sizeof_float)
self.nsnk_err = blocks.null_sink(gr.sizeof_float)
# Connect the blocks
self.tb.connect(self.nco, (self.mix, 1))
self.tb.connect(self.src, self.rrc, (self.mix, 0))
self.tb.connect(self.mix, self.fll, self.nsnk_fll)
self.tb.connect((self.fll, 1), self.vsnk_frq)
self.tb.connect((self.fll, 2), self.nsnk_phs)
self.tb.connect((self.fll, 3), self.nsnk_err)
self.tb.run()
N = 700
dst_data = self.vsnk_frq.data()[N:]
expected_result = len(dst_data) * [
-0.20,
]
self.assertFloatTuplesAlmostEqual(expected_result, dst_data, 4)
def test_000(self):
N = 1000 # number of samples to use
fs = 1000 # baseband sampling rate
freq = 100
fDTs = 0.01
K = 4
signal = analog.sig_source_c(fs, analog.GR_SIN_WAVE, freq, 1)
head = blocks.head(gr.sizeof_gr_complex, N)
op = channels.fading_model(8, fDTs=fDTs, LOS=True, K=K, seed=0)
snk = blocks.vector_sink_c()
snk1 = blocks.vector_sink_c()
self.assertAlmostEqual(K, op.K(), 4)
self.assertAlmostEqual(fDTs, op.fDTs(), 4)
def test_000(self):
N = 1000 # number of samples to use
fs = 1000 # baseband sampling rate
freq = 100
fDTs = 0.01
K = 4
signal = analog.sig_source_c(fs, analog.GR_SIN_WAVE, freq, 1)
head = blocks.head(gr.sizeof_gr_complex, N)
op = channels.fading_model(8, fDTs=fDTs, LOS=True,
K=K, seed=0)
snk = blocks.vector_sink_c()
snk1 = blocks.vector_sink_c()
self.assertAlmostEqual(K, op.K(), 4)
self.assertAlmostEqual(fDTs, op.fDTs(), 4)
def test01(self):
sps = 4
rolloff = 0.35
bw = 2 * math.pi / 100.0
ntaps = 45
# Create pulse shape filter
rrc_taps = filter.firdes.root_raised_cosine(sps, sps, 1.0, rolloff, ntaps)
# The frequency offset to correct
foffset = 0.2 / (2.0 * math.pi)
# Create a set of 1's and -1's, pulse shape and interpolate to sps
random.seed(0)
data = [2.0 * random.randint(0, 2) - 1.0 for i in xrange(200)]
self.src = blocks.vector_source_c(data, False)
self.rrc = filter.interp_fir_filter_ccf(sps, rrc_taps)
# Mix symbols with a complex sinusoid to spin them
self.nco = analog.sig_source_c(1, analog.GR_SIN_WAVE, foffset, 1)
self.mix = blocks.multiply_cc()
# FLL will despin the symbols to an arbitrary phase
self.fll = digital.fll_band_edge_cc(sps, rolloff, ntaps, bw)
# Create sinks for all outputs of the FLL
# we will only care about the freq and error outputs
self.vsnk_frq = blocks.vector_sink_f()
self.nsnk_fll = blocks.null_sink(gr.sizeof_gr_complex)
self.nsnk_phs = blocks.null_sink(gr.sizeof_float)
self.nsnk_err = blocks.null_sink(gr.sizeof_float)
# Connect the blocks
self.tb.connect(self.nco, (self.mix, 1))
self.tb.connect(self.src, self.rrc, (self.mix, 0))
self.tb.connect(self.mix, self.fll, self.nsnk_fll)
self.tb.connect((self.fll, 1), self.vsnk_frq)
self.tb.connect((self.fll, 2), self.nsnk_phs)
self.tb.connect((self.fll, 3), self.nsnk_err)
self.tb.run()
N = 700
dst_data = self.vsnk_frq.data()[N:]
expected_result = len(dst_data) * [-0.20]
self.assertFloatTuplesAlmostEqual(expected_result, dst_data, 4)
def __init__(self, noise_voltage, freq, timing):
gr.hier_block2.__init__(self, "channel_model",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_gr_complex))
timing_offset = filter.fractional_resampler_cc(0, timing)
noise_adder = blocks.add_cc()
noise = analog.noise_source_c(analog.GR_GAUSSIAN, noise_voltage, 0)
freq_offset = analog.sig_source_c(1, analog.GR_SIN_WAVE, freq, 1.0,
0.0)
mixer_offset = blocks.multiply_cc()
self.connect(self, timing_offset)
self.connect(timing_offset, (mixer_offset, 0))
self.connect(freq_offset, (mixer_offset, 1))
self.connect(mixer_offset, (noise_adder, 1))
self.connect(noise, (noise_adder, 0))
self.connect(noise_adder, self)
def __init__(self, noise_voltage, freq, timing):
gr.hier_block2.__init__(
self,
"channel_model",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_gr_complex),
)
timing_offset = filter.fractional_interpolator_cc(0, timing)
noise_adder = blocks.add_cc()
noise = analog.noise_source_c(analog.GR_GAUSSIAN, noise_voltage, 0)
freq_offset = analog.sig_source_c(1, analog.GR_SIN_WAVE, freq, 1.0, 0.0)
mixer_offset = blocks.multiply_cc()
self.connect(self, timing_offset)
self.connect(timing_offset, (mixer_offset, 0))
self.connect(freq_offset, (mixer_offset, 1))
self.connect(mixer_offset, (noise_adder, 1))
self.connect(noise, (noise_adder, 0))
self.connect(noise_adder, self)
def test_000(self):
N = 1000 # number of samples to use
fs = 1000 # baseband sampling rate
freq = 100
signal = analog.sig_source_c(fs, analog.GR_SIN_WAVE, freq, 1)
head = blocks.head(gr.sizeof_gr_complex, N)
op = channels.channel_model(0.0, 0.0, 1.0, [1,], 0)
snk = blocks.vector_sink_c()
snk1 = blocks.vector_sink_c()
op.set_noise_voltage(0.0)
op.set_frequency_offset(0.0)
op.set_taps([1,])
op.set_timing_offset(1.0)
self.tb.connect(signal, head, op, snk)
self.tb.connect(op, snk1)
self.tb.run()
dst_data = snk.data()
exp_data = snk1.data()
self.assertComplexTuplesAlmostEqual(exp_data, dst_data, 5)
def test_006(self):
''' Test the complex AGC loop (attack and decay rate inputs) '''
tb = self.tb
sampling_freq = 100
N = int(5*sampling_freq)
src1 = analog.sig_source_c(sampling_freq, analog.GR_SIN_WAVE,
sampling_freq * 0.10, 100)
dst1 = blocks.vector_sink_c()
head = blocks.head(gr.sizeof_gr_complex, N)
ref = 1
agc = analog.agc3_cc(1e-2, 1e-3, ref)
tb.connect(src1, head)
tb.connect(head, agc)
tb.connect(agc, dst1)
tb.run()
dst_data = dst1.data()
M = 100
result = map(lambda x: abs(x), dst_data[N-M:])
self.assertFloatTuplesAlmostEqual(result, M*[ref,], 4)
def test_005(self):
''' Test the complex AGC loop (attack and decay rate inputs) '''
tb = self.tb
expected_result = \
((100.000244140625+7.2191943445432116e-07j),
(0.80881959199905396+0.58764183521270752j),
(0.30894950032234192+0.95084899663925171j),
(-0.30895623564720154+0.95086973905563354j),
(-0.80887287855148315+0.58768033981323242j),
(-0.99984413385391235+5.850709250410091e-09j),
(-0.80889981985092163-0.58770018815994263j),
(-0.30897706747055054-0.95093393325805664j),
(0.30898112058639526-0.95094609260559082j),
(0.80893135070800781-0.58772283792495728j),
(0.99990922212600708-8.7766354184282136e-09j),
(0.80894720554351807+0.58773452043533325j),
(0.30899339914321899+0.95098406076431274j),
(-0.30899572372436523+0.95099133253097534j),
(-0.80896598100662231+0.58774799108505249j),
(-0.99994778633117676+1.4628290578855285e-08j),
(-0.80897533893585205-0.58775502443313599j),
(-0.30900305509567261-0.95101380348205566j),
(0.30900448560714722-0.95101797580718994j),
(0.80898630619049072-0.58776277303695679j),
(0.99997037649154663-1.7554345532744264e-08j),
(0.80899184942245483+0.58776694536209106j),
(0.30900871753692627+0.95103120803833008j),
(-0.30900952219963074+0.95103377103805542j),
(-0.8089984655380249+0.58777159452438354j),
(-0.99998390674591064+2.3406109050938539e-08j),
(-0.809001624584198-0.58777409791946411j),
(-0.30901208519935608-0.95104163885116577j),
(0.30901262164115906-0.95104306936264038j),
(0.80900543928146362-0.587776780128479j),
(0.99999171495437622-2.6332081404234486e-08j),
(0.80900734663009644+0.58777821063995361j),
(0.30901408195495605+0.95104765892028809j),
(-0.30901429057121277+0.95104855298995972j),
(-0.80900967121124268+0.58777981996536255j),
(-0.99999648332595825+3.2183805842578295e-08j),
(-0.80901080369949341-0.58778077363967896j),
(-0.30901527404785156-0.95105135440826416j),
(0.30901545286178589-0.95105189085006714j),
(0.80901217460632324-0.58778166770935059j),
(0.99999916553497314-3.5109700036173308e-08j),
(0.809012770652771+0.58778214454650879j),
(0.30901595950126648+0.9510534405708313j),
(-0.30901598930358887+0.95105385780334473j),
(-0.80901366472244263+0.58778274059295654j),
(-1.0000008344650269+4.0961388947380328e-08j),
(-0.8090139627456665-0.58778303861618042j),
(-0.30901634693145752-0.95105475187301636j),
(0.30901640653610229-0.95105493068695068j),
(0.80901449918746948-0.5877833366394043j))
sampling_freq = 100
src1 = analog.sig_source_c(sampling_freq, analog.GR_SIN_WAVE,
sampling_freq * 0.10, 100)
dst1 = blocks.vector_sink_c()
head = blocks.head(gr.sizeof_gr_complex, int(5 * sampling_freq * 0.10))
agc = analog.agc2_cc(1e-2, 1e-3, 1, 1)
tb.connect(src1, head)
tb.connect(head, agc)
tb.connect(agc, dst1)
tb.run()
dst_data = dst1.data()
self.assertComplexTuplesAlmostEqual(expected_result, dst_data, 4)
def test_001(self):
''' Test the complex AGC loop (single rate input) '''
tb = self.tb
expected_result = (
(100.000244140625 + 7.2191943445432116e-07j),
(72.892257690429688 + 52.959323883056641j), (25.089065551757812 +
77.216217041015625j),
(-22.611061096191406 + 69.589706420898438j), (-53.357715606689453 +
38.766635894775391j),
(-59.458671569824219 + 3.4792964243024471e-07j),
(-43.373462677001953 - 31.512666702270508j), (-14.94139289855957 -
45.984889984130859j),
(13.478158950805664 - 41.48150634765625j), (31.838506698608398 -
23.132022857666016j),
(35.519271850585938 - 3.1176801940091536e-07j),
(25.942903518676758 + 18.848621368408203j), (8.9492912292480469 +
27.5430908203125j),
(-8.0852642059326172 + 24.883890151977539j), (-19.131628036499023 +
13.899936676025391j),
(-21.383295059204102 + 3.1281737733479531e-07j),
(-15.650330543518066 - 11.370632171630859j), (-5.4110145568847656 -
16.65339469909668j),
(4.9008159637451172 - 15.083160400390625j), (11.628337860107422 -
8.4484796524047852j),
(13.036135673522949 - 2.288476110834381e-07j),
(9.5726661682128906 + 6.954948902130127j), (3.3216962814331055 +
10.223132133483887j),
(-3.0204284191131592 + 9.2959251403808594j), (-7.1977195739746094 +
5.2294478416442871j),
(-8.1072216033935547 + 1.8976157889483147e-07j),
(-5.9838657379150391 - 4.3475332260131836j), (-2.0879747867584229 -
6.4261269569396973j),
(1.9100792407989502 - 5.8786196708679199j), (4.5814824104309082 -
3.3286411762237549j),
(5.1967458724975586 - 1.3684227440080576e-07j),
(3.8647139072418213 + 2.8078789710998535j), (1.3594740629196167 +
4.1840314865112305j),
(-1.2544282674789429 + 3.8607344627380371j), (-3.0366206169128418 +
2.2062335014343262j),
(-3.4781389236450195 + 1.1194014604143376e-07j),
(-2.6133756637573242 - 1.8987287282943726j), (-0.9293016791343689 -
2.8600969314575195j),
(0.86727333068847656 - 2.6691930294036865j), (2.1243946552276611 -
1.5434627532958984j),
(2.4633183479309082 - 8.6486437567145913e-08j),
(1.8744727373123169 + 1.3618841171264648j), (0.67528903484344482 +
2.0783262252807617j),
(-0.63866174221038818 + 1.965599536895752j), (-1.5857341289520264 +
1.152103066444397j),
(-1.8640764951705933 +
7.6355092915036948e-08j), (-1.4381576776504517 -
1.0448826551437378j),
(-0.52529704570770264 -
1.6166983842849731j), (0.50366902351379395 - 1.5501341819763184j),
(1.26766037940979 - 0.92100900411605835j))
sampling_freq = 100
src1 = analog.sig_source_c(sampling_freq, analog.GR_SIN_WAVE,
sampling_freq * 0.10, 100.0)
dst1 = blocks.vector_sink_c()
head = blocks.head(gr.sizeof_gr_complex, int(5 * sampling_freq * 0.10))
agc = analog.agc_cc(1e-3, 1, 1)
tb.connect(src1, head)
tb.connect(head, agc)
tb.connect(agc, dst1)
tb.run()
dst_data = dst1.data()
self.assertComplexTuplesAlmostEqual(expected_result, dst_data, 4)
def test_pll_freqdet(self):
expected_result = (0.0,
4.33888922882e-08,
0.367369994515,
1.08135249597,
2.10983253908,
3.42221529438,
4.98940390402,
6.78379190842,
8.77923286024,
10.9510106794,
13.2758363182,
15.7317829127,
18.2982902299,
20.9561068599,
23.6755271122,
26.452952094,
29.2731265301,
32.1219053479,
34.9862418188,
37.8540971414,
40.7144315483,
43.5571390869,
46.3730179743,
49.1537231663,
51.8917218889,
54.58026103,
57.2015358514,
59.7513664199,
62.2380533124,
64.657612252,
67.006640002,
69.2822432184,
71.4820384499,
73.6041047056,
75.6469478817,
77.6094829742,
79.4909866472,
81.2911031615,
83.0097850853,
84.6355598352,
86.1820937186,
87.6504420946,
89.0418441206,
90.3577286819,
91.5996432431,
92.7692775646,
93.8684162704,
94.8989269904,
95.8627662892,
96.7619381633,
97.598505899,
98.362769679,
99.0579904444,
99.6992633875,
100.288805948,
100.828805921,
101.321421457,
101.76878699,
102.17300138,
102.536116055,
102.860158727,
103.147085962,
103.398830608,
103.617254366,
103.792467691,
103.939387906,
104.060030865,
104.15631756,
104.230085975,
104.283067372,
104.316933727,
104.333238432,
104.333440018,
104.318914008,
104.290941063,
104.250742554,
104.187634452,
104.103822339,
104.013227468,
103.916810336,
103.815448432,
103.709936239,
103.600997093,
103.489283183,
103.375351833,
103.259712936,
103.142828952,
103.025091195,
102.90686726,
102.776726069,
102.648078982,
102.521459607,
102.397294831,
102.275999684,
102.157882471,
102.043215927,
101.93218978,
101.824958181,
101.72159228,
101.622151366)
sampling_freq = 10e3
freq = sampling_freq / 100
loop_bw = math.pi/100.0
maxf = 1
minf = -1
src = analog.sig_source_c(sampling_freq, analog.GR_COS_WAVE, freq, 1.0)
pll = analog.pll_freqdet_cf(loop_bw, maxf, minf)
head = blocks.head(gr.sizeof_float, int (freq))
dst = blocks.vector_sink_f()
self.tb.connect(src, pll, head)
self.tb.connect(head, dst)
self.tb.run()
dst_data = dst.data()
# convert it from normalized frequency to absolute frequency (Hz)
dst_data = [i*(sampling_freq/(2*math.pi)) for i in dst_data]
self.assertFloatTuplesAlmostEqual(expected_result, dst_data, 3)
def test_pll_refout(self):
expected_result = ((1+0j),
(1+6.4087357643e-10j),
(0.999985277653+0.00542619498447j),
(0.999868750572+0.0162021834403j),
(0.99948567152+0.0320679470897j),
(0.99860727787+0.0527590736747j),
(0.996953129768+0.0780025869608j),
(0.994203746319+0.107512556016j),
(0.990011692047+0.140985429287j),
(0.984013140202+0.178095817566j),
(0.975838363171+0.218493551016j),
(0.965121984482+0.261800557375j),
(0.95151245594+0.307610183954j),
(0.934681296349+0.355486690998j),
(0.914401650429+0.404808044434j),
(0.890356600285+0.455263823271j),
(0.862329125404+0.506348133087j),
(0.830152392387+0.557536482811j),
(0.793714106083+0.608290970325j),
(0.752960026264+0.658066213131j),
(0.707896590233+0.706316053867j),
(0.658591926098+0.752500295639j),
(0.605175673962+0.796091973782j),
(0.547837555408+0.836584687233j),
(0.48682525754+0.873499393463j),
(0.42244040966+0.906390726566j),
(0.355197101831+0.934791445732j),
(0.285494059324+0.958380460739j),
(0.213591173291+0.976923108101j),
(0.139945343137+0.990159213543j),
(0.065038472414+0.997882783413j),
(-0.0106285437942+0.999943494797j),
(-0.0865436866879+0.996248066425j),
(-0.162189796567+0.986759603024j),
(-0.23705175519+0.971496999264j),
(-0.310622543097+0.950533330441j),
(-0.38240903616+0.923993110657j),
(-0.451937526464+0.89204955101j),
(-0.518758952618+0.854920566082j),
(-0.582311093807+0.812966048717j),
(-0.642372369766+0.76639264822j),
(-0.698591887951+0.715520322323j),
(-0.750654160976+0.660695314407j),
(-0.798280358315+0.602286040783j),
(-0.841228663921+0.540679454803j),
(-0.87929558754+0.476276367903j),
(-0.912315964699+0.409486919641j),
(-0.940161883831+0.340728074312j),
(-0.962742805481+0.270418733358j),
(-0.980004072189+0.198977485299j),
(-0.991925954819+0.126818284392j),
(-0.99851256609+0.0545223206282j),
(-0.999846458435-0.0175215266645j),
(-0.996021270752-0.0891158208251j),
(-0.987133920193-0.159895718098j),
(-0.973306238651-0.2295101583j),
(-0.954683184624-0.297624111176j),
(-0.931430280209-0.363919824362j),
(-0.903732538223-0.428097635508j),
(-0.871792256832-0.489875763655j),
(-0.835827112198-0.548992812634j),
(-0.796068251133-0.605206847191j),
(-0.752758979797-0.658296227455j),
(-0.706152498722-0.70805978775j),
(-0.656641483307-0.754202902317j),
(-0.604367733002-0.79670548439j),
(-0.549597978592-0.835429251194j),
(-0.492602348328-0.870254516602j),
(-0.433654457331-0.901079237461j),
(-0.373029649258-0.927819430828j),
(-0.31100410223-0.950408577919j),
(-0.247853919864-0.968797445297j),
(-0.183855071664-0.982953369617j),
(-0.119282215834-0.992860376835j),
(-0.0544078871608-0.998518764973j),
(0.0104992967099-0.999944865704j),
(0.0749994292855-0.997183561325j),
(0.138844624162-0.990314185619j),
(0.201967850327-0.979392170906j),
(0.264124274254-0.964488625526j),
(0.325075358152-0.945688128471j),
(0.3845885396-0.92308807373j),
(0.442438393831-0.89679890871j),
(0.498407125473-0.866943061352j),
(0.552284479141-0.833655714989j),
(0.603869199753-0.797083437443j),
(0.652970373631-0.757383465767j),
(0.69940674305-0.714723825455j),
(0.743007957935-0.66928255558j),
(0.78350687027-0.62138313055j),
(0.820889055729-0.571087777615j),
(0.855021059513-0.51859331131j),
(0.885780930519-0.46410369873j),
(0.913058102131-0.407829582691j),
(0.936754107475-0.349988251925j),
(0.956783294678-0.290801793337j),
(0.973072886467-0.230497643352j),
(0.985563337803-0.169307261705j),
(0.9942086339-0.1074674353j),
(0.9989772439-0.0452152714133j))
sampling_freq = 10e3
freq = sampling_freq / 100
loop_bw = math.pi/100.0
maxf = 1
minf = -1
src = analog.sig_source_c(sampling_freq, analog.GR_COS_WAVE, freq, 1.0)
pll = analog.pll_refout_cc(loop_bw, maxf, minf)
head = blocks.head(gr.sizeof_gr_complex, int (freq))
dst = blocks.vector_sink_c()
self.tb.connect(src, pll, head)
self.tb.connect(head, dst)
self.tb.run()
dst_data = dst.data()
self.assertComplexTuplesAlmostEqual(expected_result, dst_data, 4)
def test_001(self):
''' Test the complex AGC loop (single rate input) '''
tb = self.tb
expected_result = (
(100.000244140625+7.2191943445432116e-07j),
(72.892257690429688+52.959323883056641j),
(25.089065551757812+77.216217041015625j),
(-22.611061096191406+69.589706420898438j),
(-53.357715606689453+38.766635894775391j),
(-59.458671569824219+3.4792964243024471e-07j),
(-43.373462677001953-31.512666702270508j),
(-14.94139289855957-45.984889984130859j),
(13.478158950805664-41.48150634765625j),
(31.838506698608398-23.132022857666016j),
(35.519271850585938-3.1176801940091536e-07j),
(25.942903518676758+18.848621368408203j),
(8.9492912292480469+27.5430908203125j),
(-8.0852642059326172+24.883890151977539j),
(-19.131628036499023+13.899936676025391j),
(-21.383295059204102+3.1281737733479531e-07j),
(-15.650330543518066-11.370632171630859j),
(-5.4110145568847656-16.65339469909668j),
(4.9008159637451172-15.083160400390625j),
(11.628337860107422-8.4484796524047852j),
(13.036135673522949-2.288476110834381e-07j),
(9.5726661682128906+6.954948902130127j),
(3.3216962814331055+10.223132133483887j),
(-3.0204284191131592+9.2959251403808594j),
(-7.1977195739746094+5.2294478416442871j),
(-8.1072216033935547+1.8976157889483147e-07j),
(-5.9838657379150391-4.3475332260131836j),
(-2.0879747867584229-6.4261269569396973j),
(1.9100792407989502-5.8786196708679199j),
(4.5814824104309082-3.3286411762237549j),
(5.1967458724975586-1.3684227440080576e-07j),
(3.8647139072418213+2.8078789710998535j),
(1.3594740629196167+4.1840314865112305j),
(-1.2544282674789429+3.8607344627380371j),
(-3.0366206169128418+2.2062335014343262j),
(-3.4781389236450195+1.1194014604143376e-07j),
(-2.6133756637573242-1.8987287282943726j),
(-0.9293016791343689-2.8600969314575195j),
(0.86727333068847656-2.6691930294036865j),
(2.1243946552276611-1.5434627532958984j),
(2.4633183479309082-8.6486437567145913e-08j),
(1.8744727373123169+1.3618841171264648j),
(0.67528903484344482+2.0783262252807617j),
(-0.63866174221038818+1.965599536895752j),
(-1.5857341289520264+1.152103066444397j),
(-1.8640764951705933+7.6355092915036948e-08j),
(-1.4381576776504517-1.0448826551437378j),
(-0.52529704570770264-1.6166983842849731j),
(0.50366902351379395-1.5501341819763184j),
(1.26766037940979-0.92100900411605835j))
sampling_freq = 100
src1 = analog.sig_source_c(sampling_freq, analog.GR_SIN_WAVE,
sampling_freq * 0.10, 100.0)
dst1 = blocks.vector_sink_c()
head = blocks.head(gr.sizeof_gr_complex, int (5*sampling_freq * 0.10))
agc = analog.agc_cc(1e-3, 1, 1)
tb.connect(src1, head)
tb.connect(head, agc)
tb.connect(agc, dst1)
tb.run()
dst_data = dst1.data()
self.assertComplexTuplesAlmostEqual(expected_result, dst_data, 4)
def test_005(self):
''' Test the complex AGC loop (attack and decay rate inputs) '''
tb = self.tb
expected_result = \
((100.000244140625+7.2191943445432116e-07j),
(0.80881959199905396+0.58764183521270752j),
(0.30894950032234192+0.95084899663925171j),
(-0.30895623564720154+0.95086973905563354j),
(-0.80887287855148315+0.58768033981323242j),
(-0.99984413385391235+5.850709250410091e-09j),
(-0.80889981985092163-0.58770018815994263j),
(-0.30897706747055054-0.95093393325805664j),
(0.30898112058639526-0.95094609260559082j),
(0.80893135070800781-0.58772283792495728j),
(0.99990922212600708-8.7766354184282136e-09j),
(0.80894720554351807+0.58773452043533325j),
(0.30899339914321899+0.95098406076431274j),
(-0.30899572372436523+0.95099133253097534j),
(-0.80896598100662231+0.58774799108505249j),
(-0.99994778633117676+1.4628290578855285e-08j),
(-0.80897533893585205-0.58775502443313599j),
(-0.30900305509567261-0.95101380348205566j),
(0.30900448560714722-0.95101797580718994j),
(0.80898630619049072-0.58776277303695679j),
(0.99997037649154663-1.7554345532744264e-08j),
(0.80899184942245483+0.58776694536209106j),
(0.30900871753692627+0.95103120803833008j),
(-0.30900952219963074+0.95103377103805542j),
(-0.8089984655380249+0.58777159452438354j),
(-0.99998390674591064+2.3406109050938539e-08j),
(-0.809001624584198-0.58777409791946411j),
(-0.30901208519935608-0.95104163885116577j),
(0.30901262164115906-0.95104306936264038j),
(0.80900543928146362-0.587776780128479j),
(0.99999171495437622-2.6332081404234486e-08j),
(0.80900734663009644+0.58777821063995361j),
(0.30901408195495605+0.95104765892028809j),
(-0.30901429057121277+0.95104855298995972j),
(-0.80900967121124268+0.58777981996536255j),
(-0.99999648332595825+3.2183805842578295e-08j),
(-0.80901080369949341-0.58778077363967896j),
(-0.30901527404785156-0.95105135440826416j),
(0.30901545286178589-0.95105189085006714j),
(0.80901217460632324-0.58778166770935059j),
(0.99999916553497314-3.5109700036173308e-08j),
(0.809012770652771+0.58778214454650879j),
(0.30901595950126648+0.9510534405708313j),
(-0.30901598930358887+0.95105385780334473j),
(-0.80901366472244263+0.58778274059295654j),
(-1.0000008344650269+4.0961388947380328e-08j),
(-0.8090139627456665-0.58778303861618042j),
(-0.30901634693145752-0.95105475187301636j),
(0.30901640653610229-0.95105493068695068j),
(0.80901449918746948-0.5877833366394043j))
sampling_freq = 100
src1 = analog.sig_source_c(sampling_freq, analog.GR_SIN_WAVE,
sampling_freq * 0.10, 100)
dst1 = blocks.vector_sink_c()
head = blocks.head(gr.sizeof_gr_complex, int(5*sampling_freq * 0.10))
agc = analog.agc2_cc(1e-2, 1e-3, 1, 1)
tb.connect(src1, head)
tb.connect(head, agc)
tb.connect(agc, dst1)
tb.run()
dst_data = dst1.data()
self.assertComplexTuplesAlmostEqual(expected_result, dst_data, 4)
def test_pll_refout(self):
expected_result = (
(1 + 0j), (1 + 6.4087357643e-10j),
(0.999985277653 + 0.00542619498447j),
(0.999868750572 + 0.0162021834403j),
(0.99948567152 + 0.0320679470897j), (0.99860727787 +
0.0527590736747j),
(0.996953129768 + 0.0780025869608j), (0.994203746319 +
0.107512556016j),
(0.990011692047 + 0.140985429287j), (0.984013140202 +
0.178095817566j),
(0.975838363171 + 0.218493551016j),
(0.965121984482 + 0.261800557375j), (0.95151245594 +
0.307610183954j),
(0.934681296349 + 0.355486690998j), (0.914401650429 +
0.404808044434j),
(0.890356600285 + 0.455263823271j), (0.862329125404 +
0.506348133087j),
(0.830152392387 + 0.557536482811j), (0.793714106083 +
0.608290970325j),
(0.752960026264 + 0.658066213131j), (0.707896590233 +
0.706316053867j),
(0.658591926098 + 0.752500295639j), (0.605175673962 +
0.796091973782j),
(0.547837555408 + 0.836584687233j), (0.48682525754 +
0.873499393463j),
(0.42244040966 + 0.906390726566j), (0.355197101831 +
0.934791445732j),
(0.285494059324 + 0.958380460739j), (0.213591173291 +
0.976923108101j),
(0.139945343137 + 0.990159213543j), (0.065038472414 +
0.997882783413j),
(-0.0106285437942 + 0.999943494797j), (-0.0865436866879 +
0.996248066425j),
(-0.162189796567 + 0.986759603024j), (-0.23705175519 +
0.971496999264j),
(-0.310622543097 + 0.950533330441j), (-0.38240903616 +
0.923993110657j),
(-0.451937526464 + 0.89204955101j), (-0.518758952618 +
0.854920566082j),
(-0.582311093807 + 0.812966048717j), (-0.642372369766 +
0.76639264822j),
(-0.698591887951 + 0.715520322323j), (-0.750654160976 +
0.660695314407j),
(-0.798280358315 + 0.602286040783j), (-0.841228663921 +
0.540679454803j),
(-0.87929558754 + 0.476276367903j), (-0.912315964699 +
0.409486919641j),
(-0.940161883831 + 0.340728074312j), (-0.962742805481 +
0.270418733358j),
(-0.980004072189 + 0.198977485299j), (-0.991925954819 +
0.126818284392j),
(-0.99851256609 +
0.0545223206282j), (-0.999846458435 -
0.0175215266645j), (-0.996021270752 -
0.0891158208251j),
(-0.987133920193 -
0.159895718098j), (-0.973306238651 -
0.2295101583j), (-0.954683184624 -
0.297624111176j),
(-0.931430280209 -
0.363919824362j), (-0.903732538223 -
0.428097635508j), (-0.871792256832 -
0.489875763655j),
(-0.835827112198 -
0.548992812634j), (-0.796068251133 -
0.605206847191j), (-0.752758979797 -
0.658296227455j),
(-0.706152498722 -
0.70805978775j), (-0.656641483307 -
0.754202902317j), (-0.604367733002 -
0.79670548439j),
(-0.549597978592 -
0.835429251194j), (-0.492602348328 -
0.870254516602j), (-0.433654457331 -
0.901079237461j),
(-0.373029649258 -
0.927819430828j), (-0.31100410223 -
0.950408577919j), (-0.247853919864 -
0.968797445297j),
(-0.183855071664 -
0.982953369617j), (-0.119282215834 -
0.992860376835j), (-0.0544078871608 -
0.998518764973j),
(0.0104992967099 -
0.999944865704j), (0.0749994292855 -
0.997183561325j), (0.138844624162 -
0.990314185619j),
(0.201967850327 -
0.979392170906j), (0.264124274254 -
0.964488625526j), (0.325075358152 -
0.945688128471j),
(0.3845885396 - 0.92308807373j), (0.442438393831 - 0.89679890871j),
(0.498407125473 -
0.866943061352j), (0.552284479141 -
0.833655714989j), (0.603869199753 -
0.797083437443j),
(0.652970373631 -
0.757383465767j), (0.69940674305 -
0.714723825455j), (0.743007957935 -
0.66928255558j),
(0.78350687027 -
0.62138313055j), (0.820889055729 -
0.571087777615j), (0.855021059513 -
0.51859331131j),
(0.885780930519 -
0.46410369873j), (0.913058102131 -
0.407829582691j), (0.936754107475 -
0.349988251925j),
(0.956783294678 -
0.290801793337j), (0.973072886467 -
0.230497643352j), (0.985563337803 -
0.169307261705j),
(0.9942086339 - 0.1074674353j), (0.9989772439 - 0.0452152714133j))
sampling_freq = 10e3
freq = sampling_freq / 100
loop_bw = math.pi / 100.0
maxf = 1
minf = -1
src = analog.sig_source_c(sampling_freq, analog.GR_COS_WAVE, freq, 1.0)
pll = analog.pll_refout_cc(loop_bw, maxf, minf)
head = blocks.head(gr.sizeof_gr_complex, int(freq))
dst = blocks.vector_sink_c()
self.tb.connect(src, pll, head)
self.tb.connect(head, dst)
self.tb.run()
dst_data = dst.data()
self.assertComplexTuplesAlmostEqual(expected_result, dst_data, 4)
def test_pll_carriertracking(self):
expected_result = ((1.00000238419+7.21919457547e-09j),
(0.998025715351+0.062790453434j),
(0.992777824402+0.119947694242j),
(0.985192835331+0.171441286802j),
(0.976061582565+0.217501848936j),
(0.966034710407+0.258409559727j),
(0.95565611124+0.294477283955j),
(0.945357382298+0.326030552387j),
(0.935475051403+0.353395611048j),
(0.926258146763+0.376889169216j),
(0.917895197868+0.39681750536j),
(0.910515546799+0.413470208645j),
(0.904196679592+0.427117019892j),
(0.898972511292+0.438006043434j),
(0.894769787788+0.446523308754j),
(0.891652584076+0.452715367079j),
(0.8895829916+0.456773489714j),
(0.888502895832+0.458873122931j),
(0.888343691826+0.459175437689j),
(0.889035582542+0.457833081484j),
(0.890497922897+0.454985737801j),
(0.892645597458+0.450762689114j),
(0.895388305187+0.445282936096j),
(0.898648142815+0.438664674759j),
(0.902342617512+0.431016951799j),
(0.906392872334+0.422441422939j),
(0.910642921925+0.413191765547j),
(0.915039420128+0.403358519077j),
(0.919594764709+0.392864197493j),
(0.92425006628+0.381792247295j),
(0.928944349289+0.370217680931j),
(0.933634519577+0.358220815659j),
(0.938279032707+0.345874190331j),
(0.942840516567+0.333247303963j),
(0.947280526161+0.32040438056j),
(0.951574921608+0.307409763336j),
(0.955703914165+0.294323593378j),
(0.959648966789+0.281201630831j),
(0.963392794132+0.268095195293j),
(0.966880619526+0.255221515894j),
(0.970162451267+0.242447137833j),
(0.973235487938+0.229809194803j),
(0.97609680891+0.217341512442j),
(0.978744983673+0.20507311821j),
(0.981189727783+0.193033605814j),
(0.983436584473+0.181248426437j),
(0.985490739346+0.169738590717j),
(0.987353682518+0.158523857594j),
(0.989041447639+0.147622272372j),
(0.990563035011+0.137049794197j),
(0.991928339005+0.126818582416j),
(0.993117690086+0.117111675441j),
(0.994156062603+0.107930034399j),
(0.995076179504+0.0990980416536j),
(0.995887458324+0.0906178802252j),
(0.996591091156+0.0824909061193j),
(0.997202515602+0.0747182965279j),
(0.997730851173+0.0672992765903j),
(0.998185396194+0.0602316558361j),
(0.99856698513+0.0535135567188j),
(0.998885989189+0.0471420884132j),
(0.99915266037+0.0411129891872j),
(0.999372899532+0.0354214012623j),
(0.999548316002+0.0300626158714j),
(0.999680638313+0.0252036750317j),
(0.999784469604+0.020652115345j),
(0.999865531921+0.0163950324059j),
(0.999923825264+0.0124222636223j),
(0.999960243702+0.00872156023979j),
(0.999983668327+0.00528120994568j),
(0.999997138977+0.00209015607834j),
(1.00000119209-0.00086285173893j),
(0.999992132187-0.00358882546425j),
(0.999979138374-0.00609711557627j),
(0.999963641167-0.00839691981673j),
(0.999947249889-0.0104993218556j),
(0.999924004078-0.0122378543019j),
(0.999904811382-0.0136305987835j),
(0.999888062477-0.0148707330227j),
(0.9998742342-0.0159679055214j),
(0.999856114388-0.0169314742088j),
(0.999839782715-0.0177700817585j),
(0.999826967716-0.0184917747974j),
(0.999818325043-0.0191045701504j),
(0.999807476997-0.0196143388748j),
(0.999797284603-0.0200265944004j),
(0.999791204929-0.0203481912613j),
(0.99978852272-0.0205836892128j),
(0.99978530407-0.0207380950451j),
(0.999785065651-0.0206423997879j),
(0.999787807465-0.0204866230488j),
(0.999794304371-0.0202808082104j),
(0.999800384045-0.0200312435627j),
(0.999803245068-0.0197458267212j),
(0.9998087883-0.0194311738014j),
(0.999816894531-0.0190933048725j),
(0.999825954437-0.0187371373177j),
(0.999829888344-0.0183679759502j),
(0.999835848808-0.017987690866j),
(0.999844014645-0.0176006518304j))
sampling_freq = 10e3
freq = sampling_freq / 100
loop_bw = math.pi/100.0
maxf = 1
minf = -1
src = analog.sig_source_c(sampling_freq, analog.GR_COS_WAVE, freq, 1.0)
pll = analog.pll_carriertracking_cc(loop_bw, maxf, minf)
head = blocks.head(gr.sizeof_gr_complex, int (freq))
dst = blocks.vector_sink_c()
self.tb.connect(src, pll, head)
self.tb.connect(head, dst)
self.tb.run()
dst_data = dst.data()
self.assertComplexTuplesAlmostEqual(expected_result, dst_data, 5)