def __init__(self, rate, taps=None, flt_size=32, atten=100):
gr.hier_block2.__init__(self, "pfb_arb_resampler_fff",
gr.io_signature(1, 1, gr.sizeof_float), # Input signature
gr.io_signature(1, 1, gr.sizeof_float)) # Output signature
self._rate = rate
self._size = flt_size
if taps is not None:
self._taps = taps
else:
# Create a filter that covers the full bandwidth of the input signal
bw = 0.4
tb = 0.2
ripple = 0.1
#self._taps = gr.firdes.low_pass_2(self._size, self._size, bw, tb, atten)
made = False
while not made:
try:
self._taps = optfir.low_pass(self._size, self._size, bw, bw+tb, ripple, atten)
made = True
except RuntimeError:
ripple += 0.01
made = False
print("Warning: set ripple to %.4f dB. If this is a problem, adjust the attenuation or create your own filter taps." % (ripple))
# Build in an exit strategy; if we've come this far, it ain't working.
if(ripple >= 1.0):
raise RuntimeError("optfir could not generate an appropriate filter.")
self.pfb = gr.pfb_arb_resampler_fff(self._rate, self._taps, self._size)
#print "PFB has %d taps\n" % (len(self._taps),)
self.connect(self, self.pfb)
self.connect(self.pfb, self)
def test02 (self):
# Test real BPSK sync
excess_bw = 0.35
sps = 4
loop_bw = cmath.pi/100.0
nfilts = 32
init_phase = nfilts/2
max_rate_deviation = 1.5
osps = 1
ntaps = 11 * int(sps*nfilts)
#taps = gr.firdes.root_raised_cosine(nfilts, nfilts*sps,
# 1.0, excess_bw, ntaps)
taps = pfb_clock_sync_taps.taps
self.test = digital.pfb_clock_sync_fff(sps, loop_bw, taps,
nfilts, init_phase,
max_rate_deviation,
osps)
data = 1000*[1, -1]
self.src = gr.vector_source_f(data, False)
# pulse shaping interpolation filter
#rrc_taps = gr.firdes.root_raised_cosine(
# nfilts, # gain
# nfilts, # sampling rate based on 32 filters in resampler
# 1.0, # symbol rate
# excess_bw, # excess bandwidth (roll-off factor)
# ntaps)
rrc_taps = pfb_clock_sync_taps.rrc_taps
self.rrc_filter = gr.pfb_arb_resampler_fff(sps, rrc_taps)
self.snk = gr.vector_sink_f()
self.tb.connect(self.src, self.rrc_filter, self.test, self.snk)
self.tb.run()
expected_result = 1000*[-1, 1]
dst_data = self.snk.data()
# Only compare last Ncmp samples
Ncmp = 100
len_e = len(expected_result)
len_d = len(dst_data)
expected_result = expected_result[len_e - Ncmp:]
dst_data = dst_data[len_d - Ncmp:]
#for e,d in zip(expected_result, dst_data):
# print e, d
self.assertComplexTuplesAlmostEqual (expected_result, dst_data, 1)
def test02(self):
# Test real BPSK sync
excess_bw = 0.35
sps = 4
loop_bw = cmath.pi / 100.0
nfilts = 32
init_phase = nfilts / 2
max_rate_deviation = 1.5
osps = 1
ntaps = 11 * int(sps * nfilts)
#taps = gr.firdes.root_raised_cosine(nfilts, nfilts*sps,
# 1.0, excess_bw, ntaps)
taps = pfb_clock_sync_taps.taps
self.test = digital.pfb_clock_sync_fff(sps, loop_bw, taps, nfilts,
init_phase, max_rate_deviation,
osps)
data = 1000 * [1, -1]
self.src = gr.vector_source_f(data, False)
# pulse shaping interpolation filter
#rrc_taps = gr.firdes.root_raised_cosine(
# nfilts, # gain
# nfilts, # sampling rate based on 32 filters in resampler
# 1.0, # symbol rate
# excess_bw, # excess bandwidth (roll-off factor)
# ntaps)
rrc_taps = pfb_clock_sync_taps.rrc_taps
self.rrc_filter = gr.pfb_arb_resampler_fff(sps, rrc_taps)
self.snk = gr.vector_sink_f()
self.tb.connect(self.src, self.rrc_filter, self.test, self.snk)
self.tb.run()
expected_result = 1000 * [-1, 1]
dst_data = self.snk.data()
# Only compare last Ncmp samples
Ncmp = 100
len_e = len(expected_result)
len_d = len(dst_data)
expected_result = expected_result[len_e - Ncmp:]
dst_data = dst_data[len_d - Ncmp:]
#for e,d in zip(expected_result, dst_data):
# print e, d
self.assertComplexTuplesAlmostEqual(expected_result, dst_data, 1)
