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https://github.com/hb9fxq/gr-digitalhf
synced 2024-11-05 05:55:53 +00:00
prel. support for 12800 baud 110C bursts added
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@ -45,16 +45,27 @@ QAM64=np.array(
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range(64)), common.CONST_DTYPE)
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## for test
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#QAM64 = QAM64[(7,3,24,56,35,39,60,28),]
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#QAM64['symbols'] = [1, 0, 2, 6, 4, 5, 7, 3]
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QAM64p = QAM64[(3,24,56,35,39,60,28,7),]
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QAM64p['symbols'] = range(8) ## not used
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## ---- Walsh-4 codes ----------------------------------------------------------
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WALSH4 = np.array([[0,0,0,0], # 0 - 00
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[0,1,0,1], # 1 - 01
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[0,0,1,1], # 2 - 10
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[0,1,1,0]], # 3 - 11
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dtype=np.uint8)
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FROM_WALSH4 = -np.ones(256, dtype=np.int8)
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for i in range(4):
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FROM_WALSH4[np.packbits(WALSH4[i][:])[0]] = i
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## ---- constellation indices ---------------------------------------------------
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MODE_BPSK = 0
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MODE_QPSK = 1
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MODE_8PSK = 2
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MODE_16QAM = 3
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MODE_32QAM = 4
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MODE_64QAM = 5
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MODE_BPSK = 0
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MODE_QPSK = 1
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MODE_8PSK = 2
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MODE_16QAM = 3
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MODE_32QAM = 4
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MODE_64QAM = 5
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MODE_64QAMp = 6
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## ---- data scrambler -----------------------------------------------------------
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class ScrambleData(object):
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@ -76,6 +87,35 @@ class ScrambleData(object):
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self._state = np.concatenate(([self._state.dot(self._taps)&1],
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self._state[0:-1]))
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class ScrambleDataP(object):
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"""data scrambling sequence generator"""
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def __init__(self):
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self._i = 0
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state = np.array([0,0,0,0,0,0,0,0,0,0,0,1], dtype=np.uint8)
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taps = np.array([1,1,0,0,1,0,1,0,0,0,0,0], dtype=np.uint8)
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n = 10000
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m = len(state)
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sequence = np.zeros(n, dtype=np.uint8)
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sequence[0:m] = state
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for i in range(m,n):
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sequence[i] = sequence[i-m:i].dot(taps)&1
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idx = np.arange(160, dtype=np.uint32)
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self._seq = 4*sequence[3530+idx] + 2*sequence[4042+idx] + sequence[4796+idx]
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def reset(self):
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self._i = 0
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def get_seq(self):
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return self._seq
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def next(self):
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if self._i == 160:
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self._i = 0
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s = self._seq[self._i]
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self._i += 1
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return s
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## ---- preamble definitions ---------------------------------------------------
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## 184 = 8*23
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PREAMBLE=common.n_psk(8, np.array(
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@ -203,7 +243,7 @@ class PhysicalLayer(object):
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"""intialization"""
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self._sps = sps
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self._frame_counter = -2
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self._constellations = [BPSK, QPSK, PSK8, QAM16, QAM32, QAM64]
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self._constellations = [BPSK, QPSK, PSK8, QAM16, QAM32, QAM64, QAM64p]
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self._preamble = self.get_preamble()
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self._scramble = ScrambleData()
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self._viterbi_decoder = viterbi27(0x6d, 0x4f)
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@ -307,28 +347,36 @@ class PhysicalLayer(object):
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self._rate_info = rate_info = TO_RATE[self._mode['rate']]
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self._intl_info = intl_info = TO_INTERLEAVER[self._mode['interleaver']]
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print('======== rate,interleaver:', rate_info, intl_info)
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self._interleaver_frames = intl_info['frames']
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baud = rate_info['baud']
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intl_id = intl_info['id']
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intl_size = INTL_SIZE[baud][intl_id]
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intl_incr = INTL_INCR[baud][intl_id]
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if self._deintl_depunct == None:
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self._deintl_depunct = DeIntl_DePunct(size=intl_size,
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incr=intl_incr)
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self._constellation_index = rate_info['ci']
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print('constellation index', self._constellation_index)
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self._scramble.reset()
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num_bits = max(3, rate_info['bits_per_symbol'])
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iscr = np.array([self._scramble.next(num_bits) for _ in range(256)],
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dtype=np.uint8)
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print('iscr=', iscr)
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self._data_scramble = np.ones (256, dtype=np.complex64)
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self._data_scramble_xor = np.zeros(256, dtype=np.uint8)
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if rate_info['ci'] > MODE_8PSK:
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self._data_scramble_xor = iscr
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self._12800burst_mode = mode['rate']==(1,1,0) and mode['interleaver']==(0,0,1)
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print('======== rate,interleaver:', rate_info, intl_info, self._12800burst_mode)
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if self._12800burst_mode:
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self._scrp = ScrambleDataP()
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self._constellation_index = MODE_BPSK# 64QAMp
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self._data_scramble = np.ones (256, dtype=np.complex64)
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self._data_scramble_xor = np.zeros(256, dtype=np.uint8)
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##self._data_scramble = QAM64p['points'][self._scrp.next() for _ in range(256)]
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else:
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self._data_scramble = common.n_psk(8, iscr)
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self._interleaver_frames = intl_info['frames']
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baud = rate_info['baud']
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intl_id = intl_info['id']
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intl_size = INTL_SIZE[baud][intl_id]
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intl_incr = INTL_INCR[baud][intl_id]
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if self._deintl_depunct == None:
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self._deintl_depunct = DeIntl_DePunct(size=intl_size,
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incr=intl_incr)
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self._constellation_index = rate_info['ci']
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print('constellation index', self._constellation_index)
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self._scramble.reset()
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num_bits = max(3, rate_info['bits_per_symbol'])
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iscr = np.array([self._scramble.next(num_bits) for _ in range(256)],
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dtype=np.uint8)
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print('iscr=', iscr)
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self._data_scramble = np.ones (256, dtype=np.complex64)
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self._data_scramble_xor = np.zeros(256, dtype=np.uint8)
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if rate_info['ci'] > MODE_8PSK:
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self._data_scramble_xor = iscr
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else:
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self._data_scramble = common.n_psk(8, iscr)
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return success
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def make_reinserted_preamble(self, offset, success):
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@ -344,7 +392,10 @@ class PhysicalLayer(object):
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def make_data_frame(self, success):
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self._preamble_offset = -72 ## all following reinserted preambles start at index -72
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a = np.zeros(256+31, common.SYMB_SCRAMBLE_DTYPE)
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a['scramble'][:256] = self._data_scramble
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if self._12800burst_mode:
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a['scramble'][:256] = QAM64p['points'][[self._scrp.next() for _ in range(256)]]
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else:
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a['scramble'][:256] = self._data_scramble
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a['scramble_xor'][:256] = self._data_scramble_xor
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n = (self._frame_counter-1)%72
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if self._frame_counter == 72:
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@ -362,16 +413,30 @@ class PhysicalLayer(object):
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return a
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def decode_soft_dec(self, soft_dec):
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r = self._deintl_depunct.load(soft_dec)
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if r.shape[0] == 0:
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return []
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self._viterbi_decoder.reset()
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decoded_bits = np.roll(self._viterbi_decoder.udpate(r), 7)
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print('bits=', decoded_bits[:100])
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print('quality={}% ({},{})'.format(120.0*self._viterbi_decoder.quality()/(2*len(decoded_bits)),
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self._viterbi_decoder.quality(),
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len(decoded_bits)))
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return decoded_bits
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if self._12800burst_mode:
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print('decode_soft_dec', len(soft_dec))
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n = len(soft_dec) // 32
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soft_bits = np.zeros(2*n, dtype=np.float32)
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for i in range(n):
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w = np.sum(soft_dec[32*i:32*(i+1)].reshape(8,4),0)
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b = FROM_WALSH4[np.packbits(w>0)[0]] ## TODO use 2nd half of WALSH bits
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abs_soft_dec = np.mean(np.abs(w))
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print('WALSH', i, w, b, abs_soft_dec)
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soft_bits[2*i] = abs_soft_dec*(2*(b>>1)-1)
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soft_bits[2*i+1] = abs_soft_dec*(2*(b &1)-1)
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return soft_bits>0
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else:
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r = self._deintl_depunct.load(soft_dec)
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if r.shape[0] == 0:
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return []
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self._viterbi_decoder.reset()
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decoded_bits = np.roll(self._viterbi_decoder.udpate(r), 7)
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print('bits=', decoded_bits[:100])
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print('quality={}% ({},{})'.format(120.0*self._viterbi_decoder.quality()/(2*len(decoded_bits)),
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self._viterbi_decoder.quality(),
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len(decoded_bits)))
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return decoded_bits
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@staticmethod
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def get_preamble():
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@ -407,3 +472,6 @@ if __name__ == '__main__':
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# print(QAM64['points'][i])
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print([s.next(6) for _ in range(256)])
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s = ScrambleDataP()
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assert(np.all(s.get_seq()[0:20]==np.array([0,2,4,3,3,6,4,5,7,6,7,0,5,5,4,3,5,4,3,7], dtype=np.uint8)))
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