def __init__(self, encoder_list, decoder_list, esno=numpy.arange(0.0, 3.0, .25), samp_rate=3200000, threading='capillary', puncpat='11', seed=0): gr.hier_block2.__init__( self, "ber_curve_generator", gr.io_signature(0, 0, 0), gr.io_signature(len(esno) * 2, len(esno) * 2, gr.sizeof_char*1)) self.esno = esno self.samp_rate = samp_rate self.encoder_list = encoder_list self.decoder_list = decoder_list self.puncpat = puncpat self.random_gen_b_0 = blocks.vector_source_b(map(int, numpy.random.randint(0, 256, 100000)), True) self.deinterleave = blocks.deinterleave(gr.sizeof_char*1) self.connect(self.random_gen_b_0, self.deinterleave) self.ber_generators = [] for i in range(0, len(esno)): ber_generator_temp = fec_test( generic_encoder=encoder_list[i], generic_decoder=decoder_list[i], esno=esno[i], samp_rate=samp_rate, threading=threading, puncpat=puncpat, seed=seed) self.ber_generators.append(ber_generator_temp); for i in range(0, len(esno)): self.connect((self.deinterleave, i), (self.ber_generators[i])) self.connect((self.ber_generators[i], 0), (self, i*2)); self.connect((self.ber_generators[i], 1), (self, i*2 + 1));
def __init__(self, encoder_list, decoder_list, esno=numpy.arange(0.0, 3.0, .25), samp_rate=3200000, threading='capillary', puncpat='11', seed=0): gr.hier_block2.__init__( self, "ber_curve_generator", gr.io_signature(0, 0, 0), gr.io_signature(len(esno) * 2, len(esno) * 2, gr.sizeof_char * 1)) self.esno = esno self.samp_rate = samp_rate self.encoder_list = encoder_list self.decoder_list = decoder_list self.puncpat = puncpat self.random_gen_b_0 = blocks.vector_source_b( map(int, numpy.random.randint(0, 256, 100000)), True) self.deinterleave = blocks.deinterleave(gr.sizeof_char * 1) self.connect(self.random_gen_b_0, self.deinterleave) self.ber_generators = [] # FIXME It would be good to check that the encoder_list and # decoder_list have parallelism set to > 0. If parallelism # is set to 0, a map isn't passed and an indexing error is # thrown on line 53 or 54 below. for i in range(0, len(esno)): ber_generator_temp = fec_test(generic_encoder=encoder_list[i], generic_decoder=decoder_list[i], esno=esno[i], samp_rate=samp_rate, threading=threading, puncpat=puncpat, seed=seed) self.ber_generators.append(ber_generator_temp) for i in range(0, len(esno)): self.connect((self.deinterleave, i), (self.ber_generators[i])) self.connect((self.ber_generators[i], 0), (self, i * 2)) self.connect((self.ber_generators[i], 1), (self, i * 2 + 1))
def __init__(self, encoder_list, decoder_list, esno=numpy.arange(0.0, 3.0, .25), samp_rate=3200000, threading='capillary', puncpat='11', seed=0): gr.hier_block2.__init__( self, "ber_curve_generator", gr.io_signature(0, 0, 0), gr.io_signature(len(esno) * 2, len(esno) * 2, gr.sizeof_char * 1)) self.esno = esno self.samp_rate = samp_rate self.encoder_list = encoder_list self.decoder_list = decoder_list self.puncpat = puncpat self.random_gen_b_0 = blocks.vector_source_b( map(int, numpy.random.randint(0, 256, 100000)), True) self.deinterleave = blocks.deinterleave(gr.sizeof_char * 1) self.connect(self.random_gen_b_0, self.deinterleave) self.ber_generators = [] for i in range(0, len(esno)): ber_generator_temp = fec_test(generic_encoder=encoder_list[i], generic_decoder=decoder_list[i], esno=esno[i], samp_rate=samp_rate, threading=threading, puncpat=puncpat, seed=seed) self.ber_generators.append(ber_generator_temp) for i in range(0, len(esno)): self.connect((self.deinterleave, i), (self.ber_generators[i])) self.connect((self.ber_generators[i], 0), (self, i * 2)) self.connect((self.ber_generators[i], 1), (self, i * 2 + 1))
def __init__(self, encoder_list, decoder_list, esno=numpy.arange(0.0, 3.0, .25), samp_rate=3200000, threading='capillary', puncpat='11', seed=0): gr.hier_block2.__init__( self, "ber_curve_generator", gr.io_signature(0, 0, 0), gr.io_signature(len(esno) * 2, len(esno) * 2, gr.sizeof_char*1)) self.esno = esno self.samp_rate = samp_rate self.encoder_list = encoder_list self.decoder_list = decoder_list self.puncpat = puncpat self.random_gen_b_0 = blocks.vector_source_b(map(int, numpy.random.randint(0, 256, 100000)), True) self.deinterleave = blocks.deinterleave(gr.sizeof_char*1) self.connect(self.random_gen_b_0, self.deinterleave) self.ber_generators = [] # FIXME It would be good to check that the encoder_list and # decoder_list have parallelism set to > 0. If parallelism # is set to 0, a map isn't passed and an indexing error is # thrown on line 53 or 54 below. for i in range(0, len(esno)): ber_generator_temp = fec_test( generic_encoder=encoder_list[i], generic_decoder=decoder_list[i], esno=esno[i], samp_rate=samp_rate, threading=threading, puncpat=puncpat, seed=seed) self.ber_generators.append(ber_generator_temp); for i in range(0, len(esno)): self.connect((self.deinterleave, i), (self.ber_generators[i])) self.connect((self.ber_generators[i], 0), (self, i*2)); self.connect((self.ber_generators[i], 1), (self, i*2 + 1));