diff options
Diffstat (limited to 'gr-uhd/examples/python/freq_hopping.py')
| -rwxr-xr-x | gr-uhd/examples/python/freq_hopping.py | 72 |
1 files changed, 43 insertions, 29 deletions
diff --git a/gr-uhd/examples/python/freq_hopping.py b/gr-uhd/examples/python/freq_hopping.py index 8fd65aade8..871181e045 100755 --- a/gr-uhd/examples/python/freq_hopping.py +++ b/gr-uhd/examples/python/freq_hopping.py @@ -19,6 +19,7 @@ from gnuradio import gr from gnuradio import blocks from gnuradio import uhd + def setup_parser(): """ Setup the parser for the frequency hopper. """ parser = argparse.ArgumentParser( @@ -77,31 +78,34 @@ def setup_parser(): class FrequencyHopperSrc(gr.hier_block2): """ Provides tags for frequency hopping """ + def __init__( - self, - n_bursts, n_channels, - freq_delta, base_freq, dsp_tuning, - burst_length, base_time, hop_time, - post_tuning=False, - tx_gain=0, - verbose=False - ): + self, + n_bursts, n_channels, + freq_delta, base_freq, dsp_tuning, + burst_length, base_time, hop_time, + post_tuning=False, + tx_gain=0, + verbose=False + ): gr.hier_block2.__init__( self, "FrequencyHopperSrc", gr.io_signature(1, 1, gr.sizeof_gr_complex), gr.io_signature(1, 1, gr.sizeof_gr_complex), ) n_samples_total = n_bursts * burst_length - lowest_frequency = base_freq - numpy.floor(n_channels/2) * freq_delta - self.hop_sequence = [lowest_frequency + n * freq_delta for n in range(n_channels)] + lowest_frequency = base_freq - numpy.floor(n_channels / 2) * freq_delta + self.hop_sequence = [lowest_frequency + n * + freq_delta for n in range(n_channels)] numpy.random.shuffle(self.hop_sequence) # Repeat that: - self.hop_sequence = [self.hop_sequence[x % n_channels] for x in range(n_bursts)] + self.hop_sequence = [self.hop_sequence[x % n_channels] + for x in range(n_bursts)] if verbose: print("Hop Frequencies | Hop Pattern") print("=================|================================") for f in self.hop_sequence: - print("{:6.3f} MHz | ".format(f/1e6), end='') + print("{:6.3f} MHz | ".format(f / 1e6), end='') if n_channels < 50: print(" " * int((f - base_freq) / freq_delta) + "#") else: @@ -113,25 +117,28 @@ class FrequencyHopperSrc(gr.hier_block2): gain_tag.offset = 0 gain_tag.key = pmt.string_to_symbol('tx_command') gain_tag.value = pmt.to_pmt({'gain': tx_gain}) - tag_list = [gain_tag,] + tag_list = [gain_tag, ] for i in range(len(self.hop_sequence)): time = pmt.cons( - pmt.from_uint64(int(base_time + i * hop_time+0.01)), - pmt.from_double((base_time + i * hop_time+0.01) % 1), + pmt.from_uint64(int(base_time + i * hop_time + 0.01)), + pmt.from_double((base_time + i * hop_time + 0.01) % 1), ) tune_tag = gr.tag_t() tune_tag.offset = i * burst_length # TODO dsp_tuning should also be able to do post_tuning if i > 0 and post_tuning and not dsp_tuning: - tune_tag.offset -= 1 # Move it to last sample of previous burst + tune_tag.offset -= 1 # Move it to last sample of previous burst if dsp_tuning: tune_tag.key = pmt.string_to_symbol('tx_command') - tune_tag.value = pmt.to_pmt({'lo_freq': base_freq, 'dsp_freq': base_freq - self.hop_sequence[i]}) - tune_tag.value = pmt.dict_add(tune_tag.value, pmt.intern("time"),time) + tune_tag.value = pmt.to_pmt( + {'lo_freq': base_freq, 'dsp_freq': base_freq - self.hop_sequence[i]}) + tune_tag.value = pmt.dict_add( + tune_tag.value, pmt.intern("time"), time) else: tune_tag.key = pmt.string_to_symbol('tx_command') tune_tag.value = pmt.to_pmt({'freq': self.hop_sequence[i]}) - tune_tag.value = pmt.dict_add(tune_tag.value, pmt.intern('time'), time) + tune_tag.value = pmt.dict_add( + tune_tag.value, pmt.intern('time'), time) tag_list.append(tune_tag) length_tag = gr.tag_t() length_tag.offset = i * burst_length @@ -142,11 +149,12 @@ class FrequencyHopperSrc(gr.hier_block2): time_tag.offset = i * burst_length time_tag.key = pmt.string_to_symbol('tx_time') time_tag.value = pmt.make_tuple( - pmt.car(time), - pmt.cdr(time) + pmt.car(time), + pmt.cdr(time) ) tag_list.append(time_tag) - tag_source = blocks.vector_source_c((1.0,) * n_samples_total, repeat=False, tags=tag_list) + tag_source = blocks.vector_source_c( + (1.0,) * n_samples_total, repeat=False, tags=tag_list) mult = blocks.multiply_cc() self.connect(self, mult, self) self.connect(tag_source, (mult, 1)) @@ -154,10 +162,12 @@ class FrequencyHopperSrc(gr.hier_block2): class FlowGraph(gr.top_block): """ Flow graph that does the frequency hopping. """ + def __init__(self, args): gr.top_block.__init__(self) if args.input_file is not None: - src = blocks.file_source(gr.sizeof_gr_complex, args.input_file, repeat=True) + src = blocks.file_source( + gr.sizeof_gr_complex, args.input_file, repeat=True) else: src = blocks.vector_source_c((.5,) * int(1e6) * 2, repeat=True) # Setup USRP @@ -189,6 +199,7 @@ class FlowGraph(gr.top_block): ) self.connect(src, hopper_block, self.usrp) + def print_hopper_stats(args): """ Nothing to do with Grace Hopper """ print(""" @@ -205,14 +216,16 @@ Transmit Gain | {gain} dB ===================+========================= """.format( hop_time=args.hop_time, - hop_duration=1000.0/args.rate*args.samp_per_burst, + hop_duration=1000.0 / args.rate * args.samp_per_burst, gain=args.gain if args.gain else "(midpoint)", - lowest_freq=args.freq/1e6, - highest_freq=(args.freq + (args.num_channels-1) * args.freq_delta)/1e6, - freq_delta=args.freq_delta/1e6, + lowest_freq=args.freq / 1e6, + highest_freq=(args.freq + (args.num_channels - 1) * + args.freq_delta) / 1e6, + freq_delta=args.freq_delta / 1e6, num_channels=args.num_channels, - rate=args.rate/1e6, - )) + rate=args.rate / 1e6, + )) + def main(): """ Go, go, go! """ @@ -227,6 +240,7 @@ def main(): top_block.usrp.set_time_now(uhd.time_spec(0.0)) top_block.run() + if __name__ == '__main__': try: main() |