From 1bfc6b439dbcdc467bbbed43a9fd71b49524c348 Mon Sep 17 00:00:00 2001
From: Josh Morman <jmorman@gnuradio.org>
Date: Wed, 24 Nov 2021 12:41:17 -0500
Subject: uhd: pep8 formatting
Signed-off-by: Josh Morman <jmorman@gnuradio.org>
---
gr-uhd/examples/python/freq_hopping.py | 72 ++++++++++++++++++++--------------
1 file changed, 43 insertions(+), 29 deletions(-)
(limited to 'gr-uhd/examples/python')
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()
--
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