diff options
Diffstat (limited to 'dpd/main.py')
| -rwxr-xr-x | dpd/main.py | 35 |
1 files changed, 22 insertions, 13 deletions
diff --git a/dpd/main.py b/dpd/main.py index ddbbfc4..921afb2 100755 --- a/dpd/main.py +++ b/dpd/main.py @@ -12,8 +12,6 @@ predistortion module of ODR-DabMod.""" import datetime import os -import time -import sys import matplotlib matplotlib.use('GTKAgg') @@ -46,10 +44,10 @@ import src.ExtractStatistic as ExtractStatistic import src.Adapt as Adapt import src.Agc as Agc import src.TX_Agc as TX_Agc -import src.Symbol_align -import src.const -import src.MER -import src.Measure_Shoulders +from src.Symbol_align import Symbol_align +from src.Const import Const +from src.MER import MER +from src.Measure_Shoulders import Measure_Shoulders import argparse parser = argparse.ArgumentParser( @@ -91,6 +89,13 @@ parser.add_argument('-i', '--iterations', default=1, type=int, parser.add_argument('-L', '--lut', help='Use lookup table instead of polynomial predistorter', action="store_true") +parser.add_argument('--n_bins', default='64', type=int, + required=False) +parser.add_argument('--n_per_bin', default='128', type=int, + required=False) +parser.add_argument('--n_meas', default='20', type=int, + help='Number of samples to request from ODR-DabMod', + required=False) cli_args = parser.parse_args() logging.info(cli_args) @@ -106,10 +111,14 @@ target_median = cli_args.target_median rxgain = cli_args.rxgain txgain = cli_args.txgain -c = src.const.const(samplerate, target_median) -SA = src.Symbol_align.Symbol_align(c) -MER = src.MER.MER(c) -MS = src.Measure_Shoulders.Measure_Shoulder(c) +n_bins = cli_args.n_bins +n_per_bin = cli_args.n_per_bin +n_meas = cli_args.n_meas + +c = Const(samplerate, target_median, n_bins, n_per_bin, n_meas) +SA = Symbol_align(c) +MER = MER(c) +MS = Measure_Shoulders(c) meas = Measure.Measure(samplerate, port, num_req) extStat = ExtractStatistic.ExtractStatistic(c) @@ -181,7 +190,7 @@ while i < num_iter: tx, rx, phase_diff, n_per_bin = extStat.extract(txframe_aligned, rxframe_aligned) - if extStat.n_meas >= 100: + if extStat.n_meas >= c.n_meas: state = "model" else: state = "measure" @@ -212,8 +221,8 @@ while i < num_iter: rx_gain = adapt.get_rxgain() digital_gain = adapt.get_digital_gain() tx_median = np.median(np.abs(txframe_aligned)) - rx_shoulder_tuple = MS.average_shoulders(rxframe_aligned) - tx_shoulder_tuple = MS.average_shoulders(txframe_aligned) + rx_shoulder_tuple = MS.average_shoulders(rxframe_aligned) if c.MS_enable else None + tx_shoulder_tuple = MS.average_shoulders(txframe_aligned) if c.MS_enable else None logging.info(list((name, eval(name)) for name in ['i', 'tx_mer', 'tx_shoulder_tuple', 'rx_mer', |