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author | Matthias P. Braendli <matthias.braendli@mpb.li> | 2017-12-29 06:43:49 +0100 |
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committer | Matthias P. Braendli <matthias.braendli@mpb.li> | 2017-12-29 06:43:58 +0100 |
commit | a62e05c9564045044df734fd3723b3f665ad91ae (patch) | |
tree | 5a9e1570362fe9a47fe581c292f3bd84f6fd3e82 /dpd/apply_adapt_dumps.py | |
parent | bf53849fba5796d1b98254a7eeab575a50ae7996 (diff) | |
download | dabmod-a62e05c9564045044df734fd3723b3f665ad91ae.tar.gz dabmod-a62e05c9564045044df734fd3723b3f665ad91ae.tar.bz2 dabmod-a62e05c9564045044df734fd3723b3f665ad91ae.zip |
DPD: Make logging to file optional in all modules, simplify apply_adapt_dumps
Diffstat (limited to 'dpd/apply_adapt_dumps.py')
-rwxr-xr-x | dpd/apply_adapt_dumps.py | 132 |
1 files changed, 6 insertions, 126 deletions
diff --git a/dpd/apply_adapt_dumps.py b/dpd/apply_adapt_dumps.py index 6b15aff..f1f3359 100755 --- a/dpd/apply_adapt_dumps.py +++ b/dpd/apply_adapt_dumps.py @@ -6,38 +6,16 @@ # http://www.opendigitalradio.org # Licence: The MIT License, see notice at the end of this file -"""This Python script is the main file for ODR-DabMod's DPD Computation Engine. -This engine calculates and updates the parameter of the digital -predistortion module of ODR-DabMod.""" - import datetime import os -import matplotlib import glob -import natsort -matplotlib.use('GTKAgg') - import logging dt = datetime.datetime.now().isoformat() -logging_path = "/tmp/dpd_{}".format(dt).replace(".", "_").replace(":", "-") -os.makedirs(logging_path) logging.basicConfig(format='%(asctime)s - %(module)s - %(levelname)s - %(message)s', datefmt='%Y-%m-%d %H:%M:%S', - filename='{}/dpd.log'.format(logging_path), - filemode='w', level=logging.DEBUG) -# also log up to INFO to console -console = logging.StreamHandler() -console.setLevel(logging.INFO) -# set a format which is simpler for console use -formatter = logging.Formatter('%(asctime)s - %(module)s - %(levelname)s - %(message)s') -# tell the handler to use this format -console.setFormatter(formatter) -# add the handler to the root logger -logging.getLogger('').addHandler(console) - import src.Measure as Measure import src.Model as Model import src.ExtractStatistic as ExtractStatistic @@ -59,120 +37,22 @@ parser.add_argument('--port', default=50055, type=int, parser.add_argument('--rc-port', default=9400, type=int, help='port of ODR-DabMod ZMQ Remote Control to connect to (default: 9400)', required=False) -parser.add_argument('--samplerate', default=8192000, type=int, - help='Sample rate', - required=False) -parser.add_argument('--coefs', default='/tmp/poly.coef', +parser.add_argument('--coefs', default='poly.coef', help='File with DPD coefficients, which will be read by ODR-DabMod', required=False) -parser.add_argument('--txgain', default=75, - help='TX Gain', - required=False, - type=int) -parser.add_argument('--rxgain', default=30, - help='TX Gain', - required=False, - type=int) -parser.add_argument('--digital_gain', default=1, - help='Digital Gain', - required=False, - type=float) -parser.add_argument('--samps', default='81920', type=int, - help='Number of samples to request from ODR-DabMod', - required=False) -parser.add_argument('--target_median', default=0.1, - help='target_median', - required=False, - type=float) -parser.add_argument('--searchpath', default='./stored', type=str, - help='Path to search .pkl files with stored configuration' - 'for adapt', - required=False) -parser.add_argument('-L', '--lut', - help='Use lookup table instead of polynomial predistorter', - action="store_true") +parser.add_argument('file', help='File to read the DPD settings from') cli_args = parser.parse_args() port = cli_args.port port_rc = cli_args.rc_port coef_path = cli_args.coefs -digital_gain = cli_args.digital_gain -txgain = cli_args.txgain -rxgain = cli_args.rxgain -num_req = cli_args.samps -samplerate = cli_args.samplerate -searchpath = cli_args.searchpath -target_median = cli_args.target_median - -c = src.Const.Const(samplerate, target_median, False) -SA = src.Symbol_align.Symbol_align(c) -MER = src.MER.MER(c) -MS = src.Measure_Shoulders.Measure_Shoulders(c) - -meas = Measure.Measure(samplerate, port, num_req) -extStat = ExtractStatistic.ExtractStatistic(c) -adapt = Adapt.Adapt(port_rc, coef_path) -dpddata = adapt.get_predistorter - -if cli_args.lut: - model = Model.Lut(c) -else: - model = Model.Poly(c) -adapt.set_predistorter(model.get_dpd_data()) -adapt.set_digital_gain(digital_gain) -adapt.set_txgain(txgain) -adapt.set_rxgain(rxgain) - -tx_gain = adapt.get_txgain() -rx_gain = adapt.get_rxgain() -digital_gain = adapt.get_digital_gain() - -dpddata = adapt.get_predistorter() -if dpddata[0] == "poly": - coefs_am = dpddata[1] - coefs_pm = dpddata[2] - logging.info( - "TX gain {}, RX gain {}, dpd_coefs_am {}," - " dpd_coefs_pm {}, digital_gain {}".format( - tx_gain, rx_gain, coefs_am, coefs_pm, digital_gain - ) - ) -elif dpddata[0] == "lut": - scalefactor = dpddata[1] - lut = dpddata[2] - logging.info( - "TX gain {}, RX gain {}, LUT scalefactor {}," - " LUT {}, digital_gain {}".format( - tx_gain, rx_gain, scalefactor, lut, digital_gain - ) - ) -else: - logging.error("Unknown dpd data format {}".format(dpddata[0])) - -tx_agc = TX_Agc.TX_Agc(adapt, c) - -# Automatic Gain Control -agc = Agc.Agc(meas, adapt, c) -agc.run() - -paths = natsort.natsorted(glob.glob(searchpath + "/*.pkl")) -print(paths) - -for i, path in enumerate(paths): - print(i, path) - adapt.load(path) - dpddata_after = adapt.get_predistorter() - - coefs_am, coefs_pm = model.reset_coefs() - adapt.set_predistorter(("poly", coefs_am, coefs_pm)) - print("Loaded configuration without pre-distortion") +filename = cli_args.file - raw_input("Key for pre-distortion ") - adapt.set_predistorter(dpddata_after) - print("Pre-distortion done") +adapt = Adapt(port_rc, coef_path) - raw_input("Key for next ") +print("Loading and applying DPD settings from {}".format(filename)) +adapt.load(filename) # The MIT License (MIT) # |