aboutsummaryrefslogtreecommitdiffstats
path: root/dpd/main.py
diff options
context:
space:
mode:
authorMatthias P. Braendli <matthias.braendli@mpb.li>2018-05-14 11:03:12 +0200
committerMatthias P. Braendli <matthias.braendli@mpb.li>2018-05-14 11:03:12 +0200
commit6abb6defb379880000a7a8bb2021537e4ca53007 (patch)
tree0eed2c0091b8a77c68472a81b365865f913808b8 /dpd/main.py
parent1890439e8786feaaf4fa6612289812984a0c75e9 (diff)
downloaddabmod-6abb6defb379880000a7a8bb2021537e4ca53007.tar.gz
dabmod-6abb6defb379880000a7a8bb2021537e4ca53007.tar.bz2
dabmod-6abb6defb379880000a7a8bb2021537e4ca53007.zip
DPDCE: disable tx gain agc by default
Diffstat (limited to 'dpd/main.py')
-rwxr-xr-xdpd/main.py13
1 files changed, 10 insertions, 3 deletions
diff --git a/dpd/main.py b/dpd/main.py
index f17d7df..2d9426b 100755
--- a/dpd/main.py
+++ b/dpd/main.py
@@ -57,6 +57,9 @@ parser.add_argument('-i', '--iterations', default=10, type=int,
parser.add_argument('-L', '--lut',
help='Use lookup table instead of polynomial predistorter',
action="store_true")
+parser.add_argument('--enable-txgain-agc',
+ help='Enable the TX gain AGC',
+ action="store_true")
parser.add_argument('--plot',
help='Enable all plots, to be more selective choose plots in GlobalConfig.py',
action="store_true")
@@ -113,7 +116,7 @@ else:
dt = datetime.datetime.now().isoformat()
logging.basicConfig(format='%(asctime)s - %(module)s - %(levelname)s - %(message)s',
datefmt='%Y-%m-%d %H:%M:%S',
- level=logging.DEBUG)
+ level=logging.INFO)
logging_path = None
logging.info("DPDCE starting up with options: {}".format(cli_args))
@@ -213,7 +216,11 @@ if cli_args.measure:
#tx_shoulder_tuple = MS.average_shoulders(txframe_aligned)
sys.exit(0)
-tx_agc = TX_Agc(adapt, c)
+# Disable TXGain AGC by default, so that the experiments are controlled
+# better.
+tx_agc = None
+if cli_args.enable_txgain_agc:
+ tx_agc = TX_Agc(adapt, c)
state = 'report'
i = 0
@@ -225,7 +232,7 @@ while i < num_iter:
if state == 'measure':
# Get Samples and check gain
txframe_aligned, tx_ts, rxframe_aligned, rx_ts, rx_median = meas.get_samples()
- if tx_agc.adapt_if_necessary(txframe_aligned):
+ if tx_agc and tx_agc.adapt_if_necessary(txframe_aligned):
continue
# Extract usable data from measurement