Merge branch 'next' into outputRefactoring

1 files changed, 12 insertions, 135 deletions

diff --git a/dpd/apply_adapt_dumps.py b/dpd/apply_adapt_dumps.py
index 6b15aff..20bc013 100755
--- a/dpd/apply_adapt_dumps.py
+++ b/dpd/apply_adapt_dumps.py
@@ -6,173 +6,50 @@
 # 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
 import src.Adapt as Adapt
-import src.RX_Agc as Agc
-import src.TX_Agc as TX_Agc
 import argparse
 
-import src.Const
-import src.Symbol_align
-import src.Measure_Shoulders
-import src.MER
-
 parser = argparse.ArgumentParser(
-    description="DPD Computation Engine for ODR-DabMod")
+        description="Load pkl dumps DPD settings into ODR-DabMod")
 parser.add_argument('--port', default=50055, type=int,
                     help='port of DPD server to connect to (default: 50055)',
                     required=False)
 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)
+filename = cli_args.file
 
-for i, path in enumerate(paths):
-    print(i, path)
-    adapt.load(path)
-    dpddata_after = adapt.get_predistorter()
+# No need to initialise a GlobalConfig since adapt only needs this one field
+class DummyConfig:
+    def __init__(self):
+        self.plot_location = None
 
-    coefs_am, coefs_pm = model.reset_coefs()
-    adapt.set_predistorter(("poly", coefs_am, coefs_pm))
-    print("Loaded configuration without pre-distortion")
+c = DummyConfig()
 
-    raw_input("Key for pre-distortion ")
-    adapt.set_predistorter(dpddata_after)
-    print("Pre-distortion done")
+adapt = Adapt.Adapt(c, 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)
 #