diff options
| -rwxr-xr-x | dpd/main.py | 33 | ||||
| -rw-r--r-- | dpd/src/Model_Poly.py | 104 |
2 files changed, 117 insertions, 20 deletions
diff --git a/dpd/main.py b/dpd/main.py index e17cd5a..528f59c 100755 --- a/dpd/main.py +++ b/dpd/main.py @@ -42,9 +42,8 @@ import numpy as np import traceback import src.Measure as Measure import src.Model as Model -import src.Model_AM as Model_AM -import src.Model_PM as Model_PM import src.ExtractStatistic as ExtractStatistic +import src.Model_Poly import src.Adapt as Adapt import src.Agc as Agc import src.TX_Agc as TX_Agc @@ -91,15 +90,15 @@ parser.add_argument('-l', '--load-poly', cli_args = parser.parse_args() -port = int(cli_args.port) -port_rc = int(cli_args.rc_port) +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 = int(cli_args.samps) -samplerate = int(cli_args.samplerate) -num_iter = int(cli_args.iterations) +num_req = cli_args.samps +samplerate = cli_args.samplerate +num_iter = cli_args.iterations SA = src.Symbol_align.Symbol_align(samplerate) MER = src.MER.MER(samplerate) @@ -109,19 +108,15 @@ meas = Measure.Measure(samplerate, port, num_req) extStat = ExtractStatistic.ExtractStatistic(c, plot=True) adapt = Adapt.Adapt(port_rc, coef_path) -if cli_args.load_poly: - coefs_am, coefs_pm = adapt.get_coefs() - model = Model.Model(c, SA, MER, coefs_am, coefs_pm, plot=True) -else: - coefs_am, coefs_pm = [[1.0, 0, 0, 0, 0], [0, 0, 0, 0, 0]] - model = Model.Model(c, SA, MER, coefs_am, coefs_pm, plot=True) -model_am = Model_AM.Model_AM(c, plot=True) -model_pm = Model_PM.Model_PM(c, plot=True) -adapt.set_coefs(model.coefs_am, model.coefs_pm) +coefs_am, coefs_pm = adapt.get_coefs() +model_poly = src.Model_Poly.Model_Poly(c, coefs_am, coefs_pm, plot=True) +if not cli_args.load_poly: + coefs_am, coefs_pm = model_poly.get_default_coefs() + +adapt.set_coefs(model_poly.coefs_am, model_poly.coefs_pm) adapt.set_digital_gain(digital_gain) adapt.set_txgain(txgain) adapt.set_rxgain(rxgain) -print(coefs_am) tx_gain = adapt.get_txgain() rx_gain = adapt.get_rxgain() @@ -159,15 +154,13 @@ while i < num_iter: # Model elif state == "model": - coefs_am = model_am.get_next_coefs(tx, rx, coefs_am) - coefs_pm = model_pm.get_next_coefs(tx, phase_diff, coefs_pm) + coefs_am, coefs_pm = model_poly.get_next_coefs(tx, rx, phase_diff) del extStat extStat = ExtractStatistic.ExtractStatistic(c, plot=True) state = "adapt" # Adapt elif state == "adapt": - print(coefs_am) adapt.set_coefs(coefs_am, coefs_pm) state = "measure" i += 1 diff --git a/dpd/src/Model_Poly.py b/dpd/src/Model_Poly.py index e69de29..1faff24 100644 --- a/dpd/src/Model_Poly.py +++ b/dpd/src/Model_Poly.py @@ -0,0 +1,104 @@ +# -*- coding: utf-8 -*- +# +# DPD Calculation Engine, model implementation using polynomial +# +# http://www.opendigitalradio.org +# Licence: The MIT License, see notice at the end of this file + +import datetime +import os +import logging + +logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename) + +import numpy as np +import matplotlib.pyplot as plt +from sklearn import linear_model + +import src.Model_AM as Model_AM +import src.Model_PM as Model_PM + + +def assert_np_float32(x): + assert isinstance(x, np.ndarray) + assert x.dtype == np.float32 + assert x.flags.contiguous + +def _check_input_get_next_coefs(tx_abs, rx_abs, phase_diff): + assert_np_float32(tx_abs) + assert_np_float32(rx_abs) + assert_np_float32(phase_diff) + + assert tx_abs.shape == rx_abs.shape, \ + "tx_abs.shape {}, rx_abs.shape {}".format( + tx_abs.shape, rx_abs.shape) + assert tx_abs.shape == phase_diff.shape, \ + "tx_abs.shape {}, phase_diff.shape {}".format( + tx_abs.shape, phase_diff.shape) + + +class Model_Poly: + """Calculates new coefficients using the measurement and the previous + coefficients""" + + def __init__(self, + c, + coefs_am, + coefs_pm, + learning_rate_am=1.0, + learning_rate_pm=1.0, + plot=False): + assert_np_float32(coefs_am) + assert_np_float32(coefs_pm) + + self.c = c + + self.learning_rate_am = learning_rate_am + self.learning_rate_pm = learning_rate_pm + + self.coefs_am = coefs_am + self.coefs_pm = coefs_pm + + self.model_am = Model_AM.Model_AM(c, plot=True) + self.model_pm = Model_PM.Model_PM(c, plot=True) + + self.plot = plot + + def get_default_coefs(self): + self.coefs_am[:] = 0 + self.coefs_am[0] = 1 + self.coefs_pm[:] = 0 + return self.coefs_am, self.coefs_pm + + def get_next_coefs(self, tx_abs, rx_abs, phase_diff): + _check_input_get_next_coefs(tx_abs, rx_abs, phase_diff) + + coefs_am_new = self.model_am.get_next_coefs(tx_abs, rx_abs, self.coefs_am) + coefs_pm_new = self.model_pm.get_next_coefs(tx_abs, phase_diff, self.coefs_pm) + + self.coefs_am = self.coefs_am + (coefs_am_new - self.coefs_am) * self.learning_rate_am + self.coefs_pm = self.coefs_pm + (coefs_pm_new - self.coefs_pm) * self.learning_rate_pm + + return self.coefs_am, self.coefs_pm + +# The MIT License (MIT) +# +# Copyright (c) 2017 Andreas Steger +# +# Permission is hereby granted, free of charge, to any person obtaining a copy +# of this software and associated documentation files (the "Software"), to deal +# in the Software without restriction, including without limitation the rights +# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +# copies of the Software, and to permit persons to whom the Software is +# furnished to do so, subject to the following conditions: +# +# The above copyright notice and this permission notice shall be included in all +# copies or substantial portions of the Software. +# +# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +# SOFTWARE. |