# -*- coding: utf-8 -*- # # DPD Calculation Engine, model implementation for Amplitude and not Phase # # 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 def check_input_get_next_coefs(tx_dpd, rx_received): is_float32 = lambda x: (isinstance(x, np.ndarray) and x.dtype == np.float32 and x.flags.contiguous) assert is_float32(tx_dpd), \ "tx_dpd is not float32 but {}".format(tx_dpd[0].dtype) assert is_float32(rx_received), \ "rx_received is not float32 but {}".format(tx_dpd[0].dtype) class Model_AM: """Calculates new coefficients using the measurement and the previous coefficients""" def __init__(self, c, learning_rate_am=0.1, plot=False): self.c = c self.learning_rate_am = learning_rate_am self.plot = plot def _plot(self, tx_dpd, rx_received, coefs_am, coefs_am_new): if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot: tx_range, rx_est = self.calc_line(coefs_am, 0, 0.6) tx_range_new, rx_est_new = self.calc_line(coefs_am_new, 0, 0.6) dt = datetime.datetime.now().isoformat() fig_path = logging_path + "/" + dt + "_Model_AM.svg" sub_rows = 1 sub_cols = 1 fig = plt.figure(figsize=(sub_cols * 6, sub_rows / 2. * 6)) i_sub = 0 i_sub += 1 ax = plt.subplot(sub_rows, sub_cols, i_sub) ax.plot(tx_range, rx_est, label="Estimated TX", alpha=0.3, color="gray") ax.plot(tx_range_new, rx_est_new, label="New Estimated TX", color="red") ax.scatter(tx_dpd, rx_received, label="Binned Data", color="blue", s=1) ax.set_title("Model_AM") ax.set_xlabel("TX Amplitude") ax.set_ylabel("RX Amplitude") ax.legend(loc=4) fig.tight_layout() fig.savefig(fig_path) plt.close(fig) def poly(self, sig): return np.array([sig ** i for i in range(1, 6)]).T def fit_poly(self, tx_abs, rx_abs): return np.linalg.lstsq(self.poly(rx_abs), tx_abs)[0] def calc_line(self, coefs, min_amp, max_amp): rx_range = np.linspace(min_amp, max_amp) tx_est = np.sum(self.poly(rx_range) * coefs, axis=1) return tx_est, rx_range def get_next_coefs(self, tx_dpd, rx_received, coefs_am): check_input_get_next_coefs(tx_dpd, rx_received) coefs_am_new = self.fit_poly(tx_dpd, rx_received) self._plot(tx_dpd, rx_received, coefs_am, coefs_am_new) return coefs_am_new # 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.