# -*- coding: utf-8 -*- import datetime import os import logging logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename) from pynverse import inversefunc import numpy as np import matplotlib matplotlib.use('agg') import matplotlib.pyplot as plt from sklearn.linear_model import Ridge class Model: """Calculates new coefficients using the measurement and the old coefficients""" def __init__(self, coefs): self.coefs = coefs self.coefs_history = [coefs,] self.mses = [0,] self.errs = [0,] def get_next_coefs(self, txframe_aligned, rxframe_aligned): dt = datetime.datetime.now().isoformat() txframe_aligned.tofile(logging_path + "/txframe_" + dt + ".iq") rxframe_aligned.tofile(logging_path + "/rxframe_" + dt + ".iq") rx_abs = np.abs(rxframe_aligned) rx_A = np.vstack([rx_abs, rx_abs**3, rx_abs**5, rx_abs**7, rx_abs**9, ]).T rx_dpd = np.sum(rx_A * self.coefs, axis=1) rx_dpd = rx_dpd * ( np.median(np.abs(txframe_aligned)) / np.median(np.abs(rx_dpd))) err = rx_dpd - np.abs(txframe_aligned) self.errs.append(np.mean(np.abs(err**2))) a_delta = np.linalg.lstsq(rx_A, err)[0] new_coefs = self.coefs - 0.1 * a_delta new_coefs = new_coefs * (self.coefs[0] / new_coefs[0]) logging.debug("a_delta {}".format(a_delta)) logging.debug("new coefs {}".format(new_coefs)) tx_abs = np.abs(rxframe_aligned) tx_A = np.vstack([tx_abs, tx_abs**3, tx_abs**5, tx_abs**7, tx_abs**9, ]).T tx_dpd = np.sum(tx_A * new_coefs, axis=1) tx_dpd_norm = tx_dpd * ( np.median(np.abs(txframe_aligned)) / np.median(np.abs(tx_dpd))) rx_A_complex = np.vstack([rxframe_aligned, rxframe_aligned * rx_abs**2, rxframe_aligned * rx_abs**4, rxframe_aligned * rx_abs**6, rxframe_aligned * rx_abs**8, ]).T rx_post_distored = np.sum(rx_A_complex * self.coefs, axis=1) rx_post_distored = rx_post_distored * ( np.median(np.abs(txframe_aligned)) / np.median(np.abs(rx_post_distored))) mse = np.mean(np.abs((txframe_aligned - rx_post_distored)**2)) logging.debug("MSE: {}".format(mse)) self.mses.append(mse) def dpd(tx): tx_abs = np.abs(tx) tx_A_complex = np.vstack([tx, tx * tx_abs**2, tx * tx_abs**4, tx * tx_abs**6, tx * tx_abs**8, ]).T tx_dpd = np.sum(tx_A_complex * self.coefs, axis=1) return tx_dpd tx_inverse_dpd = inversefunc(dpd, y_values=txframe_aligned[:128]) tx_inverse_dpd = tx_inverse_dpd * ( np.median(np.abs(txframe_aligned)) / np.median(np.abs(tx_inverse_dpd)) ) if logging.getLogger().getEffectiveLevel() == logging.DEBUG: logging.debug("txframe: min %f, max %f, median %f" % (np.min(np.abs(txframe_aligned)), np.max(np.abs(txframe_aligned)), np.median(np.abs(txframe_aligned)) )) logging.debug("rxframe: min %f, max %f, median %f" % (np.min(np.abs(rxframe_aligned)), np.max(np.abs(rxframe_aligned)), np.median(np.abs(rxframe_aligned)) )) dt = datetime.datetime.now().isoformat() fig_path = logging_path + "/" + dt + "_Model.pdf" fig, axs = plt.subplots(7, figsize=(6,3*6)) ax = axs[0] ax.plot(np.abs(txframe_aligned[:128]), label="TX sent", linestyle=":") ax.plot(np.abs(tx_inverse_dpd[:128]), label="TX inverse dpd", color="green") ax.plot(np.abs(rxframe_aligned[:128]), label="RX received", color="red") ax.set_title("Synchronized Signals of Iteration {}".format(len(self.coefs_history))) ax.set_xlabel("Samples") ax.set_ylabel("Amplitude") ax.legend(loc=4) ax = axs[1] ax.plot(np.real(txframe_aligned[:128]), label="TX sent", linestyle=":") ax.plot(np.real(tx_inverse_dpd[:128]), label="TX inverse dpd", color="green") ax.plot(np.real(rxframe_aligned[:128]), label="RX received", color="red") ax.set_title("Synchronized Signals") ax.set_xlabel("Samples") ax.set_ylabel("Real Part") ax.legend(loc=4) ax = axs[2] ax.scatter( np.abs(txframe_aligned[:1024]), np.abs(rxframe_aligned[:1024]), s = 0.1) ax.set_title("Amplifier Characteristic") ax.set_xlabel("TX Amplitude") ax.set_ylabel("RX Amplitude") ax = axs[3] angle_diff_rad = (( (np.angle(txframe_aligned[:1024]) - np.angle(rxframe_aligned[:1024]) + np.pi) % (2 * np.pi)) - np.pi ) ax.scatter( np.abs(txframe_aligned[:1024]), angle_diff_rad * 180 / np.pi, s = 0.1 ) ax.set_title("Amplifier Characteristic") ax.set_xlabel("TX Amplitude") ax.set_ylabel("Phase Difference [deg]") ax = axs[4] ax.plot(np.abs(txframe_aligned[:128]), label="TX Frame", linestyle=":", linewidth=0.5) ax.plot(np.abs(rxframe_aligned[:128]), label="RX Frame", linestyle="--", linewidth=0.5) ax.plot(np.abs(rx_dpd[:128]), label="RX DPD Frame", linestyle="-.", linewidth=0.5) ax.plot(np.abs(tx_dpd_norm[:128]), label="TX DPD Frame Norm", linestyle="-.", linewidth=0.5) ax.legend(loc=4) ax.set_title("RX DPD") ax.set_xlabel("Samples") ax.set_ylabel("Amplitude") ax = axs[5] coefs_history = np.array(self.coefs_history) for idx, coef_hist in enumerate(coefs_history.T): ax.plot(coef_hist, label="Coef {}".format(idx), linewidth=0.5) ax.legend(loc=4) ax.set_title("Coefficient History") ax.set_xlabel("Iterations") ax.set_ylabel("Coefficient Value") ax = axs[6] coefs_history = np.array(self.coefs_history) ax.plot(self.mses, label="MSE") ax.plot(self.errs, label="ERR") ax.legend(loc=4) ax.set_title("MSE History") ax.set_xlabel("Iterations") ax.set_ylabel("MSE") fig.tight_layout() fig.savefig(fig_path) fig.clf() self.coefs = new_coefs self.coefs_history.append(self.coefs) return self.coefs # 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.