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| -rw-r--r-- | dpd/src/Model_AM.py | 115 |
1 files changed, 115 insertions, 0 deletions
diff --git a/dpd/src/Model_AM.py b/dpd/src/Model_AM.py new file mode 100644 index 0000000..5281dde --- /dev/null +++ b/dpd/src/Model_AM.py @@ -0,0 +1,115 @@ +# -*- 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 +from sklearn import linear_model + + +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(tx_dpd), \ + "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=0.1) + ax.set_title("Model_AM") + ax.set_xlabel("RX Amplitude") + ax.set_ylabel("TX Amplitude") + ax.legend(loc=4) + + fig.tight_layout() + fig.savefig(fig_path) + fig.clf() + + 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. |