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# -*- coding: utf-8 -*-
#
# DPD Computation 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
import numpy as np
import matplotlib.pyplot as plt
def is_npfloat32(array):
assert isinstance(array, np.ndarray), type(array)
assert array.dtype == np.float32, array.dtype
assert array.flags.contiguous
assert not any(np.isnan(array))
def check_input_get_next_coefs(tx_dpd, rx_received):
is_npfloat32(tx_dpd)
is_npfloat32(rx_received)
def poly(sig):
return np.array([sig ** i for i in range(1, 6)]).T
def fit_poly(tx_abs, rx_abs):
return np.linalg.lstsq(poly(rx_abs), tx_abs, rcond=None)[0]
def calc_line(coefs, min_amp, max_amp):
rx_range = np.linspace(min_amp, max_amp)
tx_est = np.sum(poly(rx_range) * coefs, axis=1)
return tx_est, rx_range
class Model_AM:
"""Calculates new coefficients using the measurement and the previous
coefficients"""
def __init__(self, c, learning_rate_am=1):
self.c = c
self.learning_rate_am = learning_rate_am
self._plot_data = None
def plot(self, plot_location, title):
if self._plot_data is not None:
tx_dpd, rx_received, coefs_am, coefs_am_new = self._plot_data
tx_range, rx_est = calc_line(coefs_am, 0, 0.6)
tx_range_new, rx_est_new = calc_line(coefs_am_new, 0, 0.6)
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 {}".format(title))
ax.set_xlabel("TX Amplitude")
ax.set_ylabel("RX Amplitude")
ax.set_xlim(-0.5, 1.5)
ax.legend(loc=4)
fig.tight_layout()
fig.savefig(plot_location)
plt.close(fig)
def get_next_coefs(self, tx_dpd, rx_received, coefs_am):
"""Calculate the next AM/AM coefficients using the extracted
statistic of TX and RX amplitude"""
check_input_get_next_coefs(tx_dpd, rx_received)
coefs_am_new = fit_poly(tx_dpd, rx_received)
coefs_am_new = coefs_am + \
self.learning_rate_am * (coefs_am_new - coefs_am)
self._plot_data = (tx_dpd, rx_received, coefs_am, coefs_am_new)
return coefs_am_new
# The MIT License (MIT)
#
# Copyright (c) 2017 Andreas Steger
# Copyright (c) 2018 Matthias P. Braendli
#
# 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.
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