From 5cf52c74e9eb6bf8a82af4509ff3eb5106f928f9 Mon Sep 17 00:00:00 2001 From: "Matthias P. Braendli" Date: Tue, 4 Dec 2018 16:45:58 +0100 Subject: Rework GUI and DPDCE --- python/dpd/Measure_Shoulders.py | 158 ++++++++++++++++++++++++++++++++++++++++ 1 file changed, 158 insertions(+) create mode 100644 python/dpd/Measure_Shoulders.py (limited to 'python/dpd/Measure_Shoulders.py') diff --git a/python/dpd/Measure_Shoulders.py b/python/dpd/Measure_Shoulders.py new file mode 100644 index 0000000..fd90050 --- /dev/null +++ b/python/dpd/Measure_Shoulders.py @@ -0,0 +1,158 @@ +# -*- coding: utf-8 -*- +# +# DPD Computation Engine, calculate peak to shoulder difference. +# +# http://www.opendigitalradio.org +# Licence: The MIT License, see notice at the end of this file + +import datetime +import os +import logging +import multiprocessing +import numpy as np +import matplotlib.pyplot as plt + + +def plt_next_axis(sub_rows, sub_cols, i_sub): + i_sub += 1 + ax = plt.subplot(sub_rows, sub_cols, i_sub) + return i_sub, ax + + +def plt_annotate(ax, x, y, title=None, legend_loc=None): + ax.set_xlabel(x) + ax.set_ylabel(y) + if title is not None: + ax.set_title(title) + if legend_loc is not None: + ax.legend(loc=legend_loc) + + +def calc_fft_db(signal, offset, c): + fft = np.fft.fftshift(np.fft.fft(signal[offset:offset + c.MS_FFT_size])) + fft_db = 20 * np.log10(np.abs(fft)) + return fft_db + + +def _calc_peak(fft, c): + assert fft.shape == (c.MS_FFT_size,), fft.shape + idxs = (c.MS_peak_start, c.MS_peak_end) + peak = np.mean(fft[idxs[0]:idxs[1]]) + return peak, idxs + + +def _calc_shoulder_hight(fft_db, c): + assert fft_db.shape == (c.MS_FFT_size,), fft_db.shape + idxs_left = (c.MS_shoulder_left_start, c.MS_shoulder_left_end) + idxs_right = (c.MS_shoulder_right_start, c.MS_shoulder_right_end) + + shoulder_left = np.mean(fft_db[idxs_left[0]:idxs_left[1]]) + shoulder_right = np.mean(fft_db[idxs_right[0]:idxs_right[1]]) + + shoulder = np.mean((shoulder_left, shoulder_right)) + return shoulder, (idxs_left, idxs_right) + + +def calc_shoulder(fft, c): + peak = _calc_peak(fft, c)[0] + shoulder = _calc_shoulder_hight(fft, c)[0] + assert (peak >= shoulder), (peak, shoulder) + return peak, shoulder + + +def shoulder_from_sig_offset(arg): + signal, offset, c = arg + fft_db = calc_fft_db(signal, offset, c) + peak, shoulder = calc_shoulder(fft_db, c) + return peak - shoulder, peak, shoulder + + +class Measure_Shoulders: + """Calculate difference between the DAB signal and the shoulder hight in the + power spectrum""" + + def __init__(self, c): + self.c = c + self.plot = c.MS_plot + + def _plot(self, signal): + if self.c.plot_location is None: + return + + dt = datetime.datetime.now().isoformat() + fig_path = self.c.plot_location + "/" + dt + "_sync_subsample_aligned.png" + + fft = calc_fft_db(signal, 100, self.c) + peak, idxs_peak = _calc_peak(fft, self.c) + shoulder, idxs_sh = _calc_shoulder_hight(fft, self.c) + + sub_rows = 1 + sub_cols = 1 + fig = plt.figure(figsize=(sub_cols * 6, sub_rows / 2. * 6)) + i_sub = 0 + + i_sub, ax = plt_next_axis(sub_rows, sub_cols, i_sub) + ax.scatter(np.arange(fft.shape[0]), fft, s=0.1, + label="FFT", + color="red") + ax.plot(idxs_peak, (peak, peak)) + ax.plot(idxs_sh[0], (shoulder, shoulder), color='blue') + ax.plot(idxs_sh[1], (shoulder, shoulder), color='blue') + plt_annotate(ax, "Frequency", "Magnitude [dB]", None, 4) + + ax.text(100, -17, str(calc_shoulder(fft, self.c))) + + ax.set_ylim(-20, 30) + fig.tight_layout() + fig.savefig(fig_path) + plt.close(fig) + + def average_shoulders(self, signal, n_avg=None): + if not self.c.MS_enable: + logging.info("Shoulder Measurement disabled via Const.py") + return None + + assert signal.shape[0] > 4 * self.c.MS_FFT_size + if n_avg is None: + n_avg = self.c.MS_averaging_size + + off_min = 0 + off_max = signal.shape[0] - self.c.MS_FFT_size + offsets = np.linspace(off_min, off_max, num=n_avg, dtype=int) + + args = zip( + [signal, ] * offsets.shape[0], + offsets, + [self.c, ] * offsets.shape[0] + ) + + pool = multiprocessing.Pool(self.c.MS_n_proc) + res = pool.map(shoulder_from_sig_offset, args) + shoulders_diff, shoulders, peaks = zip(*res) + + if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot: + self._plot(signal) + + return np.mean(shoulders_diff), np.mean(shoulders), np.mean(peaks) + +# 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. -- cgit v1.2.3