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+# -*- 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.