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authorMatthias P. Braendli <matthias.braendli@mpb.li>2018-12-04 16:45:58 +0100
committerMatthias P. Braendli <matthias.braendli@mpb.li>2018-12-04 16:45:58 +0100
commit5cf52c74e9eb6bf8a82af4509ff3eb5106f928f9 (patch)
treea7edc1dfd2b2f4469f4dc4d760fdfa83a25fa710 /python/dpd/Symbol_align.py
parentd5cbe10c0e2298b0e40161607a3da158249bdb82 (diff)
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Rework GUI and DPDCE
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diff --git a/python/dpd/Symbol_align.py b/python/dpd/Symbol_align.py
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+# -*- coding: utf-8 -*-
+#
+# DPD Computation Engine, Modulation Error Rate.
+#
+# 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 scipy
+import matplotlib
+
+matplotlib.use('agg')
+import matplotlib.pyplot as plt
+
+
+def _remove_outliers(x, stds=5):
+ deviation_from_mean = np.abs(x - np.mean(x))
+ inlier_idxs = deviation_from_mean < stds * np.std(x)
+ x = x[inlier_idxs]
+ return x
+
+
+def _calc_delta_angle(fft):
+ # Introduce invariance against carrier
+ angles = np.angle(fft) % (np.pi / 2.)
+
+ # Calculate Angle difference and compensate jumps
+ deltas_angle = np.diff(angles)
+ deltas_angle[deltas_angle > np.pi / 4.] = \
+ deltas_angle[deltas_angle > np.pi / 4.] - np.pi / 2.
+ deltas_angle[-deltas_angle > np.pi / 4.] = \
+ deltas_angle[-deltas_angle > np.pi / 4.] + np.pi / 2.
+ deltas_angle = _remove_outliers(deltas_angle)
+
+ delta_angle = np.mean(deltas_angle)
+
+ return delta_angle
+
+
+class Symbol_align:
+ """
+ Find the phase offset to the start of the DAB symbols in an
+ unaligned dab signal.
+ """
+
+ def __init__(self, c, plot=False):
+ self.c = c
+ self.plot = plot
+ pass
+
+ def _calc_offset_to_first_symbol_without_prefix(self, tx):
+ tx_orig = tx[0:-self.c.T_U]
+ tx_cut_prefix = tx[self.c.T_U:]
+
+ tx_product = np.abs(tx_orig - tx_cut_prefix)
+ tx_product_avg = np.correlate(
+ tx_product,
+ np.ones(self.c.T_C),
+ mode='valid')
+ tx_product_avg_min_filt = \
+ scipy.ndimage.filters.minimum_filter1d(
+ tx_product_avg,
+ int(1.5 * self.c.T_S)
+ )
+ peaks = np.ravel(np.where(tx_product_avg == tx_product_avg_min_filt))
+
+ offset = peaks[np.argmin([tx_product_avg[peak] for peak in peaks])]
+
+ if self.plot and self.c.plot_location is not None:
+ dt = datetime.datetime.now().isoformat()
+ fig_path = self.c.plot_location + "/" + dt + "_Symbol_align.png"
+
+ fig = plt.figure(figsize=(9, 9))
+
+ ax = fig.add_subplot(4, 1, 1)
+ ax.plot(tx_product)
+ ylim = ax.get_ylim()
+ for peak in peaks:
+ ax.plot((peak, peak), (ylim[0], ylim[1]))
+ if peak == offset:
+ ax.text(peak, ylim[0] + 0.3 * np.diff(ylim), "offset", rotation=90)
+ else:
+ ax.text(peak, ylim[0] + 0.2 * np.diff(ylim), "peak", rotation=90)
+ ax.set_xlabel("Sample")
+ ax.set_ylabel("Conj. Product")
+ ax.set_title("Difference with shifted self")
+
+ ax = fig.add_subplot(4, 1, 2)
+ ax.plot(tx_product_avg)
+ ylim = ax.get_ylim()
+ for peak in peaks:
+ ax.plot((peak, peak), (ylim[0], ylim[1]))
+ if peak == offset:
+ ax.text(peak, ylim[0] + 0.3 * np.diff(ylim), "offset", rotation=90)
+ else:
+ ax.text(peak, ylim[0] + 0.2 * np.diff(ylim), "peak", rotation=90)
+ ax.set_xlabel("Sample")
+ ax.set_ylabel("Conj. Product")
+ ax.set_title("Moving Average")
+
+ ax = fig.add_subplot(4, 1, 3)
+ ax.plot(tx_product_avg_min_filt)
+ ylim = ax.get_ylim()
+ for peak in peaks:
+ ax.plot((peak, peak), (ylim[0], ylim[1]))
+ if peak == offset:
+ ax.text(peak, ylim[0] + 0.3 * np.diff(ylim), "offset", rotation=90)
+ else:
+ ax.text(peak, ylim[0] + 0.2 * np.diff(ylim), "peak", rotation=90)
+ ax.set_xlabel("Sample")
+ ax.set_ylabel("Conj. Product")
+ ax.set_title("Min Filter")
+
+ ax = fig.add_subplot(4, 1, 4)
+ tx_product_crop = tx_product[peaks[0] - 50:peaks[0] + 50]
+ x = range(tx_product.shape[0])[peaks[0] - 50:peaks[0] + 50]
+ ax.plot(x, tx_product_crop)
+ ylim = ax.get_ylim()
+ ax.plot((peaks[0], peaks[0]), (ylim[0], ylim[1]))
+ ax.set_xlabel("Sample")
+ ax.set_ylabel("Conj. Product")
+ ax.set_title("Difference with shifted self")
+
+ fig.tight_layout()
+ fig.savefig(fig_path)
+ plt.close(fig)
+
+ # "offset" measures where the shifted signal matches the
+ # original signal. Therefore we have to subtract the size
+ # of the shift to find the offset of the symbol start.
+ return (offset + self.c.T_C) % self.c.T_S
+
+ def _delta_angle_to_samples(self, angle):
+ return - angle / self.c.phase_offset_per_sample
+
+ def _calc_sample_offset(self, sig):
+ assert sig.shape[0] == self.c.T_U, \
+ "Input length is not a Symbol without cyclic prefix"
+
+ fft = np.fft.fftshift(np.fft.fft(sig))
+ fft_crop = np.delete(fft[self.c.FFT_start:self.c.FFT_end], self.c.FFT_delete)
+ delta_angle = _calc_delta_angle(fft_crop)
+ delta_sample = self._delta_angle_to_samples(delta_angle)
+ delta_sample_int = np.round(delta_sample).astype(int)
+ error = np.abs(delta_sample_int - delta_sample)
+ if error > 0.1:
+ raise RuntimeError("Could not calculate " \
+ "sample offset. Error {}".format(error))
+ return delta_sample_int
+
+ def calc_offset(self, tx):
+ """Calculate the offset the first symbol"""
+ off_sym = self._calc_offset_to_first_symbol_without_prefix(
+ tx)
+ off_sam = self._calc_sample_offset(
+ tx[off_sym:off_sym + self.c.T_U])
+ off = (off_sym + off_sam) % self.c.T_S
+
+ assert self._calc_sample_offset(tx[off:off + self.c.T_U]) == 0, \
+ "Failed to calculate offset"
+ return off
+
+ def crop_symbol_without_cyclic_prefix(self, tx):
+ off = self.calc_offset(tx)
+ return tx[
+ off:
+ off + self.c.T_U
+ ]
+
+# 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.