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+# -*- coding: utf-8 -*-
+
+import datetime
+import os
+import logging
+logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename)
+
+import numpy as np
+import scipy
+import matplotlib
+matplotlib.use('agg')
+import matplotlib.pyplot as plt
+import src.subsample_align as sa
+import src.phase_align as pa
+from scipy import signal
+
+class Dab_Util:
+ """Collection of methods that can be applied to an array
+ complex IQ samples of a DAB signal
+ """
+ def __init__(self, sample_rate):
+ """
+ :param sample_rate: sample rate [sample/sec] to use for calculations
+ """
+ self.sample_rate = sample_rate
+ self.dab_bandwidth = 1536000 #Bandwidth of a dab signal
+ self.frame_ms = 96 #Duration of a Dab frame
+
+ def lag(self, sig_orig, sig_rec):
+ """
+ Find lag between two signals
+ Args:
+ sig_orig: The signal that has been sent
+ sig_rec: The signal that has been recored
+ """
+ off = sig_rec.shape[0]
+ c = np.abs(signal.correlate(sig_orig, sig_rec))
+
+ if logging.getLogger().getEffectiveLevel() == logging.DEBUG:
+ dt = datetime.datetime.now().isoformat()
+ corr_path = (logging_path + "/" + dt + "_tx_rx_corr.pdf")
+ plt.plot(c, label="corr")
+ plt.legend()
+ plt.savefig(corr_path)
+ plt.clf()
+
+ return np.argmax(c) - off + 1
+
+ def lag_upsampling(self, sig_orig, sig_rec, n_up):
+ if n_up != 1:
+ sig_orig_up = signal.resample(sig_orig, sig_orig.shape[0] * n_up)
+ sig_rec_up = signal.resample(sig_rec, sig_rec.shape[0] * n_up)
+ else:
+ sig_orig_up = sig_orig
+ sig_rec_up = sig_rec
+ l = self.lag(sig_orig_up, sig_rec_up)
+ l_orig = float(l) / n_up
+ return l_orig
+
+ def subsample_align_upsampling(self, sig1, sig2, n_up=32):
+ """
+ Returns an aligned version of sig1 and sig2 by cropping and subsample alignment
+ Using upsampling
+ """
+ assert(sig1.shape[0] == sig2.shape[0])
+
+ if sig1.shape[0] % 2 == 1:
+ sig1 = sig1[:-1]
+ sig2 = sig2[:-1]
+
+ sig1_up = signal.resample(sig1, sig1.shape[0] * n_up)
+ sig2_up = signal.resample(sig2, sig2.shape[0] * n_up)
+
+ off_meas = self.lag_upsampling(sig2_up, sig1_up, n_up=1)
+ off = int(abs(off_meas))
+
+ if off_meas > 0:
+ sig1_up = sig1_up[:-off]
+ sig2_up = sig2_up[off:]
+ elif off_meas < 0:
+ sig1_up = sig1_up[off:]
+ sig2_up = sig2_up[:-off]
+
+ sig1 = signal.resample(sig1_up, sig1_up.shape[0] / n_up).astype(np.complex64)
+ sig2 = signal.resample(sig2_up, sig2_up.shape[0] / n_up).astype(np.complex64)
+ return sig1, sig2
+
+ def subsample_align(self, sig1, sig2):
+ """
+ Returns an aligned version of sig1 and sig2 by cropping and subsample alignment
+ """
+
+ if logging.getLogger().getEffectiveLevel() == logging.DEBUG:
+ dt = datetime.datetime.now().isoformat()
+ fig_path = logging_path + "/" + dt + "_sync_raw.pdf"
+
+ fig, axs = plt.subplots(2)
+ axs[0].plot(np.abs(sig1[:128]), label="TX Frame")
+ axs[0].plot(np.abs(sig2[:128]), label="RX Frame")
+ axs[0].set_title("Raw Data")
+ axs[0].set_ylabel("Amplitude")
+ axs[0].set_xlabel("Samples")
+ axs[0].legend(loc=4)
+
+ axs[1].plot(np.real(sig1[:128]), label="TX Frame")
+ axs[1].plot(np.real(sig2[:128]), label="RX Frame")
+ axs[1].set_title("Raw Data")
+ axs[1].set_ylabel("Real Part")
+ axs[1].set_xlabel("Samples")
+ axs[1].legend(loc=4)
+
+ fig.tight_layout()
+ fig.savefig(fig_path)
+ fig.clf()
+
+ logging.debug("Sig1_orig: %d %s, Sig2_orig: %d %s" % (len(sig1), sig1.dtype, len(sig2), sig2.dtype))
+ off_meas = self.lag_upsampling(sig2, sig1, n_up=1)
+ off = int(abs(off_meas))
+
+ if off_meas > 0:
+ sig1 = sig1[:-off]
+ sig2 = sig2[off:]
+ elif off_meas < 0:
+ sig1 = sig1[off:]
+ sig2 = sig2[:-off]
+
+ if off % 2 == 1:
+ sig1 = sig1[:-1]
+ sig2 = sig2[:-1]
+
+ if logging.getLogger().getEffectiveLevel() == logging.DEBUG:
+ dt = datetime.datetime.now().isoformat()
+ fig_path = logging_path + "/" + dt + "_sync_sample_aligned.pdf"
+
+ fig, axs = plt.subplots(2)
+ axs[0].plot(np.abs(sig1[:128]), label="TX Frame")
+ axs[0].plot(np.abs(sig2[:128]), label="RX Frame")
+ axs[0].set_title("Sample Aligned Data")
+ axs[0].set_ylabel("Amplitude")
+ axs[0].set_xlabel("Samples")
+ axs[0].legend(loc=4)
+
+ axs[1].plot(np.real(sig1[:128]), label="TX Frame")
+ axs[1].plot(np.real(sig2[:128]), label="RX Frame")
+ axs[1].set_ylabel("Real Part")
+ axs[1].set_xlabel("Samples")
+ axs[1].legend(loc=4)
+
+ fig.tight_layout()
+ fig.savefig(fig_path)
+ fig.clf()
+
+
+ sig2 = sa.subsample_align(sig2, sig1)
+
+ if logging.getLogger().getEffectiveLevel() == logging.DEBUG:
+ dt = datetime.datetime.now().isoformat()
+ fig_path = logging_path + "/" + dt + "_sync_subsample_aligned.pdf"
+
+ fig, axs = plt.subplots(2)
+ axs[0].plot(np.abs(sig1[:128]), label="TX Frame")
+ axs[0].plot(np.abs(sig2[:128]), label="RX Frame")
+ axs[0].set_title("Subsample Aligned")
+ axs[0].set_ylabel("Amplitude")
+ axs[0].set_xlabel("Samples")
+ axs[0].legend(loc=4)
+
+ axs[1].plot(np.real(sig1[:128]), label="TX Frame")
+ axs[1].plot(np.real(sig2[:128]), label="RX Frame")
+ axs[1].set_ylabel("Real Part")
+ axs[1].set_xlabel("Samples")
+ axs[1].legend(loc=4)
+
+ fig.tight_layout()
+ fig.savefig(fig_path)
+ fig.clf()
+
+ sig2 = pa.phase_align(sig2, sig1)
+
+ if logging.getLogger().getEffectiveLevel() == logging.DEBUG:
+ dt = datetime.datetime.now().isoformat()
+ fig_path = logging_path + "/" + dt + "_sync_phase_aligned.pdf"
+
+ fig, axs = plt.subplots(2)
+ axs[0].plot(np.abs(sig1[:128]), label="TX Frame")
+ axs[0].plot(np.abs(sig2[:128]), label="RX Frame")
+ axs[0].set_title("Phase Aligned")
+ axs[0].set_ylabel("Amplitude")
+ axs[0].set_xlabel("Samples")
+ axs[0].legend(loc=4)
+
+ axs[1].plot(np.real(sig1[:128]), label="TX Frame")
+ axs[1].plot(np.real(sig2[:128]), label="RX Frame")
+ axs[1].set_ylabel("Real Part")
+ axs[1].set_xlabel("Samples")
+ axs[1].legend(loc=4)
+
+ fig.tight_layout()
+ fig.savefig(fig_path)
+ fig.clf()
+
+ logging.debug("Sig1_cut: %d %s, Sig2_cut: %d %s, off: %d" % (len(sig1), sig1.dtype, len(sig2), sig2.dtype, off))
+ return sig1, sig2
+
+ def fromfile(self, filename, offset=0, length=None):
+ if length is None:
+ return np.memmap(filename, dtype=np.complex64, mode='r', offset=64/8*offset)
+ else:
+ return np.memmap(filename, dtype=np.complex64, mode='r', offset=64/8*offset, shape=length)
+
+
+# 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.
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