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+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+#
+# Print scope and spectrum from ODR-DabMod I/Q file
+#
+# The MIT License (MIT)
+#
+# Copyright (c) 2017 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.
+import sys
+import matplotlib.pyplot as plt
+import numpy as np
+
+rate=2048000
+# T = 1/2048000 s
+# NULL symbol is 2656 T (about 1.3ms) long.
+T_NULL = 2656
+# Full transmission frame in TM1 is 96ms = 196608 T.
+T_TF = 196608
+
+num_skip_samples = 8 * T_TF
+num_analyse_samples = 2 * T_TF
+
+if len(sys.argv) < 2:
+ print("Specify .iq file name")
+ print("Expected format: complex float I/Q, 2048000 Sps")
+ print("The input file must contain at least 10 transmission frames,")
+ print("i.e. {} samples = {} seconds".format(T_TF * 10, T_TF * 10.0 / rate))
+ sys.exit(1)
+
+fd = open(sys.argv[1], 'rb')
+
+# The IQ files potentially have zero samples in the beginning, we need
+# to skip a few transmission frames
+
+
+source_data = np.fromfile(file=fd, dtype=np.complex64, count=num_skip_samples + num_analyse_samples)
+
+print("Read in {} samples".format(len(source_data)))
+
+source_data = source_data[num_skip_samples:]
+source_data_time = np.linspace(0, num_analyse_samples/rate, len(source_data))
+
+print("Signal power: {} of {} samples".format(np.sum(np.abs(source_data**2)), len(source_data)))
+
+fft_size = 4096
+
+plt.figure(figsize=(10,8))
+plt.subplot(211)
+plt.title("Real part of signal")
+plt.plot(source_data_time, np.real(source_data))
+
+signal_spectrum = np.abs(np.fft.fftshift(np.fft.fft(source_data[T_NULL:], fft_size)))
+freqs = np.fft.fftshift(np.fft.fftfreq(fft_size, d=1./rate))
+
+plt.subplot(212)
+plt.title("Spectrum of {} samples after the NULL symbol".format(fft_size))
+plt.semilogy(freqs, signal_spectrum)
+
+plt.show()