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authorandreas128 <Andreas>2017-04-01 10:17:06 +0100
committerandreas128 <Andreas>2017-04-01 10:17:06 +0100
commit6243a4fac50a9c8690e13c2df65c058e69fdcae5 (patch)
tree8e562b11f06a782974bd4d34b2f58005a3903fda /doc
parentfce4eab342a5e4bfad01c5f7e704ece35bd718bc (diff)
parent8a5b4f23dec7d22e4f2e38cb7ef7223438461df8 (diff)
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Merge branch 'next' into next_memless
Diffstat (limited to 'doc')
-rw-r--r--doc/example.ini13
-rwxr-xr-xdoc/time-freq-plot.py77
2 files changed, 85 insertions, 5 deletions
diff --git a/doc/example.ini b/doc/example.ini
index 0659813..f8cec36 100644
--- a/doc/example.ini
+++ b/doc/example.ini
@@ -141,13 +141,16 @@ output=uhd
[fileoutput]
; Two output formats are supported: In the default mode,
-; the file output writes I/Q float values (i.e. complex float)
-; to the file. The I and Q samples can take values up to
-; 100000 in absolute magnitude with gainmode FIX.
-; With gainmode VAR, they should never exceed 50000.
-; With gainmode MAX, thet are limited to 32767.
+; the file output writes I/Q float values (i.e. complex
+; float) to the file. The I and Q samples can take values up
+; to 810000 in absolute magnitude with gainmode FIX. With
+; gainmode VAR and FIX, they should never exceed 50000.
;format=complexf
;
+; When the format is set to complexf_normalised the maximal
+; amplitude written to a file, is the digital gain +-10%.
+;format=complexf_normalised
+;
; When the format is set to s8, the output writes I/Q 8-bit
; signed integers, where the magnitude is multiplied by 128/50000
; effectively mapping the gainmode VAR range of -50000 -- 50000
diff --git a/doc/time-freq-plot.py b/doc/time-freq-plot.py
new file mode 100755
index 0000000..6ece564
--- /dev/null
+++ b/doc/time-freq-plot.py
@@ -0,0 +1,77 @@
+#!/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()