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authorNao Pross <np@0hm.ch>2021-12-19 02:51:04 +0100
committerNao Pross <np@0hm.ch>2021-12-19 02:51:04 +0100
commitcbf0d8ce166a78e6d05da7253b6272db6f8861eb (patch)
tree1e6d6a7fed6190550de087197986c3a36cda4626 /doc/thesis/figures
parentAdd constellation plots for dynamic model (diff)
downloadFading-cbf0d8ce166a78e6d05da7253b6272db6f8861eb.tar.gz
Fading-cbf0d8ce166a78e6d05da7253b6272db6f8861eb.zip
Add samples for QPSK with hardware
Diffstat (limited to 'doc/thesis/figures')
-rw-r--r--doc/thesis/figures/data/flowgraphs/channel_qpsk_hw_lab.datbin0 -> 13992888 bytes
-rw-r--r--doc/thesis/figures/data/flowgraphs/equalized_qpsk_hw_lab.datbin0 -> 3497888 bytes
-rw-r--r--doc/thesis/figures/data/flowgraphs/locked_qpsk_hw_lab.datbin0 -> 3497832 bytes
-rw-r--r--doc/thesis/figures/data/flowgraphs/synchronized_qpsk_hw_lab.datbin0 -> 3497888 bytes
-rw-r--r--doc/thesis/figures/data/qpsk_hw_lab.py31
5 files changed, 31 insertions, 0 deletions
diff --git a/doc/thesis/figures/data/flowgraphs/channel_qpsk_hw_lab.dat b/doc/thesis/figures/data/flowgraphs/channel_qpsk_hw_lab.dat
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diff --git a/doc/thesis/figures/data/flowgraphs/equalized_qpsk_hw_lab.dat b/doc/thesis/figures/data/flowgraphs/equalized_qpsk_hw_lab.dat
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+++ b/doc/thesis/figures/data/flowgraphs/equalized_qpsk_hw_lab.dat
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diff --git a/doc/thesis/figures/data/flowgraphs/locked_qpsk_hw_lab.dat b/doc/thesis/figures/data/flowgraphs/locked_qpsk_hw_lab.dat
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+++ b/doc/thesis/figures/data/flowgraphs/locked_qpsk_hw_lab.dat
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diff --git a/doc/thesis/figures/data/flowgraphs/synchronized_qpsk_hw_lab.dat b/doc/thesis/figures/data/flowgraphs/synchronized_qpsk_hw_lab.dat
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+++ b/doc/thesis/figures/data/flowgraphs/synchronized_qpsk_hw_lab.dat
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diff --git a/doc/thesis/figures/data/qpsk_hw_lab.py b/doc/thesis/figures/data/qpsk_hw_lab.py
new file mode 100644
index 0000000..a8170c6
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+++ b/doc/thesis/figures/data/qpsk_hw_lab.py
@@ -0,0 +1,31 @@
+#!/usr/bin/env python3
+
+import utils
+import numpy as np
+
+# get array of samples [channel, synchronized, equalized, locked]
+samples = utils.load_samples(__file__)
+
+# range of samples we want to show
+start = 1e3
+end = start +50
+
+# select every second samples
+select_samples = lambda arr: arr[int(start):int(end):2]
+values = map(select_samples, samples)
+
+# split into imaginary and real parts
+get_parts = lambda v: (np.real(v), np.imag(v))
+parts = [p for v in map(get_parts, values) for p in v]
+
+# zip data and add header
+data = np.array(list(zip(*parts)))
+headers = [
+ "channel_re", "channel_im",
+ "synchronized_re", "synchronized_im",
+ "equalized_re", "equalized_im",
+ "locked_re", "locked_im"
+]
+
+# save to file
+utils.save_to_file(__file__, data, headers)