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author | Nao Pross <np@0hm.ch> | 2021-12-21 00:32:06 +0100 |
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committer | Nao Pross <np@0hm.ch> | 2021-12-21 00:32:06 +0100 |
commit | 1de862c5e2ac6e2baa76daf9fbe6b64050da12fc (patch) | |
tree | aa3f52261a3e1f0e1e2b359be8dd1435cca89135 /doc/thesis/figures/data/qam_hw_lab.py | |
parent | Add data and flowgraph for (broken) QAM on hardware (diff) | |
download | Fading-1de862c5e2ac6e2baa76daf9fbe6b64050da12fc.tar.gz Fading-1de862c5e2ac6e2baa76daf9fbe6b64050da12fc.zip |
Add more data for QAM, fix colormap
Diffstat (limited to '')
-rw-r--r-- | doc/thesis/figures/data/qam_hw_lab.py | 12 |
1 files changed, 8 insertions, 4 deletions
diff --git a/doc/thesis/figures/data/qam_hw_lab.py b/doc/thesis/figures/data/qam_hw_lab.py index d49cfd1..fde109a 100644 --- a/doc/thesis/figures/data/qam_hw_lab.py +++ b/doc/thesis/figures/data/qam_hw_lab.py @@ -7,24 +7,28 @@ import numpy as np samples = utils.load_samples(__file__) # range of samples we want to show -start = 20e3 -end = start +400 +start = 25e3 +end = start +800 # select every second samples -select_samples = lambda arr: arr[int(start):int(end):6] +select_samples = lambda arr: arr[int(start):int(end):8] 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] +# add 'samplenr' metadata +parts += [np.arange(0, len(parts[0]))] + # 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" + "locked_re", "locked_im", + "samplenr", ] # save to file |