Converts simulated data (.csv) into audio files (.wav) for playback. Example:
python3 lamp.py --csv2wav=simulation1/simlog1.csv
The path is relative to the pc/data directory.
smoothing
Both --analyze and --csv2wav can be used with the --smoothing argument. Smoothing reduces high-frequency oscillations in the waveforms, which visually look like fast ripples or jaggedness. Example:
python3 lamp.py --csv2wav=simulation1/simlog1.csv --smoothing=hanning,11
The first smoothing argument is the type of window function to use. hanning should be fine to use by default. The second argument is the length of the window, which is basically the number of samples that you average over when recomputing each point.
Fixes #52.
csv2wav
Converts simulated data (.csv) into audio files (.wav) for playback. Example:
python3 lamp.py --csv2wav=simulation1/simlog1.csvThe path is relative to the pc/data directory.
smoothing
Both
--analyzeand--csv2wavcan be used with the--smoothingargument. Smoothing reduces high-frequency oscillations in the waveforms, which visually look like fast ripples or jaggedness. Example:python3 lamp.py --csv2wav=simulation1/simlog1.csv --smoothing=hanning,11Example:
python3 lamp.py --csv2wav=oct_13_2019/lamp_data_0.dat --smoothing=hanning,51The first smoothing argument is the type of window function to use.
hanningshould be fine to use by default. The second argument is the length of the window, which is basically the number of samples that you average over when recomputing each point.