wavecracker 9.1.1

Description:

wavecracker 9.1.1

Wave Cracker






Abstract
Python batch tool for signal time/frequency analysis (input data: CSV or audio files).
Detailed documentation: here
Plot examples



Setup
You can install the package using pip:
python -m pip install wavecracker

Python Dependencies



Module
Version required
Notes




Python
>= 3.7
Preferably > 3.8, ref. documentation for additional details


numpy
>= 1.23.5



PyYAML
>= 6.0



pandas
>= 2.0.1



chardet
>= 4.0.0



scipy
>= 1.10.1



matplotlib
>= 3.7.1



PyWavelets
>= 1.4.1
Optional (for wavelet transform)


pydub
>= 0.25.1
Optional (for audio file processing)


moviepy
>= 1.0.3
Optional (for audio file processing)


psutil
>= 5.9.5
Optional (for hardware detailed diagnostics upon boot)



Installing extras (i.e. optional Python dependencies)
The following commands allow the installation of the extras correspondent to the optional dependencies above mentioned:
python -m pip install wavecracker[wavelet]
python -m pip install wavecracker[audio]
python -m pip install wavecracker[hwdiagnostics]

Note that some of these extras may or may not work depending on the Python version. More information in the documentation.
Other Dependencies
As mentioned above, the following directories are needed in the PATH:

PYTHON_HOME and PYTHON_HOME/Scripts

Also, but only if you are willing to process audio files, these directories must be present in the PATH, too.

The directory containing the FFMPEG executable (6.0 or upper; note, needed only for audio files processing)

Usage

We assume, in the following, that ${PACKAGE_HOME} is where the package is available after the install (typically under ${PYTHON_HOME}/Lib/site-packages/wavecracker or alike).

Open a command shell, make sure your Python install is in the PATH, and enter the following command:
python "${PACKAGE_HOME}/signalanalyzer.py" <arguments>

Many other details can be found in the documentation about:

Available command line arguments
Parameters in the configuration file

Launching the DEMO
python "${PACKAGE_HOME}/demo/launch_demo.py"

Examples
Example 1 (CSV file processing)
... .. /signalanalyzer.py --input-path ./inputdata.csv --qplot time_1 signal_1 --include-histogram --out-directory ./output_1

Explanation:

This would process a csv file named inputdata.csv (in the current directory), looking for a header with columns
named time_1 and signal_1, saving the results into a subdirectory of the current directory named output_1.
Plots typically generated are Fourier transform and others
A CSV is saved (with data about some of the calculated functions).
Note: the output directory needs to be existing.
A directory named logs has to be created in the current directory for the logs to be saved.