Tool for analysis of passive acoustic data.
This tool is a slightly modified version of PAMGuide for the statistical programming language R, originally created by Nathan Merchant [1]. The primary modifications that have been made are 1) adding support for vector input, and 2) adding support for Jupyter notebook. The original version of PAMGuide only supports WAV-files (audio files) as input. However, passive acoustic data are often stored in NetCDF or other data files (e.g. MATLAB files). These sample values can now directly be processed, rather than converting this data into audio files. This reduces processing time and reduces the risk for loss of data.
A Jupyter notebook is included here to illustrate how to use the tool. It also shows how to access data available on a Thredds server without downloading the data manually.
The processing tool requires the following software to run:
- R (Available at: https://www.r-project.org )
- PAMGuide (Available at: https://sourceforge.net/projects/pamguide/)
- Jupyter notebook ( https://jupyter.org )
- Sample data (WIFAR data available here: https://archive.norstore.no/pages/public/datasetDetail.jsf?id=10.11582/2017.00012 )
Download the files in this repository and add them to the PAMGuide folder. The whole content of this repository can be downloaded using git clone https://github.com/ec-intaros/PAMGuide-R-Tutorial
The Jupyter notebook uses example data from the WIFAR project [2], which must be downloaded from the link above and placed in the main folder.
Start the Jupyter notebook by typing jupyter notebook in a terminal, and open the notebook. The notebook contains a step by step walkthrough, illustrating how the tool is used, and also how to read in data from a Thredds server.
A detailed instruction in the use of PAMGuide, as well as an overview of the capabilities of the software, is given in the instruction manual, which is available here
[1] Merchant, N.D., Fristrup, K.M., Johnson, M.P., Tyack, P.L., Witt, M.J., Blondel, P. and Parks, S.E. (2015), Measuring acoustic habitats. Methods Ecol Evol, 6: 257-265. doi:10.1111/2041-210X.12330
[2] Waves-in-Ice Forecasting for Arctic Operators, https://www.nersc.no/project/wifar
Espen Storheim (NERSC)
This work is licensed under a Creative Commons Attribution 4.0 International License. http://creativecommons.org/licenses/by/4.0/
PAMGuide is licensed by the original creator under a Creative Commons Attribution License. https://sourceforge.net/directory/license:ccal/
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 727890.