pingverter 1.0.0a0

A Python-based converter for sonar logs used by PINGMapper

A Python-based convertor for sonar logs collected with consumer-grade fishfinders.

PINGVerter is designed to pre-process sonar logs for PINGMapper post-processing. It is not intended to function as a stand-alone package.

Compatibility

• Humminbird ( *.DAT/ *.SON/ *.IDX)
• Lowrance ( *.sl2 / *.sl3)

Installation

pip install pingverter

Usage - Example Only

PINGVerter can be used as a stand-alone engine for decoding sonar logs and exporting ping attributes to CSV. While this functionality is described here, please use PINGMapper for all sonar log processing.

Humminbird

# Import
from pingverter import hum2pingmapper

# Parameters
inFile = r'C:\Path\To\Recording\Rec00001.DAT'
projDir = r'C:\Path\To\Outputs\MyProject'

sonar_object = hum2pingmapper(inFile, projDir)

Lowrance

# Import
from pingverter import low2pingmapper

# Parameters
inFile = r'C:\Path\To\Recording\Rec00001.DAT'
projDir = r'C:\Path\To\Outputs\MyProject'

sonar_object = low2pingmapper(inFile, projDir)

Outputs from the above examples will be exported to C:\Path\To\Outputs\MyProject\meta.

Acknowledgments

PINGVerter has been made possible through mentorship, partnerships, financial support, open-source software, manuscripts, and documentation linked below.

NOTE: The contents of this repository are those of the author(s) and do not necessarily represent the views of the individuals and organizations specifically mentioned here.

• Dr. Arthur Trembanis (Post-Doc Advisor) & Dr. Daniel Buscombe (PhD Advisor)

• Coastal Sediments, Hydrodynamics and Engineering Lab (CSHEL), College of Earth, Ocean, & Environment (CEOE), University of Delaware

• PINGMapper

  • Bodine, C. S., Buscombe, D., Best, R. J., Redner, J. A., & Kaeser, A. J. (2022). PING-Mapper: Open-source software for automated benthic imaging and mapping using recreation-grade sonar. Earth and Space Science, 9, e2022EA002469. https://doi.org/10.1029/2022EA002469
  • Bodine, C. S., Buscombe, D., & Hocking, T. D. (2024). Automated river substrate mapping from sonar imagery with machine learning. Journal of Geophysical Research: Machine Learning and Computation, 1, e2024JH000135. https://doi.org/10.1029/2024JH000135

• PyHum

  • Buscombe, D., Grams, P.E., and Smith, S. (2015) "Automated riverbed sediment classification using low-cost sidescan sonar", Journal of Hydraulic Engineering, https://doi.org/10.1061/(ASCE)HY.1943-7900.0001079, 06015019.
  • Buscombe, D., 2017, Shallow water benthic imaging and substrate characterization using recreational-grade sidescan-sonar. ENVIRONMENTAL MODELLING & SOFTWARE 89, 1-18.

• SL3Reader

  • Halmai, Akos; Gradwohl Valkay, Alexandra; Czigany, Szabolcs; Ficsor, Johanna; Liptay, ZoltAn Arpad; Kiss, Kinga; Loczy, Denes and Pirkhoffer, Ervin. 2020. "Applicability of a Recreational-Grade Interferometric Sonar for the Bathymetric Survey and Monitoring of the Drava River" ISPRS International Journal of Geo-Information 9, no. 3: 149. https://doi.org/10.3390/ijgi9030149

• sonarlight - Kenneth Thoro Martinsen

• Navico (Lowrance, Simrad, B&G) Sonar Log File Format - Herbert Oppmann

• Vincent Capone - Black Laser Learning

Future Development, Collaborations, & Partnerships

If you are interested in partnering on future developments, please reach out to Cameron Bodine.