Welcome to echopype!

Welcome to echopype!#

Echopype is a package built to enable interoperability and scalability in ocean sonar data processing. These data are widely used for obtaining information about the distribution and abundance of marine animals, such as fish and krill. Our ability to collect large volumes of sonar data from a variety of ocean platforms has grown significantly in the last decade. However, most of the new data remain under-utilized. echopype aims to address the root cause of this problem - the lack of interoperable data format and scalable analysis workflows that adapt well with increasing data volume - by providing open-source tools as entry points for scientists to make discovery using these new data.

Contributors#

Wu-Jung Lee (@leewujung) founded the echopype project in 2018. It is currently led by Wu-Jung Lee and Emilio Mayorga (@emiliom), who are primary developers together. Previously, Landung “Don” Setiawan (@lsetiawan), Brandon Reyes (@b-reyes), Kavin Nguyen (@ngkavin) and Imran Majeed (@imranmaj) contributed significantly to the development of echopype. Valentina Staneva (@valentina-s) is also part of the development team.

Other contributors include: Frederic Cyr (@cyrf0006), Paul Robinson (@prarobinson), Sven Gastauer (@SvenGastauer), Marian Peña (@marianpena), Mark Langhirt (@bnwkeys), Erin LaBrecque (@erinann), Emma Ozanich (@emma-ozanich), Aaron Marburg (@amarburg). A complete list of direct contributors is on our GitHub Contributors Page.

We thank Dave Billenness of ASL Environmental Sciences for providing the AZFP Matlab Toolbox as reference for our development of AZFP support in echopype. We also thank Rick Towler (@rhtowler) of the NOAA Alaska Fisheries Science Center for providing low-level file parsing routines for Simrad EK60 and EK80 echosounders.

Echopype have also received software engineering support from the University of Washington’s Scientific Software Engineering Center (SSEC) supported by Schmidt Futures, as part of the Virtual Institute for Scientific Software (VISS) in 2023. We would like to acknowledge SSEC’s Graduate Research Scholar Anant Mittal (@anantmittal) for his contributions to the software.

Citing echopype#

Please cite echopype as follows:

Lee, W., Mayorga, E., Setiawan, L., Majeed, I., Nguyen, K., & Staneva, V. (2021). Echopype: A Python library for interoperable and scalable processing of water column sonar data for biological information. arXiv preprint arXiv:2111.00187

Citation information and project metadata are stored in CITATION.cff, which uses the Citation File Format.

License#

Echopype is licensed under the open source Apache 2.0 license.