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        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Environment :: Console",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: Apache Software License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
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        "description": ".. image:: https://travis-ci.org/OSOceanAcoustics/echopype.svg?branch=master\n    :target: https://travis-ci.org/OSOceanAcoustics/echopype\n.. image:: https://readthedocs.org/projects/echopype/badge/?version=latest\n    :target: https://echopype.readthedocs.io/en/latest/?badge=latest\n    :alt: Documentation Status\n.. image:: https://mybinder.org/badge_logo.svg\n    :target: https://mybinder.org/v2/gh/OSOceanAcoustics/echopype/master\n\nEchopype\n========\n\nEchopype is a package built for enhancing the interoperability and scalability\nin ocean sonar data processing.\nThese data are widely used for obtaining information about the distribution and\nabundance of marine animals, such as fish and krill.\nOur ability to collect large volumes of sonar data from a variety of\nocean platforms has grown significantly in the last decade.\nHowever, most of the new data remain under-utilized.\nechopype aims to address the root cause of this problem - the lack of\ninteroperable data format and scalable analysis workflows that adapt well\nwith increasing data volume - by providing open-source tools as entry points for\nscientists to make discovery using these new data.\n\n\nInstallation and Usage\n----------------------\n\nEchopype currently supports file conversion and computation of data produced by:\n\n- Simrad EK60 echosounder (``.raw`` files)\n- ASL Environmental Sciences AZFP echosounders (``.01A`` files)\n\nThe file conversion functionality converts data from manufacturer-specific\nbinary formats into a standardized netCDF files, based on which all subsequent\ncomputations are performed.\nThe data processing routines include calibration (instrument-specific), noise\nremoval, and mean volume backscattering strength (MVBS) calculation.\n\nEchopype can be installed from PyPI or through conda:\n\n.. code-block:: console\n\n    # PyPI\n    $ pip install echopype\n\n    # conda\n    $ conda install -c conda-forge echopype\n\nCheck out the `echopype documentation`_ for more details on installation and usage!\n\nWatch the `echopype talk`_  at SciPy 2019 for background, discussions and a quick demo!\n\n.. _echopype documentation: https://echopype.readthedocs.io\n.. _echopype talk: https://www.youtube.com/watch?v=qboH7MyHrpU\n\n\nContributors\n------------\n\n`Wu-Jung Lee <http://leewujung.github.io>`_ (@leewujung)\nand `Kavin Nguyen <https://github.com/ngkavin>`_ (@ngkavin)\nare the primary developers of this project.\n`Valentina Staneva <https://escience.washington.edu/people/valentina-staneva/>`_ (@valentina-s)\nprovides consultation and also contributes to the development.\n\nOther contributors include:\n`Frederic Cyr <https://github.com/cyrf0006>`_ (@cyrf0006),\n`Sven Gastauer <https://www.researchgate.net/profile/Sven_Gastauer>`_ (@SvenGastauer),\n`Marian Pe\u00f1a <https://www.researchgate.net/profile/Marian_Pena2>`_ (@marianpena),\n`Mark Langhirt <https://www.linkedin.com/in/mark-langhirt-7b33ba80>`_ (@bnwkeys),\n`Erin LaBrecque <https://www.linkedin.com/in/erin-labrecque/>`_ (@erinann),\n`Emma Ozanich <https://www.linkedin.com/in/emma-reeves-ozanich-b8671938/>`_ (@emma-ozanich),\n`Aaron Marburg <http://apl.uw.edu/people/profile.php?last_name=Marburg&first_name=Aaron>`_ (@amarburg)\n\nWe thank Dave Billenness of ASL Environmental Sciences for\nproviding the AZFP Matlab Toolbox as reference for our\ndevelopment of AZFP support in echopype.\n\n\nLicense\n-------\n\nEchopype is licensed under the open source Apache 2.0 license.\n\n\n---------------\n\nCopyright (c) 2018--, echopype Developers.\n\n\n",
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