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        "author": "Felix Heilmeyer",
        "author_email": "code@fehe.eu",
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            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Scientific/Engineering"
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        "description": "NeuroneLoader\n=============\n\n.. image:: https://travis-ci.org/heilerich/neurone_loader.svg?branch=master\n   :target: https://travis-ci.org/heilerich/neurone_loader\n   :alt: Build Status\n\n.. image:: https://coveralls.io/repos/github/heilerich/neurone_loader/badge.svg\n   :target: https://coveralls.io/github/heilerich/neurone_loader\n   :alt: Coverage Status\n.. image:: https://readthedocs.org/projects/neurone-loader/badge/?version=latest\n   :target: https://neurone-loader.readthedocs.io/en/latest/?badge=latest\n   :alt: Documentation Status\n\n.. image:: https://img.shields.io/github/license/heilerich/neurone_loader.svg\n   :target: https://github.com/heilerich/neurone_loader/blob/master/LICENSE\n   :alt: License\n\n.. image:: https://img.shields.io/pypi/v/neurone_loader.svg\n   :target: https://pypi.org/project/neurone-loader/\n   :alt: PyPi Package\n\n.. image:: https://img.shields.io/pypi/pyversions/neurone_loader.svg\n   :target: https://pypi.org/project/neurone-loader/\n   :alt: Supported Python Versions\n\n.. image:: http://joss.theoj.org/papers/c71df4f24b732eabc11b3195a9a8c94d/status.svg\n   :target: http://joss.theoj.org/papers/c71df4f24b732eabc11b3195a9a8c94d\n   :alt: JOSS status\n\nNeuroneLoader is a python module for loading neurophysiological data recorded with Bittium NeurOne (formerly MegaEMG). It \ntherefore allows using the data in pure python processing workflows using the python scientifc software stack (e.g. `numpy\n<https://www.numpy.org/>`_) without the need of prior conversion using other (proprietary) software (e.g. MATLAB).\nIt can also export it to container objects used by the popular `python-mne <https://mne-tools.github.io/stable/index.html>`_\nframework.\n\nProps to Andreas Henelius at Finnish Institute of Occupational Health for figuring out how\nto read the NeurOne binary format in pure python as part of his\nexport2hdf_ project.\n\n* `Installation`_\n* `Quick start`_\n* Documentation_\n\n.. _Documentation: https://neurone-loader.readthedocs.io/en/latest/\n.. _export2hdf: https://github.com/bwrc/export2hdf5\n\nInstallation\n------------\n\n.. code:: bash\n\n   pip install neurone_loader\n\nIf you want to export to `python-mne <https://mne-tools.github.io/stable/index.html>`_ you must also install MNE and\nall it's dependencies.\n\n.. code:: bash\n\n   pip install mne\n\n.. _quick-start:\n\nQuick start\n-----------\n\n.. code:: python\n\n   >>> from neurone_loader import Recording\n   >>> rec = Recording(path_to_recording_folder)\n   >>> rec.event_codes\n   array([  0,   1,  12,  13,  99, 128], dtype=int32)\n\nPlease note that because raw EEG recordings can be quite large this package is very memory aware. Most data will be\nloaded from disk lazily, i.e. the moment you're actually accessing it, and redundant data will be removed from memory\nas soon as it has been copied - unless you specify otherwise. Be advised that working with big recordings might still\nrequire a lot of memory.\n\nI recommend looking at the docstrings before executing anything and maybe having a look at Concepts section in\nthe Documentation_ before you start working with this package.\n\nContributing\n------------\n\nIf you encounter any problem feel free to open a issue_ on GitHub. If you found a bug and want to\nsupply a fix or if you want to contribute a new feature open a `pull request`_. Just make sure that\nyour code is not breaking any tests and you also supply tests for your code.\n\n.. _issue: https://github.com/heilerich/neurone_loader/issues\n.. _pull request: https://github.com/heilerich/neurone_loader/pulls\n\nTesting\n~~~~~~~\n\nTo run the tests you must first get the test data and then you can run the test with the following commands.\nPlease run them in the repository directory, not in the test subdirectory.\n\nTo get the test data (~2.8GB) you need to install wget_. Then you can \ndownload the data by running\n\n.. code:: bash\n\n   bash test/get_test_data.sh\n\nThen you can run the tests with\n\n.. code:: bash\n\n   python -m unittest discover -s test -t .\n\n.. _wget: https://www.gnu.org/software/wget/\n\n",
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