neurotic

Curate, visualize, annotate, and share your behavioral ephys data using Python

https://github.com/jpgill86/neurotic

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
  • .zenodo.json file
  • DOI references
    Found 8 DOI reference(s) in README
  • Academic publication links
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (13.0%) to scientific vocabulary

Keywords

annotation-tool data-management data-sharing download-manager electrophysiology neuroscience open-science python python-neo video-sync visualization
Last synced: 6 months ago · JSON representation

Repository

Curate, visualize, annotate, and share your behavioral ephys data using Python

Basic Info
Statistics
  • Stars: 33
  • Watchers: 2
  • Forks: 9
  • Open Issues: 82
  • Releases: 20
Topics
annotation-tool data-management data-sharing download-manager electrophysiology neuroscience open-science python python-neo video-sync visualization
Created over 6 years ago · Last pushed over 2 years ago
Metadata Files
Readme License

README.rst

|neurotic logo| *neurotic*: NEUROscience Tool for Interactive Characterization
==============================================================================

*Curate, visualize, annotate, and share your behavioral ephys data using Python*

:Distributions: |PyPI badge| |Anaconda badge| |Installers badge|
:Source Code:   |GitHub badge| |Feedstock badge| |Constructor badge|
:Tests Status:  |GitHub Actions badge| |Azure badge| |Docs badge| |Coverage badge|
:Citing:        |Zenodo badge| |eNeuro badge|

Documentation_ | `Release Notes`_ | `Issue Tracker`_

*neurotic* is an app for Windows, macOS, and Linux that allows you to easily
review and annotate your electrophysiology data and simultaneously captured
video. It is an easy way to load your Neo_-compatible data (see neo.io_ for
file formats) into ephyviewer_ without doing any programming. Share a single
metadata file with your colleagues and they too will quickly be looking at the
same datasets!

To use the app, first organize your datasets in a *metadata file* like this
(see `Configuring Metadata`_):

.. code-block:: yaml

    my favorite dataset:
        description: This time it actually worked!

        data_dir:           C:\local_dir_containing_files
        remote_data_dir:    http://myserver/remote_dir_containing_downloadable_files  # optional
        data_file:          data.axgx
        video_file:         video.mp4
        # etc

        video_offset: -3.4  # seconds between start of video and data acq
        epoch_encoder_possible_labels:
            - label01
            - label02
        plots:
            - channel: I2
              ylim: [-30, 30]
            - channel: RN
              ylim: [-60, 60]
            # etc

        filters:  # used only if fast loading is off (lazy=False)
            - channel: Force
              lowpass: 50
            # etc
        amplitude_discriminators:  # used only if fast loading is off (lazy=False)
            - name: B3 neuron
              channel: BN2
              units: uV
              amplitude: [50, 100]
            # etc

    another dataset:
        # etc

Open your metadata file in *neurotic* and choose a dataset. If the data and
video files aren't already on your local computer, the app can download them
for you, even from a password-protected server or from Google Drive. Finally,
click launch and the app will use a standard viewer layout to display your data
to you using ephyviewer_.

|Example screenshot|

*In the screenshot above, the video frame shows a voracious sea slug* (Aplysia
californica) *swallowing a strip of unbreakable seaweed attached to a force
transducer. Implanted electrodes recorded from a muscle and the major nerves
controlling feeding. The epoch encoder was used to mark the times when seaweed
moved into the mouth. Spikes corresponding to activity of identified neurons
were detected by* neurotic *using customizable parameters.*

The viewers are easy and intuitive to navigate (see `User Interface`_):

- Pressing the play button will scroll through your data and video in real
  time, or at a higher or lower rate if the speed parameter is changed.
- The arrow/WASD keys allow you to step through time in variable increments.
- Jump to a time by clicking on an event in the event list or a table entry in
  the epoch encoder.
- To show more or less time at once, right-click and drag right or left to
  contract or expand time.
- Scroll the mouse wheel in the trace viewer or video viewer to zoom.
- The epoch encoder can be used to block out periods of time during which
  something interesting is happening for later review or further analysis
  (saved to a CSV file).
- All panels can be hidden, undocked, stacked, or repositioned on the fly.

Electrophysiologists will find this tool useful even if they don't need the
video synchronization feature!

**Portability is easy with neurotic!** Use relative paths in your metadata file
along with a remotely accessible data store such as GIN_ or a Shared Drive on
Google Drive to make your metadata file fully portable. The same metadata file
can be copied to a different computer, and downloaded files will automatically
be saved to the right place. Data stores can be password protected and
*neurotic* will prompt you for a user name and password. This makes it easy to
share the *neurotic* experience with your colleagues! 🤪

Installing *neurotic*
---------------------

*neurotic* requires Python 3.7 or later.

Standalone Installers (recommended for beginners)
.................................................

Downloadable installers make installing *neurotic* easy for beginners. They can
be downloaded from the GitHub Releases page:

    `👉 Download installers here (listed under "Assets") 👈`__

    __ `GitHub Releases`_

These installers are intended for users who do not want to independently
install Python or conda just to use *neurotic*. They will install *neurotic*
and everything it needs (including a fully contained Python environment) into a
dedicated directory on your computer. On Windows, the installer will also
create a Start Menu shortcut for launching the app.

For developers, a recipe for building new installers using `conda constructor`_
is maintained here: `constructor recipe`_.

Alternate Method: conda (recommended for Pythonistas)
.....................................................

conda_ users can install *neurotic* and all of its dependencies with one
command::

    conda install -c conda-forge neurotic

On Windows, this will also create a Start Menu shortcut for launching the app.

Alternate Method: pip
.....................

Install *neurotic* from PyPI_ using ::

    pip install neurotic

Note that installation via ``pip`` skips one dependency: PyAV_, which is
required for displaying videos, and without which *neurotic* will ignore
videos. PyAV is not easily installed with ``pip`` on some systems, especially
Windows. The easiest way to separately install PyAV is using conda_::

    conda install -c conda-forge av

Updating *neurotic*
-------------------

The recommended method of updating *neurotic* depends on the original method of
installation.

If you are unsure what method you used, updating using ``conda`` or ``pip`` is
likely to work. Standalone installers may be safe too, though this could lead
to having multiple version installed simultaneously.

Updating with Standalone Installers
...................................

If you previously installed *neurotic* using a standalone installer, you may
install a newer version using another installer, either into a different
directory or by first uninstalling the old version. Installers can be
downloaded from the GitHub Releases page:

    `👉 Download installers here (listed under "Assets") 👈`__

    __ `GitHub Releases`_

Alternatively, if a new installer is not currently available for your platform,
or if you would just like a much faster method, you may use the command line
tools provided by the installer (via the "Anaconda Prompt" on Windows, or the
Terminal on macOS and Linux)::

    conda update -c conda-forge neurotic

Updating with conda
...................

If you installed *neurotic* with `conda`_, you can update to the latest release
using ::

    conda update -c conda-forge neurotic

Updating with pip
.................

If you installed *neurotic* using ``pip``, you can update to the latest release
available on PyPI_ using ::

    pip install -U neurotic

Development Version
...................

If you are interested in trying new, unreleased features of *neurotic*, you may
install the latest development version from GitHub_ using ::

    pip install -U git+https://github.com/jpgill86/neurotic.git

Note that if you install the development version, you may also need the latest
development version of ephyviewer_, which you can get using ::

    pip install -U git+https://github.com/NeuralEnsemble/ephyviewer.git

Getting Started
---------------

Windows users who installed using a standalone installer or conda_ should be
able to launch *neurotic* from the Start Menu.

Mac and Linux users, as well as Windows users, can use the Terminal, command
line, or Anaconda Prompt to start the app:

1. Depending on your operating system, installation method, and environment
   settings, you may be able to just launch the app from the command line by
   invoking its name::

    neurotic

2. If the command is not recognized, you likely need to first activate the
   conda environment into which the app was installed::

    conda activate 

   If you used a standalone installer, the environment name may be
   "``neurotic``", so you would use ::

    conda activate neurotic

   You can then try again invoking the app name::

    neurotic

Several examples are provided. Select one, download the associated data using
the "Download data" menu action, and then click "Launch". See `User Interface`_
for help with navigation.

Disabling "Fast loading" before launch will enable additional features
including amplitude-threshold spike detection and signal filtering.

To inspect the metadata file associated with the examples or to make changes to
it, click "Edit metadata". See `Configuring Metadata`_ for details about the
format.

If you like working with Jupyter notebooks, you can launch an example notebook
that includes a tutorial for using *neurotic*'s API::

    neurotic --launch-example-notebook

The command line interface accepts other arguments too:

.. code-block::

    usage: neurotic [-h] [-V] [--debug | --no-debug] [--lazy | --no-lazy]
                    [--thick-traces | --no-thick-traces]
                    [--show-datetime | --no-show-datetime]
                    [--ui-scale {tiny,small,medium,large,huge}]
                    [--theme {light,dark,original,printer-friendly}]
                    [--use-factory-defaults] [--launch-example-notebook]
                    [file] [dataset]

    neurotic lets you curate, visualize, annotate, and share your behavioral ephys
    data.

    positional arguments:
      file                  the path to a metadata YAML file (default: an example
                            file)
      dataset               the name of a dataset in the metadata file to select
                            initially (default: the first entry in the metadata
                            file)

    optional arguments:
      -h, --help            show this help message and exit
      -V, --version         show program's version number and exit
      --debug               enable detailed log messages for debugging
      --no-debug            disable detailed log messages for debugging (default)
      --lazy                enable fast loading (default)
      --no-lazy             disable fast loading
      --thick-traces        enable support for traces with thick lines, which has
                            a performance cost
      --no-thick-traces     disable support for traces with thick lines (default)
      --show-datetime       display the real-world date and time, which may be
                            inaccurate depending on file type and acquisition
                            software
      --no-show-datetime    do not display the real-world date and time (default)
      --ui-scale {tiny,small,medium,large,huge}
                            the scale of user interface elements, such as text
                            (default: medium)
      --theme {light,dark,original,printer-friendly}
                            a color theme for the GUI (default: light)
      --use-factory-defaults
                            start with "factory default" settings, ignoring other
                            args and your global config file

    alternative modes:
      --launch-example-notebook
                            launch Jupyter with an example notebook instead of
                            starting the standalone app (other args will be
                            ignored)

    Defaults for arguments and options can be changed in a global config file,
    .neurotic\neurotic-config.txt, located in your home directory.

Citing *neurotic*
-----------------

To cite *neurotic* in your publication, please refer to:

    Gill, J. P., Garcia, S., Ting, L. H., Wu, M., & Chiel, H. J. (2020).
    *neurotic*: Neuroscience Tool for Interactive Characterization. eNeuro,
    7(3). https://doi.org/10.1523/ENEURO.0085-20.2020

Specific versions of the software can be cited from archives at Zenodo_.

Documentation
-------------

For detailed information on configuring metadata, working examples, the API
reference guide, release notes, and more, see the Documentation_.


.. |neurotic logo| image:: https://raw.githubusercontent.com/jpgill86/neurotic/master/neurotic/gui/icons/img/neurotic-logo-30.png
    :alt: Project logo

.. |PyPI badge| image:: https://img.shields.io/pypi/v/neurotic.svg?logo=python&logoColor=white
    :target: PyPI_
    :alt: PyPI project

.. |Anaconda badge| image:: https://img.shields.io/conda/vn/conda-forge/neurotic.svg?label=anaconda&logo=anaconda&logoColor=white
    :target: `Anaconda Cloud`_
    :alt: Anaconda Cloud project

.. |Installers badge| image:: https://img.shields.io/github/v/release/jpgill86/neurotic?label=installers&logo=github&logoColor=white&sort=semver
    :target: `GitHub Releases`_
    :alt: Installers

.. |GitHub badge| image:: https://img.shields.io/badge/github-source_code-blue.svg?logo=github&logoColor=white
    :target: GitHub_
    :alt: GitHub source code

.. |Feedstock badge| image:: https://img.shields.io/badge/conda--forge-feedstock-blue.svg?logo=conda-forge&logoColor=white
    :target: `conda-forge feedstock`_
    :alt: conda-forge feedstock

.. |Constructor badge| image:: https://img.shields.io/badge/constructor-recipe-blue.svg
    :target: `constructor recipe`_
    :alt: constructor recipe

.. |GitHub Actions badge| image:: https://img.shields.io/github/actions/workflow/status/jpgill86/neurotic/tests.yml?branch=master&label=tests&logo=github&logoColor=white
    :target: `GitHub Actions`_
    :alt: Tests status

.. |Azure badge| image:: https://dev.azure.com/conda-forge/feedstock-builds/_apis/build/status/neurotic-feedstock?branchName=master
    :target: `conda-forge CI`_
    :alt: conda-forge build status

.. |Docs badge| image:: https://img.shields.io/readthedocs/neurotic/latest.svg?logo=read-the-docs&logoColor=white
    :target: ReadTheDocs_
    :alt: Documentation status

.. |Coverage badge| image:: https://coveralls.io/repos/github/jpgill86/neurotic/badge.svg?branch=master
    :target: Coveralls_
    :alt: Coverage status

.. |Zenodo badge| image:: https://img.shields.io/badge/DOI-10.5281/zenodo.3564990-blue.svg
    :target: Zenodo_
    :alt: Zenodo archive

.. |eNeuro badge| image:: https://img.shields.io/badge/DOI-10.1523/ENEURO.0085--20.2020-blue.svg
    :target: eNeuro_
    :alt: eNeuro article

.. |Example screenshot| image:: https://raw.githubusercontent.com/jpgill86/neurotic/master/docs/_static/example-screenshot.png
    :target: https://raw.githubusercontent.com/jpgill86/neurotic/master/docs/_static/example-screenshot.png
    :alt: Screenshot

.. _Anaconda Cloud: https://anaconda.org/conda-forge/neurotic
.. _conda:          https://docs.conda.io/projects/conda/en/latest/user-guide/install/
.. _conda constructor: https://github.com/conda/constructor
.. _constructor recipe: https://github.com/jpgill86/neurotic-constructor
.. _conda-forge CI: https://dev.azure.com/conda-forge/feedstock-builds/_build/latest?definitionId=8417&branchName=master
.. _conda-forge feedstock: https://github.com/conda-forge/neurotic-feedstock
.. _Configuring Metadata: https://neurotic.readthedocs.io/en/latest/metadata.html
.. _Coveralls:      https://coveralls.io/github/jpgill86/neurotic?branch=master
.. _Documentation:  https://neurotic.readthedocs.io/en/latest
.. _eNeuro:         https://doi.org/10.1523/ENEURO.0085-20.2020
.. _ephyviewer:     https://ephyviewer.readthedocs.io/en/latest
.. _GIN:            https://gin.g-node.org
.. _GitHub:         https://github.com/jpgill86/neurotic
.. _GitHub Actions: https://github.com/jpgill86/neurotic/actions?query=workflow%3Atests
.. _GitHub Releases: https://github.com/jpgill86/neurotic/releases
.. _Issue Tracker:  https://github.com/jpgill86/neurotic/issues
.. _Neo:            https://neo.readthedocs.io/en/latest
.. _neo.io:         https://neo.readthedocs.io/en/latest/io.html#module-neo.io
.. _PyAV:           https://docs.mikeboers.com/pyav/develop/overview/installation.html
.. _PyPI:           https://pypi.org/project/neurotic
.. _ReadTheDocs:    https://readthedocs.org/projects/neurotic
.. _Release Notes:  https://neurotic.readthedocs.io/en/latest/releasenotes.html
.. _User Interface: https://ephyviewer.readthedocs.io/en/latest/interface.html
.. _Zenodo:         https://doi.org/10.5281/zenodo.3564990

Owner

  • Name: Jeffrey Gill
  • Login: jpgill86
  • Kind: user

GitHub Events

Total
  • Watch event: 4
Last Year
  • Watch event: 4

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 371
  • Total Committers: 1
  • Avg Commits per committer: 371.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 18
  • Committers: 1
  • Avg Commits per committer: 18.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Jeffrey Gill j****l@g****m 371

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 53
  • Total pull requests: 50
  • Average time to close issues: 6 months
  • Average time to close pull requests: about 1 hour
  • Total issue authors: 3
  • Total pull request authors: 2
  • Average comments per issue: 0.57
  • Average comments per pull request: 1.28
  • Merged pull requests: 48
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • jpgill86 (50)
  • icarmel (2)
  • Muthu-Jeyanthi (1)
Pull Request Authors
  • jpgill86 (49)
  • icarmel (1)
Top Labels
Issue Labels
enhancement (22) bug (8) missing test (6) documentation (5) tests (1)
Pull Request Labels
documentation (18) enhancement (12) bug (10) tests (8)

Packages

  • Total packages: 2
  • Total downloads:
    • pypi 163 last-month
  • Total dependent packages: 0
    (may contain duplicates)
  • Total dependent repositories: 1
    (may contain duplicates)
  • Total versions: 27
  • Total maintainers: 1
pypi.org: neurotic

Curate, visualize, annotate, and share your behavioral ephys data using Python

  • Versions: 20
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 163 Last month
Rankings
Dependent packages count: 10.1%
Stargazers count: 11.9%
Forks count: 11.9%
Average: 15.8%
Dependent repos count: 21.5%
Downloads: 23.4%
Maintainers (1)
Last synced: 6 months ago
conda-forge.org: neurotic

neurotic is an app for Windows, macOS, and Linux that allows you to easily review and annotate your electrophysiology data and simultaneously captured video. It is an easy way to load your Neo-compatible data into ephyviewer without doing any programming. Share a single metadata file with your colleagues and they too will quickly be looking at the same datasets!

  • Versions: 7
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent repos count: 34.0%
Average: 43.3%
Stargazers count: 43.4%
Forks count: 44.7%
Dependent packages count: 51.2%
Last synced: 6 months ago

Dependencies

.github/workflows/tests.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
requirements-docs.txt pypi
  • readthedocs-sphinx-ext <2.2
  • sphinx <2
  • sphinxcontrib-programoutput *
requirements-notebook.txt pypi
  • ipython *
  • ipywidgets *
requirements-tests.txt pypi
  • coveralls * test
  • nose * test
requirements.txt pypi
  • PyDrive2 *
  • ephyviewer >=1.3.0
  • neo >=0.7.2
  • numpy *
  • packaging *
  • pandas *
  • pyqt5 *
  • pyyaml *
  • quantities *
  • requests *
  • scipy *
  • setuptools *
  • toml *
  • tqdm *