Skip to main content

A graphical user interface for MNE

Project description

PyPI Version Conda Version Python Downloads PyPI Downloads Conda License

Graphical user interface (GUI) for MNE, a Python-based toolbox for EEG/MEG analysis.

Dependencies

MNELAB requires Python >= 3.6. In addition, the following Python packages are required:

Optional dependencies provide additional features if installed:

In general, it is recommended to always use the latest package versions.

Additional features

MNELAB comes with the following features that are not (yet) available in MNE:

  • Export to EDF/BDF (requires pyEDFlib)
  • Export to EEGLAB SET
  • Export to BrainVision VHDR/VMRK/EEG (requires pybv)
  • Import XDF files (requires pyxdf)

Installation

Via pip

The latest release is available on PyPI and can be installed with:

pip install mnelab
mnelab

The mnelab command in the last line starts the application.

Via conda

An (unofficial, but regularly updated) conda package can be installed from conda-forge. We strongly suggest to install MNELAB into its own dedicated environment to ensure smooth installation and operation:

conda create -y --name mnelab -c conda-forge mnelab
conda activate mnelab
mnelab

The mnelab command in the last line starts the application. Any issues with this conda package should be reported to the respective issue tracker.

Alternatively, if for some reason you do not want to use conda-forge, you can first install all dependencies that are present in the default conda channel:

conda install pyqt numpy scipy matplotlib

Next, install the dependencies that are not in the default conda channel via pip:

pip install mne

Finally, install MNELAB as follows:

pip install --no-deps mnelab

Arch Linux

If you use Arch Linux, you can install the python-mnelab AUR package (note that this requires the python-mne AUR package).

Standalone installer

A stand-alone installer will be available soon.

Development version

Follow these steps to use the latest development version of MNELAB:

  1. Download the source code and unpack it into a folder of your choice.
  2. Open a terminal and change to the MNELAB source folder.
    • If you use Anaconda or Miniconda, install all dependencies with conda install numpy scipy matplotlib pyqt followed by pip install mne.
    • Otherwise, install all dependencies with pip install -r requirements.txt (and optionally pip install -r requirements-optional.txt).
  3. Finally, run python3 -m mnelab to start MNELAB (if this does not work try python -m mnelab, just make sure to use Python 3 because Python 2 is not supported).

Contributing

The contributing guide contains details on how to contribute to MNELAB.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mnelab-0.5.2.tar.gz (55.6 kB view details)

Uploaded Source

File details

Details for the file mnelab-0.5.2.tar.gz.

File metadata

  • Download URL: mnelab-0.5.2.tar.gz
  • Upload date:
  • Size: 55.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.6.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.4

File hashes

Hashes for mnelab-0.5.2.tar.gz
Algorithm Hash digest
SHA256 ecc7031aa6470fd46dfb645b6c048e37a9f29adae34148fa7deceaefd3f271d6
MD5 7d18b9307864434008c89a78a73f26a8
BLAKE2b-256 23036cab5f269bb0e0d2ec30b480c9582a6c5917d271b02698b4ea8d79eec413

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page